Evolution of the Observing System for Seasonal-to-Interannual Climate Prediction M. J. McPhaden, NOAA/PMEL A. Hollingsworth, ECMWF B. P. Kirtman, COLA R. W. Reynolds, NOAA/NCDC F. C. Vossepoel, IMAU/SRON S. E. Wijffels, CSIRO International CLIVAR Conference Baltimore, MD 21 June 2004

Need for a Climate Observing System  To describe and detect variability and change in the climate system (ocean, atmosphere, land, cryosphere components).  To improve our understanding of processes that control climate.  To develop models for climate forecasting.  To initialize and validate climate forecasts. International CLIVAR Conference Baltimore, MD 21 June 2004

Derives from memory contained in the bottom boundary conditions of the atmosphere Predictability on Seasonal-to- Interannual Time Scales  Ocean-atmosphere interactions (SST)  Land-atmosphere interactions (soil moisture, vegetation, etc.)  Cryosphere-atmosphere interactions (sea ice cover, permafrost, snow cover, etc.)

SST and Rainfall Anomalies DJF (El Niño) SST Rainfall Atmospheric Teleconnections

SST Data and Analysis December 1997 (El Niño) oCoC

ENSO Observing System  Developed during TOGA ( )  Complementary in situ & satellite observations  Measures key variables Sea surface temperature Surface winds Upper ocean heat content Sea level Ocean currents Other (salinity, heat fluxes fresh water fluxes) Real-Time Data Telemetry

ENSO Prediction  Models show skill out to 12 months lead time  Forecast skill based on slow evolution of upper ocean thermal structure  Forecast skill limited by weather noise, model biases & errors in initial conditions. ENSO is the most predictable year-to-year climate variation on the planet Nino-3.4 Source: NCEP

Niño 3.4 Sea Surface Temperature Forecasts from June 2002 Warm Cold Adapted from IRI, 2002 Observations

Extending and Improving ENSO Prediction: The Role of Salinity  Formation of salt stratified “barrier layers” that trap heat near the surface  Consistent analysis of ocean temperature and sea level variations in assimilation systems  Improved ocean analyses of velocity field and its effects on SST  Better ocean initial conditions for coupled dynamical model forecasts With T/S assimilation With T, no S assimilation Difference Equatorial Pacific Zonal Velocity

Convective flare-ups occur every days over the Indian Ocean. These flare- ups are characterized by towering cumulus clouds, rainfall, and westerly surface winds that propagate into the Pacific sector. MJO Convection Indian | Pacific | Atlantic Stochastic Forcing & El Niño The Madden-Julian Oscillation (MJO) June 2001 Aug 2003 cloudy/wet clear/dry Cloudiness & Rainfall (OLR, 5°N-5°S)

Climate Variability and Change ENSO, MJO, Monsoons, IOD, PDO, TAV, NAO/AO, MOC, Global Warming…

global coverage  GCOS Second Adequacy Report: “The ocean networks lack global coverage…without urgent action to address these findings, the Parties will lack the information necessary to effectively plan for and manage their response to climate change.” global coverage  U.S. Climate Change Science Program Strategic Plan: “Complete global coverage of the oceans with moored, drifting, and ship-based networks.” global coverage  OCEAN.US Implementation of the Initial U.S. IOOS: “The highest priority for the global component of the IOOS is sustained, global coverage.” A Fundamental Requirement

Tide Gauge Network45 % complete Tide Gauge Network45 % complete 3˚x3˚ Argo Profiling Float Array25% complete 3˚x3˚ Argo Profiling Float Array25% complete 5˚x5˚ Surface Drifting Buoy Array35 % complete 5˚x5˚ Surface Drifting Buoy Array35 % complete Moored BuoyExistingPlanned Moored BuoyExistingPlanned Ocean Reference StationExistingPlanned Ocean Reference StationExistingPlanned High Resolution XBT and Flux LineExistingPlanned High Resolution XBT and Flux LineExistingPlanned Frequently Repeated XBT LineExistingPlanned Frequently Repeated XBT LineExistingPlanned Carbon Inventory & Deep Ocean Line Global 10 years Carbon Inventory & Deep Ocean Line Global 10 years Sea Surface Temperature, Sea Surface Height, Surface Vector Wind, and Ocean Color from Space Source: NOAA/OGP Towards a Sustained Global Ocean Observing System

