MODIS Sea Surface Temperature (SST) Products

Similar documents
Lectures 7 and 8: 14, 16 Oct Sea Surface Temperature

Land Surface Temperature Measurements From the Split Window Channels of the NOAA 7 Advanced Very High Resolution Radiometer John C.

Long-term global time series of MODIS and VIIRS SSTs

Analysis of Pathfinder SST algorithm for global and regional conditions

Evaluation of Regressive Analysis Based Sea Surface Temperature Estimation Accuracy with NCEP/GDAS Data

Comparison between the Pathfinder Versions 5.0 and 4.1 Sea Surface Temperature Datasets: A Case Study for High Resolution

IMPROVING REGIONAL AVHRR SST MEASUREMENTS USING AATSR SST DATA

Lectures 7 and 8: 13, 18 Feb Sea Surface Temperature

Software requirements * : Part III: 2 hrs.

APPLICATIONS WITH METEOROLOGICAL SATELLITES. W. Paul Menzel. Office of Research and Applications NOAA/NESDIS University of Wisconsin Madison, WI

Estimation of ocean contribution at the MODIS near-infrared wavelengths along the east coast of the U.S.: Two case studies

Extending the Deep Blue aerosol record from SeaWiFS and MODIS to NPP-VIIRS

Thermal And Near infrared Sensor for carbon Observation (TANSO) onboard the Greenhouse gases Observing SATellite (GOSAT) Research Announcement

Study of the Influence of Thin Cirrus Clouds on Satellite Radiances Using Raman Lidar and GOES Data

VIIRS SDR Cal/Val: S-NPP Update and JPSS-1 Preparations

Monitoring Sea Surface temperature change at the Caribbean Sea, using AVHRR images. Y. Santiago Pérez, and R. Mendez Yulfo

GCOM-C/SGLI and its Lunar Calibration

GCOM-C SGLI calibration and characterization. Hiroshi Murakami JAXA/EORC Satellite instrument pre- and post-launch calibration

Vicarious calibration of GLI by global datasets. Calibration 5th Group Hiroshi Murakami (JAXA EORC)

- satellite orbits. Further Reading: Chapter 04 of the text book. Outline. - satellite sensor measurements

What is so great about nighttime VIIRS data for the detection and characterization of combustion sources?

Moderate Resolution Imaging Spectroradiometer (MODIS) Products and Potential Applications For Environmental and Climatic Monitoring in China

Chapter 4 Nadir looking UV measurement. Part-I: Theory and algorithm

MODIS On-orbit Calibration Methodologies

Orbit and Transmit Characteristics of the CloudSat Cloud Profiling Radar (CPR) JPL Document No. D-29695

Preparation and dissemination of the averaged maps and fields of selected satellite parameters for the Black Sea within the SeaDataNet project

GEOSC/METEO 597K Kevin Bowley Kaitlin Walsh

MODIS Reflective Solar Bands Calibration Algorithm and On-orbit Performance

Satellite-based Lake Surface Temperature (LST) Homa Kheyrollah Pour Claude Duguay

Generating a Climate data record for SST from Passive Microwave observations

Satellite observation of atmospheric dust

Sensitivity Analysis on Sea Surface Temperature Estimation Methods with Thermal Infrared Radiometer Data through Simulations

A Time Series of Photo-synthetically Available Radiation at the Ocean Surface from SeaWiFS and MODIS Data

Minutes of the First Meeting. of the IOCCG Working Group. L1 Requirements for Ocean-Colour Remote Sensing. April 20-21, 2010

Long-Term Time Series of Water Vapour Total Columns from GOME, SCIAMACHY and GOME-2

Sea Surface Temperatures from the GOES-8 Geostationary Satellite

Sensitivity Study of the MODIS Cloud Top Property

Tracking On-orbit Radiometric Accuracy and Stability of Suomi NPP VIIRS using Extended Low Latitude SNOs

