G. Modeling of Land-Surface Processes and the Application to Numerical Weather Forecasting
[Background]
[Validating/Improving Land-Surface Models]
[Improving the Parameterization Scheme of the Atmospheric
Surface Layer]
[WRF land-surface model development and AFWA ARGMET improvements]
[Warm-Season Evaporation Study]
[Real-Time Weather Forecasts with the Land-Surface/MM5
Coupled System and Soil Moisture Data Assimilation]
In this research and application area, our objectives are to understand, through theoretical and observational studies, the complex interactions between the land-surface and the atmosphere at micro- and meso-scales, and to use these understandings to improve land-surface models. The ultimate goal is to integrate such knowledge into numerical mesoscale weather prediction and regional climate models in order to improve predictions of the impacts of land-surface processes on regional weather, climate, and hydrology. To achieve these objectives, a number of research and application studies are conducted.
2.Validating/Improving Land-Surface Models With CASES-97
Data
This research is a collaborative effort funded by NASA Land-Surface Hydrology Program. Participants include D. Yates and F. Chen of RAP/NCAR; P. LeMone of MMM/NCAR; S. Oncley of ATD/NCAR; R. Grossman of the University of Colorado, and H. Nagai at the Japan Atomic Energy Research Institute. The project's goal is to understand the impacts of surface heterogeneity in soil moisture and surface characteristics on the transport of temperature and moisture in the atmospheric boundary layer.
The
research project focuses on the parameterization of subgrid-scale
variability for mesoscale and large-scale atmospheric models. One-month
observations obtained from CASES-97 were used to create a gridded
multi-scale (1, 5, and 10 km) data set over an area of 71x74 km^2.
Three land-surface models were used to simulate the surface heat flux
at these scales. These land-surface models include the relatively
simple OSULSM, the NCARLSM, and the complex SOLVEG that has nine canopy
layers and seven soil layers.
Figure G1 shows daytime latent heat fluxes as simulated by the above three models and as observed by eight surface stations during CASES-97 field campaign. Preliminary validation against CASES-97 observations demonstrates that these land-surface models reasonably captured the spatial heterogeneity caused by rainfall and surface characteristics at small scales.
Figure G2 shows the comparison of soil moisture between three models and observations obtained at the CASES97 stations 7 (winter wheat) at about 5 cm and 20 cm. Soil moisture in three LSMs has faster response to precipitation in soil layers closer to the ground surface. However, soil moisture evolves differently in three LSMs. For instance, more water is able to penetrate in deep layer of SOLVEG, and NCARLSM is wetter than other two models after heavy rainfall events. Although the depletion curve of soil moisture looks similar among three LSMs for the shallow surface layer at 5 cm, it has different characteristics in the deep root-zones. To improve the parameterization of hydraulic conductivity in land-surface models, continuous measurements of soil moisture profile need to be taken in field experiments, together with a comprehensive observation of surface energy budgets.
3. Improving the Parameterization Scheme of the Atmospheric Surface Layer
In this research project supported by the NASA Land Surface Hydrology Program, we are collaborating with R. Qualls at the University of Idaho to study a new approach to define the roughness length for heat and moisture over vegetated areas. A majority of modern-era land-surface models utilize the surface skin temperature, derived from surface energy balance, as the lower boundary condition for integrating the Monin-Obukhov similarity theory. But the assumptions of the Monin-Obukhov similarity theory may no longer be appropriate under these conditions. It is apparent that a roughness length for heat/moisture different from the roughness length for momentum has to be used in order to apply the similarity theory. The approach under investigation will use vegetation characteristics obtained from remote sensing to specify the roughness length for heat/moisture in the atmospheric surface-layer model, and will be evaluated against field observations. As the calculation of surface heat fluxes in mesoscale models is sensitive to the specification of this parameter, this approach will also be used in the PSU/NCAR MM5 model to examine its impact on short-range weather forecasts.
4. WRF land-surface model development and AFWA ARGMET improvements
Supported by the Air Force Weather Agency (AFWA), J. Dudhia, W. Wang, and S. Lownam, MMM/NCAR; H. Hsu and F. Chen, RAP/NCAR collaborated with NCEP (K. Mitchell and M. Ek), FSL (J. Smart and B. Shaw), AFWA (G. Gayno and J. Wegiel) to implement an advanced land-surface modeling (LSM) system in the Weather Research and Forecast (WRF) model and to improve the offline global land data assimilation system (so-called AGRMET) at AFWA. Two WRF/LSM workshops were held at NCEP (October 2000), respectively, and at NCAR (August 2001) to define the strategy of land-surface model development and to foster this collaborative effort. The following background surface fields have been implemented in WRF/SI: 1) 30-second global USGS 24-category landuse map; 2) 30-second global hybrid (30-sec for CONUS and 5-min elsewhere) Top and Bottom soil texture; 3) NESDIS 0.15-deg monthly climatology green vegetation fraction; and 4) 1-deg annual mean air temperature as lower boundary temperature. An advanced LSM has been implemented in WRF V.1+ and is being tested in real-time mode by the NCAR WRF group.
In addition, a unified NOAH/OSU LSM is being developed. A mini-workshop was held at NCAR (July 2001) with participants from NCEP, AFWA, and NCAR to define the structure of the unified LSM. This unified LSM will be tested at NCEP, AFWA, and NCAR both in uncoupled 1-D mode and in coupled mode with NCEP Eta and PSU/NCAR MM5 modeling systems. Our goal is to implement the unified LSM in the "research version" of WRF by September 2002.
5. Warm-Season Evaporation Study
In collaboration with R. Elliott and V. Sridhar at Okalahoma State University, F. Chen is applying a land-surface model to study the evolution of surface evaporation and soil moisture in the Oklahoma Mesonet area that consists of cropland, rangeland, pastureland, and forestland. The seasonal cycle of vegetation greatly varies over different land-use areas and affects the diurnal and seasonal evolution of surface heat fluxes. Different approaches to estimate the green vegetation fraction from satellite derived NDVI are being evaluated.
6. Real-Time Weather Forecasts with the Land-Surface/MM5 Coupled System and Soil Moisture Data Assimilation
An advanced land-surface model has been coupled to the PSU/NCAR MM5 model in order to improve real-time weather forecasts. This coupled system is running, in a nested mode, twice a day at various U.S. Army test ranges to support their operations. Figure G3 shows the spatial distribution of terrain and land-use type in the domain-3 with 3 km grid spacing for the Army Dugway test range located in Utah. A wide range of land-use type, including part of the Great Salt Lake (in blue), dry salt lake (aka Playa, in pink), and desert shrubs (in yellow), can be seen in this area of about 180x180 km^2 shown in Figure G4. is the model latent heat flux (evaporation) valid at 1800 UTC 13 April 2000 for the same area mentioned above. Note that the variability in land-use and soil moisture is a primary factor to influence the local and regional evaporation.
Figure G3
Figure G4
It is challenging to provide realistic initial soil moisture fields to this coupled land-surface/MM5 system, given that soil moisture is not routinely observed at continental scales. We are developing an uncoupled land-surface data assimilation system, which utilizes observed rainfall, solar radiation derived from satellite and analyzed surface wind and temperature to force a land-surface model to simulate the evolution of soil moisture. In this system, the NCEP/NOAA hourly 4-km rainfall analysis based on NEXRAD and rain gauge observations is used so that the errors in soil moisture caused by precipitation and radiation bias in coupled modeling systems could be avoided.