The Cloud_cci ATSR2-AATSRv3 dataset (covering 1995-2012) was generated within the Cloud_cci project, which was funded by the European Space Agency (ESA) as part of the ESA Climate Change Initiative (CCI) programme (Contract No.: 4000109870/13/I-NB). This dataset is one of the 6 datasets generated in Cloud_cci; all of them being based on passive-imager satellite measurements. This dataset is based on measurements from the ATSR2 and AATSR instruments (onboard the ERS2 and ENVISAT satellites) and contains a variety of cloud properties which were derived employing the Community Cloud retrieval for Climate (CC4CL; Sus et al., 2018; McGarragh et al., 2018) retrieval framework. The core cloud properties contained in the Cloud_cci ATSR2-AATSRv3 dataset are cloud mask/fraction, cloud phase, cloud top pressure/height/temperature, cloud optical thickness, cloud effective radius and cloud liquid/ice water path. Spectral cloud albedo is also included as experimental product. The cloud properties are available at different processing levels: This particular dataset contains Level-3C (monthly averages and histograms) data, while Level-3U (globally gridded, unaveraged data fields) is also available as a separate dataset. Pixel-based uncertainty estimates come along with all properties and have been propagated into the Level-3C data. The data in this dataset are a subset of the ATSR2-AATSR L3C / L3U cloud products version 3.0 dataset produced by the ESA Cloud_cci project available from https://dx.doi.org/10.5676/DWD/ESA_Cloud_cci/ATSR2-AATSR/V003. To cite the full dataset, please use the following citation: Poulsen, Caroline; McGarragh, Greg; Thomas, Gareth; Stengel, Martin; Christensen, Matthew; Povey, Adam; Proud, Simon; Carboni, Elisa; Hollmann, Rainer; Grainger, Don (2019): ESA Cloud Climate Change Initiative (ESA Cloud_cci) data: Cloud_cci ATSR2-AATSR L3C/L3U CLD_PRODUCTS v3.0, Deutscher Wetterdienst (DWD) and Rutherford Appleton Laboratory (Dataset Producer), DOI:10.5676/DWD/ESA_Cloud_cci/ATSR2-AATSR/V003

DESIRE (Dynamics of the Earth System and the Ice-Core Record) was part of QUEST (Quantifying and Understanding the Earth System) Theme 2. This dataset contains measurements of chemical traces and meteorological from the TOMCAT (Tropospheric Offline Model of Chemistry and Transport model), as part of the Work Package 1.3. The aim of this work package was to identify any atmospheric chemical signal preserved in the ice-core record that could be used to differentiate between the influences on atmospheric methane of changes in methane emissions and changes in oxidising capacity between the Last Glacial Maximum (LGM) and the pre-industrial era (PI). A series of experiments was carried out using the Cambridge parallelised-Tropospheric Offline Model of Chemistry and Transport (p-TOMCAT; v2.0 beta), the results to which are contained in this dataset.

Data from "The impact of climate change on the North Atlantic and European storm-track and blocking" project was a Natural Environment Research Council (NERC) RAPID Climate Change Research Programme project (Round 2 - NE/C509115/1 - Duration 14 Mar 2005 - 13 Mar 2008) led by Prof Sir Brian Hoskins of Imperial College London, Grantham Institute for Climate Change, with co-investigators also at the University of Reading. This dataset collection contains Unified Model climate temperature outputs from model run xcpud. Rapid Climate Change (RAPID) was a £20 million, six-year (2001-2007) programme for the Natural Environment Research Council. The programme aimed to improve the ability to quantify the probability and magnitude of future rapid change in climate, with a main (but not exclusive) focus on the role of the Atlantic Ocean's Thermohaline Circulation.

Cloud base and backscatter data from the Met Office's Vaisala CL31 ceilometer located at Brize Norton, Oxfordshire. The Met Office's laser cloud base recorders network (LCBRs), or ceilometers, returns a range of products for use in forecasting and hazard detection. The backscatter profiles can allow detection of aerosol species such as volcanic ash where suitable instrumentation is deployed. This instrument replaced a Vaisala CT25k ceilometer at the site in January 2017.

Data from "The impact of climate change on the North Atlantic and European storm-track and blocking" project was a Natural Environment Research Council (NERC) RAPID Climate Change Research Programme project (Round 2 - NE/C509115/1 - Duration 14 Mar 2005 - 13 Mar 2008) led by Prof Sir Brian Hoskins of Imperial College London, Grantham Institute for Climate Change, with co-investigators also at the University of Reading. This dataset collection contains Unified Model climate pressure outputs from model run xcpub. Rapid Climate Change (RAPID) was a £20 million, six-year (2001-2007) programme for the Natural Environment Research Council. The programme aimed to improve the ability to quantify the probability and magnitude of future rapid change in climate, with a main (but not exclusive) focus on the role of the Atlantic Ocean's Thermohaline Circulation.

A sonic anemometer and a gas analyser measuring water vapour and carbon dioxide are co-located within a compound dedicated to measuring fluxes using the eddy covariance method at Chilbolton Observatory. The eddy covariance technique is an atmospheric measurement method used to calculate vertical turbulent fluxes within the atmospheric boundary layer. This is the lowest region of the troposphere and is usually well mixed, particularly during daylight hours, due to convective heating from the sun. It is this motion in the lower troposphere that makes the technique possible. In order to properly measure the turbulent properties of the atmosphere the measurements must be made at a high frequency - 20 Hz for the Chilbolton Observatory system. A sonic anemometer measures the 3 orthogonal components of the wind velocity by measuring the changes in the time of flight of sonic pulses between 3 transmitter/receiver pairs as a result of the air velocity. A gas analyser measures the absorptance of radiation along a fixed path and uses this to determine the concentration of a gas in air. For each gas the absorptance at 2 wavelengths is measured 152 times per second, one affected by that gas and the other unaffected. There are more accurate instruments available for measuring water vapour and carbon dioxide (e.g. a relative humidity sensor for water vapour) but the benefit of the gas analyser is that it has a sufficiently fast response to resolve the rapid changes in concentration as a result of turbulence.

