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opencc-zeroNov 2023View details →

Ecological forecasts for marine resource management during climate extremes

Forecasting weather has become commonplace, but as society faces novel and uncertain environmental conditions there is a critical need to forecast ecology. Forewarning of ecosystem conditions during climate extremes can support proactive decision-making, yet applications of ecological forecasts are still limited. We showcase the capacity for existing marine management tools to transition to a forecasting configuration and provide skilful ecological forecasts up to 12 months in advance. The management tools use ocean temperature anomalies to help mitigate whale entanglements and sea turtle bycatch, and we show that forecasts can forewarn of human-wildlife interactions caused by unprecedented climate extremes. We further show that regionally downscaled forecasts are not a necessity for ecological forecasting and can be less skilful than global forecasts if they have fewer ensemble members. Our results highlight capacity for ecological forecasts to be explored for regions without the infrastructure or capacity to regionally downscale, ultimately helping to improve marine resource management and climate adaptation globally.

opencc-by-4.0Mar 2024View details →

Climate variability can outweigh the influence of climate mean changes for extreme precipitation under global warming

Dataset used to analyize role of climate variability

opencc-by-4.0Nov 2024View details →

Data accompanying publication "High-Income Groups Disproportionately Contribute to Climate Extremes Worldwide."

This dataset accompanies the publication "How High-Income Groups Disproportionately Contribute to Climate Extremes Worldwide."  In our study, we combine income-based emission inequality data with an emulator-based modeling framework to thoroughly study the link between emissions of individual, wealthy emitter groups and climate extremes worldwide. Specifically, we assess individual contributions to current global temperature levels and systematically attribute changes in regional monthly heat and drought extremes across the globe. We focus on emissions of the top 10/1/0.1 wealthiest individuals globally and in the US, the EU27, India and China. The dataset contains results for 1-in-50/100/10'000 year extremes at grid-cell level and whenever imapcts are aggregated by region we refer to the regionmask AR6 regions.  The file contents are the following: <ol> <li>Attributed_GMT.csv: attributed global mean temperature levels by emitter group</li> <li>tas_frequency_hot.nc, spei_frequency_dry.nc, spi_frequency_dry.nc: attributed changes in the frequency of extreme events for extreme heat (tas), potential droughts (spei-3) and meteorological droughts (spi-3) on grid-cell level</li> <li>tas_intensity_hot.nc, spei_intensity_dry.nc, spi_intensity_dry.nc: attributed changes in the intensity of extreme events for extreme heat (tas), potential droughts (spei-3) and meteorological droughts (spi-3) on grid-cell level</li> <li>processed_extremes_frequency.csv: attributed changes in the frequency of extreme events aggregated to ar6 land regions </li> <li>processed_extremes_intensity.csv: attributed changes in the intensity of extreme events aggregated to ar6 land regions</li> </ol>

opencc-by-4.0Feb 2024View details →

GTSM-ERA5-E dataset - Data underlying the paper "Global dataset of storm surges and extreme sea levels for 1950-2024 based on the ERA5 climate reanalysis"

Extreme sea levels, generated by storm surges and high tides, have the potential to cause coastal flooding and erosion. Global datasets are instrumental for mapping of extreme sea levels and associated societal risks. Harnessing the backward extension of the ERA5 reanalysis, we present a dataset containing the statistics of water levels based on a global hydrodynamic model (GTSMv3.0) covering the period 1950-2024. This is an extension of a previously published dataset for 1979-2018 <a href="https://www.frontiersin.org/articles/10.3389/fmars.2020.00263/full" target="_blank" rel="noopener">(Muis et al. 2020)</a>. The timeseries (10-min, hourly mean and daily maxima) are available via the Climate Data Store of ECMWF at DOI: 10.24381/cds.a6d42d60. Using this extended ERA5 dataset, we calculate percentiles and estimate extreme water levels for various return periods globally. The percentiles dataset includes the 1, 5, 10, 25, 50, 75, 90, 95 and 99th percentiles. The extreme water levels include return values for 1, 2, 5, 10, 25, 50, 75 and 100 years, and they are estimated using POT-GPD method applied with a threshold of 99th percentile of the timeseries and using a 72-hour window for declustering peak events, and MLE method for fitting the GPD parameters. The parameters (shape, scale and location) are also supplied with this dataset. Validation of the underlying timeseries and the statistical values shows that there is a good agreement between observed and modelled sea levels, with the level of agreement being very similar to that of the previously published dataset.  The extended 75-year dataset allows for a more robust estimation of extremes, often resulting in smaller uncertainties than its 40-year precursor. The present dataset can be used in global assessments of flood risk, climate variability and climate changes. Global modelling of water levels and extreme value analysis are associated with a number of uncertainties and limitations, that are particularly important to consider when conducting local assessments. Please refer to the Usage Notes in the corresponding manuscript (Aleksandrova et al. 2025, paper currently under review) for an overview of limitations.

