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Evaluation of TRMM satellite precipitation product in hydrologic simulations of La Plata Basin. Fengge Su 1 , Yang Hong 2 , and Dennis P. Lettenmaier 1 1 University of Washington, Seattle, WA 2 NASA Goddard Space Flight Center, Greenbelt, MD. 1. Background. - PowerPoint PPT Presentation
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Evaluation of TRMM satellite precipitation product in hydrologic
simulations of La Plata Basin
Fengge Su1, Yang Hong2, and Dennis P. Lettenmaier1
1University of Washington, Seattle, WA 2 NASA Goddard Space Flight Center, Greenbelt, MD
1. Background
• The objective of this study is to evaluate the TRMM-based
precipitation estimates, and their utility in hydrologic
predictions.
• Precipitation is the primary atmospheric input to hydrology
models.
• Satellite-based precipitation estimates show potential
attractions for hydrologic predictions.
• High resolution TRMM-based products are available to
research community.
• The TRMM product evaluated in this study is the TRMM
Multi-satellite Precipitation Analysis (TMPA) research
product Version 6 3B42.
• It 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.
2. Data sets and methodology
Huffman et al., 2006, The TRMM Multi-satellite Precipitation Analysis (TMPA): Quasi-Global, Multi-Year, Combined-Sensor Precipitation Estimates at Fine Scales (to appear in Journal of Hydrometeorology)
Rain gauge distribution in 1998 (846)
Rain Gauge distribution in 1999 (676)
La Plata Basin and Gauged data (1998-1999)
from NCAR and GDCN (Global Daily Climatology Network) station data
Uruguay
Parana
Paraguay
Methodology
1. Basin average precipitation estimates from the TRMM Satellite
precipitation product (Version 6 3B42) and gauges are
compared with each other at both daily and monthly time
scales.
2. The Variable Infiltration Capacity (VIC) land surface hydrology
model is forced by daily 3B42 and gauged precipitation over
several subbasions of La Plata. The simulated streamflow is
compared with each other and with available observed
streamflow.
3. Precipitation evaluation
Scattergrams of daily basin-averaged precipitation estimated from gauged and TRMM data.
Rrmse=60% Rrmse=13%
Rrmse=134% Rrmse=15%
Rrmse=44%
Scattergrams of monthly basin-averaged precipitation estimated from gauged and TRMM data.
Monthly Basin-averaged Precipitation
Daily time series of precipitation for basin 3861
19991998
Gauged TRMM
1 2 3
4 5 6
7 8 9
10 11 12
1 2 3
4 5 6
7 8 9
10 11 12
Month Month
mm
/dy
mm
/dy
Monthly time series of
precipitation from
gauged and TRMM 3B42
data for five subbasins
(1998-1999).
BasinRelative Error (%)
1998 1999 Average
3861 6 5 5.5
7870-3802 7 9 8
6301 1 7 4.0
6682 5 15 10.0
6598 5 0 2.5
FBI can indicate whether there is a tendency to underestimate (FBI<1) or overestimate (FBI>1) rainy events.
POD gives a proportion of observed rain events successfully estimated by the TRMM data.
FAR provides a measure of the 3B42’s tendency to estimate rain where none was observed.
Statistical evaluation over different subbasinsFrequency Bias Index
0
0.5
1
1.5
2
2.5
0.1 0.5 1 2 5 10 20
Threshold (mm)
FB
I
3861
6301
6682
Probability of Detection
0
0.2
0.4
0.6
0.8
1
0.1 0.5 1 2 5 10 20
Threshold (mm)P
OD
3861
6301
6682
False Alarms Ratio
0
0.2
0.4
0.6
0.8
1
0.1 0.5 1 2 5 10 20
Thresholds (mm)
FA
R
3861
6301
6682
Frequency Bias index
Probability of Detection
False Alarms Ratio
4. Hydrological Modelling4. Hydrological Modelling
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.
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.
Observed
Simulated with TRMM Prce.
Simulated with gauged Prce.
Nash-Sutcliffe efficiency (Ef)
Relative error (Er)
Daily streamflow for basin 3802
3802, Uruguay at Paso de Los Libres (Area: 189, 300 km2)
Green VS. Black: Ef = 0.85, Er = 2%
Red VS. Black: Ef = 0.48, Er = 12%
Red VS. Green: Ef = 0.54, Er = 16%
1998 1999
1998 1999
1998 1999
m3
/s m
3/s m
3/s
Daily streamflow for basin 6301, 6598, and 6682
Observed
Simulated with TRMM Prce.
Simulated with gauged Prce.
Nash-Sutcliffe efficiency (Ef)
Relative error (Er)
Red VS. Green: Ef = 0.73, Er = 4%
Red VS. Green: Ef = 0.73, Er = -1%
Red VS. Green: Ef = 0.72, Er = 18%
(a) 6301, Parana at Jupia (Area: 478,000km2)
(b) 6598, Iguazu at Estreito (Area: 63,236 km2)
(c) 6682, Paraguay at Ladario (Area: 459,990 km2)
m3
/s m
3/s m
3/s
1998 1999
1998 1999
1998 1999
Monthly streamflow for the four subbasins
Observed
Simulated with TRMM Prce.
Simulated with gauged Prce.
m3
/s m
3/s
m3
/s m3
/s
(a) 3802, Uruguay at Paso de Los Libres
(b) 6301, Parana at Jupia
(c) 6598, Iguazu at Estreito
(d) 6682, Paraguay at Ladario
1998 1999
• The Version 6 3B42 provides good performance at monthly time
scale. The 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 show low POD and high FAR.
• The 3B42-driven model results show a good ability in reproducing
the timing of floods, and in representing the low peak flows, but
tend to overestimate the high-flow peaks.
• Despite the errors in the satellite-based precipitation estimates,
this study provides encouraging results of using the TRMM 3B42
product in basin-scale hydrology predictions.
5. Conclusion