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- Author or Editor: Jiangfeng Wei x
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Abstract
This study examines a lagged soil moisture–precipitation (S–P) correlation for 24 yr of boreal summer (1979–2002) from the 40-yr ECMWF Re-Analysis (ERA-40), the NCEP–Department of Energy (DOE) reanalysis 2 (R-2), the North American Regional Reanalysis (NARR), 10 yr (1986–95) of data from phase 2 of the Global Soil Wetness Project (GSWP-2), and two 24-yr model simulations with the NCAR Community Atmosphere Model version 3.1 (CAM3). The different datasets and model simulations all show a similar negative-dominant S–P correlation pattern with wet areas having more significantly negative correlations than the dry areas. The experiments with CAM3 show that this correlation pattern is not caused by the soil moisture feedback. Rather, the combined effect of the precipitation variability and the memory of soil moisture is the main reason for this correlation pattern. Theoretical analysis confirms this conclusion and shows that the correlation pattern is related to both the precipitation spectrum and the time scale of soil moisture retention. This study suggests that the attribution of lagged correlations of precipitation with soil moisture or related variables should be done cautiously.
Abstract
This study examines a lagged soil moisture–precipitation (S–P) correlation for 24 yr of boreal summer (1979–2002) from the 40-yr ECMWF Re-Analysis (ERA-40), the NCEP–Department of Energy (DOE) reanalysis 2 (R-2), the North American Regional Reanalysis (NARR), 10 yr (1986–95) of data from phase 2 of the Global Soil Wetness Project (GSWP-2), and two 24-yr model simulations with the NCAR Community Atmosphere Model version 3.1 (CAM3). The different datasets and model simulations all show a similar negative-dominant S–P correlation pattern with wet areas having more significantly negative correlations than the dry areas. The experiments with CAM3 show that this correlation pattern is not caused by the soil moisture feedback. Rather, the combined effect of the precipitation variability and the memory of soil moisture is the main reason for this correlation pattern. Theoretical analysis confirms this conclusion and shows that the correlation pattern is related to both the precipitation spectrum and the time scale of soil moisture retention. This study suggests that the attribution of lagged correlations of precipitation with soil moisture or related variables should be done cautiously.
Abstract
The Global Land–Atmosphere Coupling Experiment (GLACE) built a framework to estimate the strength of the land–atmosphere interaction across many weather and climate models. Within this framework, GLACE-type experiments are performed with a single atmospheric model coupled to three different land models. The precipitation time series is decomposed into three frequency bands to investigate the large-scale connection between external forcing, precipitation variability and predictability, and land–atmosphere coupling strength. It is found that coupling to different land models or prescribing subsurface soil moisture does not change the global pattern of precipitation predictability and variability too much. However, the regional impact of soil moisture can be highlighted by calculating the land–atmosphere coupling strength, which shows very different patterns for the three models. The estimated precipitation predictability and land–atmosphere coupling strength is mainly associated with the low-frequency component of precipitation (periods beyond 3 weeks). Based on these findings, the land–atmosphere coupling strength is conceptually decomposed into the impact of low-frequency external forcing and the impact of soil moisture. Because most models participating in GLACE have overestimated the low-frequency component of precipitation, a calibration to the GLACE-estimated land–atmosphere coupling strength is performed. The calibrated coupling strength is generally weaker, but the global pattern does not change much. This study provides an important clarification of land–atmosphere coupling strength and increases the understanding of the land–atmosphere interaction.
Abstract
The Global Land–Atmosphere Coupling Experiment (GLACE) built a framework to estimate the strength of the land–atmosphere interaction across many weather and climate models. Within this framework, GLACE-type experiments are performed with a single atmospheric model coupled to three different land models. The precipitation time series is decomposed into three frequency bands to investigate the large-scale connection between external forcing, precipitation variability and predictability, and land–atmosphere coupling strength. It is found that coupling to different land models or prescribing subsurface soil moisture does not change the global pattern of precipitation predictability and variability too much. However, the regional impact of soil moisture can be highlighted by calculating the land–atmosphere coupling strength, which shows very different patterns for the three models. The estimated precipitation predictability and land–atmosphere coupling strength is mainly associated with the low-frequency component of precipitation (periods beyond 3 weeks). Based on these findings, the land–atmosphere coupling strength is conceptually decomposed into the impact of low-frequency external forcing and the impact of soil moisture. Because most models participating in GLACE have overestimated the low-frequency component of precipitation, a calibration to the GLACE-estimated land–atmosphere coupling strength is performed. The calibrated coupling strength is generally weaker, but the global pattern does not change much. This study provides an important clarification of land–atmosphere coupling strength and increases the understanding of the land–atmosphere interaction.
