Precipitation projections over the Tibetan Plateau(TP)show diversity among existing studies,partly due to model uncertainty.How to develop a reliable projection remains inconclusive.Here,based on the IPCC AR6–assesse...Precipitation projections over the Tibetan Plateau(TP)show diversity among existing studies,partly due to model uncertainty.How to develop a reliable projection remains inconclusive.Here,based on the IPCC AR6–assessed likely range of equilibrium climate sensitivity(ECS)and the climatological precipitation performance,the authors constrain the CMIP6(phase 6 of the Coupled Model Intercomparison Project)model projection of summer precipitation and water availability over the TP.The best estimates of precipitation changes are 0.24,0.25,and 0.45 mm d^(−1)(5.9%,6.1%,and 11.2%)under the Shared Socioeconomic Pathway(SSP)scenarios of SSP1–2.6,SSP2–4.5,and SSP5–8.5 from 2050–2099 relative to 1965–2014,respectively.The corresponding constrained projections of water availability measured by precipitation minus evaporation(P–E)are 0.10,0.09,and 0.22 mm d^(−1)(5.7%,4.9%,and 13.2%),respectively.The increase of precipitation and P–E projected by the high-ECS models,whose ECS values are higher than the upper limit of the likely range,are about 1.7 times larger than those estimated by constrained projections.Spatially,there is a larger increase in precipitation and P–E over the eastern TP,while the western part shows a relatively weak difference in precipitation and a drier trend in P–E.The wetter TP projected by the high-ECS models resulted from both an approximately 1.2–1.4 times stronger hydrological sensitivity and additional warming of 0.6℃–1.2℃ under all three scenarios during 2050–2099.This study emphasizes that selecting climate models with climate sensitivity within the likely range is crucial to reducing the uncertainty in the projection of TP precipitation and water availability changes.展开更多
A statistical regression downscaling method was used to project future changes in precipitation over eastern China based on Phase 5 of the Coupled Model Intercomparison Project (CMIPS) the Representative Concentrati...A statistical regression downscaling method was used to project future changes in precipitation over eastern China based on Phase 5 of the Coupled Model Intercomparison Project (CMIPS) the Representative Concentration Pathway (RCP) scenarios simulated by the second spectral version of the Flexible Global Ocean- Atmosphere-Land System (FGOALS-s2) model. Our val- idation results show that the downscaled time series agree well with the present observed precipitation in terms of both the annual mean and the seasonal cycle. The regres- sion models built from the historical data are then used to generate future projections. The results show that the en- hanced land-sea thermal contrast strengthens both the subtropical anticyclone over the western Pacific and the east Asian summer monsoon flow under both RCPs. However, the trend of precipitation in response to warming over the 21 st century are different across eastern Chi- na under different RCPs. The area to the north of 32°N is likely to experience an increase in annual mean precipitation, while for the area between 23°N and 32°N mean precipitation is projected to decrease slightly over this century under RCP8.5. The change difference between scenarios mainly exists in the middle and late century. The land-sea thermal contrast and the associated east Asian summer monsoon flow are stronger, such that precipitation increases more, at higher latitudes under RCP8.5 compared to under RCP4.5. For the region south of 32°N, rainfall is projected to increase slightly under RCP4.5 but decrease under RCP8.5 in the late century. At the high resolution of 5 km, our statistically downscaled results for projected precipitation can be used to force hydrological models to project hydrological processes, which will be of great benefit to regional water planning and management.展开更多
The present study has generated and analyzed Climate Change projections in Nicaragua for the period 2010-2040. The obtained results are to be used for evaluating and planning more resilient transport infrastructures i...The present study has generated and analyzed Climate Change projections in Nicaragua for the period 2010-2040. The obtained results are to be used for evaluating and planning more resilient transport infrastructures in the next decades. This study has focused its efforts to pay attention into the effect of Climate Change on precipitation and temperature from a mean and extreme event perspective. Dynamical Downscaling approach on a 4 km resolution grid has been chosen as the most appropriate methodology for the estimation of the projected climate, being able to account for local-scale factors like complex topography or local land uses properly. We selected MPI-ESM-MR as the global climate model with the best skill scores in terms of precipitation and temperature in Nicaragua. MPI-ESM-MR was coupled to a mesoscale model. We chose WRF mesoescale model as the most appropriate regional model and we optimized their physical and dynamical options in order