Biosphere-Atmosphere Transfer Scheme Research Articles

Coupling of Integrated Biosphere Simulator to Regional Climate Model Version 3

Abstract A description of the coupling of Integrated Biosphere Simulator (IBIS) to Regional Climate Model version 3 (RegCM3) is presented. IBIS introduces several key advantages to RegCM3, most notably vegetation dynamics, the coexistence of multiple plant functional types in the same grid cell, more sophisticated plant phenology, plant competition, explicit modeling of soil/plant biogeochemistry, and additional soil and snow layers. A single subroutine was created that allows RegCM3 to use IBIS for surface physics calculations. A revised initialization scheme was implemented for RegCM3–IBIS, including an IBIS-specific prescription of vegetation and soil properties. To illustrate the relative strengths and weaknesses of RegCM3–IBIS, one 4-yr numerical experiment was completed to assess ability of both RegCM3–IBIS (with static vegetation) and RegCM3 with its native land surface model, Biosphere–Atmosphere Transfer Scheme 1e (RegCM3–BATS1e), to simulate the energy and water budgets. Each model was evaluated using the NASA Surface Radiation Budget, FLUXNET micrometeorological tower observations, and Climate Research Unit Time Series 2.0. RegCM3–IBIS and RegCM3–BATS1e simulate excess shortwave radiation incident and absorbed at the surface, especially during the summer months. RegCM3–IBIS limits evapotranspiration, which allows for the correct estimation of latent heat flux, but increases surface temperature, sensible heat flux, and net longwave radiation. RegCM3–BATS1e better simulates temperature, net longwave radiation, and sensible heat flux, but systematically overestimates latent heat flux. This objective comparison of two different land surface models will help guide future adjustments to surface physics schemes within RegCM3.

Land surface coupling in regional climate simulations of the West African monsoon

Coupling of the Community Land Model (CLM3) to the ICTP Regional Climate Model (RegCM3) substantially improves the simulation of mean climate over West Africa relative to an older version of RegCM3 coupled to the Biosphere Atmosphere Transfer Scheme (BATS). Two 10-year simulations (1992–2001) show that the seasonal timing and magnitude of mean monsoon precipitation more closely match observations when the new land surface scheme is implemented. Specifically, RegCM3–CLM3 improves the timing of the monsoon advance and retreat across the Guinean Coast, and reduces a positive precipitation bias in the Sahel and Northern Africa. As a result, simulated temperatures are higher, thereby reducing the negative temperature bias found in the Guinean Coast and Sahel in RegCM3–BATS. In the RegCM3–BATS simulation, warmer temperatures in northern latitudes and wetter soils near the coast create excessively strong temperature and moist static energy gradients, which shifts the African Easterly Jet further north than observed. In the RegCM3–CLM3 simulation, the migration and position of the African Easterly Jet more closely match reanalysis winds. This improvement is triggered by drier soil conditions in the RegCM3–CLM3 simulation and an increase in evapotranspiration per unit precipitation. These results indicate that atmosphere–land surface coupling has the ability to impact regional-scale circulation and precipitation in regions exhibiting strong hydroclimatic gradients.

Improvement of surface albedo simulations over arid regions

To improve the simulation of the surface radiation budget and related thermal processes in arid regions, three sophisticated surface albedo schemes designed for such regions were incorporated into the Biosphere-Atmosphere Transfer Scheme (BATS). Two of these schemes are functions of the solar zenith angle (SZA), where the first one has one adjustable parameter defined as SZA1 scheme, and the second one has two empirical parameters defined as SZA2 scheme. The third albedo scheme is a function of solar angle and soil water that were developed based on arid-region observations from the Dunhuang field experiment (DHEX) (defined as DH scheme). We evaluated the performance of the original and newly-incorporated albedo schemes within BATS using the in-situ data from the Oasis System Energy and Water Cycle Field Experiment that was carried out in JinTa, Gansu arid area (JTEX). The results indicate that a control run by the original version of the BATS generates a constant albedo, while the SZA1 and SZA2 schemes basically can reproduce the observed diurnal cycle of surface albedo, although these two schemes still underestimate the albedo when SZA is high in the early morning and late afternoon, and overestimate it when SZA is low during noontime. The SZA2 scheme has a better overall performance than the SZA1 scheme. In addition, BATS with the DH scheme slightly improves the albedo simulation in magnitude as compared to that from the control run, but a diurnal cycle of albedo is not produced by this scheme. The SZA1 and SZA2 schemes significantly increase the surface absorbed solar radiation by nearly 70 W m−2, which further raises the ground temperature by 6 K and the sensible heat flux by 35 W m−2. The increased solar radiation, heat flux, and temperature are more consistent with the observations that those from the control run. However, a significant improvement in these three variables is not found in BATS with the DH scheme due to the neglect of the diurnal cycle of albedo. Further analysis indicates that during cloudy days the solar radiation simulations of BATS with these three schemes are not in a good agreement with the observations, which implies that a more realistic partitioning of diffuse and direct radiation is needed in future land surface process simulations.

