Author
L. Ruby Leung
Bio: L. Ruby Leung is an academic researcher from Pacific Northwest National Laboratory. The author has contributed to research in topics: Precipitation & Climate model. The author has an hindex of 64, co-authored 317 publications receiving 14222 citations.
Papers published on a yearly basis
Papers
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National Center for Atmospheric Research1, Lawrence Berkeley National Laboratory2, Oak Ridge National Laboratory3, Utrecht University4, Columbia University5, Chinese Academy of Sciences6, University of Houston7, California Institute of Technology8, University of California, Los Angeles9, Institute of Arctic and Alpine Research10, Los Alamos National Laboratory11, Harvard University12, Cooperative Institute for Research in Environmental Sciences13, University of Arizona14, University of Colorado Boulder15, Purdue University16, Michigan State University17, Argonne National Laboratory18, University of Michigan19, Auburn University20, Pacific Northwest National Laboratory21, Goddard Space Flight Center22, University of California, Irvine23, Virginia Tech24, University of Sheffield25
TL;DR: The Community Land Model (CLM) is the land component of the Community Earth System Model (CESM) and is used in several global and regional modeling systems.
Abstract: The Community Land Model (CLM) is the land component of the Community Earth System Model (CESM) and is used in several global and regional modeling systems. In this paper, we introduce model developments included in CLM version 5 (CLM5), which is the default land component for CESM2. We assess an ensemble of simulations, including prescribed and prognostic vegetation state, multiple forcing data sets, and CLM4, CLM4.5, and CLM5, against a range of metrics including from the International Land Model Benchmarking (ILAMBv2) package. CLM5 includes new and updated processes and parameterizations: (1) dynamic land units, (2) updated parameterizations and structure for hydrology and snow (spatially explicit soil depth, dry surface layer, revised groundwater scheme, revised canopy interception and canopy snow processes, updated fresh snow density, simple firn model, and Model for Scale Adaptive River Transport), (3) plant hydraulics and hydraulic redistribution, (4) revised nitrogen cycling (flexible leaf stoichiometry, leaf N optimization for photosynthesis, and carbon costs for plant nitrogen uptake), (5) global crop model with six crop types and time‐evolving irrigated areas and fertilization rates, (6) updated urban building energy, (7) carbon isotopes, and (8) updated stomatal physiology. New optional features include demographically structured dynamic vegetation model (Functionally Assembled Terrestrial Ecosystem Simulator), ozone damage to plants, and fire trace gas emissions coupling to the atmosphere. Conclusive establishment of improvement or degradation of individual variables or metrics is challenged by forcing uncertainty, parametric uncertainty, and model structural complexity, but the multivariate metrics presented here suggest a general broad improvement from CLM4 to CLM5.
661 citations
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Royal Netherlands Meteorological Institute1, Met Office2, University of Reading3, Chinese Academy of Sciences4, Texas A&M University5, National Research Council6, Barcelona Supercomputing Center7, Wageningen University and Research Centre8, Japan Agency for Marine-Earth Science and Technology9, Swedish Meteorological and Hydrological Institute10, Pacific Northwest National Laboratory11, Bureau of Meteorology12, Oak Ridge National Laboratory13, National Institute for Space Research14, University of Tokyo15, National Institute of Geophysics and Volcanology16, Alfred Wegener Institute for Polar and Marine Research17, National Center for Atmospheric Research18, Max Planck Society19
TL;DR: The High-ResMIP (High-resolution Model Intercomparison Project) as mentioned in this paper is a multi-model approach to the systematic investigation of the impact of horizontal resolution on the simulated mean climate and its variability.
