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Earth System Data Records (ESDR) and
Climate Data Records (CDR)Dave Siegel
Crystal SchaafNorm Nelson
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ESDR/CDR
• NASA Earth System Data Records (ESDR)– Defined as a unified and coherent set of observations of a
given parameter of the Earth system, which is optimized to meet specific requirements in addressing science questions
• NRC/NOAA Climate Data Record (CDR) – Defined as a time series of measurements of sufficient length,
consistency, and continuity to determine climate variability and change (Climate Data Records from Environmental Satellites, 2004)
• Fundamental CDRs (FCDRs), – calibrated and quality-controlled sensor data that have been improved
over time
• Thematic CDRs (TCDRs), – geophysical variables derived from the FCDRs.
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GCOS/GTOS Essential Climate Variables
(ECVs)Domain Essential Climate Variables
Atmospheric(over land,sea andice)
Surface: Air temperature, Precipitation, Air pressure, Surface radiation budget, Wind speed and direction, Water vapour.
Upper-air: Earth radiation budget (including solar irradiance), Upper-air temperature, Wind speed and direction, Water vapour, Cloud properties.
Composition: Carbon dioxide, Methane, Ozone, Other long-lived greenhouse gases, Aerosol properties.
Oceanic
Surface: Sea-surface temperature, Sea-surface salinity, Sea level, Sea state, Sea Ice, Current, Ocean colour (for biological activity), Carbon dioxide partial pressure.
Sub-surface: Temperature, Salinity, Current, Nutrients, Carbon, Ocean tracers, Phytoplankton.
Terrestrial
River discharge, Water use, Ground water, Lake levels, Snow cover, Glaciers and ice caps, Permafrost and seasonally-frozen ground, Albedo, Land cover (including vegetation type), Fraction of absorbed photosynthetically active radiation (FAPAR), Leaf area index (LAI), Biomass, Fire disturbance, Soil moisture.
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GCOS Principles for Monitoring Climate Variables from Satellites (GCOS, 2004)
• Constant sampling within the diurnal cycle (minimizing the effects of orbital decay and orbit drift) should be maintained.
• A suitable period of overlap for new and old satellite systems should be ensured for a period adequate to determine intersatellite biases and maintain the homogeneity and consistency of time-series observations.
• Continuity of satellite measurements (i.e., elimination of gaps in the long-term record) through appropriate launch and orbital strategies should be ensured.
• Rigorous prelaunch instrument characterization and calibration, including radiance confirmation against an international radiance scale provided by a national metrology institute, should be ensured.
• On-board calibration adequate for climate system observations should be ensured and associated instrument characteristics monitored.
• Operational production of priority climate products should be sustained and peer-reviewed new products should be introduced as appropriate.
• Data systems needed to facilitate user access to climate products, metadata, and raw data, including key data for delayed-mode analysis, should be established and maintained.
• Use of functioning baseline instruments that meet the calibration and stability requirements stated above should be maintained for as long as possible, even when these exist on decommissioned satellites.
• Complementary in situ baseline observations for satellite measurements should be maintained through appropriate activities and cooperation.
• Random errors and time-dependent biases in satellite observations and derived products should be identified.
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Land Measurements Team Earth System Data Records (ESDR)
White Papers• http://lcluc.umd.edu/Documents/land-esdr.asp
– Albedo and Anisotropy – Fire – GPP and NPP – LAI and fPAR – Land Cover and Change – PAR and Incident Solar Radiation – Phenology – Sea Ice – Snow Cover – Surface Hydrology – Surface Reflectance – Temperature and Emissivity – Vegetation Indices
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AVHRR NDVI (1981-2000)
Vegetation index (NDVI) monthly anomaly time series (Jul 1981- Dec 2000). Original Pathfinder Land (V1) and successive corrections (V2, V3)
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Long Term Data Record (AVHRR-MODIS-VIIRS) Production of the Version 2 Data Set (Oct 2007)
Long Term Data Record (AVHRR-MODIS-VIIRS) Production of the Version 2 Data Set (Oct 2007)
- Algorithms:-Vicarious calibration (Vermote/Kaufman)-Cloud screening: CLAVR-Partial Atmospheric Correction:
-Rayleigh (NCEP)-Ozone (TOMS)-Water Vapor (NCEP)
-Products:-Daily NDVI (AVH13C1)-Daily surface reflectance (AVH09C1)
-Format:-Linear Lat/Lon projection-Spatial resolution: 0.05 Deg -HDF-EOS
-Time Period:- 1981 – 2000 completed
-Distribution:-ftp and web-http://ltdr.nascom.nasa.gov/ltdr/ltdr.html
NOAA-11 - 1992193 (7/11/1992) : Ch1,Ch2 and NDVI
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AVHRR BRDF/Albedo Product:Broadband Black-Sky Albedo (July 1999)
VERY Preliminary Albedo Evaluation AVHRR 1999 – MODIS 2000
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Key Points for Land CDRs for CC&E
• Maintenance of heritage variables and sensor measurements over time – calibration, continuity, and overlap over multiple missions
• Production and maintenance of quality/confidence fields with these records – key for assimilation, gap-filling, and model assessments
• On-going validation and assessment efforts– CEOS/WGCV/LPV (Land Product Validation)
• Long term commitment to reprocessing the CDRs – as new calibration information, algorithm improvements and data
sources become available
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Ocean Color CDR’s• Multiple missions from 1978 to present
– Quality issues early in record (& into the future…)
• Fundamental & Thematic CDR Products (NRC 2004)
– Water-leaving radiance – Chlorophyll a concentration, Net primary production, etc.
• Validation – Many 1000’s obs available (SeaBASS)
• Ocean Color CDR Generation– Projects to maximize coverage (ReaSoN, GlobColour) – Little progress on cross-mission CDR’s (CIOSS 2005)
– SeaWiFS’s continuing success has slowed progress
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Obviously, quality matters…
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Stats for Overlap
Normalized Bias WiFS-Aqua = 13% WiFS-MERIS = 5% Aqua-MERIS = 14%
Normalized RMS WiFS-Aqua = 13% WiFS-MERIS = 46% Aqua-MERIS = 30%
Comparison with Field Observations (Global - GlobColour 11/07)
Normalized Bias Normalized RMS WiFS-Field = 0% WiFS-Field = 25% Aqua-Field = 4% Aqua-Field = 44% MERIS-Field = 22% MERIS-Field = 34%
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What do we want CDR’s to do?• Answer climate science questions
– Quantify trends on climate-relevant time scales– CDR’s are likely question specific
• How to build them? – Decide on question & work out the method for quantifying
answer– Need to link multiple missions (but multiple sensors!!)
• Need to be realistic – Hoping (i.e., averaging) will not work– We may not be able to do everything
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CCE Workshop Questions
• What does the carbon cycle and ecosystems community expect of this effort?
• What are our biggest challenges in this area, and how do we address them?
• Is our list of identified data records complete, or is something missing?
• Does the carbon cycle and ecosystems community need to establish priorities for these and other activities, and, if so, how should they be established?
Session II