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Long-term trends in daily temperature extremes in Iraq
Abstract
The existence of long-term persistence (LTP) in hydro-climatic time series can lead to considerable change in significance of trends. Therefore, past findings of climatic trend studies that did not consider LTP became a disputable issue. A study has been conducted to assess the trends in temperature and temperature extremes in Iraq in recent years (1965–2015) using both ordinary Mann-Kendal (MK) test; and the modified Mann-Kendall (m-MK) test, which can differentiate the multi-decadal oscillatory variations from secular trends. Trends in annual and seasonal minimum and maximum temperatures, diurnal temperature range (DTR), and 14 temperature-related extremes were assessed. MK test detected the significant increases in minimum and maximum temperature at all stations, where m-MK test detected at 86% and 80% of all stations, respectively. The temperature in Iraq is increasing 2 to 7 times faster than global temperature rise. The minimum temperature is increasing more (0.48–1.17 °C/decade) than maximum temperature (0.25–1.01 °C/decade). Temperature rise is higher in northern Iraq and in summer. The hot extremes particularly warm nights are increasing all over Iraq at a rate of 2.92–10.69 days/decade, respectively. On the other hand, numbers of cold days are decreasing at some stations at a rate of − 2.65 to − 8.40 days/decade. The use of m-MK test along with MK test confirms the significant increase in temperature and some of the temperature extremes in Iraq. This study suggests that trends in many temperature extremes in the region estimated in previous studies using MK test may be due to natural variability of climate, which empathizes the need for validation of the trends by considering LTP in time series.
... PET also plays a vital role in terrestrial water fluxes and water storage, for instance, soil moisture, surface runoff, and groundwater (Singer et al. 2021). Runoff and groundwater recharge might be affected by the changes in PET (Salman et al. 2017) and hence might affect crop water availability and crop growth. Accordingly, PET is imperative for determining irrigation scheduling and crop water requirements and estimating the water budget (Allen et al. 1998;Zhang and Wang 2021). ...
... Consequently, water security has become the biggest challenge facing the development of Iraqi agriculture and the economy (Salman et al. 2021). Iraq is considered highly vulnerable to global climate change, which has a predominantly arid and semi-arid climate, particularly in the central and southern regions, where temperature extremes and precipitation variability occur frequently (Salman et al. 2017(Salman et al. , 2018. The increasing intensity of extreme weather events, namely heat waves, dust storms, persistent droughts, and flash floods, have been reported throughout the past 20-30 years in Iraq (Tolba and Najib 2009;Salman et al. 2018). ...
... It is a significant drawback of using the MK test in most previous studies. Thus, the modified version of the classical Mann-Kendall (MMK) test, such as the MMK test proposed by Hamed (2008), should be applied to consider the influence of a significant autocorrelation coefficient present in the studied time series using the MK test (Salman et al. 2017;Nashwan et al. 2019). Yet, another considerable limitation is that most empirical methods for estimating PET in these studies depend on AT or SR. ...
Understanding the spatial variations in potential evapotranspiration (PET) and its influencing climatic variables is essential for sustainable agriculture and water resources management. However, little published research has investigated the alternation of PET due to climate change in the case of Iraq. The objective of the present study was to analyze the spatial trends in annual and seasonal PET in Iraq. Accordingly, the latest global ERA5-Land dataset of the European Centre for Medium-Range Weather Forecasts for 1981-2021 was employed. The PET was estimated using the FAO-Penman-Monteith method. The modified Mann-Kendall statistical test was applied to evaluate the significance of the trends in PET, which can separate unidirectional trends caused by climate change from the natural variability of climate. The attained results indicate that: (1) Over the past four decades, the annual and seasonal PET witnessed a significant increasing trend in almost all of Iraq, except for the alluvial plain in the eastern and southeastern parts. (2) The increasing trend in PET confirmed the patterns of the trend significance, with the highest increase of 0.28-0.65 mm/decade in southwest Iraq. (3) Summer had the highest upward trend of 0.35-0.65 mm/decade, followed by spring, autumn, and winter. (4) The air temperature was the predominant driving factor of rising PET, showing a positive correlation ranging from 0.77 to 0.88 and a contribution of 26 to 94%, mainly in the south, central, and northwest regions. The reverse contribution of wind speed and surface pressure to PET, particularly in the southeast and southwest, remains offset by the influence of air temperature and net solar radiation. Overall, the PET has risen drastically due to global climate change, indicating the potential for increased atmospheric water demand in the region.
... The arid regions, particularly those located in the western part of Asia, may experience a much higher impact (IPCC, 2007;Salman et al., 2018b;Pour et al., 2020). Because of their fragile ecosystems, the arid climatic system is highly susceptible to subtle variations of present-day climate (Sarr, 2012;Salman et al., 2017;Ahmed et al., 2019d). The extreme terrain has made precipitation spatially highly variable in the region (Barlow et al., 2016). ...
... Studies have already shown that a little change in precipitation amount can cause a significant rise in precipitation related extremes (Chiew et al., 2009;Pour et al., 2014;Khan et al., 2019;Shiru et al., 2019b). Hence, a big change in climatic variables such as precipitation may lead to climatechange-induced adversities such as hydrometeorological hazards in the western part of Asia (Salman et al., 2017(Salman et al., , 2019Pour et al., 2018;Salehie et al., 2021a). Iraq, situated in western Asia, is globally one of the least climate-resilient countries. ...
... Iraq, situated in western Asia, is globally one of the least climate-resilient countries. The country experienced a rise in temperature by a few fold faster than the global average temperature rise in the last four decades (Salman et al., 2017). It also experienced a drastic decrease in precipitation over time (Salman et al., 2018). ...
Changes in precipitation and temperature have crucial implications in the arid region due to their fragile environment. This study was an attempt to estimate possible spatiotemporal alteration of annual and seasonal precipitation and temperature in Iraq. Statistical downscaling of Coupled Model Intercomparison Project Phase 6 (CMIP6) global climate model (GCM) simulations for different shared socioeconomic pathways (SSP) was utilized. The GCMs were ranked according to their skills in simulating climate research unit (CRU) precipitation and temperature climatology along with their seasonality. Nonlocal model output statistics (MOS) models were implemented using a support vector machine (SVM) for downscaling and projection of selected GCM precipitation and temperature. Results revealed ACCESS‐CM2, BCC‐CSM2‐MR, GISS‐E2‐1‐G and MRI‐ESM2‐0 GCMs are most suitable for Iraq. The spatiotemporal changes in precipitation indicated a substantial decrease to north (up to −7.8%·mm ⁻¹ ) while an increase (around 3.0%) to south for different SSPs. Far future (2060–2099) showed both increase and decrease in precipitation than near future (2020–2059). The precipitation was projected to reduce in winter and increase in summer for all climate zones during both periods. The maximum temperature was projected to increase by 4.5°C to the north and 0.9–2°C to the south. In contrast, the minimum temperature was projected to rise by 1.0–3.5°C to both north and south. Both maximum and minimum temperatures may increase; however, more increases might be in winter and less in summer. The minimum temperature increase will be higher than the maximum temperature in the cold northern region and vice versa. Uncertainty in precipitation and temperature projections was higher for the far‐future period with higher SSPs than for the near‐future period with lower SSPs. The results of this study can guide the development of strategic policies for climate resiliency development in Iraq.
... PET also plays a vital role in terrestrial water fluxes and water storage, for instance, soil moisture, surface runoff, and groundwater (Singer et al., 2021). Runoff and groundwater recharge can be affected by the changes in PET (Salman et al., 2017) and hence might affect crop water availability and crop growth. Accordingly, PET is imperative for determining irrigation scheduling and crop water requirements and estimating the water budget (Allen et al., 1998, Zhang and. ...
... Consequently, water security has become the biggest challenge facing the development of Iraqi agriculture and the economy (Salman et al., 2021). Iraq, which is considered highly vulnerable to global climate change, has a predominantly arid and semi-arid climate, particularly in the central and southern regions, where temperature extremes and precipitation variability occur frequently (Salman et al., 2017, Salman et al., 2018. The increasing intensity of extreme weather events, namely heat waves, dust storms, persistent droughts, and flash floods, have been reported throughout the past 20-30 years in Iraq (Tolba andNajib, 2009, Salman et al., 2018). ...
... It represents a significant drawback of using the MK test in most previous studies. Thus, the modified version of the classical Mann-Kendall (MMK) test, such as the MMK test proposed by Hamed (2008), should be applied to consider the influence of a significant autocorrelation coefficient present in the studied time series using the MK test (Salman et al., 2017, Nashwan et al., 2019). Yet, another considerable limitation is that most of the applied empirical methods for estimating PET in these studies depend on AT or SR. ...
Understanding the spatial variations in Potential Evapotranspiration (PET) and its influencing climatic variables is essential for sustainable agriculture and water resources management. However, little published research has investigated the alternation of PET due to climate change in the case of Iraq. The objective of the present study was to analyze the spatial trends in annual and seasonal PET in Iraq. Accordingly, the latest global ERA5-Land dataset of the European Centre for Medium-Range Weather Forecasts for 1981‒2021 was employed. The PET was estimated using the FAO-Penman-Monteith method. The modified Mann-Kendall statistical test was applied to evaluate the significance of the trends in PET, which can separate unidirectional trends caused by climate change from the natural variability of climate. The obtained results indicate that: (1) Over the past four decades, the annual and seasonal PET witnessed a significant increasing trend in almost all of Iraq, except over the alluvial plain located in the eastern and southeastern parts. (2) The increasing trend in PET confirmed the patterns of the trend significance, with the highest increase of 0.28‒0.65 mm/decade in southwest Iraq. (3) Summer had the highest increasing trend of 0.35‒0.65 mm/decade, followed by spring, autumn, and winter. (4) The air temperature was the predominant driving factor of rising PET, showing a strong correlation ranging from 0.77 to 0.88 and a contribution of 26 to 94%, mainly in the south, central, and northwest regions. The reverse contribution of wind speed and surface pressure to PET, particularly in the southeast and southwest, remains offset by the influence of air temperature and net solar radiation. Overall, the PET has risen drastically due to global climate change, indicating the potential for increased atmospheric water demand in the region.
... It is considered one of the world's most vulnerable places to temperature increase (IPCC 2021). Previous studies have demonstrated that the MENA is extremely vulnerable to internal and external climatic influences (Salman et al. 2017(Salman et al. , 2018Dogar 2018;Nashwan et al. 2020;Sahour et al. 2020). The region climate has significant teleconnection variabilities such as the North Atlantic Oscillation (NAO) (Abualnaja et al. 2015;Barlow et al. 2016), the Mediterranean Oscillation (MO) (Hamed et al. 2021), the El Nino Southern Oscillation (ENSO) (Niranjan Kumar et al. 2016;Dogar et al. 2017) and the Indian summer monsoon (ISM) (Joseph and Zeng 2011;Liu et al. 2016). ...
... Temperatures in some parts of the region have increased at an unprecedented rate of 0.5°C per decade in winter and 1.0°C per decade in summer over the period 1900-2008(Dogar and Sato 2018. Some areas in this region already faced a temperature increase much more than the global average increase (Salman et al. 2017). Climate models also showed that the temperature in the region was projected to rise at a greater rate than in other places on the planet (Lelieveld et al. 2016). ...
Thermal bioclimate is a defining factor of agricultural production, ecological condition, public health, and species distribution. This study aimed at assessing the possible changes in the Middle East and North African (MENA) thermal bioclimate for two shared socioeconomic pathways (SSPs), SSP1-1.9 and SSP1-2.6, representing a temperature rise restricted to 1.5 and 2.0°C above the pre-industrial level at the end of the century. Therefore, the study explains the probable least change in bioclimate due to climate change and what might happen for a 0.5°C temperature rise above the 1.5°C addressed by Paris Climate Agreement. A multimodel ensemble of eight global climate models was employed for this purpose. The results indicated a 0.5°C further increase in temperature above the 1.5°C temperature rise threshold would cause a nearly 0.8 to 1.0°C increase in temperature in some parts of MENA, indicating a faster than global average increase in temperature in the region for higher temperature rise scenarios. Climate change would cause a decrease in thermal seasonality by 2-6% over nearly 90% of the study area. The diurnal temperature would decrease by 0.1 to 0.4°C over the entire south, while the annual temperature range would decrease by 0.5 to 1.5°C over a large area in the north. This would cause a decrease in isothermality nearly by 1% over most areas. The area with decreasing isothermality would expand by almost 150% for a further temperature rise by 0.5°C. The results indicate a substantial change in bioclimate in MENA for a minor temperature change.
... There are nineteen climate models of GCMs included in LARS-WG version 6, which incorporates climate projection s from CMIP5 used in the Intergovernmental Panel on Climate Change (IPCC) Fifth Assessment Report (AR5) [5]. By choosing the appropriate number of models that are appropriate and according to the study area and it is crucial to take in mind that all GCM and RCP combinations should be considered equally plausible with the assessment of the uncertainty of the future projection s of the models through validation in comparison with the baseline data for the selected locations [69]. On the basis of earlier research conducted in Iraq to assess the most suitable models to be applied in the forecasting of future climate change. ...
