Globally Gridded Satellite Observations for Climate Studies

Geostationary satellites have provided routine, high temporal resolution Earth observations since the 1970s. Despite the long period of record, use of these data in climate studies has been limited for numerous reasons, among them that no central archive of geostationary data for all international satellites exists, full temporal and spatial resolution data are voluminous, and diverse calibration and navigation formats encumber the uniform processing needed for multisatellite climate studies. The International Satellite Cloud Climatology Project (ISCCP) set the stage for overcoming these issues by archiving a subset of the full-resolution geostationary data at ~10-km resolution at 3-hourly intervals since 1983. Recent efforts at NOAA's National Climatic Data Center to provide convenient access to these data include remapping the data to a standard map projection, recalibrating the data to optimize temporal homogeneity, extending the record of observations back to 1980, and reformatting the data for broad ...

[1]  Russell L. Elsberry,et al.  Extratropical Transition of Western North Pacific Tropical Cyclones: An Overview and Conceptual Model of the Transformation Stage , 2000 .

[2]  Kenneth R. Knapp,et al.  Scientific data stewardship of international satellite cloud climatology project B1 global geostationary observations , 2008 .

[3]  N. C. Strugnell,et al.  First operational BRDF, albedo nadir reflectance products from MODIS , 2002 .

[4]  C. Gautier,et al.  A Satellite-derived Climatology of the ITCZ , 1993 .

[5]  Robert G. Ellingson,et al.  Development of the HIRS Outgoing Longwave Radiation Climate Dataset , 2007 .

[6]  Johannes Schmetz,et al.  Monitoring deep convection and convective overshooting with METEOSAT , 1997 .

[7]  Christopher C. Hennon,et al.  An Objective Algorithm for Detecting and Tracking Tropical Cloud Clusters: Implications for Tropical Cyclogenesis Prediction , 2011 .

[8]  Mark A. Bourassa,et al.  Uncertainty in Scatterometer-Derived Vorticity , 2010 .

[9]  Christopher C. Hennon,et al.  Forecasting Tropical Cyclogenesis over the Atlantic Basin Using Large-Scale Data , 2003 .

[10]  Russ Rew,et al.  NetCDF: an interface for scientific data access , 1990, IEEE Computer Graphics and Applications.

[11]  R. E. Hart,et al.  A Climatology of the Extratropical Transition of Atlantic Tropical Cyclones. , 2001 .

[12]  F. Bretherton,et al.  Upper tropospheric relative humidity from the GOES 6.7 μm channel: method and climatology for July 1987 , 1993 .

[13]  B. Pinty,et al.  Generating Global Surface Albedo Products from Multiple Geostationary Satellites , 2008 .

[14]  J. Janowiak,et al.  The Version 2 Global Precipitation Climatology Project (GPCP) Monthly Precipitation Analysis (1979-Present) , 2003 .

[15]  Yves M. Govaerts,et al.  Towards Multidecadal Consistent Meteosat Surface Albedo Time Series , 2010, Remote. Sens..

[16]  William B. Rossow,et al.  Normalization and calibration of geostationary satellite radiances for the International Satellite Cloud Climatology Project , 1993 .

[17]  Donna Mergler,et al.  Methylmercury Exposure and Health Effects in Humans: A Worldwide Concern , 2007, Ambio.

[18]  B. Hanstrum,et al.  The Capture of Tropical Cyclones by Cold Fronts off the West Coast of Australia , 1994 .

[19]  G. Magnusdottir,et al.  Intertropical Convergence Zones during the Active Season in Daily Data , 2008 .

[20]  V. F. Dvorak.  Tropical cyclone intensity analysis using satellite data , 1984 .

[21]  G. Gill,et al.  Processes influencing rainfall deposition of mercury in Florida. , 2001, Environmental science & technology.

[22]  A. Gruber,et al.  GOES Multispectral Rainfall Algorithm (GMSRA) , 2001 .

[23]  Thomas A. Cram,et al.  Estimating Hurricane Wind Structure in the Absence of Aircraft Reconnaissance , 2007 .

[24]  J. Susskind,et al.  Global Precipitation at One-Degree Daily Resolution from Multisatellite Observations , 2001 .

[25]  Nicola Pirrone,et al.  A Synthesis of Progress and Uncertainties in Attributing the Sources of Mercury in Deposition , 2007, Ambio.

