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185 results for “minimum temperature”
Marcell Experimental Forest daily maximum and minimum air temperature, 1961 - ongoing
This data publication contains daily maximum and minimum air temperature collected from 1961-ongoing at the Marcell Experimental Forest (MEF) in Itasca County, Minnesota, which is operated and maintained by the USDA Forest Service, Northern Research Station. The data come from three long-term meteorological monitoring stations.
Minimum temperature at El Verde Field Station, Rio Grande, Puerto Rico since 1975
Daily minimum air temperature at the El Verde Field Station since October 1992. Temperature is measured daily using a manual Min-Max thermometer placed in a wooded box in the understory. The box is mostly shaded by surrounding trees, but it is more exposed to sunlight after hurricanes defoliate the forest canopy (e.g., hurricane Maria in 2017). Measurements are available for workdays only, as a technician at the station collects measurements. The thermometer is reset after each reading. Notes: • An automatic Hobo pendant sensor complements reading (see El Verde Field Station Air temperature from automatic sensor). • Daily maximum air temperature available in a separated data set. • Data from before 1992 is available in dataset #181 (1975 -August 1992). Data-missing gaps were filled in by extrapolated data from other sources, making the subsequent manipulations less valuable for interpreting long term trends. Daily emperature has been measured at the El Verde Field Station since 1975 (see methods). Monthly averages have been calculated. Lowest average values for minimum temperature were recorded from January to April with nearly 18 Centigrades during this period of time (see chart). During these months, the lowest average minimum temperature was recorded in 1976 ranging from 20 to 22 Centigrades (see chart). Highest minimum montly average records are shown from June to October with peak in the vecinity of 20 Centigrades. The year with lowest minimum tempearture was 1995 and 2000 with the low values near 14 and 15 Centigrades, respectively. Support for this work was provided by grants BSR-8811902, DEB-9411973, DEB-9705814 , DEB-0080538, DEB-0218039 , DEB-0620910 , DEB-1239764, DEB-1546686, and DEB-1831952 from the National Science Foundation to the University of Puerto Rico as part of the Luquillo Long-Term Ecological Research Program. Additional support provided by the University of Puerto Rico and the International Institute of Tropical Forestry, USDA Forest Service
NOAA's National Climatic Data Center including minimum temperature and USFS RDA datasets
This dataset was originally established as a subset of relevant NOAA monthly average minimum air temperature data. This has been replaced with links to NOAA station websites which contain this data, please visit these links in the dataset file here. Previously, minimum air temperature at two stations in or near the LEF were compiled from the NOAA National Climate Data Center and posted here. Support for this work was provided by grants BSR-8811902, DEB-9411973, DEB-9705814 , DEB-0080538, DEB-0218039 , DEB-0620910 , DEB-1239764, DEB-1546686, and DEB-1831952 from the National Science Foundation to the University of Puerto Rico as part of the Luquillo Long-Term Ecological Research Program. Additional support provided by the University of Puerto Rico and the International Institute of Tropical Forestry, USDA Forest Service.
seNorge/TNa: daily minimum temperature over Norway
<p>seNorge_2018 is a collection of observational gridded datasets for the Norwegian mainland. This dataset contains the daily minimum temperature (TNa) fields for the 66-year time period 1957-2022. TNa is the minimum temperature without checking for consistency with TG/TM/TX. The grid spacing is 1 km. The data sources are: the Norwegian Meteorological Institute Climate Database, the Swedish Meteorological and Hydrological Institute Open Data API, the Finnish Meteorological Institute open data API and the European Climate Assessment & Dataset (www.ecad.eu). See also: https://github.com/metno/seNorge_docs/wiki/seNorge_2018</p>
Data set: Average daily minimum temperature in January and February in Corsica
<p>Raster providing the average of the daily minimum temperature in Celsius degrees over January and February in Corsica from 1995 to 2003 with a 0.016667x0.0166671 resolution in latitude and longitude.</p> <p>Construction: This raster was constructed from the freely available database (PVGIS © European Communities, 2001-2008) providing, in particular, monthly averages of the daily minimum temperature reconstructed over a grid with 1$\times$1km spatial resolution (Huld et al., 2006). These monthly averages correspond to the period 1995-2003 and were used by Abboud et al. (2019, 2020) to model Xylella fastidious dynamics in South Corsica.</p> <p>Load the raster in the R statistical software (v4.1.2):<br> library(raster)<br> ADMT=raster("average-daily-minimum-temperature_Corsica_Abboud-et-al_Forecasting.grd")<br> print(ADMT)<br> plot(ADMT)</p> <p>Summary information:<br> class : RasterLayer <br> dimensions : 108, 78, 8424 (nrow, ncol, ncell)<br> resolution : 0.016667, 0.016667 (x, y)<br> extent : 8.400708, 9.700734, 41.30018, 43.10021 (xmin, xmax, ymin, ymax)<br> crs : +proj=longlat +datum=WGS84 +no_defs <br> source : average-daily-minimum-temperature_Corsica_Abboud-et-al_Forecasting.grd <br> names : layer <br> values : -0.6748945, 6.75789 (min, max)</p> <p>References:<br> - Abboud, C., Bonnefon, O., Parent, E., and Soubeyrand, S. (2019). Dating and localizing an invasion from post-introduction data and a coupled reaction–diffusion–absorption model. Journal of Mathematical Biology 79, 765–789.<br> - Abboud, C., Parent, E., Bonnefon, O., and Soubeyrand, S. (2022). Forecasting pathogen dynamics with Bayesian model-averaging: Application to Xylella fastidiosa. Preprint.<br> - Huld, T. A., Suri, M., Dunlop, E. D., and Micale, F. (2006). Estimating average daytime and daily temperature profiles within Europe. Environmental Modelling & Software 21, 1650–1661.</p>
