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At least 37 records · Page 2

Regional Climate Simulation Experiments with a Variable Resolution Stretched Grid GCM

The variable resolution stretched grid (SG) version of the Goddard Earth Observing System (GEOS) GCM has been recently developed and tested in a regional climate simulation mode. The SG-approach is an alternative to the widely used nested grid approach introduced a decade ago as a pioneering step to regional climate modeling. The region of interest with a uniform about 60 km resolution used in experiments is a rectangle over the U.S. The results of one annual as well as two-month simulations for the anomalous climate event of the U.S. drought of 1988, are validated against data analysis fields and diagnostics. The efficient regional down-scaling as well as the positive impact of fine regional resolution, are obtained. The SG-concept appeared to be a promising candidate for regional and subregional climate studies and applications.

Takacs, Lawrence L.↗

Regional Warming from Aerosol Removal over the United States: Results from a Transient 2010-2050 Climate Simulation

We use a general circulation model (NASA Goddard Institute for Space Studies GCM 3) to investigate the regional climate response to removal of aerosols over the United States. We perform a pair of transient 2010e2050 climate simulations following a scenario of increasing greenhouse gas concentrations, with and without aerosols over the United States and with present-day aerosols elsewhere. We find that removing U.S. aerosol significantly enhances the warming from greenhouse gases in a spatial pattern that strongly correlates with that of the aerosol. Warming is nearly negligible outside the United States, but annual mean surface temperatures increase by 0.4e0.6 K in the eastern United States. Temperatures during summer heat waves in the Northeast rise by as much as 1e2 K due to aerosol removal, driven in part by positive feedbacks involving soil moisture and low cloud cover. Reducing U.S. aerosol sources to achieve air quality objectives could thus have significant unintended regional warming consequences.

Mickley, L. J.↗

Interactive Ozone and Methane Chemistry in GISS-E2 Historical and Future Climate Simulations

The new generation GISS climate model includes fully interactive chemistry related to ozone in historical and future simulations, and interactive methane in future simulations. Evaluation of ozone, its tropospheric precursors, and methane shows that the model captures much of the largescale spatial structure seen in recent observations. While the model is much improved compared with the previous chemistry-climate model, especially for ozone seasonality in the stratosphere, there is still slightly too rapid stratospheric circulation, too little stratosphere-to-troposphere ozone flux in the Southern Hemisphere and an Antarctic ozone hole that is too large and persists too long. Quantitative metrics of spatial and temporal correlations with satellite datasets as well as spatial autocorrelation to examine transport and mixing are presented to document improvements in model skill and provide a benchmark for future evaluations. The difference in radiative forcing (RF) calculated using modeled tropospheric ozone versus tropospheric ozone observed by TES is only 0.016W/sq. m. Historical 20th Century simulations show a steady increase in whole atmosphere ozone RF through 1970 after which there is a decrease through 2000 due to stratospheric ozone depletion. Ozone forcing increases throughout the 21st century under RCP8.5 owing to a projected recovery of stratospheric ozone depletion and increases in methane, but decreases under RCP4.5 and 2.6 due to reductions in emissions of other ozone precursors. RF from methane is 0.05 to 0.18W/ sq. m higher in our model calculations than in the RCP RF estimates. The surface temperature response to ozone through 1970 follows the increase in forcing due to tropospheric ozone. After that time, surface temperatures decrease as ozone RF declines due to stratospheric depletion. The stratospheric ozone depletion also induces substantial changes in surface winds and the Southern Ocean circulation, which may play a role in a slightly stronger response per unit forcing during later decades. Tropical precipitation shifts south during boreal summer from 1850 to 1970, but then shifts northward from 1970 to 2000, following upper tropospheric temperature gradients more strongly than those at the surface.

