Introduction to GSICS Mitch Goldberg (NOAA) For GSICS Executive Panel

Chief, Satellite Meteorology and Climatology Division Introduction to the Global Space-based Inter-Calibration System (GSICS) Mitchell D. Goldberg, GSICS Exec Panel Chair NOAA/NESDIS Chief, Satellite Meteorology and Climatology Division Mitch.Goldberg@noaa.gov 2 2

GSICS Mission To provide sustained calibration and validation of satellite observations To intercalibrate critical components of the global observing system to climate quality benchmark observations and/or reference sites To provide corrected observations and/or correction algorithms to the user community 3 3

Motivation Demanding applications require well calibrated and intercalibrated measurements Climate Data Records Radiance Assimilation in Numerical Weather Prediction Data Fusion Growing Global Observing System (GOS) Intercalibration of instruments achieves comparability of measurements from different instruments 4 4

Space-Based component of the Global Observing System (GOS) 5 Intercalibration of instruments achieves comparability of measurements from different instruments 5

POES intercalibration Simultaneous Nadir Overpass (SNO) Method -a core component in the Integrated Cal/Val System POES intercalibration Useful for remote sensing scientists, climatologists, as well as calibration and instrument scientists Support new initiatives (GEOSS and GSICS) Significant progress are expected in GOES/POES intercal in the near future Has been applied to microwave, vis/nir, and infrared radiometers for on-orbit performance trending and climate calibration support Capabilities of 0.1 K for sounders and 1% for vis/nir have been demonstrated in pilot studies Method has been adopted by other agencies 6 GOES vs. POES 6

Calibration is Critical for Climate Change Detection Is there a warming trend in the mid-troposphere ? Is the Earth Greening? How sure are we? Zou, et al, 2007 Trends for operational calibration algorithm 0.32 K Decade-1 Trends for nonlinear calibration algorithm using SNO cross calibration (Zou, et al, 2006) 0.17 K Decade-1 NDVI (normalized diff. vegetation index) Confidence in climate change detection relies on confidence in calibration. Current calibration is not stable/solid enough for climate change detection. Very often when the satellite data are recalibrated, it is likely to lead to new results in climate trends. Year Heidinger, et al Calibration uncertainties translate to uncertainties in climate change detection 7 7

Do we Care about Satellite Biases in NWP. After McNally, Bell, et al Do we Care about Satellite Biases in NWP? After McNally, Bell, et al. ECMWF, 2005 & 2009 Yes! Because: 1) We wish to understand the origin of the bias and ideally correct instrument / RT / NWP model at source 2) In principle we do not wish to apply a correction to unbiased satellite data if it is the NWP model which is biased. Doing so is likely to: Re-enforce the model bias and degrade the analysis fit to other observations Produce a biased analysis (bad for re-analysis / climate applications) The biases for all satellite channels used in NWP data assimilation are closely monitored at NWP centers. For example, the NCEP system is available at: http://www.emc.ncep.noaa.gov/gmb/gdas/radiance/ SSMIS calibration biases cause regional weather patterns More accurate satellite observations will facilitate discovery of model errors and their correction. Additional gains in forecast accuracy can be expected. 8 8

Organizations contributing to GSICS NOAA NIST NASA EUMETSAT CNES CMA JMA KMA WMO Official observers: JAXA ESA GSICS current focus is on the intercalibration of operational satellites, and makes use of key research instruments such as AIRS and MODIS to intercalibration the operational instruments 9 9

SCOPE-CM to maximize data usage Sustained and Coordinated Processing of Environmental Satellite Data Users Satellites & sensors Satellite data Essential Climate products GOS GSICS Consistent Calibrated data sets SCOPE-CM Regional/Specialized Satellite Centres Address the requirements of GCOS in a cost-effective, coordinated manner, capitalising upon the existing expertise and infrastructures. Continuous and sustained provision of high-quality ECVs GSICS enables the generation of Fundamental Climate Data records and provides the basis for sustained climate monitoring and the generation of ECV satellite products. 10

GSICS Formulation Team - 2005 Mitch Goldberg – NOAA/NESDIS (Chair) Gerald Fraser /Raju Datla– NIST Donald Hinsman – WMO (Space Program Director) Xu Jianmin (CMA) Toshiyuki Kurino (JMA) John LeMarshall - JC Sat. Data Assimilation Paul Menzel –NOAA/NESDIS Tillmann Mohr – WMO Hank Revercomb – Univ. of Wisconsin Johannes Schmetz – Eumetsat Jörg Schulz – DWD, CM SAF William Smith – Hampton University Steve Ungar – CEOS, Chairman WG Cal/Val

Building Blocks for Satellite Intercalibration Collocation Determination and distribution of locations for simultaneous observations by different sensors (space-based and in-situ) Collocation with benchmark measurements Data collection Archive, metadata - easily accessible Coordinated operational data analyses Processing centers for assembling collocated data Expert teams Assessments communication including recommendations Vicarious coefficient updates for “drifting” sensors 12 12

Other key building blocks for accurate measurements and intercalibration Extensive pre-launch characterization of all instruments traceable to SI standards Benchmark instruments in space with appropriate accuracy, spectral coverage and resolution to act as a standard for inter-calibration Independent observations (calibration/validation sites – ground based, aircraft) 13 13

GSICS Organization GCC GSICS Executive Panel CSS GPRC GRWG GDWG Calibration Support Segments (reference sites, benchmark measurements, aircraft, model simulations) Coordination Center Regional Processing Research Centers at Satellite Agencies 14 14

