Showing papers in "Earth System Science Data in 2018"

Global Carbon Budget 2018

Abstract: . Accurate assessment of anthropogenic carbon dioxide ( CO2 ) emissions and their redistribution among the atmosphere, ocean, and terrestrial biosphere – the “global carbon budget” – is important to better understand the global carbon cycle, support the development of climate policies, and project future climate change. Here we describe data sets and methodology to quantify the five major components of the global carbon budget and their uncertainties. Fossil CO2 emissions ( EFF ) are based on energy statistics and cement production data, while emissions from land use and land-use change ( ELUC ), mainly deforestation, are based on land use and land-use change data and bookkeeping models. Atmospheric CO2 concentration is measured directly and its growth rate ( GATM ) is computed from the annual changes in concentration. The ocean CO2 sink ( SOCEAN ) and terrestrial CO2 sink ( SLAND ) are estimated with global process models constrained by observations. The resulting carbon budget imbalance ( BIM ), the difference between the estimated total emissions and the estimated changes in the atmosphere, ocean, and terrestrial biosphere, is a measure of imperfect data and understanding of the contemporary carbon cycle. All uncertainties are reported as ±1σ . For the last decade available (2008–2017), EFF was 9.4±0.5 GtC yr −1 , ELUC 1.5±0.7 GtC yr −1 , GATM 4.7±0.02 GtC yr −1 , SOCEAN 2.4±0.5 GtC yr −1 , and SLAND 3.2±0.8 GtC yr −1 , with a budget imbalance BIM of 0.5 GtC yr −1 indicating overestimated emissions and/or underestimated sinks. For the year 2017 alone, the growth in EFF was about 1.6 % and emissions increased to 9.9±0.5 GtC yr −1 . Also for 2017, ELUC was 1.4±0.7 GtC yr −1 , GATM was 4.6±0.2 GtC yr −1 , SOCEAN was 2.5±0.5 GtC yr −1 , and SLAND was 3.8±0.8 GtC yr −1 , with a BIM of 0.3 GtC. The global atmospheric CO2 concentration reached 405.0±0.1 ppm averaged over 2017. For 2018, preliminary data for the first 6–9 months indicate a renewed growth in EFF of + 2.7 % (range of 1.8 % to 3.7 %) based on national emission projections for China, the US, the EU, and India and projections of gross domestic product corrected for recent changes in the carbon intensity of the economy for the rest of the world. The analysis presented here shows that the mean and trend in the five components of the global carbon budget are consistently estimated over the period of 1959–2017, but discrepancies of up to 1 GtC yr −1 persist for the representation of semi-decadal variability in CO2 fluxes. A detailed comparison among individual estimates and the introduction of a broad range of observations show (1) no consensus in the mean and trend in land-use change emissions, (2) a persistent low agreement among the different methods on the magnitude of the land CO2 flux in the northern extra-tropics, and (3) an apparent underestimation of the CO2 variability by ocean models, originating outside the tropics. This living data update documents changes in the methods and data sets used in this new global carbon budget and the progress in understanding the global carbon cycle compared with previous publications of this data set (Le Quere et al., 2018, 2016, 2015a, b, 2014, 2013). All results presented here can be downloaded from https://doi.org/10.18160/GCP-2018 .

Gridded emissions of air pollutants for the period 1970-2012 within EDGAR v4.3.2

Abstract: . The new version of the Emissions Database for Global Atmospheric Research (EDGAR v4.3.2) compiles gaseous and particulate air pollutant emissions, making use of the same anthropogenic sectors, time period (1970–2012), and international activity data that is used for estimating GHG emissions, as described in a companion paper (Janssens-Maenhout et al., 2017). All human activities, except large scale biomass burning and land use, land-use change, and forestry are included in the emissions calculation. The bottom-up compilation methodology of sector-specific emissions was applied consistently for all world countries, providing methodological transparency and comparability between countries. In addition to the activity data used to estimate GHG emissions, air pollutant emissions are determined by the process technology and end-of-pipe emission reduction abatements. Region-specific emission factors and abatement measures were selected from recent available scientific literature and reports. Compared to previous versions of EDGAR, the EDGAR v4.3.2 dataset covers all gaseous and particulate air pollutants, has extended time series (1970–2012), and has been evaluated with quality control and quality assurance (QC and QA) procedures both for the emission time series (e.g. particulate matter – PM – mass balance, gap-filling for missing data, the split-up of countries over time, few updates in the emission factors, etc.) and grid maps (full coverage of the world, complete mapping of EDGAR emissions with sector-specific proxies, etc.). This publication focuses on the gaseous air pollutants of CO, NOx, SO2, total non-methane volatile organic compounds (NMVOCs), NH3, and the aerosols PM10, PM2.5, black carbon (BC), and organic carbon (OC). Considering the 1970–2012 time period, global emissions of SO2 increased from 99 to 103 Mt, CO from 441 to 562 Mt, NOx from 68 to 122 Mt, NMVOC from 119 to 170 Mt, NH3 from 25 to 59 Mt, PM10 from 37 to 65 Mt, PM2.5 from 24 to 41 Mt, BC from 2.7 to 4.5 Mt, and OC from 9 to 11 Mt. We present the country-specific emission totals and analyze the larger emitting countries (including the European Union) to provide insights on major sector contributions. In addition, per capita and per GDP emissions and implied emission factors – the apparent emissions per unit of production or energy consumption – are presented. We find that the implied emission factors (EFs) are higher for low-income countries compared to high-income countries, but in both cases decrease from 1970 to 2012. The comparison with other global inventories, such as the Hemispheric Transport of Air Pollution Inventory (HTAP v2.2) and the Community Emission Data System (CEDS), reveals insights on the uncertainties as well as the impact of data revisions (e.g. activity data, emission factors, etc.). As an additional metric, we analyze the emission ratios of some pollutants to CO2 (e.g. CO∕CO2, NOx∕CO2, NOx∕CO, and SO2∕CO2) by sector, region, and time to identify any decoupling of air pollutant emissions from energy production activities and to demonstrate the potential of such ratios to compare to satellite-derived emission data. Gridded emissions are also made available for the 1970–2012 historic time series, disaggregated for 26 anthropogenic sectors using updated spatial proxies. The analysis of the evolution of hot spots over time allowed us to identify areas with growing emissions and where emissions should be constrained to improve global air quality (e.g. China, India, the Middle East, and some South American countries are often characterized by high emitting areas that are changing rapidly compared to Europe or the USA, where stable or decreasing emissions are evaluated). Sector- and component-specific contributions to grid-cell emissions may help the modelling and satellite communities to disaggregate atmospheric column amounts and concentrations into main emitting sectors. This work addresses not only the emission inventory and modelling communities, but also aims to broaden the usefulness of information available in a global emission inventory such as EDGAR to also include the measurement community. Data are publicly available online through the EDGAR website http://edgar.jrc.ec.europa.eu/overview.php?v=432_AP and registered under https://doi.org/10.2904/JRC_DATASET_EDGAR .

