The Met Office Hadley Centre's sea surface temperature data set, HadSST2, replaces the Met Office Historical Sea Surface Temperature dataset (MOHSST6) and is a monthly global field of SST (Sea Surface Temperature) on a 5 deg latitude by 5 deg longitude grid from 1850 to August 2013. The data are neither interpolated nor variance adjusted. The SST data are taken from the International Comprehensive Ocean-Atmosphere Data Set, ICOADS, from 1850 to 1997 and from the NCEP-GTS from 1998 to the present. HadSST2 is produced by taking in-situ measurements of SST from ships and buoys, rejecting measurements which which fail quality checks, converting the measurements to anomalies by subtracting climatological values from the measurements, and calculating a robust average of the resulting anomalies on a 5° by 5° degree monthly grid. After gridding the anomalies, bias corrections are applied to remove spurious trends caused by changes in SST measuring practices before 1942. The uncertainties due to under-sampling have been calculated for the gridded monthly data as have the uncertainties on the bias corrections. This dataset include: - SST anomaly data (HadSST2_SST_1850on.txt.gz) - 1961-1990 Climatology (HadSST2_climatology_5x5_1961_1990.txt) - numbers of observations used to calculate the average (HadSST2_nobs_1850on.txt.gz) - Estimates on the measurement and sampling errors on the SST data (HadSST2_m_and_s_errors_1850on.txt.gz) - bias-adjusted data using bias adjustments which represent the 97.5 percent and 2.5 percent confidence levels of the estimated errors on the adjustments (HadSST2_97.5_pct_bias_1850on.txt.gz and HadSST2_2.5_pct_bias_1850on.txt.gz). - Files showing the correction applied to the data e.g.: HadSST2_bucket_correction_median.txt.gz - the corrections applied to the data 1850-1941 HadSST2_bucket_correction_2.5pc.txt.gz - the lower bound of the 95% confidence range of the uncertainties 1850-1941 HadSST2_bucket_correction_97.5pc.txt.gz - the upper bound of the 95% confidence range of the uncertainties 1850-1941 A 1 degree version of HadSST2 is also available. Data were provided by the Met Office Hadley Centre. Dataset was produced by the Hadley Centre in collaboration with ICOADS.

TOPography EXperiment (TOPEX) for ocean circulation (otherwise known as Poseidon) was launched on August 10, 1992 and was a joint satellite mission between NASA, the U.S. space agency, and CNES, the French space agency, to map ocean surface topography. The first major oceanographic research vessel to sail into space, TOPEX/Poseidon helped revolutionise oceanography by proving the value of satellite ocean observations. This dataset collection contains monthly means on a 1x1 latitude/longitude grid for 12 years (1993-2004). The data contains the following parameters: wind speed, squared wind speed, cubed wind speed, wind speed * significant wave height, significant wave height, 1/sigma0(Ku) and gas transfer velocity. The dataset was produced by Fangohr, S. and D.K. Woolf of SOCS, as part of the NERC programme's Centre for observation of Air-Sea Interactions and FluXes (CASIX) and National Centre for Earth Observation (NCEO).

TOPography EXperiment (TOPEX) for ocean circulation (otherwise known as Poseidon) was launched on August 10, 1992 and was a joint satellite mission between NASA, the U.S. space agency, and CNES, the French space agency, to map ocean surface topography. The first major oceanographic research vessel to sail into space, TOPEX/Poseidon helped revolutionise oceanography by proving the value of satellite ocean observations. This dataset contains monthly means on a 1x1 latitude/longitude grid for 12 years (1993-2004). The data contains the following parameters: wind speed, squared wind speed, cubed wind speed, wind speed * significant wave height, significant wave height, 1/sigma0(Ku) and gas transfer velocity. TOPEX/Poseidon was a joint mission from the National Aeronautics and Space Administration (NASA), the U.S. space agency and the French space agency. The dataset was produced by Fangohr, S. and D.K. Woolf of SOCS, as part of the NERC programme's Centre for observation of Air-Sea Interactions and FluXes (CASIX) and National Centre for Earth Observation (NCEO).