Simulation of snow processes beneath a boreal scots pine canopy

A physically-based multi-layer snow model Snow-Atmosphere-Soil-Transfer scheme (SAST) and a land surface model Biosphere-Atmosphere Transfer Scheme (BATS) were employed to investigate how boreal forests influence snow accumulation and ablation under the canopy. Mass balance and energetics of snow beneath a Scots pine canopy in Finland at different stages of the 2003-2004 and 2004-2005 snow seasons are analyzed. For the fairly dense Scots pine forest, drop-off of the canopy-intercepted snow contributes, in some cases, twice as much to the underlying snowpack as the direct throughfall of snow. During early winter snow melting, downward turbulent sensible and condensation heat fluxes play a dominant role together with downward net longwave radiation. In the final stage of snow ablation in middle spring, downward net allwave radiation dominates the snow melting. Although the downward sensible heat flux is comparable to the net solar radiation during this period, evaporative cooling of the melting snow surface makes the turbulent heat flux weaker than net radiation. Sensitivities of snow processes to leaf area index (LAI) indicate that a denser canopy speeds up early winter snowmelt, but also suppresses melting later in the snow season. Higher LAI increases the interception of snowfall, therefore reduces snow accumulation under the canopy during the snow season; this effect and the enhancement of downward longwave radiation by denser foliage outweighs the increased attenuation of solar radiation, resulting in earlier snow ablation under a denser canopy. The difference in sensitivities to LAI in two snow seasons implies that the impact of canopy density on the underlying snowpack is modulated by interannual variations of climate regimes.

지표 에너지 수지에 미치는 구름의 복사 역할

In this study, the Slab Ocean Model (SOM) is coupled with an Atmospheric General Circulation Model (AGCM) which developed in University of Kangnung based on the land surface model of Biosphere-Atmosphere Transfer Scheme (BATS). The purposes of this study are to understand radiative role of clouds considering of the atmospheric feedback, and to compare the Clouds Radiative Forcing (CRF) come from the analyses using the clear-cloud sky method and CGCM. The new CGCM was integrated by using two sets of the clouds with radiative role (EXP-A) and without radiative role (EXP-B). Clouds in this two cases show the negative effect of difference of radiation budget at top of atmosphere (TOA). The annual global means radiation budget of this simulation at TOA is larger than the estimations () came from Earth Radiation Budget Experiment (ERBE). The work showed the surface negative effect with in the two different simulations of CRF. Otherwise, sensible heat flux in the simulation shows a great contribution with positive forcing of . It is found that cooling effect to the surface temperature due to radiative role of clouds is about . From this study it could make an accurate of the different CRF estimation considering either feedback of EXP-B or not EXP-A under clear-sky and cloud-sky conditions respectively at TOA. This result clearly shows its difference of CRF .

Comparison of ground‐based and airborne snow surface albedo parameterizations in an alpine watershed: Impact on snowpack mass balance

