Find research datasets worth reusing

opencc-zeroSep 2022View details →

Data from: Choice of prioritization method impacts recommendations for climate-informed bird conservation in the United States

Climate-informed spatial planning is urgently needed to guide initiatives aimed at both conserving biodiversity as a whole (e.g., protection of 30% of lands and waters by 2030) and recovering North American avifauna in particular. Various methods for prioritizing conservation areas exist, yet alternative methods may direct managers to different lands for protection and thus varying recommendations for meeting area-based targets. Here, we used bird species distribution models and landcover projections to systematically evaluate two widely-used methods for prioritizing areas most likely to facilitate the persistence of multiple species under climate change: (1) in situ macrorefugia, identified as areas of high predicted species retention; and (2) complementarity-based optimizations, identified using the Zonation conservation planning software. For 17 biogeographical groups in the continental United States, we compared priority areas for bird conservation derived from these two alternatives with respect to their spatial distributions and consensus (i.e., overlap), expected conservation outcomes (e.g., species and functional diversity), predicted climate change exposure, habitat characteristics, landscape configurations, and degree of formal protection. Spatial distributions of priority areas differed by biogeographical group and method, with 40.5% consensus on average across groups. Consensus was extensive within mountainous and coastal regions and limited at high latitudes (e.g., Alaska) and in flat, interior regions (e.g., grasslands). As expected, complementarity-based optimizations more efficiently represented species than retention-based in situ macrorefugia, especially for forest groups, and had greater overall biodiversity value and better habitat condition. Conversely, in situ macrorefugia encompassed higher elevations and larger contiguous patches and were expected to experience less winter-season warming. Formal protection averaged <50% across biogeographical groups, regardless of prioritization method. Our findings illustrate the value of complementarity-based optimizations for bird conservation under climate change. More broadly, comparing approaches for prioritizing areas for long-term species persistence can reveal critical tradeoffs in recommendations for climate-informed protected area planning.

opencc-by-4.0Oct 2022View details →

How well does a convection-permitting climate model represent the reverse orographic effect of extreme hourly precipitation? - Observed precipitation data

The dataset contains the rain gauge hourly rainfall series used in the paper "How well does a convection-permitting climate model represent the reverse orographic effect of extreme hourly precipitation?". Each rain gauge series is saved in one Matlab variable, organized as a structure S with five fields: S.name: the identification name of the rain gauge station S.vals_mm: series of hourly rainfall in millimeter S.time_utc: time steps series, in UTC time S.elev_m: elevation of the station, in m a.s.l. S.xy_utm: station coordinates X and Y in meter in the Reference system WGS84/UTM zone 32N

opencc-by-4.0Aug 2022View details →

Preprocessed Data for "Comparing Storm Resolving Models and Climates via Unsupervised Machine Learning"

Preprocessed Data (training and test) for 3 SRMs used in  "Comparing Storm Resolving Models and Climates via Unsupervised Machine Learning". Here we included ICON, SPCAM, and SPCAM with sea surface tem[eratures warmed by +4K. Additionally we include lat/lon information for the test data.

opencc-by-4.0Dec 2017View details →

Meteorological and Ecosystem Flux Data for: Climate Change Impacts on Net Ecosystem Productivity in a Subtropical Scrubland of Northwestern México

This dataset accompains the paper: Climate Change Impacts on Net Ecosystem Productivity in a Subtropical Scrubland of Northwestern México which is submitted for publication at the Journal of Geophysical Research - Biogeosciences  With this data set, we calibrate and validate an ecohydrological and a soil carbon model to assess climate change impacts in a subtropical scrubland located in northwest México. Model calibration and validation is performed using five continuous years of water, energy and carbon flux measurements from an eddy covariance tower and remotely-sensed vegetation indices.

opencc-zeroApr 2024View details →

Data from: Dispersal and connectivity in increasingly extreme climatic conditions

