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2,322 results for “precipitations”
The number of precipitation days of three adjacent stations (Tingri, Lazi, Nyalam) of the Mount Qomolangma in July since 1961
<p><strong>The number of precipitation days of three adjacent stations (Tingri, Lazi, Nyalam) of the Mount Qomolangma in July since 1961, light rain level, moderate rain level, heavy rain level and above.</strong></p>
The diurnal data of the aerosol extinction coefficient of the Mount Qomolangma lidar, as well as precipitation, low cloud cover, relative humidity of three adjacent stations (Tingri, Lazi, Nyalam) of the Mount Qomolangma
<p><strong>The diurnal data of the the vertical average aerosol extinction coefficient of 0.15-2.5 km of the Mount Qomolangma lidar, as well as precipitation, low cloud cover, relative humidity of three adjacent stations (Tingri, Lazi, Nyalam) of the Mount Qomolangma in July 2018 and July 2019.</strong></p>
Wood density and leaf size jointly predict woody plant growth rates across (but not within) species along a steep precipitation gradient
<p>1. Functional traits have been proposed to define key dimensions of plant ecological strategies, but we lack consensus on whether traits can accurately predict plant demography. Despite theoretical expectations, it has been challenging to find consistent relationships between functional traits and growth. 2. In this study, we quantified inter- and intraspecific trait variation and individual growth rates of woody plants across a steep moisture gradient that varies 10-fold in annual precipitation (350–3,700 mm) in southern Chile and used a hierarchical Bayesian model to predict growth as a function of trait values. 3. We show that large-leaved species with lower stem tissue density exhibited the fastest growth rates, and these two traits exhibited the highest proportion of interspecific variation. Predictions of growth improved considerably (R2 of the best model increased from 0.28 to 0.49) when species-level multiple traits and their interactions were considered. The inclusion of intraspecific trait variation (ITV), however, did not improve models of growth rate. 4. We found that trait-growth rate relationships were not always consistent across levels of biological organization; relationships observed at the interspecific level did not necessarily hold at the intraspecific level. We found that the relationships between wood density or leaf size and growth were consistent in direction across the precipitation gradient, and the relationships between leaf economics traits and growth were weak and site-specific. 5. Synthesis. Although using more than one functional trait considerably improved growth predictions, wood density and leaf size successfully predicted growth rates across (not within) species, which is consistent with a whole-plant carbon economy. We assert that these two traits are intimately linked and ultimately describe a continuum of plant architecture and carbon economy that covers multiple trait syndromes.</p>
Quantitative precipitation estimate (QPE) and forecast (QPF) exceedance comparison with flash flood reports
<p class="ParagraphText">Flash flooding remains a challenging prediction problem, which is exacerbated by the lack of a universally accepted definition of the phenomenon. In this article, we extend prior analysis to examine the correspondence of various combinations of quantitative precipitation estimates (QPE) and precipitation thresholds to observed occurrences of flash floods, additionally considering short-term quantitative precipitation forecasts from a convection-allowing model. Consistent with previous studies, there is large variability between QPE datasets in the frequency of "heavy" precipitation events. There is also large regional variability in the best thresholds for correspondence with reported flash floods. In general, Flash Flood Guidance (FFG) exceedances provide the best correspondence with observed flash floods, except in the interior western US where recurrence interval thresholds (for the southwestern US) and static thresholds (for the northern and central Rockies) provide better correspondence. Six-hour QPE provides better correspondence with observed flash floods than 1-h QPE in all regions except the west coast and southwestern US. Exceedances of precipitation thresholds in forecasts from the operational High-Resolution Rapid Refresh (HRRR) generally do not correspond with observed flash flood events as well as QPE datasets, but they outperform QPE datasets in some regions of complex terrain and sparse observational coverage such as the southwestern US. These results can provide context for forecasters seeking to identify potential flash flood events based on QPE or forecast-based exceedances of precipitation thresholds. </p>
Data for "Impact of Arctic stratospheric polar vortex on the Mediterranean precipitation" by Zhang et al., submitted to JC, 2023.
