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.

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.

This dataset represent hydrological statistics calculated over a 30‐year period, at a spatial resolution (over land) of 0.5x0.5o across the global domain. The simulations were made using the global hydrological model Mac‐PDM.09. The data files represent runoff simulated with the baseline (1961‐1990) climate, together with runoff simulated by climate change scenarios derived from CMIP3 global climate model output (i) based on specific IPCC SRES emissions scenarios (“SRES”) and (ii) scaled to represent prescribed changes in global mean temperature (“PRESC”), and from CMIP5 global climate model output based on RCP scenarios. The simulations were run at the University of Reading between 2009 and 2013. See Gosling & Arnell (2011)mfor a description and validation of Mac‐PDM.09, and Arnell & Gosling (2013) for details of the CMIP3 climate change scenarios and their application to the simulation of river runoff. Arnell & Lloyd‐Hughes (2013) describe the application of the model with CMIP5 scenarios.

QUAAC was led by Prof John Pyle (University of Cambridge), with 11 co-investigators at the Universities of Sheffield, Leeds, York, Lancaster and Manchester, and from CEH. The dataset collection includes results of the development and testing of chemistry and aerosol schemes to include in a climate model, a range of schemes to describe (interactively wherever possible) surface emissions of reactive trace gases, and new surface deposition schemes. Coupling between the chemistry/climate system and land surface processes are important controls on the atmosphere, but chemical schemes have only recently and simplistically been introduced into numerical models. QUAAC studied the role of surface processes on atmospheric oxidizing capacity and aerosol loading, building on an existing Met Office/NERC initiative to develop a new community model, UKCA, to study the interaction between climate and atmospheric composition. New chemistry and aerosol schemes were developed for inclusion in the model. Schemes were also developed to describe (interactively wherever possible) surface emissions of reactive trace gases and deposition processes.

QUEST GSI was led by Nigel Arnell (University of Reading) with co-investigators from the Universities of Aberdeen, Leeds, UEA, Edinburgh, Southampton, UCL, London School of Hygiene and Tropical Medicine, CEH and CEFAS. This dataset collection contains model data simulations under various climate, run-off and aquatic scenarios. A central aim of this project was to assess the global-scale impacts of climate change under a range of scenarios, across a number of sectors. A methodology was developed to construct scenarios from a range of climate models, representing changes under different emissions scenarios and fixed amounts of change in global mean temperature. Impacts were estimated across a range of sectors, including water resources, fluvial and coastal flooding, crop productivity and food security, ecosystem productivity and human health, at regional and global scales. The project has provided quantitative information on these impacts and their distribution across the world. The general conclusions are that impacts may be significant at relatively low levels of climate change, that estimates of impact in some sectors are very uncertain due largely to uncertainty in projected changes in rainfall (particularly in south Asia), that there are no obvious thresholds for step changes in impact that are consistent across region and sector, and that socio-economic conditions may amplify or reduce impacts, depending on context. A second project aim was to develop the methodology in such a way that it could be readily applied to estimate impacts under other climate scenarios representing for example specific policy objectives. With additional funding from other sources, the project methodology has been applied successfully to estimate the impacts avoided by a set of feasible emissions policies.

QUEST Fish was led by Dr Manuel Barange (PML) with 18 co-investigators from POL, PML, CEFAS, University of Plymouth, University of Portsmouth, CSIC (Spain), UEA, WorldFish Centre, IPSL, ICES (Denmark), Met Office, IRD (Paris) and University of North Carolina, as part of QUEST (Quantifying and Understanding the Earth System) This dataset collection contains global fish biomass estimates from the Global Coastal-Ocean Modelling System. QUEST-Fish has delivered a near-global assessment of consequences of climate change for fisheries, demonstrating excellent and innovative bridging of marine biogeochemistry models and socio-economics. QUEST-Fish specifically focused on the added impacts that climate change is likely to cause on global fish production, and on the subsequent additional risks and vulnerabilities to human societies. The team have demonstrated the broad capability of an integrated regional coastal/shelf seas model system. The physical-ecological POLCOMS-ERSEM model that underpinned the research was developed for Europe’s regional seas. Its application to 20 Large Marine Ecosystems (coastal bioregions) worldwide, covering two-thirds of the world’s fish catch, has been critically evaluated and found adequate for most regions (the physical and biogeochemical differences of the upwelling region off Peru presents challenges, with the climate impact likely to be over-expressed in the fisheries projection output).