seNorge/TNb: daily minimum temperature over Norway
<p>seNorge_2018 is a collection of observational gridded datasets for the Norwegian mainland. This dataset contains the daily minimum temperature (TNb) fields for the 65-year time period 1957-2021. TN is the minimum temperature consistent with TM/TX (yesterday at 18 UTC / today at 18 UTC). The grid spacing is 1 km. The data sources are: the Norwegian Meteorological Institute Climate Database, the Swedish Meteorological and Hydrological Institute Open Data API, the Finnish Meteorological Institute open data API and the European Climate Assessment & Dataset (www.ecad.eu). See also: https://github.com/metno/seNorge_docs/wiki/seNorge_2018</p>
Mean monthly maximum and minimum air temperature spatial grids (1971-2000), Andrews Experimental Forest
Mean monthly maximum and minimum air temperature spatial grids (1971-2000), adjusted for the effects of solar radiation and sky view factors, Andrews Experimental Forest. Maps were created using PRISM (Parameter-elevation Regressions on Independent Slopes Model), developed by Dr. Christopher Daly at Oregon State University’s PRISM Climate Group in 2010 (prism.oregonstate.edu). Grids were exported into ASCII format from GRASS GIS software; values are in degrees C x 100. Spatial resolution is 50 meters. Two sets of temperature values are available: (1) values derived from an interpolation of point station temperature values accounting for elevation; and (2) values from (1), adjusted for effects of solar radiation exposure and sky view factors. Radiation exposure and sky view factors were calculated from a two-stream solar radiation model that accounts for elevation, slope, aspect, and shading from adjacent pixels on a 50-m digital elevation model. Temperature data were obtained from selected benchmark and reference stand climate stations within the HJ Andrews, as well as National Weather Service Cooperative (COOP) and USDA NRCS Snow Telemetry (SNOTEL) stations in the vicinity. Due to the sparseness of the station data outside the Andrews, values outside the Andrews are considered to have high uncertainty. Temperature values assume an open site with no canopy cover, so are not appropriate for describing temperatures within the forest canopy. See MS033 for radiation grids used to make the radiation adjustments.
ChinaHighTEMmin: Daily Seamless 1 km Minimum Air Temperature Dataset for China (2003–Present)
<p>ChinaHighTEM is part of a series of long-term, seamless, high-resolution, and high-quality datasets of air pollutants for China (i.e., ChinaHighAirPollutants, CHAP). It is generated from big data sources (e.g., ground-based measurements, satellite remote sensing products, atmospheric reanalysis, and model simulations) using artificial intelligence, taking into account the spatiotemporal heterogeneity of air pollution.</p> <p>Here is the big data-derived seamless (spatial coverage = 100%) daily 1 km (i.e., D1K) <strong>minimum air temperature</strong> (TEMmin) dataset for China <strong>from 2003 to the present</strong>. This dataset exhibits high quality, with a cross-validation coefficient of determination (CV-R<sup>2</sup>) of 0.98 and a root-mean-square error (RMSE) of 1.53 ℃ on a daily basis.</p> <p>If you use the ChinaHighTEMmin dataset in your scientific research, please cite the following reference (Wang et al., SD, 2024):</p> <ul> <li>Wang, M., Wei, J., Wang, X., Luan, Q., and Xu, X. <a href="https://weijing-rs.github.io/publications/Wang_et_al-SD-2024.pdf" target="_blank" rel="noopener">Reconstruction of all-sky daily air temperature datasets with high accuracy in China from 2003 to 2022</a>. <em>Scientific Data</em>, 2024, 11, 1133. https://doi.org/10.1038/s41597-024-03980-z</li> </ul> <p><strong>More CHAP datasets for different air pollutants are available at: </strong><a href="https://weijing-rs.github.io/product.html"><strong>https://weijing-rs.github.io/product.html</strong></a></p>
Data for Minimum air temperature modeling using RS data
<p>Data for Minimum air temperature modeling using RS data</p>
1 km Monthly Minimum Temperature Dataset for China from 1952 to 2019 (ChinaClim_time-series)
<p>ChinaClim_time-series is a monthly temperatures and precipitation dataset in China for the period of 1952-2019 of 1km spatial resolution, the data was generated by superimposing monthly anomaly surface and baseline climatology surface (ChinaClim_baseline) based on climatologically aided interpolation (CAI). The scale factor of the data is 0.1.</p>
Subdaily meteorological measurements of temperature, direction of the movement of the clouds, and cloud cover in the Late Maunder Minimum by Louis Morin in Paris
<p>Supplementary dataset of the publication: Pliemon, T., Foelsche, U., Rohr, C., and Pfister, C.: Subdaily meteorological measurements of temperature, direction of the movement of the clouds, and cloud cover in the Late Maunder Minimum by Louis Morin in Paris, Clim. Past, 2022</p> <p>For more details see the file.</p> <p> </p>
