Presented By Suru Saha EMCNCEP Contributors Jack Woollen Daryl Kleist Dave Behringer Steve Penny Xingren Wu Bob Grumbine Mike Ek Jiarui Dong Shrinivas Moorthi ID: 786945
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Slide1
1
Reanalysis
Coupled Data Assimilation at NCEP
Presented By Suru
Saha
(EMC/NCEP)
Contributors:
Jack Woollen, Daryl Kleist, Dave
Behringer
, Steve Penny,
Xingren
Wu, Bob
Grumbine
, Mike
Ek
,
Jiarui
Dong,
Shrinivas
Moorthi
, Xu Li, Sarah Lu, Yu-Tai
Hou
,
Arun
Chawla, Henrique
Alves (all EMC)
Slide22
Operational System Attribute(s
)
System Name
AcronymAreal CoverageHorz ResCycle FreqFcst Length (hr)Climate Forecast System Reanalysis(operational, coupled atmosphere-ocean-sea-ice-land)CFSRGlobal27km(T574)6hrs9-hr coupled guess forecast
NCEP maintains and updates in real time a variety of older
Reanalyses
, such as R1, R2, plus smaller stand alone (re)analyses (GODAS, LDAS
etc
).
To discontinue them is next to impossible, which speaks to the need for
Reanalyses
amongst users.
When talking about “reanalysis” in general, this legacy aspect is included.
Slide33
Why System(s) are Operational
Primary stakeholders and requirement
drivers
The need for Reanalysis is enormous and diverse, such as:Provide initial conditions for NCEP models especially hindcasts Model verification and in-depth process studiesAtmospheric & Oceanic Diagnostic studies, as well as Climate Change StudiesProvide initial conditions for other models (GFDL, CCSM4)Reanalysis is one vital component of the calibration of forecasts Basic material for countless empirical studies, including empirical forecasts.What products are the models contributing to? At NCEP: the CFSv2 forecasts. At CPC: Pretty much 90% of all monitoring that goes on in CPC. Outside NCEP: A variety of outlets (NEI/NCAR) display and distribute our Reanalysis fieldsWhat product aspects are you trying to improve with your development plans? More resolution, higher accuracy, fewer artificial trends Increased availability and greater variety of products. Top 3 System Performance StrengthsStrength 1: The whole world is using the NCEP ReanalysesStrength 2: Using satellite radiances directly for the first time in an NCEP ReanalysisStrength 3: Coupling to the ocean in CFSR (2010) was a unique first stepTop 3 System Performance Challenges Challenge 1 : Keeping up with constant changes in the observing system.Challenge 2 : Keeping up with changing CO2 concentrations in the systemChallenge 3 : Maintaining the system in real time going forward
Slide44
System Evolution
Over the Next 5 Years
Major forcing factors
We need a unified approach to global modeling for all spatial and temporal resolutions for better management of modeling activities at NCEP. This includes a unified strategy for hindcasts for calibration (which requires initial states in a modern shape for old times, i.e Reanalysis)Science and development prioritiesUGCS Unified Global Coupled SystemAtmosphere-Land-Ocean-Seaice-Waves-Aerosol-Ionosphere interactionsTimely new Reanalysis and Reforecast for each implementationWhat are you top challenges to evolving the system(s) to meet stakeholder requirements?Challenge 1 : Using a unified hybrid ensemble approach to DA of the coupled system. Hopefully, this approach can deal with inhomogeneous data input with strong coupling.Challenge 2 : Testing the following models within the NEMS framework, to produce the 6-hour guess forecast: MOM5.1/MOM6 and/or HYCOM for the ocean SIS2/CICE/KISS for sea-ice WAVEWATCH III for waves Noah-MP for land GOCART for aerosol WAM for ionosphereChallenge 3 : Data mining and formatting new datasets for inclusion in the ReanalysisPotential opportunities for simplification going forwardUnified global DA allows for better use of resources with respect to core / physics / coupling development, but is can we unified on the different scales involved.
Slide55
Top 3 Things You Need
From the UMAC
Help with finding the required
resources for: Computing Archival DisseminationHelp with the requirements for sufficient and sustained resources to allow EMC/NCEP to properly complete this huge undertakingHelp with shielding the scientists and collaborators from spending valuable time trying to get the resources, to allow them to do their scientific jobs