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Results for “Global warming projection uncertainty”

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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At least 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Evaluation and projection of long period return values of extreme daily precipitation in the CMIP5 and CMIP6 models

Using a non-stationary Generalized Extreme Value statistical method, we calculate selected extreme daily precipitation indices and their 20 year return values from the CMIP5 and CMIP6 climate models over the historical and future periods. We evaluate model performance of these indices and their return values in replicating similar quantities calculated from multiple gridded observational products. Difficulties in interpreting model quality in the context of observational uncertainties are discussed. Projections are framed in terms of specified global warming target temperatures rather than at specific times and under specific emissions scenarios. The change in framing shifts projection uncertainty due to differences in model climate sensitivity from the values of the projections to the timing of the global warming target. At their standard resolutions, we find there are no meaningful differences between the two generations of models in their quality or projections of simulated extreme daily precipitation.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

A spatial emergent constraint on the sensitivity of soil carbon turnover to global warming

Carbon cycle feedbacks represent large uncertainties in climate change projections, and the response of soil carbon to climate change contributes the greatest uncertainty to this. Future changes in soil carbon depend on changes in litter and root inputs from plants and especially on reductions in the turnover time of soil carbon (τ s ) with warming. An approximation to the latter term for the top one metre of soil (ΔC s,τ ) can be diagnosed from projections made with the CMIP6 and CMIP5 Earth System Models (ESMs), and is found to span a large range even at 2 °C of global warming (-196 ± 117 PgC). Here, we present a constraint on ΔC s,τ , which makes use of current heterotrophic respiration and the spatial variability of τs inferred from observations. This spatial emergent constraint allows us to halve the uncertainty in ΔC s,τ at 2 °C to -232 ± 52 PgC.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Future precipitation increase constrained by climatological pattern of cloud effect

The fractional increase in global mean precipitation (?P ¯/P ¯) is a first-order measure of the hydrological cycle intensification under anthropogenic warming. However, ?P ¯/P ¯ varies by a factor of more than three among model projections, hindering credible assessments of the associated climate impacts. The uncertainty in ?P ¯/P ¯ stems from uncertainty in both hydrological sensitivity (global mean precipitation increase per unit warming) and climate sensitivity (global mean temperature increase per forcing). Here, by investigating hydrological and climate sensitivities in a unified surface-energy-balance perspective, we find that both sensitivities are significantly correlated with surface shortwave cloud feedback, which is further linked to the climatological pattern of cloud shortwave effect. The observed pattern of cloud effect thus constrains both sensitivities and consequently constrains ?P ¯/P ¯. The 5%-95% uncertainty range of ?P ¯/P ¯ from 1979-2005 to 2080-2100 under the high-emission (moderate-emission) scenario is constrained from 6.34±3.53% (4.19±2.28%) in the raw ensemble-model projection to 7.03±2.59% (4.63±1.71%). The constraint thus suggests a higher most-likely ?P ¯/P ¯ and reduces the uncertainty by ~25%, providing valuable information for impact assessments.

Zhou, Wenyu↗
DOE OSTI2023

Impact of Global Warming on U.S. Summertime Mesoscale Convective Systems: A Simple Lagrangian Parcel Model Perspective

Abstract Mesoscale convective systems (MCSs) are the dominant rainfall producer over the United States during the warm season, causing natural disasters and severe weather every year. Global climate models have large uncertainty in projecting precipitation changes in the future climate. Here, a simple Lagrangian parcel model is used to investigate the impact of global warming on MCS initiation and growth. The single-column parcel model projects a mean precipitation decrease over the central United States and an increase to its east, in agreement with the CMIP5 model projection. It also highlights the crucial role of current climate mean-state model bias in exaggerating the change in future mean precipitation projection by 25%. As for convective population, the model captures the decreased occurrence frequency of weak to moderate convection and increased frequency of strong convection due to the increased CAPE and CIN, in agreement with convection-permitting regional simulations. Novel parameterizations of gust-front propagation speed and subsidence strength are developed as guided by cloud-resolving simulations. The multicolumn parcel model employing those parameterizations captures readily the cold pool–induced upscale growth feature. It simulates smaller mesoscale clusters over the central United States under global warming due to gust-front slowdown and subsidence strength enhancement, which are further attributed to land aridity–induced weakening of initial accumulated precipitation and strengthening of updraft speed, respectively. That said, mesoscale clusters could become bigger under more favorable conditions in future climate, including boundary layer moistening, convection lifetime lengthening, and cold pool mechanical-lifting enhancement, which require further investigations to improve mechanistic understanding of future MCS changes.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Uncertainty in El Niño-like warming and California precipitation changes linked by the Interdecadal Pacific Oscillation

