RAL Advances in Land Surface Modeling Part I. Andrea Hahmann

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1 RAL Advances in Land Surface Modeling Part I Andrea Hahmann

2 Outline The ATEC real-time high-resolution land data assimilation (HRLDAS) system - Fei Chen, Kevin Manning, and Yubao Liu (RAL) The fine-mesh model and its parameterizations - Gordon Bonan, Mariana Vertenstein (CGD) and David Gochis

3 A land surface model numerically represents the water and energy exchanges that take place between the atmosphere and the land surface It includes processes such as the calculation of: rainfall interception by the canopy, drip, plant transpiration surface albedo, absorption and emission of radiation by the soil and the vegetation movement of water trough the soil column, surface runoff, snow processes ground temperatures and surface fluxes of latent, sensible and momentum (output back to atmos)

4 Land Data Assimilation System: Provides a continuous record of the state of the land surface The land surface model is run uncoupled (off-line) from its host mesoscale model (i.e., MM5 or WRF)

5 Domain-averaged soil moisture over Dugway Proving Grounds (Utah) Volumetric soil moisture content, D2 since Aug 21, 2005 layer 2 layer 3 layer 1 surface Land-use categories domains 1 and 2 12-hour precipitation

6 HRLDAS implementation HRLDAS uses the same land surface model as in coupled mesoscale model: same soil moisture climatology No mismatch of terrain, land use type, soil texture, or physical parameters No interpolation or soil moisture conversion Uses atmospheric forcing (temp, wind, etc.) from mesoscale model; observed precipitation, solar incident radiation, and water equivalent snow depth (available in real time)

7 MM5 RTFDDA for Aberdeen Test Center (ATC), Maryland domain 2 ( x=10 km) In the standard real-time fourdimensional data assimilation (RTFDDA) surface fields are initialized from interpolated NAM (previously known as ETA) fields HRLDAS example New system will use HRLDAS fields to initialize model fields Volumetric soil moisture surface layer

8 Real-time MM5 experiments Three parallel RTFDDA experiments for three ranges:dpg, WSMR, and ATC New runs (after bug fix) since Sept 17, 2005 Verification statistics compiled in real time

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10 The characteristics of the land surface are spatially heterogeneous

11 But, general circulation models usually have horizontal grid spacings of ~100 km!

12 The answer: the fine-mesh model!

13 The fine-mesh model The fine-mesh model represents sub-grid scale processes by a land sub-mesh imposed on each atmospheric model grid; Advantages: cheap (compared to high resolution runs or limited-area models), defined geographic location, sub-grid parameterizations are easy to implement;

14 surface temperature (K) precipitation (mm/day) Changes in temperature and precipitation introduced by the fine-mesh model (Hahmann and Dickinson, 2001) Significant changes in precipitation over Africa, where climate is sensitive to the location of the boundary between vegetated and non-vegetated land.

15 Sub-grid disaggregation parameterizations Introduce sub-grid scale parameterizations for a non-uniform distribution of atmospheric forcings. Precipitation Elevation Topographic Slope/Aspect

16 Precipitation disaggregation scheme The probability distribution of rainfall within the rain-covered area, µ, based on the method by Eagleson (1978) is given by QuickTime and a GIF decompressor are needed to see this picture. f ( P ) ij P ij µ µ P = exp ij P P The amount of rainfall received at a randomly selected grid point (i,j) is given by P = ln( 1 µ x) where 0<x<1 is an additionally produced random number. The process is repeated until a fraction µ of the large-scale grid square is covered with rainfall.

17 Disaggregation according to sub-grid elevation The temperature, pressure, density and humidity at a subgrid point are adjusted from the GCM value using a standard atmosphere lapse rate and the sub-grid point elevation. height temperature GCM elevation and temperature 1 1/2 1/4 surface elevation over the western US

18 Differences in water equivalent snow cover using elevationbased disaggregation

19 Disaggregation of solar insolation according to sub-grid slope and azimuth Geometry of the solar angle incidence on an inclined surface Slope and azimuth at 1km resolution over the western US

20 Insolation and snow depth differences during the melting season introduced by the sub-grid slope and aspect Water equivalent snow depth Insolation (W/m2)

21 Summary, conclusions, etc. The climate simulated using the precipitation disaggregation scheme is considerably different from that simulated using rainfall which is homogeneously distributed within the GCM grid square. Precipitation disaggregation scheme suffers from many drawbacks: unable to reproduce the spatial structure of the precipitation field; unable to reproduce the temporal and spatial memory of the precipitation processes; Drawbacks could be corrected by enhancements to the current scheme. Use observations to determine characteristic of the precipitation field and it relationship to the large-scale environment. The introduction of the effects of topography (elevation, slope and azimuth) in the fine-mesh model produces differences in snow cover in mid-latitude mountainous terrain. Changes are also seen in the atmospheric circulation near regions of steep terrain.

22 After 10 years of work... Fine-mesh model will finally be coupled to the Community Climate System Model!