<p>A detailed description of variables and model setup can be found in "Description of variables and model setup.txt"</p>
Effect of changing precipitation in different periods on precipitation use efficiency in a semi-arid grassland
<p>Climate change intensifies global and regional water cycles, leading to changes in both the magnitude and timing of precipitation. Precipitation use efficiency (PUE) plays a crucial role in measuring the response of above-ground net primary productivity (ANPP) to precipitation changes. However, little is known about how changes in precipitation during different periods affect PUE. Using a manipulation precipitation experiment in a semi-arid steppe, we simulated a 60% increase and decrease in precipitation during the early (April-June), late (July-September), and entire (April-September) growing seasons across 2015-2021 to examine the effects of changes in precipitation timing on PUE. The results showed that: (1) decreased precipitation in the late growing season (DLP) and whole growing season (DWP) stimulated PUE by an average of 0.14 and 0.12 g m<sup>-2</sup> mm<sup>-1</sup> yr<sup>-1</sup>, respectively, whereas increased precipitation in the late growing season (ILP) and whole growing season (IWP) suppressed PUE by an average of 0.11 and 0.09g m<sup>-2</sup> mm<sup>-1</sup> yr<sup>-1</sup>, respectively. By contrast, neither decreased nor increased precipitation in the early growing season affected PUE; (2) the increased PUE under DLP was primarily attributed to the increase of PUE in grass (GR) and annuals and biennials (AB), whereas the elevation of PUE under DWP was mainly due to an increase of PUE in AB. By contrast, the reduction of PUE under ILP was mainly caused by a decline of PUE in GR; (3) changes in evapotranspiration and leaf dry matter content (LDMC) explained the variation of PUE in AB while changes of PUE in GR was mainly due to the alteration of soil water content and LDMC. These results suggest that precipitation during the late growing season has a crucial influence on PUE, highlighting the importance of evapotranspiration and leaf dry matter content in regulating ecosystem productivity in the semi-arid steppe.</p>
Data from: Production of low-carbon amorphous precipitated silica and hydrated magnesium carbonate from olivine
<p>A novel process is reported that produces amorphous silica and nesquehonite (MgCO<sub>3</sub>.3H<sub>2</sub>O) from the magnesium silicate mineral olivine ((Mg,Fe)<sub>2</sub>.SiO<sub>4</sub>). The amorphous silica formed is a supplementary cementitious material (SCM) for use in concrete. The formation of nesquehonite sequesters carbon and means that the overall process is carbon negative. Nesquehonite can also be used to form low-carbon construction products such as bricks, blocks, and boards. This paper reports on key process optimisation studies. The potential for amorphous precipitated silica derived from olivine to produce carbon-negative concrete is discussed.</p>
Context-dependent impact of changes in precipitation on the stability of grassland biomass
<p>Community stability plays a crucial role in ensuring the consistent provision of ecosystem services despite environmental changes, including alterations in precipitation patterns. Over the past decades, significant progress has been made in understanding the responses of the stability of grassland plant communities and underlying mechanisms, defined as the ratio of the temporal mean biomass to the standard deviation. However, a crucial knowledge gap remains regarding whether the impacts of precipitation on the stability of grassland biomass are contingent upon specific contextual factors.</p> <p>Here, we examined the stability of above- and below-ground biomass in adjacent grass- and shrub-dominated communities through a 7-year manipulation experiment involving seven precipitation levels: 20%, 40%, and 60% decreases, as well as 20%, 40%, and 60% increases in natural rainfall, in addition to ambient precipitation.</p> <p>We found that the stability of community biomass was influenced by three contextual factors including the magnitude and directionality of precipitation, above- and below-ground biomass, and the type of vegetation. In particular, higher and more intense precipitation resulted in higher stability of above-ground biomass in both grass- and shrub-dominated communities. Conversely, higher precipitation intensity led to decreased below-ground biomass stability in grass-dominated communities but increased below-ground biomass stability in shrub-dominated communities. Species stability and species asynchrony consistently played a positive role in explaining the stability of above-ground biomass in both grass- and shrub-dominated communities. However, species asynchrony negatively influenced below-ground biomass stability in grass-dominated communities without a comparable effect in shrub-dominated communities. The preeminent contribution to the total community biomass was identified in the stability of below-ground biomass, evident in both grass-dominated and shrub-dominated communities.</p> <p><em>Synthesis.</em> This study highlights that while the specific effects of changes in precipitation may vary depending on the context, the fundamental processes governing biomass stability are consistent. These findings elucidate the desert steppe ecosystems' adaptive response to precipitation variations and emphasize their pivotal role in maintaining ecosystem functions under climatic perturbations.</p>
Dataset for paper "Process Modeling of Aerosol-cloud Interaction in Summertime Precipitating Shallow Cumulus over the Western North Atlantic"
<p>This dataset contains LES model input and post-processed model output used in paper "Process Modeling of Aerosol-cloud Interaction in Summertime Precipitating Shallow Cumulus over the Western North Atlantic".</p>
Satellite Precipitation Products data performance evaluation with observed datasets
<p>Datasets used for evaluation of Satellite Precipitation Products (SPPs). We used Three open-source datasets from different sources for our evaluation of the SPPs applicability in real-time flood forecasting.</p>
Spatial partitioning of terrestrial precipitation and corresponding dataset agreement
<p>The study of the water cycle at planetary scale is crucial for our understanding of large-scale climatic processes. However, very little is known about how terrestrial precipitation is distributed across different environments. In this study, we address this gap by employing a 17-dataset ensemble to provide, for the first time, precipitation estimates over a suite of land cover types, biomes, elevation zones, and precipitation intensity classes. We estimate annual terrestrial precipitation at approximately 114,000 ± 9,400 km3, with about 70% falling over tropical, subtropical and temperate regions. Our results highlight substantial inconsistencies, mainly, over the arid and the mountainous areas. To quantify the overall discrepancies, we utilize the concept of dataset agreement and then explore the pairwise relationships among the datasets in terms of "genealogy", concurrency, and distance. The resulting uncertainty-based partitioning demonstrates how precipitation is distributed over a wide range of environments and improves our understanding on how their conditions influence observational fidelity.</p>
Datasets for the article "Evaporative controls on Antarctic precipitation: an ECHAM6 model study using innovative water tracer diagnostics"
Open the record for dataset details and reuse information.