Abstract Marked uncertainty in California (CA) precipitation projections challenges their use in adaptation planning in the region already experiencing severe water stress. Under global warming, a westerly jet extension in the North Pacific analogous to the El Niño-like teleconnection has been suggested as a key mechanism for CA winter precipitation changes. However, this teleconnection has not been reconciled with the well-known El Niño-like warming response or the controversial role of internal variability in the precipitation uncertainty. Here we find that internal variability contributes > 70% and > 50% of uncertainty in the CA precipitation changes and the El Niño-like warming, respectively, based on analysis of 318 climate simulations from several multi-model and large ensembles. The Interdecadal Pacific Oscillation plays a key role in each contribution and in connecting the two via the westerly jet extension. This unifying understanding of the role of internal variability in CA precipitation provides critical guidance for reducing and communicating uncertainty to inform adaptation planning.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Sea-surface temperature pattern effects have slowed global warming and biased warming-based constraints on climate sensitivity

The observed rate of global warming since the 1970s has been proposed as a strong constraint on equilibrium climate sensitivity (ECS) and transient climate response (TCR)—key metrics of the global climate response to greenhouse-gas forcing. Using CMIP5/6 models, we show that the inter-model relationship between warming and these climate sensitivity metrics (the basis for the constraint) arises from a similarity in transient and equilibrium warming patterns within the models, producing an effective climate sensitivity (EffCS) governing recent warming that is comparable to the value of ECS governing long-term warming under CO 2 forcing. However, CMIP5/6 historical simulations do not reproduce observed warming patterns. When driven by observed patterns, even high ECS models produce low EffCS values consistent with the observed global warming rate. The inability of CMIP5/6 models to reproduce observed warming patterns thus results in a bias in the modeled relationship between recent global warming and climate sensitivity. Correcting for this bias means that observed warming is consistent with wide ranges of ECS and TCR extending to higher values than previously recognized. These findings are corroborated by energy balance model simulations and coupled model (CESM1-CAM5) simulations that better replicate observed patterns via tropospheric wind nudging or Antarctic meltwater fluxes. Because CMIP5/6 models fail to simulate observed warming patterns, proposed warming-based constraints on ECS, TCR, and projected global warming are biased low. The results reinforce recent findings that the unique pattern of observed warming has slowed global-mean warming over recent decades and that how the pattern will evolve in the future represents a major source of uncertainty in climate projections.

58 GEOSCIENCES↗
DOE OSTI2022

Scrutinizing entrainment and mass flux closures in shallow cumulus parameterizations using cloud-radar observations and large-eddy simulation (Final Report)

