postprocessed (downscaled an bias corrected) daily means of 2-meter-air-temperature, global radiation and daily amount of precipitation; based on regional climate projections; focussed on the period 1951-2100; gridded with 5 km horizontal spatial resolution; refers to Germany and hydrological catchment areas of Danube, Rhine, Elbe and Odra; was founded by KLIWAS (Impacts of climate change on Waterways and Navigation); provided by Department Climate and Environment Consultancy of Deutscher Wetterdienst
Waterbase serves as the EEA’s central database for managing and disseminating data regarding the status and quality of Europe's rivers, lakes, groundwater bodies, transitional, coastal, and marine waters. It also includes information on the quantity of Europe’s water resources and the emissions from point and diffuse sources of pollution into surface waters. Specifically, Waterbase - Biology focuses on biology data from rivers, lakes, transitional and coastal waters collected annually through the Water Information System for Europe (WISE) – State of Environment (SoE) reporting framework. The data are expected to be collected within monitoring programs defined under the Water Framework Directive (WFD) and used in the classification of the ecological status or potential of rivers, lakes, transitional and coastal water bodies. These datasets provide harmonised, quality-assured biological monitoring data reported by EEA member and cooperating countries, as Ecological Quality Ratios (EQRs) from all surface water categories (rivers, lakes, transitional and coastal waters).
SWIM Water Extent is a global surface water product at 10 m pixel spacing based on Sentinel-1/2 data. The collection contains binary layers indicating open surface water for each Sentinel-1/2 scene. Clouds and cloud shadows are removed using ukis-csmask (see: https://github.com/dlr-eoc/ukis-csmask ) and are represented as NoData. The water extent extraction is based on convolutional neural networks (CNN). For further information, please see the following publications: https://doi.org/10.1016/j.rse.2019.05.022 and https://doi.org/10.3390/rs11192330
The TROPOMI instrument onboard the Copernicus SENTINEL-5 Precursor satellite is a nadir-viewing, imaging spectrometer that provides global measurements of atmospheric properties and constituents on a daily basis. It is contributing to monitoring air quality and climate, providing critical information to services and decision makers. The instrument uses passive remote sensing techniques by measuring the top of atmosphere solar radiation reflected by and radiated from the earth and its atmosphere. The four spectrometers of TROPOMI cover the ultraviolet (UV), visible (VIS), Near Infra-Red (NIR) and Short Wavelength Infra-Red (SWIR) domains of the electromagnetic spectrum. The operational trace gas products generated at DLR on behave ESA are: Ozone (O3), Nitrogen Dioxide (NO2), Sulfur Dioxide (SO2), Formaldehyde (HCHO), Carbon Monoxide (CO) and Methane (CH4), together with clouds and aerosol properties. This product displays the Nitrogen Dioxide (NO2) near surface concentration for Germany and neighboring countries as derived from the POLYPHEMUS/DLR air quality model. Surface NO2 is mainly generated by anthropogenic sources, e.g. transport and industry. POLYPHEMUS/DLR is a state-of-the-art air quality model taking into consideration - meteorological conditions, - photochemistry, - anthropogenic and natural (biogenic) emissions, - TROPOMI NO2 observations for data assimilation. This Level 4 air quality product (surface NO2 at 15:00 UTC) is based on innovative algorithms, processors, data assimilation schemes and operational processing and dissemination chain developed in the framework of the INPULS project. The DLR project INPULS develops (a) innovative retrieval algorithms and processors for the generation of value-added products from the atmospheric Copernicus missions Sentinel-5 Precursor, Sentinel-4, and Sentinel-5, (b) cloud-based (re)processing systems, (c) improved data discovery and access technologies as well as server-side analytics for the users, and (d) data visualization services.
This dataset comprises key carbonate chemistry parameters measured and calculated in incubation experiments under different experimental conditions. pH, water temperature, and salinity were measured with a WTW multimeter (MultiLine® Multi 3630 IDS). Total alkalinity was determined by open-cell titration with an 888 Titrando (Metrohm). Saturation state of calcite and aragonite were calculated using phreeqpython, a Python wrapper of the PhreeqC engine (Vitens 2021) with pH, water temperature, total alkalinity, and major ions as major input, and phreeqc.dat as database for the thermodynamic data (Parkhurst and Appelo 2013). As the original Elbe water was supersaturated with carbon dioxide (CO2) with respect to the atmosphere, its partial pressure of CO2 (pCO2) level decreased during the incubation period with open flasks, which caused an adjustment of calcite saturation state (ΩC) for ambient air conditions. To adapt for the impact of pCO2 variations during the experiment, saturation state of calcite and aragonite was calculated assuming an equilibrium with an atmospheric pCO2 of 415 ppm (normalized ΩC and normalized aragonite sautration state ΩA). Since ion concentrations were measured for only a small number of samples, the ion concentrations of the remaining samples were reconstructed using stoichiometry based on the initial solution composition and total alkalinity. The concentrations of conservative ions (Na+, K+, Cl-, SO42-) were assumed remain constant, while ions related to carbonate precipitation (Ca2+, Mg2+) were calculated based on changes in measured alkalinity (see Figure 5 of the associated paper). Detailed analysis and calculation procedures are described in the Method section of the associated paper.