Global sea-level budget 1993 - present

Abstract: Global mean sea level is an integral of changes occurring in the climate system in response to unforced climate variability as well as natural and anthropogenic forcing factors. Its temporal evolution allows detecting changes (e.g., acceleration) in one or more components. Study of the sea level budget provides constraints on missing or poorly known contributions, such as the unsurveyed deep ocean or the still uncertain land water component. In the context of the World Climate Research Programme Grand Challenge entitled “Regional Sea Level and Coastal Impacts”, an international effort involving the sea level community worldwide has been recently initiated with the objective of assessing the various data sets used to estimate components of the sea level budget during the altimetry era (1993 to present). These data sets are based on the combination of a broad range of space-based and in situ observations, model estimates and algorithms. Evaluating their quality, quantifying uncertainties and identifying sources of discrepancies between component estimates is extremely useful for various applications in climate research. This effort involves several tens of scientists from about fifty research teams/institutions worldwide (www.wcrp-climate.org/grand-challenges/gc-sea- level). The results presented in this paper are a synthesis of the first assessment performed during 2017-2018. We present estimates of the altimetry-based global mean sea level (average rate of 3.1 +/- 0.3 mm/yr and acceleration of 0.1 mm/yr2 over 1993-present), as well as of the different components of the sea level budget (http://doi.org/10.17882/54854). We further examine closure of the sea level budget, comparing the observed global mean sea level with the sum of components. Ocean thermal expansion, glaciers, Greenland and Antarctica contribute by 42%, 21%, 15% and 8% to the global mean sea level over the 1993-present. We also study the sea level budget over 2005-present, using GRACE-based ocean mass estimates instead of sum of individual mass components. Results show closure of the sea level budget within 0.3 mm/yr. Substantial uncertainty remains for the land water storage component, as shown in examining individual mass contributions to sea level.

Global CO 2 emissions from cement production, 1928–2018

Abstract: . Global production of cement has grown very rapidly in recent years, and, after fossil fuels and land-use change, it is the third-largest source of anthropogenic emissions of carbon dioxide. The availability of the required data for estimating emissions from global cement production is poor, and it has been recognised that some global estimates are significantly inflated. This article assembles a large variety of available datasets, prioritising official data and emission factors, including estimates submitted to the UN Framework Convention on Climate Change (UNFCCC), plus new estimates for China and India, to present a new analysis of global process emissions from cement production. Global process emissions in 2018 were 1.50±0.12 Gt CO2 , equivalent to about 4 % of emissions from fossil fuels. Cumulative emissions from 1928 to 2018 were 38.3±2.4 Gt CO2 , 71 % of which have occurred since 1990. The data associated with this article can be found at https://doi.org/10.5281/zenodo.831454 (Andrew, 2019).

Baseline Surface Radiation Network (BSRN): structure and data description (1992-2017)

Abstract: . Small changes in the radiation budget at the earth's surface can lead to large climatological responses when persistent over time. With the increasing debate on anthropogenic influences on climatic processes during the 1980s the need for accurate radiometric measurements with higher temporal resolution was identified, and it was determined that the existing measurement networks did not have the resolution or accuracy required to meet this need. In 1988 the WMO therefore proposed the establishment of a new international Baseline Surface Radiation Network (BSRN), which should collect and centrally archive high-quality ground-based radiation measurements in 1 min resolution. BSRN began its work in 1992 with 9 stations; currently (status 2018-01-01), the network comprises 59 stations (delivering data to the archive) and 9 candidates (stations recently accepted into the network with data forthcoming to the archive) distributed over all continents and oceanic environments. The BSRN database is the World Radiation Monitoring Center (WRMC). It is hosted at the Alfred Wegener Institute (AWI) in Bremerhaven, Germany, and now offers more than 10 300 months of data from the years 1992 to 2017. All data are available at https://doi.org/10.1594/PANGAEA.880000 free of charge.

Gross and net land cover changes in the main plant functional types derived from the annual ESA CCI land cover maps (1992–2015)

Abstract: . Land-use and land-cover change (LULCC) impacts local energy and water balance and contributes on global scale to a net carbon emission to the atmosphere. The newly released annual ESA CCI (climate change initiative) land cover maps provide continuous land cover changes at 300 m resolution from 1992 to 2015, and can be used in land surface models (LSMs) to simulate LULCC effects on carbon stocks and on surface energy budgets. Here we investigate the absolute areas and gross and net changes in different plant functional types (PFTs) derived from ESA CCI products. The results are compared with other datasets. Global areas of forest, cropland and grassland PFTs from ESA are 30.4, 19.3 and 35.7 million km2 in the year 2000. The global forest area is lower than that from LUH2v2h (Hurtt et al., 2011), Hansen et al. (2013) or Houghton and Nassikas (2017) while cropland area is higher than LUH2v2h (Hurtt et al., 2011), in which cropland area is from HYDE 3.2 (Klein Goldewijk et al., 2016). Gross forest loss and gain during 1992–2015 are 1.5 and 0.9 million km2 respectively, resulting in a net forest loss of 0.6 million km2 , mainly occurring in South and Central America. The magnitudes of gross changes in forest, cropland and grassland PFTs in the ESA CCI are smaller than those in other datasets. The magnitude of global net cropland gain for the whole period is consistent with HYDE 3.2 (Klein Goldewijk et al., 2016), but most of the increases happened before 2004 in ESA and after 2007 in HYDE 3.2. Brazil, Bolivia and Indonesia are the countries with the largest net forest loss from 1992 to 2015, and the decreased areas are generally consistent with those from Hansen et al. (2013) based on Landsat 30 m resolution images. Despite discrepancies compared to other datasets, and uncertainties in converting into PFTs, the new ESA CCI products provide the first detailed long-term time series of land-cover change and can be implemented in LSMs to characterize recent carbon dynamics, and in climate models to simulate land-cover change feedbacks on climate. The annual ESA CCI land cover products can be downloaded from http://maps.elie.ucl.ac.be/CCI/viewer/download.php (Land Cover Maps – v2.0.7; see details in Sect. 5). The PFT map translation protocol and an example in 2000 can be downloaded from https://doi.org/10.5281/zenodo.834229 . The annual ESA CCI PFT maps from 1992 to 2015 at 0.5 ∘ × 0.5 ∘ resolution can also be downloaded from https://doi.org/10.5281/zenodo.1048163 .