Representing warm, shallow clouds is a challenge for Global Climate Models, which leads to uncertainty in model projections of future climate. Our study was particularly concerned with how climate models represent the effects of shallow, non-precipitating cumulus clouds. Climate models must make certain assumptions when representing low clouds such as how much dry air from outside the cloud is mixed into the warm, moist cloud updraft. This process is called “entrainment” and tends to weaken the cloud updraft and dry out the cloud, compared to a theoretical cloud with no mixing. This project was a joint observational and modeling study to derive estimates of entrainment from field observations and use high-resolution modeling to evaluate the assumptions used in climate model representations of shallow cumulus. Our research took advantage of a wide variety of Department of Energy measurements from fixed climate-monitoring locations over the Southern Great Plains of the U.S. and the in the Eastern North Atlantic, along with short-term field projects (MAGIC, CAP–MBL, ACE–ENA). During the project, the PI maintained regular collaborations with Department of Energy Scientists at Brookhaven and Argonne National Laboratories. The project funded two students, who both obtained their M.S. in Atmospheric Science and are currently in the Atmospheric Science Ph.D. program. Both were lead authors on research papers funded by this grant.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Reducing Model Uncertainty of Climate Change Impacts on High Latitude Carbon Assimilation

The Arctic Boreal Region (ABR) has a large impact on global vegetation-atmosphere interactions and is experiencing markedly greater warming than the rest of the planet, a trend that is projected to continue with anticipated future emissions of CO 2 . The ABR is a significant source of uncertainty in estimates of carbon uptake in terrestrial biosphere models (TBMs) such that reducing this uncertainty is critical for more accurately estimating global carbon cycling and understanding the response of the region to global change. Process representation and parameterization associated with gross primary productivity (GPP) drives a large amount of this model uncertainty, particularly within the next 50 years, where the response of existing vegetation to climate change will dominate estimates of GPP for the region. Furthermore, we review our current understanding and model representation of GPP in northern latitudes, focusing on vegetation composition, phenology and physiology, and consider how climate change alters these three components. We highlight challenges in the ABR for predicting GPP, but also focus on the unique opportunities for advancing knowledge and model representation, particularly through the combination of remote sensing and traditional boots-on-the-ground science.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Emergent constraints on future methane emissions from global wetlands

Future methane (CH 4 ) emissions from natural wetlands are predicted to increase due to global warming, leading to positive feedback on climate change. However, the magnitude of this increase remains highly uncertain. Here we present novel ensemble simulations of seven state-of-the-art terrestrial biosphere models to estimate wetland CH 4 emissions (eCH 4 ) during the twenty-first century. Our estimates suggest that for every 1 °C increase in global land surface temperature, there is a 24 ± 10 Tg CH 4 yr −1 increase in eCH 4 . We also identify an emergent relationship between contemporary temperature dependence and projected eCH 4 . When constrained by 163 site-year eddy-covariance measurements of eCH 4 , we show that wetland emissions can increase by 50–60% by the 2090s relative to the 2010s under a high-warming scenario. The projected decadal increase in eCH 4 from the 2010–2019 baseline to the 2030s would very likely (90% probability) offset an amount equivalent in scale to 8–10% of anthropogenic eCH 4 at the 2020 level, comparable to the reductions committed under the Global Methane Pledge. However, the constraint is dominated by mid- and high-latitude observations, with limited tropical coverage, and uncertainties in projected wetland inundation contribute substantially to uncertainty in eCH 4 . Our findings reduce the uncertainty in projected wetland methane–climate feedback and highlight its potential impacts on methane mitigation efforts to slow global warming.

Zhang, Zhen [Chinese Academy of Sciences (CAS), Be↗
DOE OSTI2023

Evaluating Shallow Convection Parameterization Assumptions With a q t – w Quadrant Analysis

Abstract Uncertainties associated with the response of shallow clouds to global warming remain a great challenge for climate projection. Due to the small size of these clouds, parameterizations are required to represent them in both current‐ and next‐generation climate models. We present a quantitative evaluation of several important assumptions used in both mass‐flux and Assumed‐PDF Higher‐Order Closure parameterizations of shallow convection. We use large‐eddy simulations (LESs) of four different shallow convection regimes as benchmarks and apply a q t (total moisture)– w (vertical velocity) quadrant analysis technique to identify the “coherent structures” of moist and dry up/down‐drafts. The statistics of these coherent structures and the environment are then used to evaluate commonly used assumptions in mass‐flux parameterizations related to (a) the convective downdrafts and (b) the subplume variability of convective updrafts. For quantitative evaluation of the PDF closure used in AP‐HOCs, we perform offline calculations with the PDF closure used in the Cloud Layers Unified By Bi‐normals and the Simplified Higher‐Order Closure schemes by supplying the closure with statistical quantities directly calculated from the LESs. Then, the impact of parameterization assumptions embedded in the PDF closure in the same two categories is analyzed and understood through comparisons of the output from the closure with the statistics of the moist and dry up/down‐drafts from the LESs.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Contributions From Cloud Morphological Changes to the Interannual Shortwave Cloud Feedback Based on MODIS and ISCCP Satellite Observations