to minimize the model uncertainty in Nicaragua. For this, model output against the available in-situ measurements from the national meteorological station network and satellite data were compared. Climate change signal was estimated by comparing the different climate statistics calculated from a model run over an historical period, 1980-2009, with a model run over a projected period, 2010-2040. The obtained results from the projected climate show an increase of the mean temperature between 0.6°C and 0.8°C and an increase of the number of days per year with maximum daily temperatures higher than 35°C. Regarding precipitation, annual projected amounts do not change remarkably with respect to the historical period. However, significant changes in the distribution of the precipitation within the wet period (May-October) were observed. Moreover, an increment between 5% and 10% of the number of days without precipitation is expected. Finally, Intensity-Duration-Frequency (IDF) projected curves show an increment of the rainfall intensity and an increment of extreme precipitation event frequency, especially in the Caribbean basin.展开更多
In the Lancang‒Mekong River basin(LMRB),agriculture,dominating the local economy,faces increasing challenges in water supply under climate change.The projection of future precipitation in this basin is essential for u...In the Lancang‒Mekong River basin(LMRB),agriculture,dominating the local economy,faces increasing challenges in water supply under climate change.The projection of future precipitation in this basin is essential for understanding the challenges.In this study,the Weather Research and Forecasting(WRF)model was applied to project the LMRB precipitation.Comparing with the historical period(1986e2005),we analyzed the changes of both the projected precipitation amount and the frequency of rainless(<0.1 mm d1),light rain(0.1e10 mm d1),moderate rain(10e25 mm d1),heavy rain(25e50 mm d1),rainstorm(50e100 mm d1),and heavy rainstorm(>100 mm d1)for three periods,namely the near-term(2016e2035),mid-term(2046e2065),and long-term(2080e2099).The results indicate that the precipitation amount during the wet season(AprileOctober)is expected to increase in most areas of the basin for the three periods.As for the precipitation during the dry season(NovembereMarch),an increase is projected in most areas for the near-term,while an increase in the lower reach of the basin and a decrease in the upper and middle reach for the mid-term and long-term.The precipitation reduction is expected to be greatest in Myanmar,Laos,Thailand,and Yunnan province of China for the mid-term.The frequency of precipitation in different intensities has prominent regional and temporal differences.During the wet season,the days of rainless and light rain are expected to decrease in the middle reach,whereas the days of rainstorm and heavy rainstorm increase.This feature is especially strong in southern Thailand,southern Laos and Cambodia in the near-term and in Laos and Thailand for the mid-term and long-term.During the dry season,there are projected increasing rainless days and decreasing days of precipitation for the other intensities in the middle reach,and opposite in the rest area of the basin.These projected precipitation changes have potential various impact in different parts of the basin.The middle reach would likely face increasing flood risks because of more days of rainstorm and heavy rainstorm,as well as more precipitation.Yunnan,Myanmar,Thailand and Laos would probably be the center of drought threatens during the dry season due to the increment of rainless days and the precipitation reduction.Besides,the seawater intrusion during the dry season in the near-term and mid-term would be more serious as a result of the precipitation decrease in southern Vietnam.展开更多
This study examines the inter-annual variability of rainfall and Mean Sea Level Pressure (</span><span style="font-family:Verdana;">M</span><span style="font-family:Verdana;"&g...This study examines the inter-annual variability of rainfall and Mean Sea Level Pressure (</span><span style="font-family:Verdana;">M</span><span style="font-family:Verdana;">SLP) over west Africa based on analysis of the Global Precipitation</span><span style="font-family:""><span style="font-family:Verdana;"> Climatology Project (GPCP) and National Center for Environmental Prediction/National Center for Atmospheric Research (NCEP/NCAR) Reanalysis respectively. An interconnection is found in this region, between Mean Sea Level Pressure (MSLP) anomaly (over Azores and St. Helena High) and monthly mean precipitation during summer (June to September: JJAS). We also found that over northern Senegal (15</span><span style="white-space:nowrap;font-family:Verdana;">°</span><span style="font-family:Verdana;">N</span></span><span style="font-family:""> </span><span style="font-family:Verdana;">-</span><span style="font-family:""> </span><span style="font-family:""><span style="font-family:Verdana;">17</span><span style="white-space:nowrap;font-family:Verdana;">°</span><span style="font-family:Verdana;">N;17</span><span