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All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Bioenergy Technologies in Long-Run Climate Change Mitigation: Results from the EMF-33 Study

Bioenergy is expected to play an important role in long-run climate change mitigation strategies as highlighted by many integrated assessment model (IAM) scenarios. These scenarios, however, also show a very wide range of results, with uncertainty about bioenergy conversion technology deployment and biomass feedstock supply. To date, the underlying differences in model assumptions and parameters for the range of results have not been conveyed. Here we explore the models and results of the 33rd study of the Stanford Energy Modeling Forum to elucidate and explore bioenergy technology specifications and constraints that underlie projected bioenergy outcomes. We first develop and report consistent bioenergy technology characterizations and modeling details. We evaluate the bioenergy technology specifications through a series of analyses—comparison with the literature, model intercomparison, and an assessment of bioenergy technology projected deployments. We find that bioenergy technology coverage and characterization varies substantially across models, spanning different conversion routes, carbon capture and storage opportunities, and technology deployment constraints. Still, the range of technology specification assumptions is largely in line with bottom-up engineering estimates. We then find that variation in bioenergy deployment across models cannot be understood from technology costs alone. Important additional determinants include biomass feedstock costs, the availability and costs of alternative mitigation options in and across end-uses, the availability of carbon dioxide removal possibilities, the speed with which large scale changes in the makeup of energy conversion facilities and integration can take place, and the relative demand for different energy services.

bioenergy↗
NASA NTRS2019

DYAMOND: The DYnamics of the Atmospheric General Circulation Modeled on Non-Hydrostatic Domains

A review of the experimental protocol and motivation for DYAMOND, the first intercomparison project of global storm-resolving models, is presented. Nine models submitted simulation output for a 40-day (1 August–10 September 2016) intercomparison period. Eight of these employed a tiling of the sphere that was uniformly less than 5 km. By resolving the transient dynamics of convective storms in the tropics, global storm-resolving models remove the need to parameterize tropical deep convection, providing a fundamentally more sound representation of the climate system and a more natural link to commensurately high-resolution data from satellite-borne sensors. The models and some basic characteristics of their output are described in more detail, as is the availability and planned use of this output for future scientific study. Tropically and zonally averaged energy budgets, precipitable water distributions, and precipitation from the model ensemble are evaluated, as is their representation of tropical cyclones and the predictability of column water vapor, the latter being important for tropical weather.

Bjorn Stevens↗
NASA NTRS2024

Evaluating Differences Among Crop Models in Simulating Soybean in-Season Growth

Crop models are useful tools for simulating agricultural systems that require continued model development and testing to increase their robustness and improve how they describe our current understanding of processes. Coordinated and “blind” evaluation of multiple models using same protocols and experimental datasets provides unique opportunities to further improve models and enhance their reliability. For soybean [Glycine max (L.) Merr.], there has been limited coordinated multi-model evaluations for the simulation of in-season plant growth dynamics. We evaluated ten dynamic soybean crop models for their simulation of in-season plant growth using data from five experiments conducted in Argentina, Brazil, France, and USA. We evaluated models after a Blind (using only phenology data) and a Full calibration (with in-season and end-of-season variables). Calibration reduced model uncertainty by reducing standard bias for the simulation of in-season variables (biomass, leaf, pod, and stem weights, and leaf area index, LAI). However, we found that most models had difficulty in reproducing leaf growth dynamics, with normalized root mean squared error (nRMSE) of 56% for leaf weight and 43% for LAI (across locations and models after Full calibration). Models with different levels of complexity and experience were capable of simulating final seed yield at maturity with reasonable accuracy (nRMSE of 8–31% after Full calibration). However, the nRMSE for pod weight (of 17–64% after Full calibration) was two-fold larger than that of seed yield. Moreover, the models differed in how they simulated timing from sowing to beginning seed growth (47–93 days) and effective seed filling period (18–54 days), owing to model structural differences in defining the reproductive developmental stages. Overall, we identified the following processes that can benefit from further model improvement: leaf expansion and senescence, reproductive phenology, and partitioning to reproductive growth. Simulation of pod wall tissue and individual seed cohorts is another aspect that many models currently lack. Model improvement can benefit from high-temporal resolution experimental datasets that concurrently account for phenology, plant growth, and partitioning. Further, we recommend collecting reproductive phenology in the field consistent with actual dry matter allocation to organs in the models and collecting multiple observations of seed and pod weight to aid model improvement for simulation of seed growth and yield formation.