This dataset contains the adjusted climatological monthly mean files of air-sea fluxes (heat fluxes only) on a global grid in netCDF format produced at the National Oceanography Centre (NOC). It was produced by the NERC COAPEC thematic programme project using inverse analysis techniques to remove the global ocean heat budget imbalance of 30 Wm-2 that was present in the NOC1.1 flux climatology. Each data file contains 12 climatological monthly means on a global 1 x 1 grid for a particular flux field: latent heat flux (hfls), net heat flux (hfns), sensible heat flux (hfss), net longwave flux (rls), net shortwave flux (rss). Units are W/m2. The flux fields were originally derived from the COADS1a (1980-93) dataset enhanced with additional metadata from the WMO47 list of ships. A full description of the fields is given in The Southampton Oceanography Centre (SOC) Ocean - Atmosphere, Heat, Momentum and Freshwater Flux Atlas (see link under Docs) and a parallel journal paper (Josey et al, 1999) describes the results of various evaluation studies (see links under Docs). It is important to note that the quality of the fields has a strong spatial dependence which reflects the global distribution of ship observations. Quality is likely to be high in the well sampled North Atlantic & North Pacific but to decrease in the Southern Hemisphere. In particular, south of 40 S the errors in the fields are likely to be large and we recognise the existence of spurious features which have been generated during the objective analysis of the original raw fields. NOC stress that caution must be taken when interpreting the fields in this region.

MarQUEST was led by Prof Andrew Watson (UEA), with 15 co-investigators at UEA/BAS, the Universities of Southampton, Essex, and Reading, and from the Plymouth Marine Laboratory and Proudman Oceanographic Laboratory. This dataset contains climatology and monthly measurements of phytoplankton Size Class from the SeaWiFS/SeaStar products. QUEST scientists cooperated in comparing various models, and examining more fundamental (physiological) approaches to understanding the planktonic ecoystem. MarQUEST also developed a module to simulate coastal ecosystems, usable in global ocean biogeochemical simulations. Finally, the project team generated an accurate physical simulation of the North Atlantic guided by data assimilation, into which ecosystem simulations can be embedded. This allows the variation in air-sea fluxes of gases (CO2, oxygen and dimethyl sulphide) from ocean to atmosphere to be quantified for the contemporary period. This data was produced by Takafumi Hirata, Plymouth Marine Laboratory, Plymouth, UK as part of NERC Programmes: Centre for the observation of Air-Sea Interaction and fluXes (CASIX), National Centre for Earth Observation (NCEO) and Quantifying and Understanding the Earth System (QUEST).

This dataset contains measurements of sea surface temperature (SST) (HadISST1.1). Dataset include monthly mean gridded (1deg grid), global SSTs from 1870 to October 2015. This product replaced the GISST/GICE (Global Sea Surface Temperature/Global sea-Ice content) data sets ended in February 2003. The SST data are taken from the Met Office Marine Data Bank (MDB), which from 1982 onwards also includes data received through the Global Telecommunications System (GTS). In order to enhance data coverage, monthly median SSTs for 1871-1995 from the Comprehensive Ocean-Atmosphere Data Set (COADS) (now ICOADS) were also used where there were no MDB data. The sea ice data are taken from a variety of sources including digitized sea ice charts and passive microwave retrievals. HadISST1 temperatures are reconstructed using a two stage reduced-space optimal interpolation procedure, followed by superposition of quality-improved gridded observations onto the reconstructions to restore local detail. The sea ice fields are made more homogeneous by compensating satellite microwave-based sea ice concentrations for the impact of surface melt effects on retrievals in the Arctic and for algorithm deficiencies in the Antarctic, and by making the historical in situ concentrations consistent with the satellite data. SSTs near sea ice are estimated using statistical relationships between SST and sea ice concentration. From May 2007 the data set of in situ measurements used in HadISST has changed. The MOHSST data set, which was previously used has been discontinued, and HadSST2 is now being used in its place. The two systems ran in parallel for several months prior to the changeover and no significant differences were seen. The data were provided by the Hadley centre (Met Office). Important Notes: On 13th March 2015: Users have noticed that there is a minor discontinuity at the dateline in HadISST1 SST fields starting in 1982. It appears to only affect gridcells just to the east of the dateline. Please note that this can affect estimates of the mean and variability of SSTs in HadISST1 when analysed across this region. On 3rd December 2010: The SSM/I satellite that is used to provide the data for the sea ice analysis in HadISST suffered a significant degradation in performance through January and February 2009. The problem affected HadISST fields from January 2009 and probably causes an underestimate of ice extent and concentration. It also affected ses surface temperatures in sea ice areas because the SSTs are estimated from the sea ice concentration. As of 3rd December 2010, the Met Office Hadley Centre has reprocessed the data from January 2009 to the present using a difference sea ice data source. This is an improvement on the previous situation but users should still note that the switch of data source at the start of 2009 might introduce a discontinuity into the record.

