The Global Precipitation Climatology Project (GPCP) CDR AT NOAA: Research to Real-time Climate Monitoring

Transcription

1 The Global Precipitation Climatology Project (GPCP) CDR AT NOAA: Research to Real-time Climate Monitoring Robert Adler, Matt Sapiano, Guojun Gu University of Maryland Pingping Xie (NCEP/CPC), George Huffman and David Bolvin (NASA- Goddard) and Long Chiu (GMU), Udo Schneider (DWD), Ralph Ferraro (NESDIS) 1

2 Project Description/Background Global Precipitation Climatology Project (GPCP) GPCP is an international, inter-agency effort under auspices of GEWEX/WCRP to provide CDR-quality global precipitation analyses at monthly, pentad and daily time scales. Climatology ( ) GPCP data used in > 1500 journal articles mm/d GPCP CDR Objectives 1) To successfully update, streamline and integrate the GPCP production code for automated production, 2) Transfer the routine production of GPCP products to CICS-MD and then to NCDC from the manually driven processing of the Co-Is, 3) Develop an interim CDR (ICDR) for GPCP monthly for operational climate analysis. GPCP products are analyses based on data sets 2

3 GPCP Products Version 2.2 NASA, NOAA, DWD, UMD, GMU, others Monthly, 2.5 Merged Analysis (1979-present) Adler et al. (2003), J. Hydromet., Huffman et al. (2009) GRL Pentad, 2.5 Merged Analysis (1979-present) Xie et al. (2003) J. Climate Daily, 1 Merged Analysis (1997-present) Huffman et al. (2001) J. Hydromet. [although produced using different data sets and algorithms, products are integrated,i.e. they add up] normally produced ~ 3 months after observation time 3

4 GPCP Monthly Analysis Product: CDR RSS SSMI/SSMIS T b s over ocean CDR SSMI/SSMIS rainrates over land (Ferraro) Geo-IR (Xie) calibrated by SSMI/SSMIS rainrates for sampling TOVS/AIRS empirical precipitation estimates at higher latitudes (ocean and land) GPCC gauge analysis to bias correct satellite estimates over land and merge with satellite based on sampling OLR Precipitation Index (OPI) (Xie) used for period before

5 Global Ocean Surface Temperature, Water Vapor and Precipitation Residual Trends (ENSO and Volcano Signals Removed) SST Column Water Vapor Climate Shift Precipitation With inter-annual ENSO and volcano signals removed, the interdecadal signal (climate shift/warming hiatus) is more obvious in surface temperature and water vapor fields, but not in global precipitation. Shift associated with Pacific Decadal Oscillation (PDO) and Atlantic Multidecadal Oscillation (AMO) Possible GPCP ocean underestimate post

6 Possible Problem with Ocean Precipitation Related to SSMI/SSMIS Transition at Jan Global Ocean Precipitation Orig., ENSO and Volcano Signals Residual Trends Possible GPCP ocean underestimate post

7 GPCP Ocean (40N-40S) Rain compared to TRMM TMI Rain ~.05 mm/d, out of 2.8 mm/d SSMI/SSMIS overlap in 2008 will be used (again) to adjust to eliminate shift. Will result in new Version 2.3 (which will also likely include an update of GPCC gauge analysis). 7

8 Patterns of Trends ( ) Surface Temperature from GISS Water Vapor from SSMI (ocean) C/decade mm/decade mm/d/decade Precipitation Trend from GPCP Is this the trend pattern of precipitation change related to global warming? 8

9 Precipitation Trend Patterns During Satellite Era GPCP Observed PDO AMO No PDO or AMO Estimate of Global Warming Precip. Trend Pattern Technique uses PDO and AMO indices and regression analyses Gu and Adler, 2014 under review 9

10 Interim CDR GPCP Monthly Analysis for October 2014 mm/day Anomaly from October Climatology An Interim CDR of monthly, global precipitation (within 10 days of the end of the month) is being produced at UMD using almost the same data sources and analysis strategy to produce an estimate of the past month s precipitation that can be used reliably to compare against the research quality GPCP product over the past 35 years. Main difference between CDR and ICDR is gauge analysis ICDR uses GPCC first guess We could examine using other gauge analyses available early in month 10

11 ICDR Anomalies mm/d 11

12 ICDR Percent of Normal Normals calculated from ) 12

13 El Nino La Nina Precipitation Anomalies Top 1/3 rd Bottom 1/3 rd of months Using Nino 3.4 Index mm/d 13

14 Evolution of ENSO Pattern July August Sep. Oct. 14

15 ENSO-Related Precipitation Indices Curtis and Adler (2008) ESPI (ENSO Precipitation Index) 15

16 ENSO Precipitation Index (ESPI) (Updated Oct 2014; Includes ICDR for Aug, Sep, Oct 2014) ESPI with CDR ESPI with ICDR Nino 3.3 SST ESPI Oct

17 Summary GPCP Climate Data Records (CDR) project to convert software to operations at NCDC on track for monthly, pentad and daily products. As an intermediate step the GPCP CDR products will be produced at CICS-MD in 2015 Techniques and software have been developed to produce an interim CDR (ICDR) for the monthly GPCP product within 10 days of the end of the month for use in climate monitoring at NCDC and elsewhere Daily precipitation ICDR should be explored with current and future high time resolution products. (GPCP Version 3 [under development] is going in this direction also) Research on past climate variations using high quality climate products such as GPCP continues under other projects 17

18 El Nino Index (EI) La Nina Index (LI) El Nino Index (EI) La Nina Index (LI) 18

19 High Time Resolution Satellite Precipitation Information (~3-hr, 25 km) Merged passive microwave observations currently available: TMPA/3B42 from NASA, CMORPH from NOAA/CPC, GSMaP from Japan TRMM satellite key to inter-calibration of rainfall. Global Precipitation Measurement (GPM) mission--gpm IMERG product will start next year automatic re-processing to beginning of TRMM era (1998) for consistent long record Also PERSIANN (IR-based, daily, calibrated by GPCP monthly) an NCDC CDR 19

20 Climatology and Variations in Intense Daily Precipitation July mm/d Mean mm/d 95 th Percentile Threshold 15 years of data 20

21 Climatology and Variations in Intense Daily Precipitation July Fraction of Days with Precip. > 25 mm 15 years of data Fraction of Days with Precip. > 50 mm Using TMPA, PERSIANN CDR, and/or CMORPH we could do similar parameters for individual months (e.g., fraction of days over 25 mm and anomaly from that climatology). Data set being used would be calibrated by GPCP monthly ICDR rain amount for consistency. 21

22 Standardized Precipitation Index (SPI) for October 2014 SPI value Category 2.00 or more Extremely wet 1.50 to 1.99 Severely wet 1.00 to 1.49 Moderately wet 0 to 0.99 Mildly wet 0 to Mild drought to Moderate drought to Severe drought 2 or less Extreme drought 22

23 SPI value Category 2.00 or more Extremely wet 1.50 to 1.99 Severely wet 1.00 to 1.49 Moderately wet 0 to 0.99 Mildly wet 0 to Mild drought to Moderate drought to Severe drought 2 or less Extreme drought 23

24 ICDR Percent of Normal (Updated Oct 2014; Normals calculated from ) 24