Objective:To determine the significance of temperature,rainfall and humidity in the seasonal abundance of Anopheles stephensi in southern Iran.Methods:Data on the monthly abundance of Anopheles stephensi larvae and ad...Objective:To determine the significance of temperature,rainfall and humidity in the seasonal abundance of Anopheles stephensi in southern Iran.Methods:Data on the monthly abundance of Anopheles stephensi larvae and adults were gathered from earlier studies conducted between 2002 and 2019 in malaria prone areas of southeastern Iran.Climatic data for the studied counties were obtained from climatology stations.Generalized estimating equations method was used for cluster correlation of data for each study site in different years.Results:A significant relationship was found between monthly density of adult and larvae of Anopheles stephensi and precipitation,max temperature and mean temperature,both with simple and multiple generalized estimating equations analysis(P<0.05).But when analysis was done with one month lag,only relationship between monthly density of adults and larvae of Anopheles stephensi and max temperature was significant(P<0.05).Conclusions:This study provides a basis for developing multivariate time series models,which can be used to develop improved appropriate epidemic prediction systems for these areas.Long-term entomological study in the studied sites by expert teams is recommended to compare the abundance of malaria vectors in the different areas and their association with climatic variables.展开更多
The synoptic circulation over Saudi Arabia is complicated and frequently governed by the effect of large-scale pressure systems. In this work, we used NCEP–NCAR global data to illustrate the relationship between clim...The synoptic circulation over Saudi Arabia is complicated and frequently governed by the effect of large-scale pressure systems. In this work, we used NCEP–NCAR global data to illustrate the relationship between climatic variables and the main pressure systems that affect the weather and climate of Saudi Arabia, and also to investigate the influence of these pressure systems on surface air temperature（SAT） and rainfall over the region in the winter season. It was found that there are two primary patterns of pressure that influence the weather and climate of Saudi Arabia. The first occurs in cases of a strengthening Subtropical High（Sub H）, a weakening Siberian High（Sib H）, a deepening of the Icelandic Low（Ice L）, or a weakening of the Sudanese Low（Sud L）. During this pattern, the Sub H combines with the Sib H and an obvious increase of sea level pressure（SLP） occurs over southern European, the Mediterranean, North Africa, and the Middle East. This belt of high pressure prevents interaction between midlatitude and extratropical systems, which leads to a decrease in the SAT,relative humidity（RH） and rainfall over Saudi Arabia. The second pattern occurs in association with a weakening of the Sub H, a strengthening of the Sib H, a weakening of the Ice L, or a deepening of the Sud L. The pattern arising in this case leads to an interaction between two different air masses： the first（cold moist） air mass is associated with the Mediterranean depression travelling from west to east, while the second（warm moist） air mass is associated with the northward oscillation of the Sud L and its inverted V-shape trough. The interaction between these two air masses increases the SAT, RH and the probability of rainfall over Saudi Arabia, especially over the northwest and northeast regions.展开更多
As per the Essential Climate Variables (ESV) of World Meterological Organisation (WMO), the physical, chemical and biological variables critically contribute to the earth’s climate. Among them, the variables such as ...As per the Essential Climate Variables (ESV) of World Meterological Organisation (WMO), the physical, chemical and biological variables critically contribute to the earth’s climate. Among them, the variables such as temperature and pH in the marine environment may affect seriously and in turn it has an impact on the biota, especially in the intertidal environment, where it has brunt force. According to United Nations Framework Convention on Climate Change (UNFCCC), the datasets should provide the empirical evidence needed to predict the climate change and evoluate the mitigation and adaptation measures. Under this context, a review was carried out to know what extent marine scientists understand this factor and what level the biodiversity was evoluated and its impact was analysed in this article. Based on the existing literature review, it was understood that only a few groups that also only few species from these groups were studied in this aspect. The remaining groups and their species and their basic trophic were not evolved in this aspect. So, the marine scientific community, environmentalist and policy makers should take stock on this aspect and give thrust on this study.展开更多
In recent years,the water level in the Mekong Delta(MD)has undergone changes,attributed to the impacts of anthropogenic activities and climate change.Declining water levels have had implications for various aspects of...In recent years,the water level in the Mekong Delta(MD)has undergone changes,attributed to the impacts of anthropogenic activities and climate change.Declining water levels have had implications for various aspects of life and aquatic ecosystems in the lower basin water bodies.Analyzing long-term trends in rainfall and water levels is crucial for enhancing our understanding.This study aims to examine the evolving patterns of water level and rainfall in the region.Data on water levels and rainfall from observation stations were gathered from the National Center for Hydrometeorological Forecasting,Vietnam,spanning from 2000 to 2014.The assessment of homogeneity and identification of trend changes were conducted using the Standard Normal Homogeneity Test(SNHT)and the Mann-Kendall test.The results indicate that changes in water levels at the Tan Chau and Chau Doc stations have been observed since 2010 due to the operation of flow-regulating structures in the upper Mekong River.Following the commencement of upstream dam operations,the water level at the headwater stations of the Mekong River has been higher than the long-term average during the dry season and lower than the average during the flood season.The study findings highlight the influence of altered rainfall patterns under the impact of climate variability(ICC)on water level trends in the study area.While rainfall plays a significant role in increasing water levels during the flood season,the operation of hydropower dams(UHDs)stands out as the primary factor driving water level reductions in the study area.展开更多
Plants play an essential role in matter and energy transformations and are key messengers in the carbon and energy cycle. Net primary productivity (NPP) reflects the capability of plants to transform solar energy into...Plants play an essential role in matter and energy transformations and are key messengers in the carbon and energy cycle. Net primary productivity (NPP) reflects the capability of plants to transform solar energy into photosynthesis. It is very sensible for factors affecting on vegetation variability such as climate, soils, plant characteristics and human activities. So, it can be used as an indicator of actual and potential trend of vegetation. In this study we used the actual NPP which was derived from MODIS to assess the response of NPP to climate variables in Gadarif State, from 2000 to 2010. The correlations between NPP and climate variables (temperature and precipitation) are calculated using Pearson’s Correlation Coefficient and ordinary least squares regression. The main results show the following 1) the correlation Coefficient between NPP and mean annual temperature is Somewhat negative for Feshaga, Rahd, Gadarif and Galabat areas and weakly negative in Faw area;2) the correlation Coefficient between NPP and annual total precipitation is weakly negative in Faw, Rahd and Galabat areas and somewhat negative in Galabat and Rahd areas. This study demonstrated that the correlation analysis between NPP and climate variables (precipitation and temperature) gives reliably result of NPP responses to climate variables that is clearly in a very large scale of study area.展开更多
