Over the past six years, our research team consisting of scientists at Texas A&M University (TAMU) and the U.S. National Science Foundation National Center for Atmospheric Research (NSF NCAR) has made major breakthroughs in advancing high-resolution global climate modeling and prediction. We have completed several thousand years of climate simulations at a tropical cyclone (TC) permitting and ocean-eddy-rich resolution (hereafter simply referred to as CESM-HR) as part of our NSF-funded project entitled "Understanding the Role of MESoscale Atmosphere-Ocean Interactions in Seasonal-to-Decadal CLImate Prediction (MESACLIP)". Among others, we completed a 500-year preindustrial control (PI-CTRL) simulation forced by a perpetual climate forcing that corresponds to the year 1850 conditions and a 10-member ensemble of historical and future transient climate simulations.The CESM-HR configuration is based on an earlier CESM version, CESM1.3, with many additional modifications and improvements. CESM-HR uses a 0.25 degree grid in the atmosphere and land components and a 0.1 degree grid in the ocean and sea-ice components. The primary reason for using an older model version, instead of the latest CESM2, is that CESM2 does not support a high-resolution version per the decision by the CESM Scientific Steering Committee. The component models within CESM1.3 are the Community Atmosphere Model version 5 (CAM5; Neale et al., 2012), the Parallel Ocean Program version 2 (POP2; Danabasoglu et al., 2012; Smith et al., 2010), the Community Ice Code version 4 (CICE4; Hunke & Lipscomb, 2008), and the Community Land Model version 4 (CLM4; Lawrence et al., 2011).Here we release the nominal 1 degree low-resolution (LR) equivalent simulations based on the same CESM1.3 code base and using the same CAM5 Spectral Element (SE) dycore used in CESM-HR to permit an as-clean-as-possible comparison of the respective LR and HR simulations. CESM LR uses a nominal 1 degree grid in all its components. Citation: The two papers linked below are the most appropriate references for these simulations. To cite the dataset, use Chang et al. (2025). We ask that you also cite the dataset itself using the reference Castruccio et al. [https://rda.ucar.edu/datasets/d651030/citation/] (2024) in any documents or publications using these data. Chang et al. (2020) describes the initial CESM-HR simulations, including the 500-year pre-industrial control simulation and the first 250-year historical and future climate simulation from 1850 to 2100. It also introduces the corresponding CESM LR experiments. We would also appreciate receiving a copy of the relevant publications. This will help us to justify keeping the data freely available online in the future. Thank you!

Climate variations on seasonal-to-decadal (S2D) timescales can have enormous social, economic, and environmental impacts, making skillful predictions on these time scales an invaluable tool for policymakers and stakeholders. Such variations modulate the likelihood and intensity of extreme weather events including, tropical cyclones (TCs), heat waves, winter storms, atmospheric rivers (ARs), and floods, which have all been associated with (1) increases in human morbidity and mortality rates; (2) severe impacts on agriculture, energy use, and industrial activity; and (3) economic costs in the billions of dollars. Changes in prevailing climate patterns are also responsible for prolonged droughts, which can have profoundly negative effects on large segments of the world population. Enhancing our foreknowledge of climate variability on S2D time scales and understanding its influence on extreme weather events could help mitigate negative impacts on human and biological populations, making climate predictions an exceptionally important climate and social science frontier.Over the past six years, our research team consisting of scientists at Texas A and M University (TAMU) and the U.S. National Science Foundation National Center for Atmospheric Research (NSF NCAR) has made major breakthroughs in advancing high-resolution global climate modeling and prediction. We have completed an unprecedented 10-member ensemble of Community Earth System Model (CESM) historical and future climate simulations at a TC-permitting and ocean-eddy-rich resolution (hereafter simply referred to as CESM-HR). This CESM-HR ensemble was completed as part of our NSF-funded project entitled "Understanding the Role of MESoscale Atmosphere-Ocean Interactions in Seasonal-to-Decadal CLImate Prediction (MESACLIP)". This ensemble is