Yongkang Xue

Modeling of land surface evaporation by four schemes and comparison with FIFE observations

We tested four land surface parameterization schemes against long-term (5 months) area-averaged observations over the 15 km × 15 km First International Satellite Land Surface Climatology Project (ISLSCP) Field Experiment (FIFE) area. This approach proved to be very beneficial to understanding the performance and limitations of different land surface models. These four surface models, embodying different complexities of the evaporation/hydrology treatment, included the traditional simple bucket model, the simple water balance (SWB) model, the Oregon State University (OSU) model, and the simplified Simple Biosphere (SSiB) model. The bucket model overestimated the evaporation during wet periods, and this resulted in unrealistically large negative sensible heat fluxes. The SWB model, despite its simple evaporation formulation, simulated well the evaporation during wet periods, but it tended to underestimate the evaporation during dry periods. Overall, the OSU model ably simulated the observed seasonal and diurnal variation in evaporation, soil moisture, sensible heat flux, and surface skin temperature. The more complex SSiB model performed similarly to the OSU model. A range of sensitivity experiments showed that some complexity in the canopy resistance scheme is important in reducing both the overestimation of evaporation during wet periods and underestimation during dry periods. Properly parameterizing not only the effect of soil moisture stress but also other canopy resistance factors, such as the vapor pressure deficit stress, is critical for canopy resistance evaluation. An overly simple canopy resistance that includes only soil moisture stress is unable to simulate observed surface evaporation during dry periods. Given a modestly comprehensive time-dependent canopy resistance treatment, a rather simple surface model such as the OSU model can provide good area-averaged surface heat fluxes for mesoscale atmospheric models.

A Simplified Biosphere Model for Global Climate Studies

MARCH 1991 Center for 0cean—Land—Atmosphere Interactions, Department of Meteorology, University of Maryland, College Park, Maryland Y. XUE, P. J. SELLERS, J. L. KINTER AND J. SHUKLA A Simplified Biosphere Model for Global Climate Studies Y. XUE, P. J. SELLERS, J. L. KINTER AND J. SHUKLA (Manuscript received 8 February 1990, in final form 7 November 1990) ABSTRACT The Simple Biosphere Model (SiB) as described in Sellers et al. is a bio—physically based model of land surface—atmosphere interaction. For some general circulation model (GCM) climate studies, further simplifi- cations are desirable to have greater computation efficiency, and more important, to consolidate the parametric representation. Three major reductions in the complexity of SiB have been achieved in the present study. The diurnal variation of surface albedo is computed in SiB by means of a comprehensive yet complex calculation. Since the diurnal cycle is quite regular for each vegetation type, this calculation can be simplified considerably. The effect of root zone soil moisture on stomatal resistance is substantial, but the computation in SiB is complicated and expensive. We have developed approximations, which simulate the elfects of reduced soil moisture more simply, keeping the essence of the biophysical concepts used in SiB. The surface stress and the fluxes of heat and moisture between the top of the vegetation canopy and an atmospheric reference level have been parameterized in an off-line version of SiB based upon the studies by Businger et al. and Paulson. We have developed a linear relationship between Richardson number and aero- dynamic resistance. Finally, the second vegetation layer of the original model does not appear explicitly after simplification. Compared to the model of Sellers et al., we have reduced the number of input parameters from 44 to 21. A comparison of results using the reduced parameter biosphere with those from the original formulation in a GCM and a zero-dimensional model shows the simplified version to reproduce the original results quite 345 closely. After simplification, the computational requirement of SiB was reduced by about 55%. 1 . Introduction Since Chamey’s ( 1975) pioneering study, several experiments have shown that variations in land surface characteristics can have a significant impact on the cli- mate. The atmosphere is sensitive to the surface albedo, soil moisture, roughness, and other surface character- istics on many time scales ( Chamey et al. 1977; Shukla and Mintz 1982; Rind 1984; Sud et al. 1988). In order to understand these interactions, not only qualitatively but also quantitatively, more realistic sur- face parameterizations than those used in the above studies are required. Since the 1970s, considerable progress in understanding surface micrometeorology has been achieved through theoretical work and ob- servations from field experiments. The results of these studies have been incorporated in simple models of the biosphere which have then been coupled to general circulation models (GCM) of the Earth’s atmosphere (Dickinson et al. 1986; Sellers et al. 1986). These models are more physically and biologically realistic than the preexisting land surface parameterizations used in GCMs. Using these models, some experiments have been carried out to investigate Corresponding author address: Dr. Yong-Kang Xue, Center for Ocean-l.and—Atmosphere Interactions, 2213 Comp. & Space Science Bldg., College Park, MD 20742-2425.