Source: JPL Towards a Sustained Global Ocean Observing System: Continuity of Satellite Missions

Global Ocean Data Assimilation System (GODAS) Coupled Ocean Atmosphere Forecast System (CFS03) SSTXBTTAO AltimeterArgo Scatterometer Stress E-P Heat Fluxes SST AnomalySurface Temperature & Rainfall Anomalies Official SST Forecast Official Probabilistic Surface Temperature & Rainfall Forecasts Seasonal Forecasts for North America with Climate Atmosphere GCM CCA, CA Markov CCA, OCN MR, ENSO Forecasters Ocean Initial Conditions IRI Source: NCEP Towards a Sustained Global Ocean Observing System: Linking to Data Assimilation and Forecast Systems

 Identify new phenomena  Develop understanding of processes  Determine predictability  Design appropriate arrays  Develop new technologies  Guide implementation Basic Applied Towards a Sustained Global Ocean Observing System: The Role of Research

 Identification of new phenomena establishes new measurement priorities and design criteria Examples in the past 10 years: Examples in the past 10 years: - Decadal Modulation of ENSO - Pacific Decadal Oscillation - Indian Ocean Dipole (aka Zonal Mode) Towards a Sustained Global Ocean Observing System: The Role of Research

 Develop new technologies New technologies introduced by research community for ocean observing system: - Low cost drifter - Low cost drifter - ATLAS mooring - ATLAS mooring - Argo floats - Argo floats - Gliders - Gliders Towards a Sustained Global Ocean Observing System: The Role of Research

 Array design & implementation Multi-year, multi-national efforts guided by process field studies, observing system simulations experiments (OSSEs) & expert scientific judgment. Towards a Sustained Global Ocean Observing System: The Role of Research

 Array design & implementation Multi-year, multi-national efforts guided by process field studies, observing system simulations experiments (OSSEs) & expert scientific judgment.  3000 floats on 3° x 3° grid.  T/S profiles to m every 10 days.  42% complete in June Towards a Sustained Global Ocean Observing System: The Role of Research

 Must be systematically planned - New managers must be technically capable - New home institution must have appropriate mandate - Systems must be considered, not piecemeal components  Must be adequately funded - New resources needed to support one-time costs of transfer - Operating costs should not be taken from research budgets  Must be transparent to users (no degradation in data quality, continuity, or access)  Must involve ongoing partnership with the research community - Scientific oversight - Data analysis and product generation - System upgrades Transition from Climate Research to Operations

“End-to-end involvement of research scientists…is the best guarantee for overall data integrity and usefulness for the long term.” --National Research Council, 1994 Transition from Climate Research to Operations

International Coordination and Implementation

1)There has been significant progress in the development of observing systems to support seasonal-to- interannual climate prediction during CLIVAR. Conclusions 2) Development of a global, sustained, integrated climate observing system is of the highest priority for the future. 4) Transition from research to operations will require ongoing involvement of the research community for scientific oversight, quality assurance, and system upgrades. 3) Research benefits from, and fundamentally contributes to, the development of climate observing systems.

Argo BuoysSOOP Tide Gauges Time Series Repeat Hyrdo Towards a Sustained Global Ocean Observing System: WOCE/TOGA/CLIVAR in situ contributions

Selected Analysis Products from the ENSO Observing System  Satellite & in situ SST analyses  Satellite scatterometer winds & altimeter sea level  Drifting buoy & altimetry-based velocity analyses  Moored buoy high resolution time series  Moored buoy, XBT, Argo heat content analyses  NCEP operational ocean model analyses