particularly timely, following the April 2023 report entitled "Extreme Weather Risk in a Changing Climate: Enhancing Prediction and Protecting Communities" from the U.S. President's Council of Advisors on Science and Technology (PCAST). Indeed, this report made several recommendations on how climate science can support the provision of information about future risks from extreme weather and highlight the urgent need for high-resolution simulations to improve predictions of extreme weather events and guide risk management strategies. More specifically, the report recognized that high-resolution simulations, in the range of 10-25km horizontal resolution, would capture extreme events more accurately than typical low-resolution (approximately 100km) climate projections, and it goes on to recommend "a focused federal effort to provide estimates of the risk that a weather event of a given severity will occur in any location and year between now and mid-century". Our 10-member CESM-HR ensemble is able to meet some of the key aspects of this PCAST report.The CESM-HR configuration is based on an earlier CESM version, CESM1.3, with many additional modifications and improvements. CESM-HR uses a 0.25 degree grid in the atmosphere and land components and a 0.1 degree grid in the ocean and sea-ice components. The primary reason for using an older model version, instead of the latest CESM2, is that CESM2 does not support a high-resolution version per the decision by the CESM Scientific Steering Committee. The component models within CESM1.3 are the Community Atmosphere Model version 5 (CAM5; Neale et al. 2012), the Parallel Ocean Program version 2 (POP2; Danabasoglu et al. 2012; Smith et al. 2010), the Community Ice Code version 4 (CICE4; Hunke and Lipscomb, 2008), and the Community Land Model version 4 (CLM4; Lawrence et al. 2011).The CESM-HR ensemble experimental design follows a similar approach as the CESM LENS1 large ensemble. We started with a 500-year preindustrial control (PI-CTRL) simulation forced by a perpetual climate forcing that corresponds to the year 1850 conditions. The first ensemble member is branched at year 250 of the PI-CTRL simulation and then integrated forward from year 1850 to 2100 (Figure 1 [https://rda.ucar.edu/OS/web/datasets/d651029/docs/Figure1_RDA_d651029.png]). Ensemble members 2-10 are subsequently started from the year 1920 of ensemble member 1 and integrated forward to 2100 (Figure 1 [https://rda.ucar.edu/OS/web/datasets/d651029/docs/Figure1_RDA_d651029.png]). Spread in the ensemble is generated by applying round-off level perturbations in the atmospheric potential temperature initial conditions for members 2-10. All 10 members use the same specified external climate forcing. Following the CMIP5 protocol for the Coupled Model Intercomparison Project phase 5 (CMIP5) experiments, historical forcing is used from 1920 to 2005 followed by the representative concentration pathway 8.5 (RCP 8.5) forcing from 2006 to 2100. RCP 8.5 is a high-emissions scenario and is frequently referred to as the "business as usual" scenario. It refers to the concentration of carbon that delivers global warming at an average of 8.5 W/m^2 across the planet by 2100. All 10 members produce a warming of approximately 4.5K at the end of 2100 in response to the applied historical and RCP 8.5 external forcing (Figure 1 [https://rda.ucar.edu/OS/web/datasets/d651029/docs/Figure1_RDA_d651029.png]). The warming produced by CESM-HR is consistent with the warming from the standard low-resolution (approximately 1 degree) version of the model. The rate of warming simulated by CESM-HR over the observed period agrees very well with the observed rate of warming derived from the Goddard Institute for Space Studies (GISS) Surface Temperature Analysis (Figure 1 [https://rda.ucar.edu/OS/web/datasets/d651029/docs/Figure1_RDA_d651029.png]).Citation: The two papers linked below are the most appropriate references for the CESM-HR ensemble. To cite the dataset, use Chang et al. (2025). We ask that you also cite the dataset itself using the reference Castruccio et al [https://rda.ucar.edu/datasets/d651029/citation/]. (2024) in any documents or publications using these data. Chang et al. (2020) describes the initial CESM-HR simulations, including the 500-year pre- industrial control simulation and the first 250-year historical and future climate simulation from 1850 to 2100. We would also appreciate receiving a copy of the relevant publications. This will help us to justify keeping the data freely available online in the future. Thank you!