Climate change has placed considerable pressure on the residential environment, agricultural, and water supplies in different areas of the world, especially arid places such as Iraq. Iraq is one of the five most vulnerable countries in the world to climate change, where it has been encountering extremes heat waves during the most recent decades resulted in drought, desertification, and rivers dried up, which led to thousands of hectares to turn dry and yellow. This study aims to investigate the trends of climate change in the middle and western regions of Iraq and future expectations. The daily maximum temperature, minimum temperature, and precipitation are downscaled using the Long Ashton Research Station Weather Generator (LARS-WG) model. Five General Circulation Models (GCMs) from Coupled Model Intercomparison Project Phase 5 (CMIP5) are employed for three future periods: the near future (2021–2040), medium future (2051–2070), and far future (2081–2100), based on two scenarios of the Representative Concentration Pathways (RCP4.5 and RCP8.5) for four selected meteorological stations representing the study area. The outcomes of the calibration and validation of the model supported its skill and reliability to downscale precipitation and temperature time series for statistical indices (R², RMSE and MBE) ranging between (0.894–0.998), (0.1270–1.9274) and (− 0.6158 to 0.0008), respectively. The results showed that the average minimum and maximum annual temperatures will increase at all selected stations across the three future periods by between 0.94 and 4.98 °C by the end of the twenty-first century. Annual changes in precipitation tend generally towards increase for the study area by average (6.09–14.31%) for RCP4.5 and (11.25–20.97%) for RCP8.5 Compared to the historical data (1990–2020). These findings can contribute to become more acquainted with the effects of climate change on the environment and encourage managers and planners to come up with plans for mitigating and adapting to these effects. They can also serve as a guide for future management of water and agricultural resources in the study region.
... The significant impacts of extreme weather and climate events on society are evident in literature (Pour et al., 2014;Salman et al., 2017;Shahid et al., 2017). With the increasing prevalence of warmer trends, the risk of population exposure to extreme events increases in the climatological stressed regions (Dutta & Chaudhuri, 2015; Nashwan In the past decade, many scientists investigated climate variability induced temperature (precipitation) patterns and extreme weather events in Pakistan (Abbas et al., 2018a(Abbas et al., , 2018bAsmat & Athar, 2017;Asmat et al., 2018;Bhatti et al., 2020;Saleem et al., 2021). ...
The increasing prevalence of warmer trends and climate extremes exacerbate the population's exposure to urban settlements. This work investigated population exposure changes to mean and extreme climate events in different Agro‐Ecological Zones (AEZs) of Pakistan and associated mechanisms (1979−2020). Spatiotemporal trends in mean and extreme temperatures revealed significant warming mainly over northern, northeastern, and southern AEZs. In contrast, mean‐to‐extreme precipitation changes showed non‐uniform patterns with a significant increase in the northeast AEZs. Population exposure to mean (extreme) temperature and precipitation events increased two‐fold during 2000–2020. The AEZs in urban settlements (i.e., Indus Delta, Northern Irrigated Plain, and Barani/Rainfall) show a maximum exposure to extreme temperatures of about 70–100 × 10 ⁶ (person‐days) in the reference period (1979−1999), which increases to 140–200 × 10 ⁶ person‐days in the recent period (2000−2020). In addition, the highest exposure to extreme precipitation days also increases to 40–200 × 10 ⁶ person‐days during 2000–2020 than 1979−1999 (20–100 × 10 ⁶ ) person‐days. Relative changes in exposure are large (60%–90%) for the AEZs across northeast Pakistan, justifying the spatial population patterns over these zones. Overall, the observed changes in exposure are primarily attributed to the climate effect (50%) over most AEZs except Northern Irrigated Plain for R10 and R20 events, where the interaction effect takes the lead. The population exposure rapidly increased over major AEZs of Pakistan, which could be more vulnerable to extreme events due to rapid urbanization and population growth in the near future.
... The test identifies the median of the lines' slopes between every pair of points in the sample. It has been widely used for estimation of change in meteorological data (Salman et al. 2017;Lu et al. 2016;Thomas and Prasannakumar 2016). ...
The Eastern Mediterranean region is a major climate change hotspot. The island of Cyprus is likely to face increases in the frequency and intensity of hotter weather conditions and heatwaves in the near future. Studies conducted on the long-term temperature changes in Cyprus are very limited. Here, we present an updated and most detailed assessment of the maximum , minimum, mean and diurnal temperature series in North Cyprus for the period 1975-2021. Data obtained from the meterological stations of North Cyprus have been analysed using Mann-Kendal (MK) test and Theil-Sen slope estimator. Overall the mean minimum temperature trend (T min) showed the highest warming rate 0.61 (0.24 ≤ T min ≤ 0.99)°C decade −1 followed by the mean temperature trend (T mean) 0.38 (0.29 ≤ T mean ≤ 0.50) °C decade −1 and the mean maximum temperature trend (T max) 0.28 (0 ≤ T max ≤ 0.50) °C decade −1. The magnitude of the warming trend observed in the overall mean minimum temperature of North Cyprus 0.61 °C decade −1 , is one of the fastest warming trends reported in the literature. A negative association was detected between the direction of prevailing winds of North Cyprus and the magnitude of increase in the mean temperature trends of the locations with coastal Mediterranean climate, which has pointed out the importance of prevailing winds regarding their cooling effect in coastal areas. The diurnal temperature range trend of North Cyprus indicates an apparent decrease (− 0.33 °C decade −1). The warming impact of urban heat island effect was detected in temperature trends of Nicosia in the Mesaoria plain. The information provided here is invaluable to consider in any climate assessment and adaptation plan in Cyprus. If the current warming trend persists into the future, it will devastatingly impact all sectors and natural systems in the region.
... ET is critical for soil mois-43 ture, surface runoff, and groundwater recharge and is essential to 44 understanding the complex interaction between energy and water 45 cycles (Jiang et al. 2019;Singer et al. 2021;Zhang and Wang 46 2021). Variations in ET might considerably influence crop growth 47 and water availability, which could cause adverse implications for 48 water availability and agricultural production (Pour et al. 2020 (Allen et al. 1998a and temperature extremes are common (Salman et al. 2018b(Salman et al. , 2017. 130 Since the early 1990s, climatic events such as frequent droughts, 131 dust storms, and flash floods have been observed frequently 132 (Salman et al. 2018b in Eq. (1): The present study adopted the most widely used 40 empirical ET o 325 models in different regions and diverse climatic conditions. ...
Accurate reference evapotranspiration (ETo) estimation is crucial for water irrigation management and sustainable agriculture planning. The difficulty in obtaining several data requirements for employing the recommended Food and Agriculture Organization Penman-Monteith method (FAO-PM) for reliable estimation of ETo has led to the development of many empirical models. This is particularly crucial for Iraq, located in West Asia (latitude: 29 15‒38 15 N and longitudes: 38 45‒48 45 E), where meteorological data are often limited or missing. The objectives of the present study were to assess the performance of 40 ETo empirical models (13 radiation-based, 13 mass-transfer-based, and 14 temperature-based) against the FAO-PM model and identify alternative models with the minimal available data in three major climatic zones of Iraq: The Mediterranean climate (MCZ), the Semi-arid (SCZ), and the Arid Desert (ACZ). The recent ERA5 dataset of the European Centre (1959‒2021) was adopted. The results indicate that:(1) The Rohwer mass-transfer method is the best for estimating ETo for two-thirds of Iraq with a mean correlation coefficient (R2) of 0.97, mean Kling-Gupta Efficiency (KGE) of 0.84, mean (PBias) of -8.92%, mean Nash-Sutcliffe Efficiency coefficient (NSE) of 0.92, and RMSE-observations standard deviation ratio (RSR) of 0.27, followed by the Penman (R2 = 0.90, KGE = 0.75, NSE = 0.77, RSR = 0.46, and PBias = 6.36%) and Caprio (R2 = 0.90, KGE = 0.66, NSE = 0.54, RSR = 0.58, and PBias = 24.64%) models. (2) Caprio is the best radiation-based model for estimating ETo, mainly in the ACZ, whereas Kharrufa is the best temperature-based model for estimating ETo, primarily in the SCZ and ACZ. Overall, the mass-transfer-based models performed better than other-based models for ETo estimation. The outcomes of this study provide a scientific reference for accurate ETo estimation using empirical models under limited data sets, which is valuable for irrigation management in Iraq. © 2023 American Society of Civil Engineers.
... Both the original Mann-Kendall (MK) and its modified version (mMK) tests are often used to detect the significance of the trend in a time series; the MK test is sensitive to autocorrelation (Ullah et al., 2018b;Khan et al., 2021), which may affect its outcomes regarding significance. On the other hand, the mMK effectively nullifies the effect of autocorrelation before determining statistical significance (Salman et al., 2017;Xie et al., 2020;Hussain et al., 2022). Therefore, the present study preferred the mMK test over the MK to overcome autocorrelation in the datasets. ...
This study assessed spatiotemporal trends in daily monsoon precipitation extremes at seasonal and sub-seasonal scales (June, July, August, and September) and their links with atmospheric circulations over Pakistan. The study used observed precipitation data from fifty in-situ stations and reanalysis products from the European Centre for Medium-Range Weather Forecasts (ECMWF) and National Centers for Environmental Prediction/the National Center for Atmospheric Research (NCEP/NCAR) during 1981–2018. A suite of seven extreme precipitation indices and non-parametric statistical techniques were used to infer trends in the frequency and intensity of extreme precipitation indices. An increase in frequency and intensity of overall extreme indices was evident, with a maximum tendency in the country’s northwestern (z-score=>2.5), central, and eastern (z-score > 4) monsoon-dominant parts. The northern and southwestern parts of the country exhibited a slight decrease (z-score <–2) in frequency and intensity. The Sen’s Slope estimator (SSE) shows an increase in western parts (0.20 days) indicating a shift in the maxima of the monsoon precipitation. The regional precipitation shows an increase in wet days (R1 mm) with higher values of mMK (3.71) and SSE (0.3) in region 2 Similar results of moderate regional increase are evident for extreme indices except regions 1 and 3. The extreme 1-day maximum precipitation increased in region 3 (mMK: 1.39, SSE: 2.32). The extremely wet days (R99p TOT) precipitation has a moderate increase in all regions with a decrease in region 1. The temporal mutations showed dynamic changes, clearly reflecting the country’s historical extreme events. The frequency and intensity of precipitation extremes negatively correlated with the altitude (R = −0.00039). The probability density function (PDF) showed a significant increase in the density during June and September with a probabilistic positive shift during July and August. The intensified mid-latitude westerlies and subtropical zonal easterlies teleconnections, strengthening of the monsoon trough, and land-ocean thermal contrast are the potential drivers of the increasing trend in precipitation extremes. The current study could serve as a benchmark for future researchers and policymakers to devise effective mitigation strategies for sustainable development.
... The Northern Arabian/Persian Gulf temperature rose by 0.8 °C between 1973(Al Senafi and Anis, 2015. Iraq experienced a rising temperature of 2-7 times faster than the global rate of increase between 1965 and 2015 (Salman et al., 2017). Egypt experienced an increase in hot days and nights (Nashwan et al., 2019). ...
A fast temperature rise has made the Middle East and North Africa (MENA) region a global hotspot of extreme heat events. Previous studies conducted in the region to evaluate extreme heat based on temperature were inadequate for assessing heat based on human thermal impacts. The present study employed the Universal Thermal Climate Index (UTCI). This index evaluates the changes in heat related to human thermal stress in MENA. This analysis employed the ERA5-HEAT dataset, derived from the Copernicus climate change service portal. The results showed that all the regions experienced an average daily UTCI representing extreme heat stress for 1 to 25 days. The daily maximum UTCI goes to the extreme level on average of 1 to 175 days a year, with the highest in the east and southwest. The annual mean UTCI in MENA is increasing from 0.1 to 0.7 °C/decade, with the highest increase in the northeast, covering eastern Saudi Arabia and most parts of Iraq and Syria. This caused a decrease in cold stress and an increase in hot stress days, with the highest increase in strong thermal stress days in the range of 4 to 16 days/decade in most of MENA. The trend in daily maximum UTCI also showed an increase in the range of 0.1 to 0.6 °C/decade, which caused an increase in the number of daily maximum UTIC above 46 °C or extreme level by 1 to 16 days/per decade, with the highest increase in central Saudi Arabia, northern Sudan and southern Mauritania. This study is the first to investigate UTCI trends in the MENA region and is expected to provide valuable information on hotspots and temporal trends in UTCI, serving as a foundation for future heat action plans to prevent heat-related illnesses throughout the region.
... Southern Iraq has a desert climate, while the temperatures are significantly lower in northern Iraq. Annual precipitation reaches to an average of 179mm [13]. Precipitation in the northern mountains range from 350mm to about 900 mm. ...
Remote sensing refers to the acquisition of data and information about a phenomenon and a territory, without a direct contact with it. It is alternative to in-situ observation. Due to its wide coverage, multi-temporal and multispectral capability, remote sensing satellites have been used for studying and monitoring the spatial distribution of the aerosol pollution (like PM2.5) in the atmosphere. PM2.5 refers to atmospheric particulate matter (PM) that has a diameter of less than 2.5 micrometers, which is about 3% the diameter of a human hair. The current study concentrates on the using of R programming language to process and analyze the retrieval PM2.5 dataset over Iraq for the period (January 1, 2020 to December 31, 2020), these data were downloaded from the European Union’s Earth observation Copernicus program through the Copernicus Atmosphere Monitoring Service (CAMs). The study presented output results of the PM2.5 concentration levels by developing an automatic tool that restructuring the netCDF file into excel file using R language. In addition, it produces different valuable charts that help in practical dataset interpretation and decision-making. The results of the study showed the variation in the spatial distribution of PM2.5 in the study area due to the diversity of pollution sources from one region to another.
