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DOE OSTI2022

Nitrification, denitrification, and competition for soil N : Evaluation of two Earth System Models against observations

Abstract Earth System Models (ESMs) have implemented nitrogen (N) cycles to account for N limitation on terrestrial carbon uptake. However, representing inputs, losses, and recycling of N in ESMs is challenging. Here, we use global rates and ratios of key soil N fluxes, including nitrification, denitrification, mineralization, leaching, immobilization, and plant uptake (both NH 4 + and NO 3 − ), from the literature to evaluate the N cycles in the land model components of two ESMs. The two land models evaluated here, E3SM Land Model version 1 (ELMv1)‐ECA and CLM5.0, originated from a common model but have diverged in their representation of plant–microbe competition for soil N. The models predict similar global rates of gross primary productivity (GPP) but have approximately two‐fold to three‐fold differences in their underlying global mineralization, immobilization, plant N uptake, nitrification, and denitrification fluxes. Both models dramatically underestimate the immobilization of NO 3 − by soil bacteria compared with literature values and predict dominance of plant uptake by a single form of mineral nitrogen (NO 3 − for ELM, with regional exceptions, and NH 4 + for CLM5.0). CLM5.0 strongly underestimates the global ratio of gross nitrification:gross mineralization and both models are likely to substantially underestimate the ratio of nitrification:denitrification. Few experimental data exist to evaluate this last ratio, in part because nitrification and denitrification are quantified using different techniques and because denitrification fluxes are difficult to measure at all. More observational constraints on soil nitrogen fluxes such as nitrification and denitrification, as well as greater scrutiny of the functional impact of introducing separate NH 4 + and NO 3 − pools into ESMs, could help to improve confidence in present and future simulations of N limitation on the carbon cycle.

Nevison, Cynthia↗

DOE OSTI2019

Climate Forcing and Trends of Organic Aerosols in the Community Earth System Model (CESM2)

The Community Earth System Model version 2 (CESM2) includes three main atmospheric configurations: the Community Atmosphere Model version 6 (CAM6) with simplified chemistry and a simplified organic aerosol (OA) scheme, CAM6 with comprehensive tropospheric and stratospheric chemistry representation (CAM6-chem), and the Whole Atmosphere Community Climate Model version 6 (WACCM6). Both, CAM6-chem and WACCM6 include a more comprehensive secondary organic aerosols (SOA) approach using the volatility basis set (vbs) scheme and prognostic stratospheric aerosols. This paper describes the different OA schemes available in the different atmospheric configurations of CESM2 and discusses differences in aerosol burden and resulting climate forcings. Derived OA burden and trends differ due to differences in OA formation using the different approaches. Regional differences in Aerosol Optical Depth with larger values using the comprehensive approach occur over SOA source regions. Stronger increasing SOA trends between 1960 and 2015 in WACCM6 compared to CAM6 are due to increasing biogenic emissions aligned with increasing surface temperatures. Using the comprehensive SOA approach further leads to improved comparisons to aircraft observations and SOA formation of ˜143 Tg/yr. We further use WACCM6 to identify source contributions of OA from biogenic, fossil fuel, and biomass burning emissions, to quantify SOA amounts and trends from these sources. Increasing SOA trends between 1960 and 2015 are the result of increasing biogenic emissions aligned with increasing surface temperatures. Biogenic emissions are at least two thirds of the total SOA burden. In addition, SOA source contributions from fossil fuel emissions become more important, with largest values over Southeast Asia. The estimated total anthropogenic forcing of OA in WACCM6 for 1995–2010 conditions is -0.43 W/m2, mostly from the aerosol direct effect.

Tilmes, S↗

DOE OSTI2025

A Fortran–Python interface for integrating machine learning parameterization into earth system models

Abstract. Parameterizations in earth system models (ESMs) are subject to biases and uncertainties arising from subjective empirical assumptions and incomplete understanding of the underlying physical processes. Recently, the growing representational capability of machine learning (ML) in solving complex problems has spawned immense interests in climate science applications. Specifically, ML-based parameterizations have been developed to represent convection, radiation, and microphysics processes in ESMs by learning from observations or high-resolution simulations, which have the potential to improve the accuracies and alleviate the uncertainties. Previous works have developed some surrogate models for these processes using ML. These surrogate models need to be coupled with the dynamical core of ESMs to investigate the effectiveness and their performance in a coupled system. In this study, we present a novel Fortran–Python interface designed to seamlessly integrate ML parameterizations into ESMs. This interface showcases high versatility by supporting popular ML frameworks like PyTorch, TensorFlow, and scikit-learn. We demonstrate the interface's modularity and reusability through two cases: an ML trigger function for convection parameterization and an ML wildfire model. We conduct a comprehensive evaluation of memory usage and computational overhead resulting from the integration of Python codes into the Fortran ESMs. By leveraging this flexible interface, ML parameterizations can be effectively developed, tested, and integrated into ESMs.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2016

