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Results for “inter-model spread”

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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46 records · Page 3
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Quantifying Changes in the Arctic Shortwave Cloud Radiative Effects

The shortwave cloud radiative effect (SWCRE) is important on the Arctic surface radiation budget and the major source of inter-model spread in predictions of Arctic climate. To better understand the individual contributions of various radiative processes to changes in SWCRE, the paper presents the use of the extended APRP (Atmospheric Radiative Perturbation Potential) method. This involves adding the absorptivity for the upward beam and considering differences in reflectivity between upward and downward beams, as well as analyzing the cloud masking effect resulting from changes in surface albedo in more detail. Using data from the CMIP5 and CMIP6 climate models, the study decomposes the SWCRE over the Arctic surface and analyzes inter-model differences in quadrupled CO2 simulations. The study takes into account the fact that the response of SWCRE to Arctic warming is influenced by changes in surface albedo, cloud amount, and cloud microphysics. Results show that in the sunlight season, the reduction in surface albedo associated with sea ice loss is directly linked to strong negative SWCRE, which explains the considerable model discrepancy. Arctic clouds can hinder the positive surface albedo feedback by changing the albedo in two ways: (1) decreasing incoming shortwave radiation due to cloud reflection and (2) by decreasing the shortwave reaching the surface after being reflected by clouds. In addition, increased (decreased) cloud amount and cloud liquid water are shown to be less (more) incoming shortwave fluxes at the surface, but not dominating factors to the Arctic surface radiation budget and its inter-model variation. Overall, the extended APRP method offers a useful tool for analyzing the complex interactions between clouds and radiative process, reasonably decomposes the individual SWCRE responses at the Arctic surface, and emphasizes that considering not only the cloud amount or its properties, but also surface albedo change is critical for the prediction of SWCRE on the Arctic surface.

Arctic cloud↗
NASA NTRS2024

Accurate Assessment of Land-Atmosphere Coupling in Climate Models Requires High Frequency Data Output

Land-atmosphere (L-A) interactions are important for understanding convective processes, climate feedbacks, the development and perpetuation of droughts, heatwaves, pluvials, and other land-centred climate anomalies. Local L-A coupling (LoCo) metrics capture relevant L-A processes, highlighting the impact of soil and vegetation states on surface flux partitioning, and the impact of surface fluxes on boundary layer (BL) growth, development, and entrainment of air above the BL. A primary goal of the Climate Process Team on Coupling Land and Atmospheric Subgrid Parameterizations (CLASP) is parameterizing and characterizing the impact of subgrid heterogeneity in global and regional earth system models (ESMs) to improve the connection between land and atmospheric states and processes. A critical step in achieving that aim is the incorporation of L-A metrics, especially LoCo metrics, into climate model diagnostic process streams. However, because land-atmosphere interactions span time scales of minutes (e.g., turbulent fluxes), hours (e.g., BL growth and decay), days (e.g., soil moisture memory), and seasons (e.g., variability of behavioural regimes between soil moisture and latent heat flux), with multiple processes of interest happening in different geographic regions at different times of year, there is not a single metric that captures all the modes, means, and methods of interaction between the land and the atmosphere. And while monthly means of most of the LoCo-relevant variables are routinely saved from ESM simulations, data storage constraints typically preclude routine archival of the hourly data that would enable the calculation of all LoCo metrics. Here we outline a reasonable data request that would allow for adequate characterization of sub-daily coupling processes between the land and the atmosphere, preserving enough sub-daily output to describe, analyse, and better understand L-A coupling in modern climate models. A secondary request involves embedding calculations within the models to determine mean properties in and above the BL to further improve characterization of model behaviour. Higher-frequency model output will (i) allow for more direct comparison with observational field campaigns on process-relevant time scales, (ii) enable demonstration of inter-model spread in L-A coupling processes, and (iii) aid in targeted identification of sources of deficiencies and opportunities for improvement of the models.

