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76 results for “extreme temperature”
Dataset for the paper "Historical model biases in monthly high temperature anomalies indicate under-projection of future temperature extremes"
<div> <div>This repository holds data and scripts related to the revision of the paper entitled: <span>"Historical model biases in monthly high temperature anomalies indicate under-projection of future temperature extremes" </span>by Lei Duan, Lyssa M. Freese, Govindasamy Bala, and Ken Caldeira. <span>The paper is currently submitted for peer review. </span>Any questions regarding the data and paper could be sent to the corresponding author: Lei Duan (leiduan@carnegiescience.edu). </div> </div>
ARISE-SAI_1.5 : CESM2 Extreme Precipitation and Temperature Indices
<p>Assessing Responses and Impacts of Solar climate intervention on the Earth system with Stratospheric Aerosol Injection (ARISE-SAI) is a set of simulations carried out with the Community Earth System Model, version 2 with the Whole Atmosphere Community Climate Model, version 6 (CESM2(WACCM6)) that aims at simulating a plausible deployment of solar climate intervention of stratospheric aerosol injection to enable community assessment of responses of the Earth system.</p> <p>This dataset uses the first set of simulations, called ARISE-SAI-1.5, that utilized the middle-of-the-road SSP2-4.5 emission scenario, and targetted a global mean surface air temperature near 1.5°C above the pre-industrial value. ARISE-SAI-1.5 is described in Richter et al. (2022). Selected data are available at Richter & Visioni (2022a,b).</p> <p>The files contained here contain processed annual daily extremes of surface temperature (TREFHT) and total precipitation (PRECT) from the ARISE-SAI-1.5 simulations and companion SSP245 simulations. Indices are those recommended by the WCRP Expert Team on Climate Change Detection Indices, Zhang et al. 2011). Methods to calculate the indices are also described in Tye et al. (2022).</p> <p><strong>Precipitation Indices</strong></p> <p>PRCPTOT, SDII, RX1D, RX5D, R10mm, R20mm, CDD, CWD, P95TOT, P99TOT</p> <p><strong>Temperature Indices</strong></p> <p>TNN, TNX, FD, TR, TN90, TN10, TN90p, TN10p, TXX, TXN, ID, SU, TX90, TX10, TX10p, TX90p, WSDI</p> <p>Where T?10 is the number of days below an annual 10th percentile threshold and T?90 is the number of days above an annual 90th percentile threshold (i.e. around 30 days per year).</p> <p>T?10p as defined by ETCCDI is the frequency of days below the rolling 5-day average climatological day of year 10th percentile. This threshold is also used for the cold spell duration index (CSDI), or consecutive days that are cool for the season.</p> <p>T?90p as defined by ETCCDI is the frequency of days above the rolling 5-day average climatological day of year 90th percentile. This threshold is also used for the warm spell duration index (WSDI), or consecutive days that are warm for the season.</p>
Datasets for the article "The temperature and density of a solar flare kernel measured from extreme ultraviolet lines of O IV"
<p>This entry contains the following files:</p><p>20120309_030933_kernel_fe8_shift.save<br>20120309_030933_kernel_fe8_shift_fits.txt<br>20110814_055342_qs_offlimb_si10.save<br>20110814_055342_qs_offlimb_si10_fits.txt</p><p>The .save files are IDL save files that can be restored into IDL using the restore command.</p><p>The 20120309 save file contains:</p><p>swspec - An IDL structure containing a 1D spectrum of the flare kernel for the EIS short wavelength (SW) channel. The format is that returned by eis-mask-spectrum.pro.<br>lwspec - As above, but for the long-wavelength (LW) channel.<br>map185 - An IDL map structure containing the Fe VIII 185.21 image that was used to select the flare kernel.<br>mask185 - An IDL structure containing the pixel mask that is used as input to eis-mask-spectrum.pro.