Evaluation of Simulated Marine Aerosol Production Using the WaveWatchIII Prognostic Wave Model Coupled to the Community Atmosphere Model within the Community Earth System Model

Primary marine aerosol (PMA) is emitted into the atmosphere via breaking wind waves on the ocean surface. Most parameterizations of PMA emissions use 10-meter wind speed as a proxy for wave action. This investigation coupled the 3 rd generation prognostic WAVEWATCH-III wind-wave model within a coupled Earth system model (ESM) to drive PMA production using wave energy dissipation rate – analogous to whitecapping – in place of 10-meter wind speed. The wind speed parameterization did not capture basin-scale variability in relations between wind and wave fields. Overall, the wave parameterization did not improve comparison between simulated versus measured AOD or Na + , thus highlighting large remaining uncertainties in model physics. Results confirm the efficacy of prognostic wind-wave models for air-sea exchange studies coupled with laboratory- and field-based characterizations of the primary physical drivers of PMA production. No discernible correlations were evident between simulated PMA fields and observed chlorophyll or sea surface temperature.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2015

Carbon isotopes in the ocean model of the Community Earth System Model (CESM1)

Carbon isotopes in the ocean are frequently used as paleoclimate proxies and as present-day geochemical ocean tracers. In order to allow a more direct comparison of climate model results with this large and currently underutilized data set, we added a carbon isotope module to the ocean model of the Community Earth System Model (CESM), containing the cycling of the stable isotope 13 C and the radioactive isotope 14 C. We implemented the 14 C tracer in two ways: in the "abiotic" case, the 14 C tracer is only subject to air–sea gas exchange, physical transport, and radioactive decay, while in the "biotic" version, the 14 C additionally follows the 13 C tracer through all biogeochemical and ecological processes. Thus, the abiotic 14 C tracer can be run without the ecosystem module, requiring significantly fewer computational resources. The carbon isotope module calculates the carbon isotopic fractionation during gas exchange, photosynthesis, and calcium carbonate formation, while any subsequent biological process such as remineralization as well as any external inputs are assumed to occur without fractionation. Given the uncertainty associated with the biological fractionation during photosynthesis, we implemented and tested three parameterizations of different complexity. Compared to present-day observations, the model is able to simulate the oceanic 14 C bomb uptake and the 13 C Suess effect reasonably well compared to observations and other model studies. Lastly, at the same time, the carbon isotopes reveal biases in the physical model, for example, too sluggish ventilation of the deep Pacific Ocean.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

Evaluation of native Earth system model output with ESMValTool v2.6.0

Earth system models (ESMs) are state-of-the-art climate models that allow numerical simulations of the past, present-day, and future climate. To extend our understanding of the Earth system and improve climate change projections, the complexity of ESMs heavily increased over the last decades. As a consequence, the amount and volume of data provided by ESMs has increased considerably. Innovative tools for a comprehensive model evaluation and analysis are required to assess the performance of these increasingly complex ESMs against observations or reanalyses. One of these tools is the Earth System Model Evaluation Tool (ESMValTool), a community diagnostic and performance metrics tool for the evaluation of ESMs. Input data for ESMValTool needs to be formatted according to the CMOR (Climate Model Output Rewriter) standard, a process that is usually referred to as “CMORization”. While this is a quasi-standard for large model intercomparison projects like the Coupled Model Intercomparison Project (CMIP), this complicates the application of ESMValTool to non-CMOR-compliant climate model output. In this paper, we describe an extension of ESMValTool introduced in v2.6.0 that allows seamless reading and processing of “native” climate model output, i.e., operational output produced by running the climate model through the standard workflow of the corresponding modeling institute. This is achieved by an extension of ESMValTool's preprocessing pipeline that performs a CMOR-like reformatting of the native model output during runtime. Thus, the rich collection of diagnostics provided by ESMValTool is now fully available for these models. For models that use unstructured grids, a further preprocessing step required to apply many common diagnostics is regridding to a regular latitude–longitude grid. Extensions to ESMValTool's regridding functions described here allow for more flexible interpolation schemes that can be used on unstructured grids. Currently, ESMValTool supports nearest-neighbor, bilinear, and first-order conservative regridding from unstructured grids to regular grids. Example applications of this new native model support are the evaluation of new model setups against predecessor versions, assessing of the performance of different simulations against observations, CMORization of native model data for contributions to model intercomparison projects, and monitoring of running climate model simulations. For the latter, new general-purpose diagnostics have been added to ESMValTool that are able to plot a wide range of variable types. Currently, five climate models are supported: CESM2 (experimental; at the moment, only surface variables are available), EC-Earth3, EMAC, ICON, and IPSL-CM6. As the framework for the CMOR-like reformatting of native model output described here is implemented in a general way, support for other climate models can be easily added.