ESTIMATION OF ATMOSPHERIC COLUMN AND NEAR SURFACE WATER VAPOR CONTENT USING THE RADIANCE VALUES OF MODIS

Daily OI SST Trip Report Richard W. Reynolds National Climatic Data Center (NCDC) Asheville, NC July 29, 2005

APPENDIX 2 OVERVIEW OF THE GLOBAL PRECIPITATION MEASUREMENT (GPM) AND THE TROPICAL RAINFALL MEASURING MISSION (TRMM) 2-1

What are Aerosols? Suspension of very small solid particles or liquid droplets Radii typically in the range of 10nm to

ENVISAT - AATSR CYCLIC REPORT #63

Thermal And Near infrared Sensor for carbon Observation (TANSO) On board the Greenhouse gases Observing SATellite (GOSAT) Research Announcement

MOPITT (Measurements of Pollution in the Troposphere) Version 6 Product User's Guide

HY-2A Satellite User s Guide

Remote Sensing I: Basics

Operational systems for SST products. Prof. Chris Merchant University of Reading UK

Adjusting Aqua MODIS TEB nonlinear calibration coefficients using iterative solution

Atmospheric Lidar The Atmospheric Lidar (ATLID) is a high-spectral resolution lidar and will be the first of its type to be flown in space.

OSI SAF SST Products and Services

MSG system over view

An Algorithm for Retrieving Land Surface Temperatures Using VIIRS Data in Combination with Multi-Sensors

On the Satellite Determination of Multilayered Multiphase Cloud Properties. Science Systems and Applications, Inc., Hampton, Virginia 2

A Comparative Study and Intercalibration Between OSMI and SeaWiFS

Use of Drifting Buoy SST in Remote Sensing. Chris Merchant University of Edinburgh Gary Corlett University of Leicester

Measuring Carbon Dioxide from the A-Train: The OCO-2 Mission

History of Aerosol Remote Sensing. Mark Smithgall Maria Zatko 597K Spring 2009

MOPITT (Measurements of Pollution in the Troposphere) Version 5 Product User's Guide

Sentinel-3A Product Notice SLSTR Level-2 Sea Surface Temperature

GMES: calibration of remote sensing datasets

VALIDATION OF CROSS-TRACK INFRARED SOUNDER (CRIS) PROFILES OVER EASTERN VIRGINIA. Author: Jonathan Geasey, Hampton University

AIRS observations of Dome Concordia in Antarctica and comparison with Automated Weather Stations during 2005

Ground and On-Orbit Characterization and Calibration of the Geosynchronous Imaging Fourier Transform Spectrometer (GIFTS)

OCEAN & SEA ICE SAF CDOP2. OSI-SAF Metop-A IASI Sea Surface Temperature L2P (OSI-208) Validation report. Version 1.4 April 2015

T. Dale Bess 1 and Takmeng Wong Atmospheric Sciences Division Langley Research Center, NASA Hampton, VA G. Louis Smith

Back to basics: From Sputnik to Envisat, and beyond: The use of satellite measurements in weather forecasting and research: Part 1 A history

Comparison of NASA AIRS and MODIS Land Surface Temperature and Infrared Emissivity Measurements from the EOS AQUA platform

Undergraduate Research Final Report: Estimation of suspended sediments using MODIS 250 m bands in Mayagüez Bay, Puerto Rico

REVISION OF THE STATEMENT OF GUIDANCE FOR GLOBAL NUMERICAL WEATHER PREDICTION. (Submitted by Dr. J. Eyre)

Sentinel-3 Sea and Land Surface Temperature Radiometer (SLSTR) Mireya Etxaluze (STFC RAL Space)

Satellite observations indicate rapid warming trend for lakes in California and Nevada

ATMOS 5140 Lecture 1 Chapter 1

Interpretation of Polar-orbiting Satellite Observations. Atmospheric Instrumentation

Lecture 4: Radiation Transfer

MOPITT (Measurements of Pollution in the Troposphere) Version 6 Product User's Guide

Richard W. Reynolds * NOAA National Climatic Data Center, Asheville, North Carolina

