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1 The important role of: continuity of observations and data products for IPCC Critical role for...

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1 The important role of: continuity of observations and data products for IPCC Critical role for GCOS and WCRP Kevin Trenberth NCAR Kevin Trenberth NCAR Slide 2 2 Climate Observations Process studies: atmosphere, ocean, land, cryosphere and their interactions Sustained observations: the climate record Enhanced monitoring Analysis, assimilation and data products Data stewardship, data access, QC JSC 2010: Observations white paper Slide 3 3 WOAP: Key climate issues Climate data records Continuity, continuity, continuity; The need for reprocessing and reanalysis of past data and coordination of these activities among agencies and variables; Includes evaluation and assessment or results Importance of calibration, accuracy, benchmarks, Space and in situ observations; Reanalysis to produce global gridded fields WOAP: Key climate issues Climate data records Continuity, continuity, continuity; The need for reprocessing and reanalysis of past data and coordination of these activities among agencies and variables; Includes evaluation and assessment or results Importance of calibration, accuracy, benchmarks, Space and in situ observations; Reanalysis to produce global gridded fields GRUAN, GPS RO, CLARREO Slide 4 World Climate Research Programme 4 WOAP-1 Reprocessing: assess variables for need and readiness, and commitments. Include in GEOSS. 5 Principles for Re-Processing Climate Data Records For climate, the value of an observational record increases with time, provided that the record is continuous and homogeneous. As datasets are used, characteristics of the data and problems are exposed, and often solutions to problems or algorithm improvements are proposed, especially for satellite measurements. Accordingly, re-processing of the record should be an integral part of the process of creating a climate data record. WOAP-1 Reprocessing: assess variables for need and readiness, and commitments. Include in GEOSS. 5 Principles for Re-Processing Climate Data Records For climate, the value of an observational record increases with time, provided that the record is continuous and homogeneous. As datasets are used, characteristics of the data and problems are exposed, and often solutions to problems or algorithm improvements are proposed, especially for satellite measurements. Accordingly, re-processing of the record should be an integral part of the process of creating a climate data record. Slide 5 World Climate Research Programme 5 Principles for Re-Processing Climate Data Records 1.Re-processing of climate data records should be motivated by a scientific goal, a specific use of the data that requires a demonstrated improvement over the currently available version or becomes possible because of improvements that can be achieved by re-processing. 2. Before re-processing commences, problems in the data record should have been identified and investigated to determine the causes of the problems and fixes or improvements should have been developed. 3. Before a data record is re-processed, the whole chain of processing from instrument calibration through retrieval to sampling should be reviewed and improvements sought. Principles for Re-Processing Climate Data Records 1.Re-processing of climate data records should be motivated by a scientific goal, a specific use of the data that requires a demonstrated improvement over the currently available version or becomes possible because of improvements that can be achieved by re-processing. 2. Before re-processing commences, problems in the data record should have been identified and investigated to determine the causes of the problems and fixes or improvements should have been developed. 3. Before a data record is re-processed, the whole chain of processing from instrument calibration through retrieval to sampling should be reviewed and improvements sought. Slide 6 World Climate Research Programme 6 Principles for Re-Processing Climate Data Records 4. The Climate Data Record Meta-data should be updated to include newly discovered aspects and characteristics of the record resulting from preparatory investigations (or any other new results) or during the re-processing and to facilitate the next re-processing. 5. An overall goal of Climate Data Record re-processing should be to increase the physical consistency among the available data products describing climate variations, as well as the continuity over time; hence, any re-processing project should also consider joint requirements with other Climate Data Records that may require coordinated re- processing of them as well. Principles for Re-Processing Climate Data Records 4. The Climate Data Record Meta-data should be updated to include newly discovered aspects and characteristics of the record resulting from preparatory investigations (or any other new results) or during the re-processing and to facilitate the next re-processing. 