Atmospheric and Climate Sciences

Published by Scientific Research Publishing
Online ISSN: 2160-0414
Relation between annual concentrations of elements in atmospheric particulate matter over Japan and the same data obtained in the region of Nonotake (data from NASN of Japan [5]). In some cases (see text) the concentration of anthropogenic element Cr was excluded from the data. The underlined cities are large industrial centres in the Japan [5]. 
Schematic representation of the flow-chamber of the PM10 type device for air sampling. 
Relationship between atmospheric PM elemental concentrations measured in the regions Odessa (Ukraine), Ljubljana (Slovenia), Vernadsky station (64 ◦ 15W; 65 ◦ 15S), South 
Geometrical method for determination of the entropy dimension D 1 , which leads 
Experimental data from the National Air Surveillance Network of Japan from 1974 to 1996 and from independent measurements performed simultaneously in the regions of Ljubljana (Slovenia), Odessa (Ukraine) and the Ukrainian "Academician Vernadsky" Antarctic station (64{\deg}15'W; 65{\deg}15'S), where the air elemental composition was determined by the standard method of atmospheric particulate matter (PM) collection on nucleopore filters and subsequent neutron activation analysis, were analyzed. Comparative analysis of different pairs of atmospheric PM element concentration data sets, measured in different regions of the Earth, revealed a stable linear (on a logarithmic scale) correlation, showing a power law increase of every atmospheric PM element mass and simultaneously the cause of this increase - fractal nature of atmospheric PM genesis. Within the framework of multifractal geometry we show that the mass (volume) distribution of atmospheric PM elemental components is a log normal distribution, which on a logarithmic scale with respect to the random variable (elemental component mass) is identical to normal distribution. This means that the parameters of two-dimensional normal distribution with respect to corresponding atmospheric PM-multifractal elemental components measured in different regions, are a priory connected by equations of direct and inverse linear regression, and the experimental manifestation of this fact is the linear correlation between the concentrations of the same elemental components in different sets of experimental atmospheric PM data.
MODIS land-surface temperature and regions of interest: (A) MODIS-Terra 22 July 2004 with 65˚N region and (B) 65˚N ACE2 DEM. Regions of interest for land-surface temperature change are represented by the 65˚N red circle A and the 120˚sector120˚sector regions B. 
Comparison plots of MODIS-Terra land-surface temperatures in the regions of interest, year 2000 through 2010: (A) 65˚N; (B) Eurasia; (C) Western North America and (D) Eastern North America and Western Europe. 
Comparison plots of MODIS-Aqua land-surface temperatures in the regions of interest, year 2002 through 2012: (A) 65˚N; (B) Eurasia; (C) Western North America and (D) Eastern North America and Western Europe. 
Change of land-surface temperature above 65˚N: (A) MODIS-Terra relative 10:30 and (B) MODIS-Aqua relative 13:30 local equator crossing times. Note: (A) that the beginning series March is from 2000 through 2010 and the ending series March is from 2001 through 2011 and (B) that the beginning series July is from year 2002 through year 2011 and the ending series July is from year 2003 through 2012. 
Change of land-surface monthly temperatures above 65˚N: (A) MODIS-Terra relative 10:30 and (B) MODISAqua relative 13:30 local equator crossing times. Note the decadal context of the months is the same as in Figure 4. 
Physical changes across the Arctic are driven in part by variations of land-surface heat absorption, conduction and re-radiation relative to solar irradiance. These changes manifest in active layer thickening and thinning, ground ice and ice wedge melting, thawing of permafrost and release and storage of carbon, energy fluxes and water. Using the MODIS sensors on NASA Aqua and Terra from March 2000 through July 2012 we investigate Arctic land-surface temperature under clear-sky condition changes and regional variations. Over this period we detect an increase in the number of days with daytime land-surface temperature above 0 degrees C: an additional 14 days for the decade. There are significant trends of increasing morning and afternoon land-surface temperatures with regional variations, on average. Variations in land-surface temperature are due to heterogeneity of surface material heat capacity and conduction. In a more general sense this is due to proportions of bare ground, ice, snow, vegetation, surface hydrology including palsa, thaw lakes and wetlands and geomorphology relative to the daytime clear-sky and seasonal variations of solar irradiance.
A four-dimensional data assimilation (FDDA) scheme based on a Newtonian relaxation (or “nudging”) was tested using observational asynoptic data collected at a coastal site in the Central Mediterranean peninsula of Calabria, southern Italy. The study is referred to an experimental campaign carried out in summer 2008. For this period a wind profiler, a sodar and two surface meteorological stations were considered. The collected measurements were used for the FDDA scheme, and the technique was incorporated into a tailored version of the Regional Atmospheric Modeling System (RAMS). All instruments are installed and operated routinely at the experimental field of the CRATI-ISAC/CNR located at 600 m from the Tyrrhenian coastline. Several simulations were performed, and the results show that the assimilation of wind and/or temperature data, both throughout the simulation time (continuous FDDA) and for a 12 h time window (forecasting configuration), produces improvements of the model performance. Considering a whole single day, improvements are sub- stantial in the case of continuous FDDA while they are smaller in the case of forecasting configuration. En- hancements, during the first six hours of each run, are generally higher. The resulting meteorological fields are finalised as input into air quality and agro-meteorological models, for short-term predictions of renew- able energy production forecast, and for atmospheric model initialization.