Minimum number of experimental data for the thermal characterization of a hot water storage tank. Videos of temperature evolution
<p>Videos that show the evolution of the instantaneous temperature profile measured and determined with the models and in the cases developed in the paper "Minimum number of experimental data for the thermal characterization of a hot water storage tank" by the same authors. Thermocline thickness evolution is also shown.</p> <p>Video 1. Evolution of the instantaneous temperature profile estimated with the 5 MEL models during the charging period. Evolution of thermocline thickness during the same period is displayed in a separate frame also for all MEL models.<br> Video 2. Evolution of the instantaneous temperature profile estimated with the 5 MDH models during the charging period. Evolution of thermocline thickness during the same period is displayed in a separate frame also for all MDH models.</p>
GPRChinaTemp1km: 1 km monthly minimum air temperature for China from January 1951 to December 2020
<p>GPRChinaTemp1km is a new high-resolution (1-km) monthly gridded air temperature dataset for China from January 1951 to December 2020. The dataset includes monthly minimum air temperature covering the main land area of China during 1951-2020, which was interpolated by the Gaussian process regression (GPR) method based on the meteorological station data. The monthly gridded temperature dataset was evaluated by the observed values of the meteorological stations from the China Meteorological Data Service Centre. The dataset is in GeoTIFF format in the WGS84 (EPSG:4326) coordinate system. The unit of the data is degree Celsius (°C).</p> <p> </p>
CHclim25 - minimum temperature (Tmin)
<p>Minimum air temperature above 2m is derived from daily 1 km resolution gridded dataset from the Swiss federal agency for meteorology and climate (MeteoSwiss) using a downscaling procedure based on local regressions with a 25 m resolution elevation model. Monthly and yearly individual and current average (1981-2010) and future average (2020-2049, 2045-2074, and 2070-2099)<strong> </strong>geoTIFF layers can be downloaded from separate zip files. </p> <p>Future layers are based on the transient daily time series of gridded climate scenarios of temperature at 0.02°D (~2.2 km) provided by the <a href="https://www.nccs.admin.ch/nccs/en/home/climate-change-and-impacts/swiss-climate-change-scenarios/ch2018---climate-scenarios-for-switzerland.html">CH2018 initiative</a>. Anomalies between monthly temperature for 1981-2010 and monthly temperature for the future period at 2.2 km were downscaled at 25 m using bilinear interpolation. Anomalies were then added to 1981-2010 average monthly variables. We calculated future climatic layers for 4 GCMs (HADGEM, ECEARTH, MPIESM, and IPSL), 3 time slices (2020-2049, 2045-2074, and 2070-2099) and 3 representative concentration pathways (RCP 2.6, 4.5 and 8.5)</p> <p>The layer files are stored in compressed GeoTIFF format with the “deflate” algorithm with option “predictor2” from the GDAL. This format has a high compression ratio but allows direct import in most GIS softwares. All the maps are projected in the Swiss coordinate system CH 1903+ LV95 (epsg:2056) with a resolution of 25x25m using the extent of the digital height model DHM25 of the Swiss office for topography (swisstopo).</p>
Kellogg Biological Station site, station NWS COOP #203504, Gull Lake Biological Station, MI, study of air temperature (mean minimum) in units of celsius 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 Kellogg Biological Station (KBS) contains air temperature (mean minimum) measurements in celsius units and were aggregated to a monthly timescale.
Kellogg Biological Station site, station NWS COOP #203504, Gull Lake Biological Station, MI, study of air temperature (mean minimum) in units of celsius on a yearly 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 Kellogg Biological Station (KBS) contains air temperature (mean minimum) measurements in celsius units and were aggregated to a yearly timescale.
California Current Ecosystem site, station Lindbergh Field Airport, San Diego, CA, study of air temperature (mean minimum) in units of celsius 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 California Current Ecosystem (CCE) contains air temperature (mean minimum) measurements in celsius units and were aggregated to a monthly timescale.
California Current Ecosystem site, station Lindbergh Field Airport, San Diego, CA, study of air temperature (mean minimum) in units of celsius on a yearly 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 California Current Ecosystem (CCE) contains air temperature (mean minimum) measurements in celsius units and were aggregated to a yearly timescale.
Konza Prairie site, station Headquarters, Meteorological Station 1, study of air temperature (mean minimum) in units of celsius 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 Konza Prairie (KNZ) contains air temperature (mean minimum) measurements in celsius units and were aggregated to a monthly timescale.
Konza Prairie site, station Headquarters, Meteorological Station 1, study of air temperature (mean minimum) in units of celsius on a yearly 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 Konza Prairie (KNZ) contains air temperature (mean minimum) measurements in celsius units and were aggregated to a yearly timescale.
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