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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Future Projections of the El Niño—Southern Oscillation and Tropical Pacific Mean State in CMIP6

Abstract The El Niño—Southern Oscillation (ENSO) is an important mode of tropical Pacific atmosphere‐ocean variability that drives teleconnections with weather and climate globally. However, prior studies using state‐of‐the‐art climate models lack consensus regarding future ENSO projections and are often impacted by tropical Pacific sea‐surface temperature (SST) biases. We used 173 simulations from 29 climate models participating in the Coupled Model Intercomparison Project, version 6 (CMIP6) to analyze model biases and future ENSO projections. We analyzed two ENSO indices, namely the ENSO Longitude Index (ELI), which measures zonal shifts in tropical Pacific deep convection and accounts for changes in background SST, and the Niño 3.4 index, which measures SST anomalies in the central‐eastern equatorial Pacific. We found that the warm eastern tropical‐subtropical Pacific SST bias typical of previous generations of climate models persists into many of the CMIP6 models. Future projections of ENSO shift toward more El Niño‐like conditions based on ELI in 48% of simulations and 55% of models, in association with a future weakening of the zonal equatorial Pacific SST gradient. On the other hand, none of the models project a significant shift toward La Niña‐like conditions. The standard deviation of the Niño 3.4 index indicates a lack of consensus on whether an increase or decrease in ENSO variability is expected in the future. Finally, we found a possible relationship between historical SST and low‐level cloud cover biases in the ENSO region and future changes in ELI; however, this result may be impacted by limitations in data availability.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

A spatial evaluation of Arctic sea ice and regional limitations in CMIP6 historical simulations

The Arctic sea ice response to a warming climate is assessed in a subset of models participating in Phase 6 of the Coupled Model Intercomparison Project (CMIP6), using several metrics in comparison with satellite observations and results from the Pan-Arctic Ice Ocean Modeling and Assimilation System and the Regional Arctic System Model. Our study examines the historical representation of sea ice extent, volume, and thickness using spatial analysis metrics, such as the integrated ice-edge error, Brier score, and Spatial Probability Score. We find that the CMIP6 multi-model mean captures the mean annual cycle and 1979-2014 sea ice trends remarkably well. However, individual models experience a wide range of uncertainty in the spatial distribution of sea ice when compared against satellite measurements and reanalysis data. Our metrics expose common and individual regional model biases, which sea ice temporal analyses alone do not capture. We identify large ice edge and ice thickness errors in Arctic sub-regions, implying possible model specific limitations in or lack of representation of some key physical processes. We postulate that many of them could be related to the oceanic forcing, especially in the marginal and shelf seas, where seasonal sea ice changes are not adequately simulated. We therefore conclude that an individual model’s ability to represent the observed/reanalysis spatial distribution still remains a challenge. We propose the spatial analysis metrics as useful tools to diagnose model limitations, narrow down possible processes affecting them, and guide future model improvements critical to the representation and projections of Arctic climate change.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Blocking Simulations in GFDL GCMs for CMIP5 and CMIP6

Abstract The frequency of atmospheric blocking has been largely underestimated by general circulation models (GCMs) participating in the Coupled Model Intercomparison Project (CMIP). Errors in the onset, persistence, barotropicity, geographical preference, seasonality, intensity, and moving speed of global blocking were diagnosed in 10 Geophysical Fluid Dynamics Laboratory (GFDL) GCMs for recent CMIP5 and CMIP6 using a detection approach that combines zonal eddies and the reversal of zonal winds. The blocking frequency, similar at 500 and 250 hPa, is underestimated by 50% in the Atlantic–Europe region during December–February but is overestimated by 60% in the Pacific–North America region during that season and by 70% in the southwest Pacific during July–August. These blocking biases at 500 hPa were investigated in the five CMIP6 models that showed improvements over the CMIP5 versions. The Atlantic–Europe underestimate corresponds to lower instantaneous blocking rates, lower persistent blocking rates, and higher persistent stationary ridge rates; the number of blocks with a duration of 4–5 days is only 40%–65% of that in observations. In contrast, the overestimate consists of excessive blocks with a duration longer than 12 days in the Pacific–North America and up to twice as many 4–6-day events in the southwest Pacific. Simulated December–February blocks up to 12 days in the Pacific–North America region tend to be stronger and to move more slowly than those in observations. Diagnostic sensitivity tests indicated that the zonal mean and zonal eddy components of the mean state play a key role, as replacing each with that of observations substantially reduced many of the outstanding biases in these GCMs.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

