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At least 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Hydrological analysis in watersheds with a variable-resolution global climate model (VR-CESM)

Traditionally, watershed-scale hydrology is simulated by distributed hydrological models with offline meteorological forcing data, or by regional regional climate models that link atmospheric and land hydrology interactions. Global climate models (GCMs) are rarely used to study watershed-scale hydrology due to the relatively coarse grid resolution, computationally expensive downscaling, and simplified physical processes. Recently, however, watershed-scale hydrology analysis has become possible in GCMs due to the development of variable-resolution GCMs that dynamically couple the hydrological processes between atmosphere and land systems at fine resolutions in selected regions and coarse resolution elsewhere. In this study, we used the variable-resolution Community Earth System Model (VR-CESM) with refined-resolution (14 km) in the western U.S. and eastern China to evaluate watershed-scale hydrology. Furthermore, we compared the historical VR-CESM outputs with gauge measurements and other hydrological models (e.g., National Water Model in the U.S.) and calibrated the subsurface runoff capacities in four mountainous watersheds. An RCP8.5 projection from 2007 to 2050 is used to estimate the impact of changing precipitation and snow climatology on watershed hydrology. We also analyzed the long-term runoff variability and the possibility of extreme runoff events as simulated by the VR-CESM. Although calibration is not possible in larger-scale watersheds, VR-CESM simulates the long-term annual variability of watersheds and provides insights on climate change impacts on hydrology. We conclude that refined-resolution VR-CESM can be used for watershed-scale hydrology analysis to understand water resources and water balance, in addition to traditional watershed-scale hydrological models. It enables hydrological analysis at multiple watersheds in one simulation and can help understand the two-way dynamics between land surface hydrology and atmospheric processes, and is especially practical for projecting climate change impacts. However, it is challenging to apply VR-CESM for hydrologic analysis in regulated watersheds as human factors (e.g., pumping, irrigation, water diversion) have not been fully addressed in VR-CESM.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

A Surface Radiation Balance Dataset from Siple Dome in West Antarctica for Atmospheric and Climate Model Evaluation

Abstract A field campaign at Siple Dome in West Antarctica during the austral summer 2019/20 offers an opportunity to evaluate climate model performance, particularly cloud microphysical simulation. Over Antarctic ice sheets and ice shelves, clouds are a major regulator of the surface energy balance, and in the warm season their presence occasionally induces surface melt that can gradually weaken an ice shelf structure. This dataset from Siple Dome, obtained using transportable and solar-powered equipment, includes surface energy balance measurements, meteorology, and cloud remote sensing. To demonstrate how these data can be used to evaluate model performance, comparisons are made with meteorological reanalysis known to give generally good performance over Antarctica (ERA5). Surface albedo measurements show expected variability with observed cloud amount, and can be used to evaluate a model’s snowpack parameterization. One case study discussed involves a squall with northerly winds, during which ERA5 fails to produce cloud cover throughout one of the days. A second case study illustrates how shortwave spectroradiometer measurements that encompass the 1.6- μ m atmospheric window reveal cloud phase transitions associated with cloud life cycle. Here, continuously precipitating mixed-phase clouds become mainly liquid water clouds from local morning through the afternoon, not reproduced by ERA5. We challenge researchers to run their various regional or global models in a manner that has the large-scale meteorology follow the conditions of this field campaign, compare cloud and radiation simulations with this Siple Dome dataset, and potentially investigate why cloud microphysical simulations or other model components might produce discrepancies with these observations. significance statement Antarctica is a critical region for understanding climate change and sea level rise, as the great ice sheets and the ice shelves are subject to increasing risk as global climate warms. Climate models have difficulties over Antarctica, particularly with simulation of cloud properties that regulate snow surface melting or refreezing. Atmospheric and climate-related field work has significant challenges in the Antarctic, due to the small number of research stations that can support state-of-the-art equipment. Here we present new data from a suite of transportable and solar-powered instruments that can be deployed to remote Antarctic sites, including regions where ice shelves are most at risk, and we demonstrate how key components of climate model simulations can be evaluated against these data.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2016

