Report on VIIRS / CrIS Participation

Paul MenzelMarch 2002

With Jeff Key, Steve Ackerman, Richard Frey,Eva Borbas, Youri Plokhenko, Kathy Strabala, Graeme Stephens

Raised concerns about VIIRS spectral selectionJan 01

VIIRS, MODIS, FY-1C, AVHRR

H2O

H2OH2O

H2O

O2

CO2

CO2

H2O

O2

O3

H2O

O2

Earth emitted spectra overlaid on Planck function envelopes

MODIS

VIIRS

Issues

1. No channels are sensitive to CO22. No channels are sensitive to UTH3. No channel pairs can detect low level T inversion,

since all channels view surface

Suggested Changes

1. Consider 1.88 instead of 1.38 um (better for separating high thin clouds from snow in polar regions)

2. Add 6.7 um (can detect inversion in polar regions to help identify clear from cloud, UTH also)

3. Add noisy 13.3 and 13.6 um channels (CO2 slicing for high thin clouds, helps CrISwith cloud clearing)

Highlighted VIIRS problems with semi-transparent cloudsFeb 01

VIIRS needs an absorbing channel for accurate Cloud Height Determination

For semi-transparent clouds (N<1 or E<1) IRW window underestimates height by 300 to 400 hPa

Semi-transparent clouds occur in 45% of HIRS obs, 50% of MODIS obs

Height correction algorithms include CO2 slicing or H2O intercept technique

GOES and MSG demonstrated H2O semi-transparency correctionto assign cirrus to correct cloud height

Cloud height EDR will not be met with current VIIRS for more than half of the cloud observations

clouds are found in 75% of all observations (they cover about 69% of 65N to 65S)global preponderance of semi-transparent clouds (about 45%)

ITCZ shows high frequency of cirrus (greater than 50%)more cirrus in summer than winter in each hemisphere

H2O Intercept and CO2 slicing compare reasonably well

IRW, CO2, and H2O height assignments for clouds using VAS from 20 to 50N and 50 to 100W for 29-31 Jan 92 (199 cases)

__________________________________________________All Mean CTP Scatter wrt RMS Deviation (hPa)

(hPa) Mean (hPa) wrt CO2 wrt H2OIRW 416 102 109 141CO2 344 87 -- 85H2O 314 65 85 --__________________________________________________

Nieman et al., 1993: JAM, 32, 1559-1568

Studying effects of surface reflection on IR soundings over landFeb 01

Temperature estimate statistics

Average absolute difference (estimate VS RAOB)

Pressure [mb]

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tre [K

]

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Estimate with reflection

Estimate without reflection

Spatial smoothness of temperature estimate

Standard deviation of second spatial derivative [* 100 km*km ]

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Estimate with reflection

First guess (forecast)

Spatial smoothness of temperature solution with and wo sfc reflection standard deviation of second spatial derivative ( multiplied by 100 * km * km)

Average absolute temp diff (solution with and wo sfc reflection vs raobs)

LW & SW emissivity estimated with RT model & GOES Obs on 06/01/00 at 10 UTC

LW

SW

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Made the case for a H2O channel on VIIRSMar 2001

VIIRS needs a water vapor channel for

Fine scale WV depictionExperience with MODIS has revealed fine scale moisture details that are important for global PW understanding (GWEX)

* continuity of these data will be important

Cloud identificationHIRS and MODIS reveal polar winter cloudy vs clear skies by searching for inversions

* forty percent of polar night is clear but thought to be cloudy without WV channel

Cloud Height determinationGOES and MSG demonstrated semi-transparency correctionto assign cirrus to correct cloud height

* avoid IRW mistakes of 300 - 400 hPa

Polar Wind trackingMODIS loops reveal opportunity for improved polar winds

* fills a global observing system hole for NWP

Cloud clearing within CrIS FOVMODIS-AIRS will be demonstrating cloud clearing of high spectral resolution sounder with high spatial resolution imager

* UTH and cloud clearing for CrIS is improved

MODIS 1 km resolution reveals fine-scale structure

IRW-WV channels

combine to detect polar inversions

BT6.7 (sees mid-trop) is warmer than

BT11 (sees sfc)

BT11-BT6.7 (from HIRS)

versus strength of temperature

inversion (from raobs)

Ackerman, 1996: Global satellite observations of negative brightness temperature differences between 11 and 6.7 um. JAM, 53, 2803-2812.

40% of HIRS obs for 1 - 5 Jul 2000 show inversions of > 5 C;these clear sky obs would be called cloudy without WV channel

% time BT11-BT6.7 < -10C Jun Jul

Aug Sep

Clouds Indicated by BT11-BT6.7 TestMODIS BT11 Image

MODIS 11 µm measurements from Antarctica near the South Pole 8 Sep 2000. Warmer temperatures are darker. Brightness temperatures vary from approximately 187K to 237K. Clear areas are lighter (colder).