The Physics behind Precipitation Onset Bias in CMIP6 Models: The Pseudo-Entrainment Diagnostic and Trade-Offs between Lapse Rate and Humidity

Conditional instability and the buoyancy of plumes drive moist convection but have a variety of representations in model convective schemes. Vertical thermodynamic structure information from Atmospheric Radiation Measurement (ARM) sites and reanalysis (ERA5), satellite-derived precipitation (TRMM3b42), and diagnostics relevant for plume buoyancy are used to assess climate models. Previous work has shown that CMIP6 models represent moist convective processes more accurately than their CMIP5 counterparts. However, certain biases in convective onset remain pervasive among generations of CMIP modeling efforts. Here we diagnose these biases in a cohort of nine CMIP6 models with sub-daily output, assessing conditional instability in profiles of equivalent potential temperature θ e and saturation equivalent potential temperature θ es in comparison to a plume model with different mixing assumptions. Most models capture qualitative aspects of the θ es vertical structure, including a substantial decrease with height in the lower free troposphere associated with the entrainment of subsaturated air. We define a “pseudo-entrainment” diagnostic that combines subsaturation and a θ es measure of conditional instability similar to what entrainment would produce under the small-buoyancy approximation. This captures the trade-off between larger θ es lapse rates (entrainment of dry air) and small subsaturation (permits positive buoyancy despite high entrainment). This pseudo-entrainment diagnostic is also a reasonable indicator of the critical value of integrated buoyancy for precipitation onset. Models with poor θ e /θ es structure (those using variants of the Tiedtke Scheme) or low entrainment runs of CAM5, and models with low subsaturation, such as NASA-GISS, lie outside the observational range in this diagnostic.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Biophysical Impact of Land-Use and Land-Cover Change on Subgrid Temperature in CMIP6 Models

In this study, we investigate the air temperature response to land-use and land-cover change (LULCC; cropland expansion and deforestation) using subgrid land model output generated by a set of CMIP6 model simulations. Our study is motivated by the fact that ongoing land-use activities are occurring at local scales, typically significantly smaller than the resolvable scale of a grid cell in Earth system models. It aims to explore the potential for a multimodel approach to better characterize LULCC local climatic effects. On an annual scale, the CMIP6 models are in general agreement that croplands are warmer than primary and secondary land (psl; mainly forests, grasslands, and bare ground) in the tropics and cooler in the mid–high latitudes, except for one model. The transition from warming to cooling occurs at approximately 40°N. Although the surface heating potential, which combines albedo and latent heat flux effects, can explain reasonably well the zonal mean latitudinal subgrid temperature variations between crop and psl tiles in the historical simulations, it does not provide a good prediction on subgrid temperature for other land tile configurations (crop vs forest; grass vs forest) under Shared Socioeconomic Pathway 5–8.5 (SSP5–8.5) forcing scenarios. A subset of simulations with the CESM2 model reveals that latitudinal subgrid temperature variation is positively related to variation in net surface shortwave radiation and negatively related to variation in the surface energy redistribution factor, with a dominant role from the latter south of 30°N. We suggest that this emergent relationship can be used to benchmark the performance of land surface parameterizations and for prediction of local temperature response to LULCC.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

High Values of the Arctic Amplification in Early Decades of the 21st Century: Causes of Discrepancy by CMIP6 Models Between Observation and Simulation

Arctic Amplification (AA) in the first decade of the 21st century has reached values between 4 and 5, with a subsequent decrease to current values of about 3.6, while the value was from 2 to 3 during the twentieth century. The ensemble mean of the CMIP6 models has difficulty in reproducing the recently observed high values of the AA. In this report, we identify the main reason for this difficulty to be the CMIP6 models overestimate of the mean global temperature trend since about 1990. The largest values of the AA are observed in winter and spring. A sharp AA peak in 1987 spring was caused by a peak in the Arctic temperature trend occurring at the same time as a dip in the trend of mean global temperature. The winter AA has increased almost monotonically since 1990. Dividing the AA between the Arctic land and ocean areas shows that the ocean area makes a larger contribution to the AA. Our future projection of the AA suggests an increasing AA for about the next decade, followed by a slow decrease to about 3.5 in the 2050s.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