Understanding the genetic diversity–area relationship(GAR)is essential for comprehending how species adapt to environmental changes,as genetic diversity is an indicator of a species’adaptive potential.Variation in e...Understanding the genetic diversity–area relationship(GAR)is essential for comprehending how species adapt to environmental changes,as genetic diversity is an indicator of a species’adaptive potential.Variation in environmental adaptation capacity exists among species and animal taxa with different distribution areas,highlighting the importance of understanding the GAR.To obtain a more comprehensive understanding of the GAR in terrestrial vertebrates,we assessed both haplotype diversity–area and nucleotide diversity–area relationships using 25,453 cytochrome c oxidase subunit I(COI)sequences from 142 amphibian species,574 bird species,and 342 mammal species.We found that both measures of genetic diversity increased with species range size across major animal groups.Nevertheless,the GAR did not differ among animal groups,while haplotype diversity performed better than nucleotide diversity in profiling the GAR,as indicated by higher R2 values.The difference in the modeling fit may stem from the distinct biological and mathematical significance of nucleotide diversity and haplotype diversity.These results suggest that the GAR follows similar rules among different animal taxa.Furthermore,haplotype diversity may serve as a more reliable indicator for assessing the potential effects of area size changes on animal populations and provide better guidance for conserving genetic diversity.展开更多
Abstract： Estimation of evapotranspiration （ET） for mountain ecosystem is of absolute importance since it serves as an important component in balancing the hydrologic cycle. The present study evaluates the performa...Abstract： Estimation of evapotranspiration （ET） for mountain ecosystem is of absolute importance since it serves as an important component in balancing the hydrologic cycle. The present study evaluates the performance of original and location specific calibrated Hargreaves equation （HARG） with the estimates of Food and Agricultural Organization （FAO） Penman Monteith （PM） method for higher altitudes in East Sikkim, India. The results show that the uncalibrated HARG model underestimates ET0 by 0.35 mm day^-1 whereas the results are significantly improved by regional calibration of the model. In addition, this paper also presents the variability in the trajectory associated with the climatic variables with the changing climate in the study site. Non- parametric Mann-Kendall （MK） test was used to investigate and understand the mean monthly trend of eight climatic parameters including reference evapotranspiration （ET0） for the period of 1985 - 2009. Trend of ET0 was estimated for the calculations done by FAO PM equation. The outcomes of the trend analysis show significant increasing （p ≤ 0.05） trend represented by higher Z-values, through MK test, for net radiation （Rn）, maximum temperature （Tmax） and minimum temperature （Train）, especially in the first months of the year. Whereas, significant （0.01 ≥ p ≤0.05） decreasing trend in vapor pressure deficit （VPD） and precipitation （P） is observed throughout the year. Declining trend in sunshine duration, VPD and ET0 is found in spring （March - May） and monsoon （June - November） season. The result displays significant （0.01≤ p ≤0.05） decreasing ET0 trend between （June - December） except in July, exhibiting the positive relation with VPD followed by sunshine duration at the station. Overall, the study emphasizes the importance of trend analysis of ET0 and other climatic variables for efficient planning and managing the agricultural practices, in identifying the changes in the meteorological parameters and to accurately assess the hydrologic water balance of the hilly regions.展开更多
This study investigates trends in extreme precipitation events(EPEs)across Antarctica from 1979 to 2023,analyzing changes in EPE frequency,intensity,and the proportion of extreme to total precipitation.Using Self-Orga...This study investigates trends in extreme precipitation events(EPEs)across Antarctica from 1979 to 2023,analyzing changes in EPE frequency,intensity,and the proportion of extreme to total precipitation.Using Self-Organizing Map(SOM)techniques,the study distinguishes the contributions from thermodynamic,dynamic,and interaction components in explaining these trends.Positive EPE occurrence trends are observed across the Bellingshausen and Weddell Seas,Dronning Maud Land,and parts of the Southern Ocean,with declines limited to Queen Mary Land.Thermodynamic factors,responsible for 96.0%of the overall trend,are driven by increased water vapor content in polar air masses.Dynamic contributions,representing 10.8%,are linked to a strengthened Amundsen Sea Low(ASL)associated with the Southern Annular Mode(SAM)and Pacific South American(PSA)trends.Interaction effects make a slightly negative contribution(-6.8%)to the overall trend.Variations in water vapor transport and vertical velocity tied to annual 500-hPa geopotential height anomalies further explain EPE trends.These findings provide insight into the atmospheric processes that influence Antarctic EPEs,with implications for understanding the climatic impact on the polar environment.展开更多
Climate variability significantly impacts agricultural water resources,particularly in regions like Vietnam's Plain of Reeds that heavily utilize rain-fed conditions.This study employs the FAO-AquaCrop model to es...Climate variability significantly impacts agricultural water resources,particularly in regions like Vietnam's Plain of Reeds that heavily utilize rain-fed conditions.This study employs the FAO-AquaCrop model to estimate current and future irrigation water needs for rice cultivation in this critical subregion,aiming to identify optimal sowing schedules(OSS)that enhance rainwater utilization and reduce irrigation dependency.The model was driven by current climate data and future projections(2041-2070 and 2071-2099)derived from downscaled Global Circulation Models under RCP4.5 and RCP8.5 scenarios.The AquaCrop model demonstrated robust performance during validation and calibration,with d-values(0.82-0.93)and R²values(0.85-0.92)indicating strong predictive accuracy for rice yield.Simulation results for efficient irrigation water potential(IWP)under RCP4.5 revealed that strategic shifts in sowing dates can substantially alter water requirements;for instance,advancing the winter-spring sowing to December 5th decreased IWP by 15.6%in the 2041-2070 period,while delaying summer-autumn crop sowing to April 20th increased IWP by 48.6%due to greater reliance on irrigation as rainfall patterns shift.Similar dynamic responses were observed for the 2071-2099 period and for autumn-winter crops.These findings underscore that AquaCrop modeling can effectively predict future irrigation needs and that adjusting cultivation calendars presents a viable,low-cost adaptation strategy.This approach allows farmers in the Plain of Reeds to optimize rainwater use,thereby reducing dependency on supplementary irrigation and mitigating the adverse impacts of climate variability,contributing to more sustainable agricultural water management.展开更多
Malaria remains a major public health challenge necessitating accurate predictive models to inform effective intervention strategies in Sierra Leone. This study compares the performance of Holt-Winters’ Exponential S...Malaria remains a major public health challenge necessitating accurate predictive models to inform effective intervention strategies in Sierra Leone. This study compares the performance of Holt-Winters’ Exponential Smoothing, Harmonic, and Artificial Neural Network (ANN) models using data from January 2018 to December 2023, incorporating both historical case records from Sierra Leone’s Health Management Information System (HMIS) and meteorological variables including humidity, precipitation, and temperature. The ANN model demonstrated superior performance, achieving a Mean Absolute Percentage Error (MAPE) of 4.74% before including climatic variables. This was further reduced to 3.9% with the inclusion of climatic variables, outperforming traditional models like Holt-Winters and Harmonic, which yielded MAPEs of 22.53% and 17.90% respectively. The ANN’s success is attributed to its ability to capture complex, non-linear relationships in the data, particularly when enhanced with relevant climatic variables. Using the optimized ANN model, we forecasted malaria cases for the next 24 months, predicting a steady increase from January 2024 to December 2025, with seasonal peaks. This study underscores the potential of machine learning approaches, particularly ANNs, in epidemiological modelling and highlights the importance of integrating environmental factors into malaria prediction models, recommending the ANN model for informing more targeted and efficient malaria control strategies to improve public health outcomes in Sierra Leone and similar settings.展开更多