The CMIP6 Sea-Ice Model Intercomparison Project (SIMIP): Understanding sea ice through climate-model simulations

A better understanding of the role of sea ice for the changing climate of our planet is the central aim of the diagnostic Coupled Model Intercomparison Project 6 (CMIP6)-endorsed Sea-Ice Model Intercomparison Project (SIMIP). To reach this aim, SIMIP requests sea-ice-related variables from climate-model simulations that allow for a better understanding and, ultimately, improvement of biases and errors in sea-ice simulations with large-scale climate models. This then allows us to better understand to what degree CMIP6 model simulations relate to reality, thus improving our confidence in answering sea-ice-related questions based on these simulations. Furthermore, the SIMIP protocol provides a standard for sea-ice model output that will streamline and hence simplify the analysis of the simulated sea-ice evolution in research projects independent of CMIP. To reach its aims, SIMIP provides a structured list of model output that allows for an examination of the three main budgets that govern the evolution of sea ice, namely the heat budget, the momentum budget, and the mass budget. Furthermore, we explain the aims of SIMIP in more detail and outline how its design allows us to answer some of the most pressing questions that sea ice still poses to the international climate-research community.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2017

Investigating added value of regional climate modeling in North American winter storm track simulations

Extratropical Cyclone (EC) characteristics depend on a combination of large-scale factors and regional processes. However, the latter are considered to be poorly represented in global climate models (GCMs), partly because their resolution is too coarse. This work describes a framework using possibilities given by regional climate models (RCMs) to gain insight into storm activity during winter over North America (NA). Recent past climate period (1981–2005) is considered to assess EC activity over NA using the NCEP regional reanalysis (NARR) as a reference, along with the European reanalysis ERA-Interim (ERAI) and two CMIP5 GCMs used to drive the Canadian Regional Climate Model—version 5 (CRCM5) and the corresponding regional-scale simulations. While ERAI and GCM simulations show basic agreement with NARR in terms of climatological storm track patterns, detailed bias analyses show that, on the one hand, ERAI presents statistically significant positive biases in terms of EC genesis and therefore occurrence while capturing their intensity fairly well. On the other hand, GCMs present large negative intensity biases in the overall NA domain and particularly over NA eastern coast. In addition, storm occurrence over the northwestern topographic regions is highly overestimated. When the CRCM5 is driven by ERAI, no significant skill deterioration arises and, more importantly, all storm characteristics near areas with marked relief and over regions with large water masses are significantly improved with respect to ERAI. Conversely, in GCMdriven simulations, the added value contributed by CRCM5 is less prominent and systematic, except over western NA areas with high topography and over the Western Atlantic coastlines where the most frequent and intense ECs are located. Despite this significant added-value on seasonalmean characteristics, a caveat is raised on the RCM ability to handle storm temporal ‘seriality’, as a measure of their temporal variability at a given location. In fact, the driving models induce some significant footprints on the RCM skill to reproduce the intra-seasonal pattern of storm activity.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2014

Evaluating Clouds, Aerosols, and their Interactions in Three Global Climate Models using COSP and Satellite Observations

Accurately representing aerosol-cloud interactions in global climate models is challenging. As parameterizations evolve, it is important to evaluate their performance with appropriate use of observations. In this work we compare aerosols, clouds, and their interactions in three climate models (AM3, CAM5, ModelE) to MODIS satellite observations. Modeled cloud properties were diagnosed using the CFMIP Observations Simulator Package (COSP). Cloud droplet number concentrations (N) were derived using the same algorithm for both satellite-simulated model values and observations. We find that aerosol optical depth tau simulated by models is similar to observations. For N, AM3 and CAM5 capture the observed spatial pattern of higher values in near-coast versus remote ocean regions, though modeled values in general are higher than observed. In contrast, ModelE simulates lower N in most near-coast versus remote regions. Aerosol- cloud interactions were computed as the sensitivity of N to tau for marine liquid clouds off the coasts of South Africa and Eastern Asia where aerosol pollution varies in time. AM3 and CAM5 are in most cases more sensitive than observations, while the sensitivity for ModelE is statistically insignificant. This widely used sensitivity could be subject to misinterpretation due to the confounding influence of meteorology on both aerosols and clouds. A simple framework for assessing the N – tau sensitivity at constant meteorology illustrates that observed sensitivity can change from positive to statistically insignificant when including the confounding influence of relative humidity. Satellite simulated values of N were compared to standard model output and found to be higher with a bias of 83 cm-3.