Abstract
The seasonal responses of the Indian summer monsoon (ISM) to dust aerosols in local (the Thar Desert) and remote (the Middle East and western China) regions are studied using the WRF Model coupled with online chemistry (WRF-Chem). Ensemble experiments are designed by perturbing model physical and chemical schemes to examine the uncertainties of model parameterizations. Model results show that the dust-induced increase in ISM total rainfall can be attributed to the remote dust in the Middle East, while the contributions from local and remote dust are very limited. Convective rainfall shows a spatially more homogeneous increase than stratiform rainfall, whose responses follow the topography. The magnitude of dust-induced increase in rainfall is comparable to that caused by anthropogenic aerosols. The Middle East dust aerosols tend to enhance the southwesterly monsoon flow, which can transport more water vapor to southern and northern India, while the anthropogenic aerosols tend to enhance the southeasterly monsoon flow, resulting in more water vapor and rainfall over northern India. Both dust and anthropogenic aerosol-induced rainfall responses can be attributed to their heating effect in the mid-to-upper troposphere, which enhances monsoon circulations. The heating effect of dust over the Iranian Plateau seems to play a bigger role than that over the Tibetan Plateau, while the heating of anthropogenic aerosols over the Tibetan Plateau is more important. Moreover, dust aerosols can decrease rainfall over the Arabian Sea through their indirect effect. This study addresses the relative roles of dust and anthropogenic aerosols in altering the ISM rainfall and provides insights into aerosol–ISM interactions.
Abstract
The seasonal responses of the Indian summer monsoon (ISM) to dust aerosols in local (the Thar Desert) and remote (the Middle East and western China) regions are studied using the WRF Model coupled with online chemistry (WRF-Chem). Ensemble experiments are designed by perturbing model physical and chemical schemes to examine the uncertainties of model parameterizations. Model results show that the dust-induced increase in ISM total rainfall can be attributed to the remote dust in the Middle East, while the contributions from local and remote dust are very limited. Convective rainfall shows a spatially more homogeneous increase than stratiform rainfall, whose responses follow the topography. The magnitude of dust-induced increase in rainfall is comparable to that caused by anthropogenic aerosols. The Middle East dust aerosols tend to enhance the southwesterly monsoon flow, which can transport more water vapor to southern and northern India, while the anthropogenic aerosols tend to enhance the southeasterly monsoon flow, resulting in more water vapor and rainfall over northern India. Both dust and anthropogenic aerosol-induced rainfall responses can be attributed to their heating effect in the mid-to-upper troposphere, which enhances monsoon circulations. The heating effect of dust over the Iranian Plateau seems to play a bigger role than that over the Tibetan Plateau, while the heating of anthropogenic aerosols over the Tibetan Plateau is more important. Moreover, dust aerosols can decrease rainfall over the Arabian Sea through their indirect effect. This study addresses the relative roles of dust and anthropogenic aerosols in altering the ISM rainfall and provides insights into aerosol–ISM interactions.
Abstract
The sensitivity of hourly precipitation to cumulus parameterization and radiation schemes is explored by using the tropical-belt configuration of the Weather Research and Forecasting (WRF) Model. The domain covers the entire tropical region from 45°S to 45°N with a grid spacing of about 45 km. A series of 5-yr simulations with four cumulus parameterization schemes [new Tiedtke (NT), Kain–Fritsch (KF), new SAS (NS), and Tiedtke (TK)] and two radiation schemes (RRTMG and CAM) are carried out. We focus on the frequencies of hourly precipitation above three thresholds (0.02 mm h−1 = light drizzle rate; 0.2 mm h−1 = moderate rate; and 2 mm h−1 = heavy rate) between the observed CMORPH products and simulations. The sensitivity is higher for precipitation frequency than amount, and frequency is dominated by the cumulus parameterization. Frequencies above the moderate rate are well reproduced, whereas frequencies above the other two rates present large deviations. No combination of physical schemes is found to perform best in reproducing the frequencies above all thresholds. Simulations using the NT and NS schemes show higher precipitation frequencies above the light drizzle rate and lower precipitation frequencies above the heavy rate than those simulations using the KF and TK schemes. Precipitation frequency is higher when reproduced by experiments using the RRTMG scheme than those using the CAM scheme, except for frequencies above the light rate over oceans. The overestimation of frequency is mainly caused by too-frequent convective rainfall. The results imply that the triggering based on the vertical velocity may increase the occurrence of a rain event and that CAPE-based closure may increase the heavy precipitation frequency in the cumulus parameterization.
