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.

This dataset presents daily data from temperature and soil moisture sensors in each experimental plot (n=9 plots). Soil temperature is measured at 5 cm and 20 cm soil depth (degrees Celsius), and soil moisture is measured as soil volumetric water content (m3 per m3). Data were collected from the climate change field site Climoor that is located in Clocaenog forest, NE Wales. The experimental field site consists of three untreated control plots (Plots 3, 6 and 9), three plots where the plant canopy air is artificially warmed during night time hours (Plots 1, 2 and 7) and three plots where rainfall is excluded from the plots at least during the plants growing season (Plots 4, 5 and 8). Data is an extension for the micromet datasets 1998-2015, 2015-2016, 2016-2021 and 2022-2023 covering the time period January 2024 to December 2024. Soil temperatures are measured with a T107 sensor from Campbell scientific. Soil moisture is measured with CS616 sensors from Campbell scientific. Temperature and moisture data are logged in minute intervals and are averaged as half-hourly. The Climoor field experiment intents to answer questions regarding the effects of warming and drought on ecosystem processes. The reported plot level temperature and soil moisture data are important to evaluate the effect of the imposed climatic treatments on ecosystem processes and functioning. Data collection, processing and quality checks were carried out by UKCEH staff. More detailed information about the field site, measurements and related datasets can be found in the documentation accompanying the data. Full details about this dataset can be found at https://doi.org/10.5285/21e8957f-48b2-4e29-8aa5-247cf060a59c

This dataset holds daily data from one automated weather station (AWS) located at the Climoor field site in Clocaenog forest, North East Wales. The data are on relative humidity (percent), air temperature (degrees Celsius), rainfall (millimetres), air pressure (millibars), net radiation (millivolts), solar radiation (kilowatts per square metre per second), photosynthetic active radiation (PAR), (micromol per square metre per second), wind speed (metres per second) and wind direction (degrees). Data is an extension for the AWS datasets 1999-2015, 2015-2016, 2016-2021, 2022-2023 and covering the time period January 2024 to December 2024. Data are logged in minute intervals, averaged to half-hourly. Data are sent from the field site to a UKCEH server. A working copy is created, quality assurance checks carried out and daily averages calculated from half-hourly records. Data which were not recorded are marked with “NA”, faulty data were replaced by “-9999”. Note, the rainfall sensor was broken during this time period, but the column is kept in the datafile for consistency with previous data records. Data collection, processing and quality checking was carried out by members of CEH and UKCEH staff. The following measures were taken with sensors from Campbell Scientific: Rainfall sums are measured with an ARG100 Tipping bucket, air pressure is measured with a CS100 Barometer. Further, Solar radiation and PAR are measured using a Skye SP1110 pyranometer and a SKP215 quantum sensor from Skye Instruments. Wind direction and speed were recorded using a windsonic 2D Ultrasonic Anemometer from Windsonic. The Climoor field experiment intends to answer questions regarding the effects of warming and drought on ecosystem processes. The reported data are collected to monitor site specific environmental conditions and their development over time. These data are important to interpret results that are collected from the climate change manipulations imposed in the field. Full details about this dataset can be found at https://doi.org/10.5285/6b3b766f-4d04-4a41-b2a4-6ca2dd1ea23a

This data contains the time series flow discharge results of hydrological simulation of the River Trent at Colwick using UKCP09 Weather Generator inputs for a variety of time slices and emissions scenarios. The Weather Generator (WG) inputs were run on a hydrological model (Leathard et al., unpublished), calibrated using the observed record 1961-2002. Each simulation is derived from one-hundred, 30-year time series of weather at the WG location 4400355 for Control, Low, Medium and High emissions scenarios for the 2020s, 2030s, 2040s, 2050s and 2080s time slices. The datasets include the relevant accompanying input WG data. Full details about this dataset can be found at https://doi.org/10.5285/986d3df3-d9bf-42eb-8e18-850b8d54f37b

This is a dataset of environmental data, vegetation cover, and community- and species-level invertebrate herbivory, sampled at 14 experimental soil plots in the Hengill geothermal valley, Iceland, from May to July 2017. The plots span a temperature gradient of 5-35 °C on average over the sampling period, yet they occur within 1 km of each other and have similar soil moisture, pH, nitrate, ammonium, and phosphate. Full details about this dataset can be found at https://doi.org/10.5285/da5d7028-2aec-4da2-96ff-f347a0dfa77e

The data contain measurements of the morphological shape of threespine stickleback from wild, F1 (filial generation 1) lab-reared, and F2-lab (filial generation 2) reared individuals. These last two groups were bred and reared from eggs in the lab. The files are in tps format and so within these contain the information regarding the population, rearing temperature, and scale factor for each specimen. The populations used are coded in a short form format but we also provide a key to decipher these names in csv format. Photos are also made available with corresponding tps files for F2 hybrid fish. Full details about this dataset can be found at https://doi.org/10.5285/a566fc20-a371-42a2-8530-9a3cade09261

This dataset provides the projections of meteorological, hydrological, and agricultural droughts for the near-future period (2021-2050) for the Mun River basin, in Northeast Thailand. Near future drought characteristics (duration, intensity, and severity) are projected for climate change (CC) scenario using 8 CMIP6 climate models (CNRM-CM6-1, CNRM-CM6-1-HR, EC-Earth3P, EC-Earth3P-HR, HadGEM3-GC31-HH, HadGEM3-GC31-HM, HadGEM3-GC31-MM, HadGEM3-GC31-LL) for SSP5-8.5 scenario. Full details about this dataset can be found at https://doi.org/10.5285/b11c040d-c3c0-43c5-a7c0-442b067dc526

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.

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 FAMOUS (FAst Met Office/UK Universities Simulator) glacial cycle model data from 150,000 years ago to present. 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.

The QUEST-GSI WP-I5 "Aquatic Ecosystems" project provided an analysis of global fisheries vulnerability across a range of global climate models, emissions scenarios, fixed degree scenarios and alternative impact metrics. This dataset contains model output data from the emission, fixed degree, Cheung potential analysis, Allison socio-economic comparison and freshwater run-off analysis scenarios. -Emission Scenarios- These results are from the analysis using the SRES emissions scenarios from the IPCC AR4 - A1b, A2, B1 and B2. -Fixed Degree- This analysis was driven by the fixed degree rise scenarios, corresponding to a fixed increase in global temperature by 2050. These are 1 to 4 degrees C, in half degree increments, with each fishery impact equally weighted across freshwater, EEZ and High Seas (see report). They are also carried out for a variety of GCMs and socio-economic scenarios. -Cheung Potential Catch Analysis- These results were generated for marine fisheries using an alternative metric to temperature change in calculating potential impact- that of predicted change in potential catch from the study carried out by W.W.L. Cheung et al. (2009 Large-scale redistribution of maximum fisheries catch potential in the global ocean under climate change. Global Change Biology 16, 24-35). This was carried out for the A1b SRES scenario using the GFDL CM2.1 global climate model. -Allison Socio-economic comparison- A comparison study using the adaptive capacity metric developed in Allison et al. (2009 Vulnerability of national economies to the impacts of climate change on fisheries. Fish and Fisheries 10, 173–196). This was undertaken for the A1b Emission Scenario using HadCM3. -Freshwater Runoff Analysis- Using predicted changes in freshwater availability from the outputs of QUEST-GSI WP-I1 global water resources project, an alternative analysis for freshwater fisheries vulnerability was carried out. This was under the 2 degrees fixed increase scenario using HadCM3.