Generation and analysis of a new global burned area product based on MODIS 250 m reflectance bands and thermal anomalies

Abstract: . This paper presents a new global burned area (BA) product, generated from the Moderate Resolution Imaging Spectroradiometer (MODIS) red (R) and near-infrared (NIR) reflectances and thermal anomaly data, thus providing the highest spatial resolution (approx. 250 m) among the existing global BA datasets. The product includes the full times series (2001–2016) of the Terra-MODIS archive. The BA detection algorithm was based on monthly composites of daily images, using temporal and spatial distance to active fires. The algorithm has two steps, the first one aiming to reduce commission errors by selecting the most clearly burned pixels (seeds), and the second one targeting to reduce omission errors by applying contextual analysis around the seed pixels. This product was developed within the European Space Agency's (ESA) Climate Change Initiative (CCI) programme, under the Fire Disturbance project (Fire_cci). The final output includes two types of BA files: monthly full-resolution continental tiles and biweekly global grid files at a degraded resolution of 0.25 ∘ . Each set of products includes several auxiliary variables that were defined by the climate users to facilitate the ingestion of the product into global dynamic vegetation and atmospheric emission models. Average annual burned area from this product was 3.81 Mkm 2 , with maximum burning in 2011 (4.1 Mkm 2 ) and minimum in 2013 (3.24 Mkm 2 ). The validation was based on a stratified random sample of 1200 pairs of Landsat images, covering the whole globe from 2003 to 2014. The validation indicates an overall accuracy of 0.9972, with much higher errors for the burned than the unburned category (global omission error of BA was estimated as 0.7090 and global commission as 0.5123). These error values are similar to other global BA products, but slightly higher than the NASA BA product (named MCD64A1, which is produced at 500 m resolution). However, commission and omission errors are better compensated in our product, with a tendency towards BA underestimation (relative bias −0.4033 ), as most existing global BA products. To understand the value of this product in detecting small fire patches ( ha), an additional validation sample of 52 Sentinel-2 scenes was generated specifically over Africa. Analysis of these results indicates a better detection accuracy of this product for small fire patches ( ha) than the equivalent 500 m MCD64A1 product, although both have high errors for these small fires. Examples of potential applications of this dataset to fire modelling based on burned patches analysis are included in this paper. The datasets are freely downloadable from the Fire_cci website ( https://www.esa-fire-cci.org/ , last access: 10 November 2018) and their repositories (pixel at full resolution: https://doi.org/cpk7 , and grid: https://doi.org/gcx9gf ).

History of chemically and radiatively important atmospheric gases from the Advanced Global Atmospheric Gases Experiment (AGAGE)

Abstract: . We present the organization, instrumentation, datasets, data interpretation, modeling, and accomplishments of the multinational global atmospheric measurement program AGAGE (Advanced Global Atmospheric Gases Experiment). AGAGE is distinguished by its capability to measure globally, at high frequency, and at multiple sites all the important species in the Montreal Protocol and all the important non-carbon-dioxide (non- CO2 ) gases assessed by the Intergovernmental Panel on Climate Change ( CO2 is also measured at several sites). The scientific objectives of AGAGE are important in furthering our understanding of global chemical and climatic phenomena. They are the following: (1) to accurately measure the temporal and spatial distributions of anthropogenic gases that contribute the majority of reactive halogen to the stratosphere and/or are strong infrared absorbers (chlorocarbons, chlorofluorocarbons – CFCs, bromocarbons, hydrochlorofluorocarbons – HCFCs, hydrofluorocarbons – HFCs and polyfluorinated compounds (perfluorocarbons – PFCs), nitrogen trifluoride – NF3 , sulfuryl fluoride – SO2F2 , and sulfur hexafluoride – SF6 ) and use these measurements to determine the global rates of their emission and/or destruction (i.e., lifetimes); (2) to accurately measure the global distributions and temporal behaviors and determine the sources and sinks of non- CO2 biogenic–anthropogenic gases important to climate change and/or ozone depletion (methane – CH4 , nitrous oxide – N2O , carbon monoxide – CO, molecular hydrogen – H2 , methyl chloride – CH3Cl , and methyl bromide – CH3Br ); (3) to identify new long-lived greenhouse and ozone-depleting gases (e.g., SO2F2 , NF3 , heavy PFCs ( C4F10 , C5F12 , C6F14 , C7F16 , and C8F18 ) and hydrofluoroolefins (HFOs; e.g., CH2 = CFCF3 ) have been identified in AGAGE), initiate the real-time monitoring of these new gases, and reconstruct their past histories from AGAGE, air archive, and firn air measurements; (4) to determine the average concentrations and trends of tropospheric hydroxyl radicals (OH) from the rates of destruction of atmospheric trichloroethane ( CH3CCl3 ), HFCs, and HCFCs and estimates of their emissions; (5) to determine from atmospheric observations and estimates of their destruction rates the magnitudes and distributions by region of surface sources and sinks of all measured gases; (6) to provide accurate data on the global accumulation of many of these trace gases that are used to test the synoptic-, regional-, and global-scale circulations predicted by three-dimensional models; and (7) to provide global and regional measurements of methane, carbon monoxide, and molecular hydrogen and estimates of hydroxyl levels to test primary atmospheric oxidation pathways at midlatitudes and the tropics. Network Information and Data Repository: http://agage.mit.edu/data or http://cdiac.ess-dive.lbl.gov/ndps/alegage.html ( https://doi.org/10.3334/CDIAC/atg.db1001 ).

The ISC-GEM Earthquake Catalogue (1904–2014): status after the Extension Project

Abstract: . We outline the work done to extend and improve the ISC-GEM Global Instrumental Earthquake Catalogue, a dataset which was first released in 2013 ( Storchak et al. , 2013 , 2015 ) . In its first version (V1) the catalogue included global earthquakes selected according to time-dependent cut-off magnitudes: 7.5 and above between 1900 and 1918 (plus significant continental earthquakes 6.5 and above); 6.25 between 1918 and 1959; 5.5 between 1960 and 2009. Such selection criteria were dictated by time and resource limitations. With the Extension Project we added both pre-1960 events below the original cut-off magnitudes (if enough station data were available to perform relocation and magnitude recomputation) and added events with magnitude 5.5 and above from 2010 to 2014. The project ran over a 4-year period during which a new version of the ISC-GEM Catalogue was released each year via the ISC website ( http://http://www.isc.ac.uk/iscgem/ , last access: 10 October 2018). For each year, not only have we added new events to the catalogue for a given time range but also revised events already in V1 if additional data became available or location and/or magnitude reassessments were required. Here we recall the general background behind the production of the ISC-GEM Catalogue and describe the features of the different periods in which the catalogue has been extended. Compared to the 2013 release, we eliminated earthquakes during the first 4 years (1900–1903) of the catalogue (due to lack of reliable station data), added approximately 12 000 and 2500 earthquakes before 1960 and between 2010 and 2014, respectively, and improved the solution for approximately 2000 earthquakes already listed in previous versions. We expect the ISC-GEM Catalogue to continue to be one of the most useful datasets for studies of the Earth's global seismicity and an important benchmark for seismic hazard analyses, and, ultimately, an asset for the seismological community as well as other geoscience fields, education and outreach activities. The ISC-GEM Catalogue is freely available at https://doi.org/10.31905/D808B825 .

seNorge2 daily precipitation, an observational gridded dataset over Norway from 1957 to the present day