58 GEOSCIENCES↗

DOE OSTI2021

Description and Demonstration of the Coupled Community Earth System Model v2 – Community Ice Sheet Model v2 (CESM2‐CISM2)

Abstract Earth system/ice‐sheet coupling is an area of recent, major Earth System Model (ESM) development. This work occurs at the intersection of glaciology and climate science and is motivated by a need for robust projections of sea‐level rise. The Community Ice Sheet Model version 2 (CISM2) is the newest component model of the Community Earth System Model version 2 (CESM2). This study describes the coupling and novel capabilities of the model, including: (1) an advanced energy‐balance‐based surface mass balance calculation in the land component with downscaling via elevation classes; (2) a closed freshwater budget from ice sheet to the ocean from surface runoff, basal melting, and ice discharge; (3) dynamic land surface types; and (4) dynamic atmospheric topography. The Earth system/ice‐sheet coupling is demonstrated in a simulation with an evolving Greenland Ice Sheet (GrIS) under an idealized high CO 2 scenario. The model simulates a large expansion of ablation areas (where surface ablation exceeds snow accumulation) and a large increase in surface runoff. This results in an elevated freshwater flux to the ocean, as well as thinning of the ice sheet and area retreat. These GrIS changes result in reduced Greenland surface albedo, changes in the sign and magnitude of sensible and latent heat fluxes, and modified surface roughness and overall ice sheet topography. Representation of these couplings between climate and ice sheets is key for the simulation of ice and climate interactions.

Muntjewerf, Laura↗

DOE OSTI2020

Technical note: Deep learning for creating surrogate models of precipitation in Earth system models

Abstract. We investigate techniques for using deep neural networks to produce surrogatemodels for short-term climate forecasts. A convolutional neural network istrained on 97 years of monthly precipitation output from the 1pctCO2 run (theCO 2 concentration increases by 1 % per year) simulated by the second-generation Canadian Earth System Model (CanESM2). The neural network clearly outperforms a persistence forecast anddoes not show substantially degraded performance even when the forecast lengthis extended to 120 months. The model is prone to underpredicting precipitationin areas characterized by intense precipitation events. Scheduled sampling(forcing the model to gradually use its own past predictions rather than groundtruth) is essential for avoiding amplification of early forecasting errors.However, the use of scheduled sampling also necessitates preforecasting(generating forecasts prior to the first forecast date) to obtain adequateperformance for the first few prediction time steps. We document the trainingprocedures and hyperparameter optimization process for researchers who wish toextend the use of neural networks in developing surrogate models.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2017

231 Pa and 230 Th in the ocean model of the Community Earth System Model (CESM1.3)

The sediment 231 Pa / 230 Th activity ratio is emerging as an important proxy for deep ocean circulation in the past. In order to allow for a direct model–data comparison and to improve our understanding of the sediment 231 Pa / 230 Th activity ratio, we implement 231 Pa and 230 Th in the ocean component of the Community Earth System Model (CESM). In addition to the fully coupled implementation of the scavenging behavior of 231 Pa and 230 Th with the active marine ecosystem module (particle-coupled: hereafter p-coupled), another form of 231 Pa and 230 Th have also been implemented with prescribed particle flux fields of the present climate (particle-fixed: hereafter p-fixed). The comparison of the two forms of 231 Pa and 230 Th helps to isolate the influence of the particle fluxes from that of ocean circulation. Under present-day climate forcing, our model is able to simulate water column 231 Pa and 230 Th activity and the sediment 231 Pa / 230 Th activity ratio in good agreement with available observations. In addition, in response to freshwater forcing, the p-coupled and p-fixed sediment 231 Pa / 230 Th activity ratios behave similarly over large areas of low productivity on long timescales, but can differ substantially in some regions of high productivity and on short timescales, indicating the importance of biological productivity in addition to ocean transport. Thus, our model provides a potentially powerful tool to help the interpretation of sediment 231 Pa / 230 Th reconstructions and to improve our understanding of past ocean circulation and climate changes.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2025

