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chlorophyll/chlorophyll_sub1_monthly_deviation (ImageServer)

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Service Description: Satellite-based assessments of ocean color began in 1978 with the launch of the Coastal Zone Color Scanner (CZCS) aboard the NASA Nimbus 7 satellite. Following a decade-long break in observations, there have been continuous satellite ocean color measurements since 1997 with Sea-Viewing Wide Field-of-View Sensor (SeaWiFS), followed by Medium Resolution Imaging Spectrometer (MERIS), Moderate Resolution Imaging Spectroradiometer (MODIS),Visible Infrared Imaging Radiometer Suite (VIIRS),Ocean Land Color Instrument (OLCI), Second Generation Global Imager (SGLI) and Ocean Color and Temperature Scanner (OCTS) with additional sensors in development. Data gaps from individual sensors are common due to revisit cycles, cloud cover, and spurious retrievals resulting from a host of confounding atmospheric and aquatic conditions. Some of these issues have been addressed by combining data from multiple sensors and creating a consistent, merged ocean color product (e.g., surface ocean chlorophyll-a concentration). The ESA Ocean Color CCI (OC-CCI) project, led by Plymouth Marine Laboratory (PML), has produced a consistent, merged chlorophyll-a product from SeaWiFS, MODIS, MERIS and VIIRS, spanning the years 1997 to 2019 (Sathyendranath et al., 2018). The merged multi-sensor product will be updated in both time and with data from additional sensors (e.g., OLCI) as part of the Copernicus Climate Change Service (C3S) and the Copernicus Marine Service (CMEMS) that will continue the time series on an operational basis. Future OC-CCI releases will also include algorithmic improvements developed under the CCI+ initiative. Chlorophyll-a concentrations for this indicator are obtained from the global ocean, 4 km spatial data from multiple sensors and creating a consistent, merged ocean color product for each pixel within a country’s EEZ.For purposes of this sub-indicator, reporting year values are compared to a baseline of years 2000 to 2004. The baseline climatology was calculated as the mean of the 5 years of each month by pixel (e.g., mean of 5 years of January) resulting in a 5 year mean of each calendar month over the period 2000 to 2004. The processing steps are outlined.

Name: chlorophyll/chlorophyll_sub1_monthly_deviation

Description: Satellite-based assessments of ocean color began in 1978 with the launch of the Coastal Zone Color Scanner (CZCS) aboard the NASA Nimbus 7 satellite. Following a decade-long break in observations, there have been continuous satellite ocean color measurements since 1997 with Sea-Viewing Wide Field-of-View Sensor (SeaWiFS), followed by Medium Resolution Imaging Spectrometer (MERIS), Moderate Resolution Imaging Spectroradiometer (MODIS),Visible Infrared Imaging Radiometer Suite (VIIRS),Ocean Land Color Instrument (OLCI), Second Generation Global Imager (SGLI) and Ocean Color and Temperature Scanner (OCTS) with additional sensors in development. Data gaps from individual sensors are common due to revisit cycles, cloud cover, and spurious retrievals resulting from a host of confounding atmospheric and aquatic conditions. Some of these issues have been addressed by combining data from multiple sensors and creating a consistent, merged ocean color product (e.g., surface ocean chlorophyll-a concentration). The ESA Ocean Color CCI (OC-CCI) project, led by Plymouth Marine Laboratory (PML), has produced a consistent, merged chlorophyll-a product from SeaWiFS, MODIS, MERIS and VIIRS, spanning the years 1997 to 2019 (Sathyendranath et al., 2018). The merged multi-sensor product will be updated in both time and with data from additional sensors (e.g., OLCI) as part of the Copernicus Climate Change Service (C3S) and the Copernicus Marine Service (CMEMS) that will continue the time series on an operational basis. Future OC-CCI releases will also include algorithmic improvements developed under the CCI+ initiative. Chlorophyll-a concentrations for this indicator are obtained from the global ocean, 4 km spatial data from multiple sensors and creating a consistent, merged ocean color product for each pixel within a country’s EEZ.For purposes of this sub-indicator, reporting year values are compared to a baseline of years 2000 to 2004. The baseline climatology was calculated as the mean of the 5 years of each month by pixel (e.g., mean of 5 years of January) resulting in a 5 year mean of each calendar month over the period 2000 to 2004. The processing steps are outlined.

Single Fused Map Cache: false

Extent: Initial Extent: Full Extent: Time Info: Pixel Size X: 4638.185806500943

Pixel Size Y: 4638.185806500943

Band Count: 1

Pixel Type: F32

RasterFunction Infos: {"rasterFunctionInfos": [{ "name": "None", "description": "", "help": "" }]}

Mensuration Capabilities: Basic

Inspection Capabilities:

Has Histograms: true

Has Colormap: false

Has Multi Dimensions : true

Rendering Rule:

Min Scale: 0

Max Scale: 0

Copyright Text: GEO Blue Planet, United Nations Environment Programme (UNEP), Esri

Service Data Type: esriImageServiceDataTypeScientific

Min Values: 0.005671035964041948

Max Values: 99.97590637207031

Mean Values: 1.8676736812066566

Standard Deviation Values: 2.8709626827284445

Object ID Field:

Fields: None

Default Mosaic Method: Center

Allowed Mosaic Methods:

SortField:

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Mosaic Operator: First

Default Compression Quality: 75

Default Resampling Method: Bilinear

Max Record Count: null

Max Image Height: 4100

Max Image Width: 15000

Max Download Image Count: null

Max Mosaic Image Count: null

Allow Raster Function: true

Allow Copy: true

Allow Analysis: true

Allow Compute TiePoints: false

Supports Statistics: false

Supports Advanced Queries: false

Use StandardizedQueries: true

Raster Type Infos: Has Raster Attribute Table: false

Edit Fields Info: null

Ownership Based AccessControl For Rasters: null

Child Resources:   Info   Histograms   Statistics   Key Properties   Legend   Raster Function Infos   Multidimensional Info   Slices

Supported Operations:   Export Image   Identify   Measure   Compute Histograms   Compute Statistics Histograms   Get Samples   Compute Class Statistics   Query Boundary   Compute Pixel Location   Compute Angles   Validate   Project