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Data and Code Availability Stament for Halifa-Marín et al., 2023 (Environmental Research: Climate)

This file provides the R codes and datasets to reproduce the analyses made in the mentioned study, Halifa-Marín et al., 2023 (Environmental Research: Climate), and the supplementary material (figures).

Predicting International and Internal Migration in Guatemala with Social, Physical and Climatic Variables (Data)

Accompanying data for the Depsky and Pons (2023) PLoS ONE publication - Predicting International and Internal Migration in Guatemala with Social, Physical and Climatic Variables. This repository contains tables of the raw 2018 Guatemalan national census values at the individual, household, and residence levels, as well as its migration-specific data table. Municipality-average climate values from ERA5-Land are provided as well, in addition to a shapefile of the municipal boundaries. All standardized outcome and predictor variables used for each of the five models are provided as separate tables as well.

Morphed extreme weather data for Vantaa and Sodankylä under RCP climate change scenarios by 2030, 2050 and 2080

Morphed extreme weather data for 2 Finnish locations: Vantaa and Sodankylä. Created for "Near-, medium- and long-term impacts of climate change on the thermal energy consumption of buildings in Finland under RCP climate scenarios" publication (<a title="Persistent link using digital object identifier" href="https://doi.org/10.1016/j.energy.2024.131636" target="_blank" rel="noreferrer noopener">https://doi.org/10.1016/j.energy.2024.131636</a>). Used climate change scenarios are RPC2.6, RCP4.5 and RCP8.5. Data is created for 2030, 2050 and 2080 and includes 6 extreme weather scenarios:  <ul> <li>W1 - Winter with high heating demand</li> <li>W2 - Winter with low heating demand</li> <li>W3 - Winter with the coldest individual day by average temperature</li> <li>S1 - Summer with the lowest cooling demand</li> <li>S2 - Summer with the highest heating demand</li> <li>S3 - Summer with the warmest individual day by average temperature</li> </ul> Selected years and the procedure for their selection are described in <a title="Persistent link using digital object identifier" href="https://doi.org/10.1016/j.energy.2024.131636" target="_blank" rel="noreferrer noopener">https://doi.org/10.1016/j.energy.2024.131636</a>. Original weather data is downloaded for the selected years from Finnish Meteorological Institute's Open data repository: https://www.ilmatieteenlaitos.fi/havaintojen-lataus under CC BY 4.0 licence. Future change in climate is based on Finnish Meteorological Institute's data used in creating Test Reference Year weather files (<a href="https://www.ilmatieteenlaitos.fi/energialaskenta-try2020">https://www.ilmatieteenlaitos.fi/energialaskenta-try2020</a>) for which the climate change data is presented by Ruosteenoja et al. (2016). The data is statistically downscaled through a method called morphing created by Belcher et al. (2005) with some parts using methods from Räisänen & Räty (2013) and Jylhä et al, (2015). Morphing was computationally conducted through created software <a href="https://github.com/japulk/Weather-Morphing-Tool">https://github.com/japulk/Weather-Morphing-Tool</a> For additional information please refer to <a href="https://doi.org/10.1016/j.energy.2024.131636">original article</a> or contact the authors.

Data for "Global Precipitation Correction Across a Range of Climates Using CycleGAN"

# Data for "Global Precipitation Correction Across a Range of Climates Using CycleGAN" This repository contains the data used in the paper "Global Precipitation Correction Across a Range of Climates Using CycleGAN" by J. McGibbon et al. (2023, *in review*). `train_val` contains the model outputs for the training and validation sets used in the paper. Model spinup data is not included. The C384 runs are stored as a single series along a concatenated time axes. All C384 data has been coarsened to C384 resolution. `ramping_data` contains the model outputs from the 4-year, 3-month ramping simulation, including spinup data. `predicted` is included for convenience, and contains the model outputs from the "best" model, as was used to create figures shown in the paper. This model output was created from the CycleGAN using the validation dataset (stored in `train_val`) as input, and years 2 and 3 of the ramping simulation in `ramping_data` (following the 3-month spinup period). Ramping predictions are stored as separate datasets for the C48 (backwards) prediction and the C384 prediction. Validation data is stored alongside its respective target data in a single netCDF file, labelled "processed-agg". These filenames are intentionally left unchanged so that they correspond with the names of files used in the `process_combined_aggregate.py` script in `projects/cyclegan` of the code DOI for this paper, which was used to create its figures.

