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This white paper addresses DOE AI4ESP focus areas #1 and #3. We propose to leverage advances in machine learning and artificial intelligence to create a new unsupervised cloud classification framework that will produce new datasets and cloud process understanding to reduce biases in Earth system models.
Arctic aerosols play a significant role in the aerosol-radiation and aerosol-cloud interactions, but ground-based measurements are insufficient to explain the interaction of aerosols and clouds in a vertically stratified Arctic atmosphere. This study shows the vertical variability of aerosol particle composition via tethered balloon system at Oliktok Point, Alaska, in August 2019, at different cloud layers for two case studies (background aerosol condition and polluted condition). Multi-modal micro-spectroscopy analysis of samples during the background case reveals a broadening of chemically specific size distribution above cloud top with a high abundance of sulfate and core-shell morphology, suggesting possible cloud processing of aerosols. The pollution case also indicates a broadening of size distribution at the upper cloud layer with the dominance of carbonaceous aerosol, which suggests the potential of carbonaceous aerosols for Arctic cloud formation. Here this study provides insights into the vertical profile of Arctic aerosols on cloud formation.
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Globally, on average, the release rate of aerosols from clouds is estimated to be about 6,000 Tg/yr and an aerosol particle is estimated to experience about three cloud cycles. Cloud processing of aerosol produces aerosols that have dramatically different physicochemical properties compared to their original form. Cloud processing may transform particles to efficient cloud condensation nuclei (CCN) or ice nucleating particles (INP) that can further participate in cloud formation. We investigated cloud processing of aerosol during the U.S. Department of Energy (DOE)’s Atmospheric Radiation Measurement (ARM) Surface Atmosphere Integrated Field Laboratory (SAIL) field campaign using multi-modal offline analysis techniques available at DOE’s Environmental Molecular Sciences Laboratory (EMSL). The main scientific aim of this project was to understand the processes that transform aerosols (chemically, and physically), and influence aerosol-cloud interactions. Aerosol particles undergo significant modifications due to warm (cloud droplets) and cold cloud (ice crystals) processing. Cloud processing of aerosol has important effects on the atmospheric aerosol number and mass concentration, size distribution, phase separation, and chemical composition.
Soot particles form during combustion of carbonaceous materials and impact climate and air quality. When freshly emitted, they are typically fractal-like aggregates. After atmospheric aging, they can act as cloud condensation nuclei, and water condensation or evaporation restructure them to more compact aggregates, affecting their optical, aerodynamic, and surface properties. Here we survey the morphology of ambient soot particles from various locations and different environmental and aging conditions. We used electron microscopy and show extensive soot compaction after cloud processing. We further performed laboratory experiments to simulate atmospheric cloud processing under controlled conditions. We find that soot particles sampled after evaporating the cloud droplets, are significantly more compact than freshly emitted and interstitial soot, confirming that cloud processing, not just exposure to high humidity, compacts soot. Our findings have implications for how the radiative, surface, and aerodynamic properties, and the fate of soot particles are represented in numerical models.
Low clouds over the ocean are a critical component of our planet’s energy budget because they emit almost as much energy as the surface while being much more reflective than the ocean, resulting in a strong net cooling effect. Despite their importance, low marine clouds remain a persistent source of uncertainty in future climate projections. This project explored how the dynamics, thermodynamics and spatial organization of low clouds is represented in a particular physical simplification, or parameterization, of small-scale air motions and cloud processes commonly employed in global atmospheric models used for short-term weather and longer-term earth system prediction. The overall goal was to develop long-term observational products to constrain numerical model representations of turbulence and cloud processes using observations from the US Department of Energy’s (DOE) Atmospheric Radiation Measurement (ARM) program’s Eastern North Atlantic (ENA) site. These constraints were then used to demonstrate the type of information that can be gained from confronting simulations with the observations and we assessed the performance of a parameterization in simulating periods of low clouds at ENA. Finally, we used detailed computational fluid dynamics simulations of turbulence and cloud properties to evaluate general physical assumptions embedded in simplified representations of clouds and turbulence for global models of the atmosphere.
In preparation for the NISAR launch and data collection in 2024, the NISAR Project Science Team is building workflows for each Science Team discipline (Ecosystems, Cryosphere, and Solid Earth). This abstract focuses on the Ecosystem disciplines and the development of on-demand cloud-processing workflows for wetlands inundation, forest biomass, agricultural active crop area, and forest disturbance. The workflow simulates NISAR data using UAVSAR or ALOS-2 Single Look Complex data, which are processed to Level 2 geocoded polarimetric covariance matrix products using InSAR Scientific Computing Environment 3.0 software and to Level 3 science products using the Algorithm Theoretical Basis Documents. In this presentation, we describe these workflows and efforts to improve efficiency and data accessibility by using a cloud processing system. We present preliminary sample products from each Ecosystem discipline: inundation, forest biomass, crop area, and forest disturbance.
