Issues in global precipitation estimation Issues in global precipitation estimation for hydrologic predictionfor hydrologic prediction

Dennis P. Lettenmaier, Nathalie Voisin, and John C. Schaake, Jr.

EGU 2009, NH 1.1, Precipitation Science

April 22, 2009

Parana

Parag

uay

Urugu

ay

Low

er B

asin

The problem: Sparse precipitation station coverage in many land areas: Can remote sensing or NWP analysis fields fill the gap?

Global precipitation data setsa) Adam et al 2006

(gauge based)

b) ERA-40

c) GPCP 1DDGPCP 1DD v A2006

ERA-40 v A2006

ERA-40 v GPCP 1DD

Pan Arctic Water Surface Balance

Yenisei basin

P

Pan Arctic Water Surface Balance

Lena basin

P

Pan Arctic Water Surface Balance

Ob basin

P

Pan Arctic Water Surface Balance

Mackenzie basin

P

La Plata Basin TRMM 3B42 RP vs. gridded observations -- daily

La Plata Basin -- TRMM 3B42 RP vs. gridded observations -- monthly

Annual mean

precipitation over La

Plata basin from gridded

gauge, TMPA V.6 (gauge

adjusted), TMPA-RT,

CMORPH, and PERSIANN

estimates for the years

2003-2005.

Difference of annual

precipitation between

satellite and gauge

estimates.

mm/yr

mm/yr

Precipitation evaluation- spatial fieldsGauge TMPA V.6

Bias relative to gauge estimates for each year ( 2003, 2004, and 2005).

The bias significantly decreased in 2005 over basins 3802 and 6598 for the three real-time satellite precipitation products.

Annual mean simulated

runoff forced by the

gauge, TMPA V.6, TMPA-

RT, CMORPH, and

PERSIANN estimates for

the years 2003-2005.

Difference of annual

simulated runoff between

satellite-driven and gauge-

observation-driven

simulations.

mm/yr

mm/yr

Gauge TMPA V.6

Spatial fields of annual mean simulated runoff (2003-2005)

Daily simulated streamflow for basin 3802, Uruguay at Paso de los Libres (Area: 189, 300km2, Jan 2003~Aug 2006)

Simulated with satellite Precip

Simulated with gauge Precip Bias TMPA (%)

RT (%)

CMORPH (%)

PERSIANN (%)

2003 20 110 110 105

2004 32 120 142 73

2005 22 39 55 17

FIG. 7. Spatial fields of annual mean precipitation (mm/yr) from this study (a), CRU (b), VasclimO (c), and ERA-40 reanalysis (d) for La Plata Basin (1979-1999).

Some questions

• What can the hydrology community do to persuade the satellite precipitation product community (and program managers) to produce reanalyses of satellite only products that can be tested in a hydrologic setting?

• Are we better off assimilating satellite data in NWPs, and using the analysis fields as our best estimates of precipitation, in lieu of precipitation estimates made directly from satellite sensors (e.g., TMPA, CMORPH, etc)?

• Who is doing such an evaluation, which seems critical as the GPM era draws near?