Global hourly t2m storyline data in the 2015-2019 (2017-2019) period in the present (2 and 4 K warmer climates)

Global hourly t2m storyline data (in the 2015-2019 (2017-2019) period in the present (2 and 4 K warmer climates) are provided in three .nc files (one file for each climate, with 2038-2040 and 2093-2095 in the model representing 2017-2019 for the 2 and 4 K warmer climates respectively). For the joint 2017-2019 period, ensemble member one used in Sánchez-Benítez et al. 2022 (see more details about the methodology used there) is provided. Meanwhile, the 2015-2016 present-climate data come from a nudged simulation which is identical to the present-climate nudged simulation described in Sánchez-Benítez et al. 2022, except that the simulation is branched off already in 1979 instead of 2017.

opencc-by-4.0Jul 2023View details →

Supporting data for "Linearity of the climate system response to raising and lowering West Antarctic and coastal Antarctic topography" by Andrew G. Pauling, Cecilia M. Bitz and Eric J. Steig

Contains the model output and topography files necessary to reproduce the results of "Linearity of the climate system response to raising and lowering West Antarctic and coastal Antarctic topography" by Andrew G. Pauling, Cecilia M. Bitz and Eric J. Steig. Published in Journal of Climate, <a href="https://doi.org/10.1175/JCLI-D-22-0416.1">https://doi.org/10.1175/JCLI-D-22-0416.1</a>. Please download and extract the data from each of the tar.gz.files. A description of the directories, run names, and use of the topography files is given in the file readme.txt within the dataset.

opencc-zeroJul 2023View details →

Data for: Phylogenomics and historical biogeography of Hydrangeeae (Hydrangeaceae) elucidate the effects of geologic and climatic dynamics on diversification

Demonstrating the process of transregional biogeography and mechanisms underlying evolutionary radiations is crucial to understanding biological evolution. Here, we use Hydrangeeae (Hydrangeaceae), a tribe with a unique disjunct distribution and complex trait variations, using a solid phylogenetic framework, to investigate how geographical and climatic factors interact with functional traits to trigger plant evolutionary radiations. We constructed the first highly supported and dated phylogenetic framework using 79 protein-coding genes obtained from 81 plastomes, representing 63 species and all major clades, and found that most extant species originated from asynchronous diversification of two lineages undergoing repeated expansion and retraction, at middle and high latitudes of the Northern Hemisphere between East Asia and North America, during the Eocene to Pleistocene (driven by geologic and climatic dynamics). In accordance with these drivers, interactions of flora between central-eastern China and Japan occurred frequently after the Late Tertiary. We found that resource limitation and range fragmentation likely accelerated the diversification of Hydrangeeae, which supports the resource-use hypothesis. Our study sheds light on the evolutionary radiation and assembly of flora within East Asia, and the East Asian-North American disjunction, through integration of phylogenomic and biogeographic data with functional trait and ecological data.

opencc-zeroJul 2023View details →

Model simulation data used in "The global impact of the transport sectors on the atmospheric aerosol and the resulting climate effects under the Shared Socioeconomic Pathways (SSPs)" (Righi et al., Earth Syst. Dynam., 2023)

This dataset contains the output of the EMAC global model simulations analysed and discussed in Righi et al. (Earth Syst. Dynam., 2023). For details see the README.md file.

opencc-by-4.0Jul 2023View details →

Data for "Feeding climate and biodiversity goals with novel plant-based meat and milk alternatives"

Research data supporting the study  "Feeding climate and biodiversity goals with novel plant-based meat and milk alternatives". It contains: 1) merged.gdx - data derived from the original scenario database 2) map.csv - mapping of food commodities to food groups used for analysis 3) manure.csv -  results on nitrogen input to cropland and N crop fertilization from manure 4) AgMIP_regions.shp - shape file used to make maps 5) Paper_visuals_NCOM.R - R script to analyze and visualize the data. It reproduces the main figures in the paper and the appendix    last tested for R Studio 2022.12.0 Build 353, Release (7d165dcf, 2022-12-03) for Windows 10 Pro, 64-bit operating system Instructions: The R code, file 4, reads in files 1, 2 and 3 and generates figures, tables and maps. The directories (line 50 and 58) need to be updated to the location of the data (the current folder).

