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476 results for “monthly precipitation”
Jornada Basin LTER/Jornada Experimental Range site, station LTER Weather Station at Jornada Basin LTER, study of nitrogen from nitrate in precipitation (volume-weighted concentration) in units of milligramsPerLiter on a monthly timescale
The EcoTrends project was established in 2004 by Dr. Debra Peters (Jornada Basin LTER, USDA-ARS Jornada Experimental Range) and Dr. Ariel Lugo (Luquillo LTER, USDA-FS Luquillo Experimental Forest) to support the collection and analysis of long-term ecological datasets. The project is a large synthesis effort focused on improving the accessibility and use of long-term data. At present, there are ~50 state and federally funded research sites that are participating and contributing to the EcoTrends project, including all 26 Long-Term Ecological Research (LTER) sites and sites funded by the USDA Agriculture Research Service (ARS), USDA Forest Service, US Department of Energy, US Geological Survey (USGS) and numerous universities. Data from the EcoTrends project are available through an exploratory web portal (http://www.ecotrends.info). This web portal enables the continuation of data compilation and accessibility by users through an interactive web application. Ongoing data compilation is updated through both manual and automatic processing as part of the LTER Provenance Aware Synthesis Tracking Architecture (PASTA). The web portal is a collaboration between the Jornada LTER and the LTER Network Office. The following dataset from Jornada Basin LTER/Jornada Experimental Range (JRN) contains nitrogen from nitrate in precipitation (volume-weighted concentration) measurements in milligramsPerLiter units and were aggregated to a monthly timescale.
Jornada Basin LTER/Jornada Experimental Range site, station LTER Weather Station at Jornada Basin LTER, study of nitrate in precipitation (volume-weighted concentration) in units of milligramsPerLiter on a monthly timescale
The EcoTrends project was established in 2004 by Dr. Debra Peters (Jornada Basin LTER, USDA-ARS Jornada Experimental Range) and Dr. Ariel Lugo (Luquillo LTER, USDA-FS Luquillo Experimental Forest) to support the collection and analysis of long-term ecological datasets. The project is a large synthesis effort focused on improving the accessibility and use of long-term data. At present, there are ~50 state and federally funded research sites that are participating and contributing to the EcoTrends project, including all 26 Long-Term Ecological Research (LTER) sites and sites funded by the USDA Agriculture Research Service (ARS), USDA Forest Service, US Department of Energy, US Geological Survey (USGS) and numerous universities. Data from the EcoTrends project are available through an exploratory web portal (http://www.ecotrends.info). This web portal enables the continuation of data compilation and accessibility by users through an interactive web application. Ongoing data compilation is updated through both manual and automatic processing as part of the LTER Provenance Aware Synthesis Tracking Architecture (PASTA). The web portal is a collaboration between the Jornada LTER and the LTER Network Office. The following dataset from Jornada Basin LTER/Jornada Experimental Range (JRN) contains nitrate in precipitation (volume-weighted concentration) measurements in milligramsPerLiter units and were aggregated to a monthly timescale.
Jornada Basin LTER/Jornada Experimental Range site, station LTER Weather Station at Jornada Basin LTER, study of phosphorus from phosphate in precipitation (volume-weighted concentration) in units of milligramsPerLiter on a monthly timescale
The EcoTrends project was established in 2004 by Dr. Debra Peters (Jornada Basin LTER, USDA-ARS Jornada Experimental Range) and Dr. Ariel Lugo (Luquillo LTER, USDA-FS Luquillo Experimental Forest) to support the collection and analysis of long-term ecological datasets. The project is a large synthesis effort focused on improving the accessibility and use of long-term data. At present, there are ~50 state and federally funded research sites that are participating and contributing to the EcoTrends project, including all 26 Long-Term Ecological Research (LTER) sites and sites funded by the USDA Agriculture Research Service (ARS), USDA Forest Service, US Department of Energy, US Geological Survey (USGS) and numerous universities. Data from the EcoTrends project are available through an exploratory web portal (http://www.ecotrends.info). This web portal enables the continuation of data compilation and accessibility by users through an interactive web application. Ongoing data compilation is updated through both manual and automatic processing as part of the LTER Provenance Aware Synthesis Tracking Architecture (PASTA). The web portal is a collaboration between the Jornada LTER and the LTER Network Office. The following dataset from Jornada Basin LTER/Jornada Experimental Range (JRN) contains phosphorus from phosphate in precipitation (volume-weighted concentration) measurements in milligramsPerLiter units and were aggregated to a monthly timescale.
