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Abstract
Frozen soil distributed over alpine cold regions causes obvious changes in the soil hydrothermal regime and influences the water–heat exchanges between land and atmosphere. In this study, by comparing the effects of snow cover anomalies and frozen soil thawing anomalies on the soil hydrothermal regime, the impact of the frozen soil thawing anomalies in spring on precipitation in early summer over the Tibetan Plateau (TP) was investigated via diagnostic analysis and model simulations. The results show that a delay (advance) in the anomalies of frozen soil thawing in spring can induce distinct cold (warm) anomalies in the soil temperature in the eastern TP. These soil temperature cold (warm) anomalies further weaken (enhance) the surface diabatic heating over the mideastern TP; meanwhile, the anomalies in the western TP are inconspicuous. Compared to the albedo effect of snow cover anomalies, impacts of frozen soil thawing anomalies on soil hydrothermal regime and surface diabatic heating can persist longer from April to June. Corresponding to the anomalous delay (advance) of frozen soil thawing, the monsoon cell is weakened (enhanced) over the southern and northern TP, resulting in less (more) water vapor advection over the eastern TP and more (less) water vapor advection over the southwestern TP. This difference in water vapor advection induces a west–east reversed pattern of precipitation anomalies in June over the TP. The results have potential for improving our understanding of the interactions between the cryosphere and climate in cold regions.
Significance Statement
Frozen soil and snow are widely distributed over alpine and high-latitude cold regions, and their feedbacks to climate have attracted much attention. The purpose of this study is to investigate the role of frozen soil in effects of snow cover anomalies on surface diabatic heating and its feedback to subsequent precipitation over the Tibetan Plateau. The results highlight that frozen soil modulates the effect of snow cover anomalies on the soil hydrothermal regime from April to June and interseasonal variations of frozen soil thawing anomaly zones result in a thermal contrast between the western and eastern Tibetan Plateau, which further lead to a reversed pattern of early summer precipitation anomalies over the Tibetan Plateau. These findings emphasize the role of frozen soil in land–atmosphere interactions.
Abstract
Frozen soil distributed over alpine cold regions causes obvious changes in the soil hydrothermal regime and influences the water–heat exchanges between land and atmosphere. In this study, by comparing the effects of snow cover anomalies and frozen soil thawing anomalies on the soil hydrothermal regime, the impact of the frozen soil thawing anomalies in spring on precipitation in early summer over the Tibetan Plateau (TP) was investigated via diagnostic analysis and model simulations. The results show that a delay (advance) in the anomalies of frozen soil thawing in spring can induce distinct cold (warm) anomalies in the soil temperature in the eastern TP. These soil temperature cold (warm) anomalies further weaken (enhance) the surface diabatic heating over the mideastern TP; meanwhile, the anomalies in the western TP are inconspicuous. Compared to the albedo effect of snow cover anomalies, impacts of frozen soil thawing anomalies on soil hydrothermal regime and surface diabatic heating can persist longer from April to June. Corresponding to the anomalous delay (advance) of frozen soil thawing, the monsoon cell is weakened (enhanced) over the southern and northern TP, resulting in less (more) water vapor advection over the eastern TP and more (less) water vapor advection over the southwestern TP. This difference in water vapor advection induces a west–east reversed pattern of precipitation anomalies in June over the TP. The results have potential for improving our understanding of the interactions between the cryosphere and climate in cold regions.
Significance Statement
Frozen soil and snow are widely distributed over alpine and high-latitude cold regions, and their feedbacks to climate have attracted much attention. The purpose of this study is to investigate the role of frozen soil in effects of snow cover anomalies on surface diabatic heating and its feedback to subsequent precipitation over the Tibetan Plateau. The results highlight that frozen soil modulates the effect of snow cover anomalies on the soil hydrothermal regime from April to June and interseasonal variations of frozen soil thawing anomaly zones result in a thermal contrast between the western and eastern Tibetan Plateau, which further lead to a reversed pattern of early summer precipitation anomalies over the Tibetan Plateau. These findings emphasize the role of frozen soil in land–atmosphere interactions.
