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

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

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

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.

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.

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.

Parameter Clouds Water Vapor TOA Radiation Precipitation SRF Radiation Atmospheric Circulation Evaporation 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 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.).

8 Large disparities among different analyses Daily SST (1 Jan 2007) Reynolds and Chelton 2010 JC Sea Level OHC Palmer et al 2010 OceanObs09

Total sea ice area, 2007 and 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.

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 (%)

Trends in LH Flux?

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

13 ReanalysisHoriz.ResDatesVintageStatus NCEP/NCAR R1T present1995ongoing NCEP-DOE R2T present2001ongoing CFSR (NCEP)T present2009thru 2009, ongoing C20r (NOAA)T Complete, in progress ERA-40T done ERA-InterimT present2009ongoing JRA-25T present2006ongoing JRA-55T underway MERRA (NASA) 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

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 Satellite Data Streams assimilated

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 k/6h k k 20064,220k

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

Global mean precipitation

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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

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 makers and users. 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 makers and users.

The coordinated collection, analysis and reanalysis of climate observations is required to describe the structure and variability of the climate system. Observations give the basis for evaluating and improving models, and models providing the framework and impetus for deciding what observations to take. Special efforts required to obtain, analyse and assimilate data from the new generation of environmental satellites. Enables the generation of descriptions of states of the coupled climate system consistent with all variables and the physical framework provided by models, both for prediction and for documenting the climate record. Role of WCRP

Advocate improved observations and analysis suitable for climate (satisfying the GCOS Climate Monitoring Principles to ensure continuity of record). This especially includes those from space. Data set development: evaluating observations and promoting global reprocessing and reanalysis. Develop new products and datasets, analytical and diagnostic techniques, high level derived products: for use in understanding and analyzing climate variability and change, and for evaluating models. Mechanisms and modes of variability in climate anomalies; operational attribution, numerical experimentation in near real time to allow reliable statements to be made not only about what the state of the climate is, but also why it is the way it is and the mechanisms involved.

Role of WCRP Data assimilation and analysis: initializing of coupled models for prediction. Provide advice on best datasets for various purposes (climatologies and time series) and their merits and limitations. (Error bars are greatly needed.) High priority needs are to have assessments of datasets for use in evaluating climate models, and specifically those used in the AR5 IPCC report that will participate in the CMIP5 activity

Role of WCRP Help improve and promote sound data stewardship, including data archiving, management, and access. This includes making sure that climate-related data variables are reaching data archives, and that standards are set for archiving new types of data. Help make data accessible and available e.g., through the internet. Promote shared efforts for data quality control.

26 Climate Information System Trenberth, 2008 WMO Bull WCRP

Imperative: A climate information system Observations: forcings, atmosphere, ocean, land Analysis: comprehensive, integrated, products Assimilation: model based, initialization Attribution: understanding, causes Assessment: global, regions, impacts, planning Predictions: multiple time scales Decision Making : impacts, adaptation Observations: forcings, atmosphere, ocean, land Analysis: comprehensive, integrated, products Assimilation: model based, initialization Attribution: understanding, causes Assessment: global, regions, impacts, planning Predictions: multiple time scales Decision Making : impacts, adaptation An Integrated Earth System Information System