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ABSTRACT The objective of the Land Data Assimilation System (LDAS) project is to improve the initialization of land surface state variables for numerical.

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Presentation on theme: "ABSTRACT The objective of the Land Data Assimilation System (LDAS) project is to improve the initialization of land surface state variables for numerical."— Presentation transcript:

1 ABSTRACT The objective of the Land Data Assimilation System (LDAS) project is to improve the initialization of land surface state variables for numerical weather prediction, and eventually to provide the basis for assimilation of land surface state variables, such as soil moisture and snow water storage, into weather and climate forecasts. In addition to a real-time pathway, LDAS has utilized multi-decadal retrospective studies to aid in estimation of the parameters for land surface models needed for real-time applications. The retrospective studies are also intended to provide diagnostic information that can aid in improvement of land surface process representations. The retrospective pathway, in addition to its roles in parameter estimation and model diagnostics, affords the opportunity to evaluate the climatology of various surface energy and moisture fluxes, and their spatial patterns and variability. We summarize results from implementation of LDAS-North America retrospective results using the Variable Infiltration Capacity (VIC) model, run in an off-line mode at a 3-hour time step for 10 years (1988-97) for the Mississippi River basin at 1/8 degree spatial resolution, as well as preliminary results for a 50-year simulation (1950-2000) over the entire continental U.S. The model is constrained by observed precipitation and temperature, and is calibrated against observed streamflow at key points throughout the region. For the Mississippi River basin, comparisons are made between predicted water balance fluxes, storages, and soil moisture persistence using both the 10- and 50-year simulations. Because the model is driven by observed (or derived from observed) surface meteorology and radiative forcings, and is validated with streamflow, the model is constrained to produce long-term mean evapotranspiration that closely balances the precipitation and runoff. The observed and simulated fluxes, therefore, can in a sense be considered analogous to a "land surface reanalysis" which can be used to help diagnose coupled model results. LDAS Long-Term Retrospective Land Surface Data Set: 1950-2000 Edwin P. Maurer, Andrew W. Wood, and Dennis P. Lettenmaier a Department of Civil and Environmental Engineering, Box 352700, University of Washington, Seattle, WA 98195 Use of the Derived Data Set as a Benchmark in Coupled Model Diagnosis In contrast to the VIC model, NCEP/NCAR Reanalysis (Reanalysis-1, Kalnay, et al., 1996) and NCEP/DOE AMIP II (Reanalysis-2, Kanamitsu, et al., 2000) include a simplified land surface representation, with many parameters set as global constants (e.g., wilting point=0.12, critical pt=0.25, porosity=0.47, canopy coverage=70%, soil depth=2 m). They both include a soil moisture adjustment (nudging) term, and do not require closure of the surface water budget. They do not include any precipitation observations, but are driven by that simulated by the reanalysis model. The major difference at the land surface between the two reanalyses is that Reanalysis-2 corrects some of the known biases in Reanalysis-1, and replaces the soil moisture nudging to climatology in Reanalysis-1 with limits on infiltration based on observed precipitation. Using as a benchmark observations of precipitation and the VIC-simulation results for other water balance components, a preliminary diagnostic evaluation can be made of the Reanalysis-1 and -2 models: In Reanalysis-1, there is the well-documented overprediction of summer precipitation in the southeastern Mississippi River basin. Improvement is seen in Reanalysis-2, though an overprediction still exists. There is an overprediction of evapotranspiration in all months for both Reanalysis-1 and -2, and this occurs throughout the basin. Runoff patterns do not match VIC spatially or temporally for either Reanalysis-1 or -2. The large soil moisture cycle in Reanalysis-1 (5 times the amplitude of VIC) is largely remedied in Reanalysis-2. In Reanalysis-1 the magnitude of the soil moisture adjustment is comparable (1.6 mm/d) to principal forcing term P (2.2 mm/d), showing the large non-closure of the surface water budget. Snow water equivalent is underpredicted in Reanalysis-1, and overpredicted in Reanalysis-2, and for both model formulations the melt occurs earlier than with VIC. See Maurer et al. (2001a; 2001b) for a more detailed discussion. Use of GCIP Results for Reanalysis-1 and -2 Water Budget Diagnosis Precipitation and Evapotranspiration MAM Seasonal Average Evapotranspiration, mm d -1 Seasonal Average Precipitation, mm d -1 DJF JJA VIC/OBS Reanalysis-1 Reanalysis-2 Soil Moisture and Snow Water Equivalent VIC Reanalysis-1 Reanalysis-2 DJF MAM DJF MAM Seasonal Average Soil Moisture, mm Seasonal Average Snow Water Equivalent, mm Water Budget Evaluation Over Mississippi River Basin 2 -2 0 2 4 6 PRECIP., P -2 0 2 4 6 mm/d EVAP, E -2 0 2 4 6 mm/d RUNOFF, N -2 0 2 4 6 mm/d  STORAGE,  W 0 100 200 300 mm JFMAMJJASOND SOIL MOISTURE -2 0 2 4 6 mm/d JFMAMJJASOND NUDGING mm/d VIC/Observations Reanalysis-1 Reanalysis-2 Hydrologic Model Validation 1 Extension of Data Set to LDAS-North America Region 3 The