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At least 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Evaluating the impacts of Variable Message Signs on Airport Curbside Performance Using Microsimulation

Curbs play a vital role in facilitating vehicle access and egress for individuals at airports. Inefficiently allocating this resource hinders airport accessibility and productivity, resulting in congestion, longer travel times, and increased pollution. As airport demand fluctuates throughout the day and grows over time, airports face intensified curbside pressure. Yet, curb management research is significantly less robust at airports than in urban areas. Given the unbalanced nature of airport demand—riders tend to arrive simultaneously at specific entrances at certain hours—Variable Message Sign (VMS) arises as a cost-effective technology to divert vehicles from congested to underutilized curbs. Still, VMS implementation faces a significant challenge. Historically, airports have managed VMS heuristically and by intuition rather than an evidence-based approach. This research investigates the impacts of implementing VMS on curb performance at airports. By considering different driver compliance rates (DCR), we aim to determine when the sign should be turned on and off to diverge traffic to avoid undesired externalities while enhancing curb performance. Using a validated agent-based microsimulation model, VISSIM, we analyzed the Seattle-Tacoma (SeaTac) Airport as a case study. We modeled sixteen VMS management scenarios and a baseline where the message sign is not displayed, diverging vehicles between the departures and arrivals access levels at four different moments (early morning, morning, afternoon, and late night). We quantified the effects of VMS using seven metrics, including curb productivity index (CPI), curb accessibility (CA), queue length, queue duration, delay, vehicle counts, and emissions. The results of each scenario were compared against the baseline using absolute and relative changes and Repeated Measures ANOVA. Overall, VMS improved curb performance and traffic conditions at the airport, reducing emissions by 14.8% to 8.9%. Moreover, significant reductions in queue length (1,150 ft to 100 ft) and duration (15 to 144 minutes) were observed in the sending link under all VMS policies. However, impacts on the receiving link varied based on congestion, with significant increases in queue duration (9.8 to 24 min) when congested but no substantial changes in free flow. Notably, diverging vehicles to congested links resulted in non-significant results, and activating late and deactivating late VMS affected curb productivity (-5.8% to -61.4%), curb accessibility (-16.5% to -25.8%), cumulative counts (-33.4% to -59.4%), and vehicle delay (95.98% to 594.3%). Activating VMS before congestion begins in the sending link and deactivating before a queue forms in the receiving link yield the most significant improvements: 8.1% to 10.1% in CPI, 9.4% to9.6% in CA, -29.3% to -77.9% in total delay, -11.6% to -13.9% in total emissions, and 101% to 103% in cumulative counts. As the analysis was made with a wide range of time periods, access levels, driver compliance rates, and scenarios, we believe our findings can provide valuable insights into how airports should manage VMS. Our work introduces a novel approach to the scientific airport literature, as some of our metrics were previously unexplored. Additionally, we propose a methodology that other airports can adopt to maximize their curb performance.

Gutierrez, Jorge D.↗
NASA NTRS1997

An Interagency Study of Depainting Techniques

Many popular and widely used paint stripping products now contain methylene chloride as their active ingredient. However, the Environmental Protection Agency (EPA) will critically curb the use of methylene chloride under an aerospace national emission standard for hazardous air pollutants (NESHAP) within the next 2-1/2 years. An effort is underway to identify and evaluate alternative depainting technologies emphasizing those believed to be both effective and environmentally benign. On behalf of the EPA and in cooperation with the U. S. Air Force (USAF), the National Aeronautics and Space Administration (NASA) is conducting a technical assessment of nine alternative technologies (i.e.: chemical stripping, two CO2 blasting processes, FLASHJET(TM) coating removal, laser stripping, plastic media blasting, sodium bicarbonate wet stripping, high-pressure water stripping, and wheat starch blasting). These depainting processes represent five removal method categories, namely abrasive, impact, cryogenic, thermal, and/or molecular bonding dissociation. This paper discusses the test plan and parameters for this interagency study. Several thicknesses of clad and non-clad aluminum substrates were used to prepare test specimens, which have been cut, cleaned, painted, and environmentally aged. Each depainting process has been assigned a specimen lot, which is now undergoing an initial strip cycle. Metallurgical impacts will be determined after these specimens complete five cycles of preparation and stripping.

