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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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At least 433 records · Page 24

Generalized Aerosol/Chemistry Interface (GIANT): A Community Effort to Advance Collaborative Science across Weather and Climate Models

Atmospheric aerosol and chemistry modules are key elements in Earth system models (ESMs), as they predict air pollutant concentrations and properties that can impact human health, weather, and climate. The current uncertainty in climate projections is partly due to the inaccurate representation of aerosol direct and indirect forcing. Aerosol/chemistry parameterizations used within ESMs and other atmospheric models span large structural and parameter uncertainties that are difficult to assess independently of their host models. Moreover, there is a strong need for a standardized interface between aerosol/chemistry modules and the host model to facilitate portability of aerosol/chemistry parameterizations from one model to another, allowing not only a comparison between different parameterizations within the same modeling framework, but also quantifying the impact of different model frameworks on aerosol/chemistry predictions. To address this need, we have initiated a new community effort to coordinate the construction of a Generalized Aerosol/Chemistry Interface (GIANT) for use across weather and climate models. We aim to organize a series of community workshops and hackathons to design and build GIANT, which will serve as the interface between a range of aerosol/chemistry modules and the physics and dynamics components of atmospheric host models. GIANT will leverage ongoing efforts at the U.S. modeling centers focused on building next-generation ESMs and the international AeroCom initiative to implement this common aerosol/chemistry interface. GIANT will create transformative opportunities for scientists and students to conduct innovative research to better characterize structural and parametric uncertainties in aerosol/chemistry modules, and to develop a common set of aerosol/chemistry parameterizations.

54 ENVIRONMENTAL SCIENCES↗

The effect of nonlinear diffusive heat transport in a simple climate model

The effects of nonlinear diffusive heat transport in North's (1975) model is reexamined. By inserting the nonlinearity into the original energy balance equation rather than the spectrally transformed linear algebraic equations, and including one more mode in the spectral expansion, it is found that nonlinear diffusion does give a significantly different sensitivity for states near the current climate. For linear diffusion, an increase of 0.1% of the solar constant from the present value is sufficient to melt all the ice on the earth, whereas an increase of about five times as large is required for nonlinear diffusion. This difference in sensitivity shows the importance of dynamical modeling in simple climate models.

Lin, C. A.↗

The seasonal response of the Held-Suarez climate model to prescribed ocean temperature anomalies. I - Results of decadal integrations

Anomalies in ocean surface temperature have been identified as possible causes of variations in the climate of particular seasons or as a source of interannual climatic variability, and attempts have been made to forecast seasonal climate by using ocean temperatures as predictor variables. However, the seasonal atmospheric response to ocean temperature anomalies has not yet been systematically investigated with nonlinear models. The present investigation is concerned with ten-year integrations involving a model of intermediate complexity, the Held-Suarez climate model. The calculations have been performed to investigate the changes in seasonal climate which result from a fixed anomaly imposed on a seasonally varying, global ocean temperature field. Part I of the paper provides a report on the results of these decadal integrations. Attention is given to model properties, the experimental design, and the anomaly experiments.

Phillips, T. J.↗

Design for and efficient dynamic climate model with realistic geography

The long term climate sensitivity which include realistic atmospheric dynamics are severely restricted by the expense of integrating atmospheric general circulation models are discussed. Taking as an example models used at GSFC for this dynamic model is an alternative which is of much lower horizontal or vertical resolution. The model of Heid and Suarez uses only two levels in the vertical and, although it has conventional grid resolution in the meridional direction, horizontal resolution is reduced by keeping only a few degrees of freedom in the zonal wavenumber spectrum. Without zonally asymmetric forcing this model simulates a day in roughly 1/2 second on a CRAY. The model under discussion is a fully finite differenced, zonally asymmetric version of the Heid-Suarez model. It is anticipated that speeds can be obtained a few seconds a day roughly 50 times faster than moderate resolution, multilayer GCM's.