Abstract: . The conventional climate gridded datasets based on observations only are widely used in atmospheric sciences; our focus in this paper is on climate and hydrology. On the Norwegian mainland, seNorge2 provides high-resolution fields of daily total precipitation for applications requiring long-term datasets at regional or national level, where the challenge is to simulate small-scale processes often taking place in complex terrain. The dataset constitutes a valuable meteorological input for snow and hydrological simulations; it is updated daily and presented on a high-resolution grid (1 km of grid spacing). The climate archive goes back to 1957. The spatial interpolation scheme builds upon classical methods, such as optimal interpolation and successive-correction schemes. An original approach based on (spatial) scale-separation concepts has been implemented which uses geographical coordinates and elevation as complementary information in the interpolation. seNorge2 daily precipitation fields represent local precipitation features at spatial scales of a few kilometers, depending on the station network density. In the surroundings of a station or in dense station areas, the predictions are quite accurate even for intense precipitation. For most of the grid points, the performances are comparable to or better than a state-of-the-art pan-European dataset (E-OBS), because of the higher effective resolution of seNorge2. However, in very data-sparse areas, such as in the mountainous region of southern Norway, seNorge2 underestimates precipitation because it does not make use of enough geographical information to compensate for the lack of observations. The evaluation of seNorge2 as the meteorological forcing for the seNorge snow model and the DDD (Distance Distribution Dynamics) rainfall–runoff model shows that both models have been able to make profitable use of seNorge2, partly because of the automatic calibration procedure they incorporate for precipitation. The seNorge2 dataset 1957–2015 is available at https://doi.org/10.5281/zenodo.845733 . Daily updates from 2015 onwards are available at http://thredds.met.no/thredds/catalog/metusers/senorge2/seNorge2/provisional_archive/PREC1d/gridded_dataset/catalog.html .

Development and analysis of the Soil Water Infiltration Global database

Abstract: . In this paper, we present and analyze a novel global database of soil infiltration measurements, the Soil Water Infiltration Global (SWIG) database. In total, 5023 infiltration curves were collected across all continents in the SWIG database. These data were either provided and quality checked by the scientists who performed the experiments or they were digitized from published articles. Data from 54 different countries were included in the database with major contributions from Iran, China, and the USA. In addition to its extensive geographical coverage, the collected infiltration curves cover research from 1976 to late 2017. Basic information on measurement location and method, soil properties, and land use was gathered along with the infiltration data, making the database valuable for the development of pedotransfer functions (PTFs) for estimating soil hydraulic properties, for the evaluation of infiltration measurement methods, and for developing and validating infiltration models. Soil textural information (clay, silt, and sand content) is available for 3842 out of 5023 infiltration measurements ( ∼ 76%) covering nearly all soil USDA textural classes except for the sandy clay and silt classes. Information on land use is available for 76 % of the experimental sites with agricultural land use as the dominant type ( ∼ 40%). We are convinced that the SWIG database will allow for a better parameterization of the infiltration process in land surface models and for testing infiltration models. All collected data and related soil characteristics are provided online in *.xlsx and *.csv formats for reference, and we add a disclaimer that the database is for public domain use only and can be copied freely by referencing it. Supplementary data are available at https://doi.org/10.1594/PANGAEA.885492 (Rahmati et al., 2018). Data quality assessment is strongly advised prior to any use of this database. Finally, we would like to encourage scientists to extend and update the SWIG database by uploading new data to it.

A consistent glacier inventory for Karakoram and Pamir derived from Landsat data: distribution of debris cover and mapping challenges

Abstract: . Knowledge about the coverage and characteristics of glaciers in High Mountain Asia (HMA) is still incomplete and heterogeneous. However, several applications, such as modelling of past or future glacier development, run-off, or glacier volume, rely on the existence and accessibility of complete datasets. In particular, precise outlines of glacier extent are required to spatially constrain glacier-specific calculations such as length, area, and volume changes or flow velocities. As a contribution to the Randolph Glacier Inventory (RGI) and the Global Land Ice Measurements from Space (GLIMS) glacier database, we have produced a homogeneous inventory of the Pamir and the Karakoram mountain ranges using 28 Landsat TM and ETM + scenes acquired around the year 2000. We applied a standardized method of automated digital glacier mapping and manual correction using coherence images from the Advanced Land Observing Satellite 1 (ALOS-1) Phased Array type L-band Synthetic Aperture Radar 1 (PALSAR-1) as an additional source of information; we then (i) separated the glacier complexes into individual glaciers using drainage divides derived by watershed analysis from the ASTER global digital elevation model version 2 (GDEM2) and (ii) separately delineated all debris-covered areas. Assessment of uncertainties was performed for debris-covered and clean-ice glacier parts using the buffer method and independent multiple digitizing of three glaciers representing key challenges such as shadows and debris cover. Indeed, along with seasonal snow at high elevations, shadow and debris cover represent the largest uncertainties in our final dataset. In total, we mapped more than 27 800 glaciers >0.02 km 2 covering an area of 35 520±1948 km 2 and an elevation range from 2260 to 8600 m. Regional median glacier elevations vary from 4150 m (Pamir Alai) to almost 5400 m (Karakoram), which is largely due to differences in temperature and precipitation. Supraglacial debris covers an area of 3587±662 km 2 , i.e. 10 % of the total glacierized area. Larger glaciers have a higher share in debris-covered area (up to >20 %), making it an important factor to be considered in subsequent applications ( https://doi.org/10.1594/PANGAEA.894707 ).

GRACILE: a comprehensive climatology of atmospheric gravity wave parameters based on satellite limb soundings

Abstract: . Gravity waves are one of the main drivers of atmospheric dynamics. The spatial resolution of most global atmospheric models, however, is too coarse to properly resolve the small scales of gravity waves, which range from tens to a few thousand kilometers horizontally, and from below 1 km to tens of kilometers vertically. Gravity wave source processes involve even smaller scales. Therefore, general circulation models (GCMs) and chemistry climate models (CCMs) usually parametrize the effect of gravity waves on the global circulation. These parametrizations are very simplified. For this reason, comparisons with global observations of gravity waves are needed for an improvement of parametrizations and an alleviation of model biases. We present a gravity wave climatology based on atmospheric infrared limb emissions observed by satellite (GRACILE). GRACILE is a global data set of gravity wave distributions observed in the stratosphere and the mesosphere by the infrared limb sounding satellite instruments High Resolution Dynamics Limb Sounder (HIRDLS) and Sounding of the Atmosphere using Broadband Emission Radiometry (SABER). Typical distributions (zonal averages and global maps) of gravity wave vertical wavelengths and along-track horizontal wavenumbers are provided, as well as gravity wave temperature variances, potential energies and absolute momentum fluxes. This global data set captures the typical seasonal variations of these parameters, as well as their spatial variations. The GRACILE data set is suitable for scientific studies, and it can serve for comparison with other instruments (ground-based, airborne, or other satellite instruments) and for comparison with gravity wave distributions, both resolved and parametrized, in GCMs and CCMs. The GRACILE data set is available as supplementary data at https://doi.org/10.1594/PANGAEA.879658 .