Ozone↗

Sensitivity of a GCM climate simulation to differences in continental versus maritime cloud drop size

Extensive observations indicate a distinct difference between maritime and continental effective drop size, r(sub e), for warm clouds. The latest version of the National Center for Atmospheric Research (NCAR) Community Climate Model (CCM2) is used to explore the sensitivity of differentiating between continental and maritime r(sub e) on the simulated climate. The results of this study indicate that the smaller drop size over continents leads to a reduction of surface-absorbed solar radiation from 20 to 60 W/sq m. This reduction in surface solar flux leads to a cooling of the continents by up to -3.5 K. The reduction in surface solar flux and temperature also leads to a reduction in latent heat flux and precipitation over land. In the January simulation, there is a significant shift in tropical precipitation associated with the Australian monsoon. This shift leads to a response in the extra tropical geopotential height field over the western United States. All of these changes reduce biases in the current version of CCM2.

Kiehl, J. T.↗

Snow Physics and Meltwater Hydrology of the SSiB Model Employed for Climate Simulation Studies with GEOS 2 GCM

Present-day climate models produce large climate drifts that interfere with the climate signals simulated in modelling studies. The simplifying assumptions of the physical parameterization of snow and ice processes lead to large biases in the annual cycles of surface temperature, evapotranspiration, and the water budget, which in turn causes erroneous land-atmosphere interactions. Since land processes are vital for climate prediction, and snow and snowmelt processes have been shown to affect Indian monsoons and North American rainfall and hydrology, special attention is now being given to cold land processes and their influence on the simulated annual cycle in GCMs. The snow model of the SSiB land-surface model being used at Goddard has evolved from a unified single snow-soil layer interacting with a deep soil layer through a force-restore procedure to a two-layer snow model atop a ground layer separated by a snow-ground interface. When the snow cover is deep, force-restore occurs within the snow layers. However, several other simplifying assumptions such as homogeneous snow cover, an empirical depth related surface albedo, snowmelt and melt-freeze in the diurnal cycles, and neglect of latent heat of soil freezing and thawing still remain as nagging problems. Several important influences of these assumptions will be discussed with the goal of improving them to better simulate the snowmelt and meltwater hydrology. Nevertheless, the current snow model (Mocko and Sud, 2000, submitted) better simulates cold land processes as compared to the original SSiB. This was confirmed against observations of soil moisture, runoff, and snow cover in global GSWP (Sud and Mocko, 1999) and point-scale Valdai simulations over seasonal snow regions. New results from the current snow model SSiB from the 10-year PILPS 2e intercomparison in northern Scandinavia will be presented.

Mocko, David M.↗

Regional Climate Simulation of the Anomalous Events of 1998 using a Stretched-Grid GCM with Multiple Areas of Interest

The GEOS (Goddard Earth Observing System) stretched-grid (SG) GCM developed and thoroughly tested over the last few years, is used for simulating the major anomalous regional climate events of 1998. The anomalous regional climate events are simulated simultaneously during the 13 months long (November-1997 - December-1998) SG-GCM simulation due to using the new SG-design with multiple (four) areas of interest. The following areas/regions of interest (one at each global quadrant) are implemented: U.S./Northern Mexico, the El-Nino/Brazil area, India-China, and Eastern Indian Ocean/Australia.

Fox-Rabinovitz, M. S.↗

A GPU‐Based Ocean Dynamical Core for Routine Mesoscale‐Resolving Climate Simulations

Abstract We describe an ocean hydrostatic dynamical core implemented in Oceananigans optimized for Graphical Processing Unit (GPU) architectures. On 64 A100 GPUs, equivalent to 16 computational nodes in current state‐of‐the‐art supercomputers, our dynamical core can simulate a decade of near‐global ocean dynamics per wall‐clock day at an 8‐km horizontal resolution; a resolution adequate to resolve the ocean's mesoscale eddy field. Such efficiency, achieved with relatively modest hardware resources, suggests that climate simulations on GPUs can incorporate fully eddy‐resolving ocean models. This removes a major source of systematic bias in current IPCC coupled model projections, the parameterization of ocean eddies, and represents a major advance in climate modeling. We discuss the computational strategies, focusing on GPU‐specific optimization and numerical implementation details that enable such high performance.