Suarez, M. J.↗

Accelerated Climate Model for Energy (ACME): Ocean and Sea-Ice Processes

The primary goal of this project was to understand the role of the ocean and sea-ice components in the evolution of the climate in both a high-resolution fully-coupled 1850 preindustrial control and present day transient climate simulations run using the Energy Exascale Earth System Model (E3SM), formerly known as the Accelerated Climate Model for Energy (ACME). Two distinct approaches to the initialization of the present day transients were tested: in the first, an ensemble of three transients used atmospheric reanalysis forced 0.1-degree ocean/sea-ice states, while a fourth transient was branched off the preindustrial control. Biases from the control were inherited by its successor transient, in particular, sea surface temperatures (SSTs) at high latitudes were too warm and too much northward meridional heat transport occurred in the North Atlantic Ocean. SSTs in the Northern Hemisphere and Atlantic meridional heat transport increased in the transients initialized from the ocean/sea-ice simulation over a 40-50 year period to largely resemble the transient branched off the control simulation. Excessive absorbed solar radiation (ASR) is considered to be responsible for the SST biases as well as the formation of mode waters in lighter density classes than in reality both in the Southern Ocean and the North Atlantic Ocean subtropical gyre. These mode waters ventilate the thermocline waters to the north of their formation sites explaining the excessive Atlantic meridional heat transport and some of the warming in the high-latitude North Atlantic Ocean after multiple decades.

54 ENVIRONMENTAL SCIENCES↗

Investigating Downscaling Methods and Evaluating Climate Models for Use in Estimating Regional Water Resources in Mountainous Regions under Changing Climatic Conditions

The purpose of this three-year study is to develop and evaluate techniques to estimate the range of potential hydrological impacts of climate change in mountainous areas. Three main objectives are set out in the proposal. (1) To develop and evaluate transfer functions to link tropospheric circulation to regional snowfall. (2) To evaluate a suite of General Circulation Models (GCMs) for use in estimating synoptic scale circulation and the resultant regional snowfall. And (3) to estimate the range of potential hydrological impacts of changing climate in the two case study areas: the Upper Colorado River basin, and the Catskill Mountains of southeastern New York State. Both regions provide water to large populations.

Frei, Allan↗

Springtime soil moisture, natural climatic variability, and North American drought as simulated by the NCAR Community Climate Model 1

Previous results concerning the role that summertime soil moisture reductions can play in amplifying or maintaining North American droughts are extended to include the role of springtime soil moisture reductions and the role that natural climatic variability, as expressed in soil moisture, can play. General circulation model (GCM) simulations with the NCAR Community Climate Model have been made with initial desert-like soil moisture anomalies imposed on 1 May and on 1 March. The May simulation maintained the imposed anomaly throughout the summer, while in the March simulation the anomaly was ameliorated within one month. Thus, the timing of soil moisture reductions may be crucial. A 10-year model control integration with prescribed sea surface temperatures yielded 1 year with late spring and summer soil moisture values similar to those of the 1 May anomaly simulation. This suggests that occasional widespread North American droughts may be an inherent feature of at least the GCM employed for this study. The results also demonstrate the important role played by moisture transport from the Gulf of Mexico in modulating or ameliorating drought conditions for much of the south-central United States, a topic that requires considerable further investigation.

Oglesby, Robert J.↗

Investigating Mars South Residual CO2 Cap with a Global Climate Model

The CO2 cycle is one of the three controlling climate cycles on Mars. One aspect of the CO2 cycle that is not yet fully understood is the existence of a residual CO2 ice cap that is offset from the south pole. Previous investigations suggest that the atmosphere may control the placement of the south residual cap (e.g., Colaprete et al., 2005). These investigations show that topographically forced stationary eddies in the south during southern hemisphere winter produce colder atmospheric temperatures and increased CO2 snowfall over the hemisphere where the residual cap resides. Since precipitated CO2 ice produces higher surface albedos than directly deposited CO2 ice, it is plausible that CO2 snowfall resulting from the zonally asymmetric atmospheric circulation produces surface ice albedos high enough to maintain a residual cap only in one hemisphere. The goal of the current work is to further evaluate Colaprete et al.'s hypothesis by investigating model-predicted seasonally varying snowfall patterns in the southern polar region and the atmospheric circulation components that control them.