THE FEASIBILITY OF EXTRACTING LOWLEVEL WIND BY TRACING LOW LEVEL MOISTURE OBSERVED IN IR IMAGERY OVER CLOUD FREE OCEAN AREA IN THE TROPICS

Satellite Oceanography and Applications 1: Introduction, SST, Ocean color

ERBE Geographic Scene and Monthly Snow Data

Quality control methods for KOOS operational sea surface temperature products

Radiative Climatology of the North Slope of Alaska and the Adjacent Arctic Ocean

NASA s Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) AVIRIS: PEARL HARBOR, HAWAII

Variability in Global Top-of-Atmosphere Shortwave Radiation Between 2000 And 2005

In-flight Calibration Techniques Using Natural Targets. CNES Activities on Calibration of Space Sensors

The SeaFlux Turbulent Flux Dataset Version 1.0 Documentation

Remote Sensing How we know what we know A Brief Tour

Multi-Sensor Satellite Retrievals of Sea Surface Temperature

F O U N D A T I O N A L C O U R S E

THREE-WAY ERROR ANALYSIS BETWEEN AATSR, AMSR-E AND IN SITU SEA SURFACE TEMPERATURE OBSERVATIONS.

Impacts of Atmospheric Corrections on Algal Bloom Detection Techniques

Current Status of the Stratospheric Ozone Layer From: UNEP Environmental Effects of Ozone Depletion and Its Interaction with Climate Change

The current status of FY-3D

Remote sensing of sea ice

A AVHRR NDVI dataset for Svalbard. Stian Solbø, Inge Lauknes, Cecilie Sneberg Grøtteland, Stine Skrunes, Hannah Vickers, Kjell Arild Høgda

GCOM-W1 now on the A-Train

Influence of Clouds and Aerosols on the Earth s Radiation Budget Using Clouds and the Earth s Radiant Energy System (CERES) Measurements

CLAVR-x is the Clouds from AVHRR Extended Processing System. Responsible for AVHRR cloud products and other products at various times.

The MODIS Cloud Data Record

AIRS Level 1b. Tom Pagano AIRS Project Project Manager. Hartmut Aumann AIRS Project Scientist

Transcription:

MODIS Sea Surface Temperature (SST) Products Summary: Sea surface temperature (SST) products have been derived from the MODIS (MODerate Resolution Imaging Spectroradiometer) sensors onboard the NASA Terra and Aqua platforms since November 2000. These SST products are derived from the MODIS mid-infrared (IR) and thermal IR channels and are available in various spatial and temporal resolutions. Table of Contents: 1 Data Set Overview 2 Investigator(s) 3 Theory of Measurements 4 Equipment 5 Data Acquisition Methods 6 Observations 7 Data Description 8 Data Organization 9 Data Manipulations 10 Errors 11 Notes 12 Application of the Data Set 13 Future Modifications and Plans 14 Software 15 Data Access 16 Output Products and Availability 17 References 18 Glossary of Terms 19 List of Acronyms 20 Document Information 1. Data Set Overview: Data Set Identification: This guide refers to PO.DAAC products 162, 163, 184 and 185 under the names Aqua/Terra MODIS Global Level 3 Mapped Thermal IR SST and MODIS Global Level 3 Mapped mid-ir SST respectively. Data Set Introduction: SST is derived from the MODIS IR channels using two channels in either the thermal IR (11-12 um) or channels in the mid-ir region (3.8-4.1 um). The approach is similar to the multi-channel sea surface temperature (MCSST) method used to generate AVHRR-based SST.