We measured stable and reactive trace gases with an airborne Fourier transform infrared spectrometer (AFTIR) on the University of Washington Convair-580 research aircraft in August/September 2000 during the SAFARI 2000 dry season campaign in Southern Africa. The measurements included vertical profiles of C02, CO, H20, and CH4 up to 5.5 km on six occasions above instrumented ground sites and below the TERRA satellite and ER-2 high-flying research aircraft. We also measured the trace gas emissions from 10 African savanna fires. Five of these fires featured extensive ground-based fuel characterization, and two were in the humid savanna ecosystem that accounts for most African biomass burning. The major constituents we detected in nascent CH3OOH, HCHO, CH30H, HCN, NH3, HCOOH, and C2H2. These are the first quantitative measurements of the initial emissions of oxygenated volatile organic compounds (OVOC), NH3, and HCN from African savanna fires. On average, we measured 5.3 g/kg of OVOC and 3.6 g/kg of hydrocarbons (including CH4) in the initial emissions from the fires. Thus, the OVOC will have profound, largely unexplored effects on tropical tropospheric chemistry. The HCN emission factor was only weakly dependent on fire type; the average value (0.53 g/kg) is about 20 times that of a previous recommendation. HCN may be useful as a tracer for savanna fires. Delta O3/Delta CO and Delta CH3COO/Delta CO increased to as much as 9% in <1 h of photochemical processing downwind of fires. Direct measurements showed that cloud processing of smoke greatly reduced CH30H, NH3, CH3COOH, SO2, and NO2 levels, but significantly increased HCHO and NO.
The BiLateral Operational Storm-Scale Observation and Modeling (BLOSSOM) project was initiated to establish a long-term supersite to improve understanding of cloud physical states and processes as well as to support satellite and climate model programs over the WFF site via a bilateral approach of storm-scale observations and process modeling. This study highlights a noble systematic validation framework of the BLOSSOM ensemble cloud-process simulations through mixed-phase, light-rain, and deep-convective precipitation cases. The framework consists of creating a domain-shifted ensemble of large-scale forcing datasets, and configuring and performing cloud-process simulations with three different bulk microphysics schemes. Validation uses NASA S-band dual-POLarimetric radar (NPOL) observations in the form of statistical composites and skill scores via a polarimetric radar simulator and newly developed CfRad Data tool (CfRAD). While the simulations capture the overall structures of the reflectivity composites, polarimetric signals are still poorly simulated, mainly due to a lack of representation of ice microphysics diversity in shapes, orientation distributions, and their complex mixtures. Despite the limitation, this new ensemble-based validation framework demonstrates that 1) no particular forcing or microphysics scheme outperforms the rest and 2) the skill scores of coarse- and fine-resolution ensemble simulations with different domain-shifted forcing and microphysics schemes are highly correlated with each other with no clear improvement. On the other hand, this suggests that coarse-resolution ensemble simulations are relevant for selecting the best meteorological forcing and microphysics scheme before conducting computationally demanding large eddy simulations (LESs) in support of aircraft and satellite instrument development as well as cloud-precipitation-convection parameterizations.
Abstract Southern Africa produces a third of global biomass burning emissions, which have a long atmospheric lifetime and influence regional radiation balance and climate. Here, we use airmass trajectories to link different aircraft observations to investigate the evolution of biomass-burning aerosols during their westward transport from Southern Africa over the south-eastern Atlantic, where a semi-permanent stratocumulus cloud deck is located. Our results show secondary organic aerosol formation during the initial 3 days of transport, followed by decreases in organic aerosol via photolysis before reaching equilibrium. Aerosol absorption wavelength dependency decreases with ageing, due to an increase in particle size and photochemical bleaching of brown carbon. Cloud processing, including aqueous-phase reaction and scavenging, contributes to the oxidation of organic aerosols, while it strongly reduces large diameter particles and single-scattering albedo of biomass burning aerosols. Together, these processes resulted in a marine boundary layer with fewer yet more oxidized and absorbing aerosols.