[26]  M. Murray,et al.  Effects of Environmental Methylmercury on the Health of Wild Birds, Mammals, and Fish , 2007, Ambio.

[27]  A. Smirnov,et al.  AERONET-a federated instrument network and data archive for aerosol Characterization , 1998 .

[28]  Chris Funk,et al.  Mapping recent decadal climate variations in precipitation and temperature across eastern Africa and the Sahel , 2012 .

[29]  Mark A. Bourassa,et al.  EARLY DETECTION OF TROPICAL CYCLONES USING SEAWINDS-DERIVED VORTICITY , 2001 .

[30]  Padhraic Smyth,et al.  Diurnal cycle of the Intertropical Convergence Zone in the east Pacific , 2010 .

[31]  Cheng-shang Lee,et al.  Observational Analysis of Tropical Cyclogenesis in the Western North Pacific. Part I: Structural Evolution of Cloud Clusters , 1989 .

[32]  Tomás Soler,et al.  Determination of Look Angles to Geostationary Communication Satellites , 1994 .

[33]  Charles S. Zender,et al.  Analysis of self-describing gridded geoscience data with netCDF Operators (NCO) , 2008, Environ. Model. Softw..

[34]  J. Janowiak,et al.  A Real–Time Global Half–Hourly Pixel–Resolution Infrared Dataset and Its Applications , 2001 .

[35]  J. Janowiak,et al.  CMORPH: A Method that Produces Global Precipitation Estimates from Passive Microwave and Infrared Data at High Spatial and Temporal Resolution , 2004 .

[36]  A. Heidinger,et al.  The HIRS outgoing longwave radiation product from hybrid polar and geosynchronous satellite observations , 2004 .

[37]  D. Jacob,et al.  Seasonal and spatial patterns of mercury wet deposition in the United States: Constraints on the contribution from North American anthropogenic sources , 2008 .

[38]  George J. Huffman,et al.  Latitudinally and seasonally dependent zenith-angle corrections for geostationary satellite IR brightness temperatures , 2001 .

[39]  Lei Shi,et al.  Scene Radiance–Dependent Intersatellite Biases of HIRS Longwave Channels , 2008 .

[40]  Thomas M. Smith,et al.  An Improved In Situ and Satellite SST Analysis for Climate , 2002 .

[41]  Sarah C. Jones,et al.  The extratropical transition of tropical cyclones : forecast challenges, current understanding, and future directions , 2003 .

[42]  Kenneth R. Knapp,et al.  Quantification of aerosol signal in GOES 8 visible imagery over the United States , 2002 .

[43]  G. Magnusdottir,et al.  The ITCZ in the central and eastern pacific on synoptic time scales , 2006 .

[44]  F. J. Turk,et al.  Toward improved characterization of remotely sensed precipitation regimes with MODIS/AMSR-E blended data techniques , 2005, IEEE Transactions on Geoscience and Remote Sensing.

[45]  Kenneth R. Knapp,et al.  New global tropical cyclone data set from ISCCP B1 geostationary satellite observations , 2007 .

[46]  M. Sinclair.  Extratropical Transition of Southwest Pacific Tropical Cyclones. Part I: Climatology and Mean Structure Changes , 2002 .

[47]  Changyong Cao,et al.  Spectral Bias Estimation of Historical HIRS Using IASI Observations for Improved Fundamental Climate Data Records , 2009 .

[48]  R. Murnane,et al.  A globally consistent reanalysis of hurricane variability and trends , 2007 .

[49]  J. Elsner,et al.  The increasing intensity of the strongest tropical cyclones , 2008, Nature.

[50]  B. Soden,et al.  Diurnal cycle of convection, clouds, and water vapor in the tropical upper troposphere: Satellites versus a general circulation model , 2004 .

[51]  V. F. Dvorak.  Tropical Cyclone Intensity Analysis and Forecasting from Satellite Imagery , 1975 .

[52]  Bruce R. Barkstrom,et al.  Scientific Data Stewardship: Lessons Learned from a Satallite–Data Rescue Effort , 2007 .

[53]  Hal S. Stern,et al.  Detecting the ITCZ in Instantaneous Satellite Data using Spatiotemporal Statistical Modeling: ITCZ Climatology in the East Pacific , 2011 .