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We developed a global dataset of downscaled future projections developed by applying a statistical method for climate model downscaling and bias correction. To develop the dataset, we applied the delta method, which comprises the sum of interpolated anomalies of each GCM to the WorldClim 1-km spatial resolution dataset. The GCMs were the 35 Coupled Model Intercomparison Project Phase 5 (CMIP5) models, for four representative concentrations pathways (RCPs). For each of these, we used the 30-year future periods named as 2030s (mean of 2020-2049), 2050s (2040-2069), 2070s (2060-2089) and 2080s (2070-2099) with three climate variables (mean monthly maximum and minimum temperatures and monthly rainfall). From these, we also derive a set of bioclimatic indices.
---- The SMAA02 TTAAii Data Designators decode as: T1 (S): Surface data T1T2 (SM): Main synoptic hour A1A2 (AA): Antarctic(The bulletin collects reports from stations: 89251 Sejong) (2: Refer to WMO No.386 - Manual on the GTS - Attachment II.5)
Products of liquid water path (LWP), rain water path (RWP) and integrated water vapor (IWV, also called precipitable water vapor (PWV)) are retrieved from microwave radiometer observations with auxiliary measurements from backscatter lidar and cloud radar. The nadir measurements were taken by the German High Altitude and Long range research aircraft (HALO) during the Next generation Advanced Remote sensing for VALidation campaign 2 (NARVAL2) in August 2016. Products are provided over tropical Atlantic east of Barbados. This experiment provides column integrated quantities as seen from satellite perspective but with higher spatially resolution (about 1 km footprint) than available from microwave satellites.
---- The IUKK01 TTAAii Data Designators decode (2) as: T1 (I): Observational data (Binary coded) - BUFR. T2 (U): Upper air. A1 (K): Radio soundings from fixed land stations (up to 100 hPa) TEMP (parts A, B). A2 (K): 180° - 90°E southern hemisphere. (2: Refer to WMO No.386 - Manual on the GTS - Attachment II.5) ---- Correspondence with the C13 common BUFR/CREX code table: (002/004) or (Vertical soundings (other than satellite) -- Upper-level temperature/humidity/wind reports from fixed-land stations (TEMP)) data type / data sub-type. ---- The bulletin collects reports from stations: 89859 Jangbogo
Global paleoclimate simulations are carried out on the basis of the so-called time slice technique. The simulations are performed with the state-of-the-art global circulation model ECHAM5 (Roeckner et al., 2003) at a spectral resolution of T106 (∼1.125°×1.125°) and 19 vertical levels. Different time slices are selected at a time interval of approx. 1000 years from each other, from 6000 years ago to pre-industrial times. For each time slice a simulation is carried out over a period of 30 years. As boundary conditions prescribed sea ice fraction and sea surface temperatures were used, which were derived from a continuous simulation with transient periods. This simulation was performed with the coupled atmosphere-ocean circulation model ECHO-G, consisting of the ECHAM4 (Roeckner et al., 1996) and the ocean model HOPE (Wolff et al., 1997), at a spectral resolution of T30 (∼3.75◦×3.75◦). Further information on simulation realization can be found in Wagner et al. (2007). Detailed information on the model set-up can be found in Russo and Cubasch (2016). Russo, E. and Cubasch, U.: Mid-to-late Holocene temperature evolution and atmospheric dynamics over Europe in regional model simulations, Clim. Past, 12, 1645-1662, https://doi.org/10.5194/cp-12-1645-2016, 2016.
---- The bulletin is coded as BUFR code form: FM 94 (BUFR, Binary universal form for the representation of meteorological data) . (Refer to WMO No.306 - Manual on Codes for the definition of WMO international codes) ---- The IOBC 40 TTAAii Data Designators decode (2) as: T1 (I): Observational data - BUFR. T2 (O): Oceanographic/limnographic A1 (B): Buoy Observations A2 (C): Area between 90°N - 05°N, 070°E - 180°E. (2: Refer to WMO No.386 - Manual on the GTS - Attachment II.5) ---- WMO No.9 - Volume C1 'Remarks' field: AUTOMATIC STATIONS (Drifting BUOYS)
This is version v1.1 of the hydrographic part of the "Baltic and North Sea Climatology (BNSC)". It turned out that the original hydrographic data product of the BNSC (BNSClim hydrographic part (Version 1.0)) was erroneous. The errors occurred by accidentally reading obsolete files in two of the intermediate steps of the production procedure. By this, the basis of observations was altered. This happened after the quality control and interpolation of the observations on standard depths, in the step where the observations are sorted into the chosen grid (this affects temperature and salinity) and in the following step, the correction of the temporal sampling error (this affects only salinity). These errors were corrected in this Version 1.1. The parameters provided are water temperature and salinity on 105 depth levels. The data product comprises the time period from 1873-2015 and is based on more than one million observational profiles, which were obtained from several different data sources in the region of the Baltic, the North Sea and adjacent areas of the North Atlantic Ocean (15°W-30°E, 47°N-66°N). Intersection of observational data from different