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ERA5-Land Reanalysis Temperature Data Addressing Heatwaves in Portugal
Abstract
In this research, heatwaves in Portugal were analysed using high-resolution daily minimum and maximum temperature data (Tmin and Tmax) from the European Reanalysis of Global Climate Observations (ERA5-Land) for the period from 1 October 1980 to 30 September 2021 (41 hydrological years) at four differentiated climatological locations in the country. The ERA5-Land temperature data were validated at the monthly level against ground-based observations from the Portuguese Institute for Sea and Atmosphere (IPMA), finding good agreement between the two data sets. Heatwaves were defined using the heatwave magnitude index (HWMI), which identifies a heatwave as a period of three or more consecutive days where temperatures exceed the daily threshold defined for the reference period. Additionally to an increasing trend in Tmin magnitude, more than 650 heatwave days of Tmin were identified at each of the four ERA5-Land locations, with the grid-point centred in the capital urban area, i.e., Lisbon, having the highest number of heatwave days. Regarding the heatwave days of Tmax, the locations with the highest occurrences, each with more than 830 d in the 41-year period, were in the north and interior. Both Tmin and Tmax heatwave occurrences were coupled with a kernel rate estimation technique for their annual frequency analysis. Overall, the results showed a clear increase in the frequency of heatwave days in Portugal, particularly for Tmax in the last two decades. This also evidenced geographical variations in the phenomenon’s occurrence, with the southern location experiencing a higher increase in heatwave days of Tmax than the northern and interior grid-points.
... In such cases, a good (and perhaps the only) alternative is gridded datasets, such as reanalysis products. Many studies have used different gridded data (including reanalysis) to examine HW characteristics and climatology in specific regions [9,[15][16][17][18][19][20]. ...
In this research, based on a case study of Ukraine, we (1) examined the sensitivity of heatwave (HW) climatology to input gridded data and (2) statistically compared HW metrics (such as duration, intensity, etc.) calculated from the gridded data against similar results derived from high-quality station time series. For the first task, we used a mini statistical ensemble of gridded datasets of the daily maximum air temperature (TX). The ensemble included the following: ClimUAd and E-OBS (Ukrainian and European observation-based gridded data, respectively), reanalyzes ERA5, ERA5-Land, NOAA-CIRES 20CR V2c and V3, and NCEP-NCAR R1. For the second task, the same gridded data were used along with 178 quality-controlled and homogenized TX station time series from Ukraine. HWs and their metrics were defined according to the approach summarized by Perkins and Alexander (2013). All calculations were performed for the period 1950–2014. Our results showed that, depending on the gridded dataset, the calculated values of HW metrics might differ significantly. Even after averaging over the study period and the territory of Ukraine, the ranges between the max and min values of HW metrics remain large. For instance, the spread in HW number per year may be up to six events. However, the differences in the trend slopes of HW metrics are less pronounced. In addition, the comparison of HW calculations derived using gridded and station data showed that E-OBS, ERA5, and ERA5-Land provide similar verification statistics. The evaluation statistics for 20CRV3 are worse compared to E-OBS, ERA5, and ERA5-Land, but significantly better than for 20CRV2c and NCEP-NCAR R1. Our findings can aid in selecting gridded datasets for calculating reliable HW climatology and, consequently, contribute to developing climate adaptation strategies for extreme temperature events in Ukraine, its neighboring countries, and potentially across Europe.