</p><p>The Gaussian fits to the spectra (as performed with the routine spec-gauss-eis.pro) are stored in 20120309_030933_kernel_fe8<i>s</i>hift_fits.txt. This file can be read with read_line_fits.pro in Solarsoft.</p><p>The 20110814 dataset is used to obtain an off-limb coronal spectrum for calibration purposes. The save file contains:</p><p>swspec - An IDL structure containing a 1D spectrum of the off-limb region for the EIS SW channel. The format is that returned by eis-mask-spectrum.pro.<br>lwspec - As above, but for the LW channel.<br>map - An IDL map structure containing the Si X 272 image that was used to select off-limb region.<br>mask - An IDL structure containing the pixel mask that is used as input to eis-mask-spectrum.pro.</p><p>The Gaussian fits to the spectra (as performed with the routine spec-gauss-eis.pro) are stored in 20110814_055342_qs_offlimb_si10_fits.txt. This file can be read with read_line_fits.pro in Solarsoft. </p><p> </p><p> </p><p> </p><p> </p><p> </p><p> </p><p> </p>
Future Projections of Temperature Extremes and Urban Heat Island in Paris using Deep Learning
<p>Future projections of 2-meter maximum and minimum temperature and land surface temperature in Paris, France, using Deep Learning, under four Shared Socioeconomic Pathways. ERA5 and GCM ensemble data at their original resolution are also included. The DL (Convolutional Neural Network) model architecture and trained weights are also available. The Python script to generate the boxplots of the future projections is also included.</p>
Global LAke Surface water Temperature (GLAST): Compound thermal extremes in lakes
<p>This database contains daily maximum temperature, daily minimum temperature, and daily mean temperature for 92,245 lakes globally from 1981 to 2020. These daily time series were derived from hourly simulation data.</p> <p>The database also includes annual statistics of six types of thermal extreme events calculated from the daily lake temperature time series:</p> <ul> <li>daytime hot extreme events (hot day–mild night)</li> <li>nighttime hot extreme events (mild day–hot night)</li> <li>compound hot extreme events (hot day–hot night)</li> <li>daytime cold extreme events (cold day–mild night)</li> <li>nighttime cold extreme events (mild day–cold night)</li> <li>compound cold extreme events (cold day–cold night)</li> </ul> <p> </p> <p>The annual statistics provided for these events include metrics such as frequency, intensity, duration, and total days. Additionally, annual statistics of extreme air temperature events over the lakes are included.</p> <p>Details about the hourly-scale lake temperature simulation methodology can be found in the paper <em>"Global lakes are warming slower than surface air temperature due to accelerated evaporation"</em> (Tong et al., 2023, Nature Water). Definitions and calculation methods for thermal extreme events in lakes and atmosphere are provided in <em>"Day-night compound thermal extremes in lakes"</em> (Tong et al., 2025).</p> <p>For detailed information about the contents of each data file, please refer to the accompanying <strong>readme.docx</strong> file.</p> <p>For more datasets on global aquatic environments, please visit the official website of the Global Aqua Remote Sensing (GARS) Laboratory, led by Prof. Lian Feng: <a href="https://garslab.com/?cat=1">https://garslab.com/?cat=1</a>.</p>
Dataset in support of the study "Getting the leaves right matters for estimating temperature extremes"
<p>Dataset in support of the study “Getting the leaves right matters for estimating temperature extremes"</p>
The Meltwater Pulse1A Triggered an Extreme Cooling Event: Evidence From Southern China. Meltwater Pulse Cooling Event (MCE). Winter temperature data during the last deglacial of Huguangyan Maar lake, Surface water temperature and seasonal diatom assemblage data of Huguangyan and Yunlong Lake.
