An evaluation of the Biosphere–Atmosphere Transfer Scheme (BATS) snow submodel was conducted, both in a stand-alone mode and within the National Center for Atmospheric Research (NCAR) Community Climate Model version 3 (CCM3). We... more
An evaluation of the Biosphere–Atmosphere Transfer Scheme (BATS) snow submodel was conducted, both in a stand-alone mode and within the National Center for Atmospheric Research (NCAR) Community Climate Model version 3 (CCM3). We evaluated, in the stand-alone mode, the performance of BATS parameterizations at local scales using ground-based observations from the former Soviet Union and fromMammoth Mountain, California. The BATS snow scheme reproduces well the seasonal evolution of snow water equivalent in both sites, and the results for the MammothMountain site compare well with those from a more complex, physically based model (SNTHERM). In the coupled mode, we evaluated the modelled snow cover extent, snow mass, precipitation and temperature from BATS as linked to the NCAR CCM3 using available observations. The coupled models capture the broad pattern of seasonal and geographical distribution of snow cover, with better overall performance than the passive microwave snow data derive...
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Environmental Engineering, Civil Engineering, Environmental Science, Atmospheric Modeling, Seasonality, and 13 moreformer Soviet Union, North America, Geographic distribution, Air Temperature, Model Generation, Microwave radiometer, Snow Cover, Physics based Modeling, Hydrological Processes, Passive Microwave Components, Hydrological, Snow Depth, and Snow water equivalent
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Abstract Flash floods-caused losses are rapidly increasing due to climate change induced extreme weather events and economic development in the world. The WRF-Hydro-RAPID model coupled with land surface model and a vector-based flow... more
Abstract Flash floods-caused losses are rapidly increasing due to climate change induced extreme weather events and economic development in the world. The WRF-Hydro-RAPID model coupled with land surface model and a vector-based flow routing module is able to simulate discharge at any reach of a watershed, making it a good tool for flood simulation and forecasting. We investigated the flood simulation capability of the WRF-Hydro-RAPID model and evaluated the utility of a multi-source precipitation merging method based on the mixed geographically weighted regression model and Bi-square function (MGWR-BI algorithm), which produces precipitation as forcing with improved quality and resolution, to enhance the simulation accuracy of the WRF-Hydro-RAPID model for the Daheba Watershed, a first-order sub-basin of the Yangtze River Basin. The merged precipitation data have substantial higher quality than the downscaled original CPC MORPHing technique satellite precipitation data (CMORPHd) (r = 0.64-0.74 and RMSE = 1.59-6.64 mm/h for the merged data vs. r = -0.11-0.06 and RMSE = 3.31-8.25 mm/h for the CMORPHd data) by comparing to the ground observations. Floods are better forecasted and simulated by the WRF-Hydro-RAPID model driven by the merged precipitation data than the CMORPHd precipitation data for the four nested medium and small watersheds. Performance of the WRF-Hydro-RAPID model at the watershed outlet station does not differ those at the three inner stations, proving that the WRF-Hydro-RAPID model has a consistent performance in space. The combination of the WRF-Hydro-RAPID with the precipitation merging method makes it a valuable tool for flood simulation of medium and small watersheds.
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The accuracy of land surface hydrological simulations using an offline land surface model (LSM) depends largely on the quality of the atmospheric forcing data. In this study, Global Land Data Assimilation System (GLDAS) forcing data and... more
The accuracy of land surface hydrological simulations using an offline land surface model (LSM) depends largely on the quality of the atmospheric forcing data. In this study, Global Land Data Assimilation System (GLDAS) forcing data and the newly developed China Meteorological Administration Land Data Assimilation System (CLDAS) forcing data are used to drive the Noah LSM with multiple parameterizations (Noah-MP) and to explore how the newly developed CLDAS forcing data improve land surface hydrological simulations over mainland China. The monthly soil moisture (SM) and evapotranspiration (ET) simulations are then compared and evaluated against observations. The results show that the Noah-MP driven by the CLDAS forcing data (referred to as CLDAS_Noah-MP) significantly improves the simulations in most cases over mainland China and its eight river basins. CLDAS_Noah-MP increases the correlation coefficient (R) values from 0.451 to 0.534 for the SM simulations at a depth range of 0–ss10 cm in mainland China, especially in the eastern monsoon area such as the Huang-Huai-Hai Plain, the southern Yangtze River basin, and the Zhujiang River basin. Moreover, the root-mean-square error is reduced from 0.078 to 0.068 m3 m−3 for the SM simulations, and from 12.9 to 11.4 mm month−1 for the ET simulations over mainland China, especially in the southern Yangtze River basin and Zhujiang River basin. This study demonstrates that, by merging more in situ and remote sensing observations in regional atmospheric forcing data, offline LSM simulations can better simulate regional-scale land surface hydrological processes.