Bias-corrected EURO-CORDEX daily temperature and precipitation dataset for Hungary
<p>These datasets contain bias-corrected regional climate model outputs for daily precipitation, near surface mean-, minimum- and maximum temperature for the historical period 1993-2005 on a regular 0.11°x0.11° lon/lat grid (between latitudes 45.6825°N and 48.6525°N, and longitudes 15.9075°E and 22.9475°E).</p> <p> </p> <p>The datasets contain daily outputs of the following high-resolution (0.11°) regional climate models from the framework of EURO-CORDEX (Jacob et al., 2014):</p> <p>-CCLM</p> <p>-HIRHAM</p> <p>-RACMO</p> <p>-RCA</p> <p>-REMO</p> <p> </p> <p>The reference dataset is HUCLIM, which covers Hungary for the period 1971-2022 (downloaded in 2023) produced by the HungaroMet Hungarian Meteorological Service.</p> <p>File format: NetCDF</p> <p>All bias-corrected data produced by the use of HUCLIM have been created following the work of Mezghani et al. (2017).</p> <p> </p> <p>References:</p> <p>Jacob, D., Petersen, J., Eggert, B., Alias, A., Christensen, O.B., Bouwer, L.M., Braun, A., Colette, A., Déqué, M., Georgievski, G., Georgopoulou, E., Gobiet, A., Menut, L., Nikulin, G., Haensler, A., Hempelmann, N., Jones, C., Keuler, K., Kovats, S., Kröner, N., Kotlarski, S., Kriegsmann, A., Martin, E., van Meijgaard, E., Moseley, C., Pfeifer, S., Preuschmann, S., Radermacher, C., Radtke, K., Rechid, D., Rounsevel, M., Samuelsson, P., Somot, S., Soussana, J.-F., Teichmann, C., Valentini, R., Vautard, R., Weber, B. and Yiou, P. (2014) EURO-CORDEX New high resolution climate change projections for European impact research. Reg. Environ. Change, 14, 563–578. <a href="https://doi.org/10.1007/s10113-013-0499-2" target="_blank" rel="noopener">https://doi.org/10.1007/s10113-013-0499-2</a></p> <p>Mezghani, A., Dobler, A., Haugen, J.E., Benestad, R.E., Parding, K.M., Piniewski, M., Kardel, I. and Kundzewicz, Z.W. (2017) CHASE-PL Climate Projection dataset over Poland – bias adjustment of EURO-CORDEX simulations. Earth Syst. Sci. Data, 9, 905–925. <a href="https://doi.org/10.5194/essd-9-905-2017" target="_blank" rel="noopener">https://doi.org/10.5194/essd-9-905-2017</a></p> <p> </p>
Relative Contributions of Field-Aligned Currents and Particle Precipitation to the Inter-Hemispheric Asymmetry at High Latitudes During 2015 St. Patrick Day Storm
<p>Data for Space Weather paper "Relative Contributions of Field-Aligned Currents and Particle Precipitation to the Inter-Hemispheric Asymmetry at High Latitudes During 2015 St. Patrick Day Storm". </p>
Model output for a storyline analysis of hurricane Irma's precipitation under various levels of climate warming
<p>Understanding how extreme weather, such as tropical cyclones, will change with future climate warming is an interesting computational challenge. Here, the hindcast approach is used to create different storylines of a particular tropical cyclone, Hurricane Irma (2017). Using the Community Atmosphere Model, we explore how Irma's precipitation would change under various levels of climate warming. Analysis is focused on a 48-hour period where the simulated hurricane tracks reasonably represent Irma's observed track. Under future scenarios of 2 K, 3 K, and 4 K global average surface temperature increase above pre-industrial levels, the mean 3-hourly rainfall rates in the simulated storms increase by 3-7%/K compared to present. This change increases in magnitude for the 95th and 99th percentile 3-hourly rates, which intensify by 10-13%/K and 17-21%/K, respectively. Over Florida, the simulated mean rainfall accumulations increase by 16-26%/K, with local maxima increasing by 18-43%/K. All percent changes increase monotonically with warming level.</p>
Dataset for "Decreased northern hemisphere precipitation from consecutive CO2 doublings is associated with significant AMOC weakening"