Disentangling atmospheric, hydrological, and coupling uncertainties in compound flood modeling within a coupled Earth system model

Compound riverine and coastal flooding is usually driven by complex interactions among meteorological, hydrological, and ocean extremes. However, existing efforts to model this phenomenon often do not integrate hydrological processes across atmosphere–land–river–ocean systems, leading to substantial uncertainties that have not been fully examined. To bridge this gap, we leverage the new capabilities of the Energy Exascale Earth System Model (E3SM) that enable a multi-component framework that integrates coastally refined atmospheric, terrestrial, and oceanic components. We evaluate compound uncertainties arising from two-way land–river–ocean coupling in E3SM and track the cascading meteorological and hydrological uncertainties through ensemble simulations over the Delaware River basin and estuary during Hurricane Irene (2011). Our findings highlight the importance of two-way river–ocean coupling to compound flood modeling and demonstrate E3SM's capability in capturing compound flood extent near the coast, with a hit rate over 0.75. Our study shows the growing uncertainties that transition from atmospheric forcings to flood distribution and severity. Furthermore, an analysis based on artificial neural networks is used to assess the roles of hydrological drivers, such as infiltration and soil moisture, in the generation of compound flooding. The response of compound floods to tropical cyclones (TCs) is found to be susceptible to these often overlooked drivers. For instance, the flooded area could increase more than 2-fold (∼2.4) if Hurricane Irene were preceded by an extreme antecedent soil moisture condition (AMC). The results not only support the use of a multi-component framework for interactive flooding processes, but also underscore the necessity of broader definitions of compound flooding that encompass the simultaneous occurrence of intense precipitation, storm surge, and high AMC during TCs.

Feng, Dongyu [Pacific Northwest National Laborator↗

NASA NTRS2024

Future CH4 Budgets as Modelled By A Fully Coupled Earth System Model Using Prescribed GHG Concentrations vs. Interactive CH4 Sources and Sinks

We have used the NASA Goddard Institute for Space Studies (GISS) Earth system model GISS-E2.1 to study the future budgets and trends of global and regional CH4 under different emission scenarios. GISS-E2.1 is one of the few ESMs that can be driven by anthropogenic CH4 emissions, as well as interactive natural sources such as wetlands, and can simulate the tropospheric CH4 chemistry. In frame of the recent short-lived climate forcers (SLCFs) assessment by the Arctic Monitoring and Assessment Programme (AMAP), we used the GISS-E2.1 model with prescribed long-lived greenhouse gas (GHG) concentrations. In the present study, we have supplemented these simulations using the interactive CH4 sources and sinks in order to quantify the model performance and the sensitivity to CH4 sources and sinks. We have used the Current Legislation (CLE) and the Maximum Feasible Reduction (MFR) emission scenarios from the Eclipse V6b emission database to simulate the future chemical composition and climate impacts from 2015 to 2050. We have also simulated 1995-2014 in order to evaluate the model performance following the AMAP-SLCF protocol. The prescribed GHG version underestimates the Global Atmospheric Watch (GAW) surface CH4 observations during the period between 1995 and 2023 by 1% [-8.4%-2.0%], with a correlation (r) of 0.71 [-0.41 0.99]. The largest underestimations are over the continental emission regions such as North America, Europe, and Asia, while biases are smallest over oceans. On the other hand, the simulation with interactive sources and sinks underestimates the GAW observations more than the prescribed simulation, by 18.5% [-25% -10.4%], with a lower r of 0.36 [-0.82 0.93]. Opposite to the prescribed simulation, the biases are largest over oceans and smaller over the continents, however they are still larger over land than the prescribed simulation. The interactive simulation, with large sources virtually over land and strong sink over oceans, has a land/ocean ratio larger than 1 while the prescribed simulation has this ratio equal to 1 as it distributes the global prescribed CH4 concentration equally in longitude over a given latitude. This clearly shows that the interactive sources and sinks should be represented in models in order to realistically simulate the chemical composition and the oxidative capacity of the atmosphere. As expected, the MFR scenario simulates lower global surface CH4 concentrations and burdens compared to the CLE scenario, however in both cases, global surface CH4 and burden continue to increase through 2050 compared to present day. In the CLE scenario, increases are largest over the equatorial belt, in particular over India and East China, while the MFR scenario shows increases over the whole Southern Hemisphere, however much smaller compared to CLE. Finally, the interactive simulation shows that the chemical CH4 sink increases in the CLE scenario, while it slightly decreases in the MFR, leading to a larger CH4 lifetime in the MFR scenario compared to in the CLE scenario.