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Snow cover affects the thermal conditions of the Tibetan Plateau through snow–albedo feedback and snowmelt, which, in turn, modulates the Asian summer monsoon climate. An accurate estimation of the snow condition on the Tibetan Plateau is... more
Snow cover affects the thermal conditions of the Tibetan Plateau through snow–albedo feedback and snowmelt, which, in turn, modulates the Asian summer monsoon climate. An accurate estimation of the snow condition on the Tibetan Plateau is therefore of great importance in both seasonal forecasts and climate studies. Estimation of snow water equivalent (SWE) over the Tibetan Plateau is challenging due to the high altitude, complex terrain, and insufficient in situ observations. Multiple SWE products derived from satellite estimates, reanalyses, regional climate model simulations, and land data assimilations are intercompared in terms of daily, seasonal, and annual variations and are then evaluated against in situ SWE observations. The results show a relatively consistent seasonal to interannual variability of the SWE estimates among the products. The discrepancies in magnitude are large, however, especially in winter and spring. Evaluation against in situ SWE observations indicates th...
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Continental-scale snow radiance assimilation (RA) experiments are conducted in order to improve snow estimates across snow and land-cover types in North America. In the experiments, the ensemble adjustment Kalman filter is applied and the... more
Continental-scale snow radiance assimilation (RA) experiments are conducted in order to improve snow estimates across snow and land-cover types in North America. In the experiments, the ensemble adjustment Kalman filter is applied and the Advanced Microwave Scanning Radiometer for Earth Observing System (AMSR-E) brightness temperature T B observations are assimilated into an RA system composed of the Community Land Model, version 4 (CLM4); radiative transfer models (RTMs); and the Data Assimilation Research Testbed (DART). The performance of two snowpack RTMs, the Dense Media Radiative Transfer–Multi-Layers model (DMRT-ML), and the Microwave Emission Model of Layered Snowpacks (MEMLS) in improving snow depth estimates through RA is compared. Continental-scale snow estimates are enhanced through RA by using AMSR-E T B at the 18.7- and 23.8-GHz channels [3% (DMRT-ML) and 2% (MEMLS) improvements compared to the cases using the 18.7- and 36.5-GHz channels] and by considering the vegetat...
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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).... more
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 enh...
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The absorptive properties of dust aerosols largely determine the magnitude of their radiative impacts on the climate system. Currently, climate models use globally constant values of dust imaginary refractive index (IRI), a parameter... more
The absorptive properties of dust aerosols largely determine the magnitude of their radiative impacts on the climate system. Currently, climate models use globally constant values of dust imaginary refractive index (IRI), a parameter describing the dust absorption efficiency of solar radiation, although it is highly variable. Here we show with model experiments that the dust-induced Indian summer monsoon (ISM) rainfall differences (with dust minus without dust) change from -9% to 23% of long-term climatology as the dust IRI is changed from zero to the highest values used in the current literature. A comparison of the model results with surface observations, satellite retrievals, and reanalysis data sets indicates that the dust IRI values used in most current climate models are too low, tending to significantly underestimate dust radiative impacts on the ISM system. This study highlights the necessity for developing a parameterization of dust IRI for climate studies.