style="white-space:nowrap;font-family:Verdana;">°</span><span style="font-family:Verdana;">W</span></span><span style="font-family:""> </span><span style="font-family:Verdana;">-</span><span style="font-family:""> </span><span style="font-family:""><span style="font-family:Verdana;">13</span><span style="white-space:nowrap;font-family:Verdana;">°</span><span style="font-family:Verdana;"></span><span style="font-family:Verdana;">W) the SLP to the north is strong;the wind converges at 200</span></span><span style="font-family:""> </span><span style="font-family:Verdana;">hPa corresponding to the position of the African Easterly Jet (AEJ) the rotational wind 700</span><span style="font-family:""> </span><span style="font-family:""><span style="font-family:Verdana;">hPa (corresponding to the position of the African Easterly Jet (AEJ) coming from the north-east is negative. In this region, the precipitation is related to the SLP to the north with the opposite sign. The Empirical Orthogonal Functions (EOF) of SLP is also presented, including the mean spectrum of precipitation and pressures to the north (15</span><span style="white-space:nowrap;font-family:Verdana;">°</span><span style="font-family:Verdana;">N</span></span><span style="font-family:""> </span><span style="font-family:Verdana;">-</span><span style="font-family:""> </span><span style="font-family:""><span style="font-family:Verdana;">40</span><span style="white-space:nowrap;font-family:Verdana;">°</span><span style="font-family:Verdana;">N and 50</span><span style="white-space:nowrap;font-family:Verdana;">°</span><span style="font-family:Verdana;">W</span></span><span style="font-family:""> </span><span style="font-family:Verdana;">-</span><span style="font-family:""> </span><span style="font-family:""><span style="font-family:Verdana;">25</span><span style="white-space:nowrap;font-family:Verdana;">°</span><span style="font-family:Verdana;">W) and south (40</span><span style="white-space:nowrap;font-family:Verdana;">°</span><span style="font-family:Verdana;">S</span></span><span style="font-family:""> </span><span style="font-family:Verdana;">-</span><span style="font-family:""> </span><span style="font-family:""><span style="font-family:Verdana;">10</span><span style="white-space:nowrap;font-family:Verdana;">°</span><span style="font-family:Verdana;">S and 40</span><span style="white-space:nowrap;font-family:Verdana;">°</span><span style="font-family:Verdana;">W</span></span><span style="font-family:""> </span><span style="font-family:Verdana;">-</span><span style="font-family:""> </span><span style="font-family:""><span style="font-family:Verdana;">0</span><span style="white-space:nowrap;font-family:Verdana;">°</span><span style="font-family:Verdana;">E). The dominant EOF of Sea Level Pressures north and south of the Atlantic Ocean for GPCP represents about 62.2% and 69.4% of the variance, respectively. The second and third EOFs of the pressure to the north account for 24.0% and 6.5% respectively. The second and third EOFs of the pressure to the south represent 12.5% and 8.9% respectively. Wet years in the north of Senegal were associated with anomalous low-pressure areas over the north Atlantic Ocean as opposed to the dry years which exhibited an anomalous high-pressure area in the same region. On the other hand, over the South Atlantic, an opposition is noted. The wavelet analysis method is applied to the SLP showings to the north, south and precipitation in our study area. The indices prove to be very consistent, especially during intervals of high variance.展开更多
The Global Precipitation Climatology Project (GPCP) monthly rainfall data and the rainfall records observed by 740 rain gauges in the mainland of China are used to analyze similarities and differences of the precipi...The Global Precipitation Climatology Project (GPCP) monthly rainfall data and the rainfall records observed by 740 rain gauges in the mainland of China are used to analyze similarities and differences of the precipitation in China in the period from January 1980 to December 2000. Results expose significantly consistent rainfall distributions between the both data in multi-year mean, multi-year seasonal mean, and multi-year monthly mean. Departures of monthly rainfall for each dataset also show a high correlation with an over 0.8 correlation coefficient. Analysis indicates small differences of both datasets during autumn, winter, and spring, but relative large ones in summer. Generally, the GPCP has trend of overestimating the rainfall rate. Based on above good relationship of both datasets, the GPCP data, are used to represent distributions and variations of precipitation in the Tibetan Plateau and Northwest China. Results indicate positive departures of precipitation in summer in the west part of Tibetan Plateau in the 1980s and negative departures after the 1980s. For the west part of Northwest China, analysis illustrates precipitation decreases a little, but no clear variation tendency.展开更多
基金supported by the Second Tibetan Plateau Scientific Expedition and Research(STEP)program[grant number 2019QZKK0102]the Chinese Academy of Sciences[grant number 060GJHZ2023079GC].