While climate change has been shown to impact several life-history traits of wild-living animal populations, little is known about its effects on dispersal and connectivity. Here, we capitalize on the highly variable flooding regime of the Okavango Delta to investigate impacts of changing environmental conditions on dispersal and connectivity of the endangered African wild dog (Lycaon pictus). Based on remote sensed flood extents observed over 20 years, we derive two extreme flood scenarios: a minimum and a maximum flood extent; representative of very dry and very wet environmental periods. These conditions are akin to those anticipated under increased climatic variability, as it is expected under climate change. Using a movement model parametrized with GPS data from dispersing individuals, we simulate 12,000 individual dispersal trajectories across the ecosystem under both scenarios and investigate patterns of connectivity. Across the entire ecosystem, surface water coverage during maximum flood extent reduces dispersal success (i.e., the propensity of individuals to disperse between adjacent subpopulations) by 12% and increases dispersal durations by 17%. Locally, however, dispersal success diminishes by as much as 78%. Depending on the flood extent, alternative dispersal corridors emerge, some of which in the immediate vicinity of human-dominated landscapes. Notably, under maximum flood extent, the number of dispersing trajectories moving into human-dominated landscapes decreases by 41% at the Okavango Delta's inflow, but increases by 126% at the Delta's distal end. This may drive the amplification of human-wildlife conflict. Whilst predicting the impacts of climate change on environmental conditions on-the-ground remains challenging, our results highlight that environmental change may have significant consequences for dispersal patterns and connectivity, and ultimately, population viability. Acknowledging and anticipating such impacts will be key to effective conservation strategies and to preserve vital dispersal corridors in light of climate change and other human-related landscape alterations.

opencc-zeroApr 2024View details →

Data from: Genetic variation in growth and leaf traits associated with local adaptation to climate in yellow birch (Betula alleghaniensis Britton)

Understanding patterns of variation in functional traits of hardwood trees is crucial for conserving and managing North American temperate forests under climate change. This study examined provenance variation of yellow birch (Betula alleghaniensis Britton) in growth, biomass allocation, leaf morphology, and stable carbon isotope composition. Trees were grown from ten seed sources originating from across Canada and the northern USA. Height and diameter were not significantly related to climate at seed origin, suggesting that variation may be better explained by site factors, such as soil pH and soil moisture. In contrast, carbon isotope composition and leaf morphological traits were significantly correlated to climate variables including temperature, precipitation, and solar radiation. Provenances from warmer, drier localities tended to have higher stable carbon isotope ratio (δ13C), greater specific leaf area, and narrower leaf width than their counterparts from cooler, wetter climates. Thus, variation in leaf morphological traits appears to be involved in adaptation of yellow birch to variation in temperature and moisture availability across the species' range. Our results suggest that there may exist potential for selection and breeding of drought resistant yellow birch genotypes to aid in reforestation under climate change.

opencc-by-4.0Apr 2024View details →

MDM data for "Wind driven ocean circulation changes can amplify future cooling of the North Atlantic warming hole" - submitted to Journal of Climate

Data files for MDM simulation used in Journal of Climate submission, "Wind driven ocean circulation changes can amplify future cooling of the North Atlantic warming hole"

opencc-zeroDec 2023View details →

Data from: The functional diversity–productivity relationship of woody plants is climatically sensitive

Plot-scale experiments show that functional diversity (FD) plays a pivotal role in maintaining ecosystem functions such as net primary productivity (NPP). However, how FD affects NPP across larger scales under varying climatic conditions is sparsely studied, yet is important for forest–atmosphere interactions and policy development. Hence, we assess the effects of functional dispersion (FDis) and community-weighted means (CWMs) of woody plant traits on NPP across China and if such effects are modulated by climatic conditions at large scale. Using comprehensive datasets on distribution, functional traits and productivity for 9120 Chinese woody plant species, we evaluated the distribution pattern and the relationships of FDis and CWM (including three orthogonal trait indicators: plant size, photosynthetic capacity and flower duration) with NPP through multiple linear regression models. Structural equation models were used to test the effects of climatic conditions on FDis/CWM–NPP relationships. We found both general FD effects, but also that the magnitude of these could be modified by climate, with CWM and FDis of plant size especially promoting NPP in warm and wet regions, respectively. Climate indirectly increased NPP through positive effects on CWM or FDis, notably via mean photosynthetic capacity. This study provides the first comprehensive evidence for FD effects on NPP under varying climates at large scale. Importantly, our results suggest a general increase in the importance of plant traits for woody vegetation NPP with rising temperatures and wetter climates. Restoration and reforestation actions need to carefully consider not just CWMs and FDis, but, as an additional path, also their interactions with climate, to predict how FD may promote ecosystem functioning under future climatic conditions.

