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Kilometre-scale regional climate model simulations of two atmospheric river case studies in West Antarctica

Regional climate model simulations produced using the MetUM, HCLIM and Polar-WRF models at 1 km horizontal grid spacing. The data span two case studies in which an atmospheric river made landfall over the Amundsen Sea Embayment and Thwaites / Pine Island ice shelves. The first is a winter case (23-30 June 2020) and the second a summer case (3-9 February 2020).  Data are gridded, in native model coordinates, and saved as netcdf. Data produced by: HCLIM: José Abraham Torres MetUM: Ella Gilbert Polar-WRF: Denys Pishniak Data were produced to support the analysis presented in Gilbert et al. (2024) [preprint] . The research was funded by the PolarRES project, which is funded under the EU's Horizon 2020 programme call H2020-LC-CLA-2018-2019-2020 under grant agreement 101003590. MetUM simulations were performed on the ARCHER2 UK National Supercomputer.

Model data and figure code for results and figures in the manuscript submitted to Geophysical Research Letters "Hysteresis of the Antarctic ice sheet with a coupled ice sheet climate model"

This folder contains the model data and figure code for results and figures in the manuscript submitted to Geophysical Research Letters "Hysteresis of the Antarctic ice sheet with a coupled ice sheet climate model" The code for plotting the figures is the notebook Plot_figures.ipynb Fig1/simulation_output/ : Model output necessary for plotting the first figure  The last timestep of each simulation is provided. There is one file for 1D variables (ice volume, ice volume above flotation), and one file for 2D variables (ice sheet thickness for instance). <ul> <li>melt_insoPI_output/ : melt branch, pre-industrial insolation. Results for different CO2 levels</li> <li>growth_insoPI_output/ : growth branch, pre-industrial insolation. Results for different CO2 levels</li> <li>melt_insoMAX_output/ : melt branch, maximum insolation. Results for different CO2 levels</li> <li>growth_insoMIN_output/ : growth branch, minimum insolation. Results for different CO2 levels</li> </ul> compute_SLR_equivalent.py : code to compute the ice sheet volume in SLRe based on model output Fig1/SLR_files/ : contains the equilibrium ice sheet volume of the different simulations according to the CO2 level   Fig2/simulation_output/ : Model output necessary for plotting the second figure  The last timestep of each simulation is provided.  <ul> <li>melt_insoPI_enhancedmelt_albfb/ : melt branch, pre-industrial insolation, enhanced melt and albedo feedback. Results for different CO2 levels</li> <li>growth_insoPI_enhancedmelt_albfb/ : growth branch, pre-industrial insolation, enhanced melt and albedo feedback. Results for different CO2 levels</li> <li>melt_insoPI_enhancedmelt_fixedalb/ : melt branch, pre-industrial insolation, enhanced melt, no albedo feedback. Results for different CO2 levels</li> <li>growth_insoPI_enhancedmelt_fixedalb/: growth branch, pre-industrial insolation, enhanced melt, no albedo feedback. Results for different CO2 levels</li> </ul> compute_SLR_equivalent.py : code to compute the ice sheet volume in SLRe based on model output Fig2/SLR_files/ : contains the equilibrium ice sheet volume of the different simulations according to the CO2 level   Fig3/simulation_output/ : Model output necessary for plotting the third figure  <ul> <li>1xCO2_nocoupling/ : simulation with pre-industrial CO2 levels and insolation and no coupling to the ice sheet model</li> <li>8xCO2_nocoupling/ : simulation with 8xpiCO2 (pre-industrial CO2) levels, pre-industrial insolation and no coupling to the ice sheet model</li> <li>8xCO2_transient_albfb/ : quasi transient simulation, 8xpiCO2 levels,  pre-industrial insolation, coupling with the ice sheet model </li> <li>8xCO2_transient_fixedalb/ : quasi transient simulation, 8xpiCO2 levels,  pre-industrial insolation, coupling with the ice sheet model excluding the albedo-melt feedback</li> </ul>

Scherrenberg et al. (2024) supplement (Climate of the past): Ice-sheet model code, and output of Northern Hemisphere ice-sheet evolution of the past 800 kyr

