Using Statistical Downscaling to Quantify the GCM-Related Uncertainty in Regional Climate Change Scenarios: A Case Study of Swedish Precipitation

There are a number of sources of uncertainty in regional climate change scenarios. When statistical downscaling is used to obtain regional climate change scenarios, the uncertainty may originate from the uncertainties in the global climate models used, the skill of the statistical model, and the forcing scenarios applied to the global climate model. The uncertainty associated with global climate models can be evaluated by examining the differences in the predictors and in the downscaled climate change scenarios based on a set of different global climate models. When standardized global climate model simulations such as the second phase of the Coupled Model Intercomparison Project （CMIP2） are used, the difference in the downscaled variables mainly reflects differences in the climate models and the natural variability in the simulated climates. It is proposed that the spread of the estimates can be taken as a measure of the uncertainty associated with global climate models. The proposed method is applied to the estimation of global-climate-model-related uncertainty in regional precipitation change scenarios in Sweden. Results from statistical downscaling based on 17 global climate models show that there is an overall increase in annual precipitation all over Sweden although a considerable spread of the changes in the precipitation exists. The general increase can be attributed to the increased large-scale precipitation and the enhanced westerly wind. The estimated uncertainty is nearly independent of region. However, there is a seasonal dependence. The estimates for winter show the highest level of confidence, while the estimates for summer show the least.

Effect of Climate Change on Wetland Ecological Environment in Heihe River Basin in Recent 51 Years

[Objective] The effect of climate change on wetland ecological environment in Heihe River basin was researched.[Method] Based on meteorological data from six meteorological stations in Heihe River basin from 1959 to 2009,the effect of climate change on wetland ecological environment in Heihe River basin in recent 51 years was studied by means of statistical method.[Result] Temperature and precipitation in Heihe River basin showed obvious increasing trend in recent 51 years,especially in recent 20 years;climate change made Heihe River basin more and more dry,specially in mountain area;wetland ecological environment closely related to climate responded to climate change,such as groundwater level rise,wetland area decrease,agriculture planting structure change,meteorological disaster increase,destroyed biodiversity and so on.[Conclusion] Our study had important significance for the protection and development of wetland resources.

Effects of Climate Changes on the Ecological Environment of Panjin Wetland in Recent 50 Years

Based on the monitoring data of temperature,precipitation,sunshine and other meteorological elements,agro-meteorological and ecological observation data in Panjin wetland during 1957-2006,using statistical analysis method,the effects of climate change on the ecological environment system in Panjin wetland were studied.The results showed that in the past 50 years,the climatic factors in Panjin wetland experienced the changes characterized by the increase of air temperature,the reduction of precipitation days,decrease of sunshine hours,decrease of average wind speed and average relative humidity.The ecological environment that was closely related with the climate of Panjin wetland had also made a response to climate changes,including changes in growing season,increase in insect pests and plant diseases,animal and plant phenology changes and sea-level rise.

HUMAN IMPACTS ON THE ECOLOGICAL ENVIRONMENT AND MODERN URBAN CLIMATE CHANGE IN THE LOESS PLATEAU

The influence of human activities on environment and climate change is the most conspicuous problem of the Loess Plateau, and it may be divided into two aspects: firstly, the excessive utilization of land by the human race causes the destruction of vegetation, and consequently large expanse of land is under desertification and the characteristics of the ground surface and the water and heat exchange on the ground surface have changed; secondly, the use of coal by industries produces a huge amount of carbon dioxide and trace elements, which enter into the atmosphere to cause air pollution.Data of 1951-1990 are collected from 69 meteorological stations on the Loess Plateau. After analysis, the decadal variations of temperature and rainfall in the last 40 years are obtained as follows: (1) In the arid zone of the north- west of the Loess Plateau, the increase in temperature is the largest. For the past 40 years, the annual mean temperature has increased 0.7-1.0 ℃ . In the semiarid zone of the middle

Climate Change and Its Impact on Ecological Environment in Western Liaoning in Recent 50 years

Based on the observation data of meteorological stations in western Liaoning from 1971 to 2020,the trend,Morlet wavelet,MK mutation and other methods were used to analyze the data.The results show that the annual average temperature of western Liaoning was 9.29℃;the annual average precipitation was 542.2 mm,and the trend change was not obvious;the temperature had obvious quasi-13-year,quasi-19-year and quasi-45-year cycles,and the precipitation had quasi-3-year,quasi-6-year,quasi-14-year and quasi-29-year cycles;there was a sudden change in temperature in 1990,and the warming was significant after the sudden change;the typical abrupt changes of precipitation occurred in 1979 and 2000,but the abrupt changes were not significant.

