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71 results for “past climate”
Calculated moisture sources for the Yangtse River Valley for past, present and future climate using a Lagrangian moisture source diagnostic
<p>This dataset contains calculated moisture sources for the Yangtse River Valley (110–122°E and 27–33°N, eastern China) for past, present and future climate using a Lagrangian moisture source diagnostic. The dataset comprises gridded monthly moisture source data files and monthly time series files for a Last Glacial Maximum (LGM) simulation and a Pre-Industrial reference simulation (PRE) with CAM5.1 using prescribed sea surface temperatures, and a control simulation (CTL, 2001-2010) and a climate scenario run with representative concentration pathway 6 (RCP, 2061-2070) with the coupled NorESM-1M model. Each file covers a 10-year time period, computed with the Lagrangian moisture source diagnostic WaterSip (Sodemann et al., 2008).</p>
Paleoclimate Data-Model Comparison and the Role of Climate Forcings over the Past 1500 Years
<p>The past 1500 years provide a valuable opportunity to study the response of the climate system to external forcings. However, the integration of paleoclimate proxies with climate modeling is critical to improving the understanding of climate dynamics. In this paper, a climate system model and proxy records are therefore used to study the role of natural and anthropogenic forcings in driving the global climate. The inverse and forward approaches to paleoclimate data-model comparison are applied, and sources of uncertainty are identified and discussed. In the first of two case studies, the climate model simulations are compared with multiproxy temperature reconstructions. Robust solar and volcanic signals are detected in Southern Hemisphere temperatures, with a possible volcanic signal detected in the Northern Hemisphere. The anthropogenic signal dominates during the industrial period. It is also found that seasonal and geographical biases may cause multiproxy reconstructions to overestimate the magnitude of the long-term preindustrial cooling trend. In the second case study, the model simulations are compared with a coral d18O record from the central Pacific Ocean. It is found that greenhouse gases, solar irradiance, and volcanic eruptions all influence the mean state of the central Pacific, but there is no evidence that natural or anthropogenic forcings have any systematic impact on El Nino-Southern Oscillation. The proxy climate relationship is found to change over time, challenging the assumption of stationarity that underlies the interpretation of paleoclimate proxies. These case studies demonstrate the value of paleoclimate data-model comparison but also highlight the limitations of current techniques and demonstrate the need to develop alternative approaches.</p>
Past and future effects of climate on the metapopulation dynamics of a NorthEast Atlantic seabird across two centuries
<p>Datasets required to run code for contribution:</p> <p>Past and future effects of climate on the metapopulation dynamics of a NorthEast Atlantic seabird across two centuries</p> <p>Jana WE Jeglinski, Holly I Niven, Sarah Wanless, Robert T. Barrett, Mike P. Harris, Jochen Dierschke and Jason Matthiopoulos</p> <p>Extension of a Bayesian metapopulation model fit to colony census data for all Northeast Atlantic colonies of the Northern gannet (<em>Morus bassanus</em>) described in Jeglinski et al. (2023) to investigate mechanistic relationships with climate and forecast metapopulation dynamics under two climate scenarios. </p>
Understanding ENSO dynamics through the exploration of past climates
<p>The palaeoclimate record shows that significant changes in ENSO characteristics took place during the Holocene. Exploring these changes, using both data and models, provides a means of understanding ENSO dynamics. Previous modelling studies have suggested a mechanism whereby changes in the Earth’s orbital geometry explain the strengthening of ENSO over the Holocene. Decreasing summer insolation over the Asian landmass resulted in a weakening of the Asian monsoon system. This led to a weakening of the easterly trade winds in the western Pacific, creating conditions more favourable for El Niño development. To explore this hypothesised forcing mechanism, we use a climate system model to conduct a suite of simulations of the climate of the past 8,000 years. In the early Holocene, we find that the Asian summer monsoon system is intensified, resulting in an amplification of the easterly trade winds in the western Pacific. The stronger trade winds represent a barrier to the eastward propagation of westerly wind bursts, therefore inhibiting the onset of El Niño events. The fundamental behaviour of ENSO remains unchanged, with the major change over the Holocene being the influence of the background state of the Pacific on the susceptibility of the ocean to the initiation of El Niño events.</p>
