# Presentation: 414363

## Use of Satellite Data in Numerical Weather Prediction:  Present Status and Future Challenges

*“**Where America’s Climate, Weather and Ocean Services Begin”*

- 3rd Annual Symposium on Future National Operational Environmental Satellite Systems
- San Antonio, TX
- January 16, 2007

- Dr. Louis W. Uccellini
- Director, National Centers for Environmental Prediction

## Present
Prediction Process
Path Forward: Joint Center for Satellite Data Assimilation
Forecast performance and related satellite impacts
Future
Considerations for Success – a balanced approach
Accelerating the use of NPOESS data
LEO – GEO 
Summary

- Prediction Process
- Path Forward: Joint Center for Satellite Data Assimilation
- Forecast performance and related satellite impacts
- Future
- Considerations for Success – a balanced approach
- Accelerating the use of NPOESS data
- LEO – GEO
- Summary

- Overview

## The NOAA Prediction Process

## The Path to NOAA’s Seamless Suite of Products and Prediction Services

**Research, Development and Technology Infusion**

**Respond &**** Feedback**

**IBM Supercomputer at Gaithersburg, MD Computer Center**

***Feedback***

**Distribute**

**- Process**
**- Assimilate**
**- Predict**

**Observe**

**Products & Forecast Services**

**To Serve Diverse **
**Customer Base **
**e.g., National Association of **
**State Energy Officials,**
**Emergency Managers, Water Resource Agencies, ...**

- NCEP

- Prediction is now inherently linked to numerical models

## Model Dependencies:

**They all start with global observing network**

**Global**
**Forecast **
**System**

-   Climate
-   Forecast
-   System

- NOAH Land Surface Model

- Dispersion

- Air Quality

- Basis for How Predictions are Made

- Aviation
- Hourly Forecast

**G**
**L**
**O**
**B**
**A**
**L**

**D**
**A**
**T**
**A**

**Ocean**

- Ocean

**North American**
** ****Mesoscale Model**
**(NAM)**

**Ocean**

- Short-Range
- Ensemble

**Medium **
**Range**
**Ensemble**
**(NAEFS)**

- Severe Weather

**Hurricane WRF**

**Hurricane/GFDL**

- HYCOM
- Ocean

## Importance of Global Observations

- Global                                                   observations
- Oceans
- Atmosphere
- Land
- Cryosphere
- Global Observing Network is essential for all short to medium range forecasts

- 1 Day

- 5-7 Days

- 5-7 Days

- 2-4 Days

- 5-7 Days

- 2-4 Days

## The Environmental Forecast Process

- Observations

- Analysis

- Model Forecast

- Post-processed Model Data

- Forecaster

- User (public, industry...)

- Numerical
- Forecast
- System

- Data
- Assimilation

- Observations , Analysis and Modeling Systems are now Linked

- Has implications for how to apply CAL/VAL to future instruments

## Forecast Performance

## Record

**Record**
**Value**

**Record**
**Improvement**

## Reasons Behind Improvements

- Began using satellite radiances in 94-95
- Began using “raw” radiances (as opposed to cloud-cleared) 98-99
- Other improvement  due to a balance among
- Observations
- Data Assimilation & Model technology
- Computing resources
- Estimated 30-40% of improvement from observations (principally global LEO satellite data) and 60-70% from data assimilation and modeling techniques and computing resources

## NHC Atlantic 72 hr Track Forecast Errors

**NHC Atlantic 72 hr Track Forecast Errors**

**Advances Related**
**To USWRP**

**Major Upgrades in Global and**
**Hurricane Numerical models**

## 2006 UPGRADES  SHOULD PROVIDE SIGNIFCIANTLY  BETTER INTENSITY PREDICTION

## Comms 

- 2001

- 2002

- 2003

- 2004

- 2005

**Comms **
**Upgrade**

- 2006

**Notes:**
The data points for the Cray operations in Suitland are typical for the entire life of the system.  

When the J90 backup operations were in place, additional products were being delivered to the NWS Telecommunications gateway from backup operations at OSO.  Those backup products were not included in these statistics.  This summary only covers products delivered from NCEP directly.

