The 13th JCSDA Technical Review Meeting & Science Workshop on Satellite Data Assimilation NCWCP, May 13-15, 2015 College Park, MD JCSDA-related Satellite Data Assimilation Research and Training Activities at CIRA Milija Zupanski and Chris Kummerow Cooperative Institute for Research in the Atmosphere Fort Collins, Colorado

Outline CIRA Background CIRA satellite DA research CIRA-NOAA Graduate Student Training Program in Data Assimilation Summary and future development

CIRA Background 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 Research Theme III: Data Assimilation GOES-R Objective 1: Carbon cycle assimilation Objective 2: Water cycle assimilation Objective 3: Air quality assimilation GPM Objective 4: Applications of assimilation to model analysis and verification Objective 5: Applications of assimilation to observing system assessment and new observations Outline slide CarbonTracker Use of NOAA observations, data assimilation and modeling systems Support collaboration between NOAA, NASA, DoD and JCSDA Milija Zupanski CIRA/CSU

CIRA Satellite Data Assimilation Research 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

Highlights of CIRA Satellite Data Assimilation Research related to JCSDA mission 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)

First assimilation of GMI precipitation-affected radiances 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 guess GMI radiance Hydrometeor (qrain) analysis increments Accumulated 6-hour precipitation forecast First assimilation of GMI precipitation-affected radiances From Sara Zhang (NASA/GMAO)

DA Challenge of new observation types 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, … Cloud hydrometeor, lightning flash rate can impact the initial conditions of standard dynamical variables, thus providing the environment adjustment

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” 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

Project Description The scientific focus of this project is to 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: adopting and optimizing the GLM lightning observation operator that is suited for NOAA global forecasting and data assimilation, and incorporating the lightning observation operator in NOAA global data assimilation system

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” 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

Project Description The scientific focus of this project is to Use GSI to assimilate satellite moisture/precipitation data in near-core and hurricane core environment for use by NOAA operational HWRF model, and evaluate the impact on the analysis and prediction of hurricane intensity, structure, and precipitation. GPM GOES-R We plan to achieve this by: developing this capability for the NOAA operational hurricane WRF (HWRF) modeling system for assimilation in the core, and near- core environment

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