Overview of Global Space-based Inter-Calibration System (GSICS) Mitch Goldberg, NOAA/NESDIS GSICS Executive Panel chair 2nd GSICS User Workshop

ECMWF Meeting, Reading UK June 22, 2001 What is GSICS? Global Space-based Inter-Calibration System (GSICS) Goal - Enhance calibration and validation of satellite observations and to intercalibrate critical components global observing system Part of WMO Space Programme GSICS Implementation Plan and Program formally endorsed at CGMS 34 (11/06) N:\Briefings\International\ECMWF June 22 2001\ECMWF Jun_22_2001.ppt

ECMWF Meeting, Reading UK June 22, 2001 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 correction coefficients and algorithms to the user community for current and historical data 3 N:\Briefings\International\ECMWF June 22 2001\ECMWF Jun_22_2001.ppt

ECMWF Meeting, Reading UK June 22, 2001 Or in technical terms: Quantify the differences – magnitude and uncertainty Correct the differences – physical basis and empirical removal Diagnose the differences – root cause analysis N:\Briefings\International\ECMWF June 22 2001\ECMWF Jun_22_2001.ppt

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) 5 5

Calibration is Critical for Climate Change Detection Before intercalibraion After intercalibration Trend of global oceanic total precipitable water decreases from 0.54 mm/decade to 0.34 mm/decade after intercalibrations! Calibration uncertainties translate to uncertainties in climate change detection 6 6 6

Satellite Intercalibration SSM/I Observations (Yang et al. , J. Appl Satellite Intercalibration SSM/I Observations (Yang et al., J. Appl. Meteor. and Climatology)

SSMIS calibration biases cause regional weather patterns 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

Difference between JRA25 vs ECMWF and JRA25 vs ERA Interim (column water vapor above 500 mb) Larger differences with ERAIM ~13 % vs ~1 % with ECMWF WX analysis ERAIM - JRA25 ECMWF - JRA25 ECMWF Weather analysis and Reanalysis is different because the ECMWF bias tuning changed in 2006.

Problems associated with Radiance Applications Multiple error sources: Observations (biases) Spectral Response Functions Radiative transfer Inversion Technique/Data Assimilation Model Physics

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

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)

GSICS organization Organizations contributing to GSICS: CMA, CNES, EUMETSAT, ISRO, JAXA, JMA, KMA, NASA, NIST, NOAA, WMO, ESA Overseen by GSICS Executive Panel Assisted by Research Working Group and Data management Working Group GSICS activities rely on: GSICS Coordination Centre (GCC) operated by NOAA/NESDIS Processing & Research Centres (GPRC) operated by each satellite operator Calibration Support Segments (CSS) including field sites and laboratories GSICS as an element of the space-based component of the Global Observing System GSICS activities rely on a GSICS Coordination Centre (GCC) operated by NOAA/NESDIS, several GSICS Processing and Research Centres (GPRC) operated by each satellite operator, and will benefit of Calibration Support Segments including field sites and laboratories. Activities are overseen by a GSICS Executive Panel assisted by a Research Working Group and a Data management Working Group. Coordination Center Calibration Support Segments (reference sites, benchmark measurements, aircraft, model simulations) Regional Processing Research Centers at Operational Space Agencies

ECMWF Meeting, Reading UK June 22, 2001 Current focus of GSICS Interagency collaboration on algorithms (GRWG) and data exchange and formats (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 14 14 N:\Briefings\International\ECMWF June 22 2001\ECMWF Jun_22_2001.ppt 14

ECMWF Meeting, Reading UK June 22, 2001 Current focus of GSICS 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 15 15 N:\Briefings\International\ECMWF June 22 2001\ECMWF Jun_22_2001.ppt 15

First GSICS Guideline document Best Practice Guidelines for Pre-Launch Characterization and Calibration of Instruments for Passive Optical Remote Sensing Report to GSICS Executive Panel R.U. Datla, J.P. Rice, K. Lykke and B.C. Johnson (NIST) J.J. Butler and X. Xiong (NASA) September 2009

ECMWF Meeting, Reading UK First international coordinated GSICS project is the intercalibration of geostationary infrared channels with IASI and AIRS June 22, 2001 Ch6 Ch4 Ch3 Ch2 IASI AIRS Web Accessible 17 17 N:\Briefings\International\ECMWF June 22 2001\ECMWF Jun_22_2001.ppt 17

ECMWF Meeting, Reading UK GSICS Correction Algorithm for Geostationary Infrared Imagers GSICS will provide correction coefficients for all GEOs from 2003 (beginning of AIRS record) to present ECMWF Meeting, Reading UK June 22, 2001 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 figures to the left show the difference between observed and calculated brightness temperatures (from NCEP analysis) before and after correction The bias is reduced from 3 K to nearly zero. Before 3K Bias After: ~ 0K Bias 18 N:\Briefings\International\ECMWF June 22 2001\ECMWF Jun_22_2001.ppt

ECMWF Meeting, Reading UK June 22, 2001 CNES SADE Data Base is critical for assessing stability of visible/near infrared reference instruments for intercalibration 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 19 N:\Briefings\International\ECMWF June 22 2001\ECMWF Jun_22_2001.ppt 19