A GOMOS (Global Ozone Monitoring by Occultation of Stars) occultation spectrum of star Sirius at a tangent altitude of 14780 m (courtesy of J.-P. Bertaux and L. Blanot, Service d'Aéronomie, Verrières-le-Buisson, France). Bottom dotted spectrum is the ratio F ★ /F 0 (
, left frame, plots spectra of different types of blue skies: three blue day-time spectra (traces (1)) in different directions observed in the mid-afternoon (3~P.M. local time, observations of August 28, 2010), the sun is then well above the horizon; and two twilight blue sky spectra, one on the horizon 180˚from180˚from the sun and one at the zenith observed 5 minutes later (observations of October 11, 2010). As found by Wulf, Moore, and Melvin [17] the major difference between daylight and twilight blue skies is the presence of ozone in the latter spectra. Analytically the blue sky spectra of  deduce one from the other by a T-transformation of Equation (1) (, right plot), and differ by the amount of Rayleigh extinction, ozone absorption, and aerosol exitinction, sun-rays have experienced on their way through the atmosphere. Zenith spectrum (1) (upper trace) is well fitted (yellow spectrum of ) by the spectrum of the sun 6 times a Rayleigh function R (Equation (2)) with exponent a = 0.005 ( ). The generic analytical expression of a blue sky spectrum is therefore 
Blue sky. Left: three mid-afternoon blue sky spectra (top traces (1)), a twilight blue horizon in the direction opposite to the sun (2) and a zenith spectrum observed a few minutes later (3). The top trace is a zenith spectrum, the two dotted spectra were observed in the anti-solar direction at 60ånd 30˚elevation30˚elevation. The top red dashed line is a fit of the zenith blue sky spectrum by Rayleigh scattering of sunlight ( 
The color of the sky in day-time and at twilight is studied by means of spectroscopy, which provides an unambiguous way to understand and quantify why a sky is blue, pink, or red. The colors a daylight sky can take primarily owe to Rayleigh extinction and ozone absorption. Spectra of the sky illuminated by the sun can generally be represented by a generic analytical expression which involves the Rayleigh function R ≈ 1/λ^4 e(?a/λ^4), ozone absorption, and, to a lesser extend, aerosol extinction. This study is based on a representative sample of spectra selected from a few hundred observations taken in different places, times, and dates, with a portable fiber spectrometer.
Saturation curves for water substance onto the p T -plane ( p T and T T are called triple-point data): e wT = 6.11 mb; T T = 0.0098  ̊C . 
Troposphere specific regions depending on the manner in which V changes with T ( V and T are respectively volume and temperature of an air parcel): (d V /d T ) > 0; the particle swells when its temperature increases (so it becomes lighter); (d V /d T ) < 0 the particle shrinks when its temperature increases (so it becomes less light). 
Carnot Cycle in pV-diagram. A-B: isothermal expansion; B-C: adiabatic expansion; C-D: isothermal compression; D-A: adiabatic compression 
Carnot Cycle in TS-diagram. 
(a)-(d) Tornadoes are like little-bombs triggered by cloud’s additional greenhouse (Mbane, 2013). Indeed, Rayleigh and Reynolds numbers of passive convection motions depend mainly on air parcel temperature and humidity. Within additional greenhouse, temperature and water vapor increase exponentially and finally (as atmosphere is a dissipative system) trigger violent adiabatic expansion or tornadoes (as Rayleigh and Reynolds numbers become higher and generate turbulent motions). 
Atmospheric or climate phenomena are usually a combination of elementary events whose scales range from the very small (microscopic) to the infinitely large (synoptic). This means that build reasoning from ground-or space-based observations only, regardless of the physics of elementary processes, inevitably leads to erroneous results. Given the fact that plots of Troposphere Tricellular Circulation are only based on weather mean conditions measured near the ground (i.e.: pressure and winds fields observed at the surface of the earth), we want to improve these representations of the general circulation of the atmosphere, by using both Clausius-Clapeyron Relation and Carnot Principle derived respectively in 1832 and 1824. Indeed, Clausius-Clapeyron relation shows precisely that, unlike the dry water vapor that can be assimilated to the ideal gas at many circumstances, the saturated water vapor has, in an air parcel at the same time cold (temperature below 0.0098˚C) and rich in moisture (vapor pressure above 6.11 mb), thermoelastic properties diametrically opposed to those of ideal gas (including dry water vapor). Vertical profiles of temperature and water vapor in the atmosphere provided by ground-or space-based observations lead to the location of a troposphere region in which the ideal gas assumption should be banned: hence appropriate and unique plot of earth's atmosphere tricellular circulation.
Monthly mean summer (DJF) temperature and precipitation from Global Historical Climate Network (GHCN-V3) for the period of 1870-2011, are analyzed to assess the role of teleconnections on climate of Darwin, Australia. Indices of El Nino-Southern Oscillation (ENSO), Antarctic Oscillation (AAO), Pacific Decadal Oscillation (PDO), North Atlantic Oscillation (NAO), Arctic Oscillation (AO), and Pacific North American Oscillation (PNA) are extracted from monthly means and compared with climatic data of Darwin. Most of these climate modes are shown to have a strong influence on the monthly mean summer temperature and precipitation. ENSO is shown to have a positive relationship with the amount of precipitation received and a negative relationship with the temperature. Where an El Nino event produces warmer drier conditions and a La Nina event produces colder wetter conditions. The AAO is shown to cause cold and dry conditions during the positive phase and warm and wet conditions during the negative phase. The PDO is shown to cause El Nino like condition during the positive phase causing warmer, drier weather, and La Nina like conditions during the negative phase causing cooler, wetter weather. Through the analysis it is also shown that the NAO, AO, and PNA have little effect on the temperature and precipitation patterns of Darwin.