Silvestri, Simone [Massachusetts Institute of Tech↗

Regional Climate Simulation and Data Assimilation with Variable-Resolution GCMs

Variable resolution GCMs using a global stretched grid (SG) with enhanced regional resolution over one or multiple areas of interest represents a viable new approach to regional climateklimate change and data assimilation studies and applications. The multiple areas of interest, at least one within each global quadrant, include the major global mountains and major global monsoonal circulations over North America, South America, India-China, and Australia. They also can include the polar domains, and the European and African regions. The SG-approach provides an efficient regional downscaling to mesoscales, and it is an ideal tool for representing consistent interactions of globaYlarge- and regionallmeso- scales while preserving the high quality of global circulation. Basically, the SG-GCM simulations are no different from those of the traditional uniform-grid GCM simulations besides using a variable-resolution grid. Several existing SG-GCMs developed by major centers and groups are briefly described. The major discussion is based on the GEOS (Goddard Earth Observing System) SG-GCM regional climate simulations.

Fox-Rabinovitz, Michael S.↗

Unprecedented cloud resolution in a GPU-enabled full-physics atmospheric climate simulation on OLCF’s summit supercomputer

Clouds represent a key uncertainty in future climate projection. While explicit cloud resolution remains beyond our computational grasp for global climate, we can incorporate important cloud effects through a computational middle ground called the Multi-scale Modeling Framework (MMF), also known as Super Parameterization. This algorithmic approach embeds high-resolution Cloud Resolving Models (CRMs) to represent moist convective processes within each grid column in a Global Climate Model (GCM). The MMF code requires no parallel data transfers and provides a self-contained target for acceleration. This study investigates the performance of the Energy Exascale Earth System Model-MMF (E3SM-MMF) code on the OLCF Summit supercomputer at an unprecedented scale of simulation. Hundreds of kernels in the roughly 10K lines of code in the E3SM-MMF CRM were ported to GPUs with OpenACC directives. A high-resolution benchmark using 4600 nodes on Summit demonstrates the computational capability of the GPU-enabled E3SM-MMF code in a full physics climate simulation.

58 GEOSCIENCES↗

Framework for idealized climate simulations with spatiotemporal stochastic clouds and planetary-scale circulations

In climate predictions, clouds are the leading source of uncertainty. This is partly because, to simulate the fluid dynamics of climate over the entire globe, a large grid spacing must be used, so clouds are a subgrid-scale parametrization rather than a resolved feature. Here, a framework is investigated with finer grid spacing of O(1) or O(10)km so that some clouds are not subgrid-scale; instead, clouds evolve on the numerical grid. This cloud evolution is achieved using stochastic modeling. Hence, the framework is idealized in the sense that the full fluid dynamics of cloud circulations is still not resolved, and simplified vertical structures are used. Nevertheless, the fluid dynamics model includes evolving clouds that interactively adjust in size, shape, lifetime, and regional coverage. In addition, different cloud types are included with different roles in the climate system, including deep convective clouds and also boundary-layer clouds such as shallow cumulus and stratocumulus clouds. Other basic aspects of the idealized climate system are planetary-scale circulations (e.g., Walker circulation) and radiation. With these ingredients (evolving clouds, planetary-scale circulations, and radiation), the framework has the potential for idealized investigations of climate change with interactive cloud–radiative feedback of individual clouds. Here, the formulation of the model equations is presented, and numerical simulations are shown to illustrate the model dynamics and climate change.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