CH4↗

DOE OSTI2015

Development of hybrid 3-D hydrological modeling for the NCAR Community Earth System Model (CESM)

58 GEOSCIENCES↗

DOE OSTI2017

Significant inconsistency of vegetation carbon density in CMIP5 Earth system models against observational data

Abstract Earth system models (ESMs) have been widely used for projecting global vegetation carbon dynamics, yet how well ESMs performed for simulating vegetation carbon density remains untested. We compiled observational data of vegetation carbon density from literature and existing data sets to evaluate nine ESMs at site, biome, latitude, and global scales. Three variables—root (including fine and coarse roots), total vegetation carbon density, and the root:total vegetation carbon ratios (R/T ratios), were chosen for ESM evaluation. ESM models performed well in simulating the spatial distribution of carbon densities in root ( r = 0.71) and total vegetation ( r = 0.62). However, ESM models had significant biases in simulating absolute carbon densities in root and total vegetation biomass across the majority of land ecosystems, especially in tropical and arctic ecosystems. Particularly, ESMs significantly overestimated carbon density in root (183%) and total vegetation biomass (167%) in climate zones of 10°S–10°N. Substantial discrepancies between modeled and observed R/T ratios were found: the R/T ratios from ESMs were relatively constant, approximately 0.2 across all ecosystems, along latitudinal gradients, and in tropic, temperate, and arctic climatic zones, which was significantly different from the observed large variations in the R/T ratios (0.1–0.8). There were substantial inconsistencies between ESM‐derived carbon density in root and total vegetation biomass and the R/T ratio at multiple scales, indicating urgent needs for model improvements on carbon allocation algorithms and more intensive field campaigns targeting carbon density in all key vegetation components.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2025

Baseline Climate Variables for Earth System Modelling

The Baseline Climate Variables for Earth System Modelling (ESM-BCVs) are defined as a list of 135 variables which have high utility for the evaluation and exploitation of climate simulations. The list reflects the most frequently used elements of the Coupled Model Intercomparison Project Phase 6 (CMIP6) archive. Successive phases of CMIP have supported strong results in science and substantially influence international climate policy formulation. This paper responds to both interest in exploiting CMIP data standards in a broader range of climate modelling activities and a need to achieve greater clarity about the significance and intention of variables in the CMIP Data Request. As Earth system modelling archives grow in scale and complexity, there are emerging problems associated with weak standardisation at the variable collection level. That is, there are good standards covering how specific variables should be archived, but this paper fills a gap in the standardisation of which variables should be archived. The ESM-BCV list is intended as a resource for ESM intercomparison projects (MIPs) developing requests to enable greater consistency among MIPs and as a reference for modelling centres to enhance consistency within MIPs. Provisional planning for the CMIP7 Data Request exploits the ESM-BCVs as a core element. The baseline variable list includes 98 variables which have modest or minor data volume footprints and could be generated systematically when simulations are produced and archived for exploitation by the World Climate Research Programme (WCRP) community. A further 35 variables are classed as “high volume” and are only suitable for production when the resource implications are justified.

Juckes, Martin [University of Oxford (United Kingd↗

NASA NTRS2015

Development of a Grid-Independent Geos-Chem Chemical Transport Model (v9-02) as an Atmospheric Chemistry Module for Earth System Models