This study examines the trends in heatwave characteristics across mainland Portugal from 1980/1981 to 2022/2023, utilising ERA5-Land reanalysis data. To achieve this, the study applies the Heatwave Magnitude Index (HWMI) to identify heatwave days for minimum (Tmin) and maximum (Tmax) temperatures across 15 grid-points representing Portugal’s diverse geography and climate. Three key annual parameters are analysed: the number of heatwave days (ANDH), the average temperature during heatwaves (AATW), and the intensity of heatwave events (AIHD). Results reveal a consistent increase in heatwave persistence throughout mainland Portugal, with more pronounced trends observed for Tmax compared to Tmin. ANDH Tmin shows upward trends across all grid-points, with increases ranging from 0.8 to 4.2 days per decade. ANDH Tmax exhibits even more significant increases, with 11 out of 15 grid-points showing statistically significant rises, ranging from 2.2 to 4.4 days per decade. Coastal areas, particularly in the south, demonstrate the most substantial increases in heatwave persistence. The intensity of heatwaves, as measured by AIHD, also shows positive trends across all grid-points for both Tmin and Tmax, with southern locations experiencing the most significant increases. The study also discusses decadal trends in annual averages of Tmin and Tmax, as well as extreme measures such as annual minimum (AMIN) and annual maximum (AMAX), daily temperatures spatially represented across mainland Portugal. These analyses reveal widespread warming trends, with more pronounced increases in Tmax compared to Tmin. The AMIN and AMAX trends further corroborate the overall warming pattern from the heatwave analyses, with notable spatial variations observed. The findings indicate a substantial worsening in the occurrence, duration, and intensity of heatwave events. This increased persistence of heatwaves, especially evident from the early 2000s onwards, suggests a potential climate regime shift in mainland Portugal. The results underscore the need for adaptive strategies to address the growing challenges posed by more frequent and intense heatwaves in the region.
Weather and climate conditions drive the evolution of tropical glaciers which play an important role as water reservoirs for Peruvian inhabitants in the arid coast and semi-arid Andean region. The scarcity of long-term high-quality observations over Peruvian glaciers has motivated the extensive use of reanalysis data to describe the climatic evolution of
these glaciers. However, the representativeness and uncertainties of these reanalysis products over these glaciers are still poorly constrained. This study evaluates the ability of the ERA5-Land reanalysis (ERA5L) to reproduce hourly and monthly 2 m air temperature and relative humidity (T2m and Rh2m, respectively) over several Peruvian glaciers. We compared the ERA5L with data from four on-glacier automatic weather stations (AWS), whose hourly time series were completed with nearby stations, for the period January 2017 to December 2019. Results indicates a better performance of the reanalysis for T2m (r >0.80) than for Rh2m (~0.4< r <~0.6) in all four glaciers. Concerning the observations, both parameters show a daily cycle influenced by the presence of the glacier. This influence is more prominent during the dry months when the so-called glacier damping and cooling effects are stronger. On a monthly time scale, the ERA5L validation for both
parameters are better in wet outer tropical sites (RMSE between ±0.2°C for T2m and between 3%-7% for Rh2m) rather than in dry outer tropical sites (RMSE between ±0.2°C for T2m and between 3%-7% for Rh2m). Among all sites considered in the study, the Rh2m bias is the highest in the Cavalca glacier (correlation of 0.81; RMSE 13%, MAE 11% and bias 8.3%) and the lowest in Artesonraju glacier (correlation of 0.96; RMSE 3%; MAE 2.3% and bias -0.8%). Based on certain considerations outlined in this paper, it is appropriate to use ERA5L to characterize T2m and Rh2m conditions on Peruvian glaciers, particularly in the wet outer tropics.
Persistent heat extremes can have severe impacts on ecosystems and societies, including excess mortality, wildfires, and harvest failures. Here we identify Europe as a heatwave hotspot, exhibiting upward trends that are three-to-four times faster compared to the rest of the northern midlatitudes over the past 42 years. This accelerated trend is linked to atmospheric dynamical changes via an increase in the frequency and persistence of double jet stream states over Eurasia. We find that double jet occurrences are particularly important for western European heatwaves, explaining up to 35% of temperature variability. The upward trend in the persistence of double jet events explains almost all of the accelerated heatwave trend in western Europe, and about 30% of it over the extended European region. Those findings provide evidence that in addition to thermodynamical drivers, atmospheric dynamical changes have contributed to the increased rate of European heatwaves, with implications for risk management and potential adaptation strategies. Europe is a heatwave hotspot exhibiting three-to-four times faster upward trends compared to the rest of the northern midlatitudes. Here, this accelerated trend is linked to the increased persistence of Eurasian double jets in the upper troposphere.
