Soil Initialization Strategy for Use in Limited-Area Weather Prediction Systems
Tóm tắt
Three diverse methods of initializing soil moisture and temperature in limited-area numerical weather prediction models are compared and assessed through the use of nonstandard surface observations to identify the approach that best combines ease of implementation, improvement in forecast skill, and realistic estimations of soil parameters. The first method initializes the limited-area model soil prognostic variables by a simple interpolation from a parent global model that is used to provide the lateral boundary conditions for the forecasts, thus ensuring that the limited-area model’s soil field cannot evolve far from the host model. The second method uses the soil properties generated by a previous limited-area model forecast, allowing the soil moisture to evolve over time to a new equilibrium consistent with the regional model’s hydrological cycle. The third method implements a new local soil moisture variational analysis system that uses screen-level temperature to adjust the soil water content, allowing the use of high-resolution station data that may be available to a regional meteorological service.
The methods are tested in a suite of short-term weather forecasts performed with the Consortium for Small Scale Modeling (COSMO) model over the period September–November 2008, using the ECMWF Integrated Forecast System (IFS) model to provide the lateral boundary conditions. Extensive comparisons to observations show that substantial improvements in forecast skills are achievable with improved soil temperature initialization while a smaller additional benefit in the prediction of surface fluxes is possible with the soil moisture analysis. The analysis suggests that keeping the model prognostic variables close to equilibrium with the soil state, especially for temperature, is more relevant than correcting the soil moisture initial values. In particular, if a local soil analysis system is not available, it seems preferable to adopt an “open loop” strategy rather than the interpolation from the host global model analysis. This appears to be especially true for the COSMO model in its current operational configuration since the soil–vegetation–atmosphere transfer (SVAT) scheme of the ECMWF global host model and that of COSMO are radically diverse.
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Tài liệu tham khảo
Beljaars, 1996, The anomalous rainfall over the United States during July 1993: Sensitivity to land surface parameterization and soil moisture anomalies, Mon. Wea. Rev., 124, 362, 10.1175/1520-0493(1996)124<0362:TAROTU>2.0.CO;2
Benoit, 1976
Bouttier, 1993, Sequential assimilation of soil moisture from atmospheric low-level parameters. Part I: Sensitivity and calibration studies, J. Appl. Meteor., 32, 1335, 10.1175/1520-0450(1993)032<1335:SAOSMF>2.0.CO;2
Budyko, 1974, Climate and Life
Cleveland, 1991, Local regression models
Commission of the European Communities, 1995, CORINE land cover
Courtier, 1994, A strategy for operational implementation of 4D-Var, using an incremental approach, Quart. J. Roy. Meteor. Soc., 120, 1367, 10.1002/qj.49712051912
Crow, 2001, An observation system simulation experiment for the impact of land surface heterogeneity on AMSR-E soil moisture retrieval, IEEE Trans. Geosci. Remote Sens., 39, 1622, 10.1109/36.942540
Dickinson, 1986, Biosphere–Atmosphere Transfer Scheme (BATS) for the NCAR Community Climate Model
Doms, 2004, A description of the non-hydrostatic regional model LM
Douville, 2000, Evaluation of the optimum interpolation and nudging techniques for soil moisture analysis using FIFE data, Mon. Wea. Rev., 128, 1733, 10.1175/1520-0493(2000)128<1733:EOTOIA>2.0.CO;2
Drusch, 2007, Assimilation of screen-level variables in ECMWF’s Integrated Forecast System: A study on the impact on the forecast quality and analyzed soil moisture, Mon. Wea. Rev., 135, 300, 10.1175/MWR3309.1
Evensen, 2003, The ensemble Kalman filter: Theoretical formulation and practical implementation, Ocean Dyn., 53, 343, 10.1007/s10236-003-0036-9
