Results for “CLIMATE MODELS” — Page 84

DOE OSTI2017

County-Level Climate Uncertainty for Risk Assessments: Volume 7 Appendix F - Forecast Minimum Near-Surface Air Temperature

This report uses the CMIP5 series of climate model simulations to produce country- level uncertainty distributions for use in socioeconomic risk assessments of climate change impacts. It provides appropriate probability distributions, by month, for 169 countries and autonomous-areas on temperature, precipitation, maximum temperature, maximum wind speed, humidity, runoff, soil moisture and evaporation for the historical period (1976-2005), and for decadal time periods to 2100. It also provides historical and future distributions for the Arctic region on ice concentration, ice thickness, age of ice, and ice ridging in 15-degree longitude arc segments from the Arctic Circle to 80 degrees latitude, plus two polar semicircular regions from 80 to 90 degrees latitude. The uncertainty is meant to describe the lack of knowledge rather than imprecision in the physical simulation because the emphasis is on unfalsified risk and its use to determine potential socioeconomic impacts. The full report is contained in 27 volumes.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2017

County-Level Climate Uncertainty for Risk Assessments: Volume 13 Appendix L - Forecast Relative Humidity

This report uses the CMIP5 series of climate model simulations to produce country- level uncertainty distributions for use in socioeconomic risk assessments of climate change impacts. It provides appropriate probability distributions, by month, for 169 countries and autonomous-areas on temperature, precipitation, maximum temperature, maximum wind speed, humidity, runoff, soil moisture and evaporation for the historical period (1976-2005), and for decadal time periods to 2100. It also provides historical and future distributions for the Arctic region on ice concentration, ice thickness, age of ice, and ice ridging in 15-degree longitude arc segments from the Arctic Circle to 80 degrees latitude, plus two polar semicircular regions from 80 to 90 degrees latitude. The uncertainty is meant to describe the lack of knowledge rather than imprecision in the physical simulation because the emphasis is on unfalsified risk and its use to determine potential socioeconomic impacts. The full report is contained in 27 volumes.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2017

County-Level Climate Uncertainty for Risk Assessments: Volume 5 Appendix D—Forecast Maximum Near-Surface Air Temperature.

This report uses the CMIP5 series of climate model simulations to produce country- level uncertainty distributions for use in socioeconomic risk assessments of climate change impacts. It provides appropriate probability distributions, by month, for 169 countries and autonomous-areas on temperature, precipitation, maximum temperature, maximum wind speed, humidity, runoff, soil moisture and evaporation for the historical period (1976-2005), and for decadal time periods to 2100. It also provides historical and future distributions for the Arctic region on ice concentration, ice thickness, age of ice, and ice ridging in 15-degree longitude arc segments from the Arctic Circle to 80 degrees latitude, plus two polar semicircular regions from 80 to 90 degrees latitude. The uncertainty is meant to describe the lack of knowledge rather than imprecision in the physical simulation because the emphasis is on unfalsified risk and its use to determine potential socioeconomic impacts. The full report is contained in 27 volumes.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2017

County-Level Climate Uncertainty for Risk Assessments: Volume 11, Appendix J - Forecast Evaporation

This report uses the CMIP5 series of climate model simulations to produce country- level uncertainty distributions for use in socioeconomic risk assessments of climate change impacts. It provides appropriate probability distributions, by month, for 169 countries and autonomous-areas on temperature, precipitation, maximum temperature, maximum wind speed, humidity, runoff, soil moisture and evaporation for the historical period (1976-2005), and for decadal time periods to 2100. It also provides historical and future distributions for the Arctic region on ice concentration, ice thickness, age of ice, and ice ridging in 15-degree longitude arc segments from the Arctic Circle to 80 degrees latitude, plus two polar semicircular regions from 80 to 90 degrees latitude. The uncertainty is meant to describe the lack of knowledge rather than imprecision in the physical simulation because the emphasis is on unfalsified risk and its use to determine potential socioeconomic impacts. The full report is contained in 27 volumes.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2020

Experimental protocol for sea level projections from ISMIP6 stand-alone ice sheet models