History of coronavirus naming in relationship to virus taxonomy and diseases caused by these viruses [2].
Location map of Conakry in Republic of Guinea.
Cumulative numbers of confirmed cases: (a) and (b) corresponds respectively COVID-19 and Death cases curves evolution in Conakry (Republic of Guinea) between March 1 and May 31, 2020. second confirmed cases were recorded on March 20 and the number kept increasing to reach a total of 16 confirmed cases by the end of March 2020. During the first week of April 2020, the number of cases increased from 16 to 100 confirmed cases. The same trend continues during the second week to reach a pic of 1351 cases. The month of May is characterized by an unprecedented and alarming increase in the number of COVID-19 confirmed cases. The confirmed cases drastically increased from 1351 to 1750, during the first week of May 2020. This trend continues to reach the pic of 3706 confirmed cases, which positioned Guinea among the most affected west African countries. Figure 6(b) presents evolution curve of death cases recorded in Conakry due to COVID-19 between March and May 2020. As per see Figure 6(b), the whole of March, despite the slight increase in the number of confirmed cases recorded no deaths due to COVID-19. The first death of COVID-19 in Conakry was recorded on April 16, 2020, and the highest case is 15 recorded on May 31, 2020. The last two weeks of April and May between 16 and the end of month respectively are marked by a trend increasing of death cases. The highest number of death cases per day was 7, recorded from April 26 to April 30. The month of May was identified having the highest morbidity and mortality due to COVID-19, with a minimum of 2 recorded cases per day throughout the month, except on May 2 and May 4.
Anomalies of COVID-19, minimum relative humidity (RHmin) and minimum temperature (Tmin) in Conakry. The red, black and blue curve are respectively COVID-19 cases, Tmin and RHmin from March 1 to May 31, 2020.
Anomalies of COVID-19, minimum Relative Humidity (RHmax) and minimum temperature (Tmax) in Conakry. The red, black and blue curve are respectively COVID-19 cases, Tmax and RHmax from March 1 to May 31, 2020.
Abstract The coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), dates back to December 29, 2019, in Wuhan, China. It quickly spreads like wildfire to all continents in the following months. In Guinea, the first case of COVID-19 and death were all reported respectively on March 12 and April 16, 2020. Since then, several studies have found a relationship between certain environmental conditions such as the meteorological factors to have the potential of contributing to the spread of the virus. Thus, this study aims at examining the extent to which observed meteorological factors might have contributed to the spread of the coronavirus disease 2019 (COVID-19) cases in Conakry, from March 1 to May 31, 2020. Meteorological factors such as temperature (Tmin, Tmean and Tmax) and relative humidity (RHmin, RHmean and RHmax) were analyzed together with the data on the COVID-19. The dynamic of the COVID-19 in Guinea was analyzed along with that of some west African countries. The analysis on the dynamic of the COVID-19 pandemic in West Africa indicated Guinea as one of the most affected countries by the pandemic after Nigeria and Ghana. The study found that in general an increase in the temperature is linked to a decline in the COVID-19 number of cases and deaths, while an increase in the humidity is positively correlated to the number of cases and deaths. Nevertheless, from this study it was also observed that low temperature, mild diurnal temperature and high humidity are likely to favor its transmission. The study therefore, recommends that habitations and hospital rooms should be kept in relatively low humidity and relatively higher temperature to minimize the spread of the (SARS-CoV-2). Keywords Conakry, Guinea, COVID-19, Meteorological Factors, Temperature, Humidity
Researches are being carried out worldwide to understand the nature of temperature change during recent past at different geographical scales so that comprehensive inferences can be drawn about recent temperature trend and future climate. Detection of turning points in time series of meteorological parameters puts challenges to the researches. In this work, the temperature time series from 1941 to 2010 for Asansol observatory, West Bengal, India, has been considered to understand the nature, trends and change points in the data set using sequential version of Mann-Kendall test statistic. Literatures suggest that use of this test statistic is the most appropriate for detecting climatic abrupt changes as compared to other statistical tests in use. This method has been employed upon monthly average temperatures recorded over the said 70 years for detection of abrupt changes in the average temperature of each of the months. The approximate potential trend turning points have been calculated separately for each month (January to December). Sequential version of Mann-Kendall test statistic values for the months of July and August is significant at 95% confidence level (p < 0.05). The average temperature for most of the other months has shown an increasing trend but more significant rise in July and August temperature has been recognized since 1960s.
By making use of Empirical Orthogonal Function (EOF) analysis the spatial and temporal variability was investigated in January over the period of 1950 to 2000 in Pakistan. The analysis is based on the combination of ground observed mean monthly temperature data and National Centre for Environmental Prediction (NCEP) reanalysis data of sea level pressure (SLP) and 500-hPa fields. The results reasonably reveal that the variation in January temperature have links with global te-leconnections at SLP and 500-hPa pressure heights. The analysis shows variability at interannual to interdecadal time scale. The interannual variation is more prominent than the interdecadal signal of temperature anomaly. The simulated coefficient patterns show reasonable variation with regional detail from south (north) to north (south) in the study area. The study could be useful as baseline information for climate change studies in Pakistan.
