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d 4. d 1. d 2. P G. d 3. Gridded Rainfall Estimation for Distributed Modeling in Western Mountainous Areas. Fekadu Moreda 1,3 , Shuzheng Cong 1,2 ,, John Schaake 1,4 , Michael Smith 1 1 OHD, 2 UCAR, 3 MHW, 4 RTi, Inc.
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Gridded Rainfall Estimation for Distributed Modeling in Western Mountainous Areas
Fekadu Moreda1,3, Shuzheng Cong1,2,, John Schaake1,4, Michael Smith1
1OHD, 2UCAR, 3 MHW, 4RTi, Inc.
Office of Hydrologic Development, NOAA National Weather Service 1325 East-West Highway, Silver Spring, MD 20910, U.S.A.
www.nws.noaa.gov/oh/hl e-mail [email protected]
AGU 2006 Spring Meeting
May 23 - 27, Baltimore, MD
4. Results Cont’d.
Comparison of Precipitation Averages over Operational Scale Basins
Estimation of precipitation in mountainous areas continues to be problematic. It is well known that radar-based methods are limited due to beam blockage. In these areas, in order to run a distributed model that accounts for spatially variable precipitation, we have generated hourly gridded rainfall estimates from gauge observations. These estimates will be used as basic data sets to support the second phase of the NWS-sponsored Distributed Hydrologic Model Intercomparison Project (DMIP 2).
One of the major foci of DMIP 2 is to better understand the modeling and data issues in western mountainous areas in order to provide better water resources products and services to the Nation. In light of these goals, we perform several analyses to evaluate the gridded estimates for DMIP 2 experiments. These gridded inputs are used to generate mean areal precipitation (MAPX) time series for comparison to the traditional mean areal precipitation (MAP) time series derived by the NWS California-Nevada River Forecast Center (CNRFC) for model calibration. We use two of the DMIP 2 basins in California and Nevada: the North Fork of the American River (catchment area 885 sq. km) and the East Fork of the Carson River (catchment area 922 sq. km) as test areas. For operational forecasting, the basins are sub-divided into elevation zones.
Analyses are preformed for a wider rectangular area (Figure 1) and for subbasins. For the rectangular area we compared PRISM and gridded products based on annual precipitation, monthly time series and regression of monthly time series.
For the subbasins, we compared six-hourly mean areal precipitation time series derived from gridded products to CNRFC MAP time series. The analyses include typical-year monthly comparisons, regression fit, and overall statistics.
Figure 6. Typical-year monthly comparison of the MAP and MAPX for higher elevation zone (North Fork American River)
Figure 7. Typical-year monthly comparison of the MAP and MAPX for lower elevation zone (North Fork American American River)
Figure 2. Illustration of inverse distance weights
Figure 8. Regression fit of six-hourly precipitation time series of the three basins: higher elevation zones
Figure 9. Regression fit of six-hourlyprecipitation time series of the three basins: lower elevation zones
2. Study Area and Data
4. Results - For the Rectangular Area – Test with PRISM data
Figure 3. Annual precipitation derived from grids matches the annual PRISM for the entire rectangular box
Table 2. Overall statistics of the MAP and MAPX time series for period of 1996-2002
H Hourly gages
D Daily gages
SD SNOTEL gages
Center of HRAP grids
Figure 1. The study area covers the above rectangularareawhich encompasses the American and Carson River Basins
Figure 4. Monthly precipitation time series of the gridded precipitation match the monthly PRISM time series for the rectangular area.
(1) Overall differences between the MAP and MAPX are very small for the NF American River for both subbasins: higher and lower elevation zones. For the Carson River basins the overall difference is up to 10%. The difference tends to be higher with less correlation when the subbasin size is small. For example, the lower Carson River basin GRDNLW exhibits a 10% bias between the CNRFC MAP and the MAPX time series.
(2) The comparison of the areal averaged gridded products validates the use of the generated data for distributed model simulations in DMIP 2.
(3) The effect of the gridded input in terms of flow generation will be studied using several models in DMIP 2.
Table 1. Subdivision of the basins based on elevation zones
Figure 5. As expected, high correlation exists between the monthly gridded precipitation and PRISM
Anderson, E.A., 2002. Calibration of Conceptual Hydrologic Models for Use in River Forecasting. http://www.nws.noaa.gov/oh/hrl/calb/calibration1102/main.htm
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