opencc-by-4.0Aug 2023View details →

NEMO-FABM-ERSEM-MIZER climate change simulation data

This dataset corresponds to data produced from running NEMO-FABM-ERSEM MIZER on the AMM7 domain as part of the COMFORT project and used in the Deliverable 3.3 (see related identifiers). A scientific manuscript is in preparation. The climate simulation was run from 1981-2100 forced by atmospheric and lateral boundary condition from the IPSL-CMR5a-MR (RCP 8.5) climate simulation (Dufresne et al., 2013; WCRP, 2016)  . Data reported here are from 1990-2100, unless otherwise stated.    Data has been post-processed to convert it to depth independent (2D), monthly averaged variables. Consequently all data are either depth-integrated, mean across depth (temperature, salinity) or surface data (nutrients). For access to the raw data  or more details, please contact Helen Powley (hpo@pml.ac.uk).

opencc-zeroAug 2023View details →

Data from: Accelerating local extinction associated with very recent climate change

Climate change has already caused local extinction in many plants and animals, based on surveys spanning many decades. As climate change accelerates, the pace of these extinctions may also accelerate, potentially leading to large-scale, species-level extinctions. We tested this hypothesis in a montane lizard. We resurveyed 18 mountain ranges in 2021–2022 after only ~7 years. We found rates of local extinction among the fastest ever recorded, which have tripled in the past ~7 years relative to the preceding ~42 years. Further, climate change generated local extinction in ~7 years similar to that seen in other organisms over ~70 years. Yet, contrary to expectations, populations at two of the hottest sites survived. We found that genomic data helped predict which populations survived and which went extinct. Overall, we show the increasing risk to biodiversity posed by accelerating climate change, and the opportunity to study its effects over surprisingly brief timescales.

opencc-by-4.0Aug 2023View details →

Research Data for Research Activity "Virtual Climatization"

Machining workpieces on machine tools is an inherently energy intensive process. To achieve ever increasing tolerance requirements, thermal disturbances on machine tool and workpiece and resulting thermo-elastic deformations need to be addressed. Instead of cooling whole shopfloor environments and machines, desensitizing the process against temperature changes has the potential to reduce the carbon footprint of machining processes. To develop models for machine tool error prediction due to temperature, a comprehensive and diverse data set is essential. It includes data sources that capture relevant information about the machine tool's thermal behavior and its corresponding error. Hence, an experiment moving a machine tool with a fixed path is run for several hundred times with the same path for each run. Simultaneously, the actual machine position is measured using a laser tracker and component temperature is tracked.   <a href="https://git-ce.rwth-aachen.de/mark.sanders/bzt-data">https://git-ce.rwth-aachen.de/mark.sanders/bzt-data</a>

Data from: The sequential direct and indirect effects of mountain uplift, climatic niche and floral trait evolution on diversification dynamics in an Andean plant clade

Why and how organismal lineages radiate is commonly studied through either assessing abiotic factors (biogeography, geomorphological processes, climate) or biotic factors (traits, interactions). Despite increasing awareness that both abiotic and biotic processes may have important joint effects on diversification dynamics, few attempts have been made to quantify the relative importance and timing of these factors, and their potentially interlinked direct and indirect effects, on lineage diversification. We here combine assessments of historical biogeography, geomorphology, climatic niche, vegetative and floral trait evolution to test whether these factors jointly, or in isolation, explain diversification dynamics of a Neotropical plant clade (Merianieae, Melastomataceae). After estimating ancestral areas and disparification over time in climate and trait space, we employ Phylogenetic Path Analyses as a synthesis tool to test eleven hypotheses on the individual direct and indirect effects of these factors on diversification rates. We find strongest support for interlinked effects of colonization of the uplifting Andes during the mid-Miocene and rapid abiotic climatic niche evolution in explaining a burst in diversification rate in Merianieae. Within Andean habitats, later disparification in floral trait space allowed for the exploitation of wider pollination niches (i.e., shifts from bee to vertebrate pollinators), but did not affect diversification rates. Our approach of including both vegetative and floral trait evolution, rare in assessments of plant diversification in general, highlights important pre-adaptations to mountain colonization, specifically woody habit and larger flowers. Overall, and in concert with the idea that ecological opportunity is a key element of evolutionary radiations, our results suggest that a combination of rapid niche evolution and pre-adapted traits were critical for the exploitation of newly available niche space in the Andes in the mid-Miocene. Further, our results emphasize the importance of incorporating both abiotic and biotic factors into the same analytical framework if we aim to quantify the relative and interlinked effects of these processes on diversification.

