N A T I O N A L O C E A N I C A N D A T M O S P H E R I C A D M I N I S T R A T I O N

JCSDA Technical Review Meeting and Science WorkshopMay 21-23, 2014

JCSDA 12th Annual Technical Review Meeting and Science Workshop on Satellite Data Assimilation

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Overview of (some of) NESDIS Contributionsto the JCSDA

Presented by

Sid Ahmed Boukabara

Senior Data Assimilation Scientist, NESDIS/STAR

Contributions from:NOAA NESDIS teams (DRT, JPSS/GOES-R PG), and JCSDA External Research Program (FFO)

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JCSDA Technical Review Meeting and Science WorkshopMay 21-23, 2014

Introduction

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NESDIS does not run a data assimilation system in real-time Strong interest in Accelerating/Optimizing use of satellite data NESDIS funds multiple projects that impact satellite data assimilation Approach:

Develop Tools needed to facilitate the use of satellite data CLBLM, CRTM & CSEM Satellite Data Thinning & Representation Optimization CMFT Centralized BUFRization Tool General Satellite QC Tool (MIIDAPS)

Accelerate/Optimize use of satellite data OSCAT, GPM, ATMS, SSMIS, GOES-R, Etc Proxy data for day-1 readiness Advance DA Science to allow more satellite data to be used (cloudy/rainy, ..)

Reach out to external research community Proving ground & Risk Reduction Programs FFO Visiting Scientists, Etc O2R Environment (S4 and JIBB Support and Upgrade)

Work closely with NWS through directed research for R2O

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JCSDA Technical Review Meeting and Science WorkshopMay 21-23, 2014 3

Contents

O2R and Engaging the Community4

Introduction1

Accelerating/Optimizing Use of Satellite Data 3

Facilitating Using Satellite Data (Community Tools)2

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JCSDA Technical Review Meeting and Science WorkshopMay 21-23, 2014

CRTM Mission• Satellite radiance simulation and assimilation for passive MW, IR, & Visible sensors of NOAA,NASA,DoD satellites, and others (200 sensors) • Simulation of clear/cloudy/precipitating scenes, globally

CRTM Applications• Data assimilation in supporting of weather forecasting• Physical retrieval algorithm for products• Stability and accuracy monitoring of satellite observations• Education and Research: reanalysis, climate studies, air quality forecasting, and a radiative tool for students

CRTM Future Development• Acquarius, SMOS, SMAP, ..• CRTM for CMAQ• CRTM unapodized capability• CRTM for cloudy/rainy data assimilation

ATMS Ch. 4 (O-B) GDAS

CRTM

4

(slide based on Q. Liu presentation)

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JCSDA Technical Review Meeting and Science WorkshopMay 21-23, 2014

CLBLM

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An effort has been initiated to modernize the LBLRTM. Collaborative work between JCSDA and AER.

Features of CLBLM Modern coding standards Streamlined Interface (inputs, outputs and spectroscopy) Modular Easy to maintain and upgrade Parallel processing For all spectral regions

Status: Design/Planning Phase LBLRTM de-coding Early stage of implementation

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JCSDA Technical Review Meeting and Science WorkshopMay 21-23, 2014

CSEM:

Microwave

Physical Model

Database

Empirical Models

Vis Infrared

Physical Model

Database

Empirical Models

Sea Ice Snow

Can

opy

Desert

Ocean

Community Surface Emissivity Model

For all Spectral regions and for all surface types

Combination of models, LUTs, empirical

Centralizes all developments for the JCSDA emissivity effort

Fully Integrated with CRTM

Summary and Plans available. Feedback and suggestions welcome

(slide from M. Chen & F. Weng)

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JCSDA Technical Review Meeting and Science WorkshopMay 21-23, 2014

1DVAR Pre-Processing (MIIDAPS) Efforts are on going to:

– Use 1DVAR as a pre-processor to NWP for quality control purposes

– QC of satellite data, rain and ice detection, coast contamination,

– RFI for imagers, etc) – based on MiRS technology

(significant leverage)– Implement dynamically-

retrieved emissivity in the NWP to allow assimilation of surface –sensitive channels

– Assess assimilating sounding products in cloudy/rainy conditions

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O-A(MIIDAPS)

O-A(Oper.)

