JCSDA-related Satellite Data Assimilation

Research and Training Activities at CIRAMilija Zupanski and Chris Kummerow

Cooperative Institute for Research in the Atmosphere

Fort Collins, Colorado

The 13th JCSDA Technical Review Meeting & Science Workshop on Satellite Data Assimilation

NCWCP, May 13-15, 2015College Park, MD

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CIRA Background

CIRA satellite DA research

CIRA-NOAA Graduate Student Training Program in Data Assimilation

Summary and future development

Outline

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NOAA Cooperative institute at Colorado State University, co-located with Atmospheric Science Department

Promotes and conducts multi-disciplinary cooperation among CI and NOAA research scientists, University faculty, staff and students in the context of NOAA-specified research theme areas in satellite applications for weather/climate forecasting

Extensive research in data assimilation, in particular satellite data assimilation• Fort Collins DA group: Steven Fletcher, Karina Apodaca, Ting-

Chi Wu, Anton Kliewer, David Baker, Andrew Schuh, graduate students

• CIRA employees working on data assimilation at NOAA/GSD in Boulder, NCWCP in College Park

CIRA Background

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CIRA Research Theme III: Data Assimilation

Objective 1: Carbon cycle assimilation

• Use of NOAA observations, data assimilation and modeling systems• Support collaboration between NOAA, NASA, DoD and JCSDA

Objective 2: Water cycle assimilation

Objective 3: Air quality assimilation Objective 4: Applications of assimilation to model analysis andverification Objective 5: Applications of assimilation to observing system assessment and new observations

CarbonTracker

GPM

GOES-R

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Long history in processing satellite data and satellite applications

Co-located with satellite data processing and satellite product research teams working with JPSS, GOES-R, GPM, CLOUDSAT

Development and applications of new satellite data assimilation and cloud retrieval methodologies

Direct support of NOAA and NASA DA development

CIRA Satellite Data Assimilation Research

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Assimilation of cloud and precipitation-affected satellite radiances• Infrared (GOES-R ABI, MSG SEVIRI, GEMS ABI, CrIS)• Microwave (GMI, TMI, AMSUA, AMSUB, ATMS, MHS, AMSRE, AMSR2)

Assimilation of new observation types • GOES-R GLM• GPM rainfall product

Modeling systems• Global, regional and cloud resolving • Coupled systems

Systems and algorithms• WRF-NMM, HWRF, GFS (NOAA operational systems)• Gridpoint Statistical Interpolation (GSI) data assimilation• Community Radiative Transfer Model (CRTM)• NU-WRF (NASA regional unified model)

Highlights of CIRA Satellite Data Assimilation Research related to JCSDA mission

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Highlights of CIRA Satellite Data Assimilation Research: All-sky GMI radiances

NASA Unified WRF (NU-WRF) NASA WRF Ensemble Data Assimilation System (WRF-EDAS) Using DPR for radiance bias correction High-precipitation event over the Southeast US (~15 May 2014)

First assimilation of GMI precipitation-affected radiances

First guess GMI radianceHydrometeor (qrain)analysis increments

Accumulated 6-hour precipitation forecast

From Sara Zhang (NASA/GMAO)

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Problem: If forecast error covariance has a less-reliable or non-existent cross-variable correlations, how to design observation operator?• Relevant to all DA methods (variational, hybrid variational-

ensemble, and ensemble DA)• Strategy: Custom design observation operator in order to

provide the impact of the particular observation on the initial conditions of ps,T,u,v, …

DA Challenge of new observation types

Cloud hydrometeor, lightning flash rate can impact the initial conditions of standard dynamical variables, thus providing the environment adjustment

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• Initial tests with regional modeling systems (WRF-NMM,WRF-ARW)

• Next step with global modeling systems (GFS)

• Challenge: Extract the information about the storm environment from lightning observations

• Karina Apodaca’s poster

Highlights of CIRA Satellite Data Assimilation Research related to JCSDA mission: GOES-R GLM data assimilation

“Incorporating the GOES-R Geostationary Lightning Mapper Assimilation into the GSI for use in the NCEP Global System”

Project Description

The scientific focus of this project is to o develop the capability to assimilate GOES-R