Data for: Range reshuffling: climate change, invasive species, and the case of Nothofagus forests in Aotearoa New Zealand

Aim: The impact of climate change on forest biodiversity and ecosystem services will be partly determined by the relative fortunes of invasive and native forest trees under future conditions. Aotearoa New Zealand has high conservation value native forests and one of the world's worst invasive tree problems. We assess the relative effects of habitat redistribution on native Nothofagus and invasive conifer (Pinaceae) species in New Zealand as a case study on the compounding impacts of climate change and tree invasions. Location: Aotearoa New Zealand Methods: We use species distribution models (SDMs) to predict the current and future distribution of habitat for five native Nothofagus species and 13 invasive conifer species under two 2070 climate scenarios. We calculate habitat loss/gain for all species and examine overlap between the invasive and native species now and in the future. Results: Most species will lose habitat overall. The native species saw large changes in the distribution of habitat with extensive losses in North Island and gains mostly in South Island. Concerningly, we found that most new habitat for Nothofagus was also suitable for at least one invasive species. However, there were refugia for the native species in the wetter parts of the climate space. Main conclusion: If the predicted changes in habitat distribution translate to shifts in forest distribution it would cause widespread ecological disruption. We discuss how acclimation, adaptation and biotic interactions may delay some changes. But we also highlight how the poor migration and establishment capacity of native Nothofagus and the competitive ability of invasive conifers will be a persistent conservation challenge in areas of both new habitat and forest retreat. Pinaceae are problematic invaders globally, and our results highlight that control of invasions and active native forest restoration will likely be key to managing forest biodiversity under future climates.

opencc-by-4.0Apr 2023View details →

Climatic records and within field data on yield and harvest quality over a whole vineyard estate.

The data were obtained on a 30 ha vineyard located in a peri-urban area near a city of 10,000 inhabitants (Villeneuve-lès-Maguelone, France; 43.532300° N, 3.864230° E). The data includes 3 types of data: <ul> <li> Block(s) data: the data describes each vineyard block. The description parameters of the blocks are the identity, the year of plantation, the variety of the grapes, the area, the inter-row distance and vine-distance. The data is provided as vector data (.shp and associated files) using the WGS84 global coordinate reference system for latitude and longitude. The data is composed of 68 features. </li> <li> Agronomic data: The data describes production parameters for each “harvest sector” for the 2022 harvest season. A harvest sector is the area covered by the harvester to fill a harvest trailer before its departure to a cellar. The mean area of these harvest sectors over the vineyard is equal to 0.3 ha. The data is provided as vector data (.shp and associated files) using the WGS84 global coordinate reference system for latitude and longitude. The data is composed of 87 features associated with 87 harvest sectors. Each harvest sector is characterized by the harvest date, the block(s) id(s) that it belongs to, the percentage of unproductive plants(Uplants) and yield parameters (Mass, Yield and Yield PP). For 50 of them, harvest quality parameters are available (Sugar, Alcohol, Total acidity, pH, Yeast Assimilable Nitrogen and Organic Nitrogen). </li> <li> Weather data: the data consists of meteorological data for the 2020, 2021 and 2022 years recorded by a weather station located in the center of the vineyard. The recorded parameters are the followings: date, hour, relative humidity, rain gauge and air temperature. The acquisition time step is 15 minutes. The data are provided in Comma Separated Values (CSV) format. It is composed of 97988 lines. Each line describes meteorological data recorded at a given time. </li> </ul>

opencc-by-4.0May 2023View details →

Data for the publication "Significant Increase in Graupel and Lightning Occurrence in a Warmer Climate Simulated by Prognostic Graupel Parameterization"

This dataset includes a set of 11yr simulations using the MIROC6 global aerosol-climate model under the pre-industrial (PI, aerosol emission at the year 1850), present-day (PD, aerosol emission at the year 2000), and future warming (SST+4K, a uniform 4 K increase in sea surface temperature) conditions. The data are used in the manuscript entitled "Significant Increase in Graupel and Lightning Occurrence in a Warmer Climate Simulated by Prognostic Graupel Parameterization".