Supplement to Scherrenberg et al. (2024), article in Climate of the Past. This data-set contains ice-sheet model (IMAU-ICE) code (see IMAU_ICE_Code.zip; see https://github.com/IMAU-paleo/IMAU-ICE/tree/main for the most recent version of the model), the model output and configuration files (see Data_output.zip), and scripts to create figures (see Scripts_and_Figures.zip). Please note that additional input fields are required to run IMAU-ICE and to produce the figures. See Scherrenberg et al., (2024) for more information or contact the corresponding author. Citation: M.D.W. Scherrenberg, C.J. Berends, R.S.W. van de Wal: Late Pleistocene glacial terminations accelerated by proglacial lakes, climate of the past, special issue "icy landscapes of the past", 2024

opennotspecifiedJul 2021View details →

Fig. 4 Species distribution models for Vaejovis carolinianus. Results were projected onto LGM conditions from MIROC a and CCSM4 b data sources invoking the model generated using current climates data c in Pliocene origins, Pleistocene refugia, and postglacial range expansions in southern devil scorpions (Vaejovidae: Vaejovis carolinianus)

Fig. 4 Species distribution models for Vaejovis carolinianus. Results were projected onto LGM conditions from MIROC a and CCSM4 b data sources invoking the model generated using current climates data c. Localities used to test and train the model are indicated by

opencc-by-4.0Dec 2023View details →

Investigating the "Too Bright" Issue Pertaining to Non-PBL Clouds over the South Pacific Trade-Wind Region in CMIP6 Global Climate Models

<a href="../api/records/13314147/draft/files/f09.C6.B-hist.SON_ANN.tar.gz/content" target="_blank" rel="noopener noreferrer">f09.C6.B-hist.SON_ANN.tar.g</a>z CESM2-CAM6 with falling ice radiative effects (FIREs), fully coupled run folloing CMIP6 historical run, same as CESM2-CAM6 in CMIP6 data port.   The data includes with netcdf self description. f09.C6.B-hist.h01_AWNC_ANN_15L-CDO_1x1.nc f09.C6.B-hist.h01_CLDHGH_ANN_climo-CDO.nc f09.C6.B-hist.h01_CLDLIQ_ANN_15L-CDO_1x1.nc f09.C6.B-hist.h01_CLDLOW_ANN_climo-CDO.nc f09.C6.B-hist.h01_CLDMED_ANN_climo-CDO.nc f09.C6.B-hist.h01_CLDTOT_ANN_climo-CDO.nc f09.C6.B-hist.h01_CLOUD_ANN_15L-CDO_1x1.nc f09.C6.B-hist.h01_CLOUDFRAC_CLUBB_ANN_15L-CDO_1x1.nc f09.C6.B-hist.h01_CONCLD_ANN_15L-CDO_1x1.nc f09.C6.B-hist.h01_FREQL_ANN_15L-CDO_1x1.nc f09.C6.B-hist.h01_ICWMR_ANN_15L-CDO_1x1.nc f09.C6.B-hist.h01_NUMLIQ_ANN_15L-CDO_1x1.nc f09.C6.B-hist.h01_OMEGA_ANN_15L-CDO_1x1.nc f09.C6.B-hist.h01_PRECC_ANN_climo-CDO.nc f09.C6.B-hist.h01_PRECL_ANN_climo-CDO.nc f09.C6.B-hist.h01_SST_ANN_climo-CDO.nc f09.C6.B-hist.h01_tauy_ANN_climo-CDO.nc <a href="../api/records/13314147/draft/files/f09.C6.B-hist.SON_ANN.tar.gz/content" target="_blank" rel="noopener noreferrer">f09.C6.B-hist.NOS_ANN.tar.g</a>z CESM2-CAM6 without falling ice radiative effects (FIREs), fully coupled run folloing CMIP6 historical run, same as CESM2-CAM6 in CMIP6 data port. f09.C6.B-hist.nos81_AWNC_ANN_15L-CDO_1x1.nc f09.C6.B-hist.nos81_CDNUMC_ANN_climo-CDO.nc f09.C6.B-hist.nos81_CLDHGH_ANN_climo-CDO.nc f09.C6.B-hist.nos81_CLDLIQ_ANN_15L-CDO_1x1.nc f09.C6.B-hist.nos81_CLDLOW_ANN_climo-CDO.nc f09.C6.B-hist.nos81_CLDMED_ANN_climo-CDO.nc f09.C6.B-hist.nos81_CLDTOT_ANN_climo-CDO.nc f09.C6.B-hist.nos81_CLOUD_ANN_15L-CDO_1x1.nc f09.C6.B-hist.nos81_CLOUDFRAC_CLUBB_ANN_15L-CDO_1x1.nc f09.C6.B-hist.nos81_CONCLD_ANN_15L-CDO_1x1.nc f09.C6.B-hist.nos81_FREQL_ANN_15L-CDO_1x1.nc f09.C6.B-hist.nos81_ICWMR_ANN_15L-CDO_1x1.nc f09.C6.B-hist.nos81_NUMLIQ_ANN_15L-CDO_1x1.nc f09.C6.B-hist.nos81_OMEGA_ANN_15L-CDO_1x1.nc f09.C6.B-hist.nos81_PRECC_ANN_climo-CDO.nc f09.C6.B-hist.nos81_PRECL_ANN_climo-CDO.nc f09.C6.B-hist.nos81_SST_ANN_climo-CDO.nc f09.C6.B-hist.nos81_taux_ANN_climo-CDO.nc f09.C6.B-hist.nos81_tauy_ANN_climo-CDO.nc