CO2 cycle↗

Update and Status of the Mars Climate Modeling Center at NASA Ames Research Center

NASA Ames Research Center has a long-established history in the study and numerical modeling of Mars’ atmosphere and climate. Such studies began with the late Jim Pollack and have continued under the leaderships of Bob Haberle, Jeff Hollingsworth, and now Melinda Kahre. Our group has grown to more than 10 members, including civil servants, research scientists, postdocs, and students. While we still prioritize science and the model development that supports it, we have recently enhanced efforts to make our codes and output publicly available and boost community engagement through the hosting of modeling tutorials, etc. Here our goal is to present the status of the Ames Mars GCM, our ongoing science projects, the tools we have recently made publicly available, and our plans for releases and continued community engagement.

M. A. Kahre↗

Latitude-dependent sensitivity to stationary perturbations in simple climate models

The steady-state zonally averaged climate is perturbed by adding a latitude-dependent heat source to an energy balance equation of the simplified Budyko-Sellers type. The latitude of the ice edge, which is attached to an isotherm, becomes dependent on the strength of the perturbation. This dependence is given in terms of the well-known iceline-solar constant relation, and the latitude dependence of the perturbed temperature field is then uniquely determined. The exact analytical solution is linearized and expressed in terms of a superposition of line sources at various latitudes. The main features are: (1) The total temperature response is a sum of the direct effect of the perturbation and an indirect ice-albedo effect proportional to the solar ice-edge sensitivity; and (2) the indirect feedback effect produces an enhanced response in polar latitudes.

Salmun, H.↗

Ensemble Spread Behavior in Coupled Climate Models: Insights From the Energy Exascale Earth System Model Version 1 Large Ensemble

AbstractAssessing uncertainty in future climate projections requires understanding both internal climate variability and external forcing. For this reason, single‐model initial condition large ensembles (SMILEs) run with Earth System Models (ESMs) have recently become popular. Here we present a new 20‐member SMILE with the Energy Exascale Earth System Model version 1 (E3SMv1‐LE), which uses a “macro” initialization strategy choosing coupled atmosphere/ocean states based on inter‐basin contrasts in ocean heat content (OHC). The E3SMv1‐LE simulates tropical climate variability well, albeit with a muted warming trend over the twentieth century due to overly strong aerosol forcing. The E3SMv1‐LE's initial climate spread is comparable to other (larger) SMILEs, suggesting that maximizing inter‐basin ocean heat contrasts may be an efficient method of generating ensemble spread. We also compare different ensemble spread across multiple SMILEs, using surface air temperature and OHC. The Community Earth system Model version 1, the only ensemble which utilizes a “micro” initialization approach perturbing only atmospheric initial conditions, yields lower spread in the first ∼30 years. The E3SMv1‐LE exhibits a relatively large spread, with some evidence for anthropogenic forcing influencing spread in the late twentieth century. However, systematic effects of differing “macro” initialization strategies are difficult to detect, possibly resulting from differing model physics or responses to external forcing. Notably, the method of standardizing results affects ensemble spread: control simulations for most models have either large background trends or multi‐centennial variability in OHC. This spurious disequlibrium behavior is a substantial roadblock to understanding both internal climate variability and its response to forcing.

Stevenson, Samantha↗

Response of the Quasi–Biennial Oscillation to a warming climate in global climate models

We compare the response of the Quasi–Biennial Oscillation (QBO) to a warming climate in eleven atmosphere general circulation models that performed time–slice simulations for present–day, doubled, and quadrupled CO 2 climates. No consistency was found among the models for the QBO period response, with the period decreasing by 8 months in some models and lengthening by up to 13 months in others in the doubled CO 2 simulations. In the quadrupled CO 2 simulations, a reduction in QBO period of 14 months was found in some models, whereas in several others the tropical oscillation no longer resembled the present–day QBO, although it could still be identified in the deseasonalized zonal mean zonal wind timeseries. In contrast, all the models projected a decrease in the QBO amplitude in a warmer climate with the largest relative decrease near 60 hPa. In simulations with doubled and quadrupled CO 2 , the multi–model mean QBO amplitudes decreased by 36 and 51%, respectively. Across the models the differences in the QBO period response were most strongly related to how the gravity wave momentum flux entering the stratosphere and tropical vertical residual velocity responded to the increases in CO 2 amounts. Likewise it was found that the robust decrease in QBO amplitudes was correlated across the models to changes in vertical residual velocity, parametrized gravity wave momentum fluxes, and to some degree the resolved upward wave flux. Here, we argue that uncertainty in the representation of the parameterized gravity waves is the most likely cause of the spread among the eleven models in the QBO's response to climate change.

