# Presentation: 371585

## Adaptive Use of AQUA Brightness Temperatures in Winter Storm Reconnaissance Case Studies

- Lacey Holland and Zoltan Toth
- Ackn.: Russ Treadon, Stephen Lord,
- Lars-Peter Riishojgaard

## Motivation

- Currently, computationally expensive to include all AIRS data in the GFS
- Try to mitigate the effects by including a smaller subset of the data over ‘sensitive’ areas determined during the Winter Storm Reconnaissance (WSR) program
- Why WSR?
- Already operational (since 2001)
- Geared toward improving forecasts of significant winter weather by determining where to place additional observations
- Most years show improvement in 60-80% of cases targeted

## How the impact of AIRS was evaluated

- CASE SELECTION
- 7 Cases selected from Winter Storm Reconnaissance (WSR) program during 2003
- Forecasts with high RMSE for given lead time chosen
- DATA SELECTION
- AIRS data assimilated only in locations identified as having the most potential for forecast improvement as determined through WSR (areas containing 90% or more of maximum sens. value)
- Somewhat larger area covered by the AIRS data compared to WSR dropsonde coverage
- EVALUATION
- Impact tested by comparing two forecast/analysis GFS cycles (T126L28), identical except that one contains AIRS data while the other does not
- Control has all operationally available data (including WSR dropsondes)

## Data Impact of AIRS on 500 hPa Temperature (top left),

- IR Satellite Image (top right), and estimated sensitivity (left) for 18 Feb 2003 at 00 UTC

- Light purple shading indicates AIRS data selection
- Violet squares indicate dropsonde locations
- Red ellipse shows verification region

- Impact outside the targeted areas is due to small differences between the first guess forecasts.  Sensitive areas show no data impact due to cloud coverage.

**Notes:**
"Impact outside purple targeted areas is due to small differences between first guess forecasts"); also, state the obvious - "Sensitive areas show no data impact due to cloud coverage" 

## Improved/Neutral/Degraded classification based on RMSE of forecasts verified against raobs over WSR pre-defined verification area

| SFC. PRES.
(based on RMSE) | AIRS + drops vs. drops only | Drops vs. no drops |
| --- | --- | --- |
| Improved | 0 | 4 |
| Neutral | 3 | 2 |
| Degraded | 4 | 1 |

| TEMP 
(1000-250 hPa) | AIRS + drops vs. drops only | Drops vs. no drops |
| --- | --- | --- |
| Improved | 1 | 3 |
| Neutral | 5 | 2 |
| Degraded | 1 | 2 |

| VECTOR WIND (1000-250 hPa) | AIRS + drops | Drops vs. no drops |
| --- | --- | --- |
| Improved | 1 | 1 |
| Neutral | 3 | 1 |
| Degraded | 3 | 5 |

| SPECIFIC HUMIDITY (1000-250 hPa) | AIRS + drops vs. drops only | Drops only vs. no drops |
| --- | --- | --- |
| Improved | 6 | 4 |
| Neutral | 1 | 1 |
| Degraded | 0 | 2 |

## Overall impact of AIRS on WSR forecasts

| OVERALL | AIRS + drops vs. drops only | Drops vs. no drops |
| --- | --- | --- |
| Improved | 2 | 4 |
| Neutral | 1 | 0 |
| Degraded | 4 | 3 |

-   determined by comparing the number of fields (temperature, vector wind, humidity between 1000-250 hPa as well as sfc pressure) that were improved or degraded for each case

-  While the addition of dropsondes shows a slight positive impact, the addition of AIRS data has no overall benefit

## Summary and Future Work

- Used codes and scripts implemented in NCEP operations (WSR, AIRS)
- Performed case studies using AIRS data over sensitive areas
- Largely neutral impact
- In future:
- further expand coverage of sensitive areas included
- Expand out to 80-75% max value of sensitive regions
- Expand area based on forecast lead time (larger areas for longer lead times)
- Other impact studies

**Notes:**
Other impact studies = AMSU-A; impact without dropsondes, but including AIRS, and without AIRS or dropsondes;

## BACKGROUND

## AIRS Related Data Assimilation Work with the NCEP GDAS

- Russ Treadon, Stacie Bender, John Derber
- Ackn.: Stephen Lord

## Operational processing 
ingest:  12 UTC, 16 September 2003 
dump:  12 UTC, 13 April 2004
Global analysis code (SSI)
more accurate & efficient OPTRAN
modify quality control for cloudy IR radiances
more flexible horizontal thinning and weighting* (* not yet in operational SSI)

- ingest:  12 UTC, 16 September 2003
- dump:  12 UTC, 13 April 2004
- Global analysis code (SSI)
- more accurate & efficient OPTRAN
- modify quality control for cloudy IR radiances
- more flexible horizontal thinning and weighting* (* not yet in operational SSI)

- Project Status at NCEP

## Non-operational monitoring/assimilation
near real-time monitoring via global parallel
(wwwt.emc.ncep.noaa.gov/gmb/gdas/radiance/prx)
impact studies ongoing
AQUA AMSU:  neutral forecast/analysis impact
Operational monitoring/assimilation
increase SSI wall clock time
5 minutes longer for AQUA monitoring
8 minutes longer for AQUA assimilation
implementation to follow NCEP CCS upgrade
	(CCS = Central Computer System)

- near real-time monitoring via global parallel
- (wwwt.emc.ncep.noaa.gov/gmb/gdas/radiance/prx)
- impact studies ongoing
- AQUA AMSU:  neutral forecast/analysis impact
- Operational monitoring/assimilation
- increase SSI wall clock time
- 5 minutes longer for AQUA monitoring
- 8 minutes longer for AQUA assimilation
- implementation to follow NCEP CCS upgrade
- 	(CCS = _*C*_entral _*C*_omputer _*S*_ystem)

- Project Status at NCEP

## conservative detection of IR cloudy radiances
examine sensitivity, Tb, of simulated Tb to presence of cloud
those channels for which Tb exceeds an empirical threshold are not assimilated

- examine sensitivity, Tb, of simulated Tb to presence of cloud
- those channels for which Tb exceeds an empirical threshold are not assimilated

- SSI modifications

## more flexible horizontal thinning/weighting
account for sensors measuring similar quantities
specify sensor groupings (all IR, all AMSU-A, etc)
specify relative weighting for sensors within group

- account for sensors measuring similar quantities
- specify sensor groupings (all IR, all AMSU-A, etc)
- specify relative weighting for sensors within group

- SSI modifications

## Ongoing/Future work

- Continue offline Global Data Assimilation System runs
- add AQUA AIRS
- add AQUA AIRS and AMSU-A
- replace NOAA-16 HIRS/3 & AMSU-A with AQUA AIRS & AMSU-A
- Upgrade SSI code
- implement improved thinning/weighting of Tb
- Operational AQUA monitoring/assimilation
- await NCEP CCS upgrade