Exploitation of CryoSat 2 data over the open and coastal ocean

Greenland Geothermal Heat Flow Database and Map

Climate change is one of the greatest societal challenges of the 21st century. The dominant source of global warming is the increase of anthropogenic greenhouse gases in the Earth`s atmosphere. atmosphere. The two most important of those species are carbon dioxide (CO2) and methane (CH4). Together they account for ~82% of the anthropogenic radiative forcing. However, uncertainties in our knowledge of the budgets of these gases, which are determined by their sources and sinks, as well as inadequately understood feedback mechanisms, limit the accuracy of current climate change projections from the local to the global scale. To reliably predict the climate of our planet, and to guide political conventions on greenhouse gas avoidance, adequate knowledge of the sources and sinks of these greenhouse gases, their feedbacks, and the quantification of natural versus anthropogenic fluxes is mandatory. Wetland emissions of methane constitute the largest single source of methane to the atmosphere, even when considering all anthropogenic emissions, and are the most uncertain part of the budget. After the tropics, the largest distribution of wetlands is in the Arctic. The Arctic is warming twice as fast as compared to the global average, making climate changess polar effects more intense than anywhere else in the world. The Arctic accounts for nearly 50% of all organic carbon stored in the planetss soil but rising temperatures and thawing permafrost threatens its stability. The main objectives and tasks of MethaneCAMP are to: Collaborate and coordinate with the AMPAC (Artic Methane and Permafrost Challenge) initiative and forming AMPAC network aiming to contribute to bottom:up and top-down estimates of changes in methane emissions in the Arctic. Prepare a high-latitude-focused assessment of current atmospheric CH4 retrievals from medium spatial resolution and high spatial resolution instruments. Identify the improvement potential for high-latitude retrievals of CH4, test and validate these improvements and synthesize the potential of joint strategies. Analyse the changes in the Arctic CH4 with specific focus on i) quantifying longer:term trends, ii) identifying hot spots directly from observations, and iii) studying the apportionment between biogenic and anthropogenic CH4 sources by employing multi-scale Arctic CH4 observations in inverse modelling.

Gridded product containing a spatial interpolation of the point product onto a uniform grid of elevation and uncertainty. The gridded product is published on a monthly basis with one product per region on a 2km grid in polar stereographic coordinates. The monthly product contains 3 months of data on a rolling basis each month and uses the Thematic point product as its input. For example, the January 2020 gridded product will contain point data for a window starting on 1st December 2019 and ending on 29th February 2020.

Estimates of these four freshwater fluxes: discharge from rivers; inflow through ice and melt run off; outflow of freshwater in sea ice; and in/outflow of freshwater through ocean currents.

Sea Surface Salinity (SSS) is a key indicator of the freshwater fluxes and an important variable to understand the changes the Arctic is facing. However, salinity in-situ measurements are very sparse in the Arctic region. For this reason, remote sensing salinity measurements (currently provided by L-band radiometry satellites, SMOS and SMAP) are of special relevance for this region. The retrieval of SSS in the Arctic represents a challenge, because brightness temperatures measured by L-band satellites are less sensitive to salinity in cold waters. An additional drawback consists in the presence of sea ice, that contaminates the brightness temperature and must be adequately processed. The ESA Arctic+ Salinity project (Dec 2018 – June 2020) will contribute to reduce the knowledge gap in the characterization of the freshwater flux changes in the Arctic region.

Satellite LRM, SAR, SARIN polar altimeter product generated from Cryosat data by DTU Space

Automated open source processing chain using Sentinel-3 OLCI and SLSTR sensors to determine a dry/wet snow and clean/polluted bare ice spectral and broadband optical albedo 1 km daily product for land ice (glaciers, ice caps, ice sheet)

Generated by inverting DTU15 Gravity field (generated from Cryosat Data) and combining with existing bathymetries

The study aimed at exploring, developing and validating different approaches to retrieve snow thickness over sea ice; to develop a new prototype processor; and to produce and validate an experimental dataset of snow thickness over the Arctic.