54 ENVIRONMENTAL SCIENCES↗

AMOC stability and diverging response to Arctic sea ice decline in two climate models

This study compares the impacts of Arctic sea ice decline on the Atlantic meridional overturning circulation (AMOC) in two configurations of the Community Earth System Model with different horizontal resolution. In a suite of model experiments, we impose radiative imbalance at the ice surface, replicating a loss of sea ice cover comparable to that observed during 1979–2014, and we find dramatic differences in the AMOC response between the two models. In the lower-resolution configuration, the AMOC weakens by about one-third over the first 100 years, approaching a new quasi-equilibrium. By contrast, in the higher-resolution configuration, the AMOC weakens by ~10% during the first 20–30 years followed by a full recovery driven by invigorated deep water formation in the Labrador Sea and adjacent regions. We investigate these differences using a diagnostic AMOC stability indicator, which reflects the AMOC freshwater transport in and out of the basin and hence the strength of the basin-scale salt-advection feedback. This indicator suggests that the AMOC in the lower-resolution model is less stable and more sensitive to surface perturbations, as confirmed by hosing experiments mimicking Arctic freshening due to sea ice decline. Differences between the models’ mean states, including the Atlantic Ocean mean surface freshwater fluxes, control the differences in AMOC stability. Our results demonstrate that the AMOC stability indicator is indeed useful for evaluating AMOC sensitivity to perturbations. We emphasize that, despite the differences in the long-term adjustment, both models simulate a multidecadal AMOC weakening caused by Arctic sea ice decline, relevant to climate change.

54 ENVIRONMENTAL SCIENCES↗

The Dynamics of Megafire Smoke Plumes in Climate Models: Why a Converged Solution Matters for Physical Interpretations

As the climate system warms, megafires have become more frequent with devastating effects. A byproduct of these events is the creation of smoke plumes that can rise into the stratosphere and spread across the globe where they reside for many months. To gain a deeper understanding of the plume dynamics, global climate simulations of a megafire were performed at a wide range of grid spacings from 2.0° down to 7 km, including a 7 km nonhydrostatic experiment. The analysis focuses on how the resolved dynamics affects the specification of the plume characteristics such as injection height and black carbon (BC) mass. Prior studies initialize the smoke plume at one or a few grid points and this is shown here to produce severely dissipative dynamics. In order to validate such simulations with observations, enhancements of the plume characteristics to offset the dissipation is necessary. Using a numerically converged simulation, sensitivity tests show that to approximate the observed stratospheric lifetime, a reduction in BC fraction by 50% is necessary for external mixtures. The vorticity dynamics of the plume is also analyzed with a Lagrangian budget to understand the mechanisms responsible for the evolution of a collocated anticyclonic vortex. The results can be distilled down into a simple conceptual model. As the plume rises, the air diverges at the top of the updraft where the largest concentrations of smoke are found. This divergence induces a dilution of the background cyclonic absolute vorticity producing an anticyclonic vortex. Vortex decay occurs from opposite arguments.

54 ENVIRONMENTAL SCIENCES↗

POPSnet-SGP: A Pilot Aerosol Microphysics Network for Targeting Climate Model Uncertainty Interim Field Campaign Report

Aerosols mediate the radiative fluxes in clear and cloudy skies and dominate the uncertainty in the radiative forcing of climate. Relatively dense networks of aerosol optical depth measurements have been used to effectively constrain simulated aerosol optical properties, but model diversity of aerosol microphysical properties is much larger (Mann et al. 2014, Myhre et al. 2009). A better understanding of aerosol microphysics is essential as they are the fundamental pieces of information required to convert aerosol emissions information to radiative and cloud-nucleating properties that drive radiative effects and forcing of climate. Model representation of aerosol microphysical properties has lagged in part due to their inherently greater spatial variability, but also due to a lack of available observations. This project – the Printed Optical Particle Spectrometer Network (POPSnet)-Southern Great Plains (SGP) Pilot – launched the first spatially dense network of aerosol size distribution measurements over an area the size of a global model grid cell and demonstrated its use in providing valuable information regarding the spatial variability of aerosol microphysical properties and its drivers for improving model constraints.