Goal is to have a community QC tool for satellite data assimilation pre-processing:extend the MIIDAPS to all Sensors (IR & MW, geo/Pol)

Bias: -0.2StdDev: 0.43

Points Passing QC

(slide courtesy of K. Garrett)

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JCSDA Technical Review Meeting and Science WorkshopMay 21-23, 2014

Community Satellite data Thinning and Representation Optimization Tool (CSTROT)

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Thinning & Representation is an important aspect of assimilating satellite data

An effort is on-going to optimize this aspect through a standalone tool (CSTROT)

Features include:– Different representations

(superobing / sampling)– Variability based thinning– Flexible (sampling rate)– Applicable to different observations

The tool could also serve as a super-sampling tool for ROI (for regional data assimilation) (Effort led by T. Zhu)

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JCSDA Technical Review Meeting and Science WorkshopMay 21-23, 2014

CMFT: Community Multi-Format Tool

Part of the O2R environment For Researchers who do not have access

to BUFR files. It is NOT a new tool. It is instead a tool that centralizes all

BUFR formatting kits that exist in a single, user-friendly tool for researchers to use.

Works from many input formats (HDF, ncdf, etc)

Outputs are in BUFR format (WMO flavor and NCEP flavor of BUFR)

Packaged to be user-friendly (GUI), but also applicable to operations (the GUI generates scripts that can run operationally)

Being extended to AMSR-2, GPM, etc

The list of data CMFT can process:

AMSUAAMSUBMHSSSMISGPSROSNPP ATMSSNPP CRISMLSOMIHIRS3HIRS4TRMM/TMISuper TMIEtc..

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JCSDA Technical Review Meeting and Science WorkshopMay 21-23, 2014 10

Contents

O2R and Engaging the Community4

Introduction1

Accelerating/Optimizing Use of Satellite Data 3

Facilitating Using Satellite Data (Community Tools)2

N A T I O N A L O C E A N I C A N D A T M O S P H E R I C A D M I N I S T R A T I O N

JCSDA Technical Review Meeting and Science WorkshopMay 21-23, 2014

GPM Data Assimilation in JCSDA

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JCSDA is an early adopter of the GPM (GMI) data:

– Close interaction with GPM science team before launch

– High on priority list of the JCSDA executive team (tracked action item)

– Listed in the FY14 Directed research activities

Status:

– BUFRization of the L1B and L1C complete (for testing purposes)

– Close coordination with GMAO on-going– NOAA-NASA MOU in progress to coordinate on

cloudy radiance assimilation

Future Steps:– Assessment of GPM/GMI data on GSI/GFS– Assessment of GPM/GMI on GSI/HWRF– Continued coordination with NASA/GMAO – Close interaction with NWS/NCEP on GPM data

assimilation transition to NCEP GSI– Assess GPM data impact in active regions

(Rain, ice, cloud)(slide courtesy of E. Jones)

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JCSDA Technical Review Meeting and Science WorkshopMay 21-23, 2014

OSCAT Data Assimilation Effort has led to parallel testing

of OSCAT DA in the next version of the GDAS system

Both NESDIS and KNMI OSCAT data were investigated

Pre-assessment was done characterize filtering, thinning, biases and observation error

Errors in wind direction was found to have a bigger effect on A/C than intensity

OSCAT has since failed in orbit Lessons learned will apply to

ASCAT and other scatt. data12

Impact assessment of the OSCAT scatterometer data assimilation. These plots represent the forecast impact (b) and verification results (a) of OSCAT winds experiments. They represent the change in anomaly correlation and RMS (increase or decrease) of the surface wind speed at 0.995 sigma level. The impact, globally, at 48 hours lead time is mixed, but overall positive. Plot courtesy of Li Bi, Riverside Inc, JCSDA Active Sensors data assimilation scientist.

a

b

(slide courtesy of L. Bi)

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JCSDA Technical Review Meeting and Science WorkshopMay 21-23, 2014 13

AMSR-2 Data Assimilation Land and Atmospheric Activities

Assimilation of Satellite Soil Moisture Product from AMSR2 in NCEP Global Forecast System. M. Ek (NCEP) and Zhan (NESDIS). JCSDA Directed research funded project. This effort is JCSDA-facilitated. In this figure, the Noah LSM multiple year means and standard deviations are used to scale the surface layer soil moisture retrievals before assimilation

AMSR2 Soil Moisture (Reference)

GFS-EnKF: After AMSR2 Soil Moisture DA

GFS: Without AMSR2 Soil Moisture DA

JCSDA is actively working on assimilating AMSR-2 data:

– Close interaction between NOAA Scientists

– Listed in the FY14 Directed research activities

– Land applications (soil moisture)

– Atmospheric Application (moisture)

Status:

– Soil moisture data from AMSR-2 combined with other sensors producing SM

– Impact assessment performed – Moisture profiling information

content assessed

Future Steps:– Assessment of GPM/GMI data

on GSI– Continued coordination with

NASA/GMAO – Close interaction with

NWS/NCEP on GPM data assimilation transition to NCEP GSI trunk

Assessment of the vertical moisture information content in AMSR-2 data, showing tropospheric sounding capability, prior to assessing the impact in a GSI environment.

