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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Constraining effects of aerosol-cloud interaction by accounting for coupling between cloud and land surface

Aerosol-cloud interactions (ACIs) are vital for regulating Earth’s climate by influencing energy and water cycles. Yet, effects of ACI bear large uncertainties, evidenced by systematic discrepancies between observed and modeled estimates. This study quantifies a major bias in ACI determinations, stemming from conventional surface or space measurements that fail to capture aerosol at the cloud level unless the cloud is coupled with land surface. We introduce an advanced approach to determine radiative forcing of ACI by accounting for cloud-surface coupling. By integrating field observations, satellite data, and model simulations, this approach reveals a drastic alteration in aerosol vertical transport and ACI effects caused by cloud coupling. In coupled regimes, aerosols enhance cloud droplet number concentration across the boundary layer more homogeneously than in decoupled conditions, under which aerosols from the free atmosphere predominantly affect cloud properties, leading to marked cooling effects. Our findings spotlight cloud-surface coupling as a key factor for ACI quantification, hinting at potential underassessments in traditional estimates.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Analysis of aerosol cloud interactions with a consistent signal of meteorology and other influencing parameters

Quantifying the impact of aerosols on cloud micro/macro physical properties and estimating the signature of Aerosol Cloud Interactions (ACI) is one of the challenging tasks in atmospheric sciences. The Moderate Resolution Imaging Spectroradiometer and the European Centre for Medium-Range Weather Forecasts ERA-5 reanalysis data are employed to systematically study the ACI over the monsoon region in Pakistan. Based on the monsoon occurrence and rainfall intensity, the whole region is divided into three sub-regions labeled as highly intensive (R1), moderately intensive (R2) and weak (R3) monsoon region. The results indicate that the monthly mean Aerosol Optical Depth (AOD) peaks in the summer monsoon months (Jun, Jul, Aug, Sep). Here, the well-known Twomey effect whereby the Cloud Droplet Radius (CDR) decreases with increasing AOD holds only over R3; the opposite effects (Anti-Twomey effect) are found over R1 and R2, all passing the test of statistical significance (p<0.05). The multi-year AOD is found to be positively correlated with Cloud Liquid Water Path (CLWP) and Cloud Optical Depth (COD) over R1 and R2, suggesting that thicker clouds containing more water droplets are formed in polluted atmosphere. Over R3, decreases in CLWP and COD are found with increasing AOD only when AOD is less than~0.325. The analysis of ACI over R1 and R2 during the winter months shows similar but stronger responses of CDR, CLWP and COD to the variation in AOD. The weaker responses during the summer monsoon season may attributed to the occurrence of high level cloud and unstable atmospheric condition. Further investigation of the influences of Relative Humidity and pressure vertical velocity on the CDR-AOD relationships shows that although the magnitude of the CDR-AOD correlations change with meteorological conditions, the sign of correlations remain unchanged with meteorological conditions.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Droplet collection efficiencies inferred from satellite retrievals constrain effective radiative forcing of aerosol–cloud interactions

Abstract. Process-oriented observational constraints for the anthropogenic effective radiative forcing due to aerosol–cloud interactions (ERFaci) are highly desirable because the uncertainty associated with ERFaci poses a significant challenge to climate prediction. The contoured frequency by optical depth diagram (CFODD) analysis supports the evaluation of model representation of cloud liquid-to-rain conversion processes because the slope of a CFODD, generated from joint MODerate Resolution Imaging Spectroradiometer (MODIS)-CloudSat cloud retrievals, provides an estimate of cloud droplet collection efficiency in single-layer warm liquid clouds. Here, we present an updated CFODD analysis as an observational constraint on the ERFaci due to warm rain processes and apply it to the U.S. Department of Energy's Energy Exascale Earth System Model version 2 (E3SMv2). A series of sensitivity experiments shows that E3SMv2 droplet collection efficiencies and ERFaci are highly sensitive to autoconversion, i.e., the rate of mass transfer from cloud liquid to rain, yielding a strong correlation between the CFODD slope and the shortwave component of ERFaci (ERFaciSW; Pearson's R=-0.91). E3SMv2's CFODD slope (0.20 ± 0.04) is in agreement with observations (0.20 ± 0.03). The strong sensitivity of ERFaciSW to the CFODD slope provides a useful constraint on highly uncertain warm rain processes, whereby ERFaciSW, constrained by MODIS-CloudSat, is estimated by calculating the intercept of the linear association between the ERFaciSW and the CFODD slopes, using the MODIS-CloudSat CFODD slope as a reference.