Abstract
The sensitivity of hourly precipitation to cumulus parameterization and radiation schemes is explored by using the tropical-belt configuration of the Weather Research and Forecasting (WRF) Model. The domain covers the entire tropical region from 45°S to 45°N with a grid spacing of about 45 km. A series of 5-yr simulations with four cumulus parameterization schemes [new Tiedtke (NT), Kain–Fritsch (KF), new SAS (NS), and Tiedtke (TK)] and two radiation schemes (RRTMG and CAM) are carried out. We focus on the frequencies of hourly precipitation above three thresholds (0.02 mm h−1 = light drizzle rate; 0.2 mm h−1 = moderate rate; and 2 mm h−1 = heavy rate) between the observed CMORPH products and simulations. The sensitivity is higher for precipitation frequency than amount, and frequency is dominated by the cumulus parameterization. Frequencies above the moderate rate are well reproduced, whereas frequencies above the other two rates present large deviations. No combination of physical schemes is found to perform best in reproducing the frequencies above all thresholds. Simulations using the NT and NS schemes show higher precipitation frequencies above the light drizzle rate and lower precipitation frequencies above the heavy rate than those simulations using the KF and TK schemes. Precipitation frequency is higher when reproduced by experiments using the RRTMG scheme than those using the CAM scheme, except for frequencies above the light rate over oceans. The overestimation of frequency is mainly caused by too-frequent convective rainfall. The results imply that the triggering based on the vertical velocity may increase the occurrence of a rain event and that CAPE-based closure may increase the heavy precipitation frequency in the cumulus parameterization.
Abstract
Under the background of global warming, the Eurasian warming features evident spatial heterogeneity, and Northeast Asia (NEA) is one of the regions with the most significant summer warming. Based on reanalysis data and the CESM1.2.2 model, we investigated the possible impacts of spring Eurasian snowmelt on recent NEA summer warming and the relevant mechanisms. Results show that increased (decreased) spring snowmelt over eastern Europe to western Siberia (EEWS) is closely linked to NEA summer warming (cooling). Increased spring snowmelt can wet the soil, weakening surface sensible heating to the atmosphere and cooling the atmosphere. The persistent anomalous soil moisture and surface sensible heat induce geopotential height decrease over EEWS and strengthen the eastward-propagating wave train. Furthermore, positive geopotential height anomalies appear in downstream NEA in summer via the adjustment of the atmospheric circulation. Controlled by the anomalous high pressure system, the west part of NEA is affected by the southerly warm advection, while the east is affected by adiabatic warming induced by the dominant descending motion. Meanwhile, decreased cloud and increased incident solar radiation over NEA favor summer land surface warming. Model results suggest that CESM1.2.2 can basically reproduce the positive correlation between NEA summer land surface temperature and EEWS spring snowmelt. With the positive spring snowmelt forcing, the simulated positive soil moisture and negative sensible heat anomalies persist from spring to summer over EEWS. Consequently, negative geopotential height anomalies appear over the snowmelt region while positive anomalies occur around Lake Baikal, resulting in evident NEA land surface warming.
Abstract
Under the background of global warming, the Eurasian warming features evident spatial heterogeneity, and Northeast Asia (NEA) is one of the regions with the most significant summer warming. Based on reanalysis data and the CESM1.2.2 model, we investigated the possible impacts of spring Eurasian snowmelt on recent NEA summer warming and the relevant mechanisms. Results show that increased (decreased) spring snowmelt over eastern Europe to western Siberia (EEWS) is closely linked to NEA summer warming (cooling). Increased spring snowmelt can wet the soil, weakening surface sensible heating to the atmosphere and cooling the atmosphere. The persistent anomalous soil moisture and surface sensible heat induce geopotential height decrease over EEWS and strengthen the eastward-propagating wave train. Furthermore, positive geopotential height anomalies appear in downstream NEA in summer via the adjustment of the atmospheric circulation. Controlled by the anomalous high pressure system, the west part of NEA is affected by the southerly warm advection, while the east is affected by adiabatic warming induced by the dominant descending motion. Meanwhile, decreased cloud and increased incident solar radiation over NEA favor summer land surface warming. Model results suggest that CESM1.2.2 can basically reproduce the positive correlation between NEA summer land surface temperature and EEWS spring snowmelt. With the positive spring snowmelt forcing, the simulated positive soil moisture and negative sensible heat anomalies persist from spring to summer over EEWS. Consequently, negative geopotential height anomalies appear over the snowmelt region while positive anomalies occur around Lake Baikal, resulting in evident NEA land surface warming.
