Product showcase tac_sst_010

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Mercator Ocean International

cmems ga

Global SST product examples
• OSTIA Near real time foundation SSTs (the
temperature from which the diurnal cycle
develops)
• OSTIA Reprocessed foundation SSTs covering
late-1981 to 2019
• Daily average skin SSTs at 20 cm depth from late-
1981 to 2019 from the European Space Agency
Climate Change Initiative (ESA CCI) and the
Copernicus Climate Change Service (C3S)
Hourly average skin SSTs
produced daily in near
real time (left: differences
between the skin and
foundation SST)
Daily ensemble of
global level 4 analyses
produced around the
world

• Near real time, daily mean (night-time), L3S and L4 foundation SSTs (the temperature free of diurnal cycle)
at HR (high-res., 1/16°) and UHR (ultra-high res., 1/100°) spatial resolution from 2008 up to real time
• Reprocessed, daily mean (night-time), L4 foundation SSTs from 1982 to 2019 at 0.05° based on ESA CCI-
and C3S upstream L3C SST data
Mediterranean and Black Sea SST product examples
Upcoming products
Diurnal (hourly mean) sub-
skin SSTs produced daily in
near real time at 1/16°

Baltic Sea SST product examples
SST_BAL_SST_L4_NRT_OBSERVATIONS _010_007_b SST_BAL_SST_L3S_NRT_OBSERVATIONS_010_032

European Seas SST product examples
SST_EUR_PHY_L4_NRT_010_031
Operational since December 2020
SST_EUR_SST_L3C_NRT_OBSERVATIONS_010_009_b
METEOFRANCE-EUR-SST_L3MONOSENSOR_NRT-OBS-SLSTRB-
EUR-AVHRR_METOP_B_FULL_TIME_SERIE
Operational since March2020

European North West shelf/Iberia Biscay Irish Seas SST product example
Level 4 analysis, covering the European North
West shelf/Iberia Biscay Irish Seas (0.02° x 0.02°)
Both NRT and REP products result from the merging and
interpolation of various satellite SST level 2 data after inter-
calibration and bias correction
SST_ATL_SST_L4_NRT_OBSERVATIONS_010_025
SST_ATL_SST_L4_REP_OBSERVATIONS_010_025

Sentinel-1 satellites, ESA’s Synthetic Aperture Radar (SAR) mission, provide continuous data from the Earth surface in weekly to biweekly time intervals. This data availability provides an unprecedented opportunity to continuously monitor the Earth surface motion in areas prone to geohazards; such as regions of high seismic and volcanic activities, with the end goal of supporting the Early Warning Systems. However, the great challenge is to derive insights from Terabytes of satellite image sequences, in a computationally-efficient and time-critical manner. We’ve risen to this challenge by designing innovative signal processing and deep learning algorithms to efficiently mine this invaluable wealth of data. This talk gives on overview of our designed solutions, as well as a demonstration of these solutions in the Tectonic and Volcanic monitoring of South America (TecVolSA) project.

6.1.3 Methodologies for climate rational for adaptation

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The European Copernicus programme with its Sentinel satellites is one of the most ambitious Earth observation programmes to date with all data being freely accessible. Copernicus addresses several thematic areas including land, marine, atmosphere, climate change, emergency management and security. Different satellite types have been and will be further launched; hence, weather independent Radar data, optical and infrared data are now available. In Europe the revisit time is between 3-5 days, allowing to monitor the same areas at high frequency. Actual land use, forest structure, and vegetation phases can be recorded promptly, to name only a few examples. While the Copernicus program is well perceived in the Earth observation community, the new data sets are still widely unnoticed or underused in the GIS community as well as in public administration, also due to the sheer amount of available data in the Petabyte range and the need of notable computational power. This is a great opportunity for specialized service providers to develop new applications for administration, science, and business in order to find new ways of retrieving information from Petabytes of raw data. In our talk we will present an open source approach to a processing such data in a cloud based system, providing standardized OGC Web Services by GeoServer and MapProxy software. The backend of the system is able to timely post-process and analyze Sentinel data in an automated way using the GRASS GIS and GDAL software. We have developed a REST API based system that allows the user to automatically derive thematic data layers based on algorithms provided by the portal. This greatly simplifies the user’s life since own topical layers can be generated without the need of deep technical knowledge of software, hardware and time series management. We believe that this approach likely widens up the potential user group of the Copernicus program. At the same time, it connects two worlds that are often unnecessarily disentangled: the GIS and the remote sensing communities. The presentation is completed by some examples and practical use cases, illustrating the idea of the workflow and the architecture of the portal.

