Over-determined charbonate chemstry dataset from different kinds of manipulation (TA, DIC) and water types (natural and artificial seawater)

The growing field of ocean acidification research is concerned with the investigation of organism responses to increasing pCO2 values. One important approach in this context is culture work using seawater with adjusted CO2 levels. As aqueous pCO2 is difficult to measure directly in small-scale experiments, it is generally calculated from two other measured parameters of the carbonate system (often AT, CT or pH). Unfortunately, the overall uncertainties of measured and subsequently calculated values are often unknown. Especially under high pCO2, this can become a severe problem with respect to the interpretation of physiological and ecological data. In the few datasets from ocean acidification research where all three of these parameters were measured, pCO2 values calculated from AT and CT are typically about 30% lower (i.e. ~300 µatm at a target pCO2 of 1000 µatm) than those calculated from AT and pH or CT and pH. This study presents and discusses these discrepancies as well as likely consequences for the ocean acidification community. Until this problem is solved, one has to consider that calculated parameters of the carbonate system (e.g. pCO2, calcite saturation state) may not be comparable between studies, and that this may have important implications for the interpretation of CO2 perturbation experiments.

Plant Functional Type (PFT) map over Siberia derived from GlobCover 2005 dataset, link to dataset in NetCDF format

High-latitude ecosystems play an important role in the global carbon cycle and in regulating the climate system and are presently undergoing rapid environmental change. Accurate land cover data sets are required to both document these changes as well as to provide land-surface information for benchmarking and initializing Earth system models. Earth system models also require specific land cover classification systems based on plant functional types (PFTs), rather than species or ecosystems, and so post-processing of existing land cover data is often required. This study compares over Siberia, multiple land cover data sets against one another and with auxiliary data to identify key uncertainties that contribute to variability in PFT classifications that would introduce errors in Earth system modeling. Land cover classification systems from GLC 2000, GlobCover 2005 and 2009, and MODIS collections 5 and 5.1 are first aggregated to a common legend, and then compared to high-resolution land cover classification systems, vegetation continuous fields (MODIS VCFs) and satellite-derived tree heights (to discriminate against sparse, shrub, and forest vegetation). The GlobCover data set, with a lower threshold for tree cover and taller tree heights and a better spatial resolution, tends to have better distributions of tree cover compared to high-resolution data. It has therefore been chosen to build new PFT maps for the ORCHIDEE land surface model at 1 km scale. Compared to the original PFT data set, the new PFT maps based on GlobCover 2005 and an updated cross-walking approach mainly differ in the characterization of forests and degree of tree cover. The partition of grasslands and bare soils now appears more realistic compared with ground truth data. This new vegetation map provides a framework for further development of new PFTs in the ORCHIDEE model like shrubs, lichens and mosses, to represent the water and carbon cycles in northern latitudes better. Updated land cover data sets are critical for improving and maintaining the relevance of Earth system models for assessing climate and human impacts on biogeochemistry and biophysics.

Heat index at 2 m above ground: A globally gridded dataset based on reanalysis data from 1979-2013, links to GeoTIFFs

The increase in global mean temperatures resulting from climate change has wide reaching consequences for the earth's ecosystems and other natural systems. Many studies have been devoted to evaluating the distribution and effects of these changes. We go a step further and evaluate global changes to the heat index, a measure of temperature as perceived by humans. Heat index, which is computed from temperature and relative humidity, is more important than temperature for the health of humans and other animals. Even in cases where the heat index does not reach dangerous levels from a health perspective, it has been shown to be an important factor in worker productivity and thus in economic productivity. We compute heat index from dewpoint temperature and absolute temperature 2 m above ground from the ERA-Interim reanalysis dataset for the years 1979-2013. The data is provided aggregated to daily minima, means and maxima. Furthermore, the data is temporally aggregated to monthly and yearly values and spatially aggregated to the level of countries after being weighted by population density in order to demonstrate its usefulness for the analysis of its impact on human health and productivity. The resulting data deliver insights into the spatiotemporal development of near-ground heat index during the course of the past 3 decades. It is shown that the impact of changing heat index is unevenly distributed through space and time, affecting some areas differently than others. The likelihood of dangerous heat index events has increased globally. Also, heat index climate groups that would formerly be expected closer to the tropics have spread latitudinally to include areas closer to the poles. The data can serve in future studies as a basis for evaluating and understanding the evolution of heat index in the course of climate change, as well as its impact on human health and productivity.