Jornada Basin LTER/Jornada Experimental Range site, station LTER Weather Station at Jornada Basin LTER, study of phosphate in precipitation (volume-weighted concentration) in units of milligramsPerLiter on a monthly timescale
The EcoTrends project was established in 2004 by Dr. Debra Peters (Jornada Basin LTER, USDA-ARS Jornada Experimental Range) and Dr. Ariel Lugo (Luquillo LTER, USDA-FS Luquillo Experimental Forest) to support the collection and analysis of long-term ecological datasets. The project is a large synthesis effort focused on improving the accessibility and use of long-term data. At present, there are ~50 state and federally funded research sites that are participating and contributing to the EcoTrends project, including all 26 Long-Term Ecological Research (LTER) sites and sites funded by the USDA Agriculture Research Service (ARS), USDA Forest Service, US Department of Energy, US Geological Survey (USGS) and numerous universities. Data from the EcoTrends project are available through an exploratory web portal (http://www.ecotrends.info). This web portal enables the continuation of data compilation and accessibility by users through an interactive web application. Ongoing data compilation is updated through both manual and automatic processing as part of the LTER Provenance Aware Synthesis Tracking Architecture (PASTA). The web portal is a collaboration between the Jornada LTER and the LTER Network Office. The following dataset from Jornada Basin LTER/Jornada Experimental Range (JRN) contains phosphate in precipitation (volume-weighted concentration) measurements in milligramsPerLiter units and were aggregated to a monthly timescale.
Jornada Basin LTER/Jornada Experimental Range site, station LTER Weather Station at Jornada Basin LTER, study of sulfur from sulfate in precipitation (volume-weighted concentration) in units of milligramsPerLiter on a monthly timescale
The EcoTrends project was established in 2004 by Dr. Debra Peters (Jornada Basin LTER, USDA-ARS Jornada Experimental Range) and Dr. Ariel Lugo (Luquillo LTER, USDA-FS Luquillo Experimental Forest) to support the collection and analysis of long-term ecological datasets. The project is a large synthesis effort focused on improving the accessibility and use of long-term data. At present, there are ~50 state and federally funded research sites that are participating and contributing to the EcoTrends project, including all 26 Long-Term Ecological Research (LTER) sites and sites funded by the USDA Agriculture Research Service (ARS), USDA Forest Service, US Department of Energy, US Geological Survey (USGS) and numerous universities. Data from the EcoTrends project are available through an exploratory web portal (http://www.ecotrends.info). This web portal enables the continuation of data compilation and accessibility by users through an interactive web application. Ongoing data compilation is updated through both manual and automatic processing as part of the LTER Provenance Aware Synthesis Tracking Architecture (PASTA). The web portal is a collaboration between the Jornada LTER and the LTER Network Office. The following dataset from Jornada Basin LTER/Jornada Experimental Range (JRN) contains sulfur from sulfate in precipitation (volume-weighted concentration) measurements in milligramsPerLiter units and were aggregated to a monthly timescale.
Jornada Basin LTER/Jornada Experimental Range site, station LTER Weather Station at Jornada Basin LTER, study of sulfate in precipitation (volume-weighted concentration) in units of milligramsPerLiter on a monthly timescale
The EcoTrends project was established in 2004 by Dr. Debra Peters (Jornada Basin LTER, USDA-ARS Jornada Experimental Range) and Dr. Ariel Lugo (Luquillo LTER, USDA-FS Luquillo Experimental Forest) to support the collection and analysis of long-term ecological datasets. The project is a large synthesis effort focused on improving the accessibility and use of long-term data. At present, there are ~50 state and federally funded research sites that are participating and contributing to the EcoTrends project, including all 26 Long-Term Ecological Research (LTER) sites and sites funded by the USDA Agriculture Research Service (ARS), USDA Forest Service, US Department of Energy, US Geological Survey (USGS) and numerous universities. Data from the EcoTrends project are available through an exploratory web portal (http://www.ecotrends.info). This web portal enables the continuation of data compilation and accessibility by users through an interactive web application. Ongoing data compilation is updated through both manual and automatic processing as part of the LTER Provenance Aware Synthesis Tracking Architecture (PASTA). The web portal is a collaboration between the Jornada LTER and the LTER Network Office. The following dataset from Jornada Basin LTER/Jornada Experimental Range (JRN) contains sulfate in precipitation (volume-weighted concentration) measurements in milligramsPerLiter units and were aggregated to a monthly timescale.