... Crop reference evapotranspiration (ET o ), a vital element in the hydrological cycle, plays a significant role in the effective use of existing water resources and planning sustainable water management. An immediate and certain consequence of global warming is an increase in temperature (Salman et al. 2017;Pour et al. 2019). Increasing temperature will alter ET o , which will have significant impacts on water resources. ...
The present study evaluates the capability of a novel optimization method in modeling daily crop reference evapotranspiration (ETo), a critical issue in water resource management. A hybrid predictive model based on the artificial neural network (ANN) algorithm that is embedded within the COOT method (COOT bird natural life model-artificial neural network (COOT-ANN)) is developed and evaluated for its suitability for the prediction of daily ETo at seven meteorological stations in different states of Australia. Accordingly, a daily statistical period of 12 years (01-01-2010 to 31-12-2021) for climatic data of maximum temperature, minimum temperature, and ETo were collected. The results are evaluated using six performance criteria metrics: correlation coefficient (R), root mean square error (RMSE), Nash–Sutcliffe efficiency (NSE), RMSE-observation standard deviation ratio (RSR), Scatter Index (SI), and mean absolute error (MAE) along with the Taylor diagrams. The performance of the COOT-ANN model was compared with those of the conventional ANN model. The results showed that the COOT-ANN hybrid model outperforms the ANN model at all seven stations by 0.803%, 4.127%, 3.359%, 4.072%, 4.148%, and 3.665% based on the average values of the R, RMSE, NSE, RSR, SI, and MAE criteria, respectively. So, this study provides an innovative method for prediction in agricultural and water resource studies.
Graphical abstract
... The country's topography is similar to a large basin comprised of alluvial plains of the Tigris and Euphrates Rivers surrounded by mountains in the north and the east. Based on land formation, the country can be divided into (i) mountains in the north and northwest, comprised of nearly 21% of the country; (ii) hilly undulating landscape in the south and the west of the mountainous region encompasses approximately 9.6% of the country; (iii) the central depositional plain accounts 30%; (iv) the barren western Plateau in the western Euphrates Valley comprising 39.2% of Iraq's total area (Salman et al., 2017). ...
Estimation of total water availability has paramount importance in planning sustainable development of a region, particularly in arid water-scarce areas. Coarse-resolution of existing total water availability or terrestrial water storage anomaly (TWSA) data is the major limitation of their applications in different sectors. An attempt has been made to downscale Gravity Recovery and Climate Experiment (GRACE) TWSA data to develop a high-resolution gridded data product of the total water availability of Iraq. European reanalysis (ERA5) precipitation, evapotranspiration, surface runoff, subsurface runoff and soil water contents data were used to downscale GRACE 1.0º spatial resolution monthly TWSA to 0.1º spatial resolution for the period 20022020. A machine learning (ML)-based recursive feature elimination algorithm was used to identify the optimum input combination according to the nonlinear relationship of ERA5 variables with GRACE water equivalence data. The selected subset of inputs was used to develop the downscaling models using three classical ML algorithms for the available GRACE measurement points over Iraq. The models were calibrated at 70% of GRACE grid point locations and validated in the rest of the points. Finally, the model was used to predict TWSA at each ERA5 grid point to generate Iraq's high-resolution water availability dataset. The results showed higher performance of random forest in downscaling TWSA compared to other algorithms. The model estimated the TWSA at validation points with Kling-Gupta Efficiency (KGE) in the range of 0.50.91 and Nash-Sutcliff Efficiency (NSE) between 0.54 and 0.88. The modelled high-resolution TWSA data shows higher availability of water resources in the north, particularly northeast of Iraq, and the least in the southeast. The technique developed in this study can be implemented in developing a high-resolution gridded water availability dataset from satellite GRACE data in the region where in-situ estimation is very limited.
keywords Water equivalence data; downscaling; GRACE; ERA5; machine learning.
... In general, the decrease in precipitation is a consequence of anthropogenic activities and changes in vegetation cover (Seager et al., 2009;Wehner et al., 2011;Cook et al., 2015;Touma et al., 2015;Spinoni et al., 2020). Furthermore, changes in climate systems have shown negative trends in precipitation volumes and positive trends in environmental temperatures in Mexico, generating an intensification of the drought conditions (Alexander et al., 2006;Li et al., 2009;Tabari and Talaee, 2011;Salman et al., 2017;Del-Toro-Guerrero and Kretzschmar, 2020). ...
Introduction: Drought is a slow evolution phenomenon drastically affecting the environment and human activities. Nowadays, there are several indices to study drought. They can be based on in-site measurements of meteorological stations or remote perception data. However, Mexico's number of functioning meteorological stations from the National Meteorological Service (NMS) is steadily decreasing. Nevertheless, the NMS reports drought conditions through the Mexican Drought Monitor (MDM), which uses different methods to estimate drought levels. These reports are provided every 15 days for each municipality. However, the methods the NMS utilizes are unknown to the general public. Thus, in-situ studies which try to estimate drought are limited by the MDM data constrictions. Consequently, remote perception is an alternative to solve the lack of stations and the MDM data restrictions, depending on the region. Therefore, this research aims to: 1) Develop a methodology to quantify drought intensity based on the Normalized Difference Drought Index (NDDI) with Landsat 8 multispectral images in the municipalities of the central zone of the Gulf of Mexico for drought and no drought periods. 2) Analyze and compare the NDDI behavior against the MDM from the NMS during the same periods. Methods: The methodology consisted of estimating the NDDI by using Landsat 8 multispectral images. Further on, NDDI drought values were compared with the MDM. Results: Results showed that NDDI values increase from July to October during a drought period, coinciding with months when precipitation is low, and temperature is high. Additionally, it was found that the NDDI coincides with the MDM data in 46% of the municipalities having drought conditions when temperatures increased 2.1°C and precipitations decreased by 668 mm. Furthermore, the NDDI coincided in 16% of the municipalities during no drought periods with the maximum increases in temperatures at 1.4°C and precipitation reduced by 386 mm. Discussion: The NDDI estimated by Landsat 8 images can determine drought behavior in the study zone during periods with limited reduced precipitation and temperature increases. CITATION Salas-Martínez F, Valdés-Rodríguez OA, Palacios-Wassenaar OM, Márquez-Grajales A and Rodríguez-Hernández LD (2023), Methodological estimation to quantify drought intensity based on the NDDI index with Landsat 8 multispectral images in the central zone of the Gulf of Mexico.
... Iraq is located in southwest Asia between the coordinates 28 to 38 • N and 38 to 48.5 • E and has a total land area of 438,320 km 2 [34]. Baghdad, Mosul, and Basrah are the major Iraqi cities considered for IDF curve development in this study. ...
This study generates intensity-duration-frequency curves for three important cities in Iraq using Global Precipitation Measurement Integrated Multi-Satellite Retrievals for Global Precipitation Measurement (IMERG), Global Satellite Mapping of Precipitation near real-time (GSMaP NRT), and gauge corrected (GSMaP GC) satellite precipitation datasets. Many probability distribution functions were used to fit the maximum yearly rainfall data. The Sherman equation was used to create intensity-duration-frequency (IDF) curves for rainfall intensities with 2-, 5-, 10-, 25-, 50-, and 100-year return periods, with the estimated coefficients of the best-fit distribution serving as the fitting parameters. The discrepancy between the IDF curves produced from the satellites and the observed data was used to bias correct the satellite IDF curves. The Generalized Extreme Value Distribution model best describes the hourly rainfall distribution of satellite data. GSMaP GC was the best option for creating IDF curves with higher correlations with observed data at Baghdad, Basra, and Mosul. The study indicates the necessity of gauge correction of satellite rainfall data to reduce under-and overestimating observed rainfall. GSMaP GC can reasonably estimate rainfall in a predominantly arid climate region like Iraq. The generated IDF curves may be an important step toward achieving sustainable urban stormwater management in the country.
... The Middle East and North Africa (MENA) region is considered particularly vulnerable to increasing temperatures, with temperatures rising considerably faster than the global average (Salman et al. 2017). An increase in temperature variation implies changes in both variability and averages, resulting in the To study the impact of climate change on water resources, climate projections into the future generated by general circulation models (GCMs) are fundamental. ...
This study builds on previous studies and proposes a combined approach for shortlisting and selecting representative climate simulations for impact studies in the Souss watershed in Morocco. The selection procedure consists of selecting climate simulations on the basis of predicted changes in means and extremes, climate model performance in simulating past climate and bias correction. Unlike the selection methods proposed in the literature that begin with a pre-selection of simulations based on changes in means, the approach recommended in this study involves an initial pre-selection of simulations by the ability of the models to simulate the base period climate. The proposed procedure involved selecting a set of general circulation models (GCMs) from the Phase 5 Coupled Model Intercomparison Project (CMIP5) and regional climate models (RCMs) from the Coordinated Regional Downscaling Experiment (CORDEX) project to project spatiotemporal changes in precipitation and temperature for the RCP4.5 and RCP8.5 scenarios. Climate changes between 1975–2005 and 2066–2095 were analyzed for the watershed. By 2066–2095, precipitation is projected to decrease by -12.2 to -30.1% under the RCP4.5 scenario and by -5.2 to -65.4% under the RCP8.5 scenario. Mean temperature is projected to increase by 2.3 to 2.6°C under RCP4.5 and by 4.4 to 4.7% under RCP8.5. For both scenarios, a decline in precipitation is projected while temperature is expected to increase. The Palmer Drought Severity Index (PDSI) revealed that the Souss watershed, characterized by incipient drought during the historical period, will experience mild and moderate drought in 2066–2095 under the RCP4.5 and RCP8.5 scenarios, respectively.
... Iraq generally has climates of the continental and subtropical semiarid types, except for the mountainous parts in the north and northeastern regions, which have a Mediterranean climate. Winters are generally mild, with temperatures ranging from chilly to cold, whereas summers are hot and dry, with temperatures ranging from hot in the north to extremely hot (greater than 45 • C) in the south [26]. The semi-arid climate puts the country at serious risk from climate change consequences. ...
Ambitious plans for the decarbonization of the global energy system necessitate the scaling up of renewable energy exploitation. This could render the energy supply system more susceptible to the effects of climate change as most renewables are climate-dependent by nature. Therefore, understanding the consequences of climate change on renewable energy systems at a regional level plays an important role in the financial management, process optimization, and energy yield assessment of these systems. In this work, the key objective is to examine the projected impacts of surface insolation and temperature fluctuations on the future photovoltaic (PV) energy potentials in Iraq. Projections are quantified across two climate scenarios, RCP4.5 and RCP8.5, which represent the intermediate and worst-case scenarios in which insolation will rise by 4.5 and 8.5 W/m2 by the beginning of the next century. The results show that the average temperature across the country is anticipated to rise by 1.5 °C and 2.4 °C under RCP4.5 and RCP8.5, respectively. The results also show that the change in solar PV potential relative to current climatic conditions, would be −0.3 to 8.1% under RCP4.5 while it is −5.1 to 6.3% under RCP8.5 by the beginning of the next century. The highest potentials are predicted in the western parts, and the greatest drops are in the southeastern parts. Temporal stability of PV potentials also appears to be little affected by future climatic scenarios, with some southern parts even indicating a little positive rise. So, even though climate change is expected to cause small drops in PV output in some areas, it is unlikely to pose a danger under RCP4.5 to PV productivity in Iraq.
... The nonstationarity in hydrometeorological variables, such as precipitation (Dhakal et al. 2015;Gu et al. 2019;Vu and Mishra, 2019), temperature (Aziz et al. 2020;Carney et al. 2020;Kärner, 2002), and drought index (Das et al. 2020;Kwon and Lall, 2016;Wu et al. 2020), has been extensively studied. Most of the existing research has focused on the long-term trends of hydrometeorological variables (Byakatonda et al. 2018;Meshram et al. 2017;Salman et al. 2017) and on the change-points in these variables (Ahmadi et al. 2018;Jiang et al. 2019;Liu et al. 2020). Such studies have discovered that, under the increasing influence of global warming, more high temperature events and extreme droughts have shown increasing trends of occurrence in the United States (Ge et al. 2016), China (Ye et al. 2019), Southeast Asia (Dong et al. 2021), Australia (Sharples et al. 2021), and Brazil (Geirinhas et al. 2021). ...
Most of studies on change-point at a regional or global scale have only examined a single hydrometeorological variable and have been unable to identify any underlying explanations. In this study, we identified change-points and long-term trends of six wildfire-related variables and attempted to explain the cause of change-point from atmospheric–oceanic indices. As a result, we discovered that the main change-point dates for the precipitation, temperature, and drought codes, as well as the duff moisture code, fine fuel moisture code, and fire weather index, were 1995–2000 and 2000–2005, respectively. Furthermore, the relationship between the change-point of six variables and atmospheric–oceanic indices was discussed through the correlation coefficient. For example, the Atlantic Multidecadal Oscillation was found to dominate the precipitation in West Africa. In addition, we divided the globe into eight homogenous wildfire weather zones based on the change-point dates and long-term trends of the six variables.
... Küresel ısınma bazı bölgelerde çok şiddetli gerçekleşmektedir. Örneğin Irak'taki sıcaklık artışının küresel sıcaklık artışından 2 ila 7 kat daha hızlı olduğu ve minimum sıcaklıkların maksimum sıcaklılardan daha çok arttığı ifade edilmiştir [9]. ...