Upscaled diurnal cycles of land-atmosphere fluxes: a new global half-hourly data product

Abstract: Interactions between the biosphere and the atmosphere can be well characterized by fluxes between the two In particular, carbon and energy fluxes play a major role in understanding biogeochemical processes on an ecosystem level or global scale However, the fluxes can only be measured at individual sites, eg, by eddy covariance towers, and an upscaling of these local observations is required to analyze global patterns Previous work focused on upscaling monthly, 8-day, or daily average values, and global maps for each flux have been provided accordingly In this paper, we raise the upscaling of carbon and energy fluxes between land and atmosphere to the next level by increasing the temporal resolution to subdaily timescales We provide continuous half-hourly fluxes for the period from 2001 to 2014 at 05° spatial resolution, which allows for analyzing diurnal cycles globally The data set contains four fluxes: gross primary production (GPP), net ecosystem exchange (NEE), latent heat (LE), and sensible heat (H) We propose two prediction approaches for the diurnal cycles based on large-scale regression models and compare them in extensive cross-validation experiments using different sets of predictor variables We analyze the results for a set of FLUXNET tower sites showing the suitability of our approaches for this upscaling task Finally, we have selected one approach to calculate the global half-hourly data products based on predictor variables from remote sensing and meteorology at daily resolution as well as half-hourly potential radiation In addition, we provide a derived product that only contains monthly average diurnal cycles, which is a lightweight version in terms of data storage that still allows studying the important characteristics of diurnal patterns globally We recommend to primarily use these monthly average diurnal cycles, because they are less affected by the impacts of day-to-day variation, observation noise, and short-term fluctuations on subdaily timescales compared to the full half-hourly flux products The global half-hourly data products are available at https://doiorg/1017871/BACI224

A general database of hydrometeor single scattering properties at microwave and sub-millimetre wavelengths

Abstract: . A main limitation today in simulations and inversions of microwave observations of ice hydrometeors (cloud ice, snow, hail, etc.) is the lack of data describing the interaction between electromagnetic waves and the particles. To improve the situation, the development of a comprehensive dataset of such scattering properties has been started. The database aims at giving a broad coverage in both frequency (1 to 886 GHz) and temperature (190 to 270 K), to support both passive and active current and planned measurements, and to provide data corresponding to the full Stokes vector. This first version of the database is restricted to totally random particle orientation. Data for 34 particle sets, i.e. habits, have been generated. About 17 of the habits can be classified as single crystals, three habits can be seen as heavily rimed particles, and the remaining habits are aggregates of different types, e.g. snow and hail. The particle sizes considered vary between the habits, but maximum diameters of 10 and 20 mm are typical values for the largest single crystal and aggregate particles, respectively, and the number of sizes per habit is at least 30. Particles containing liquid water are also inside the scope of the database, but this phase of water is so far only represented by a liquid sphere habit. The database is built upon the netCDF4 file format. Interfaces to browse, extract and convert data for selected radiative transfer models are provided in MATLAB and Python. The database and associated tools are publicly available from Zenodo ( https://doi.org/10.5281/zenodo.1175572 , Ekelund et al., 2018b), and https://doi.org/10.5281/zenodo.1175588 , Mendrok et al., 2018, respectively). Planned extensions include non-spherical raindrops, melting particles and a second orientation case that can be denoted as azimuthally random.

The SISAL database: a global resource to document oxygen and carbon isotope records from speleothems

Abstract: . Stable isotope records from speleothems provide information on past climate changes, most particularly information that can be used to reconstruct past changes in precipitation and atmospheric circulation. These records are increasingly being used to provide “out-of-sample” evaluations of isotope-enabled climate models. SISAL (Speleothem Isotope Synthesis and Analysis) is an international working group of the Past Global Changes (PAGES) project. The working group aims to provide a comprehensive compilation of speleothem isotope records for climate reconstruction and model evaluation. The SISAL database contains data for individual speleothems, grouped by cave system. Stable isotopes of oxygen and carbon ( δ18 O, δ13 C) measurements are referenced by distance from the top or bottom of the speleothem. Additional tables provide information on dating, including information on the dates used to construct the original age model and sufficient information to assess the quality of each data set and to erect a standardized chronology across different speleothems. The metadata table provides location information, information on the full range of measurements carried out on each speleothem and information on the cave system that is relevant to the interpretation of the records, as well as citations for both publications and archived data. The compiled data are available at https://doi.org/10.17864/1947.147 .

Integrated high-resolution dataset of high-intensity European and Mediterranean flash floods

Abstract: . This paper describes an integrated, high-resolution dataset of hydro-meteorological variables (rainfall and discharge) concerning a number of high-intensity flash floods that occurred in Europe and in the Mediterranean region from 1991 to 2015. This type of dataset is rare in the scientific literature because flash floods are typically poorly observed hydrological extremes. Valuable features of the dataset (hereinafter referred to as the EuroMedeFF database) include (i) its coverage of varied hydro-climatic regions, ranging from Continental Europe through the Mediterranean to Arid climates, (ii) the high space–time resolution radar rainfall estimates, and (iii) the dense spatial sampling of the flood response, by observed hydrographs and/or flood peak estimates from post-flood surveys. Flash floods included in the database are selected based on the limited upstream catchment areas (up to 3000 km2), the limited storm durations (up to 2 days), and the unit peak flood magnitude. The EuroMedeFF database comprises 49 events that occurred in France, Israel, Italy, Romania, Germany and Slovenia, and constitutes a sample of rainfall and flood discharge extremes in different climates. The dataset may be of help to hydrologists as well as other scientific communities because it offers benchmark data for the identification and analysis of the hydro-meteorological causative processes, evaluation of flash flood hydrological models and for hydro-meteorological forecast systems. The dataset also provides a template for the analysis of the space–time variability of flash flood triggering rainfall fields and of the effects of their estimation on the flood response modelling. The dataset is made available to the public with the following DOI: https://doi.org/10.6096/MISTRALS-HyMeX.1493 .

The SUMup Dataset: Compiled Measurements of Surface Mass Balance Components over Ice Sheets and Sea Ice with Analysis over Greenland

Abstract: . Increasing atmospheric temperatures over ice cover affect surface processes, including melt, snowfall, and snow density. Here, we present the Surface Mass Balance and Snow on Sea Ice Working Group (SUMup) dataset, a standardized dataset of Arctic and Antarctic observations of surface mass balance components. The July 2018 SUMup dataset consists of three subdatasets, snow/firn density ( https://doi.org/10.18739/A2JH3D23R ), at least near-annually resolved snow accumulation on land ice ( https://doi.org/10.18739/A2DR2P790 ), and snow depth on sea ice ( https://doi.org/10.18739/A2WS8HK6X ), to monitor change and improve estimates of surface mass balance. The measurements in this dataset were compiled from field notes, papers, technical reports, and digital files. SUMup is a compiled, community-based dataset that can be and has been used to evaluate modeling efforts and remote sensing retrievals. Active submission of new or past measurements is encouraged. Analysis of the dataset shows that Greenland Ice Sheet density measurements in the top 1 m do not show a strong relationship with annual temperature. At Summit Station, Greenland, accumulation and surface density measurements vary seasonally with lower values during summer months. The SUMup dataset is a dynamic, living dataset that will be updated and expanded for community use as new measurements are taken and new processes are discovered and quantified.