Objective Mapping of Argo data in the Weddell Gyre: a gridded dataset of upper ocean water properties, link to data files in NetCDF format

The Weddell Gyre plays a crucial role in the regulation of climate by transferring heat into the deep ocean through deep and bottom water mass formation. However, our understanding of Weddell Gyre water mass properties is limited to regions of data availability, primarily along the Prime Meridian. The aim is to provide a dataset of the upper water column properties of the entire Weddell Gyre. Objective mapping was applied to Argo float data in order to produce spatially gridded, time composite maps of temperature and salinity for fixed pressure levels ranging from 50 to 2000 dbar, as well as temperature, salinity and pressure at the level of the sub-surface temperature maximum. While the data are currently too limited to incorporate time into the gridded structure, the data are extensive enough to produce maps of the entire region across three time composite periods (2002-2005, 2006-2009 and 2010-2013), which can be used to determine how representative conclusions drawn from data collected along general RV transect lines are on a gyre scale perspective. The time composite data sets are provided as netCDF files; one for each time period. Mapped fields of conservative temperature, absolute salinity and potential density are provided for 41 vertical pressure levels. The above variables as well as pressure are provided at the level of the sub-surface temperature maximum. Corresponding mapping errors are also included in the netCDF files. Further details are provided in the global attributes, such as the unit variables and structure of the corresponding data array (i.e. latitude x longitude x vertical pressure level). In addition, all files ending in "_potTpSal" provide mapped fields of potential temperature and practical salinity.

Arctic Siberia: Modern pollen dataset and pollen spectra changes over the last 7,000 years from a lacustrine sediment core (southern Taymyr region)

Palaeoecological investigations in the larch forest-tundra ecotone in northern Siberia have the potential to reveal Holocene environmental variations, which likely have consequences for global climate change because of the strong high-latitude feedback mechanisms. A sediment core, collected from a small lake (radius ~100 m), was used to reconstruct the development of the lake and its catchment as well as vegetation and summer temperatures over the last 7100 calibrated years. A multi-proxy approach was taken including pollen and sedimentological analyses. Our data indicate a gradual replacement of open larch forests by tundra with scattered single trees as found today in the vicinity of the lake. An overall trend of cooling summer temperature from a ~2 °C warmer-than-present mid-Holocene summer temperatures until the establishment of modern conditions around 3000 years ago is reconstructed based on a regional pollen-climate transfer function. The inference of regional vegetation changes was compared to local changes in the lake's catchment. An initial small water depression occurred from 7100 to 6500 cal years BP. Afterwards, a small lake formed and deepened, probably due to thermokarst processes. Although the general trends of local and regional environmental change match, the lake catchment changes show higher variability. Furthermore, changes in the lake catchment slightly precede those in the regional vegetation. Both proxies highlight that marked environmental changes occurred in the Siberian forest-tundra ecotone over the course of the Holocene.

Global Fuelbed Dataset

This dataset presents the first global fuel map, containing all the parameters required to be input in the Fuel Characteristic Classification System (FCCS). The dataset was developed from different spatial variables, both based on satellite Earth observation products and fuel databases, and is comprised by a global fuelbed map and a database that includes the parameters of each fuelbed that affect fire behavior and effects. A total of 274 fuelbeds were created and parameterized, and can be input into FCCS to obtain fire potentials, surface fire behavior and carbon biomass for each fuelbed. The global fuel dataset can be used for a varied range of applications, including fire danger assessment, fire behavior estimations, fuel consumption calculations and emissions inventories.

A 18-years long (1993-2011) snow and meteorological dataset from a mid-altitude mountain site (Col de Porte, France, 1325 altitude)

A quality-controlled snow and meteorological dataset spanning the period 1 August 1993-31 July 2011 is presented, originating from the experimental station Col de Porte (1325 m altitude, Chartreuse range, France). Emphasis is placed on meteorological data relevant to the observation and modelling of the seasonal snowpack. In-situ driving data, at the hourly resolution, consist of measurements of air temperature, relative humidity, windspeed, incoming short-wave and long-wave radiation, precipitation rate partitioned between snow- and rainfall, with a focus on the snow-dominated season. Meteorological data for the three summer months (generally from 10 June to 20 September), when the continuity of the field record is not warranted, are taken from a local meteorological reanalysis (SAFRAN), in order to provide a continuous and consistent gap-free record. Data relevant to snowpack properties are provided at the daily (snow depth, snow water equivalent, runoff and albedo) and hourly (snow depth, albedo, runoff, surface temperature, soil temperature) time resolution. Internal snowpack information is provided from weekly manual snowpit observations (mostly consisting in penetration resistance, snow type, snow temperature and density profiles) and from a hourly record of temperature and height of vertically free ''settling'' disks. This dataset has been partially used in the past to assist in developing snowpack models and is presented here comprehensively for the purpose of multi-year model performance assessment. The data is placed on the PANGAEA repository (doi:10.1594/PANGAEA.774249) as well as on the public ftp server ftp://ftp-cnrm.meteo.fr/pub-cencdp/.