CMIP6-based Multi-model Hydroclimate Projection over the Conterminous US

We present a suite of high-resolution downscaled hydro-climate projections over the conterminous United States (CONUS) based on a six-member General Climate Model (GCM) ensemble from the Coupled Models Intercomparison Project phase 6 (CMIP6). The CMIP6 GCMs are downscaled using two different downscaling approaches (statistical-based DBCCA & dynamical-based RegCM) based on two meteorological reference observations (Daymet & Livneh), and then fed to two calibrated hydrologic models (VIC & PRMS) to simulate projected future hydrologic responses. Each ensemble member covers 1980–2019 in the historic period and 2020–2059 in the near-term future period under the high-end (SSP585) emission scenario. Major variables such as daily maximum temperature (tmax), daily minimum temperature (tmin), daily total precipitation (prcp), daily average wind speed (wind), and daily total runoff (runoff) at 1/24° (~4 km) spatial resolution across the CONUS are provided through this data portal. This dataset is derived to support the SECURE Water Act Section 9505 Assessment for the US Department of Energy (DOE) Water Power Technologies Office (WPTO). Further details of this dataset can be referred to Kao et al. (2022) and Rastogi et al. (2022).

13 HYDRO ENERGY↗
DOE OSTI2025

ILAMBv2.7 benchmarking results comparing E3SMv2.1 land-atmosphere coupled (BGCv2LNDATM) and stand alone land (ELM) simulations with CMIP6 emission driven historical simulations

This dataset contains land model benchmarking results for the Energy Exascale Earth System Model version 2.1 (E3SMv2.1), including outputs from both coupled biogeochemistry simulations and stand-alone land model simulations. These results are compared against several emission-driven historical simulations from the Coupled Model Intercomparison Project Phase 6 (CMIP6). Benchmarking was conducted using the International Land Model Benchmarking (ILAMB) package, version 2.7 (ILAMBv2.7). CMIP6 model outputs were sourced from the Earth System Grid Federation (ESGF), while the E3SMv2.1 results were derived from raw model outputs. These outputs underwent processing steps such as time serialization, conservative regridding, and data standardization to ensure comparability. For spatial interpolation, the Earth System Modeling Framework (ESMF) tool, ESMF_RegridWeightGen, was employed to generate regridding weights, enabling the transformation of E3SM’s native cubed-sphere grid to a regular latitude-longitude grid.

Feng, Sha [PNNL]↗
DOE OSTI2021

Climate model projections from the Scenario Model Intercomparison Project (ScenarioMIP) of CMIP6