The weather in Australia is significantly influenced by water vapor evaporated fromwarm ocean surfaces,which is closely associated with various extreme weather events in the region,such as floods,droughts,and bushfire...The weather in Australia is significantly influenced by water vapor evaporated fromwarm ocean surfaces,which is closely associated with various extreme weather events in the region,such as floods,droughts,and bushfires.This study utilizes Precipitable Water Vapor(PWV)data from 15 Global Navigation Satellite System(GNSS)stations spanning 2010 to 2019 to investigate the spatiotemporal distribution of atmospheric water vapor across Australia,aiming to improve the accuracy of forecasting hazardous weather events.The results indicate distinct regional features in the spatial distribution of PWV.PWV gradually decreases from coastal areas toward inland regions and increases from south to north.Temporally,the overall trend of PWV remains consistent.From an annual trend perspective,most areas exhibit a decline in PWV content,with the exception of the southwestern coastal region,which shows an increasing trend.Furthermore,the study explores the correlations between PWV content and elevation,latitude,and longitude.Among these,latitude demonstrates the strongest correlation with PWV,with a correlation coefficient as high as 0.88,highlighting the significant impact of latitude on water vapor distribution.展开更多
Extreme waves may considerably impact crucial coastal and marine engineering structures. The First Scientific Assessment Report on Ocean and Climate Change of China and The Fourth Assessment Report on Climate Change o...Extreme waves may considerably impact crucial coastal and marine engineering structures. The First Scientific Assessment Report on Ocean and Climate Change of China and The Fourth Assessment Report on Climate Change of China were published in 2020 and 2022, respectively.However, no concrete results on the long-term trends in wave changes in China have been obtained. In this study, long-term trends in extreme wave elements over the past 55 years were investigated using wave data from five in situ observation sites(i.e., Lao Hu Tan, Cheng Shan Tou,Ri Zhao, Nan Ji, Wei Zhou) along the coast of China. The five stations showed different trends in wave height. Results show a general downward trend in wave heights at the LHT and CST stations, reaching-0.78 and-1.44 cm/a, respectively, in summer at middle and high latitudes. NJI stations at middle-to-low latitudes are influenced by the winter monsoon and summer tropical cyclones, showing a substantial increase in extreme wave heights(0.7 cm/a in winter and 2.68 cm/a in summer). The cumulative duration of H_(1/10) ≥ 3 m at NJI and RZH has grown since 1990.展开更多
We developed a sophisticated method to depict the spatial and seasonal characterization of net primary productivity (NPP) and climate variables. The role of climate variability in the seasonal variation of NPP exerts ...We developed a sophisticated method to depict the spatial and seasonal characterization of net primary productivity (NPP) and climate variables. The role of climate variability in the seasonal variation of NPP exerts delayed and continuous effects. This study expands on this by mapping the seasonal characterization of NPP and climate variables from space using geographic information system (GIS) technology at the pixel level. Our approach was developed in southeastern China using moderate-resolution imaging spectroradiometer (MODIS) data. The results showed that air temperature,precipitation and sunshine percentage contributed significantly to seasonal variation of NPP. In the northern portion of the study area,a significant positive 32-d lagged correlation was observed between seasonal variation of NPP and climate (P<0.01),and the influences of changing climate on NPP lasted for 48 d or 64 d. In central southeastern China,NPP showed 16-d,48-d,and 96-d lagged correlation with air temperature,precipitation,and sunshine percentage,respectively (P<0.01); the influences of air temperature and precipitation on NPP lasted for 48 d or 64 d,while sunshine influence on NPP only persisted for 16 d. Due to complex topography and vegetation distribution in the southern part of the study region,the spatial patterns of vegetation-climate relationship became complicated and diversiform,especially for precipitation influences on NPP. In the northern part of the study area,all vegetation NPP had an almost similar response to seasonal variation of air temperature except for broad crops. The impacts of seasonal variation of precipitation and sunshine on broad and cereal crop NPP were slightly different from other vegetation NPP.展开更多
Soil organic carbon (SOC) plays an important role in global carbon cycles.Large spatial variations in SOC contents result in uncertain estimates of the SOC pool and its changes.In the present study,the key variables e...Soil organic carbon (SOC) plays an important role in global carbon cycles.Large spatial variations in SOC contents result in uncertain estimates of the SOC pool and its changes.In the present study,the key variables explaining the SOC contents of croplands (CPs) and non-croplands (NCPs) in Chinese provinces were investigated.Data on SOC and other soil properties (obtained from the Second National Soil Survey conducted in the late 1970s to the early 1990s),climate parameters,as well as the proportion of the CP to the total land area (Pcp) were used.SOC content variations within a province were larger than those among provinces.Soil clay and total phosphorus content,ratio of annual precipitation to mean temperature,as well as Pcp were able to explain 75% of the SOC content variations in whole soil samples.Soil pH,mean temperature during the growing season from May to October,and mean annual wind velocity were able to explain 63% of the SOC content variations in NCP soils.Compared with NCP soils,CP soils had lower SOC contents,with smaller variations within and among provinces and lower C/N ratios.Stepwise regression showed that the soil clay content was a unique factor significantly correlated with the SOC content of CP soils.However,this factor only explained 24% of the variations.This result suggested that variables related to human activities had greater effects on SOC content variations in CP soils than soil properties and climate parameters.Based on SOC contents directly averaged from soil samples and estimated by regression equations,the total SOC pool in the topsoil (0-20 cm) of China was estimated at 60.02 Pg and 57.6 Pg.Thousands of years of intensive cultivation in China resulted in CP topsoil SOC loss of 4.34-4.98 Pg.展开更多
The relationships between climate conditions and wood density in tropical forests are still poorly understood.To quantify spatial dependence of wood density in the state of Minas Gerais(MG,Brazil),map spatial distribu...The relationships between climate conditions and wood density in tropical forests are still poorly understood.To quantify spatial dependence of wood density in the state of Minas Gerais(MG,Brazil),map spatial distribution of density,and correlate density with climate variables,we extracted data from the Forest Inventory of Minas Gerais for 1988 trees scaled throughout the territory and measured wood density of discs removed from the trees.Environmental variables were extracted from the database of the Ecological-Economic Zoning of Minas Gerais.For spatial analysis,tree densities were measured at 44 georeferenced sampling points.The data were subjected to exploratory analysis,variography,cross-validation,model selection,and ordinary kriging.The relationships between wood density and environmental variables were calculated using dispersion matrices,linear correlation,and regression.Wood density proved to be highly spatially dependent,reaching a correlation of 96%,and was highly continuous over a distance of 228 km.The distribution of wood density followed a continuous gradient of 514-659 kg m^(−3),enabling corre-lation with environment variables.Density was correlated with mean annual precipitation(−0.57),temperature(0.63),and evapotranspiration(0.83).Geostatistical methods proved useful in predicting wood density in native tropical forests with different climate conditions.Our results confirmed the sensitivity of wood density to climate change,which could affect future carbon stock in forests.展开更多
Ommastrephes bartramii is an ecologically dependent species and has great commercial values among the AsiaPacific countries. This squid widely inhabits the North Pacific, one of the most dynamic marine environments in...Ommastrephes bartramii is an ecologically dependent species and has great commercial values among the AsiaPacific countries. This squid widely inhabits the North Pacific, one of the most dynamic marine environments in the world, subjecting to multi-scale climatic events such as the Pacific Decadal Oscillation（PDO）. Commercial fishery data from the Chinese squid-jigging fleets during 1995-2011 are used to evaluate the influences of climatic and oceanic environmental variations on the spatial distribution of O. bartramii. Significant interannual and seasonal variability are observed in the longitudinal and latitudinal gravity centers（LONG and LATG） of fishing ground of O. bartramii. The LATG mainly occurred in the waters with the suitable ranges of environmental variables estimated by the generalized additive model. The apparent north-south spatial shift in the annual LATG appeares to be associated with the PDO phenomenon and is closely related to the sea surface temperature（SST）and sea surface height（SSH） on the fishing ground, whereas the mixed layer depth（MLD） might contribute limited impacts to the distribution pattern of O. bartramii. The warm PDO regimes tend to yield cold SST and low SSH, resulting in a southward shift of LATG, while the cold PDO phases provid warm SST and elevated SSH,resulting in a northward shift of LATG. A regression model is developed to help understand and predict the fishing ground distributions of O. bartramii and improve the fishery management.展开更多