Analysis of soil hydraulic and thermal properties for land surface modeling over the Tibetan Plateau

Abstract: . Soil information (e.g., soil texture and porosity) from existing soil datasets over the Tibetan Plateau (TP) is claimed to be inadequate and even inaccurate for determining soil hydraulic properties (SHP) and soil thermal properties (STP), hampering the understanding of the land surface process over TP. As the soil varies across three dominant climate zones (i.e., arid, semi-arid and subhumid) over the TP, the associated SHP and STP are expected to vary correspondingly. To obtain an explicit insight into the soil hydrothermal properties over the TP, in situ and laboratory measurements of over 30 soil property profiles were obtained across the climate zones. Results show that porosity and SHP and STP differ across the climate zones and strongly depend on soil texture. In particular, it is proposed that gravel impact on porosity and SHP and STP are both considered in the arid zone and in deep layers of the semi-arid zone. Parameterization schemes for porosity, SHP and STP are investigated and compared with measurements taken. To determine the SHP, including soil water retention curves (SWRCs) and hydraulic conductivities, the pedotransfer functions (PTFs) developed by Cosby et al. (1984) (for the Clapp–Hornberger model) and the continuous PTFs given by Wosten et al. (1999) (for the Van Genuchten–Mualem model) are recommended. The STP parameterization scheme proposed by Farouki (1981) based on the model of De Vries (1963) performed better across the TP than other schemes. Using the parameterization schemes mentioned above, the uncertainties of five existing regional and global soil datasets and their derived SHP and STP over the TP are quantified through comparison with in situ and laboratory measurements. The measured soil physical properties dataset is available at https://data.4tu.nl/repository/uuid:c712717c-6ac0-47ff-9d58-97f88082ddc0 .

A 20-year record (1998–2017) of permafrost, active layer and meteorological conditions at a high Arctic permafrost research site (Bayelva, Spitsbergen)

Abstract: . Most permafrost is located in the Arctic, where frozen organic carbon makes it an important component of the global climate system. Despite the fact that the Arctic climate changes more rapidly than the rest of the globe, observational data density in the region is low. Permafrost thaw and carbon release to the atmosphere are a positive feedback mechanism that can exacerbate global warming. This positive feedback functions via changing land–atmosphere energy and mass exchanges. There is thus a great need to understand links between the energy balance, which can vary rapidly over hourly to annual timescales, and permafrost, which changes slowly over long time periods. This understanding thus mandates long-term observational data sets. Such a data set is available from the Bayelva site at Ny-Alesund, Svalbard, where meteorology, energy balance components and subsurface observations have been made for the last 20 years. Additional data include a high-resolution digital elevation model (DEM) that can be used together with the snow physical information for snowpack modeling and a panchromatic image. This paper presents the data set produced so far, explains instrumentation, calibration, processing and data quality control, as well as the sources for various resulting data sets. The resulting data set is unique in the Arctic and serves as a baseline for future studies. The mean permafrost temperature is −2.8 °C, with a zero-amplitude depth at 5.5 m (2009–2017). Since the data provide observations of temporally variable parameters that mitigate energy fluxes between permafrost and atmosphere, such as snow depth and soil moisture content, they are suitable for use in integrating, calibrating and testing permafrost as a component in earth system models. The presented data are available in the Supplement for this paper (time series) and through the PANGAEA and Zenodo data portals: time series ( https://doi.org/10.1594/PANGAEA.880120 , https://zenodo.org/record/1139714 ) and HRSC-AX data products ( https://doi.org/10.1594/PANGAEA.884730 , https://zenodo.org/record/1145373 ).

OCTOPUS: an open cosmogenic isotope and luminescence database

Abstract: . We present a database of cosmogenic radionuclide and luminescence measurements in fluvial sediment. With support from the Australian National Data Service (ANDS) we have built infrastructure for hosting and maintaining the data at the University of Wollongong and making this available to the research community via an Open Geospatial Consortium (OGC)-compliant web service. The cosmogenic radionuclide (CRN) part of the database consists of 10Be and 26Al measurements in modern fluvial sediment samples from across the globe, along with ancillary geospatial vector and raster layers, including sample site, basin outline, digital elevation model, gradient raster, flow-direction and flow-accumulation rasters, atmospheric pressure raster, and CRN production scaling and topographic shielding factor rasters. Sample metadata are comprehensive and include all necessary information for the recalculation of denudation rates using CAIRN, an open-source program for calculating basin-wide denudation rates from 10Be and 26Al data. Further all data have been recalculated and harmonised using the same program. The luminescence part of the database consists of thermoluminescence (TL) and optically stimulated luminescence (OSL) measurements in fluvial sediment samples from stratigraphic sections and sediment cores from across the Australian continent and includes ancillary vector and raster geospatial data. The database can be interrogated and downloaded via a custom-built web map service. More advanced interrogation and exporting to various data formats, including the ESRI Shapefile and Google Earth's KML, is also possible via the Web Feature Service (WFS) capability running on the OCTOPUS server. Use of open standards also ensures that data layers are visible to other OGC-compliant data-sharing services. OCTOPUS and its associated data curation framework provide the opportunity for researchers to reuse previously published but otherwise unusable CRN and luminescence data. This delivers the potential to harness old but valuable data that would otherwise be lost to the research community. OCTOPUS can be accessed at https://earth.uow.edu.au (last access: 28 November 2018). The individual data collections can also be accessed via the following DOIs: https://doi.org/10.4225/48/5a8367feac9b2 (CRN International), https://doi.org/10.4225/48/5a836cdfac9b5 (CRN Australia), and https://doi.org/10.4225/48/5a836db1ac9b6 (OSL & TL Australia).

Biophysics and vegetation cover change: a process-based evaluation framework for confronting land surface models with satellite observations

Abstract: . Land use and land cover change (LULCC) alter the biophysical properties of the Earth's surface. The associated changes in vegetation cover can perturb the local surface energy balance, which in turn can affect the local climate. The sign and magnitude of this change in climate depends on the specific vegetation transition, its timing and its location, as well as on the background climate. Land surface models (LSMs) can be used to simulate such land–climate interactions and study their impact in past and future climates, but their capacity to model biophysical effects accurately across the globe remain unclear due to the complexity of the phenomena. Here we present a framework to evaluate the performance of such models with respect to a dedicated dataset derived from satellite remote sensing observations. Idealized simulations from four LSMs (JULES, ORCHIDEE, JSBACH and CLM) are combined with satellite observations to analyse the changes in radiative and turbulent fluxes caused by 15 specific vegetation cover transitions across geographic, seasonal and climatic gradients. The seasonal variation in net radiation associated with land cover change is the process that models capture best, whereas LSMs perform poorly when simulating spatial and climatic gradients of variation in latent, sensible and ground heat fluxes induced by land cover transitions. We expect that this analysis will help identify model limitations and prioritize efforts in model development as well as inform where consensus between model and observations is already met, ultimately helping to improve the robustness and consistency of model simulations to better inform land-based mitigation and adaptation policies. The dataset consisting of both harmonized model simulation and remote sensing estimations is available at https://doi.org/10.5281/zenodo.1182145 .