Antalya is one of the most important cities of Turkey in terms of agriculture, tourism and population. In this study, the global warming case of Antalya was investigated by using the monthly mean maximum, monthly mean minimum and monthly mean temperature data of Elmalı, Korkuteli, Antalya, Manavgat and Gazipaşa meteorology stations between 1970 and 2017. For this aim, trend analyses were performed by Mann Kendall Rank Correlation method and beginnings of trends were determined. Run, interquartile range and autocorrelation tests were applied before trend analysis test. 99.99% confidence interval was used for all tests. Run test results indicated that the data is homogenous. According autocorrelation test results, there is not autocorrelation in tha data except monthly mean minimum temperature data of Antalya station for August. Therefore, prewhitening was used for monthly mean minimum temperature data of Antalya station for August. The 12-month average value of the increasing trend was calculated as 98.33% for the mean temperature, 88.33% for the mean maximum temperature and 80% for the mean minimum temperature. The 12-month average value of the statistically significant increasing trend was calculated as 10% for the mean temperature, 5% for the mean minimum temperature and 0% for the mean maximum temperature. If 95% confidence level was used for Mann-Kendall test, the 12-month average value of the statistically significant increasing trend was calculated as 61.9% for the mean temperature, 34.5% for the mean maximum temperature and 51.2% for the mean minimum temperature. These results show that there is global warming in Antalya. The beginnings of statistically significant trends vary between 1992 and 2009. While water consumption is increasing due to increase in agriculture, tourism and population in Antalya, the global warming detected in this study shows that both water consumption and losses in water resources will increase further. Precautions are suggested in the results section.
... Only ten temperature extremes were implemented in this study as they are the most applicable in this study area (Table 1). These extremes were used in the nearby arid region as thresholds for estimating temperature extremes (Salman et al. 2017;Salehie et al. 2022b). The indices were selected from the Expert Team on Climate Change Detection and Indices (ETCCDI) recommended list considering their relevance to the climate of Egypt. ...
Global warming has amplified the frequency of temperature extremes, especially in hot dry countries, which could have serious consequences for the natural and built environments. Egypt is one of the hot desert climate regions that are more susceptible to climate change and associated hazards. This study attempted to project the changes in temperature extremes for three Shared Socioeconomic Pathways (SSPs), namely, SSP1-2.6, SSP2-4.5, and SSP5-8.5 and two future periods (early future: 2020-2059 and late future: 2060-2099) by using daily maximum (T max) and minimum temperature (T min) of general circulation model (GCMs) of Coupled Model Inter-comparison Project phase 6 (CMIP6). The findings showed that most temperature extreme indices would increase especially by the end of the century. In the late future, the change in the mean T min (4.3 °C) was projected to be higher than the mean T max (3.7 °C). Annual maximum T max , temperature above 95th percentile of T max , and the number of hot days above 40 °C and 45 °C were projected to increase in the range 3.0-5.4 °C, 1.5-4.8 °C, 20-95 days, and 10-52 days, respectively. In contrast, the annual minimum of T min , temperature below the 5th percentile, and the annual percentage of cold nights were projected to change in the range of 2.95-5.0 °C, 1.4-3.6 °C, and − 0.1-0.1%, respectively. In all the cases, the lowest changes would be for SSP1-2.6 in the early period and the greatest changes for SSP5-8.5 in the late period. The study indicates that the country is likely to experience a rise in hot extremes and a decline in cold extremes. Therefore, Egypt should take long-term adaptation plans to build social resiliency to rising hot extremes.
... Båld (2022) identified drought and water scarcity as Iraq's most serious environmental concerns. Climate change is causing a temperature rise in Iraq much faster than in any other country in MENA (Salman et al. 2017). A decline in precipitation has also been noticed in Iraq in recent decades (Salman et al. 2018a). ...
Semiarid climate has made Iraq one of the most vulnerable regions to droughts. Semiarid climate has made Iraq one of the most vulnerable regions to droughts. Rising temperatures and declining precipitation, as projected by climate models, would aggravate droughts in the country. This study examined the spatiotemporal variation of drought in Iraq using CMIP6 models for the shared socioeconomic pathways (SSPs). The historical simulations of 21 GCMs were evaluated to choose a GCM subset. A support vector machine (SVM) was used to downscaled the simulations of the selected GCM to 0.5° resolution. Downscaled simulations were used to estimate drought employing standardized precipitation evapotranspiration index (SPEI) for the near (2020–2059) and far future (2060–2099) in comparison to the reference period (1975–2014). EC-Earth3-Veg, BCC-CSM2-MR and ACCESS-CM2 performed the best in simulating Iraq's climate. Historical drought simulation revealed northern Iraq is most prone to droughts of all severities and time scales. The projections of drought revealed a decline in drought frequency in the near but a large rise in the late period. A greater decline in the near future and a rise in the far future were projected for SSP2-4.5 and SSP5-8.5. In both scenarios, drought frequency for all severities was projected to decrease between 0 and 40% in the near future, while moderate and severe droughts were to increase by up to 45% in the far future. Most scenarios showed a decrease in extreme droughts up to 30% in the drought-prone northern region, signifying a shift in the extreme drought-prone zone in Iraq. Drought management in Iraq can be benefited from the maps created in this study. The drought projections for SSPs can be used to update the strategies adopted based on RCPs.
... Only ten temperature extremes were implemented in this study as they are the most applicable in this study area (Table 1). These extremes were used in the nearby arid region as thresholds for estimating temperature extremes (Salman et al. 2017;Salehie et al. 2022b). ...
Global warming has amplified the frequency and other properties of temperature extremes, especially in hot dry countries, and significantly affected the environment. Egypt is one of the hot desert climate regions that are more susceptible to climate change and associated hazards. This study attempted to project the changes in temperature extremes for three Shared Socioeconomic Pathways (SSPs), namely SSP1-2.6, SSP2-4.5, and SSP5-8.5 and two future periods (early future: 2020–2059, and late future: 2060–2099) by using annual maximum (Tmax) and minimum temperature (Tmin) of general circulation model (GCMs) of Coupled Model Inter-comparison Project phase 6 (CMIP6). The findings showed that most temperature extremes indices would increase especially by the end of the century. In the late future, the change in the mean minimum temperature (4.3°C) was projected to be higher than the mean maximum temperature (3.7°C). The number of hot days would increase by more than 80 days in the late future over the south and southeast of the country. Contrarily, the cold night temperatures would decrease by -0.95 to -3.0°C for different SSPs. The study indicates that the country is likely to experience an additional hotter climate rather than a colder one.
... We applied the modified Mann-Kendall method (MMK) (Hamed et al., 1998) to check the significance and magnitude of trends in the 10 EPIs. The MMK method not only considers the effect of auto-correlation in time series but also strengthens the ability of distinguishing the multidecadal oscillatory variations from secular trends (Salman et al., 2017). Detailed processes for implementation of the MMK method can be found in Huang et al. (2014). ...
Precipitation extremes have large influences on hydrological, ecological and agricultural systems. This study aimed to investigate variations of precipitation extremes in China's mainland over 1961–2100 based on 27 newly released General Circulation Models (GCMs) in Coupled Model Intercomparison Project phase 6 (CMIP6) under four shared socioeconomic pathway scenarios (SSPs). 10 extreme precipitation indices (EPIs) were extracted for quantifying changes of precipitation extremes. A statistical downscaling method was applied to downscale original precipitation data from the GCMs. Taylor diagram and interannual variability skill methods were used to evaluate performance of the downscaled GCM data for simulating the EPIs. The results displayed that: (1) The downscaled 27 GCMs performed well for the wet EPIs. Based on the multi-model ensemble results, more severe and frequent precipitation extremes over 2015–2100 were projected. (2) The largest changes in extreme precipitation intensities over 2015–2100 would occur in central and southeast China. The maximum changes in extreme precipitation frequencies would occur in Tibetan Plateau and central and southern China. (3) Precipitation extremes in Xinjiang and Tibetan Plateau would be more sensitive to climate change than other sub-regions. The future EPI generally have longer than 10-year of primary periods. (4) The GCMs had larger contribution than the SSPs to the uncertainty in projecting the 10 EPIs. (5) CMIP6 models performed better than CMIP5 models in reproducing interannual variations of EPIs. This study supplies useful information to cope with future intensified precipitation extremes in China.
... Furthermore, most research in the cold and temperate regions has focused on new species (3)(4). Iraq is one of the warmest countries on the planet, mainly because of the range of extreme environmental and climatic conditions (5). Iraq's grows naturally in saline lands (halophytes), with some other types of plants such as Alhagi maurorum, Salsola longifolia and Haloxylon articulatum, all of which are classified as perennial halophytes (8). ...
Background and Objectives: Yeasts are an important portion of microbial communities of soil due to their bioactivity for ecosystem safety. Soil yeast abundance and diversity are likely to be affected under harsh environmental and climatic conditions. In Iraq, human activity and climatic changes especially high temperature which may alter microbial communities in soil. Very little is known about yeast abundance and diversity in a hot climatic region. Materials and Methods: By PCR technique, soil yeast abundance and diversity were investigated under extreme environmental and climatic conditions, as well as the effects of soil properties and vegetation cover in semi-arid lands. Results: In all, 126 yeast strains were isolated and identified as belonging to 13 genera and 26 known species. The maximum quantity of yeast was 0.8 × 10 2 CFU g-1 of soil, with significantly varied in abundance and diversity depending on soil properties and presence of vegetation. Conclusion: The results show that soil yeast abundance in these regions was significantly decreased. However, semi-arid lands are still rich in yeast diversity, and many species have adapted to survive in such conditions.
... Iraq suffers from temperature raising due to natural factors such as drought, insufficient rainfall, and desertification. Iraq's temperature is rising at a rate that is 2 to 7 times higher than the global average, the minimum temperature (0.48-1.17 °C/decade) is rising faster than the maximum temperature (0.25-1.01 °C/decade) (Salman et al., 2017). As a result, natural vegetation, food production, and land fertility have decreased in Iraq (Mzuri et al., 2021a). ...
The temperature rise has become a serious environmental concern affected by both human and natural factors. Worldwide, rising land surface temperatures have emerged as the most pressing issue facing the twenty-first century. In the last two decades, a curious change was realized in temperature in the Duhok district of Iraq. Hence, this study examined the spatiotemporal land surface temperature distribution and Modified Soil Adjusted Vegetation Index (MSAVI2) and the correlation between them in the Duhok district in three different years 2001, 2011, and 2021 using Landsat satellite images. Air temperature data from seven weather stations were used to validate the land surface temperature results. The study's findings revealed that the Duhok district’s LST has risen during the study period. In general, the average land surface temperature has been increasing at a rate of 0.15 °C per year. Other findings showed that the vegetation cover of the Duhok district has changed dynamically. In all three years of study, the regression analysis results indicated that there was a negative correlation between LST and MSAVI2. This method of evaluation will be useful in guiding future urban management work and local government strategies.
... Water scarcity is predicted to increase due to climate change, increasing water consumption upstream (Turkey, Iran, and Syria) [5]. There is also evidence that the temperature in Iraq will rise two to seven times faster than the world average, according to Salman et al. [6]. Furthermore, Iraq's future rainfall patterns and amounts are anticipated to be significantly affected based on various forms of analyses and scenarios [7]. ...
Accurate streamflow prediction is significant when developing water resource management and planning, forecasting floods, and mitigating flood damage. This research developed a novel methodology that involves data pre-processing and an artificial neural network (ANN) optimised with the coefficient-based particle swarm optimisation and chaotic gravitational search algorithm (CPSOCGSA-ANN) to forecast the monthly water streamflow. The monthly streamflow data of the Tigris River at Amarah City, Iraq, from 2010 to 2020, were used to build and evaluate the suggested methodology. The performance of CPSOCGSA was compared with the slim mold algorithm (SMA) and marine predator algorithm (MPA). The principal findings of this research are that data preprocessing effectively improves the data quality and determines the optimum predictor scenario. The hybrid CPSOCGSA-ANN outperformed both the SMA-ANN and MPA-ANN algorithms. The suggested methodology offered accurate results with a coefficient of determination of 0.91, and 100% of the data were scattered between the agreement limits of the Bland–Altman diagram. The research results represent a further step toward developing hybrid models in hydrology applications.
... Hamed (2008Hamed ( , 2009) modified the MK (MMK) method to resolve the issue of the LTP in time series, thus improving the capability of the MK test to discriminate multi-scale variability from the unidirectional trend. In recent years, the application of MMK test in several studies also confirmed that the trends previously obtained using MK test are mostly caused by multi-decadal variability and cannot be expected to continue (Khan et al. 2018a;Lacombe and Rockstroh 2012;Markonis and Koutsoyiannis 2016;Salman et al. 2017aSalman et al. , b, 2018. This highlights the importance of re-assessments of climatic trends by involving the influence of LTP or long-term autocorrelation. ...
... Reference evapotranspiration (ETo), which is one of the vital elements in the hydrological cycle, plays an important role in the effective use of existing water resources and important planning in water management. An immediate and certain consequence of global warming is an increase in temperature (Salman et al. 2017;Pour et al. 2019). Increasing temperatures will alter ETo, which will have significant impacts on water resources. ...
The present study evaluates the capability of a novel optimization method in modeling daily reference evapotranspiration (ET 0 ), a critical issue in water resource management. A hybrid predictive model based on the ANN Algorithm that is embedded within the COOT method (COOT bird natural life model- Artificial Neural Network (COOT-ANN)) is developed and evaluated for its suitability for the prediction of daily ET 0 at seven meteorological stations in different states of Australia. Accordingly, a daily statistical period of 12 years (01-01-2010 to 31-12-2021) for climatic data of maximum temperature, minimum temperature, and ET 0 were collected. The results are evaluated using six performance criteria metrics: correlation coefficient (R), Root Mean Square Error (RMSE), Nash-Sutcliffe efficiency (NSE), RMSE-observation standard deviation ratio (RSR), Scatter Index (SI), and mean absolute error (MAE) along with the Taylor diagrams. The performance of the COOT-ANN model was compared with those of the conventional ANN model. The results showed that the COOT-ANN hybrid model outperforms the ANN model at all seven stations; and so this study provides an innovative method for prediction in agricultural and water resources studies.