aerosols↗
DOE OSTI2016

The impact of equilibrating hemispheric albedos on tropical performance in the HadGEM2-ES coupled climate model

Despite the fact that the southern hemisphere contains a far greater proportion of dark ocean than the northern hemisphere, the total amount of sunlight reflected from the hemispheres is equal. However, the majority of climate models do not adequately represent this equivalence. Here we examine the impact of equilibrating hemispheric albedos by various idealised methods in a comprehensive coupled climate model and find significant improvements in what have been considered longstanding and apparently intractable model biases. Monsoon precipitation biases almost vanish over all continental land areas, the penetration of monsoon rainfall across the Sahel and the west African monsoon “jump” become well represented, and indicators of hurricane frequency are significantly improved. The results appear not to be model specific, implying that hemispheric albedo equivalence may provide a fundamental constraint for climate models that must be satisfied if the dynamics driving these processes, in particular the strength of the Hadley cell, are to be adequately represented. Cross-equatorial energy transport is implicated as a crucial component that must be accurately modelled in coupled general circulation models. The results also suggest that the commonly used practice of prescribing sea-surface temperatures in models provides a less accurate represention of precipitation than constraining the hemispheric albedos.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2015

Sensitivity of a global climate model to the critical Richardson number in the boundary layer parameterization

The critical bulk Richardson number (Ri cr ) is an important parameter in planetary boundary layer (PBL) parameterization schemes used in many climate models. This paper examines the sensitivity of a Global Climate Model, the Beijing Climate Center Atmospheric General Circulation Model, BCC_AGCM to Ri cr . The results show that the simulated global average of PBL height increases nearly linearly with Ri cr , with a change of about 114 m for a change of 0.5 in Ri cr . The surface sensible (latent) heat flux decreases (increases) as Ri cr increases. The influence of Ri cr on surface air temperature and specific humidity is not significant. The increasing Ri cr may affect the location of the Westerly Belt in the Southern Hemisphere. Further diagnosis reveals that changes in Ri cr affect stratiform and convective precipitations differently. Increasing Ri cr leads to an increase in the stratiform precipitation but a decrease in the convective precipitation. Significant changes of convective precipitation occur over the inter-tropical convergence zone, while changes of stratiform precipitation mostly appear over arid land such as North Africa and Middle East.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Co-Evolving Climate Models under Uncertainty to Improve Predictive Skill

Focal Area: Predictive modeling through the use of AI techniques and AI-derived model components; the use of AI and other tools to design a prediction system comprising of a hierarchy of models Science Challenge: Advances in modeling of climate and improved observational capabilities have led to great improvements in understanding large-scale historical climate effects. It however remains a challenge to reliably predict the risk of fine-scale regional climate events on human systems even as such risks are on the rise because warmer and wetter climates are more prone to hydrometeorological extremes,

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

High-resolution climate model datasets for energy infrastructure planning in a renewable-dependent future

Electrification and renewables deployment efforts are amplifying the interdependence of the climate and energy systems. Increases in climate model resolution, which is now approaching that of reanalysis datasets and operational weather forecast models, present a unique opportunity to use future climate projections for energy infrastructure planning. In this Perspective, we review recent developments in high-resolution climate modeling, which have been driven by increased computing power and advanced software tools. We then look ahead to discuss how high-resolution climate data can be used to plan for a renewable-dependent future, and envision a unified climate-energy model framework that captures the two-way feedbacks between these interdependent systems.

