Bosilovich_NEWS_highlight_011507

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GEOS5/MERRA Precipitation Evaluation

GEOS5 in the figures refers to a preproduction version of the 1/2

° MERRA reanalysis system

Top Figure

– 19 continental and oceanic regions mean precipitation from GPCP observations for JJA 2004 compared with reanalyses and another observational data set (CMAP)

Lower Figure

– Spatial correlation of

JJA2004 precipitation of Reanalyses to

GPCP (the CMAP/GPCP correlations provide an estimate of the uncertainty in the observations; the blue line provides a climatological minimum correlation)

The test results are encouraging that

MERRA can provide substantially improved precipitation estimates compared with other reanalyses.

Presented at AMS Jan 2007

Bosilovich, Chen, Robertson and Adler, 2007:

Evaluation of Global Precipitation in

Reanalyses. AMS Conf on Hydrology, San

Antonio TX, Jan 2007.

0.90

0.85

0.80

0.75

JJA2004 Regional Precipitation

7

6

5

4

JRA25

GEOS5

NCEPR1

NCEPR2

GEOS4

3

2

1

CMAP

1:1

CMAP Reg

0

G5 Reg

0 1 2 3 4 5 6 7

GPCP

Global Precipitation Correlations to GPCP (JJA2004)

1.00

0.95

0.70

0.65

0.60

CMAP

JRA25

GEOS5

NCEPR1

NCEPR2

GEOS4

JJA-UN

Global Land Ocean 15s-15n

• Further Comments on the slide not to be put up on the projector

• The top figure is JJA 2004 P means for 19 regions (See fig 14 in preprint) scattered against GPCP. The red line is the linear regression of the GEOS5-GPCP data (GPCP and CMAP fits are close together). The brown line is the regression of GPCP-CMAP merged observation data sets, showing their uncertainty.

• The bottom figure shows the spatial correlation of the reanalyses and CMAP against GPCP monthly mean for the globe, global land, global oceans and the tropics. The brown bar shows the upper limit of spatial correlation given the uncertainties in GPCP and CMAP.

The blue line show the minimum correlation with climatological skill

(in the preprint, see the discussion on “Unmatched Correlations”). I have also done this calculation for all of the 19 regions mentioned previously, and GEOS5 is at or near the highest spatial correlation in

18 (Africa shows lower correlations) compared to all the reanalyses.

• I see this as an extremely positive result for GEOS5 relative to the existing reanalyses, and the data it can provide for NEWS. However, while this experiment was run with the G5 ½ degree configuration, it was GEOS5 Beta9. Several science changes and bug fixes have been implemented since. There is an experiment with the latest

GEOS5 Beta10 for MERRA going now, for which we will redo this.

Scatter to GPCP or CMAP

JJA2004 Regional Precipitation

3

2

1

0

7

6

5

4

0 1 2 3 4 5 6 7

GPCP

JRA25

GEOS5

NCEPR1

NCEPR2

GEOS4

CMAP

1:1

CMAP Reg

G5 Reg

JJA2004 Regional Precipitation

2

1

0

4

3

7

6

5

0 1 2 3 4 5 6 7

CMAP

JRA25

GEOS5

NCEPR1

NCEPR2

GEOS4

GPCP

1:1

GPCP Reg

G5 Reg

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