Current predictions and projections of future sea-level changes are based on Coupled Model Intercomparison Project (CMIP) class climate model simulations. Although this class of models is capable of simulating global sea-level rise and its basic spatial patterns, they are unable to robustly and accurately predict or project future regional and local sea-level changes because of their limitations in representing complex coastline and bathymetry features and regional ocean circulations with their coarse (approximately 100 km) horizontal resolutions. More specifically, sea-level changes within the Gulf of Mexico are closely linked to changes in the Loop Current and its eddies, which cannot be resolved by these CMIP-class models.To address this fundamental issue, we have completed two projections with the Community Earth System Model (CESM) at a Tropical Cyclone-permitting and ocean-mesoscale-eddy-rich horizontal resolution (hereafter simply referred to as CESM-HR). The CESM-HR configuration is based on an earlier CESM version, CESM1.3, with many additional modifications and improvements. CESM-HR uses a 0.25 degree grid in the atmosphere and land components and a 0.1 degree grid in the ocean and sea-ice components. The primary reason for using an older model version, instead of the latest CESM2, is that CESM2 does not support a high-resolution version per the decision by the CESM Scientific Steering Committee. The component models within CESM1.3 are the Community Atmosphere Model version 5 (CAM5; Neale et al., 2012), the Parallel Ocean Program version 2 (POP2; Danabasoglu et al., 2012; Smith et al., 2010), the Community Ice Code version 4 (CICE4; Hunke and Lipscomb, 2008), and the Community Land Model version 4 (CLM4; Lawrence et al., 2011).Following the protocol for the CMIP phase 5 (CMIP5) experiments, the representative concentration pathway 2.6 (RCP 2.6) and representative concentration pathway 4.5 (RCP 4.5) were used to force the model from 2006 to 2100. RCP 2.6 represents a pathway where greenhouse gas emissions are strongly reduced. This scenario is a so-called "peak" scenario, which means it shows a level of radiative forcing by greenhouse gas emissions peaking by mid-century then returning to 2.6 W/m^2 by 2100. RCP 4.5 represents a stabilization scenario, which means the radiative forcing level stabilizes at 4.5 W/m^2 before 2100 by employing of a range of technologies and strategies for reducing greenhouse gas emissions. This CESM-HR ensemble was completed as part of our National Academy of Sciences (NAS) funded project entitled "Improving Prediction and Projection of Gulf of Mexico Sea-Level Changes Using Eddy-Resolving Earth System Models (iPOGS)". This effort is complementary to the 10-member ensemble of CESM-HR historical and future (with RCP 8.5 forcing) climate simulations produced by our National Science Foundation (NSF) funded project entitled "Understanding the role of mesoscale atmosphere-ocean interactions in seasonal-to-decadal climate prediction (MESACLIP)". The RCP 2.6 and 4.5 simulation starts at the end of the member #3 of the 10-member ensemble of historical simulation from MESACLIP, enabling the exploration of future projections associated with varying levels of mitigation and future greenhouse gas emissions. For example, Figure 1 [https://rda.ucar.edu/OS/web/datasets/d651043/docs/global_steric_ts.png] shows the global-mean dynamical sea level (DSL) from simulations under different forcings. The stronger warming associated with the RCP 8.5 forcing results in an additional 10 cm rise in global-mean DSL by 2100 compared to that of the RCP 6.0 ensemble.Citation: The two papers linked below are the most appropriate references for the CESM-HR ensemble. To cite the dataset, use Chang et al. (2025). We ask that you also cite the dataset itself using the reference Castruccio et al. (2025) [https://rda.ucar.edu/datasets/d651043/citation/] in any documents or publications using these data. Chang et al. (2020) describes the initial CESM-HR simulations, including the 500-year pre- industrial control simulation and the first 250-year historical and future climate simulation from 1850 to 2100. We would also appreciate receiving a copy of the relevant publications. This will help us to justify keeping the data freely available online in the future. Thank you!