opencc-by-4.0Oct 2021View details →

Supporting data for ``Summer-Winter Contrast in the Response of Precipitation Extremes to Climate Change over Northern Hemisphere Land'"

Here we have the processed data used in the preprint ``'Summer-Winter Contrast in the Response of Precipitation Extremes to Climate Change over Northern Hemisphere Land'' The README.md file includes explanations about the data in the repository.

opencc-by-4.0Mar 2022View details →

Supplementary Material: Climate-sensitive disease outbreaks in the aftermath of extreme climatic events: a scoping review

Supplemental experimental procedures General Information Here we provide the data extraction of the studies retrieved for the scoping review "Climate-sensitive disease outbreaks in the aftermath of extreme climatic events" following PRISMA-ScR guidelines. Data were extracted for the following variables: title, first author, year of publication, country/region studied, extreme climate event, extreme climate event name (tropical cyclones are often named e.g. Typhoon Haiyan), Index used to measure climate anomaly, extreme climate event definition, text description of extreme climate event, disease, outbreak definition, time period of the study, data source, baseline/reference period, study design, statistics, outcome, outcome quantification, outbreak risk, qualitative description of extreme climate event and outbreak risk, time lag.  Outcome was defined as either disease cases or incidence.

opencc-zeroAug 2022View details →

Comparing climatic suitability and niche distances to explain populations responses to extreme climatic events

Habitat suitability calculated from Species Distribution Models (SDMs) has been used to assess population performance, but empirical studies have provided weak or inconclusive support to this approach. Novel approaches measuring population distances to niche centroid and margin in environmental space have been recently proposed to explain population performance, particularly when populations experience exceptional environmental conditions that may place them outside of the species niche. Here, we use data of co-occurring species' decay, gathered after an extreme drought event occurring in the SE of the Iberian Peninsula which highly affected rich semiarid shrubland communities, to compare the relationship between population decay (mortality and remaining green canopy) and (1) distances between populations' location and species niche margin and centroid in the environmental space, and (2) climatic suitability estimated from frequently used SDMs (here MaxEnt) considering both the extreme climatic episode and the average reference climatic period before this. We found that both SDMs-derived suitability and distances to species niche properly predict populations performance when considering the reference climatic period; but climatic suitability failed to predict performance considering the extreme climate period. In addition, while distance to niche margins accurately predict both mortality and remaining green canopy responses, centroid distances failed to explain mortality, suggesting that indexes containing information about the position to niche margin (inside or outside) are better to predict binary responses. We conclude that the location of populations in the environmental space is consistent with performance responses to extreme drought. Niche distances appear to be a more efficient approach than the use of climate suitability indices derived from more frequently used SDMs to explain population performance when dealing with environmental conditions that are located outside the species environmental niche. The use of this alternative metrics may be particularly useful when designing conservation measures to mitigate impacts of shifting environmental conditions.

opencc-zeroOct 2022View details →

Data from: Can extreme climatic events induce shifts in adaptive potential? A conceptual framework and empirical test with Anolis lizards