Abstract. The Scenario Model Intercomparison Project (ScenarioMIP) defines and coordinates the main set of future climate projections, based on concentration-driven simulations, within the Coupled Model Intercomparison Project phase 6 (CMIP6). This paper presents a range of its outcomes by synthesizing results from the participating global coupled Earth system models. We limit our scope to the analysis of strictly geophysical outcomes: mainly global averages and spatial patterns of change for surface air temperature and precipitation. We also compare CMIP6 projections to CMIP5 results, especially for those scenarios that were designed to provide continuity across the CMIP phases, at the same time highlighting important differences in forcing composition, as well as in results. The range of future temperature and precipitation changes by the end of the century (2081–2100) encompassing the Tier 1 experiments based on the Shared Socioeconomic Pathway (SSP) scenarios (SSP1-2.6, SSP2-4.5, SSP3-7.0 and SSP5-8.5) and SSP1-1.9 spans a larger range of outcomes compared to CMIP5, due to higher warming (by close to 1.5 ∘C) reached at the upper end of the 5 %–95 % envelope of the highest scenario (SSP5-8.5). This is due to both the wider range of radiative forcing that the new scenarios cover and the higher climate sensitivities in some of the new models compared to their CMIP5 predecessors. Spatial patterns of change for temperature and precipitation averaged over models and scenarios have familiar features, and an analysis of their variations confirms model structural differences to be the dominant source of uncertainty. Models also differ with respect to the size and evolution of internal variability as measured by individual models' initial condition ensemble spreads, according to a set of initial condition ensemble simulations available under SSP3-7.0. These experiments suggest a tendency for internal variability to decrease along the course of the century in this scenario, a result that will benefit from further analysis over a larger set of models. Benefits of mitigation, all else being equal in terms of societal drivers, appear clearly when comparing scenarios developed under the same SSP but to which different degrees of mitigation have been applied. It is also found that a mild overshoot in temperature of a few decades around mid-century, as represented in SSP5-3.4OS, does not affect the end outcome of temperature and precipitation changes by 2100, which return to the same levels as those reached by the gradually increasing SSP4-3.4 (not erasing the possibility, however, that other aspects of the system may not be as easily reversible). Central estimates of the time at which the ensemble means of the different scenarios reach a given warming level might be biased by the inclusion of models that have shown faster warming in the historical period than the observed. Those estimates show all scenarios reaching 1.5 ∘C of warming compared to the 1850–1900 baseline in the second half of the current decade, with the time span between slow and fast warming covering between 20 and 27 years from present. The warming level of 2 ∘C of warming is reached as early as 2039 by the ensemble mean under SSP5-8.5 but as late as the mid-2060s under SSP1-2.6. The highest warming level considered (5 ∘C) is reached by the ensemble mean only under SSP5-8.5 and not until the mid-2090s.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Global and northern-high-latitude net ecosystem production in the 21st century from CMIP6 experiments

Climate warming is accelerating the changes in the global terrestrial ecosystems and particularly those in the northern high latitudes (NHLs; poleward of 50° N) and rendering the land–atmosphere carbon exchange highly uncertain. The Coupled Model Intercomparison Project Phase 6 (CMIP6) employs the most updated climate models to estimate terrestrial ecosystem carbon dynamics driven by a new set of socioeconomic and climate change pathways. By analyzing the future (2015–2100) carbon fluxes estimated by 10 CMIP6 models, we quantitatively evaluated the projected magnitudes, trends, and uncertainties in the global and NHL carbon fluxes under four scenarios plus the role of NHLs in the global terrestrial ecosystem carbon dynamics. Overall, the models suggest that the global and NHL terrestrial ecosystems will be consistent carbon sinks in the future, and the magnitude of the carbon sinks is projected to be larger under scenarios with higher radiative forcing. By the end of this century, the models on average estimate the NHL net ecosystem productivity (NEP) as 0.54 ± 0.77, 1.01 ± 0.98, 0.97 ± 1.62, and 1.05 ± 1.83 Pg C yr –1 under SSP126, SSP245, SSP370, and SSP585, respectively. The uncertainties are not substantially reduced compared with earlier results, e.g., the Coupled Climate–Carbon Cycle Model Intercomparison Project (C4MIP). Although NHLs contribute a small fraction of the global carbon sink (~13 %), the relative uncertainties in NHL NEP are much larger than the global level. Our results provide insights into future carbon flux evolutions under future scenarios and highlight the urgent need to constrain the large uncertainties associated with model projections for making better climate mitigation strategies.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Regime-oriented causal model evaluation of Atlantic–Pacific teleconnections in CMIP6

The climate system and its spatio-temporal changes are strongly affected by modes of long-term internal variability, like the Pacific decadal variability (PDV) and the Atlantic multidecadal variability (AMV). As they alternate between warm and cold phases, the interplay between PDV and AMV varies over decadal to multidecadal timescales. Here, we use a causal discovery method to derive fingerprints in the Atlantic–Pacific interactions and to investigate their phase-dependent changes. Dependent on the phases of PDV and AMV, different regimes with characteristic causal fingerprints are identified in reanalyses in a first step. In a second step, a regime-oriented causal model evaluation is performed to evaluate the ability of models participating in the Coupled Model Intercomparison Project Phase 6 (CMIP6) in representing the observed changing interactions between PDV, AMV and their extra-tropical teleconnections. The causal graphs obtained from reanalyses detect a direct opposite-sign response from AMV to PDV when analyzing the complete 1900–2014 period and during several defined regimes within that period, for example, when AMV is going through its negative (cold) phase. Reanalyses also demonstrate a same-sign response from PDV to AMV during the cold phase of PDV. Historical CMIP6 simulations exhibit varying skill in simulating the observed causal patterns. Generally, large-ensemble (LE) simulations showed better network similarity when PDV and AMV were out of phase compared to other regimes. Also, the two largest ensembles (in terms of number of members) were found to contain realizations with similar causal fingerprints to observations. For most regimes, these same models showed higher network similarity when compared to each other. This work shows how causal discovery on LEs complements the available diagnostics and statistical metrics of climate variability to provide a powerful tool for climate model evaluation.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Observations for Model Intercomparison Project (Obs4MIPs): status for CMIP6