Analysis and prediction of reference evapotranspiration with climate change in Xiangjiang River Basin, China

Reference evapotranspiration （ETo） is often used to estimate actual evapotranspiration in water balance studies. In this study, the present and future spatial distributions and temporal trends of ETo in the Xiangjiang River Basin （XJRB） in China were analyzed. ETo during the period from 1961 to 2010 was calculated with historical meteorological data using the FAO Penman-Monteith （FAO P-M） method, while ETo during the period from 2011 to 2100 was downscaled from the Coupled Model Intercomparison Project Phase 5 （CMIP5） outputs under two emission scenarios, representative concentration pathway 4.5 and representative concentration pathway 8.5 （RCP45 and RCP85）, using the statistical downscaling model （SDSM）. The spatial distribution and temporal trend of ETo were interpreted with the inverse distance weighted （IDW） method and Mann-Kendall test method, respectively. Results show that： （1） the mean annual ETo of the XJRB is 1 006.3 mm during the period from 1961 to 2010, and the lowest and highest values are found in the northeast and northwest parts due to the high latitude and spatial distribution of climatic factors, respectively; （2） the SDSM performs well in simulating the present ETo and can be used to predict the future ETo in the XJRB; and （3） CMIP5 predicts upward trends in annual ETo under the RCP45 and RCP85 scenarios during the period from 2011 to 2100. Compared with the reference period （1961-1990）, ETo increases by 9.8%, 12.6%, and 15.6% under the RCP45 scenario and 10.2%, 19.1%, and 27.3% under the RCP85 scenario during the periods from 2011 to 2040, from 2041 to 2070, and from 2071 to 2100, respectively. The predicted increasing ETo under the RCP85 scenario is greater than that under the RCP45 scenario during the period from 2011 to 2100.

Hydrological Impacts of Climate Change on Streamflow of Dongliao River Watershed in Jilin Province,China

The impacts of future climate change on streamflow of the Dongliao River Watershed located in Jilin Prov-ince, China have been evaluated quantitatively by using a general circulation model （HadCM3） coupled with the Soil and Water Assessment Tool （SWAT） hydrological model. The model was calibrated and validated against the historical monitored data from 2005 to 2009. The streamflow was estimated by downscaling HadCM3 outputs to the daily mean temperature and precipitation series, derived for three 30-year time slices, 2020s, 2050s and 2080s. Results suggest that daily mean temperature increases with a changing rate of 0.435~C per decade, and precipitation decreases with a changing rate of 0.761 mm per decade. Compared with other seasons, the precipitation in summer shows significant downward trend, while a significant upward trend in autumn. The annual streamflow demonstrates a general down-ward trend with a decreasing rate of 0.405 m^3/s per decade. The streamflow shows significant downward and upward trends in summer and in autumn, respectively. The decreasing rate of streamflow in summer reaches 1.97 m^3/s per decade, which contributes primarily to the decrease of streamflow. The results of this work would be of great benifit to the design of economic and social development planning in the study area.

Hydrological Impact Assessment of Climate Change on Lake Tana’s Water Balance, Ethiopia

The aim of this study is to evaluate the hydrological impacts of climate change on the water balance of Lake Tana in Ethiopia. Impact assessments are by downscaled General Circulation Model (GCM) output and hydrological modeling. For A2 and B2 emission scenarios, precipitation, maximum and minimum temperature estimates from the HadCM3 GCM were used. GCM output was downscaled using the Statistical DownScaling Model (SDSM 4.2). Impact analyses were applied for three future time periods: early, mid and late 21st century. Over-lake evaporation is estimated by Hardgrave’s method, and over-lake precipitation is estimated by inverse distance weighing interpolation, whereas inflows from gauged and ungauged catchments are simulated by the HBV hydrological model. Findings indicate increases in maximum and minimum temperature on annual base for both emission scenarios. The projection of mean annual over lake precipitation for both A2 and B2 emission scenarios shows increasing pattern for 21st century in comparison to the baseline period. The increase of mean annual precipitation for A2 emission scenario is 9% (112 mm/year), 10% (125 mm/year) and 11% (137 mm/year) for the three future periods respectively. B2 emission scenario mean annual precipitation shows increase by 9% (111 mm/year), 10% (122 mm/year) and 10% (130 mm/year) respectively for the three future periods. Findings indicate consistent increases of lake storage for all three future periods for both A2 and B2 emission scenarios.