Beall, Charlotte M. (ORCID:0000000311370835)↗
DOE OSTI2022

Environmental effects on aerosol–cloud interaction in non-precipitating marine boundary layer (MBL) clouds over the eastern North Atlantic

Abstract. Over the eastern North Atlantic (ENA) ocean, a total of 20 non-precipitating single-layer marine boundary layer (MBL) stratus and stratocumulus cloud cases are selected to investigate the impacts of the environmental variables on the aerosol–cloud interaction (ACIr) using the ground-based measurements from the Department of Energy Atmospheric Radiation Measurement (ARM) facility at the ENA site during 2016–2018. The ACIr represents the relative change in cloud droplet effective radius re with respect to the relative change in cloud condensation nuclei (CCN) number concentration at 0.2 % supersaturation (NCCN,0.2 %) in the stratified water vapor environment. The ACIr values vary from −0.01 to 0.22 with increasing sub-cloud boundary layer precipitable water vapor (PWVBL) conditions, indicating that re is more sensitive to the CCN loading under sufficient water vapor supply, owing to the combined effect of enhanced condensational growth and coalescence processes associated with higher Nc and PWVBL. The principal component analysis shows that the most pronounced pattern during the selected cases is the co-variations in the MBL conditions characterized by the vertical component of turbulence kinetic energy (TKEw), the decoupling index (Di), and PWVBL. The environmental effects on ACIr emerge after the data are stratified into different TKEw regimes. The ACIr values, under both lower and higher PWVBL conditions, more than double from the low-TKEw to high-TKEw regime. This can be explained by the fact that stronger boundary layer turbulence maintains a well-mixed MBL, strengthening the connection between cloud microphysical properties and the below-cloud CCN and moisture sources. With sufficient water vapor and low CCN loading, the active coalescence process broadens the cloud droplet size spectra and consequently results in an enlargement of re. The enhanced activation of CCN and the cloud droplet condensational growth induced by the higher below-cloud CCN loading can effectively decrease re, which jointly presents as the increased ACIr. This study examines the importance of environmental effects on the ACIr assessments and provides observational constraints to future model evaluations of aerosol–cloud interactions.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2009

Aerosol-Cloud Interaction Determined by Both in Situ and Satellite Data Over a Northern High-Latitude Site

The first aerosol indirect effect over a clean, northern high-latitude site was investigated by determining the aerosol cloud interaction (ACI) using three different approaches; ground-based in situ measurements, combined ground-based in situ measurements 5 and satellite retrievals and using only satellite retrievals. The obtained values of ACI were highest for in situ ground-based data, clearly lower for combined ground-based and satellite data, and lowest for data relying solely on satellite retrievals. One of the key findings of this study was the high sensitivity of ACI to the definition of the aerosol burden. We showed that at least a part of the variability in ACI can be explained by 10 how different investigators have related dierent cloud properties to "aerosol burden".

Lihavainen, H.↗
DOE OSTI2026

The role of local shipping emissions in aerosol-cloud interactions in the central Arctic

