# Presentation: 928227

## NOAA-18 Instrument Calibration and Validation Briefing  

- NOAA/NESDIS/Office of Research and Applications
- As of the Week of June 27, 2005
- For archived activities and latest news, please visit
- http://www.orbit.nesdis.noaa.gov/smcd/spb/n18calval

## Weekly Highlights (June 27-July1)

- HIRS
- HIRS noises remain fluctuating
- Noises for all LW channels tend to be coherent
- ORA recommended ITT to examine the source for generating these noise (e.g. clamp system)
- AMSU-A geolocation errors
- A2 is off less than 0.7 MHS scanline along track and 0.36 MHS FOVs across track
- A1 display 2-3 K cross-track asymmetry
- MHS
- MHS is off by about one scanline along track

## NOAA-18 Instrument Payload

- AVHRR/4 Advanced Very High Resolution Radiometer
- HIRS/4 High Resolution Infrared Sounder
- AMSU-A Advanced Microwave Sounding Unit-A
- MHS Microwave Humidity Sounder
- SBUV/2 Solar Backscattered Ultraviolet Radiometer

**We focus on these instruments:**

## Calibration and Validation Legend 

- PRT:  Platinum Resistance Thermometers
- NEDN/T: Noise Equivalent Delta Radiance/Temperature
- ATOVS: Advanced TIROS Operational Vertical Sounder (TOVS)
- TOAST: Total Ozone Analysis using SBUV/2 and TOVS
- MSPPS: Microwave Surface and Precipitation Product System
- NDVI: Normalized Difference Vegetation Index
- SST: Sea Surface Temperature
- UV: Ultraviolet
- TPW: Total Precipitable Water
- CLW: Cloud Liquid Water

## ORA NOAA-18 Instrument Cal/Val Mission Goals

- Monitor and improve NOAA-18 instrument post-launch calibration
- Assess and quantify instrument noises though analyzing calibration target counts and channel measurements
- Monitor possible instrument  anomaly and provide recommended solution
- Quantify satellite geolocation errors
- Characterize other biases in radiance and products such as cross-track asymmetry through forward modeling and inter-satellite calibration
- Validate NESDIS NOAA-18 products (ATOVS and MSPPS, TOAST, UV index, NDVI, SST) for operational implementation
- Provide early demonstration and assessments of NOAA-18 data for improving numerical weather prediction through JCSDA

## Our Team  

- Mitch Goldberg: ORA/SMCD Division Chief, - Management and Technical Oversight
- Fuzhong Weng: ORA/SMCD/Sensor Physics Branch Chief and NOAA-18 cal/val team leader, instrument asymmetry and microwave products and algorithms, radiance bias assessments for NWP model applications
- Changyong Cao: HIRS instrument calibration
- Fred Wu: AVHRR VIS/IR instrument calibration
- Tsan Mo: AMSU/MHS instrument calibration
- Jerry Sullivan: AVHRR thermal channel calibration/ NDVI validation
- Tony Reale: HIRS/AMSU/MHS sounding channel/products validation
- Mike Chalfant: HIRS/AMSU/MHS sounding channel/products validation /geolocation
- Ralph Ferraro: AMSU/MHS window channels/MSPPS products validation
- Larry Flynn: SBUV product validation
- Tom Kleespies: AMSU on-orbit verification
- Hank Drahos: Sounding product validation
- Dan Tarpley: AVHRR product NDVI monitoring
- John LeMashall:  Impacts assessments of NOAA-18 data for NWP applications

## An important signature of the NOAA-18/HIRS noise found in DDS1 (Dwell Data Set 1)

- Description of the NOAA-18/HIRS noise problem:
- 	For each LW channel, the count jumps from one FOV to the next significantly, and almost randomly, regardless of SV, IWT, or EV.
- Despite the randomness of the count variation from one FOV to the next for a given channel, the count for one channel can be calculated from another channel with a linear function with small residuals. This is a distinct signature (more like a signal than a noise).
- This signature has the following characteristics:
- 	1). For a given FOV, the volt/count for ch1-12 must always go up or down in tandem, and in linear proportion
- 	2). Between FOVs, they jump up and down together, dramatically, and randomly (or somewhat randomly).

- 56 samples for all 12 channels

- Unexpected correlation between ch1 and ch11

- Space dwell data 300 scanlines, June 9, 2005

## Time Sequence and Channel Correlation Analysis

- For each HIRS FOV cycle,
- 	dVch = Vch – V0,
- 		Where dVch = delta volt for a channel
- 		 Vch = volt for a channel
- 		ch = 1, 2, 3, 4, 11, 7, 8, 10, 6, 5, 12, 9 (in order)
- 		 V0 = value for the clamp target, which is set once for each cycle (every 0.1 sec, or one rotation of the filterwheel).
- Unlike a FPA based system, a filterwheel based radiometer such as HIRS generates each channel for an FOV separately, one at a time with the rotation of the filterwheel.  It is very difficult to get signals that are correlated across channels at all times.
- Very few places in the instrument can produce this signature. Possibilities:
- Clamp system and related circuit.
- Clamp system itself
- Interference of the clamp system or through the clamp system (many possible freqs. ).
- Other possibilities: must be able to produce this signature, which is difficult.

- HIRS filterwheel (inner ring for LW channels)

- Clamp target

- V0

- Vch

## Update from DDS3(Dwell Data Set 3)

- The magnitude of the noise has come down significantly since DDS1. As expected, this signature becomes weaker relative to the  random noise which attenuated the correlation.
- Two groups of correlation emerged, which were not apparent in DDS1 (or perhaps overshadowed by the strong correlation among all channels).
- Group 1: ch 1, 2, 3, 4, 11, and 7.
- Group 2: ch 5, 6, 7, 8, 9, 10, 12
- Note: ch 11 is weakly correlated with both groups

- Group1
- Ex: ch 2 vs. ch5

- Group 2
- Ex: ch6 vs. ch5

- Ch2 vs. ch5 correlation disappeared

## Relationship to Frequency Analysis

- For a given channel, the jump from one FOV to the next (0.1 sec or 10 Hz) appears to be random (more so in recent data).
- May not show on the Fourier spectrum (Fourier transform of a random function)
- External interference with different freq.: The signature is more likely to be generated if it is a disturbance through the clamp system
- Direct interference on individual channels will require both specific frequency (such as 10 Hz) and synchronization with 10 Hz, which is difficult to sustain.

## AMSU Cal/Val News 

- AMSU-A geo-location and co-registration are investigated by Tom Kleespies (ORA) and Ralf Bennartz (UWisc)
- Accurate FOV matching through Back-Gilbert convolution
-  A2 is off less than 0.7 MHS scanline along track and 0.36 MHS FOVs across track
- AMSU-A cross-track asymmetry
- Global simulated brightness temperatures using JCSDA CRTM and NCEP GDAS outputs
- A1 displays larger than expected cross-track asymmetry

## AMSU Navigation  Study 

## AMSU-A1 Asymmetry 

**Shown are the NOAA-18 AMSU-A window channel asymmetry characterized by the differences****between observed and simulated brightness temperatures. NOAA-18 AMSU-A1 module displays much **
**larger cross-track asymmetry than previous AMSU-A1 and will impact sounding products. **