<div> <div>Zhang, X., Waugh, D. W., Mitevski, I., Orbe, C., & Polvani, L. M. (2024). Decreased northern hemisphere precipitation from consecutive CO2 doublings is associated with significant AMOC weakening. <em>Environmental Research: Climate</em>. <a href="https://doi.org/10.1088/2752-5295/ad929c">https://doi.org/10.1088/2752-5295/ad929c</a></div> </div> <p>We analyzed surface temperature (TS), precipitation (PR), and the Atlantic meridional overturning circulation (AMOC) streamfunction from multiple coupled climate models simulations across different abrupt CO2 forcing experiments. The original data are downloaded from the CMIP6 archive, the LongrunMIP archive (https://www.longrunmip.org/), and from a previous study by Mitevski et al. (2021, doi: 10.1029/2020GL090861). Data are post processed using Python code and are saved in NetCDF format.</p> <p>Files and variables:</p> <p>File: AMOC.zip</p> <p>Description: This folder includes NetCDF files of the Atlantic meridional overturning circulation (AMOC) streamfunction (in Sv) time series from all models. File names indicate model names.</p> <p>File: TS_PR.zip</p> <p>Description: This folder includes NetCDF files of spatially varying (in latitude and longitude) surface temperature (TS, in K) and precipitation (PR, in kg s-1 m-2) time series from all models. File names indicate model names.</p> <p>The data can be viewed using Python packages Xarray, Matplotlib, and Cartopy, as well as NCO.</p> <p>Other publicly accessible locations of the data:</p> <p>https://aims2.llnl.gov/search/cmip6/</p>
Climate characteristics and trends of extreme daily precipitation events associated with cold fronts in the metropolitan region of São Paulo, Brazil
<p>Data used in the paper "Climate characteristics and trends of extreme daily precipitation events associated with cold fronts in the metropolitan region of São Paulo, Brazil" from Theoretical and Applied Climatology</p>
Data - Quantifying dynamic linkages between precipitation, groundwater recharge, and streamflow using ensemble rainfall‐runoff analysis
<p>The data support the analysis conducted in "Quantifying Dynamic Linkages Between Precipitation, Groundwater Recharge, and Streamflow Using Ensemble Rainfall‐Runoff Analysis", accepted for publication in Water Resources Research (https://doi.org/10.1029/2024WR037821) by Huibin Gao, Qin Ju, Dawei Zhang, Zhenlong Wang, Zhenchun Hao, and James Kirchner.</p> <p> </p>
EEAR-Clim: A high density observational dataset of daily precipitation and air temperature for the Extended European Alpine Region
<p>Data, metadata and code for paper published in Earth System Science Data:</p> <p>A high density observational dataset of daily precipitation and air temperature for the Extended Alpine Region</p> <p> </p> <p><strong>Code </strong>(working copy all written in R statistical software): scripts.zip</p> <ul> <li>to read and process data in from different sources</li> <li>to perform intra and inter-stations quality control</li> <li>to perform break detection and homogenization</li> <li>to read results of quality control and homogenization</li> </ul> <p><strong>Data</strong>:</p> <ul> <li>Daily time series of air temperature (mean, minimum and maximum) and precipitation as .zip files, grouped by data provider.</li> <li>Information on column content is provided in separate files "data_readme.txt"</li> <li>about 10000 stations from Italy, France, Switzerland, Austria, Germany, Slovenia, Croatia, Bosnia-Herzegovina, Czech Republic, Slovakia and Hungary</li> <li>Meta data (code, name, longitude, latitude, elevation, measurements availability for each variable, starting date, ending date) in "metadata.zip", including a file for each data provider</li> <li>If you <strong>use the data you agree to adhere to the respective data provider's terms</strong> as listed in "License.pdf"</li> <li>The license terms especially (and additionally to any other terms of the single data providers) include: <strong>Attribution</strong> — You must give appropriate credit, provide a link to the license, and indicate if changes were made. You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use. [from <a href="https://creativecommons.org/licenses/by/4.0/">CC BY 4.0</a>] </li> </ul> <p> </p> <p><strong>Version history:</strong></p> <p>v1.0: initial upload</p> <p>v2.0: update of data policies; addition of France and Croatia time series</p>
Precipitation data in Seoul, Korea during 1778-1907
<p>Precipitation records from the 18th century were extracted from the digitization of ancient national documents. We provide improved data that removes errors and omissions from past research data</p> <ul> <li>Corrected for wrong date 1786-1-1, 1786-1-2, 1786-1-3, 1874-1-1</li> </ul>
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
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)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
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.