The lack of consistent, accurate information on evapotranspiration (ET) and consumptive use of water by irrigated agriculture is one of the most important data gaps for water managers in the western United States (U.S.) and other arid agricultural regions globally. The ability to easily access information on ET is central to improving water budgets across the West, advancing the use of data-driven irrigation management strategies, and expanding incentive-driven conservation programs. Recent advances in remote sensing of ET have led to the development of multiple approaches for field-scale ET mapping that have been used for local and regional water resource management applications by U.S. state and federal agencies. The OpenET project is a community-driven effort that is building upon these advances to develop an operational system for generating and distributing ET data at a field scale using an ensemble of six well-established satellite-based approaches for mapping ET. Key objectives of OpenET include: Increasing access to remotely sensed ET data through a web-based data explorer and data services; supporting the use of ET data for a range of water resource management applications; and development of use cases and training resources for agricultural producers and water resource managers. Here we describe the OpenET framework, including the models used in the ensemble, the satellite, meteorological, and ancillary data inputs to the system, and the OpenET data visualization and access tools. We also summarize an extensive intercomparison and accuracy assessment conducted using ground measurements of ET from 139 flux tower sites instrumented with open path eddy covariance systems. Results calculated for 24 cropland sites from Phase I of the intercomparison and accuracy assessment demonstrate strong agreement between the satellite-driven ET models and the flux tower ET data. For the six models that have been evaluated to date (ALEXI/DisALEXI, eeMETRIC, geeSEBAL, PT-JPL, SIMS, and SSEBop) and the ensemble mean, the weighted average mean absolute error (MAE) values across all sites range from 13.6 to 21.6 mm/month at a monthly timestep, and 0.74 to 1.07 mm/day at a daily timestep. At seasonal time scales, for all but one of the models the weighted mean total ET is within ±8% of both the ensemble mean and the weighted mean total ET calculated from the flux tower data. Overall, the ensemble mean performs as well as any individual model across nearly all accuracy statistics for croplands, though some individual models may perform better for specific sites and regions. We conclude with three brief use cases to illustrate current applications and benefits of increased access to ET data, and discuss key lessons learned from the development of OpenET.
Framed within the Copernicus Climate Change Service (C3S) of the European Commission, the European Centre for Medium-Range Weather Forecasts (ECMWF) is producing an enhanced global dataset for the land component of the fifth generation of European ReAnalysis (ERA5), hereafter referred to as ERA5-Land. Once completed, the period covered will span from 1950 to the present, with continuous updates to support land monitoring applications. ERA5-Land describes the evolution of the water and energy cycles over land in a consistent manner over the production period, which, among others, could be used to analyse trends and anomalies. This is achieved through global high-resolution numerical integrations of the ECMWF land surface model driven by the downscaled meteorological forcing from the ERA5 climate reanalysis, including an elevation correction for the thermodynamic near-surface state. ERA5-Land shares with ERA5 most of the parameterizations that guarantees the use of the state-of-the-art land surface modelling applied to numerical weather prediction (NWP) models. A main advantage of ERA5-Land compared to ERA5 and the older ERA-Interim is the horizontal resolution, which is enhanced globally to 9 km compared to 31 km (ERA5) or 80 km (ERA-Interim), whereas the temporal resolution is hourly as in ERA5. Evaluation against independent in situ observations and global model or satellite-based reference datasets shows the added value of ERA5-Land in the description of the hydrological cycle, in particular with enhanced soil moisture and lake description, and an overall better agreement of river discharge estimations with available observations. However, ERA5-Land snow depth fields present a mixed performance when compared to those of ERA5, depending on geographical location and altitude. The description of the energy cycle shows comparable results with ERA5. Nevertheless, ERA5-Land reduces the global averaged root mean square error of the skin temperature, taking as reference MODIS data, mainly due to the contribution of coastal points where spatial resolution is important. Since January 2020, the ERA5-Land period available has extended from January 1981 to the near present, with a 2- to 3-month delay with respect to real time. The segment prior to 1981 is in production, aiming for a release of the whole dataset in summer/autumn 2021. The high spatial and temporal resolution of ERA5-Land, its extended period, and the consistency of the fields produced makes it a valuable dataset to support hydrological studies, to initialize NWP and climate models, and to support diverse applications dealing with water resource, land, and environmental management.