Jornada Basin LTER/Jornada Experimental Range site, station LTER Weather Station at Jornada Basin LTER, study of total nitrogen in precipitation (volume-weighted concentration) in units of milligramsPerLiter on a monthly timescale
The EcoTrends project was established in 2004 by Dr. Debra Peters (Jornada Basin LTER, USDA-ARS Jornada Experimental Range) and Dr. Ariel Lugo (Luquillo LTER, USDA-FS Luquillo Experimental Forest) to support the collection and analysis of long-term ecological datasets. The project is a large synthesis effort focused on improving the accessibility and use of long-term data. At present, there are ~50 state and federally funded research sites that are participating and contributing to the EcoTrends project, including all 26 Long-Term Ecological Research (LTER) sites and sites funded by the USDA Agriculture Research Service (ARS), USDA Forest Service, US Department of Energy, US Geological Survey (USGS) and numerous universities. Data from the EcoTrends project are available through an exploratory web portal (http://www.ecotrends.info). This web portal enables the continuation of data compilation and accessibility by users through an interactive web application. Ongoing data compilation is updated through both manual and automatic processing as part of the LTER Provenance Aware Synthesis Tracking Architecture (PASTA). The web portal is a collaboration between the Jornada LTER and the LTER Network Office. The following dataset from Jornada Basin LTER/Jornada Experimental Range (JRN) contains total nitrogen in precipitation (volume-weighted concentration) measurements in milligramsPerLiter units and were aggregated to a monthly timescale.
Jornada Basin LTER/Jornada Experimental Range site, station LTER Weather Station at Jornada Basin LTER, study of total phosphorus in precipitation (volume-weighted concentration) in units of milligramsPerLiter on a monthly timescale
The EcoTrends project was established in 2004 by Dr. Debra Peters (Jornada Basin LTER, USDA-ARS Jornada Experimental Range) and Dr. Ariel Lugo (Luquillo LTER, USDA-FS Luquillo Experimental Forest) to support the collection and analysis of long-term ecological datasets. The project is a large synthesis effort focused on improving the accessibility and use of long-term data. At present, there are ~50 state and federally funded research sites that are participating and contributing to the EcoTrends project, including all 26 Long-Term Ecological Research (LTER) sites and sites funded by the USDA Agriculture Research Service (ARS), USDA Forest Service, US Department of Energy, US Geological Survey (USGS) and numerous universities. Data from the EcoTrends project are available through an exploratory web portal (http://www.ecotrends.info). This web portal enables the continuation of data compilation and accessibility by users through an interactive web application. Ongoing data compilation is updated through both manual and automatic processing as part of the LTER Provenance Aware Synthesis Tracking Architecture (PASTA). The web portal is a collaboration between the Jornada LTER and the LTER Network Office. The following dataset from Jornada Basin LTER/Jornada Experimental Range (JRN) contains total phosphorus in precipitation (volume-weighted concentration) measurements in milligramsPerLiter units and were aggregated to a monthly timescale.
Jornada Basin LTER/Jornada Experimental Range site, station NWS COOP #294426, Jornada Experimental Range, NM, study of precipitation in units of centimeter on a monthly timescale
The EcoTrends project was established in 2004 by Dr. Debra Peters (Jornada Basin LTER, USDA-ARS Jornada Experimental Range) and Dr. Ariel Lugo (Luquillo LTER, USDA-FS Luquillo Experimental Forest) to support the collection and analysis of long-term ecological datasets. The project is a large synthesis effort focused on improving the accessibility and use of long-term data. At present, there are ~50 state and federally funded research sites that are participating and contributing to the EcoTrends project, including all 26 Long-Term Ecological Research (LTER) sites and sites funded by the USDA Agriculture Research Service (ARS), USDA Forest Service, US Department of Energy, US Geological Survey (USGS) and numerous universities. Data from the EcoTrends project are available through an exploratory web portal (http://www.ecotrends.info). This web portal enables the continuation of data compilation and accessibility by users through an interactive web application. Ongoing data compilation is updated through both manual and automatic processing as part of the LTER Provenance Aware Synthesis Tracking Architecture (PASTA). The web portal is a collaboration between the Jornada LTER and the LTER Network Office. The following dataset from Jornada Basin LTER/Jornada Experimental Range (JRN) contains precipitation measurements in centimeter units and were aggregated to a monthly timescale.
