1. High Resolution Gauge – Satellite Merged Analyses of Precipitation: A 15-Year Record Pingping Xie, Soo-Hyun Yoo, Robert Joyce, Yelena Yarosh, Shaorong Wu, and Roger Lin 2012.10.16.

2. Objectives Reprocessing CMORPH for the entire TRMM era (1998-present) using a consistent version algorithm and fixed versions of inputs throughout the data period Performing bias correction / magnitude adjustment Blending bias-corrected CMORPH with gauge analysis

3. CMORPH Reprocessing 1) Algorithm and Inputs Algorithm CMORPH algorithm as of 2009 Joyce et al (2004) No KF enhancements Inputs PMW L2 retrievals (GPROF 2004) CPC Geo sat IR at 4km (Janowiak et al. 1999) NESDIS daily snow maps

4.  8kmx8km / 60 o S-60 o N  30-min interval / January 1998 to the present CMORPH Reprocessing 2) Products

5. Regionally different Temporally changing Non-linear CMORPH Bias Correction 1) Bias in the raw CMORPH

6. Over Land –PDF matching against daily gauge analysis –PDF tables established as a function of region and season using historical and real-time data Over Ocean –Calibration against a long-term record (pentad GPCP) with stable quality but coarser resolution (2.5 o lat/lon, 5-day) CMORPH Bias Correction 2) Strategy

7.  Large-scale bias removed  Correlation improved Daily Gauge KF-CMORPH Gauge-Adjusted KF-CMORPH 2000-2009 Annual Mean Comparison over Africa CMORPH Bias Correction 1) Results over land

8. CPC Original CPC HS CRTD CPC RT CRTD 0.098-0.247-0.171 0.003-0.481-0.142 0.8480.177-0.135 -0.512-0.540-0.261 -1.128-0.477-0.256 -2.755-0.921-0.467  Bias in mm/day  Bias reduced substantially in CPC version of the estimates CMORPH Bias Correction 1) Comparison with daily gauge for June 2011 RegionCPC Original CPC HS CRTD CPC RT CRTD Globe0.5510.6170.647 60N-40N0.5350.5490.587 40N-20N0.5780.6500.677 20N-20S0.5530.5840.602 20S-40S0.6050.7150.767 40S-60S0.6660.6840.698 CorrelationBias

9. CMORPH Bias Correction 1) Applications in verification of CFSR precipitation

10. Combining Bias-Crtd CMORPH with Gauge 1) Strategy –This is only possible for several regions due to different daily ending time in the gauge reports Africa (06Z) CONUS/MEX (12Z) S. America(12Z) Australia(00Z) China(00Z) –Based on Xie and Xiong (2011) Combining the bias-corrected CMORPH with gauge observations through the Optimal Interpolation (OI) over selected regions where gauge observations have the same daily ending time CMORPH and gauge data are used as the first guess and observations, respectively

11. Gauge analysis depict heavy rain but tend to extend the raining area Satellite data tend to under-estimate Merged analysis present improved depiction of the heavy rain Combining Bias-Crtd CMORPH with Gauge 2. Example

12.  Reports from up to 28 stns available in a 0.25 o lat/lon grid box over Seoul  Arithmetic mean of 28-stn reports taken as the ‘truth’  Gauge analyses using 1000 combinations of sub-set stations are combined with bias-corrected CMORPH and compared to the ‘truth’ at the grid box over Seoul  Correlation is calculated for the combined analyses and the input gauge / CMORPH. Results are plotted in different colors for different gauge network densities Combining Bias-Crtd CMORPH with Gauge 3. Validations

13. Summary Three sets of gauge-satellite precipitation analyses Reprocessed CMORPH Satellite Estimates Global 8kmx8km; 30-min 1998 to the present Bias-corrected Satellite Estimates Global 8kmx8km; 30-min 1998 to the present Gauge-satellite combined analyses Regional 0.25 o lat/lon; daily 1998 to the present