The Observations for Model Intercomparison Project (Obs4MIPs) was initiated in 2010 to facilitate the use of observations in climate model evaluation and research, with a particular target being the Coupled Model Intercomparison Project (CMIP), a major initiative of the World Climate Research Programme (WCRP). To this end, Obs4MIPs (1) targets observed variables that can be compared to CMIP model variables; (2) utilizes dataset formatting specifications and metadata requirements closely aligned with CMIP model output; (3) provides brief technical documentation for each dataset, designed for nonexperts and tailored towards relevance for model evaluation, including information on uncertainty, dataset merits, and limitations; and (4) disseminates the data through the Earth System Grid Federation (ESGF) platforms, making the observations searchable and accessible via the same portals as the model output. Taken together, these characteristics of the organization and structure of obs4MIPs should entice a more diverse community of researchers to engage in the comparison of model output with observations and to contribute to a more comprehensive evaluation of the climate models. At present, the number of obs4MIPs datasets has grown to about 80; many are undergoing updates, with another 20 or so in preparation, and more than 100 are proposed and under consideration. A partial list of current global satellite-based datasets includes humidity and temperature profiles; a wide range of cloud and aerosol observations; ocean surface wind, temperature, height, and sea ice fraction; surface and top-of-atmosphere longwave and shortwave radiation; and ozone (O 3 ), methane (CH 4 ), and carbon dioxide (CO 2 ) products. A partial list of proposed products expected to be useful in analyzing CMIP6 results includes the following: alternative products for the above quantities, additional products for ocean surface flux and chlorophyll products, a number of vegetation products (e.g., FAPAR, LAI, burned area fraction), ice sheet mass and height, carbon monoxide (CO), and nitrogen dioxide (NO 2 ). While most existing obs4MIPs datasets consist of monthly-mean gridded data over the global domain, products with higher time resolution (e.g., daily) and/or regional products are now receiving more attention. Along with an increasing number of datasets, obs4MIPs has implemented a number of capability upgrades including (1) an updated obs4MIPs data specifications document that provides additional search facets and generally improves congruence with CMIP6 specifications for model datasets, (2) a set of six easily understood indicators that help guide users as to a dataset's maturity and suitability for application, and (3) an option to supply supplemental information about a dataset beyond what can be found in the standard metadata. With the maturation of the obs4MIPs framework, the dataset inclusion process, and the dataset formatting guidelines and resources, the scope of the observations being considered is expected to grow to include gridded in situ datasets as well as datasets with a regional focus, and the ultimate intent is to judiciously expand this scope to any observation dataset that has applicability for evaluation of the types of Earth system models used in CMIP.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Harmonization of global land use change and management for the period 850–2100 (LUH2) for CMIP6