Geostationary Lightning Mapper (GLM) observations in the NOAA/NCEP global data assimilation system (GDAS)

We plan to achieve this by:o adopting and optimizing the GLM lightning

observation operator that is suited for NOAA global forecasting and data assimilation, and

o incorporating the lightning observation operator in NOAA global data assimilation system

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• Application with NOAA HWRF model

• Assimilation of customized TRMM/GPM cloud hydrometeor retrievals

• Next step all-sky satellite radiances from ATMS and CrIS

• Challenge: Make cloud hydrometeor retrievals impact the initial conditions of mass/wind control variables in GSI

• Ting-Chi Wu’s poster

Highlights of CIRA Satellite Data Assimilation Research: Assimilation of satellite precipitation data for hurricanes

“Assimilation of Moisture and Precipitation Observations in Cloudy Regions of Hurricane Inner Core Environments to Improve Hurricane

Intensity, Structure and Precipitation”

Project Description The scientific focus of this project is to

o Use GSI to assimilate satellite moisture/precipitation data in near-core and hurricane core environment for use by NOAA operational HWRF model, and

o evaluate the impact on the analysis and prediction of hurricane intensity, structure, and precipitation.

We plan to achieve this by:(1) developing this capability for the NOAA

operational hurricane WRF (HWRF) modeling system for assimilation in the core, and near-core environment

GPM

GOES-R

CIRA-NOAA Graduate Student Training Program in Data Assimilation

New program started in 2015 Motivation Objective Building on pre-existing expertise and convenient location

• Extensive DA research and development at CIRA, in particular the satellite DA

• Co-located with ATS/CSU, with strong background in satellite and modeling research and applications

Future

CIRA-NOAA Graduate Student Training Program in Data Assimilation: Motivation

Data assimilation has become a necessity in Numerical Weather Prediction (NWP)

Although the need for data assimilation is clearly increasing, there is a noticeable lack of skilled data assimilation scientists entering the job market.

Fortunately, there is a great interest among young scientists completing their graduate studies to begin working in the field of data assimilation.

Develop a formal training of these scientists in data assimilation in order to help in ameliorating the problem, with clear benefits to government labs and research institutions. Currently focused on NOAA operational systems (GSI, CRTM, WRF-NMM, HWRF, GFS).

CIRA-NOAA Graduate Student Training Program in Data Assimilation: Goal/Objective

In collaboration between CIRA and NOAA, develop a one-year graduate student training program in data assimilation

Aim the program at recent graduates who have general skills in geosciences, mathematics, or engineering, and who are motivated and willing to learn about data assimilation

Combine theoretical and practical DA teaching and training

CIRA-NOAA Graduate Student Training Program in Data Assimilation: Training Plan

Brief theoretical introduction to data assimilation

Advanced topics related to practical realization of variational, ensemble, and hybrid variational-ensemble methods, and the outstanding issues

Cover the typical sources of observations, in particular the satellite observations

Decide on a problem of mutual interest and conduct a data assimilation study

Work conducted on JCSDA S4 computer

At the end, anticipate that the data assimilation study will result in a conference paper or a peer-reviewed manuscript. Present the completed research to the interested NOAA Labs and Centers

CIRA-NOAA Graduate Student Training Program in Data Assimilation: Interns

Two interns in 2015

Both interns are highly motivated and have the required mathematical and computational skills

Biljana Orescanin (MS)

- Background in carbon transport, plant phenology, land surface

- MS from Colorado State University

James Taylor (PhD)

- Background in global modeling, MJO, tropical convection

- PhD from University of Reading, UK

CIRA-NOAA Graduate Student Training Program in Data Assimilation: Future

Produce well-trained data assimilation scientists for potential work at NOAA

Strengthen the program by improving the coordination between NOAA scientists and DA interns

Build a strong, systematic way of training the motivated scientists

Extend the program to other interested Government Labs and Centers (e.g., NASA, NRL)

Increase the number of interns

Summary

CIRA has a long history in satellite data assimilation

Data assimilation research activities focus on JCSDA-relevant applications

New CIRA-NOAA data assimilation training program started in 2015

JCSDA computing support (S4) for training

Great potential for helping NOAA in hiring the scientists who are highly-skilled in data assimilation and familiar with NOAA operational systems