The surface temperature-mediated change in cloud properties, referred to as the cloud feedback, continues to dominate the uncertainty in climate projections. A larger number of contemporary global climate models (GCMs) project a higher degree of warming than the previous generation of GCMs. This greater projected warming has been attributed to a less negative cloud feedback in the Southern Ocean. Here, we apply a novel “double decomposition method” that employs the “cloud radiative kernel” and “cloud regime” concepts, to two data sets of satellite observations to decompose the interannual cloud feedback into contributions arising from changes within and shifts between cloud morphologies. Our results show that contributions from the latter to the cloud feedback are large for certain regimes. We then focus on interpreting how both changes within and between cloud morphologies impact the shortwave cloud optical depth feedback over the Southern Ocean in light of additional observations. Results from the former cloud morphological changes reveal the importance of the wind response to warming increases low- and mid-level cloud optical thickness in the same region. Results from the latter cloud morphological changes reveal that a general shift from thick storm-track clouds to thinner oceanic low-level clouds contributes to a positive feedback over the Southern Ocean that is offset by shifts from thinner broken clouds to thicker mid- and low-level clouds. Our novel analysis can be applied to evaluate GCMs and potentially diagnose shortcomings pertaining to their physical parameterizations of particular cloud morphologies.

58 GEOSCIENCES↗
DOE OSTI2022

Mesoscale Convective Systems Simulated by a High–Resolution Global Nonhydrostatic Model Over the United States and China

Mesoscale convective systems (MCSs) contribute a large fraction of warm-season precipitation and generate hazardous weather with substantial socio-economic impacts. Uncertainties in convection parameterizations in climate models limit our understanding of MCS characteristics and reliability of future projection. We examine the MCS simulation from the global 14-km Nonhydrostatic ICosahedral Atmospheric Model (NICAM) without cumulus parameterization against satellite observation from Global Precipitation Measurement (GPM) during 2001-2008. We focus on MCSs over the central U.S. and eastern China where MCSs prevail from March to August. A process-oriented tracking method incorporating both cloud and precipitation criteria is used to identify and track MCSs. About 140/100 MCSs initiate in the central U.S./eastern China per warm season and most of them initiate east of high mountains and in coastal regions. The frequency distribution of MCS lifetime is well captured in NICAM. But the simulated MCSs have stronger precipitation, smaller precipitation area, and larger cold cloud system than observed in both regions, which may be caused by weak entrainment as it is not well resolved at 14 km resolution. Here, the simulated MCS number is also underestimated in summer. By examining the climatological and MCS large-scale environments, the significant underestimation of MCS number in summer over the central U.S. may be attributed to the large climatological dry bias in the atmosphere. For China, mean moisture in summer is well simulated but deficiency in capturing the dynamic condition related to the coastal topography for triggering convection may have contributed to underestimation of MCS even in a sufficiently moist environment.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

The Observed and Projected Changes of Global Monsoons: Current Status and Future Perspectives

