1 David M. Legler U.S. CLIVAR Office usclivar.org CLIVAR A presentation for the NVODS Workshop September 11, 2003 and member of US-DMAC committee as well as former chair of the WOCE Data Products Committee…

2 What is CLIVAR? (hint: it’s involves more than the ocean!) Scope of activities CLIVAR needs/requirements CLIVAR and data management

3 CLIVAR Climate Variability and Predictability What causes the variability of the earth's climate on time scales from seasons to centuries and can we predict it? Can we distinguish natural from anthropogenic induced variability? Science Plan U.S. CLIVAR SSC formed - Summer 1998 International CLIVAR Conference - December 1998 CLIVAR will extend for at least another 10 years

4 Illustrative questions for CLIVAR How can we better predict El Niño and its impact on climate? What are its links to higher frequency (e.g., MJO) and to decadal variability? Decadal variability has been shown to impact climate in many regions…can we ever predict this variability? What are the some of the mechanisms than can lead to abrupt climate change? How does El Niño change under a changing climate?

5 U.S. CLIVAR Objectives Identify and understand the major patterns of climate variability on seasonal and longer time scales and evaluate their predictability; Expand our capacity to predict short-term (seasonal to interannual) climate variability and search for ways to predict decadal variability; Better document the record of rapid climate changes in the past,as well as the mechanisms for these events, and evaluate the potential for abrupt climate changes in the future; Evaluate and enhance the reliability of models used to project climate change resulting from human activity, including anthropogenic changes in atmospheric composition; and Detect and describe any global climate changes that may occur.

6 The CLIVAR Vision... An important legacy of CLIVAR will be an improved climate observing system,as well as a more comprehensive and useful climate record CLIVAR will contribute the fundamental underpinnings of critical physical processes that lead to reducing uncertainties in coupled climate models used for prediction CLIVAR will help contribute to the development of robust dynamical frameworks for understanding climate changes

7 Approach Improvements in the instrumental record and observing system –document past, ongoing, and future climate fluctuations –better elucidate their structures and mechanisms –provide initial conditions for model data assimilation and forecasting Model application, experimentation, and improvement –develop long-term model data sets (e.g. retrospective analyses) to study climate variability –assess inadequacies and improve the capabilities of models to simulate and predict climate variability –explore mechanisms of climate variability –develop dynamical hypotheses to help focus observational requirements

8 Approach Empirical studies of the climate record from instruments, satellites and proxy records, and climate model simulations –define patterns of climate variability –develop and test hypotheses Regional and process field studies –quantify specific processes that must be included in successful climate models –Identify processes for which present treatment is inadequate.

9 CLIVAR Regional Implementation Working groups address global synthesis, modeling, and prediction

10 Atlantic Basin Issues NAO/AO/AM –Mechanisms that govern its variability? –Low-frequency trends? –Ocean, land, sea- ice feedbacks? –Numerous applications TAV –Influence of ENSO, NAO? –Role of coupling in TNA? Of subtropical cells? –Extent of land influences? –Climate predictability beyond tropics? MOC –Variability of ocean heat transport? –Sensitivity to sfc forcing? –Role of thermohaline circulation in abrupt climate change?

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12 East Pacific Investigation of Climate Processes in the Coupled Ocean-Atmosphere System (EPIC) IOP: Sep/Oct ships, 2 aircraft Enhanced Monitoring Enhancements to the TAO array IMET mooring at 20S Radionsonde, flux msmts, etc. from twice-yearly TAO tender cruises 95W, 110W Enhanced Regional Obs Terrestrial and lower-atm obs

13 Other Observations & Products of Interest

14 Modeling Activities Some Objectives: Improve predictions on seasonal-to-interannual time scales Assess predictability of decadal variability Evaluate and enhance the reliability of models used to project climate change U.S. teams of modelers, observationalists, and diagnosticians will address two major areas of uncertainties in climate change models – Ocean mixing and low-latitude cloud feedbacks Development of robust dynamical synthesis frameworks (e.g. data assimilation) for understanding climate variability and predictability and to guide observation system design Recent workshops on – Ocean data assimilation – Atmospheric data assimilation/reanalyses – Coupled data assimilation CLIVAR will generate and utilize many TB of model data/products…data management challenge