Arctic shipping is projected to increase as sea ice retreats, yet the impact of modern low-sulfur ship emissions on Arctic clouds and radiation remain poorly constrained. We use year-long in situ observations from the MOSAiC expedition to characterize ship-aerosol-cloud interactions for an icebreaker burning ultra-low sulfur fuel (0.1% mass per mass). Exhaust plumes were found to be strongly enriched in Aitken-mode particles, organic aerosol, and black carbon, but showed no detectable enhancement in particulate sulfate. Despite reduced hygroscopicity relative to ambient aerosols, ship emissions substantially increased local cloud condensation nuclei concentrations. A droplet activation parameterization was applied to quantify responses in cloud droplet number concentration ( N d ) to ship-induced perturbations in low-level Arctic clouds. In winter, abundant background accumulation-mode particles from Arctic haze supplied nearly all cloud droplets, while additional particles from ship emissions had little impact on N d . In contrast, during summer months, when unperturbed background aerosol concentrations are low, ship emissions nearly doubled N d compared to average background conditions and increased N d by a factor of five compared to very clean background conditions (25th percentile of background aerosol number concentrations). Longwave radiative transfer simulations for typical conditions of summer Arctic low-level clouds/fog suggest that these ship-induced increases in N d locally (i.e. <100 km downwind) lead to enhanced net surface longwave fluxes and consequent warming, primarily for optically thin clouds (liquid water path (LWP) ⩽ 30 g·m −2 ). For LWP = 10 g · m −2 , ship emissions lead to an increase of 1 W · m −2 in cloud longwave forcing at the surface compared to average unperturbed conditions (+7% relative increase), and up to 4 W · m −2 when compared to very clean background conditions (+22% relative increase). Even ultra-low sulfur fuel emissions can therefore locally and episodically modify Arctic cloud microphysics and radiative properties, especially during summer, implying that future increases in Arctic shipping could have non-negligible regional climate impacts.

Arctic↗
NASA NTRS2016

Improving Our Fundamental Understanding of the Role of Aerosol Cloud Interactions in the Climate System

The effect of an increase in atmospheric aerosol concentrations on the distribution and radiative properties of Earth's clouds is the most uncertain component of the overall global radiative forcing from preindustrial time. General circulation models (GCMs) are the tool for predicting future climate, but the treatment of aerosols, clouds, and aerosol−cloud radiative effects carries large uncertainties that directly affect GCM predictions, such as climate sensitivity. Predictions are hampered by the large range of scales of interaction between various components that need to be captured. Observation systems (remote sensing, in situ) are increasingly being used to constrain predictions, but significant challenges exist, to some extent because of the large range of scales and the fact that the various measuring systems tend to address different scales. Fine-scale models represent clouds, aerosols, and aerosol−cloud interactions with high fidelity but do not include interactions with the larger scale and are therefore limited from a climatic point of view. We suggest strategies for improving estimates of aerosol−cloud relationships in climate models, for new remote sensing and in situ measurements, and for quantifying and reducing model uncertainty.

general circulation models↗
DOE OSTI2021

Local limits of detection for anthropogenic aerosol-cloud interactions

Ship tracks are quasi-linear cloud patterns produced from the interaction of ship emissions with low boundary layer clouds. They are visible throughout the diurnal cycle in satellite images from space-borne assets like the Advanced Baseline Imagers (ABI) aboard the National Oceanic and Atmospheric Administration Geostationary Operational Environmental Satellites (GOES-R). However, complex atmospheric dynamics often make it difficult to identify and characterize the formation and evolution of tracks. Ship tracks have the potential to increase a cloud's albedo and reduce the impact of global warming. Thus, it is important to study these patterns to better understand the complex atmospheric interactions between aerosols and clouds to improve our climate models, and examine the efficacy of climate interventions, such as marine cloud brightening. Over the course of this 3-year project, we have developed novel data-driven techniques that advance our ability to assess the effects of ship emissions on marine environments and the risks of future marine cloud brightening efforts. The three main innovative technical contributions we will document here are a method to track aerosol injections using optical flow, a stochastic simulation model for track formations and an automated detection algorithm for efficient identification of ship tracks in large datasets.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Impact of Turbulence Representation on the Relationship Between Cloud Feedback and Aerosol‐Cloud Interaction in an E3SMv2 Perturbed Parameter Ensemble

Recent studies reveal an anti‐correlation between global cloud feedback (CF) and effective radiative forcing due to aerosol‐cloud interaction (ERFaci) in Earth system models, but the physical mechanisms underlying it remain uncertain. Here we investigate how different turbulence representations contribute to this relationship over the global ocean using an ensemble of Energy Exascale Earth System Model version 2 simulations with perturbed turbulence parameters. The anti‐correlation appears only in the tropical ascent regime. In the Northern Hemisphere midlatitude and high latitude regimes, there is no significant correlation, and in the tropical marine low cloud and Southern Ocean regimes, the correlation is positive. These opposite correlations are primarily driven by opposing CF responses to perturbed parameters. We find that the mean‐state turbulent mixing strength affects both CF and ERFaci, enabling strong correlations in certain regimes. This study highlights the complex linkages between CF and ERFaci through turbulent processes across diverse cloud regimes.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