Projection of the contribution of ice sheets to sea level change as part of the Coupled Model Intercomparison Project Phase 6 (CMIP6) takes the form of simulations from coupled ice sheet–climate models and stand-alone ice sheet models, overseen by the Ice Sheet Model Intercomparison Project for CMIP6 (ISMIP6). This paper describes the experimental setup for process-based sea level change projections to be performed with stand-alone Greenland and Antarctic ice sheet models in the context of ISMIP6. The ISMIP6 protocol relies on a suite of polar atmospheric and oceanic CMIP-based forcing for ice sheet models, in order to explore the uncertainty in projected sea level change due to future emissions scenarios, CMIP models, ice sheet models, and parameterizations for ice–ocean interactions. We describe here the approach taken for defining the suite of ISMIP6 stand-alone ice sheet simulations, document the experimental framework and implementation, and present an overview of the ISMIP6 forcing to be used by participating ice sheet modeling groups.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2018

The KLIWAS North Sea Climatology. Part II: Assessment against Global Reanalyses

Observational reference datasets are needed in atmosphere and ocean for quality assessments of climate models and for the evaluation of atmospheric reanalyses. To meet this demand on the regional scale, the Climate Water Navigation (KLIWAS) North Sea climatology (KNSC) was developed. This paper uses KNSC to assess the quality of five atmospheric reanalysis products [ERA-40; ERA-Interim; NCEP-1; 20CR, version 2 (20CRv2); and MERRA] over the North Sea from 1979 to 2001. Differences in sea level pressure (2-m air temperature) can be found in coastal regions for ERA-40/ERA-Interim and MERRA, and are more pronounced during positive (negative) phases of the NAO. 20CRv2 shows biases over the entire North Sea and all seasons of several hectopascals. ERA-40 and ERA-Interim show a negative 2-m air temperature bias relative to KNSC along the coastal mainland of Europe, especially during winter months, possibly a result of a remaining land influence. Mean differences result from winter and fall, mostly remaining within measurement uncertainties. Despite the upgrades in the model setup, ERA-Interim shows negligible differences from ERA-40. 20CRv2 and MERRA show positive (negative) biases during the summer (winter) half year. NCEP-1 follows ERA-40/ERA-Interim but mostly with slightly higher differences. All five reanalyses reproduce the decadal variability and climate shift signals present in KNSC fields. Overall, only 20CRv2 has to be considered as clearly unsatisfactorily regarding biases, MAE, and RMSE compared to all other datasets investigated. This study suggests that similar intercomparison studies, performed over other parts of the world’s oceans, especially coastal regions, can be very helpful in identifying shortcomings in atmospheric reanalysis products.

Engineering↗

DOE OSTI2026

Rates of Sea‐Level Rise Are Highly Sensitive to Ice Viscosity Parameters in Model Benchmarks

Glacier flow plays a major role in current and future rates of globally averaged sea-level rise. The viscosity of glacial ice, controlling the rate of flow, decreases as stress increases and is highly sensitive to the value of the stress exponent, $n$, in the constitutive equation for viscous flow. Glaciologists and climate modelers almost exclusively assume $n=3$ when modeling ice flow and projecting sea-level rise through forward modeling. However, recent work suggests that $n\approx 4$ better fits observations, prompting the question: How sensitive are projections of sea-level rise to the value of $n$? We use an established community ice flow model and standard benchmark experiments designed as an idealized representation of Pine Island Glacier, West Antarctica. While initializing an $n=3$ model to match observations of an $n=4$ ice sheet is possible, we find that incorrectly assuming $n=3$ when in fact $n=4$ dramatically underestimates rates of sea-level rise. The scale of this error grows nonlinearly with the magnitude of the climate forcing, acting to increase projection uncertainties. Additionally, we find that models often account for this stress-dependent rheology mismatch during model initialization in a way that masks this rheological effect in the short term while leaving model outputs vulnerable to larger biases in longer-term projections. Initializations to observations of Pine Island Glacier display similar rheology-mismatch fingerprints to our idealized example.

climate sensitivity↗

DOE OSTI2022

Understanding the Drivers of Atlantic Multidecadal Variability using a Stochastic Model Hierarchy