Subglacial valleys preserved in the highlands of south and east Greenland record restricted ice extent during past warmer climates: Datasets
<p>This dataset contains the following files:</p><ul><li><strong>mountain_glacial_valleys_2km.shp (and ancillary files: .dbf, .prj, .shx)</strong>: ESRI shapefile of the subglacial valleys mapped along the southern and eastern highlands of Greenland using MODIS Mosaic of Greenland imagery and radio-echo sounding data.</li><li><strong>mountain_glacial_limit.shp (and ancillary files: .dbf, .prj, .shx)</strong>: ESRI shapefile of the interpreted palaeo-glacial valley limit along the southern and eastern highlands of Greenland based on the distribution and morphology of the mapped subglacial valleys.</li><li><strong>ex_g5km_10ka_hy_east.nc</strong>: NetCDF file of the Parallel Ice Sheet Model output spatially variable fields for the best-fitting simulation for the eastern highlands (run at 5 km horizontal resolution for 10,000 model years).</li><li><strong>ts_g5km_10ka_hy_east.nc</strong>: NetCDF file of the Parallel Ice Sheet Model output scalar time series for the best-fitting simulation for the eastern highlands (run at 5 km horizontal resolution for 10,000 model years).</li><li><strong>ex_g5km_10ka_hy_south.nc</strong>: NetCDF file of the Parallel Ice Sheet Model output spatially variable fields for the best-fitting simulation for the southern highlands (run at 5 km horizontal resolution for 10,000 model years).</li><li><strong>ts_g5km_10ka_hy_south.nc</strong>: NetCDF file of the Parallel Ice Sheet Model output scalar time series for the best-fitting simulation for the southern highlands (run at 5 km horizontal resolution for 10,000 model years).</li></ul>
Supplementary material for "Increased sensitivity of marine invertebrates to metal toxicity in the past two decades linked to Climate Change and Ocean Acidification: revelations from a natural population of sea urchins in the Mediterranean Sea." by "Davide Sartori, Guido Scatena, Cristina Vrinceanu, Andrea Gaion".
<p>Satellite observations of environmental factors and effect concentration 50 for copper to sea urchin, from 2003 to 2022.</p>
Internal climate variability and spatial temperature correlations during the past 2000 years
<p>Climate model output of the iLOVECLIM model. The repository contains:</p> <p>Data on 9 ensemble members corresponding to ensemble members 1-9 in the publication:</p> <p>1: 0ka_trans_013000to015000.nc</p> <p>2: 0ka_trans_precipcorr_AC_x0.4_AS_x1.6_013000to015000.nc</p> <p>3: 0ka_trans_7params_6_013000to015000.nc</p> <p>4: 0ka_trans_7params_12_013000to015000.nc</p> <p>5: 0ka_trans_7params_30_013000to015000.nc</p> <p>6: 0ka_trans_8params_6_013000to015000.nc</p> <p>7: 0ka_trans_8params_26_013000to015000.nc</p> <p>8: 0ka_trans_8params_35_013000to015000.nc</p> <p>9: 0ka_trans_8params_40_013000to015000.nc</p> <p> </p> <p>Three different data files for every ensemble member</p> <p>atmym: yearly mean atmospheric output (t2m is used for temperature in the manuscript)</p> <p>CLIO2: yearly mean ocean surface output (temp is used for SST in the manuscript)</p> <p>graevolu: collection of monthly mean 1 dimensional ocean outputs (ADPro is used for AMOC strength in the manuscript)</p>
Documents presenting past climate change adaptations (2008 - 2020)
<p>Using a systematic review approach, we identified a global dataset of 301 reported adaptation responses of small-scale fishers to climate change. Here we show the references of the selected documents (n = 60) through the systematic review from which the adaptation responses for data analysis were extracted.</p>
TA B L E 1 Summary of model fit, based on the area under the curve (AUC) of the receiver operating characteristic (ROC) for training data, and the most important bioclimatic variables in past, present, and future (2070) Maxent models of 13 bat species included in this study. in Southern Africa's Great Escarpment as an amphitheater of climate-driven diversification and a buffer against future climate change in bats
TA B L E 1 Summary of model fit, based on the area under the curve (AUC) of the receiver operating characteristic (ROC) for training data, and the most important bioclimatic variables in past, present, and future (2070) Maxent models of 13 bat species included in this study.