... In addition, when the successive ten-year time period of the last 40 years is examined individually, each decade has been recorded as warmer than the previous one (IPCC, 2021). Furthermore, the increase in average temperatures in some regions is more than in the earth's average temperature (Salman et al., 2017). The effects of climate change have an increasing trend on a global scale, which is significant in evaluating future climate changes and mitigation of their effects on a regional scale. ...
In this study, future projections of monthly total precipitation and monthly average temperatures are carried out using 22 global circulation models (GCMs) from phase 6 of the Coupled Model Intercomparison Project (CMIP6) of the Mediterranean region. The Multi-Model Ensembles (MME) are created with GCMs that best estimate observed values with the Artificial Neural Networks (ANN) based statistical downscaling method. The performance of GCMs is evaluated with six different statistical performance criteria. The MMEs are found to be better than used individual GCMs in simulating historical temperature and precipitation in the region. The projections are made for the years 2021–2100 according to the two integrated scenarios of socio-economic development and greenhouse gas emissions (SSP2–4.5, SSP5–8.5). The projections with the MMEs show that decreasing precipitation is calculated as 15% for SSP2–4.5 and 20% for SSP5–8.5. Also, the increase in temperature is found between 1.0 and 2.2 °C and between 1.8 and 3.1 °C for the SSP2–4.5 and SSP5–8.5, respectively. In addition, the possible decrease in precipitation in the coastal part of the region is higher than in other regions. On the other hand, possible temperature increases in the region's high altitudes have been determined more than in the coastal areas.
... The approach is resilient against outliers and missing numbers and is less susceptible to abrupt breakpoints [16]. The test is susceptible to a serial correlation which might impact the test outcomes [17], [18]. The sequential correlation strategy was used in the present study to assess the statistical significance of trends in the climatic data set before the MK test was run. ...
The monthly ground-based precipitation data from 39 stations were utilized to analyze the variation in Punjab Province from 1960-2019. The Mann-Kendall method was employed to evaluate precipitation spatial-temporal trends. There are also major periods, from 1974 to 1977 and 2009 to 2015, with rising yearly precipitation. The southern Punjab area noted a greater value of the coefficient of variation (CoV) for yearly precipitation. Summer & winter season showing increasing trend on overall stations. In contrast, autumn and spring show a decreasing trend for many stations. It can be found that the Punjab province has become wetter in summer and winter from the period of 1961 to 2019.
... The climate of Al-Najaf desert is characterized by extremely hot summers and cool winters, with future scenarios indicating a global increase in temperatures due to global warming; in the last several years, in fact, temperature extremes reached 50 °C in southern parts of Iraq during summer [24], with maximum peaks of 54 °C in the southern desert [47]. The annual average of minimum temperature is increasing faster than maximum temperature and the overall temperature in Iraq is found to increase much faster compared to the global average [48]. Although precipitation is generally very low, the region receives transitory violent rainstorms in winter, which result in the uprooting of some trees [37,38]. ...
Many thousands of tree species are declining in the world, for which conservation actions are urgent. This dramatic situation is particularly evident for trees closely related to freshwater ecosystems, considered the environments most threatened by global change. In extremely arid environments such as deserts, where the few plant species present are able to survive by exploiting the little water available, the situation is extremely critical. A representative case is Vachellia gerrardii subsp. negevensis, a tree with a wide distribution range but locally restricted to small and isolated populations. Knowledge about this tree is incomplete in Iraq and, to fill this gap, several surveys were conducted in the Al-Najaf desert over three years (2019-2021). In each locality where this species was found, several ecological and population parameters were recorded. Our results indicate that Vachellia gerrardii subsp. negevensis was restricted to a single population, fragmented into five subpopulations confined in extremely peculiar ecological niches. Several threats related to anthropogenic activities and climate change affect the population, causing a significant reduction in the population size combined with a continuous decline in habitat quality and number of mature plants. Despite this critical situation, there are no conservation measures for this species. The establishment of a national preserve or part would be important and constitutes the fundamental prerequisite for the conservation of multiple species.
... At present, most researches mainly used the extreme climate indices defined by the Expert Team on Climate Change Detection and Indices (ETCCDI) to analyze the temporal and spatial distribution characteristics of high temperature and its changing laws (Khan et al., 2018;Mcgree et al., 2019;Poudel et al., 2020;Ruml et al., 2017;Salman et al., 2017;Zhang et al., 2019). Zhou et al. (2016) analyzed the temperature indices changes in China from 1961 to 2010 and the results indicated that the warm extremes in China exhibited an increasing trend. ...
The daily highest air temperature (Tmax) is a key parameter for global and regional high temperature analysis which is very difficult to obtain in areas where there are no meteorological observation stations. This study proposes an estimation framework for obtaining high-precision Tmax. Firstly, we build a near-surface air temperature diurnal variation model to estimate Tmax with a spatial resolution of 0.1∘ for China from 1979 to 2018 based on multi-source data. Then, in order to further improve the estimation accuracy, we divided China into six regions according to climate conditions and topography and established calibration models for different regions. The analysis shows that the mean absolute error (MAE) of the dataset (https://doi.org/10.5281/zenodo.6322881, Wang et al., 2021) after correction with the calibration models is about 1.07 ∘C and the root mean square error (RMSE) is about 1.52 ∘C, which is higher than that before correction to nearly 1 ∘C. The spatial–temporal variations analysis of Tmax in China indicated that the annual and seasonal mean Tmax in most areas of China showed an increasing trend. In summer and autumn, the Tmax in northeast China increased the fastest among the six regions, which was 0.4∘C per 10 years and 0.39∘C per 10 years, respectively. The number of summer days and warm days showed an increasing trend in all regions while the number of icing days and cold days showed a decreasing trend. The abnormal temperature changes mainly occurred in El Niño years or La Niña years. We found that the influence of the Indian Ocean basin warming (IOBW) on air temperature in China was generally greater than those of the North Atlantic Oscillation and the NINO3.4 area sea surface temperature after making analysis of ocean climate modal indices with air temperature. In general, this Tmax dataset and analysis are of great significance to the study of climate change in China, especially for environmental protection.
... The estimated prevalence was high (31%), with the most significant incidence of myiasis monitored during April and July. Probably the main reason, from north to south, Iraq has tropical weather and the most extended summer, with temperature increased 2 to 7 times faster than global temperature (24). The temperature shown above is a linearly optimal degree for unleashing screwworm flies, leading them to become overly abundant and potentially causing infestation (25). ...
Abstract
Thepresent study was carried out to describe some epidemiological facts of myiasis infestations in cattle; therefore, Staphylococcus aureus was isolated and identified from various infested sites with maggots from February to September 2019. It involved three districts (Shatt-Alarab, Al-Qurnah, and Al-Dyr) north of Basrah Governorate/Iraq. A total of 54 herds/owners were visited, with 150 cattle were found to be infested with maggots and diagnosed from different sites of the animal body. The result was indicated that 31% (95%Cl, 26.9-35.4) of examined animals were infested with myiasis, and there were no significant differences detected between sex and ages of the animal groups under study. Staphylococcus aureus was diagnosed using classical methods as morphological characteristics, physiological (coagulase tube method), biochemical tests, and growth on selective medium as Mannitol Salt Agar (MSA) at a percentage of 32% (48/150). Polymerase chain reaction (PCR) was performed to amplify the nuc gene in this isolated species, indicating the presence of nuc size (423) bp compared with a ladder used. The study clearly states that myiasis is a severe threat to cattle populations and that veterinary and agriculture authorities must recall control measures. These measures should be forged to include using a trapping/catch system, applying effective treatment, spraying pesticides, and sterilizing male flies with radiation to inhibit producing offspring.
Keywords: Myiasis infestation, identification Staphylococcus aureus, cattle owners, Basrah province.
... In term of the climatic changes, Iraq is highly affected by the global climatic changes due to its position in the arid area (Salman et al, 2017). Extensive variance in precipitation, temperature which in turn affected on the water discharge rates and increase the salinity (IPCC, 2007;Feleke et al., 2016). ...
In this study, four sites were selected,extended from Haditha reservoir to Al- Hindiya Barrage included Al- Ramadi and Al- Falluja sites, on Euphrates River stretch to conduct an environmental study about the effect of deceasing discharge on the water quality for the period extended from 2005 to 2020. Shedding light on the climate parameters as one of the most effective parameters on the discharge rate. As a novel aspect of this study, the discharge records, as well as the organic and inorganic pollutants were assessed, which includes;major ions (cations and anions), trace elements and the most important biological analysis such; (BOD5, COD, E. coli, fecal coliform bacteria and total bacteria count (TBC) MPN/100 ml). For this purpose, the statistical package for social sciences (SPSS), asmulti variant analysishas been applied to evaluate variables sources groups. The results revels two groups of pollutant sources; (F1) which represented 71.27%of total variance, having Eigen value 4.9, includes the pollutants resulting from anthropogenic sources as; total dissolved solids, E. coli, total bacteria count, Fecal coliform bacteria (FCB), BOD5 and COD.
... The nonparametric trend diagnosis was done by Mann-Kendall (MK) test in this study. MK test is used because of the detection of trends in meteorological data series, it has been widely used (Salman et al. 2017). Therefore, the Mann-Kendall test is applied to rainfall data from 1961 to 2019. ...
The meteorological drought dynamics and its impacts on rice productivity has been evaluated for the Indian Summer Monsoon Rainfall (ISMR) season using the standardized precipitation index (SPI) over the middle Gangetic plains (MGP) of Bihar. The meteorological drought over the ISMR period was found to be a recurring phenomenon coinciding with the rice growing season over Bihar. The rice crop has an intensive water requirement; therefore, it is significantly impacted by the meteorological droughts. In the present study, spatiotemporal characteristics viz. intensity, frequency, and probability of meteorological drought has been assessed along with an investigation for significant trends and detection of regime shift points to identify the impact of drought on rice production. For the purpose, SPI-4 derived from high resolution gridded daily rainfall data (0.25° × 0.25°) from India Meteorological Department (IMD) has been considered to analyse the meteorological drought episodes over agro-climatic zones of Bihar from 1961 to 2019. The regime shifts were determined using the Rodionov test for the drought dynamics and production of rice in Bihar. A moderate to severe drought-prone zone was found over the zone BRZ3B; while zone BRZ2 and BRZ3A showed comparatively a greater number of mild drought events persisting with more than 70% probability of occurrence. An inkling of increasing dependency on groundwater is found, which is in turn governing the rice production regime. The present study shows there is a substantial need for climate resilience and food security policies incorporating the subtle linkage between SPI variability and crop production, especially over rice producing regions of the globe.
... The Mann-Kendall test is a nonparametric test method, which is widely used to detect the long-term change trend and mutation point of the precipitation and temperature [38,39]. The formulas were as follows: where k = 1, 2, …, n; ( ) ...
The aim of this study was to identify the impacts of different driving factors on terrestrial ecosystem evolution. The Yellow River Basin was selected as the study area, of which terrestrial ecosystem was deeply affected by climatic change and human activities. We constructed four scenarios (including without any impacts, affected by climate change, by human activities and by both impacts), and the discrepancies between them reflected the impacts of climate change or human activities. Based on this, the future land use simulation model was used to simulate the land use distribution under the four scenarios, and then, the ecosystem services values (ESV) and landscape patterns index were evaluated. The results indicated that affected by climate change during 1995–2015, the Mean Patch Area of the forestland decreased by 0.19% and the landscape patterns became fragmented. Meanwhile, the total ESV decreased by 0.03 billion dollars and the ecosystem regulation services were weakened. Under the influences of human activities, the Contagion index decreased by 1.71% and the landscape patterns became dispersed. Simultaneously, the total ESV increased by 0.56 billion dollars, but the function tends to be unitary. In addition, these effects showed great spatial heterogeneity. This study provides scientific support for ecological protection in the Yellow River Basin.
... The estimated prevalence was high (31%), with the most significant incidence of myiasis monitored during April and July. Probably the main reason, from north to south, Iraq has tropical weather and the most extended summer, with temperature increased 2 to 7 times faster than global temperature (24). The temperature shown above is a linearly optimal degree for unleashing screwworm flies, leading them to become overly abundant and potentially causing infestation (25). ...
The present study was carried out to describe some epidemiological facts of myiasis infestations in cattle; therefore, Staphylococcus aureus was isolated and identified from various infested sites with maggots from February to September 2019. It involved three districts (Shatt-Alarab, Al-Qurnah, and Al-Dyr) north of Basrah Governorate/Iraq. A total of 54 herds/owners were visited, with 150 cattle were found to be infested with maggots and diagnosed from different sites of the animal body. The result was indicated that 31% (95%Cl, 26.9-35.4) of examined animals were infested with myiasis, and there were no significant differences detected between sex and ages of the animal groups under study. Staphylococcus aureus was diagnosed using classical methods as morphological characteristics, physiological (coagulase tube method), biochemical tests, and growth on selective medium as Mannitol Salt Agar (MSA) at a percentage of 32% (48/150). Polymerase chain reaction (PCR) was performed to amplify the nuc gene in this isolated species, indicating the presence of nuc size (423) bp compared with a ladder used. The study clearly states that myiasis is a severe threat to cattle populations and that veterinary and agriculture authorities must recall control measures. These measures should be forged to include using a trapping/catch system, applying effective treatment, spraying pesticides, and sterilizing male flies with radiation to inhibit producing offspring.
