Reanalysis at NCEP Recent Developments, Current Efforts, Future Plans Bob Kistler IMSG/EMC/NCEP Representing EMC and CPC staff, contractors and visiting.

Slides:



Advertisements
Similar presentations
Improved CanSIPS Initialization from Offline CLASS Simulation and Data Assimilation Aaron Berg CanSISE Workshop.
Advertisements

Integrated Earth System Analysis Workshop Report Held November 2010, Baltimore MD Details at 2PM – POS Panel.
Numerical Weather Prediction Readiness for NPP And JPSS Data Assimilation Experiments for CrIS and ATMS Kevin Garrett 1, Sid Boukabara 2, James Jung 3,
An Examination of the Radiative Fluxes in Various Reanalyses with an Emphasis on the Global Budget Wesley Ebisuzaki 1, S. K. Yang 1,2, Li Zhang 1,2, Arun.
Some Problems in CFSRR Investigated and Solutions Tested for CFSRL Jack Woollen, Bob Kistler, Craig Long, Daryl Kleist, Xingren Wu, Suru Saha, Wesley Ebisuzaki.
Atmospheric Reanalyses Update Mike Bosilovich. ReanalysisHoriz.ResDatesVintageStatus NCEP/NCAR R1T present1995ongoing NCEP-DOE R2T present2001ongoing.
NOAA/NWS Change to WRF 13 June What’s Happening? WRF replaces the eta as the NAM –NAM is the North American Mesoscale “timeslot” or “Model Run”
The next NCEP Climate Forecast System Status Hua-Lu Pan and Suru Saha EMC/NCEP.
THE BEST ANALYZED AIR- SEA FLUXES FOR SEASONAL FORECASTING 2.12 Glenn H. White, W. Wang, S. Saha, D. Behringer, S. Nadiga and H.-L. Pan Global Climate.
My Agenda for CFS Diagnostics Ancient Chinese proverb: “ Even a 9-month forecast begins with a single time step.” --Hua-Lu Pan.
The NCEP operational Climate Forecast System : configuration, products, and plan for the future Hua-Lu Pan Environmental Modeling Center NCEP.
Tolman, December 1, 2014The NPS- looking forward, 1/10 The NCEP Production Suite Looking forward Hendrik L. Tolman Director, Environmental Modeling Center.
Impact of Sea Surface Temperature and Soil Moisture on Seasonal Rainfall Prediction over the Sahel Wassila M. Thiaw and Kingtse C. Mo Climate Prediction.
4. Models of the climate system. Earth’s Climate System Sun IceOceanLand Sub-surface Earth Atmosphere Climate model components.
Improved NCEP SST Analysis
UMAC data callpage 1 of 16Global Ensemble Forecast System - GEFS Global Ensemble Forecast System Yuejian Zhu Ensemble Team Leader, Environmental Modeling.
Tolman, May 7, 2015MAPP Webinar, 1/14 Transition to operations at EMC What works and what does not work Hendrik L. Tolman Director, Environmental Modeling.
1 Ensemble Reforecasts Presented By: Yuejian Zhu (NWS/NCEP) Contributors:
Xingren Wu and Robert Grumbine
CPC Forecasts: Current and Future Methods and Requirements Ed O’Lenic NOAA-NWS-Climate Prediction Center Camp Springs, Maryland ,
Alan Robock Department of Environmental Sciences Rutgers University, New Brunswick, New Jersey USA
Polar Communications and Weather Mission Canadian Context and Benefits.
NW NCNE SCSESW Rootzone: TOTAL PERCENTILEANOMALY Noah VEGETATION TYPE 2-meter Column Soil Moisture GR2/OSU LIS/Noah 01 May Climatology.
A Comparison of the Northern American Regional Reanalysis (NARR) to an Ensemble of Analyses Including CFSR Wesley Ebisuzaki 1, Fedor Mesinger 2, Li Zhang.
1 Reanalysis Coupled Data Assimilation at NCEP Presented By Suru Saha (EMC/NCEP) Contributors: Jack Woollen, Daryl Kleist, Dave Behringer, Steve Penny,
NCEP Production Suite Review: Land-Hydrology at NCEP
1 Global Model Development Priorities Presented By: Hendrik Tolman & Vijay Tallapragada (NWS/NCEP) Contributors: GCWMB (EMC), NGGPS (NWS)
Suru Saha and Hua-Lu Pan, EMC/NCEP With Input from Stephen Lord, Mark Iredell, Shrinivas Moorthi, David Behringer, Ken Mitchell, Bob Kistler, Jack Woollen,
1 Coupled Modeling for Seasonal to Interannual Presented By Suru Saha (EMC/NCEP) Contributors: Jack Woollen, Daryl Kleist, Dave Behringer, Steve Penny,
R.Sutton RT4 coordinated experiments Rowan Sutton Centre for Global Atmospheric Modelling Department of Meteorology University of Reading.
Rongqian Yang, Kenneth Mitchell, Jesse Meng NCEP Environmental Modeling Center (EMC) Summer and Winter Season Reforecast Experiments with the NCEP Coupled.
CPPA Past/Ongoing Activities - Ocean-Atmosphere Interactions - Address systematic ocean-atmosphere model biases - Eastern Pacific Investigation of Climate.
Modern Era Retrospective-analysis for Research and Applications: Introduction to NASA’s Modern Era Retrospective-analysis for Research and Applications:
Tolman, May 13, 2015JCSDA NWS overview, 1/11 JCSDA Activities and Plans NWS overview & plans Hendrik L. Tolman Director, Environmental Modeling Center.
Course Evaluation Closes June 8th.
1 JRA-55 the Japanese 55-year reanalysis project - status and plan - Climate Prediction Division Japan Meteorological Agency.
The NOAA Operational Model Archive and Distribution System NOMADS The NOAA Operational Model Archive and Distribution System NOMADS Dave Clark for Glenn.
1 Coupled Modeling for Week 3 & 4 Presented By: Suru Saha & Yuejian Zhu (NWS/NCEP)
Objects Basic Research (Hypotheses and Understanding) Applied Research (Applications and Tools) AO/NAO A10 (subseasonal to decadal time scales)AO/NAO Explore.
ENSO Update Michelle L’Heureux Team Members: Mike Halpert, Wanqiu Wang, Yan Xue, Gerry Bell, Zeng-Zhen Hu, Vern Kousky, Wayne Higgins, and Arun Kumar NOAA.
1 Arun Kumar Climate Prediction Center 27 October 2010 Ocean Observations and Seasonal-to-Interannual Prediction Arun Kumar Climate Prediction Center NCEP.
National Weather Service Water Science and Services John J. Kelly, Jr. Director, National Weather Service NOAA Science Advisory Board November 6, 2001.
Suru Saha and Hua-Lu Pan, EMC/NCEP With Input from Stephen Lord, Mark Iredell, Shrinivas Moorthi, David Behringer, Ken Mitchell, Bob Kistler, Jack Woollen,
NOAA Council on Long-Term Climate Monitoring (CLTCM) Eighth Meeting in Chicago, Illinois, March The Council identified three strategic issues.
The evolution of climate modeling Kevin Hennessy on behalf of CSIRO & the Bureau of Meteorology Tuesday 30 th September 2003 Canberra Short course & Climate.
NOAA Intra-Seasonal to Interannual Prediction (ISIP) and Climate Prediction Program for Americas (CPPA) Jin Huang NOAA Office of Global Programs November.
NOAA’s Climate Prediction Center & *Environmental Modeling Center Camp Springs, MD Impact of High-Frequency Variability of Soil Moisture on Seasonal.
1 Proposal for a Climate-Weather Hydromet Test Bed “Where America’s Climate and Weather Services Begin” Louis W. Uccellini Director, NCEP NAME Forecaster.
CTB computer resources / CFSRR project Hua-Lu Pan.
Advances in Lake-Effect Process Prediction within NOAA’s Climate Forecast System for North America: A Project Progress Report Jiming Jin and Shaobo Zhang.
Recent and planed NCEP climate modeling activities Hua-Lu Pan EMC/NCEP.
Reanalysis Needs for Climate Monitoring Craig S Long Arun Kumar and Wesley Ebisuzaki CPC NOAA Climate Test Bed (CTB) Meeting – November 9-10, NCWCP.
Multi-Model Ensembles for Climate Attribution Arun Kumar Climate Prediction Center NCEP/NOAA Acknowledgements: Bhaskar Jha; Marty Hoerling; Ming Ji & OGP;
National Centers for Environmental Prediction: “Where America’s Climate, Weather and Ocean Services Begin” An Overview.
Climate Prediction Center: Challenges and Needs Jon Gottschalck and Arun Kumar with contributions from Dave DeWitt and Mike Halpert NCEP Production Review.
1 NCEP’s Climate Forecast System as a National Model “Where America’s Climate, Weather and Ocean Services Begin” 32 nd Climate Diagnostics and Prediction.
Suru Saha and Hua-Lu Pan, EMC/NCEP With Input from Stephen Lord, Mark Iredell, Shrinivas Moorthi, David Behringer, Ken Mitchell, Bob Kistler, Jack Woollen,
NAME SWG th Annual NOAA Climate Diagnostics and Prediction Workshop State College, Pennsylvania Oct. 28, 2005.
1 A review of CFS forecast skill for Wanqiu Wang, Arun Kumar and Yan Xue CPC/NCEP/NOAA.
Climate Mission Outcome A predictive understanding of the global climate system on time scales of weeks to decades with quantified uncertainties sufficient.
1/39 Seasonal Prediction of Asian Monsoon: Predictability Issues and Limitations Arun Kumar Climate Prediction Center
ESSL Holland, CCSM Workshop 0606 Predicting the Earth System Across Scales: Both Ways Summary:Rationale Approach and Current Focus Improved Simulation.
Status and Outlook Evaluating CFSR Air-Sea Heat, Freshwater, and Momentum Fluxes in the context of the Global Energy and Freshwater Budgets PI: Lisan.
UNIFIED GLOBAL COUPLED SYSTEM (UGCS) FOR WEATHER AND CLIMATE PREDICTION Saha-UMAC-09Aug2016.
GFDL Climate Model Status and Plans for Product Generation
WORLD CLIMATE RESEARCH PROGRAMME
WRN Workshop NWS Funding Opportunities
Hydrology and Water Management Applications of GCIP Research
Progress in Seasonal Forecasting at NCEP
Ongoing and Planned Activities in Sub-seasonal Forecasting at the NCEP
Presentation transcript:

Reanalysis at NCEP Recent Developments, Current Efforts, Future Plans Bob Kistler IMSG/EMC/NCEP Representing EMC and CPC staff, contractors and visiting scientists “From the Sun to the Sea… Where America’s Climate, Weather, Ocean and Space Weather Services Begin”

CFSR and CFSv2 model Major improvement: radiation (McICA) CFSR Strengths: High resolution and hourly output CFSR Weaknesses: Stream boundaries Ocean Soil Moisture Stratosphere Tropical issues TOVS > ATOVS

CFSR and CFSv2 model Operational Implementation of the new system: Spring 2011 CFSv2 Model Reforecasts and opnl. Seasonal fcsts. Monte Carlo Independent Column Approximation (McICA) implementation of the Rapid Radiative Transfer Model (RRTM) adapted from AER, Inc.Monte Carlo Independent Column Approximation (McICA) implementation of the Rapid Radiative Transfer Model (RRTM) adapted from AER, Inc. Proved to be the “best available” assimilation model for CFSRL Proved to be the “best available” assimilation model for CFSRL

CFSR Strengths High resolution and hourly output High resolution and hourly output Period from 1998 > Period from 1998 > Examples Examples Depiction of synoptic rainfallDepiction of synoptic rainfall MJO Intraseasonal RainfallMJO Intraseasonal Rainfall Tropical Instability Waves (TIW)Tropical Instability Waves (TIW) Better NWP Initial ConditionsBetter NWP Initial Conditions 4

CFSR Weaknesses Stream boundaries Stream boundaries OceanOcean Soil MoistureSoil Moisture stratospherestratosphere Soil Moisture Sub-Surface Ocean Temperature

CFSR Weaknesses Tropical issues Tropical issues QBOQBO TC noiseTC noise Fit to tropo. ObsFit to tropo. Obs Singapore raob U-comp CFSR U-comp

CFSR Weaknesses TOVS > ATOVS TOVS > ATOVS AMSU-AAMSU-A NOAA-15 Oct 1998NOAA-15 Oct 1998 NOAA-16 Feb 2001NOAA-16 Feb 2001 NOAA 15 --> NOAA 16 --> Li Zhang, Arun Kumar, and Wanqiu Wang (2012), J. Geophys. Res Influence of changes in observations on precipitation: A case study for the Climate Forecast System Reanalysis (CFSR)