Central Arizona - Phoenix Urban LTER site, station NWS COOP #021026, Buckeye AZ, study of precipitation in units of centimeter on a monthly timescale
The EcoTrends project was established in 2004 by Dr. Debra Peters (Jornada Basin LTER, USDA-ARS Jornada Experimental Range) and Dr. Ariel Lugo (Luquillo LTER, USDA-FS Luquillo Experimental Forest) to support the collection and analysis of long-term ecological datasets. The project is a large synthesis effort focused on improving the accessibility and use of long-term data. At present, there are ~50 state and federally funded research sites that are participating and contributing to the EcoTrends project, including all 26 Long-Term Ecological Research (LTER) sites and sites funded by the USDA Agriculture Research Service (ARS), USDA Forest Service, US Department of Energy, US Geological Survey (USGS) and numerous universities. Data from the EcoTrends project are available through an exploratory web portal (http://www.ecotrends.info). This web portal enables the continuation of data compilation and accessibility by users through an interactive web application. Ongoing data compilation is updated through both manual and automatic processing as part of the LTER Provenance Aware Synthesis Tracking Architecture (PASTA). The web portal is a collaboration between the Jornada LTER and the LTER Network Office. The following dataset from Central Arizona - Phoenix Urban LTER (CAP) contains precipitation measurements in centimeter units and were aggregated to a monthly timescale.
Monthly precipitation from Fort Snelling near MPLS airport: Meterologic Measurements at Cedar Creek Natural History Area
Meteorological measurements include air temperature, precipitation, wind speed and direction, soil temperature, and relative humidity. These measurements are taken on an hourly basis.
SGS-LTER Graduate Student Research: Monthly Nitrogen Mineralization Rates as Biochemical Responses of US Great Plains Grasslands to Regional and Interannual Variability in Precipitation (1999-2001)
This data package was produced by researchers working on the Shortgrass Steppe Long Term Ecological Research (SGS-LTER) Project, administered at Colorado State University. Long-term datasets and background information (proposals, reports, photographs, etc.) on the SGS-LTER project are contained in a comprehensive project collection within the Digital Collections of Colorado (http://digitool.library.colostate.edu/R/?func=collections&collection_id=3429). The data table and associated metadata document, which is generated in Ecological Metadata Language, may be available through other repositories serving the ecological research community and represent components of the larger SGS-LTER project collection. Additional information and referenced materials can be found: http://hdl.handle.net/10217/85531. Carbon (C) sequestration potential in grasslands is thought to be high due to the large soil organic carbon pools characteristic of these ecosystems. Inputs of C (aboveground net primary productivity) are highly correlated to precipitation across the Great Plains region; however, changes in C pool size at a specific site are governed by the relative input and output rates across time. Our objective was to quantify the ecosystem C response of three grassland community types (shortgrass steppe, mixed grass and tallgrass prairie) to interannual variation in precipitation. At five sites across a precipitation gradient in the Great Plains, we measured net primary production (NPP), soil respiration (SRESP), and litter decomposition rates for three consecutive years. NPP, SRESP, and litter decomposition increased from shortgrass steppe (175, 454, and 47 g C m-2 yr-1) to tallgrass prairie (408, 1221, and 348 g C m-2 yr-1 for NPP, SRESP, and litter decomposition respectively). Increased growing season precipitation between study years resulted in increased NPP, SRESP, and litter decomposition at almost all sites. However, the regional patterns of the interannual NPP, SRESP, and lit
FIGURE 2. Total monthly precipitation measured near the study sites during 1998, 1999 and 2001 in Mygalomorph spiders from southwestern Oregon, USA, with descriptions of four new species
FIGURE 2. Total monthly precipitation measured near the study sites during 1998, 1999 and 2001. Studies took place over the following time periods: 3 June–13 October 1998; 7 June–27 September 1999; 11 June–9 October 2001.