Assessment of Future Climate Change Scenario in Halaba District, Southern Ethiopia

Climate change is one environmental threat that poses great challenges to the future development prospects of Ethiopia. The study used the statistically downscaled daily data in 30-years intervals from the second generation of the Earth System Model (CanESM2) under two Representative Concentration Pathways (RCPs): RCP 4.5 and RCP 8.5 for three future time slices;near-term (2010-2039), mid-century (2040-2069) and end-century (2071-2099) were generated. The observed data of maximum and minimum temperature and precipitation are a good simulation with the modeled data during the calibration and validation periods using the correlation coefficient (R2), the Nash-Sutcliffe efficiency (NSE), and the Root Mean Square Error (RMSE). The projected annual minimum and maximum temperatures are expected to increase by 0.091°C, 0.517°C, and 0.73°C and 0.072°C, 0.245°C, and 0.358°C in the 2020s, 2050s, and 2080s under the intermediate scenario, respectively. Under RCP8.5, the annual minimum and maximum temperatures are expected to increase by 0.192°C, 0.409°C, and 0.708°C, 0.402°C, 4.352°C, and 8.750°C in the 2020s, 2050s, and 2080s, respectively. Besides, the precipitation is expected to increase under intermediate and high emission scenarios by 1.314%, 7.643%, and 12.239%, and 1.269%, 10.316% and 26.298% in the 2020s, 2050s, and 2080s, respectively. Temperature and precipitation are projected to increase in total amounts under all-time slices and emissions pathways. In both emission scenarios, the greatest changes in maximum temperature, minimum temperature, and precipitation are predicted by the end of the century. This implies climate smart actions in development policies and activities need to consider locally downscale expected climatic changes.

An in-depth view of climate change:addressing climate change while making a transition on the development mode

While fossil fuels greatly contribute to human society,they pose great challenges to natural resources,the environment,and climate change.Developed countries,like the United States,formulated strategic measures to ensure their sustainable development and leading positions in the world.These measures include new green policies,development of shale gas,revitalization of nuclear power,energy independence,reindustrialization,and new low-carbon development based on a combination of Internet technology and renewable energy.Developing countries are also trying to introduce balanced strategies of poverty alleviation and sustainable development.Globally,industrial civilization is being transformed to ecological civilization and green,low-carbon development is a global trend.Addressing climate change provides new strategic factors to further this development.China should take substantial actions to realize sustainable development in a new road:China is in the critical stage of changing its development mode,so it is vital to choose an appropriate development path.This extensive development comes at the high price of consuming too much resources and scarring the environment.Mitigation and adaptation strategies for addressing climate change can help the transition of development.Based on the analysis of the development data of developed countries,the author introduces the concept of"two-type developed countries"with an understanding that not all developed countries must take the same development mode.He also holds the view that China should achieve modernization in a more energy-saving and more carbon-efficient manner compared with that of two-type developed countries.An analysis of"two competitions"that China is facing shows that changing the developing mode is urgent and China should grasp this opportunity in the next five to ten years,which is a key period for this transition.This paper discusses the low-carbon development goals and the three-step process.Low-carbon development does not necessarily restrict economic development.It,however,can expedite the transition of the development mode and this is a low-carbon and green development path.Transition of the development mode includes implementation of China's green and low-carbon energy strategies,low-carbon society construction,development of agriculture and forestry,garbage sorting and utilization,innovation of urbanization,etc.Improvement of national infrastructure construction includes water safety,environment and climate monitoring system,intelligent energy web,basic database,etc.Addressing climate change can significantly improve the nation's basic research level.In summary,it mitigates backward production capability,extensive development,and environmental damage while promoting technological advancement,scientific development,and ecological civilization.