Cook, B.↗
DOE OSTI2026

Open-Source Data for MAC-POSTS: Mobility Data Analytics Center - Prediction, Optimization, and Simulation Toolkit for Transportation Systems

MAC-POSTS (Mobility Data Analytics Center - Prediction, Optimization, and Simulation toolkit for Transportation Systems) is a toolkit for dynamic transportation network modeling. Developed by the Mobility Data Analytics Center (MAC) at Carnegie Mellon University, this package implements many classic dynamic transportation network models, as well as new models proposed by MAC members. It has served as one building block for many other models and research projects. As such, this package used to be treated as an internal research project of the MAC lab, and admittedly, the code base is messy, and the interface is hard to use. However, we are working hard to make it a generally usable and useful toolkit for dynamic transportation network modeling. We would really appreciate any feedback, comments, suggestions, or criticisms.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
NASA NTRS2012

Curb Mounting, Vertical Mobility, and Inverted Mobility on Rough Surfaces Using Microspine-Enabled Robots

Three robots that extend microspine technology to enable advanced mobility are presented. First, the Durable Reconnaissance and Observation Platform (DROP) and the ReconRobotics Scout platform use a new rotary configuration of microspines to provide improved soldier-portable reconnaissance by moving rapidly over curbs and obstacles, transitioning from horizontal to vertical surfaces, climbing rough walls and surviving impacts. Next, the four-legged LEMUR robot uses new configurations of opposed microspines to anchor to both manmade and natural rough surfaces. Using these anchors as feet enables mobility in unstructured environments, from urban disaster areas to deserts and caves.

microspines↗
DOE OSTI2024

A Model for Optimally Allocating Curbside Space Among Competing Uses

The emergence of various new forms of urban mobility services in recent years is leading to new pressures on curbside space. Municipalities, the entities typically responsible for managing the curbside, are in many instances handling these growing pressures by reallocating portions of the curbside away from traditional uses (such as metered and residential parking) in favor of uses such as ridehailing, scooter and bike-share corrals. As yet, however, such actions are being undertaken on an ad-hoc basis, due to the rapidly growing complexity of the curbside and the lack of standard analytical approaches. This lack of analytical capability is due to the traditional focus of transportation network modeling being focused predominantly on the interaction of supply and demand on links and nodes, with limited focus on link edges (the curbside). In this paper we address this research need by proposing a framework for modeling inter-modal competition for curbside space, inspired by the classical Bid-Rent Model of urban land use, intended to support curb managers to move towards maximizing the aspects of economic welfare that relate to curb access. In the bi-level model, choices made by the curbside manager impact travelers’ mode choices, and vice versa. We then present a simple numerical case study to demonstrate the properties of the proposed model, showing its tractability, flexibility, and intuitive sensitivity to systematic variation in inputs. The framework demonstrates the type of adaptive and evolving approach needed to maximize benefits from increasingly dynamic curb management strategies. The paper concludes with a brief discussion of future research needs to advance this line of inquiry.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2026

Alginate–Amorphous Calcium Carbonate Hydrogels for Controlled Therapeutic Release

Alginate hydrogels are widely explored as biocompatible matrices for transdermal delivery of therapeutic compounds but burst release and mechanical stability remain persistent challenges in drug delivery systems. This experimental study investigated alginate–amorphous calcium carbonate (ACC) hydrogel composites designed to regulate release of model anti-inflammatory compound, ibuprofen. Hydrogels containing 1.6–2.0 wt% sodium alginate were crosslinked with CaCl₂ and combined with ACC through two incorporation pathways: (i) separate addition of ACC and ibuprofen or (ii) co-precipitation of ACC onto ibuprofen prior to hydrogel incorporation. Hydrogels without ACC served as Control. Biocomposite structure and properties were characterized and release profiles quantified using Korsmeyer–Peppas (KP) model.Burst release was curbed as crosslinking time increased, highlighting importance of network density in diffusion control. Co-precipitating ACC with ibuprofen prior to incorporating into the hydrogel suppressed burst release and sustained release for > ~72 h. Rheological measurements indicate ACC reinforces hydrogel network, increasing storage modulus while maintaining hydration and flexibility. KP model indicates release is diffusion-controlled, with deviations reflecting contributions from diffusion barriers and morphologic/structural changes near the ACC coated ibuprofen. ACC within alginate hydrogels provides a strategy for tuning drug release while preserving mechanical properties relevant to transdermal applications.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Soil microbiome interventions for carbon sequestration and climate mitigation