The full ERA5-Land hourly and monthly averaged datasets presented in this paper are available through the C3S Climate Data Store at https://doi.org/10.24381/cds.e2161bac and https://doi.org/10.24381/cds.68d2bb30, respectively.
Research on heat waves (periods of excessively hot weather, which may be accompanied by high humidity) is a newly emerging research topic within the field of climate change research with high relevance for the whole of society. In this study, we analyzed the rapidly growing scientific literature dealing with heat waves. No summarizing overview has been published on this literature hitherto. We developed a suitable search query to retrieve the relevant literature covered by the Web of Science (WoS) as complete as possible and to exclude irrelevant literature ( n = 8,011 papers). The time evolution of the publications shows that research dealing with heat waves is a highly dynamic research topic, doubling within about 5 years. An analysis of the thematic content reveals the most severe heat wave events within the recent decades (1995 and 2003), the cities and countries/regions affected (USA, Europe, and Australia), and the ecological and medical impacts (drought, urban heat islands, excess hospital admissions, and mortality). An alarming finding is that the limit for survivability may be reached at the end of the twenty-first century in many regions of the world due to the fatal combination of rising temperatures and humidity levels measured as “wet-bulb temperature” (WBT). Risk estimation and future strategies for adaptation to hot weather are major political issues. We identified 104 citation classics, which include fundamental early works of research on heat waves and more recent works (which are characterized by a relatively strong connection to climate change).
The availability of satellite and reanalysis climate datasets and their applicability have been greatly promoted in hy-dro-climatic studies. However, such climatic products are still subject to considerable uncertainties and an evaluation of the products is necessary for applications in specific regions. This study aims to evaluate the reliability of nine gridded precipitation and temperature datasets against ground-based observations in the upper Tekeze River basin (UTB) of Ethiopia from 1982 to 2016. Precipitation, maximum temperature (T max), minimum temperature (T min), and mean temperature (T mean) were evaluated at daily and monthly timescales. The results show that the best estimates of precipitation are from the EartH2Observe, WFDEI, and ERA-Interim reanalysis data Merged and Bias-corrected for the Inter-Sectoral Impact Model Intercomparison Project (EWEMBI), and the Climate Hazards Group InfraRed Precipitation with Station data (CHIRPS) datasets. The percentage biases and correlation coefficients (CCs) are within ± 15% and > 0.5, respectively, for both EWEMBI and CHIRPS at the two timescales. All products underestimate the drought conditions indicated by the standardized precipitation index (SPI), while the EWEMBI and CHIRPS datasets show higher agreement with the observations than other datasets. The T mean estimates produced by the ECMWF Re-Analysis version 5 (ERA5) and the Climate Hazards Group InfraRed Temperature with Station data (CHIRTS) are the closest to the observations, with CCs of 0.65 and 0.55, respectively, at the daily timescale. The CHIRTS and EWEMBI datasets show better representations of T max (T min), with CCs of 0.69 (0.72) and 0.62 (0.68), respectively, at the monthly timescale. The temperature extremes are better captured by the ERA5 (T mean), CHIRTS (T max), and EWEMBI (T min) datasets. The findings of this study provide useful information to select the most appropriate dataset for hydrometeorological studies in the UTB and could help to improve the regional representation of global datasets. Citation: Reda, K. W., X. C. Liu, Q. H. Tang, et al., 2021: Evaluation of global gridded precipitation and temperature datasets against gauged observations over the upper Tekeze River basin, Ethiopia.