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Abstract Large amounts of mineral dust are injected into the atmosphere during dust storms, which are common in the Middle East and North Africa (MENA) where most of the global dust hotspots are located. In this work, we present... more
Abstract Large amounts of mineral dust are injected into the atmosphere during dust storms, which are common in the Middle East and North Africa (MENA) where most of the global dust hotspots are located. In this work, we present simulations of dust emission using the Community Earth System Model Version 1.2.2 (CESM 1.2.2) and evaluate how well it captures the spatio-temporal characteristics of dust emission in the MENA region with a focus on large-scale dust storm mobilization. We explicitly focus our analysis on the model’s two major input parameters that affect the vertical mass flux of dust—surface winds and the soil erodibility factor. We analyze dust emissions in simulations with both prognostic CESM winds and with CESM winds that are nudged towards ERA-Interim reanalysis values. Simulations with three existing erodibility maps and a new observation-based erodibility map are also conducted. We compare the simulated results with MODIS satellite data, MACC reanalysis data, AERONET station data, and CALIPSO 3-d aerosol profile data. The dust emission simulated by CESM, when driven by nudged reanalysis winds, compares reasonably well with observations on daily to monthly time scales despite CESM being a global General Circulation Model. However, considerable bias exists around known high dust source locations in northwest/northeast Africa and over the Arabian Peninsula where recurring large-scale dust storms are common. The new observation-based erodibility map, which can represent anthropogenic dust sources that are not directly represented by existing erodibility maps, shows improved performance in terms of the simulated dust optical depth (DOD) and aerosol optical depth (AOD) compared to existing erodibility maps although the performance of different erodibility maps varies by region.
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This paper evaluates the simulation of snow by the Community Land Model, version 4 (CLM4), the land model component of the Community Earth System Model, version 1.0.4 (CESM1.0.4). CLM4 was run in an offline mode forced with the corrected... more
This paper evaluates the simulation of snow by the Community Land Model, version 4 (CLM4), the land model component of the Community Earth System Model, version 1.0.4 (CESM1.0.4). CLM4 was run in an offline mode forced with the corrected land-only replay of the Modern-Era Retrospective Analysis for Research and Applications (MERRA-Land) and the output was evaluated for the period from January 2001 to January 2011 over the Northern Hemisphere poleward of 30°N. Simulated snow-cover fraction (SCF), snow depth, and snow water equivalent (SWE) were compared against a set of observations including the Moderate Resolution Imaging Spectroradiometer (MODIS) SCF, the Interactive Multisensor Snow and Ice Mapping System (IMS) snow cover, the Canadian Meteorological Centre (CMC) daily snow analysis products, snow depth from the National Weather Service Cooperative Observer (COOP) program, and Snowpack Telemetry (SNOTEL) SWE observations. CLM4 SCF was converted into snow-cover extent (SCE) to com...
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The response of the Indian summer monsoon (ISM) circulation and precipitation to Middle East dust aerosols on sub-seasonal timescales is studied using observations and the Weather Research and Forecasting model with chemistry (WRF-Chem).... more
The response of the Indian summer monsoon (ISM) circulation and precipitation to Middle East dust aerosols on sub-seasonal timescales is studied using observations and the Weather Research and Forecasting model with chemistry (WRF-Chem). Satellite data shows that the ISM rainfall in coastal southwest India, central and northern India, and Pakistan are closely associated with Middle East dust aerosols. The physical mechanism behind this dust–ISM rainfall connection is examined through ensemble simulations with and without dust emission. Each ensemble includes 16 members with various physical and chemical schemes to consider the model uncertainties in parameterizing shortwave radiation, the planetary boundary layer, and aerosol chemical mixing rules. Experiments show that dust aerosols increase rainfall by about 0.44 mm day<sup>−1</sup> (~ 10%) in coastal southwest India, central and northern India, and northern Pakistan, a pattern consistent with the observed relationship...
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Snow cover modulates energy and water fluxes at the surface due to its thermal and hydrologic characteristics (e.g., high albedo, low thermal conductivity and water holding capacity). Furthermore, given the fact that the snowpack is one... more
Snow cover modulates energy and water fluxes at the surface due to its thermal and hydrologic characteristics (e.g., high albedo, low thermal conductivity and water holding capacity). Furthermore, given the fact that the snowpack is one of the most important freshwater reservoirs, understanding its spatial and temporal variations is crucial for hydrologic and climate studies. It has been demonstrated that radiance assimilation (RA), which assimilates passive microwave (PM) brightness temperature (Tb) observations directly into the land surface model (LSM), can be used to improve snow water equivalent (SWE) estimates compared to the assimilation of Tb-based SWE retrievals. In a RA, a radiative transfer model (RTM) is used as an observational operator to predict Tb observations. This study is a preliminary study that aims to assess the performance of the coupled LSM/RTM. In this study, the Community Land Model version 4 (CLM4), a state of the art, distributed, physically based LSM, wa...