Kirsten L. Findell↗
NASA NTRS2024

Observational Constraint on A Feedback From Supercooled Clouds Reduces Projected Warming Uncertainty

The increase of carbon-dioxide-doubling-induced warming (climate sensitivity) in the latest climate models is primarily attributed to a larger extratropical cloud feedback. This is thought to be partly driven by a greater ratio of supercooled liquid-phase clouds to all clouds, termed liquid phase ratio. We use an instrument simulator approach to show that this ratio has increased in the latest climate models and is overestimated rather than underestimated as previously thought. In our analysis of multiple models, a greater ratio corresponds to stronger negative cloud feedback, in contradiction with single-model-based studies. We trace this unexpected result to a cloud feedback involving a shift from supercooled to warm clouds as climate warms, which corresponds to greater cloud amount and optical depth and weakens the extratropical cloud feedback. Better constraining this ratio in climate models – and thus this supercooled cloud feedback – impacts their climate sensitivities by up to 1 ˚C and reduces inter-model spread.

Climate and Earth system modelling↗
NASA NTRS2017

Inter-Model Warming Projection Spread: Inherited Traits from Control Climate Diversity

Since Chaney’s report, the range of global warming projections in response to a doubling of CO2—from 1.5 °C to 4.5 °C or greater—remains largely unscathed by the onslaught of new scientific insights. Conventional thinking regards inter-model differences in climate feedbacks as the sole cause of the warming projection spread (WPS). Our findings shed new light on this issue indicating that climate feedbacks inherit diversity from the model control climate, besides the models’ intrinsic climate feedback diversity that is independent of the control climate state. Regulated by the control climate ice coverage, models with greater (lesser) ice coverage generally possess a colder (warmer) and drier (moister) climate, exhibit a stronger (weaker) ice-albedo feedback, and experience greater (weaker) warming. The water vapor feedback also inherits diversity from the control climate but in an opposite way: a colder (warmer) climate generally possesses a weaker (stronger) water vapor feedback, yielding a weaker (stronger) warming. These inherited traits influence the warming response in opposing manners, resulting in a weaker correlation between the WPS and control climate diversity. Our study indicates that a better understanding of the diversity amongst climate model mean states may help to narrow down the range of global warming projections.

Climate feedbacks↗
DOE OSTI2019

Divergence in land surface modeling: linking spread to structure

Divergence in land carbon cycle simulation is persistent and widespread. Regardless of model intercomparison project, results from individual models diverge significantly from each other and, in consequence, from reference datasets. Here we link model spread to structure using a 15-member ensemble of land surface models from the Multi-scale synthesis and Terrestrial Model Intercomparison Project (MsTMIP) as a test case. Our analysis uses functional benchmarks and model structure as predicted by model skill in a machine learning framework to isolate discrete aspects of model structure associated with divergence. We also quantify how initial conditions prejudice present-day model outcomes after centennial-scale transient simulations. Overall, the functional benchmark and machine learning exercises emphasize the importance of ecosystem structure in correctly simulating carbon and water cycling, highlight uncertainties in the structure of carbon pools, and advise against hard parametric limits on ecosystem function. We also find that initial conditions explain 90% of variation in global satellite-era values—initial conditions largely predetermine transient endpoints, historical environmental change notwithstanding. As MsTMIP prescribes forcing data and spin-up protocol, the range in initial conditions and high levels of predetermination are also structural. Our results suggest that methodological tools linking divergence to discrete aspects of model structure would complement current community best practices in model development.

58 GEOSCIENCES↗
DOE OSTI2023

Climate response to off-equatorial stratospheric sulfur injections in three Earth system models – Part 2: Stratospheric and free-tropospheric response

