1. CCl/CLIVAR/JCOMM ETCCDI Workshop De Bilt 13-15 May 2008 Climate Indices from Marine Data Val Swail - Environment Canada, Toronto Scott Woodruff - NOAA Earth System Research Laboratory, Boulder Elizabeth Kent - National Oceanography Centre, Southampton David Parker - Met Office, Exeter

2. CLIMAR-III: Third JCOMM Workshop on Advances in Marine Climatology 6-9 May 2008, Gdynia, Poland

3. FOCI ANTICIPATED FOR MARINE INDICES detection and attribution of climate change detection and attribution of climate change impact on marine industries (fishing, shipping, oil and gas production, tourism) impact on marine industries (fishing, shipping, oil and gas production, tourism) sea-level change sea-level change marine hazards (extreme winds and waves, harmful algal blooms, pollution) marine hazards (extreme winds and waves, harmful algal blooms, pollution) changes in hydrological cycle changes in hydrological cycle changes in ocean circulation changes in ocean circulation changes in sea ice and ice bergs changes in sea ice and ice bergs effects on coastal communities effects on coastal communities ocean acidification ocean acidification

4. QUESTIONS Posed to CLIMAR-III What observational data are needed (available) for climate change detection and attribution? What analyses of these data can provide information useful for climate change detection and attribution? What international coordination on data issues would improve climate change detection and attribution? What are the indices with most impact? What indices should we include on version 1 of our list for marine indices? How can we use what we have learned about data set uncertainties for indices? How do we make indices available to users? Common web site such as ETCCDI or links to that site? How do we develop indices for inclusion in IPCC AR5 in 2013 with increased focus on extremes and regional aspects? What other products should we consider for marine climatology?

5. CHARACTERISTICS REQUIRED FROM INDICES Indices should cover a range of time and space scales, multi-decadal to daily, global to regional and be relevant to their target audience Indices should cover a range of time and space scales, multi-decadal to daily, global to regional and be relevant to their target audience Indices should represent important impact-relevant aspects of the climate system and where possible link to the IPCC. Indices should represent important impact-relevant aspects of the climate system and where possible link to the IPCC. It must be possible to calculate and update the indices from existing data. It must be possible to calculate and update the indices from existing data. The indices must be prioritized due to limits in capacity. The indices must be prioritized due to limits in capacity. Indices can synthesize information and reduce noise by combining different components of the climate system. Indices can synthesize information and reduce noise by combining different components of the climate system. Indices should be based on homogenized and quality controlled datasets, well- understood models or reanalyses, or reliable predictions. Indices should be based on homogenized and quality controlled datasets, well- understood models or reanalyses, or reliable predictions. Indices should have a good signal to noise ratio. Indices should have a good signal to noise ratio. A subset of indices should be suitable for presentation to politicians A subset of indices should be suitable for presentation to politicians Common climate indices should be developed for models and observations Common climate indices should be developed for models and observations Indices should be robust for detection, important and doable Indices should be robust for detection, important and doable

6. MARINE DATA SOURCES AND PROGRAMS ICOADS – ships (from 1662), moored and drifting buoys ICOADS – ships (from 1662), moored and drifting buoys World Ocean Database (WOD) World Ocean Database (WOD) Global Digital Sea Ice Data Bank (GDSIDB) Global Digital Sea Ice Data Bank (GDSIDB) Permanent Service for Mean Sea Level (PSMSL) Permanent Service for Mean Sea Level (PSMSL) Derived data sets – HadISST, HadSLP, HadGOA (www.hadobs.org ) Derived data sets – HadISST, HadSLP, HadGOA (www.hadobs.org )www.hadobs.org Satellite – SST, wind, wave, ice, sea level Satellite – SST, wind, wave, ice, sea level Reanalyses Reanalyses Shipboard Automated Meteorological and Oceanographic System Initiative Shipboard Automated Meteorological and Oceanographic System Initiative Global Ocean Surface Underway Data Pilot Project Global Ocean Surface Underway Data Pilot Project Ship Observations Team Ship Observations Team Data Buoy Cooperation Panel Data Buoy Cooperation Panel Argo Argo Ocean Sites Ocean Sites Global Sea Level Observing System Global Sea Level Observing System International Ocean Carbon Coordination Project International Ocean Carbon Coordination Project Global Temperature and Salinity Profile Program Global Temperature and Salinity Profile Program JCOMMOPS (www.jcommops.org ) JCOMMOPS (www.jcommops.org )www.jcommops.org

7. Annual numbers of marine reports in ICOADS, stratified by platform type for 1936 to 2005 (Woodruff et al. 2008)

8. The potential for marine indices OperationalResources required Research required Data required Large scale pressure (e.g. NAO, PNA) Temperature indicesAtlantic Meridional Circulation Max & min temperatures Large scale temperature (e.g ENSO) Marine winds and pressures CurrentsWind gusts Sea Ice parametersWavesPolar lows.Storm surges Ocean heat contentSea levelHydrographic time series (e.g. ICES) Extremes Salinity measuresFisheries information & biology Precipitation Ocean transports and water mass properties Ocean chemistry (e.g. dissolved oxygen) Ph/Ocean Acidification Hurricanes Clouds, humidity.

9. “Operational” Marine Indices Large Scale Pressure Indices Calculated by many different groups. Selection available from Ocean Observing Panel for Climate (OOPC) website. Link to existing sources Large Scale Temperatures Indices Global mean temperature. Gridded temperature anomalies. Long term datasets, back to 1850 Available from www.hadobs.orgwww.hadobs.org El Nino (e.g. Nino 3.4 Temperatures), link to OOPC website Sea Ice E.g. global scale ice extent; regional ice extents Available from JCOMM Expert Team on Sea Ice or US National Snow and Ice Data Center.