The station-based error information of monthly snow depth, precipitation and air temperature for CMIP6 models in mainland China
<p>This dataset contains the data of monthly snow depth in terms of RMSD (cm), spatial correlation (R<sub>s</sub>), temporal correlation (R<sub>t</sub>), consistency index (CI), and Hotspot score (H-score) of the 1415 weather stations (only 342 stations with longterm observations were available for R<sub>t</sub>, CI and H-score) in China used for evaluating the snow depth simulated or estimated from 31 CMIP6 models, MERRA2 reanalysis and a remote sensing snow depth dataset (Che). It also includes the data of errors and accumulated errors of monthly precipitation (mm) and air temperature (℃) from the 342 stations of all the 31 CMIP6 models, which can be used for constructing the regression models for analyzing error sources of snow depth simulations. The NA values of monthly precipitation and temperature indicate that the effects of accumulated errors were ignored for the corresponding month and station.</p>
Daily, monthly and annual data from A decade (2008-2017) of water stable-isotope composition of precipitation at Concordia Station, East Antarctica
<p><span>A ten-year record of oxygen and hydrogen isotopic composition of precipitation is here presented: from 2008 to 2017, 1483 daily precipitation samples were collected all-year round on a raised platform at Concordia Station, East Antarctica.</span></p> <p><span>The dataset is discussed in the following pubblication:</span></p> <p><span>Dreossi, G., Masiol, M., Stenni, B., Zannoni, D., Scarchilli, C., Ciardini, V., Casado, M., Landais, A., Werner, M., Cauquoin, A., Casasanta, G., Del Guasta, M., Posocco, V., and Barbante, C.: A decade (2008–2017) of water stable-isotope composition of precipitation at Concordia Station, East Antarctica, EGUsphere [preprint], https://doi.org/10.5194/egusphere-2023-2813, 2023.</span></p> <p><span>The dataset includes 3 main datasheets:</span></p> <p><span>1. DAILY data with date, daily dataset for isotopes (δ<sup>18</sup>O, δ<sup>2</sup>H, d-excess), starting and ending date and hour, temperature and RH from the AWS (aws.temp and aws.RH, respectively) and the ERA5 temperature and total precipitation (era5.t2m and era5.tp, respectively);</span></p> <p><span>2. MONTHLY data with months, monthly averages for isotopes (δ<sup>18</sup>O, δ<sup>2</sup>H, d-excess), monthly averages for isotopes weighted for AWS temperature (δ<sup>18</sup>O.aws.temp, δ<sup>2</sup>H.aws.temp, d-excess.aws.temp), monthly averages for isotopes weighted for ERA5 total precipitation (δ<sup>18</sup>O.era5.tp, δ<sup>2</sup>H.era5.tp, d-excess.era5.tp), monthly averages for air temperature and RH from the AWS (aws.temp and aws.RH, respectively) and the ERA5 temperature and total precipitation (era5.t2m and era5.tp, respectively);</span></p> <p><span>3. ANNUAL data with years, annual averages for isotopes (δ<sup>18</sup>O, δ<sup>2</sup>H, d-excess), annual averages for isotopes weighted for AWS temperature (δ<sup>18</sup>O.aws.temp, δ<sup>2</sup>H.aws.temp, d-excess.aws.temp), annual averages for isotopes weighted for ERA5 total precipitation (δ<sup>18</sup>O.era5.tp, δ<sup>2</sup>H.era5.tp, d-excess.era5.tp), annual averages for air temperature and RH from the AWS (aws.temp and aws.RH, respectively) and the ERA5 temperature and total precipitation (era5.t2m and era5.tp, respectively).</span></p>
ERA5-Land monthly: Total precipitation, monthly time series for Mauritania at 30 arc seconds (ca. 1000 meter) resolution (2019 - 2023)
<p>ERA5-Land total precipitation monthly time series for Mauritania at 30 arc seconds (ca. 1000 meter) resolution (2019 - 2023)</p> <p>Source data:<br>ERA5-Land is a reanalysis dataset providing a consistent view of the evolution of land variables over several decades at an enhanced resolution compared to ERA5. ERA5-Land has been produced by replaying the land component of the ECMWF ERA5 climate reanalysis. Reanalysis combines model data with observations from across the world into a globally complete and consistent dataset using the laws of physics. Reanalysis produces data that goes several decades back in time, providing an accurate description of the climate of the past.</p> <p>Total precipitation:<br>Accumulated liquid and frozen water, including rain and snow, that falls to the Earth's surface. It is the sum of large-scale precipitation (that precipitation which is generated by large-scale weather patterns, such as troughs and cold fronts) and convective precipitation (generated by convection which occurs when air at lower levels in the atmosphere is warmer and less dense than the air above, so it rises). Precipitation variables do not include fog, dew or the precipitation that evaporates in the atmosphere before it lands at the surface of the Earth. This variable is accumulated from the beginning of the forecast time to the end of the forecast step. The units of precipitation are depth in metres. It is the depth the water would have if it were spread evenly over the grid box. Care should be taken when comparing model variables with observations, because observations are often local to a particular point in space and time, rather than representing averages over a model grid box and model time step.