Agricultural Model Intercomparison and Improvement↗
NASA NTRS1986

Radiation flux tables for ICRCCM using the GLA GCM radiation codes

Tabulated values of longwave and shortwave radiation fluxes and also cooling and heating rates in the atmosphere for standard atmospheric profiles are presented. The radiation codes used in the Goddard general circulation model were employed for the computations. These results were obtained for an international intercomparison projected called Intercomparison of Radiation Codes in Climate Models (ICRCCM).

HARSHVARDHAN↗
NASA NTRS2022

AgMIP Regional Integrated Assessment of Agricultural Systems in Nioro, Senegal: Representative Agricultural Pathways, Climate, Crop and Economic Datasets

This paper describes the datasets that were used to implement an AgMIP Regional Integrated Assessment for the Nioro region of Senegal to assess the potential impacts of climate change on the principal agricultural system in the Senegal peanut basin and to assess adaptations of that system to climate change under current as well as future climate and socio-economic conditions. This dataset includes the Representative Agricultural Pathways developed for Nioro from 2000-2050; the climate data that were used to implement crop yield simulations; the data that were used to parameterize the DSSAT and APSIM crop models, including historical climate data and future climate scenarios; and the data that were used to parameterize the Tradeoff Analysis Model for Multi-dimensional Impact Assessment (TOAMD) economic simulation model, as well as simulated model outputs.

AgMIP↗
NASA NTRS1999

Climatological Structures of the GRIPS Models: Mean States and Forcing

The GCM-Reality Intercomparison Project for SPARC (GRIPS) is assessing and monitoring the performance of state-of-the-art general circulation models (GCMs). A wide variety of tasks have been initiated. These are designed to: (1) assess the ability of the GCMs to represent the current climatological structure of the troposphere and middle atmosphere,(2) to compare their response to imposed forcing anomalies, and (3) to estimate the certainty with which future climate perturbations can be predicted. This paper is concerned with assessments of the climatological states in the GCM simulations. Comparing the simulations with observational datasets reveals considerable discrepancies in the modelled fields. While it might be anticipated that certain types of biases in the model simulations might be related to the formulation of different aspects of the numerical package (dynamical schemes, cloud schemes, radiation transfer, inclusion of gravity wave drag), there is no clear relationship between these features. This paper attempts to draw a more comprehensive picture of the GCMs'performance than has previously been shown, by comparing the dominant forcing mechanisms in the models with observational estimates, and relating model deficiencies to the differences in the physical mechanisms in the GCMS.

Pawson, Steven↗
NASA NTRS2002

Tropical Cumulus Convection and Upward Propagating Waves in Middle Atmospheric GCMs

It is recognized that the resolved tropical wave spectrum can vary considerably between general circulation models (GCMs) and that these differences can have an important impact on the simulated climate. A comprehensive comparison of the waves is presented for the December-January-February period using high-frequency (three-hourly) data archives from eight GCMs and one simple model participating in the GCM Reality Intercomparison Project for SPARC (GRIPS). Quantitative measures of the structure and causes of the wavenumber-frequency structure of resolved waves and their impacts on the climate are given. Space-time spectral analysis reveals that the wave spectrum throughout the middle atmosphere is linked to variability of convective precipitation, which is determined by the parameterized convection. The variability of the precipitation spectrum differs by more than an order of magnitude between the models, with additional changes in the spectral distribution (especially the frequency). These differences can be explained primarily by the choice of different, cumulus par amet erizations: quasi-equilibrium mass-flux schemes tend to produce small variability, while the moist-convective adjustment scheme is most active. Comparison with observational estimates of precipitation variability suggests that the model values are scattered around the truth. This result indicates that a significant portion of the forcing of the equatorial quasi-biennial oscillation (QBO) is provided by waves with scales that are not resolved in present-day GCMs, since only the moist convective adjustment scheme (which has the largest transient variability) can force a QBO in models that have no parameterization of non-stationary gravity waves. Parameterized cumulus convection also impacts the nonmigrating tides in the equatorial region. In most of the models, momentum transport by diurnal nonmigrating tides in the mesosphere is larger than that by Kelvin waves, being more significant than has been thought. It is shown that the equatorial semi-annual oscillation in the models examined is driven mainly by gravity waves with periods shorter than three days, with at least some contribution from parameterized gravity waves; the contribution from the ultra-fast zonal wavenumber-1 Kelvin waves is negligible.