Abstract: . Robust projections and predictions of climate variability and change, particularly at regional scales, rely on the driving processes being represented with fidelity in model simulations. The role of enhanced horizontal resolution in improved process representation in all components of the climate system is of growing interest, particularly as some recent simulations suggest both the possibility of significant changes in large-scale aspects of circulation as well as improvements in small-scale processes and extremes. However, such high-resolution global simulations at climate timescales, with resolutions of at least 50 km in the atmosphere and 0.25° in the ocean, have been performed at relatively few research centres and generally without overall coordination, primarily due to their computational cost. Assessing the robustness of the response of simulated climate to model resolution requires a large multi-model ensemble using a coordinated set of experiments. The Coupled Model Intercomparison Project 6 (CMIP6) is the ideal framework within which to conduct such a study, due to the strong link to models being developed for the CMIP DECK experiments and other model intercomparison projects (MIPs). Increases in high-performance computing (HPC) resources, as well as the revised experimental design for CMIP6, now enable a detailed investigation of the impact of increased resolution up to synoptic weather scales on the simulated mean climate and its variability. The High Resolution Model Intercomparison Project (HighResMIP) presented in this paper applies, for the first time, a multi-model approach to the systematic investigation of the impact of horizontal resolution. A coordinated set of experiments has been designed to assess both a standard and an enhanced horizontal-resolution simulation in the atmosphere and ocean. The set of HighResMIP experiments is divided into three tiers consisting of atmosphere-only and coupled runs and spanning the period 1950–2050, with the possibility of extending to 2100, together with some additional targeted experiments. This paper describes the experimental set-up of HighResMIP, the analysis plan, the connection with the other CMIP6 endorsed MIPs, as well as the DECK and CMIP6 historical simulations. HighResMIP thereby focuses on one of the CMIP6 broad questions, “what are the origins and consequences of systematic model biases?”, but we also discuss how it addresses the World Climate Research Program (WCRP) grand challenges.
608 citations
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TL;DR: In this article, the authors reviewed the latest progress in regional climate modeling studies, including RCM development, applications of RCMs to dynamical downscaling for climate change assessment, seasonal climate predictions and climate process studies, and the study of regional climate predictability.
Abstract: Regional climate modeling with regional climate models (RCMs) has matured over the past decade and allows for meaningful utilization in a broad spectrum of applications. In this paper, latest progresses in regional climate modeling studies are reviewed, including RCM development, applications of RCMs to dynamical downscaling for climate change assessment, seasonal climate predictions and climate process studies, and the study of regional climate predictability. Challenges and potential directions of future research in this important area are discussed, with the focus on those to which less attention has been given previously, such as the importance of ensemble simulations, further development and improvement of regional climate modeling approach, modeling extreme climate events and sub-daily variation of clouds and precipitation, model evaluation and diagnostics, applications of RCMs to climate process studies and seasonal predictions, and development of regional earth system models. It is believed that with both the demonstrated credibility of RCMs’ capability in reproducing not only monthly to seasonal mean climate and interannual variability but also the extreme climate events when driven by good quality reanalysis and the continuous improvements in the skill of global general circulation models (GCMs) in simulating large-scale atmospheric circulation, regional climate modeling will remain an important dynamicalmore » downscaling tool for providing the needed information for assessing climate change impacts and seasonal climate predictions, and a powerful tool for improving our understanding of regional climate processes. An internationally coordinated effort can be developed with different focuses by different groups to advance regional climate modeling studies. It is also recognized that since the final quality of the results from nested RCMs depends in part on the realism of the large-scale forcing provided by GCMs, the reduction of errors and improvement in physics parameterizations in both GCMs and RCMs remain a priority for climate modeling community.« less
442 citations
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Lawrence Livermore National Laboratory1, Los Alamos National Laboratory2, University of Houston3, Oak Ridge National Laboratory4, Lawrence Berkeley National Laboratory5, University of Arizona6, Pacific Northwest National Laboratory7, Sandia National Laboratories8, University of British Columbia9, Argonne National Laboratory10, University of Michigan11, University of Wisconsin–Milwaukee12, National Center for Atmospheric Research13, Brookhaven National Laboratory14, University of California, San Diego15, House of Representatives16, Gwangju Institute of Science and Technology17, University of California, Irvine18
TL;DR: Energy Exascale Earth System Model (E3SM) project as mentioned in this paper is a project of the U.S. Department of Energy that aims to develop and validate the E3SM model.
Abstract: Energy Exascale Earth System Model (E3SM) project - U.S. Department of Energy, Office of Science, Office of Biological and Environmental Research; Climate Model Development and Validation activity - Office of Biological and Environmental Research in the US Department of Energy Office of Science; Regional and Global Modeling and Analysis Program of the U.S. Department of Energy, Office of Science, Office of Biological and Environmental Research; National Research Foundation [NRF_2017R1A2b4007480]; Office of Science of the U.S. Department of Energy [DE-AC02-05CH11231]; DOE Office of Science User Facility [DE-AC05-00OR22725]; U.S. Department of Energy by Lawrence Livermore National Laboratory [DE-AC52-07NA27344]; DOE [DE-AC05-76RLO1830]; National Center for Atmospheric Research - National Science Foundation [1852977];[DE-SC0012778]
437 citations
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TL;DR: In this paper, the authors used the Penn State/NCAR Mesoscale Model (MM5) to downscale the PCM control (20 years) and three future (2040-2060) climate simulations to yield ensemble regional climate simulations at 40 km spatial resolution.