文摘Precipitation projections over the Tibetan Plateau(TP)show diversity among existing studies,partly due to model uncertainty.How to develop a reliable projection remains inconclusive.Here,based on the IPCC AR6–assessed likely range of equilibrium climate sensitivity(ECS)and the climatological precipitation performance,the authors constrain the CMIP6(phase 6 of the Coupled Model Intercomparison Project)model projection of summer precipitation and water availability over the TP.The best estimates of precipitation changes are 0.24,0.25,and 0.45 mm d^(−1)(5.9%,6.1%,and 11.2%)under the Shared Socioeconomic Pathway(SSP)scenarios of SSP1–2.6,SSP2–4.5,and SSP5–8.5 from 2050–2099 relative to 1965–2014,respectively.The corresponding constrained projections of water availability measured by precipitation minus evaporation(P–E)are 0.10,0.09,and 0.22 mm d^(−1)(5.7%,4.9%,and 13.2%),respectively.The increase of precipitation and P–E projected by the high-ECS models,whose ECS values are higher than the upper limit of the likely range,are about 1.7 times larger than those estimated by constrained projections.Spatially,there is a larger increase in precipitation and P–E over the eastern TP,while the western part shows a relatively weak difference in precipitation and a drier trend in P–E.The wetter TP projected by the high-ECS models resulted from both an approximately 1.2–1.4 times stronger hydrological sensitivity and additional warming of 0.6℃–1.2℃ under all three scenarios during 2050–2099.This study emphasizes that selecting climate models with climate sensitivity within the likely range is crucial to reducing the uncertainty in the projection of TP precipitation and water availability changes.
基金financed by the National Basic Research Program of China (Grant No. 2010CB428502)the National Natural Science Foundation of China (Grant No. 40925015)
文摘A statistical regression downscaling method was used to project future changes in precipitation over eastern China based on Phase 5 of the Coupled Model Intercomparison Project (CMIPS) the Representative Concentration Pathway (RCP) scenarios simulated by the second spectral version of the Flexible Global Ocean- Atmosphere-Land System (FGOALS-s2) model. Our val- idation results show that the downscaled time series agree well with the present observed precipitation in terms of both the annual mean and the seasonal cycle. The regres- sion models built from the historical data are then used to generate future projections. The results show that the en- hanced land-sea thermal contrast strengthens both the subtropical anticyclone over the western Pacific and the east Asian summer monsoon flow under both RCPs. However, the trend of precipitation in response to warming over the 21 st century are different across eastern Chi- na under different RCPs. The area to the north of 32°N is likely to experience an increase in annual mean precipitation, while for the area between 23°N and 32°N mean precipitation is projected to decrease slightly over this century under RCP8.5. The change difference between scenarios mainly exists in the middle and late century. The land-sea thermal contrast and the associated east Asian summer monsoon flow are stronger, such that precipitation increases more, at higher latitudes under RCP8.5 compared to under RCP4.5. For the region south of 32°N, rainfall is projected to increase slightly under RCP4.5 but decrease under RCP8.5 in the late century. At the high resolution of 5 km, our statistically downscaled results for projected precipitation can be used to force hydrological models to project hydrological processes, which will be of great benefit to regional water planning and management.
文摘The present study has generated and analyzed Climate Change projections in Nicaragua for the period 2010-2040. The obtained results are to be used for evaluating and planning more resilient transport infrastructures in the next decades. This study has focused its efforts to pay attention into the effect of Climate Change on precipitation and temperature from a mean and extreme event perspective. Dynamical Downscaling approach on a 4 km resolution grid has been chosen as the most appropriate methodology for the estimation of the projected climate, being able to account for local-scale factors like complex topography or local land uses properly. We selected MPI-ESM-MR as the global climate model with the best skill scores in terms of precipitation and temperature in Nicaragua. MPI-ESM-MR was coupled to a mesoscale model. We chose WRF mesoescale model as the most appropriate regional model and we optimized their physical and dynamical options in order to minimize the model uncertainty in Nicaragua. For this, model output against the available in-situ measurements from the national meteorological station network and satellite data were compared. Climate change signal was estimated by comparing the different climate statistics calculated from a model run over an historical period, 1980-2009, with a model run over a projected period, 2010-2040. The obtained results from the projected climate show an increase of the mean temperature between 0.6°C and 0.8°C and an increase of the number of days per year with maximum daily temperatures higher than 35°C. Regarding precipitation, annual projected amounts do not change remarkably with respect to the historical period. However, significant changes in the distribution of the precipitation within the wet period (May-October) were observed. Moreover, an increment between 5% and 10% of the number of days without precipitation is expected. Finally, Intensity-Duration-Frequency (IDF) projected curves show an increment of the rainfall intensity and an increment of extreme precipitation event frequency, especially in the Caribbean basin.
