Publications -- Query Results

Publications Home \| Show All \| Simple Search \| Advanced Search \| Journal Articles \| Reports \| White Papers	Login Quick Search: Field: contains: ...
1-1 of 1 record found matching your query:

Select All Deselect All

<< 1 >>

List View

Citations

Details

	Record
	Author	Liu, Y.; Minnett, P.J.
	Title	Sampling errors in satellite-derived infrared sea-surface temperatures. Part I: Global and regional MODIS fields			Type	Journal Article
	Year	2016	Publication	Remote Sensing of Environment	Abbreviated Journal	Remote Sensing of Environment
	Volume	177	Issue		Pages	48-64
	Keywords	Sea Surface Temperature (SST); Climate Data Records (CDR); MODIS; Sampling errors
	Abstract	Long time series of accurate Sea Surface Temperatures (SSTs) are needed to resolve subtle signals that may be indicative of a changing climate. Motivated by the stringent requirements on SST accuracy required for Climate Data Records (CDR) we quantify sampling errors in satellite SSTs. Infrared sensors, including the Moderate Resolution Imaging Spectroradiometer (MODIS), have sampling errors caused by incomplete coverage primarily due to clouds and inter-swath gaps (gaps between successive swaths/orbits). Unlike retrieval errors, the sampling errors are introduced when calculating mean values and in generating gap-free SST fields. We generate MODIS-sampled SST fields by superimposing MODIS cloud masks on top of the Multi-scale Ultrahigh Resolution (MUR) SST field for the same day. Based on the MODIS-sampled fields, we calculate sampling errors at different temporal and spatial resolutions to examine the impacts at different scales. Our results indicate that sampling errors are significant, more so in the high latitudes, especially the Arctic. The 30 degrees N-30 degrees S zonal band is found to have the smallest errors; a notable exception is the persistent negative errors found in the Tropical Instability Wave area, where the mesoscale ocean-atmosphere interaction leads to a more frequently satellite sampling above the cold sections of the wave area. The global mean sampling error is generally positive and increases approximately exponentially with missing data fraction at a fixed averaging interval, while error variability is mainly controlled by SST variability. Areas with persistent cloud cover have large sampling errors in temporally averaged SSTs. We conclude that the sampling error can be an important or even dominant component of the error budget of mean and gap-free SST fields. Climate data generation and interpretation of satellite-derived SST CDRs and their application must be conducted with due regard to the sampling error.
	Address
	Corporate Author				Thesis
	Publisher		Place of Publication		Editor
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN	0034-4257	ISBN		Medium
	Area		Expedition		Conference
	Notes				Approved	no
	Call Number	FCI @ refbase @			Serial	1012
Permanent link to this record

Select All Deselect All

<< 1 >>

List View

Citations

Details

All Found Records Selected Records:

Save Citations: Format:

Export Records: Format:

Home

CQL Search | Library Search | Show Record | Extract Citations

Help

The Florida Climate Institute (FCI) is a multi-disciplinary network of national and international research and public organizations, scientists, and individuals concerned with achieving a better understanding of climate variability and change.