<p>Here we present results of The lake averaged monthly mean surface water temperature over the period from September 2013 to August 2015 from Yunlong Tianchi Lake(YL)(25°52.2′N, 99°16.8′E, altitude: 2551 m a.s.l), southwestern China. The dataset include sediment trap main diatom percentages over the period from September 2013 to August 2015 from YL. Lake water temperature profiles at different depths (1, 3, 6, 9, 11, 13, 16 m) from November 2008 to May 2009 in Huguang Maar Lake (HML)(21°9′N, 110°17′E), Southern China. AMS radiocarbon dates of plant remains and bulk sediment samples for Huguangyan Maar Lake over the last ~17 cal ka BP. The main diatom assemblage percentages (%) from 17 to 10 cal ka BP at Huguangyan Maar Lake. Diatom-based reconstruction of winter temperature (WT) from 17 to 10 cal ka BP at Huguangyan Maar Lake.</p>
Figure 2 in Climate variability of extreme air temperature events in the Eastern Black Sea
Figure 2. Changes in the mean monthly air temperature anomalies at the surface (relative to seasonal variability) smoothed by annual (orange) and eight-year (violet) gliding averaging in the eastern part of the Black Sea (42° - 45°N, 37° - 42°E). Their linear trend is shown by black line and the accumulated sum of anomalies after removing the linear trend – by green line. Average values of anomalies for warm and cold half-year are marked by red and blue dots respectively.
Figure 1 in Climate variability of extreme air temperature events in the Eastern Black Sea
Figure 1. Changes in mean monthly air temperature at the surface (red) and their linear trend (blue) in the eastern part of the Black Sea (42° - 45°N, 37° - 42°E).
Figure 4 in Climate variability of extreme air temperature events in the Eastern Black Sea
Figure 4. The annual changes in the mean amplitude (upper part), the number (middle part) and the mean duration (bottom part) of extreme events with positive (red lines) and negative (blue lines) air temperature anomalies in the eastern part of the Black Sea (42° - 45°N, 37° - 42°E), exceeding two standard deviations, and their linear trends.
Figure 3 in Climate variability of extreme air temperature events in the Eastern Black Sea
Figure 3. The annual changes in the mean amplitude (upper part), the number (middle part) and the mean duration (bottom part) of extreme events with positive (red lines) and negative (blue lines) air temperature anomalies in the eastern part of the Black Sea (42° - 45°N, 37° - 42°E), exceeding one standard deviation, and their linear trends.
MCMC samples from an analysis reported in a paper titled "A Song of Neither Ice nor Fire: Temperature extremes had no impact on violent conflict among European societies during the 2nd millennium"
<p>These data are posterior samples from an MCMC used to estimate parameters for a Bayesian state-space time-series regression model. They are products of an analysis reported in "A Song of Neither Ice nor Fire: Temperature extremes had no impact on violent conflict among European societies during the 2nd millennium", an academic paper that has recently been submitted for peer review. We have archived the MCMC samples here in order to facilitate peer review, replication, and open science.</p> <p>The samples are stored in .RData format (matrices when loaded into an R environment) and the R code used to produce them is provided in a GitHub repo (https://github.com/wccarleton/extreme-conflict). Each .RData file contains a matrix called "samples". The columns of the matrix are each an MCMC chain for a given (column name) model parameter monitored during the MCMC simulation. See the aforementioned GitHub repo for more details.<br> <br> </p>
Photosynthetic heat tolerances and extreme leaf temperatures
<p>Photosynthetic heat tolerances (PHTs) have several potential applications including predicting which species will be most vulnerable to climate change. Given that plants exhibit unique thermoregulatory traits that influence leaf temperatures, and that leaf temperatures can be decoupled from ambient air temperatures, we hypothesized that PHTs should be correlated to extreme leaf temperature as opposed to air temperatures.<b> </b>We measured thermoregulatory traits, maximum leaf temperatures (T<sub>MO</sub>), and two metrics of PHTs (T<sub>crit</sub> and T<sub>50</sub>) for 19 plant species growing in Fairchild Tropical Botanic Garden (Coral Gables, FL, USA). Thermoregulatory traits measured at the Garden were used to parameterize a leaf energy balance model to predict maximum in situ leaf temperatures (T<sub>MIS</sub>) across the geographic distributions of 13 species. T<sub>MO</sub> and T<sub>MIS</sub> were positively correlated with T<sub>50</sub> but were not correlated with T<sub>crit</sub>. The breath of species' thermal safety margins (the difference between T<sub>50</sub> and leaf temperatures) was negatively correlated with T<sub>50</sub>. Our results provide observational and theoretical support for the hypothesis that PHTs may be adaptations to extreme leaf temperature, but refute the assumption that species with higher PHTs are less susceptible to thermal damage. We introduce a novel method for studying plant ecophysiology by incorporating biophysical and species distribution models.</p>