The Aqua-Planet Experiment (APE): CONTROL SST Simulation

Climate simulations by 16 atmospheric general circulation models (AGCMs) are compared on an aqua-planet, a water-covered Earth with prescribed sea surface temperature varying only in latitude. The idealised configuration is designed to expose differences in the circulation simulated by different models. Basic features of the aqua-planet climate are characterised by comparison with Earth. The models display a wide range of behaviour. The balanced component of the tropospheric mean flow, and mid-latitude eddy covariances subject to budget constraints, vary relatively little among the models. In contrast, differences in damping in the dynamical core strongly influence transient eddy amplitudes. Historical uncertainty in modelled lower stratospheric temperatures persists in APE.Aspects of the circulation generated more directly by interactions between the resolved fluid dynamics and parameterized moist processes vary greatly. The tropical Hadley circulation forms either a single or double inter-tropical convergence zone (ITCZ) at the equator, with large variations in mean precipitation. The equatorial wave spectrum shows a wide range of precipitation intensity and propagation characteristics. Kelvin mode-like eastward propagation with remarkably constant phase speed dominates in most models. Westward propagation, less dispersive than the equatorial Rossby modes, dominates in a few models or occurs within an eastward propagating envelope in others. The mean structure of the ITCZ is related to precipitation variability, consistent with previous studies.The aqua-planet global energy balance is unknown but the models produce a surprisingly large range of top of atmosphere global net flux, dominated by differences in shortwave reflection by clouds. A number of newly developed models, not optimised for Earth climate, contribute to this. Possible reasons for differences in the optimised models are discussed.The aqua-planet configuration is intended as one component of an experimental hierarchy used to evaluate AGCMs. This comparison does suggest that the range of model behaviour could be better understood and reduced in conjunction with Earth climate simulations. Controlled experimentation is required to explore individual model behavior and investigate convergence of the aqua-planet climate with increasing resolution.

AGCM↗

Crowdsourcing the Frontier: Advancing Hybrid Physics‐ML Climate Simulation via a $\$$50,000 Kaggle Competition

Subgrid machine-learning (machine learning [ML]) parameterizations have the potential to introduce a new generation of climate models that incorporate the effects of higher-resolution physics without incurring the prohibitive computational cost associated with more explicit physics-based simulations. However, important issues, ranging from online instability to inconsistent online performance, have limited their operational use for long-term climate projections. To more rapidly drive progress in solving these issues, domain scientists and ML researchers opened up the offline aspect of this problem to the broader ML and data science community with the release of ClimSim, a NeurIPS Data sets and Benchmarks publication, and an associated Kaggle competition. This paper reports on the downstream results of the Kaggle competition by coupling emulators inspired by the winning teams' architectures to an interactive climate model (including full cloud microphysics, a regime historically prone to online instability) and systematically evaluating their online performance. Our results demonstrate that online stability in the low-resolution real-geography setting is reproducible across multiple diverse architectures, which we consider a key milestone. All tested architectures exhibit strikingly similar offline and online biases, though their responses to architecture-agnostic design choices (e.g., expanding the list of input variables) can differ significantly. Multiple Kaggle-inspired architectures achieve state-of-the-art results on certain metrics such as zonal mean bias patterns and global Root Mean Squared Error, indicating that crowdsourcing the essence of the offline problem is one path to improving online performance in hybrid physics-AI climate simulation.

Environmental sciences↗

Accelerated Snowmelt Protocol to Simulate Climate Change Induced Impacts on Snowpack Dependent Ecosystems

