NCAR Contribution to A U.S. National Multi-Model Ensemble (NMME) ISI Prediction System
NCAR brought the latest version of the Community Earth System Model (version 1, CESM1) into the mix of models in the NMME effort. This new version uses our newest atmospheric model CAM5 and produces a coupled climate and ENSO that are generally as good or better than those of the Community Climate S...
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ftosti:oai:osti.gov:1226920 2023-07-30T04:02:09+02:00 NCAR Contribution to A U.S. National Multi-Model Ensemble (NMME) ISI Prediction System Tribbia, Joseph 2017-08-07 application/pdf http://www.osti.gov/servlets/purl/1226920 https://www.osti.gov/biblio/1226920 https://doi.org/10.2172/1226920 unknown http://www.osti.gov/servlets/purl/1226920 https://www.osti.gov/biblio/1226920 https://doi.org/10.2172/1226920 doi:10.2172/1226920 58 GEOSCIENCES 54 ENVIRONMENTAL SCIENCES 2017 ftosti https://doi.org/10.2172/1226920 2023-07-11T09:04:02Z NCAR brought the latest version of the Community Earth System Model (version 1, CESM1) into the mix of models in the NMME effort. This new version uses our newest atmospheric model CAM5 and produces a coupled climate and ENSO that are generally as good or better than those of the Community Climate System Model version 4 (CCSM4). Compared to CCSM4, the new coupled model has a superior climate response with respect to low clouds in both the subtropical stratus regimes and the Arctic. However, CESM1 has been run to date using a prognostic aerosol model that more than doubles its computational cost. We are currently evaluating a version of the new model using prescribed aerosols and expect it will be ready for integrations in summer 2012. Because of this NCAR has not been able to complete the hindcast integrations using the NCAR loosely-coupled ensemble Kalman filter assimilation method nor has it contributed to the current (Stage I) NMME operational utilization. The expectation is that this model will be included in the NMME in late 2012 or early 2013. The initialization method will utilize the Ensemble Kalman Filter Assimilation methods developed at NCAR using the Data Assimilation Research Testbed (DART) in conjunction with Jeff Anderson’s team in CISL. This methodology has been used in our decadal prediction contributions to CMIP5. During the course of this project, NCAR has setup and performed all the needed hindcast and forecast simulations and provide the requested fields to our collaborators. In addition, NCAR researchers have participated fully in research themes (i) and (ii). Specifically, i) we have begun to evaluate and optimize our system in hindcast mode, focusing on the optimal number of ensemble members, methodologies to recalibrate individual dynamical models, and accessing our forecasts across multiple time scales, i.e., beyond two weeks, and ii) we have begun investigation of the role of different ocean initial conditions in seasonal forecasts. The completion of the calibration hindcasts for ... Other/Unknown Material Arctic SciTec Connect (Office of Scientific and Technical Information - OSTI, U.S. Department of Energy) Arctic Isi ENVELOPE(-38.550,-38.550,65.617,65.617) |
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SciTec Connect (Office of Scientific and Technical Information - OSTI, U.S. Department of Energy) |
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58 GEOSCIENCES 54 ENVIRONMENTAL SCIENCES |
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58 GEOSCIENCES 54 ENVIRONMENTAL SCIENCES Tribbia, Joseph NCAR Contribution to A U.S. National Multi-Model Ensemble (NMME) ISI Prediction System |
topic_facet |
58 GEOSCIENCES 54 ENVIRONMENTAL SCIENCES |
description |
NCAR brought the latest version of the Community Earth System Model (version 1, CESM1) into the mix of models in the NMME effort. This new version uses our newest atmospheric model CAM5 and produces a coupled climate and ENSO that are generally as good or better than those of the Community Climate System Model version 4 (CCSM4). Compared to CCSM4, the new coupled model has a superior climate response with respect to low clouds in both the subtropical stratus regimes and the Arctic. However, CESM1 has been run to date using a prognostic aerosol model that more than doubles its computational cost. We are currently evaluating a version of the new model using prescribed aerosols and expect it will be ready for integrations in summer 2012. Because of this NCAR has not been able to complete the hindcast integrations using the NCAR loosely-coupled ensemble Kalman filter assimilation method nor has it contributed to the current (Stage I) NMME operational utilization. The expectation is that this model will be included in the NMME in late 2012 or early 2013. The initialization method will utilize the Ensemble Kalman Filter Assimilation methods developed at NCAR using the Data Assimilation Research Testbed (DART) in conjunction with Jeff Anderson’s team in CISL. This methodology has been used in our decadal prediction contributions to CMIP5. During the course of this project, NCAR has setup and performed all the needed hindcast and forecast simulations and provide the requested fields to our collaborators. In addition, NCAR researchers have participated fully in research themes (i) and (ii). Specifically, i) we have begun to evaluate and optimize our system in hindcast mode, focusing on the optimal number of ensemble members, methodologies to recalibrate individual dynamical models, and accessing our forecasts across multiple time scales, i.e., beyond two weeks, and ii) we have begun investigation of the role of different ocean initial conditions in seasonal forecasts. The completion of the calibration hindcasts for ... |
author |
Tribbia, Joseph |
author_facet |
Tribbia, Joseph |
author_sort |
Tribbia, Joseph |
title |
NCAR Contribution to A U.S. National Multi-Model Ensemble (NMME) ISI Prediction System |
title_short |
NCAR Contribution to A U.S. National Multi-Model Ensemble (NMME) ISI Prediction System |
title_full |
NCAR Contribution to A U.S. National Multi-Model Ensemble (NMME) ISI Prediction System |
title_fullStr |
NCAR Contribution to A U.S. National Multi-Model Ensemble (NMME) ISI Prediction System |
title_full_unstemmed |
NCAR Contribution to A U.S. National Multi-Model Ensemble (NMME) ISI Prediction System |
title_sort |
ncar contribution to a u.s. national multi-model ensemble (nmme) isi prediction system |
publishDate |
2017 |
url |
http://www.osti.gov/servlets/purl/1226920 https://www.osti.gov/biblio/1226920 https://doi.org/10.2172/1226920 |
long_lat |
ENVELOPE(-38.550,-38.550,65.617,65.617) |
geographic |
Arctic Isi |
geographic_facet |
Arctic Isi |
genre |
Arctic |
genre_facet |
Arctic |
op_relation |
http://www.osti.gov/servlets/purl/1226920 https://www.osti.gov/biblio/1226920 https://doi.org/10.2172/1226920 doi:10.2172/1226920 |
op_doi |
https://doi.org/10.2172/1226920 |
_version_ |
1772812878244478976 |