Abstract
With the improvement of meteorological forcings and surface parameters, high-resolution land surface modeling is expected to provide locally relevant information. Yet, its added value over the state-of-the-art global reanalysis products requires long-term evaluations over large areas, given uneven climate warming and significant land cover change. Here, the Conjunctive Surface–Subsurface Process version 2 (CSSPv2) model, with a reasonable representation of runoff generation, subgrid soil moisture variability and urban dynamics, is calibrated and used to perform a 6-km resolution simulation over China during 1979–2017. Evaluations against observations at thousands of stations and several satellite-based products show that the CSSPv2 has 67%, 29%, and 15% lower simulation errors for snow depth, evapotranspiration (ET), and surface and root-zone soil moisture, respectively, than nine global products. The median Kling–Gupta efficiency of the streamflow for 83 river basins is 0.66 after bulk calibrations, which is 0.38 higher than that of global datasets. The CSSPv2 also accurately simulates urban heat islands (UHIs) and the patterns and magnitudes of long-term snow depth, ET, and soil moisture trends. However, the global products do not detect UHIs and overestimate the trends (or show opposite trends) of snow depth and ET. Sensitivity experiments with coarse-resolution forcings and surface parameters reveal that advanced model physics and high-resolution surface parameters are vital for improved simulations of snow depth, ET, soil moisture, and UHIs, whereas high-resolution meteorological forcings are critical for modeling long-term trends. Our research emphasizes the substantial added value of long-term high-resolution land surface modeling to present global products at continental scales.
Significance Statement
Highly heterogeneous changes of terrestrial water and energy require kilometer-scale land surface information for the adaptation. High-resolution land surface modeling has been regarded as a promising approach to provide locally relevant information, but most applications are limited to a small region or a short period. By performing sets of 6-km resolution simulations over China during 1979–2017 with the Conjunctive Surface–Subsurface Process version 2 land model, here we show that high-resolution modeling has 15%–67% lower simulation errors of snow depth, streamflow, evapotranspiration, and soil moisture than nine global products, and the improvement is mainly attributed to the advances in model physical parameterizations and high-resolution surface parameters. Our results emphasize the great added value of kilometer-scale land surface modeling at continental scales.
Abstract
With the improvement of meteorological forcings and surface parameters, high-resolution land surface modeling is expected to provide locally relevant information. Yet, its added value over the state-of-the-art global reanalysis products requires long-term evaluations over large areas, given uneven climate warming and significant land cover change. Here, the Conjunctive Surface–Subsurface Process version 2 (CSSPv2) model, with a reasonable representation of runoff generation, subgrid soil moisture variability and urban dynamics, is calibrated and used to perform a 6-km resolution simulation over China during 1979–2017. Evaluations against observations at thousands of stations and several satellite-based products show that the CSSPv2 has 67%, 29%, and 15% lower simulation errors for snow depth, evapotranspiration (ET), and surface and root-zone soil moisture, respectively, than nine global products. The median Kling–Gupta efficiency of the streamflow for 83 river basins is 0.66 after bulk calibrations, which is 0.38 higher than that of global datasets. The CSSPv2 also accurately simulates urban heat islands (UHIs) and the patterns and magnitudes of long-term snow depth, ET, and soil moisture trends. However, the global products do not detect UHIs and overestimate the trends (or show opposite trends) of snow depth and ET. Sensitivity experiments with coarse-resolution forcings and surface parameters reveal that advanced model physics and high-resolution surface parameters are vital for improved simulations of snow depth, ET, soil moisture, and UHIs, whereas high-resolution meteorological forcings are critical for modeling long-term trends. Our research emphasizes the substantial added value of long-term high-resolution land surface modeling to present global products at continental scales.
Significance Statement
Highly heterogeneous changes of terrestrial water and energy require kilometer-scale land surface information for the adaptation. High-resolution land surface modeling has been regarded as a promising approach to provide locally relevant information, but most applications are limited to a small region or a short period. By performing sets of 6-km resolution simulations over China during 1979–2017 with the Conjunctive Surface–Subsurface Process version 2 land model, here we show that high-resolution modeling has 15%–67% lower simulation errors of snow depth, streamflow, evapotranspiration, and soil moisture than nine global products, and the improvement is mainly attributed to the advances in model physical parameterizations and high-resolution surface parameters. Our results emphasize the great added value of kilometer-scale land surface modeling at continental scales.