Field studies that simulate the effects of climate change are important for a predictive understanding of ecosystem responses to a changing environment. Among many concerns, regional warming can result in advanced timing of spring snowmelt in snowpack dependent ecosystems, which could lead to longer snow-free periods and drier summer soils. Past studies investigating these impacts of climate change have manipulated snowmelt with a variety of techniques that include manual snowpack alteration with a shovel, infrared radiation, black sand and fabric covers. Within these studies however, sufficient documentation of methods is limited, which can make experimental reproduction difficult. Here, we outline a detailed plot-scale protocol that utilizes a permeable black geotextile fabric deployed on top of an isothermal spring snowpack to induce advanced snowmelt. The method offers a reliable and cost-effective approach to induce snowmelt by passively increasing solar radiation absorption at the snow surface. In addition, control configurations with no snowpack manipulation are paired adjacent to the induced snowmelt plot for experimental comparison. Past and ongoing deployments in Colorado subalpine ecosystems indicate that this approach can accelerate snowmelt by 14-23 days, effectively mimicking snowmelt timing at lower elevations. This protocol can be applied to a variety of studies to understand the hydrological, ecological, and geochemical impacts of regional warming in snowpack dependent ecosystems.

54 ENVIRONMENTAL SCIENCES↗

A hierarchical evaluation framework for assessing climate simulations relevant to the energy-water-land nexus (Final Report)

The overarching goal was to construct a hierarchy of new and well-tested metrics and analysis tools that support both fundamental and use-inspired research. Motivating this goal was a convergence of needs from climate scientists and stakeholders alike for a systematic, robust framework of model evaluation and diagnosis to provide scientific insights, inform model development, support best practices for the use of climate model outputs, and facilitate communication of climate information in the evolving landscapes of multi-model, multi-resolution, and large ensemble simulations that generate terabytes of data for any single climate run. Steps toward attaining these goals benefited from expertise and established capability of the project team, which included leadership of the North American Regional Climate Change Assessment Program (NARCCAP) and the Coordinated Regional Downscaling Experiment (CORDEX), development of hierarchical model evaluation approaches, and successful research in the analysis and diagnosis of climate model skill, as well as the understanding and modeling of regional climate processes in North America. As part of the overarching goal, the project worked to disseminate a suite of methodologies, algorithms, and software components that the wider community can employ to advance climate science and applications. With rigorous demonstration, the evaluation framework and the mix of standard and high risk / high reward approaches helped form the basis for future development of a computationally enabled user-friendly system for community use.

17 WIND ENERGY↗

Radiative Forcing in the ACCMIP Historical and Future Climate Simulations

A primary goal of the Atmospheric Chemistry and Climate Model IntercomparisonProject (ACCMIP) was to characterize the short-lived drivers of preindustrial to 2100climate change in the current generation of climate models. Here we evaluate historicaland 5 future radiative forcing in the 10 ACCMIP models that included aerosols, 8 of whichalso participated in the Coupled Model Intercomparison Project phase 5 (CMIP5).The models generally reproduce present-day climatological total aerosol opticaldepth (AOD) relatively well. components to this total, however, and most appear to underestimate AOD over East10 Asia. The models generally capture 1980-2000 AOD trends fairly well, though theyunderpredict AOD increases over the YellowEastern Sea. They appear to strongly underestimate absorbing AOD, especially in East Asia, South and Southeast Asia, SouthAmerica and Southern Hemisphere Africa.We examined both the conventional direct radiative forcing at the tropopause (RF) and the forcing including rapid adjustments (adjusted forcing AF, including direct andindirect effects). The models calculated all aerosol all-sky 1850 to 2000 global meanannual average RF ranges from 0.06 to 0.49 W m(sup -2), with a mean of 0.26 W m(sup -2) and a median of 0.27 W m(sup -2. Adjusting for missing aerosol components in some modelsbrings the range to 0.12 to 0.62W m(sup -2), with a mean of 0.39W m(sup -2). Screen20ing the models based on their ability to capture spatial patterns and magnitudes ofAOD and AOD trends yields a quality-controlled mean of 0.42W m(sup -2) and range of0.33 to 0.50 W m(sup -2) (accounting for missing components). The CMIP5 subset of ACCMIPmodels spans 0.06 to 0.49W m(sup -2), suggesting some CMIP5 simulations likelyhave too little aerosol RF. A substantial, but not well quantified, contribution to histori25cal aerosol RF may come from climate feedbacks (35 to 58). The mean aerosol AF during this period is 1.12W m(sup -2) (median value 1.16W m(sup -2), range 0.72 to1.44W m(sup -2), indicating that adjustments to aerosols, which include cloud, water vaporand temperature, lead to stronger forcing than the aerosol direct RF.