Cascade was a NERC funded consortium project to study organized convection and scale interactions in the tropical atmosphere using large domain cloud system resolving model simulations. The xfncl simulation was made using the Met Office Unified Model (UM) at 1.5km resolution over the domain 40E-183E, 22S-22N which encompasses the Indian Ocean West Pacific Warm Pool. Cascade Warm Pool simulations coincide with the Year of Tropical Convection. This dataset contains Warm Pool 1.5km model measurements from xfncl run.

This is the HadISDH.land 4.4.0.2021f version of the Met Office Hadley Centre Integrated Surface Dataset of Humidity (HadISDH). HadISDH.land is a near-global gridded monthly mean land surface humidity climate monitoring product. It is created from in situ observations of air temperature and dew point temperature from weather stations. The observations have been quality controlled and homogenised. Uncertainty estimates for observation issues and gridbox sampling are provided (see data quality statement section below). The data are provided by the Met Office Hadley Centre and this version spans 1/1/1973 to 31/12/2021. The data are monthly gridded (5 degree by 5 degree) fields. Products are available for temperature and six humidity variables: specific humidity (q), relative humidity (RH), dew point temperature (Td), wet bulb temperature (Tw), vapour pressure (e), dew point depression (DPD). This version extends the previous version to the end of 2021. Users are advised to read the update document in the Docs section for full details on all changes from the previous release. As in previous years, the annual scrape of NOAAs Integrated Surface Dataset for HadISD.3.1.2.202101p, which is the basis of HadISDH.land, has pulled through some historical changes to stations. This, and the additional year of data, results in small changes to station selection. The homogeneity adjustments differ slightly due to sensitivity to the addition and loss of stations, historical changes to stations previously included and the additional 12 months of data. To keep informed about updates, news and announcements follow the HadOBS team on twitter @metofficeHadOBS. For more detailed information e.g bug fixes, routine updates and other exploratory analysis, see the HadISDH blog: http://hadisdh.blogspot.co.uk/ References: When using the dataset in a paper please cite the following papers (see Docs for link to the publications) and this dataset (using the "citable as" reference): Willett, K. M., Dunn, R. J. H., Thorne, P. W., Bell, S., de Podesta, M., Parker, D. E., Jones, P. D., and Williams Jr., C. N.: HadISDH land surface multi-variable humidity and temperature record for climate monitoring, Clim. Past, 10, 1983-2006, doi:10.5194/cp-10-1983-2014, 2014. Dunn, R. J. H., et al. 2016: Expanding HadISD: quality-controlled, sub-daily station data from 1931, Geoscientific Instrumentation, Methods and Data Systems, 5, 473-491. Smith, A., N. Lott, and R. Vose, 2011: The Integrated Surface Database: Recent Developments and Partnerships. Bulletin of the American Meteorological Society, 92, 704-708, doi:10.1175/2011BAMS3015.1 We strongly recommend that you read these papers before making use of the data, more detail on the dataset can be found in an earlier publication: Willett, K. M., Williams Jr., C. N., Dunn, R. J. H., Thorne, P. W., Bell, S., de Podesta, M., Jones, P. D., and Parker D. E., 2013: HadISDH: An updated land surface specific humidity product for climate monitoring. Climate of the Past, 9, 657-677, doi:10.5194/cp-9-657-2013.

Cloud base and backscatter data from the Met Éireann's Vaisala Ct25k ceilometer located at Shannon, South West, Ireland. The Met Éireann's laser cloud base recorders network (LCBRs), or ceilometers, returns a range of products for use in forecasting and hazard detection. The backscatter profiles can allow detection of aerosol species such as volcanic ash where suitable instrumentation is deployed.

Data from "The Predictability of rapid climate change associated with the Atlantic thermohaline circulation" project. This was a Natural Environment Research Council (NERC) RAPID Climate Change Research Programme project (Round 2 - NE/C509174/1 - Duration 1 Jan 2005 - 18 Sep 2008) led by Prof Rowan Sutton of the University of Reading, with co-investigators at the University of Oxford and at the National Oceanography Centre. The dataset identifies the dominant sources of uncertainty in General Circulation Model predictions of the Thermohaline Circulation. This dataset contains meteorology model output from the HadCM3 control ensemble. Forecasts of the future behaviour of the Atlantic Thermohaline Circulation (THC) are needed to inform policy on climate change. Such forecasts must be probabilistic taking into account the principal sources of uncertainty. It is not possible to sample exhaustively all sources of uncertainty because the number of degrees of freedom is too great. Consequently a future forecasting system will be reliant on strategies to identify those dimensions of uncertainty that are most important. This project developed an objective methodology to identify the dominant sources of uncertainty in General Circulation Model predictions of the THC. Perturbations to oceanic initial conditions and climate model parameters that generate the most rapid change in the THC and related aspects of climate were identified. These perturbations were used to produce an early probabilistic forecast for the behaviour of the THC up to 2100. The results were also feed directly into the next generation of ensemble climate predictions being developed at the UK Hadley Centre. Rapid Climate Change (RAPID) was a £20 million, six-year (2001-2007) programme for the Natural Environment Research Council. The programme aimed to improve the ability to quantify the probability and magnitude of future rapid change in climate, with a main (but not exclusive) focus on the role of the Atlantic Ocean's Thermohaline Circulation.