Applied Research Centers (ARCs)

The mission of the Climate Dynamics and Experimental Prediction (CDEP) program element is to advance climate services for NOAA by contributing to the development and implementation of coupled ocean-land-atmosphere forecast systems based on dynamical models and by fostering the development of new prediction and application techniques. CDEP sponsors a critical mass of focused research and development at the NOAA Applied Research Centers (ARCs), and aims to benefit climate forecasters at the Climate Prediction Center (CPC) and the International Research Institute for Climate Prediction (IRI) and users of such forecasts. Please see the ARCs Presentation (PDF file).

The Applied Research Centers:

Climate Diagnostics Applied Research Center (CDARC)

CDARC proactively delivers research products and experimental services that provide explanations of current and evolving climate and predictions of future climate and extreme events with drought-related research and applications in support of NIDIS as the near-term priority.

Research is coordinated around five foci that contribute to CDEP objectives:

• Reforecasts and Weather-Climate: develop reliable and improve probabilistic short term climate forecast products
• Historical Reanalysis: produce a 100-year global climate reanalysis based on surface pressure data using ensemble data assimilation techniques
• Climate Attribution: improve climate attribution capabilities to meet policy and decision maker needs for explanations of the climate system.
• Climate System Diagnosis: improve understanding of dynamical processes and predictability of the the climate system
• Regional Applications and Services: improve delivery of regional climate products and services needed to manage climate-related risks.

Center for Ocean-Land-Atmosphere Studies (COLA)

COLA was established to improve understanding and prediction of the Earth's climate variations and to share both the fruits of this research and the tools necessary to carry out this research with society as a whole. Scientists at COLA are dedicated to understanding climate fluctuations on seasonal, interannual, and decadal scales, with special emphasis on the interactions between Earth's atmosphere, oceans, and land surfaces. The primary goal of COLA is to explore, establish and quantify the variability and predictability of climate through the use of state-of-the-art dynamical coupled ocean, land, atmosphere models, and to harvest this predictability for societally beneficial predictions. The scientific premise for research at COLA is that there is a predictable element of the Earth's current climate that makes it possible to accurately forecast climate variations. While the chaotic nature of the global atmosphere is known to impose a limit on the predictability of the state of the climate at a given instant, the hypothesis behind COLA's research suggests that there is predictability in the midst of chaos, and that accurate climate forecasts with lead times longer than the inherent limit of deterministic predictability are possible. http://grads.iges.org/cola.html.

Experimental Climate Prediction Center (ECPC)

The Scripps ECPC is developing an integrated regional climate prediction capability by undertaking basic research to identify coupled land-atmosphere-ocean linkages on seasonal to interannual time scales and then developing appropriate climate prediction methodologies focused on coupled numerical global and regional atmospheric models, single column models, ocean models, hydrologic, water-resource models, and fire danger models. ECPC models are being used to make routine experimental forecasts, which are continually evaluated in order to demonstrate their utility to various sectors on temporal scales ranging from seasonal to interannual but also touching upon daily and decadal to centennial time scales. Once we have demonstrated the usefulness of various forecast tools and methodologies, our goal is to transfer these experimental methodologies to NCEP, IRI and various regional application centers. http://ecpc.ucsd.edu/.

Center for Ocean-Atmospheric Prediction Studies (Florida State Univ.)

COAPS performs research in air-sea interactions including ocean modeling, coupled air-sea modeling, climate prediction on scales of months to decades, statistical studies and predictions of social and economic consequences of ocean-atmospheric variations. http://www.coaps.fsu.edu/.

Center for Science in the Earth System (CSES - University of Washington/JISAO)

The Center for Science in the Earth System (CSES) performs research into variations in global and regional climate, and investigates the applications of climate forecasts and associated information. Areas of emphasis include: the manifestations of the Pacific Decadal Oscillation (PDO) and the Arctic Oscillation (AO) on the Pacific Northwest; the development of methods for downscaling climate forecasts to regional scale, monitoring and assessment of regional climate variability, and the dissemination of climate information to the public. http://www.cses.washington.edu/

Geophysical Fluid Dynamics Laboratory (GFDL)

The modeling efforts of the NOAA Geophysical Fluid Dynamics Laboratory (GFDL) contribute to CDEP through collaborative efforts in prediction/predictability and ocean data assimilation. http://www.gfdl.noaa.gov/.

NCEP/Environmental Modeling Center (EMC)

The global modeling efforts of the Environmental Modeling Center (EMC) of the National Centers for Environmental Prediction (NCEP) contribute to CDEP through collaborative efforts in global coupled modeling, data assimilation, and regional modeling http://www.emc.ncep.noaa.gov/.

IRI Modeling and Prediction Research Group

The Modeling and Prediction Research Group of the International Research for Climate Prediction (IRI) contributes to CDEP though its efforts in ocean modeling and data assimilation, atmospheric model diagnosis, regional downscaling, and prediction/predictability research. http://iri.columbia.edu/climate/research/.

NASA Seasonal-to-Interannual Prediction Project (NSIPP)

The goal of the NASA Seasonal-to-Interannual Prediction Project (NSIPP) is to develop an assimilation and forecast system capable of using a combination of satellite and in situ data to improve the prediction of ENSO and other major seasonal-to-interannual signals and their teleconnections. http://nsipp.gsfc.nasa.gov/.