Mike McPhaden NOAA/PMEL Seattle, Washington ENSO Observations Mike McPhaden NOAA/PMEL Seattle, Washington CLIVAR ENSO Workshop Paris, France 17-19 November 2010

Required for Description, Understanding and Prediction Observations Required for Description, Understanding and Prediction 2

Initial Global Ocean Observing System for Climate Status against the GCOS Implementation Plan and JCOMM targets Total in situ networks 60% May 2008 87% 100% 62% 81% 100% 79% 43% 24% 48% GOOS

A Short History of ENSO Observations Paleo Proxies Instrumental 1850s Matthew Fontaine Maury 1950s IGY & Bjerknes 1960s Satellite era for weather 1980s AVHRR, Geosat altimetry 1985-94 TOGA 1990s High precision altimetry, scatterometry The climate data record in the Pacific for detailed ENSO studies begins around 1980. Only since then has there been sufficient data from below the surface and from space data to describe and diagnose observed variations.  30 years of systematic subsurface ocean and satellite observations for describing, analyzing and developing forecasting capabilities for ENSO 4

Current Conditions http://www.pmel.noaa.gov/tao/ Global Tropical Array

Current Conditions http://www.pmel.noaa.gov/tao/ Global Tropical Array

El Niño vs La Niña http://www.pmel.noaa.gov/tao/ Global Tropical Array

Recharge Oscillator Theory (Wyrtki, 1985; Cane et al, 1986; Jin, 1997) Meinen & McPhaden, 2000

Upper Ocean Heat Content and ENSO Build up of excess heat content along equator is a necessary precondition for El Niño to occur. El Niño purges excess heat to higher latitudes, which terminates the event. The time between El Niños is determined by the time to recharge. Note that heat content builds up prior to all El Ninos of the past 25 years. The strongest El Nino in 97-98 also had that largest prior build up. During each El Nino heat content dropped often to large negative values. Next El Nino did not occur until heat content anomaly was again in positive territory. After Meinen & McPhaden, 2000 Heat content based on TAO/TRITON, XBT and Argo data

Global Tropical Array Upper Ocean Heat Content and ENSO After Meinen & McPhaden, 2000 Heat content based TAO/TRITON, XBT and Argo data Upper ocean heat content variations are the source of predictability for the ENSO cycle Global Tropical Array

Lead Time Changes Switch to WWV for exact comparison with MM; they used WWV. T300 and WWV are almost identical.

Seasonality of Lead Time Changes McPhaden,, 2003: “Tropical Pacific Ocean heat content variations and ENSO persistence barriers.” GRL

Trends in Central Pacific El Niño SSTs SST anomaly Dec 2009 Lee & McPhaden, Geophys. Res. Lett., 2010 Niño-4 SST Central Pacific El Niños are increasing in frequency and amplitude

EP vs CP El Niños 3/5 EP 3/4 CP

Ratio of CP/EP El Niños Increases Under Global Warming 20th century simulations 21st century A1B scenario TAO/TRITON: a partnership between NOAA/PMEL and the Japan Marine Earth Science and Technology Agency. ATLAS moorings are the workhorse. These moorings were developed at PMEL. Mean Thermocline Depth Yeh et al, Nature, 2009

Changes in Background Conditions

Differences in El Niño Composites EP CP CP-EP

Mean State  El Niño Statistics? ENSO ?

Summary 30 years of systematic subsurface ocean and satellite observations available for detailed studies of ENSO and its decadal modulation Lead time of ocean heat content (WWV) a predictor of ENSO SST has decreased from 2-3 seasons to ~1 season in the first decade of the 21st century Loss of predictability concentrated early in the calendar year Changes correspond to increasing incidence of CP El Niños Corresponds to decadal changes in background conditions (winds, thermocline depth, SST) Natural variability? Influence of global warming? CLIVAR ENSO Workshop Paris, France 17-19 November 2010

The rationale for developing a forecasting capability is that skillful ENSO forecasts offer advance warning for protecting against, or taking advantage of, ENSO related changes in environmental conditions that affect life, property, and economic vitality. ENSO is the most predictable year-to-year fluctuation of the climate system because of the way slow changes in ocean heat content precondition the system for warm and cold events to occur. To make forecasts, one need models and real-time data to initialize them. The first El Nino to be successfully predicted was the 1986-87 El Nino. Since then, considerable effort has been put into developing and improving ENSO forecast models. There are now about 20 groups world wide making routine forecasts And in the future?

Global Tropical Array Global Tropical Moored Buoy Array: TRITON Global Tropical Moored Buoy Array: A coordinated, sustained, multi-national effort to develop and implement moored buoy observing systems for climate research and forecasting throughout the global tropics ATLAS Key attributes: Real-time Ocean-atmosphere High temporal resolution Basin scale A contribution to GOOS, GCOS, and GEOSS Global Tropical Array

Eastern vs Central Pacific (“Modoki”) El Niños Ashok, 2009 Eastern Pacific Niño-3.4 Central Pacific(Modoki) Niño-4

A Short History of ENSO Observations Paleo proxy Instrumental 1850s Matthew Fontaine Maury 1950s IGY & Bjerknes 1960s Satellite era for weather satellites 1980s AVHRR, Geosat altimetry 1985-94 TOGA 1990s High precision altimetry, scatterometry 23