Abstract: To study the impacts of climate change on water resources in the western U.S., global climate simulations were produced using the National Center for Atmospheric Research/Department of Energy (NCAR/DOE) Parallel Climate Model (PCM). The Penn State/NCAR Mesoscale Model (MM5) was used to downscale the PCM control (20 years) and three future(2040–2060) climate simulations to yield ensemble regional climate simulations at 40 km spatial resolution for the western U.S. This paper describes the regional simulations and focuses on the hydroclimate conditions in the Columbia River Basin (CRB) and Sacramento-San Joaquin River (SSJ) Basin. Results based on global and regional simulations show that by mid-century, the average regional warming of 1 to 2.5 °C strongly affects snowpack in the western U.S. Along coastal mountains, reduction in annual snowpack was about70% as indicated by the regional simulations. Besides changes in mean temperature, precipitation, and snowpack, cold season extreme daily precipitation increased by 5 to 15 mm/day (15–20%) along theCascades and the Sierra. The warming resulted in increased rainfall at the expense of reduced snowfall, and reduced snow accumulation (or earlier snowmelt) during the cold season. In the CRB, these changes were accompanied by more frequent rain-on-snow events. Overall, they induced higher likelihood of wintertime flooding and reduced runoff and soil moisture in the summer. Changes in surface water and energy budgets in the CRB and SSJ basin were affected mainly by changes in surface temperature, which were statistically significant at the 0.95 confidence level. Changes in precipitation, while spatially incoherent, were not statistically significant except for the drying trend during summer. Because snow and runoff are highly sensitive tospatial distributions of temperature and precipitation, this study shows that (1) downscaling provides more realistic estimates of hydrologic impacts in mountainous regions such as the western U.S., and (2) despite relatively small changes in temperature and precipitation, changes in snowpack and runoff can be much larger on monthly to seasonal time scales because the effects of temperature and precipitation are integrated over time and space through various surface hydrological and land-atmosphere feedback processes. Although the results reported in this study were derived from an ensemble of regional climate simulations driven by a global climate model that displays low climate sensitivity compared with most other models, climate change was found to significantly affect water resources in the western U.S. by the mid twenty-first century.
399 citations
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University of Illinois at Urbana–Champaign1, Joint Institute for the Study of the Atmosphere and Ocean2, Cooperative Institute for Research in Environmental Sciences3, University of Leeds4, University of Oslo5, United States Environmental Protection Agency6, University of Michigan7, Pacific Northwest National Laboratory8, German Aerospace Center9, United States Department of Energy10, Max Planck Society11, University of Tokyo12, National Oceanic and Atmospheric Administration13, Forschungszentrum Jülich14, Norwegian Meteorological Institute15, Indian Institute of Technology Bombay16, China Meteorological Administration17, Peking University18, Met Office19, Desert Research Institute20, Clarkson University21, Stanford University22, European Centre for Medium-Range Weather Forecasts23, International Institute of Minnesota24, Goddard Institute for Space Studies25, Yale University26, University of Washington27, University of California, Irvine28
TL;DR: In this paper, the authors provided an assessment of black-carbon climate forcing that is comprehensive in its inclusion of all known and relevant processes and that is quantitative in providing best estimates and uncertainties of the main forcing terms: direct solar absorption; influence on liquid, mixed phase, and ice clouds; and deposition on snow and ice.