climate change↗
DOE OSTI2014

The Specified Chemistry Whole Atmosphere Community Climate Model (SC‐WACCM)

Abstract We here present, document and validate a new atmospheric component of the Community Earth System Model (CESM1): the Specified Chemistry Whole Atmosphere Community Climate Model (SC‐WACCM). As the name implies, SC‐WACCM is a middle atmosphere‐resolving model with prescribed, rather than interactive chemistry. Ozone concentrations are specified throughout the atmosphere, using zonal and monthly mean climatologies computed by a companion integration with the Whole Atmosphere Community Climate Model (WACCM). Above 65 km, in addition, the climatological chemical and shortwave heating, nitrogen oxide, atomic and molecular oxygen and carbon dioxide are also prescribed from the companion WACCM integration. We carefully compare the climatology and the climate variability of preindustrial integrations of SC‐WACCM and WACCM each coupled with active land, ocean and sea‐ice components. We note some differences in upper stratospheric and lower mesospheric temperature, just below the 65 km transition level, due to the diurnal ozone cycle that is not captured when monthly mean ozone is used. Nonetheless, we find that the climatology and variability of the stratosphere, the troposphere and surface climate are nearly identical in SC‐WACCM and WACCM. Notably, the frequency and amplitude of Northern Hemisphere stratospheric sudden warmings in the two integrations are not significantly different. Also, we compare WACCM and SC‐WACCM to CCSM4, the “low‐top” version of CESM1, and we find very significant differences in the stratospheric climatology and variability. The removal of the chemistry reduces the computational cost of SC‐WACCM to approximately one half of WACCM: in fact, SC‐WACCM is only 2.5 times more expensive than CCSM4 at the same horizontal resolution. This considerable reduction in computational cost makes the new SC‐WACCM component of CESM1 ideally suited for studies of stratosphere‐troposphere dynamical coupling and, more generally, the role of the stratosphere in the climate system.

Smith, K. L.↗
DOE OSTI2015

A review on regional convection‐permitting climate modeling: Demonstrations, prospects, and challenges

Abstract Regional climate modeling using convection‐permitting models (CPMs; horizontal grid spacing <4 km) emerges as a promising framework to provide more reliable climate information on regional to local scales compared to traditionally used large‐scale models (LSMs; horizontal grid spacing >10 km). CPMs no longer rely on convection parameterization schemes, which had been identified as a major source of errors and uncertainties in LSMs. Moreover, CPMs allow for a more accurate representation of surface and orography fields. The drawback of CPMs is the high demand on computational resources. For this reason, first CPM climate simulations only appeared a decade ago. In this study, we aim to provide a common basis for CPM climate simulations by giving a holistic review of the topic. The most important components in CPMs such as physical parameterizations and dynamical formulations are discussed critically. An overview of weaknesses and an outlook on required future developments is provided. Most importantly, this review presents the consolidated outcome of studies that addressed the added value of CPM climate simulations compared to LSMs. Improvements are evident mostly for climate statistics related to deep convection, mountainous regions, or extreme events. The climate change signals of CPM simulations suggest an increase in flash floods, changes in hail storm characteristics, and reductions in the snowpack over mountains. In conclusion, CPMs are a very promising tool for future climate research. However, coordinated modeling programs are crucially needed to advance parameterizations of unresolved physics and to assess the full potential of CPMs.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Hydrostatic and Non‐Hydrostatic Baroclinic Instability in the Dynamical Core of the DOE Global Climate Model