Data from: Phenotypic plasticity and genetic diversity shed light on endemism of rare Boechera perstellata and its potential vulnerability to climate warming

Premise of the study: The rapid pace of contemporary environmental change puts many species at risk, especially rare species constrained by limited capacity to adapt or migrate due to low genetic diversity and/or fitness. But the ability to acclimate can provide another way to persist through change. We compared the capacity of rare Boechera perstellata (Braun's rockcress) and widespread B. laevigata to acclimate to change. Methods: We investigated the phenotypic plasticity of growth, biomass allocation, and leaf morphology of individuals of B. perstellata and B. laevigata propagated from seed collected from several populations throughout their ranges in a growth chamber experiment to assess their capacity to acclimate. Concurrently, we assessed the genetic diversity of sampled populations using 17 microsatellite loci to assess evolutionary potential. Key results: Plasticity was limited in both rare B. perstellata and widespread B. laevigata, but differences in the plasticity of root traits between species suggest that B. perstellata may have less capacity to acclimate to change. In contrast to its widespread congener, B. perstellata exhibited no plasticity in response to temperature and weaker plastic responses to water availability. As expected, B. perstellata also had lower levels of observed heterozygosity than B. laevigata at the species level, but population-level trends in diversity measures were inconsistent due to high heterogeneity among B. laevigata populations. Conclusions: Overall, the ability of phenotypic plasticity to broadly explain the rarity of B. perstellata vs. commonness of B. laevigata is limited. However, some contextual aspects of our plasticity findings compared with its relatively low genetic variability may shed light on the narrow range and habitat associations of B. perstellata and suggest its vulnerability to climate warming due to acclimatory and evolutionary constraints.

opencc-by-4.0Sep 2023View details →

Data supporting: "Bayesian diagnosis of climate feedback evolution and forced temperature response"

This data set supports the paper: Calafat, F. M., & Cael, B. B. (2023). Bayesian diagnosis of climate feedback evolution and forced temperature response, Geophysical Research Letters, submitted. Please cite this paper when using this data set. Data description: <ul> <li>EBM_estimates.nc: this file contains Bayesian estimates from the energy balance model, including estimates of the climate feedback parameter and forced global average temperature change.</li> <li>EBM_input_data.nc: this file contains all of the data used as input to the Bayesian energy balance model.</li> </ul>

Data from: The impacts of climate change, energy policy, and traditional ecological practices on future firewood availability for Diné (Navajo) People

Simulated data and code from: Socio-economic predictors of Inuit hunting choices and their implications for climate change adaptation

These data are part of a data portal that accompanies the special issue 'Climate change adaptation needs a science of culture,' published in Philosophical Transactions of the Royal Society B in 2023. To access the data portal, please visit <a href="https://doi.org/10.5061/dryad.bnzs7h4h4">10.5061/dryad.bnzs7h4h4</a>. Summary Repository of R and Stan code to simulate and analyse foraging trip data (patch choice and harvest success). <a class="anchor" href="https://github.com/fhillemann/MSrepo_harvest_patch_choice#accompanying-manuscript"></a>Accompanying manuscript F. Hillemann, B. A. Beheim, E. Ready. 2023. Socio-economic predictors of Inuit hunting strategies and their implications for climate change adaptation. Phil. Trans. R. Soc. B 378: 20220395. <a href="https://doi.org/10.1098/rstb.2022.0395" rel="nofollow">https://doi.org/10.1098/rstb.2022.0395</a> Manuscript Abstract: In the Arctic, seasonal variation in the accessibility of the land, sea ice, and open waters influences which resources can be harvested safely and efficiently. Climate stressors are also increasingly affecting access to subsistence resources. Within Inuit communities, people differ in their involvement with subsistence activities, but little is known about how engagement in the cash economy (time and money available) and other socio-economic factors shape the food production choices of Inuit harvesters, and their ability to adapt to rapid ecological change. We analyse 281 foraging trips involving 23 Inuit harvesters from Kangiqsujuaq, Nunavik, using a Bayesian approach modelling both patch choice and within-patch success. Gender and income predict Inuit harvest strategies: while men, especially men from low-income households, often visit patches with a relatively low success probability, women and high-income hunters generally have a higher propensity to choose low-risk patches. Inland hunting, marine hunting, and fishing differ in the required equipment and effort, and hunters may have to shift their subsistence activities if certain patches become less profitable or less safe due to high costs of transportation or climate change (e.g., navigate larger areas inland instead of targeting seals on the sea ice). Our finding that household income predicts patch choice suggests that the capacity to maintain access to country foods depends on engagement with the cash economy.