Supplementary data from: Current and past climate co-shape community-level plant species richness in the Western Siberian Arctic
<p>The Arctic ecosystems and their species are exposed to amplified climate warming and, in some regions, to rapidly developing economic activities. We used macroecological modeling to estimate the community-level species richness across the Western Siberian tundra, with climate variables and anthropogenic influence identified as main explanatory factors. Our results reveal complex spatial patterns of community-level species richness in the Western Siberian Arctic. We show that climatic factors such as temperature (including paleotemperature) and precipitation are the main drivers of plant species richness in this area, and the role of relief is clearly secondary.</p> <p>Here we present a supplementing dataset to the analysis of our paper "Current and past climate co-shape community-level plant species richness in the Western Siberian Arctic"<strong> </strong>(<a href="https://doi.org/10.1002/ece3.11140">https://doi.org/10.1002/ece3.11140</a>). Our research is based on the Western Siberian part of the Russian Arctic Vegetation Archive (AVA-RUS, <a href="http://avarus.space">http://avarus.space</a>), with 1483 Braun-Blanquet plots observed from 2005-2018.</p> <p>The dataset contains geolocated species richness data along with sampled raster data on environmental and anthropogenic predictors used for modeling. The scripts are used for paleoclimatic data sampling; testing univariate predictive performance and limited collinearity for all predictors; fitting four different modes: random forest, gradient boosting machine, generalized linear model, and generalized additive model; their validation and projection. Detailed information regarding the data structure and the applied methods could be found in the paper.</p>
Figure 3. The effective population size through recent time for 3 in Comparative analyses of past population dynamics between two subterranean zokor species and the response to climate changes
Figure 3. The effective population size through recent time for 3 clades of Gansu zokor (Eospalax cansus).
Data from: Species-specific traits mediate avian demographic responses under past climate change
<p>Anticipating species' responses to environmental change is a<span> pressing mission in biodiversity conservation. Despite decades of research investigating how climate change may affect population sizes, historical context is lacking and the traits which mediate demographic sensitivity to changing climate remain elusive. We use whole-genome sequence data to reconstruct the demographic histories of 263 bird species over the past million years and identify networks of interacting morphological and life-history traits associated with changes in effective population size (<em>N<sub>e</sub></em>) in response to climate warming and cooling. Our results identify direct and indirect effects of key traits representing survival, reproduction, and dispersal processes on long-term demographic responses to climate change and highlight traits most likely to influence population responses to ongoing climate warming.</span></p>
Supplementary data from: Current and past climate co-shape community-level plant species richness in the Western Siberian Arctic
Open the record for dataset details and reuse information.
Data from: Species-specific traits mediate avian demographic responses under past climate change
Open the record for dataset details and reuse information.
Supporting model data for Paleogeographic controls on the evolution of Late Cretaceous ocean circulation by Ladant, J.-B., et al. in Climate of the Past, doi:10.5194/cp-2019-157.
<p>The dataset is comprised of CCSM4 model variables required to reproduce the figures shown in the following manuscript:</p> <p>Ladant, J.-B., C. J. Poulsen, F. Fluteau, C. R. Tabor, K. G. MacLeod, E. E. Martin, S. J. Haynes and M. A. Rostami, Paleogeographic controls on the evolution of Late Cretaceous ocean circulation, Climate of the Past, doi:10.5194/cp-2019-157.</p>
Messinian vegetation and climate of the intermontane Florina-Ptolemais-Servia Basin, NW Greece: How well do plant fossils reflect past environments?
The late Miocene is marked by pronounced environmental changes and the appearance of strong temperature and precipitation seasonality. Although environmental heterogeneity is to be expected during this time, it is challenging to reconstruct palaeoenvironments using plant fossils. We investigated leaves and dispersed spores/pollen from 6.4–6 Ma strata in the intermontane Florina-Ptolemais-Servia Basin (FPS) of NW Greece. To assess how well plant fossils reflect the actual vegetation of the FPS, we assigned fossil-taxa to biomes providing a measure for environmental heterogeneity. Additionally, the palynological assemblage was compared to pollen spectra from modern lake sediments to assess biases in spore/pollen representation in the pollen record. We found a close match of the Vegora assemblage with modern Fagus–Abies forests of Turkey. Using taxonomic affinities of leaf fossils, we further established close similarities of the Vegora assemblage with modern laurophyllous oak forests of Afghanistan. Finally, using information from sedimentary environment and taphonomy, we distinguished local and distantly growing vegetation types. We then subjected the plant assemblage of Vegora to different methods of climate reconstruction and discussed their potentials and limitations. Leaf and spore/pollen records allow accurate reconstructions of palaeoenvironments in the FPS, whereas extra-regional vegetation from coastal lowlands is likely not captured.