The method linking general circulation models' (GCMs') outputs with crop growthsimulation models' inputs has been the first choice in the studies of impacts of climate change.Changes in climatic variabilit...The method linking general circulation models' (GCMs') outputs with crop growthsimulation models' inputs has been the first choice in the studies of impacts of climate change.Changes in climatic variability, however were not considered in most studies due to limitedknowledge concerned Changes in climatic means derived from a general circulation model DKRZOPYC were input into a stochastic weather generator WGEN run for synthetic daily climate scenarios.Monte Carlo stochastic sampling method was adopted to generate climate change scenarios withvarious possible climatic veriabilities. A dynamic simulation model for maize growth anddevelopment of MZMOD was used to assess the potenhal implication of the changes in both climaticmeans and variability nd the boacts of crop management in changing climate on maize productionin Northeast China. The results indicated that maize yield would be reduced to various degrees inmost of the sensitivity experiments of climatic variability associating with the shortening of theduration of phenological phase of different sowing dates. The Anpacts of the diverse distributions ofclimatic factors detetmined by multiple changes in climatic variability on maire production and itsvariation, however, are not identical and have distinct regional disparities. Yield reduction caused bychanges in climatic means may be alleviated or aggravated by didributions of certain climaticvariables in line with the corresponding climatic variability according to the sensitivity analyses.Consequently, the hypothesis keeping climatic variability constant in the traditional research imposesrestriction on the overall inveshgation of the impacts of climate change on maize production.展开更多
In the past few decades,meteorological datasets from remote sensing techniques in agricultural and water resources management have been used by various researchers and managers.Based on the literature,meteorological d...In the past few decades,meteorological datasets from remote sensing techniques in agricultural and water resources management have been used by various researchers and managers.Based on the literature,meteorological datasets are not more accurate than synoptic stations,but their various advantages,such as spatial coverage,time coverage,accessibility,and free use,have made these techniques superior,and sometimes we can use them instead of synoptic stations.In this study,we used four meteorological datasets,including Climatic Research Unit gridded Time Series(CRU TS),Global Precipitation Climatology Centre(GPCC),Agricultural National Aeronautics and Space Administration Modern-Era Retrospective Analysis for Research and Applications(AgMERRA),Agricultural Climate Forecast System Reanalysis(AgCFSR),to estimate climate variables,i.e.,precipitation,maximum temperature,and minimum temperature,and crop variables,i.e.,reference evapotranspiration,irrigation requirement,biomass,and yield of maize,in Qazvin Province of Iran during 1980-2009.At first,data were gathered from the four meteorological datasets and synoptic station in this province,and climate variables were calculated.Then,after using the AquaCrop model to calculate the crop variables,we compared the results of the synoptic station and meteorological datasets.All the four meteorological datasets showed strong performance for estimating climate variables.AgMERRA and AgCFSR had more accurate estimations for precipitation and maximum temperature.However,their normalized root mean square error was inferior to CRU for minimum temperature.Furthermore,they were all very efficient for estimating the biomass and yield of maize in this province.For reference evapotranspiration and irrigation requirement CRU TS and GPCC were the most efficient rather than AgMERRA and AgCFSR.But for the estimation of biomass and yield,all the four meteorological datasets were reliable.To sum up,GPCC and AgCFSR were the two best datasets in this study.This study suggests the use of meteorological datasets in water resource management and agricultural management to monitor past changes and estimate recent trends.展开更多
A weather station is proposed especially designed for developing countries, and to meet the standards of the international scientific community making research on the earth system. The station would measure in situ se...A weather station is proposed especially designed for developing countries, and to meet the standards of the international scientific community making research on the earth system. The station would measure in situ several ECV （essential climate variables）. These data may enable an agricultural breakthrough in countries lacking meteorological infrastructure, help in climate change monitoring, and facilitate diffusion of wind energy. A pre-feasibility analysis is presented. It appears interesting that the station is supplied by a social enterprise. A research to establish the best shelter design using computational fluid dynamics is also reported. The criterion is the accuracy with which the surface air temperature is reproduced inside the shelter. A design following recommendations by the WMO （World Meteorological Organization）, a smaller design with identical geometry, and two alternative small designs are analyzed. All four designs are simulated in PVC, natural rubber and wood, with and without white paint coating. The smaller shelters perform better. The influence of the material, dimensions and design is smaller than that of the white paint. Shelters made of PVC or rubber, and/or in alternative designs, may be more interesting if other criteria are considered, like whether logistics, manufacturing, etc. are more sustainable, easier and/or cheaper.展开更多
Climate changes are affecting water resources around the world and the Mo Basin (MB) in Togo is no exception to this observation. This study aims at analyzing the influence of hydro-climatical data in the Mo Basin. To...Climate changes are affecting water resources around the world and the Mo Basin (MB) in Togo is no exception to this observation. This study aims at analyzing the influence of hydro-climatical data in the Mo Basin. To achieve this, Pettit’s stationarity break tests, Hubert’s segmentation, Nicholson’s [1] reduced centered index, Lamb [2] and flow coefficients have been applied. In addition, temperature, precipitation, evapotranspiration, relative humidity and discharge data from 1961 to 2018 have been used for this purpose. While rainfall is decreasing despite an increase of 22.8% at the Fazao station and 2.8% at Sotouboua station, the flow coefficients evolve synchronously with the precipitation data and show a strong link between both parameters. The climatic balance sheet is positive six months in the year (May to October), throughout the period of observation (1961-2018). Only 1962 and 1963 recorded an annual rainfall greater than the annual evapotranspiration. The other years undergo a climatic drought, increasingly pronounced, which strongly impacts the hydrology of rivers. This has a strong impact on water resources and food security and resources of the Fazao-Malfakassa reserve in the region.展开更多
基金financially supported by Research Deputy,Tehran University of Medical Sciences,Project No.29953
文摘Objective:To determine the significance of temperature,rainfall and humidity in the seasonal abundance of Anopheles stephensi in southern Iran.Methods:Data on the monthly abundance of Anopheles stephensi larvae and adults were gathered from earlier studies conducted between 2002 and 2019 in malaria prone areas of southeastern Iran.Climatic data for the studied counties were obtained from climatology stations.Generalized estimating equations method was used for cluster correlation of data for each study site in different years.Results:A significant relationship was found between monthly density of adult and larvae of Anopheles stephensi and precipitation,max temperature and mean temperature,both with simple and multiple generalized estimating equations analysis(P<0.05).But when analysis was done with one month lag,only relationship between monthly density of adults and larvae of Anopheles stephensi and max temperature was significant(P<0.05).Conclusions:This study provides a basis for developing multivariate time series models,which can be used to develop improved appropriate epidemic prediction systems for these areas.Long-term entomological study in the studied sites by expert teams is recommended to compare the abundance of malaria vectors in the different areas and their association with climatic variables.