Abstract: Black carbon aerosol plays a unique and important role in Earth's climate system. Black carbon is a type of carbonaceous material with a unique combination of physical properties. This assessment provides an evaluation of black-carbon climate forcing that is comprehensive in its inclusion of all known and relevant processes and that is quantitative in providing best estimates and uncertainties of the main forcing terms: direct solar absorption; influence on liquid, mixed phase, and ice clouds; and deposition on snow and ice. These effects are calculated with climate models, but when possible, they are evaluated with both microphysical measurements and field observations. Predominant sources are combustion related, namely, fossil fuels for transportation, solid fuels for industrial and residential uses, and open burning of biomass. Total global emissions of black carbon using bottom-up inventory methods are 7500 Gg yr−1 in the year 2000 with an uncertainty range of 2000 to 29000. However, global atmospheric absorption attributable to black carbon is too low in many models and should be increased by a factor of almost 3. After this scaling, the best estimate for the industrial-era (1750 to 2005) direct radiative forcing of atmospheric black carbon is +0.71 W m−2 with 90% uncertainty bounds of (+0.08, +1.27) W m−2. Total direct forcing by all black carbon sources, without subtracting the preindustrial background, is estimated as +0.88 (+0.17, +1.48) W m−2. Direct radiative forcing alone does not capture important rapid adjustment mechanisms. A framework is described and used for quantifying climate forcings, including rapid adjustments. The best estimate of industrial-era climate forcing of black carbon through all forcing mechanisms, including clouds and cryosphere forcing, is +1.1 W m−2 with 90% uncertainty bounds of +0.17 to +2.1 W m−2. Thus, there is a very high probability that black carbon emissions, independent of co-emitted species, have a positive forcing and warm the climate. We estimate that black carbon, with a total climate forcing of +1.1 W m−2, is the second most important human emission in terms of its climate forcing in the present-day atmosphere; only carbon dioxide is estimated to have a greater forcing. Sources that emit black carbon also emit other short-lived species that may either cool or warm climate. Climate forcings from co-emitted species are estimated and used in the framework described herein. When the principal effects of short-lived co-emissions, including cooling agents such as sulfur dioxide, are included in net forcing, energy-related sources (fossil fuel and biofuel) have an industrial-era climate forcing of +0.22 (−0.50 to +1.08) W m−2 during the first year after emission. For a few of these sources, such as diesel engines and possibly residential biofuels, warming is strong enough that eliminating all short-lived emissions from these sources would reduce net climate forcing (i.e., produce cooling). When open burning emissions, which emit high levels of organic matter, are included in the total, the best estimate of net industrial-era climate forcing by all short-lived species from black-carbon-rich sources becomes slightly negative (−0.06 W m−2 with 90% uncertainty bounds of −1.45 to +1.29 W m−2). The uncertainties in net climate forcing from black-carbon-rich sources are substantial, largely due to lack of knowledge about cloud interactions with both black carbon and co-emitted organic carbon. In prioritizing potential black-carbon mitigation actions, non-science factors, such as technical feasibility, costs, policy design, and implementation feasibility play important roles. The major sources of black carbon are presently in different stages with regard to the feasibility for near-term mitigation. This assessment, by evaluating the large number and complexity of the associated physical and radiative processes in black-carbon climate forcing, sets a baseline from which to improve future climate forcing estimates.
4,591 citations
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TL;DR: In this article, the authors present a document, redatto, voted and pubblicato by the Ipcc -Comitato intergovernativo sui cambiamenti climatici - illustra la sintesi delle ricerche svolte su questo tema rilevante.
Abstract: Cause, conseguenze e strategie di mitigazione Proponiamo il primo di una serie di articoli in cui affronteremo l’attuale problema dei mutamenti climatici. Presentiamo il documento redatto, votato e pubblicato dall’Ipcc - Comitato intergovernativo sui cambiamenti climatici - che illustra la sintesi delle ricerche svolte su questo tema rilevante.
4,187 citations
01 Jan 1989
TL;DR: In this article, a two-dimensional version of the Pennsylvania State University mesoscale model has been applied to Winter Monsoon Experiment data in order to simulate the diurnally occurring convection observed over the South China Sea.
Abstract: Abstract A two-dimensional version of the Pennsylvania State University mesoscale model has been applied to Winter Monsoon Experiment data in order to simulate the diurnally occurring convection observed over the South China Sea. The domain includes a representation of part of Borneo as well as the sea so that the model can simulate the initiation of convection. Also included in the model are parameterizations of mesoscale ice phase and moisture processes and longwave and shortwave radiation with a diurnal cycle. This allows use of the model to test the relative importance of various heating mechanisms to the stratiform cloud deck, which typically occupies several hundred kilometers of the domain. Frank and Cohen's cumulus parameterization scheme is employed to represent vital unresolved vertical transports in the convective area. The major conclusions are: Ice phase processes are important in determining the level of maximum large-scale heating and vertical motion because there is a strong anvil componen...
3,813 citations
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TL;DR: The second most important contribution to anthropogenic climate warming, after carbon dioxide emissions, was made by black carbon emissions as mentioned in this paper, which is an efficient absorbing agent of solar irradiation that is preferentially emitted in the tropics and can form atmospheric brown clouds in mixture with other aerosols.
Abstract: Black carbon in soot is an efficient absorbing agent of solar irradiation that is preferentially emitted in the tropics and can form atmospheric brown clouds in mixture with other aerosols. These factors combine to make black carbon emissions the second most important contribution to anthropogenic climate warming, after carbon dioxide emissions.
3,060 citations