CFSRL status 13 months on NOAA R&D Vapor – Feb 2011:Mar months on NOAA R&D Vapor – Feb 2011:Mar 2012 Pre-empted 1 month for 2011 tropical outlook forecastsPre-empted 1 month for 2011 tropical outlook forecasts Limited to only 1 streamLimited to only 1 stream Assimilation prediction model Assimilation prediction model Anticipated opnl. CFS/GFS coupled system (unification mindset)Anticipated opnl. CFS/GFS coupled system (unification mindset) Ran years to assess first stream boundary Ocean was improved, but… Clouds, fluxes worse than CFSR model QBO was still inferior to R1, ERA-I, MERRA CFSv2 seasonal prediction model as assimilation modelCFSv2 seasonal prediction model as assimilation model The McICA radiation interaction tuned at T126L64 led to better clouds and fluxes than the CFSR model TOVS > ATOVS transition TOVS > ATOVS transition Gained insight from MERRA and ERA-I, CPC AMIPGained insight from MERRA and ERA-I, CPC AMIP Ran an impact test of revised moisture radiances (upcoming slides)Ran an impact test of revised moisture radiances (upcoming slides)

An overview of the proposed NOAA’s climate reanalysis effort The key concept: The key concept: both NCEP and ESRL (that comprises the core of the NOAA’s reanalysis expertise) will work with the same model and data assimilation infrastructure (e.g., GFS, Hybrid EnKF, observational data base, boundary conditions).both NCEP and ESRL (that comprises the core of the NOAA’s reanalysis expertise) will work with the same model and data assimilation infrastructure (e.g., GFS, Hybrid EnKF, observational data base, boundary conditions). Specific details within the infrastructure that will be pursued by NCEP or ESRL can differ with minimal duplication of resources.Specific details within the infrastructure that will be pursued by NCEP or ESRL can differ with minimal duplication of resources. This strategy promotes significant enhancements of portability, communication, leveraging of expertise in all the aspects of the common infrastructure for the climate reanalysis.This strategy promotes significant enhancements of portability, communication, leveraging of expertise in all the aspects of the common infrastructure for the climate reanalysis.

An overview of the proposed NOAA’s climate reanalysis effort, cont. Within the “common infrastructure” paradigm: NCEP will focus on the 1948-present with goals of replacing R1 NCEP will focus on the 1948-present with goals of replacing R1 AMIP runs will test efforts to eliminate the exisiting cold bias AMIP runs will test efforts to eliminate the exisiting cold bias ESRL will focus on a sparse-input based climate reanalysis back to the 19 th century. ESRL will focus on a sparse-input based climate reanalysis back to the 19 th century. NCEP and ESRL will collaborate on the configuration of the hybrid data assimilation system where ESRL has considerable expertise, particularly for the pre-satellite period NCEP and ESRL will collaborate on the configuration of the hybrid data assimilation system where ESRL has considerable expertise, particularly for the pre-satellite period Hybrid assimilation can allow for uncertainties in the : Hybrid assimilation can allow for uncertainties in the : atmospheric boundary conditions, such as SSTs and sea iceatmospheric boundary conditions, such as SSTs and sea ice radiative forcings, such as solar variabilityradiative forcings, such as solar variability CO2, and volcanic aerosolsCO2, and volcanic aerosols offline analysis fields, such as snow cover and precipitationoffline analysis fields, such as snow cover and precipitation Within this framework there is a natural opportunity to utilize OSE approaches to clarify issues introduced by qualitative and quantitative changes in observing systems throughout the historical record Within this framework there is a natural opportunity to utilize OSE approaches to clarify issues introduced by qualitative and quantitative changes in observing systems throughout the historical record

First Priority The critical problem to be solved.. The critical problem to be solved.. And it’s not just a reanalysis issue And it’s not just a reanalysis issue e.g. Next generation CFS (CFSv3)e.g. Next generation CFS (CFSv3) The Cold bias of the prediction model The Cold bias of the prediction model It distorts the entire water cycleIt distorts the entire water cycle Assimilation of H2O sensitive radiances Assimilation of H2O sensitive radiances Clouds Clouds Almost all radiative fluxes Almost all radiative fluxes Precipitation Precipitation