Multivariate adaptation to climatic shifts may be limited by trait integration that causes genetic variation to be low in the direction of selection. However, strong episodes of selection induced by extreme climatic pressures may facilitate future population-wide responses if selection reduces trait integration and increases adaptive potential (i.e., evolvability). We explain this counter-intuitive framework for extreme climatic events in which directional selection leads to increased evolvability and exemplify its use in a case study. We tested this hypothesis in two populations of the lizard Anolis scriptus that experienced hurricane-induced selection on limb traits. We surveyed populations immediately before and after the hurricane as well as the offspring of post-hurricane survivors, allowing us to estimate both selection and response to selection on key functional traits: forelimb length, hindlimb length, and toepad area. Direct selection was parallel in both islands and strong in several limb traits. Even though overall limb integration did not change after the hurricane, both populations showed a non-significant tendency toward increased evolvability after the hurricane despite the direction of selection not being aligned with the axis of most variance (i.e., body size). The population with comparably lower between-limb integration showed a less constrained response to selection. Hurricane-induced selection, not aligned with the pattern of high trait correlations, likely conflicts with selection occurring during normal ecological conditions that favor functional coordination between limb traits, and would likely need to be very strong and more persistent to elicit a greater change in trait integration and evolvability. Future tests of this hypothesis should use G-matrices in a variety of wild organisms experiencing selection due to extreme climatic events.

opencc-zeroApr 2024View details →

When resilience is not enough: 2022 extreme marine heatwave threatens climatic refugia for a habitat-forming Mediterranean octocoral

Climate change is impacting ecosystems worldwide, and the Mediterranean Sea is no exception. Extreme climatic events, such as marine heat waves (MHWs), are increasing in frequency, extent, and intensity during the last decades, which has been associated with an increase in mass mortality events for multiple species. Coralligenous assemblages, where the octocoral Paramuricea clavata lives, are strongly affected by MHWs. The Medes Islands Marine Reserve (NW Mediterranean) was considered a climate refugia for P. clavata, as their populations were showing some resilience to these changing conditions. In this study, we assessed the impacts of the MHWs that occurred between 2016 and 2022 in seven shallow populations of the octocoral P. clavata from a Mediterranean Marine Protected Area. The years that the mortality rates increased significantly were associated with the ones with strong MHWs, 2022 being the one with higher mortalities. In 2022, with 50 MHW days, the proportion of total affected colonies was almost 70%, with a proportion of the injured surface of almost 40%, reaching levels never attained in our study site since the monitoring was started. We also found spatial variability between the monitored populations. Whereas few of them showed low levels of mortality, others lost around 75% of their biomass. The significant impacts documented here raise concerns about the future of shallow P. clavata populations across the Mediterranean, suggesting that the resilience of this species may not be maintained to sustain these populations face the ongoing warming trends.

opencc-by-4.0May 2024View details →

Risk Assessment of Extreme Precipitation on to Low- and Medium-Voltage Electrical Infrastructure Under the Influence of Climate Change

Open the record for dataset details and reuse information.

opencc-by-4.0Jun 2019View details →

CESM1.2 simulation data for "Simulation of Eocene extreme warmth and high climate sensitivity through cloud feedbacks"

CESM1.2 simulation data for Early Eocene Citations: Zhu, J., Poulsen, C. J., & Tierney, J. E. (2019). Simulation of Eocene extreme warmth and high climate sensitivity through cloud feedbacks. Science Advances, 5(9), eaax1874. <a href="https://doi.org/10.1126/sciadv.aax1874">https://doi.org/10.1126/sciadv.aax1874</a> Zhu, J., Poulsen, C. J., Otto-Bliesner, B. L., Liu, Z., Brady, E. C., & Noone, D. C. (2020). Simulation of early Eocene water isotopes using an Earth system model and its implication for past climate reconstruction. Earth and Planetary Science Letters, 537, 116164. <a href="https://doi.org/10.1016/j.epsl.2020.116164" rel="nofollow">https://doi.org/10.1016/j.epsl.2020.116164</a>   <ul> <li>Data set includes climatology (12 months) sea-surface temperature (TEMP), surface temperature (TS) and surface temperature at reference height (TREFHT) from four Eocene simulations with 1×, 3×, 6× and 9× preindustrial level of CO2 (284.7 ppmv), and a preindustrial simulation.</li> <li>Climatology was calculated from averaging data over the last 100 years of each simulation.</li> <li>TS and TREFHT are on the atmosphere grid of 1.9 × 2.5° (latitude × longitude).</li> <li>TEMP is on the POP ocean grid (~1°; see here: http://www.cesm.ucar.edu/models/cesm1.2/pop2/).</li> <li>NEW on July 09, 2024: restart files for the Eocene simulations.</li> </ul> A case folder is available on GitHub: <a href="https://github.com/jiang-zhu/icesm1.2_eocene_cheyenne">https://github.com/jiang-zhu/icesm1.2_eocene_cheyenne</a>

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.