ABSTRACT Snow cover at high latitudes is an excellent natural insulator that can maintain the underlying ground at a higher temperature than the overlying atmosphere. Soil impermeability usually varies when snow cover accumulates, which... more
ABSTRACT Snow cover at high latitudes is an excellent natural insulator that can maintain the underlying ground at a higher temperature than the overlying atmosphere. Soil impermeability usually varies when snow cover accumulates, which is closely related to soil and landscape freeze/thaw status. How snow cover affects the landscape frozen fraction and soil impermeability and how this impermeability regulates hydrological processes in cold regions have not been fully assessed and quantified. In order to understand these processes, this study performed a series of experiments by using the Community Land Model version 4 (CLM4). We first simulated the top-soil-layer ice, snow ice, and canopy ice to calculate the landscape frozen fraction, which was evaluated based on the Special Sensor Microwave/Imager (SSM/I) observed landscape freeze/thaw earth system data record (FT-ESDR) in two selected regions at high latitudes. Then two soil impermeability parameterizations were validated against various in situ and satellite observations. The results suggest the following: (1) compared to SSM/I FT-ESDR, CLM4 can capture the overall landscape freeze/thaw status in the regions north of 60°N in boreal winter and spring; (2) as the snow cover fraction approaches unity, the CLM4-simulated landscape frozen fraction is mainly controlled by the snow ice amount, resulting in step changes between SSM/I FT-ESDR observed and CLM4-simulated landscape frozen fractions; and (3) in most of the cold regions, the tim
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Previous work has shown that the addition of a lumped, unconfined aquifer model to a land-surface model (LSM) decreases the sensitivity of modeled monthly change in terrestrial water storage (dTWS) to selection of subsurface hydrologic... more
Previous work has shown that the addition of a lumped, unconfined aquifer model to a land-surface model (LSM) decreases the sensitivity of modeled monthly change in terrestrial water storage (dTWS) to selection of subsurface hydrologic parameters. In the work presented here, we investigate why adding an aquifer model as the lower boundary condition increases the robustness of LSM-simulated dTWS. We
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Land exchanges momentum, energy, water, aerosols, carbon dioxide and other trace gases with its overlying atmosphere. The land surface influences climate on local, regional and global scales across a wide range of timescales. This review... more
Land exchanges momentum, energy, water, aerosols, carbon dioxide and other trace gases with its overlying atmosphere. The land surface influences climate on local, regional and global scales across a wide range of timescales. This review concentrates on the rapid (i.e., seconds to seasons) biophysical and hydrological aspects of land surface processes. This paper provides the historical development of land surface models designed for short-term weather and climate studies, ranging from the early, simple "bucket" models to recent sophisticated soil-vegetation-atmosphere transfer schemes. Major research issues are reviewed by grouping into datasets, coupling to atmospheric models, component processes, and sub-grid-scale variability and scaling. Significant problems remain to be addressed, including the difficulties in parameterizing hillslope runoff, fractional snow cover, stomatal resistance, evapotranspiration, and sub-grid-scale variability and scaling. However, further p...
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A regional-scale weather model is used to determine the potential for flood forecasting based on model-predicted rainfall. Extreme precipitation and flooding events are a significant concern in central Texas, due to both the high... more
A regional-scale weather model is used to determine the potential for flood forecasting based on model-predicted rainfall. Extreme precipitation and flooding events are a significant concern in central Texas, due to both the high occurrence and severity of flooding in the area. However, many current regional prediction models do not provide sufficient accuracy at the watershed scale necessary for flood mitigation efforts. The Weather Research and Forecasting (WRF) model, created with the purpose of improving upon the current fifth-generation Pennsylvania State University–National Center for Atmospheric Research (PSU–NCAR) Mesoscale Model (MM5), is specifically designed for regional grid spacings of 1–10 km. Previous research by the authors resulted in the development of a regional-scale prediction system over the San Antonio River basin, using a geographic information system (GIS) database, a hydrologic model, and a hydraulic model. Observed precipitation drives the prediction syste...