Intensity and variability of droughts are considered inIranduring the period 1951 to 2005. Four variables are considered: the Palmer Drought Severity Index (PDSI), the soil moisture, the temperature and the precipitation (products used for the analysis are downloaded from the NCAR website). Link with the climatic indexLa Ninais also considered (NOAA downloadable products is used). The analysis is based on basic statistical approaches (correlation, linear regressions and Principal Component Analysis). The analysis shows that PDSI is highly correlated to the soil moisture and poorly correlated to the other variables—although the temperature in the warm season shows high correlation to the PDSI and that a severe drought was experienced during 1999-2002 inthe country.
Location of the Yangtze River basin. 
Daily precipitation data during 1960-2002 from 150 stations in the Yangtze River basin were analyzed with the help of linear trend analysis. Highest 5-day and 10-day precipitation amount (R5D and R10D) and percentile daily precipitation maxima (prec95p for 95th percentile and prec99p for 99th percentile) were accepted as the precipitation extreme index. The frequency of the R5D and R10D was in downward trend, this phenomenon is more obvious in the middle Yangtze River basin; The stations with total precipitation of R5D and R10D are in significant upward trend (> 95% confidence level) are mostly located in the lower Yangtze River basin and the south-western part of the Yangtze River basin; 2) the spatial distribution of the frequency of total precipitation of the percentile daily precipitation maxima is similar to that of R5D and R10D. However the frequency of prec95p and prec99p is in significant upward trend. The upward trend of total precipitation changes of prec95p and prec99p is more obvious than that of frequency of prec95p and prec99p. The regions dominated by upward trend of frequency/total precipitation of prec95p and prec99p are also the lower Yangtze River basin and south-western part of the Yangtze River basin. Therefore the occurrence probability of the flash floods in the lower Yangtze River basin and south-western part of the Yangtze River basin will be greater.
This study aimed to detect trends in the long-term hydro-climatic series using non-parametric methods. The annual and seasonal linear trends of rainfall, temperature, runoff, water level and evaporation were analysed for stations in downstream Kaduna River Basin during 1975-2014. The non-parametric Mann-Kendall and Sen’s estimator of slope procedures were adopted to identify if there exists an increasing or decreasing trend with their statistical significance at 95% level of confidence. The datasets were checked to account for auto-correlation prior to determining trends using Mann-Kendall test. The existence of abrupt changes was detected by means of Cumulative Sum Charts and Bootstrapping analysis. The results of study indicated increasing trends for seasonal and annual temperature and runoff series. Water level and evaporation revealed statistically decreasing trends both on annual and seasonal periods. However, for the period 1975 to 2014 no significant distinctive trend was observed for rainfall at the investigated stations. Change-points in time series were identified in all the investigated hydro-climatic records for the sub-basin. Generally, the detection of the trend for hydro-climatic variables by Mann-Kendall test conforms to Sen’s test results. It is concluded that the basin is sensitive to climate variability and water stress impacts which will affect food security. So, it would be necessary to make adjustments in the adaptive water-use strategies being adopted at present in the catchment.
Distribution plots of rainfall over Kakamega Meteorological Station. Two successive climate regimes are compared here: 1957 to 1986 versus 1987 to 2016 climate period.
Distribution plots of rainfall over Kisumu Meteorological Station. Two successive climate regimes are compared here: 1957 to1986 versus 1987 to 2016 climate period.
Distribution plots of rainfall over Kisii. Two successive climate regimes are compared here: 1957 to1986 versus 1987 to 2016 climate period.
Boxplots showing variability in a number of rainy days, onset of long rains, cessation of long rains, onset and cessation of short rains from left to right in Julian days. Inserted are the coefficients of variability.
Selected weather stations in LVB.
Climate extremes have increased in the recent past and they are further being exacerbated by climate change and variability. In this paper, we sought to determine rainfall characteristics over the Lake Victoria Basin of Kenya in 1987-2016, as a basis of understanding climate variability. The methodology used included; Standardized Precipitation Index to depict variability, coefficient of variation for spatial analysis and the Mann-Kendall test to test the presence of trends in data. We established that Lake Victoria basin is relatively wet through-out the year, with two distinct rainfall seasons March-April-May (MAM) and October-November-December (OND) that support human livelihood and ecology. The normal wetness conditions have declined over time, paving way for both dry and wet extremes conditions between 1997-1998 and 2002-2006, respectively. The rainfall extremes have become frequent in the last decade in 2007-2016. We also established a decline in the MAM rainfall seasons, and an increase during the October-December rainfall seasons in 1987-2016. Furthermore, the number of rainy days has declined with the on- set and cessations of both long rains and short rains having shown a variability of at least 50% and 30% respectively, in a range of about 100 to 200 Julian days. The decline in wet condition is likely to affect economic activities especially the rainfed agriculture. The changing rainfall trends over the basin therefore, call for proper human livelihood planning and ecological monitoring in order to achieve ecological sustainability.
Time series of daily UV radiation measured by the ground-based Brewer spectrophotometer #115 in Hong Kong during 1995-2005 were studied through statistics analysis, with focus on the variability and long term changes in relation to total ozone, clouds and AOD (Aerosol Optical Depth). The 11-year mean UV daily dose is 2644±262 J/m2, with maxima(3311 J/m2) in 2000 and minima (2415 J/m2) in 2002. The data were compared with that from TOMS (Total Ozone Mapping Spectrometer) Version 8 and show general agreement between the two. However, the Brewer UV measurement is about 10% lower compared to TOMS data. Apart from the common-known strong seasonal cycle, 26 month periodical was resolved by use of wavelet analysis, which was believed to be associated with quasi-biennial oscillation (QBO) of general circulation. In cloudy days, the annual mean UV daily dose decrease 3.5% to 44.5% compared to clear days. It was also found that surface UV irradiance has close relation to air pollution. Under clear sky condition, 1% AOD increase will lead to 0.2% UV decrease. While global UV radiation increase due to the worldwide observed ozone depletion, investigations indicate that this trend is not significant in Hong Kong during the last 11 years. The possible causes can be attributed to the compensative effect from two aspects. One is the increase of UV resulting from the reduction of clouds with rate of 0.56/10 yr. The other is the decrease of UV due to the enhancement of total ozone and AOD with a rate of 4.23 DU/10 yr and 0.33/10 yr, respectively.