Germany is obligated to report its national emissions of greenhouse gases, annually, to the European Union and the United Nations. Over 80 % of the greenhouse-gas emissions reported by Germany occur via combustion of fossil fuels. The great majority of the emissions consist of carbon dioxide. To calculate carbon dioxide emissions, one needs both the relevant activity data and suitable emission factors, with the latter depending on the applicable fuel quality and input quantities. In light of these elements' importance for emission factors, the German inventory uses country-specific emission factors rather than international, average factors. To determine such factors, one requires a detailed knowledge of the fuel compositions involved, especially with regard to carbon content and net calorific values. The present publication provides an overview of the quality characteristics of the most important fuels used in Germany and of the CO 2 emission factors calculated on the basis of those characteristics. Since annual greenhouse-gas emissions have to be calculated back to 1990, the study also considers fuels that are no longer used today. To that end, archival data are used. Gaps in the data are closed with the help of methods for recalculation back through the base year. Veröffentlicht in Climate Change | 29/2022.
The ISAH02 TTAAii Data Designators decode as: T1 (I): Observational data (Binary coded) - BUFR T1T2 (IS): Surface/sea level T1T2A1 (ISA): Routinely scheduled observations for distribution from automatic (fixed or mobile) land stations (e.g. 0000, 0100, … or 0220, 0240, 0300, …, or 0715, 0745, ... UTC) A2 (H): 90°E - 0° tropical belt(The bulletin collects reports from stations: HKMP;) (Remarks from Volume-C: XXX)
Atmospheric CO2 concentrations present a repetitive pattern of gradual decline and rapid increase during the last climate cycles, closely related to temperature and sea level change. During the Last Glacial Maximum (LGM; 23-19 kyr BP), when sea level was ca. 120 m below present, the ocean must have stored additionally about 750 Gt carbon. There is consensus that the Southern Ocean represents a key area governing past and present CO2 change. The latter is not only of high scientific but also of socio-economic and political concern since the Southern Ocean provides the potential for an efficient sink of anthropogenic carbon. However, the sensitivity of this carbon sink to climate-change induced reorganizations in wind patterns, ocean circulation, stratification, sea ice extent and biological production remains under debate. Models were not yet able to reproduce the necessary mechanisms involved, potentially due to a lack of the dynamic representation/resolution of atmospheric and oceanic circulation as well as missing carbon cycling. Data on past Southern Ocean hydrography and productivity are mainly from the Atlantic sector, thus do not adequately document conditions in the Pacific sector. This sector is not only the largest part of the Southern Ocean, but it also represents the main drainage area of the marine-based West Antarctic Ice Sheet (WAIS). In the proposed study we aim to generate paleo-data sets with a newly established proxy method from sediment core transects across the Pacific Southern Ocean. This will enhance the baselines for the understanding and modeling of the Southern Ocean's role in carbon cyling, i.e. ocean/atmosphere CO2 exchange and carbon sequestration. It will also allow insight into the response of the WAIS to past warmer than present conditions. Paired isotope measurements (oxygen, silicon) will be made on purified diatoms and radiolarians to describe glacial/interglacial contrasts in physical and nutrient properties at surface and subsurface water depth. This will be used to test (i) the impact of yet unconsidered dust-borne micronutrient deposition on the glacial South Pacific on shifts of primary productivity, Si-uptake rates and carbon export, (ii) the 'silicic-acid leakage' hypothesis (SALH) and (iii) the formation and extent of surface water stratification. Diatom and radiolarian oxygen isotopes will provide information on the timing of surface ocean salinity anomalies resulting from WAIS melt water. Climate model simulations using a complex coupled atmosphere ocean general circulation model (AOGCM) in combination with a sophisticated ocean biogeochemical model including Si-isotopes will be used for comparison with the paleo records. The analysis will cover spatial as well as temporal variability patterns of Southern Ocean hydrography, nutrient cycling and air-sea CO2-exchange. With the help of the climate model we aim to better separate and statistically analyse the individual impacts of ocean circulation and bio
The IUSD02 TTAAii Data Designators decode as: T1 (I): Observational data (Binary coded) - BUFR T1T2 (IU): Upper air T1T2A1 (IUS): Radiosondes/pibal reports from fixed land stations (entire sounding) A2 (D): 90°E - 0° northern hemisphere(The bulletin collects reports from stations: 10113;Norderney;) (Remarks from Volume-C: high resolution 2 sec.)
The Global Ozone Monitoring Experiment-2 (GOME-2) instrument continues the long-term monitoring of atmospheric trace gas constituents started with GOME / ERS-2 and SCIAMACHY / Envisat. Currently, there are three GOME-2 instruments operating on board EUMETSAT's Meteorological Operational satellites MetOp-A, -B, and -C, launched in October 2006, September 2012, and November 2018, respectively. GOME-2 can measure a range of atmospheric trace constituents, with the emphasis on global ozone distributions. Furthermore, cloud properties and intensities of ultraviolet radiation are retrieved. These data are crucial for monitoring the atmospheric composition and the detection of pollutants. DLR generates operational GOME-2 / MetOp level 2 products in the framework of EUMETSAT's Satellite Application Facility on Atmospheric Chemistry Monitoring (AC-SAF). GOME-2 near-real-time products are available already two hours after sensing. The operational SO2 total column products are generated using the algorithm GDP (GOME Data Processor) version 4.x integrated into the UPAS (Universal Processor for UV / VIS Atmospheric Spectrometers) processor for generating level 2 trace gas and cloud products. GDP 4.x performs a DOAS fit for SO2 slant column followed by an AMF / VCD computation using a single wavelength. Corrections are applied to the slant column for equatorial offset, interference of SO2 and SO2 absorption, and SZA dependence. For more details please refer to relevant peer-review papers listed on the GOME and GOME-2 documentation pages: https://atmos.eoc.dlr.de/app/docs/
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