Abstract The dynamical core of the Department of Energy global climate model is used to understand the role of non‐hydrostatic dynamics in the simulation of dry and moist baroclinic waves. To reduce computational cost, the Diabatic Acceleration and REscaling approach is adopted. Scale analysis and numerical simulations suggest that the model solution is not distorted by the change of spherical metric terms due to the change of Earth radius, neither are the inter‐scale interactions strongly altered as indicated by the analysis of spectral flux. Compared with hydrostatic simulations, the onset of baroclinic instability is delayed under non‐hydrostatic dynamics as the associated weaker vertical motions tend to increase the critical wavelength and narrow the range of waves that can be baroclinically unstable. During the development of baroclinic waves, non‐hydrostatic dynamics tends to induce vertical motions in the upper troposphere, accelerating the eastward propagation of upper‐level ridges through their impact on local vorticity tendency. These processes reduce the westward tilt of the vertical ridge axes and suppress the conversion of mean flow available potential energy to eddy kinetic energy, leading to weaker baroclinic eddies than in hydrostatic simulations. The contrasts between hydrostatic and non‐hydrostatic settings hold in supplemental experiments that vary the background flow Rossby number, the amount of water vapor content and vertical resolution. We also find that mesoscale and smaller‐scale activities can be considerably under‐represented when the vertical resolution is limited to that typically used in global climate models.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

Final Report on "Collaborative Research to Narrow Uncertainties in Precipitation and the Hydrological Cycle in Climate Models"

The central objectives of this work have been to explore and improve the depiction of precipitation and related processes in climate models by developing and analyzing observations and their gridded analyses, and developing new approaches and metrics. All three groups worked with the NCAR-based Community Earth System Model (CESM) and international community Climate Model Inter-comparison Project version 5 (CMIP5) models in various ways. At NCAR and SUNYA an initial focus was on the observational record, including updating of the river discharge dataset. A major focus at NCAR was extensive work on new datasets of hourly precipitation from CMORPH (observations) and CESM, and commentary on and validation of the CESM. SUNYA contributed to the comparison and evaluation of existing precipitation products widely used in climate research, the analysis of precipitation characteristics in CESM and other CMIP5 models, and decadal precipitation variability associated with decadal variability. At NCAR and SUNYA work was focused on the frequency and intensity of precipitation, including their dependence on the temporal and spatial resolution of the data used to calculate the frequency and intensity, as well as additional analyses on the effects of precipitation data uncertainties on the estimated historical drying trends. LLNL focused on the diurnal cycle. New insights have resulted in the characteristics of precipitation (frequency, intensity, amount, duration, diurnal cycle, covariability in space and time) and evaluation of these in models. In general models perform poorly and this provides a much-needed focus on what aspects of models are greatly in need of improvement. A substantial number of papers have now been published on these topics. The focus on the characteristics of precipitation and not just amount also provides a natural entrée into examining the extremes of precipitation, that are very important to the general public in terms of impacts. Examples are the deluges from Florence and Harvey, and extensive work has been performed on the latter. On the other side of the coin, considerable work has been performed on dry spells and drought, including improvements in a drought index. There has been considerable outreach to the general public, especially through the media, but also via talks and lectures, and a strong educational component at SUNYA. For example, the Harvey paper has an altimetrics rating of 827 and is the highest for any paper from that journal, it is at the 99th percentile of all papers of the same age, and is in the top 95 percent of all papers. The energy cycle and ocean heat content has been another focus. The entire atmospheric energy cycle has been reformulated and applied to the latest data to include effects from the enthalpy of precipitation. Relationships between ocean heat content and sea level rise have also been extensively explored in observations and models, with new insights into the role of Mount Pinatubo volcanic eruption on distorting and hiding the accelerating sea level rise. This work has been also widely featured in news media. The “year without a summer” has also been explored in the past using models, and how changes in the vertical structure and stability of the ocean with a warming climate may influence a future such volcanic event by amplifying the surface temperature response.

