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81 results for “Ice and climate”
Support Materials for Manuscript "Climate change induces rapid growth of dead ice in Asian glaciers" Review
<div>Description of support materials of paper "Climate change induces rapid growth of dead ice in Asian glaciers".</div> <div> </div> <div>The detailed description of files is below:</div> <div> </div> <div>· Total.csv</div> <div>The subregional statistics of HMA dead ice area and mass in 2100 under different SSPs.</div> <div> </div> <div>· Folder ./Inventory</div> <div>Interdecadal potential dead ice inventory in HMA.</div> <div> </div> <div>· Folder ./Individual</div> <div>Interdecadal statistics of individual glaciers' dead ice in HMA for their ablation (unit: Gt), area (unit: km2) and mass (unit: Gt).</div>
Code and data for "Sensitivity of Northern Hemisphere climate to ice-ocean interface heat flux parameterizations"
<p>This repository provides the source code and modeled data for three different ice-ocean heat flux<br> parameterizations of a 1-D idealized model, as well as 3-D climate models including CICE,<br> MPIOM and COSMOS, which are used in a GMD manuscript called "Sensitivity of Northern Hemisphere climate to ice-ocean interface heat flux parameterizations". The NCL-based scripts for plotting the figures are also provided.</p> <p><br> The file all.tar.gz consists of 4 folders as the following:</p> <p>1. 1-D<br> In the 1-D folder one can find the matlab source code for the 1-D idealized model with main.m being the main script and the others sub-scripts for calculating seasonal changes of different forcings, involving the surface albedo (albedo.m), shortwave fluxes (shortwave.m) and all other kinds of fluxes (otherfluxes.m).</p> <p>2. code<br> The code folder provides the source code of the three models used in our study: CICE, MPIOM and COSMOS.</p> <p>The most important code in terms of the ice-ocean heat flux in CICE can be found at code/cice/source/ice_therm_vertical.F90. The switch of the options of the three parameterizations can be achieved by changing the parameter "oceanic_heat" (1 for icebath, 2 for 2eq and 3 for 3eq) in the namelist when running the model.</p> <p>The mpiom folder contains the three different set of MPIOM source code for the three ice-ocean heat flux parameterizations respectively.</p> <p>In cosmos, one could find 4 sub-folders, with the folder echam5 containing the source code for the atmosphere module ECHAM5, and the other 3 folders containing the MPIOM source code incorporating with the three different ice-ocean heat flux parameterizations, similar as the mpiom folder.</p> <p>3. data<br> This folder provides the simulated output from the three models: CICE, MPIOM and COSMOS. Each model folder contains three sub-folders called 2eq, 3eq and icebath, representing the modelled data for the 2eq, 3eq and icebath parameterizations respectively. For CICE, we upload the modeled results of the last 10 years. For MPIOM and COSMOS, as the original data set are too large, here we upload the climatology of the data from the last 100 simulation years. Note that in cosmos, there are some additional variables which are listed seperately, namely the AMOC (amoc.nc), the sea surface pressure (slp.nc) as well as the surface temperature (tsurf.nc). reg.nc contains ocean temperature and salinity which have been interpolated onto a 1x1 regular grid.</p> <p>4. plot_figures<br> This folder gives the scripts based on NCL to plot the figures in the manuscript, with the *.ncl files being the plotting scripts and the *.eps being the figures. <br> All the code, data, scripts can be used by anyone who has interest.</p> <p> </p>
Supporting Data for Hahn et al. J. Climate: Seasonality in Arctic Warming Driven By Sea Ice Effective Heat Capacity
<p>This dataset includes CESM model experiment output for Hahn et al.: “Seasonality in Arctic Warming Driven By Sea Ice Effective Heat Capacity” submitted to Journal of Climate. Here we provide monthly climatologies averaged over the last thirty years for the Ice, No ice, and No ice, set albedo experiments with preindustrial and doubled CO<sub>2</sub> forcing. The variables hyam, hybm, and P0, useful for interpolating to pressure levels, are included in the FlatSOM1850.Q.nc file.</p>
A Gaussian process emulator for simulating ice sheet-climate interactions on a multi-million year timescale: CLISEMv1.0 (Video supplement)
<p>This video illustrates the ice sheet evolution during a 3 Myr period for three different emulators as described in the manuscript "A Gaussian process emulator for simulating ice sheet - climate interactions on a multi-million year timescale", submitted to Geoscientific Model Development. The ice sheet is forced by declining carbon dioxide concentrations from 980 to 720 ppmv and orbital parameter variations during the late Eocene (between 38 Ma and 35 Ma).</p>
Impact of Ural blocking on early-winter climate variability under different Barents-Kara sea ice conditions
<p>Model data from "Impact of Ural blocking on early-winter climate variability under different Barents-Kara sea ice conditions".</p>
Last glacial cycle simulations forced by PMIP3 climate with a matrix and index method using a 3D thermodynamical ice-sheet model IMAU-ICE
<p>IMAU-ICE 2.0 model output of the ice evolution during the last glacial cycle at a 10 ka temporal resolution, as described in Scherrenberg at al., 2023.</p>
data for the paper "Seasonal Prediction of Regional Arctic Sea Ice Using the High-Resolution Climate Prediction System CMA-CPSv3"
<p>CMA-CPSv3 data for the paper "Seasonal Prediction of Regional Arctic Sea Ice Using the High-Resolution Climate Prediction System CMA-CPSv3"</p>
Data from: Caribou, water, and ice – fine-scale movements of a migratory arctic ungulate in the context of climate change
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Climate and ice in the last glacial maximum explain patterns of isolation by distance inferred for alpine grasshoppers
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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).