Abstract. Human land use activities have resulted in large changes to the biogeochemical and biophysical properties of the Earth's surface, with consequences for climate and other ecosystem services. In the future, land use activities are likely to expand and/or intensify further to meet growing demands for food, fiber, and energy. As part of the World Climate Research Program Coupled Model Intercomparison Project (CMIP6), the international community has developed the next generation of advanced Earth system models (ESMs) to estimate the combined effects of human activities (e.g., land use and fossil fuel emissions) on the carbon–climate system. A new set of historical data based on the History of the Global Environment database (HYDE), and multiple alternative scenarios of the future (2015–2100) from Integrated Assessment Model (IAM) teams, is required as input for these models. With most ESM simulations for CMIP6 now completed, it is important to document the land use patterns used by those simulations. Here we present results from the Land-Use Harmonization 2 (LUH2) project, which smoothly connects updated historical reconstructions of land use with eight new future projections in the format required for ESMs. The harmonization strategy estimates the fractional land use patterns, underlying land use transitions, key agricultural management information, and resulting secondary lands annually, while minimizing the differences between the end of the historical reconstruction and IAM initial conditions and preserving changes depicted by the IAMs in the future. The new approach builds on a similar effort from CMIP5 and is now provided at higher resolution (0.25∘×0.25∘) over a longer time domain (850–2100, with extensions to 2300) with more detail (including multiple crop and pasture types and associated management practices) using more input datasets (including Landsat remote sensing data) and updated algorithms (wood harvest and shifting cultivation); it is assessed via a new diagnostic package. The new LUH2 products contain > 50 times the information content of the datasets used in CMIP5 and are designed to enable new and improved estimates of the combined effects of land use on the global carbon–climate system.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Description of historical and future projection simulations by the global coupled E3SMv1.0 model as used in CMIP6

Abstract. This paper documents the experimental setup and general features of the coupled historical and future climate simulations with the first version of the US Department of Energy (DOE) Energy Exascale Earth System Model (E3SMv1.0). The future projected climate characteristics of E3SMv1.0 at the highest emission scenario (SSP5-8.5) designed in the Scenario Model Intercomparison Project (ScenarioMIP) and the SSP5-8.5 greenhouse gas (GHG) only forcing experiment are analyzed with a focus on regional responses of atmosphere, ocean, sea ice, and land. Due to its high equilibrium climate sensitivity (ECS of 5.3 K), E3SMv1.0 is one of the Coupled Model Intercomparison Project phase 6 (CMIP6) models with the largest surface warming by the end of the 21st century under the high-emission SSP5-8.5 scenario. The global mean precipitation change is highly correlated with the global temperature change, while the spatial pattern of the change in runoff is consistent with the precipitation changes. The oceanic mixed layer generally shoals throughout the global ocean. The annual mean Atlantic meridional overturning circulation (AMOC) is overly weak with a slower change from ∼ 11 to ∼ 6 Sv (Sverdrup) relative to other CMIP6 models. The sea ice, especially in the Northern Hemisphere, decreases rapidly with large seasonal variability. We detect a significant polar amplification in E3SMv1.0 from the atmosphere, ocean, and sea ice. Comparing the SSP5-8.5 all-forcing experiment with the GHG-only experiment, we find that the unmasking of the aerosol effects due to the decline of the aerosol loading in the future projection period causes transient accelerated warming in the all-forcing experiment in the first half of the 21st century. While the oceanic climate response is mainly controlled by the GHG forcing, the land runoff response is impacted primarily by forcings other than GHG over certain regions, e.g., southern North America, southern Africa, central Africa, and eastern Asia. However, the importance of the GHG forcing on the land runoff changes grows in the future climate projection period compared to the historical period.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Global variance decomposition of downscaled and bias-corrected CMIP6 climate projections

This dataset provides the results of a global variance decomposition of downscaled and bias-corrected CMIP6 climate projections. The total projection variance for a set of climate metrics is partitioned into contributions from: scenario uncertainty, model/GCM uncertainty, downscaling and bias-correction uncertainty, and interannual variability. The contribution from each source is expressed as a percentage of the total variance. Seven climate metrics are analyzed: Annual average temperature (avg_tas.nc) Annual total precipitation (tot_pr.nc) Annual maximum of daily maximum temperature (max_tasmax.nc) Annual maximum 1-day precipitation (max_pr.nc) Annual number of extremely hot days (hot_days.nc) Annual number of extremely wet days (wet_days.nc) Annual number of dry days (dry_days.nc) Extremely hot/wet days are defined to occur when temperature/precipitation exceeds the local 99th percentile defined over 1980-2014. Dry days are defined to occur when daily precipitation is less than 1mm. all_metrics_timesliced.nc gives the results for all metrics averaged over three 20-year periods: 2020-2039, 2050-2069, 2080-2099. For more details on the methods, see: Lafferty & Sriver, Downscaling and bias-correction contribute considerable uncertainty to local climate projections in CMIP6, npj Climate & Atmospheric Science (2023) An interactive visualization of this data can be found at: https://lafferty-sriver-2023-downscaling-uncertainty.msdlive.org