opencc-zeroApr 2024View details →

Data from: Influences of ski-runs, meadow management and climate on the occupancy of reptiles and amphibians in a high-altitude environment of Italy

Alpine ecosystems harbour a rich and highly-specialized biodiversity which is particularly susceptible to anthropogenic disturbances such as habitat loss and fragmentation as well as to climate change. Combined with other forms of land-use conversion, construction and maintenance of ski resorts can have severe consequences on alpine biodiversity. In this study, we show how one amphibian and two reptile species, namely Rana temporaria, Zootoca vivipara and Vipera berus, respond to such impacts by means of a multi-season occupancy analysis. We found all three species both in and outside ski-runs, showing that these habitats do not necessarily preclude their occurrence. Contrarily, this is influenced more by microhabitat availability, such as ground vegetation, humid areas, and rock cover, rather than by macro-characteristics like elevation or habitat type. Moreover, we found a climatic influence on the year-to-year occupancy change of the species, with activity-months conditions being more relevant than overwintering ones. Our results demonstrate how, in the specific case of reptiles and amphibians, ski resorts do not necessarily limit species' occurrence and that a mild series of management actions might secure the species' persistence in the area.

opencc-by-4.0Dec 2023View details →

Data for climate-resilient snowpack estimation in the Western United States

Generated and preprocessed files for the resilient snowpack estimation project. All preprocessed data were originally produced by the WUS-D3 project (https://dept.atmos.ucla.edu/alexhall/downscaling-cmip6) or PRISM (https://www.prism.oregonstate.edu/).

opencc-by-4.0May 2024View details →

Changes Monitoring in Hongjiannao Lake from 1987-2023 using Google Earth Engine and Analysis of Climatic and Anthropogenic Forces (Climatic Data)

This dataset presents temporal (1987 to 2023) climatic data for the weather station near Hongjiannao Lake.

opencc-by-nc-sa-4.0May 2024View details →

Spotlight Project Data - How people of colour experience and engage with climate change in Britain

<div> <div> <div> <div> This repository contains data from a survey which was designed by Charles Ogunbode and Jeremy Kidwell to capture climate change-related experiences, perceptions, emotions, actions and policy preferences among UK people of colour. We are grateful for input on instrument design and analysis by Nick Anim, Dr Amiera Sawas and Serayna Solanki as well as from the project steering group: Zarina Ahmad (University of Manchester), Sara Jane Nii-Adjei (Christian Aid), Meena Rajput (Greenpeace), Reuben Fakoya-Brooks (REED Ecological Network/British Ecological Society) and Dr Neema Begum (University of Nottingham). Respondents included ethnic minority UK residents aged 18 years or over (N = 1,008) and the sample was gathered in March 2022 by Qualtrics Research Services. The instrument was pre-tested with a smaller number of respondents (N = 180) on 25 Feb 2022. The data is provided in plain-text tab-separated values format (.tsv) as well as in SPSS .sav file format. The latter is recommended for analysis, and there is an associated code repository (linked below) which contains R code used to load and analyse this data (using the haven() SPSS library). We have also included the original instrument used to collect survey data in qualtrics .qsf format and docx format. Please note: some data columns have been redacted and are not included in this data release. The research was funded by a Research England QR-PSF award made through the University of Birmingham. We very much hope that by making this data as widely available as possible, other colleagues may find opportunities to expand on this research. Towards that end, we have also made available (a) <a href="https://zenodo.org/records/11130504">an open-access plain language report </a>analysing this data, (b) <a href="https://github.com/climate-experiences/spotlight-report">all of the R code written to produce the analysis in our report</a> which others may freely use and appropriate and (c) an open access online textbook which introduces the R programming language to researchers who may not have existing data science expereince. <a href="https://kidwellj.github.io/hacking_religion_textbook/chapter_2.html">Chapter two of that textbook</a> makes explicit (and more basic) use of this dataset with specific examples and explanations of how to build the code. </div> </div> </div> </div>

Data from: Small but connected islands can maintain populations and genetic diversity under climate change