The CLoud–Aerosol–Radiation Interaction and Forcing: Year 2017 (CLARIFY-2017) measurement campaign

The representations of clouds, aerosols, and cloud–aerosol–radiation impacts remain some of the largest uncertainties in climate change, limiting our ability to accurately reconstruct past climate and predict future climate. The south-east Atlantic is a region where high atmospheric aerosol loadings and semi-permanent stratocumulus clouds are co-located, providing an optimum region for studying the full range of aerosol–radiation and aerosol–cloud interactions and their perturbations of the Earth's radiation budget. While satellite measurements have provided some useful insights into aerosol–radiation and aerosol–cloud interactions over the region, these observations do not have the spatial and temporal resolution, nor the required level of precision to allow for a process-level assessment. Detailed measurements from high spatial and temporal resolution airborne atmospheric measurements in the region are very sparse, limiting their use in assessing the performance of aerosol modelling in numerical weather prediction and climate models. CLARIFY-2017 was a major consortium programme consisting of five principal UK universities with project partners from the UK Met Office and European- and USA-based universities and research centres involved in the complementary ORACLES, LASIC, and AEROCLO-sA projects. The aims of CLARIFY-2017 were fourfold: (1) to improve the representation and reduce uncertainty in model estimates of the direct, semi-direct, and indirect radiative effect of absorbing biomass burning aerosols; (2) to improve our knowledge and representation of the processes determining stratocumulus cloud microphysical and radiative properties and their transition to cumulus regimes; (3) to challenge, validate, and improve satellite retrievals of cloud and aerosol properties and their radiative impacts; (4) to improve the impacts of aerosols in weather and climate numerical models. This paper describes the modelling and measurement strategies central to the CLARIFY-2017 deployment of the FAAM BAe146 instrumented aircraft campaign, summarizes the flight objectives and flight patterns, and highlights some key results from our initial analyses.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2010

Analyzing the Effect of Intraseasonal Meteorological Variability and Land Cover on Aerosol-Cloud Interactions During the Amazonian Biomass Burning Season

High resolution aerosol, cloud, water vapor, and atmospheric profile data from the Moderate Resolution Imaging Spectroradiometer (MODIS) are utilized to examine the impact of aerosols on clouds during the Amazonian biomass burning season in Rondnia, Brazil. It is found that increasing background column water vapor (CWV) throughout this transition season between the Amazon dry and wet seasons exerts a strong effect on cloud properties. As a result, aerosol-cloud correlations should be stratified by column water vapor to achieve a more accurate assessment of the effect of aerosols on clouds. Previous studies ignored the systematic changes to meteorological factors during the transition season, leading to possible misinterpretation of their results. Cloud fraction is shown generally to increase with aerosol optical depth (AOD) for both low and high values of column water vapor, whereas the relationship between cloud optical depth (COD) and AOD exhibits a different relationship. COD increases with AOD until AOD approx. 0.25 due to the first indirect (microphysical) effect. At higher values of AOD, COD is found to decrease with increasing AOD, which may be due to: (1) the inhibition of cloud development by absorbing aerosols (radiative effect) and/or (2) a retrieval artifact in which the measured reflectance in the visible is less than expected from a cloud top either from the darkening of clouds through the addition of carbonaceous biomass burning aerosols or subpixel dark surface contamination in the measured cloud reflectance. If (1) is a contributing mechanism, as we suspect, then a linear relationship between the indirect effect and increasing AOD, assumed in a majority of GCMs, is inaccurate since these models do not include treatment of aerosol absorption in and around clouds. The effect of aerosols on both column water vapor and clouds over varying land surface types is also analyzed. The study finds that the difference in column water vapor between forest and pasture is not correlated with aerosol loading, supporting the assumption that temporal variation of column water vapor is primarily a function of the larger-scale meteorology. However, a difference in the response of cloud fraction to increasing AOD is observed between forest and pasture. This suggests that dissimilarities between other meteorological factors, such as atmospheric stability, are likely to have an impact on aerosol-cloud correlations between different land-cover types.