Abstract
The operational coupled land–atmosphere forecast model from the National Centers for Environmental Prediction (NCEP) is evaluated for the strength and characteristics of its coupling in the water cycle between land and atmosphere. Following the protocols of the Global Land–Atmosphere Coupling Experiment (GLACE) it is found that the Global Forecast System (GFS) atmospheric model coupled to the Noah land surface model exhibits extraordinarily weak land–atmosphere coupling, much as its predecessor, the GFS–Oregon State University (OSU) coupled system. The coupling strength is evaluated by the ability of subsurface soil wetness to affect locally the time series of precipitation. The surface fluxes in Noah are also found to be rather insensitive to subsurface soil wetness. Comparison to another atmospheric model coupled to Noah as well as a different land surface model show that Noah is responsible for some of the lack of sensitivity, primarily because its thick (10 cm) surface layer dominates the variability in surface latent heat fluxes. Noah is found to be as responsive as other land surface models to surface soil wetness and temperature variations, suggesting the design of the GLACE sensitivity experiment (based only on subsurface soil wetness) handicapped the Noah model. Additional experiments, in which the parameterization of evapotranspiration is altered, as well as experiments where surface soil wetness is also constrained, isolate the GFS atmospheric model as the principal source of the weak sensitivity of precipitation to land surface states.
Abstract
The operational coupled land–atmosphere forecast model from the National Centers for Environmental Prediction (NCEP) is evaluated for the strength and characteristics of its coupling in the water cycle between land and atmosphere. Following the protocols of the Global Land–Atmosphere Coupling Experiment (GLACE) it is found that the Global Forecast System (GFS) atmospheric model coupled to the Noah land surface model exhibits extraordinarily weak land–atmosphere coupling, much as its predecessor, the GFS–Oregon State University (OSU) coupled system. The coupling strength is evaluated by the ability of subsurface soil wetness to affect locally the time series of precipitation. The surface fluxes in Noah are also found to be rather insensitive to subsurface soil wetness. Comparison to another atmospheric model coupled to Noah as well as a different land surface model show that Noah is responsible for some of the lack of sensitivity, primarily because its thick (10 cm) surface layer dominates the variability in surface latent heat fluxes. Noah is found to be as responsive as other land surface models to surface soil wetness and temperature variations, suggesting the design of the GLACE sensitivity experiment (based only on subsurface soil wetness) handicapped the Noah model. Additional experiments, in which the parameterization of evapotranspiration is altered, as well as experiments where surface soil wetness is also constrained, isolate the GFS atmospheric model as the principal source of the weak sensitivity of precipitation to land surface states.
Abstract
A quasi-isentropic, back-trajectory scheme is applied to output from the Modern-Era Retrospective Analysis for Research and Applications (MERRA) and a land-only replay with corrected precipitation to estimate surface evaporative sources of moisture supplying precipitation over every ice-free land location for the period 1979–2005. The evaporative source patterns for any location and time period are effectively two-dimensional probability distributions. As such, the evaporative sources for extreme situations like droughts or wet intervals can be compared to the corresponding climatological distributions using the method of relative entropy. Significant differences are found to be common and widespread for droughts, but not wet periods, when monthly data are examined. At pentad temporal resolution, which is more able to isolate floods and situations of atmospheric rivers, values of relative entropy over North America are typically 50%–400% larger than at monthly time scales. Significant differences suggest that moisture transport may be a key factor in precipitation extremes. Where evaporative sources do not change significantly, it implies other local causes may underlie the extreme events.
Abstract
A quasi-isentropic, back-trajectory scheme is applied to output from the Modern-Era Retrospective Analysis for Research and Applications (MERRA) and a land-only replay with corrected precipitation to estimate surface evaporative sources of moisture supplying precipitation over every ice-free land location for the period 1979–2005. The evaporative source patterns for any location and time period are effectively two-dimensional probability distributions. As such, the evaporative sources for extreme situations like droughts or wet intervals can be compared to the corresponding climatological distributions using the method of relative entropy. Significant differences are found to be common and widespread for droughts, but not wet periods, when monthly data are examined. At pentad temporal resolution, which is more able to isolate floods and situations of atmospheric rivers, values of relative entropy over North America are typically 50%–400% larger than at monthly time scales. Significant differences suggest that moisture transport may be a key factor in precipitation extremes. Where evaporative sources do not change significantly, it implies other local causes may underlie the extreme events.