In response to the striking effects of environmental change, conservation strategies often include the identification of conservation areas that can effectively maintain vulnerable species. Consequently, identifying system-specific conditions that maintain the demographic and genetic viability of species of conservation concern is essential. Connectivity plays a critical role in the persistence of populations. Islands have been model systems to understand connectivity and metapopulation processes and have emerged as particularly favorable targets for conservation. While islands can be isolated from mainland disturbances, it is unknown what degree of isolation is necessary to avoid unfavorable changes but remain sufficiently connected to maintain population viability. To test this question, we explored connectivity within the Apostle Islands, an archipelago of 22 islands within Lake Superior, by comparing historical and contemporary trends in ice bridge connectivity and by simulating the effect of reduced connectivity within this system. We developed a demographically informed individual-based model to explicitly test the role of connectivity to influence the persistence and genetic diversity of American marten (Martes americana), a forest carnivore at risk across its southern range boundary. We found that genetic diversity was resilient to moderate changes in ice cover, but a complete loss of connectivity resulted in rapid genetic erosion. Despite genetic erosion, populations persisted as long as nominal connectivity occurred between islands. Our work suggests that connectivity will decline, but martens would be resilient to moderate changes, and, in the short term, the Apostle Islands can act as a refuge along this species' southern range boundary. Identifying thresholds in connectivity that maintain populations but allow for isolation from disturbance will be necessary to identify suitable areas for species conservation across space and time.

Data from: Vrba was right: Historical climatic fragmentation, and not current climate, explains mammal biogeography

Climate plays a crucial role in shaping species distribution and evolution over time. Dr. Elisabeth Vrba's Resource-Use hypothesis posited that zones at the extremes of temperature and precipitation conditions should host a greater number of climate specialist species than other zones because of higher historical fragmentation. Here, we tested this hypothesis by examining climate-induced fragmentation over the past 5 million years. Our findings revealed that, as stated by Vrba, the number of climate specialist species increases with historical regional climate fragmentation, whereas climate generalist species richness decreases. This relationship is approximately 40% stronger than the correlation between current climate and species richness for climate specialist species and 77% stronger for generalist species. These evidences suggest that the effect of climate historical fragmentation is more significant than that of current climate conditions in explaining mammal biogeography. These results provide empirical support for the role of historical climate fragmentation and physiography in shaping the distribution and evolution of life on Earth.

Data from: Local adaptation of Pinus leiophylla under climate and land use change models in the Avocado Belt of Michoacán

Climate change and land use change are two main drivers of global biodiversity decline, decreasing the amount of genetic diversity that populations harbor and altering the patterns of local adaptation. Methods in landscape genomics allow measuring the effect of these anthropogenic disturbances on the adaptation of populations. However, both factors have rarely been considered simultaneously. We modeled the spatial turnover in allele frequencies of 19 localities of Pinus leiophylla across the Avocado Belt in Michoacán state, Mexico which could change under climate change and land use change scenarios, in addition to evaluating assisted gene flow strategies and connectivity metrics across the landscape to identify priority conservation areas. We found that localities at the center-east regions would be more vulnerable to climate change, while localities in the west area will be more threatened by actions of land use change. However, assisted gene flow actions could reduce their risk of extinction for both scenarios. Connectivity patterns will also be modified by future habitat loss, with the central and eastern parts having the highest connectivity values. These results show that the areas with the highest priority for conservation are in the eastern zones, which include the Monarch Butterfly Biosphere Reserve. This work is useful as a framework that incorporates distinct layers of information to provide a robust representation of the response of populations to future anthropogenic disturbances.

opencanada-crownMay 2024View details →

Ottawa climate data for building simulations with urban heat island effects and nature-based solutions