TenHoeve, J. E.↗
DOE OSTI2021

Facilitating better and faster simulations of aerosol-cloud interactions in Earth system models

Focal Area(s): 1. 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 a hierarchy of models. 2. Insight gleaned from complex data (both observed and simulated) using AI, big data analytics, and other advanced methods, including explainable AI and physics- or knowledge-guided AI. Science Challenge: One major challenge that Earth system models (ESMs) face in providing credible prediction of the Earth system and its water cycle characteristics (e.g., mean state, variability, and extreme events) is to accurately simulate aerosol-cloud interactions (ACI). The physical, chemical, and dynamical processes affecting ACI are extremely complex and they range from nanoscale to planetary scale. In each model development cycle, scientists spend significant efforts investigating model deficiencies and uncertainties associated with aerosols (e.g., emissions, chemical processes, aerosol microphysics, and transport) and clouds (e.g., macrophysics, microphysics, turbulence, and large-scale circulation) in order to develop improved treatments. However, despite decades of active research, ACI is still a major source of uncertainty in climate projections, even though great progress has been made. Specific scientific challenges include: (i) Parameterizations are developed based on limited data; (ii) The complexity of a parameterization required for accurate predictions is not understood; (iii) Incomplete and unknown physics leads to errors in the fully coupled Earth system; and (iv) Complex physics is computationally too expensive to employ in ESMs.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Interconnection of Aerosol‐Cloud Interactions and Cloud Feedback Through Warm Rain Process

Recent research has revealed a correlation within the Coupled Model Intercomparison Project Phase 6 (CMIP6) simulations: models exhibiting more pronounced warming due to positive cloud feedback simultaneously show enhanced cooling from aerosol‐cloud interactions (ACI). However, the interplay between ACI and cloud feedback is not well understood in these models. Our study addresses this gap by modifying the autoconversion rate in two Earth system models (ESMs), elucidating how ACI could connect with cloud feedback through the warm rain process. We find that higher autoconversion rates, which are associated with stronger ACI, suppress the increase in cloud liquid water path (LWP) and cloud optical depth with warming by enhancing the precipitation efficiency over the extratropical regions, leading to a larger positive cloud feedback. This study offers new insights into the compensatory mechanism between ACI and cloud feedback through the warm rain process and highlights the importance of constraining the autoconversion parameterization in models.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2008

Ground-based Network and Supersite Measurements for Studying Aerosol Properties and Aerosol-Cloud Interactions

From radiometric principles, it is expected that the retrieved properties of extensive aerosols and clouds from reflected/emitted measurements by satellite (and/or aircraft) should be consistent with those retrieved from transmitted/emitted radiance observed at the surface. Although space-borne remote sensing observations contain large spatial domain, they are often plagued by contamination of surface signatures. Thus, ground-based in-situ and remote-sensing measurements, where signals come directly from atmospheric constituents, the sun, and the Earth-atmosphere interactions, provide additional information content for comparisons that confirm quantitatively the usefulness of the integrated surface, aircraft, and satellite datasets. The development and deployment of AERONET (AErosol RObotic NETwork) sunphotometer network and SMART-COMMIT (Surface-sensing Measurements for Atmospheric Radiative Transfer - Chemical, Optical & Microphysical Measurements of In-situ Troposphere) mobile supersite are aimed for the optimal utilization of collocated ground-based observations as constraints to yield higher fidelity satellite retrievals and to determine any sampling bias due to target conditions. To characterize the regional natural and anthropogenic aerosols, AERONET is an internationally federated network of unique sunphotometry that contains more than 250 permanent sites worldwide. Since 1993, there are more than 480 million aerosol optical depth observations and about 15 sites have continuous records longer than 10 years for annual/seasonal trend analyses. To quantify the energetics of the surface-atmosphere system and the atmospheric processes, SMART-COMMIT instrument into three categories: flux radiometer, radiance sensor and in-situ probe. Through participation in many satellite remote-sensing/retrieval and validation projects over eight years, SMART-COMMIT have gradually refine( and been proven vital for field deployment. In this paper, we will demonstrate the capability of AERONET SMART-COMMIT in current Asian Monsoon Year-2008 campaigns that are designed and being executed to study the compelling variability in temporal scale of both anthropogenic and natural aerosols (e.g., airborne dust, smoke, mega-city pollutant). Feedback mechanisms between aerosol radiative effects and monsoon dynamics have been recently proposed, however there is a lack of consensus on whether aerosol forcing would be more likely to enhance or reduce the strength of the monsoon circulation. We envision robust approaches which well-collocated ground-based measurements and space-borne observations will greatly advance our understanding of absorbing aerosols (e.g., "Global Dimming" vs. "Elevated Heat-Pump" effects) on aerosol cloud water cycle interactions.