基金funded by the Deanship of Scientific Research (DSR), King Abdulaziz University, Jeddah (Grant No. 155-003-D1433)the DSR for their technical and financial support
文摘The synoptic circulation over Saudi Arabia is complicated and frequently governed by the effect of large-scale pressure systems. In this work, we used NCEP–NCAR global data to illustrate the relationship between climatic variables and the main pressure systems that affect the weather and climate of Saudi Arabia, and also to investigate the influence of these pressure systems on surface air temperature（SAT） and rainfall over the region in the winter season. It was found that there are two primary patterns of pressure that influence the weather and climate of Saudi Arabia. The first occurs in cases of a strengthening Subtropical High（Sub H）, a weakening Siberian High（Sib H）, a deepening of the Icelandic Low（Ice L）, or a weakening of the Sudanese Low（Sud L）. During this pattern, the Sub H combines with the Sib H and an obvious increase of sea level pressure（SLP） occurs over southern European, the Mediterranean, North Africa, and the Middle East. This belt of high pressure prevents interaction between midlatitude and extratropical systems, which leads to a decrease in the SAT,relative humidity（RH） and rainfall over Saudi Arabia. The second pattern occurs in association with a weakening of the Sub H, a strengthening of the Sib H, a weakening of the Ice L, or a deepening of the Sud L. The pattern arising in this case leads to an interaction between two different air masses： the first（cold moist） air mass is associated with the Mediterranean depression travelling from west to east, while the second（warm moist） air mass is associated with the northward oscillation of the Sud L and its inverted V-shape trough. The interaction between these two air masses increases the SAT, RH and the probability of rainfall over Saudi Arabia, especially over the northwest and northeast regions.
文摘As per the Essential Climate Variables (ESV) of World Meterological Organisation (WMO), the physical, chemical and biological variables critically contribute to the earth’s climate. Among them, the variables such as temperature and pH in the marine environment may affect seriously and in turn it has an impact on the biota, especially in the intertidal environment, where it has brunt force. According to United Nations Framework Convention on Climate Change (UNFCCC), the datasets should provide the empirical evidence needed to predict the climate change and evoluate the mitigation and adaptation measures. Under this context, a review was carried out to know what extent marine scientists understand this factor and what level the biodiversity was evoluated and its impact was analysed in this article. Based on the existing literature review, it was understood that only a few groups that also only few species from these groups were studied in this aspect. The remaining groups and their species and their basic trophic were not evolved in this aspect. So, the marine scientific community, environmentalist and policy makers should take stock on this aspect and give thrust on this study.
基金funded by the University of Science,VNU-HCM under grant number T2022-10 project entitled“Water level variability in the Mekong Delta under the impacts of anthropogenic and climatic factors”.
文摘In recent years,the water level in the Mekong Delta(MD)has undergone changes,attributed to the impacts of anthropogenic activities and climate change.Declining water levels have had implications for various aspects of life and aquatic ecosystems in the lower basin water bodies.Analyzing long-term trends in rainfall and water levels is crucial for enhancing our understanding.This study aims to examine the evolving patterns of water level and rainfall in the region.Data on water levels and rainfall from observation stations were gathered from the National Center for Hydrometeorological Forecasting,Vietnam,spanning from 2000 to 2014.The assessment of homogeneity and identification of trend changes were conducted using the Standard Normal Homogeneity Test(SNHT)and the Mann-Kendall test.The results indicate that changes in water levels at the Tan Chau and Chau Doc stations have been observed since 2010 due to the operation of flow-regulating structures in the upper Mekong River.Following the commencement of upstream dam operations,the water level at the headwater stations of the Mekong River has been higher than the long-term average during the dry season and lower than the average during the flood season.The study findings highlight the influence of altered rainfall patterns under the impact of climate variability(ICC)on water level trends in the study area.While rainfall plays a significant role in increasing water levels during the flood season,the operation of hydropower dams(UHDs)stands out as the primary factor driving water level reductions in the study area.
文摘Plants play an essential role in matter and energy transformations and are key messengers in the carbon and energy cycle. Net primary productivity (NPP) reflects the capability of plants to transform solar energy into photosynthesis. It is very sensible for factors affecting on vegetation variability such as climate, soils, plant characteristics and human activities. So, it can be used as an indicator of actual and potential trend of vegetation. In this study we used the actual NPP which was derived from MODIS to assess the response of NPP to climate variables in Gadarif State, from 2000 to 2010. The correlations between NPP and climate variables (temperature and precipitation) are calculated using Pearson’s Correlation Coefficient and ordinary least squares regression. The main results show the following 1) the correlation Coefficient between NPP and mean annual temperature is Somewhat negative for Feshaga, Rahd, Gadarif and Galabat areas and weakly negative in Faw area;2) the correlation Coefficient between NPP and annual total precipitation is weakly negative in Faw, Rahd and Galabat areas and somewhat negative in Galabat and Rahd areas. This study demonstrated that the correlation analysis between NPP and climate variables (precipitation and temperature) gives reliably result of NPP responses to climate variables that is clearly in a very large scale of study area.
基金supported by the National Natural Science Foundation of China(32130013,32070434)the National Key Research and Development Program of China(2022YFC2601601)+1 种基金the Second Tibetan Plateau Scientific Expedition and Research(STEP)program(2019QZKK05010112,2019QZKK0304-02)Hainan Tropical Rainforest Conservation Research Project,ZDYF2023RDYL01(supported by the Hainan Institute of National Park,HINP,KY-24ZK02).