Two commonly used snow surface albedo models were evaluated using albedo data from the Airborne Visible/Infrared Imaging Spectroradiometer (AVIRIS), and their influence on snowmelt timing and magnitude was assessed using a net radiation/temperature index snowmelt model, a series of satellite‐based snow covered area scenes, and on‐site snow surveys. Albedo estimates using an explicit representation of snow surface temperature, snow age, and solar illumination angle, based on the Biosphere Atmosphere Transfer Scheme (BATS), were within the 0.02 AVIRIS measurement error for 78% of the snow‐covered portions of the watershed. Conversely, albedo values estimated using a simple model based solely on snow surface age underestimated AVIRIS‐observed albedo. Correlations between the timing of snowmelt and observed runoff using the BATS albedo model (R2 = 0.69) were significantly better than those using the age‐based approach (R2 = 0.59) and were comparable to using AVIRIS data (R2 = 0.73). Snow extent was simulated most accurately with the AVIRIS parameterization; average map accuracy was 79 and 10% greater than when using the age‐based and BATS albedo parameterizations, respectively. The error in snow water equivalent for April was 14% for BATS versus 39% for the age‐based albedo; however, it was less than 1% for simulations using AVIRIS albedo data. Thus the BATS albedo estimates performed better than the age‐based albedo but did not outperform simulations using AVIRIS albedo data.

The Hydrological Balance of the October 2000 Flood in Piedmont, Italy: Quantitative Analysis and Simulation

This paper aims to analyze in detail the flood event that occurred in October 2000 over the northwestern Italian regions and to test the capability of mesoscale model RAMS-LSPM in reproducing the main characteristics of the hydrological budget components during the event. On 13-16 October 2000, a deep, quasi-stationary trough hung over the western Mediterranean, causing extreme precipitation over northwestern Italy. Values exceeded 600 mm in four days, causing huge flooding and landslides with significant damage to houses and infrastructures. Also several lives were reported lost in the Italian regions of Piedmont and Aosta Valley. This disastrous flood was associated with heavy rainfall episodes over a relatively small area during the course of a four-day period. The intense rainfall over the Alps was enhanced by the confluence of the surface southeasterly flow and of the upper-level southerly current. This confluence was strongest over the zones where the maxima of rainfall and vertical wind velocity were observed. This event was analyzed in detail, using the observational network of the Piedmont Region, the GTS network, and model analyses. The interest was focused on the detailed distribution of precipitation in time and space, in order to understand the dominant role of complex orography in enhancing and modifying the precipitation distribution, and on the hydrological budget. The mesoscale Regional Atmospheric Modelling System (RAMS), driven by the European Centre for Medium-Range Weather Forecasts analyses, was used to simulate this event. The interest was focused on the hydrologic budget during the flood; thus the original soil water balance scheme of RAMS (a simplified version of BATS, the Biosphere Atmosphere Transfer Scheme) was replaced by the Land Surface Process Model (LSPM). This method, already applied in the analysis of a previous flood that occurred on the same region in 1994, allowed all components of the hydrologic budget to be inferred during the flood episode, particularly the surface runoff and soil moisture content. The results of the simulation demonstrated that the coupled model RAMS-LSPM was able to give a quite realistic representation of the flood. The coupling with LSPM improved RAMS not only because the coupled model could represent the upper- and surface-level fields (geopotential, potential temperature, and specific humidity), but also because it provided quantitative estimates of the hydrologic budget and other surface parameters.

The coupling of the Common Land Model (CLM0) to a regional climate model (RegCM)

We replace the existing land surface parameterization scheme, the Biosphere-Atmosphere Transfer Scheme (BATS), in a regional climate model (RegCM) with the newly developed Common Land Model (CLM0). The main improvements of CLM0 include a detailed 10-layer soil model, the distinction between soil ice and water phases, a linked photosynthesis-stomatal conductance model, a multilayer snow model, and an improved runoff parameterization. We compare the performance of CLM0 and BATS as coupled to the RegCM in a one year simulation over East Asia. We find that the RegCM/CLM0 improves the winter cold bias present in the RegCM/BATS simulation. With respect to the surface energy balance, lower CLM0 albedos allow the absorption of more solar radiation at the surface. CLM0 tends to simulate higher sensible heat and lower latent heat fluxes than its BATS counterpart. The surface water balance also changes considerably between the two land surface schemes. Compared to BATS, CLM0 precipitation is reduced overall and surface runoff is increased, thereby allowing less water to enter the soil column. Evapotranspiration is lower in CLM0 due to lower ground evaporation, which leads to a wetter surface soil in CLM0 in spite of less precipitation input. However, transpiration is greater in CLM0 than BATS, which has an overall effect of less surface storage during the summertime. Comparison with station observations indicates that CLM0 tends to improve the simulation of root zone soil water content compared to BATS. Another pronounced difference between the two schemes is that CLM0 produces lower snow amounts than BATS because of different snow models and warmer CLM0 temperatures. In this case, BATS snow cover amounts are more in line with observations. Overall, except for the snow amounts, CLM0 appears to improve the RegCM simulation of the surface energy and water budgets compared to BATS.

