# Presentation: 193135

## NASA’s Weather Research ProgramNWS SRH SOO-NASA/SPoRT Joint Workshop

**Dr. Tsengdar Lee **
**July 11-13, 2006**

## Turning Observations into Knowledge Products

**Turning Observations into Knowledge Products**

## System of Systems Framework

## NASA’s Weather Research Activities

**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

## Turning Observations into Knowledge Products

**Turning Observations into Knowledge Products**

## Mission Support Backbone

- Bay

- CIEF

- Midwest

- MSFC

- DC

- CIEF

- GSFC

- CIEF

- South

- East

- KSC

- DFRC

- JPL

- HQ

- LRC

- ARC

- GRC

- SSC

- MAF

*OC*

*48*

*OC*

*48*

**Lambda Services**

- CIEF

- South

- Central

- JSC

- CIEF

- Midwest

- MSFC

- DC

- CIEF

- GSFC

- CIEF

- South

- East

- KSC

- DFRC

- JPL

- HQ

- LRC

- ARC

- GRC

- SSC

- MAF

*OC*

*48*

*OC*

*48*

**Core **

**Lambda Services**

- CIEF

- South

- Central

- JSC

- WSC

- WSC

- WSTF

- CIEF

- Bay

**Mission Support Backbone**

## Interactive Visual Supercomputing

**Interactive Visual Supercomputing**

## Ideal Architecture VisionData Centric, Multi-Tiered

**Compute Environment**
**Multi-tiered Platforms**

**Common Front End**

**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**

**Capability Systems**

**Capacity Systems**

**Capacity Systems**

## Project Columbia computing facility
World’s fourth fastest computer with 51.8 Teraflops throughput
10240 processors
Earth Science modeling and data assimilation has been the prime usage of the systems

- World’s fourth fastest computer with 51.8 Teraflops throughput
- 10240 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

**Establishing a Modeling Environment**

## Project FastPath

## TRL DefinitionsNASA

**Technology Readiness Level**

**Notes:**
You probably are more familiar with this representation of TRLs. This is a NASA slide.

## NCEP’s Role in the Model Transition Process

**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-
- Implementation
- Testing

- 8. Implementation
- Delivery

- 	 1	2	3          4	5	6        7         8        OPS   **Support     Svc Centrs   User**

## SPoRT’s Role in the R&O Process

**NWS**

**SPoRT’s Role in the R&O Process**

**  ****NOAA**
**Research**

**Observation**
**   ****System**

**Effort**

- Highlights

## AIRS Data Impact on NCEP GFS

**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 (2002 - 2010)

**Improved JCSDA data assimilation science**

**2002**

**2004**

**2007**

**2008**

**2009    **

**2005**

**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  -----------------------------------------------------4D 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

**Notes:**
SSMIS op inst.1 only AMSU, no NOAA 17, ailing NOAA15 UKMO     MODIS QC BUFR ISSUES    AIRS  Utilisation  OZONE

## Some Major Accomplishments

**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

**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 - 3.9********m– fog product (1000m)**
**  ****water vapor - 6.7********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**

## Terra / Aqua Data Availability

**      **_**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 10-15 minute delay based on ftp scripts**

## MODIS/AMSR-E Data

_**Data  provided in D2D**_
**access like GOES satellite data**
**correspond to WFO coverage areas at highest resolution**
_**Examples:**_

** ****color composites**

** ****TPW**

** ****SSTs**

** ****rain rates**

**  ****& composite SST**

**Previews available http://weather.msfc.nasa.gov/sport/sport_observations.html**

**MODIS/AMSR-E Data**
**Access in AWIPS**

## Impact of MODIS SSTs on

**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***

**MODIS SST- RTG SST (K)**
**14 May 2004**

**Impact of MODIS SSTs on**
**Mesoscale Weather**

## WRF Hurricane Forecasts

**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**

## Summary

**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**