Climate variations on seasonal-to-decadal (S2D) timescales can have enormous social, economic, and environmental impacts, making skillful predictions on these time scales an invaluable tool for policymakers and stakeholders. Such variations modulate the likelihood and intensity of extreme weather events including, tropical cyclones (TCs), heat waves, winter storms, atmospheric rivers (ARs), and floods, which have all been associated with (1) increases in human morbidity and mortality rates; (2) severe impacts on agriculture, energy use, and industrial activity; and (3) economic costs in the billions of dollars. Changes in prevailing climate patterns are also responsible for prolonged droughts, which can have profoundly negative effects on large segments of the world population. Enhancing our foreknowledge of climate variability on S2D time scales and understanding its influence on extreme weather events could help mitigate negative impacts on human and biological populations, making climate predictions an exceptionally important climate and social science frontier.Over the past six years, our research team consisting of scientists at Texas A&M University (TAMU) and the U.S. National Science Foundation National Center for Atmospheric Research (NSF NCAR) has made major breakthroughs in advancing high-resolution global climate modeling and prediction. We have completed an unprecedented 10-member ensemble of Community Earth System Model (CESM) historical and future climate simulations at a tropical cyclone-permitting and ocean-eddy-rich resolution (hereafter simply referred to as CESM-HR). This CESM-HR ensemble was completed as part of our NSF-funded project entitled "Understanding the Role of MESoscale Atmosphere-Ocean Interactions in Seasonal-to-Decadal CLImate Prediction (MESACLIP)". This ensemble is particularly timely, following the April 2023 report entitled "Extreme Weather Risk in a Changing Climate: Enhancing Prediction and Protecting Communities" from the U.S. President's Council of Advisors on Science and Technology (PCAST). Indeed, this report made several recommendations on how climate science can support the provision of information about future risks from extreme weather and highlight the urgent need for high-resolution simulations to improve predictions of extreme weather events and guide risk management strategies. More specifically, the report recognized that high-resolution simulations, in the range of 10 to 25 km horizontal resolution, would capture extreme events more accurately than typical low-resolution (approximately 100 km) climate projections, and it goes on to recommend "a focused federal effort to provide estimates of the risk that a weather event of a given severity will occur in any location and year between now and mid-century". Our 10-member CESM-HR ensemble is able to meet some of the key aspects of this PCAST report.The CESM-HR configuration is based on an earlier CESM version, CESM1.3, with many additional modifications and improvements. CESM-HR uses a 0.25 degree grid in the atmosphere and land components and a 0.1 degree grid in the ocean and sea-ice components. The primary reason for using an older model version, instead of the latest CESM2, is that CESM2 does not support a high-resolution version per the decision by the CESM Scientific Steering Committee. The component models within CESM1.3 are the Community Atmosphere Model version 5 (CAM5; Neale et al., 2012), the Parallel Ocean Program version 2 (POP2; Danabasoglu et al., 2012; Smith et al., 2010), the Community Ice Code version 4 (CICE4; Hunke & Lipscomb, 2008), and the Community Land Model version 4 (CLM4; Lawrence et al., 2011).The CESM-HR ensemble experimental design follows a similar approach as the CESM LENS1 large ensemble. We started with a 500-year preindustrial control (PI-CTRL) simulation forced by a perpetual climate forcing that corresponds to the year 1850 conditions. The first ensemble member is branched at year 250 of the PI-CTRL simulation and then integrated forward from year 1850 to 2100 (Figure 1 [https://rda.ucar.edu/OS/web/datasets/d651009/docs/Figure1_RDA_d651009.png]). Ensemble members 2-10 are subsequently started from the year 1920 of ensemble member 1 and integrated forward to 2100 (Figure 1 [https://rda.ucar.edu/OS/web/datasets/d651009/docs/Figure1_RDA_d651009.png]). Spread in the ensemble is generated by applying round-off level perturbations in the atmospheric potential temperature initial conditions for members 2-10. All 10 members use the same specified external climate forcing. Following the CMIP5 protocol for the Coupled Model Intercomparison Project phase 5 (CMIP5) experiments, historical forcing is used from 1920 to 2005 followed by the representative concentration pathway 8.5 (RCP 8.5) forcing from 2006 to 2100. RCP 8.5 is a high-emissions scenario and is frequently referred to as the "business as usual" scenario. It refers to the concentration of carbon that delivers global warming at an average of 8.5 W/m^2 across the planet by 2100. All 10 members produce a warming of approximately 4.5K at the end of 2100 in response to the applied historical and RCP 8.5 external forcing (Figure 1 [https://rda.ucar.edu/OS/web/datasets/d651009/docs/Figure1_RDA_d651009.png]). The warming produced by CESM-HR is consistent with the warming from the standard low-resolution (approximately 1 degree) version of the model. The rate of warming simulated by CESM-HR over the observed period agrees very well with the observed rate of warming derived from the Goddard Institute for Space Studies (GISS) Surface Temperature Analysis (Figure 1 [https://rda.ucar.edu/OS/web/datasets/d651009/docs/Figure1_RDA_d651009.png]).Citation: The two papers linked below are the most appropriate references for the CESM-HR ensemble. To cite the dataset, use Chang et al. (2025). We ask that you also cite the dataset itself using the reference Castruccio et al [https://rda.ucar.edu/datasets/d651009/citation/]. (2024) in any documents or publications using these data. Chang et al. (2020) describes the initial CESM-HR simulations, including the 500-year pre- industrial control simulation and the first 250-year historical and future climate simulation from 1850 to 2100. We would also appreciate receiving a copy of the relevant publications. This will help us to justify keeping the data freely available online in the future. Thank you!