The paper constitutes Part 2 of a study performing a first systematic inter-model comparison of the atmospheric responses to stratospheric aerosol injection (SAI) at various single latitudes in the tropics, as simulated by three state-of-the-art Earth system models – CESM2-WACCM6, UKESM1.0, and GISS-E2.1-G. Building on Part 1 (Visioni et al., 2023) we demonstrate the role of biases in the climatological circulation and specific aspects of the model microphysics in driving the inter-model differences in the simulated sulfate distributions. We then characterize the simulated changes in stratospheric and free-tropospheric temperatures, ozone, water vapor, and large-scale circulation, elucidating the role of the above aspects in the surface SAI responses discussed in Part 1. We show that the differences in the aerosol spatial distribution can be explained by the significantly faster shallow branches of the Brewer–Dobson circulation in CESM2, a relatively isolated tropical pipe and older tropical age of air in UKESM, and smaller aerosol sizes and relatively stronger horizontal mixing (thus very young stratospheric age of air) in the two GISS versions used. We also find a large spread in the magnitudes of the tropical lower-stratospheric warming amongst the models, driven by microphysical, chemical, and dynamical differences. These lead to large differences in stratospheric water vapor responses, with significant increases in stratospheric water vapor under SAI in CESM2 and GISS that were largely not reproduced in UKESM. For ozone, good agreement was found in the tropical stratosphere amongst the models with more complex microphysics, with lower stratospheric ozone changes consistent with the SAI-induced modulation of the large-scale circulation and the resulting changes in transport. In contrast, we find a large inter-model spread in the Antarctic ozone responses that can largely be explained by the differences in the simulated latitudinal distributions of aerosols as well as the degree of implementation of heterogeneous halogen chemistry on sulfate in the models. The use of GISS runs with bulk microphysics demonstrates the importance of more detailed treatment of aerosol processes, with contrastingly different stratospheric SAI responses to the models using the two-moment aerosol treatment; however, some problems in halogen chemistry in GISS are also identified that require further attention. Overall, our results contribute to an increased understanding of the underlying physical mechanisms as well as identifying and narrowing the uncertainty in model projections of climate impacts from SAI.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

The future of the El Niño–Southern Oscillation: using large ensembles to illuminate time-varying responses and inter-model differences

Future changes in the El Niño–Southern Oscillation (ENSO) are uncertain, both because future projections differ between climate models and because the large internal variability of ENSO clouds the diagnosis of forced changes in observations and individual climate model simulations. By leveraging 14 single model initial-condition large ensembles (SMILEs), we robustly isolate the time-evolving response of ENSO sea surface temperature (SST) variability to anthropogenic forcing from internal variability in each SMILE. We find nonlinear changes in time in many models and considerable inter-model differences in projected changes in ENSO and the mean-state tropical Pacific zonal SST gradient. We demonstrate a linear relationship between the change in ENSO SST variability and the tropical Pacific zonal SST gradient, although forced changes in the tropical Pacific SST gradient often occur later in the 21st century than changes in ENSO SST variability, which can lead to departures from the linear relationship. Single-forcing SMILEs show a potential contribution of anthropogenic forcing (aerosols and greenhouse gases) to historical changes in ENSO SST variability, while the observed historical strengthening of the tropical Pacific SST gradient sits on the edge of the model spread for those models for which single-forcing SMILEs are available. Our results highlight the value of SMILEs for investigating time-dependent forced responses and inter-model differences in ENSO projections. The nonlinear changes in ENSO SST variability found in many models demonstrate the importance of characterizing this time-dependent behavior, as it implies that ENSO impacts may vary dramatically throughout the 21st century.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Amplified drought trends in Nepal increase the potential for Himalayan wildfires

Here we report in the spring 2021, Nepal underwent a record wildfire season in which active fires were detected at a rate 10 times greater than the 2002–2020 average. Prior to these major wildfire events, the country experienced a prolonged precipitation deficit and extreme drought during the post-monsoon period (starting in October 2020). An analysis using observational, reanalysis, and climate model ensemble data indicates that both climate variability and climate change-induced severe drought conditions were at play. Further analysis of climate model outputs suggests the likely reoccurrence of drought conditions, thus favoring active wildfire seasons in Nepal throughout the twenty-first century. While the inter-model uncertainty is large and direct modeling of wildfire spread and suppression has not been completed, the demonstrated relationship between a drought index (the standardized precipitation and evapotranspiration index) and subsequent fire activity may offer actionable opportunities for forest managers to employ the monitoring and projection of climate anomalies at sub-seasonal to decadal timescales to inform their management strategies for Nepal’s wildlands.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Implementation and Evaluation of Emission‐Driven Land‐Atmosphere Coupled Simulation in E3SMv2.1