... Extreme heat events are becoming more frequent around the country. Over the past 100 years, precipitation has been highly variable with different trends in different parts of the country (Salman et al. 2017). In Iraq, November typically brings wet weather after long dry summer. ...
Rainfall is most important factor influencing the atmospheric cycle of the atmosphere, since its spatial and temporal distributions are very complex. Heavy rainfall events may cause flash floods in the arid and semi-arid regions Middle East. The present study investigates the synoptic and dynamics situations of four extreme rainfall events that occurred in Iraq on 04, 15, 24, and 30 of November 2018. Rainfall data were acquired from the Global Precipitation Mission (GPM), and surface and upper meteorological variable were acquired from the European Centre for Medium-Range Weather Forecasts (ECMWF) Reanalysis v5 (ERA5). The Rainfall analysis showed that November 2018 was characterized by the most unusual heavy rain events during the past two decades with a maximum of 200 mm/month (an anomaly of about 120 mm/month) near the town of Kut in the east part of the country (with an anomaly of about 120 mm/month). Analysis of surface and upper level charts indicated that during the four events the region was dominated by the Active Red Sea Trough (ARST), a situation when RST at the surface is associated by mid-tropospheric trough. The results also denoted that moisture was transported from equatorial north east Africa and the Red Sea towards north east regions including Iraq. The 850 hPa chart denoted that the warm moist air was advancing towards the cooler areas with a maximum speed of 20 m/s above the axis of the RST. The negative vertical pressure velocity along with high values of relative humidity suggests that cloud continued to develop at that level. 500 hPa charts showed that during all four events there was a positive vorticity advection towards the areas where rain was falling. This advection process contributes to a lifting of the air to upper levels. The 200 hPa composite maps of polar front jet stream and ageostrophic divergence indicated that in all four events there were high air suction from lower levels which enforced upward vertical motion at these levels and deepening low pressure areas at the surface.
... Iraq climate regions can be categorised into four divisions: I, Mediterranean climate (dry summer subtropical), which includes the mountainous zone, which is 21% of the total area; II, steppe climate (9.6% of the total area); III, subtropical semi-arid steppe, which represents the Mesopotamian plain zone, 30.2% of the total area; and IV, subtropical desert, which includes the western plateau, 39.2% of the total area (Salman et al., 2017 as shown in Figure 1(c). Combustion operations from natural gas correlated with oil production, has resulted in the release of millions of tonnes of pollutants into the atmosphere. ...
One of the greatest challenges facing the world today is global warming. Long-term analysis of spatiotemporal variations in widespread heat days (WHDs) is one approach to monitoring this phenomenon, rather than focusing on the temperature trend. The objective of this study was to reconstruct the temporal and spatial variation of WHDs in the Middle East and North Africa (MENA) using the long-term NOAA/CIRES/DOE 20th Century Reanalysis (V2) (20CRv2) reanalysis data between 1871 and 2012. Based on a 90% probability of occurrence, the temperature threshold for detecting WHDs was defined to be different for each grid point. Then, most WHDs of each month (142 samples) were identified based on the connected component labelling method. The results showed that most WHDs for each month occurred mainly after 2000. In general, the western parts of Iran, Syria, southern Turkey, Saudi Arabia, Kuwait, Egypt and northern Sudan had the highest density of WHDs. In the second period (1941–2012), the extent of WHDs increased compared to the first period (1871–1941). The spatial relationship between WHDs density in the first and second periods showed no statistical relationship, indicating that WHDs were completely different in the two periods. The results of this study contribute to a better understanding of the effects of global warming by using the relatively longest data sets. The comparison between the two periods shows that the WHDs in MENA have changed in extent (instead of variability).
Link: https://iraq.un.org/en/130256-climate-change-risks-and-opportunities-iraqi-agrifood-value-chains-itc
Climate change hazards are affecting the competitiveness of farmers and agribusiness in Iraq, according to a new report by the International Trade Centre (ITC). Although the number of farmers adopting sustainable farming practices is increasing, resilience to climate change is constrained by weak markets for climate adapted seeds and water efficient technologies, lack of climate-proofed infrastructure and limited access to finance.
These findings are detailed in the report “Climate Change risks and opportunities in Iraqi agri-food value chains” published as part of the European Union (EU) funded ITC project “Strengthening the agriculture and agri-food value chain and improving trade policy in Iraq” ( SAAVI).
The report maps out key climate change risks affecting the tomato and animal products value chains in Iraq and quantifies their impacts on sector competitiveness.
Climate and environmental risks for agribusiness are pervasive in Iraq. The main risk is the scarcity and poor quality of water, due to regional climate-change, a lack of international water regulation, poor water management practices and ageing infrastructure.
Other environment-related hazards include degraded soils, animal stress from high temperatures, and an absence of cold storage and transport equipment. These risks reduce agri-business competitiveness as farmers and businesses cope with crop failures and livestock losses, high input prices and post- harvest losses. All of this hampers farm productivity, limiting investment in adaptation measures and threatening product safety and quality.
Building resilience to climate risks requires access to finance, inputs such as climate-adapted seeds, water efficient technologies and extension services, all of which are weak in Iraq. Despite these challenges, the report finds that farmers and agribusiness are adopting basic yet effective solutions for adaptation to climate change
There is potential for Iraq to meet the growing demand for climate related goods and services, for example organic greenhouse farming and water purification services, and there are key roles for young entrepreneurs to play in fostering innovation in these markets.
About SAAVI
Strengthening the Agriculture and Agri-food Value Chain and Improving trade policy in Iraq (SAAVI) project contributes to inclusive economic growth and job creation, particularly for youth, by improving Iraq’s agriculture competitiveness and supporting trade development. The project began in November 2020, with a budget of EUR 22.5 million, is funded by the European Union (EU) and implemented by ITC..
The project forms part of the overall EU special measure for supporting employment creation and improving economic governance in Iraq.
Climate change is a phenomenon that has affected natural ecosystems and all aspects of human life in recent years. Therefore, identifying and predicting climate change can greatly help manage it and reduce its harmful effects. The purpose of the present study is to identify whether or not occurrence of climate change by extreme indices including TXx and TNn during 1961-2015. In addition, CanESM2 model use under three scenarios to predict future climatic scenarios and the data were processed using SDSM model to detect the temperature of the studied stations. To this aim, the maximum and minimum daily temperature data of Sanandej and Saqez synoptic stations were used. Mann-Kendall test use to detect the trend of temperature extreme indices and Sen’s estimator applied to magnitude of trend. Subsequently, climate forecasts were carried out under three scenarios of RCP2.6, RCP4.5 and RCP8.5 of CanESM2 model and two extreme indices were obtained in 2020-2050. The results showed that both of extreme indices had a significant trend and the TNn have a significant trend in Saghez during the baseline period. In the case of the generated scenarios, only RCP2.6 was meaningful in two Indices for Sanandej and in TXx have a significant trend for Saghez. The results showed that in the case study, the highest maximum and the lowest minimum temperature will increase under three scenarios over the next 30 years by one percent compared to the average of baseline period. It should be noted that this increase will occur over a period of 30-year and will certainly increase in the longer term.
The global changes in climate and extreme weather have already begun to affect
people and nature around the world. The changing climate impacts wildlife
species, the habitat destruction, over exploitation of wildlife as well as disease.
Currently 54% of Iraqi cultivated land faced challenges due to desertification.
While the percentage of dried marshlands in Iraq turns into 90%. Since the
country is wealthy with biodiversity, this precious heritage needs the urgent call
and attention to scale up efforts for establishment of sustainable Protected Areas
and of eco system of wildlife under climate change scenarios. The focus of the
paper is to examine existing legal framework on the process of conservation of
wildlife in Iraq and identify the legal barriers for the purpose of saving and
protecting the survive wildlife. The paper adopts the qualitative doctrinal methods
by analysing the environmental legislation such as “Law No. 27(2009) for
Environment Protection and Improvement and Law of Wild Animals Protection
No. 17 of 2010” in Iraq. Based on the discussion, the paper concludes that the
current legal frameworks in Iraq on conservation of wildlife are insufficient to
response the climate change. Further, the enforcement is weak and the
commitment and poor coordination between relevant institutions also become
challenges to protect wildlife in Iraq.
Keywords: legal framework, Wildlife protection, climate change, Iraq
Water level (WL) forecasting has become a difficult undertaking due to spatiotemporal fluctuations in climatic factors and complex physical processes. This paper proposes a novel hybrid machine learning model based on an artificial neural network (ANN) and the Marine Predators algorithm (MPA) for modeling monthly water levels of the Tigris River in Al-Kut, Iraq. Data preprocessing techniques are employed to enhance data quality and determine the optimal input model. Historical data for water level and climatic factors data are utilized from 2011 to 2020 to build and assess the model. MPA-ANN algorithm’s performance is compared with recent constriction coefficient-based particle swarm optimization and chaotic gravitational search algorithm (CPSOCGSA-ANN) and slime mold algorithm (SMA-ANN) to reduce uncertainty and raise the prediction range. The finding demonstrated that singular spectrum analysis is a highly effective method to denoise time series. MPA-ANN outperformed CPSOCGSA-ANN and SMA-ANN algorithms based on different statistical criteria. The suggested novel methodology offers good results with scatter index (SI) = 0.0009 and coefficient of determination (R2 = 0.98).
One of the greatest challenges facing the world today is global warming. Long-term analysis of spatiotemporal variations in widespread heat days (WHDs) is one approach to monitoring this phenomenon, rather than focusing on the temperature trend. The objective of this study was to reconstruct the temporal and spatial variation of WHDs in the Middle East and North Africa (MENA) using the long-term NOAA/CIRES/ DOE 20th Century Reanalysis (V2) (20CRv2) reanalysis data between 1871 and 2012. Based on a 90% probability of occurrence, the temperature threshold for detecting WHDs was defined to be different for each grid point. Then, most WHDs of each month (142 samples) were identified based on the connected component labeling method. The results showed that most WHDs for each month occurred mainly after 2000. In general, the western parts of Iran, Syria, southern Turkey, Saudi Arabia, Kuwait, Egypt, and northern Sudan had the highest density of WHDs. In the second period (1941 to 2012), the extent of WHDs increased compared to the first period (1871 to 1941). The spatial relationship between WHDs density in the first and second periods showed no statistical relationship, indicating that WHDs were completely different in the two periods. The results of this study contribute to a better understanding of the effects of global warming by using the relatively longest data sets. The comparison between the two periods shows that the WHDs in MENA have changed in extent (instead of variability).
Modelling drought is vital to water resources management, particularly in arid areas, to
reduce its effects. Drought severity and frequency are significantly influenced by climate change. In this study, a novel hybrid methodology was built, data preprocessing and artificial neural network (ANN) combined with the constriction coefficient‐based particle swarm optimisation and chaotic gravitational search algorithm (CPSOCGSA), to forecast standard precipitation index (SPI) based on climatic factors. Additionally, the marine predators algorithm (MPA) and the slime mould algo‐rithm (SMA) were used to validate the performance of the CPSOCGSA algorithm. Climatic factors data from 1990 to 2020 were employed to create and evaluate the SPI 1, SPI 3, and SPI 6 models for Al‐Kut City, Iraq. The results indicated that data preprocessing methods improve data quality and
find the best predictors scenario. The performance of CPSOCGSA‐ANN is better than MPA‐ANN and SMA‐ANN algorithms based on various statistical criteria (i.e., R², MAE, and RMSE). The pro‐posed methodology yield R² = 0.93, 0.93, and 0.88 for SPI 1, SPI 3, and SPI 6, respectively.
Climate behavior study analysis of the values of the famous temperature variables for each of the (minimum and maximum) temperatures that were studied in four main stations in Iraq (Mosul, Baghdad, Rutbah, Basra) during the period 1980-2017. The research aims to know the increase in the monthly rates of minimum and maximum temperature values and their impact on global warming, as the data were taken from satellites registered by the European Center for Medium-Range Weather Forecasts (ECMWF). Mann-Kendall statistical tests were used to calculate the important trends in the minimum and maximum temperature rates for each of the four previously mentioned stations. The results showed that there is a noticeable increase in the monthly average of minimum and maximum temperatures and that the general behavior of the trend of minimum and maximum temperatures tends to rise in its values in all regions of Iraq.
The extreme temperature has become more frequent and intense due to global warming, particularly in dry regions, causing devastating impacts on humans and ecosystems. The transboundary Amu river basin (ARB) is the most vulnerable region in Central Asia (CA) to extreme weather linked to climate change. This study aimed to project warm and cold extremes in ARB for four Shared Socioeconomic Pathways (SSP1-2.6, SSP2-4.5, SSP3-7.0 and SSP5-8.5) and two time-horizons, 2020–2059 and 2060–2099, using daily maximum (Tmax) and minimum temperature (Tmin) simulations of global climate models (GCMs) of Coupled Model Inter-comparison Project phase six (CMIP6). Results revealed that the basin’s west experiences more hot extremes and the east more cold extremes. Climate change would cause a significant increase in the annual mean of Tmax and Tmin. However, the increase in mean Tmin would be much higher (5.0ºC ) than the mean Tmax (4.6ºC ). It would cause an increase in the hot extremes and a decrease in the cold extremes in the basin. The higher increase in the hot extremes would be in the west, while the higher decrease in the cold extreme in the basin’s east. The number of days above 40℃ would increase from 45 to 60 days in the basin’s west and northwest compared to the historical period. The number of days below − 20℃ would decrease up to 45 days in the basin’s east. Overall, the decrease in cold extremes would be much faster than the increase in hot extremes.