Lafferty, David↗
DOE OSTI2023

Towards understanding the robust strengthening of ENSO and more frequent extreme El Niño events in CMIP6 global warming simulations

The El Niño Southern Oscillation (ENSO) has profound impacts on weather patterns across the globe, yet there is no consensus on its response to global warming. Several modelling studies find a stronger ENSO in global warming scenarios, while other studies suggest ENSO weakening. Using a broad range of models from the Coupled Model Intercomparison Project phase 6 (CMIP6) and four types of warming experiments, here we show that the majority of the models predict a stronger ENSO by century-end in Shared Social Pathway (SSP) experiments, and in idealized 1pctCO 2 and abrupt 4xCO 2 experiments. Several models, however, do predict no change or ENSO weakening, especially in the idealized experiments. Critically, the strongest forcing (abrupt-4xCO 2 ) does not induce the strongest ENSO response, while differences between the models are much greater than those between warming scenarios. For the long-term response (over 1000 years) the models disagree even on the sign of change. Furthermore, changes in ENSO sea surface temperature (SST) variability are only modestly correlated with the tropical Pacific mean state change. The highest correlation for ENSO SST amplitude is found with the mean zonal SST gradient in the SSP5-8.5 experiment (R = –0.58). In contrast, changes in ENSO rainfall variability correlate well with changes in the mean state, as well as with changes in ENSO SST variability. When evaluating the Bjerknes Stability Index for a subset of models, we find that it is not a reliable predictor of ENSO strengthening, as this index tends to predict greater stability with warming. We argue that the enhanced ENSO stability is offset by increases in atmospheric noise or/and potential nonlinear effects. However, a robust inter-model mechanism that can explain a stronger ENSO simulated with global warming is still lacking. Therefore, caution should be exercised when considering ENSO changes based on a single model or warming scenario.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Climate Change Projection in the Twenty-First Century Simulated by NIMS-KMA CMIP6 Model Based on New GHGs Concentration Pathways

Abstract The National Institute of Meteorological Sciences-Korea Meteorological Administration (NIMS-KMA) has participated in the Coupled Model Inter-comparison Project (CMIP) and provided long-term simulations using the coupled climate model. The NIMS-KMA produces new future projections using the ensemble mean of KMA Advanced Community Earth system model (K-ACE) and UK Earth System Model version1 (UKESM1) simulations to provide scientific information of future climate changes. In this study, we analyze four experiments those conducted following the new shared socioeconomic pathway (SSP) based scenarios to examine projected climate change in the twenty-first century. Present day (PD) simulations show high performance skill in both climate mean and variability, which provide a reliability of the climate models and reduces the uncertainty in response to future forcing. In future projections, global temperature increases from 1.92 °C to 5.20 °C relative to the PD level (1995–2014). Global mean precipitation increases from 5.1% to 10.1% and sea ice extent decreases from 19% to 62% in the Arctic and from 18% to 54% in the Antarctic. In addition, climate changes are accelerating toward the late twenty-first century. Our CMIP6 simulations are released to the public through the Earth System Grid Federation (ESGF) international data sharing portal and are used to support the establishment of the national adaptation plan for climate change in South Korea.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Cloud Feedback Uncertainty in the Equatorial Pacific Across CMIP6 Models

Cloud feedback is the largest uncertainty in estimating Equilibrium Climate Sensitivity. In this study we focus on the equatorial Pacific, where CMIP6 model cloud feedback spread is notably large. Cloud radiative effects in this region are relevant for the global climate. Our findings show that models predict a consistent shift towards the ascent regime in response to El Nino-like sea surface warming. Models diverge in terms of the radiative impact due to differences in cloud characteristics in ascent and subsidence regimes. Using the observed relationship between circulation regime and cloud radiative effect, we find a reduction in the regional mean cloud feedback estimate from 0.77 to 0.22 W m -2 K -1 , though this does not substantially lessen the model spread in total feedback. Pathways to reduce this spread include: improving confidence in the regional ocean warming pattern, and using observations and models to understand cloud type and circulation interactions.

CMIP6↗