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  • Author or Editor: Gudrun Magnusdottir x
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Caroline L. Bain
,
Jorge De Paz
,
Jason Kramer
,
Gudrun Magnusdottir
,
Padhraic Smyth
,
Hal Stern
, and
Chia-chi Wang

Abstract

A Markov random field (MRF) statistical model is introduced, developed, and validated for detecting the east Pacific intertropical convergence zone in instantaneous satellite data from May through October. The MRF statistical model uses satellite data at a given location as well as information from its neighboring points (in time and space) to decide whether the given point is classified as ITCZ or non-ITCZ. Two different labels of ITCZ occurrence are produced. IR-only labels result from running the model with 3-hourly infrared data available for a 30-yr period, 1980–2009. All-data labels result from running the model with additional satellite data (visible and total precipitable water), available from 1995 to 2008. IR-only labels detect less area of ITCZ than all-data labels, especially where the ITCZ is shallower. Yet, qualitatively, the results for the two sets of labels are similar.

The seasonal distribution of the ITCZ through the summer half year is presented, showing typical location and extent. The ITCZ is mostly confined to the eastern Pacific in May, and becomes more zonally distributed toward September and October each year. Northward and westward shifts in the location of the ITCZ occur in line with the seasonal cycle and warm sea surface temperatures. The ITCZ is quite variable on interannual time scales and highly correlated with ENSO variability. When the ENSO signal was removed from labels, interannual variability remained high. The resulting IR-only labels, representing the longer time series, showed no evidence of a trend in location nor evidence of a trend in area for the 30-yr period.

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Kenneth R. Knapp
,
Steve Ansari
,
Caroline L. Bain
,
Mark A. Bourassa
,
Michael J. Dickinson
,
Chris Funk
,
Chip N. Helms
,
Christopher C. Hennon
,
Christopher D. Holmes
,
George J. Huffman
,
James P. Kossin
,
Hai-Tien Lee
,
Alexander Loew
, and
Gudrun Magnusdottir

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 public distribution. The Gridded Satellite (GridSat) dataset includes observations from the visible, infrared window, and infrared water vapor channels. Data are stored in Network Common Data Format (netCDF) using standards that permit a wide variety of tools and libraries to process the data quickly and easily. A novel data layering approach, together with appropriate satellite and file metadata, allows users to access GridSat data at varying levels of complexity based on their needs. The result is a climate data record already in use by the meteorological community. Examples include reanalysis of tropical cyclones, studies of global precipitation, and detection and tracking of the intertropical convergence zone.

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Mark A. Bourassa
,
Sarah T. Gille
,
Cecilia Bitz
,
David Carlson
,
Ivana Cerovecki
,
Carol Anne Clayson
,
Meghan F. Cronin
,
Will M. Drennan
,
Chris W. Fairall
,
Ross N. Hoffman
,
Gudrun Magnusdottir
,
Rachel T. Pinker
,
Ian A. Renfrew
,
Mark Serreze
,
Kevin Speer
,
Lynne D. Talley
, and
Gary A. Wick

Polar regions have great sensitivity to climate forcing; however, understanding of the physical processes coupling the atmosphere and ocean in these regions is relatively poor. Improving our knowledge of high-latitude surface fluxes will require close collaboration among meteorologists, oceanographers, ice physicists, and climatologists, and between observationalists and modelers, as well as new combinations of in situ measurements and satellite remote sensing. This article describes the deficiencies in our current state of knowledge about air–sea surface fluxes in high latitudes, the sensitivity of various high-latitude processes to changes in surface fluxes, and the scientific requirements for surface fluxes at high latitudes. We inventory the reasons, both logistical and physical, why existing flux products do not meet these requirements. Capturing an annual cycle in fluxes requires that instruments function through long periods of cold polar darkness, often far from support services, in situations subject to icing and extreme wave conditions. Furthermore, frequent cloud cover at high latitudes restricts the availability of surface and atmospheric data from visible and infrared (IR) wavelength satellite sensors. Recommendations are made for improving high-latitude fluxes, including 1) acquiring more in situ observations, 2) developing improved satellite-flux-observing capabilities, 3) making observations and flux products more accessible, and 4) encouraging flux intercomparisons.

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