Browsing by Subject "Land surface modeling"
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Item New insights into dust aerosol entrainment mechanisms from satellite/ground-based data, climate modeling, and wind-tunnel experiments(2016-05) Parajuli, Sagar Prasad; Yang, Zong-liang; Kocurek, Gary; Dickinson, Robert E; Zobeck, Ted M; Wei, JiangfengAtmospheric dust aerosols have implications for Earth’s radiation budget, biogeochemical cycles, hydrological cycles, human health, and visibility. Currently, there is a considerable mismatch between climate model simulations and observations in representing the dust cycle in terms of emission, transport, and deposition. This mismatch is related partly to our inadequate understanding of the complex dust emission processes and partly to the way these processes are represented in climate models. In this work, we examine these problems from various perspectives with an interdisciplinary approach by integrating wind-tunnel experiments, geomorphological mapping, satellite observations, land surface modeling, atmospheric reanalysis, and fully coupled earth system modeling. The primary science contributions of this work are summarized here. First, we developed a detailed regional land cover map of the dust belt, the Middle East and North Africa. The developed map can be integrated in any regional dust models for better representing the spatial variation in dust source erodibility. We also developed a new observation-based soil erodibility map in global scale based on the correlation between reanalysis surface winds and satellite-observed aerosol optical depth data (AOD). Second, we integrated the developed observation-based erodibility map into the Community Earth System Model (CESM) and evaluated CESM’s performance in simulating mineral dust emission over the dust belt. Results show that the new erodibility map improves dust simulations in terms of AOD/dust optical depth (DOD) and the CESM captures large scale dust storms reasonably well when the winds are nudged towards ERA-Interim reanalysis data. Third, we conducted wind tunnel experiments and explored some of the lesser understood physical mechanisms of dust emission in sandblasting and direct aerodynamic entrainment. Results indicate that surface roughness can control dust emission in direct aerodynamic entrainment and that dust emission by direct aerodynamic entrainment can be significant under certain conditions compared to sandblasting. Lastly, we develop a principal component analysis based technique to extract locally mobilized dust component from the AOD data, which otherwise represent a mixture of several aerosol types and advected dust/aerosols.Item Towards actionable climate and flood prediction : understanding and advancing land surface modeling with enriched geospatial information(2018-05-03) Lin, Peirong; Yang, Zong-liang; Cardenas, Meinhard B.; Dickinson, Robert E.; Koster, Randal D.; Wei, JiangfengLand surface models (LSMs) are central to our understanding and prediction of the terrestrial hydrological cycle. This dissertation focuses on using enriched geospatial information from remote sensing (RS) and geographic information system (GIS) to advance the snow and river routing component of state-of-the-art LSMs, and assessing their roles in predicting temperature, precipitation, and streamflow. In Chapters 2 and 3, the first systematic studies are conducted to quantify the role of land snow data assimilation (DA) in seasonal climate forecast. Using 7-yr DA products that assimilated the Moderate Resolution Imaging Spectroradiometer (MODIS) snow cover fraction (SCF) and the Gravity Recovery and Climate Experiment (GRACE) terrestrial water storage (TWS), I find a local improvement of 5%–25% in the temperature forecast, where the delayed improvement at higher latitudes is explained by incoming solar radiation that is key to the snow–atmosphere coupling. Focusing on the Asia monsoon, I detect an improvement in the precipitation forecast, which is more robust over central north India with sensor-dependent behaviors in different seasons. The results clarify that to successfully translate DA to useful atmospheric prediction skill, the regional snow–atmosphere coupling, the DA uncertainties, and the monsoon sensitivity to thermal forcing over land need to be jointly considered. In Chapters 4 and 5, I introduce a vector-based river routing model to be coupled with traditional grid-based LSMs. By conducting comprehensive model evaluations in the Texas “Flash Flood Alley” in high-impact historical floods, I identify the model strengths and weaknesses in simulating flood discharges. The best modeling results are then used to reveal the hydrometeorological factors responsible for a record-breaking local flood, which includes the rainfall location and basin physiographic features, the initial wetness in the deeper soil layer, and the flow velocity in the river network. The assessed modeling advancements have actionable societal implications because they apply to the Community Land Model 4 (CLM4) and the Noah model with multi-parameterizations (Noah-MP), both LSMs are adopted by major operational forecasting centers. They may also inform future LSM developments that aim to unify the “top-down” atmospheric modeling and the “bottom-up” hydrological modeling approaches in a generic framework.Item Towards river flow computation at the continental scale(2009-08) David, Cédric H., 1981-; Maidment, David R.; Yang, Zong-liangThe work presented in this dissertation informs on river network modeling at large scales using geographic information systems, parallel computing and the latest advancements of atmospheric and land surface modeling. This work is motivated by the availability of a vector-based Geographic Information System dataset that describes the networks of streams and rivers in the United States, and how they are connected. A land surface model called Noah-distributed is used to provide lateral inflow to an NHDPlus river network in the Guadalupe River Basin in Texas. Challenges related to the projection of gridded hydrographic data from a coordinate system to another are investigated. The different representations of the shape of the Earth used in atmospheric science (spherical) and hydrology (spheroidal) can lead to a significant North-South shift on the order of 20 km at mid latitudes. A river network model called RAPID is developed and applied in a four-year study of the Guadalupe and San Antonio River Basins in Texas using the river network of NHDPlus. Gage measurements are used to estimate flow wave celerities in a river network and to assess the quality of RAPID flow computations. The performance of RAPID in a massively-parallel computing environment is tested and further investigation of its scalability is needed before using RAPID at the state or federal level. The replacement by RAPID of the river routing scheme used in SIM-France -- a hydro-meteorological model -- is investigated in a ten-year study of river flow in France. While the formulation of RAPID improves the functionality of SIM-France, the flow simulations are comparable in accuracy to those previously obtained by SIM-France. Sub-basin parameterization was found to improve model results. A single criterion for quantifying the quality of river flow simulations using several river gages globally in a river network is developed that normalizes the square error of modeled flow to allow equal treatment of all gaging stations regardless of the magnitude of flow. The use of this criterion as the cost function for parameter estimation in RAPID allows better results than by increasing the degree of spatial variability in model parameters.