文摘Understanding the genetic diversity–area relationship(GAR)is essential for comprehending how species adapt to environmental changes,as genetic diversity is an indicator of a species’adaptive potential.Variation in environmental adaptation capacity exists among species and animal taxa with different distribution areas,highlighting the importance of understanding the GAR.To obtain a more comprehensive understanding of the GAR in terrestrial vertebrates,we assessed both haplotype diversity–area and nucleotide diversity–area relationships using 25,453 cytochrome c oxidase subunit I(COI)sequences from 142 amphibian species,574 bird species,and 342 mammal species.We found that both measures of genetic diversity increased with species range size across major animal groups.Nevertheless,the GAR did not differ among animal groups,while haplotype diversity performed better than nucleotide diversity in profiling the GAR,as indicated by higher R2 values.The difference in the modeling fit may stem from the distinct biological and mathematical significance of nucleotide diversity and haplotype diversity.These results suggest that the GAR follows similar rules among different animal taxa.Furthermore,haplotype diversity may serve as a more reliable indicator for assessing the potential effects of area size changes on animal populations and provide better guidance for conserving genetic diversity.
文摘Abstract： Estimation of evapotranspiration （ET） for mountain ecosystem is of absolute importance since it serves as an important component in balancing the hydrologic cycle. The present study evaluates the performance of original and location specific calibrated Hargreaves equation （HARG） with the estimates of Food and Agricultural Organization （FAO） Penman Monteith （PM） method for higher altitudes in East Sikkim, India. The results show that the uncalibrated HARG model underestimates ET0 by 0.35 mm day^-1 whereas the results are significantly improved by regional calibration of the model. In addition, this paper also presents the variability in the trajectory associated with the climatic variables with the changing climate in the study site. Non- parametric Mann-Kendall （MK） test was used to investigate and understand the mean monthly trend of eight climatic parameters including reference evapotranspiration （ET0） for the period of 1985 - 2009. Trend of ET0 was estimated for the calculations done by FAO PM equation. The outcomes of the trend analysis show significant increasing （p ≤ 0.05） trend represented by higher Z-values, through MK test, for net radiation （Rn）, maximum temperature （Tmax） and minimum temperature （Train）, especially in the first months of the year. Whereas, significant （0.01 ≥ p ≤0.05） decreasing trend in vapor pressure deficit （VPD） and precipitation （P） is observed throughout the year. Declining trend in sunshine duration, VPD and ET0 is found in spring （March - May） and monsoon （June - November） season. The result displays significant （0.01≤ p ≤0.05） decreasing ET0 trend between （June - December） except in July, exhibiting the positive relation with VPD followed by sunshine duration at the station. Overall, the study emphasizes the importance of trend analysis of ET0 and other climatic variables for efficient planning and managing the agricultural practices, in identifying the changes in the meteorological parameters and to accurately assess the hydrologic water balance of the hilly regions.
基金supported by the National Key R&D Program of China(2022YFE0106300)Norges Forskningsråd(328886).
文摘This study investigates trends in extreme precipitation events(EPEs)across Antarctica from 1979 to 2023,analyzing changes in EPE frequency,intensity,and the proportion of extreme to total precipitation.Using Self-Organizing Map(SOM)techniques,the study distinguishes the contributions from thermodynamic,dynamic,and interaction components in explaining these trends.Positive EPE occurrence trends are observed across the Bellingshausen and Weddell Seas,Dronning Maud Land,and parts of the Southern Ocean,with declines limited to Queen Mary Land.Thermodynamic factors,responsible for 96.0%of the overall trend,are driven by increased water vapor content in polar air masses.Dynamic contributions,representing 10.8%,are linked to a strengthened Amundsen Sea Low(ASL)associated with the Southern Annular Mode(SAM)and Pacific South American(PSA)trends.Interaction effects make a slightly negative contribution(-6.8%)to the overall trend.Variations in water vapor transport and vertical velocity tied to annual 500-hPa geopotential height anomalies further explain EPE trends.These findings provide insight into the atmospheric processes that influence Antarctic EPEs,with implications for understanding the climatic impact on the polar environment.
文摘Climate variability significantly impacts agricultural water resources,particularly in regions like Vietnam's Plain of Reeds that heavily utilize rain-fed conditions.This study employs the FAO-AquaCrop model to estimate current and future irrigation water needs for rice cultivation in this critical subregion,aiming to identify optimal sowing schedules(OSS)that enhance rainwater utilization and reduce irrigation dependency.The model was driven by current climate data and future projections(2041-2070 and 2071-2099)derived from downscaled Global Circulation Models under RCP4.5 and RCP8.5 scenarios.The AquaCrop model demonstrated robust performance during validation and calibration,with d-values(0.82-0.93)and R²values(0.85-0.92)indicating strong predictive accuracy for rice yield.Simulation results for efficient irrigation water potential(IWP)under RCP4.5 revealed that strategic shifts in sowing dates can substantially alter water requirements;for instance,advancing the winter-spring sowing to December 5th decreased IWP by 15.6%in the 2041-2070 period,while delaying summer-autumn crop sowing to April 20th increased IWP by 48.6%due to greater reliance on irrigation as rainfall patterns shift.Similar dynamic responses were observed for the 2071-2099 period and for autumn-winter crops.These findings underscore that AquaCrop modeling can effectively predict future irrigation needs and that adjusting cultivation calendars presents a viable,low-cost adaptation strategy.This approach allows farmers in the Plain of Reeds to optimize rainwater use,thereby reducing dependency on supplementary irrigation and mitigating the adverse impacts of climate variability,contributing to more sustainable agricultural water management.
文摘Malaria remains a major public health challenge necessitating accurate predictive models to inform effective intervention strategies in Sierra Leone. This study compares the performance of Holt-Winters’ Exponential Smoothing, Harmonic, and Artificial Neural Network (ANN) models using data from January 2018 to December 2023, incorporating both historical case records from Sierra Leone’s Health Management Information System (HMIS) and meteorological variables including humidity, precipitation, and temperature. The ANN model demonstrated superior performance, achieving a Mean Absolute Percentage Error (MAPE) of 4.74% before including climatic variables. This was further reduced to 3.9% with the inclusion of climatic variables, outperforming traditional models like Holt-Winters and Harmonic, which yielded MAPEs of 22.53% and 17.90% respectively. The ANN’s success is attributed to its ability to capture complex, non-linear relationships in the data, particularly when enhanced with relevant climatic variables. Using the optimized ANN model, we forecasted malaria cases for the next 24 months, predicting a steady increase from January 2024 to December 2025, with seasonal peaks. This study underscores the potential of machine learning approaches, particularly ANNs, in epidemiological modelling and highlights the importance of integrating environmental factors into malaria prediction models, recommending the ANN model for informing more targeted and efficient malaria control strategies to improve public health outcomes in Sierra Leone and similar settings.