Giard, 2000, Implementation of a new assimilation scheme for soil and surface variables in a global NWP model, Mon. Wea. Rev., 128, 997, 10.1175/1520-0493(2000)128<0997:IOANAS>2.0.CO;2
Hammer, 1970, Cloud development and distribution around Khartoum, Weather, 25, 411, 10.1002/j.1477-8696.1970.tb04131.x
Hess, 2001, Assimilation of screen-level observations by variational soil moisture analysis, Meteor. Atmos. Phys., 77, 145, 10.1007/s007030170023
Hess, 2008, Evaluation of the variational soil moisture assimilation scheme at Deutscher Wetterdienst, Quart. J. Roy. Meteor. Soc., 134, 1499, 10.1002/qj.306
Jacobs, 2008, Evaluation of European Land Data Assimilation System (ELDAS) products using in situ observations, Tellus, 60A, 1023, 10.1111/j.1600-0870.2008.00351.x
Lange, 2009, Parametrisation of the sensitivity DT2m/dw in soil moisture analysis
Louis, 1979, A parametric model of vertical eddy fluxes in the atmosphere, Bound.-Layer Meteor., 17, 187, 10.1007/BF00117978
Macpherson, 1996, The impact of MOPS moisture data in the U. K. Meteorological Office mesoscale data assimilation scheme, Mon. Wea. Rev., 124, 1746, 10.1175/1520-0493(1996)124<1746:TIOMMD>2.0.CO;2
Mahfouf, 1991, Analysis of soil moisture from near-surface parameters: A feasibility study, J. Appl. Meteor., 30, 1534, 10.1175/1520-0450(1991)030<1534:AOSMFN>2.0.CO;2
Njoku, 2003, Soil moisture retrieval from AMSR-E, IEEE Trans. Geosci. Remote Sens., 41, 215, 10.1109/TGRS.2002.808243
Ott, 2004, A local ensemble Kalman filter for atmospheric data assimilation, Tellus, 56A, 415, 10.3402/tellusa.v56i5.14462
Papale, 2006, Towards a standardized processing of net ecosystem exchange measured with eddy covariance technique: Algorithms and uncertainty estimation, Biogeosciences, 3, 571, 10.5194/bg-3-571-2006
Rhodin, 1999, Variational analysis of effective soil moisture from screen-level atmospheric parameters: Application to a short-range weather forecast model, Quart. J. Roy. Meteor. Soc., 125, 2427, 10.1002/qj.49712555905
Ritter, 1992, A comprehensive radiation scheme for numerical weather prediction models with potential applications in climate simulations, Mon. Wea. Rev., 120, 303, 10.1175/1520-0493(1992)120<0303:ACRSFN>2.0.CO;2
Robock, 2000, The Global Soil Moisture Data Bank, Bull. Amer. Meteor. Soc., 81, 1281, 10.1175/1520-0477(2000)081<1281:TGSMDB>2.3.CO;2
Schär, 1999, The soil–precipitation feedback: A process study with a regional climate model, J. Climate, 12, 722, 10.1175/1520-0442(1999)012<0722:TSPFAP>2.0.CO;2
Schrodin, 2001, The multi-layer-version of the DWD soil model TERRA/LM
Segal, 1988, Evaluation of vegetation effects on the generation and modification of mesoscale circulations, J. Atmos. Sci., 45, 2268, 10.1175/1520-0469(1988)045<2268:EOVEOT>2.0.CO;2
Segal, 1995, Scaling evaluation of the effect of surface characteristics on potential for deep convection over uniform terrain, Mon. Wea. Rev., 123, 383, 10.1175/1520-0493(1995)123<0383:SEOTEO>2.0.CO;2
Smith, 1994, Initialization of soil-water content in regional-scale atmospheric prediction models, Bull. Amer. Meteor. Soc., 75, 585, 10.1175/1520-0477(1994)075<0585:IOSWCI>2.0.CO;2
Steppeler, 2003, Meso-gamma scale forecasts using the non-hydrostatic model LM, Meteor. Atmos. Phys., 82, 75, 10.1007/s00703-001-0592-9
Teuling, 2009, Parameter sensitivity in LSMs: An analysis using stochastic soil moisture models and ELDAS soil parameters, J. Hydrometeor., 10, 751, 10.1175/2008JHM1033.1
Tiedtke, 1989, A comprehensive mass flux scheme for cumulus parameterization in large-scale models, Mon. Wea. Rev., 117, 1779, 10.1175/1520-0493(1989)117<1779:ACMFSF>2.0.CO;2
Van den Hurk, 2003, The Torne-Kalix PILPS 2 (e) experiment as a test bed for modifications to the ECMWF land surface scheme, Global Planet. Change, 38, 165, 10.1016/S0921-8181(03)00027-4
Van den Hurk, 2000, Offline validation of the ERA40 surface scheme
Van Wijk, 1966, Periodic temperature variations in a homogeneous soil
Viterbo, 1995, An improved land surface parameterization scheme in the ECMWF model and its validation, J. Climate, 8, 2716, 10.1175/1520-0442(1995)008<2716:AILSPS>2.0.CO;2