FireMAFS was led by Prof Martin Wooster (Kings College, London) as part of QUEST Theme 3 (Quantifying and Understanding the Earth System) project. The objective of FireMAFS was to resolve limitations of fire modelling by developing a robust method to forecast fire activity (fire 'danger' indices, ignition probabilities, burnt area, fire intensity etc), via a process-based model of fire-vegetation interactions, tested, improved, and constrained. This used a state-of-the-art EO data products and driven by seasonal weather forecasts issued with many months lead-time. This dataset contains the MODIS Land Cover Type product multiple classification schemes, which describe land cover properties derived from observations spanning a year’s input of Terra and Aqua data. The data are stored in a 10 arc minute grid.

FireMAFS was led by Prof Martin Wooster (Kings College, London) as part of QUEST Theme 3 (Quantifying and Understanding the Earth System) project. This dataset collection contains the MODIS Land Cover Type product multiple classification schemes, which describe land cover properties derived from observations spanning a year’s input of Terra and Aqua data. The data are stored in a 10 arc minute grid. Fire was the most important disturbance agent worldwide in terms of area and variety of biomass affected, a major mechanism by which carbon is transferred from the land to the atmosphere, and a globally significant source of aerosols and many trace gas species. Despite such clear coupling between fire, climate, and vegetation, fire was not modelled as an interactive component of the climate/earth systems models of full complexity or intermediate complexity, that are used to model terrestrial ecosystem processes principally for simulating CO2 exchanges. The objective of FireMAFS was to resolve these limitations by developing a robust method to forecast fire activity (fire 'danger' indices, ignition probabilities, burnt area, fire intensity etc), via a process-based model of fire-vegetation interactions, tested, improved, and constrained. This used a state-of-the-art EO data products and driven by seasonal weather forecasts issued with many months lead-time. Much of the activity of FireMAFS was shaped by the research and technical priorities of QUESTESM (earth system model). Key activities included the progressive development of the JULES-ED and SPITFIRE submodels. Fire is now very well represented in QESM (Quest Earth System Model), making progress towards a modelling capability for fire risk forecasting in the context of global change.

This dataset provides model output for 20th and 21st-century ice-ocean simulations in the Amundsen Sea. The simulations are performed with the MITgcm model at 1/10 degree resolution, including components for the ocean, sea ice, and ice shelf thermodynamics. Atmospheric forcing is provided by the CESM1 climate model for the historical period (1920-2005) and four future scenarios (2006-2100), using 5-10 ensemble members each. The open ocean boundaries are forced by either the corresponding CESM1 simulation or a present-day climatology. The simulations were completed in 2022 by Kaitlin Naughten at the British Antarctic Survey (Polar Oceans team). UKRI Fund for International Collaboration NE/S011994/1

This data set represents the model results plotted in the figures in Bett et al. (2020). Data portrays Amundsen Sea freshwater fluxes and freshwater passive tracer results, along with the results on the effect of grounded icebergs and iceberg melt on sea ice and oceanic heat content. These results are derived from Amundsen Sea regional model simulations over the period 1979-2018, with the first 10 years regarded as model spin up. For full descriptions of the results plotted in each figure see Bett et al. (2020).

This dataset provides model output for 20th-century ice-ocean simulations in the Amundsen Sea, Antarctica. The simulations are performed with the MITgcm model at 1/10 degree resolution, including components for the ocean, sea ice, and ice shelf thermodynamics. Atmospheric forcing is provided by the CESM Pacific Pacemaker Ensemble, using 20 members from 1920-2013. An additional simulation is forced with the ERA5 atmospheric reanalysis from 1920-2013. The simulations were completed in 2021 by Kaitlin Naughten at the British Antarctic Survey (Polar Oceans team). Supported by UKRI Fund for International Collaboration NE/S011994/1.

This dataset represents model output from 4 simulations of Store Glacier produced using the Elmer/Ice glacier model equipped with novel 3D calving subroutines. As described in the paper associated with this dataset (Todd et al., JGR, 2018), the model is initialised with velocity observations and then forced with present day environmental forcing. The simulation covers a 5 year time period with no fixed dates. Funding was provided by the NERC grant NE/K500884/1.

This dataset contains all datasets used in Yang et al. ACP (2019), especially the model-data comparison data and pTOMCAT''s model experimental results. The data include pTOMCAT model output of sea salt aerosol (SSA) and the cruise data from the Weddell Sea, they include blowing snow particles and aerosol number density and regrouped size spectrum over open ocean, marginal sea ice zone and packed sea ice. It also contains monthly sea salt aerosol sodium concentrations at eight polar sites in both northern and southern hemispheres: Alert, Barrow, Summit, Palmer, Neumayer, Halley, Kohnen and Concordia (Dome C). The Weddell Sea particle data (both blowing snow and aerosol) are from 29m above the sea level (not including near surface data). The data period only covers 13 June-26 July 2013. To get access to a full cruise dataset, see the companion paper by Frey et al. (2019) and the DOI link. This study was supported by NERC-funded BLOWSEA project (NE/J023051/1) and the German RV Polarstern.