1. Rain Gauge Data Merged with CMORPH* Yields: RMORPH
*CPC Morphing Technique
Rain Gauge Data Merged with CMORPH* Yields: RMORPH
John Janowiak Climate Prediction Center/NCEP/NWS
Jianyin Liang China Meteorological Agency
Pingping Xie Climate Prediction Center/NCEP/NWS
Robert Joyce CPC / RS Information Systems
IPWG Melbourne, Australia October 24, 2006

2. ? GPM offers 3-hr sampling … to get finer temporal sampling …
(microwave) ?
1.5 hours apart
GPM offers 3-hr sampling … to get finer temporal sampling …
take advantage of 30-minute sampling afforded by Geo-IR data
Premise: Error in using IR to interpolate precip.
features identified by PMW <
Error in deriving precip. directly from IR
So avoid deriving precipitation estimates directly from IR …

3. ? Derive motion vectors from ½ hourly IR
(microwave) ?
1.5 hours apart
Derive motion vectors from ½ hourly IR
Apply motion to PMW-derived precipitation
“Morph”
(Joyce et al., J. Hydromet, 2004)

6. Biases in Satellite Estimates

7. Gauge-CMORPH Merging Algorithm Step 1: Bias Correction
Assumptions
- Biases relatively stable over a region and time
- Biases can be approximated as ratios between the estimates & gauges
Procedures
- Performed once a day using data for all 24 hourly slots
- Each day: RATIO = GAUGE / CMORPH (last 30 days; each gauge)
- Optimal Interpolation (OI) technique (Gandin 1965) applied to ratios
- “Un”biased CMORPH: CMORPH x RATIOanalyzed

8. Gauge-CMORPH Merging Algorithm Step 2: Combining Gauge & Satellite Data
Bias-corrected satellite estimates and gauge data combined via Optimum Interpolation Technique (“OI”)
- Bias-corrected satellite estimates used as first-guess
- Gauge data are incorporated
- Relative weighting at a grid box is a function of:
- quality of satellite estimates at the grid box;
- density of local gauge network density

9. Proof-of-Concept: Guang-Dong Province over Southern China
Topography
Guang-Dong
Tibet plateau
South China Sea

10. Hourly precipitation
reports from
394 stations over
~150,000 km2
(~380km2/gauge)

11. An Example for 03Z, May 5, 2005 GAUGE ONLY ORIGINAL CMORPH
BIAS CORRECTED
MERGED

12. An Example for 03Z, May 5, 2005 GAUGE ONLY ORIGINAL CMORPH
BIAS CORRECTED
MERGED

13. Mean Precipitation from April 1 – June 30, 2005
GAUGE ONLY
ORIGINAL CMORPH
BIAS CORRECTED
MERGED

14. Hourly Gauge-Satellite Merged

15. PDF of Hourly Precipitation for April - June, 2005
Frequency of No-Rain Events
Gauge Station: %
Gauge Analysis: 81.5%
Original CMORPH: 77.3%
Gauge-CMORPH Merged: 83.3%
Frequency of Events with Rain

16. Dense Gauge Locations: Disaggregate Gauge Data
Use hourly CMORPH to partition daily gauge amounts
into hourly amounts (i.e. “disaggregate”)
- United States
- Australia
- China?

17. Valid for 24 hrs ending 12z August 8, 2006

18. Valid for 24 hrs ending 12z August 8, 2006
Daily sum of
hourly amounts
Daily RMORPH constrained
to daily gauge amount
Gauge data partitioned into
hourly amounts
Spurious coverage of light
gauge amounts reduced

20. Where to from Here?
Transition regional prototype to global
Experiment with OI tuning parameters
Cross-validation testing
4. Explore bias-adjustment for oceanic precip
- Normalize estimates to TRMM “2B31”
(TMI/PR)
- ATLAS buoys?
- Radar?

21. Thanks for listening

22. An Example for 03Z, May 5, 2005 GAUGE ONLY ORIGINAL CMORPH
BIAS CORRECTED
MERGED

23. An Example for 03Z, May 5, 2005 GAUGE ONLY ORIGINAL CMORPH
BIAS CORRECTED
MERGED

24. (microwave)
(in time)

25. Observed
(in time)

26. 2/3 +
1/3
1/3 +
2/3