Inclusion of Urban Landscape in a Climate Model: How Can Satellite Data Help?

rban regions, which cover only approximately 0.2% of the earths’ land surface, contain about half of the human population (UNPD 2001). Modeling urban weather and climate is critical for human welfare, but has been hampered for at least two reasons: i) no urban landscape has been included in global and regional climate models (GCMs and RCMs, respectively), and ii) detailed information on urban characteristics is hard to obtain. With the advance of satellite observations, adding urban schemes into climate models in order to scale pro-jections of global/regional climate to urban areas becomes essential. Inclusion of urbanized landscape into climate models was discussed in depth at the fall American Geophysical Union (AGU) meeting of 2003 in the session entitled “Human-induced climate variations linked to urbanization: From observations to modeling,” which took place on 12 December 2003 in San Francisco, California (most of the presenta-tions of this session can be found online at www.atmos.umd.edu/~mjin/AGU03urban.html). The following notes summarize what is known and what needs to be advanced on this topic.In a GCM and RCM, land physical processes are simulated in a land surface model, which is coupled with the atmosphere model through exchanges of heat fluxes, water, and momentum. Currently, an urban classification is not included in any major GCM/RCM land surface model [e.g., the second National Center for Atmospheric Research (NCAR) Community Land Model (CLM2), National Aero-nautics and Space Administration (NASA) Global Modeling and Assimilation Office (GMAO) unified land surface model, Biosphere–Atmosphere Transfer Scheme (BATS), simple Biosphere model, version 2 (SIB2), etc.]. This exclusion makes GCMs/RCMs in-adequate for realistically simulating urban modifica-tions to climate.The same land surface model can be coupled to a GCM or RCM. For example, the NCAR CLM is coupled to both the NCAR community atmosphere

Design of a Regional Climate Model for the Simulation of South China Summer Monsoon Rainfall

The objective of this study is to modify a regional climate model (RCM)—the Regional Climate Model of the National Climate Center of China—to simulate the summer monsoon rainfall over South China and the South China Sea. Such a modification is necessary because this RCM was designed for studying the climate over central and north China where precipitation processes are very different from those occurring further south so that simulations using the basic parameters of the original model give precipitation amounts much less than those observed.Using the National Centers for Environmental Prediction/National Center for Atmospheric Research (NCEP/NCAR) reanalysis data, many sensitivity experiments have been carried out for the months of April to June 1998, which include modifying the cumulus parameterization scheme, the large-scale precipitation scheme, the radiation scheme, the surface exchange processes, and the size of the buffer zone. The design of all the experiments is either to enhance the moisture provision to the atmosphere over South China and the South China Sea, or to help the model atmosphere realize the moisture to form precipitation. It is found that indeed modifications to the various parameters can produce rainfall amounts much closer to those observed.Based on the results of these experiments, an “optimal” design of the RCM is reached and tested for its effectiveness using the NCEP reanalyses for two wet years (1994 and 1997) and two dry years (1996 and 1999) during which rainfall in May and June over South China were above/below normal respectively. The physical processes in this design include the Kuo scheme for convective precipitation, the Pal scheme for large-scale precipitation, the Holtslag scheme for the planetary boundary layer, the radiation transfer scheme of the NCAR Community Climate Model Version 3, and the Biosphere-Atmosphere Transfer Scheme for the land surface process. The width of the buffer zone is reduced and the effective cloud droplet radius is fixed at different values over land and ocean. The neutral drag coefficient is prescribed as a function of surface wind speed, and the heat and moisture exchange coefficients are set at values larger than that of momentum. The simulations based on this design for all the five years are found to be much closer to observations than those from the control.