Current predictions and projections of future sea-level changes are based on Coupled Model Intercomparison Project (CMIP) class climate model simulations. Although this class of models is capable of simulating global sea-level rise and its basic spatial patterns, they are unable to robustly and accurately predict or project future regional and local sea-level changes because of their limitations in representing complex coastline and bathymetry features and regional ocean circulations with their coarse (approximately 100 km) horizontal resolutions. More specifically, sea-level changes within the Gulf of Mexico are closely linked to changes in the Loop Current and its eddies, which cannot be resolved by these CMIP-class models.To address this fundamental issue, we have completed a 10-member ensemble of simulations with the Community Earth System Model (CESM) at a Tropical Cyclone-permitting and ocean-mesoscale-eddy-rich horizontal resolution (hereafter simply referred to as CESM-HR). The CESM-HR configuration is based on an earlier CESM version, CESM1.3, with many additional modifications and improvements. CESM-HR uses a 0.25 degree grid in the atmosphere and land components and a 0.1 degree grid in the ocean and sea-ice components. The primary reason for using an older model version, instead of the latest CESM2, is that CESM2 does not support a high-resolution version per the decision by the CESM Scientific Steering Committee. The component models within CESM1.3 are the Community Atmosphere Model version 5 (CAM5; Neale et al., 2012), the Parallel Ocean Program version 2 (POP2; Danabasoglu et al., 2012; Smith et al., 2010), the Community Ice Code version 4 (CICE4; Hunke and Lipscomb, 2008), and the Community Land Model version 4 (CLM4; Lawrence et al., 2011).Following the protocol for the CMIP phase 5 (CMIP5) experiments, the representative concentration pathway 6.0 (RCP 6.0) was used to force the model from 2006 to 2100. RCP 6.0 represents a stabilization scenario, where the greenhouse gas emission rate is high initially, but total radiative forcing is stabilized after 2100 through the use of various technologies and strategies for reducing emissions. In this scenario, the specified amount of carbon concentration results in an average global radiative forcing increase of 6.0 W/m^2 by 2100. This CESM-HR ensemble was completed as part of our National Academy of Sciences (NAS) funded project entitled "Improving Prediction and Projection of Gulf of Mexico Sea-Level Changes Using Eddy-Resolving Earth System Models (iPOGS)". This effort is complementary to the 10-member ensemble of CESM-HR historical and future (with RCP 8.5 forcing) climate simulations produced by our National Science Foundation (NSF) funded project entitled "Understanding the role of mesoscale atmosphere-ocean interactions in seasonal-to-decadal climate prediction (MESACLIP)". Each RCP 6.0 simulation starts at the end of the corresponding historical simulation from MESACLIP, enabling the exploration of future projections associated with varying levels of mitigation and future greenhouse gas emissions. For example, Figure 1 [https://rda.ucar.edu/OS/web/datasets/d651008/docs/Figure1_RDA_d651008.png] shows the global-mean dynamical sea level (DSL) from simulations under different forcings. The stronger warming associated with the RCP 8.5 forcing results in an additional 10 cm rise in global-mean DSL by 2100 compared to that of the RCP 6.0 ensemble.Citation: The two papers linked below are the most appropriate references for the CESM-HR ensemble. To cite the dataset, use Chang et al. (2025). We ask that you also cite the dataset itself using the reference Castruccio et al [https://rda.ucar.edu/datasets/d651008/citation/]. (2024) in any documents or publications using these data. Chang et al. (2020) describes the initial CESM-HR simulations, including the 500-year pre- industrial control simulation and the first 250-year historical and future climate simulation from 1850 to 2100. We would also appreciate receiving a copy of the relevant publications. This will help us to justify keeping the data freely available online in the future. Thank you!