Context-dependent effects of relative temperature extremes on bill morphology in a songbird
<p><span>Species increasingly face environmental extremes. While responses of morphological traits to changes in average environmental conditions are well-documented, responses to environmental extremes remain poorly understood. Bird bills contribute to thermoregulation, with considerable heat loss possible through the bill surface, and with bill morphology shaped by long-term thermal conditions. We used museum specimens to investigate the relationship of bill surface area (SA) in dark-eyed juncos <i>Junco hyemalis</i> to traditional measures of climate (temperature and precipitation) and to a novel measure of short-term relative temperature extremity, which quantifies the degree to which temperature maxima or minima have diverged from the recent five-year norm. We found that bill SA exhibits different patterns of association with relative extremity depending on the overall temperature regime and on precipitation. While thermoregulatory function predicts larger bill SA at higher relative temperature extremities, we found this to be the case only when the measure of temperature extremity existed in an environmental context that opposed it: relative minimum temperature in a warm climate, or relative maximum temperature in a cool climate. When, instead, environmental context amplified the relative temperature extremity, we found a negative relationship between bill SA and relative temperature extremity. We also found that the strength of associations between bill SA and relative temperature extremity increased as precipitation increased. Our results suggest that trait responses to environmental variation may qualitatively differ depending on the overall environmental context, and that environmental change that extremifies already-extreme environments should be of particular concern. Extreme-on-extreme environmental change may produce responses that cannot be predicted from observations in less extreme contexts, which should make it a priority for research on species' responses to climate change as well as trait evolution generally.Species increasingly face environmental extremes. Morphological responses to changes in average environmental conditions are well-documented, but responses to environmental extremes remain poorly understood. We used museum specimens to investigate relationships between a thermoregulatory morphological trait, bird bill surface area (SA), and a measure of short-term relative temperature extremity (RTE), which quantifies the degree that temperature maxima or minima diverge from the five-year norm. Using a widespread, generalist species, <i>Junco hyemalis</i>, we found that SA exhibited different patterns of association with RTE depending on the overall temperature regime and on precipitation. While thermoregulatory function predicts larger SA at higher RTE, we found this only when the RTE existed in an environmental context that opposed it: atypically cold minimum temperature in a warm climate, or atypically warm maximum temperature in a cool climate. When environmental context amplified the RTE, we found a negative relationship between SA and RTE. We also found that the strength of associations between SA and RTE increased with precipitation. Our results suggest that trait responses to environmental variation may qualitatively differ depending on the overall environmental context, and that environmental change that extremifies already-extreme environments may produce responses that cannot be predicted from observations in less extreme contexts.</span></p>
Dataset for plots and results in manuscript: "Reliance on fossil fuels increases during extreme temperature events in the continental United States"
<p>These are the dataset for plots and results in the manuscript titled "Reliance on fossil fuels increases during extreme temperature events in the continental United States".</p><p>Figure 1,2,3,4,5 are the dataset used for analysis and plotting the figures in the manuscript.</p><p>Other dataset are the 34 years' air temperature and population-weighted air temperature thresholds for detecting extreme temperature events in each U.S. states. For example, Ta_threshold(1990-2023)_99th_percentiles.csv is the 99th percentiles for each U.S. states.</p><p>Any questions and further assitance or collaborations are welcome to contact through: wz2481@columbia.edu, happystillwaterzhao@gmail.com</p><p> </p><p> </p>
