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Dennis P. Lettenmaier and Fengge Su Department of Civil and Environmental Engineering

Evaluation of the TRMM Multi-satellite Precipitation Analysis (TMPA) and its utility in hydrologic prediction in La Plata Basin. Dennis P. Lettenmaier and Fengge Su Department of Civil and Environmental Engineering University of Washington, Seattle, WA 98195, USA. 1. Background.

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Dennis P. Lettenmaier and Fengge Su Department of Civil and Environmental Engineering

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  1. Evaluation of the TRMM Multi-satellite Precipitation Analysis (TMPA) and its utility in hydrologic prediction in La Plata Basin Dennis P. Lettenmaier andFengge Su Department of Civil and Environmental Engineering University of Washington, Seattle, WA 98195, USA

  2. 1. Background • Objective of this study: Evaluate TRMM-based precipitation estimates, and their utility in hydrologic (streamflow) predictions. • This initial hydrologic effectiveness assessment of TRMM products for La Plata Basin can provide useful insights into the potential hydrologic utility of the Global Precipitation Measurement mission (GPM) • A first step in development of a global hydrologic assessment framework for satellite-based precipitation products.

  3. 2. Data sets and methodology • The TRMM product evaluated in this study is the TRMM Multi-satellite Precipitation Analysis (TMPA) research product Version 6 3B42 for the years of 1998-2006. • V6 3B42 combines precipitation estimates from multiple satellites, as well as gauge analyses, where available, at a 3-hour time step and 0.25° degree spatial resolution. • The data set covers the latitude band 50°N-S for the period 1998 to the delayed present. Huffman et al., 2007, The TRMM Multi-satellite Precipitation Analysis (TMPA): Quasi-Global, Multi-Year, Combined-Sensor Precipitation Estimates at Fine Scales (Journal of Hydrometeorology 8, 38-55)

  4. La Plata Basin and gauge-based gridded daily precipitation for the years of 1998-2006 Sources: South American gridded daily precipitation (0.25° ) which was constructed from daily meteorological stations (Liebmann and Allured, 2005). Rain gauge distributions in 2005. Blue triangles are streamflow stations. Colored areas highlight four subbasins with relative dense station coverage.

  5. Methodology • Basin average precipitation estimates from the TRMM Satellite precipitation product (Version 6 3B42) and gauge estimates for 1998-2006 are compared with each other at both daily and monthly time scales. • The Variable Infiltration Capacity (VIC) land surface hydrology model is forced by the daily 3B42 and gridded gauged precipitation estimates over several subbasions of La Plata. The two streamflow simulations are compared with each other and with available observed streamflow.

  6. 3. Precipitation evaluation R2=0.63 Rrmse=0.94 R2=0.41 Rrmse=1.38 R2=0.39 Rrmse=1.69 R2=0.42 Rrmse=1.70 R2=0.0.45 Rrmse=1.51 R2=0.58 Rrmse=0.86 R2=0.54 Rrmse=1.02 Scattergrams of daily basin-averaged precipitation from gauged and TRMM V.6 3B42 estimates for La Plata basin tributaries for the period January 1998 to August 2006.

  7. Daily time series of precipitation for basin 3802 Gauged 1998 TRMM 1999 2000 2001 2002

  8. Statistical evaluation over different subbasins Frequency Bias index FBI can indicate whether there is a tendency to underestimate (FBI<1) or overestimate (FBI>1) rainy events. Probability of Detection POD gives a proportion of observed rain events successfully estimated by the TRMM data. False Alarms Ratio FAR provides a measure of the 3B42’s tendency to estimate rain where none was observed.

  9. Monthly Basin-averaged Precipitation R2=0.95 Rrmse=0.23 R2=0.99 Rrmse=0.13 R2=0.99 Rrmse=0.17 R2=0.95 Rrmse=0.16 R2=0.96 Rrmse=0.14 R2=0.98 Rrmse=0.10 R2=0.97 Rrmse=0.12 Scattergrams of monthly basin-averaged precipitation estimated from gauged and TRMM for seven subbasins in La Plata (Jan 1998-Aug 2006).

  10. Monthly time series of precipitation from gauged and TRMM V.6 3B42 estimates for seven subbasins in La Plata (Jan 1998-Aug 2006). 6682 (Area: 459,990 km2) Gauged TMPA 6301 (Area: 478,000 km2) 6598 (Area: 63,236 km2) 3802 (Area: 189,300 km2) 7870 (Area: 240,000 km2) 3402 (Area: 975,000 km2) 2401 (Area: 1,100,000 km2)

  11. 4. Hydrological Modelling • Model features: • multiple vegetation classes in each cell; • energy and water budget closure at each time step; • subgrid infiltration and runoff variability; • and non-linear baseflow generation. The VIC (Liang et al, 1994;1996) model is a grid-based land surface scheme designed both for inclusion in GCMs, and for use as a stand-alone macro-scale hydrological model.

  12. Observed Simulated with TRMM Prce. Simulated with gauged Prce. Daily streamflow for basin 3802 (Area: 189, 300 km2) m3/s m3/sm3/s Green VS. Black: Ef = 0.85, Er = 2% 1998 1999 2000 Red VS. Black: Ef = 0.45, Er = 24% 1998 1999 2000 Red VS. Green: Ef = 0.71, Er = 24% 2001 2002 2003 Nash-Sutcliffe efficiency (Ef) Relative error (Er)

  13. Observed Simulated with TRMM Prce. Simulated with gauged Prce. Daily streamflow for basin 6301, Parana at Jupia (Area: 478,000km2) m3/s m3/sm3/s Red VS. Green: Ef = 0.62, Er = 22% Nash-Sutcliffe efficiency (Ef) Relative error (Er)

  14. Observed Simulated with TRMM Prce. Simulated with gauged Prce. Daily streamflow for basin 6598, Iguazu at Estreito (Area: 63,236 km2) m3/s m3/sm3/s Red VS. Green: Ef = 0.62, Er = 22% Nash-Sutcliffe efficiency (Ef) Relative error (Er)

  15. Observed Simulated with TRMM Prce. Simulated with gauged Prce. Streamflow (m3/s) Monthly time series of streamflow at seven locations within La Plata basin for the years of 1998-2006. (a) 6682, Paraguay at Ladario (Area: 459,990 km2) (b) 6301, Parana at Jupia (Area: 478,000km2) (c) 6598, Iguazu at Estreito (Area: 63,236 km2) (d) 3802, Uruguay at Paso de los Libres (Area: 189,300 km2) (e) 7870, Uruguay at Concordia (Area: 240,000 km2) (f) 3402, Parana at Posadas (Area: 975,000 km2) (g) 2401, Paraguay at Bermejo (Area: 1,100,000 km2) Nash-Sutcliffe efficiency (Ef) Relative error (Er) 1998 1999 2000 2001 2002 2003 2004 2005 2006

  16. 5. Conclusions • The Version 6 3B42 precipitation matches observations closely at monthly time scale (essentially by construct) . Daily estimates show a good performance for the low and medium precipitation thresholds. For higher thresholds, satellite estimates tend to overestimate the frequency of rain events, and to show low POD and high FAR. • The 3B42-driven model results show reasonable ability to capture low and mid-range daily flows, but tend to overestimate high flows. • Monthly adjustment is key to getting streamflow volumes (about) right – is there a viable way of doing this in the absence of gauge estimates? • This study is encouraging to the extent that the rescaled satellite estimates provide plausible estimates of area covered by precipitating events. • Key caveat is that hydrological model was calibrated to gridded gauge estimates – need to investigate hydrological prediction errors when model is calibrated to satellite products

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