Emissions-driven (prognostic CO 2 ) simulations are essential for representing two-way carbon-climate feedback in Earth System Models. We present an emissions-driven land–atmosphere coupled biogeochemistry (BGC) configuration (BGCLNDATM_progCO2) in version 2.1 of the Energy Exascale Earth System Model (E3SMv2.1). This is the first E3SM configuration that performs land-atmosphere emission-hindcasts. Here, we document its implementation, evaluate the model's performance against observations and other models, and propose a structured evaluation protocol for such emissions-driven simulations. We conducted transient historical simulations (1850–2014) with BGCLNDATM_progCO2 and compare them to reference simulations—a land-atmosphere coupled simulation without BGC and a standalone land simulation with BGC, both using prescribed CO 2 concentrations—and to observations. BGCLNDATM_progCO2 overestimates atmospheric CO 2 concentrations by 11–23 ppm yet stays within the 40-ppm spread CMIP6 emission-driven models and retains physical climate properties comparable to the reference runs. The CO 2 biases are partly attributed to underrepresented oceanic CO 2 uptake and inadequate representations of some terrestrial processes. In general, introducing prognostic CO 2 did not change physical climate metrics at the global scale but had larger regional effects, particularly over land where spatially heterogeneous CO 2 and prognostic leaf area index influenced surface energy balance. Finally, we propose a general evaluation protocol including spin-up assessment, atmospheric CO 2 benchmarking, physical climate evaluation, and land biogeochemical analysis to support scientific rigor and facilitate inter-model comparisons. The new configuration lays the groundwork for future enhancements, including improved terrestrial biogeochemical processes, integrated marine biogeochemistry, and additional human–Earth system interactions. These developments advance E3SM toward fully coupled emissions-driven simulations, enabling more accurate carbon–climate feedback projections and informing mitigation policy by providing physically consistent carbon-budget metrics for mitigation scenarios.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Results of the second Ice Shelf–Ocean Model Intercomparison Project (ISOMIP+)

Ocean-driven basal melting of Antarctic ice shelves plays an important role in the mass loss of the Antarctic Ice Sheet. Ice shelf cavity-resolving ocean models are a valuable tool for understanding ice shelf-ocean interactions and for simulating projections of ice shelf and ocean states under future climate. Designed to assess the current state of ice shelf–ocean modelling, the second Ice Shelf–Ocean Model Intercomparison Project, ISOMIP+, consists of 12 ocean model configurations submitted with a common, idealised experimental setup. Here, we focus on the experiments Ocean0–2 (Asay-Davis et al., 2016), which are ocean models with idealised, static ice shelf geometries, but where the ocean reaches a balance with prescribed far-field ocean conditions. Different thermal transfer coefficient values (ranging from 0.011 to 0.2) are used for each model in the melting parameterisation to achieve a common, tuned melt rate since the models cover a range of types of vertical coordinates, ice–ocean boundary layer treatments, and numerical schemes. These model differences lead to spread in the resultant ocean properties, circulation, boundary-layer structure and spatial distribution of melting. We also highlight similarities between models, such as a shared linear relationship across most models between melt rate and overturning and barotropic streamfunctions during the spin-up and spin-down, demonstrating a robust relationship between melt and circulation across models and forcing conditions. The ISOMIP+ results provide a systematic comparison of ice shelf cavity-capable ocean models. However, we also demonstrate the need for realistic ice shelf–ocean model intercomparison projects (some already underway) to assess model biases and inter-model variation against sparse observations. Further research is needed to understand the differences between models and further improve our modelled representations of the ice–ocean boundary layer and ice shelf cavity circulation.

54 ENVIRONMENTAL SCIENCES↗