Even after the IBM SP became operational in Bowie, data ingest and product generation continued on the Cray J90s in Suitland.  May 2000 is the first full month with no dependency on the Suitland complex.

Operations on the IBM SP has been extremely stable.  Product Delivery in December achieved its highest level, with 98.7% of products delivered on time.  Note the dramatic improvement in OOS retrieval of products from the Phase II system.

## Path Forward:Joint Center for Satellite Data Assimilation

## JCSDA Mission and Vision

- Mission:  To accelerate and improve the quantitative use of research and operational satellite data in weather, ocean, climate and environmental analysis and prediction systems
- Vision:  A weather, ocean, climate and environmental analysis and prediction community empowered to effectively use increasing amounts of advanced satellite observations

## The Joint Center for Satellite Data Assimilation

- Formed in 2001
- Infrastructure for real-time access to operational and research satellite data from GOES, AMSU, Quikscat, AIRS, MODIS, COSMIC, WINDSAT,...
- Community fast forward radiative transfer scheme ... operational data assimilation and model forecast systems available to research and forecast communities
- NASA/GFSC and NOAA working on identical data assimilation system
- Supports “internal” and “external research” and data assessments on NOAA/NCEP computers

- The Research Community is now using the operational infrastructure.

- The Operational Community is now accelerating use of satellite data.

**Notes:**
Good morning! It’s a plsre tbh. Prvldge t attnd JCSDA SWG  mting worg by  FW deputy director of Joint Center and excon by SL NWS/EMC director, dep. Director. Mting credit to three managing the joint center program. Mtg provides Op to talk on roadmap despit being here for 4wd. .. premier 

During the last couple of years, with strong supports from all upper-level management, satellite data assimilation activities within NOAA/NASA have been gradually consolidated into a joint center program. This program will be soon of national and international visibility. Its success will mean a lot to all of us. Its ultimate outcomes would be many and much improved weather and climate prediction skills. 

A few months ago, I gave a brief at NESDIS front office on Joint center program plan. Since then, we have made a quite advances in many areas. It is about time to report to you again.   
Plsre tbh, plsre t att. JCSDA SW wo and r by FW & SL. Clarified MI Made aw of M Ach to date. Hpe to contr   Backgrnd bal vw.      

## JCSDA Roadmap

***Convene a series of workshops to train the next generation of satellite data assimilation experts***
***Support university attempts to enhance data assimilation curricula***

***Enhance Community Radiative Transfer Model to include radiative transfer for clouds and precipitation***
***Develop assimilation system for clouds and precipitation***

***Optimize utilization of hyperspectral observations***
***Exploit capabilities of research satellite instruments and observations***
***Develop and assess wind lidar assimilation methods***
***Assess and Implement operationally GPS Radio Occultation data (i.e., COSMIC)***
***Perform observing system simulation experiments***

***Advance the science of data assimilation using weather, climate, ocean atmospheric, chemistry, and air quality models; implement four-dimensional data assimilation***

***Build on heritage of AIRS to prepare for the assimilation of IASI, NPP (i.e., CrIS, ATMS), NPOESS and GOES-R***

***Advance common data assimilation infrastructure***
***Assimilate current  satellite data,***
***(SSMIS, WindSat, full MODIS and AIRS, etc.)***

## Working Off The Roadmap

- Began development of a common assimilation infrastructure at NOAA and NASA
- Began development of a common NOAA/NASA land data assimilation system
- Interfaces established between JCSDA, numerical models and external researchers
- Implemented significant enhancements to the Community Radiative Transfer Model (CRTM)
- Improved snow/sea ice emissivity model; permits 300% increase in sounding data usage over high latitudes; improved polar forecasts
- AIRS radiances and MODIS polar winds have been implemented with significantly improved operational forecasts
- Preparing for COSMIC implementation; Q3 implementation planned, one year after launch
- Jason altimeter data are being tested in the NCEP global ocean data assimilation system
- JCSDA Federally Funded Opportunity (FFO) Program is paying off:  For example, improved data assimilation physics for stratospheric ozone has been implemented operationally as a result of a grant awarded to NRL (McCormack, PI); improvements such as “Optimal Spectral Selection” have been implemented operationally in the CRTM as a result of a contract awarded to AER  (Moncet, PI)