The MODIS data are available in a variety of spatial resolutions and temporal periods. The Level 3 mapped products are global gridded data sets with all points filled even over land. The Level 3 mapped files are derived from the Level 3 binned files. Objective/Purpose: The purpose of MODIS SST is to provide high quality global measurements of this parameter. MODIS SST is superior to AVHRR SST due to the higher sensitivity and lower signal-to-noise characteristics of the MODIS instrument. The mid-ir channels are especially useful in the high water vapor, low-latitude regions compared with previous radiometers. They are also less suspectible to aerosol contamination compared to the 11-12 um channels. Summary of Parameters: Sea Surface Temperature Discussion: In order to understand the processes involved in global climate change many different scientific measurements are needed. One of the parameters critical to understanding how the oceans affect climate on a global scale is sea surface temperature (SST). An example of the importance of this measurement for climate studies is their use in the study of the Western Boundary Currents of the world's oceans. The Western Boundary Currents play an important role in the Earth's heat balance. They carry a tremendous amount of heat poleward from low-latitude regions. Because the currents exhibit strong SST gradients, the SST measurements can be used to determine their displacements. Knowledge of the displacements, in turn, allows us to improve our understanding of ocean circulation and heat transport. SST measurements are also critical parameters in coupled atmospheric-ocean global circulation models (GCMs) for determining air-sea interaction, atmospheric convection, and model boundary conditions. Related Data Sets: AVHRR Pathfinder SST, AVHRR MCSST, and ATSR SST products. Also GHRSST products. 2. Investigator(s): Investigator(s) Name and Title: Dr. Robert Evans revans@rsmas.miami.edu University of Miami/Rosentiel School of Marine and Atmospheric Sciences 3. Theory of Measurements: Briefly, radiative transfer theory is used to correct for the effects of the atmosphere on the observations by utilizing "windows" of the electromagnetic spectrum where little or no atmospheric absorption occurs. Channel radiances are transformed (through the use of the Planck function) to units of temperature, then compared to a-priori (in situ) temperatures for algorithm development. Adjustments to skin temperature are made through comparisons with in situ radiometer measurements.

4. Equipment: Sensor/Instrument Description: Collection Environment: MODIS instrument. More information on MODIS can be found here. Source/Platform: NASA Terra and Aqua satellites Source/Platform Mission Objectives: The Terra and Aqua platforms contain a number of instruments whose purpose is to observe the Earth's oceans, land and atmosphere to study global climate. Key Variables: Terra/Aqua is in a sun-synchronous near polar orbit at an altitude of 705 km with a descending node of 10:30 a.m. The MODIS sensor detects emitted and reflected radiance in 36 channels (windows) spanning the visible to IR spectrum (0.4-14.4 um). Quantization is 12 bit. More information can be found here. Principles of Operation: MODIS is a scanning radiometer whereby the viewing optics scan side-to-side with respect to the ground track via a rotating mirror. The scan rate is 20.3 rpm. Specifically (from http://ltpwww.gsfc.nasa.gov/modis/modis.html): "The Scan Mirror Assembly uses a continuously rotating double-sided scan mirror to scan +/- 55- degree driven by a motor encoder built to operate at 100 percent duty cycle throughout the 6-year instrument design life. The optical system consists of a two-mirror off-axis afocal telescope which directs energy to four refractive objective assemblies; one for each of the VIS, NIR, SWIR/MWIR and LWIR spectral regions covering a total spectral range of 0.4 to 14.4 um. " Sensor/Instrument Measurement Geometry: A +/- 55-degree scanning pattern at the Terra/Aqua orbit of 705 km altitude achieves a 2330 km ground swath providing global coverage every one to two days. Manufacturer of Sensor/Instrument: Raytheon Santa Barbara Remote Sensing, Goleta, California Calibration:

Specifications: For the IR channels onboard calibration consists of a v-groove Blackbody as well as a view to space. Additional onboard calibrators consist of a Solar Diffuser, a Spectroradiometric calibration assembly and a Solar Diffuser Stability Monitor. Tolerance: The noise equivalent temperature difference (NET) for the IR channels are: MODIS Channel Bandwidth (um) NET (degk) 20 3.66-3.84 0.05 22 3.929-3.989 0.07 23 4.02-4.08 0.07 31 10.78-11.28 0.05 32 11.77-12.27 0.05 Frequency of Calibration: A blackbody measurement is taken for each scan. 5. Data Acquisition Methods: Terra and Aqua capture data on onboard tape recorders for later retransmission. MODIS data (along with data from other sensors on Terra and Aqua ) are then transferred to ground stations in White Sands, New Mexico, via the Tracking and Data Relay Satellite System (TDRSS). The data are then sent to the EOS Data and Operations System (EDOS) at the Goddard Space Flight Center. After Level 0 processing at EDOS, the Ocean Biology Processing Group (OBPG) produces the Level 1A, Level 1B, geolocation and cloud mask products. Higher-level geophysical products are also produced by the OBPG. The JPL PO.DAAC is acting as a mirror site for MODIS Level 3 SST products distributed by the OBPG. 6. Observations: Data Notes: Currently the MODIS SST algorithm coefficients are derived by regressing MODIS brightness temperature against buoy SST matchups. Field Notes: Not Applicable 7. Data Description:

Spatial Characteristics: The MODIS SST products are distributed at various resolutions separated in ascending and descending orbits. The highest resolution for the Level 3 mapped products is 4.63 km. All Level 3 mapped products are derived from gridding the 4.63 km Level 3 binned data. The 4.63 km observations are themselves derived from binning and averaging (not subsampling) the nominal 1 km observations. Spatial Coverage: Global Spatial Coverage Map: Not available Spatial Resolution: 4.63 km, and 9.26 km (mapped products) Projection: Cylindrical equal angle projection for the mapped products. Grid Description: The 4.63 km mapped product has 4320 rows and 8640 columns The 9.26 km mapped product has 2160 rows and 4320 columns Temporal Characteristics: Temporal Coverage: Data are available from November 2000 to present for Terra products, and December 2002 to present for Aqua. Temporal Coverage Map: Not applicable Temporal Resolution: Daily, weekly (8 day), monthly and annual. Data Characteristics: Parameter/Variable:

Sea surface temperature Variable Description/Definition: The temperature of the sea surface Unit of Measurement: degrees Celsius Data Source: MODIS Data Range: -2 to 32 degrees Celsius Sample Data Record: Not available. 8. Data Organization: Data Granularity: Each Level 3 mapped product for each spatial and temporal resolution are stored in separate files for daytime and nighttime mid-ir and thermal IR data. The mapped products contain an SST array (scaled integers) and a quality flag array. File format is HDF version 4. A description of the Level 3 mapped filename format can be found here. Data Format: All data are stored in HDF4 format files. 9. Data Manipulations: Formulae: Derivation Techniques and Algorithms: The original SST derivation paradigm was designed to use a radiative transfer model in conjunction with atmospheric profile data from radiosonde or atmospheric models (to determine the atmospheric transmittance) to propagate the SST signal to the satellite accounting for absorption and scattering effects and derive the empirical SST algorithm coefficients (Brown and Minnett, 1999). This approach apparently has deficiencies due to improper radiometer characterization. Instead, the SST derivation is similar to the NLSST approach (Walton, 1988)

used in AVHRR processing whereby the coefficients are determined by regressing MODIS brightness temperature to known measured surface temperatures. In this case, drifting and moored buoys are used as the reference. Measurements from the M-AERI (Marine-Atmosphere Emitted Radiance Interferometer) in situ radiometer are then used to convert the regressed SST to a skin SST measurement. Data Processing Sequence: Processing Steps: Processed from level 1A at OBPG to geophsyical products. Processing Changes: Most recent version is 5.x for Terra products and 5.x for Aqua products. Calculations: Special Corrections/Adjustments: Currently the empirical coefficients in the MODIS SST algorithm are derived by regressing MODIS brightness temperatures to in situ observations from drifting and moored buoys. Measurements from the M-AERI in situ radiometer are then used to convert the regressed SST to a skin SST measurement (approximately -0.2 degc adjustment). Calculated Variables: Skin sea surface temperature. Graphs and Plots: Not applicable 10. Errors: Sources of Error: One of the greatest limitations is the obstruction by clouds in the field of view. Other sources of error include atmospheric gases and emissions, aerosols, as well as water surface characteristics. The daytime mid-ir SST suffer from reflected sunlight. Quality Assessment: Data Validation by Source: All quality control occurs at OBPG during Level 1 to 2 processing using an extensive suite of tests for cloud contamination etc. In constructing the bins of 1 km observations at each resolution, only