opencc-by-4.0Sep 2024View details →

Towards Dynamical Annual To Decadal Climate Prediction Using the IAP-CAS Model

We execute a set of Annual to Decadal (A2D) hindcast experiments using the IAP-CAS model (FGOALS-f2), which integrates 129 months of each prediction initialized from 1981 to 2015 annually, and evaluate the results of this experiment. The IAP-CAS model output associated with this work is stored here.

opencc-by-4.0Oct 2024View details →

Supporting Dataset for the study "Influence of Floodplains and Groundwater Dynamics on the Present-Day Climate simulated by the CNRM Model"

This archive contains the data used in the study "Influence of Floodplains and Groundwater Dynamics on the Present-Day Climate simulated by the CNRM Model" submitted to <a href="https://www.earth-system-dynamics.net/">Earth System Dynamics</a>.

Supporting Data for "The Vertical Structure of Tropical Temperature Change in Global Storm-Resolving Model Simulations of Climate Change"

Code and netcdf files of processed X-SHiELD and CMIP6 simulations to reproduce the figures of the revised submission of Timothy M. Merlis, Ilai Guendelman, Kai-Yuan Cheng, Lucas Harris, Yan-Ting Chen, Christopher S. Bretherton, Maximilien Bolot, Linjiong Zhou, Alex Kaltenbaugh, Spencer K. Clark, and Stephan Fueglistaler (2024): "The Vertical Structure of Tropical Temperature Change in Global Storm-Resolving Model Simulations of Climate Change".

embargoedcc-by-4.0Oct 2024View details →

EPJSOIL SERENA WP3 T3.3 : France climatic and agricultural change modelling dataset (Naizin)

The internal EJP SOIL project SERENA contributed to the evaluation of soil multifunctionality aiming at providing assessment tools for land planning and soil policies at different scales. By co-working with relevant stakeholders, the project provided co-developed indicators and associated cookbooks to assess and map them, to report both on soil degradation, soil-based ecosystem services and their bundles, under actual conditions and for climate and land-use changes, at the regional, national, and European scales.   Data aims to explore the effect of climate change according to different climate scenario up to 2050, and to understand the resistance of soil in response to climate change and different type of agricultural management. Additionally, it aims to understand the relations between SES, and the main factors affecting Soil Ecosystem Services (SES) variations. Data has been produced by the SERENA team WP3 T3.3 France using JAVA-STICS 10.0.0 model and the STICSonR package, using the input files specified in the data. Results consit of the yearly data of SES calculated from the daily modeling from STICS. Because of the file size of daily results from STICS, such file are not part of the dataset. Input data and R scripts used are instead provided. Naizin’s soil data come from Walter et al. (1993, 1996, 1998), climatic data were obtained from SAFRAN climatic data provided by Météo-France and were downloaded via the SICLIMA platform developed by AgroClim-INRAE. Plants and fertilizers data come from default dataset from STICS. All input data are available as part of this dataset.

opencc-zeroDec 2014View details →

Data from: Do ecological niche models accurately identify climatic determinants of species ranges?

