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  • This dataset contains atmospheric data, such as wind field and surface air temperature, obtained by running the weather@home general circulation model for the year 2010. The aim of this dataset is to study the 2010 weather extremes which have affected Western Russian and Pakistan. The dataset contains data for both the regional and global GCM models provided as NetCDF v3 files. The gridded global model output is at 1.25°x1.875° (N96) horizontal resolution. The regional model output is provided on a rotated longitude-latitude grid at a 50 km (0.44°x0.44°) horizontal resolution centred over South Asia. In order to compare 2010 data to the climatology of the model, the climatology is calculated for the years 1986 to 2016. This dataset has been produced by the University of Oxford, in cooperation the Potsdam Institute for Climate Impact Research and the VU University of Amsterdam in the context of the GOTHAM project, funded by the Belmont Forum through the Natural Environment Research Council (NE/P006779/1). The weather@home model runs on the climateprecictions.net platform, which provides a volunteer distributed computational system. This dataset contains weather@home global and regional simulations for the year 2010 and for the climatology of both models for the period 1986-2016. The data comprises of: ~700 ensemble members for weather@home (global model) for 2010 (batch 778) ~700 ensemble members for weather@home (regional model, South Asia) for 2010 (nested on batch 778) ~170 ensemble members per year for the period (1987-2016) for weather@home (global model) (batch 845) ~100 ensemble members per year for the period (1986-2015) for weather@home (regional model, South Asia) (batch 697, not nested on batch 845) extracted variables: At daily resolution: geopotential height 300 hPa (item16202), meridional wind velocity at 300 hPa (item15202), surface air temperature at 1.5m (item 3236), precipitation (item5216) At monthly resolution: soil moisture (item8208)

  • 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 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.

  • This dataset contains the fractional contributions of three phytoplankton size classes (micro-, nano- and picoplankton) over the globe for the period 1997-2007, as produced by the Plymouth Marine Laboratory (PML) using SeaWIFs data. A 10 year monthly climatology is available together with accompanying maps. This dataset was produced as part of the National Centre for Earth Observation (NCEO) Theme 2 programme (Monitoring, Diagnosis and Prediction of the Global Carbon-Cycle), Quantification of ocean biogeochemistry and carbon fluxes sub-theme 6 (ST6).

  • This dataset contains the fractional contributions of three phytoplankton size classes (micro-, nano- and picoplankton) in monthly averages over the globe for the period 1997-2007, as produced by the Plymouth Marine Laboratory (PML) using SeaWIFs data (The dataset was produced by the Plymouth Marine Laboratory by applying the algorithm of Brewin et al. (2010) directly to monthly SeaWiFS Level 3 composites of chlorophyll on a pixel-by-pixel basis.). A 10 year monthly climatology is also available as a separate dataset. Accompanying maps are available. This dataset was produced as part of the National Centre for Earth Observation (NCEO) Theme 2 programme (Monitoring, Diagnosis and Prediction of the Global Carbon-Cycle), Quantification of ocean biogeochemistry and carbon fluxes sub-theme 6 (ST6).

  • This dataset collection contains a 10 year monthly climatology and monthly composites of the fractional contributions of three phytoplankton size classes (micro-, nano- and picoplankton) over the globe for the period Sep 1997-2007, as produced by the Plymouth Marine Laboratory (PML) using SeaWIFs data. Accompanying maps are also available. This dataset contributes to fulfilling the first objective of the National Centre for Earth Observation (NCEO) Theme 2 programme (Monitoring, Diagnosis and Prediction of the Global Carbon-Cycle), Quantification of ocean biogeochemistry and carbon fluxes sub-theme 6 (ST6): Quantify the global oceanic organic C cycle using OC data, partitioned into phytoplankton (pigments, biomass, size structure & PFTs), particulate organic C, coloured dissolved organic matter (CDOM), dissolved and particulate inorganic components. Understanding the interaction between phytoplankton and the in-water light field is crucial to model ocean primary production and to improve our comprehension of the role of biological processes in the ocean–carbon cycle. The absorption coefficient of phytoplankton is a fundamental quantity in marine primary production models because: - it alters the transmission of light underwater; - it modifies the photosynthetic response of phytoplankton to available light; - it can be used as a direct indicator of phytoplankton abundance and phytoplankton size; - it can be used as an indicator of environmental variability It is well known that the phytoplankton absorption coefficient is a function of the dominant phytoplankton pigment, chlorophyll-a, and that this relationship is directly linked to changes in both pigment composition and size structure.

  • The Global Ocean Surface Temperature Atlas Plus (GOSTAplus) contains maps of Sea Surface Temperature (SST) climatologies and anomalies, Night Marine Air temperature climatologies and anomalies and Sea Ice coverage spanning the period 1851-1995. Dataset includes gridded, global SSTs from 1951-1990 and Sea Ice coverage from 1903 to 1994. The data are provided by the Met Office. Updated version of some data also available on request (to 1998).

  • 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 collection contains climatology, soil. population, ecosystem and land cover data. To facilitate this data exchange, and to avoid replication of the often labour-intensive efforts to source and visualize data, QUEST set up the QUEST Earth System Data Initiative - QESDI - a mechanism for easy, centralized access with flexible statistical and visualization tools for consistent processing and presentation of global data sets.

  • The ESA Climate Change Initiative Aerosol project has produced a number of global aerosol Essential Climate Variable (ECV) products from a set of European satellite instruments with different characteristics. This dataset comprises Level 3 Absorbing Aerosol Index (AAI) products, using the Multi-Sensor UVAI algorithm, Version 1.5.7. L3 products are provided as Daily and Monthly gridded products as well as a monthly climatology. For further details about these data products please see the linked documentation.