Climate variations on seasonal-to-decadal (S2D) timescales can have enormous social, economic, and environmental impacts, making skillful predictions on these time scales an invaluable tool for policymakers and stakeholders. Such variations modulate the likelihood and intensity of extreme weather events including, tropical cyclones (TCs), heat waves, winter storms, atmospheric rivers (ARs), and floods, which have all been associated with (1) increases in human morbidity and mortality rates; (2) severe impacts on agriculture, energy use, and industrial activity; and (3) economic costs in the billions of dollars. Changes in prevailing climate patterns are also responsible for prolonged droughts, which can have profoundly negative effects on large segments of the world population. Enhancing our foreknowledge of climate variability on S2D time scales and understanding its influence on extreme weather events could help mitigate negative impacts on human and biological populations, making climate predictions an exceptionally important climate and social science frontier.Over the past six years, our research team consisting of scientists at Texas A and M University (TAMU) and the U.S. National Science Foundation National Center for Atmospheric Research (NSF NCAR) has made major breakthroughs in advancing high-resolution global climate modeling and prediction. We have completed an unprecedented 10-member ensemble of Community Earth System Model (CESM) historical and future climate simulations at a TC-permitting and ocean-eddy-rich resolution (hereafter simply referred to as CESM-HR). This CESM-HR ensemble was completed as part of our NSF-funded project entitled "Understanding the Role of MESoscale Atmosphere-Ocean Interactions in Seasonal-to-Decadal CLImate Prediction (MESACLIP)". This ensemble is particularly timely, following the April 2023 report entitled "Extreme Weather Risk in a Changing Climate: Enhancing Prediction and Protecting Communities" from the U.S. President's Council of Advisors on Science and Technology (PCAST). Indeed, this report made several recommendations on how climate science can support the provision of information about future risks from extreme weather and highlight the urgent need for high-resolution simulations to improve predictions of extreme weather events and guide risk management strategies. More specifically, the report recognized that high-resolution simulations, in the range of 10-25km horizontal resolution, would capture extreme events more accurately than typical low-resolution (approximately 100km) climate projections, and it goes on to recommend "a focused federal effort to provide estimates of the risk that a weather event of a given severity will occur in any location and year between now and mid-century". Our 10-member CESM-HR ensemble is able to meet some of the key aspects of this PCAST report.The CESM-HR configuration is based on an earlier CESM version, CESM1.3, with many additional modifications and improvements. CESM-HR uses a 0.25 degree grid in the atmosphere and land components and a 0.1 degree grid in the ocean and sea-ice components. The primary reason for using an older model version, instead of the latest CESM2, is that CESM2 does not support a high-resolution version per the decision by the CESM Scientific Steering Committee. The component models within CESM1.3 are the Community Atmosphere Model version 5 (CAM5; Neale et al. 2012), the Parallel Ocean Program version 2 (POP2; Danabasoglu et al. 2012; Smith et al. 2010), the Community Ice Code version 4 (CICE4; Hunke and Lipscomb, 2008), and the Community Land Model version 4 (CLM4; Lawrence et al. 2011).The CESM-HR ensemble experimental design follows a similar approach as the CESM LENS1 large ensemble. We started with a 500-year preindustrial control (PI-CTRL) simulation forced by a perpetual climate forcing that corresponds to the year 1850 conditions. The first ensemble member is branched at year 250 of the PI-CTRL simulation and then integrated forward from year 1850 to 2100 (Figure 1 [https://rda.ucar.edu/OS/web/datasets/d651007/docs/Figure1_RDA_d651007.png]). Ensemble members 2-10 are subsequently started from the year 1920 of ensemble member 1 and integrated forward to 2100 (Figure 1 [https://rda.ucar.edu/OS/web/datasets/d651007/docs/Figure1_RDA_d651007.png]). Spread in the ensemble is generated by applying round-off level perturbations in the atmospheric potential temperature initial conditions for members 2-10. All 10 members use the same specified external climate forcing. Following the CMIP5 protocol for the Coupled Model Intercomparison Project phase 5 (CMIP5) experiments, historical forcing is used from 1920 to 2005 followed by the representative concentration pathway 8.5 (RCP 8.5) forcing from 2006 to 2100. RCP 8.5 is a high-emissions scenario and is frequently referred to as the "business as usual" scenario. It refers to the concentration of carbon that delivers global warming at an average of 8.5 W/m^2 across the planet by 2100. All 10 members produce a warming of approximately 4.5K at the end of 2100 in response to the applied historical and RCP 8.5 external forcing (Figure 1 [https://rda.ucar.edu/OS/web/datasets/d651007/docs/Figure1_RDA_d651007.png]). The warming produced by CESM-HR is consistent with the warming from the standard low-resolution (approximately 1 degree) version of the model. The rate of warming simulated by CESM-HR over the observed period agrees very well with the observed rate of warming derived from the Goddard Institute for Space Studies (GISS) Surface Temperature Analysis (Figure 1 [https://rda.ucar.edu/OS/web/datasets/d651007/docs/Figure1_RDA_d651007.png]).Citation: The two papers linked below are the most appropriate references for the CESM-HR ensemble. To cite the dataset, use Chang et al. (2025). We ask that you also cite the dataset itself using the reference Castruccio et al [https://rda.ucar.edu/datasets/d651007/citation/]. (2024) in any documents or publications using these data. Chang et al. (2020) describes the initial CESM-HR simulations, including the 500-year pre- industrial control simulation and the first 250-year historical and future climate simulation from 1850 to 2100. We would also appreciate receiving a copy of the relevant publications. This will help us to justify keeping the data freely available online in the future. Thank you!