Abstract
An atmospheric general circulation model (AGCM) is coupled to three different land surface schemes (LSSs), both individually and in combination (i.e., the LSSs receive the same AGCM forcing each time step and the averaged upward surface fluxes are passed back to the AGCM), to study the uncertainty of simulated climatologies and variabilities caused by different LSSs. This tiling of the LSSs is done to study the uncertainty of simulated mean climate and climate variability caused by variations between LSSs. The three LSSs produce significantly different surface fluxes over most of the land, no matter whether they are coupled individually or in combination. Although the three LSSs receive the same atmospheric forcing in the combined experiment, the inter-LSS spread of latent heat flux can be larger or smaller than the individually coupled experiment, depending mostly on the evaporation regime of the schemes in different regions. Differences in precipitation are the main reason for the different latent heat fluxes over semiarid regions, but for sensible heat flux, the atmospheric differences and LSS differences have comparable contributions. The influence of LSS uncertainties on the simulation of surface temperature is strongest in dry seasons, and its influence on daily maximum temperature is stronger than on minimum temperature. Land–atmosphere interaction can dampen the impact of LSS uncertainties on surface temperature in the tropics, but can strengthen their impact in middle to high latitudes. Variations in the persistence of surface heat fluxes exist among the LSSs, which, however, have little impact on the global pattern of precipitation persistence. The results provide guidance to future diagnosis of model uncertainties related to LSSs.
Abstract
An atmospheric general circulation model (AGCM) is coupled to three different land surface schemes (LSSs), both individually and in combination (i.e., the LSSs receive the same AGCM forcing each time step and the averaged upward surface fluxes are passed back to the AGCM), to study the uncertainty of simulated climatologies and variabilities caused by different LSSs. This tiling of the LSSs is done to study the uncertainty of simulated mean climate and climate variability caused by variations between LSSs. The three LSSs produce significantly different surface fluxes over most of the land, no matter whether they are coupled individually or in combination. Although the three LSSs receive the same atmospheric forcing in the combined experiment, the inter-LSS spread of latent heat flux can be larger or smaller than the individually coupled experiment, depending mostly on the evaporation regime of the schemes in different regions. Differences in precipitation are the main reason for the different latent heat fluxes over semiarid regions, but for sensible heat flux, the atmospheric differences and LSS differences have comparable contributions. The influence of LSS uncertainties on the simulation of surface temperature is strongest in dry seasons, and its influence on daily maximum temperature is stronger than on minimum temperature. Land–atmosphere interaction can dampen the impact of LSS uncertainties on surface temperature in the tropics, but can strengthen their impact in middle to high latitudes. Variations in the persistence of surface heat fluxes exist among the LSSs, which, however, have little impact on the global pattern of precipitation persistence. The results provide guidance to future diagnosis of model uncertainties related to LSSs.
Abstract
Previous studies detected significant negative correlations between the nonuniform land surface warming and the decadal weakened activities of the summer extratropical cyclones (ECs) over East Asia and the East Asian summer monsoon (EASM) after the early 1990s. Here such relationships are further examined and the possible mechanisms are explored via numerical sensitivity experiments with a regional climate model (RegCM4.5). The positive/negative sensible heat flux (SH) anomalies were added as a forcing to a key region near 50°N of East Asia in RegCM4.5 to simulate the observed ground surface temperature (GST) anomalies. The model results suggest that the nonuniform land surface warming over the Lake Baikal area (50°–60°N, 90°–120°E) can indeed cause the weakening of the extratropical cyclogenesis and affect the decadal weakening of the EASM. Warm (cold) GST forcing over the key GST region can lead to decreasing (increasing) atmospheric baroclinicity and related energy conversion of the EC activity over the key EC region (40°–50°N, 90°–120°E), resulting in an evidently weakening (enhancing) of the ECs over East Asia. Meanwhile, precipitation shows a dipole pattern with significantly suppressed (enhanced) precipitation in northern and northeastern China, and slightly enhanced (suppressed) rainfall south of 40°N of East Asia, mainly over the East China Sea. Lake Baikal and its adjacent areas are occupied by a strong anticyclonic (cyclonic) circulation while the southeast coastal areas of China have a relatively weak cyclonic (anticyclonic) circulation accompanied with an anomalous northeasterly (southwesterly) wind to the southeast of the anticyclonic circulation, which is opposite to (coincident with) the atmospheric circulation anomalies that are associated with the second mode of the EASM.