Abstract
In this study, we calibrate a regional climate model’s (RCM) underlying land surface model (LSM). In addition to providing a realistic representation of runoff across the hydroclimatically diverse western United States, this is done to take advantage of the RCM’s ability to physically resolve meteorological forcing data in ungauged regions, and to prepare the calibrated hydrologic model for tight coupling, or the ability to represent land surface–atmosphere interactions, with the RCM. Specifically, we use a 9-km resolution meteorological forcing dataset across the western United States, from the fifth generation ECMWF Reanalysis (ERA5) downscaled by the Weather Research Forecasting (WRF) regional climate model, as an offline forcing for Noah-Multiparameterization (Noah-MP). We detail the steps involved in producing an LSM capable of accurately representing runoff, including physical parameterization selection, parameter calibration, and regionalization to ungauged basins. Based on our model evaluation from 1954 to 2021 for 586 basins with daily natural streamflow, the streamflow bias is reduced from 24.2% to 4.4%, and the median daily Nash–Sutcliffe efficiency (NSE) is improved from 0.12 to 0.36. When validating against basins with monthly natural streamflow data, we obtain a similar reduction in bias and a median monthly NSE improvement from 0.18 to 0.56. In this study, we also discover the optimal setup when using a donor-basin method to regionalize parameters to ungauged basins, which can vary by 0.06 NSE for unique designs of this regionalization method.
Significance Statement
This study provides useful guidance for improving a land surface model to accurately represent runoff across a spatially extensive and hydroclimatically diverse region (the western United States). The land surface model is updated to represent runoff more accurately at gauged basins, and then additionally updated for basins without observational data using a mathematical approach called the donor-basin method. We make use of a regional climate model’s reanalysis-derived meteorological data and its underlying land surface model to achieve realistic runoff. The calibrated land surface model can thus be tightly coupled in subsequent studies in a manner that should more accurately reflect runoff conditions. Findings from this study will serve as a useful reference for the atmospheric (and hydrologic) modeling communities and their ability to represent large-scale hydrology accurately.
Abstract
In this study, we calibrate a regional climate model’s (RCM) underlying land surface model (LSM). In addition to providing a realistic representation of runoff across the hydroclimatically diverse western United States, this is done to take advantage of the RCM’s ability to physically resolve meteorological forcing data in ungauged regions, and to prepare the calibrated hydrologic model for tight coupling, or the ability to represent land surface–atmosphere interactions, with the RCM. Specifically, we use a 9-km resolution meteorological forcing dataset across the western United States, from the fifth generation ECMWF Reanalysis (ERA5) downscaled by the Weather Research Forecasting (WRF) regional climate model, as an offline forcing for Noah-Multiparameterization (Noah-MP). We detail the steps involved in producing an LSM capable of accurately representing runoff, including physical parameterization selection, parameter calibration, and regionalization to ungauged basins. Based on our model evaluation from 1954 to 2021 for 586 basins with daily natural streamflow, the streamflow bias is reduced from 24.2% to 4.4%, and the median daily Nash–Sutcliffe efficiency (NSE) is improved from 0.12 to 0.36. When validating against basins with monthly natural streamflow data, we obtain a similar reduction in bias and a median monthly NSE improvement from 0.18 to 0.56. In this study, we also discover the optimal setup when using a donor-basin method to regionalize parameters to ungauged basins, which can vary by 0.06 NSE for unique designs of this regionalization method.
Significance Statement
This study provides useful guidance for improving a land surface model to accurately represent runoff across a spatially extensive and hydroclimatically diverse region (the western United States). The land surface model is updated to represent runoff more accurately at gauged basins, and then additionally updated for basins without observational data using a mathematical approach called the donor-basin method. We make use of a regional climate model’s reanalysis-derived meteorological data and its underlying land surface model to achieve realistic runoff. The calibrated land surface model can thus be tightly coupled in subsequent studies in a manner that should more accurately reflect runoff conditions. Findings from this study will serve as a useful reference for the atmospheric (and hydrologic) modeling communities and their ability to represent large-scale hydrology accurately.