Atmospheric river detection tool (ARDT) catalogues, source data, and ocean daily used for Shields, Li et al., 2024 Communications Earth and Environment entitled "Response of the upper ocean to northeast Pacific atmospheric rivers under climate change".Datasets include: (1) Three ARDTs (Shields/Kiehl, Mundhenk/Nardi, IPART) catalogues. AR detection data includes timestamps and geographic location for AR landfalls where atmospheric rivers intersect the North American coastline (1960-2100). (2) Source AR tracking data from CESM1.3 High Resolution model (25km atmosphere/land, roughly 0.1 ocean/ice) historical and RCP8.5 simulations 1960-2100, 6 hourly intervals. Note for ARDT catalogues, timestamps and latitude can be matched to the source data for full AR spatial footprints and was originally produced under the iHESP project and now part of MESACLIP. (3) Ocean daily data use for all results in Shields, Hui, et al. 2024. including SST, SSH, HXML, EVAP, SEN, PREC, SSS (1920-2100). Files are NetCDF format.

2017 mangrove forest extent mapping data products at 20m resolution for 11 countries in West Africa created using a combination of Sentinel-2 and Sentinel-1 satellite imagery (Senegal, The Gambia, Guinea Bissau, Guinea, Sierra Leone, Liberia, Cote D’Ivoire, Ghana, Togo, Benin, and Nigeria). This dataset includes 9 GeoTIFF files (Senegal and The Gambia combined, Togo and Benin combined).

Evaluation of the correction of the reduplicate biological samples. Table S2. Known miRNAs identified from stamen and pistil libraries. Table S3. Differentially expressed known and novel miRNAs between stamen and pistil CK-2d libraries. Table S4. Novel miRNAs identified from stamen and pistil libraries. Table S5. Differentially expressed miRNAs shared between stamen and pistil under heat stress condition. Table S6. Stamen specific differentially expressed miRNAs. Table S7. Pistil specific differentially expressed miRNAs. Table S8. Target genes of differentially expressed miRNAs in stamen. Table S9. Target genes of differentially expressed miRNAs in pistil. Table S10. List of primers used for qRT-PCR analysis. Table S11. List of primers used for RLM-5â ˛ RACE analysis. (XLS 299Â kb)

Evaluation of the correction of the reduplicate biological samples. Table S2. Known miRNAs identified from stamen and pistil libraries. Table S3. Differentially expressed known and novel miRNAs between stamen and pistil CK-2d libraries. Table S4. Novel miRNAs identified from stamen and pistil libraries. Table S5. Differentially expressed miRNAs shared between stamen and pistil under heat stress condition. Table S6. Stamen specific differentially expressed miRNAs. Table S7. Pistil specific differentially expressed miRNAs. Table S8. Target genes of differentially expressed miRNAs in stamen. Table S9. Target genes of differentially expressed miRNAs in pistil. Table S10. List of primers used for qRT-PCR analysis. Table S11. List of primers used for RLM-5â ˛ RACE analysis. (XLS 299Â kb)