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Jingfeng Wang and Rafael L. Bras

Abstract

An extremum hypothesis of turbulent transport in the atmospheric surface layer is postulated. The hypothesis has led to a unique solution of Monin–Obukhov similarity equations in terms of simple expressions linking shear stress (momentum flux) and heat flux to mean wind shear and temperature gradient. The extremum solution is consistent with the well-known asymptotic properties of the surface layer. Validation of the extremum solution has been made by comparison to field measurements of momentum and heat fluxes. Furthermore, a modeling test of predicting surface heat fluxes using the results of this work is presented. A critical reexamination of the interpretation of the Obukhov length is given.

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Jingfeng Wang and Rafael L. Bras
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Husayn El Sharif, Jingfeng Wang, and Aris P. Georgakakos

Abstract

Agricultural models, such as the Decision Support System for Agrotechnology Transfer cropping system model (DSSAT-CSM), have been developed for predicting crop yield at field and regional scales and to provide useful information for water resources management. A potentially valuable input to agricultural models is soil moisture. Presently, no observations of soil moisture exist covering the entire United States at adequate time (daily) and space (~10 km or less) resolutions desired for crop yield assessments. Data products from NASA’s upcoming Soil Moisture Active Passive (SMAP) mission will fill the gap. The objective of this study is to demonstrate the usefulness of the SMAP soil moisture data in modeling and forecasting crop yields and irrigation amount. A simple, efficient data assimilation algorithm is presented in which the agricultural crop model DSSAT-CSM is constrained to produce modeled crop yield and irrigation amounts that are consistent with SMAP-type data. Numerical experiments demonstrate that incorporating the SMAP data into the agricultural model provides an added benefit of reducing the uncertainty of modeled crop yields when the weather input data to the crop model are subject to large uncertainty.

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William B. Bennett, Jingfeng Wang, and Rafael L. Bras

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This study investigates the use of a previously published algorithm for estimating ground heat flux (GHF) at the global scale. The method is based on an analytical solution of the diffusion equation for heat transfer in a soil layer and has been shown to be effective at the point scale. The algorithm has several advantageous properties: 1) it only needs a single-level input of surface (skin) temperature, 2) the time-mean GHF can be derived directly from time-mean skin temperature, 3) it has reduced sensitivity to the variability in soil thermal properties and moisture, 4) it does not requires snow depth, and 5) it is computationally effective. A global map of the necessary thermal inertia parameter is derived using reanalysis data as a function of soil type. These parameter estimates are comparable to values obtained from in situ observations. The new global GHF estimates are generally consistent with the reanalysis GHF output simulated using two-layer soil hydrology models. The authors argue that the new algorithm is more robust and trustworthy in regions where they differ. The proposed algorithm offers potential benefits for direct assimilation of observations of surface temperature as well as GHF into the reanalysis models at various time scales.

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Ryan Knox, Gautam Bisht, Jingfeng Wang, and Rafael Bras

Abstract

Prior research has shown that deforestation in the southwestern Amazon enhances the formation of nonprecipitating shallow cumulus clouds, while deep cumulus convection was favored over forested land. The research presented here further investigates the trends of hydrometeors in the area by examining how precipitation frequency changes as a function of distance to the forest’s edge. Measurements are made from the precipitation radar on the Tropical Rainfall Measuring Mission (TRMM; TRMM 2A25) satellite, and continuous forest coverage is retrieved from the Moderate Resolution Imaging Spectroradiometer (MODIS; MODIS MCD12Q1). The event-based areal fractions of precipitation coverage (precipitation fraction) are calculated; referenced to forested, nonforested, and forest-edge land cover; and compared. As results are generally consistent with previous findings, the novel conclusions here extend that precipitation frequency in the southwestern Amazon (i) decreases over regions of nonforests far removed (10-plus km) from forest borders but (ii) increases within several kilometers of the forest edges, particularly over the nonforest side of the transition.

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Sanaz Moghim, Andrew Jay Bowen, Sepideh Sarachi, and Jingfeng Wang

Abstract

A new algorithm is formulated for retrieving hourly time series of surface hydrometeorological variables including net radiation, sensible heat flux, and near-surface air temperature aided by hourly visible images from the Geostationary Operational Environmental Satellite (GOES) and in situ observations of mean daily air temperature. The algorithm is based on two unconventional, recently developed methods: the maximum entropy production model of surface heat fluxes and the half-order derivative–integral model that has been tested previously. The close agreement between the retrieved hourly variables using remotely sensed input and the corresponding field observations indicates that this algorithm is an effective tool in remote sensing of the earth system.