Changes in snowmelt-related streamflow timing have implications for water availability and use as well as ecologically relevant shifts in streamflow. Historical trends in snowmelt-related streamflow timing (winter-spring center volume date, WSCVD) were computed for minimally disturbed river basins in the conterminous United States. WSCVD was computed by summing daily streamflow for a seasonal window then calculating the day that half of the seasonal volume had flowed past the gage. We used basins where at least 30 percent of annual precipitation was received as snow, and streamflow data were restricted to regionally based winter-spring periods to focus the analyses on snowmelt-related streamflow. Trends over time in WSCVD at gages in the eastern U.S. were relatively homogenous in magnitude and direction and statistically significant; median WSCVD was earlier by 8.2 days (1.1 days/decade) and 8.6 days (1.6 days/decade) for 1940–2014 and 1960–2014 periods respectively. Fewer trends in the West were significant though most trends indicated earlier WSCVD over time. Trends at low-to-mid elevation (
Objectives:
A request to report laboratory values to a specific number of decimal places represents a delicate balance between clinical interpretation of a true analytical change versus laboratory understanding of analytical imprecision and significant figures. Prostate specific antigen (PSA) was used as an example to determine if an immunoassay routinely reported to the hundredths decimal place based on significant figure assessment in our laboratory was capable of providing analytically meaningful results when reported to the thousandths places when requested by clinicians.
Design and methods:
Results of imprecision studies of a representative PSA assay (Roche MODULAR E170) employing two methods of statistical analysis are reported. Sample pools were generated with target values of 0.01 and 0.20 μg/L PSA as determined by the E170. Intra-assay imprecision studies were conducted and the resultant data were analyzed using two independent statistical methods to evaluate reporting limits.
Results:
These statistical methods indicated reporting results to the thousandths place at the two assessed concentrations was an appropriate reflection of the measurement imprecision for the representative assay. This approach used two independent statistical tests to determine the ability of an analytical system to support a desired reporting level. Importantly, data were generated during a routine intra-assay imprecision study, thus this approach does not require extra data collection by the laboratory.
Conclusions:
Independent statistical analysis must be used to determine appropriate significant figure limitations for clinically relevant analytes. Establishing these limits is the responsibility of the laboratory and should be determined prior to providing clinical results.
Study region: Namibia.
Study focus: The lack of ground observations has long been a major obstacle in studying rainfall patterns in many dryland regions, particularly in the data scarce African continent. In this study, a continuous 6-year (2008–2013) daily record of ground observations collected from Weltevrede Farm at the edge of the Namib Desert was used to evaluate TRMM Multi-satellite Precipitation Analysis (TMPA, 0.25° resolution) daily rainfall estimates of this area. A Mann-Kendall trend analysis was conducted using all the available annual TMPA satellite data (1998–2015) to examine long-term trends in rainfall amount, intensity, frequency and seasonal variations over four locations across a rainfall gradient.
New hydrological insights for the region: The agreement between ground and satellite rainfall data was generally good at annual/monthly scales but large variations were observed at the daily scale. Results showed a spatial variability of rainfall trends across the rainfall gradient. We observed significant changes in frequency along with insignificant changes in intensity and no changes in total amount for the driest location, but no changes in any of the rainfall parameters were observed for the three wetter locations. The results also showed increased rainfall variability for the driest location. This study provided a useful approach of using TMPA data associated with trend analysis to extend the data record for ecohydrological studies for similar data scarce conditions. The results of this study will also help constrain IPCC predictions in this region.
This study focuses on the use of science sources as experts in news stories about climate change coverage in the Great Lakes region of the US and Canada. We examine, using the hierarchy of influences model, whether the use of scientific sources in climate change coverage may be related to factors such as geographic location, reporting frequency, and authorship, in the prestige press as well as regional and local media. The study found that as many or more non-scientists than scientists are selected as sources regardless of geographic location, reporting frequency, or authorship. However, the study also found that the more stories reporters produce on this topic, the more likely their stories are to use and give prominence to science sources. In addition, the articles included few denier sources, but denier views are more likely to appear in a more prominent location in the articles than supporters when stories are framed as conflict over global warming. These results highlight the need for additional research examining the expertise of climate scientists in news stories to better understand news decision-making in the context of complex scientific reporting.
Mean annual and monthly averages of mean (Tmean), maximum (Tmax) and minimum (Tmin) air temperature from seven stations in Iraq were analysed to detect the inter-annual variation, long-term temporal and spatial trends distribution over the period 1941–2013. Due to non-homogeneous problems, this period has been divided into two short separated periods (1941–1980 and 1995–2013), in order to compute temperature trends. In this context two statistical tests were used: linear regression and Mann-Kendall. The time series of mean annual temperature indicate the current warming period over Iraq identical with the global warming, which has started since the middle of seventh decade of the last century. The 2010 was the warmest year in all stations. Three distinct inter-annual temperature variation patterns were observed. These were probably the effects of micro-scale and meso-scale factors. The first one represents central and northern Iraq. The second represents the south of Iraq and Kirkuk station and the third one is a characteristic for eastern Iraq. Temperature trend analysis revealed that there are general upward trends with the strongest warming trends identified in the summer months which are around 89 % of the total significant monthly trends. Spatially, in both periods the southern region of Iraq is most affected by the warming trend in Tmean and Tmax. When considering Tmin, the southern and northern regions both are affected by warming with more pronounced trend intensity in the northern stations. No significant trend occurs Hai station in both periods and Baghdad has the still less trend value. In the first period the highest rise of Tmean and Tmax values are observed in July and June in Nasiriya station at 0.61 °C/decade and 0.63 °C/decade, respectively and in Mosul station for Tmin in August is 1.41 °C/decade. Moreover, in the period from 1995 to 2013, the highest warming trend of Tmean and Tmax were in Hai station for March at 1.48 °C/decade and at 1.85 °C/decade, respectively. Baghdad station experienced the highest significant trend for Tmin in August at 1.89 °C/decade.
The ensemble results of CMIP5 climate models that applied the RCP4.5 and RCP8.5 scenarios have been used to investigate climate change and temperature extremes in the Middle East and North Africa (MENA). Uncertainty evaluation of climate projections indicates good model agreement for temperature but much less for precipitation. Results imply that climate warming in the MENA is strongest in summer while elsewhere it is typically stronger in winter. The summertime warming extends the thermal low at the surface from South Asia across the Middle East over North Africa, as the hot desert climate intensifies and becomes more extreme. Observations and model calculations of the recent past consistently show increasing heat extremes, which are projected to accelerate in future. The number of warm days and nights may increase sharply. On average in the MENA, the maximum temperature during the hottest days in the recent past was about 43 °C, which could increase to about 46 °C by the middle of the century and reach almost 50 °C by the end of the century, the latter according to the RCP8.5 (business-as-usual) scenario. This will have important consequences for human health and society.
Due to the substantial decrease of water resources as well as the increase in demand and climate change phenomenon, analyzing the trend of hydrological parameters is of paramount importance. In the present study, investigations were carried out to identify the trends in streamflow at 20 hydrometric stations and 11 rainfall gauging stations located in Karkheh River Basin (KRB), Iran, in monthly, seasonal, and annual time scales during the last 38 years from 1974 to 2011. This study has been conducted using two versions of Mann–Kendall tests, including (i) Mann–Kendall test by considering all the significant autocorrelation structure (MK3) and (ii) Mann–Kendall test by considering LTP and Hurst coefficient (MK4). The results indicate that the KRB streamflow trend (using both test versions) has decreased in all three time scales. There is a significant decreasing trend in 78 and 73 % of the monthly cases using the MK3 and MK4 tests, respectively, while these percentages changed to 80 and 70 % on seasonal and annual time scales, respectively. Investigation of the trend line slope using Theil–Sen’s estimator showed a negative trend in all three time scales. The use of MK4 test instead of the MK3 test has caused a decrease in the significance level of Mann–Kendall Z-statistic values. The results of the precipitation trends indicate both increasing and decreasing trends. Also, the correlation between the area average streamflow and precipitation shows a strong correlation in annual time scale in the KRB.
In this work, the design and power consumption analysis of NOR based 4 × 4 semiconductor read-only-memory (ROM) array has been presented. In this study, row decoder and column decoder has been considered in order to retrieve the data from ROM array. All the circuits are designed using nanodimensional metal oxide semiconductor (MOS) transistor. The average power consumption across the ROM array structure has been reported for the MOS transistors with channel length of 32, 22 and 16 nm. Selecting the row lines and column lines using row decoder and column decoder, data written inside the ROM array has been retrieved. In order to verify the data inside the ROM array, simulated waveforms are presented. Overall design and power consumption analysis of the ROM array in nano regime has been analyzed with the help of Tanner SPICE (T-SPICE) tools. It is seen that as power supply voltage VDD increases the average power consumption across the ROM structure also increases. This indicates that for low power design the value of VDD needs to be downscaled. Comparison of the average power consumption for MOS transistors having channel length 32, 22 and 16 nm has been reported.
In this study, trends of the seasonal and annual maximum (T-max), minimum (T-min), and mean (T) air temperatures, as well as rainfall amounts (R-a) time series were investigated for eleven stations in Iraq for the period 1972-2011 (40 years). Four statistical tests including homogeneity, Mann-Kendall (MK), Sen's slope estimator and linear regression were used for the analysis. The results revealed that annual mean of T-max, T-min, and T time series showed statistically significant increasing trends over 81.8, 100, and 100% of the stations at the 0.001 level and they experienced an increase of 0.50, 0.67, and 0.58 degrees C/decade, respectively; while the annual rainfall has shown decreasing trends at 90.9% of the stations and it experienced a decrease of -20.50 mm/decade. Seasonally, the highest increase of T-max, T-min, and T values have been found over the extreme south of the country during summer at the rates of 1.47, 1.06, and 1.16 degrees C/decade, respectively, while the highest decrease of R-a values has been found in the northern part of the country during winter at the rate of -36.35 mm/decade.
The coastlines have been identified as the most vulnerable regions with respect to hydrological hazards as a result of climate change and variability. The east of peninsular Malaysia is not an exception for this, considering the evidence of heavy rainfall resulting in floods as an annual phenomenon and also water scarcity due to long dry spells in the region. This study examines recent trends in rainfall and rainfall- related extremes such as, maximum daily rainfall, number of rainy days, average rainfall intensity, heavy rainfall days, extreme rainfall days, and precipitation concentration index in the east coast of peninsular Malaysia. Recent 40 years (1971–2010) rainfall records from 54 stations along the east coast of peninsular Malaysia have been analyzed using the non-parametric Mann–Kendall test and the Sen’s slope method. The Monte Carlo simulation technique has been used to determine the field significance of the regional trends. The results showed that there was a substantial increase in the annual rainfall as well as the rainfall during the monsoon period. Also, there was an increase in the number of heavy rainfall days during the past four decades.
This study analyses spatial and temporal trends in extreme temperature indices over Nigeria. The percentile indices were calculated from newly homogenized daily minimum and maximum temperature data for the period 1971–2012 for 21 stations in Nigeria. Indices describing the characteristics of hot extremes and cold extremes are calculated with the RClimDex software. The annual and seasonal trends in these indices are obtained using the ordinary least square fit and the statistical significance tested using the R-based modified Mann–Kendall test. We examine characteristics of these indices for the entire country and separately for the three geographical zones in Nigeria: Guinea, Savanna, and Sahel. The spatial and temporal patterns of trends in the indices indicate that Nigeria has experienced statistically significant increase in the frequency of hot extreme and decrease in cold extreme events. Although majority of the stations have significant trends in warm days and warm nights, the annual trend is greatest in warm nights. In addition, the rate of warming in minimum temperature (‘warm nights’) is stronger in June, July, August (JJA) and September, October, November (SON) compare with December, January, February (DJF) and March, April, May (MAM). As for the trends in cold days and cold nights, the trends in cold nights are larger than for cold days at both the annual and seasonal scales. The regional analysis indicates that trends in warm nights and cold nights are most pronounced in Guinea and Sahel regions.
In this study, changes in the spatial and temporal patterns of climate extreme indices were analyzed. Daily maximum and minimum air temperature, precipitation, and their association with climate change were used as the basis for tracking changes at 50 meteorological stations in Iran over the period 1975–2010. Sixteen indices of extreme temperature and 11 indices of extreme precipitation, which have been quality controlled and tested for homogeneity and missing data, are examined. Temperature extremes show a warming trend, with a large proportion of stations having statistically significant trends for all temperature indices. Over the last 15 years (1995–2010), the annual frequency of warm days and nights has increased by 12 and 14 days/decade, respectively. The number of cold days and nights has decreased by 4 and 3 days/decade, respectively. The annual mean maximum and minimum temperatures averaged across Iran both increased by 0.031 and 0.059 °C/decade. The probability of cold nights has gradually decreased from more than 20 % in 1975–1986 to less than 15 % in 1999–2010, whereas the mean frequency of warm days has increased abruptly between the first 12-year period (1975–1986) and the recent 12-year period (1999–2010) from 18 to 40 %, respectively. There are no systematic regional trends over the study period in total precipitation or in the frequency and duration of extreme precipitation events. Statistically significant trends in extreme precipitation events are observed at less than 15 % of all weather stations, with no spatially coherent pattern of change, whereas statistically significant changes in extreme temperature events have occurred at more than 85 % of all weather stations, forming strongly coherent spatial patterns.