Statistical Downscaling of Precipitation and Temperature Using Long Ashton Research Station Weather Generator in Zambia: A Case of Mount Makulu Agriculture Research Station

The Long Ashton Research Station Weather Generator (LARS-WG) is a stochastic weather generator used for the simulation of weather data at a single site under both current and future climate conditions using General Circulation Models (GCM). It was calibrated using the baseline (1981-2010) and evaluated to determine its suitability in generating synthetic weather data for 2020 and 2055 according to the projections of HadCM3 and BCCR-BCM2 GCMs under SRB1 and SRA1B scenarios at Mount Makulu (Latitude: 15.550°S, Longitude: 28.250°E, Elevation: 1213 meter), Zambia. Three weather parameters—precipitation, minimum and maximum temperature were simulated using LARS-WG v5.5 for observed station and AgMERRA reanalysis data for Mount Makulu. Monthly means and variances of observed and generated daily precipitation, maximum temperature and minimum temperature were used to evaluate the suitability of LARS-WG. Other climatic conditions such as wet and dry spells, seasonal frost and heat spells distributions were also used to assess the performance of the model. The results showed that these variables were modeled with good accuracy and LARS-WG could be used with high confidence to reproduce the current and future climate scenarios. Mount Makulu did not experience any seasonal frost. The average temperatures for the baseline (Observed station data: 1981-2010 and AgMERRA reanalysis: 1981-2010) were 21.33°C and 22.21°C, respectively. Using the observed station data, the average temperature under SRB1 (2020), SRA1B (2020), SRB1 (2055), SRA1B (2055) would be 21.90°C, 21.94°C, 22.83°C and 23.18°C, respectively. Under the AgMERRA reanalysis, the average temperatures would be 22.75°C (SRB1: 2020), 22.80°C (SRA1B: 2020), 23.69°C (SRB1: 2055) and 24.05°C (SRA1B: 2055). The HadCM3 and BCM2 GCMs ensemble mean showed that the number of days with precipitation would increase while the mean precipitation amount in 2020s and 2050s under SRA1B would reduce by 6.19% to 6.65%. Precipitation would increase under SRB1 (Observed), SRA1B, and SRB1 (AgMERRA) from 0.31% to 5.2% in 2020s and 2055s, respectively.

Impact of climate change on water resources in the Yarmouk River Basin of Jordan

Understanding the impact of climate change on water resources is important for developing regional adaptive water management strategies. This study investigated the impact of climate change on water resources in the Yarmouk River Basin(YRB) of Jordan by analyzing the historical trends and future projections of temperature, precipitation, and streamflow. Simple linear regression was used to analyze temperature and precipitation trends from 1989 to 2017 at Irbid, Mafraq, and Samar stations. The Statistical Downscaling Model(SDSM) was applied to predict changes in temperature and precipitation from 2018 to 2100 under three Representative Concentration Pathway(RCP) scenarios(i.e., RCP2.6, RCP4.5, and RCP8.5), and the Soil and Water Assessment Tool(SWAT) was utilized to estimate their potential impact on streamflow at Addasiyia station. Analysis of data from 1989 to 2017 revealed that mean maximum and minimum temperatures increased at all stations, with average rises of 1.62℃ and 1.39℃, respectively. The precipitation trends varied across all stations, showing a significant increase at Mafraq station, an insignificant increase at Irbid station, and an insignificant decrease at Samar station. Historical analysis of streamflow data revealed a decreasing trend with a slope of –0.168. Significant increases in both mean minimum and mean maximum temperatures across all stations suggested that evaporation is the dominant process within the basin, leading to reduced streamflow. Under the RCP scenarios, projections indicated that mean maximum temperatures will increase by 0.32℃ to 1.52℃, while precipitation will decrease by 8.5% to 43.0% throughout the 21st century. Future streamflow projections indicated reductions in streamflow ranging from 8.7% to 84.8% over the same period. The mathematical model results showed a 39.4% reduction in streamflow by 2050, nearly double the SWAT model's estimate under RCP8.5 scenario. This research provides novel insights into the regional impact of climate change on water resources, emphasizing the urgent need to address these environmental challenges to ensure a sustainable water supply in Jordan.