The GEWEX Water Vapor Assessment Archive of Water Vapour Products from Satellite Observations and Reanalyses

Abstract: . The Global Energy and Water cycle Exchanges (GEWEX) Data and Assessments Panel (GDAP) initiated the GEWEX Water Vapor Assessment (G-VAP), which has the main objectives to quantify the current state of the art in water vapour products being constructed for climate applications and to support the selection process of suitable water vapour products by GDAP for its production of globally consistent water and energy cycle products. During the construction of the G-VAP data archive, freely available and mature satellite and reanalysis data records with a minimum temporal coverage of 10 years were considered. The archive contains total column water vapour (TCWV) as well as specific humidity and temperature at four pressure levels (1000, 700, 500, 300 hPa) from 22 different data records. All data records were remapped to a regular longitude–latitude grid of 2 ∘ × 2 ∘ . The archive consists of four different folders: 22 TCWV data records covering the period 2003–2008, 11 TCWV data records covering the period 1988–2008, as well as 7 specific humidity and 7 temperature data records covering the period 1988–2009. The G-VAP data archive is referenced under the following digital object identifier (doi): https://doi.org/10.5676/EUM_SAF_CM/GVAP/V001 . Within G-VAP, the characterization of water vapour products is, among other ways, achieved through intercomparisons of the considered data records, as a whole and grouped into three classes of predominant retrieval condition: clear-sky, cloudy-sky and all-sky. Associated results are shown using the 22 TCWV data records. The standard deviations among the 22 TCWV data records have been analysed and exhibit distinct maxima over central Africa and the tropical warm pool (in absolute terms) as well as over the poles and mountain regions (in relative terms). The variability in TCWV within each class can be large and prohibits conclusions about systematic differences in TCWV between the classes.

Present-day surface deformation of the Alpine region inferred from geodetic techniques

Abstract: . We provide a present-day surface-kinematics model for the Alpine region and surroundings based on a high-level data analysis of about 300 geodetic stations continuously operating over more than 12 years. This model includes a deformation model, a continuous surface-kinematic (velocity) field, and a strain field consistently assessed for the entire Alpine mountain belt. Special care is given to the use of the newest Global Navigation Satellite Systems (GNSS) processing standards to determine high-precision 3-D station coordinates. The coordinate solution refers to the reference frame IGb08, epoch 2010.0. The mean precision of the station positions at the reference epoch is ±1.1 mm in N and E and ±2.3 mm in height. The mean precision of the station velocities is ±0.2 mm a −1 in N and E and ±0.4 mm a −1 in height. The deformation model is derived from the point-wise station velocities using a geodetic least-squares collocation (LSC) approach with empirically determined covariance functions. According to our results, no significant horizontal deformation is detected in the Western Alps, while across the Southern and Eastern Alps the deformation vectors describe a progressive eastward rotation towards Pannonia. This kinematic pattern also makes evident an increasing magnitude of the deformation from 0.1 mm a −1 in the western part of Switzerland up to about 1.3 mm a −1 in the Austrian Alps. The largest shortening is observed along the southern front of the Eastern Alps (in the northern area of the Venetian-Friuli Basin) and in the northern part of the Apennine Peninsula, where rates reach 2 and 3 mm a −1 , respectively. The average accuracy of the horizontal deformation model is ±0.2 mm a −1 . Regarding the vertical kinematics, our results clearly show an ongoing average uplift rate of 1.8 mm a −1 of the entire mountain chain, with the exception of the southern part of the Western Alps, where no significant uplift (less than 0.5 mm a −1 ) is detected. The fastest uplift rates (more than 2 mm a −1 ) occur in the central area of the Western Alps, in the Swiss Alps, and in the Southern Alps in the boundary region between Switzerland, Austria, and Italy. The general uplift observed across the Alpine mountain chain decreases towards the outer regions to stable values between 0.0 and 0.5 mm a −1 and, in some cases, to subsidence like in the Liguro-Provencal and Vienna basins, where vertical rates of −0.8 and −0.3 mm a −1 are observed, respectively. In the surrounding region, three regional subsidence regimes are identified: the Rhone-Bresse Graben with −0.8 mm a −1 , the Rhine Graben with −1.3 mm a −1 , and the Venetian-Friuli Basin with −1.5 mm a −1 . The estimated uncertainty of our vertical motion model across the Alpine mountain belt is about ±0.3 mm a −1 . The strain field inferred from the deformation model shows two main contrasting strain regimes: (i) shortening across the south-eastern front of the Alps and the northern part of the Dinarides and (ii) extension in the Apennines. The pattern of the principal strain axes indicates that the compression directions are more or less perpendicular to the thrust belt fronts, reaching maximum values of 20 × 10 - 9 a −1 in the Venetian-Friuli and Po basins. Across the Alpine mountain belt, we observe a slight dilatation regime in the Western Alps, which smoothly changes to a contraction regime in western Austria and southern Germany, reaching maximum shortening values of 6 × 10 - 9 a −1 in north-eastern Austria. The numerical results of this study are available at https://doi.pangaea.de/10.1594/PANGAEA.886889 .

The Berkeley High Resolution Tropospheric NO 2 product

Abstract: . We describe upgrades to the Berkeley High Resolution (BEHR) NO2 satellite retrieval product. BEHR v3.0B builds on the NASA version 3 standard Ozone Monitoring Instrument (OMI) tropospheric NO2 product to provide a high spatial resolution product for a domain covering the continental United States and lower Canada that is consistent with daily variations in the 12 km a priori NO2 profiles. Other improvements to the BEHR v3.0 product include surface reflectance and elevation, and factors affecting the NO2 a priori profiles such as lightning and anthropogenic emissions. We describe the retrieval algorithm in detail and evaluate the impact of changes to the algorithm between v2.1C and v3.0B on the retrieved NO2 vertical column densities (VCDs). Not surprisingly, we find that, on average, the changes to the a priori NO2 profiles and the update to the new NASA slant column densities have the greatest impact on the retrieved VCDs. More significantly, we find that using daily a priori profiles results in greater average VCDs than using monthly profiles in regions and times with significant lightning activity. The BEHR product is available as four subproducts on the University of California DASH repository, using monthly a priori profiles at native OMI pixel resolution ( https://doi.org/10.6078/D1N086 ) and regridded to 0.05° × 0.05° ( https://doi.org/10.6078/D1RQ3G ) and using daily a priori profiles at native OMI ( https://doi.org/10.6078/D1WH41 ) and regridded ( https://doi.org/10.6078/D12D5X ) resolutions. The subproducts using monthly profiles are currently available from January 2005 to July 2017, and will be expanded to more recent years. The subproducts using daily profiles are currently available for years 2005–2010 and 2012–2014; 2011 and 2015 on will be added as the necessary input data are simulated for those years.