Abstract
We analyze uncertainty in model-based estimates of probable maximum precipitation (PMP) as used in dam spillway design. Our focus is on model-based PMP derived from Weather Research and Forecasting (WRF) Model reconstructions of severe historical storms, amplified by the addition of moisture in the boundary conditions [so-called relative humidity maximization (RHM)]. By scaling moisture and predicting the resulting precipitation, the model-based approach arguably is more realistic than currently used techniques [documented in NOAA’s Hydrometeorological Reports (HMRs)], which assume that precipitation scales linearly with moisture. Despite the important improvement this represents, model-based PMP is subject to several sources of uncertainty that have slowed adoption in operational settings. We analyze an ensemble of PMP simulations that reflect recognized sources of uncertainty including the following: 1) initial condition error, 2) choice of physics parameterizations, and 3) upscale propagating model errors. We apply this ensemble approach to the Feather River watershed (Oroville Dam) in California for the storms of February 1986 and January 1997, which produced some of the largest floods on record at that location, after carrying out in-depth evaluations of model reconstructions. Differences in the maximized 72-h precipitation totals across the 56 ensemble members we produced for each storm are modest, ranging from ±7% of ensemble mean. Our results suggest that while model-based PMP estimates should be interpreted as a range of values, model uncertainty appears to be relatively small for the major atmospheric river–driven flood events we investigated.
Abstract
We analyze uncertainty in model-based estimates of probable maximum precipitation (PMP) as used in dam spillway design. Our focus is on model-based PMP derived from Weather Research and Forecasting (WRF) Model reconstructions of severe historical storms, amplified by the addition of moisture in the boundary conditions [so-called relative humidity maximization (RHM)]. By scaling moisture and predicting the resulting precipitation, the model-based approach arguably is more realistic than currently used techniques [documented in NOAA’s Hydrometeorological Reports (HMRs)], which assume that precipitation scales linearly with moisture. Despite the important improvement this represents, model-based PMP is subject to several sources of uncertainty that have slowed adoption in operational settings. We analyze an ensemble of PMP simulations that reflect recognized sources of uncertainty including the following: 1) initial condition error, 2) choice of physics parameterizations, and 3) upscale propagating model errors. We apply this ensemble approach to the Feather River watershed (Oroville Dam) in California for the storms of February 1986 and January 1997, which produced some of the largest floods on record at that location, after carrying out in-depth evaluations of model reconstructions. Differences in the maximized 72-h precipitation totals across the 56 ensemble members we produced for each storm are modest, ranging from ±7% of ensemble mean. Our results suggest that while model-based PMP estimates should be interpreted as a range of values, model uncertainty appears to be relatively small for the major atmospheric river–driven flood events we investigated.
Abstract
Anthropogenic climate change is affecting rivers worldwide, threatening water availability and altering the risk of natural hazards. Understanding the pattern of regional streamflow trends can help to inform region-specific policies to mitigate and adapt to any negative impacts on society and the environment. We present a benchmark dataset of long, near-natural streamflow records across Aotearoa New Zealand (NZ) and the first nationwide analysis of observed spatiotemporal streamflow trends. Individual records rarely have significant trends, but when aggregated within homogenous hydrologic regions (determined through cluster analyses), significant regional trends emerge. A multitemporal approach that uses all available data for each region and considers trend significance over time reveals the influence of decadal variability in some seasons and regions, and consistent trends in others. Over the last 50+ years, winter streamflow has significantly increased in the west South Island and has significantly decreased in the north North Island; summer streamflow has significantly decreased for most of the North Island; autumn streamflow has generally dried nationwide; and spring streamflow has increased along the west coast and decreased along the east coast. Correlations between streamflow and dynamic and thermodynamic climate indices reveal the dominant drivers of hydrologic behavior across NZ. Consistencies between the observed near-natural streamflow trends and observed changes in circulation and thermodynamic processes suggest possible climate change impacts on NZ hydrology.