Horinouchi, T.↗
NASA NTRS2002

Simulation of High-Latitude Hydrological Processes in the Torne-Kalix Basin: PILPS Phase 2(e): Equivalent Model Representation and Sensitivity Experiments - 3

The Project for Intercomparison of Land Surface Parameterization Schemes (PILPS) Phase 2(e) showed that in cold regions the annual runoff production in Land Surface Schemes (LSSs) is closely related to the maximum snow accumulation, which in turn is controlled in large part by winter sublimation. To help further explain the relationship between snow cover, turbulent exchanges and runoff production, a simple equivalent model-(SEM) was devised to reproduce the seasonal and annual fluxes simulated by 13 LSSs that participated in PILPS Phase 2(e). The design of the SEM relates the annual partitioning of precipitation and energy in the LSSs to three primary parameters: snow albedo, effective aerodynamic resistance and evaporation efficiency. Isolation of each of the parameters showed that the annual runoff production was most sensitive to the aerodynamic resistance. The SEM was somewhat successful in reproducing the observed LSS response to a decrease in shortwave radiation and changes in wind speed forcings. SEM parameters derived from the reduced shortwave forcings suggested that increased winter stability suppressed turbulent heat fluxes over snow. Because winter sensible heat fluxes were largely negative, reductions in winter shortwave radiation imply an increase in annual average sensible heat.

Bowling, Laura C.↗
DOE OSTI2022

Object-Based Evaluation of Tropical Precipitation Systems in DYAMOND Simulations over the Maritime Continent

The present study uses an object-based evaluation metric to examine the precipitation bias over the Maritime Continent in the global cloud-resolving models. We specifically focus on the difference between the models that directly resolve convection and those using convection parameterization. The 40-day hindcast experiments of the DYnamics of the Atmospheric general circulation Modeled On Non-hydrostatic Domain (DYAMOND) intercomparison project are evaluated against the high-resolution satellite rainfall products. The hindcast of the Central Weather Bureau Global Forecast System (CWBGFS) under the DYAMOND protocol is also included. The results indicate that most models simulate insufficient numbers of large precipitation system [object-based precipitation system (OPS), > 370 km in scale], indicating weaker convection organization. The observation indicates that the maximum precipitation within the OPS intensifies with increasing object size. All of the models capture this positive relationship, but most of them overestimate the sensitivity. Most of the models overestimate both the frequency and intensity of small OPS (< 160 km), except for the models with convection parameterization [i.e., CWBGFS, European Centre for Medium-Range Weather Forecasts Integrated Forecasting System (IFS)-9 km]. Although most of the models can reproduce the observed peak time of diurnal precipitation over the land area in the Maritime Continent, the simulated fractional contribution of different sizes of OPS to the total precipitation varies from model to model, and their peak times do not follow the observed ones with delayed peak times as the size of OPS increases from small, mid-size, to large categories. Most of the models reasonably capture the mean diurnal cycle peak time, but only the models with convection parameterization and Model for Prediction Across Scales (MPAS) can represent the diurnal evolution of fractional contribution from different OPSs. The implications of the current results to the upscale processes of the tropical convection systems in the global models are also discussed.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

The Aerosol Model Benchmarking Repository: A toolkit for model intercomparison

The Aerosol Model Benchmarking Repository and Standards (AMBRS) project was initiated to provide tools and to establish community standards for benchmarking aerosol models. This report describes a set of open-source tools for building, running, and analyzing aerosol box model simulations in a standardized framework. The framework consists of three core components: AMBuilder, a CMake-based build system that compiles supported models consistently; AMBRS, a Python module that defines unified numerical experiments and executes them with aligned inputs; and PyParticle, an aerosol analysis package that standardizes output, computes diagnostics, and visualizes simulation results. Together, these tools enable reproducible intercomparison of aerosol schemes and support process-level evaluation of how model simplifications affect predictions of size distributions, cloud condensation nuclei activity, and other relevant properties relevant for the Earth-Energy system. Beyond its role in benchmarking, AMBRS provides a platform for studying aerosol processes across scales and can be used to generate training data for AI/ML applications in support of a broader hierarchical aerosol modeling strategy.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Modular hybrid modeling to increase efficiency, explore structural uncertainty, and allow multidimensional complexity scaling in land surface models

Land surface models (LSMs) are indispensable tools for predicting hydrologic extremes, as well as a particularly uncertain component of Earth system models that has stubbornly resisted the convergence in projections over several successive generations of model intercomparisons. This uncertainty in LSMs is poorly quantified and poorly attributed to specific processes, which has hampered efforts to focus research in reducing uncertainty. This has resulted from sparse sampling of the possible uncertainty space—which is high-dimensional and has contributions from parametric, structural, initial, and boundary condition uncertainties—as an artifact of CMIP-type ensembles of opportunity and limitations inherent in observational benchmarks. A new approach is needed to understand and reduce this uncertainty, based around individual LSMs that can represent the breadth of assumptions represented in current CMIP-type efforts, while at the same time exploring that uncertainty in a systematic way, confronting multiple types of observations, and where justified, replacing process representations with ML-driven emulators. We propose an approach of modular hybrid modeling to address these challenges.