58 GEOSCIENCES↗
DOE OSTI2023

The Lack of a QBO-MJO Connection in Climate Models With a Nudged Stratosphere

The observed stratospheric quasi-biennial oscillation (QBO) and the tropospheric Madden-Julian oscillation (MJO) are strongly connected in boreal winter, with stronger MJO activity when lower-stratospheric winds are easterly. However, the current generation of climate models with internally generated representations of the QBO and MJO do not simulate the observed QBO-MJO connection, for reasons that remain unclear. Furthermore, this study builds on prior work exploring the QBO-MJO link in climate models whose stratospheric winds are relaxed toward reanalysis, reducing stratospheric biases in the model and imposing a realistic QBO. A series of ensemble experiments are performed using four state-of-the-art climate models capable of representing the MJO over the period 1980–2015, each with similar nudging in the stratosphere. In these four models, nudging leads to a good representation of QBO wind and temperature signals, however no model simulates the observed QBO-MJO relationship. Biases in MJO vertical structure and cloud-radiative feedbacks are investigated, but no conclusive model bias or mechanism is identified that explains the lack of a QBO-MJO connection.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Vertical dependence of horizontal variation of cloud microphysics: observations from the ACE-ENA field campaign and implications for warm-rain simulation in climate models

Abstract. In the current global climate models (GCMs), the nonlinearity effect of subgrid cloud variations on the parameterization of warm-rain process, e.g., the autoconversion rate, is often treated by multiplying the resolved-scale warm-rain process rates by a so-called enhancement factor (EF). In this study, we investigate the subgrid-scale horizontal variations and covariation of cloud water content (qc) and cloud droplet number concentration (Nc) in marine boundary layer (MBL) clouds based on the in situ measurements from a recent field campaign and study the implications for the autoconversion rate EF in GCMs. Based on a few carefully selected cases from the field campaign, we found that in contrast to the enhancing effect of qc and Nc variations that tends to make EF > 1, the strong positive correlation between qc and Nc results in a suppressing effect that tends to make EF < 1. This effect is especially strong at cloud top, where the qc and Nc correlation can be as high as 0.95. We also found that the physically complete EF that accounts for the covariation of qc and Nc is significantly smaller than its counterpart that accounts only for the subgrid variation of qc, especially at cloud top. Although this study is based on limited cases, it suggests that the subgrid variations of Nc and its correlation with qc both need to be considered for an accurate simulation of the autoconversion process in GCMs.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

ARM Data-Oriented Metrics and Diagnostics Package for Climate Model Evaluation

A Python-based metrics and diagnostics package is currently being developed by the U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) Infrastructure Team at Lawrence Livermore National Laboratory (LLNL) to facilitate the use of long-term, high-frequency measurements from the ARM Facility in evaluating the regional climate simulation of clouds, radiation, and precipitation. This metrics and diagnostics package computes climatological means of targeted climate model simulation and generates tables and plots for comparing the model simulation with ARM observational data. The Coupled Model Intercomparison Project (CMIP) model data sets are also included in the package to enable model intercomparison as demonstrated in Zhang et al. (2017). The mean of the CMIP model can serve as a reference for individual models. Basic performance metrics are computed to measure the accuracy of mean state and variability of climate models. The evaluated physical quantities include cloud fraction, temperature, relative humidity, cloud liquid water path, total column water vapor, precipitation, sensible and latent heat fluxes, and radiative fluxes, with plan to extend to more fields, such as aerosol and microphysics properties. Process-oriented diagnostics focusing on individual cloud- and precipitation-related phenomena are also being developed for the evaluation and development of specific model physical parameterizations. The version 1.0 package is designed based on data collected at ARM’s Southern Great Plains (SGP) Research Facility, with the plan to extend to other ARM sites. The metrics and diagnostics package is currently built upon standard Python libraries and additional Python packages developed by DOE (such as CDMS and CDAT). The ARM metrics and diagnostic package is available publicly with the hope that it can serve as an easy entry point for climate modelers to compare their models with ARM data. In this report, we first present the input data, which constitutes the core content of the metrics and diagnostics package in section 2, and a user's guide documenting the workflow/structure of the version 1.0 codes, and including step-by-step instruction for running the package in section 3.

54 ENVIRONMENTAL SCIENCES↗