Mitigating climate change in soil ecosystems involves complex plant and microbial processes regulating carbon pools and flows. Here, we advocate for the use of soil microbiome interventions to help increase soil carbon stocks and curb greenhouse gas emissions from managed soils. Direct interventions include the introduction of microbial strains, consortia, phage, and soil transplants, whereas indirect interventions include managing soil conditions or additives to modulate community composition or its activities. Approaches to increase soil carbon stocks using microbially catalyzed processes include increasing carbon inputs from plants, promoting soil organic matter (SOM) formation, and reducing SOM turnover and production of diverse greenhouse gases. Marginal or degraded soils may provide the greatest opportunities for enhancing global soil carbon stocks. Among the many knowledge gaps in this field, crucial gaps include the processes influencing the transformation of plant-derived soil carbon inputs into SOM and the identity of the microbes and microbial activities impacting this transformation. As a critical step forward, we encourage broadening the current widespread screening of potentially beneficial soil microorganisms to encompass functions relevant to stimulating soil carbon stocks. Moreover, in developing these interventions, we must consider the potential ecological ramifications and uncertainties, such as incurred by the widespread introduction of homogenous inoculants and consortia, and the need for site-specificity given the extreme variation among soil habitats. Incentivization and implementation at large spatial scales could effectively harness increases in soil carbon stocks, helping to mitigate the impacts of climate change.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Estimating Total Methane Emissions from the Denver-Julesburg Basin Using Bottom-Up Approaches

Methane is a powerful greenhouse gas with a 25 times higher 100-year warming potential than carbon dioxide and is a target for mitigation to achieve climate goals. To control and curb methane emissions, estimates are required from the sources and sectors which are typically generated using bottom-up methods. However, recent studies have shown that national and international bottom-up approaches can significantly underestimate emissions. In this study, we present three bottom-up approaches used to estimate methane emissions from all emission sectors in the Denver-Julesburg basin, CO, USA. Our data show emissions generated from all three methods are lower than historic measurements. A Tier 1/2 approach using IPCC emission factors estimated 2022 methane emissions of 358 Gg (0.8% of produced methane lost by the energy sector), while a Tier 3 EPA-based approach estimated emissions of 269 Gg (0.2%). Using emission factors informed by contemporary and region-specific measurement studies, emissions of 212 Gg (0.2%) were calculated. The largest difference in emissions estimates were a result of using the Mechanistic Air Emissions Simulator (MAES) for the production and transport of oil and gas in the DJ basin. The MAES accounts for changes to regulatory practice in the DJ basin, which include comprehensive requirements for compressors, pneumatics, equipment leaks, and fugitive emissions, which were implemented to reduce emissions starting in 2014. The measurement revealed that normalized gas loss is predicted to have been reduced by a factor of 20 when compared to 10-year-old normalization loss measurements and a factor of 10 less than a nearby oil and production area (Delaware basin, TX); however, we suggest that more measurements should be made to ensure that the long-tail emission distribution has been captured by the modeling. This study suggests that regulations implemented by the Colorado Department of Public Health and Environment could have reduced emissions by a factor of 20, but contemporary regional measurements should be made to ensure these bottom-up calculations are realistic.

03 NATURAL GAS↗
NASA NTRS2005

Spatial Predictive Modeling and Remote Sensing of Land Use Change in the Chesapeake Bay Watershed

This project was focused on modeling the processes by which increasing demand for developed land uses, brought about by changes in the regional economy and the socio-demographics of the region, are translated into a changing spatial pattern of land use. Our study focused on a portion of the Chesapeake Bay Watershed where the spatial patterns of sprawl represent a set of conditions generally prevalent in much of the U.S. Working in the region permitted us access to (i) a time-series of multi-scale and multi-temporal (including historical) satellite imagery and (ii) an established network of collaborating partners and agencies willing to share resources and to utilize developed techniques and model results. In addition, a unique parcel-level tax assessment database and linked parcel boundary maps exists for two counties in the Maryland portion of this region that made it possible to establish a historical cross-section time-series database of parcel level development decisions. Scenario analyses of future land use dynamics provided critical quantitative insight into the impact of alternative land management and policy decisions. These also have been specifically aimed at addressing growth control policies aimed at curbing exurban (sprawl) development. Our initial technical approach included three components: (i) spatial econometric modeling of the development decision, (ii) remote sensing of suburban change and residential land use density, including comparisons of past change from Landsat analyses and more traditional sources, and (iii) linkages between the two through variable initialization and supplementation of parcel level data. To these we added a fourth component, (iv) cellular automata modeling of urbanization, which proved to be a valuable addition to the project. This project has generated both remote sensing and spatially explicit socio-economic data to estimate and calibrate the parameters for two different types of land use change models and has undertaken analyses of these models. One (the CA model) is driven largely by observations on past patterns of land use change, while the other (the EC model) is driven by mechanisms of the land use change decision at the parcel level. Our project may be the first serious attempt at developing both types of models for the same area, using as much common data as possible. We have identified the strengths and weaknesses of the two approaches and plan to continue to revise each model in the light of new data and new lessons learned through continued collaboration. Questions, approaches, findings, publication and presentation lists concerning the research are also presented.