Data for "Antarctic ice-sheet meltwater reduces transient warming and climate sensitivity through the sea-surface temperature pattern effect"
<p>Data of the Historical Hosing simulations presented in "Antarctic ice-sheet meltwater reduces transient warming and climate sensitivity through the sea-surface temperature pattern effect" submitted to Geophysical Research Letters</p> <p>Authors: Yue Dong, Andrew G. Pauling, Shaina Sadai, Kyle C. Armour </p> <p>Abstract:</p> <p>Coupled global climate models (GCMs) generally fail to reproduce the observed sea-surface temperature (SST) trend pattern since the 1980s. The model-observation discrepancies may arise in part from the lack of realistic Antarctic ice-sheet meltwater imbalance in GCMs. Here we employ two sets of CESM1-CAM5 simulations forced by anomalous Antarctic meltwater fluxes over 1980--2013 and into the 21st century. Both show a reduced global warming rate and an SST trend pattern that better resembles observations. The meltwater drives surface cooling in the Southern Ocean and the tropical southeast Pacific, in turn increasing low-cloud cover and driving radiative feedbacks to become more stabilizing (corresponding to a lower effective climate sensitivity). These feedback changes contribute more than ocean heat uptake efficiency changes in reducing the global warming rate. Accurately projecting historical and future warming thus requires improved representation of Antarctic meltwater and its impacts in models. </p>
Arctic and Antarctic sea ice thickness climate data record from ERS-1, ERS-2, Envisat and CryoSat-2
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Output of CAM simulations performed for study "Impact of cloud physics on the Greenland Ice Sheet near-surface climate: a study with the Community Atmosphere Model"
<p>Output of CAM simulations performed for study "Impact of cloud physics on the Greenland Ice Sheet near-surface climate: a study with the Community Atmosphere Model" in JGR-Atmospheres (2020). </p> <p>Output are NetCDF files containing annual means (named 'yearmean', 2007-2013), or multi-annual monthly means ('ymonmean', 2007-2012) of various variables that are of interest and/or used for analysis in this study. The file name starts with the variable name. Fields are global, at a resolution of 0.9 x 1.25 degrees latitude/longitude.</p> <p>The test simulations are named (as discussed in the paper):</p> <p>cam4_clm5<br> cam5_clm5<br> cam6_noicenucl_clm5<br> cam6_noclubb_clm5<br> cam6_mg1_clm5<br> cam6</p>
Data_Mass and heat balance of a lake ice cover in the Central Asian arid climate zone
<p>The data of the article "Mass and heat balance of a lake ice cover in the Central Asian arid climate zone".</p>
NOAA/NSIDC Climate Data Record of Passive Microwave Sea Ice Concentration, Version 5
This data set provides a Climate Data Record (CDR) of sea ice concentration from passive microwave data. The CDR algorithm output is a rule-based combination of ice concentration estimates from two well-established algorithms: the NASA Team (NT) algorithm (Cavalieri et al. 1984) and NASA Bootstrap (BT) algorithm (Comiso 1986). The CDR is a consistent, daily and monthly time series of sea ice concentrations from 25 October 1978 through the most recent processing for both the north and south polar regions. All data are on a 25 km x 25 km grid.Note: A near-real-time version of this data set also exists to fill the gap between the time that this data set is updated through to the present. The data set is called the Near-Real-Time NOAA/NSIDC Climate Data Record of Passive Microwave Sea Ice Concentration (https://nsidc.org/data/g10016).
Impacts of Climate on the Eco-Systems and Chemistry of the Arctic Pacific Environment (ICESCAPE)
Impacts of Climate on the Eco-Systems and Chemistry of the Arctic Pacific Environment (ICESCAPE) was a multi-year NASA shipborne project. The bulk of the research took place in the Beaufort and Chukchi Seas in the summers of 2010 and 2011.
Near-Real-Time NOAA/NSIDC Climate Data Record of Passive Microwave Sea Ice Concentration, Version 3
This data set provides a near-real-time Climate Data Record (CDR) of sea ice concentration from passive microwave data. The Near-real-time NOAA/NSIDC Climate Data Record of Passive Microwave Sea Ice Concentration (NRT CDR) data set is the near-real-time version of the final NOAA/NSIDC Climate Data Record of Passive Microwave Sea Ice Concentration (G02202). The NRT CDR is designed to fill the temporal gap between updates of the final CDR, occurring every three to six months, and to provide the most recent data.
Unified Sea Ice Thickness Climate Data Record, 1947 Onward, Version 1
The Unified Sea Ice Thickness Climate Data Record, 1947 Onward is the result of a concerted effort to collect as many observations as possible of Arctic and Antarctic sea ice draft, freeboard, and thickness and to format them consistently with clear documentation, allowing the scientific community to better utilize what is now a considerable body of observations.
Benefits of sea ice thickness initialization for the Arctic decadal climate prediction skill in EC-Earth3: data
<p>Data used in Tian et al (2020) in GMD Discussion on Benefits of sea ice thickness initialization for the Arctic decadal climate prediction skill in EC-Earth3. Date are used to generate figures and to execute routines; path2data4sensitivity_experiment is a text file, which contains links to ORAS5 reanalysis data as well as initial conditions/results of the sensitivity experiments.</p>
EAMv1 outputs Macquarie Island- Long-term variability in immersion-mode marine ice-nucleating particles from climate model simulations and observations
<p>EAMv1 outputs for the ACP publication </p> <p>https://acp.copernicus.org/articles/23/5735/2023/acp-23-5735-2023.pdf</p> <p>We have archived the outputs from the EAMv1 control simulations. </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.