Global-mean radiative forcing versus 1850 value for each of the following sources: (a) Long-lived greenhouse gases; (b) All aerosols; (c) Tropospheric ozone; (d) Changes in land use; (e) Changes in solar irradiance; (f) Volcanic eruptions; (g) Total of all sources. Aerosol forcing displayed in panel (b) is calculated based on HADCRUT4 optimization for prescribed emissions; all other forcings are prescribed. 
Measurements show that the Earth's global-average near-surface temperature has increased by about 0.8˚C since the 19th century. It is critically important to determine whether this global warming is due to natural causes, as contended by climate contrarians, or by human activities, as argued by the Intergovernmental Panel on Climate Change. This study updates our earlier calculations which showed that the observed global warming was predominantly human-caused. Two independent methods are used to analyze the temperature measurements: Singular Spectrum Analysis and Climate Model Simulation. The concurrence of the results of the two methods, each using 13 additional years of temperature measurements from 1998 through 2010, shows that it is humanity, not nature, that has increased the Earth's global temperature since the 19th century. Humanity is also responsible for the most recent period of warming from 1976 to 2010. Internal climate variability is primarily responsible for the early 20th century warming from 1904 to 1944 and the subsequent cooling from 1944 to 1976. It is also found that the equilibrium climate sensitivity is on the low side of the range given in the IPCC Fourth Assessment Report.
Enrichment factors of 24 elements in PM 2.5 samples.
Scatter-plots of PM 2.5 OC and EC concentrations in four seasons. 
The chemical and physical characteristics of PM2.5, especially their temporal and geographical variations, have been explored in metropolitan Hangzhou area (China) by a field campaign from September 2010 to July 2011. Annual average concentrations of PM2.5 and PM10 during non-raining days were 106 - 131 μg.m-3 and 127 - 158 μg.m-3, respectively, at three stations in urban breathing zones, while corresponding concentrations of PM2.5 and PM10 at an urban background station (16 mabove ground level in a park) were 78 and 104 μg.m-3, respectively. For comparison, the annual average PM10 concentration at a suburban station (5 mAGL) was 93 μg.m-3. Detailed chemical analyses were also conducted for all samples collected during the campaign. We found that toxic metals (Cd, As, Pb, Zn, Mo, Cu, Hg) were highly enriched in the breathing zones due to anthropogenic activities, while soluble ions (, , ) and total carbon accounted for majority of PM2.5 mass. Unlike most areas in China where sulfate was several times of nitrate in fine PM, nitrate was as important as sulfate and highly correlated with ammonium during the campaign. Thus, a historical shift from sulfate-dominant fine PM to nitrate-dominant fine PM was documented.
The CMAQ modeling domain. The black, red, and blue boxes denote domains over the 36-km continental US, the 12-km western US, and the 12-km eastern US, respectively (filled yellow, orange, blue, green, and red colors denote s ub-regions northeast, southeast, Midwest, central and west for statistics). 
Summary of observational databases used in the model evaluation.
Seasonal-mean performance statistics for column predictions over the 36-km CONUS domainin 2002 1 .
A multiple-pollutant version of CMAQ v4.6 (i.e., CMAQ-MP) has been applied by the US EPA over continental US in 2002 to demonstrate the model's capability in reproducing the long-term trends of ambient criteria and hazardous air pollutants (CAPs and HAPs, respectively) in support of regulatory analysis for air quality management. In this study, a comprehensive model performance evaluation for the full year of 2002 is performed for the first time for CMAQ-MP using the surface networks and satellite measurements. CMAQ-MP shows a comparable and improved performance for most CAPs species as compared to an older version of CMAQ that did not treat HAPs and used older versions of na-tional emission inventories. CMAQ-MP generally gives better performance for CAPs than for HAPs. Max 8-h ozone (O 3) mixing ratios are well reproduced in the O 3 season. The seasonal-mean performance is fairly good for fine particu-late matter (PM 2.5), sulfate , and mercury (Hg) wet deposition and worse for other CAPs and HAPs species. The reasons for the model biases may be attributed to uncertainties in emissions for some species (e.g., ammonia (NH 3), elemental carbon (EC), primary organic aerosol (POA), HAPs), gas/aerosol chemistry treatments (e.g., secondary or-ganic aerosol formation, meteorology (e.g., overestimate in summer precipitation), measurements (e.g.,  2 4 SO   3 NO ), and the use of a coarse grid resolution. CMAQ cannot well reproduce spatial and seasonal variations of column variables except for nitrogen dioxide (NO 2) and the ratio of column mass of HCHO/NO 2 . Possible reasons include inaccurate seasonal allocation or underestimation of emissions, inaccurate BCONs at higher altitudes, lack of model treatments such as mineral dust or plume-in-grid process, and limitations and errors in satellite data retrievals. The process analysis results show that in addition to transport, gas chemistry or aerosol/emissions play the most important roles for O 3 or PM 2.5 , respectively. For most HAPs, emissions are important sources and cloud processes are a major sink. Simulated 2 2 3 H O HNO P P and HCHO/NO 2 indicate VOC-limited chemistry in major urban areas throughout the year and in other non-urban areas in winter, but NO X -limited chemistry in most areas in summer.