Clouds are indicated in white. From the operational MODIS cloud mask algorithm. IRW test alone would have declared warmer temps clear; the opposite is true

Winds from MODIS: An Arctic ExampleWater vapor winds from MODIS for a case in the western Arctic. The wind vectors were derived

from a sequence of three images, each separated by 100 minutes.

Positive impact of two weeks of polar winds in ECMWF Fcst Model

Explored Advantage of 1.88 vs 1.38 um for Polar CirrusMar 01

MODIS 1.38 um channel is saturating over clear sky in Arctic

1.88 um clear sky reflectance would be less than 1.38 um

Clear sky and ice cloud contrast would be maintained

The case for 1.88 um channel on VIIRS

1.88 um band alleviates problems with cirrus detection over snow in very dry atmospheres, e.g., Antarctica. Advantages of 1.88 include (a) both new and old snow are darker at 1.88 than 1.38 um and (b) the 1.88 um MAS band gives better cloud mask results than the 1.38 um MODIS band.

While ice clouds are more absorbing at 1.88 um, the contrast between clear and cloudy reflectances, at least over snow, is similar. Thus for polar applications, if the same signal-to-noise ratio can be obtained as that specified for the 1.38 um band, it appears that it would be advantageous to replace the 1.38 um band with a 1.88 um band.

Identified VIIRS Polar Night Cloud Mask ProblemsDec 2001

VIIRS vs MODIS Cloud Mask Comparison

• VIIRS will not have .945, 6.7, or 13.9m bands– This affects:

• High thick cloud detection (6.7 and 13.9m threshold tests) especially over land at night.

• Polar cloud detection at night (11-6.7m BTDIF inversion test).

• Sunglint regions (less tests performed ).

• Daytime and Nighttime land - fewer groups can push result into different clear category (Cloud/Uncertain threshold is .67)

68.209.,59.209. 34

VIIRS sees too many clouds over Antarctica

MODIS Band 31MODIS Cloud mask VIIRS Cloud mask(No 11-6.5m test)

green – clear; white – cloud; red - uncertain

23:40 UTC 4 June 2001

MODIS and VIIRS Cloud Mask Results - Category: High Confident Cloud

Night Only - 4 June 2001

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What happens if you add back the 6.7 m band?

• VIIRS cloud mask looks very similar to the original MODIS cloud mask.

• Why? :• High thick clouds can now be found with a straight

6.7 m BT threshold test.

• Polar clouds are more accurately determined at night using 11-6.7m BTDIF inversion test.

• Sunglint regions will use 4 group tests instead of 3 -just as the MODIS cloud mask does.

MODIS and VIIRS cloud masks - Category: High Confident Cloud Night Only - 4 June 2001

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Cloud mask comparison: Polar Night - Antarctica

MODIS Band 31

MODIS Cloud mask

VIIRS Cloud mask(wo 11-6.7m test)

VIIRS Cloud mask(with 11-6.7m test)

23:40 UTC 4 June 2001

green – clear; white – cloud; red - uncertain

Assisted drafting NPP Cal / Val PlanNov 2001

Draft 

National Polar-orbiting Operational Environmental Satellite System [NPOESS]Preparatory Project [NPP]

 NPP

Calibration and Product ValidationPlan

  

December 30, 2001  

NATIONAL POLAR-ORBITING OPERATIONAL ENVIRONMENTAL SATELLITE SYSTEM (NPOESS)

INTEGRATED PROGRAM OFFICE 

and the 

NATIONAL AERONAUTICS AND SPACE ADMINISTRATION

Studying combined GPS and CrIS retrievalsDec 01

Temperature (K) Humidity (%) IR: HIRS CrIS

Simulation of GPS improvements (RMS) on 700 temperature (first column) and humidity (second) retrievals derived from HIRS/CrIS (IR), AMSU (MW) and surface data. Retrievals with AMSU (upper

panels) and without (lower panels) are shown. AMSU improvements on temperature retrievals (upper third panel). GPS + HIRS + AMSU (dashed line) and GPS+ CrIS + AMSU (solid line) bias

and RMS errors wrt RAOBS are shown as a reference in lower third panel.

Presented at 1st CHAMP Science Meeting, GFZ Potsdam, January 22-25, 2002 by Eva Borbas

Exploring sensitivity of CrIS radiances to CO2 amountsDec 01

In a wet atm changes to spectra for CO2 increase of 10 (red) and 20 (blue) ppm

In a dry atm changes to spectra for CO2 increase of 10 (red) and 20 (blue) ppm

From Engelen et al., 2001

(Right) Maximum level at any level in every temperature retrieved when CO2

is prescribed as a single monthly mean value. (Left) Zonal-height cross-section of the temperature retrieval errors when CO2 is prescribed as a single

monthly-global mean value

ProposalStephens, Kumer, Menzel

Carbon Dioxide measurements from an airborne spectrometer in support of operational temperature

soundings and the study of the Carbon Cycle.  Development of NPOESS Airborne CO2 Spectrometer System (NACOOSS) proposed for ER2 deployment to measure CO2 profiles and impact on NAST-I temperature and moisture retrievals.