在第2代加拿大地球系统模型(the second generation Canadian earth system model,CanESM2)中的3种典型浓度路径(representative concentration pathways,RCPs)情景(RCP2.6、RCP4.5和RCP8.5)下,基于统计降尺度模型(statistical down sca...在第2代加拿大地球系统模型(the second generation Canadian earth system model,CanESM2)中的3种典型浓度路径(representative concentration pathways,RCPs)情景(RCP2.6、RCP4.5和RCP8.5)下,基于统计降尺度模型(statistical down scaling model,SDSM)研究兰江流域未来年份温度和降水量的变化趋势。结果表明:1)SDSM在兰江流域具有较好的适用性,各站点最高温度、最低温度、降水量的解释方差分别为70.62%~79.74%、69.61%~78.76%、28.56%~41.45%;2)3种RCPs情景下温度均呈上升趋势,且上升幅度随辐射强迫度上升而同步增大,至21世纪末,RCP2.6、RCP4.5、RCP8.5情景下的最高温度分别较基准期上升0.06℃、1.22℃、2.76℃,最低温度分别较基准期上升0.35℃、1.15℃、3.01℃;3)RCP2.6情景下的降水量总体呈下降趋势,至2080—2100年下降0.98%,RCP4.5情景下的降水量呈先上升后下降趋势,至2050—2079年达到峰值,较基准期上升12.03%,RCP8.5情景下的降水量呈先下降后快速上升趋势,至2080—2100年上升38.08%。研究结果可为兰江流域内水资源管理、生态文明建设及社会经济可持续发展提供依据和理论支持。展开更多
Drought is one of the most significant environmental disasters,especially in arid and semi-arid regions.Drought indices as a tool for management practices seeking to deal with the drought phenomenon are widely used ar...Drought is one of the most significant environmental disasters,especially in arid and semi-arid regions.Drought indices as a tool for management practices seeking to deal with the drought phenomenon are widely used around the world.One of these indicators is the Palmer drought severity index(PDSI),which is used in many parts of the world to assess the drought situation and continuation.In this study,the drought state of Fars Province in Iran was evaluated by using the PDSI over 1995-2014 according to meteorological data from six weather stations in the province.A statistical downscaling model(SDSM)was used to apply the output results of the general circulation model in Fars Province.To implement data processing and prediction of climate data,a statistical period 1995-2014 was considered as the monitoring period,and a statistical period 2019-2048 was for the prediction period.The results revealed that there is a good agreement between the simulated precipitation(R2>0.63;R2,determination coefficient;MAE<0.52;MAE,mean absolute error;RMSE<0.56;RMSE,Root Mean Squared Error)and temperature(R2>0.95,MAE<1.74,and RMSE<1.78)with the observed data from the stations.The results of the drought monitoring model presented that dry periods would increase over the next three decades as compared to the historical data.The studies showed the highest drought in the meteorological stations Abadeh and Lar during the prediction period under two future scenarios representative concentration pathways(RCP4.5 and RCP8.5).According to the results of the validation periods and efficiency criteria,we suggest that the SDSM is a proper tool for predicting drought in arid and semi-arid regions.展开更多
In order to explore the climate change in the Dawen River basin,based on the data of six weather stations in the Dawen River basin from 1966 to 2017,Mann-Kendall test and wavelet analysis were used to study the temper...In order to explore the climate change in the Dawen River basin,based on the data of six weather stations in the Dawen River basin from 1966 to 2017,Mann-Kendall test and wavelet analysis were used to study the temperature and precipitation trends,mutations and cycles in the region.In addition,based on the three scenarios of RCP2.6,RCP4.5,and RCP8.5 under the CanESM2 model,SDSM was used to compare and analyze the future climate change of the Dawen River basin.The results revealed that:the annual mean temperature of the Dawen River basin had increased significantly since 1966(p<0.01);in different scenarios,the spatial distribution of the projected maximum temperature,minimum temperature and precipitation will hardly change compared with that in history;the temperature and precipitation in the Dawen River basin will generally increase in the future.The rising trend of maximum and minimum temperature under the three scenarios is in the EP<MP<LP,and June and November was the months with the highest increase;the future precipitation will have the highest increase in July and August.Under the RCP4.5 and RCP8.5 scenarios,the annual maximum and minimum temperatures in the future will increase with the increase in time scale.展开更多
The paper describes the application of SDSM （statistical downscaling model） and ANNs （artificial neural networks） models for prediction of the hydrological trend due to the climate-change. The SDSM has been calibr...The paper describes the application of SDSM （statistical downscaling model） and ANNs （artificial neural networks） models for prediction of the hydrological trend due to the climate-change. The SDSM has been calibrated and generated for the possible future scenarios of meteorological variables, which are temperature and rainfall by using GCMs （global climate models）. The GCM used is SRES A2. The downscaled meteorological variables corresponding to SDSM were then used as input to the ANNs model calibrated with observed station data to simulate the corresponding future streamflow changes in the sub-catchment of Kurau River. This study has discovered the hydrological trend over the catchment. The projected monthly streamflow has shown a decreasing trend due to the increase in the, mean of temperature for overall months, except the month of August and November.展开更多