Monitoring sites (ITO, Sirifort and DCE), major roadways and power plants. 
Count of exceedances for particulate matter.
Correlations of pollutants.
We analyzed 1-hour, 8-hour and 24-hour averaged criteria pollutants (NO2, SO2, CO, PM2.5 and PM10) during 2004-2009 at three observational sites i.e. Income Tax Office (ITO), Sirifort and Delhi College of Engineering (DCE) in Delhi, India. The analysis reveals increased pollutant concentrations at the urban ITO site as compared to the other two sites, suggesting the need to better locate hot spots in designing the monitoring network. There is also significant year to year variation in the design value trends of criteria pollutants at these three sites, which may be attributed to meteorological variations and local-level emission fluctuations. Correlations among criteria pollutants vary annually and spatially from site to site, indicating the heterogeneous nature of air mix. The annual ratios of CO/NOx are considerably higher than SO2/NOx confirming that vehicular source emissions are the primary contributors to air pollution in Delhi. The seasonal analysis of criteria pollutants reveals relatively higher concentrations in winter because of limited pollutant dispersion and lower concentrations during the monsoon period (rainy season). The diurnal averages of criteria pollutants reveal that vehicular emissions strongly influence temporal variations of these pollutants. Weekdays and weekend diurnal averages do not show noticeable differences.
This paper presents the longitudinal distribution of total ozone along several latitudinal circles from both hemispheres during a strong geomagnetic storm that occurred on 24 August 2005 after a solar proton event (the maximum flux of protons with energy > 10 MeV was 1.70 × 107 protons on 23 August). For that, we use average daily values of total ozone observations (=column ozone amount) in Dobson units for the period 18-25 August 2005 (obtained from the Total Ozone Mapping Spectrometer, TOMS). The considered storm occurred after a relatively quiet geomagnetic period and it is not superposed by another perturbation, which permit us to identify clearly the effects of the geomagnetic storm on total ozone. The results show statistically significant decreases in ozone along the latitudinal circles 70°N and 70°S (summer and winter), no statistically significant effects at middle latitudes (40°S) and sparse statistically significant increases at low latitudes (20°S). The role of some mechanisms to explain the features observed is considered.
Study area: Lamto (6˚31N and 5˚02W), Côte d'Ivoire (adapted from Diawara et al., 2014).
Precipitation-temperature diagram over 2008-2015 period. GSS, GSP, PSS and PSP are the great dry season, the great wet season, the short dry season and the short-wet season respectively.
Mean monthly changes in TER (in black) and GPP (in blue) of the TER/GPP ratio (in red) observed at the Lamto station over 2008-2015.
Interannual Variations of NEE (red) and Temperature (black), rainfall (blue) and radiative flux (green) in the Lamto region over the 2008-2015 period.
Mean monthly variations of standardized anomalies of the NEE flux (red) and Temperature (black), rainfall (blue) and radiative flux (green) and, their associated correlation coefficients over the 2008-2015 period.
The temporal variations of the Gross Primary Productivity (GPP), the Total Ecosystem Respiration (TER) and the Net Ecosystem Exchange (NEE), and their responses to meteorological conditions (e.g. temperature, radiative flux and precipitation) at Lamto, in wet savannah region across Côte d’Ivoire are analyzed using GFED-CASA and daily meteorological data recorded over the 2008-2015 period. The study shows the links between these carbon fluxes and climate variability at Lamto that is subject to high anthropogenic pressures and seasonal bushfires. The correlative statistics from multiple regression methods were used to assess the different relationships and show how they change in time. The results show important seasonal variability in the Gross Primary Productivity and the Total Ecosystem Respiration mainly associated with the changes in temperature and radiative flux. In addition, the statistical analysis suggests a high correlation between meteorological conditions and the GPP and TER. These climatic conditions may explain 83% and 79% of the variances of GPP and TER respectively. Moreover, the interannual variability of the Net Ecosystem Exchange indicates that around Lamto, in the subhu-mid savannah, the ecosystem behaves as a carbon sink similar to other West African ecosystems. On the other hand, there is no clear link between the NEE and temperature, radiative flux and precipitation. This lack of connec-tion may suggest a limited response of the NEE interannual dynamics related to the changes in climatic features.
25 November 2009 is an unforgettable day for the people in Jeddah, the second largest city in the Kingdom of Saudi Arabia (KSA). On that day, Jeddah turned into a disaster zone following a short heavy rainfall event that triggered flash floods leaving 122 fatalities and considerable losses. Numerical experiments using the Pennsylvania State University-National Center for Atmospheric research mesoscale meteorological model (MM5) have been performed to investigate the event. It was caused by a short quasi-stationary mesoscale convective system that developed over Jeddah and lasted for about 8 hours. Rainfall totals computed by the model exceeded 400 mmin some localities in the southern part of Jeddah city and to the north of Jeddah in Thuwal city. The limited available observed rainfall totals, atKingAbdulAzizInternationalAirportand wadiQaws rain gauges, and Jeddah’s weather radar observations corroborates the ability of the model to reproduce the spatial and temporal characteristics of the rainfall event. A synoptic environment characterized by warmRed Seasurface temperatures and high humidity in the low levels of the troposphere. A stationary anticyclone centered over the southeast of theArabian Peninsulaconcentrated the water vapour flow to a narrow passage over Jeddah. Simulation results suggested that the development of a mesolow by latent heat release, as well as cyclogenesis induced by Al Hejaz escarpments, could have played an important role in enhancing the event by providing low-level convergence and enhanced upslope winds, and upper level atmospheric instability.