Climate Change Downscaling Using Stochastic Weather Generator Model in Rift Valley Basins of Ethiopia

Agriculture is the mainstay of Ethiopian economy. Developing country like Ethiopia suffers from climate change, due to their limited economic capability to build irrigation projects to combat the trouble. This study generates climate change in rift valley basins of Ethiopia for three time periods (2020s, 2055s and 2090s) by using two emission scenarios: SRA1B and SRB1 for faster technological and environmental extreme respectively. First, outputs of 15 General Circulation Models (GCMs) under two emission scenarios (SRA1B and SRB1) are statistically downscaled by using LARS-WG software. Probability assessment of bounded range with known distributions is used to deal with the uncertainties of GCMs’ outputs. These GCMs outputs are weighted by considering the ability of each model to simulate historical records. The study result indicates that LARS-WG 5.5 version model is more uncertain to simulate future mean rainfall than generating maximum and minimum mean temperatures. GCMs weight difference for mean rainfall is 0.83 whereas weight difference for minimum and maximum mean temperatures is 0.09 among GCMs models. The study results indicate minimum and maximum temperatures absolute increase in the range of 0.34˚C to 0.58˚C, 0.94˚C to 1.8˚C and 1.42˚C to 3.2˚C and 0.32˚C to 0.56˚C, 0.91˚C to 1.8˚C and 1.34˚C to 3.04˚C respectively in the near-term (2020s), mid-term (2055s) and long-term (2090s) under both emission scenarios. The expected rainfall change percentage during these three time periods considering this GCMs weight difference into account ranges from -2.3% to 7%, 0.375% to 15.83% and 2.625% to 31.1% in the same three time periods. In conclusion, the study results indicate that in coming three time periods, maximum and minimum temperature and rainfall increase is expected in rift valley of basins of Ethiopia.

Analysis of Trents of Future Temperature in the Bosten Lake Basin Based on a Statistical Downscaling Model

SDSM统计降尺度模型是解决空间尺度不匹配问题的有效工具,它使气候变化响应研究得以在区域尺度上展开。本文将SDSM模型应用于博斯腾湖流域分析它的适用性,并对流域未来最高和最低气温的变化趋势进行了预测。以日最高气温和最低气温为预报量,选取合适的NCEP大气环流因子为预报因子,建立预报量与预报因子间的回归关系。使用1961-1990、1991-2001年的实测数据和NCEP大气变量分别对SDSM模型进行率定和验证,效果较好。把HadCM3输出的A2、B2情景下的大气环流变量作为模型输入变量,模拟流域未来3个时期(21世纪20、50和90年代)的气温变化。结果显示,流域未来日最高气温和日最低气温都呈现明显上升趋势,升高幅度依次为:日最高气温】日平均气温】日最低气温,且A2情景下气温增幅略大于B2情景下的增幅;冬季气温增幅最小,夏季增幅最大。分析结果可为博斯腾湖流域开展气候变化的水文响应研究以及气候变化的适应性研究提供科学依据。

Projected hydrologic regime changes in the Poyang Lake Basin due to climate change

Poyang Lake, the largest freshwater lake in China, and its surrounding sub-basins have suffered frequent floods and droughts in recent decades. To better understand and quantitatively assess hydrological impacts of climate change in the region, this study adopted the Statistical Downscaling Model （SDSM） to downseale the outputs of a Global Climate Model （GCM） under three scenarios （RCP2.6, RCP4.5 and RCP8.5） as recommended by the fifth phase of the Coupled Model Inter-comparison Project （CMIP5） during future periods （2010-2099） in the Poyang Lake Basin. A semi-distributed two-parameter monthly water balance model was also used to simulate and predict projected changes of runoff in the Ganjiang sub-basin. Results indicate that： 1） SDSM can simulate monthly mean precipitation reasonably well, while a bias correction procedure should be applied to downscaled extreme precipitation indices （EPI） before being employed to simulate future precipitation; 2） for annual mean precipitation, a mixed pattern of positive or negative changes are detected in the entire basin, with a slightly higher or lower trend in the 2020s and 2050s, with a consistent increase in the 2080s; 3） all six EPI show a general increase under RCP4.5 and RCP8.5 scenarios, while a mixed pattern of positive and negative changes is detected for most indices under the RCP2.6 scenario; and 4） the future runoff in the Ganjiang sub-basin shows an overall decreasing trend for all periods but the 2080s under the RCP8.5 scenario when runoff is more sensitive to changes in precipitation than evaporation.