Within the Copernicus Climate Change Service (C3S), ECMWF is producing the ERA5 reanalysis which, once completed, will embody a detailed record of the global atmosphere, land surface and ocean waves from 1950 onwards. This new reanalysis replaces the ERA‐Interim reanalysis (spanning 1979 onwards) which was started in 2006. ERA5 is based on the Integrated Forecasting System (IFS) Cy41r2 which was operational in 2016. ERA5 thus benefits from a decade of developments in model physics, core dynamics and data assimilation. In addition to a significantly enhanced horizontal resolution of 31 km, compared to 80 km for ERA‐Interim, ERA5 has hourly output throughout, and an uncertainty estimate from an ensemble (3‐hourly at half the horizontal resolution). This paper describes the general set‐up of ERA5, as well as a basic evaluation of characteristics and performance, with a focus on the dataset from 1979 onwards which is currently publicly available. Re‐forecasts from ERA5 analyses show a gain of up to one day in skill with respect to ERA‐Interim. Comparison with radiosonde and PILOT data prior to assimilation shows an improved fit for temperature, wind and humidity in the troposphere, but not the stratosphere. A comparison with independent buoy data shows a much improved fit for ocean wave height. The uncertainty estimate reflects the evolution of the observing systems used in ERA5. The enhanced temporal and spatial resolution allows for a detailed evolution of weather systems. For precipitation, global‐mean correlation with monthly‐mean GPCP data is increased from 67% to 77%. In general, low‐frequency variability is found to be well represented and from 10 hPa downwards general patterns of anomalies in temperature match those from the ERA‐Interim, MERRA‐2 and JRA‐55 reanalyses.
The summers of 2018 and 2019 were characterized by unusually warm conditions over Europe. Here, we describe the intense heatwaves striking the Iberian Peninsula in early August 2018 and late June 2019. The 2018 episode was relatively short-lived but outstanding in amplitude, particularly in western Iberia. Similar to previous mega-heatwaves, the 2019 event was long-lasting and affected large areas of western and central Europe, including eastern Iberia. During these events, many absolute temperature records were broken in western and eastern Iberia, respectively (some of them standing since 2003). In both cases, a cyclonic circulation off the coast in the northeastern Atlantic and a strong subtropical ridge pattern over the affected area promoted the advection of an anomalously warm air mass. This paper highlights the role of these very warm, stable and dry air intrusions of Saharan origin in the western and eastern Iberia heatwave events. Using a thermodynamical classification based on the geopotential height thickness and potential temperature, we show how the magnitude and poleward extension of these Saharan intrusions were unprecedented in the period since 1948. The relationship between Iberian heatwaves and Saharan warm air intrusions is discussed in the long-term context, showing a closer link in southern sectors of the Peninsula. However, a consistent poleward trend in the latitudinal extension of these subtropical intrusions reveals their increasing relevance for heatwaves in northern sectors of Iberia and western Europe. This overall trend is accompanied by an apparent “see-saw” in the occurrence of subtropical intrusions between eastern and western Iberia on multi-decadal scales.
Global reanalysis products are extensively used for hydrologic applications in sparse data regions. European Centre for Medium‐Range Weather Forecasts Re‐Analysis version 5 (ERA‐5), among the new‐era reanalysis products, has been significantly improved for horizontal and vertical resolutions and data assimilation. However, the new‐era reanalysis products (ERA‐5, Climate Forecast System Reanalysis, ERA‐Interim, Modern Era Retrospective Analysis for Research and Applications version 2, and Japanese 55‐year Reanalysis Project) have not been evaluated for the hydrologic applications in India specially to understand if ERA‐5 outperforms the other reanalysis products or not. Here we use the five new‐era reanalysis products for the monsoon (June–September) season precipitation, maximum (Tmax) and minimum (Tmin) temperatures, total runoff, evapotranspiration, and soil moisture against the observations from India Meteorological Department in India for 1980–2018. We use a well‐calibrated and evaluated hydrological model (the Variable Infiltration Capacity model) to simulate hydrologic variables using the forcing from India Meteorological Department and reanalysis products. In addition, we evaluated the reanalysis products for streamflow and annual water budget for the two basins located in the diverse climatic settings in India. Our results show that ERA‐5 outperforms the other reanalysis products for the monsoon season precipitation, Tmax, evapotranspiration, and soil moisture. However, Climate Forecast System Reanalysis performs better than ERA‐5 for the monsoon season total runoff in India. Performance for streamflow and annual water budget for ERA‐5 is either better or comparable to the other reanalysis products in the two river basins. Overall, we find that ERA‐5 performs better than the other reanalysis products and can be used for the hydrologic assessments in India.
