Showing papers by "Michele M. Rienecker published in 2010"

Ocean information provided through ensemble ocean syntheses

Abstract: Analyzing ocean variability, understanding its importance for the climate system, and quantifying its socio-economic impacts are among the primarymotivations for obtaining ongoing global ocean observations. There are several possible approaches to address these tasks. One with much potential for future ocean information services and for climate predictionsis called ocean synthesis, and is concerned with merging all available ocean observations with the dynamics embedded in an ocean circulation model to obtain estimates of the changing ocean that are more accurate than either system alone can provide. The field of ocean synthesis has matured over the last decade. Several global ocean syntheses exist today and can be used toinvestigate key scientific questions, such as changes in sea level, heat content, or transports. This CWP summarizes climate variability as seen by several ocean syntheses, describes similarities and differences in these solutions and uses results to highlight developments necessary over the next decade to improve ocean products and services. It appears that multi-model ensemble approaches can be useful to obtain better estimates of the ocean. To make full use of such a system, though, one needs detailed errorinformation not only about data and models, but also about the estimated states. Results show that estimates tend to cluster around methodologies and therefore are not necessarily independent from each other. Results also reveal the impact of a historically under-sampled ocean on estimates of inter-decadal variability in the ocean. To improve future estimates, we need not only to sustain the existing observing system but to extend it to include full-depth ARGO-type measurements, enhanced information about boundary currents and transports through key regions, and to keep all important satellitesensors flying indefinitely, including altimetry, gravimetry and ice thickness, microwave SST observations, wind stress measurements and oceancolor. We also need to maintain ocean state estimation as an integral part of the ocean observing and information system.

Role of the ocean observing system in an end-to-end seasonal forecasting system

Abstract: There is clear demand for reliable forecasts of climate at seasonal time scales for a variety of societal applications. This paper discusses the role of ocean observations in the different components of a seasonal forecasting system, namely the initialization of the ocean, coupled model development and calibration of model output, concluding that the maintenance and enhancement of the current observing system is of paramount importance for further progress in seasonal forecasting. It is shown that the assimilation of ocean observations improves the skill of seasonal forecasts. Results indicate that no observing system is redundant. Independent observations, not directly assimilated, are necessary for the improvement of assimilation methods and numerical models, thus increasing the information content of the observations. Forecast calibration requires long observational records to produce historical ocean initial conditions. These are equivalent to ocean re-analyses, which, continuously brought up to real-time, allow the monitoring of relevant climate variables. The current forecasting systems are not making optimal use of the existing observations, in particular in regions where model error is large and/or where the initialization is inadequate. This is particularly noticeable in the equatorial Atlantic. Improvements in numerical models and initialization strategies are needed to exploit the full potential of current and future observing systems.

The Impact of Ocean Data Assimilation on Seasonal-to-Interannual Forecasts: A Case Study of the 2006 El Nino Event

Abstract: This study investigates the impact of four different ocean analyses on coupled forecasts of the 2006 El Nino event. Forecasts initialized in June 2006 using ocean analyses from an assimilation that uses flow-dependent background error covariances are compared with those using static error covariances that are not flow dependent. The flow-dependent error covariances reflect the error structures related to the background ENSO instability and are generated by the coupled breeding method. The ocean analyses used in this study result from the assimilation of temperature and salinity, with the salinity data available from Argo floats. Of the analyses, the one using information from the coupled bred vectors (BV) replicates the observed equatorial long wave propagation best and exhibits more warming features leading to the 2006 El Nino event. The forecasts initialized from the BV-based analysis agree best with the observations in terms of the growth of the warm anomaly through two warming phases. This better performance is related to the impact of the salinity analysis on the state evolution in the equatorial thermocline. The early warming is traced back to salinity differences in the upper ocean of the equatorial central Pacific, while the second warming, corresponding to the mature phase, is associated with the effect of the salinity assimilation on the depth of the thermocline in the western equatorial Pacific. The series of forecast experiments conducted here show that the structure of the salinity in the initial conditions is important to the forecasts of the extension of the warm pool and the evolution of the 2006 El Ni o event.

Synthesis and assimilation systems: essential adjuncts to the Global Ocean Observing System

Abstract: Ocean assimilation systems synthesize diverse in situ and satellite data streams into four-dimensional state estimates by combining the various observations with the model. Assimilation is particularly important for the ocean where subsurface observations, even today, are sparse and intermittent compared with the scales needed to represent ocean variability and where satellites only sense the surface. Developments in assimilation and in the observing system have advanced our understanding and prediction of ocean variations at mesoscale and climate scales. Use of these systems for assessing the observing system helps identify the strengths of each observation type. Results indicate that the ocean remains under-sampled and that further improvements in the observing system are needed. Prospects for future advances lie in improved models and better estimates of error statistics for both models and observations. Future developments will be increasingly towards consistent analyses across components of the Earth system. However, even today ocean synthesis and assimilation systems are providing products that are useful for many applications and should be considered an integral part of the global ocean observing and information system.

Decadal Prediction Efforts in GMAO (Global Modeling and Assimilation Office)

Abstract: The Global Modeling and Assimilation Office (GMAO) plans to use our GEOS-5 atmosphere-ocean general circulation model (AOGCM) to explore issues associated with predictability on decadal time scales and to contribute to the decadal prediction project that is part ofCMIP5. The GEOS-5 AOGCM is comprised of the GEOS-5 AGCM with the Catchment Land Surface Model, coupled to GFDL's MOM, version 4. We have assimilation systems for both the atmosphere and ocean. For our climate prediction efforts, the atmosphere will be initialized from the GEOS-5 Modem Era Retrospective-analysis for Research and Applications (MERRA), available from 1979 to present at 112 resolution, and from 1948 to present at 2 resolution. The ocean assimilation is conducted within the coupled model framework, using the MERRA as a constraint for both the atmosphere and the ocean. The decadal prediction experiments will be conducted with a 1 atmosphere and a 112 ocean. Some initial results will be presented, focusing on initialization aspects of the GEOS-5 system.