Abstract
Anthropogenic climate change is affecting rivers worldwide, threatening water availability and altering the risk of natural hazards. Understanding the pattern of regional streamflow trends can help to inform region-specific policies to mitigate and adapt to any negative impacts on society and the environment. We present a benchmark dataset of long, near-natural streamflow records across Aotearoa New Zealand (NZ) and the first nationwide analysis of observed spatiotemporal streamflow trends. Individual records rarely have significant trends, but when aggregated within homogenous hydrologic regions (determined through cluster analyses), significant regional trends emerge. A multitemporal approach that uses all available data for each region and considers trend significance over time reveals the influence of decadal variability in some seasons and regions, and consistent trends in others. Over the last 50+ years, winter streamflow has significantly increased in the west South Island and has significantly decreased in the north North Island; summer streamflow has significantly decreased for most of the North Island; autumn streamflow has generally dried nationwide; and spring streamflow has increased along the west coast and decreased along the east coast. Correlations between streamflow and dynamic and thermodynamic climate indices reveal the dominant drivers of hydrologic behavior across NZ. Consistencies between the observed near-natural streamflow trends and observed changes in circulation and thermodynamic processes suggest possible climate change impacts on NZ hydrology.
Abstract
Moisture transport and changes in the source–sink relationship play a vital role in the atmospheric branch of the hydrological cycle. Lagrangian approaches have emerged as the dominant tool to account for estimations of moisture sources and sinks; those that use the FLEXPART model fed by ERA-Interim reanalysis are most commonly used. With the release of the higher spatial resolution ERA5, it is crucial to compare the representation of moisture sources and sinks using the FLEXPART Lagrangian model with different resolutions in the input data, as well as its version for WRF-ARW input data, the FLEXPART-WRF. In this study, we compare this model for 2014 and moisture sources for the Iberian Peninsula and moisture sinks of North Atlantic and Mediterranean. For comparison criteria, we considered FLEXPARTv9.0 outputs forced by ERA-Interim reanalysis as “control” values. It is concluded that FLEXPARTv10.3 forced with ERA5 data at various horizontal resolutions (0.5° and 1°) represents moisture source and sink zones as represented forced by ERA-Interim (1°). In addition, the version fed with the dynamic downscaling WRF-ARW outputs (∼20 km), previously forced with ERA5, also represents these patterns accurately, allowing this tool to be used in future investigations at higher resolutions and for regional domains.
Significance Statement
The FLEXPART dispersion model forced with ERA5 reanalysis data at various resolutions represents moisture source and sink zones compared to when it is forced by ERA-Interim. When the Weather Research and Forecasting Model is used to dynamically downscale ERA5, FLEXPART-WRF can also represent moisture sources and sinks, allowing this tool to be used in future investigations requiring higher resolution and regional domains and on regions with a predominance of complex orography due to its ability to represent local moisture transport.
Abstract
Moisture transport and changes in the source–sink relationship play a vital role in the atmospheric branch of the hydrological cycle. Lagrangian approaches have emerged as the dominant tool to account for estimations of moisture sources and sinks; those that use the FLEXPART model fed by ERA-Interim reanalysis are most commonly used. With the release of the higher spatial resolution ERA5, it is crucial to compare the representation of moisture sources and sinks using the FLEXPART Lagrangian model with different resolutions in the input data, as well as its version for WRF-ARW input data, the FLEXPART-WRF. In this study, we compare this model for 2014 and moisture sources for the Iberian Peninsula and moisture sinks of North Atlantic and Mediterranean. For comparison criteria, we considered FLEXPARTv9.0 outputs forced by ERA-Interim reanalysis as “control” values. It is concluded that FLEXPARTv10.3 forced with ERA5 data at various horizontal resolutions (0.5° and 1°) represents moisture source and sink zones as represented forced by ERA-Interim (1°). In addition, the version fed with the dynamic downscaling WRF-ARW outputs (∼20 km), previously forced with ERA5, also represents these patterns accurately, allowing this tool to be used in future investigations at higher resolutions and for regional domains.
Significance Statement
The FLEXPART dispersion model forced with ERA5 reanalysis data at various resolutions represents moisture source and sink zones compared to when it is forced by ERA-Interim. When the Weather Research and Forecasting Model is used to dynamically downscale ERA5, FLEXPART-WRF can also represent moisture sources and sinks, allowing this tool to be used in future investigations requiring higher resolution and regional domains and on regions with a predominance of complex orography due to its ability to represent local moisture transport.