The Common Land Model

The Common Land Model (CLM) was developed for community use by a grassroots collaboration of scientists who have an interest in making a general land model available for public use and further development. The major model characteristics include enough unevenly spaced layers to adequately represent soil temperature and soil moisture, and a multilayer parameterization of snow processes; an explicit treatment of the mass of liquid water and ice water and their phase change within the snow and soil system; a runoff parameterization following the TOPMODEL concept; a canopy photo synthesis-conductance model that describes the simultaneous transfer of CO2 and water vapor into and out of vegetation; and a tiled treatment of the subgrid fraction of energy and water balance. CLM has been extensively evaluated in offline mode and coupling runs with the NCAR Community Climate Model (CCM3). The results of two offline runs, presented as examples, are compared with observations and with the simulation of three other land models [the Biosphere-Atmosphere Transfer Scheme (BATS), Bonan's Land Surface Model (LSM), and the 1994 version of the Chinese Academy of Sciences Institute of Atmospheric Physics LSM (IAP94)].

Impacts of model calibration on high-latitude land-surface processes: PILPS 2(e) calibration/validation experiments

In the PILPS 2(e) experiment, the Snow Atmosphere Soil Transfer (SAST) land-surface scheme developed from the Biosphere–Atmosphere Transfer Scheme (BATS) showed difficulty in accurately simulating the patterns and quantities of runoff resulting from heavy snowmelt in the high-latitude Torne–Kalix River basin (shared by Sweden and Finland). This difficulty exposes the model deficiency in runoff formations. After representing subsurface runoff and calibrating the parameters, the accuracy of hydrograph prediction improved substantially. However, even with the accurate precipitation and runoff, the predicted soil moisture and its variation were highly “model-dependent”. Knowledge obtained from the experiment is discussed.

Effects of the land-surface heterogeneities in temperature and moisture from the “combined approach” on regional climate: a sensitivity study

In order to better understand the land–atmosphere interactions and increase the predictability of climate models, it is very important to investigate the effects of land-surface heterogeneities, in which the temperature and moisture heterogeneities are very significant. In this paper, the land-surface scheme BATS [Dickinson, R.E., Henderson-Sellers, A., Kennedy, P.J., Wilson, M.F., 1993. Biosphere /Atmosphere Transfer Scheme (BATS) Version 1e as Coupled to the NCAR Community Climate Model. NCAR Tech. Note TN-387+STR, National Center for Atmospheric Research, Boulder, CO], in the NCAR regional climate model RegCM2, was treated with a “combined approach” that is computationally effective to represent land-surface heterogeneities in temperature and moisture, and was tested by using real data of China during the summer monsoon in 1991 as initial and boundary conditions. Different from the results of the off-line simulations for warm season in Giorgi [Mon. Weather Rev. 125 (1997a) 1900], as for temperature, we used a cosine probability density function (PDF), which is more effective in computation and different from the linear PDF applied by Giorgi [Mon. Weather Rev. 125 (1997b) 1885]; we can see that the summer monsoon climate is generally sensitive to the temperature heterogeneity (e.g., precipitation is sensitive to the temperature heterogeneity). Similar to the results in Giorgi [Mon. Weather Rev. 125 (1997b) 1900], the regional climate seems to be very sensitive to the moisture heterogeneity, which shows a regularity as changing with the heterogeneity, i.e., with the heterogeneity increasing, the mean sensible heat flux is generally increased, while the mean latent heat flux is generally decreased. So, the capability of simulation for summer monsoon climate may be improved via the appropriate representation of the heterogeneities in temperature and moisture. In addition, other results reveal the limitations of off-line experiments, and therefore the coupling of the land-surface scheme (with the inclusion of heterogeneity representation) to the atmospheric model is necessary for the study on land–atmosphere interactions.

Correcting the orbit drift effect on AVHRR land surface skin temperature measurements

The orbital drift of the National Oceanic and Atmospheric Administration (NOAA)-7, -9, -11, -14 series of satellites results in a significant cooling effect on their afternoon path Advanced Very High Resolution Radiometer (AVHRR) land surface skin temperature (Ts ) measurements. This effect mixes with the signal of true variations in the climate system, and thus prevents Ts from being directly used in climate change and global warming studies. This paper applies a physically based ‘typical pattern technique’ to remove the orbit drift effect from Ts . The technique utilizes a lookup table of representative land skin temperature diurnal cycles derived from the National Center for Atmospheric Research (NCAR) Climate Community Model (CCM3) coupled with the land surface model, Biosphere–Atmosphere Transfer Scheme (BATS). The generated typical patterns of Ts diurnal cycle are functions of vegetation type, season and latitude, and are combined with satellite observations to remove the cooling effect. Applying this methodology to eighteen years of AVHRR (1981–1998) Ts observations yields an improved skin temperature dataset. Analysis of the drift-corrected skin temperature illustrates a warming trend at the surface over the past two decades, a result which agrees well with the observed surface air temperature trend. A discussion of uncertainties in this technique is also presented.