Contiguous United States wildland fire emission estimates during 2003–2015

Abstract: . Wildfires are a major source of air pollutants in the United States. Wildfire smoke can trigger severe pollution episodes with substantial impacts on public health. In addition to acute episodes, wildfires can have a marginal effect on air quality at significant distances from the source, presenting significant challenges to air regulators' efforts to meet National Ambient Air Quality Standards. Improved emission estimates are needed to quantify the contribution of wildfires to air pollution and thereby inform decision-making activities related to the control and regulation of anthropogenic air pollution sources. To address the need of air regulators and land managers for improved wildfire emission estimates, we developed the Missoula Fire Lab Emission Inventory (MFLEI), a retrospective, daily wildfire emission inventory for the contiguous United States (CONUS). MFLEI was produced using multiple datasets of fire activity and burned area, a newly developed wildland fuels map and an updated emission factor database. Daily burned area is based on a combination of Monitoring Trends in Burn Severity (MTBS) data, Moderate Resolution Imaging Spectroradiometer (MODIS) burned area and active fire detection products, incident fire perimeters, and a spatial wildfire occurrence database. The fuel type classification map is a merger of a national forest type map, produced by the USDA Forest Service (USFS) Forest Inventory and Analysis (FIA) program and the Geospatial Technology and Applications Center (GTAC), with a shrub and grassland vegetation map developed by the USFS Missoula Forestry Sciences Laboratory. Forest fuel loading is from a fuel classification developed from a large set ( > 26 000 sites) of FIA surface fuel measurements. Herbaceous fuel loading is estimated using site-specific parameters with the Normalized Difference Vegetation Index from MODIS. Shrub fuel loading is quantified by applying numerous allometric equations linking stand structure and composition to biomass and fuels, with the structure and composition data derived from geospatial data layers of the LANDFIRE project. MFLEI provides estimates of CONUS daily wildfire burned area, fuel consumption, and pollutant emissions at a 250 m × 250 m resolution for 2003–2015. A spatially aggregated emission product (10 km × 10 km, 1 day) with uncertainty estimates is included to provide a representation of emission uncertainties at a spatial scale pertinent to air quality modeling. MFLEI will be updated, with recent years, as the MTBS burned area product becomes available. The data associated with this article can be found at https://doi.org/10.2737/RDS-2017-0039 (Urbanski et al., 2017).

A high-resolution air temperature data set for the Chinese Tian Shan in 1979–2016

Abstract: . The Chinese Tian Shan (also known as the Chinese Tianshan Mountains, CTM) have a complex ecological environmental system. They not only have a large number of desert oases but also support many glaciers. The arid climate and the shortage of water resources are the important factors restricting the area's socioeconomic development. This study presents a unique high-resolution (1 km, 6-hourly) air temperature data set for the Chinese Tian Shan (41.1814–45.9945 ∘ N, 77.3484–96.9989 ∘ E) from 1979 to 2016 based on a robust elevation correction framework. The data set was validated by 24 meteorological stations at a daily scale. Compared to original ERA-Interim temperature, the Nash–Sutcliffe efficiency coefficient increased from 0.90 to 0.94 for all test sites. Approximately 24 % of the root-mean-square error was reduced from 3.75 to 2.85 ∘ C. A skill score based on the probability density function, which was used to validate the reliability of the new data set for capturing the distributions, improved from 0.86 to 0.91 for all test sites. The data set was able to capture the warming trends compared to observations at annual and seasonal scales, except for winter. We concluded that the new high-resolution data set is generally reliable for climate change investigation over the Chinese Tian Shan. However, the new data set is expected to be further validated based on more observations. This data set will be helpful for potential users to improve local climate monitoring, modeling, and environmental studies in the Chinese Tian Shan. The data set presented in this article is published in the Network Common Data Form (NetCDF) at https://doi.org/10.1594/PANGAEA.887700 . The data set includes 288 nc files and one user guidance txt file.

Estimating the thickness of unconsolidated coastal aquifers along the global coastline

Abstract: . Knowledge of aquifer thickness is crucial for setting up numerical groundwater flow models to support groundwater resource management and control. Fresh groundwater reserves in coastal aquifers are particularly under threat of salinization and depletion as a result of climate change, sea-level rise, and excessive groundwater withdrawal under urbanization. To correctly assess the possible impacts of these pressures we need better information about subsurface conditions in coastal zones. Here, we propose a method that combines available global datasets to estimate, along the global coastline, the aquifer thickness in areas formed by unconsolidated sediments. To validate our final estimation results, we collected both borehole and literature data. Additionally, we performed a numerical modelling study to evaluate the effects of varying aquifer thickness and geological complexity on simulated saltwater intrusion. The results show that our aquifer thickness estimates can indeed be used for regional-scale groundwater flow modelling but that for local assessments additional geological information should be included. The final dataset has been made publicly available ( https://doi.pangaea.de/10.1594/PANGAEA.880771 ).

A rescued dataset of sub-daily meteorological observations for Europe and the southern Mediterranean region, 1877-2012

Abstract: . Sub-daily meteorological observations are needed for input to and assessment of high-resolution reanalysis products to improve understanding of weather and climate variability. While there are millions of such weather observations that have been collected by various organisations, many are yet to be transcribed into a useable format. Under the auspices of the Uncertainties in Ensembles of Regional ReAnalyses (UERRA) project, we describe the compilation and development of a digital dataset of 8.8 million meteorological observations of essential climate variables (ECVs) rescued across the European and southern Mediterranean region. By presenting the entire chain of data preparation, from the identification of regions lacking in digitised sub-daily data and the location of original sources, through the digitisation of the observations to the quality control procedures applied, we provide a rescued dataset that is as traceable as possible for use by the research community. Data from 127 stations and of 15 climate variables in the northern African and European sectors have been prepared for the period 1877 to 2012. Quality control of the data using a two-step semi-automatic statistical approach identified 3.5 % of observations that required correction or removal, on par with previous data rescue efforts. In addition to providing a new sub-daily meteorological dataset for the research community, our experience in the development of this sub-daily dataset gives us an opportunity to share some suggestions for future data rescue projects. All versions of the dataset, from the raw digitised data to data that have been quality controlled and converted to standard units, are available on PANGAEA: https://doi.org/10.1594/PANGAEA.886511 (Ashcroft et al., 2018).

The Raam regional soil moisture monitoring network in the Netherlands

Abstract: . We have established a soil moisture profile monitoring network in the Raam region in the Netherlands. This region faces water shortages during summers and excess of water during winters and after extreme precipitation events. Water management can benefit from reliable information on the soil water availability and water storing capacity in the unsaturated zone. In situ measurements provide a direct source of information on which water managers can base their decisions. Moreover, these measurements are commonly used as a reference for the calibration and validation of soil moisture content products derived from earth observations or obtained by model simulations. Distributed over the Raam region, we have equipped 14 agricultural fields and 1 natural grass field with soil moisture and soil temperature monitoring instrumentation, consisting of Decagon 5TM sensors installed at depths of 5, 10, 20, 40 and 80 cm. In total, 12 stations are located within the Raam catchment (catchment area of 223 km2), and 5 of these stations are located within the closed sub-catchment Hooge Raam (catchment area of 41 km2). Soil-specific calibration functions that have been developed for the 5TM sensors under laboratory conditions lead to an accuracy of 0.02 m3 m−3. The first set of measurements has been retrieved for the period 5 April 2016–4 April 2017. In this paper, we describe the Raam monitoring network and instrumentation, the soil-specific calibration of the sensors, the first year of measurements, and additional measurements (soil temperature, phreatic groundwater levels and meteorological data) and information (elevation, soil physical characteristics, land cover and a geohydrological model) available for performing scientific research. The data are available at https://doi.org/10.4121/uuid:dc364e97-d44a-403f-82a7-121902deeb56 .