文摘在第2代加拿大地球系统模型(the second generation Canadian earth system model,CanESM2)中的3种典型浓度路径(representative concentration pathways,RCPs)情景(RCP2.6、RCP4.5和RCP8.5)下,基于统计降尺度模型(statistical down scaling model,SDSM)研究兰江流域未来年份温度和降水量的变化趋势。结果表明:1)SDSM在兰江流域具有较好的适用性,各站点最高温度、最低温度、降水量的解释方差分别为70.62%~79.74%、69.61%~78.76%、28.56%~41.45%;2)3种RCPs情景下温度均呈上升趋势,且上升幅度随辐射强迫度上升而同步增大,至21世纪末,RCP2.6、RCP4.5、RCP8.5情景下的最高温度分别较基准期上升0.06℃、1.22℃、2.76℃,最低温度分别较基准期上升0.35℃、1.15℃、3.01℃;3)RCP2.6情景下的降水量总体呈下降趋势,至2080—2100年下降0.98%,RCP4.5情景下的降水量呈先上升后下降趋势,至2050—2079年达到峰值,较基准期上升12.03%,RCP8.5情景下的降水量呈先下降后快速上升趋势,至2080—2100年上升38.08%。研究结果可为兰江流域内水资源管理、生态文明建设及社会经济可持续发展提供依据和理论支持。
文摘Drought is one of the most significant environmental disasters,especially in arid and semi-arid regions.Drought indices as a tool for management practices seeking to deal with the drought phenomenon are widely used around the world.One of these indicators is the Palmer drought severity index(PDSI),which is used in many parts of the world to assess the drought situation and continuation.In this study,the drought state of Fars Province in Iran was evaluated by using the PDSI over 1995-2014 according to meteorological data from six weather stations in the province.A statistical downscaling model(SDSM)was used to apply the output results of the general circulation model in Fars Province.To implement data processing and prediction of climate data,a statistical period 1995-2014 was considered as the monitoring period,and a statistical period 2019-2048 was for the prediction period.The results revealed that there is a good agreement between the simulated precipitation(R2>0.63;R2,determination coefficient;MAE<0.52;MAE,mean absolute error;RMSE<0.56;RMSE,Root Mean Squared Error)and temperature(R2>0.95,MAE<1.74,and RMSE<1.78)with the observed data from the stations.The results of the drought monitoring model presented that dry periods would increase over the next three decades as compared to the historical data.The studies showed the highest drought in the meteorological stations Abadeh and Lar during the prediction period under two future scenarios representative concentration pathways(RCP4.5 and RCP8.5).According to the results of the validation periods and efficiency criteria,we suggest that the SDSM is a proper tool for predicting drought in arid and semi-arid regions.
基金National Natural Science Foundation of China(41471160)。
文摘In order to explore the climate change in the Dawen River basin,based on the data of six weather stations in the Dawen River basin from 1966 to 2017,Mann-Kendall test and wavelet analysis were used to study the temperature and precipitation trends,mutations and cycles in the region.In addition,based on the three scenarios of RCP2.6,RCP4.5,and RCP8.5 under the CanESM2 model,SDSM was used to compare and analyze the future climate change of the Dawen River basin.The results revealed that:the annual mean temperature of the Dawen River basin had increased significantly since 1966(p<0.01);in different scenarios,the spatial distribution of the projected maximum temperature,minimum temperature and precipitation will hardly change compared with that in history;the temperature and precipitation in the Dawen River basin will generally increase in the future.The rising trend of maximum and minimum temperature under the three scenarios is in the EP<MP<LP,and June and November was the months with the highest increase;the future precipitation will have the highest increase in July and August.Under the RCP4.5 and RCP8.5 scenarios,the annual maximum and minimum temperatures in the future will increase with the increase in time scale.
文摘The paper describes the application of SDSM （statistical downscaling model） and ANNs （artificial neural networks） models for prediction of the hydrological trend due to the climate-change. The SDSM has been calibrated and generated for the possible future scenarios of meteorological variables, which are temperature and rainfall by using GCMs （global climate models）. The GCM used is SRES A2. The downscaled meteorological variables corresponding to SDSM were then used as input to the ANNs model calibrated with observed station data to simulate the corresponding future streamflow changes in the sub-catchment of Kurau River. This study has discovered the hydrological trend over the catchment. The projected monthly streamflow has shown a decreasing trend due to the increase in the, mean of temperature for overall months, except the month of August and November.