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SUMMARY This paper describes a study in which, for the first time, advanced systems-engineering parameter-estimation techniques were applied to data from several field studies to estimate the preferred set of parameters for some of the... more
SUMMARY This paper describes a study in which, for the first time, advanced systems-engineering parameter-estimation techniques were applied to data from several field studies to estimate the preferred set of parameters for some of the most common hiomes represented in an ...
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The authors introduce and compare the performance of the unified Noah land surface model (LSM) and its augments with physically based, more conceptually realistic hydrologic parameterizations. Forty-five days of 30-min data collected over... more
The authors introduce and compare the performance of the unified Noah land surface model (LSM) and its augments with physically based, more conceptually realistic hydrologic parameterizations. Forty-five days of 30-min data collected over nine sites in transition zones are used to evaluate (i) their benchmark, the standard Noah LSM release 2.7 (STD); (ii) a version equipped with a short-term phenology module (DV); and (iii) one that couples a lumped, unconfined aquifer model to the model soil column (GW). Their model intercomparison, enhanced by multiobjective calibration and model sensitivity analysis, shows that, under the evaluation conditions, the current set of enhancements to Noah fails to yield significant improvement in the accuracy of simulated, high-frequency, warm-season turbulent fluxes, and near-surface states across these sites. Qualitatively, the versions of DV and GW implemented degrade model robustness, as defined by the sensitivity of model performance to uncertain...
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Continuous Improvement, Hydrometeorology, High Frequency, Model Identification, Atmospheric sciences, and 15 morePerformance Model, Data Collection, Mantle Transition Zone, Bias Correction, Evaluation Model, Model Evaluation, Model development, High Resolution, Hydrologic Models, Multiple model, Cost Function, Land Surface Model, Parameter Uncertainty, parameter space, and Model performance
The ability of two versions of the Noah land surface model (LSM) to simulate the water cycle of the Little Washita River experimental watershed is evaluated. One version that uses the standard hydrological parameterizations of Noah 2.7... more
The ability of two versions of the Noah land surface model (LSM) to simulate the water cycle of the Little Washita River experimental watershed is evaluated. One version that uses the standard hydrological parameterizations of Noah 2.7 (STD) is compared another version that replaces STD’s subsurface hydrology with a simple aquifer model and topography-related surface and subsurface runoff parameterizations (GW). Simulations on a distributed grid at fine resolution are compared to the long-term distribution of observed daily-mean runoff, the spatial statistics of observed soil moisture, and locally observed latent heat flux. The evaluation targets the typical behavior of ensembles of models that use realistic, near-optimal sets of parameters important to runoff. STD and GW overestimate the ratio of runoff to evapotranspiration. In the subset of STD and GW runs that best reproduce the timing and the volume of streamflow, the surface-to-subsurface runoff ratio is overestimated and simu...
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The energy and water balances at the earth's surface are dramatically influenced by the presence of snow cover. Therefore, soil temperature and moisture for snow-covered and snow-free areas can be very different. In computing these... more
The energy and water balances at the earth's surface are dramatically influenced by the presence of snow cover. Therefore, soil temperature and moisture for snow-covered and snow-free areas can be very different. In computing these soil state variables, many land surface schemes in climate models do not explicitly distinguish between snow-covered and snow-free areas. Even if they do, some schemes average these state variables to calculate grid-mean energy fluxes and these averaged state variables are then used at the beginning of the next time step. This latter approach introduces a numerical error in that heat is redistributed from snow-free areas to snow-covered areas, resulting in a more rapid snowmelt. This study focuses on the latter approach and examines the sensitivity of soil moisture and streamflow to the treatment of the soil state variables in the presence of snow cover by using WATCLASS, a land surface scheme linked with a hydrologic model. The model was tested for t...