report on viirs / cris participation paul menzel march 2002
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Report on VIIRS / CrIS Participation Paul Menzel March 2002 With Jeff Key, Steve Ackerman, Richard Frey, Eva Borbas, Youri Plokhenko, Kathy Strabala, Graeme Stephens. Raised concerns about VIIRS spectral selection Jan 01. VIIRS , MODIS , FY-1C , AVHRR. CO2. O2. O3. H2O. O2. H2O. - PowerPoint PPT PresentationTRANSCRIPT
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]
Tem
pera
tre [K
]
0.25
0.75
1.25
1.75
2.25
2.75
10
15
20
25
30
50
60
70
85
100
115
135
150
200
250
300
350
400
430
470
500
570
620
670
700
780
850
925
950
1000
First guess (forecast)
Estimate with reflection
Estimate without reflection
Spatial smoothness of temperature estimate
Standard deviation of second spatial derivative [* 100 km*km ]
Pressure [mb]
Tem
era
tu
re [K
]
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
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85
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925
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Estimate without reflection
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
0.8
0.8
1.0
1.0
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
0
20
40
60
80
100
-90 -60 -30 0 30 60 90
Latitude
Pe
rce
nt
VI I RS
MODI S
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
0
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-90 -60 -30 0 30 60 90
Latitude
Per
cent VI I RS
MODI S
VI I RS+B27
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.