</p> <p>Processing steps:<br>The original hourly ERA5-Land data has been spatially enhanced from 0.1 degree to 30 arc seconds (approx. 1000 m) spatial resolution by image fusion with CHELSA data (V1.2) (<a href="https://chelsa-climate.org/">https://chelsa-climate.org/</a>). For each day we used the corresponding monthly long-term average of CHELSA. The aim was to use the fine spatial detail of CHELSA and at the same time preserve the general regional pattern and fine temporal detail of ERA5-Land. The steps included aggregation and enhancement, specifically: <br>1. spatially aggregate CHELSA to the resolution of ERA5-Land <br>2. calculate proportion of ERA5-Land / aggregated CHELSA <br>3. interpolate proportion with a Gaussian filter to 30 arc seconds <br>4. multiply the interpolated proportions with CHELSA <br>Using proportions ensures that areas without precipitation remain areas without precipitation. Only if there was actual precipitation in a given area, precipitation was redistributed according to the spatial detail of CHELSA.</p> <p>The spatially enhanced daily ERA5-Land data has been aggregated to monthly resolution, by calculating the sum of the precipitation per pixel over each month.</p> <p>File naming:<br><code>ERA5_land_monthly_prectot_sum_30sec_YYYY_MM_01T00_00_00_int.tif</code> <br>e.g.:<code>ERA5_land_monthly_prectot_sum_30sec_2023_12_01T00_00_00_int.tif</code></p> <p>The date within the filename is year and month of aggregated timestamp.</p> <p>Pixel values:<br>mm * 10<br>Scaled to Integer, example: value 218 = 21.8 mm</p> <p>Projection + EPSG code:<br>Latitude-Longitude/WGS84 (EPSG: 4326)</p> <p>Spatial extent:<br>north: 28:18N<br>south: 14:42N<br>west: 17:05W<br>east: 4:49W</p> <p>Temporal extent:<br>January 2019 - December 2023</p> <p>Spatial resolution:<br>30 arc seconds (approx. 1000 m)</p> <p>Temporal resolution:<br>monthly</p> <p>Lineage:<br>Dataset has been processed from original Copernicus Climate Data Store (ERA5-Land) data sources. As auxiliary data CHELSA climate data has been used.</p> <p>Software used:<br>GRASS GIS 8.3.2</p> <p>Format: GeoTIFF</p> <p>Original ERA5-Land dataset license:<br><a href="https://cds.climate.copernicus.eu/api/v2/terms/static/licence-to-use-copernicus-products.pdf">https://cds.climate.copernicus.eu/api/v2/terms/static/licence-to-use-copernicus-products.pdf</a></p> <p>CHELSA climatologies (V1.2): Data used: Karger D.N., Conrad, O., Böhner, J., Kawohl, T., Kreft, H., Soria-Auza, R.W., Zimmermann, N.E, Linder, H.P., Kessler, M. (2018): Data from: Climatologies at high resolution for the earth's land surface areas. Dryad digital repository. <a href="http://dx.doi.org/doi:10.5061/dryad.kd1d4">http://dx.doi.org/doi:10.5061/dryad.kd1d4</a><br>Original peer-reviewed publication: Karger, D.N., Conrad, O., Böhner, J., Kawohl, T., Kreft, H., Soria-Auza, R.W., Zimmermann, N.E., Linder, P., Kessler, M. (2017): Climatologies at high resolution for the Earth land surface areas. Scientific Data. 4 170122. <a href="https://doi.org/10.1038/sdata.2017.122">https://doi.org/10.1038/sdata.2017.122</a></p> <p>Representation type: Grid</p> <p>Processed by:<br>mundialis GmbH & Co. KG, Germany (<a href="https://www.mundialis.de/">https://www.mundialis.de/</a>)</p> <p>Contact: <br>mundialis GmbH & Co. KG, info@mundialis.de</p> <p> </p>
Monthly precipitation series for Mediterranean countries
<p>Raw monthly precipitation series for different countries of the Mediterranean region.</p>
A cross-checked global monthly weather station database for precipitation covering the period 1901 to 2010
<p>This database entry represents a comprehensive compilation of monthly weather station records for precipitation from multiple data sources for the period 1901-2010, with an emphasis on climate normal averages for the period 1961-1990. The database corresponds to the journal publication: Castellanos-Acuña, D. and Hamann, A. 2020. A cross-checked global monthly weather station database for precipitation covering the period 1901 to 2010. Geoscience Data Journal (https://rmets.onlinelibrary.wiley.com/journal/20496060, article in press, January 2020).