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Mercator Ocean newsletter 33

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Greetings all, This month’s newsletter is devoted to ocean indices aiming at a better understanding of the state of the ocean climate. Ocean climate indices can be linked to major patterns of climate variability and usually have a significant social impact. The estimation of the ocean climate indices along with their uncertainty is thus crucial: It gives an indication of our ability to measure the ocean. It is as well a useful tool for decision making. Ocean climate indices also provide an at-a-glance overview of the state of the ocean climate, and a way to talk to a wider audience about the ocean observing system. Several groups of experts are now working on various ocean indicators using ocean forecast models, satellite data and reanalysis models in observing system simulation experiments, among which the OOPC, NOAA and MERSEA/Boss4Gmes communities for example: http://ioc3.unesco.org/oopc/state_of_the_ocean/index.php http://www.cpc.ncep.noaa.gov/products/analysis_monitoring/enso_advisory/ http://www.aoml.noaa.gov/phod/cyclone/data/method.html http://www.mersea.eu.org/Indicators-with-B4G.html Scientific articles about Ocean indices in the present Newsletter are displayed as follows: The first article by Von Schuckmann et al. is dealing with the estimation of global ocean indicators from a gridded hydrographic field. Then, Crosnier et al. are describing the need to conduct intercomparison of model analyses and forecast in order for experts to provide a reliable scientific expertise on ocean climate indicators. The next article by Coppini et al. is telling us about ocean indices computed from the Mediterranean Forecasting System for the European Environment Agency and Boss4Gmes. Then Buarque et al. are revisiting the Tropical Cyclone Heat Potential Index in order to better represent the ocean heat content that interacts with Hurricane. The last article by Greiner et al. is dealing with the assessment of robust ocean indicators and gives an example with oceanic predictors for the Sahel precipitations. The next July 2009 newsletter will review the current work on data assimilation and its techniques and progress for operational oceanography. We wish you a pleasant reading.

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Product showcase tac_sst_010

1. SST S S T - T A C P r o d u c t s

2. Global SST product examples • OSTIA Near real time foundation SSTs (the temperature from which the diurnal cycle develops) • OSTIA Reprocessed foundation SSTs covering late-1981 to 2019 • Daily average skin SSTs at 20 cm depth from late- 1981 to 2019 from the European Space Agency Climate Change Initiative (ESA CCI) and the Copernicus Climate Change Service (C3S) Hourly average skin SSTs produced daily in near real time (left: differences between the skin and foundation SST) Daily ensemble of global level 4 analyses produced around the world

3. • Near real time, daily mean (night-time), L3S and L4 foundation SSTs (the temperature free of diurnal cycle) at HR (high-res., 1/16°) and UHR (ultra-high res., 1/100°) spatial resolution from 2008 up to real time • Reprocessed, daily mean (night-time), L4 foundation SSTs from 1982 to 2019 at 0.05° based on ESA CCI- and C3S upstream L3C SST data Mediterranean and Black Sea SST product examples Upcoming products Diurnal (hourly mean) sub- skin SSTs produced daily in near real time at 1/16°

4. Baltic Sea SST product examples SST_BAL_SST_L4_NRT_OBSERVATIONS _010_007_b SST_BAL_SST_L3S_NRT_OBSERVATIONS_010_032

5. European Seas SST product examples SST_EUR_PHY_L4_NRT_010_031 Operational since December 2020 SST_EUR_SST_L3C_NRT_OBSERVATIONS_010_009_b METEOFRANCE-EUR-SST_L3MONOSENSOR_NRT-OBS-SLSTRB- EUR-AVHRR_METOP_B_FULL_TIME_SERIE Operational since March2020

6. European North West shelf/Iberia Biscay Irish Seas SST product example Level 4 analysis, covering the European North West shelf/Iberia Biscay Irish Seas (0.02° x 0.02°) Both NRT and REP products result from the merging and interpolation of various satellite SST level 2 data after inter- calibration and bias correction SST_ATL_SST_L4_NRT_OBSERVATIONS_010_025 SST_ATL_SST_L4_REP_OBSERVATIONS_010_025

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