(courtesy K. Garrett, M. Ek, X. Zhan)

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JCSDA Technical Review Meeting and Science WorkshopMay 21-23, 2014 14

(slide courtesy of E. Maddy)

Unfiltered

Filtered

AMV Data Assimilation Activities A coordinated AMV Data Assimilation effort is being

initiated in the JCSDA through coordination between NESDIS, NWS, Navy, NASA and U. Wisconsin

Goal:– Maximize the impact of AMV in NOAA systems – Learn from Navy/NASA experience using AMVs– R2O transition of academia projects that were proven

to offer added value– Prepare for AMV from future sensors (Himawari-8,

GOES-R)

Status:– 2 Inter-agency agreements (IAAs) (NOAA-NASA,

NOAA-Navy) being routed for approval

– Grant proposal already submitted by UW (to leverage previously funded projects)

– Assessment of the AMV data being digested in GSI –on going in NESDIS-

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JCSDA Technical Review Meeting and Science WorkshopMay 21-23, 2014 15

Contents

O2R and Engaging the Community4

Introduction1

Accelerating/Optimizing Use of Satellite Data 3

Facilitating Using Satellite Data (Community Tools)2

N A T I O N A L O C E A N I C A N D A T M O S P H E R I C A D M I N I S T R A T I O N

JCSDA Technical Review Meeting and Science WorkshopMay 21-23, 2014

O2R/R2O Environment Goal: Accelerates the use of satellite data in NWP centers

How: Build a solid O2R environment for a successful R2O

Ensures resources are in place: supercomputer –S4&JIBB-, a software integration team, etc.

Operations-consistency

Both JIBB and S4 are scheduled to be upgraded

In progress:– Extension of O2R to include Ocean DA (NCODA,

HYCOM)– Extension of O2R to include Land Systems (LIS).– Extension of O2R to include NAM

Scientific efforts in

satellite DA in academia,

CIs

Scientific efforts in satellite DA

funded by partner agencies

Scientific efforts in satellite DA in

research community

JCSDA’s own DA

Activities

NWP Operational CentersOngoing Baseline

Improvement in NWP centersObjective: Improvements in Forecast skills

Diverse R&D activities

Select projects for Transition

Example of S4 Disk Space Usage%

More than ~ 50 users on both JIBB and S4 (total more than ~100). Mixture of NOAA and Researchers

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JCSDA Technical Review Meeting and Science WorkshopMay 21-23, 2014 17

Mid-Upper TropMid-Upper

Trop

SpectroscopyMean residuals from 36 AIRS ARM TWP cases using Tobin et al. best estimate sonde profiles

Mid-Upper TropMid-Upper

Trop

CO2 v3CO2 v2Previous version

(2006) No P/R line cpl HITRAN 2000 CO2 parameters

Latest version (2011)

• P, Q and R line coupling• Lamouroux et al. widths and

line coupling• Tashkun positions, intensities• Updated CO2 and H2O

continua

Improved agreement (Obs - Calc) and consistency across spectral bands!(slide courtesy of V. Payne, formerly AER Inc.)

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JCSDA Technical Review Meeting and Science WorkshopMay 21-23, 2014

Impacts of ATMS on Track Forecast of Hurricane Sandy

23 24 25 26 27 28 29 October 2012

SAT SAT+ATMS

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(slide courtesy of F. Weng.)

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JCSDA Technical Review Meeting and Science WorkshopMay 21-23, 2014

Supporting the JCSDA External Research

Project #

Proposal Number(s) Title Institution PI

112,10

Modernization of the Community line-by-line models and CRTM-OSS

Implementation Atmospheric & Environmental

Research (AER)Jean-Luc Moncet, PI

Eli Mlawer, co-PI

215

Improvement and validation of JCSDA’s Community Radiative Transfer Model (CRTM) Optical

PropertiesTexas A&M University

Ping Yang, PI

3 4

Evaluation and Improvement of Land Surface States and

Parameters to Increase Assimilation of Surface-Sensitive Channels and Improve Operational Forecast Skill

University Corporation for Atmospheric

Research

Michael Barlage, PIXubin Zeng, co-PI

4 5

Assimilation of All-Sky Microwave and Infrared Satellite radiances:

from research to Operations

National Center for Atmospheric Research

University of Wisconsin, Cooperative

Institute for Meteorological Satellite

StudiesThomas Auligne, PI

Selected Projects through the NOAA Federally-Funded Opportunity (FFO) –FY13

The FY15 External Research Opportunity target time: Sept-Oct 2014. Status: Identification of gaps and priorities.

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JCSDA Technical Review Meeting and Science WorkshopMay 21-23, 2014 20

Questions?