Calibration Opportunity Prediction Data Acquisition Scheduler Integrated Cal/Val System Architecture Calibration Opportunity Prediction Data Acquisition Scheduler Calibration Opportunity Register (CORE) Raw Data Acquisition for Calibration Analyses Stored Raw Data for Calibration Analyses 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 Calibration Updates

Promoting access to instrument performance monitoring is also part of GSICS GSICS beginning to develop observing system monitoring tools for all GSICS partners. Above is example of NOAA tool for NOAA-19 OV and long-term monitoring The system has detected instrument anomalies, provided an important tool for diagnoses, data quality assurance, and for short and long term applications To better support the operations, we have developed comprehensive on-orbit verification for newly launched satellites and an integrated cal/val system. Courtesy of F.Weng 21

Engage User Community (First GSICS Users’ Workshop – September 2009) Satellite Community – generation of CDRs New WMO Space Programme SCOPE-CM ISCCP - Blended geo & leo cloud information Agency CDR programs - NOAA, EUMETSAT Satellite Community - NWP direct radiance assimilation Reanalysis Community Next ECMWF reanalysis – 2012 - 2015 GSICS first major deliverable: Correction Coefficients for all GEO IR using IASI/AIRS as reference from 2003 – 2010+ Satellite Acquisition Programs Prelaunch instrument characterization guidelines Cal/Val Plans Request for new products: GEO solar channels, LEO microwave instruments

MSU/AMSU FCDR Coordination funded by NOAA CDR Program and NESDIS STAR Develop consistent radiance Fundamental Climate Data Record (FCDR) to support consistent modeling reanalysis and consistent satellite retrievals Develop consistent atmospheric temperature thematic climate data record (TCDR) for climate service support  climate change research, climate change monitoring, validating climate model simulation… And also, for temperature channels, we don’t have the dynamic range problem. Which means the SNO ranges covers 80% of the global temperature, which is not bad at all compare to the water vapor channels.

Before and After Inter-Satellite Calibration AMSU CH6 (Cheng-Zhi Zhou) NOAA operational calibrated inter-satellite difference time series (Before Inter-satellite calibration); Ocean Mean NOAA-15 CH6 has strong calibration nonlinearity Time-dependent calibration coefficients for NOAA-15 are introduced at Level-1c After SNO recalibration, inter-satellite differences close to zero Recalibrated trend is expected to be different from NOAA-15 Inter-satellite difference time series after SNO Inter-satellite calibration, AMSU-A CH6 The project is recently funded by the NOAA SDS program. A science team for the CDR development is established.

GPS-RO simulated MSU channel 4 vs SNO recalibrated MSU channel 4 products Scattering plots of 10 x10 degree binned TLS from 200106 to 200812 Mean(RSS‐RO_AMSU) =‐0.99 Std (RSS‐RO_AMSU) =1.67 R=0.99 Mean(UAH‐RO_AMSU) =0.02 Std (UAH‐RO_AMSU) =2.06 R=0.99 Mean(NOAA‐RO_AMSU) =-0.49 Std (NOAA‐RO_AMSU) =0.5 R=0.99 From Ben Ho of NCAR, NOAA CDR Workshop, Silver Spring, Maryland March 22-24

Bias Correction of Recalibrated MSU data in NCEP CFSR Reanalysis Recalibrated MSU level-1c data were assimilated into NCEP CFSR and NASA MERRA reanalysis systems Bias correction pattern for recalibrated MSU data are much smoother, since instrument errors were removed before assimilation I do not want to say the sno calibration solves everything, but it indeed improves the radiance in many aspects. Here is the summary of the MSU issues I listed before and how the sno calibration improves them Before Recalibration After Recalibration MSU Channel 2 bias correction patterns in NCEP CFSR reanalysis from 1978-2007. Recalibrated MSU data after 1987 were assimilated into CFSR (plot from Saha et al. 2010)

GPM affiliation with GSICS ECMWF Meeting, Reading UK June 22, 2001 GPM affiliation with GSICS Research working group - Consensus algorithms Data working group - Formats, Servers GSICS Executive Panel GRWG GDWG GCC CSS GPRC Calibration Support Segments Coordination Center Regional Processing Research Centers at Satellite Agencies GPM X-Cal Working Group CSS GPRC CSS GPRC GPM X-cal: Plan to sustain X-cal in future Similar Structure to GSICS Interested in using GSICS product acceptance procedure Precipitation Processing System at Goddard N:\Briefings\International\ECMWF June 22 2001\ECMWF Jun_22_2001.ppt

GSICS Interface to SCOPE-CM Sustained & Coordinated Processing of Environmental satellite data for Climate Monitoring (SCOPE-CM) WMO Initiative based on activities of existing initiatives (GOS, GCOS and GSICS) Provides international cooperation and coordination framework To generate multi-mission and global satellite climate data records (FCDRs & TCDRs) Serve users and other organisations (e.g. WMO Regional Climate Centres RCC, National Weather Services) => The way toward operational production of high quality ECVs on a global scale Aside – as an example of how GSICS can fit into the scheme of things.

GSICS Outcome Coordinated international intersatellite calibration program Exchange of critical datasets for cal/val Best practices/requirements for monitoring observing system performance Best practices/requirements for prelaunch characterisation (with CEOS WGCV) Establish requirements for cal/val (with CEOS WGCV) Advocate for benchmark systems Quarterly reports of observing system performance and recommended solutions Improved sensor characterisation High quality radiances for NWP & Climate