58 GEOSCIENCES↗
NASA NTRSDate not supplied

Integrated National and Regional Agricultural Planning with AgMIP Tools and Methods

AgMIP, through its unique integration of multi-modeling approaches with stakeholder engagement, has advanced co-development of decision support tools and adaptation strategies in the face of climate change and other shocks (especially COVID-19). This has helped generate actionable information for adaptation planning processes in developing countries. Local-to-national stakeholders and decision-makers appreciate the research-informed stakeholder dialogue as very helpful in identifying research and policy gaps. These motivate concise recommendations for productivity-enhancing, environmentally sound technologies, and inclusive development approaches. Furthermore, these stakeholder dialogues help bridge the gaps between policy, research, and adaptation strategies, especially for low-input smallholder farming systems.

Agricultural Model Intercomparison and Improvement↗
NASA NTRS2022

The TRAPPIST-1 Habitable Atmosphere Intercomparison (THAI). Part III: Simulated Observables - The Return of the Spectrum

The TRAPPIST-1 Habitable Atmosphere Intercomparison (THAI) is a community project that aims to quantify how differences in general circulation models (GCMs) could impact the climate prediction for TRAPPIST-le and, subsequently its atmospheric characterization in transit. Four GCMs have participated in THAI so far: ExoCAM, LMD-Generic, ROCKE-3D and the UM. This paper, focused on the simulated observations, is the third part of a trilogy, following the analysis of two land planet scenarios (part I) and two aquaplanet scenarios (part II). Here, we show a robust agreement between the simulated spectra and the number of transits estimated to detect the land planet atmospheres. For the cloudy aquaplanet ones, a 5-σ detection of CO2 could be achieved in about 10 transits if the atmosphere contains at least 1 bar of CO2. That number can vary by 41- 56% depending on the GCM used to predict the terminator profiles, principally due to differences in the cloud deck altitude, with ExoCAM and LMD-G producing higher clouds than ROCKE-3D and UM. Therefore, for the first time, this work provides "GCM uncertainty error bars" of ~ 50% that need to be considered in future analyses of transmission spectra. We also analyzed the inter-transit variability induced by weather patterns and changes of terminator cloudiness between transits. Its magnitude differs significantly between the GCMs but its impact on the transmission spectra is within the measurement uncertainties. THAI has demonstrated the importance of model intercomparison for exoplanets and also paved the way for a larger project to develop an intercomparison meta-framework, namely the Climates Using Interactive Suites of Intercomparisons Nested for Exoplanet Studies (CUISINES).

Exoplanet atmospheres↗
DOE OSTI2022

Intercomparison of Dynamically and Statistically Downscaled Climate Change Projections over the Midwest and Great Lakes Region

Downscaling of global climate model (GCMs) simulations is a key element of regional-to-local-scale climate change projections that can inform impact assessments, long-term planning, and resource management in different sectors. Here, we conduct an intercomparison between statistically and dynamically downscaled GCMs simulations using the hybrid delta (HD) and the Weather Research and Forecast (WRF) Model, respectively, over the Midwest and Great Lakes region to 1) validate their performance in reproducing extreme daily precipitation (P) and daily maximum temperature (T max ) for summer and winter and 2) evaluate projections of extremes in the future. Our results show the HD statistical downscaling approach, which includes large-scale bias correction of GCM inputs, can reproduce observed extreme P and T max reasonably well for both summer and winter. However, raw historical WRF simulations show significant bias in both extreme P and T max for both seasons. Interestingly, the convection-permitting WRF simulation at 4-km grid spacing does not produce better results for seasonal extremes than the WRF simulation at 12 km using a parameterized convection scheme. Despite a broad similarity for winter extreme P projections, the projected changes in the future summer storms are quite different between downscaling methods; WRF simulations show substantial increases in summer extreme precipitation, while the changes projected by the HD approach exhibit moderate decreases overall. The WRF simulations at 4 km also show a pronounced decoupling effect between seasonal totals and extreme daily P for summer, which suggests that there could be more intense summer extremes at two different time scales, with more severe individual convective storms combined with longer summer droughts at the end of the twenty-first century.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1999