Tsay, Si-Chee↗
NASA NTRS2019

Strong Dependence of Atmospheric Feedbacks on Mixed-Phase Microphysics and Aerosol-Cloud Interactions in HadGEM3

We analyze the atmospheric processes that explain the large changes in radiative feed-backs between the two latest climate configurations of the Hadley Centre Global Environmental model. We use a large set of atmosphere-only climate-change simulations (amip and amip-p4K) to separate the contributions to the differences in feedback parameter from all the atmospheric model developments between the two latest model configurations. We show that the differences are mostly driven by changes in the shortwave cloud radiative feedback in the midlatitudes, mainly over the Southern Ocean. Two new schemes explain most of the differences: the introduction of a new aerosol scheme; and the development of a new mixed-phase cloud scheme. Both schemes reduce the strength of the pre-existing shortwave negative cloud feedback in the midlatitudes. The new aerosol scheme dampens a strong aerosol-cloud interaction, and it also suppresses a negative clear-sky shortwave feedback. The mixed-phase scheme increases the amount of cloud liquid water path (LWP) in the present-day, thereby reducing the radiative effciency of the increase of LWP in the warmer climate. It also enhances a strong, pre-existing, positive cloud fraction feedback. We assess the realism of the changes by comparing present-day simulations against observations, and discuss avenues that could help constrain the relevant processes.

HadGEM3↗
DOE OSTI2022

Assessing effective radiative forcing from aerosol–cloud interactions over the global ocean

How clouds respond to anthropogenic sulfate aerosols is one of the largest sources of uncertainty in the radiative forcing of climate over the industrial era. This uncertainty limits our ability to predict equilibrium climate sensitivity (ECS)—the equilibrium global warming following a doubling of atmospheric CO 2 . Here, we use satellite observations to quantify relationships between sulfate aerosols and low-level clouds while carefully controlling for meteorology. We then combine the relationships with estimates of the change in sulfate concentration since about 1850 to constrain the associated radiative forcing. We estimate that the cloud-mediated radiative forcing from anthropogenic sulfate aerosols is − 1.11 ± 0.43 W m −2 over the global ocean (95% confidence). This constraint implies that ECS is likely between 2.9 and 4.5 K (66% confidence). Our results indicate that aerosol forcing is less uncertain and ECS is probably larger than the ranges proposed by recent climate assessments.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Toward data assimilation of ship-induced aerosol–cloud interactions

Satellite imagery can detect temporary cloud trails or ship tracks formed from aerosols emitted from large ships traversing our oceans, a phenomenon that global climate models cannot directly reproduce. Ship tracks are observable examples of marine cloud brightening, a potential solar climate intervention that shows promise in helping combat climate change. In this paper, we demonstrate a simulation-based approach in learning the behavior of ship tracks based upon a novel stochastic emulation mechanism. Our method uses wind fields to determine the movement of aerosol–cloud tracks and uses a stochastic partial differential equation (SPDE) to model their persistence behavior. This SPDE incorporates both a drift and diffusion term which describes the movement of aerosol particles via wind and their diffusivity through the atmosphere, respectively. We first present our proposed approach with examples using simulated wind fields and ship paths. We then successfully demonstrate our tool by applying the approximate Bayesian computation method-sequential Monte Carlo for data assimilation.

54 ENVIRONMENTAL SCIENCES↗