The flood of November 1994 in Piedmont, Italy: a quantitative analysis and simulation

AbstractThe disastrous flood that occurred in the southern area of Piedmont (north‐western Italy) at the beginning of November 1994 was associated with heavy rainfall episodes over a relatively small area in a course of events spanning the period 3–6 November 1994. The most intense rainfall (for which values over 200 mm were reported) occurred in two regions located in the upper reach of the Tanaro and Bormida river basins (Maritime Alps) and over the north‐west sector of the Alps. The distribution of rainfall intensities was different in the two areas where the precipitation peaks were observed. In the former, almost all rainfall was concentrated between the 4 and 5 November; in the second, rainfall was intense but spread over the entire period. The intense rainfall over these two mountain areas was enhanced by the confluence of the surface south‐easterly flow and of the upper‐level southerly current. This confluence was strongest over the two zones in which the maxima of rainfall and vertical wind velocity were observed. The cyclonic area was stationary over Western Europe for three consecutive days (4–6 November), due to the blocking situation over Eastern Europe. The mesoscale Regional Atmospheric Modelling System (RAMS), driven by the European Centre for Medium‐Range Weather Forecasts analyses, was used to simulate this event. We focused our attention on the target area (Tanaro and Bormida valleys). As we were interested in the hydrologic budget during the flood, we replaced the original soil scheme of RAMS (a version of Biosphere Atmosphere Transfer Scheme (BATS), too simplified to allow very detailed pattern resolution) with the Land Surface Process Model (LSPM). This method allowed all components of the hydrologic budget to be inferred during the flood episode, particularly the runoff and soil moisture content. The results of the simulation demonstrated that the coupled model RAMS–LSPM was able to give a quite realistic representation of a mesoscale event such as the flood event in this study. The coupling with LSPM improved RAMS not only because the coupled model can represent the upper‐ and surface‐level fields (geopotential, potential temperature and specific humidity), but also because it provides quantitative estimates of the hydrologic budget and other surface parameters. Copyright © 2002 John Wiley & Sons, Ltd.

Impacts of Climate Change and Land Use Change on Runoff from a Great Lakes Watershed

Daily VEMAP output from the Hadley Coupled Climate Model (HadCM2) and land use projections from the Southeastern Michigan Council of Governments are used to examine the impacts of climate change and land use change on a regional watershed in southeastern lower Michigan. The precipitation, temperature, moisture, and solar radiation output from HadCM2 are processed before they are used as input to a modified version of the Biosphere-Atmosphere Transfer Scheme (BATS). The modified BATS model (BATS/HYDRO) includes the original 18 BATS land use types along with six new urban land classes as well as an improved surface runoff model, which accounts for impervious surfaces and depression storage. The daily VEMAP output is verified against observations and shown to be appropriate for use as input to the BATS/HYDRO model. The BATS/HYDRO model is then tested with observed NCEP/NCAR Reanalysis Data and shown to reproduce observed runoff for the period 1990 to 1992 with minimal tuning of initial soil moisture content and daily rainfall distribution. The BATS/HYDRO model is then run using VEMAP output as input for two time periods, 1994 to 2003 and 2090 to 2099 and two land use scenarios, current and future. Model results show that changing climate and changing land use will increase the percentage of precipitation that results in surface runoff from 17.1% to 21.4%. This 4.3% increase is partitioned into a 2.5% increase due to climate change and a 1.6% increase due to land use change.