GLACE: The Global Land–Atmosphere Coupling Experiment. Part I: Overview

Abstract The Global Land–Atmosphere Coupling Experiment (GLACE) is a model intercomparison study focusing on a typically neglected yet critical element of numerical weather and climate modeling: land–atmosphere coupling strength, or the degree to which anomalies in land surface state (e.g., soil moisture) can affect rainfall generation and other atmospheric processes. The 12 AGCM groups participating in GLACE performed a series of simple numerical experiments that allow the objective quantification of this element for boreal summer. The derived coupling strengths vary widely. Some similarity, however, is found in the spatial patterns generated by the models, with enough similarity to pinpoint multimodel “hot spots” of land–atmosphere coupling. For boreal summer, such hot spots for precipitation and temperature are found over large regions of Africa, central North America, and India; a hot spot for temperature is also found over eastern China. The design of the GLACE simulations are described in full detai...

The Influence of Land Surface Properties on Sahel Climate. Part 1: Desertification

Abstract This is a general circulation model sensitivity study of the physical mechanisms of the effects of desertification on the Sahel drought. The model vegetation types were changed in the prescribed desertification area, which led to changes in the surface characteristics. The model was integrated for three months (June, July, August) with climatological surface conditions (control) and desertification conditions (anomaly) to examine the summer season response to the changed surface conditions. The control and anomaly experiments consisted of five pairs of integrations with different initial conditions and / or sea surface temperature boundary conditions. In the desertification experiment, the moisture flux convergence and rainfall were reduced in the test area and increased to the immediate south of this area. The simulated anomaly dipole pattern was similar to the observed African drought patterns in which the axis of the maximum rainfall shifts to the south. The circulation changes in the desertif...

The Project for Intercomparison of Land-surface Parameterization / / Schemes PILPS Phase 2 c Red-Arkansas River basin experiment: 1. Experiment description and summary intercomparisons

Abstract Sixteen land-surface schemes participating in the Project for the Intercomparison of Land-surface Schemes (PILPS) Phase 2(c) were run using 10 years (1979–1988) of forcing data for the Red–Arkansas River basins in the Southern Great Plains region of the United States. Forcing data (precipitation, incoming radiation and surface meteorology) and land-surface characteristics (soil and vegetation parameters) were provided to each of the participating schemes. Two groups of runs are presented. (1) Calibration–validation runs, using data from six small catchments distributed across the modeling domain. These runs were designed to test the ability of the schemes to transfer information about model parameters to other catchments and to the computational grid boxes. (2) Base-runs, using data for 1979–1988, designed to evaluate the ability of the schemes to reproduce measured energy and water fluxes over multiple seasonal cycles across a climatically diverse, continental-scale basin. All schemes completed the base-runs but five schemes chose not to calibrate. Observational data (from 1980–1986) including daily river flows and monthly basin total evaporation estimated through an atmospheric budget analysis, were used to evaluate model performance. In general, the results are consistent with earlier PILPS experiments in terms of differences among models in predicted water and energy fluxes. The mean annual net radiation varied between 80 and 105 W m −2 (excluding one model). The mean annual Bowen ratio varied from 0.52 to 1.73 (also excluding one model) as compared to the data-estimated value of 0.92. The run-off ratios varied from a low of 0.02 to a high of 0.41, as compared to an observed value of 0.15. In general, those schemes that did not calibrate performed worse, not only on the validation catchments, but also at the scale of the entire modeling domain. This suggests that further PILPS experiments on the value of calibration need to be carried out.

Evaluation of forest snow processes models (SnowMIP2)

Thirty-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 t ...

The project for intercomparison of land-surface parameterization schemes (PILPS) phase 2(c) Red-Arkansas River basin experiment: 3. Spatial and temporal analysis of water fluxes

The energy components of sixteen Soil-Vegetation Atmospheric Transfer (SVAT) schemes were analyzed and intercompared using 10 years of surface meteorological and radiative forcing data from the Red-Arkansas River basin in the Southern Great Plains of the United States. Comparisons of simulated surface energy fluxes among models showed that the net radiation and surface temperature generally had the best agreement among the schemes. On an average (annual and monthly) basis, the estimated latent heat fluxes agreed (to within approximate estimation errors) with the latent heat fluxes derived from a radiosonde-based atmospheric budget method for slightly more than half of the schemes. The sensible heat fluxes had larger differences among the schemes than did the latent heat fluxes, and the model-simulated ground heat fluxes had large variations among the schemes. The spatial patterns of the model-computed net radiation and surface temperature were generally similar among the schemes, and appear reasonable and consistent with observations of related variables, such as surface air temperature. The spatial mean patterns of latent and sensible heat fluxes were less similar than for net radiation, and the spatial patterns of the ground heat flux vary greatly among the 16 schemes. Generally, there is less similarity among the models in the temporal (interannual) variability of surface fluxes and temperature than there is in the mean fields, even for schemes with similar mean fields.

