GOES Imager IR Midnight Calibration Anomaly and Correction

Slides:



Advertisements
Similar presentations
10 th GSICS EXP Meeting, June , Geneva NOAA GPRC Report to the GSICS 10 th EXP 6-8 June 2011, Geneva, Switzerland.
Advertisements

Development of a Simulated Synthetic Natural Color ABI Product for GOES-R AQPG Hai Zhang UMBC 1/12/2012 GOES-R AQPG workshop.
Statistics Measures of Regression and Prediction Intervals.
1 Weekly Report on GOES-14 PLT Science Test NOAA / NESDIS / STAR X. Wu, G. Rancic, F. Yu December 18, 2009.
Where m is the first order gain, q is the second order gain, is the observed blackbody counts, is the observed space counts, is the radiance of the blackbody,
GOES-14 PLT Weekly Report Fangfang Yu Gordana Rancic 12/31/2009.
Assessment of GOES Imager Infrared Radiometric Calibration Accuracy toward Long-term Climate Data Record Fangfang Yu 1*, Xiangqian Wu 2, Scott Lindstrom.
Development and evaluation of Passive Microwave SWE retrieval equations for mountainous area Naoki Mizukami.
Abstract The Advanced Baseline Imager (ABI) instrument onboard the GOES-R series satellites, which is expected to be launched in the year 2014, has considerable.
THE NOAA SSU STRATOSPHERIC TEMPERATURE CLIMATE DATA RECORD Cheng-Zhi Zou NOAA/NESDIS/Center For Satellite Applications and Research Haifeng Qian, Lilong.
An assessment of the NRLMSISE-00 density thermosphere description in presence of space weather events C. Lathuillère and M. Menvielle The data and the.
LECTURE 3: ANALYSIS OF EXPERIMENTAL DATA
Ozone time series and trends Various groups compute trends in different ways. One goal of the workshop is to be able to compare time series and trends.
Radiative transfer in the thermal infrared and the surface source term
P1.56 Seasonal, Diurnal, and Weather Related Variations of Clear Sky Land Surface Temperature: A Statistical Assessment K. Y. Vinnikov (University of Maryland,
The MODIS SST hypercube is a multi-dimensional look up table of SST retrieval uncertainty, bias and standard deviation, determined from comprehensive analysis.
NASA, CGMS-44, 7 June 2016 Coordination Group for Meteorological Satellites - CGMS LIMB CORRECTION OF POLAR- ORBITING IMAGERY FOR THE IMPROVED INTERPRETATION.
JMA Report 24 Mar 2009 Yoshihiko Tahara Incorrect RMA equation reported in the January meeting GSICS correction for MTSAT –Don’t we need standard GSICS.
Characterizing Diurnal Calibration Variations using Double-Differences Fangfang Yu.
Bias analysis and correction for MetOp/AVHRR IR channel using AVHRR-IASI inter-comparison Tiejun Chang and Xiangqian Wu GSICS Joint Research and data Working.
JMA GPRC report Arata OKUYAMA Meteorological Satellite Center,
Regression and Correlation of Data Summary
GSICS Inter-Calibration for Infrared Bands with Hyperspectral Sounder
Fangfang Yu, Fuzhong Weng, Xiangqian Wu, and Ninghai Sun
Review of EUMETSAT’s GEO-LEO Correction
Report from KMA 17th GSICS Executive Panel, Biot, 2-3 June 2016
GPM Microwave Radiometer Vicarious Cold Calibration
Fangfang Yu and Xiangqian Wu
Fangfang Yu and Xiangqian Wu
Second GSICS Users’Workshop:
Fangfang Yu, Xiangqian Wu and Tom Stone
DCC inter-calibration of Himawari-8/AHI VNIR bands
GOES-16 ABI Lunar Data Preparation to GIRO
GOES-East DCC analysis
GOES Lunar Calibration
Fangfang Yu and Fred Wu 22 March 2011
Combining Vicarious Calibrations
AC-9/AC-S data analysis from CDOM Lab
Characterizing DCC as invariant calibration target
Practice Mid-Term Exam
User’s Expectations of GSICS
NOAA-KMA Collaboration on Imager Midnight IR Calibration Anomaly
AHI IR Tb bias variation diurnal & at low temperature
Diurnal and Seasonal variations of COMS IR inter-calibration
Elementary Statistics: Picturing The World
AP STATISTICS LESSON 3 – 3 (DAY 2)
NOAA/NESDIS/Center for Satellite Applications and Research
GEO-GEO products – diurnal variations
GOES Imager Lunar Calibration: Angular Variation of the Scan Mirror Visible Reflectivity Fangfang Yu (ERT, Xiangqian Wu(NOAA/NESDIS), Tom Stone(USGS),
Scatterplots and Correlation
Inter-satellite Calibration of HIRS OLR Time Series
KMA Agency Report NMSC/KMA
Fangfang Yu1 and Xiangqian Wu2
GOES DCC Deseasonalization & AHI DCC Calibration
Homework 4a: Trend Forecasting and Future Uncertainties
GRWG+GDWG Web Meeting on Calibration Change Alerts
Na Xu, Xiuqing Hu, Lin Chen, Min Min
SRF Retrieval Using VIIRS/AIRS/IASI radiances
Use of GSICS to Improve Operational Radiometric Calibration
Developing GSICS products for IR channels of GEO imagers Tim Hewison
Ch 4.1 & 4.2 Two dimensions concept
Inter-Comparison between COMS/MI and Himawari-8/AHI
Presentation of GSICS Inter-Calibration Results - Web Displays
goes-16/17 abi lunar calibration
Cal/Val-Related Activities at CICS
G16 ABI B07 Cold Scene Bias to IASI - Action: GIR j
G16 vs. G17 IR Inter-comparison: Some Experiences and Lessons from validation toward GEO-GEO Inter-calibration Fangfang Yu, Xiangqian Wu, Hyelim Yoo and.
Inter-calibration results of COMS/MI using with and without MBCC
Inter-calibration result of COMS/MI using before and after reprocessed CrIS data March 2019 Minju Gu and Dohyeong Kim.
Midnight calibration errors on MTSAT-2
Presentation transcript:

GOES Imager IR Midnight Calibration Anomaly and Correction Fangfang Yu, Xiangqian Wu, M. K. Rama Varma Raja and Haifeng Qian

Midnight calibration anomaly and correction Causes of Midnight calibration anomaly (Johnson et al. 1996) Extra radiation reflected by the non-unity emissivity of BB to the detectors, when the instrument is viewing the BB. Scattered solar radiation contamination at space view Most pronounced at pre-eclipse and post-eclipse around the equinox. Current operational remedy: midnight blackbody calibration correction (MBCC) (Johnson et al. 1996, Weinreb and Han 2003) non-perfect BB effect Contaminated SPLK effect Figure. Original calibration slopes of GOES-8 Imager Ch2 (from Johnson et al. 1996)

Diurnal Cal. Variation and MBCC Calibration Evaluation Time dependent Tb bias and the standard deviation (at 30 minute time bin), as well the onset frequency of MBCC application for the winter of 2008. (Yu et al. 2011)

MBCC correction residual Impact of one of MBCC slopes on the diurnal calibration variations, calculated using Equation 9. (mean Tb 1:30pm – Tb 1:30am). The results with high frequency of MBCC onset (>80%) are in bold-italic font. Channel name GOES11 - AIRS GOES12 -AIRS Winter Summer Ch3 0.12 0.13 - Ch4 0.49 0.48 Ch5 Ch6 0.04 -0.11 Efficiently and sufficiently applied at Ch2 When sufficiently applied, it can work efficiently at Ch3, Ch5 and Ch6 to reduce the Tb bias to less than 0.15K Even sufficiently applied, it works less efficiently at Ch4 with residual (mean Tb difference to the day-time data) of 0.5K bias. (Yu et al. 2011)

Time-dependent correction during the midnight effect time Calibration uncertainty Duration and amplitude vary at different IR channel Depends on the frequency of MBCC application Change with seasons Has seasonal long-term trending Time-series of Tb bias to AIRS at midnight time for GOES-11 Ch4 Evaluation of MBCC performance for each channel and in each month for GOES-11

Time-dependent correction during the midnight effect time Look up table for each month Binned at 30-minute interval: BB calibration interval Mean and standard deviation of the mean monthly Tb bias to AIRS/IASI at each half-hour bin. Linear calibration coefficients (a and b) at each half-hour bin Statistically at least 150 collocation pairs is needed to get reliable coefficients.

18:00 18:30 19:00 19:30 20:00 20:30 21:00 21:30 22:00 22:30 23:00 23:30 00:00 00:30 01:00 01:30 02:00 02:30 GOES-11 Ch4 03:00 03:30 04:00 04:30 05:00

Summary The MBCC works sufficiently at most IR channels except Ch4 when sufficiently applied, However, Only Ch2 is always sufficiently applied Large residual still remains at Ch4, even sufficiently applied The duration and amplitude of midnight calibration anomaly vary at different seasons at different IR channels Seasonal long-term trending Use the time-dependent correction (e.g. LUT table) derived from one month night-time collocation data binned at half-hour time interval: coincidently with BB calibration and MBCC application intervals Duration: ~10pm – ~04am Mean Tb bias/standard deviation and linear regression coefficients