The relative importance of ocean and atmospheric dynamics in generating Atlantic Multidecadal Variability (AMV) remains an open question. Comparisons between climate models with SLAB and fully-dynamic (FULL) ocean components are often used to explore this question, but cannot reveal how individual ocean processes generate these differences. We build a hierarchy of physically interpretable stochastic models to investigate the contribution of two upper-ocean processes to AMV: the role of seasonal variation and mixed-layer entrainment. This interpretability arises from the stochastic model’s simplified representation of sea surface temperature (SST), considering only the local upper ocean response to white-noise atmospheric forcing and its impact on surface heat exchange. We focus on understanding differences between SLAB and FULL non-eddy resolving pre-industrial control simulations of the Community Earth System Model 1 (CESM), and estimate the stochastic model parameters from each respective simulation. Despite its simplicity, the stochastic model reproduces temporal characteristics of SST variability in the SPG, including reemergence, seasonal-to-interannual persistence and power spectra. Furthermore, unrealistically persistent SST of the CESM-SLAB ocean simulation is reproduced in the equivalent stochastic model configuration where the mixed-layer depth (MLD) is constant. The stochastic model also reveals that vertical entrainment primarily damps SST variability, thus explaining why SLAB exhibits larger SST variance than FULL. Here, the stochastic model driven by temporally stochastic, spatially coherent forcing patterns reproduces the canonical AMV pattern. However, the amplitude of low-frequency variability remains underestimated, suggesting a role for ocean dynamics beyond entrainment.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2014

Pathways of sulfate enhancement by natural and anthropogenic mineral aerosols in China

China, the world’s largest consumer of coal, emits approximately 30 million tons of sulfur dioxide (SO₂) per year. SO₂ is subsequently oxidized to sulfate in the atmosphere. However, large gaps exist between model-predicted and measured sulfate levels in China. Long-term field observations and numerical simulations were integrated to investigate the effect of mineral aerosols on sulfate formation. We found that mineral aerosols contributed a nationwide average of approximately 22% to sulfate production in 2006. The increased sulfate concentration was approximately 2 μg m⁻³ in the entire China. In East China and the Sichuan Basin, the increments reached 6.3 μg m⁻³ and 7.3 μg m⁻³, respectively. Mineral aerosols led to faster SO₂ oxidation through three pathways. First, more SO₂ was dissolved as cloud water alkalinity increased due to water-soluble mineral cations. Sulfate production was then enhanced through the aqueous-phase oxidation of S(IV) (dissolved sulfur in oxidation state +4). The contribution to the national sulfate production was 5%. Second, sulfate was enhanced through S(IV) catalyzed oxidation by transition metals. The contribution to the annual sulfate production was 8%, with 19% during the winter that decreased to 2% during the summer. Third, SO₂ reacts on the surface of mineral aerosols to produce sulfate. The contribution to the national average sulfate concentration was 9% with 16% during the winter and a negligible effect during the summer. The inclusion of mineral aerosols does resolve model discrepancies with sulfate observations in China, especially during the winter. These three pathways, which are not fully considered in most current chemistry-climate models, will significantly impact assessments regarding the effects of aerosol on climate change in China.

Huang, Xin↗

DOE OSTI2015

Climate change impacts on US agriculture and forestry: benefits of global climate stabilization

Increasing atmospheric carbon dioxide levels, higher temperatures, altered precipitation patterns, and other climate change impacts have already begun to affect US agriculture and forestry, with impacts expected to become more substantial in the future. There have been numerous studies of climate change impacts on agriculture or forestry, but relatively little research examining the long-term net impacts of a stabilization scenario relative to a case with unabated climate change. We provide an analysis of the potential benefits of global climate change mitigation for US agriculture and forestry through 2100, accounting for landowner decisions regarding land use, crop mix, and management practices. The analytic approach involves a combination of climate models, a crop process model (EPIC), a dynamic vegetation model used for forests (MC1), and an economic model of the US forestry and agricultural sector (FASOM-GHG). We find substantial impacts on productivity, commodity markets, and consumer and producer welfare for the stabilization scenario relative to unabated climate change, though the magnitude and direction of impacts vary across regions and commodities. Although there is variability in welfare impacts across climate simulations, we find positive net benefits from stabilization in all cases, with cumulative impacts ranging from $32.7 billion to $54.5 billion over the period 2015-2100. Our estimates contribute to the literature on potential benefits of GHG mitigation and can help inform policy decisions weighing alternative mitigation and adaptation actions.

agricultural modeling↗

DOE OSTI2024

Provincial-scale assessment of direct air capture to meet China’s climate neutrality goal under limited bioenergy supply