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Jingfeng Wang, Rafael L. Bras, and Elfatih A. B. Eltahir

Abstract

A numerical mesoscale model has been used to investigate the impact of mesoscale circulations on the distribution of precipitation and cloudiness over a deforested area in Amazonia. Observed patterns of deforestation in Rondônia, Amazonia, with scales on the order of 10 km were used in this study to describe land surface conditions. Various simulations have been performed to identify the conditions under which the mesoscale circulations induced by the heterogeneous land surface could enhance cloudiness and local rainfall. The simulation results suggest that the synoptic forcing, in terms of atmospheric stability and background horizontal wind, dominates during the rainy season; synoptic conditions were so favorable to moist convection that the added effect of surface heterogeneity was negligible. During the dry season, a noticeable impact of mesoscale circulations resulting in enhancement of shallow clouds was simulated; the mesoscale circulations also triggered scattered deep convection that altered the spatial distribution of precipitation. During the break period, the transition from the rainy season to the dry season, the impact of mesoscale circulations on low-level clouds was evident only after reducing the magnitude of the background wind.

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Jingfeng Wang, Rafael L. Bars, and Elfatih A. B. Eltahir

Abstract

This paper presents a three-dimensional stochastic linear model of the mesoscale circulation induced by the variability of turbulent sensible heat flux over land surface. The primitive equations relating wind field, geo-potential, and potential temperature are formulated as a system of stochastic partial differential equations and solved analytically. The solution is based on spectral representations of homogeneous random fields. The flow intensity is found to be proportional to the standard deviation of the turbulent sensible heat flux into the atmosphere. Large (small) scales of spatial variability in the surface heating preferably impact circulations at high (low) altitudes. The mesoscale fluxes associated with the atmospheric flow are related to explicit functions of atmospheric stability, variance of turbulent heat flux, and synoptic wind. The authors find that the vertical momentum flux is significant in the presence of synoptic wind and that the flow perpendicular to the direction of the synoptic wind is responsible for this momentum flux. The proposed linear theory identifies the synoptic conditions under which the land-surface heterogeneity may play a role in atmospheric circulations at the mesoscale.

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Jingfeng Wang, Elfatih A. B. Eltahir, and Rafael L. Bras

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Mesoscale circulations forced by a random distribution of surface sensible heat flux have been investigated using a three-dimensional numerical model. The complex land surface is modeled as a homogeneous random field characterized by a spectral distribution. Standard deviation and length scale of the sensible heat flux at the surface have been identified as the important parameters that describe the thermal variability of land surface. The form of the covariance of the random surface forcing is not critical in driving the mesoscale circulation. The thermally induced mesoscale circulation is significant and extends up to about 5 km when the atmosphere is neutral. It becomes weak and is suppressed when the atmosphere is stable. The mesoscale momentum flux is much stronger than the corresponding turbulent momentum flux in the neutral atmosphere, while the two are comparable in the stable atmosphere. The mesoscale heat flux has a different vertical profile than turbulent heat flux and may provide a major heat transport mechanism beyond the planetary boundary layer. The impact of synoptic wind on the mesoscale circulations is relatively weak. Nonlinear advection terms are responsible for momentum flux in the absence of synoptic wind.

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Liao-Fan Lin, Ardeshir M. Ebtehaj, Rafael L. Bras, Alejandro N. Flores, and Jingfeng Wang

Abstract

The objective of this study is to develop a framework for dynamically downscaling spaceborne precipitation products using the Weather Research and Forecasting (WRF) Model with four-dimensional variational data assimilation (4D-Var). Numerical experiments have been conducted to 1) understand the sensitivity of precipitation downscaling through point-scale precipitation data assimilation and 2) investigate the impact of seasonality and associated changes in precipitation-generating mechanisms on the quality of spatiotemporal downscaling of precipitation. The point-scale experiment suggests that assimilating precipitation can significantly affect the precipitation analysis, forecast, and downscaling. Because of occasional overestimation or underestimation of small-scale summertime precipitation extremes, the numerical experiments presented here demonstrate that the wintertime assimilation produces downscaled precipitation estimates that are in closer agreement with the reference National Centers for Environmental Prediction stage IV dataset than similar summertime experiments. This study concludes that the WRF 4D-Var system is able to effectively downscale a 6-h precipitation product with a spatial resolution of 20 km to hourly precipitation with a spatial resolution of less than 10 km in grid spacing—relevant to finescale hydrologic applications for the era of the Global Precipitation Measurement mission.

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