Defining species' niches is central to understanding their distributions and is thus fundamental to basic ecology and climate change projections. Ecological niche models (ENMs) are a key component of making accurate projections and include descriptions of the niche in terms of both response curves and rankings of variable importance. In this study, we evaluate Maxent's ranking of environmental variables based on their importance in delimiting species' range boundaries by asking whether these same variables also govern annual recruitment based on long-term demographic studies. We found that Maxent-based assessments of variable importance in setting range boundaries in the California tiger salamander (Ambystoma californiense; CTS) correlate very well with how important those variables are in governing ongoing recruitment of CTS at the population level. This strong correlation suggests that Maxent's ranking of variable importance captures biologically realistic assessments of factors governing population persistence. However, this result holds only when Maxent models are built using best-practice procedures and variables are ranked based on permutation importance. Our study highlights the need for building high-quality niche models and provides encouraging evidence that when such models are built, they can reflect important aspects of a species' ecology.

opencc-zeroDec 2011View details →

Data from: Spatially explicit models of dynamic histories: examination of the genetic consequences of Pleistocene glaciation and recent climate change on the American Pika.

A central goal of phylogeography is to identify and characterize the processes underlying divergence. One of the biggest impediments currently faced is how to capture the spatiotemporal dynamic under which a species evolved. Here we described an approach that couples species distribution models (SDMs), demographic and genetic models in a spatiotemporally explicit manner. Analyses of American Pika (Ochotona priniceps) from the sky islands of the central Rocky Mountains of North America are used to provide insights into key questions about integrative approaches in landscape genetics, population genetics and phylogeography. This includes (i) general issues surrounding the conversion of time-specific SDMs into simple continuous, dynamic landscapes from past to current, and (ii) the utility of SDMs to inform demographic models with deme-specific carrying capacities and migration potentials, as well as (iii) the contribution of the temporal dynamic of colonization history in shaping genetic patterns of contemporary populations. Our results support that the inclusion of a spatiotemporal dynamic is an important factor when studying the impact of distributional shifts on patterns of genetic data. Our results also demonstrate the utility of SDMs to generate species-specific predictions about patterns of genetic variation that account for varying degrees of habitat specialization and life-history characteristics of taxa. Nevertheless, the results highlight some key issues when converting SDMs for use in demographic models. Because the transformations have direct affects on the genetic consequence of population expansion by prescribing how habitat heterogeneity and spatiotemporal variation is related to the species-specific demographic model, it is important to consider alternative transformations when studying the genetic consequences of distributional shifts.

opencc-by-4.0Dec 2020View details →

R-scripts for the calculation of HW and Bioclimatic models in: "Small vertebrate and mollusc community response to the Holocene environment and climate changes in the Kraków-Częstochowa Upland (Poland)"

HW_Holocene: Tables and R script used for calculation of HW percentage values. PalBER_Bioclimaticmodel_modified: Tables and R script used for the calculation of the climate values through Bioclimatic model. Modified after Royer et al., 2020.

opencc-zeroAug 2022View details →

Presence, precipitation, and temperature data used to estimate eastern forest songbird historical distributions using climatic niche modeling

Boundaries between vegetation types, known as ecotones, can be dynamic in response to climatic changes. The North American Great Plains includes a forest-grassland ecotone in the south-central United States that has expanded and contracted in recent decades in response to historical periods of drought and pluvial conditions. This dynamic region also marks a western distributional limit for many passerine birds that typically breed in forests of the eastern United States. To better understand the influence that variability can exert on broad-scale biodiversity, we explored historical longitudinal shifts in the western extent of breeding ranges of eastern forest songbirds in response to the variable climate of the southern Great Plains. We used climatic niche modeling to estimate current distributional limits of nine species of forest-breeding passerines from 30-year average climate conditions from 1980 to 2010. During this time the southern Great Plains experienced an unprecedented wet period without periodic multi-year droughts that characterized the region's long-term climate from the early 1900s. Species' climatic niche models were then projected onto two historical drought periods: 1952–1958 and 1966–1972. Threshold models for each of the three time periods revealed dramatic breeding range contraction and expansion along the forest-grassland ecotone. Precipitation was the most important climate variable defining breeding ranges of these nine eastern forest songbirds. Range limits extended farther west into southern Great Plains during the more recent pluvial conditions of 1980–2010 and contracted during historical drought periods. An independent dataset from BBS was used to validate 1966–1972 range limit projections. Periods of lower precipitation in the forest-grassland ecotone are likely responsible for limiting the western extent of eastern forest songbird breeding distributions. Projected increases in temperature and drought conditions in the southern Great Plains associated with climate change may reverse range expansions observed in the past 30 years.