Any system designed to simulate the earth's atmosphere general circulation, must necessarily be based on the spatial-or temporal average conditions. Irregularities in the profiles of air motions that we observe on daily weather maps often make lose any real meaning to the general circulation. As complicated and inconsistent that is the daily traffic of air particles, it is interesting to define a general circulation characteristic of the average air transportation around the globe. Indeed, this transport responds to a need to transfer heat from the equator (heat source) to the poles (cold sources). Mbane Biouele formula (2009), derived from Clausius-Clapeyron relation (1832), now allows faithful and unique representation of the tricellular general circulation: Hence, the possibility of access to the earth's atmosphere prevailing surface winds in summer as well as winter.
Tropical cyclone Phet is the second strongest tropical cyclone ever recorded in the Arabian Sea. Phet made landfall in the northeast mountainous area of Oman in early morning on 4 June in 2010, causing a breaking record rainfall in this arid region of 488 mm/48 h. The cyclone heavy rainfall triggered flash floods causing enormous losses in lives and infrastructure in northeast Oman. The state of the art Advanced Research WRF model is used to study the atmospheric circulation and to reproduce the heavy rainfall over Oman. Three one-way nested domains with 32 vertical layers with terrain following sigma coordinate are used to setup eight numerical experiments aiming to investigate the effect of initialization time, horizontal grid resolution and terrain elevations on reproducing the cyclone track, intensity and heavy rainfall. Simulation results show negligible effect of model initialization time on cyclone track, intensity and rainfall. In contrast, the orographic effect played a substantial role in rainfall simulation over northeast Oman. The heavy rainfall was a combination of the cyclone circulation effect and the orographic lifting in the mountains. The northeasterly cyclone moist-warm wind was lifted in the Omani mountains releasing its potential energy and enhancing further thermal convection. The numerical experiment with the highest terrain elevation (RUN3.3-C) resulted in overestimation of observed rainfall due to the enhanced topographic lifting of the saturated cyclone wind. Experiment with similar horizontal grid resolution but smoother terrain elevation (RUN3.3-TER) resulted in much less rainfall amount comparable to the observed values. The increased precipitation in RUN3.3-C is due to the increase in the rain- water and cloud water and graupel of the explicit moisture scheme.
Modelings of the studied months are presented, seeing that the most water accumulation was registered in June 2012 with 85 mm and the less in December 2011 with 0 mm. The highest accumulation of humidity was recorded in May with 85% and the lowest accumulation was recorded in December 2011 with 48%. 2Dand 3D graphics were obtained by use of Puebla city coordinates and data was located in the z-axis, for distinguishing in a precise way the maxima and minima concentrations in the different months of year. 
This work presents the results of the analysis of meteorological variables applying the modeling Ion-Wavelets in a hypothetical manner. In this case the Morlet wavelet transform is used, which is the result of a huge number of researches made in the80’s and applied to various physical phenomena derived from natural chaotic processes; the data were processed using the phenomenon “El Nino” and CO2 (Carbon dioxide) due to the fact that these are the meteorological phenomena which best adapt to our object of study correlating with distribution of Gauss and Morlet during the study period in the Puebla Valley.
Atmospheric flow in the presence of a blocking system (high pressure) in the Southern Hemisphere [5].
Southeast region of Brazil (in red) and adjacent South Atlantic Ocean.
illustrates the air temperature anomalies in January and February 2014. It is noted that the observed temperatures were 1˚C to 2˚C above the climatological temperatures. However, it is noteworthy that these values are average and attenuated by the reanalysis parameterization. According to the National Institute of Meteorology (INMET), January 2014 was the warmest month in São Paulo city since 1943, with a mean maximum temperature of 31.9˚C. In the Rio de Janeiro city, January 2014 recorded a mean maximum temperature of 36.2˚C against the climatological average of 32˚C in the summer months [10]. The anticyclonic circulation cooperated for a smooth reduction in moisture availability in the eastern sector of Brazil in January and February 2014 (Figure 9). Checking the specific humidity anomalies at 2 meters also in Figure 9, it was noted that there were no significant irregularities over the country during the summer. Although the sufficient moisture in the atmosphere, physical and dynamic conditions associated with the subsidence movement of the blocking high pressure did not allow the development of deep cloudiness and, hence, precipitation . Thus, it was not registered any episode of South Atlantic Convergence Zone (SACZ), the moisture convergent flow in the lower troposphere that is responsible for the peak of the rainy season between December and February in the Midwest and Southeast regions of Brazil [11]. February 2014 was the month in which the absence of rainfall became strongly critical in climatological terms, in addition to installing a vehement concern about the reservoirs that store water to supply the population in Southeastern Brazil. Figure 10 shows the INMET precipitation climatology for Brazil in February [12]. It is observed that the average rainfall is about 180 to 220 mm in the south-central region of the southeastern country. However, according to the total rainfall in February recorded by CPTEC—Center for Weather Forecast and Climate Studies (Figure 11), the rainfall volume did not exceed 50 mm in most of the region [13], representing just around 25% of normal and a negative anomaly of 100 to 200 mm. It was showed that, for the east and west sectors of South America, the frequency of blockings is higher during the winter and spring months [14]. Wherefore, the atmospheric blocking that developed over the South Atlantic Ocean and energetically acted on the Southeastern Brazil was characterized as anomalous because of its duration of about 30 subsequent days during the summer. This led to an unusual rainy season, with rainfall amounts far below normal.  