10. OOPC State of the Ocean

12. Multivariate ENSO Index (MEI) Based on the six main observed variables over the tropical Pacific: sea-level pressure, zonal and meridional surface wind, surface air and sea temperature and total cloudiness fraction, in ICOADS. Based on the six main observed variables over the tropical Pacific: sea-level pressure, zonal and meridional surface wind, surface air and sea temperature and total cloudiness fraction, in ICOADS. MEI is calculated as the first unrotated Principal Component (PC) of all six observed fields combined. Negative values of the MEI represent the cold ENSO phase, La Niña, while positive MEI values represent the warm ENSO phase (El Niño). MEI is calculated as the first unrotated Principal Component (PC) of all six observed fields combined. Negative values of the MEI represent the cold ENSO phase, La Niña, while positive MEI values represent the warm ENSO phase (El Niño). http://www.cdc.noaa.gov/people/klaus.wolter/MEI/ http://www.cdc.noaa.gov/people/klaus.wolter/MEI/

13. 13 Hadley Centre for Climate Prediction and Research Global temperature Annual Anomalies and uncertainties 1850-2005 Monthly anomalies: 1850 – Jul 2006

14. Temperature trend over 1901-2003

15. 15 Hadley Centre for Climate Prediction and Research Monthly Surface Temperature Sept. 2006 PercentilesAnomalies Tropical Central and EastPacific SST Anomalies, 1850-2005

16. Trends in warm days 1950-2003 Blue and red dots indicate trends significant at the 5% confidence level. Crosses denote non- significant trends. Days with tmax > 90 th percentile

17. 17 Hadley Centre for Climate Prediction and Research Annual sea-ice extent changes, 1973-2006 (updated from IPCC, 2001) Retreating until late1990s. Little retreat 1998-2003 2006 record low so far Antarctic sea-ice Not declining since 1976 Arctic sea ice

18. © Crown copyright Background: ocean heat uptake Lyman et al., [2006] Heat content for Anomaly for the upper 300m See Gregory et al. [2004] To address these questions we require: (i) (i)Comprehensive error estimates for observed time series. (ii) (ii)Ocean climate indices with a high signal-to-noise ratio and small uncertainties. Questions: (i) (i)What is the rate of oceanic heat uptake? (trend?) (ii) (ii)Is the decadal variability seen in the observations (but not the models) real?

19. Marine Indices Requiring Resources Temperature - air and sea – mean & percentiles Humidity – mean or median Cloud cover- mean Wind and wave mean, max, from observations 10 and 90 percentiles, frequency greater than percentile thresholds (absolute values – gale and storm winds; 3 and 6 m waves?); sea and swell? From reanalysis or satellites? Sea Level - mean global and regional anomalies Storm Surge, Storm Tide, frequency, extreme Sub-surface ocean Salinity - surface salinity Temperature – isotherm depth (which?) heat content anomaly (to 300m) water mass properties (volume of 18˚ water?)

20. Global Wave Climatology Atlas S. Caires, G. Komen, A. Sterl, V. Swail www.knmi.nl/waveatlas

21. Number of gridpoints Year of changepoint Monthly mean wind speed 1966 Monthly mean sig. wave height Number of gridpoints Year of changepoint 1966 Number of gridpoints of a significant changepoint in the indicated year Wind speed – locations of changepoint in Nov. 1966Sig. wave height – location of changepoint in Nov. 1966 Grid-boxes of significant changepoint are shown in black xx

22. Monthly mean wind speed (m/s) at (40.5°N, 40.5°W) Nov. 1966Dec. 1997 Monthly mean sig. wave height (m) at (40.5°N, 40.5°W) Nov. 1966Dec. 1997

23. GLOSS Network Sea level, storm surge indices

24. http://www.cdc.noaa.gov/coads-las/servlets/dataset

25. © Crown copyright Eighteen Degree Water (subtropical mode water (STMW)) volume in the North Atlantic (defined as volume of water with temperature between 18.5 C and 17.5 C in the subtropical North Atlantic). Correlated with the NAO at lag 6 yrs (NAO leads the EDW) r=0.36 for ‘winter’ (Feb, Mar, Apr) after Kwon & Riser, 2004 Source: HadGOA HadGOA: monitoring water masses CO 2 Uptake (Bates et al).

26. © Crown copyright Changes in mean T and isotherm depths Mean 14C isotherm depth Mean T above 14C isotherm 1985-2004 minus 1961-1980  Deepening of isotherms in N. Atlantic associated with change in phase of NAO.  Large areas of slight shoaling and smaller areas of large deepening  Wide-spread warming signal.  Less prone to aliasing from changes in ocean circulation than z-levels.  Greater insight into underlying physical mechanisms

27. More Speculative Marine Indices Temperature - min, max and higher percentiles Wind and wave - higher percentiles and extremes Measures of persistence Storm Surge inundation zones Sea Ice – ice thickness and stages of development; iceberg propagation Currents Biological – Harmful Algal Blooms, coral bleaching Atlantic Meridional Overturning Circulation

28. Enabling Mechanisms ICOADS - Critical and critically under-resourced Proposed new initiative for value-added ICOADS (QC, bias corrections, etc.) JCOMM Expert Teams Wind Waves and Storm Surges Sea Ice Marine Climatology Task Team on the Marine-meteorological and Oceanographic Summaries (TT-MOCS) Task Team on Delayed-Mode VOS (TT-DMVOS) Engage expertise within the CLIMAR community to assist in the development and production of marine indices(marineclimatology.net) marineclimatology.net Liaise with other groups interested in marine indices such as the AOPC and OOPC

29. The End!