As cities face rising temperatures, increased frequency of extreme weather events, and altered precipitation patterns, buildings are subjected to increasing energy demand, heat stress, thermal comfort issues, and decreased service life. Therefore, evaluating building performance under changing climate conditions is essential for building sustainable and resilient communities. Unique climate characteristics of cities, such as the urban heat island effect, are not well simulated by global or regional climate models, and is therefore often not included in typical building analyses. Consequently, a computationally efficient approach is used to generate “urbanized” climate data, derived from regional climate models, to prepare building simulation climate data that incorporate urban effects. We demonstrate this process using existing climate data for Ottawa airport’s weather station and extend it to prepare projections for scenarios where nature-based solutions, such as increased greenery and albedo, were implemented. We find significant improvements in the representation of the urban heat island and subsequent cooling effects of nature-based solutions in the urbanized climate data. This dataset allows building practitioners to evaluate building performance under historical and potential future changes in climate, considering the complex interactions within the urban canopy and the implementation of mitigation efforts such as nature-based solutions. This dataset contains hourly historical and future weather files for use in building simulations for the city of Ottawa, Canada. While similar weather files are usually based on measurements taken at a city's nearby airport, the current dataset utilizes a novel statistical-dynamical downscaling technique which involves the use of the dynamical Weather Research and Forecasting (WRF) model combined with a statistical approach and climate projections from an ensemble of 15 Canadian Regional Climate Model 4 (CanRCM4) to generate urban climate data which includes the effects of the urban heat island and different nature-based solutions (NBS) as mitigation strategies (such as increasing surface albedo and greenery). Additionally, different levels of implementation of these mitigation strategies were produced, for example, when the albedo is increased to 0.40 (ALBD40) and 0.80 (ALBD80), and similarly for the green and combined scenarios, GRN40, GRN80, COMB40, and COMB80. The URBAN scenario is considered the control case where the urban heat island effects are accounted for in the data, but the NBS scenarios are not yet implemtned.  The data are stored in large CSV files, where the rows consists of all 15 realizations of the CanRCM4 ensemble and the variables make up the columns. For example, each 31-year period is repeated 15 times, once for each of the RCM realizations. Therefore, there are 4,073,400 (15x31x8760) rows in each file. We recommend viewing the data using packages from Python or R.     The historical and future global warming thresholds and their corresponding time periods are as follows: <table> <tbody> <tr> <td> Global Warming Scenario </td> <td> Time Period </td> </tr> <tr> <td> Historical </td> <td> 1991-2021 </td> </tr> <tr> <td> Global Warming 0.5ºC </td> <td> 2003-2033 </td> </tr> <tr> <td> Global Warming 1.0ºC </td> <td> 2014-2044 </td> </tr> <tr> <td> Global Warming 1.5ºC </td> <td> 2024-2054 </td> </tr> <tr> <td> Global Warming 2.0ºC </td> <td> 2034-2064 </td> </tr> <tr> <td> Global Warming 2.5ºC </td> <td> 2042-2072 </td> </tr> <tr> <td> Global Warming 3.0ºC </td> <td> 2051-2081 </td> </tr> <tr> <td> Global Warming 3.5ºC </td> <td> 2064-2094 </td> </tr> </tbody> </table>   The following variables are included in the files: <table> <tbody> <tr> <td>Variable</td> <td>Description</td> </tr> <tr> <td>RUN</td> <td>Run number (R1-R15) of Canadian Regional Climate Model, CanRCM4 large ensemble associated with the selected reference year data</td> </tr> <tr> <td>YEAR</td> <td>Year associated with the record</td> </tr> <tr> <td>MONTH</td> <td>Month associated with the record</td> </tr> <tr> <td>DAY</td> <td>Day of the month associated with the record</td> </tr> <tr> <td>HOUR</td> <td>Hour associated with the record</td> </tr> <tr> <td>YDAY</td> <td>Day of the year associated with the record</td> </tr> <tr> <td>DRI_kJPerM2</td> <td>Direct horizontal irradiance in kJ/m2 (total from previous HOUR to the HOUR indicated)</td> </tr> <tr> <td>DHI_kJperM2</td> <td>Diffused horizontal irradiance in kJ/m2 (total from previous HOUR to the HOUR indicated)</td> </tr> <tr> <td>DNI_kJperM2</td> <td>Direct normal irradiance in kJ/m2 (total from previous HOUR to the HOUR indicated)</td> </tr> <tr> <td>GHI_kJperM2</td> <td>Global horizontal irradiance in kJ/m2 (total from previous HOUR to the HOUR indicated)</td> </tr> <tr> <td>TCC_Percent</td> <td>Instantaneous total cloud cover at the HOUR in % (range: 0-100)</td> </tr> <tr> <td>RAIN_Mm</td> <td>Total rainfall in mm (total from previous HOUR to the HOUR indicated)</td> </tr> <tr> <td>WDIR_ClockwiseDegFromNorth</td> <td>Instantaneous wind direction at the HOUR in degrees (measured clockwise from the North)</td> </tr> <tr> <td>WSP_MPerSec</td> <td>Instantaneous wind speed at the HOUR in meters/sec</td> </tr> <tr> <td>RHUM_Percent</td> <td>Instantaneous relative humidity at the HOUR in %</td> </tr> <tr> <td>TEMP_K</td> <td>Instantaneous temperature at the HOUR in Kelvin</td> </tr> <tr> <td>ATMPR_Pa</td> <td>Instantaneous atmospheric pressure at the HOUR in Pascal</td> </tr> <tr> <td>SnowC_Yes1No0 </td> <td>Instantaneous snow-cover at the HOUR (1 - snow; 0 - no snow)</td> </tr> <tr> <td>SNWD_Cm</td> <td>Instantaneous snow depth at the HOUR in cm</td> </tr> </tbody> </table>