In Autumn 1995, the Goddard Distributed Active Archive Center (GDAAC) compiled the Climatology Interdisciplinary Data Collection (CIDC) to facilitate interdisciplinary studies related to climate and global change. This data collection has been produced in collaboration with the Center for Earth Observing and Space Research (CEOSR), Institute for Computational Sciences and Informatics (CSI), and George Mason University. It was designed for the study of global change, seasonal to interannual climate change, and other phenomena that require from one to dozens of interacting parameters. A few of the possible study areas are the depletion of stratospheric ozone, the weather changes associated with the periodic El Niño Southern Oscillation (ENSO) events, periodic droughts, and global warming. Short background information scenarios are given on the CD for the Monsoon, El Niño, and global warming phenomena. The CD set also contains read software and the Gridded Analysis and Display System (GrADS). Data from the scientific disciplines dealing with meteorology and atmospheric sciences, land surface, ocean, cryosphere, biosphere, the Sun, and remote sensing science have been gathered into one place and, where feasible, presented in a common format (monthly means with a 1° x 1° world grid, or commensurable resolution and IEEE 32-bit floating point numbers). Over 70 physical parameters from some 25 separate datasets are represented. The Data Collection Overview document on the CDs lists alphabetically all the physical parameters along with the dataset(s) in which they can be found. It also contains a separate listing of each dataset, its origin, and the parameters included. Each dataset is also accompanied by a detailed user's guide. The Climatology Interdisciplinary Data Collection (CIDC) has been subdivided into seven categories. The grouping is influenced by the types of physical parameters involved and partially by the way that they are processed. Because of this the same physical parameter may appear in several datasets and in more than one category. When this occurs different algorithms have normally been used to produce the parameter. The included datasets included below. Atmospheric dynamics & atmospheric sounding products Radiation and clouds Biosphere data Measured variable atmospheric constituents Measured surface temperature and pressure Hydrological data Remote sensing science The data on the CD set was collected in a variety of ways, using remote sensing, direct measurements, and model output. The individual datasets were provided in a variety of forms. In some cases this required the data publication team to regrid and reformat datasets and in others to produce monthly averages from finer resolution data. The specific handling for each dataset is detailed in the documentation. The regridded, reformatted, integrated, and peer reviewed datasets are published on this four-volume CD collection. The data are held online at the BADC are public and are made available for browsing purposes. Volume 1: Biosphere, Hydrology, Surface Temperature, Ozone, Greenhouse Gases Volume 2: Atmospheric Dynamics Volume 3: Radiation and Clouds Volume 4: Atmospheric Surroundings