China has large, estimated potential for direct air carbon capture and storage (DACCS) but its deployment locations and impacts at the subnational scale remain unclear. This is largely because higher spatial resolution studies on carbon dioxide removal (CDR) in China have focused mainly on bioenergy with carbon capture and storage. This study uses a spatially detailed integrated energy-economy-climate model to evaluate DACCS for 31 provinces in China as the country pursues its goal of climate neutrality by 2060. We find that DACCS could expand China’s negative emissions capacity, particularly under sustainability-minded limits on bioenergy supply that are informed by bottom-up studies. But providing low-carbon electricity for multiple GtCO 2 yr -1 DACCS may require over 600 GW of additional wind and solar capacity nationwide and comprise up to 30% of electricity demand in China’s northern provinces. Investment requirements for DACCS range from 330 to 530 billion dollars by 2060 but could be repaid manyfold in the form of avoided mitigation costs, which DACCS deployment could reduce by up to $6 trillion over the same period. Enhanced efforts to lower residual CO 2 emissions that must be offset with CDR under a net-zero paradigm reduce but do not eliminate the use of DACCS for mitigation. For decision-makers and the energy-economy models guiding them, our results highlight the value of expanding beyond the current reliance on biomass for negative emissions in China.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2017

Low-Cloud Feedbacks from Cloud-Controlling Factors: A Review

Abstract The response to warming of tropical low-level clouds including both marine stratocumulus and trade cumulus is a major source of uncertainty in projections of future climate. Climate model simulations of the response vary widely, reflecting the difficulty the models have in simulating these clouds. These inadequacies have led to alternative approaches to predict low-cloud feedbacks. Here, we review an observational approach that relies on the assumption that observed relationships between low clouds and the “cloud-controlling factors” of the large-scale environment are invariant across time-scales. With this assumption, and given predictions of how the cloud-controlling factors change with climate warming, one can predict low-cloud feedbacks without using any model simulation of low clouds. We discuss both fundamental and implementation issues with this approach and suggest steps that could reduce uncertainty in the predicted low-cloud feedback. Recent studies using this approach predict that the tropical low-cloud feedback is positive mainly due to the observation that reflection of solar radiation by low clouds decreases as temperature increases, holding all other cloud-controlling factors fixed. The positive feedback from temperature is partially offset by a negative feedback from the tendency for the inversion strength to increase in a warming world, with other cloud-controlling factors playing a smaller role. A consensus estimate from these studies for the contribution of tropical low clouds to the global mean cloud feedback is 0.25 ± 0.18 W m −2 K −1 (90% confidence interval), suggesting it is very unlikely that tropical low clouds reduce total global cloud feedback. Because the prediction of positive tropical low-cloud feedback with this approach is consistent with independent evidence from low-cloud feedback studies using high-resolution cloud models, progress is being made in reducing this key climate uncertainty.

58 GEOSCIENCES↗

DOE OSTI2014

Recent seasonal asymmetric changes in the NAO (a marked summer decline and increased winter variability) and associated changes in the AO and Greenland Blocking Index

Recent changes are found in the means and variability of the North Atlantic Oscillation (NAO) index. There has been a sustained significant recent decrease in the summer NAO since the 1990s and, at the same time, a striking increase in variability of the winter – especially December – NAO that resulted in three of five (two of five) record high (record low) NAO Decembers occurring during 2004–2013 in the 115-year record. These NAO changes are related to an increasing trend in the Greenland Blocking Index (GBI, high pressure over Greenland) in summer and a more variable GBI in December. The enhanced early winter NAO variability originates mainly at the southern node of the NAO but is also related to the more variable GBI in December. Transition seasons (spring and autumn) have remained relatively unchanged over the last 30 years. These results are corroborated using several NAO indices. The Arctic Oscillation (AO) index, although strongly correlated with the NAO, does not show the recent sustained significant summer decrease, but it does show enhanced early winter variability. These recent observed changes are not present in the current generation of global climate models, although the latest process studies do offer insight into their causes. We invoke several plausible climate forcings and feedbacks to explain the recent NAO changes.