Longwave Radiative Flux Calculations in the TOVS Pathfinder Path A Data Set

A radiative transfer model developed to calculate outgoing longwave radiation (OLR) and downwelling longwave, surface flux (DSF) from the Television and Infrared Operational Satellite (TIROS) Operational Vertical Sounder (TOVS) Pathfinder Path A retrieval products is described. The model covers the spectral range of 2 to 2800 cm in 14 medium medium spectral bands. For each band, transmittances are parameterized as a function of temperature, water vapor, and ozone profiles. The form of the band transmittance parameterization is a modified version of the approach we use to model channel transmittances for the High Resolution Infrared Sounder 2 (HIRS2) instrument. We separately derive effective zenith angle for each spectral band such that band-averaged radiance calculated at that angle best approximates directionally integrated radiance for that band. We develop the transmittance parameterization at these band-dependent effective zenith angles to incorporate directional integration of radiances required in the calculations of OLR and DSF. The model calculations of OLR and DSF are accurate and differ by less than 1% from our line-by-line calculations. Also, the model results are within 1% range of other line-by-line calculations provided by the Intercomparison of Radiation Codes in Climate Models (ICRCCM) project for clear-sky and cloudy conditions. The model is currently used to calculate global, multiyear (1985-1998) OLR and DSF from the TOVS Pathfinder Path A Retrievals.

Mehta, Amita↗
NASA NTRS2004

"Hot Spots" of Land Atmosphere Coupling

Previous estimates of land-atmosphere interaction (the impact of soil moisture on precipitation) have been limited by a severe paucity of relevant observational data and by the model-dependence of the various computational estimates. To counter this limitation, a dozen climate modeling groups have recently performed the same highly-controlled numerical experiment as part of a coordinated intercomparison project. This allows, for the first time ever, a superior multi-model approach to the estimation of the regions on the globe where precipitation is affected by soil moisture anomalies during Northern Hemisphere summer. Such estimation has many potential benefits; it can contribute, for example, to seasonal rainfall prediction efforts.

Koster, Randal D.↗
NASA NTRSDate not supplied

Overview of the SPARC Reanalysis Intercomparison Project (S-RIP) during 2013-2020

The Stratosphere-troposphere Processes And their Role in Climate (SPARC) project is one of the four core projects of the World Climate Research Programme (WCRP). Researchers interested in SPARC use global atmospheric reanalysis products to understand a wide range of processes and variability in the atmosphere, to validate chemistry climate models, and to investigate and identify climate change. The SPARC Reanalysis Intercomparison Project (S-RIP) was initiated in 2011 and officially started in 2013 to conduct a coordinated intercomparison of all major global atmospheric reanalysis data sets. The S-RIP has been aiming at writing up an assessment report in the SPARC report series (to be published by the end of 2020) (1) on overall quality of temperature, winds, ozone, and water vapor data, (2) on more process- and region-oriented evaluation of the Brewer–Dobson circulation, extratropical stratosphere-troposphere coupling, extratropical upper troposphere and lower stratosphere, the tropical tropopause layer, the quasi-biennial oscillation, polar processes, and the upper stratosphere and lower mesosphere, and (3) with a coordinated description of the reanalysis systems. We also have an inter-journal special issue on "The SPARC Reanalysis Intercomparison Project (S-RIP)" in Atmospheric Chemistry and Physics (ACP) and Earth System Science Data (ESSD). In the presentation, we will discuss key findings and recommendations as well as the evaluation of this rst phase of the S-RIP activity.

Masatomo Fujiwara↗
DOE OSTI2025

GCAM Regional Tuning: A framework to tune GCAM parameters

GCAM assumptions typically generate scenarios that are designed to be internally consistent and globally coherent. The gcamdata tool which facilitates the compilation of data sets and user assumptions is not well suited to tailoring to specific country or regional realities, sponsor requirements, or perform harmonization for model intercomparison needs. As described in this report, the GCAM Regional Tuning project develops a computational framework that enables users to adjust GCAM parameters, so model outputs match targeted outcomes at user-defined spatial, temporal, and sectoral resolutions. The framework integrates GCAM, gcamdata, and gcamwrapper with a set of flexible “tuning directives” and an iterative numerical solver. Users can define targets (e.g., technology shares in power generation, BEV uptake, sectoral service demands), select tuners that manipulate relevant GCAM parameters (e.g., share weights, cost adders, elasticities), and export tuned parameters as reusable GCAM XML inputs for future runs. We demonstrate the approach and document usage, diagnostics, and known limitations, and we outline potential future directions.

97 MATHEMATICS AND COMPUTING↗