54 ENVIRONMENTAL SCIENCES↗

Combining artificial intelligence, Earth observations, and climate models to improve predictability of ice-biogeochemistry interactions

Focal Area: Predictive Modeling. We describe how artificial intelligence (AI) can be combined with state-of-the-science Earth system models to better predict future regional climate responses. To demonstrate, we describe a case study in biogeochemical interactions with sea ice. Science Challenge: Biogeochemical models are poorly constrained for high latitude systems. Machine learning methods and edge computing can be combined with Earth system models, such as the Energy Exascale Earth System Model (E3SM), to gain insight into ice-biogeochemical interactions and improve sea ice extent prediction.

54 ENVIRONMENTAL SCIENCES↗

Modelling climate change impacts on maize yields under low nitrogen input conditions in sub‐Saharan Africa

Smallholder farmers in sub‐Saharan Africa (SSA) currently grow rainfed maize with limited inputs including fertilizer. Climate change may exacerbate current production constraints. Crop models can help quantify the potential impact of climate change on maize yields, but a comprehensive multimodel assessment of simulation accuracy and uncertainty in these low‐input systems is currently lacking. We evaluated the impact of varying [CO2], temperature and rainfall conditions on maize yield, for different nitrogen (N) inputs (0, 80, 160 kg N/ha) for five environments in SSA, including cool subhumid Ethiopia, cool semi‐arid Rwanda, hot subhumid Ghana and hot semi‐arid Mali and Benin using an ensemble of 25 maize models. Models were calibrated with measured grain yield, plant biomass, plant N, leaf area index, harvest index and in‐season soil water content from 2‐year experiments in each country to assess their ability to simulate observed yield. Simulated responses to climate change factors were explored and compared between models. Calibrated models reproduced measured grain yield variations well with average relative root mean square error of 26%, although uncertainty in model prediction was substantial (CV = 28%). Model ensembles gave greater accuracy than any model taken at random. Nitrogen fertilization controlled the response to variations in [CO2], temperature and rainfall. Without N fertilizer input, maize (i) benefited less from an increase in atmospheric [CO2], (ii) was less affected by higher temperature or decreasing rainfall and (iii) was more affected by increased rainfall because N leaching was more critical. The model inter-comparison revealed that simulation of daily soil N supply and N leaching plays a crucial role in simulating climate change impacts for low-input systems. Climate change and N input interactions have strong implications for the design of robust adaptation practices across SSA, because the impact of climate change will be modified if farmers intensify maize production with more mineral fertilizer.

Crop simulation model↗

Numerically Relevant Timescales in the MG2 Microphysics Model

Climate models rely on parameterizations of a variety of processes in the atmospheric physics, but a common concern is that the temporal resolution is too coarse to consistently resolve the behavior that individual parameterizations are designed to capture. This study examines timescales numerically derived from the Morrison-Gettelman (MG2) microphysics as implemented within the Energy Exascale Earth System Model, version 1 (E3SMv1). Numerically relevant timescales in MG2 are derived by computing the eigenspectrum of its Jacobian. These timescales are found to often be smaller than the default 5 min time step used for MG2. The fast timescales are then heuristically connected to individual microphysics processes. By substepping a few particular rain processes within MG2, the time discretization error for those processes was considerably reduced with minimal additional expense to the overall microphysics. While this improvement has a substantial effect on the target processes and on the vertical distribution of stratiform-derived rain within E3SMv1, the overall model climate is found to not be sensitive to MG2 time step. Here, we hypothesize that this is because the surface climate does not depend strongly on certain process rates, especially MG2's rain evaporation rate.

58 GEOSCIENCES↗