The Impact of Desertification in the Mongolian and the Inner Mongolian Grassland on the Regional Climate

This is an investigation of the impact of and mechanisms for biosphere feedback in the northeast Asian grassland on the regional climate. Desertification in the Inner Mongolian grassland has dramatically increased during the past 40 years. The Center for Ocean-Land-Atmosphere Studies atmospheric general circulation model, which includes a biosphere model, was used to test the impact of this desertification. In the grassland experiment, areas of Mongolia and Inner Mongolia were specified as grassland. In the desertification experiment, these areas were specified as desert. Each experiment consists of six integrations with different atmospheric initial conditions and different specifications of the extent of the desertification area. All integrations were 90 days in length, beginning in early June and continuing through August, coincident with the period of the East Asian summer monsoon. The desertification had a significant impact on the simulated climate. During the past 40 years, the observed rainfall has decreased in northern and southern China but increased in central China, and the Inner Mongolian grassland and northern China have become warmer. The simulated rainfall and surface temperature differences between the desertification integrations and the grassland integrations are consistent with these observed changes. The water balance and surface energy balance were altered by the desertification. The reduction in evaporation in the desertification experiment dominated the changes in the local surface energy budget. The reduction in convective latent heating above the surface layer enhanced sinking motion (or weakened rising motion) over the desertification area and over the adjacent area to the south. Coincidentally, the monsoon circulation was weakened and the rainfall was reduced.

Simulation of high-latitude hydrological processes in the Torne-Kalix basin: PILPS Phase 2(e) 1: Experiment description and summary intercomparisons

Abstract Twenty-one land-surface schemes (LSSs) participated in the Project for Intercomparison of Land-surface Parameterizations (PILPS) Phase 2(e) experiment, which used data from the Torne–Kalix Rivers in northern Scandinavia. Atmospheric forcing data (precipitation, air temperature, specific humidity, wind speed, downward shortwave and longwave radiation) for a 20-year period (1979–1998) were provided to the 21 participating modeling groups for 218 1/4° grid cells that represented the study domain. The first decade (1979–1988) of the period was used for model spin-up. The quality of meteorologic forcing variables is of particular concern in high-latitude experiments and the quality of the gridded dataset was assessed to the extent possible. The lack of sub-daily precipitation, underestimation of true precipitation and the necessity to estimate incoming solar radiation were the primary data concerns for this study. The results from two of the three types of runs are analyzed in this, the first of a three-part paper: (1) calibration–validation runs—calibration of model parameters using observed streamflow was allowed for two small catchments (570 and 1300 km2), and parameters were then transferred to two other catchments of roughly similar size (2600 and 1500 km2) to assess the ability of models to represent ungauged areas elsewhere; and 2) reruns—using revised forcing data (to resolve problems with apparent underestimation of solar radiation of approximately 36%, and certain other problems with surface wind in the original forcing data). Model results for the period 1989–1998 are used to evaluate the performance of the participating land-surface schemes in a context that allows exploration of their ability to capture key processes spatially. In general, the experiment demonstrated that many of the LSSs are able to capture the limitations imposed on annual latent heat by the small net radiation available in this high-latitude environment. Simulated annual average net radiation varied between 16 and 40 W/m2 for the 21 models, and latent heat varied between 18 and 36 W/m2. Among-model differences in winter latent heat due to the treatment of aerodynamic resistance appear to be at least as important as those attributable to the treatment of canopy interception. In many models, the small annual net radiation forced negative sensible heat on average, which varied among the models between −11 and 9 W/m2. Even though the largest evaporation rates occur in the summer (June, July and August), model-predicted snow sublimation in winter has proportionately more influence on differences in annual runoff volume among the models. A calibration experiment for four small sub-catchments of the Torne–Kalix basin showed that model parameters that are typically adjusted during calibration, those that control storage of moisture in the soil column or on the land surface via ponding, influence the seasonal distribution of runoff, but have relatively little impact on annual runoff ratios. Similarly, there was no relationship between annual runoff ratios and the proportion of surface and subsurface discharge for the basin as a whole.

Use of Midlatitude Soil Moisture and Meteorological Observations to Validate Soil Moisture Simulations with Biosphere and Bucket Models

Abstract Soil moisture observations in sites with natural vegetation were made for several decades in the former Soviet Union at hundreds of stations. In this paper, the authors use data from six of these stations from different climatic regimes, along with ancillary meteorological and actinometric data, to demonstrate a method to validate soil moisture simulations with biosphere and bucket models. Some early and current general circulation models (GCMS) use bucket models for soil hydrology calculations. More recently, the Simple Biosphere Model (SiB) was developed to incorporate the effects of vegetation on fluxes of moisture, momentum, and energy at the earths surface into soil hydrology models. Until now, the bucket and SiB have been verified by comparison with actual soil moisture data only on a limited basis. In this study, a Simplified SiB (SSIB) soil hydrology model and a 15-cm bucket model are forced by observed meteorological and actinometric data every 3 h for 6-yr simulations at the six statio...