Projected heat wave increasing trends over China based on combined dynamical and multiple statistical downscaling methods

Extensive investigations on the projection of heat waves(HWs)were conducted on the basis of coarse-resolution global climate models(GCMs).However,these investigations still fail to characterise the future changes in HWs regionally over China.PRECIS dynamical downscaling with a horizontal resolution of 25 km×25 km was employed on the basis of GCM-HadCM3 to provide reliable projections on HWs over the Chinese mainland,and six statistical downscaling methods were used for bias correction under RCP4.5 and RCP8.5 scenarios.The multi-method ensemble(MME)of the top three dynamical downscaling methods with good performance was used to project future changes.Results showed that PRECIS primarily replicated the detailed spatiotemporal pattern of HWs.However,PRECIS overestimated the HWs in the Northwest and Southeast and expanded the areas of HWs in the Northeast and Southwest.Three statistical downscaling methods(quantile mapping,CDF-t and quantile delta mapping)demonstrated good performance in improving PRECIS simulation for reproducing HWs.By contrast,parametric-based trend-preserving approaches such as scaled distribution mapping and ISI-MIP are outperformed by the three aforementioned methods in downscaling HWs,particularly in the high latitudes of China.Based on MME projections,at the end of the 21st century,the national average of the number of HW days each year,the length of the longest HW event in the year and the extreme maximum temperature in HW will increase by 3 times,1 time and 1.3℃,respectively,under the RCP4.5 scenario,whilst that under the RCP8.5 scenario will increase by 8 times,3 times and 3.7℃,respectively,relative to 1986-2005.The Northwest is regionally projected to suffer long and hot HWs,whilst the South and Southeast will experience frequent consecutive HWs.Thus,HWs projected by the combined dynamical and statistical downscaling method are highly reliable in projecting HWs over China.

VIC distributed hydrological model to predict climate change impact in the Hanjiang Basin

The climate impact studies in hydrology often rely on climate change information at fine spatial resolution. However, the general circulation model (GCM), which is widely used to simulate future climate scenario, operates on a coarse scale and does not provide reliable data on local or regional scale for hydrological modeling. Therefore the outputs from GCM have to be downscaled to obtain the information fit for hydrologic studies. The variable infiltration capacity (VIC) distributed hydrological model with 9×9 km2 grid resolution was applied and calibrated in the Hanjiang Basin. Validation results show that SSVM can approximate observed precipitation and temperature data reasonably well, and that the VIC model can simulate runoff hydrograph with high model efficiency and low relative error. By applying the SSVM model, the trends of precipitation and temperature (including daily mean temperature, daily maximum temperature and daily minimum temperature) projected from CGCM2 under A2 and B2 scenarios will decrease in the 2020s (2011―2040), and increase in the 2080s (2071―2100). However, in the 2050s (2041―2070), the precipitation will be decreased under A2 scenario and no significant changes under B2 scenario, but the temperature will be not obviously changed under both climate change scenarios. Under both climate change scenarios, the impact analysis of runoff, made with the downscaled precipitation and temperature time series as input of the VIC distributed model, has resulted in a decreasing trend for the 2020s and 2050s, and an overall increasing trend for the 2080s.

Ecological environment quality evaluation of the Sahel region in Africa based on remote sensing ecological index

Long-term monitoring of the ecological environment changes is helpful for the protection of the ecological environment.Based on the ecological environment of the Sahel region in Africa,we established a remote sensing ecological index(RSEI)model for this region by combining dryness,moisture,greenness,and desertification indicators.Using the Moderate-resolution Imaging Spectroradiometer(MODIS)data in Google Earth Engine(GEE)platform,this study analyzed the ecological environment quality of the Sahel region during the period of 2001-2020.We used liner regression and fluctuation analysis methods to study the trend and fluctuation of RSEI,and utilized the stepwise regression approach to analyze the contribution of each indicator to the RSEI.Further,the correlation analysis was used to analyze the correlation between RSEI and precipitation,and Hurst index was applied to evaluate the change trend of RSEI in the future.The results show that RSEI of the Sahel region exhibited spatial heterogeneity.Specifically,it exhibited a decrease in gradient from south to north of the Sahel region.Moreover,RSEI in parts of the Sahel region presented non-zonal features.Different land-cover types demonstrated different RSEI values and changing trends.We found that RSEI and precipitation were positively correlated,suggesting that precipitation is the controlling factor of RSEI.The areas where RSEI values presented an increasing trend were slightly less than the areas where RSEI values presented a decreasing trend.In the Sahel region,the areas with the ecological environment characterized by continuous deterioration and continuous improvement accounted for 44.02%and 28.29%of the total study area,respectively,and the areas in which the ecological environment was changing from improvement to deterioration and from deterioration to improvement accounted for 12.42%and 15.26%of the whole area,respectively.In the face of the current ecological environment and future change trends of RSEI in the Sahel region,the research results provide a reference for the construction of the"Green Great Wall"(GGW)ecological environment project in Africa.

