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2,322 results for “precipitations”
Tampere - Surface runoff in relation to precipitation
<p>Results of the computed runoff coefficients from two methods in Vuores neighbourhood of Tampere: 1. direct runoff measurement from a stream; 2. process-based hydraulic modelling for storms with 1-, 10- and 100-year return period with and without the NBS interventions.</p>
EMIC-driven precipitation events observed by ELFIN, using proton precipitation as a proxy for EMIC waves
<p>This dataset lists the time intervals of the precipitation events observed by ELFIN nearby proton precipitation (a proxy for EMIC waves). This dataset is analyzed in the paper "Electron Precipitation Observed by ELFIN Using Proton Precipitation as a Proxy for Electromagnetic Ion Cyclotron (EMIC) Waves", currently under review in Geophysical Research Letters.</p>
Nonlinear response of productivity to precipitation extremes in the Inner Mongolia grassland
<p>As precipitation (PPT) regimes are becoming more extreme worldwide, our understanding of how terrestrial ecosystems will respond to this aspect of climate change remains unclear. We addressed this research gap by a PPT gradient experiment that included PPT amounts simulating extremely dry and wet years in combination with a long-term (40 years) observational study in a grassland ecosystem. This study illustrates how a grassland responded to greater PPT variability and highlights the role of limiting resource shift in ecosystem responses to climate extremes. Thus, to accurately forecast future ecosystem feedbacks to climate change, we should take into account the negative asymmetric feature of ecosystem response to stronger climate variability.</p>
Retrieving accurate precipitable water vapor based on GNSS multi-antenna PPP with an ocean-based dynamic experiment
<p>GNSS-derived PWVs during a 4-day shipborne experiment are included in this repository. There are four solutions with four different processing strategies, namely PPP without constraints (Conventional), with baseline length constraint only (Bl), with common ZTD constraint only (Com), and with both baseline length and common ZTD constraints (Bl+Com). The suffix 'Smooth' in the file names represents the PWV results after backward smoothing.</p>
Precipitation and sounding data on 24 July 2014 in Naqu
<p>This dataset provides the observational precipitation and sounding data on 24 July 2014 in Naqu, China.</p> <p>Data are accessible upon request at the China Meteorological Data Network National Meteorological Science Data Center (http: //data.cma.cn)</p>
Sharing data and code supporting the article entitled "Thermodynamically enhanced precipitation extremes due to counterbalancing influences of anthropogenic greenhouse gases and aerosols"
<p>The public data repository contains the data and plotting code supporting the article entitled "Thermodynamically enhanced precipitation extremes due to counterbalancing influences of anthropogenic greenhouse gases and aerosols". The dataset includes annual maximum one-day precipitation (Rx1day), its proxy computed by a physical scaling diagnostic (scaling), and the decomposed components of the scaling (i.e., thermodynamic response, dynamic response, and their interaction). Several reanalyses (including ERA5 and JRA55) and CMIP6 simulations under several scenarios (including ALL, GHG, AER, and piControl) are applied to compute the historical Rx1day, scaling, and the associated components following a GitHub Python repository (<a href="https://github.com/oliverangelil/precip_extremes_scaling">https://github.com/oliverangelil/precip_extremes_scaling</a>). Note that the decomposed components are calculated as anomalies. </p> <p>The data results of the extreme precipitation decomposition in the NetCDF format are available in zip files “<em><strong>ERA5</strong></em>”, "<em><strong>JRA55</strong></em>", "<em><strong>ALL</strong></em>", "<em><strong>GHG</strong></em>", "<em><strong>AER</strong></em>", "<em><strong>NAT</strong></em>", and "<em><strong>piControl</strong></em>". Code for visualizations is available in the "<em><strong>Jupyter Notebooks</strong></em>" zip file.</p>
Figure S51 in Supplementary Materials for Precipitation is the main axis of tropical plant phylogenetic turnover across space and time
Figure S51. Higher resolution version of Figure 1. See Figure 1 for caption.
Figure S12 in Supplementary Materials for Precipitation is the main axis of tropical plant phylogenetic turnover across space and time
Figure S12 (lef). Numbers of taxa per alignment.
Figure S8 in Supplementary Materials for Precipitation is the main axis of tropical plant phylogenetic turnover across space and time
Figure S8 (lef). Percentages of reads on target per sample.
Figure S7 in Supplementary Materials for Precipitation is the main axis of tropical plant phylogenetic turnover across space and time
Figure S7 (lef). Fractions of filtered reads per sample.
Figure S9 in Supplementary Materials for Precipitation is the main axis of tropical plant phylogenetic turnover across space and time
Figure S9 (lef). Numbers of genes recovered with at least 75% of the target length per sample.
Figure S6 in Supplementary Materials for Precipitation is the main axis of tropical plant phylogenetic turnover across space and time
Figure S6 (lef). Fractions of duplicated reads per sample.
Figure S11 in Supplementary Materials for Precipitation is the main axis of tropical plant phylogenetic turnover across space and time
Figure S11 (lef). Numbers of nucleotide sites per alignment.
Figure S5 in Supplementary Materials for Precipitation is the main axis of tropical plant phylogenetic turnover across space and time
Figure S5. Overview of species tree inference workflow with PhyloBayes.
Figure S4 in Supplementary Materials for Precipitation is the main axis of tropical plant phylogenetic turnover across space and time
Figure S4. Overview of species tree inference workflow with RAxML.
Figure S1 in Supplementary Materials for Precipitation is the main axis of tropical plant phylogenetic turnover across space and time
Figure S1. Overview of the data cleaning and target assembly workflow.
Figure S2 in Supplementary Materials for Precipitation is the main axis of tropical plant phylogenetic turnover across space and time
Figure S2. Overview and results of the orthology assessment workflow.
Figure S35 in Supplementary Materials for Precipitation is the main axis of tropical plant phylogenetic turnover across space and time
Figure S35. Mimosoid taxon and genus richness per half degree latitude/longitude grid cell.
Figure S3 in Supplementary Materials for Precipitation is the main axis of tropical plant phylogenetic turnover across space and time
Figure S3. Overview of species tree inference workflow with ASTRAL-3.
CHclim25 - sum of precipitation (Prec)
<p>Sum of precipitation are derived from daily 1 km resolution gridded dataset from the Swiss federal agency for meteorology and climate (MeteoSwiss) using a bilinear downscaling to 25 m resolution. 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 sum of precipitation for 1981-2010 and monthly sum of precipitation 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>
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
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