Global Vegetation Root Distribution for Land Modeling

Abstract Vegetation root distribution is one of the factors that determine the overall water holding capacity of the land surface and the relative rates of water extraction from different soil layers for vegetation transpiration. Despite its importance, significantly different root distributions are used by different land surface models. Using a comprehensive global field survey dataset, vegetation root distribution (including rooting depth) has been developed here for three of the most widely used land cover classifications [i.e., the Biosphere–Atmosphere Transfer Scheme (BATS), International Geosphere–Biosphere Program (IGBP), and version 2 of the Simple Biosphere Model (SiB2)] for direct use by any land model with any number of soil layers.

Comparison of albedos computed by land surface models and evaluation against remotely sensed data

The albedos of two land surface models, the Biosphere‐Atmosphere Transfer Scheme (BATS) and the NCAR Land Surface Model (LSM), are compared with remotely sensed data and each other. The model albedos differ primarily because of their assumptions about and model differences in soil moisture content, soil color, snow albedo, shading of snow by canopy, and prescribed parameters for each land cover type. Global albedo maps for February and July 1995, developed from the advanced very high resolution radiometer (AVHRR) data, are used to evaluate model albedos. The models display a high bias as compared to the remotely sensed values in desert and semidesert regions. Over North Africa, LSM, whose albedos were previously tuned to data from the Earth Radiation Budget Experiment (ERBE), has the highest albedos. Elsewhere, and overall, BATS has the highest bias for desert and semidesert regions. Both models demonstrate a high bias over regions of winter snow, where the AVHRR data are expected to have a negative bias. LSM has especially high winter albedos, apparently because of intercepted snow increasing its canopy albedo.

Impact of field-calibrated vegetation parameters on GCM climate simulations

This paper describes a study in which, for the first time, advanced systems-engineering parameter-estimation techniques were applied to data from several field studies to estimate the preferred set of parameters for some of the most common biomes represented in an advanced Soil-Vegetation-Atmosphere Transfer (SVAT) scheme (BATS2, a recent version of the Biosphere-Atmosphere Transfer Scheme); the effect on modelled climate was also investigated. Observational data from field sites in Brazil, Canada, Arizona and Kansas/Oklahoma in the USA, and the Netherlands were chosen as representative of tropical rain forest, coniferous forest, semi-arid vegetation, agricultural crops, and grassland biomes, respectively. Together, these five biomes make up 50% of the land area represented in BATS2. Multi-criteria calibration algorithms do not produce a unique set of model parameters and, when different combinations of the available objective functions at each site are considered, the number of solutions increases substantially. The need for a single parameter-set for each site (biome) is an important practical issue that was necessarily addressed in this study. A procedure was defined in which optimized parameter-sets were successively discarded by successively applying a cut-off threshold to single observable objective functions following a preference hierarchy. In this study, only the vegetation-related parameters are calibrated for each of the five biomes and implemented into BATS2; however, in a separate experiment, the effect of including soil parameters in the optimization was investigated. When the calibrated parameters are adopted and used in BATS2, there are significant changes between the climates calculated in an eight-year run with Version 3 of the Community Climate Model and in an equivalent eight-year run in which the original default parameters were used. The overall conclusion of this exploratory study is that advanced parameter-estimation techniques and appropriate field data can be used successfully to improve representation of surface exchanges and the modelled climate given by a GCM, by defining appropriate values for vegetation-related parameters in an advanced SVAT scheme.

Impact of Small-Scale Rainfall Variability on Larger-Scale Spatial Organization of Land–Atmosphere Fluxes

A coupled modeling framework is used in this study to investigate the effect of subgrid-scale rainfall variability on the spatial structure of the evolving storm and on other surface variables and water and energy fluxes. The Fifth-Generation Pennsylvania State University–National Center for Atmospheric Research Mesoscale Model coupled with the Biosphere–Atmosphere Transfer Scheme is combined with a dynamical/statistical scheme for statistically downscaling rainfall. Model simulations with and without including subgrid-scale rainfall variability are compared at the grid scale to quantify the propagation of small-scale rainfall heterogeneities through the nonlinear land–atmosphere system. It was found that including subgrid-scale rainfall variability (here on the order of 3 km) affects the spatial organization of the storm system itself, surface temperature, soil moisture, and sensible and latent heat fluxes. These effects were found to occur at spatial scales much larger than the scale at which rainfall variability was prescribed, illustrating the pronounced nonlinear spatial dynamics of the land–atmosphere system and its important role on hydrometeorological predictions.