opencc-by-4.0Aug 2021View details →

GFDL-ESM2G Model data and scripts in support of "The deep ocean's role in climate and CO2 sensitivity"

GFDL-ESM2G Model data and analysis scripts in support of the manuscript "The deep ocean's role in climate and CO2 sensitivity" by John Dunne and Lori Sentman submitted to Geophysical Research Letters including results from experiments with progressively shoaled maximum ocean depths of 4000 m to 1000 m in 500 m increments.

opencc-by-4.0Sep 2021View details →

Data for the manuscript entitled "AMOC variability and watermass transformations in the AWI climate model" by Sidorenko et al. 2021, submitted to JAMES

Data is stored in a SHELVE persistent storage as produced in Python 3.7.4. The visualisation example is provided in a Jupyter Python Notebook.

opencc-zeroDec 2021View details →

Lineage-level distribution models lead to more realistic climate change predictions for a threatened crayfish

Aim: As climate change presents a major threat to biodiversity in the next decades, it is critical to assess its impact on species habitat suitability to inform biodiversity conservation. Species distribution models (SDMs) are a widely used tool to assess climate change impacts on species' geographical distributions. As the term suggests, the species-level is the most commonly used taxonomic unit in SDMs. However, recently it has been demonstrated that SDMs considering taxonomic resolution below (or above) the species-level can make more reliable predictions of biodiversity change when different populations exhibit local adaptation. Here, we tested this idea using the Japanese crayfish (Cambaroides japonicus), a threatened species encompassing two geographically structured and phylogenetically distinct genetic lineages. Location: Northern Japan. Methods: We first estimated niche differentiation between the two lineages of C. japonicus using n-dimensional hypervolumes, then made climate change predictions of habitat suitability using SDMs constructed at two phylogenetic levels: species and intraspecific lineage. Results: Our results showed only intermediate niche overlap, demonstrating measurable niche differences between the two lineages. The species-level SDM made future predictions that predicted much broader and severe impacts of climate change. However, the lineage-level SDMs led to reduced climate change impacts overall, and also suggested that the eastern lineage may be more resilient to climate change than the western one. Main conclusions: The two lineages of C. japonicus occupy different niche spaces. Compared with lineage-level models, species-level models can overestimate climate change impacts. These results not only have important implications for designing future conservation strategies for this threatened species, but also highlight the need for incorporating genetic information into SDMs to obtain realistic predictions of biodiversity change.

opencc-by-4.0Oct 2021View details →

Data and model code for study: Mechanistic modelling of marsh seedling establishment provides a positive outlook for coastal wetland restoration under global climate change

This folder will include data and model code for study: Mechanistic modelling of marsh seedling establishment provides a positive outlook for coastal wetland restoration under global climate change.

opencc-by-4.0Dec 2021View details →

Physics‐Based Narrowband Optical Parameters for Snow Albedo Simulation in Climate Models

This is a supplementary file for a submitted paper"Physics-based effective broadband optical parameters for snow albedo simulation in climate models". The authors derived a set of snow optical properties that effective in broadband snow radiative transfer simulation. These parameters are physically-based.

opencc-by-4.0Nov 2022View details →

Processed model output used in 'The impact of winds on AMOC in a fully-coupled climate model'

Processed model output from wind-nudging experiments used to investigate the Atlantic Meridional Overturning Circulation.    For further details, see  Roach, L. A, Blanchard-Wrigglesworth E. Ragen, S., Cheng, W., Armour, K. and Bitz, C. M.. (2022). The impact of winds on AMOC in a fully-coupled climate model. In review at Geophysical Research Letters