Abstract
The Lower Mississippi River has experienced a cluster of extreme floods during the past two decades. The Bonnet Carré spillway, which is located on the Mississippi River immediately upstream of New Orleans, has been operated 15 times since its completion in 1931, with 7 occurrences after 2008. In this study, we examine rainfall and atmospheric water balance components associated with Lower Mississippi River flooding in 2008, 2011, and 2015–19. We focus on multiple time scales—1, 3, 7, and 14 days—reflecting contributions from individual storm systems and the aggregate contributions from a sequence of storm systems. Atmospheric water balance variables—integrated water vapor flux (IVT) and precipitable water—are central to our assessment of the storm environment for Lower Mississippi flood events. We find anomalously large IVT corridors accompany the critical periods of heavy rainfall and are organized in southwest–northeast orientation over the Mississippi domain. Atmospheric rivers play an important role as agents of extremes in water vapor flux and rainfall. We conduct climatological analyses of IVT and precipitable water extremes across the four time scales using 40 years of North American Regional Reanalysis (NARR) fields from 1979 to 2018. We find significant increasing trends in both variables at all time scales. Increases in IVT especially cover large regions of the Mississippi domain. The findings point to increased vulnerability faced by the Mississippi flood control system in the current and future climate.
Abstract
The Lower Mississippi River has experienced a cluster of extreme floods during the past two decades. The Bonnet Carré spillway, which is located on the Mississippi River immediately upstream of New Orleans, has been operated 15 times since its completion in 1931, with 7 occurrences after 2008. In this study, we examine rainfall and atmospheric water balance components associated with Lower Mississippi River flooding in 2008, 2011, and 2015–19. We focus on multiple time scales—1, 3, 7, and 14 days—reflecting contributions from individual storm systems and the aggregate contributions from a sequence of storm systems. Atmospheric water balance variables—integrated water vapor flux (IVT) and precipitable water—are central to our assessment of the storm environment for Lower Mississippi flood events. We find anomalously large IVT corridors accompany the critical periods of heavy rainfall and are organized in southwest–northeast orientation over the Mississippi domain. Atmospheric rivers play an important role as agents of extremes in water vapor flux and rainfall. We conduct climatological analyses of IVT and precipitable water extremes across the four time scales using 40 years of North American Regional Reanalysis (NARR) fields from 1979 to 2018. We find significant increasing trends in both variables at all time scales. Increases in IVT especially cover large regions of the Mississippi domain. The findings point to increased vulnerability faced by the Mississippi flood control system in the current and future climate.
Abstract
Transboundary rivers are often the cause of water-related international disputes. One example is the Amu Darya River, with a catchment area of 470 000 km2, which passes through five countries and provides water resources for 89 million people. Intensified human activities and climate change in this region have altered hydrological processes and led to water-related conflicts and ecosystem degradation. Understanding streamflow composition and quantifying the change impacts on streamflow in the Amu Darya basin (ADB) are imperative to water resources management. Here, a degree-day glacier-melt scheme coupled offline with the Variable Infiltration Capacity hydrological model (VIC-glacier), forced by daily precipitation, maximum and minimum air temperature, and wind speed, is used to examine streamflow composition and changes during 1953–2019. Results show large differences in streamflow composition among the tributaries. There is a decrease in the snowmelt component (−260.8 m3 s−1) and rainfall component (−30.1 m3 s−1) at Kerki but an increase in the glacier melt component (160.0 m3 s−1) during drought years. In contrast, there is an increase in the snowmelt component (378.6 m3 s−1) and rainfall component (12.0 m3 s−1) but a decrease in the glacier melt component (−201.8 m3 s−1) during wet years. Using the VIC-glacier and climate elasticity approach, impacts of human activities and climate change on streamflow at Kerki and Kiziljar during 1956–2015 are quantified. Both methods agree and show a dominant role played by human activities in streamflow reduction, with contributions ranging 103.2%–122.1%; however, the contribution of climate change ranges from −22.1% to −3.2%.
