Second ET2.2 meeting, Offenbach, Germany, 27-29 October 2009

1. Progress and efforts on the responsible actions related to the ET2.2 workplanXiaolan L. WangClimate Research DivisionScience and Technology BranchEnvironment Canada Second ET2.2 meeting, Offenbach, Germany, 27-29 October 2009

2. Climate monitoring priorities: 1. Development of application of satellite and in-situ data for climate monitoring and climate-change detection 2. Improvements in monitoring global and continental extremes (create an accessible database of global and continental extremes) 3. Stimulation and coordination of phenological practices and promoting the use of phenological data in climate monitoring activities 4. Capacity building in climate monitoring in developing countries Team’s efforts: the WMO Bulletin paper, the web site, the State of the Climate translation, … Other action items in which I am supposed to be involved: Action-2: A web-based “capacity audit” of satellite and in-situ climatologies and related activities - I think Rainer has done a good job in this area - my contribution is mainly limited to development of data homogenization techniques tohelp define the climatology and extremes (details later) Action-5: Capacity building through demonstration on the ET2.2 web site– not completed - got some updates for this action item from a research in the internet The “Stage of ET2.2 WP realization” needs to be updated, and to add in Actions 2,3,5,6,12,13,16 - see the document

3. Almost the same adjustment for all data in the segment Smaller absolute adjustments for larger values For a daily maximum temperature series with 2 changepoints - to be adjusted to the last segment (Seg. 3) Climate Data Homogenization ~ Defining the historical climatologyand extremes (climate indices calculation ~ ET2.1) - development of data homogenization techniques/algorithms – RHtestV3 Quantile-Matching (QM) Adjustment Algorithm for Gaussian data (e.g. temperatures) Quantile-Matching Adjustment Algorithm for non-negative data (e.g. wind speeds) - development of techniques for homogenization of daily precipitation series – RHtest_dlyPrcp Quantile-Matching Adjustment Algorithm for non-zero daily precipitation amounts The RHtestV3, RHtest_dlyPrcp, and RClimDeX software packages available at http://cccma.seos.uvic.ca/ETCCDMI/software.shtml • homogenization of Canadian temperature, • pressure and • surface wind speed • adjustment of Canadian precipitation for • wetting loss, gauge undercatch, … • - will homogenize Canadian daily precipitation Adjusted/Homogenized Canadian Climate Database (AHCCD) - made available to the public athttp://www.cccma.bc.ec.gc.ca/hccd/index.shtml - used in producing Climate Trends and Variability Bulletin (CTVB; see next slides)

4. Summer 2009 – 27th warmest since 1948 Summer 2009 – 30th wettest since 1948 Summer 1998 – warmest since 1948 Summer (June-August) Summer 2005 – wettest since 1948 Wettest:2005 Driest:1958 Climate Trends and Variations Bulletin (CTVB) Current bulletins at http://www.msc-smc.ec.gc.ca/ccrm/bulletin/national_e.cfm past bulletins at http://www.msc-smc.ec.gc.ca/ccrm/bulletin/archive_e.cfm CTVB places mean temperature and total precipitation, for the most recent season or year, in a spatial and historical context - national summary:

5. Canada - National Summary: Warmest Coolest Temp. trend Wettest Driest Winter 2005/06 1971/72 +0.35˚C/decade 1964/65 1977/78 (Dec-Feb) (+3.9˚ C) (-3.2˚C) (greatest warming) (+19.4%) (-20.1%) Spring 1998 1974 +0.23˚C/decade 1979 1956 (Mar-May)(+3.2˚ C) (-1.8˚C) (+28.8%) (-21.3%) Summer 1998 1968 +0.15˚C/decade 2005 1958 (Jun-Aug) (+1.8˚ C) (-0.8˚C) (+21.2%) (-14.3%) Autumn 1998 1986 +0.11˚C/decade 1981 1976 (Sep-Nov) (+2.3˚ C) (-1.8˚C) (+24.1%) (-20.3%) Warmest 5 years since 1948:all except two years occurred after 1986 Rank 1 2 3 4 5 Winter 2006 1987 2007 1998 1960 Spring 1998 2006 1999 2005 1988 Summer 1998 2006 2008 1989 2001 Autumn 1998 2005 1948 2003 2001

6. * warmest to coldest Climate Trends and Variations Bulletin (CTVB) Canada - Regional Summary, e.g. (based on data for 1948-2009)

7. Climate extremes monitoring in Canada • Climate Summaries available at http://www.climate.weatheroffice.ec.gc.ca/prods_servs/cdn_climate_summary_e.html - Monthly extremes and averages of Temp. and Precip. amount - Degree days above/below 18ºC - Snow on the Ground at the end of the month - Bright sunshine hours … • Climate Data Almanacs http://www.climate.weatheroffice.ec.gc.ca/climateData/canada_e.html (select Almanac in the interval box)

8. Climate extremes monitoring in Canada (cont’d) • Customized graphs of daily extremes available at http://www.climate.weatheroffice.ec.gc.ca/climateData/canada_e.html (select daily in the interval box, then click on a station, then select customizable chart in the navigation box at the bottom right of the daily page) • Canadian Atlantic Region Monthly Climate and Storm Summaries available at http://atlantic-web1.ns.ec.gc.ca/climatecentre/default.asp?lang=en&n=30733EE3 • Quebec Region Climate Monitoring website http://www.criacc.qc.ca/climat/suivi/200608_e.html - Daily/monthly/seasonal/annual climate summaries, extreme events - Table of historical extreme maximum temperatures in Quebec

9. The Blended Precipitation Project ~ Defining the historical climatologyand extremes To blend in-situ precipitation data with Satellite Precipitation Estimates (SPEs)  Blended (gridded) precipitation data for Canada – critical for filling in the data gaps in the North - Clean up and homogenize in-situ P data (to the extent possible)  “clean” in-situ P - Develop methods to combine different SPEs (SSM/I, AIRS, TVOS) for Canada  mSPE0 - Develop methods to remove biases in the combined multi-sensor SPEs  mSPE1 • Develop methods to blend the clean in-situ P with the bias-removed mSPEs, i.e., mSPE1 •  Blended (gridded) precipitation data for Canada (Product 1) • Investigate the use of GEM or RCM precipitation fields in addition, or as an alternative, to • the SPEs as background fields •  Blended (gridded) Precipitation Analysis for Canada (Product 2) • * in collaboration with Vincent Fortin (CaPA project) • Test temporal homogeneity of the blended precipitation data series, • assess trends and variability, and comparison with other datasets

10. mSPE1: Bias-removed mSPEs Obs’d Field (Kriging) Blended Field Case Study - July 2003: mSPE0: Original mSPEs SSM/I + AIRS (GPROF, UMORA) In summary: In data sparse regions, the blended field has more details than does the ordinary kriging field, which comes from the mSPEs; otherwise they are similar. (mm/day)

11. %Days with wind speed exceedence of 17 m/s for Dec. 2008 %Days with wave height exceedence of 6 m for Dec. 2008 Wind and Ocean Wave Climatology (Atlas) – North Atlantic and Beaufort Sea (Environment Canada’s wind re-reanalysis and wave hindcasts): http://www.oceanweather.net/MSC50WaveAtlas/ - monthly means and anomalies - extremes (percentiles) and anomalies …

12. Thank you very much!