1. Cooperative Research Programs (CoRP) Satellite Climate Studies Branch (SCSB) 1 1 Reconstruction of Near-Global Precipitation Variations Based on Gauges and Correlations with SST and SLP Thomas Smith 1 Phillip Arkin 2 1. NOAA/NESDIS/STAR SCSB and CICS, College Park, Maryland 2. CICS/ESSIC/University of Maryland, College Park, Maryland Cooperative Institute for Climate and Satellites (CICS) Earth System Science Interdisciplinary Center (ESSIC)

2. Cooperative Research Programs (CoRP) Satellite Climate Studies Branch (SCSB) 2 2 Outline All analyses are of Precipitation Anomalies Base Satellite Data –IR (from 1979), MW (from mid 1980s) –Need global satellite analyses for reconstruction statistics Direct Reconstructions: fitting data to Empirical Orthogonal Functions (REOF) –EOF (or PC) analysis, for covariance maps –Fit available gauge-station data to a set of covariance maps –Monthly gauge-based 5-degree analyses available beginning 1900 Indirect Reconstructions: using Canonical Correlation Analysis (RCCA) –Correlate fields of sea-surface temperature (SST) and sea-level pressure (SLP) with fields of precipitation –Both SST and SLP analyzed for the 20 th century Merged Direct & Indirect Reconstructions –Direct Recons for over land and interannual and shorter variations over oceans –Indirect Recons more reliable for multi-decadal variations over oceans

3. Cooperative Research Programs (CoRP) Satellite Climate Studies Branch (SCSB) 3 3 Satellite-Based Analyses Monthly analyses, 1979-Present Several analyses available –Global precipitation climatology project (GPCP), multiple inputs, begins 1979, developed for climate studies –CAMS/OPI, several inputs, begins 1979, developed for interannual studies –Optimum Interpolation (OI) of MW and ERA-40 reanalysis, begins 1987, data problems over land before 1992 New OI analyses being tested in an attempt to obtain longer record using OI methods

4. Cooperative Research Programs (CoRP) Satellite Climate Studies Branch (SCSB) 4 4 Anomaly S.D. CAMS/OPI ocean S.D. more concentrated in tropics –OIP best for convective precipitation Both GPCP and OI S.D. have more extra-tropical variations –GPCP uses mix of satellite estimates + gauges –OI uses only microwave estimates, stronger variations than GPCP

5. Cooperative Research Programs (CoRP) Satellite Climate Studies Branch (SCSB) 5 5 Reconstruction Based on EOFs (REOF) EOF spatial covariance modes –3 regions: 80S-20S, 30S-30N, 20N-80N –Separate so tropics do not dominate –Only large-scale modes used In each region, fit available gauge anomalies to the set of modes –3 areas merged with smoothing at boundaries Cross-validation testing to find the best set of modes for each region –For S.H. 5 EOFs, for Tropics 15 EOFs, for N.H. 10 EOFs

6. Cooperative Research Programs (CoRP) Satellite Climate Studies Branch (SCSB) 6 6 Gauge Sampling of 5-deg Regions Gauge-based analyses, annual averages of monthly % sampling –Global Historical Climate Network (GHCN) –Global Precipitation Climatology Center (GPCC) –Climate Research Unit (CRU) CRU gives best sampling of 5-deg areas in historical period –Differences due to data processing & how many stations needed to form a 5- deg area –Test all & use CRU based analysis

7. Cooperative Research Programs (CoRP) Satellite Climate Studies Branch (SCSB) 7 7 REOF Spatial Statistics Global spatial standard deviation (upper) –Similar interannual changes –GHCN low before 1940 (low sampling) –CRU strong most of record –Filtered GPCP strong at the end of record Global spatial correlation between analyses –High GHCN, CRU for high- sampling period, lower values before 1940

8. Cooperative Research Programs (CoRP) Satellite Climate Studies Branch (SCSB) 8 8 Regression Against SOI SOI represents ENSO interannual variability (annual averages) Shows typical ENSO precipitation patterns GHCN-based recon gives slightly weaker regression

9. Cooperative Research Programs (CoRP) Satellite Climate Studies Branch (SCSB) 9 9 Regression Against NAO Dec-March Regression Similar patterns, especially in Northern Hemisphere GPCC tropical Pacific different from the others

10. Cooperative Research Programs (CoRP) Satellite Climate Studies Branch (SCSB) 10 Reconstructions Based on CCA (RCCA), and Comparisons to REOFs Canonical Correlation Analysis (CCA) –Fields of predictors correlated with a predictand field –Data smoothed and condensed using EOFs before CCA computed Training Data: GPCP, SST, SLP (1979-2004) –Annual average anomalies, GPCP satellite based –SST and SLP give ocean observations correlated with precipitation on long time scales Analysis Data: SST, SLP (1900-2004) –SST & SLP global analyses available

11. Cooperative Research Programs (CoRP) Satellite Climate Studies Branch (SCSB) 11 Ocean Comparisons RCCA & REOF ocean averages, filtered RCCA & REOF differ before 1980 –1970s climate shift in RCCA –REOF does not resolve trend in RCCA & in AR4 ensemble RCCA & REOF(GPCP) similar –REOF(GPCP) can be used for updates

12. Cooperative Research Programs (CoRP) Satellite Climate Studies Branch (SCSB) 12 Merged Reconstructions REOF reliable over land where gauges are available Interannual REOF reliable over oceans, but multi-decadal REOF less reliable over oceans Multi-decadal RCCA appears to be more reliable over oceans Merge by replacing ocean multi-decadal REOF with ocean multi-decadal from RCCA For recent period, use REOF(GPCP)

13. Cooperative Research Programs (CoRP) Satellite Climate Studies Branch (SCSB) 13 Merged Recon Averages Filtered Recons for All Areas and Ocean Areas Ocean average changes most Including land removes the 1970s climate shift and most interannual variations

14. Cooperative Research Programs (CoRP) Satellite Climate Studies Branch (SCSB) 14 Normalized Joint EOF Merged Recon and AR4 Ensemble Both annual averaged and filtered before JEOF First mode indicates joint trend-like variations –Tropical ENSO-like increase –Mid-latitude decrease –High-latitude increase –Pattern differences may reflect model biases

15. Cooperative Research Programs (CoRP) Satellite Climate Studies Branch (SCSB) 15 Summary & Conclusions EOF-based reconstructions resolve oceanic interannual variations through the 20 th century –Direct reconstruction using the available gauge data –Over land REOF does best for all variations CCA-based reconstructions resolve oceanic multi-decadal variations through the 20 th century –Indirect method using correlations with better sampled variables Merged analysis takes advantage of the best qualities of both Future improvements possible with new data or refined reconstruction methods –Extended reanalyses may yield independent precipitation information Data available at http://cics.umd.edu/~tsmith/recpr/