Hydrologic Model The hydrologic model is the VIC macroscale land surface model (see Liang et al., 1994 and http://www.hydro.washington.edu/ for model details), which has been applied off-line at 1/8° resolution. Forcing variables are daily precipitation, maximum and minimum temperatures (from NCDC cooperative observer stations in the U.S, and from Mexican and Canadian government sources), wind from NCEP Reanalysis, and humidity and incoming shortwave and longwave radiation (derived from temperature and precipitation using established relationships). Soil parameters are taken from the Penn State State Soil Geographic Database (STATSGO) database for the continental U.S., and the FAO global soil map for areas outside the U.S. Land cover is from the University of Maryland 1-km Global Land Cover product (derived from AVHRR). VIC has been shown to reproduce observed streamflow when forced with observed precipitation, and closes its water budget by construct. This, and the use of physical representations of the soil moisture and runoff producing processes, suggests that other surface flux and state variables can serve as reliable surrogates for observations that are not otherwise available. These derived fluxes can arguably be used as a benchmark against which to compare coupled models, and to investigate land surface responses to climatic forcing. VIC MODEL VALIDATION The VIC model is calibrated by adjusting the soil depths, baseflow parameters and infiltration capacity curve parameter to reproduce observed streamflow. Runoff from each 1/8 degree grid cell is routed to points with estimated naturalized flows (or if not available, measured flows), where the hydrographs are compared. The VIC model is also validated using the Illinois soil moisture data set of Hollinger and Isard (1994), which includes observations from 1981-1996, using soil moistures in the top 1 meter of the soil column. Although the measurements are not directly comparable (due to different the use of 19 observing stations are compared to the 17 1/8º modeled grid cells that contain the observation points), good agreement can be seen of average fluxes, interannual variation, and persistence characteristics. Stream Flow Hydrograph Comparison Illinois Soil Moisture Comparison A comprehensive data set forcing data and hydrologic model output has been archived, with the following characteristics: 1/8ºspatial resolution, for a total of 76,864 grid cells 3-hour time step Continuous data from 1 January 1950 - 31 July 2000 (to be periodically updated as observed forcing data becomes available) Domain is shown in charts below (Mexico is in process) Illustration of Soil Moisture Persistence REFERENCES Hollinger, S.E. and S.A. Isard, A soil moisture climatology of Illinois, J. Clim. 7, 822-833, 1994. Huang, J., H.M. van Den Dool,and K.P. Georgakakos, Analysis of Model-calculated soil moisture over the United States (1931- 1993) and applications to long-range temperature forecasts, J. Clim 9, 1350-1362, 1996. Kalnay, E., et al., The NCEP/NCAR 40-year reanalysis project, Bull. Am. Meteorol. Soc., 77, 437-471, 1996 Kanamitsu, M., W. Ebisuzaki, J. Woolen, J. Potter, and M. Fiorino, An overview of NCEP/DOE Reanalysis-2, in Proceedings, Second WCRP International Conference on Reanalyses, Rep. WCRP-109, World Meteorol. Org., Geneva, 2000. Liang, X., D. P. Lettenmaier, E. F. Wood, and S. J. Burges, A Simple hydrologically Based Model of Land Surface Water and Energy Fluxes for GCMs, J.Geophys. Res., 99(D7), 14,415-14,428, 1994. Maurer, E.P., G.M. O'Donnell, D.P. Lettenmaier, and J.O. Roads, 2001a, Evaluation of NCEP/NCAR Reanalysis Water and Energy Budgets using Macroscale Hydrologic Simulations, In: Land Surface Hydrology, Meteorology, and Climate: Observations and Modeling, AGU series in Water Science and Applications, V. Lakshmi, J. Albertson, and J. Schaake eds., pp. 137-15 Maurer, E.P., G.M. O'Donnell, D.P. Lettenmaier, and J.O. Roads, 2001b, Evaluation of the Land Surface Water Budget in NCEP/NCAR and NCEP/DOE AMIP-II Reanalyses using an Off-line Hydrologic Model. (J. Geophys. Res., in press) The land surface flux and state variables are produced at a 3-hour timestep over North America (between latitudes 25 and 53) for the period Jan. 1950-Jul. 2000. These are archived in netCDF format, and are available to the public via ftp. As the data are processed, they will be available through the link at: http://www.hydro.washington.edu/ where announcements of the complete data set availability and updates will also be posted. As an example of exploratory analysis using this data set, we show the persistence of soil moisture anomalies over the domain. These are based on the full 50+ year timeseries at each grid cell. These patterns are consistent with those produced by Huang, et al (1996). The array of water and energy variables presented with this data set allows investigation of many correlations between variables that has not previously been possible at this scale. Shown below is an example of the seasonal variation of soil moisture, scaled by its dynamic range for a 20-year period. The drying of the soil through the year is especially evident in the east coast and southwest regions. Shown to the right is the 20-year soil moisture range scaled by average annual precipitation. Regions with high values have a soil column that stores, and later releases, a greater proportion of the annual precipitation, and therefore has greater capability to exhibit persistence. 4 Summary of Archived Data Availability


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