15 CLIVAR Needs… The requirements for developing climate data are stringent as the signals we are trying to detect are often very small CLIVAR needs access to a variety of obs, models, analyses, paleo-proxy data, archives, etc from multiple disciplines (e.g. ocean, atm, land) to address the coupled climate system Access to browse products Time-critical data/products are needed for climate forecasting (e.g. ENSO predictions) Data/products of a known quality –Attributes that describe errors, uncertainties, and data quality must be an integral part of the data system –Versioning/tracking/tagging is critical (experiments must be repeatable)…observational data can be corrected many times.

16 CLIVAR and Data Management WOCE heritage: CLIVAR has picked up some parts of the WOCE (ocean) data system…BUT CLIVAR is more than the oceans! CLIVAR is the home for –Some observation system elements and their data systems –Field experiment observation data (UCAR-JOSS) –Numerous model and value-added products –Various regional/system-wide data/product activities Many (not all) of these consider data management All of them need to be fully entrained in the development of a comprehensive climate data/product/info management system

17 Legacy of WOCE WOCE V3 DVD’s 2 DVDs, 12GB data 10+ yrs of in-situ & satellite ocean data and products netCDF-COARDS compliant files Consistent and documented QC Common metadata stds, conventions, etc. Search tool/file pointers

18 WOCE Data System CLIVAR Data Assembly Data Centers (DACs) play a central role in assembling, QC’ing, and distributing ocean data All DACs have OpenDAP servers, some with LAS, etc Knowledgeable and cooperative team

19 CLIVAR’s Role in Data Management Helps to develop and assess requirements of the systems that will deliver climate data, products, and information; Implements some (e.g. ocean) elements of the observing system and their respective data management systems, the frontline for new obs technology and data systems Develops synthesis frameworks (e.g. data assimilation/reanalyses) that utilize (and assess) the climate observations, products, and information; Contributes assembled data, products and their attributes; Cooperates with other activities (DMAC, OTI, OOPC, etc) leading data system development; Provides feedback on acceptable metadata and data “models”; Help sustain current Data Assembly Centers (DACs), regional, and specialized data centers CLIVAR Global Synthesis and Observations Panel (GSOP) is the CLIVAR group charged with addressing data management issues. First meeting is being planned (early 2004)

20 For Consideration –CLIVAR is an important customer/user of NVODS –CLIVAR can contribute data, metadata to global component of IOOS …help develop IOOS data system –CLIVAR can help extend NVODS technology to other disciplines –Importance of products (very different from observations) Model/value-added products Browse products What metadata should be included? –Importance of a data/metadata model and standards encourage contributions of a more comprehensive set of data/metadata Sufficiently extensible to address stringent needs of climate

21 Further Information:

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23 NVODS Activities…CLIVAR Input 1.Develop a Comprehensive IOOS Data Model 2.Deliver time-critical (real-time) data to data assembly and operational modeling sites Characterize the need for real-time data. 3.Develop DMAC Middleware Determine the breadth of data management solutions in use by IOOS data suppliers, which must be supported by IOOS middleware. Determine the breadth of legacy and new client applications that should be supported. Similarly survey and prioritize requirements for delivery of formatted subsets to users. 4.Make data available using IOOS middleware solution Work with suppliers of data to make data available through the DMAC middleware solution. 5.Data Manipulation Services Prioritize Data Manipulation Services, including aggregation, re-gridding, and simple transforms such as averages and extrema. 6.Develop Metrics and Implement Performance Monitoring Determine specifications for Metrics and Performance Monitoring. 7.Implement Middleware Security (Cross-discipline effort with all DMAC) 8.Provide guaranteed geo-temporal-referenced browse for all IOOS data