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Hua Su

Researcher at University of Texas at Austin

Publications -  11
Citations -  1266

Hua Su is an academic researcher from University of Texas at Austin. The author has contributed to research in topics: Snow & Precipitation. The author has an hindex of 10, co-authored 11 publications receiving 1123 citations.

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Development of a simple groundwater model for use in climate models and evaluation with Gravity Recovery and Climate Experiment data

TL;DR: In this article, the authors developed a simple groundwater model (SIMGM) by representing recharge and discharge processes of the water storage in an unconfined aquifer, which is added as a single integration element below the soil of a land surface model.
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Evaluation of forest snow processes models (SnowMIP2)

Nick Rutter, +53 more
TL;DR: In this article, three snowpack models of varying complexity and purpose were evaluated across a wide range of hydrometeorological and forest canopy conditions at five Northern Hemisphere locations, for up to three months.
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Impact of moisture flux convergence and soil moisture on precipitation: a case study for the southern United States with implications for the globe

TL;DR: In this article, the influence of atmospheric moisture fluxes and land surface soil moisture on local precipitation, with a focus on the southern United States (U.S.), was investigated, and it was shown that the variation of moisture flux convergence (MFC) is more important than that of soil moisture for precipitation variation over the southern U.S.
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Multisensor snow data assimilation at the continental scale: The value of Gravity Recovery and Climate Experiment terrestrial water storage information

TL;DR: In this paper, a multisensor snow data assimilation system over North America (from January 2002 to June 2007) was established, with the goal of better estimation of snowpack (in particular, snow water equivalent and snow depth) via incorporating both Gravity Recovery and Climate Experiment (GRACE) terrestrial water storage (TWS) and Moderate Resolution Imaging Spectroradiometer (MODIS) snow cover fraction (SCF) information into the Community Land Model.
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Enhancing the estimation of continental-scale snow water equivalent by assimilating MODIS snow cover with the ensemble Kalman filter

TL;DR: In this paper, the authors investigated the feasibility of a framework for developing high quality continental-scale snow water equivalent (SWE) data sets over North America, through the EnKF approach, which assimilates the snow cover fraction observed by the Moderate Resolution Imaging Spectroradiometer (MODIS) into the Community Land Model (CLM).