The Uses of Marine Surface Data in Climate Research

1. The Uses of Marine Surface Data in Climate Research David Parker, Hadley Centre, Met Office MARCDAT-2, Met Office, Exeter, October 17-20, 2005 .

2. Uses of marine surface data in climate research • Global climate monitoring • Empirical studies of ocean-atmosphere interaction • Multivariate analyses of climatic variations • Forcing of atmospheric general circulation models: • Climate change detection/attribution • Validation or improvement of land surface air temperatures • Boundary and near-surface conditions for atmospheric and oceanic models and reanalyses • Validation of coupled atmosphere-ocean general circulation models • Initial conditions for seasonal to decadal prediction

3. Global climate monitoring: IPCC

4. Global climate monitoring: IPCC Zonal-average SST anomalies (°C) (relative to 1961-90) in the Atlantic (top), Indian (middle) and Pacific (bottom) Oceans, 1900-2004. Annual anomalies are smoothed 1:3:4:3:1 to show multi-annual variations

5. Global climate monitoring: Climatological Summaries Scheme From Elanor Gowland: POSTER

6. Empirical studies of ocean-atmosphere interaction E Tropical Pacific SST (left) and SST gradients (right) from (top to bottom) AVHRR, Reynolds OI, Real-Time Global SST analysis, and AMSR. From Chelton and Wentz (BAMS August 2005)

7. Multivariate analyses of climate variations: coverage of HadSLP data in 5° cells 1851-60, 1861-70, 1911-20, 1941-50, 1971-80, 1991-2000. From Allen & Ansell (2005)

8. Multivariate analyses of climatic variations Mean sea level pressure during UK heatwaves. From Ansell et al., 2005

9. Multivariate analyses of climatic variations El Nino 1877-8 SST MSLP U V Precip Sea level Alexey Kaplan

10. Multivariate analyses of climatic variations Significant wave heights versus atmospheric circulation. From Vika Grigorieva and Sergey Gulev

11. Multivariate analyses of climatic variations • Vasily Smolyanitsky (sea ice)

12. Forcing of atmospheric GCMs: Climate change detection/attribution • Forcing an atmospheric GCM with historical SSTs: • Ensures that interannual variability is well represented, so comparisons with vs. without external forcings are more likely to be able to detect their signals. • BUT the historical SSTs already largely subsume the effects of these forcings, so detection/attribution is only possible over land and interpretation may be ambiguous; AND atmospheric forcing of the ocean cannot be represented. • SO “Pacemaker” partly-coupled atmosphere-ocean experiments are being planned, specifying SST only in key areas where the ocean forces the atmosphere.

13. Forcing of atmospheric GCMs: Validation and improvement of land surface air temperatures From Folland (International J. Climatology, 2005)

14. Boundary and near-surface conditions for atmospheric and oceanic models and reanalyses • ECMWF plans 70-year atmospheric reanalysis back to 1940s: Adrian Simmons. Needs include good metadata (e.g., type of wind observation; anemometer heights) and excellent SST and sea ice concentration and, ideally, ice thickness. • NOAA/CDC plans surface-data-based atmospheric reanalysis back to 1900 or before: Gil Compo

15. Influence of high-resolution SST on atmospheric analyses From Chelton and Wentz (BAMS August 2005)

16. Validation of coupled atmosphere-ocean general circulation models Summary of fluxes: global annual means Ian Culverwell & Helene Banks (POSTER)

17. Validation of coupled atmosphere-ocean general circulation models Top: Annual cycles of standard deviation of Niño 3 SST. Bottom: Power spectra of Niño SST anomalies. HadISST (solid), HadCM3 (dots), HadCEM (dash) and HadGEM1 (dash-dot). From Johns et al. (submitted to J. Climate 2005)

18. Validation of coupled atmosphere-ocean general circulation models Seasonal cycles of sea-ice area (Alison McLaren et al: POSTER)

19. Validation of coupled atmosphere-ocean general circulation models Mean cyclone strength anomaly (hPa), December-February, from ERA40 (top left), HadAM3 (top right), HadGEM1 (bottom left) and HadGAM1 (bottom right). From Ringer et al. (submitted to J. Climate 2005).

20. Validation of coupled atmosphere-ocean general circulation models North Atlantic Oscillation, defined as EOF1 of MSLP over the North Atlantic region, in HadCM3 (top), HadGEM1 (middle) and observations (GMSLP - bottom). Time series show the principal component for 140 years of model simulation or for 1871-1998 for observations. From Ringer et al. (submitted to J. Climate 2005).

21. Initial conditions for seasonal to decadal prediction Control (solid with dotted 5% and 95% error-bars) and test (dashed) anomaly correlations of hindcast (up to 10 seasons) global (top) and Niño 3 (bottom) annually averaged 1.5m surface air temperatures. The test includes altimeter data in its initialisation of ocean currents and therefore sets out with a better balance than the control. Stephen Cusack et al: POSTER

22. Conclusions • The range of uses of marine surface data in climate research is expanding • Marine (and all other) data records need to be of climate-quality, following the GCOS Climate Monitoring Principles.