5. An overall goal of Climate Data Record re-processing should be to increase the physical consistency among the available data products describing climate variations, as well as the continuity over time; hence, any re-processing project should also consider joint requirements with other Climate Data Records that may require coordinated re- processing of them as well. Slide 7 Parameter Clouds Water Vapor TOA Radiation Precipitation SRF Radiation Atmospheric Circulation Evaporation 1979198519901995200020052010 TIME Available Global GEWEX+ Datasets Pentad Daily 3 6 hrs 50 km 250 km 100 km 50 km 100 km WCRP/GCOS WOAP workshop: ESRIN, Frascati 18-20 April 2011 Evaluation of satellite climate datasets identification of best practices in evaluating and inter- comparing global climate datasets, especially where there is more than one data set for a given parameter (e.g., surface temperature, sea ice concentrations, etc.). Slide 8 8 Large disparities among different analyses Daily SST (1 Jan 2007) Reynolds and Chelton 2010 JC Sea Level OHC Palmer et al 2010 OceanObs09 Slide 9 Total sea ice area, 2007 and 2008 2007 2008 NASA Team NASA Team 2 SSM/I Bootstrap AMSR Bootstrap ASI Cal/Val (York) Bristol Norsex Avg. of 8 algorithms & 1 st. dev. range No single algorithm clearly superior The largest factor for ice concentration/extent consistency is intercalibration of the products through transitions through different generations of satellite-borne sensors. Slide 10 High Cloud Amount (July) absolute values depend on instrument sensitivity & method, but distributions similar CALIPSO AIRS-LMD ISCCP PATMOS-x MODIS-ST MODIS-CE (%) CALIPSO CALIPSO ( > 0.1) AIRS_LMD ISCCP TOVS Path-B HCA (%) Slide 11 Trends in LH Flux? Slide 12 12 Reanalysis 1.Reanalysis is an essential part of climate services, especially in monitoring, attribution and prediction 2.Major problems remain from the changing observing system 3.There is not a problem with lack of reanalyses, but: 1.lack of an end to end program with adequate vetting and evaluation of products (and the funding for that), and 2.Reanalysis is all done in a research domain and not sustained, so that key personnel can be lost. 3.Lack of adequate vetting and diagnosis Slide 13 13 ReanalysisHoriz.ResDatesVintageStatus NCEP/NCAR R1T621948-present1995ongoing NCEP-DOE R2T621979-present2001ongoing CFSR (NCEP)T3821979-present2009thru 2009, ongoing C20r (NOAA)T621875-20082009Complete, in progress ERA-40T1591957-20022004done ERA-InterimT2551989-present2009ongoing JRA-25T1061979-present2006ongoing JRA-55T3191958-20122009underway MERRA (NASA)0.5 1979-present2009thru 2010, ongoing Current atmospheric reanalyses, with the horizontal resolution (latitude; T159 is equivalent to about 0.8 ), the starting and ending dates, the approximate vintage of the model and analysis system, and current status. Atmospheric Reanalyses Slide 14 Nov NOAA-18 EOS Aqua Oct F08 F15 SSM/I JulDec F10 Nov Dec F11 Dec F13 May F14 May Dec Aug AprJul AprJun Jul GOES-08 GOES-10 GOES-12 TIROS-N DecFeb JulAprOctNov NOAA-6 FebSep NOAA-7 MayJunJul Oct NOAA-8 JanNov NOAA-9 NOAA-10 DecSep NovJanSep NOAA-11 JunSep NOAA-12 Jan NOAA-14 Sep NOAA-15 Nov NOAA-16 Jul NOAA-17 Dec TOVS ATOVS EOS Aqua GOES Sounders 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 00 01 02 03 04 05 06 07 08 Satellite Data Streams assimilated Slide 15 The Changing Observing System 1973 77K Obs every 6hrs 1979 325K Obs every 6hrs 1987 550K Obs every 6hrs 2006 4.2M Obs every 6hrs 1973 77k/6h 1987550k 1979324k 20064,220k Slide 16 NWP Forecast skill scores continue to improve Extratropical NH and SH forecasts: 12 month means plotted at last month. Updated from Simmons and Hollingsworth 2002 SH skill became comparable to NH after about 2002! Reanalysis Slide 17 Global mean precipitation Slide 18 18 Slide 19 19 Slide 20 World Climate Research Programme 20 Future needs: Observations and Analysis Observations: in situ and from space (that satisfy the climate observing principles); A performance tracking system; Climate Data Records (CDRs) The ingest, archival, stewardship of data, data management; Access to data Data (re)processing and analysis The analysis and reanalysis of the observations and derivation of products, Data assimilation and model initialization Observations: in situ and from space (that satisfy the climate observing principles); A performance tracking system; Climate Data Records (CDRs) The ingest, archival, stewardship of data, data management; Access to data Data (re)processing and analysis The analysis and reanalysis of the observations and derivation of products, Data assimilation and model initialization Slide 21 Future needs: Models Data assimilation and model initialization Better, more complete models Assessment of what has happened and why (attribution) including likely impacts on human and eco-systems; Prediction of near-term climate change over several decades: ensembles Statistical models: applications Downscaling, regional information Responsiveness to decision ma

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