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  • Author or Editor: Joseph G. Alfieri x
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Joseph G. Alfieri
,
Peter D. Blanken
,
David N. Yates
, and
Konrad Steffen

Abstract

Nearly one-half of the earth’s terrestrial surface is susceptible to drought, which can have significant social, economic, and environmental impacts. Therefore, it is important to develop better descriptions and models of the processes linking the land surface and atmosphere during drought. Using data collected during the International H2O Project, the study presented here investigates the effects of variations in the environmental factors driving the latent heat flux (λE) during drought conditions at a rangeland site located in the panhandle of Oklahoma. Specifically, this study focuses on the relationships of λE with vapor pressure deficit, wind speed, net radiation, soil moisture content, and greenness fraction. While each of these environmental factors has an influence, soil moisture content is the key control on λE. The role of soil moisture in regulating λE is explained in terms of the surface resistance to water vapor transfer. The results show that λE transitioned between being water or energy limited during the course of the drought. The implications of this on the ability to understand and model drought conditions and transitions into or out of droughts are discussed.

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Cezar Kongoli
,
William P. Kustas
,
Martha C. Anderson
,
John M. Norman
,
Joseph G. Alfieri
,
Gerald N. Flerchinger
, and
Danny Marks

Abstract

The utility of a snow–vegetation energy balance model for estimating surface energy fluxes is evaluated with field measurements at two sites in a rangeland ecosystem in southwestern Idaho during the winter of 2007: one site dominated by aspen vegetation and the other by sagebrush. Model parameterizations are adopted from the two-source energy balance (TSEB) modeling scheme, which estimates fluxes from the vegetation and surface substrate separately using remotely sensed measurements of land surface temperature. Modifications include development of routines to account for surface snowmelt energy flux and snow masking of vegetation. Comparisons between modeled and measured surface energy fluxes of net radiation and turbulent heat showed reasonable agreement when considering measurement uncertainties in snow environments and the simplified algorithm used for the snow surface heat flux, particularly on a daily basis. There was generally better performance over the aspen field site, likely due to more reliable input data of snow depth/snow cover. The model was robust in capturing the evolution of surface energy fluxes during melt periods. The model behavior was also consistent with previous studies that indicate the occurrence of upward sensible heat fluxes during daytime owing to solar heating of vegetation limbs and branches, which often exceeds the downward sensible heat flux driving the snowmelt. However, model simulations over aspen trees showed that the upward sensible heat flux could be reversed for a lower canopy fraction owing to the dominance of downward sensible heat flux over snow. This indicates that reliable vegetation or snow cover fraction inputs to the model are needed for estimating fluxes over snow-covered landscapes.

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Wade T. Crow
,
Concepcion Arroyo Gomez
,
Joaquín Muñoz Sabater
,
Thomas Holmes
,
Christopher R. Hain
,
Fangni Lei
,
Jianzhi Dong
,
Joseph G. Alfieri
, and
Martha C. Anderson

Abstract

The assimilation of L-band surface brightness temperature (Tb) into the land surface model (LSM) component of a numerical weather prediction (NWP) system is generally expected to improve the quality of summertime 2-m air temperature (T2m) forecasts during water-limited surface conditions. However, recent retrospective results from the European Centre for Medium-Range Weather Forecasts (ECMWF) suggest that the assimilation of L-band Tb from the European Space Agency’s (ESA) Soil Moisture Ocean Salinity (SMOS) mission may, under certain circumstances, degrade the accuracy of growing-season 24-h T2m forecasts within the central United States. To diagnose the source of this degradation, we evaluate ECMWF soil moisture (SM) and evapotranspiration (ET) forecasts using both in situ and remote sensing resources. Results demonstrate that the assimilation of SMOS Tb broadly improves the ECMWF SM analysis in the central United States while simultaneously degrading the quality of 24-h ET forecasts. Based on a recently derived map of true global SM–ET coupling and a synthetic fraternal twin data assimilation experiment, we argue that the spatial and temporal characteristics of ECMWF SM analyses and ET forecast errors are consistent with the hypothesis that the ECMWF LSM overcouples SM and ET and, as a result, is unable to effectively convert an improved SM analysis into enhanced ET and T2m forecasts. We demonstrate that this overcoupling is likely linked to the systematic underestimation of root-zone soil water storage capacity by LSMs within the U.S. Corn Belt region.

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Margaret A. LeMone
,
Fei Chen
,
Joseph G. Alfieri
,
Mukul Tewari
,
Bart Geerts
,
Qun Miao
,
Robert L. Grossman
, and
Richard L. Coulter

Abstract

Analyses of daytime fair-weather aircraft and surface-flux tower data from the May–June 2002 International H2O Project (IHOP_2002) and the April–May 1997 Cooperative Atmosphere Surface Exchange Study (CASES-97) are used to document the role of vegetation, soil moisture, and terrain in determining the horizontal variability of latent heat LE and sensible heat H along a 46-km flight track in southeast Kansas. Combining the two field experiments clearly reveals the strong influence of vegetation cover, with H maxima over sparse/dormant vegetation, and H minima over green vegetation; and, to a lesser extent, LE maxima over green vegetation, and LE minima over sparse/dormant vegetation. If the small number of cases is producing the correct trend, other effects of vegetation and the impact of soil moisture emerge through examining the slope ΔxyLE/Δxy H for the best-fit straight line for plots of time-averaged LE as a function of time-averaged H over the area. Based on the surface energy balance, H + LE = R netG sfc, where R net is the net radiation and G sfc is the flux into the soil; R netG sfc ∼ constant over the area implies an approximately −1 slope. Right after rainfall, H and LE vary too little horizontally to define a slope. After sufficient drying to produce enough horizontal variation to define a slope, a steep (∼−2) slope emerges. The slope becomes shallower and better defined with time as H and LE horizontal variability increases. Similarly, the slope becomes more negative with moister soils. In addition, the slope can change with time of day due to phase differences in H and LE. These trends are based on land surface model (LSM) runs and observations collected under nearly clear skies; the vegetation is unstressed for the days examined. LSM runs suggest terrain may also play a role, but observational support is weak.

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