</p> <p>We use digital elevation models and nearby stations to search for inconsistencies in reported station locations and recorded precipitation values. We also estimated missing values in weather station time series using a linear model approach based on interpolated anomaly surfaces. The resulting station records were ranked into ten classes, according to the completeness of records, the reliability of missing value estimations and other criteria. We corrected incomplete or erroneous location and elevation information for 12% of all available station records. A total of 23% of monthly records that had missing values could be estimated with high or moderate confidence. We sub-sampled our global database of more than 80,000 stations with various spatial filters, so that only the highest quality station for a given area was retained.</p> <p>Our contribution significantly enhances global data coverage compared to individual databases currently available. Even when accepting only the stations within the top two quality ranks in our combined database, and applying the coarsest spatial filter of one station per approximately 1,600 km², the remaining station count of more than 20,000 stations exceeds the largest alternative database (without a spatial filter applied) by more than 50%.</p> <p>The database contains a "Station Statistics" file with various flags indicating station quality and completeness of records. Monthly precipitation data is provided as one large file, but also broken down into regional files with less than one million rows each. Climate normal estimates for the 1961-1990 period, useful as a baseline prior to significant anthropogenic warming, are provided in multiple files with global coverage, but with different spatial filters applied that select the highest quality stations based for a global grid at different resolutions.</p>
GPM SAPHIR on MT1 (PRPS) Climate-based Radiometer Precipitation Profiling L3 1 month 0.25 x 0.25 degree V06 (GPM_3PRPSMT1SAPHIR_CLIM) at GES DISC
The "CLIM" products differ from their "regular" counterparts (without the "CLIM" in the name) by the ancillary data they use. They are Climate-Reference products, which requires homogeneous ancillary data over the climate time series. Hence, the ECMWF-Interim (European Centre for Medium-Range Weather Forecasts, 2-3 months lag behind the regular production) reanalysis is used as ancillary data to derive surface and atmospheric conditions required by the GPROF algorithm for the "CLIM" output. The Precipitation Retrieval and Profiling Scheme (PRPS)is designed to provide a best estimate of precipitation based upon matched SAPHIR-DPR observations. This fulfils in part the essence of GPM (and its predecessor, TRMM) in which the core observatory acts as a calibrator of precipitation retrievals for the international constellation of passive microwave instruments. In doing so the retrievals from the partner constellation sensors are able to provide greater temporal sampling and great spatial coverage than is possible from the DPR instrument alone. However, the limitations of the DPR instrument are transferred through the retrieval scheme to the resulting precipitation products.Fundamental to the design of the PRPS is the independence from any dynamic ancillary data sets: the retrieval is based solely upon the satellite radiances, a static a priori radiance-rainrate database (and index), and (static) topographical data. Critically, the technique is independent of any model information, unlike the retrievals generated through the Goddard PROFiling (GPROF) scheme: this independence is advantageous when generating products across time scales from near real-time (inaccessibility to modeldata) to climatological scales (circumventing trends in model data).The algorithm is designed to generate instantaneous estimates of precipitation at a constant resolution (regardless of scan position), for all scan positions and scan lines. In addition to the actual precipitation estimate, an assessment of the error is made, and a measure of the ‘fit’ of the observations to the database provided. A quality flag is also provided, with any bad data generating a ‘missing flag’ in the retrieval.
GPM GMI (GPROF) Radiometer Precipitation Profiling L3 1 month 0.25 degree x 0.25 degree V07 (GPM_3GPROFGPMGMI) at GES DISC
Version 07 is the current version of the data set. Older versions will no longer be available and have been superseded by Version 07.3GPROF products provide global gridded monthly/daily precipitation averages from multiple satellites that can be used for climate studies. The 3GPROF products are based on retrievals from high-quality microwave sensors, which are sensitive to liquid and ice-phase precipitation hydrometeors in the atmosphere.
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Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
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DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.