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44 results for “climate observations”
Data for "Why Climate Sensitivity may be Constrained by Observable Natural Variability"
<p>Surface temperature and top-of-atmosphere radiation data from a 700-yr CO<sub>2</sub>-doubling experiment performed with the fully-coupled CESM1. Given on the CAM5 native grid (1 degree nominal resolution) as annual means. </p> <p>Data include annual TS (radiative surface temperature; in K), FLNT (net longwave radiation out at top-of-atmosphere), FSNT (net shortwave radiation in at top-of-atmosphere), FLNTC (net clear-sky longwave radiation out at top-of-atmosphere) and FSNTC (net clear-sky shortwave radiation out at top-of-atmosphere).</p>
Data from: Sporadic sampling not climatic forcing drives observed early hominin diversity
The role of climate change in the origin and diversification of early hominins is hotly debated. Most accounts of early hominin evolution link observed fluctuations in species diversity to directional shifts in climate or periods of intense climatic instability. None of these hypotheses, however, have tested whether observed diversity patterns are distorted by variation in the quality of the hominin fossil record. Here, we present a detailed examination of early hominin diversity dynamics, including both taxic and phylogenetically corrected diversity estimates. Unlike past studies, we compare these estimates to sampling metrics for rock availability (hominin-, primate-, and mammal-bearing formations) and collection effort, in order to assess the geological and anthropogenic controls on the sampling of the early hominin fossil record. Taxic diversity, primate-bearing formations, and collection effort show strong positive correlations, demonstrating that observed patterns of early hominin taxic diversity can be explained by temporal heterogeneity in fossil sampling rather than genuine evolutionary processes. Peak taxic diversity at 1.9 million years ago (Ma) is a sampling artefact, reflecting merely maximal rock availability and collection effort. In contrast, phylogenetic diversity estimates imply peak diversity at 2.4 Ma and show little relation to sampling metrics. We find that apparent relationships between early hominin diversity and indicators of climatic instability are, in fact, driven largely by variation in suitable rock exposure and collection effort. Our results suggest that significant improvements in the quality of the fossil record are required before the role of climate in hominin evolution can be reliably determined.
Data from: Too much of a good thing? Supplementing current species observations with fossil data to assess climate change vulnerability via ecological niche models
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Data from: Sporadic sampling not climatic forcing drives observed early hominin diversity
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Climate underpins continent-wide patterns of carotenoid-based feather color consistent with Gloger’s observations
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Climate‐driven tree growth and mortality in the Black Forest, Germany: Long‐term observations
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Data from: Phenological responses to multiple environmental drivers under climate change: insights from a long-term observational study and a manipulative field experiment
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The Effects of Climate Downscaling Technique and Observational Dataset on Modeled Ecological Responses: Supporting Data Tables
These data have been prepared as a supplement to Pourmokhtarian et al. (2016; full citation below), where complete details on methods can be found. We evaluated three downscaling methods: the delta method (or the change factor method); monthly quantile mapping (Bias Correction-Spatial Disaggregation, or BCSD); and daily quantile regression (Asynchronous Regional Regression Model, or ARRM). Additionally, we trained outputs from four atmosphere-ocean general circulation models (AOGCMs) (CCSM3, HadCM3, PCM, and GFDL-CM2.1) driven by higher (A1fi) and lower (B1) future emissions scenarios on two sets of observations (1/8th degree resolution grid vs. individual weather station) to generate the high-resolution climate input for the forest biogeochemical model PnET-BGC (8 ensembles of 6 runs). This dataset consists of three files - 1) a zip archive file of all raw daily downscaled AOGCMs (csv format; years 1960-2099; delta method 2012-2099 only) which were used as input for PnET-BGC model, 2) a zip archive file of all PnET-BGC output files for each model run (csv format; years 1000-2100), and 3) a pdf document file that describes the content of the input and output files. Data were also used from the following Hubbard Brook longterm datasests: Daily Streamflow Watershed 6: http://dx.doi.org/10.6073/pasta/727ee240e0b1e10c92fa28641bedb0a3 Chemistry of Streamwater at the Hubbard Brook Experimental Forest, Watershed 6: http://dx.doi.org/10.6073/pasta/2ec152b0ab1d4e64aa40f4aa9bc492ac Daily Precipitation Watershed 6: http://dx.doi.org/10.6073/pasta/17c8ff8b160bf7893ef39f75a02652e5 Daily Maximum/Minimum Temperature Data: http://dx.doi.org/10.6073/pasta/2a4ab5522ce15f28196a6035802b09e8 Daily Solar Radiation Data: http://dx.doi.org/10.6073/pasta/2fa098a5aa191c64e622b253c0fee5af These data were gathered as part of the Hubbard Brook Ecosystem Study (HBES). The HBES is a collaborative effort at the Hubbard Brook Experimental Forest, which is operated and maintained by the USDA Forest
Data from: Observed forest sensitivity to climate implies large changes in 21st century North American forest growth
Predicting long-term trends in forest growth requires accurate characterisation of how the relationship between forest productivity and climatic stress varies across climatic regimes. Using a network of over two million tree-ring observations spanning North America and a space-for-time substitution methodology, we forecast climate impacts on future forest growth. We explored differing scenarios of increased water-use efficiency (WUE) due to CO2-fertilisation, which we simulated as increased effective precipitation. In our forecasts: (1) climate change negatively impacted forest growth rates in the interior west and positively impacted forest growth along the western, southeastern and northeastern coasts; (2) shifting climate sensitivities offset positive effects of warming on high-latitude forests, leaving no evidence for continued 'boreal greening'; and (3) it took a 72% WUE enhancement to compensate for continentally averaged growth declines under RCP 8.5. Our results highlight the importance of locally adapted forest management strategies to handle regional differences in growth responses to climate change.