Weather dataset (Typical Downscaled Year, Extreme Cold Year, Extreme Warm Year) for building energy simulations (.epw format) in recent past climate, Kortrijk Kennedy Park, Belgium
<p>Typical Downscaled Year (TDY), Extreme Cold Year and Extreme Warm Year based on the methodology of Nik (2016), is extracted for the location of Kortrijk Kennedy Park (50°48'2"N 3°16'13" E) from the EC-Earth driven convection-permitting climate model COSMO-CLM for the Belgian domain extended with land-surface scheme TERRA_URB(v2.0) making use of the SURY (Semi-empirical URban canopY) parameterization ( Wouters et al. 2016). The integrations are identical to the ones which are described in Vanden Broucke et al. (2019). The climate model has a spatial resolution of 2.8 km and an hourly temporal resolution and is available for the recent past (1976-2004) and future (2070-2098) as 30-year datasets. For this dataset, the TDY, ECY, and EWY are extracted for the recent past period. A bias correction is applied for the following variables: temperature (as described in Ramon et al. 2020), solar radiation and relative humidity as described in Ramon et al. (202X).</p>
Weather dataset (Typical Downscaled Year, Extreme Cold Year, Extreme Warm Year) for building energy simulations (.epw format) in recent past climate, Antwerp Berchem, Belgium
<p>Typical Downscaled Year (TDY), Extreme Cold Year and Extreme Warm Year based on the methodology of Nik (2016), is extracted for the location of Antwerp Berchem (51°12'00"N 4°26'24" E) from the EC-Earth driven convection-permitting climate model COSMO-CLM for the Belgian domain extended with land-surface scheme TERRA_URB(v2.0) making use of the SURY (Semi-empirical URban canopY) parameterization ( Wouters et al. 2016). The integrations are identical to the ones which are described in Vanden Broucke et al. (2019). The climate model has a spatial resolution of 2.8 km and an hourly temporal resolution and is available for the recent past (1976-2004) and future (2070-2098) as 30-year datasets. For this dataset, the TDY, ECY, and EWY are extracted for the recent past period. A bias correction is applied for the following variables: temperature (as described in Ramon et al. 2020), solar radiation and relative humidity as described in Ramon et al. (202X).</p>
Weather dataset (Typical Downscaled Year, Extreme Cold Year, Extreme Warm Year) for building energy simulations (.epw format) in recent past climate, Leuven Casa Blanca, Belgium
<p>Typical Downscaled Year (TDY), Extreme Cold Year and Extreme Warm Year based on the methodology of Nik (2016), is extracted for the location of the Casa Blanca Neighbourhood Leuven (50°52'48"N 4°43'48"E) from the EC-Earth driven convection-permitting climate model COSMO-CLM for the Belgian domain extended with land-surface scheme TERRA_URB(v2.0) making use of the SURY (Semi-empirical URban canopY) parameterization ( Wouters et al. 2016). The integrations are identical to the ones which are described in Vanden Broucke et al. (2019). The climate model has a spatial resolution of 2.8 km and an hourly temporal resolution and is available for the recent past (1976-2004) and future (2070-2098) as 30-year datasets. For this dataset, the TDY, ECY, and EWY are extracted for the recent past period. A bias correction is applied for the following variables: temperature (as described in Ramon et al. 2020), solar radiation and relative humidity as described in Ramon et al. (202X).</p>
Weather dataset (Typical Downscaled Year, Extreme Cold Year, Extreme Warm Year) for building energy simulations (.epw format) in recent past climate, Uccle KMI, Belgium
<p>Typical Downscaled Year (TDY), Extreme Cold Year and Extreme Warm Year based on the methodology of Nik (2016), is extracted for the location of Uccle KMI (50°47'49"N 4°21'29" E) from the EC-Earth driven convection-permitting climate model COSMO-CLM for the Belgian domain extended with land-surface scheme TERRA_URB(v2.0) making use of the SURY (Semi-empirical URban canopY) parameterization ( Wouters et al. 2016). The integrations are identical to the ones which are described in Vanden Broucke et al. (2019). The climate model has a spatial resolution of 2.8 km and an hourly temporal resolution and is available for the recent past (1976-2004) and future (2070-2098) as 30-year datasets. For this dataset, the TDY, ECY, and EWY are extracted for the recent past period. A bias correction is applied for the following variables: temperature (as described in Ramon et al. 2020), solar radiation and relative humidity as described in Ramon et al. (202X).</p>
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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.