Mean, maximum and minimum sea surface temperature maps of 2020

The superficial sea temperature (SST) map package was built with daily-mean data remotely collected. The package contains mean, max, min SST maps at high resolution (~1km) collected during 2020. The maps were also built over the four quarters of the year. These layers are provided with the suffixes Q1 to Q4.

Date ( Creation ): 2020-11-11

Identifier: https://geonetwork.bioinfo.szn.it/geonetwork/srv/ita/catalog.search#/metadata/4d976fb1-2854-4258-a099-0eccc340ad4d

Credit: SZN

Status: Completed

Resource provider

Stazione Zoologica Anton Dohrn - Salvatore Valente ( )

Maintenance and update frequency: As needed

Keywords

feamp
campania
temperature

GEMET - INSPIRE themes, version 1.0 GEMET - INSPIRE themes, version 1.0 ( Theme )

Hydrography

Use limitation: None

Use constraints: Other restrictions

Other constraints: Data policy of the project (link)

Access constraints: Other restrictions

Other constraints: Data policy of the project (link)

Classification: Unclassified

Spatial representation type: Grid

Distance: 0.01 degree

Metadata language: it

Character set: UTF8

Topic category

Oceans

Reference system identifier: WGS 1984 (EPSG 4326)

Spatial representation info

No information provided.

Number of dimensions: 3

Cell geometry: Area

Distribution format

GeoTiff ( .tif )

Distributor

Stazione Zoologica Antonio Dohrn - Marilù Chiusano ( BIOINforMA BIOINformatics FOR MArine biology Bioinformatics Services, Consultancy and Education )

OnLine resource: https://geonode.bioinfo.szn.it/s/9TC9TrPFrpxTZxZ ( WWW:LINK-1.0-http--link )

Hierarchy level: Dataset

Other: raster

Conformance result

Date ( Revision ): 2020-08-04

Explanation: Validated in Geonetwork according to the ISO19115 rules (23/23) and the INSPIRE rules (29/29)

Pass: Yes

Statement: The rasters were built in R statistical software using public available data downloaded from Copernicus Marine Environment Monitoring Service (https://resources.marine.copernicus.eu/?option=com_csw&task=results). The netCDF files were converted into 3-dimensional arrays (longitude, latitude and time) and reanalyzed in order to extract the mean/max/min value of each pixel over the year and over a specific quarter of the year.