observations of the same quality are binned. Different quality levels are never mixed. For example, a bin of quality level 0 only contains the highest quality 1 km observations that passed all quality control tests. No 1 km pixels of a lessor quality are used to determine the statistics of this bin. Confidence Level/Accuracy Judgement: Unknown Measurement Error for Parameters: The SST data can be considered accurate to +/- 0.4 degrees Celsius Additional Quality Assessments: None Data Verification by Data Center: More information can be found in Brown and Minnett (1999) 11. Notes: Limitations of the Data: Known Problems with the Data: Daytime mid-ir SST products suffer from reflected sunlight contamination. Usage Guidance: It is highly recommended that the users filter the SST using the commensurate quality files. The flags are: 0 (good), 1 (questionable), 2 (clouds), 255 (land, gross clouds, and other errors). A quality flag of 0 is recommended. Flag 1 can be used under some circumstances. Any Other Relevant Information about the Study: Not applicable 12. Application of the Data Set: Global climate studies, heat transport and ocean circulation. 13. Future Modifications and Plans: None

14. Software: Software Description: The JPL PO.DAAC supplies IDL, C and FORTRAN read software for the MODIS HDF files. The C and FORTRAN read software require that the HDF v4 library be installed. Software Access: Read software can be found on the PO.DAAC FTP site. 15. Data Access: Contact Information: User Services Office Physical Oceanography Distributed Active Archive Center (PO.DAAC) Jet Propulsion Laboratory (JPL) Phone: (626) 744-5508 Fax: (626) 744-5506 Email: podaac@podaac.jpl.nasa.gov URL: http://podaac.jpl.nasa.gov Data Center Identification: Jet Propulsion Laboratory (JPL) Physical Oceanography Archive Center (PO.DAAC) Procedures for Obtaining Data: Level 3 mapped data are available on the PO.DAAC FTP site. Data Center Status/Plans: Ongoing 16. Output Products and Availability: Currently the Level 3 mapped products are only available via electronic FTP distribution. They are also available via POET, an interactive subsetting tool and also OPenDAP. 17. References: Walton, C.C., W. G. Pichel, and J.F. Sapper, 1998, The development and operational application of nonlinear algorithms for the measurement of sea surface temperatures with the NOAA polarorbiting environmental satellites, Journal of Geophysical Research, 103: (C12) 27999-28012.

Brown, O.B., and P.J. Minnett, 1999, MODIS Infrared Sea Surface Temperature Algorithm Theoretical Basis Document, Ver 2.0, http://modis.gsfc.nasa.gov/data/atbd/atbd_mod25.pdf 18. Glossary of Terms: Sea Surface Temperature: the temperature of the layer of sea water nearest the atmosphere. 19. List of Acronyms: AVHRR...Advanced Very High-Resolution Radiometer EOS...Earth Observing System FTP...File Transfer Protocol GAC...Global Area Coverage HDF...Hierarchical Data Format IFOV...Internal Field of View JPL...Jet Propulsion Laboratory MCSST...Multichannel Sea Surface Temperatures MODAPS...MODIS Adaptive Processing System NAVOCEANO...Naval Oceanographic Office NASA...National Aeronautics and Space Administration NOAA...National Oceanic and Atmospheric Administration OBPG...Ocean Biology Processing Group PO.DAAC...Physical Oceanography Distributed Active Archive Center SST...Sea Surface Temperature 20. Document Information: Document Revision Date: 25 April 2007 Document Review Date: 8 March 2002 Document ID: CL 02-0691 Citation: Document Curator: Ed Armstrong JPL PO.DAAC Document URL:

http://podaac.jpl.nasa.gov:2031/dataset_docs/modis_sst.html