Climate reanalyses provide key information to calibrate proxy records in regions with scarce direct observations. The climate reanalysis used to perform a proxy calibration should accurately reproduce the local climate variability. Here we present a regional scale evaluation of meteorological parameters using ERA-Interim and ERA5 reanalyses compared to in-situ observations from 13 automatic weather stations (AWS), located in the southern Antarctic Peninsula and Ellsworth Land, Antarctica. Both reanalyses seem to perform better in the escarpment area (>1000 m a.s.l) than on the coast. A significant improvement is observed in the performance of ERA5 over ERA-Interim. ERA5 is highly accurate, representing the magnitude and variability of near-surface air temperature and wind regimes. The higher spatial and temporal resolution provided by ERA5 reduces significantly the cold coastal biases identified in ERA-Interim and increases the accuracy representing the wind direction and wind speed in the escarpment. The slight underestimation in the wind speed obtained from the reanalyses could be attributed to an interplay of topographic factors and the effect of local wind regimes. Three sites in this region are highlighted for their potential for ice core studies. These sites are likely to provide accurate proxy calibrations for future palaeoclimatic reconstructions.
It is widely acknowledged that the climate is warming globally and within the UK. In this paper, studies which assess the direct impact of current increased temperatures and heat-waves on health and those which project future health impacts of heat under different climate change scenarios in the UK are reviewed.
This review finds that all UK studies demonstrate an increase in heat-related mortality occurring at temperatures above threshold values, with respiratory deaths being more sensitive to heat than deaths from cardiovascular disease (although the burden from cardiovascular deaths is greater in absolute terms). The relationship between heat and other health outcomes such as hospital admissions, myocardial infarctions and birth outcomes is less consistent. We highlight the main populations who are vulnerable to heat. Within the UK, these are older populations, those with certain co-morbidities and those living in Greater London, the South East and Eastern regions.
In all assessments of heat-related impacts using different climate change scenarios, deaths are expected to increase due to hotter temperatures, with some studies demonstrating that an increase in the elderly population will also amplify burdens. However, key gaps in knowledge are found in relation to how urbanisation and population adaptation to heat will affect health impacts, and in relation to current and future strategies for effective, sustainable and equitable adaptation to heat. These and other key gaps in knowledge, both in terms of research needs and knowledge required to make sound public- health policy, are discussed.
Electronic supplementary material
The online version of this article (10.1186/s12940-017-0322-5) contains supplementary material, which is available to authorized users.
An extreme heat wave occurred in Russia in the summer of 2010. It had serious impacts on humans and natural ecosystems, it was the strongest recorded globally in recent decades and exceeded in amplitude and spatial extent the previous hottest European summer in 2003. Earlier studies have not succeeded in comparing the magnitude of heat waves across continents and in time. This study introduces a new Heat Wave Magnitude Index (HWMI) that can be compared over space and time. The index is based on the analysis of daily maximum temperature, in order to classify the strongest heat waves that occurred worldwide during the three study periods 1980-1990, 1991-2001 and 2002-2012. In addition, multi-model ensemble outputs from the Intercomparison Project Phase 5 (CMIP5) are used to project future occurrence and severity of heat waves, under different Representative Concentration Pathways (RCP), adopted by the Intergovernmental Panel on Climate Change (IPCC) for its fifth Assessment Report (AR5). Results show that the percentage of global area affected by heat waves has increased in recent decades. Moreover, model predictions reveal an increase in the probability of occurrence of extreme and very extreme heat waves in the coming years: in particular, by the end of this century, under the most severe IPCC AR5 scenario, events of the same severity as that in Russia in the summer of 2010 will become the norm and are projected to occur as often as every two years for regions such as southern Europe, North America, South America, Africa and Indonesia.
Heat waves have been linked with an increase in mortality, but the associated risk has been only partly characterized.
We examined this association by decomposing the risk for temperature into a "main effect" due to independent effects of daily high temperatures, and an "added" effect due to sustained duration of heat during waves, using data from 108 communities in the United States during 1987-2000. We adopted different definitions of heat-wave days on the basis of combinations of temperature thresholds and days of duration. The main effect was estimated through distributed lag nonlinear functions of temperature, which account for nonlinear delayed effects and short-time harvesting. We defined the main effect as the relative risk between the median city-specific temperature during heat-wave days and the 75th percentile of the year-round distribution. The added effect was defined first using a simple indicator, and then a function of consecutive heat-wave days. City-specific main and added effects were pooled through univariate and multivariate meta-analytic techniques.