## AIRS Data Usage per Six Hourly Analysis Cycle

**AIRS data coverage at 06 UTC on 31 January 2004. (Obs-Calc. Brightness Temperatures at 661.8 cm****-1 ****are shown) **

| 
Data Category | Number of AIRS Channels |
| --- | --- |
| Total Data Input to Analysis
Data Selected for Possible Use
Data Used in 3D VAR Analysis(Clear Radiances) | ~200x106 radiances (channels) 
~2.1x106 radiances (channels)
~0.85x106 radiances (channels) |

**AIRS Data Usage per Six Hourly Analysis Cycle**

## Figure 1(b). 500hPa Z Anomaly Correlations for the GFS with (Ops.+AIRS) and without (Ops.) AIRS data,  Southern hemisphere, January 2004

**Figure 1(b). 500hPa Z Anomaly Correlations for the GFS with (Ops.+AIRS) and without (Ops.) AIRS data,  Southern hemisphere, January 2004**

## Figure 3(b). 500hPa Z Anomaly Correlations for the GFS with (Ops.+AIRS) and without (Ops.) AIRS data,  Northern hemisphere, January 2004

**Figure 3(b). 500hPa Z Anomaly Correlations for the GFS with (Ops.+AIRS) and without (Ops.) AIRS data,  Northern hemisphere, January 2004**

## Future

## Future Considerations

- JCSDA Mission: Accelerate and improve the    quantitative use of research and operational satellite data in weather and climate analysis     and prediction models
- Success requires a balance among:
- Observations
- Science (e.g., emissivity issues, data assimilation, ...)
- Computer capacity

## Five Order of Magnitude Increases in SatelliteData Over Ten Years (2000-2010)

- Selected = Observations selected as suitable for use (cloud free, ...)*
- Assimilated = Observations actually assimilated into models

- Five Order of Magnitude Increases in SatelliteData Over Ten Years (2000-2010)

- Count (Millions)

**Daily Satellite & **
**Radar Observation Count**

- 2000

- 1990

- 2010

**100 M obs**

**125 M obs**

**Level 2 Radar**

**239 M obs**

- Satellite Data Ingest

- Received Data

**Daily Percentage of Data**
**Ingested into Models**

- Selected Data

**100%**

**7%**

- Assimilated Data

**239.5M**

**17.3M**

**5.2M**

**2%**

- *2006 Data

- 3

- *Science, data resolution, computer issues,... need to be addressed

## Accelerating the Use of Satellite Data

- Data use/ sensitivity issues over land, ice, snow
- Have to think in terms of a new CAL/VAL paradigm. Can’t separate data from model as part of the CAL/VAL step. The operational modeling community and JCSDA need the data immediately after launch.
- It is not just “R2O”    It is also “O2R”.  The research community should make better use of the unique operational infrastructure (data, data assimilation, modeling, ...).
- Speed of delivery is most crucial issue – The NPOESS data delivery requirement set at 28 minutes is an incredibly important advancement.
- Important issue facing us:  computer capacity does not match existing and planned needs for research, transition and operational steps.
- The transition process itself needs to be fixed – the time is now for resurrecting the NASA/NOAA Operational Satellite Improvement Program (OSIP) for LEO and especially GEO

## LEO - GEO

- “Balanced”  approach
- Successful application of satellites for global observations and weather prediction dictates need for geostationary sounder with 30 minute to one hour temporal resolution
- Risk reduction!
- Instrument development      Research      transition      operations demands an OSIP process and NASA research leadership

## Balance is needed among observations, modeling and computational power
All predictions depend on a Global Observing System 
The Global Observing System is increasingly dominated by satellite observations (research and operations)
Getting ready for NPOESS:  must prepare for
Increased data accuracy (high spectral and spatial resolution)
Increased volume of data
Improved CAL/VAL process to insure accelerated use of data
Sustaining the timeliness of operational products and services
Improved data assimilation and model prediction systems to ingest and use all satellite data in real time for a total Earth System
To be ready for NPOESS: A successful JCSDA
To succeed in the total transition process for LEO and GEO:  need to resurrect OSIP