Data from: Data for habitat quality or quantity? Niche marginality across 21 plants and animals suggests differential responses between highland and lowland species to past climatic changes

Climatic changes can affect species distributions, population abundance, and evolution. Such organismal responses could be determined by the amount and quality of available habitats, which can vary independently. In this study, we assessed changes in habitat quantity and quality independently to generate explicit predictions of the species' responses to climatic changes between Last Glacial Maximum (LGM) and present day. We built ecological niche models and distribution models for 21 reptile, mammal, and plant taxa from the Baja California peninsula inhabiting lowland or highland environments. Geological data suggests the CCSM global circulation model is a better representation of LGM climate for the Baja California peninsula. Significant niche divergence was detected for all clades within species, along with significant differences in the niche breadth and area of distribution between northern and southern clades. Most clades showed a reduction in distribution area towards LGM. Further, niche marginality (used as a measure of habitat quality) was higher during LGM for most clades, except for northern highland species. Our results suggest that changes in habitat quantity and quality can affect organismal response independently. This allows the prediction of genomic signatures associated with changes in effective population size and selection pressure that could be explicitly tested to support our models.

opencc-zeroJun 2024View details →

Data from: Climate refugia along Lake Superior's shores: Disjunct arctic-alpine plants rely on cool shoreline temperatures but are unlikely to persist under climate warming

Climate refugia can serve as remnant habitat or stepping stones for species dispersal under climate warming. The largest freshwater lake by surface area, Lake Superior, USA and Canada, serves as a model system for understanding cooling-mediated local refugia, as its cool water temperatures and wave action have maintained shoreline habitats suitable for southern disjunct populations of arctic-alpine plants since deglaciation. Here we seek to explain spatial patterns and environmental drivers of arctic-alpine plant refugia along Lake Superior's shores, and assess future risk to refugia under moderate (+3.5 °C) and warmest (+5.7 °C) climate warming scenarios. First, we examined how the interactive effects of summer surface water temperatures and wind affected onshore temperatures, resulting in areas of cooler refugia. Second, we developed an ecological niche model for presence of disjunct arctic-alpine refugia (pooling 1253 occurrences from 58 species) along the lake's shoreline. Third, we fit species distribution models for 20 of the most common arctic-alpine disjunct species and predicted presence to identify refugia hotspots. Finally, we used the two climate warming scenarios to predict changes in presence of refugia and disjunct hotspots. Bedrock type, elevation above water, inland distance, July land surface temperature from MODIS/Terra satellite, and near-shore depth of water were the best predictors of disjunct occurrences. Overall, we predicted 2,236 km of the shoreline (51%) as disjunct refugia habitat for at least one species under current conditions, but this was reduced to 20% and 7% with moderate (894 km) and warmest (313 km) climate change projections.

opencc-zeroJun 2024View details →

Climate Hazards Data Integration and Visualization for the Climate Adaptations Solutions Accelerator through School-Community Hubs

Community engagement in planning is essential for effective and just climate adaptation. However, historically underserved communities are often difficult to reach through traditional means of soliciting public input. The Climate Adaptation Solutions Accelerator (CASA) through School-Community Hubs project identifies public schools as promising sites for building both community engagement and community capacity for climate adaptation. To serve in this role, schools need information about the intersecting threats climate change poses to the communities they serve. The Climate Hazard Dashboard for California Schools is a platform that maps the current and future risks associated with five climate hazards, including wildfire, extreme heat days, wildfire extreme precipitation, flooding, and sea level rise, for the nearly 10,000 public schools serving Kindergarten through Grade 12 students in California. Each hazard is mapped and visualized at the school level, providing an accessible way for administrators, teachers, students, and neighborhoods to explore data reflecting the climate hazards they face, at a scale relevant to their communities. The dashboard also provides an aggregate summary hazard metric.