WRF model configuration and data used for the NHESS manuscript "Droughts in Germany: Performance of Regional Climate Models in reproducing observed characteristics"
<p>The file contains:</p> <ul> <li>the namelist.input document with the description of the WRF model configuration used in Warscher et al. (2019)</li> <li>WRF simulation outputs from the reanalysis run: monthly values for the time period 1980-2009 of precipitation, maximum and minimum temperature (needed for the SPEI calculation) from the innermost (5 km grid resolution) and second innermost (15 km) domain; from both domains the same section, relevant for the study, was taken; the data was bilineraily interpolated to 12.5 km horizontal grid resolution to match the EUR-11 CORDEX format</li> </ul> <p> </p>
Code and Data for "Bridging Gaps in the Climate Observation Network"
<p>The code and data used in the paper "Bridging Gaps in the Climate Observation Network: A Physics-based Nonlinear Dynamical Interpolation of Lagrangian Ice Floe Measurements via Data-Driven Stochastic Model"</p>
Raw Data for Publication "Earth observations reveal impacts of climate variability on maize cropping systems in Sub-Saharan Africa"
<p>Phenological metrics extracted for all agricultural fields used in the study. Data also includes the coordinates of the fields.</p>
Victorian Water and Climate dataset: long-term streamflow, climate, and vegetation observation records and catchment attributes
<p>This dataset contains streamflow, climate, and vegetation data for 155 minimally impaired catchments in Victoria, Australia. </p> <p>What's included:</p> <p>- Streamflow long-term observation records in daily, monthly, and hydroannual (based on March to February water year) resolution</p> <p>- Catchment climate characteristics in daily, monthly, and hydroannual resolution</p> <p>- Catchment vegetation characteristics in monthly resolution and actual evapotranspiration estimate in monthly and hydroannual resolution</p> <p>- Catchment boundaries</p> <p>- Catchment attributes (topographic, geological, soil, groundwater, vegetation, and human impacts characteristics)</p> <p>- Hydroclimatic characteristics for 3 different periods.</p> <p>Precipitation (p), streamflow (q), and PET (pet) data and their derivatives are in mm (i.e. normalised by catchment area). </p> <p>A paper containing a detailed description of the data including units, data sources, and processing details is submitted, please contact Margarita Saft for a private copy of the draft.</p>
Greenhouse gas forcing and climate feedback signatures identified in hyperspectral infrared satellite observations (Data)
<p>README file for LBL-ERA5, LBL-GCM, and band datasets used in:<br> Raghuraman et al., 2023, Geophysical Research Letters,<br> "Greenhouse gas forcing and climate feedback signatures identified in hyperspectral infrared satellite observations "</p> <p>Point of Contact: Shiv Priyam Raghuraman, shivr@alumni.princeton.edu</p> <p> </p> <p>LBL-ERA5</p> <p>6 files (3 experiments with olr and olr_clr output separately):</p> <p>2003-2021.GFDL.all-2010-o3_*.nc - varying WMGHG,Ts,T,q,clouds, fixed o3</p> <p>2003-2021.GFDL.fo3_*.nc - varying WMGHG and fixed Ts,T,q,clouds,surface albedo,o3</p> <p>2003-2021.GFDL.ff_*.nc - fixed Ts,T,q,clouds,surface albedo, varying o3</p> <p> </p> <p>LBL-GCM (clear-sky only)</p> <p>4 AM4 files:</p> <p>AM4piclim-control.nc (for ERF)</p> <p>AM4piclim-4xCO2_1xCO2IRF.nc (for ERF)</p> <p>AM4piclim-control_STRAT.nc (for SARF)</p> <p>AM4piclim-4xCO2_1xCO2IRF_STRAT.nc (for SARF)</p> <p>4 CM3/AM3 files:</p> <p>CTLAM3CM3_P1_APR_allctm_E1_RFM_1CM_A2_WN3_1xCO2N.nc (for \lambda)</p> <p>EXPAM3CM3_P1_APR_allctm_E1_RFM_1CM_A2_WN3_1xCO2N.nc (for \lambda)</p> <p>CTLAM3CM3_P1_2003C.nc (for IRF)</p> <p>CTLAM3CM3_P1_2021C.nc (for IRF)</p> <p> </p> <p>Band-AM4/MERRA-Total: GFDL AM4 with prescribed SSTs and sea-ice (AMIP) and nudged with MERRA winds</p> <p>2 files:</p> <p>atmos.200001-202112.olr.nc - all-sky OLR</p> <p>atmos.200001-202112.olr_clr.nc - clear-sky OLR</p> <p> </p> <p>Observational and reanalysis files used in paper (AIRS, CERES EBAF and SSF, GISTEMP, ERA5 input data) can be downloaded from their respective websites (see paper's "Open Research" section).</p> <p> </p>
Data from: Observed forest sensitivity to climate implies large changes in 21st century North American forest growth
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Contributions of the Liquid and Ice Phases to Global Surface Precipitation: Observations and Global Climate Modeling
This study is the first to reach a global view of the precipitation process partitioning, using a combination of satellite and global climate modeling data. The pathways investigated are (1) precipitating ice (ice/snow/graupel) that forms above the freezing level and melts to produce rain (S) followed by additional condensation and collection as the melted precipitating ice falls to the surface (R); (2) growth completely through condensation and collection (coalescence), warm rain (W); and (3) precipitating ice (primarily snow) that falls to the surface (SS). To quantify the amounts, data from satellite-based radar measurements—CloudSat, GPM, and TRMM—are used, as well as climate model simulations from the Community Atmosphere Model (CAM) and the UK Met Office Unified Model (UM).