Meteorology & Atmospheric Sciences↗

DOE OSTI2014

Climate Science: Tropical Expansion by Ocean Swing

The tropical belt has become wider over the past decades, but climate models fall short of capturing the full rate of the expansion. The latest analysis of the climate simulations suggests that a long-term swing of the Pacific Decadal Oscillation is the main missing cause.

climate zone↗

DOE OSTI2017

A Hindcast Experiment Using the GCAM 3.0 Agriculture and Land-Use Module

We report results of a “hindcast” experiment focusing on the agricultural and land-use component of the Global Change Assessment Model (GCAM). We initialize GCAM to reproduce observed agriculture and land use in 1990 and forecast agriculture and land use patterns on 1-year time steps to 2010. We report overall model performance for 9 crops in 14 regions. We report areas where the hindcast is in relatively good agreement with observations and areas where the correspondence is poorer. We find that when given observed crop yields as input data, producers in GCAM implicitly have perfect foresight for yields leading to over compensation for year-to-year yield variation. We explore a simple model in which planting decisions are based on expectations but production depends on actual yields and find that this addresses the implicit perfect foresight problem. Second, while existing policies are implicitly calibrated into IAMs, changes in those policies over the period of analysis can have a dramatic effect on the fidelity model output. Third, we demonstrate that IAMs can employ techniques similar to those used by the climate modeling community to evaluate model skill. We find that hindcasting has the potential to yield substantial benefits to the IAM community.

hindcast, gc, agriculture and landuse modeling, va↗

DOE OSTI2020

Soil moisture and hydrology projections of the permafrost region – a model intercomparison

Abstract. This study investigates and compares soil moisture and hydrology projections of broadly used land models with permafrost processes and highlights the causes and impacts of permafrost zone soil moisture projections. Climate models project warmer temperatures and increases in precipitation (P) which will intensify evapotranspiration (ET) and runoff in land models. However, this study shows that most models project a long-term drying of the surface soil (0–20 cm) for the permafrost region despite increases in the net air–surface water flux (P-ET). Drying is generally explained by infiltration of moisture to deeper soil layers as the active layer deepens or permafrost thaws completely. Although most models agree on drying, the projections vary strongly in magnitude and spatial pattern. Land models tend to agree with decadal runoff trends but underestimate runoff volume when compared to gauge data across the major Arctic river basins, potentially indicating model structural limitations. Coordinated efforts to address the ongoing challenges presented in this study will help reduce uncertainty in our capability to predict the future Arctic hydrological state and associated land–atmosphere biogeochemical processes across spatial and temporal scales.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2015

The effect of large-scale model time step and multiscale coupling frequency on cloud climatology, vertical structure, and rainfall extremes in a superparameterized GCM

The effect of global climate model (GCM) time step—which also controls how frequently global and embedded cloud resolving scales are coupled—is examined in the Superparameterized Community Atmosphere Model ver 3.0. Systematic bias reductions of time-mean shortwave cloud forcing (~10 W/m 2 ) and longwave cloud forcing (~5 W/m 2 ) occur as scale coupling frequency increases, but with systematically increasing rainfall variance and extremes throughout the tropics. An overarching change in the vertical structure of deep tropical convection, favoring more bottom-heavy deep convection as a global model time step is reduced may help orchestrate these responses. The weak temperature gradient approximation is more faithfully satisfied when a high scale coupling frequency (a short global model time step) is used. These findings are distinct from the global model time step sensitivities of conventionally parameterized GCMs and have implications for understanding emergent behaviors of multiscale deep convective organization in superparameterized GCMs. Lastly, the results may also be useful for helping to tune them.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2025

Boundary-Layer-Coupled and Decoupled Clouds in Global Storm-Resolving Models: Comparisons With the ARM Observations

The accurate representation of interactions between clouds and planetary boundary layer (PBL) is a persistent challenge in climate models, critical for simulating surface energy budget. The emergence of kilometer-grid-scale global storm resolving models (GSRMs) offers the potential for enhanced details of PBL processes in these complex interactions. This study evaluates the representation of PBL-coupled and decoupled clouds in nine GSRM simulations against extensive ground-based observations by the Department of Energy Atmospheric Radiation Measurement (ARM) program, across six sites encompassing diverse regimes such as marine and continental environments in tropics and midlatitude. By differentiating coupling based on the relative positions between cloud bases and PBL tops, our analysis focuses on the simulation of PBL height, cloud frequency, position and vertical extent. The GSRMs generally exhibit commendable agreements with observed cloud structures and PBL diurnal cycles across different ARM sites. In contrast to the relatively consistent representation of decoupled clouds, discrepancies exist between the simulated and the observed coupled clouds, particularly in areas of intense convection, for example, over tropical rainforests and mountainous regions. These biases are probably associated with the models' tendency to underestimate the boundary layer humidity and the frequency of coupled clouds within different ranges of PBL heights. This study underscores the importance for continuous improvements in the representation of boundary layer and convection within these global kilometer-grid-scale models.

54 ENVIRONMENTAL SCIENCES↗