- All predictions depend on a Global Observing System
- The Global Observing System is increasingly dominated by satellite observations (research and operations)
- Getting ready for NPOESS:  must prepare for
- Increased data accuracy (high spectral and spatial resolution)
- Increased volume of data
- Improved CAL/VAL process to insure accelerated use of data
- Sustaining the timeliness of operational products and services
- Improved data assimilation and model prediction systems to ingest and use all satellite data in real time for a total Earth System
- To be ready for NPOESS: A successful JCSDA
- To succeed in the total transition process for LEO and GEO:  need to resurrect OSIP

- Summary

## Appendix

## Computing Capability

- Receives Over 239 Million Global Observations Daily
- Sustained Computational Speed:  1.485 Trillion Calculations/Sec
- Generates More Than 14.8 Million Model Fields Each Day
- 6 million of which are derived from the global ensemble
- Global Models (Weather, Ocean, Climate)
- Regional Models (Aviation, Severe Weather, Fire Weather)
- Hazards Models (Hurricane, Volcanic Ash, Dispersion)
- Backup located in Fairmont, WV
- 3x upgrade scheduled to be operational January 23, 2007

***Commissioned/Operational IBM Supercomputer in Gaithersburg, MD (June 6, 2003)***

**Primary Weather ****	****$13.9 M**
**Primary Climate ****	****$5.3 M**
**Backup ****	****	****$7.2 M**
**Total:   ****	****	****$26.4 M**

## Satellite data used operationally 

**Satellite data used operationally **
**within the NCEP Global Forecast System (2007)**

| AIRS sounder radiances
HIRS sounder radiances
AMSU-A sounder radiances
AMSU-B sounder radiances
MODIS polar winds
GOES sounder radiances
GOES, Meteosat, GMS winds
GOES precipitation rate
SSM/I ocean surface wind speeds
SSM/I precipitation rates | TRMM precipitation rates 
ERS-2 ocean surface wind vectors
Quikscat ocean surface wind vectors
AVHRR SST
AVHRR vegetation fraction
AVHRR surface type
Multi-satellite snow cover
Multi-satellite sea ice
SBUV/2 ozone profile and total ozone
 |
| --- | --- |

## North American Model (NAM) NMM 

- Total precip from 06z cycle 12/20/06
- North American Model (NAM) NMM

## “Sometimes our profession has a big success...we saw a major one this week. As you know, a devastating windstorm struck the Northwest late Thursday/early Friday.  Winds reached 80-90 mph in places with 70 knot gusts common place.  Over a million customers lost power...The forecasts were nearly perfect.  4-5 days out the GFS clearly showed the threat and for the several days before the storm hit, both the GFS and the NAM consistently showed the correct evolution and storm intensity...this is as good as it gets... excellent model runs, NWS waiting until they were sure and hitting the warnings well before the event, population and media acknowledging we got it right on a critical and major event... To get a storm this well so far in advance is clear evidence that what you are doing to improve data assimilation over the ocean using satellite assets is really paying off.” – Professor Clifford Mass, Dept. of Atmospheric Sciences, U. of Washington, 12/17/06

- “Sometimes our profession has a big success...we saw a major one this week. As you know, a devastating windstorm struck the Northwest late Thursday/early Friday.  Winds reached 80-90 mph in places with 70 knot gusts common place.  Over a million customers lost power...The forecasts were nearly perfect.  4-5 days out the GFS clearly showed the threat and for the several days before the storm hit, both the GFS and the NAM consistently showed the correct evolution and storm intensity...this is as good as it gets... excellent model runs, NWS waiting until they were sure and hitting the warnings well before the event, population and media acknowledging we got it right on a critical and major event... To get a storm this well so far in advance is clear evidence that what you are doing to improve data assimilation over the ocean using satellite assets is really paying off.” – **Professor Clifford Mass, Dept. of Atmospheric Sciences, U. of Washington, 12/17/06**