Pre-LBA Anglo-Brazilian Amazonian Climate Observation Study (ABRACOS) Data
The data set presents the principal data from the Anglo-BRazilian Amazonian Climate Observation Study (ABRACOS) (Gash et al, 1996) and provides quality controlled information from five of the study topics considered by the project in five zipped files containing ASCII text data. The five study topics include Micrometeorology, Climate, Carbon Dioxide and Water Vapor, Plant Physiology, and Soil Moisture. The objectives of the ABRACOS were to monitor Amazonian climate and improve the understanding of the consequences of deforestation and to provide data for the calibration and validation of GCMs and GCM sub-models of Amazonian forest and post-deforestation pasture (Shuttleworth et al, 1991). Three areas were instrumented, each with different soils, dry season intensities and deforestation densities (Gash et al, 1996). In each area, an automatic weather station and soil moisture measurement equipment were installed: in a primary forest site and in nearby cattle pasture, for monitoring climate and soil status throughout the year. Additional intensive periods of study (or Missions), of varying duration, were operated at these sites: for calibration purposes, to understand the physical processes relevant to each site, and for detailed comparisons between sites. These data were collected under the ABRACOS project and made available by the UK Institute of Hydrology and the Instituto Nacional de Pesquisas Espaciais (Brazil). ABRACOS is a collaboration between the Agencia Brasileira de Cooperacao and the UK Overseas Development Administration. The processed, quality controlled and integrated data in the documented Pre-LBA data sets were originally published as a set of three CD_ROMs (Marengo and Victoria, 1998) but are now archived individually.
Supporting Data for Sagoo et al. GRL: Observationally Constrained Cloud Phase Unmasks Orbitally Driven Climate Feedbacks
<p>This dataset includes CESM climatologies relevant for Sagoo et al.: “Observationally Constrained Cloud Phase Unmasks Orbitally Driven Climate Feedbacks” in Geophysical Research Letters. Data is included for high (HI) and low (LO) obliquity experiments with the default model (OOTB) and with supercooled liquid fraction constrained to satellite observations (SLF1 and SLF2), as described in the manuscript. </p>
IPCC Fourth Assessment Report (AR4) Observed Climate Change Impacts Database
The Intergovernmental Panel on Climate Change (IPCC) Fourth Assessment Report (AR4) Observed Climate Change Impacts Database contains observed responses to climate change across a wide range of systems as well as regions. These data were taken from the Intergovernmental Panel on Climate Change Fourth Assessment Report and Rosenzweig et al. (2008). It consists of responses in the the physical, terrestrial biological systems and marine-ecosystems. The observations that were selected include data that demonstrate a statistically significant trend in change in either direction in systems related to temperature or other climate change variable, and the is for at least 20 years between 1970 and 2004, although study periods may extend earlier or later. For each observation, the data series is described in terms of system, region, longitude and latitude, dates and duration, statistical significance, type of impact, and whether or not land use was identified as a driving factor. System changes are taken from ~80 studies (of which ~75 are new since the IPCC Third Assessment Report) containing more than 29,500 data series. Observations in the database are characterized as a "change consistent with warming" or a "change not consistent with warming", based on information from the underlying studies.
IPCC Fifth Assessment Report (AR5) Observed Climate Change Impacts Database, Version 2.01
The Intergovernmental Panel on Climate Change Fifth Assessment Report (AR5) Observed Climate Change Impacts Database, Version 2.01 contains observed responses to climate change across a wide range of systems as well as regions. These responses include systems for which climate change has played a major role in observed changes, regional-scale impacts where climate change has played a minor role, and sub-regional impacts. Impacts on physical, biological, and human systems were differentiated, and the area impacted can vary from specific locations to broad areas such as a major river basin.
ScienceDex guides
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.