Transcript gsics - WCRP-Home

Global Space-based Inter-calibration
System (GSICS)
4th WCRP Observations and Assimilation Panel
(WOAP) Meeting
Barbara J. Ryan
Director, WMO Space Programme
30 March 2010
Hamburg
Motivation
• Applications require well-calibrated and inter-calibrated
measurements
– Radiance Assimilation in Numerical Weather Prediction
– Data Fusion
– Climate Data Records
• Expanding Global Observing System (GOS)
• Inter-calibration of instruments achieves comparability of
measurements from different instruments
Global Space-based Inter-Calibration
System (GSICS)
• To enhance and sustain calibration and validation of
satellite observations
• To intercalibrate critical components of the Global
Observing System (GOS) – to climate quality benchmark
observations and/or reference sites
• To provide corrected observations and/or correction
algorithms to the user community for current and historical
data
• GSICS Implementation Plan and Programme formally
endorsed at CGMS-34 (Nov. 2006)
Actions
• Quantify the differences – magnitude
and uncertainty
• Correct the differences – physical basis
and empirical removal
• Diagnose the differences – root cause
analysis
Space-based Component of
WMO’s Global Observing System (GOS)
Intercalibration of instruments for comparability of measurements from different instruments
Global Space-based Inter-calibration
System (GSICS)
POLAR- POLAR intercalibration
•To ensure consistency of
datasets from different
missions and operators
• Implementation Plan adopted
Nov.2006
•8 Organizations currently
contributing (+WMO)
GEO versus Polar-orbiting
Simultaneous Nadir Overpass
(SNO) inter-calibration
method
• Images: NOAA/NESDIS
Satellite Biases in NWP
After McNally, Bell, et al. ECMWF, 2005 & 2009
Understand the origin of the bias
and ideally correct instrument /
RT / NWP model at source
In principle do not want 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)
SSMIS calibration biases
indicate regional weather
patterns
More accurate satellite observations will facilitate
discovery of model errors and their correction.
Additional gains in forecast accuracy can be expected
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Difference between JRA-25 vs ECMWF and JRA-25 vs ERA Interim
(column water vapor above 500 mb)
Larger differences with ERAIM (13%) vs ECMWF WX analysis (1%)
ERAIM - JRA-25
ECMWF - JRA-25
ECMWF Weather analysis and reanalysis different because the ECMWF
bias-tuning changed in 2006. According to Tony McNally, ECMWF will turn
off bias-tuning of AIRS water vapor channels to correct the problem.
Calibration is Critical for Climate Change
Detection
Before Intercalibraion
After Intercalibration
Calibration uncertainties translate to uncertainties in climate change
detection. Trend of global oceanic total precipitable water decreases
from 0.54 mm/decade to 0.34 mm/decade after intercalibration.
Organizations contributing to GSICS
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NOAA
NASA
NIST
EUMETSAT
CNES
CMA
JMA
KMA
WMO
Observers:
JAXA
ESA
CEOS Precipitation
Constellation is working
with GSICS via GPM X-Cal
Working Group
Current focus is on the intercalibration of
operational satellites, and makes use of key
research instruments like AIRS and MODIS as
reference instruments
GSICS Structure
Research working group
- Consensus algorithms
GRWG
Calibration
Support
Segments
(reference
sites,
benchmark
measuremen
ts, aircraft,
model
simulations)
CSS
CSS
CSS
GSICS
Executive Panel
GCC
Data working group
- Formats, Servers
GDWG
GPRC
GPRC
GPRC
Coordination Center Regional Processing Research
Centers at Satellite Agencies
Current Workplan
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Interagency collaboration on algorithms (GRWG) and data
exchange and formats (GDWG)
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Product acceptance and documentation requirements, metadata
standards, data formats, website standards
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Routine intercalibration (monitor and correct) all operational GEO
Infrared imagers using IASI and AIRS
– MODIS and Deep Convective Clouds for visible channels
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Intercalibration of LEO instruments
– HIRS, SSMI, AMSU, MHS, AVHRR, AIRS, IASI, FY3,
– GOME-2, OMI, SBUV
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Traceability
– Campaigns
– Key collocation datasets
– Requirements for pre-launch calibration
•
Root causes and corrections
Best Practice Guidelines for Pre-Launch
Characterization and Calibration of
Instruments for Optical Remote Sensing
GSICS Guideline Document
First international coordinated GSICS project is the
intercalibration of geostationary infrared channels with
IASI and AIRS
IASI
AIRS
Ch6
Ch4
Ch3
Ch2
Web Accessible
GSICS Correction Algorithm for Geostationary Infrared Imagers
GSICS will provide correction coefficients for all GEOs
from 2003 (beginning of AIRS record) to present
The first major deliverable to the user community is
the GSICS correction algorithm for geostationary
satellites.
Before 3K Bias
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
After: ~ 0K Bias
The bias is reduced from 3 K to nearly zero
Web-based Monitoring MTSATAIRS/IASI
• Monitoring
Example from
JMA website
• MTSAT-1R –
AIRS/IASI
• Time Series of
Bias
– at 220, 250,
290K
Monitoring GOES12-AIRS at NOAA
Monitoring Meteosat9-IASI
IR3.9-IR12.0: Small, stable Biases <0.2K ± 0.05K
IR13.4:
Larger Bias ~-1K
-0.05K/mnth+Jump
Time series of brightness temperature differences between MSG2-IASI
for typical clear-sky radiances. Error bars represent statistical
uncertainty on each mean bias (may be very small).
GSICS Correction available for MSG
• EUMETSAT routinely
runs prototype intercalibration of MSGIASI
• Results published
on webpage for Intercalibration Services :
–http://www.eumetsa
t.int/Home/Main/Acc
ess_to_Data/Intercal
ibrationServices
• Webpage also allows
access to
coefficients required
to apply GSICS
Correction
• Users can implement
this as change in
calibration
coefficients
User Community Engagement
Meeting 9/09
– Satellite Community – generation of CDRs
• SCOPE-CM
• ISCCP
• National programs - SDS, SAFs,
– Satellite Community - NWP direct radiance assimilation
– Reanalysis Community
• Next reanalysis – 2012 - 2015
• GSICS first major deliverable - intercalibrated geostationary data
using IASI/AIRS from 2003 – 2010+
– Satellite Acquisition Programs
• Prelaunch instrument characterization guidelines
• Cal/Val Plans
User feedback: Geostationary intercalibration, Microwave Intercalibration
GSICS Outcomes
• Coordinated international intersatellite calibration program
• Exchange of critical datasets for cal/val
• Best practices/requirements for monitoring observing
system performance (with CEOS WGCV)
• Best practices/requirements for prelaunch
characterization (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 characterization
• High quality radiances for weather, climate &
environmental applications