Abstract
Transboundary rivers are often the cause of water-related international disputes. One example is the Amu Darya River, with a catchment area of 470 000 km2, which passes through five countries and provides water resources for 89 million people. Intensified human activities and climate change in this region have altered hydrological processes and led to water-related conflicts and ecosystem degradation. Understanding streamflow composition and quantifying the change impacts on streamflow in the Amu Darya basin (ADB) are imperative to water resources management. Here, a degree-day glacier-melt scheme coupled offline with the Variable Infiltration Capacity hydrological model (VIC-glacier), forced by daily precipitation, maximum and minimum air temperature, and wind speed, is used to examine streamflow composition and changes during 1953–2019. Results show large differences in streamflow composition among the tributaries. There is a decrease in the snowmelt component (−260.8 m3 s−1) and rainfall component (−30.1 m3 s−1) at Kerki but an increase in the glacier melt component (160.0 m3 s−1) during drought years. In contrast, there is an increase in the snowmelt component (378.6 m3 s−1) and rainfall component (12.0 m3 s−1) but a decrease in the glacier melt component (−201.8 m3 s−1) during wet years. Using the VIC-glacier and climate elasticity approach, impacts of human activities and climate change on streamflow at Kerki and Kiziljar during 1956–2015 are quantified. Both methods agree and show a dominant role played by human activities in streamflow reduction, with contributions ranging 103.2%–122.1%; however, the contribution of climate change ranges from −22.1% to −3.2%.
Abstract
We present a global-scale evaluation of surface shortwave (SW↓) radiative fluxes as derived with cloud amount information from the U.S. Air Force (USAF) Cloud Depiction Forecast System (CDFS) II World-Wide Merged Cloud Analysis (WWMCA) and implemented in the framework of the NASA Land Information System (LIS). Evaluation of this product is done against ground observations, a satellite-based product from the Moderate Resolution Imaging Spectroradiometer (MODIS), and several reanalysis outputs. While the LIS/USAF product tends to overestimate the SW↓ fluxes when compared to ground observations and satellite estimates, its performance is comparable or better than the following reanalysis products: ERA5, CFSR, and MERRA-2. Results are presented using all available observations over the globe and independently for several regional domains of interest. When evaluated against ground observations over the globe, the bias in the LIS/USAF product at daily time scale was about 9.34 W m−2 and the RMS was 29.20 W m−2 while over the United States the bias was about 10.65 W m−2 and the RMS was 35.31 W m−2. The sample sizes used were not uniform over the different regions, and the quality of both ground truth and the outputs of the other products may vary regionally. It is important to note that the LIS/USAF is a near-real-time (NRT) product of interest for potential users and as such fills a need that is not met by most products. Due to latency issues, the level of observational inputs in the NRT product is less than in the reanalysis data.
Significance Statement
We evaluate a current scheme to produce surface radiative fluxes in the NASA Land Information System (LIS) framework as driven with cloud amount information from the U.S. Air Force (USAF) Cloud Depiction Forecast System (CDFS) II World-Wide Merged Cloud Analysis (WWMCA). The LIS/USAF product is provided at near–real time and as such, fills a need that is not met by most products. Information used for evaluation are ground observations, MODIS satellite-based estimates, and independent outputs from several reanalysis. Since the various LIS products are used by the hydrometeorology community, this manuscript should be of interest to the users of the LIS/USAF information on surface radiative fluxes.
Abstract
We present a global-scale evaluation of surface shortwave (SW↓) radiative fluxes as derived with cloud amount information from the U.S. Air Force (USAF) Cloud Depiction Forecast System (CDFS) II World-Wide Merged Cloud Analysis (WWMCA) and implemented in the framework of the NASA Land Information System (LIS). Evaluation of this product is done against ground observations, a satellite-based product from the Moderate Resolution Imaging Spectroradiometer (MODIS), and several reanalysis outputs. While the LIS/USAF product tends to overestimate the SW↓ fluxes when compared to ground observations and satellite estimates, its performance is comparable or better than the following reanalysis products: ERA5, CFSR, and MERRA-2. Results are presented using all available observations over the globe and independently for several regional domains of interest. When evaluated against ground observations over the globe, the bias in the LIS/USAF product at daily time scale was about 9.34 W m−2 and the RMS was 29.20 W m−2 while over the United States the bias was about 10.65 W m−2 and the RMS was 35.31 W m−2. The sample sizes used were not uniform over the different regions, and the quality of both ground truth and the outputs of the other products may vary regionally. It is important to note that the LIS/USAF is a near-real-time (NRT) product of interest for potential users and as such fills a need that is not met by most products. Due to latency issues, the level of observational inputs in the NRT product is less than in the reanalysis data.