Mean field of air temperature anomalies (˚C) for January and February 2014.  
Under conditions of atmospheric blocking, the presence of a quasi-stationary anticyclone of large amplitude disrupts the normal eastward progression of the synoptic systems. These blockings correspond mainly to a positive anomaly of the air pressure. As a result, in the regions affected by the blocking occur several consecutive dry days and temperatures above average. This paper aims to discuss synoptically the atmospheric blocking phenomenon occurred in January and February 2014 in the South Atlantic Ocean, affecting especially the Southeastern Brazil and sectors that depend on the quantity of water for their activities in the region, such as agriculture and electricity generation. The significant population concentration makes this area emphatically vulnerable to long periods of drought, especially during the summer, affecting the water supply for the population. In order to achieve this goal, data of geopotential height at 850/500 hPa, streamlines in 850/500 hPa, pressure, temperature, humidity and wind at surface were evaluated through NCEP/ NCAR reanalysis (CFSRv2—Climate Forecast System Reanalysis Version 2) with 0.2˚×2˚× 0.2˚resolu2˚resolu-tion. The analysis showed that the stationary anticyclone was configured dynamically favorable to blocking in the lower and middle levels of the atmosphere. Thus, atmospheric pressure at mean sea level presented values above normal combined with high average air temperature. By the cli-matological analysis, it was noted that there were emphatic negative precipitation anomalies over Southeastern Brazil. This atmospheric blocking was characterized as anomalous due to its long duration in a considered rainy season.
This study aimed at establishing and quantifying the evolution and socio-economic impacts of extreme rainfall events in October 2019. The study also focused on ascertaining the extent to which the Indian Ocean Dipole (IOD) and the El Niño Southern Oscillation (ENSO) influenced anomalous rainfall over East Africa (EA) in October 2019. It employed Singular Value Decomposition (SVD) methods to analyze inter-annual variability of EA rainfall and the Sea Surface Temperature Anomalies (SSTA) over the Indian and Pacific Ocean with a focus on October to December 2019 rainfall season. The SVD analysis enabled the exploration of the leading modes from the mean monthly rainfall and SSTs leading to the determination of the likely influence of the IOD and ENSO respectively. The first SVD coupled modes, which dominate the co-variability between the October rainfall over the EA domain, and SSTA over the Indian and Pacific Oceans based on 1981 to 2010 climatology indicate the monopole positive co-variability with rainfall over the entire EA domain. The corresponding spatial pattern for the SSTA over the Indian Ocean (IO) recaptures the positive IOD event while the central equatorial Pacific Ocean (i.e., over Niño 3.4 region) reveals a monopole positive loading, a typical signal for the warm phase of ENSO. The positive rainfall anomaly over the EA during October is found to be associated with either the IOD event or ENSO condition events independently or in phase. However, the inter-annual variability between October rainfall over EA and ENSO reveals a moderate relationship (r = 0.4212) while a robust association (r = 0.7084) is revealed with IOD. Comparatively, the October 2019 rainfall anomaly peaks the highest in history over the EA and was found to be coupled with highest positive IOD event in record. Unlikely, the 1997 October rainfall (which peaked the second in history), was associated with the co-occurrence of the positive phase of ENSO and IOD events. The findings of this study suggest that the positive IOD coupled mode had large impact on the distribution and variability of the October 2019 rainfall over the EA region.
In our Fair Plan 5 paper, we compared the CO2 emissions of the 80%-Emission-Reduction-By-2050 (80/50) Plan with the CO2 emissions of our Fair Plan to Safeguard Earth’s Climate. We found that the 80/50 Plan reduced CO2 emissions more rapidly than necessary to achieve the principal objective of the Fair Plan: to keep Global Warming (GW) within the 2˚C (3.6˚F) limit adopted by the UN Framework Convention on Climate Change (UNFCCC) “to prevent dangerous anthropogenic interference with the climate system”. Here, we ask the “What If” question: “What would the GW of the 80/50 Plan be post 2100 if its CO2 emissions post 2100 were kept at their 2100 value?” We find that although the GW of the 80/50 Plan decreases slightly over part of the 21st century, it does not remain constant thereafter. Rather, the GW of the 80/50 Plan begins to increase in 2088, exceeds that of the Fair Plan beginning in 2230, exceeds the 2˚C (3.6˚F) limit of the UNFCCC in 2596, and ends the millennium at 2.7˚C (4.8˚F). Thus, not only does the 80/50 Plan phase out humanity’s CO2 emissions faster than necessary to fulfill the UNFCCC constraint, it also fails that constraint if its CO2 emissions post 2100 are kept at their 2100 value. Accordingly, we believe that the Fair Plan to Safeguard Earth’s Climate is superior to the 80/50 Plan.
Top-cited authors
Mojtaba Zoljoodi
  • Iranian National for Oceanography and Atmospheric Science
Ali Didevarasl
  • uniss-CMCC
Shweta Bhati
  • Indian Institute of Technology Delhi
Manju Mohan
  • Indian Institute of Technology Delhi
Michael Schlesinger
  • University of Illinois, Urbana-Champaign