GSICS Components GSICS Executive Panel – reps from each satellite agency Priorities, objectives and agreements GSICS Processing and Research Centers (GPRCs) Satellite agencies Activities: Pre-launch calibration Intersatellite calibration Supporting research GSICS Coordination Center (GCC) – NESDIS/STAR Help in implementation of algorithms at GPRCs (if requested) Establish and implement procedures for product acceptance Maintain baseline intercalibration algorithms Quarterly reports on progress and performance Transmit calibration opportunities (overpasses) with reference sites 15 15

Calibration Support Segments (CSS) The GSICS Calibration Support Segments (CSS) will be carried out by participating satellite agencies, national standards laboratories, major NWP centers, and national research laboratories. CSS activities are: Prelaunch Characterisation, reference instruments, SI traceability Earth-based reference sites, such as stable desert areas, long-term specially equipped ground sites, and special field campaigns, will be used to monitor satellite instrument performance. Extra-terrestrial calibration sources, such as the sun, the moon, and the stars, will provide stable calibration targets for on-orbit monitoring of instrument calibration Model simulations will allow comparisons of radiances computed from NWP analyses of atmospheric conditions with those observed by satellite instruments Benchmark measurements of the highest accuracy by special satellite and ground-based instruments will help nail down satellite instrument calibrations 16 16

Current focus of GSICS Interagency collaboration on algorithms (GRWG) and data (GDWG) Product acceptance and documentation requirements, metadata standards, data formats, website standards Routine intercalibration (monitor and correct) of all operational GEO Infrared imagers using IASI and AIRS MODIS and Deep Convective Clouds for visible channels Intercalibration of LEO instruments HIRS, SSMI, AMSU, MHS, AVHRR, AIRS, IASI, FY3, GOME-2, OMI, SBUV Traceability Campaigns Key collocation datasets Requirements for pre-launch calibration Root causes and corrections 17 17 17

Best Practice Guidelines for Pre-Launch Characterization and Calibration of Instruments for Optical Remote Sensing

Importance of Reference Measurements Climate applications = information with high confidence Challenge - long term stability, accuracy, precision of observations. AIRS and IASI have exceptional long term stability and remarkable accuracy; likewise MODIS and MERIS 19 19

Intercalibration of GOES with IASI and AIRS Ch6 Ch4 Ch3 Ch2 IASI AIRS Web Accessible 20 20 20

GSICS Correction Algorithm for Geostationary Infrared Imagers Before 3K Bias After ~0K Bias The first major deliverable to the user community is the GSICS correction algorithm for geostationary satellites. The user applies the correction to the original data using GSICS provided software and coefficients. The correction adjusts the GOES data to be consistent with IASI and AIRS. The above figure shows the difference between observed and calculated brightness temperatures (from NCEP analysis) for GOES-12 channel 6 before and after the correction, respectively. The bias is reduced from 3 K to nearly zero. 21 21 21

GCC GEO to LEO Collocations compared with EUMETSAT GPRC 22

Root Causes and Corrections SRF Shift for NOAA-18 HIRS Channel 5 Without SRF shift With SRF shift 0.2 cm-1 … the second factor, the spectral shift, which explains for some of the remaining differences. There are other things in ICVS that GSICS can use. This is just one example. Since the HIRS sounding channels are located at the slope region of the atmospheric spectra, a small shift of the SRF can cause biases in observed radiances. Details can be referred to Wang et al. (manuscript for JTECH, 2006)

19 sites selected over North Africa and Arabia CNES SADE Data Base Time series of the ratio of the ESA MERIS to NASA MODIS 0.665 micron visible channel reflectance from observations at 19 desert sites in North Africa and Saudi Arabia. The results show very good agreement and stability between the two sensors 19 sites selected over North Africa and Arabia GSICS – Feb 2008 – Claire Tinel / CNES 24 24

Use of Deep Convective Clouds to calibrated Visible and NIR channels Monitoring of the GOES-8 visible (0.63µm) channel using the DCC and LEO/GEO inter-calibration methods. The left panel (a) shows the GOES-8 visible gain during 1998 through 2003, based on the inter-calibration VIRS and GOES-8. The right panel (b) shows the relative DCC calibration, normalized to the VIRS/GOES-8 gain on January 2001, based on the degradation of the DCC visible digital counts over time. A 2nd order regression is also plotted for each method. Note the excellent agreement between the two calibration methods. 25 25

Calibration Opportunity Prediction Data Acquisition Scheduler Integrated Cal/Val System Architecture Calibration Opportunity Prediction Data Acquisition Scheduler Calibration Opportunity Register (COR) Raw Data Acquisition for Calibration Analyses Store Raw Data for Calibration Analysis SNO/ SCO Rad. Bias and Spectral Analysis Calibration Parameter Noise/ Stability Monitoring RTM Model Rad. at Calibration Reference Sites Inter-sensor Bias and Spectral Analysis Earth & Lunar Calibration Geolocation Assessment (Coastlines, etc.) Assessment Reports and GSICS Corrections 26 26

GSICS Objectives To improve the use of space-based global observations for weather, climate and environmental applications through operational inter-calibration of satellite sensors. Observations are well calibrated through operational analysis of instrument performance, satellite intercalibration, and validation over reference sites Pre-launch testing is traceable to SI standards Provide ability to re-calibrate archived satellite data with consensus GSICS algorithms, leading to stable fundamental climate data records (FCDRs) 27 27 27

Engage the User Community Satellite Community – generation of CDRs New WMO Space Programme SCOPE-CM ISCCP National programs - SDS, SAFs, Satellite Community - NWP direct radiance assimilation Reanalysis Community Next reanalysis – 2012 - 2015 GSICS major deliverable - intercalibrated geostationary data using IASI/AIRS from 2003 – 2010+ Satellite Acquisition Programs Prelaunch instrument characterization guidelines Cal/Val Plans 28