基金the model data,and the support from Li Chongyin Academician Workstation of Yunnan province.This work was supported by the National Natural Science Foundation of China(U1902209)the Chinese Academy of Sciences and the Key Science Foundation of Yunnan Province(2016FA041)+1 种基金the External Cooperation Program of Bureau of International Cooperation(GJHZ1729)the Science and Technology Project of SGCC(State Grid Corporation of China)[Research and application of multi-spatial scale variation of photovoltaic output characteristics considering complex factors such as cloud and floating dust](NY71-19-013).
文摘In the Lancang‒Mekong River basin(LMRB),agriculture,dominating the local economy,faces increasing challenges in water supply under climate change.The projection of future precipitation in this basin is essential for understanding the challenges.In this study,the Weather Research and Forecasting(WRF)model was applied to project the LMRB precipitation.Comparing with the historical period(1986e2005),we analyzed the changes of both the projected precipitation amount and the frequency of rainless(<0.1 mm d1),light rain(0.1e10 mm d1),moderate rain(10e25 mm d1),heavy rain(25e50 mm d1),rainstorm(50e100 mm d1),and heavy rainstorm(>100 mm d1)for three periods,namely the near-term(2016e2035),mid-term(2046e2065),and long-term(2080e2099).The results indicate that the precipitation amount during the wet season(AprileOctober)is expected to increase in most areas of the basin for the three periods.As for the precipitation during the dry season(NovembereMarch),an increase is projected in most areas for the near-term,while an increase in the lower reach of the basin and a decrease in the upper and middle reach for the mid-term and long-term.The precipitation reduction is expected to be greatest in Myanmar,Laos,Thailand,and Yunnan province of China for the mid-term.The frequency of precipitation in different intensities has prominent regional and temporal differences.During the wet season,the days of rainless and light rain are expected to decrease in the middle reach,whereas the days of rainstorm and heavy rainstorm increase.This feature is especially strong in southern Thailand,southern Laos and Cambodia in the near-term and in Laos and Thailand for the mid-term and long-term.During the dry season,there are projected increasing rainless days and decreasing days of precipitation for the other intensities in the middle reach,and opposite in the rest area of the basin.These projected precipitation changes have potential various impact in different parts of the basin.The middle reach would likely face increasing flood risks because of more days of rainstorm and heavy rainstorm,as well as more precipitation.Yunnan,Myanmar,Thailand and Laos would probably be the center of drought threatens during the dry season due to the increment of rainless days and the precipitation reduction.Besides,the seawater intrusion during the dry season in the near-term and mid-term would be more serious as a result of the precipitation decrease in southern Vietnam.