基金funded by Jiangsu Province Geological Engineering Environment Intelligent Monitoring Engineering Research Center Open Fund,grant number 2023-ZNJKJJ-08The National Natural Science Foundation of China,grant number 41674036.
文摘The weather in Australia is significantly influenced by water vapor evaporated fromwarm ocean surfaces,which is closely associated with various extreme weather events in the region,such as floods,droughts,and bushfires.This study utilizes Precipitable Water Vapor(PWV)data from 15 Global Navigation Satellite System(GNSS)stations spanning 2010 to 2019 to investigate the spatiotemporal distribution of atmospheric water vapor across Australia,aiming to improve the accuracy of forecasting hazardous weather events.The results indicate distinct regional features in the spatial distribution of PWV.PWV gradually decreases from coastal areas toward inland regions and increases from south to north.Temporally,the overall trend of PWV remains consistent.From an annual trend perspective,most areas exhibit a decline in PWV content,with the exception of the southwestern coastal region,which shows an increasing trend.Furthermore,the study explores the correlations between PWV content and elevation,latitude,and longitude.Among these,latitude demonstrates the strongest correlation with PWV,with a correlation coefficient as high as 0.88,highlighting the significant impact of latitude on water vapor distribution.
基金Supported by the National Natural Science Foundation of China (No. 52271271)National Key Research and Development Program of China (No. 2022YFE0104500)Major Science and Technology Projects of the Ministry of Water Resources (No. SKS-2022025)。
文摘Extreme waves may considerably impact crucial coastal and marine engineering structures. The First Scientific Assessment Report on Ocean and Climate Change of China and The Fourth Assessment Report on Climate Change of China were published in 2020 and 2022, respectively.However, no concrete results on the long-term trends in wave changes in China have been obtained. In this study, long-term trends in extreme wave elements over the past 55 years were investigated using wave data from five in situ observation sites(i.e., Lao Hu Tan, Cheng Shan Tou,Ri Zhao, Nan Ji, Wei Zhou) along the coast of China. The five stations showed different trends in wave height. Results show a general downward trend in wave heights at the LHT and CST stations, reaching-0.78 and-1.44 cm/a, respectively, in summer at middle and high latitudes. NJI stations at middle-to-low latitudes are influenced by the winter monsoon and summer tropical cyclones, showing a substantial increase in extreme wave heights(0.7 cm/a in winter and 2.68 cm/a in summer). The cumulative duration of H_(1/10) ≥ 3 m at NJI and RZH has grown since 1990.
基金Project supported by the National High-Tech Research and Development Program (863) of China (No. 2006AA120101)the National Natural Science Foundation of China (Nos. 40871158 and 40875070)the Key Technologies Research and Development Program of China (No. 2006BAD10A01)
文摘We developed a sophisticated method to depict the spatial and seasonal characterization of net primary productivity (NPP) and climate variables. The role of climate variability in the seasonal variation of NPP exerts delayed and continuous effects. This study expands on this by mapping the seasonal characterization of NPP and climate variables from space using geographic information system (GIS) technology at the pixel level. Our approach was developed in southeastern China using moderate-resolution imaging spectroradiometer (MODIS) data. The results showed that air temperature,precipitation and sunshine percentage contributed significantly to seasonal variation of NPP. In the northern portion of the study area,a significant positive 32-d lagged correlation was observed between seasonal variation of NPP and climate (P<0.01),and the influences of changing climate on NPP lasted for 48 d or 64 d. In central southeastern China,NPP showed 16-d,48-d,and 96-d lagged correlation with air temperature,precipitation,and sunshine percentage,respectively (P<0.01); the influences of air temperature and precipitation on NPP lasted for 48 d or 64 d,while sunshine influence on NPP only persisted for 16 d. Due to complex topography and vegetation distribution in the southern part of the study region,the spatial patterns of vegetation-climate relationship became complicated and diversiform,especially for precipitation influences on NPP. In the northern part of the study area,all vegetation NPP had an almost similar response to seasonal variation of air temperature except for broad crops. The impacts of seasonal variation of precipitation and sunshine on broad and cereal crop NPP were slightly different from other vegetation NPP.
基金Under the auspices of National Social Science Foundation of China(No.09CJL026)Talentgaining Program of Hubei Normal University(No.2008F19)+1 种基金National Natural Science Foundation of China(No.40621001)CAS Research Program on Soil Biosystems and Agro-Product Safety(No.CXTD-Z2005-4)
文摘Soil organic carbon (SOC) plays an important role in global carbon cycles.Large spatial variations in SOC contents result in uncertain estimates of the SOC pool and its changes.In the present study,the key variables explaining the SOC contents of croplands (CPs) and non-croplands (NCPs) in Chinese provinces were investigated.Data on SOC and other soil properties (obtained from the Second National Soil Survey conducted in the late 1970s to the early 1990s),climate parameters,as well as the proportion of the CP to the total land area (Pcp) were used.SOC content variations within a province were larger than those among provinces.Soil clay and total phosphorus content,ratio of annual precipitation to mean temperature,as well as Pcp were able to explain 75% of the SOC content variations in whole soil samples.Soil pH,mean temperature during the growing season from May to October,and mean annual wind velocity were able to explain 63% of the SOC content variations in NCP soils.Compared with NCP soils,CP soils had lower SOC contents,with smaller variations within and among provinces and lower C/N ratios.Stepwise regression showed that the soil clay content was a unique factor significantly correlated with the SOC content of CP soils.However,this factor only explained 24% of the variations.This result suggested that variables related to human activities had greater effects on SOC content variations in CP soils than soil properties and climate parameters.Based on SOC contents directly averaged from soil samples and estimated by regression equations,the total SOC pool in the topsoil (0-20 cm) of China was estimated at 60.02 Pg and 57.6 Pg.Thousands of years of intensive cultivation in China resulted in CP topsoil SOC loss of 4.34-4.98 Pg.
文摘The relationships between climate conditions and wood density in tropical forests are still poorly understood.To quantify spatial dependence of wood density in the state of Minas Gerais(MG,Brazil),map spatial distribution of density,and correlate density with climate variables,we extracted data from the Forest Inventory of Minas Gerais for 1988 trees scaled throughout the territory and measured wood density of discs removed from the trees.Environmental variables were extracted from the database of the Ecological-Economic Zoning of Minas Gerais.For spatial analysis,tree densities were measured at 44 georeferenced sampling points.The data were subjected to exploratory analysis,variography,cross-validation,model selection,and ordinary kriging.The relationships between wood density and environmental variables were calculated using dispersion matrices,linear correlation,and regression.Wood density proved to be highly spatially dependent,reaching a correlation of 96%,and was highly continuous over a distance of 228 km.The distribution of wood density followed a continuous gradient of 514-659 kg m^(−3),enabling corre-lation with environment variables.Density was correlated with mean annual precipitation(−0.57),temperature(0.63),and evapotranspiration(0.83).Geostatistical methods proved useful in predicting wood density in native tropical forests with different climate conditions.Our results confirmed the sensitivity of wood density to climate change,which could affect future carbon stock in forests.