The global monsoon system, encompassing the Asian-Australian, African, and American monsoons, sustains two-thirds of the world’s population by regulating water resources and agriculture. Monsoon anomalies pose severe risks, including floods and droughts. Recent research associated with the implementation of the Global Monsoons Model Intercomparison Project under the umbrella of CMIP6 has advanced our understanding of its historical variability and driving mechanisms. Observational data reveal a 20th-century shift: increased rainfall pre-1950s, followed by aridification and partial recovery post-1980s, driven by both internal variability (e.g., Atlantic Multidecadal Oscillation) and external forcings (greenhouse gases, aerosols), while ENSO drives interannual variability through ocean-atmosphere interactions. Future projections under greenhouse forcing suggest long-term monsoon intensification, though regional disparities and model uncertainties persist. Models indicate robust trends but struggle to quantify extremes, where thermodynamic effects (warming-induced moisture rise) uniformly boost heavy rainfall, while dynamical shifts (circulation changes) create spatial heterogeneity. Volcanic eruptions and proposed solar radiation modification (SRM) further complicate predictions: tropical eruptions suppress monsoons, whereas high-latitude events alter cross-equatorial flows, highlighting unresolved feedbacks. The emergent constraint approach is booming in terms of correcting future projections and reducing uncertainty with respect to the global monsoons. Critical challenges remain. Model biases and sparse 20th-century observational data hinder accurate attribution. The interplay between natural variability and anthropogenic forcings, along with nonlinear extreme precipitation risks under warming, demands deeper mechanistic insights. Additionally, SRM’s regional impacts and hemispheric monsoon interactions require systematic evaluation. Addressing these gaps necessitates enhanced observational networks, refined climate models, and interdisciplinary efforts to disentangle multiscale drivers, ultimately improving resilience strategies for monsoon-dependent regions.

climate extreme events↗
DOE OSTI2021

Projected land ice contributions to twenty-first-century sea level rise

The land ice contribution to global mean sea level rise has not yet been predicted using ice sheet and glacier models for the latest set of socio-economic scenarios, nor using coordinated exploration of uncertainties arising from the various computer models involved. Two recent international projects generated a large suite of projections using multiple models, but primarily used previous-generation scenarios and climate models, and could not fully explore known uncertainties. Here we estimate probability distributions for these projections under the new scenarios using statistical emulation of the ice sheet and glacier models. In this work, we find that limiting global warming to 1.5 degrees Celsius would halve the land ice contribution to twenty-first-century sea level rise, relative to current emissions pledges. The median decreases from 25 to 13 centimetres sea level equivalent (SLE) by 2100, with glaciers responsible for half the sea level contribution. The projected Antarctic contribution does not show a clear response to the emissions scenario, owing to uncertainties in the competing processes of increasing ice loss and snowfall accumulation in a warming climate. However, under risk-averse (pessimistic) assumptions, Antarctic ice loss could be five times higher, increasing the median land ice contribution to 42 centimetres SLE under current policies and pledges, with the 95th percentile projection exceeding half a metre even under 1.5 degrees Celsius warming. This would severely limit the possibility of mitigating future coastal flooding. Given this large range (between 13 centimetres SLE using the main projections under 1.5 degrees Celsius warming and 42 centimetres SLE using risk-averse projections under current pledges), adaptation planning for twenty-first-century sea level rise must account for a factor-of-three uncertainty in the land ice contribution until climate policies and the Antarctic response are further constrained.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Implications of a Pervasive Climate Model Bias for Low‐Cloud Feedback

Abstract How low clouds respond to warming constitutes a key uncertainty for climate projections. Here we observationally constrain low‐cloud feedback through a controlling factor analysis based on ridge regression. We find a moderately positive global low‐cloud feedback (0.45 W , 90% range 0.18–0.72 W ), about twice the mean value (0.22 W ) of 16 models from the Coupled Model Intercomparison Project. We link this discrepancy to a pervasive model mean‐state bias: models underestimate the low‐cloud response to warming because (a) they systematically underestimate present‐day tropical marine low‐cloud amount, and (b) the low‐cloud sensitivity to warming is proportional to this present‐day low‐cloud amount. Our results hence highlight the importance of reducing model biases in both the mean state of clouds and their sensitivity to environmental factors for accurate climate change projections.

