Earth System Data Records (ESDR) and

Climate Data Records (CDR)Dave Siegel

Crystal SchaafNorm Nelson

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.

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.

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.

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

AVHRR NDVI (1981-2000)

Vegetation index (NDVI) monthly anomaly time series (Jul 1981- Dec 2000). Original Pathfinder Land (V1) and successive corrections (V2, V3)

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

AVHRR BRDF/Albedo Product:Broadband Black-Sky Albedo (July 1999)

VERY Preliminary Albedo Evaluation AVHRR 1999 – MODIS 2000

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

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

Obviously, quality matters…

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%

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

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