Significance Statement
We evaluate a current scheme to produce surface radiative fluxes in the NASA Land Information System (LIS) framework as driven with cloud amount information from the U.S. Air Force (USAF) Cloud Depiction Forecast System (CDFS) II World-Wide Merged Cloud Analysis (WWMCA). The LIS/USAF product is provided at near–real time and as such, fills a need that is not met by most products. Information used for evaluation are ground observations, MODIS satellite-based estimates, and independent outputs from several reanalysis. Since the various LIS products are used by the hydrometeorology community, this manuscript should be of interest to the users of the LIS/USAF information on surface radiative fluxes.
Abstract
Knowledge gain in the characteristics and mechanisms of drought propagation is indispensable for timely drought early warning and risk reduction over the grassland eco-region. This study focused on the Xilin River basin, which is a typical inland river basin located in the Inner Mongolia temperate steppe, China. The characteristics of meteorological and hydrological drought were assessed by applying the standardized precipitation index and standardized streamflow index. The propagation relationship between meteorological and hydrological droughts was then investigated from both static and dynamic perspectives, and the possible reasons for its temporal dynamics were discussed by considering environmental factors. Our results showed that the Xilin River basin has suffered from more serious meteorological drought than hydrological drought during the past 60 years, with a stationary evolution of meteorological drought but an overall drying trend in hydrological drought. The propagation from meteorological to hydrological droughts exhibited obvious seasonality, characterized by stronger intensity and shorter response time in the wet season. Nonstationary behaviors were identified for the temporal patterns of drought propagation time, especially showing a significant trend in April, May, and August. The dynamic changes in propagation time affected by regional forces were principally ruled by the precipitation variation positively and strongly, and they were moderately controlled by temperature, vegetation cover, and deep-layer soil moisture, with season-dependent effects. The effects of low-frequency atmospheric anomalies on drought propagation will be further investigated in future studies, which are expected to provide a better understanding of the physical mechanism of the large-scale climate forcing on local drought condition.
Significance Statement
A new research approach was proposed to assess the propagation relationship between meteorological and hydrological drought from both static and dynamic perspectives, and the possible reasons for the temporal dynamics were discussed by considering environmental factors. Focusing on an inland river basin over the Inner Mongolia typical steppe, the propagation from meteorological to hydrological droughts showed obvious seasonality. Nonstationary behaviors were identified for the temporal patterns of drought propagation time, which could be explained by the regional hydrometeorological conditions. The advanced understanding of drought propagation provides a scientific base for water resources planning and drought management within a grassland region.
Abstract
Knowledge gain in the characteristics and mechanisms of drought propagation is indispensable for timely drought early warning and risk reduction over the grassland eco-region. This study focused on the Xilin River basin, which is a typical inland river basin located in the Inner Mongolia temperate steppe, China. The characteristics of meteorological and hydrological drought were assessed by applying the standardized precipitation index and standardized streamflow index. The propagation relationship between meteorological and hydrological droughts was then investigated from both static and dynamic perspectives, and the possible reasons for its temporal dynamics were discussed by considering environmental factors. Our results showed that the Xilin River basin has suffered from more serious meteorological drought than hydrological drought during the past 60 years, with a stationary evolution of meteorological drought but an overall drying trend in hydrological drought. The propagation from meteorological to hydrological droughts exhibited obvious seasonality, characterized by stronger intensity and shorter response time in the wet season. Nonstationary behaviors were identified for the temporal patterns of drought propagation time, especially showing a significant trend in April, May, and August. The dynamic changes in propagation time affected by regional forces were principally ruled by the precipitation variation positively and strongly, and they were moderately controlled by temperature, vegetation cover, and deep-layer soil moisture, with season-dependent effects. The effects of low-frequency atmospheric anomalies on drought propagation will be further investigated in future studies, which are expected to provide a better understanding of the physical mechanism of the large-scale climate forcing on local drought condition.
Significance Statement
A new research approach was proposed to assess the propagation relationship between meteorological and hydrological drought from both static and dynamic perspectives, and the possible reasons for the temporal dynamics were discussed by considering environmental factors. Focusing on an inland river basin over the Inner Mongolia typical steppe, the propagation from meteorological to hydrological droughts showed obvious seasonality. Nonstationary behaviors were identified for the temporal patterns of drought propagation time, which could be explained by the regional hydrometeorological conditions. The advanced understanding of drought propagation provides a scientific base for water resources planning and drought management within a grassland region.
