QUEST projects both used and produced an immense variety of global data sets that needed to be shared efficiently between the project teams. These global synthesis data sets are also a key part of QUEST's legacy, providing a powerful way of communicating the results of QUEST among and beyond the UK Earth System research community. This dataset contains monthly climatology measurements for 1961-1990.

QUEST projects both used and produced an immense variety of global data sets that needed to be shared efficiently between the project teams. These global synthesis data sets are also a key part of QUEST's legacy, providing a powerful way of communicating the results of QUEST among and beyond the UK Earth System research community. This dataset contains decadal surface meteorology climatologies from CRU TS3.0 data 1901- 2000. Data includes parameters such as temperature, water vapour and precipitation.

QUEST projects both used and produced an immense variety of global data sets that needed to be shared efficiently between the project teams. These global synthesis data sets are also a key part of QUEST's legacy, providing a powerful way of communicating the results of QUEST among and beyond the UK Earth System research community. This dataset contains socio-economic scenarios from the IPCC SRES report.

QUEST projects both used and produced an immense variety of global data sets that needed to be shared efficiently between the project teams. These global synthesis data sets are also a key part of QUEST's legacy, providing a powerful way of communicating the results of QUEST among and beyond the UK Earth System research community. This dataset contains 30 year surface meteorology climatologies from CRU TS3.0 data. Data includes parameters such as temperature, water vapour and precipitation.

QUEST projects both used and produced an immense variety of global data sets that needed to be shared efficiently between the project teams. These global synthesis data sets are also a key part of QUEST's legacy, providing a powerful way of communicating the results of QUEST among and beyond the UK Earth System research community. This dataset contains global Population Distribution (1990), Terrestrial Area and Country Name Information on a One by One Degree Grid Cell Basis.

The QUEST-GSI WPd1 "Climate scenarios". The aim was to construct climate scenarios representing the effects of uncertainty and different rates of climate forcing. This dataset contains model data which construct climate scenarios. The project requires climate scenarios which (a) characterise the uncertainty in the climate change associated with a given forcing, including changes in climate variability and extreme events, and (b) allow the construction of generalised relationships between climate forcing and impact.

Quaternary QUEST was led by Dr Tim Lenton at UEA, with a team of 10 co-investigators at the Universities of Cambridge, Oxford, Reading, Leeds, Bristol, Southampton and at UEA. This dataset contains the Quaternary QUEST marine isotope data compilation for the last 150,000 years. The project team aimed to compile a synthesis of palaeodata from sediments and ice cores, improve the synchronization of these records with each other, and use this greater understanding of the Earth’s ancient atmosphere to improve Earth system models simulating climate over very long timescales. A combined long-term data synthesis and modelling approach has helped to constrain some key mechanisms responsible for glacial-interglacial CO2 change, and Quaternary QUEST have narrowed the field of ocean processes that could have caused glacial CO2 drawdown.

QUERCC addresses land surface processes over timescales from days to centuries, with particular emphasis on the carbon cycle. Some processes are already well represented and validated in Dynamic Global Vegetation Models (DGVMs), while others that are known to impact on the carbon cycle are not. Independent carbon and vegetation data sets are being compared against DVGMs to assess their current state, and further key modules will be developed for nutrient cycling, which exerts a major feedback on carbon exchange, and for a greater resolution of plant processes. This dataset contains a global map of plant functional types that exert significant impacts on the carbon cycle as modelled by the Rothamsted Research institute based on the FAO (Food and Agriculture Organization) soil properties.

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.