This dataset contains measurements of sea ice content (HadISST1.1). Dataset include monthly mean gridded (1deg grid), global Ice content from 1870 to October 2015. This product replaced the GISST/GICE (Global Sea Surface Temperature/Global sea-Ice content) data sets ended in February 2003. The sea ice data are taken from a variety of sources including digitized sea ice charts and passive microwave retrievals. The sea ice fields are made more homogeneous by compensating satellite microwave-based sea ice concentrations for the impact of surface melt effects on retrievals in the Arctic and for algorithm deficiencies in the Antarctic, and by making the historical in situ concentrations consistent with the satellite data. SSTs near sea ice are estimated using statistical relationships between SST and sea ice concentration. From May 2007 the data set of in situ measurements used in HadISST has changed. The MOHSST data set, which was previously used has been discontinued, and HadSST2 is now being used in its place. The two systems ran in parallel for several months prior to the changeover and no significant differences were seen. The data were provided by the Hadley centre (Met Office). Important Notes: On 13th March 2015: Users have noticed that there is a minor discontinuity at the dateline in HadISST1 SST fields starting in 1982. It appears to only affect gridcells just to the east of the dateline. Please note that this can affect estimates of the mean and variability of SSTs in HadISST1 when analysed across this region. On 8th March 2011: The switch of satellite source data at the start of 2009 introduced a discontinuity in the fields of sea ice in both the Arctic and Antarctic. On 3rd December 2010: The SSM/I satellite that is used to provide the data for the sea ice analysis in HadISST suffered a significant degradation in performance through January and February 2009. The problem affected HadISST fields from January 2009 and probably causes an underestimate of ice extent and concentration. It also affected ses surface temperatures in sea ice areas because the SSTs are estimated from the sea ice concentration. As of 3rd December 2010, the Met Office Hadley Centre has reprocessed the data from January 2009 to the present using a difference sea ice data source. This is an improvement on the previous situation but users should still note that the switch of data source at the start of 2009 might introduce a discontinuity into the record.

MarQUEST was led by Prof Andrew Watson (UEA), with 15 co-investigators at UEA/BAS, the Universities of Southampton, Essex, and Reading, and from the Plymouth Marine Laboratory and Proudman Oceanographic Laboratory. This dataset collection contains ocean optical, chemical and plankton model measurements from SeaWiFS/SeaStar Level 3 products. MarQUEST developed new methods of validating ocean biogeochemistry models, making use of remote sensing ocean colour data, in situ data sets and ongoing observations from the major European programmes CarboOcean and EUR-OCEANS. In the past, ocean biogeochemical models represented biological processes in very simple or rigid ways (e.g., single nutrient limitation, a single generic primary producer), limiting understanding of the role of ecosystems in the climate system. Increasing the complexity of models has presented new challenges for their validation; it is also not clear what the ‘optimal’ complexity of a model should be for any given real-world problem. QUEST scientists cooperated in comparing various models, and examining more fundamental (physiological) approaches to understanding the planktonic ecoystem. MarQUEST also developed a module to simulate coastal ecosystems usable in global ocean biogeochemical simulations. Finally, the project team generated an accurate physical simulation of the North Atlantic guided by data assimilation, into which ecosystem simulations can be embedded. This allows the variation in air-sea fluxes of gases (CO2, oxygen and dimethyl sulphide) from ocean to atmosphere to be quantified for the contemporary period.

The Met Office Hadley Centre's sea surface temperature data set, HadSST2, replaces the Met Office Historical Sea Surface Temperature dataset (MOHSST6) and is a monthly global field of SST (Sea Surface Temperature) on a 5 deg latitude by 5 deg longitude grid from 1850 to 2013. The data are neither interpolated nor variance adjusted. The observations that make up this dataset are taken from the International Comprehensive Ocean-Atmosphere DataSet, ICOADS (see http://www.cdc.noaa.gov/coads/), until 1997 and from the NCEP GTS archive thereafter. Individual observations must first pass a series of quality checks (track check, reality check, positional check, climatology check, buddy check, duplicate check). The quality-checked observations in each 1degree longitude X 1degree latitude X pentad gridbox are then averaged using a winsorised average. The pentad climatology is then subtracted from these pentad superobs and the resulting anomalies are averaged to 5degree X 5degree X monthly resolution. The data are then bias-corrected for the use of buckets in the period 1850-1941.