Goetz, Scott J.↗
NASA NTRS2012

Alternate-Fueled Combustion-Sector Emissions

In order to meet rapidly growing demand for fuel, as well as address environmental concerns, the aviation industry has been testing alternate fuels for performance and technical usability in commercial and military aircraft. Currently, alternate aviation fuels must satisfy MIL-DTL- 83133F(2008) (military) or ASTM D 7566- Annex(2011) (commercial) standards and are termed drop-in fuel replacements. Fuel blends of up to 50% alternative fuel blended with petroleum (JP-8), which have become a practical alternative, are individually certified on the market. In order to make alternate fuels (and blends) a viable option for aviation, the fuel must be able to perform at a similar or higher level than traditional petroleum fuel. They also attempt to curb harmful emissions, and therefore a truly effective alternate fuel would emit at or under the level of currently used fuel. This paper analyzes data from gaseous and particulate emissions of an aircraft combustor sector. The data were evaluated at various inlet conditions, including variation in pressure and temperature, fuel-to-air ratios, and percent composition of alternate fuel. Traditional JP-8+100 data were taken as a baseline, and blends of JP- 8+100 with synthetic-paraffinic-kerosene (SPK) fuel (Fischer-Tropsch (FT)) were used for comparison. Gaseous and particulate emissions, as well as flame luminosity, were assessed for differences between FT composition of 0%, 50%, and 100%. The data showed that SPK fuel (a FT-derived fuel) had slightly lower harmful gaseous emissions, and smoke number information corroborated the hypothesis that SPK-FT fuels are cleaner burning fuels.

Saxena, Nikita T.↗
NASA NTRS2013

Alternate-Fueled Combustor-Sector Emissions

In order to meet rapidly growing demand for fuel, as well as address environmental concerns, the aviation industry has been testing alternate fuels for performance and technical usability in commercial and military aircraft. In order to make alternate fuels (and blends) a viable option for aviation, the fuel must be able to perform at a similar or higher level than traditional petroleum fuel. They also attempt to curb harmful emissions, and therefore a truly effective alternate fuel would emit at or under the level of currently used fuel. This report analyzes data from gaseous and particulate emissions of an aircraft combustor sector. The data were evaluated at various inlet conditions, including variation in pressure and temperature, fuel-to-air ratios, and percent composition of alternate fuel. Traditional JP-8+100 data were taken as a baseline, and blends of JP-8+100 with synthetic-paraffinic-kerosene (SPK) fuel (Fischer-Tropsch (FT)) were used for comparison. Gaseous and particulate emissions, as well as flame luminosity, were assessed for differences between FT composition of 0, 50, and 100 percent. The data show that SPK fuel (an FT-derived fuel) had slightly lower harmful gaseous emissions, and smoke number information corroborated the hypothesis that SPK-FT fuels are cleaner burning fuels.

Saxena, Nikita T.↗
NASA NTRS2019

Success of Montreal Protocol Demonstrated by Comparing High-Quality UV Measurements with “World Avoided” Calculations from Two Chemistry-Climate Models