58 GEOSCIENCES↗
DOE OSTI2022

A High-End Estimate of Sea Level Rise for Practitioners

Sea level rise (SLR) is a long-lasting consequence of climate change because global anthropogenic warming takes centuries to millennia to equilibrate for the deep ocean and ice sheets. SLR projections based on climate models support policy analysis, risk assessment and adaptation planning today, despite their large uncertainties. The central range of the SLR distribution is estimated by process-based models. However, risk-averse practitioners often require information about plausible future conditions that lie in the tails of the SLR distribution, which are poorly defined by existing models. Here, a community effort combining scientists and practitioners builds on a framework of discussing physical evidence to quantify high-end global SLR for practitioners. The approach is complementary to the IPCC AR6 report and provides further physically plausible high-end scenarios. High-end estimates for the different SLR components are developed for two climate scenarios at two timescales. For global warming of +2°C in 2100 (RCP2.6/SSP1-2.6) relative to pre-industrial values our high-end global SLR estimates are up to 0.9 m in 2100 and 2.5 m in 2300. Similarly, for a (RCP8.5/SSP5-8.5), we estimate up to 1.6 m in 2100 and up to 10.4 m in 2300. The large and growing differences between the scenarios beyond 2100 emphasize the long-term benefits of mitigation. However, even a modest 2°C warming may cause multi-meter SLR on centennial time scales with profound consequences for coastal areas. Earlier high-end assessments focused on instability mechanisms in Antarctica, while here we emphasize the importance of the timing of ice shelf collapse around Antarctica. This is highly uncertain due to low understanding of the driving processes. Hence both process understanding and emission scenario control high-end SLR.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

How Moist and Dry Intrusions Control the Local Hydrologic Cycle in Present and Future Climates

Models disagree on the magnitude of the intensification of hydrologic cycle extremes under climate change. Changes in these extremes are expected to scale with the Clausius-Clapeyron relation but may locally diverge due to the uncertain response of the atmospheric general circulation. Recent work has identified that the circulation contribution (the “dynamic” component) is the largest contributor to uncertainty in changes in hydrologic cycle extremes. In this work, we develop an exact budget for changes in wet and dry extremes based on changes in the associated moist and dry intrusions behind those extremes. We decompose changes into four contributors: thermodynamic, low-level convergence, anomalous meridional moisture advection, and zonal wave activity convergence. In analyzing these changes, we show that low-level convergence is the main dynamic contributor to the tropical and subtropical annual response, consistent with weakening of the Hadley circulation, and we show that anomalous meridional moisture advection is the primary dynamic contributor annually for the extratropics, consistent with storm track changes. We achieve a clean separation between dynamic and thermodynamic contributions through an empirical scaling between extremes and their associated wave activities, showing again that shifting storm tracks and expanding subtropics are critical to the dynamic response of the transient hydrologic cycle. We infer that changes in the large-scale circulation are predominantly responsible for the annual, dynamic response of hydrologic cycle extremes and therefore an important contributor to uncertainty in future projections.

Hydrological cycle, hydrological extremes, dynamic↗
DOE OSTI2021

Does Regional Hydroclimate Change Scale Linearly With Global Warming?

Many aspects of climate change scale linearly with global warming. However, nonlinear changes are possible, especially in the context of hydroclimate, and under emissions scenarios with stabilized global temperature, as aspired to by current climate targets. In CMIP5 and 6, a progressively larger land area shows nonlinear changes as a function of global warming when considering precipitation, evaporation, and soil moisture, with the latter showing nonlinearity over ~50% of global land. Here, using ensemble simulations with the Community Earth System Model 1, in which individual forcing factors are held constant, we illustrate how nonadditive responses to anthropogenic greenhouse gases and industrial and fire-related aerosols can yield complex soil moisture changes in certain regions. This complexity contributes to uncertainty in regional soil moisture projections and suggests that the timing of, as well as model response uncertainty to, future aerosol reductions will have significant impacts on regional hydroclimate change as global temperatures stabilize.

54 ENVIRONMENTAL SCIENCES↗