The CRU CY datasets consists of country averages at a monthly, seasonal and annual frequency, for ten climate variables in 289 countries. Spatial averages are calculated using area-weighted means. Variables include cloud cover (cld), diurnal temperature range (dtr), frost day frequency (frs), precipitation (pre), daily mean temperature (tmp), monthly average daily maximum (tmx) and minimum (tmn) temperature, vapour pressure (vap), Potential Evapo-transpiration (pet) and wet day frequency (wet). The CRU CY datasets produced by the Climatic Research Unit (CRU) at the University of East Anglia. Spatial averages are calculated using area-weighted means. CRU CY is derived directly from the CRU TS dataset and version numbering is matched between the two datasets. Thus, the first official version of CRU CY is v3.21, as it is based on CRU TS v3.21 (1901-2012) and the latest version of CRU-CY is v3.26 based on CRU TS v3.26 (1901-2017) for 289 countries. The data are available as text files with the extension '.per' and can be opened by most text editors. To understand the CRU-CY dataset, it is important to understand the construction and limitations of the underlying dataset, CRU TS. It is therefore recommended that all users read the paper referenced below (Harris et al, 2014).

World Climate Research Programme (WCRP) Coupled Model Intercomparison Project Phase 6 (CMIP6): Collection of simulations from the National Center for Atmospheric Research (NCAR) CESM2-WACCM model. The official CMIP6 Citation, and its associated DOI, is provided as an online resource linked to this record.

Soil Moisture data (version 04.7) from the European Space Agency's (ESA) Soil Moisture Climate Change Initiative (CCI) project. This dataset collection contains three surface soil moisture datasets, alongside ancilliary data products. The ACTIVE and PASSIVE products have been created by fusing satellite scatterometer and radiometer soil moisture products respectively. In the case of the ACTIVE product, these have been derived from the AMI-WS and ASCAT satellite instruments and for the PASSIVE product from the satellite instruments SMMR, SSM/I, TMI, AMSR-E, WindSat, AMSR2 and SMOS. The COMBINED product is generated from the Level 2 active and passive instruments.. The homogenized and merged products present a global coverage of surface soil moisture at a spatial resolution of 0.25 degrees. The products are provided as global daily images, in NetCDF-4 classic file format, the PASSIVE and COMBINED products covering the period (yyyy-mm-dd) 1978-11-01 to 2019-12-31 and the ACTIVE product covering 1991-08-05 to 2019-12-31. The soil moisture data for the PASSIVE and the COMBINED product are provided in volumetric units [m3 m-3], while the ACTIVE soil moisture data are expressed in percent of saturation [%]. For information regarding the theoretical and algorithmic base of the datasets, please see the Algorithm Theoretical Baseline Document (ATBD). Other additional documentation and information documentation relating to the datasets can also be found on the CCI Soil Moisture project web site or in the Product Specification Document. The data set should be cited using the all of the following references: 1. Gruber, A., Scanlon, T., van der Schalie, R., Wagner, W., and Dorigo, W. (2019). Evolution of the ESA CCI Soil Moisture climate data records and their underlying merging methodology, Earth Syst. Sci. Data, 11, 717–739, https://doi.org/10.5194/essd-11-717-2019 2. Dorigo, W.A., Wagner, W., Albergel, C., Albrecht, F., Balsamo, G., Brocca, L., Chung, D., Ertl, M., Forkel, M., Gruber, A., Haas, E., Hamer, D. P. Hirschi, M., Ikonen, J., De Jeu, R. Kidd, R. Lahoz, W., Liu, Y.Y., Miralles, D., Lecomte, P. (2017). ESA CCI Soil Moisture for improved Earth system understanding: State-of-the art and future directions. In Remote Sensing of Environment, 2017, ISSN 0034-4257, https://doi.org/10.1016/j.rse.2017.07.001 3. Gruber, A., Dorigo, W. A., Crow, W., Wagner W. (2017). Triple Collocation-Based Merging of Satellite Soil Moisture Retrievals. IEEE Transactions on Geoscience and Remote Sensing. PP. 1-13. 10.1109/TGRS.2017.2734070

A collection of measurements made for the Deep Convective Microphysics Experiment (DCMEX) project. This includes in-situ airborne observations by the FAAM BAE-146 aircraft, cloud images from 2 NCAS cameras deployed at 3 sites in the area during the course of the field campaign and meteorological and aerosol measurements made at two groundbased stations. DCMEX examined the formation and development of clouds over mountains and was based in the Magdalena Mountains, New Mexico area, between July and August 2022. Associated datasets are also available: Timelapse footage of deep convective clouds in New Mexico produced during the DCMEX field campaign https://doi.org/10.5281/zenodo.7756710 DCMEX ground based radar data https://doi.org/10.5281/zenodo.10472266 and, the aircraft ice nucleating particle filter analysis https://doi.org/10.5518/1476

In-situ airborne observations by the DO228-212 /D-CFFU - DLR aircraft aircraft for HYPPOS- HYdrodynamic control of Primary Producers in Optically Shallow fluvial lakes .

In-situ airborne observations by the FAAM BAE-146 aircraft for ZWAMPS FAAM Aircraft Project (Zwamps).

In-situ airborne observations by the FAAM BAE-146 aircraft for URBan VISibility in UK (VISURB).

In-situ airborne observations by the FAAM BAE-146 aircraft for FAAM Atmospheric Reactive Nitrogen Cycling over the Ocean (ARNA)

In-situ airborne observations by the FAAM BAE-146 aircraft for Met Office Civil Contingency Aircraft intercomparison (MOCCA).

In-situ airborne observations by the FAAM BAE-146 aircraft for BUNCEFIELD SMOKE EXPERIMENT (Buncefield Smoke Experiment).