基金The National High-Tech R&D Program(863 Program)of China under contract No.2012AA092303the Project of Public Science and Technology Research Funds Projects of Ocean under contract No.20155014+3 种基金the National Key Technologies R&D Program of China under contract No.2013BAD13B00the Shanghai Universities First-Class Disciplines Project(Fisheries)the Funding Program for Outstanding Dissertations in Shanghai Ocean Universitythe Shanghai Ocean University International Center for Marine Studies
文摘Ommastrephes bartramii is an ecologically dependent species and has great commercial values among the AsiaPacific countries. This squid widely inhabits the North Pacific, one of the most dynamic marine environments in the world, subjecting to multi-scale climatic events such as the Pacific Decadal Oscillation（PDO）. Commercial fishery data from the Chinese squid-jigging fleets during 1995-2011 are used to evaluate the influences of climatic and oceanic environmental variations on the spatial distribution of O. bartramii. Significant interannual and seasonal variability are observed in the longitudinal and latitudinal gravity centers（LONG and LATG） of fishing ground of O. bartramii. The LATG mainly occurred in the waters with the suitable ranges of environmental variables estimated by the generalized additive model. The apparent north-south spatial shift in the annual LATG appeares to be associated with the PDO phenomenon and is closely related to the sea surface temperature（SST）and sea surface height（SSH） on the fishing ground, whereas the mixed layer depth（MLD） might contribute limited impacts to the distribution pattern of O. bartramii. The warm PDO regimes tend to yield cold SST and low SSH, resulting in a southward shift of LATG, while the cold PDO phases provid warm SST and elevated SSH,resulting in a northward shift of LATG. A regression model is developed to help understand and predict the fishing ground distributions of O. bartramii and improve the fishery management.
文摘The method linking general circulation models' (GCMs') outputs with crop growthsimulation models' inputs has been the first choice in the studies of impacts of climate change.Changes in climatic variability, however were not considered in most studies due to limitedknowledge concerned Changes in climatic means derived from a general circulation model DKRZOPYC were input into a stochastic weather generator WGEN run for synthetic daily climate scenarios.Monte Carlo stochastic sampling method was adopted to generate climate change scenarios withvarious possible climatic veriabilities. A dynamic simulation model for maize growth anddevelopment of MZMOD was used to assess the potenhal implication of the changes in both climaticmeans and variability nd the boacts of crop management in changing climate on maize productionin Northeast China. The results indicated that maize yield would be reduced to various degrees inmost of the sensitivity experiments of climatic variability associating with the shortening of theduration of phenological phase of different sowing dates. The Anpacts of the diverse distributions ofclimatic factors detetmined by multiple changes in climatic variability on maire production and itsvariation, however, are not identical and have distinct regional disparities. Yield reduction caused bychanges in climatic means may be alleviated or aggravated by didributions of certain climaticvariables in line with the corresponding climatic variability according to the sensitivity analyses.Consequently, the hypothesis keeping climatic variability constant in the traditional research imposesrestriction on the overall inveshgation of the impacts of climate change on maize production.
文摘In the past few decades,meteorological datasets from remote sensing techniques in agricultural and water resources management have been used by various researchers and managers.Based on the literature,meteorological datasets are not more accurate than synoptic stations,but their various advantages,such as spatial coverage,time coverage,accessibility,and free use,have made these techniques superior,and sometimes we can use them instead of synoptic stations.In this study,we used four meteorological datasets,including Climatic Research Unit gridded Time Series(CRU TS),Global Precipitation Climatology Centre(GPCC),Agricultural National Aeronautics and Space Administration Modern-Era Retrospective Analysis for Research and Applications(AgMERRA),Agricultural Climate Forecast System Reanalysis(AgCFSR),to estimate climate variables,i.e.,precipitation,maximum temperature,and minimum temperature,and crop variables,i.e.,reference evapotranspiration,irrigation requirement,biomass,and yield of maize,in Qazvin Province of Iran during 1980-2009.At first,data were gathered from the four meteorological datasets and synoptic station in this province,and climate variables were calculated.Then,after using the AquaCrop model to calculate the crop variables,we compared the results of the synoptic station and meteorological datasets.All the four meteorological datasets showed strong performance for estimating climate variables.AgMERRA and AgCFSR had more accurate estimations for precipitation and maximum temperature.However,their normalized root mean square error was inferior to CRU for minimum temperature.Furthermore,they were all very efficient for estimating the biomass and yield of maize in this province.For reference evapotranspiration and irrigation requirement CRU TS and GPCC were the most efficient rather than AgMERRA and AgCFSR.But for the estimation of biomass and yield,all the four meteorological datasets were reliable.To sum up,GPCC and AgCFSR were the two best datasets in this study.This study suggests the use of meteorological datasets in water resource management and agricultural management to monitor past changes and estimate recent trends.
文摘A weather station is proposed especially designed for developing countries, and to meet the standards of the international scientific community making research on the earth system. The station would measure in situ several ECV （essential climate variables）. These data may enable an agricultural breakthrough in countries lacking meteorological infrastructure, help in climate change monitoring, and facilitate diffusion of wind energy. A pre-feasibility analysis is presented. It appears interesting that the station is supplied by a social enterprise. A research to establish the best shelter design using computational fluid dynamics is also reported. The criterion is the accuracy with which the surface air temperature is reproduced inside the shelter. A design following recommendations by the WMO （World Meteorological Organization）, a smaller design with identical geometry, and two alternative small designs are analyzed. All four designs are simulated in PVC, natural rubber and wood, with and without white paint coating. The smaller shelters perform better. The influence of the material, dimensions and design is smaller than that of the white paint. Shelters made of PVC or rubber, and/or in alternative designs, may be more interesting if other criteria are considered, like whether logistics, manufacturing, etc. are more sustainable, easier and/or cheaper.
文摘Climate changes are affecting water resources around the world and the Mo Basin (MB) in Togo is no exception to this observation. This study aims at analyzing the influence of hydro-climatical data in the Mo Basin. To achieve this, Pettit’s stationarity break tests, Hubert’s segmentation, Nicholson’s [1] reduced centered index, Lamb [2] and flow coefficients have been applied. In addition, temperature, precipitation, evapotranspiration, relative humidity and discharge data from 1961 to 2018 have been used for this purpose. While rainfall is decreasing despite an increase of 22.8% at the Fazao station and 2.8% at Sotouboua station, the flow coefficients evolve synchronously with the precipitation data and show a strong link between both parameters. The climatic balance sheet is positive six months in the year (May to October), throughout the period of observation (1961-2018). Only 1962 and 1963 recorded an annual rainfall greater than the annual evapotranspiration. The other years undergo a climatic drought, increasingly pronounced, which strongly impacts the hydrology of rivers. This has a strong impact on water resources and food security and resources of the Fazao-Malfakassa reserve in the region.