Climate Change and Heavy Rainfall-Related Water Damage Insurance Claims and Losses in Ontario, Canada

The objective of this paper was to project possible impacts of climate change on heavy rainfall-related water damage insurance claims and incurred losses for four selected cites (Kitchener-Waterloo, London, Ottawa, and Toronto) located at Ontario, Canada. To achieve this goal, the future climate change scenarios and rainfall simulations, at local scale, were needed. A statistical downscaling method was used to downscale five global climate model (GCM) scenarios to selected weather stations. The downscaled meteorological variables included surface and upper-air hourly temperature, dew point, west-east and south-north winds, air pressure, and total cloud cover. These variables are necessary to project future daily rainfall quantities using within-weather-type rainfall simulation models. A model result verification process has been built into the whole exercise, including rainfall simulation modeling and the development of downscaling transfer functions. The results of the verification, based on historical observations of the outcome variables simulated by the models, showed a very good agreement. To effectively evaluate heavy rainfall-related water damage insurance claims and incurred losses, a rainfall index was developed considering rainfall intensity and duration. The index was evaluated to link with insurance data as to determination of a critical threshold of the rainfall index for triggering high numbers of rainfall-related water damage insurance claims and incurred losses. The relationship between rainfall index and insurance data was used with future rainfall simulations to project changes in future heavy rainfall-related sewer flood risks in terms of water damage insurance claims and incurred losses. The modeled results showed that, averaged over the five GCM scenarios and across the study area, both the monthly total number of rainfall-related water damage claims and incurred losses could increase by about 13%, 20% and 30% for the periods 2016-2035, 2046-2065, and 2081-2100, respectively (from the four-city seasonal average of 12 ± 1.7 thousand claims and $88 ± $21 million during April-September 1992-2002). Within the context of this study, increases in the future number of insurance claims and incurred losses in the study area are driven by only increases in future heavy rainfall events.

Projecting future precipitation change across the semi-arid Borana lowland,southern Ethiopia

Climate change caused by past,current,and future greenhouse gas emissions has become a major concern for scientists in the field in many countries and regions of the world.This study modelled future precipitation change by downscaling a set of large-scale climate predictor variables(predictors)from the second generation Canadian Earth System Model(CanESM2)under two Representative Concentration Pathway(RCP)emission scenarios(RCP4.5 and RCP8.5)in the semi-arid Borana lowland,southern Ethiopia.The Statistical DownScaling Model(SDSM)4.2.9 was employed to downscale and project future precipitation change in the middle(2036-2065;2050s)and far(2066-2095;2080s)future at the local scale.Historical precipitation observations from eight meteorological stations stretching from 1981 to 1995 and 1996 to 2005 were used for the model calibration and validation,respectively,and the time period of 1981-2018 was considered and used as the baseline period to analyze future precipitation change.The results revealed that the surface-specific humidity and the geopotential height at 500 hPa were the preferred large-scale predictors.Compared to the middle future(2050s),precipitation showed a much greater increase in the far future(2080s)under both RCP4.5 and RCP8.5 scenarios at all meteorological stations(except Teletele and Dillo stations).At Teltele station,the projected annual precipitation will decrease by 26.53%(2050s)and 39.45%(2080s)under RCP4.5 scenario,and 34.99%(2050s)and 60.62%(2080s)under RCP8.5 scenario.Seasonally,the main rainy period would shift from spring(March to May)to autumn(September to November)at Dehas,Dire,Moyale,and Teltele stations,but for Arero and Yabelo stations,spring would consistently receive more precipitation than autumn.It can be concluded that future precipitation in the semi-arid Borana lowland is predicted to differ under the two climate scenarios(RCP4.5 and RCP8.5),showing an increasing trend at most meteorological stations.This information could be helpful for policymakers to design adaptation plans in water resources management,and we suggest that the government should give more attention to improve early warning systems in drought-prone areas by providing dependable climate forecast information as early as possible.