data sources is avoided and the in situ data were objected to an elaborate automatic quality control to identify erroneous observations that would bias the data product. Additionally, a correction of the temporal sampling error was applied to minimize the impact of the temporal distribution of the observations on the created temporal mean fields. The data product consists of gridded mean fields of water temperature and salinity. The spatial resolution is 0.25° in meridional and zonal direction. The depth levels are irregularly distributed: for the depth interval from 0 to 50m the distance between the single depth levels is 5m. Below 50m, the distance increases progressively by 1m to the last depth level of 4985m. The dimensions of the data product are 180*76*105 (longitude, latitude, depth). The BNSC climatology consists, on the one hand, of time series of monthly and annual mean values of the hydrographic parameters as fields of box averages. Grid boxes that show no observations are left empty. Based on these time series, decadal monthly mean fields are created for the decades 1956-1965, 1966-1975, 1976-1985, 1986-1995, 1996-2005, 2006-2015 as another part of the data product. Again, gaps remain in observational data-void regions. The third part of the data product results from above mentioned decadal mean fields: horizontally interpolated fields by application of the method of objective analysis. Consequently, this subset does not contain gaps. Available parameters: box averages: monthly and annual mean, resp. standard deviation, number of observations decadal box averages: decadal monthly mean, resp. standard deviation, mean year, standard deviation to mean year, number of years decadal interpolated mean: interpolated monthly mean, absolute median deviation, number of bins, first guess, relative interpolation error, mean year, mean distance The products and a description of the differences between v1.0 and v1.1 are publicly available at the ICDC portal ( https://icdc.cen.uni-hamburg.de/1/daten/ocean/bnsc/)
---- The bulletin is coded as BUFR code form: FM 94 (BUFR, Binary universal form for the representation of meteorological data) . (Refer to WMO No.306 - Manual on Codes for the definition of WMO international codes) ---- The ISMK01 TTAAii Data Designators decode (2) as: T1 (I): Observational data (Binary coded) - BUFR. T2 (S): Surface/sea level. A1 (M): Main synoptic observations from fixed land stations (SMxx). A2 (K): 180° - 90°E southern hemisphere. (2: Refer to WMO No.386 - Manual on the GTS - Attachment II.5) ---- Correspondence with the C13 common BUFR/CREX code table: (000/001) or (Surface data land --Main synoptic observations from fixed-land stations (SYNOP)) data type / data sub-type. ---- The bulletin collects reports from stations: ANTARCTIC JANGBOGO STATION ---- Please review: Bulletin constraints (gmd:resourceConstraints) should reflect the GTS Category (WMO_DataLicenseCode) and GTS Priority (WMO_GTSProductCategoryCode) of the bulletin. Bulletin Originator (gmd:pointOfContact). Bulletin Distributor (gmd:distributorContact and gmd:name in all instances of gmd:MD_DigitalTransferOptions). Online distribution details for the bulletin (all instances of gmd:MD_DigitalTransferOptions). MANDATED: Insert at least one thematic keyword from the WMO_CodeList dictionary (gmd:MD_Keywords/@id="WMOCodeListKeywords")
---- The SMAA01 TTAAii Data Designators decode as: T1 (S): Surface data T1T2 (SM): Main synoptic hour A1A2 (AA): Antarctic(The bulletin collects reports from stations: 89859 Jangbogo) (2: Refer to WMO No.386 - Manual on the GTS - Attachment II.5)
A marine physical biogeochemical model simulation was performed for the year 2012 covering the North Sea and Baltic Sea. Only data for the western Baltic Sea are provided here. The model output has been validated in Neumann et al. (2018a, doi: 10.5194/os-2018-71). The work was funded by the German Federal Ministry of Transport and Digital Infrastructure (BMVI, FKZ 50EW1601, https://www.io-warnemuende.de/meramo-en.html). The simulation was performed at the North-German Supercomputing Alliance (HLRN, project id: mvk00054, zulassung.hlrn.de/kurzbeschreibungen/mvk00054.pdf). The model output data were processed and evaluated on servers provided by the project 'PROSO - Prozesse von Spurenstoffen in der Ostsee' (FKZ 03F0779A). The model simulation was forced by operational meteorological data of the German Weather Service (DWD). Atmospheric nitrogen deposition data of medium spatial resolution of 16x16 km2 were provided by the Helmholtz-Zentrum Geesthacht within the EU BONUS SHEBA Project (Karl et al., 2019, doi: 10.5194/acp-2018-1317). Information on the riverine inputs, boundary conditions, and the model itself are provided in detail in Neumann et al. (2018b, doi: 10.5194/bg-2018-364). Nitrogen from atmospheric deposition of shipping-related nitrogen, agricultural-related nitrogen, and total nitrogen has been tagged in the model simulation according to a method by Menésguen et al. (2006, 10.4319/lo.2006.51.1_part_2.0591). Therefore, all nitrogen-containing model variables exist four times in the output: once as regular variables and once per tagged nitrogen source (total, shipping-related, agricultural-related). The concentrations of all prognostic biogeochemical model variables are given in nitrogen units according to the Redfield ratio.