Example data for: Pitfalls in diagnosing temperature extremes
<p>Pre-calculated extreme frequencies for ERA5 using a 31 day running window for the 90th percentile. The accompanying code is at: https://github.com/lukasbrunner/running_window_bias</p>
Spatial variation in avian bill size is associated with temperature extremes in a major radiation of Australian passerines
<p>Morphology is integral to body temperature regulation. Recent advances in understanding of thermal physiology suggest a role of the avian bill in thermoregulation. To explore the adaptive significance of bill size for thermoregulation we characterized relationships between bill size and climate extremes. Most previous studies have focussed on climate means, ignoring extremes, and do not reflect thermoregulatory costs experienced over shorter time scales. Using 79 species (9,847 museum specimens), we explore how bill size variation is associated with temperature extremes in a large and diverse radiation of Australasian birds, Meliphagides. Overall, across the continent, bill size variation was associated with both climate extremes and means and was most strongly associated with winter temperatures; associations at the level of climate zones differed from continent-wide associations, were complex and non-linear, yet consistent with physiology and a thermoregulatory role for avian bills. We provide strong evidence that climate extremes have contributed to the evolution of bill morphology in relation to thermoregulation and demonstrate the importance of including extremes to understand fine-scale trait variation across space. Increasing frequency and intensity of climate extremes, a signature of climate change, may lead to changes in bill size, but this is yet to be tested.</p>
Data and Scripts for "Temperature Extremes and Human Health in Cyprus Investigating the Impact of Heat and Cold Waves"_Version 2
<p>This folder contains the R data and scripts required for reproducing the results of the manuscript "Temperature Extremes and Human Health in Cyprus: Investigating the Impact of Heat and Cold Waves". (Version2)</p>
Data for "Extreme Weather Variability on Hot Rocky Exoplanet 55 Cancri e Explained by Magma Temperature-Cloud Feedback"
<p>Data supporting "Extreme Weather Variability on Hot Rocky Exoplanet 55 Cancri e Explained by Magma Temperature-Cloud Feedback" by Loftus*, Luo*, Fan, & Kite (2025). </p> <p>* Note, these authors contributed equally.</p>
The effects of temperature extremes on survival in two semi-arid Australian bird communities over three decades, with predictions to 2104
<p>Aim: Organisms in arid and semi-arid regions are frequently exposed to climatic extremes and accordingly among the most vulnerable to climate change. Studies of seasonal differences in vital rates, which mediate effects of climate on viability, are rare in arid species limiting ability to project population trends. We quantified survival patterns for two bird communities as a function of expo-sure to temperature extremes in winter and summer, then project survival patterns to 2104.</p> <p>Location: semi-arid eastern Australia</p> <p>Time period: 1986-2016; 1986-2104</p> <p>Major taxa studied: Birds</p> <p>Methods: Using mark recapture time-dependent Cormack-Jolly-Seber models and data for 37 species from two 30-year ringing programs, we tested for effects on 6-monthly survival of expo-sure to temperatures >38oC and <0oC. We then predicted future survival for different emission scenarios, testing whether changes in survival associated with warming winters would be suffi-cient to offset the effects of rising summer temperatures. Results: Survival probability declined strongly with increasing exposure to days >38oC and to a lesser extent to days <0oC, with temperature extremes explaining 43% and 13% of temporal varia-tion in survival among years, respectively. Summer survival patterns were similar across avian guilds but only survival of nectarivores declined in winter. Our models predict that gains in winter survival will not offset reductions in summer survival.</p> <p>Annual survival is predicted to decline sub-stantially by the end of the century: from 0.63 in 1986 to 0.43 in 2104 under an optimistic emis-sion scenario and to 0.11 under a pessimistic scenario. Main conclusions: We highlight the significance of temperature extremes for species' persistence in arid and semi-arid regions, comprising 70% of Australia's land mass, and 40% globally. Our demography-based results are consistent with physiological-based projections evaluating avian survival in arid and semi-arid regions globally and suggest rising summer temperatures pose a risk to population persistence in these regions. </p>
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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.