Climate Models↗

Evaluating the Dominant Components of Warming in Pliocene Climate Simulations

The Pliocene Model Intercomparison Project (PlioMIP) is the first coordinated climate model comparison for a warmer palaeoclimate with atmospheric CO2 significantly higher than pre-industrial concentrations. The simulations of the mid-Pliocene warm period show global warming of between 1.8 and 3.6 C above pre-industrial surface air temperatures, with significant polar amplification. Here we perform energy balance calculations on all eight of the coupled ocean-atmosphere simulations within PlioMIP Experiment 2 to evaluate the causes of the increased temperatures and differences between the models. In the tropics simulated warming is dominated by greenhouse gas increases, with the cloud component of planetary albedo enhancing the warming in most of the models, but by widely varying amounts. The responses to mid-Pliocene climate forcing in the Northern Hemisphere midlatitudes are substantially different between the climate models, with the only consistent response being a warming due to increased greenhouse gases. In the high latitudes all the energy balance components become important, but the dominant warming influence comes from the clear sky albedo, only partially offset by the increases in the cooling impact of cloud albedo. This demonstrates the importance of specified ice sheet and high latitude vegetation boundary conditions and simulated sea ice and snow albedo feedbacks. The largest components in the overall uncertainty are associated with clouds in the tropics and polar clear sky albedo, particularly in sea ice regions. These simulations show that albedo feedbacks, particularly those of sea ice and ice sheets, provide the most significant enhancements to high latitude warming in the Pliocene.

climate models↗

Exploring ENSO-Induced Anomalies over North America in Historical and Future Climate Simulations That Use HadGEM2-ESM Output to Drive WRF

Projected changes to the El Niño Southern Oscillation (ENSO) climate mode have been explored using global Earth system models (ESMs). Regional expressions of such changes have yet to be fully advanced and may require the use of regional downscaling. Here, we employ regional climate modeling (RCM) using the Weather Research and Forecasting (WRF) model at convection-permitting resolution and nested in output from the HadGEM2 ESM. We quantify ENSO teleconnections to temperature and precipitation anomalies in historical and future climate scenarios over eastern North America. Two paired simulations are run, a strong El Niño (positive ENSO phase) and a weak La Niña (negative ENSO phase), for the historical and future years. The HadGEM2 direct output and HadGEM2-WRF simulation output are compared to the anomalies derived from the NOAA ENSO Climate Normals dataset. The near-surface temperature and precipitation differences by ENSO phase, as represented by the HadGEM2-WRF historical simulations, show a poor degree of association with the NOAA ENSO Climate Normals, in part because of the large biases in the HadGEM2 model. Downscaling with the WRF model does improve the agreement with the observations, and large discrepancies remain. The model chain HadGEM2-WRF reverses the sign of the ENSO phase response over eastern North America under simulations of the future climate with high greenhouse gas forcing, but due to the poor agreement with the NOAA ENSO Climate Normals it is difficult to assign confidence to this prediction.

54 ENVIRONMENTAL SCIENCES↗

Summary of results of January climate simulations with the GISS coarse-mesh model

The large scale climates generated by extended runs of the model are relatively independent of the initial atmospheric conditions, if the first few months of each simulation are discarded. The perpetual January simulations with a specified SST field produced excessive snow accumulation over the continents of the Northern Hemisphere. Mass exchanges between the cold (warm) continents and the warm (cold) adjacent oceans produced significant surface pressure changes over the oceans as well as over the land. The effect of terrain and terrain elevation on the amount of precipitation was examined. The evaporation of continental moisture was calculated to cause large increases in precipitation over the continents.

Spar, J.↗