The Montreal protocol on Substances that Deplete the ozone Layer has been hailed as the most successful environmental treaty ever (https://www.unenvironment.org/news-and-stories/story/montreal-protocol-triumph-treaty). Yet, although our main concern about ozone depletion is the subsequent increase in harmful solar UV radiation at the earth’s surface, no studies to date have demonstrated its effectiveness in that regard. Here we use long-term UV Index (UVI) data derived from high-quality UV spectroradiometer measurements to demonstrate its success in curbing increases in UV radiation. Without this landmark agreement, UVi values would have increased at mid-latitude locations by approximately 20% between the early 1990s and today and would approximately quadruple at mid-latitudes by 2100. In contrast, an analysis of UVI data from multiple clean-air sites shows that maximum daily UVI values have remained essentially constant over the last ~20 years in all seasons, and may even have decreased slightly in the southern hemisphere, especially in Antarctica, where effects of ozone depletion were larger. Reconstructions of the UVi from total ozone data show evidence of increasing UVI levels in the 1980s, but unfortunately, there are no high-quality UV measurements available prior to the early 1990s to confirm these increases with direct observations.

UV Index (UVI) data derived from high-quality UV s↗
DOE OSTI2026

Structural Analysis of 23S rRNA Methylating Enzyme Cfr Reveals RNA-Binding Determinants for Methylation Regiospecificity and Antibiotic Resistance

The 23S rRNA methylating enzyme Cfr, found in pathogens including Staphylococcus aureus, Clostridium difficile, Escherichia coli, and Klebsiella pneumoniae, confers resistance to phenicols, lincosamides, oxazolidinones (including linezolid), pleuromutilins, and streptogramins A (the PhLOPS A phenotype). Cfr catalyzes methylation of the C8 position of the A2503 base in 23S rRNA, the recognition site of the above antibiotic classes. Along with the RlmN housekeeping enzyme, Cfr can also promote methylation of the C2 position of the same base. The molecular and structural basis of Cfr’s dual substrate specificity is not known, which hinders our ability to design Cfr-targeting inhibitors necessary to curb PhLOPS A resistance. Here, we present the first crystal structure of Cfr and a detailed analysis of its possible interactions with rRNA. Using structure-guided mutagenesis, mass spectrometry analysis of in cellulo 23S rRNA methylated species, and in cellulo resistance studies, we identify the key amino acids essential for Cfr methylation and multidrug resistance activity. In particular, we found that Cfr’s Q329 residue is important for C8- specific methylation. These data provide a framework for further studies of the biochemistry, structure, and inhibition of this important resistance determinant.

AlphaFold↗
NASA NTRS2013

Regenerable Sorbent for CO2 Removal

A durable, high-capacity regenerable sorbent can remove CO2 from the breathing loop under a Martian atmosphere. The system design allows near-ambient temperature operation, needs only a small temperature swing, and sorbent regeneration takes place at or above 8 torr, eliminating the potential for Martian atmosphere to leak into the regeneration bed and into the breathing loop. The physical adsorbent can be used in a metabolic, heat-driven TSA system to remove CO2 from the breathing loop of the astronaut and reject it to the Martian atmosphere. Two (or more) alternating sorbent beds continuously scrub and reject CO2 from the spacesuit ventilation loop. The sorbent beds are cycled, alternately absorbing CO2 from the vent loop and rejecting the adsorbed material into the environment at a high CO2 partial pressure (above 8 torr). The system does not need to run the adsorber at cryogenic temperatures, and uses a much smaller temperature swing. The sorbent removes CO2 via a weak chemical interaction. The interaction is strong enough to enable CO2 adsorption even at 3 to 7.6 torr. However, because the interaction between the surface adsorption sites and the CO2 is relatively weak, the heat input needed to regenerate the sorbent is much lower than that for chemical absorbents. The sorbent developed in this project could potentially find use in a large commercial market in the removal of CO2 emissions from coal-fired power plants, if regulations are put in place to curb carbon emissions from power plants.

