Science Mission Directorate NASA’s Weather Research Program NWS SRH SOO-NASA/SPoRT Joint Workshop Dr. Tsengdar Lee July 11-13, 2006

Turning Observations into Knowledge Products

System of Systems Framework

NASA’s Weather Research Activities  Under Earth Science Research Division/Research and Analysis Program and Applied Science Program  Invest in basic and applied weather research and development  Collaborate closely with NOAA colleagues  Developed algorithms in satellite data assimilation and retrieval  Applied directly to short and medium range weather forecast  SPoRT and JCSDA are two of the major investments SMD ESD R&A Program Wx Research Applied Science Program Appl Wx Research HPDPSDAPD

Turning Observations into Knowledge Products

Bay CIEF Midwest MSFC DC CIEF GSFC CIEF South East KSC DFRC JPLHQ LRCARC GRC SSCMAF OC48 OC48 Lambda Services CIEF South Central JSC CIEF Midwest MSFC DC CIEF GSFC CIEF South East KSC DFRC JPLHQ LRC ARC GRC SSCMAF OC48 OC48 Core Lambda Services CIEF South Central JSC WSC WSTF CIEF Bay Mission Support Backbone 2.5 Gbps lambda SONET OC48 (2.5 Gbps) SONET OC12 (622 Mbps) SONET OC3 (155 Mbps)

Interactive Visual Supercomputing

Compute Environment Multi-tiered Platforms Common Front End Storage Area Network GB/s Ideal Architecture Vision Data Centric, Multi-Tiered Shared High Speed Disk Hierarchical Storage Management High Speed Research Network High Speed Access to Other Sites Next Generation Platforms Visualization Environment NASA Mission Support Network Capability Systems Capacity Systems

Project Columbia computing facility World’s fourth fastest computer with 51.8 Teraflops throughput processors Earth Science modeling and data assimilation has been the prime usage of the systems Collaboration with Science Mission Computing and Modeling and Analysis Research

Establishing a Modeling Environment

Project FastPath

TRL Definitions NASA Technology Readiness Level

EMC NCO R&D Operations Delivery Criteria Transition from Research to Operations Requirements EMC NCEP’s Role in the Model Transition Process OPS Life cycle Support Service Centers NOAA Research (GFDL/URI) Concept of Operations Service Centers (TPC) Test Beds JHT JCSDA User Basic Research Observation System Launch List – Model Implementation Process Field Offices Effort EMC and NCO have critical roles in the transition from NOAA R&D to operations Applied research Other Agency, Academia 1..Identified for Selection 2. Code/Algorithm Assessment and/or Development 3. Interface with Operational Codes 4. Level I:- Preliminary Testing (Lower Resolution) 5. Level II:- Preliminary Testing (DA/Higher Resolution) 6. EMC Pre- Implementation Testing (Packaging and Calibration) 7. NCO Pre- Implementat ion Testing 8. Implementation Delivery OPS Support Svc Centrs User

NWS SPoRT’s Role in the R&O Process NOAA Research Observation System Effort

Highlights

AIRS Data Impact on NCEP GFS Data Category Number of AIRS Channels Total Data Input to Analysis Data Selected for Possible Use Data Used in 3D VAR Analysis (Clear Radiances) ~200x10 6 radiances (channels) ~2.1x10 6 radiances (channels) ~0.85x10 6 radiances (channels) Current preliminary impact study shows that the use of a small fraction (~0.5%) of AIRS clear only data can provide significant 3 to 6 –day forecast skill improvement in both northern & southern Hemispheres S.H. N.H.

JCSDA Road Map ( ) Improved JCSDA data assimilation science OK Required 2003 Advanced JCSDA community-based radiative transfer model, Advanced data thinning techniques Science Advance By 2010, a numerical weather prediction community will be empowered to effectively assimilate increasing amounts of advanced satellite observations 2010 AMSU, HIRS, SSM/I, Quikscat, AVHRR, TMI, GOES assimilated AIRS, ATMS, CrIS, VIIRS, IASI, SSM/IS, AMSR, WINDSAT, GPS,more products assimilated Pre-JCSDA data assimilation science Radiative transfer model, OPTRAN, ocean microwave emissivity, microwave land emissivity model, and GFS data assimilation system were developed The radiances of satellite sounding channels were assimilated into EMC global model under only clear atmospheric conditions. Some satellite surface products (SST, GVI and snow cover, wind) were used in EMC models A beta version of JCSDA community-based radiative transfer model (CRTM) transfer model will be developed, including non- raining clouds, snow and sea ice surface conditions The radiances from advanced sounders will be used. Cloudy radiances will be tested under rain-free atmospheres, more products (ozone, water vapor winds) NPOESS sensors ( CMIS, ATMS…) GIFTS, GOES-R The CRTM include cloud, precipitation, scattering The radiances can be assimilated under all conditions with the state-of- the science NWP models Resources: 3D VAR D VAR 2006