文摘This study examines the inter-annual variability of rainfall and Mean Sea Level Pressure (</span><span style="font-family:Verdana;">M</span><span style="font-family:Verdana;">SLP) over west Africa based on analysis of the Global Precipitation</span><span style="font-family:""><span style="font-family:Verdana;"> Climatology Project (GPCP) and National Center for Environmental Prediction/National Center for Atmospheric Research (NCEP/NCAR) Reanalysis respectively. An interconnection is found in this region, between Mean Sea Level Pressure (MSLP) anomaly (over Azores and St. Helena High) and monthly mean precipitation during summer (June to September: JJAS). We also found that over northern Senegal (15</span><span style="white-space:nowrap;font-family:Verdana;">°</span><span style="font-family:Verdana;">N</span></span><span style="font-family:""> </span><span style="font-family:Verdana;">-</span><span style="font-family:""> </span><span style="font-family:""><span style="font-family:Verdana;">17</span><span style="white-space:nowrap;font-family:Verdana;">°</span><span style="font-family:Verdana;">N;17</span><span style="white-space:nowrap;font-family:Verdana;">°</span><span style="font-family:Verdana;">W</span></span><span style="font-family:""> </span><span style="font-family:Verdana;">-</span><span style="font-family:""> </span><span style="font-family:""><span style="font-family:Verdana;">13</span><span style="white-space:nowrap;font-family:Verdana;">°</span><span style="font-family:Verdana;"></span><span style="font-family:Verdana;">W) the SLP to the north is strong;the wind converges at 200</span></span><span style="font-family:""> </span><span style="font-family:Verdana;">hPa corresponding to the position of the African Easterly Jet (AEJ) the rotational wind 700</span><span style="font-family:""> </span><span style="font-family:""><span style="font-family:Verdana;">hPa (corresponding to the position of the African Easterly Jet (AEJ) coming from the north-east is negative. In this region, the precipitation is related to the SLP to the north with the opposite sign. The Empirical Orthogonal Functions (EOF) of SLP is also presented, including the mean spectrum of precipitation and pressures to the north (15</span><span style="white-space:nowrap;font-family:Verdana;">°</span><span style="font-family:Verdana;">N</span></span><span style="font-family:""> </span><span style="font-family:Verdana;">-</span><span style="font-family:""> </span><span style="font-family:""><span style="font-family:Verdana;">40</span><span style="white-space:nowrap;font-family:Verdana;">°</span><span style="font-family:Verdana;">N and 50</span><span style="white-space:nowrap;font-family:Verdana;">°</span><span style="font-family:Verdana;">W</span></span><span style="font-family:""> </span><span style="font-family:Verdana;">-</span><span style="font-family:""> </span><span style="font-family:""><span style="font-family:Verdana;">25</span><span style="white-space:nowrap;font-family:Verdana;">°</span><span style="font-family:Verdana;">W) and south (40</span><span style="white-space:nowrap;font-family:Verdana;">°</span><span style="font-family:Verdana;">S</span></span><span style="font-family:""> </span><span style="font-family:Verdana;">-</span><span style="font-family:""> </span><span style="font-family:""><span style="font-family:Verdana;">10</span><span style="white-space:nowrap;font-family:Verdana;">°</span><span style="font-family:Verdana;">S and 40</span><span style="white-space:nowrap;font-family:Verdana;">°</span><span style="font-family:Verdana;">W</span></span><span style="font-family:""> </span><span style="font-family:Verdana;">-</span><span style="font-family:""> </span><span style="font-family:""><span style="font-family:Verdana;">0</span><span style="white-space:nowrap;font-family:Verdana;">°</span><span style="font-family:Verdana;">E). The dominant EOF of Sea Level Pressures north and south of the Atlantic Ocean for GPCP represents about 62.2% and 69.4% of the variance, respectively. The second and third EOFs of the pressure to the north account for 24.0% and 6.5% respectively. The second and third EOFs of the pressure to the south represent 12.5% and 8.9% respectively. Wet years in the north of Senegal were associated with anomalous low-pressure areas over the north Atlantic Ocean as opposed to the dry years which exhibited an anomalous high-pressure area in the same region. On the other hand, over the South Atlantic, an opposition is noted. The wavelet analysis method is applied to the SLP showings to the north, south and precipitation in our study area. The indices prove to be very consistent, especially during intervals of high variance.
基金Supported by Grants of NKBRDPC (No.2004CB418304),NSFC grant of the Joint Research Fund for Overseas Chinese Young Scholars (No.40428006),NSFC (Nos.40175015 and 40375018).
文摘The Global Precipitation Climatology Project (GPCP) monthly rainfall data and the rainfall records observed by 740 rain gauges in the mainland of China are used to analyze similarities and differences of the precipitation in China in the period from January 1980 to December 2000. Results expose significantly consistent rainfall distributions between the both data in multi-year mean, multi-year seasonal mean, and multi-year monthly mean. Departures of monthly rainfall for each dataset also show a high correlation with an over 0.8 correlation coefficient. Analysis indicates small differences of both datasets during autumn, winter, and spring, but relative large ones in summer. Generally, the GPCP has trend of overestimating the rainfall rate. Based on above good relationship of both datasets, the GPCP data, are used to represent distributions and variations of precipitation in the Tibetan Plateau and Northwest China. Results indicate positive departures of precipitation in summer in the west part of Tibetan Plateau in the 1980s and negative departures after the 1980s. For the west part of Northwest China, analysis illustrates precipitation decreases a little, but no clear variation tendency.