Arid regions of Rajasthan in India are characterized by harsh environments, fragile ecosystems, and limited water resources and arable lands. Desertification is one of the major land-degradation problems in these regions. Recent changes in the regional climatic regime and the low availability of water in this northwestern state of India, pose the threat of desertification in the agriculturally productive part of the state. This study aims to delineate the environmentally sensitive areas to desertification in the districts of Jhunjhunun and Sikar in Rajasthan, India. It uses geospatial data from various sources, and combines them to calculate an environmental sensitivity index (ESI), which will allow the quantification of the area's vulnerability to desertification. The study uses the analytical hierarchical process (AHP) to assign respective weights to individual factors for each index calculation. Land-cover maps and socio-economic data have been used to understand their relationship with ESI. Results showed that 13 percent and 45 percent of the study area are under highly sensitive and moderately sensitive zones, respectively. Mapping and monitoring of environmentally sensitive areas in such arid regions are critical to sustainable use and planning of natural resources namely water and land-cover and are helpful in determining priority actions and their successful implementation.
Precipitation trend analysis, on distinct spatial and temporal aspects, has been of great interest due to the increased attention given to global climate change by the hydro-climatological community. The aim of this study is: 1) to detect precipitation trends using the Mann-Kendall method in annual and monthly time scales at 42 stations in the Urmia Lake Basin (ULB); 2) to evaluate these detected trends in conjunction with the spatial interpolation techniques; namely, inverse distance weighting (IDW), ordinary Kriging (OK) and completely regularised spline (CRS) using GIS model. Results showed that both decreasing and increasing trends was observed at all time scales over the basin. Assessment of interpolation methods exhibited that the OK with an RMSE value of 1.14 was the best interpolation technique according to the cross-validation results. Briefly, the OK technique is concluded as the best method in the interpolation procedures based on the cross-validation and spatial clustering outcomes.
This work seeks to understand the variability of warm and cool events during summer in Turkey. Daily maximum air temperature data from 97 weather stations were analyzed to determine percentile threshold values (99th, 95th, 90th, 1st, 5th, and 10th) at each station. Trends in the percentile values were determined using the Mann-Kendall trend test. The analysis demonstrates an increase in frequency of warm, hot, and extremely hot days, whereas cool, cold, and extremely cold days show a decreasing trend. Increasing trends are statistically significant at the 0.05 and 0.01 levels for 13 and 46% of the stations, respectively. Significant decreasing trends have been detected at 0.05 and 0.01 levels for 19 and 15% of 97 stations, respectively. Analysis of the observations shows that the number of warm and hot event started to increase in the 1970s. Warm events are comparatively more numerous than cold events in western and southern parts of the country.
While the rise in global mean temperature over the past several decades is now widely acknowledged, the issue as to whether and to what extent temperature variability is changing continues to undergo debate. Here, variability refers to the spread of the temperature distribution. Much attention has been given to the effects that changes in mean temperature have on extremes, but these changes are accompanied by changes in variability, and it is actually the two together, in addition to all aspects of a changing climate pattern, that influence extremes. Since extremes have some of the largest impacts on society and ecology, changing temperature variability must be considered in tandem with a gradually increasing temperature mean. Previous studies of trends in temperature variability have produced conflicting results. Here we investigated ten long-term instrumental records in Europe of minimum, mean and maximum temperatures, looking for trends in seasonal, annual and decadal measures of variability (standard deviation and various quantile ranges) as well as asymmetries in the trends of extreme versus mean temperatures via quantile regression. We found consistent and accelerating mean warming during 1864–2012. In the last 40 years (1973–2012) trends for Tmax were higher than for Tmin, reaching up to 0.8 °C per 10a in spring. On the other hand, variability trends were not as uniform: significant changes occurred in opposing directions depending on the season, as well as when comparing 1864–2012 trends to those of 1973–2012. Moreover, if variability changed, then it changed asymmetrically, that is only in the part above or below the median. Consequently, trends in the extreme high and low quantiles differed. Regional differences indicated that in winter, high-alpine stations had increasing variability trends for Tmax especially at the upper tail compared to no changes or decreasing variability at low altitude stations. In contrast, summer variability increased at all stations studied.
This paper presents key results from analysis of surface meteorological observations collected in the Northern Arabian/Persian Gulf (N Gulf; Kuwait, Bahrain, and NE Saudi Arabia), which spans a 40-years period (1973–2012). The first part of this study analyzes climate variability in the N Gulf, and relates them to teleconnection patterns (North Atlantic Oscillation, El Nino Southern Oscillation, and Indian Ocean Dipole). Results of the analysis indicate that during the study period the climate in the region experienced a general trend of increase in temperature (0.8°C), decrease in barometric pressure (1 mbar), reduction in humidity (6%), and decrease in visibility (9%). Significant correlations were found between the three teleconnection patterns and the meteorological conditions suggesting that seasonal variabilities in air temperature, barometric pressure, and precipitation are closely related to the teleconnection patterns. The second part of this study examines the 40-year variability of Shamal events (strong NW winds that commonly generate significant dust storms). The data suggests that on average Shamal events occur at a rate of 10 events year–1 with 85% of the events occurring during the summer and winter. The number of these events has increased in the past 14 years of the study period. These events resulted in abrupt changes in meteorological conditions: an increase in wind speed of 2.7 m s–1, a decrease in visibility of 1.7 km, and reduction in humidity of 4.3%. Seasonal variations in temperature (an increase in temperature during summer of 0.8°C, and a decrease of 1.5°C during winter) and barometric pressure (a decrease in barometric pressure during summer of 0.6 mbar and an increase of 7.8 mbar during winter) were observed during Shamal events.
Research on climate change impacts and related adaptation to water demand is still very limited. A review summarising the findings related to climate change impacts on water demand is carried out in this article. A water management strategy is also proposed, which would help with adaptation to growing pressure on water resources due to climate change and socio-economic development. The study reveals that climate change will increase global water demand, though this will vary widely with geographic location and climatic conditions. Water demand in agriculture will be affected more heavily than will demands in other sectors. As irrigation comprises the major portion of global consumptive water use, increased water demand in irrigation may cause severe stress on water resources. Studies suggest that water demand management or water supply management alone will not able to adapt to mounting water stress. A combination of both water supply and water demand management strategies is necessary in order to adapt to varying environmental and associated uncertainties. A case study from the Haihe River basin of China is presented, to illustrate the effectiveness of water demand management strategies used alongside water supply management in adapting to environmental changes. It is expected that the study will help guide policy responses, with the goal of mitigating the impacts of climate change on water resources.
The current model for energy production, based on the intense use of fossil fuels, is both unsustainable and environmentally harmful and consequently, a shift is needed in the direction of integrating the renewable energy sources into the energy balance. However, these energy sources are unpredictable and uncontrollable as they strongly depend on time varying and uncertain hydrometeorological variables such as wind speed, sunshine duration and solar radiation. To study the design and management of renewable energy systems we investigate both the properties of marginal distributions and the dependence properties of these natural processes, including possible long-term persistence by estimating and analyzing the Hurst coefficient. To this aim we use time series of wind speed and sunshine duration retrieved from European databases of daily records. We also study a stochastic simulation framework for both wind and solar systems using the software system Castalia, which performs multivariate and multi-time-scale stochastic simulation, in order to conduct simultaneous generation of synthetic time series of wind speed and sunshine duration, on yearly, monthly and daily scale.
In most of Argentina, the warming since 1901 was a little lower than the global average, although with strong trends in temperature extremes and in heat waves during the most recent decades. There was a remarkable increase in precipitation over most of subtropical Argentina, especially since 1960. This has favored agriculture yields and the extension of crop lands into semiarid regions, but this increase also came with more frequent heavy rainfalls and consequent flooding of rural and urban areas. Since the early 1970s, the main rivers of the Plata Basin have increased their mean flows, but this was attributable not only to increased precipitation, but also to land use changes. In contrast, over the Andes Mountains, reduced rainfall and increased temperature has led to glaciers receding and reduced river flows. Climate projections for the first half of this century maintain observed trends and raise additional concerns that in most cases can be dealt with timely adaptation policies. However, by the end of this century, under an extreme emissions scenario, the projected warming reaches 3.5°C in the north of the country with respect to present‐day conditions. There is insufficient knowledge to assume that this warming would not create severe damages to the people and the economy of Argentina. Because of the damages and casualties that heat waves and extreme precipitation events are already producing, the first and most urgent adaptation required is to reinforce early warning systems and contingency planning to cope with climatic extremes and their consequences on health. WIREs Clim Change 2015, 6:151–169. doi: 10.1002/wcc.316
This article is categorized under: Trans‐Disciplinary Perspectives > National Reviews
Earth's climate has experienced notable changes during the past 50–70 years when global surface temperature has risen by 0.8ºC during the 20th century. This was a consequence of the rise in the concentration of biogenic gases (carbon dioxide, methane, nitrous oxide, chlorofluorocarbons, and ozone) in the atmosphere that contribute, along with water vapor, to the so-called 'greenhouse effect'. Most of the emissions of greenhouse gases have been, and still are, the product of human activities, namely, the excessive use of fossil energy, deforestations in the humid tropics with associated poor land use-management, and wide-scale degradation of soils under crop cultivation and animal/pasture ecosystems. General Circulation Models predict that atmospheric CO 2 concentration will probably reach 700 µmol(CO 2) mol –1 . This can result in rise of Earth's temperature from 1.5 to over 5ºC by the end of this century. This may instigate 0.60–1.0 m rise in sea level, with impacts on coastal lowlands across continents. Crop modeling predicts significant changes in agricultural ecosystems. The mid-and high-latitude regions might reap the benefits of warming and CO 2 fertilization effects via increasing total production and yield of C 3 plants coupled with greater water-use efficiencies. The tropical/subtropical regions will probably suffer the worst impacts of global climate changes. These impacts include wide-scale socioeconomic changes, such as degradation and losses of natural resources, low agricultural production, and lower crop yields, increased risks of hunger, and above all waves of human migration and dislocation. Due to inherent cassava tolerance to heat, water stress, and poor soils, this crop is highly adaptable to warming climate. Such a trait should enhance its role in food security in the tropics and subtropics.
Food security in India is tightly linked to rainfall variability. Trends in Indian rainfall records have been extensively studied but the subject remains complicated by the high spatiotemporal variability of rainfall arising from complex atmospheric dynamics. For various reasons past studies have often produced inconsistent results. This paper presents an analysis of recent trends in monthly and seasonal cumulative rainfall depth, number of rainy days and maximum daily rainfall, and in the monsoon occurrence (onset, peak and retreat). A modified version of the Mann-Kendall test, accounting for the scaling effect, was applied to 29 variables derived from square-degree-resolution daily gridded rainfall (1951–2007). The mapping of gridded trend slopes and the regional average Kendall test were used concurrently to assess the field significance of regional trends in areas exhibiting spatial homogeneity in trend directions. The statistics we used account for temporal and spatial correlations, and thus reduce the risk of overestimating the significance of local and regional trends. Our results i/ improve available knowledge (e.g. 5 %-field-significant delay of the monsoon onset in Northern India); ii/ provide a solid statistical basis to previous qualitative observations (e.g. 1 %-field-significant increase/decrease in pre-monsoon rainfall depth in northeast/southwest India); and, iii/ when compared to recent studies, show that the field significance level of regional trends (e.g. in rainfall extremes) is test-dependent. General trend patterns were found to align well with the geography of anthropogenic atmospheric disturbances and their effect on rainfall, confirming the paramount role of global warming in recent rainfall changes.
Heat-wave events are commonly recognized as adverse impacts on agriculture, forests, and economic activities. Several studies showed that future climate changes in the western Mediterranean Basin will lead to an increase in extreme weather events, mainly in the summer season. For this reason, it is crucial to improve our knowledge and investigate the effects of extreme temperature events on wildland fire activity. This work analyses the relation between high temperature days (air temperature higher than 25°C at 850hPa) and large wildland fires in Sardinia (Italy) during 1991-2009 period and the influence of high temperature days on large wildland fires was remarkable. The results showed that neither the number of fires nor the area burned decreased under high temperature days, although a decrease of both indicators was observed on the other days. Additionally, the average size of fires, the probability of large fire occurrence, the daily area burned and daily number of fires resulted higher in high temperature days.
This study provides an overview of projected changes in climate extremes indices defined by the Expert Team on Climate Change Detection and Indices (ETCCDI). The temperature- and precipitation-based indices are computed with a consistent methodology for climate change simulations using different emission scenarios in the Coupled Model Intercomparison Project Phase 3 (CMIP3) and Phase 5 (CMIP5) multimodel ensembles. We analyze changes in the indices on global and regional scales over the 21st century relative to the reference period 1981–2000. In general, changes in indices based on daily minimum temperatures are found to be more pronounced than in indices based on daily maximum temperatures. Extreme precipitation generally increases faster than total wet-day precipitation. In regions, such as Australia, Central America, South Africa, and the Mediterranean, increases in consecutive dry days coincide with decreases in heavy precipitation days and maximum consecutive 5 day precipitation, which indicates future intensification of dry conditions. Particularly for the precipitation-based indices, there can be a wide disagreement about the sign of change between the models in some regions. Changes in temperature and precipitation indices are most pronounced under RCP8.5, with projected changes exceeding those discussed in previous studies based on SRES scenarios. The complete set of indices is made available via the ETCCDI indices archive to encourage further studies on the various aspects of changes in extremes.