Short Term Priorities MODIS: MODIS AMV assessment and enhancement. Accelerate assimilation into operational models. AIRS: Improved utilization of AIRS Improve data coverage of assimilated data. Improve spectral content in assimilated data. Improve QC using other satellite data (e.g. MODIS, AMSU) Investigate using cloudy scene radiances and cloud clearing options Improve RT Ozone estimates Reduce operational assimilation time penalty (Transmittance Upgrade) SSMIS: Collaborate with the SSMIS CALVAL Team to jointly help assess SSMIS data. Accelerate assimilation into operational model as appropriate

Some Major Accomplishments  Common assimilation infrastructure at NOAA and NASA  Common NOAA/NASA land data assimilation system  Interfaces between JCSDA models and external researchers  Community radiative transfer model-Significant new developments, New release June  Snow/sea ice emissivity model – permits 300% increase in sounding data usage over high latitudes – improved polar forecasts  Advanced satellite data systems such as EOS (MODIS Winds, Aqua AIRS, AMSR-E) tested for implementation MODIS winds, polar regions - improved forecasts. Current Implementation Aqua AIRS - improved forecasts. Current Implementation  Improved physically based SST analysis  Advanced satellite data systems such as DMSP (SSMIS), CHAMP GPS being tested for implementation  Impact studies of POES AMSU, Quikscat, GOES and EOS AIRS/MODIS with JCSDA data assimilation systems completed.

SPoRT Center Structure

MODIS / AMSR-E MODIS imagery orbital track map single visible image (250m) natural color 3 ch. composite (500m) long wave infrared - 11  m (1000m) short wave infrared – 3.9  m (1000m) 11  m  m– fog product (1000m) water vapor  m (1000m) MODIS products cloud top pressure (5km) precipitable water (5km) lifted index (5km) land surface temperature (LST) – 1 km SST - single time and composite – 1km AMSR-E products (5km) rain rates (instantaneous) convective fraction SST precipitable water ocean surface wind speed

MODIS (on the NASA Terra and Aqua polar orbiting satellites) provides up to 4 passes a day for a given region Terra: nominal 10:30am (d) / 10:30pm (a) overpass time Aqua: nominal 1:30pm (a) / 1:30am (d) overpass Terra / Aqua Data Availability Orbital tracks - recent past and future orbital visualizations available in AWIPS Latency - most MODIS data and products are available on the Southern Region server within 30 minutes of collection – additional minute delay based on ftp scripts

Data provided in D2D access like GOES satellite data correspond to WFO coverage areas at highest resolution Examples: color composites TPW SSTs rain rates May 28, 2004 COMPOSITE & composite SST Previews available MODIS/AMSR-E Data Access in AWIPS

Methodology:  2 km resolution with 51 levels  Physics differences from operational WRF: No cumulus parameterization WSM 6-class microphysics scheme  24h simulations run daily for May 2004  Parallel runs for both the RTG SSTs and the MODIS SST composites 3h WRF simulation 24h WRF simulation ADAS MODIS SST- RTG SST (K) 14 May 2004 Impact of MODIS SSTs on Mesoscale Weather

WRF Hurricane Forecasts  In collaboration with Goddard Space Flight Center, run test cases to determine if WRF forecasts are sensitive to SSTs  Domain configured like May 2004 runs  24 – 48 h forecasts  Initialized with 40 km NAM analyses  NAM 3h forecasts used for LBCs  Parallel forecasts with either RTG SSTs or MODIS SST composite New Orleans, LA Radar Reflectivity 42h forecast of 3h accumulated precip (in) Hurricane Katrina 06 UTC August 29, 2005

 Use of MODIS SST composites is currently ongoing in operational WRF forecasts  May 2004 simulations and hurricane forecasts provide the opportunity to determine the impact of MODIS SSTs on regional forecasts  Preliminary work suggests that the WRF model appears to respond appropriately to high-resolution SST data  Greatest impact of MODIS SSTs is seen in the marine boundary layer Summary