Abstract
Previous studies detected significant negative correlations between the nonuniform land surface warming and the decadal weakened activities of the summer extratropical cyclones (ECs) over East Asia and the East Asian summer monsoon (EASM) after the early 1990s. Here such relationships are further examined and the possible mechanisms are explored via numerical sensitivity experiments with a regional climate model (RegCM4.5). The positive/negative sensible heat flux (SH) anomalies were added as a forcing to a key region near 50°N of East Asia in RegCM4.5 to simulate the observed ground surface temperature (GST) anomalies. The model results suggest that the nonuniform land surface warming over the Lake Baikal area (50°–60°N, 90°–120°E) can indeed cause the weakening of the extratropical cyclogenesis and affect the decadal weakening of the EASM. Warm (cold) GST forcing over the key GST region can lead to decreasing (increasing) atmospheric baroclinicity and related energy conversion of the EC activity over the key EC region (40°–50°N, 90°–120°E), resulting in an evidently weakening (enhancing) of the ECs over East Asia. Meanwhile, precipitation shows a dipole pattern with significantly suppressed (enhanced) precipitation in northern and northeastern China, and slightly enhanced (suppressed) rainfall south of 40°N of East Asia, mainly over the East China Sea. Lake Baikal and its adjacent areas are occupied by a strong anticyclonic (cyclonic) circulation while the southeast coastal areas of China have a relatively weak cyclonic (anticyclonic) circulation accompanied with an anomalous northeasterly (southwesterly) wind to the southeast of the anticyclonic circulation, which is opposite to (coincident with) the atmospheric circulation anomalies that are associated with the second mode of the EASM.
Abstract
Irrigation is an important human activity that may impact local and regional climate, but current climate model simulations and data assimilation systems generally do not explicitly include it. The European Centre for Medium-Range Weather Forecasts (ECMWF) Interim Re-Analysis (ERA-Interim) shows more irrigation signal in surface evapotranspiration (ET) than the Modern-Era Retrospective Analysis for Research and Applications (MERRA) because ERA-Interim adjusts soil moisture according to the observed surface temperature and humidity while MERRA has no explicit consideration of irrigation at the surface. But, when compared with the results from a hydrological model with detailed considerations of agriculture, the ET from both reanalyses show large deficiencies in capturing the impact of irrigation. Here, a back-trajectory method is used to estimate the contribution of irrigation to precipitation over local and surrounding regions, using MERRA with observation-based corrections and added irrigation-caused ET increase from the hydrological model. Results show substantial contributions of irrigation to precipitation over heavily irrigated regions in Asia, but the precipitation increase is much less than the ET increase over most areas, indicating that irrigation could lead to water deficits over these regions. For the same increase in ET, precipitation increases are larger over wetter areas where convection is more easily triggered, but the percentage increase in precipitation is similar for different areas. There are substantial regional differences in the patterns of irrigation impact, but, for all the studied regions, the highest percentage contribution to precipitation is over local land.
Abstract
Irrigation is an important human activity that may impact local and regional climate, but current climate model simulations and data assimilation systems generally do not explicitly include it. The European Centre for Medium-Range Weather Forecasts (ECMWF) Interim Re-Analysis (ERA-Interim) shows more irrigation signal in surface evapotranspiration (ET) than the Modern-Era Retrospective Analysis for Research and Applications (MERRA) because ERA-Interim adjusts soil moisture according to the observed surface temperature and humidity while MERRA has no explicit consideration of irrigation at the surface. But, when compared with the results from a hydrological model with detailed considerations of agriculture, the ET from both reanalyses show large deficiencies in capturing the impact of irrigation. Here, a back-trajectory method is used to estimate the contribution of irrigation to precipitation over local and surrounding regions, using MERRA with observation-based corrections and added irrigation-caused ET increase from the hydrological model. Results show substantial contributions of irrigation to precipitation over heavily irrigated regions in Asia, but the precipitation increase is much less than the ET increase over most areas, indicating that irrigation could lead to water deficits over these regions. For the same increase in ET, precipitation increases are larger over wetter areas where convection is more easily triggered, but the percentage increase in precipitation is similar for different areas. There are substantial regional differences in the patterns of irrigation impact, but, for all the studied regions, the highest percentage contribution to precipitation is over local land.