The GEOS-Chem global chemical transport model (CTM), used by a large atmospheric chemistry research community, has been re-engineered to also serve as an atmospheric chemistry module for Earth system models (ESMs). This was done using an Earth System Modeling Framework (ESMF) interface that operates independently of the GEOSChem scientific code, permitting the exact same GEOSChem code to be used as an ESM module or as a standalone CTM. In this manner, the continual stream of updates contributed by the CTM user community is automatically passed on to the ESM module, which remains state of science and referenced to the latest version of the standard GEOS-Chem CTM. A major step in this re-engineering was to make GEOS-Chem grid independent, i.e., capable of using any geophysical grid specified at run time. GEOS-Chem data sockets were also created for communication between modules and with external ESM code. The grid-independent, ESMF-compatible GEOS-Chem is now the standard version of the GEOS-Chem CTM. It has been implemented as an atmospheric chemistry module into the NASA GEOS- 5 ESM. The coupled GEOS-5-GEOS-Chem system was tested for scalability and performance with a tropospheric oxidant-aerosol simulation (120 coupled species, 66 transported tracers) using 48-240 cores and message-passing interface (MPI) distributed-memory parallelization. Numerical experiments demonstrate that the GEOS-Chem chemistry module scales efficiently for the number of cores tested, with no degradation as the number of cores increases. Although inclusion of atmospheric chemistry in ESMs is computationally expensive, the excellent scalability of the chemistry module means that the relative cost goes down with increasing number of cores in a massively parallel environment.

CTM↗

DOE OSTI2015

Development of hybrid 3-D hydrological modeling for the NCAR Community Earth System Model (CESM)

This is the Final Report of our four-year (3-year plus one-year no cost extension) collaborative project between the University of Arizona (UA) and the National Center for Atmospheric Research (NCAR). The overall objective of our project is to develop and evaluate the first hybrid 3-D hydrological model with a horizontal grid spacing of 1 km for the NCAR Community Earth System Model (CESM). We have made substantial progress in model development and evaluation, computational efficiencies and software engineering, and data development and evaluation, as discussed in Sections 2-4. Section 5 presents our success in data dissemination, while Section 6 discusses the scientific impacts of our work. Section 7 discusses education and mentoring success of our project, while Section 8 lists our relevant DOE services. All peer-reviewed papers that acknowledged this project are listed in Section 9. Highlights of our achievements include: • We have finished 20 papers (most published already) on model development and evaluation, computational efficiencies and software engineering, and data development and evaluation • The global datasets developed under this project have been permanently archived and publicly available • Some of our research results have already been implemented in WRF and CLM • Patrick Broxton and Michael Brunke have received their Ph.D. • PI Zeng has served on DOE proposal review panels and DOE lab scientific focus area (SFA) review panels

58 GEOSCIENCES↗

NASA NTRS2026

Modeling Large Dust Aerosols in the Community Earth System Model Version 2 (CESM2)

Dust aerosols have a wide size distribution from less than 0.1 to over 100 μm and dominate Earth's atmospheric aerosol mass. However, most Earth system models (ESMs) inadequately represent dust aerosols larger than 10 μm in diameter, limiting the accuracy of the simulated dust cycle and climate impacts. Here, we introduce a new modeling framework that captures the full observed size distribution of dust aerosols, incorporating recent advances into a mineral-resolved version of the Community ESM, while addressing known issues in previous versions. Comprehensive evaluation against diverse observations of bulk dust and component minerals demonstrates that the model reproduces the observed dust cycle across particle sizes. Incorporating the previously unrepresented large-dust fractions substantially alters dust budget estimates, highlighting potential changes in simulated climate impacts and underscoring the importance of comprehensive size-resolved dust modeling. Despite these advancements, uncertainties persist. Our results indicate that a size-dependent reduction in settling velocity is required to reproduce the observed dust size distribution downwind of source regions. Specifically, in the new model, the gravitational settling velocity of dust particles larger than 10 μm in diameter must be reduced by as much as 85% to achieve agreement with observations. This empirical reduction serves as a constraint on physics-based models of dust settling. Future developments should address misrepresented physical processes that hinder accurate modeling of the large dust aerosol transport. Expanding observational data sets covering the full-size distribution is also essential to better constrain the dust cycle and improve the representation of dust optical properties and climate effects.

mineral dust↗

DOE OSTI2021

Black-Box Neural System Identification and Differentiable Programming to Improve Earth System Model Predictions February

Focal Area(s): Focal Area 2: AI for predictive modeling, including AI-derived model components, and AI-enabled applications including parameter optimization, data assimilation, and uncertainty quantification. Focal Area 1: AI-assisted data assimilation using numerical Earth system models. Science Challenge: Earth system models have structural biases that lead to uncertain predictions, and their complexity and expense makes it difficult constraining the models with data or improved physical understanding.

54 ENVIRONMENTAL SCIENCES↗