The main objective of the SWIM Level 3 (L3) product is to provide global gridded wave statistics from the along-track directional wave spectra measures, as observed with SWIM instrument onboard CFOSAT. CFOSAT (Chinese French Ocean SATellite) is a french-chinese mission launched in 2018, whose aim is to provide wind (SCAT instrument) and wave (SWIM instrument) measurements over the sea surface. The processing uses the integrated parameters (wave length, significant wave height, direction) of the wave systems associated with the individual partitions retrieved from SWIM wave spectra, computing monthly statistics such as distribution, min, max, mean and median over a global 2 degree resolution grid. Three sub-products are generated separately for each SWIM beam (from 4° to 10°) from respectively the SWIM Level 2 spectra produced by the CWWIC center (CNES), the SWIM Level 2S spectra produced by the IWWOC center (Ifremer) and forecast spectra produced from WaveWatch3 wave model at Ifremer as an independent source for comparison. The SWIM level 3 dataset is generated in delayed mode. It is currently mainly meant as a validation dataset aiming at inter-comparing the different SWIM Level 2 between each other, with an independent model (here WaveWatch3) or other external similar wave statistics products. The SWIM L3 dataset is generated and distributed by Ifremer / CERSAT in the frame of the Ifremer Wind and Wave Operation Center (IWWOC) co-funded by Ifremer and CNES and dedicated to the processing of the delayed mode data of CFOSAT mission.

The main objectives of this dataset is to gather the ocean swells measured by different sensors, including satellite and in-situ sources, that were generated by a given tropical cyclone (TC). This dataset aims at providing characteristics of these swells such as their direction, wavelength (or period) and energy but also the date when they left the influence of the tropical cyclone wind to propagate freely. Wave spectra in tropical cyclones vary strongly per quadrant and provide information about the current and past state of the wave field. However, inside TCs, waves measurements including the wave system direction, energy and wavelength are rare and difficult to obtain with in-situ and remote sensing technics. For this dataset, both moored and drifting buoys are considered as long as they provide wave systems measurements. For the satellite contribution, Synthetic Aperture Radar (SAR) and real aperture radar (RAR) instruments can significantly contribute to the TC-generated waves documentation. Indeed, ocean wave spectra can be derived from modulations of the backscatter in SAR and RAR signal. SAR on board European satellite and in particular the SAR series developed since ERS-1 by ESA and now ESA/Copernicus with Sentinel-1 mission (S-1) are good candidates to provide these ocean waves systems characteristics thanks to the dedicated acquisition mode : the so-called Wave Mode. The wave spectrometer SWIM developed by the French space Agency (CNES) and embedded on the Chinese-French Oceanography SATellite (CFOSAT) has been launched more recently with a new measurement concept relying on a RAR and can certainly complement the S-1 data collection. Although the reasons are different, these two systems are limited for measuring waves generation area within the TC vortex where strong rain rates and wind regimes are observed. Far enough from their source, satellite acquisitions are thus expected to be able to observe these ocean swells during more favorable met-ocean conditions for waves retrieval inversion. As a consequence, our analysis is focused on waves originating from TC but that have been able to propagate far from their source. The analysis of swell measurements far from their area of generation to locate the storm source has been firstly applied to data from one single in-situ wave station (wave energy with frequency and direction) collected 2 miles off shore from San Clemente Island, California and extended to a network of several wave stations in the sixties. More recently, the gathering of swell system observed with SAR far from a storm to characterize the waves properties across the ocean has proven to be efficient in the case of extra-tropical storms. Yet, such analysis is not adapted to Tropical Cyclone whose size is much smaller and currently existing wave datasets do not allow for an accurate monitoring of the tropical cyclones swells. This multi-sensor Level-3 tropical cyclone waves dataset intends to fill this gap and opens for an alternate way of estimating tropical cyclone waves properties over all ocean basins and for all tropical cyclones. This dataset was produced in the frame of the ESA funded Marine Atmosphere eXtreme Satellite Synergy (MAXSS) project. The primary objective of the ESA Marine Atmosphere eXtreme Satellite Synergy (MAXSS) project is to provide guidance and innovative methodologies to maximize the synergetic use of available Earth Observation data (satellite, in situ) to improve understanding about the multi-scale dynamical characteristics of extreme air-sea interaction.

The primary objective of the ESA Marine Atmosphere eXtreme Satellite Synergy (MAXSS) project is to provide guidance and innovative methodologies to maximize the synergetic use of available Earth Observation data (satellite, in situ) to improve understanding about the multi-scale dynamical characteristics of extreme air-sea interaction. This dataset, produced in the frame of MAXSS project, provides multi-variate observations for Arctic polar lows (PL), for a selection of storm tracks extracted from Rojo et al (2019) during the period 2010-2018. The observations are taken from more than 35 satellite, numerical model and in situ sources, providing the inner and surface ocean conditions for a comprehensive range of parameters (sea surface height, surface winds, waves, precipitation, temperature, salinity, ocean colour, ...) before, during and after the storm passage. Different colocation radii and time windows are used depending on the parameter and observation dataset. The assembled data are stored in a standardized NetCDF4 file format and organised per basin, year, and storm name to ease data manipulation for users that are not used to work with this wealth of data.