The added wave effect was small (0.2%-2.8% excess relative risk, depending on wave definition) compared with the main effect (4.9%-8.0%), and was apparent only after 4 consecutive heat-wave days.
Most of the excess risk with heat waves in the United States can be simply summarized as the independent effects of individual days' temperatures. A smaller added effect arises in heat waves lasting more than 4 days.
Many environmental processes and ecological systems are being affected by the warming temperatures as a result of climate change. To correctly identify and attribute the uncertainty estimates in these systems, an investigation of temperature trend signal existing in the datasets that are used to study such systems is necessary. In this study, the trend of widely used ERA5 and ERA5-Land temperature estimates between 1951 and 2020 were validated using temperature trends from ground station-based observations in Turkey. The investigation included datasets obtained over 540 stations, and the seasonality and spatio-temporal variability of the trend accuracy was also investigated. On average, the trends of observations over all stations were 0.82 °C/decade and 0.30 °C/decade for the periods 2001–2020 and 1951–2020, respectively, indicating strong evidence of climate change. When the model datasets used spatially and temporally continuous datasets, the trends identified were 0.91 °C/decade and 0.21 °C/decade over the entire Turkey for the years 2001–2020 and 1951–2020, respectively. The difference in the 70-year trends of the two estimates was attributed to the missing datasets in observations. The differences between the trends of model estimates and observations were higher for the first decade than for the last two decades, stressing the impact of improved model estimates over time. All products showed heavy seasonality, suggesting that winter trends (1.3 °C/decade on average) are much higher than the summer (0.3 °C/decade) between 2001 and 2020. The results indicated a high degree of consistency between the trends of ERA5/ERA5-Land and observations, implying they may be used as a replacement to observations.
Heat waves have significant impacts on both ecosystems and human beings. This is compounded by future climate scenarios which indicate more frequent and severe heat waves in certain locations. There are members of communities that are more vulnerable to the effects of heat waves such as the elderly and infants and this presents particular challenges for the future. Hence it is timely to undertake a critical and systematic review of the effects of heat waves and mechanisms to mitigate their effects. There are significant implications associated with heat waves such as extra power consumption, community health, water consumption and quality, and additional costs within the natural and built environments. One of the critical issues is peak electricity demand which is closely linked with factors such as building occupant health and costs to consumers. Utilization of renewable and sustainable energy helps to mitigate this specific issue. Common policy instruments to deal with risks associated with heat waves include heat impact assessment and heat warning system. Similarly, building design should take impacts of heat waves into consideration such as dwelling adaptation. This review provides useful inputs to both policy making and industry practice on improving the resilience of urban and regional areas in the event of extreme weather conditions such as heat waves in the future.
The performance of a Didcot-type thermometer screen on an Automatic Weather Station and a conventional Stevenson screen were compared, both with each other and against an aspirated Assmann psychrometer. Maximum temperature in the Didcot screen exceeded the conventional screen maximum by up to 1 K on calm, sunny days, and Didcot minimum temperatures were as much as 1.5 K less than the screen minima on still, clear nights; mean temperature discrepancies between screens were + 0.3 and − 0.4 K for maxima and minima, respectively. The apparent psychrometric constant for the Didcot screen was 1.0 mbar K−1 which increased to 1.2 mbar K−1 when u < 2 m s−1 in contrast to the value of 0.799 mbar K−1 frequently used for the Stevenson screen.
Nonstationarities in the occurrence rates of flood events in Portuguese watersheds
- A T Silva
- M Portela
- M Naghettini
Nonstationarity and Uncertainty of Extreme Hydrological Events
- A Silva
OpenET: filling a critical data gap in water management for the western United States
- F S Melton
- FS Melton
Evaluation of global gridded precipitation and temperature datasets against gauged observations over the Upper Tekeze River Basin
- K W Reda
- X Liu
- Q Tang
- T G Gebremicael