Alptekin, Gokhan↗
DOE OSTI2026

Computational Analysis of Hydraulic Efficiency of Michigan DOT Covers J and K

Drainage structures are used in urban street and highway systems to capture stormwater runoff. These structures typically consist of catch basins fitted with grates, inlets, or combination grate/inlet configurations that collect runoff and convey it through buried drainage systems. They are strategically placed within curb-and-gutter systems to enhance public safety by efficiently removing water from roadways and thereby reducing the risk of hydroplaning. The performance of drainage structures is commonly evaluated in terms of hydraulic efficiency, defined as the percentage of flow captured by the basin relative to the total flow reaching the structure. Understanding the hydraulic performance of these structures allows designers to properly space inlets, resulting in cost-effective designs that also help ensure the safety of the traveling public. MDOT uses a variety of drainage structures for runoff capture, as documented in Michigan Department of Transportation (MDOT) Drainage Manual. Many of these structures incorporate sinusoidal-type grates that are not addressed in HEC-22. Because physical modeling of these structures has been limited, further analysis is needed to verify their capture efficiency. Under current MDOT practice, the capture efficiency of these grates is estimated by assuming performance similar to that of a comparably sized reticuline grate described in HEC22. The first phase of this effort, titled Computational Analysis of Hydraulic Efficiency of Michigan DOT Cover C, focused on evaluating the hydraulic performance of MDOT’s Cover C grate. Cover C was selected as the initial test candidate because its sinusoidal pattern is representative of other MDOT grates, while it is typically used in high-volume, higher-speed applications. A similar version, Cover CX, is used on interstate highways but does not include transverse bars for bicycle safety. The current second phase of the study expands this work to evaluate MDOT’s Covers J and K. These grates were selected for additional analysis to further assess the hydraulic performance of MDOT drainage structures that are not directly represented by grate configurations in HEC-22. The results of this phase will build on the findings from the Cover C analysis and support improved understanding of the capture efficiency of MDOT’s standard drainage grates. This report is intended to serve as a companion document to the earlier study, Computational Analysis of Hydraulic Efficiency of Michigan DOT Cover C [3]. The present work applies the same overall CFD-based evaluation approach to MDOT Covers J and K and compares the resulting performance trends with those previously identified for Cover C. In particular, both studies assess on-grade interception efficiency, sag-location hydraulic capacity, and the effects of partial obstruction relative to HEC-22-based design estimates.

42 ENGINEERING↗
DOE OSTI2025

Extraction, purification, and reuse of dyes from coloured polyester textiles

The removal of dyes from coloured textile waste represents a sustainable approach to textile recycling, enabling the recovery of valuable chemical, and material resources that would otherwise be discarded. Up to 40% of the greenhouse gas emissions from textiles originate from dye production, making efficient recycling of dyes a major opportunity for curbing emissions and minimizing waste in both textile manufacturing and recycling. Here, in this study, we demonstrate a process for the extraction, purification, and reuse of mixed dyes from polyester textiles using bio-based, non-hazardous solvents selected on the basis of computational predictions for polyester and dye solubilities. Extracted dyes are purified to individual compounds using counter-current chromatography and analysed via liquid chromatography-mass spectrometry. Post-extraction characterization of the extracted dyes and polymer substrate confirms dye colour retention and polyester fabric property preservation. Dye recycling is demonstrated by redyeing colour-free fabrics with the recovered dyes. We further show a potential process configuration for dye removal using a flow-through reactor packed with a textile substrate. The proposed dye removal process produces reusable, recyclable dyes, and dye-free fabrics, thus facilitating textile recycling.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Neural Networks to Find the Optimal Forcing for Offsetting the Anthropogenic Climate Change Effects

Abstract Of great relevance to climate engineering is the systematic relationship between the radiative forcing to the climate system and the response of the system, a relationship often represented by the linear response function (LRF) of the system. However, estimating the LRF often becomes an ill-posed inverse problem due to high-dimensionality and nonunique relationships between the forcing and response. Recent advances in machine learning make it possible to address the ill-posed inverse problem through regularization and sparse system fitting. Here, we develop a convolutional neural network (CNN) for regularized inversion. The CNN is trained using the surface temperature responses from a set of Green’s function perturbation experiments as imagery input data together with data sample densification. The resulting CNN model can infer the forcing pattern responsible for the temperature response from out-of-sample forcing scenarios. This promising proof of concept suggests a possible strategy for estimating the optimal forcing to negate certain undesirable effects of climate change. The limited success of this effort underscores the challenges of solving an inverse problem for a climate system with inherent nonlinearity. Significance Statement Predicting the climate response for a given climate forcing is a direct problem, while inferring the forcing for a given desired climate response is often an inverse, ill-posed, problem, posing a new challenge to the climate community. This study makes the first attempt to infer the radiative forcing for a given target pattern of global surface temperature response using a deep learning approach. The resulting deeply trained convolutional neural network inversion model shows promise in capturing the forcing pattern corresponding to a given surface temperature response, with a significant implication on the design of an optimal solar radiation management strategy for curbing global warming. This study also highlights the technical challenges that future research should prioritize in seeking feasible solutions to the inverse climate problem.

Ren, Huiying↗