Dimethyl sulfide (DMS) is the major sulfur species emitted from the ocean. The gas-phase oxidation of DMS by hydroxyl radicals proceeds through the stable, soluble intermediate hydroperoxymethyl thioformate (HPMTF), eventually forming carbonyl sulfide (OCS) and sulfur dioxide (SO 2 ). Recent work has shown that HPMTF is efficiently lost to marine boundary layer (MBL) clouds, thus arresting OCS and SO 2 production and their contributions to new-particle formation and growth events. To date, no long-term field studies exist to assess the extent to which frequent cloud processing impacts the fate of HPMTF. Here, we present 6 weeks of measurements of the cloud fraction and the marine sulfur species methanethiol, DMS, and HPMTF made at the Atmospheric Radiation Measurement (ARM) research facility on Graciosa Island, Azores, Portugal. Using an observationally constrained chemical box model, we determine that cloud loss is the dominant sink of HPMTF in this region of the MBL during the study, accounting for 79 %–91 % of HPMTF loss on average. When accounting for HPMTF uptake to clouds, we calculate campaign average reductions in DMS-derived MBL SO 2 and OCS of 52 %–60 % and 80 %–92 % for the study period. Using yearly measurements of the site- and satellite-measured 3D cloud fraction and DMS climatology, we infer that HPMTF cloud loss is the dominant sink of HPMTF in the eastern North Atlantic during all seasons and occurs on timescales faster than what is prescribed in global chemical transport models. Accurately resolving this rapid loss of HPMTF to clouds has important implications for constraining drivers of MBL new-particle formation.
Methods for processing a 3D point cloud of a building into polygons using an electronic computing device are presented, the methods including: causing the electronic computing device to receive the 3D point cloud; causing the electronic computing device to segment the 3D point cloud into a number of facades; and causing the electronic computing device to generate a number of polygons representing the number of facades. In some embodiments, the causing the electronic computing device to segment the 3D point cloud into a number of facades includes: performing voxel downsampling operation on the 3D point cloud; calculating a point normal for every point in the voxel downsampled 3D point cloud; and performing region growing to find each of the number of facades.
Abstract In this study, we find significant sensitivity to the choice of time step for the Energy Exascale Earth System Model's atmospheric component, leading to large decreases in the magnitude of cloud forcing when the time step is reduced to 10 s. Reducing the time step size for the microphysics increases precipitation, leading to a drying of the atmosphere and an increase in surface evaporation. This effect is amplified when the microphysics is substepped together with other cloud physics processes. Coupling the model's dynamics and physics more frequently reduces cloud fraction at lower altitudes, while producing more cloud liquid at higher altitudes. Reducing the deep convection time step also reduces low cloud mass and cloud fraction. Together, these results suggest that cloud physics in a global circulation model can depend strongly on time step and, in particular, on the frequency with which cloud‐related processes are coupled with each other and with the model dynamics.
A numerical cumulus ensemble model is presented, which covers a large area, and resolves individual cumulus clouds. The clouds produced by the model simulation are illustrated. Scatter plots of cloud amount vs relative humidity are examined. Plans for a cumulus ensemble model study on the effects of boundary layer processes on cloud formation are discussed.
Cloud microphysics is inevitably affected by the smoke particle (CCN, cloud condensation nuclei) size distributions below the clouds. Therefore, size distributions parameterized as spectral bin microphysics are needed to explicitly study the effects of atmospheric aerosol concentration on cloud development, rainfall production, and rainfall rates for convective clouds. Recently, a detailed spectral-bin microphysical scheme was implemented into the Goddard Cumulus Ensemble (GCE) model. The formulation for the explicit spectral bin microphysical processes is based on solving stochastic kinetic equations for the size distribution functions of water droplets (i.e., cloud droplets and raindrops), and several types of ice particles [i.e. pristine ice crystals (columnar and plate-like), snow (dendrites and aggregates), graupel and frozen drops/hail]. Each type is described by a special size distribution function containing many categories (i.e., 33 bins). Atmospheric aerosols are also described using number density size-distribution functions. The model is tested by studying the evolution of deep cloud systems in the west Pacific warm pool region, the sub-tropics (Florida) and midlatitudes using identical thermodynamic conditions but with different concentrations of CCN: a low "clean" concentration and a high "dirty" concentration. Results indicate that the low CCN concentration case produces rainfall at the surface sooner than the high CeN case but has less cloud water mass aloft. Because the spectral-bin model explicitly calculates and allows for the examination of both the mass and number concentration of species in each size category, a detailed analysis of the instantaneous size spectrum can be obtained for these cases. It is shown that since the low (CN case produces fewer droplets, larger sizes develop due to greater condensational and collection growth, leading to a broader size spectrum in comparison to the high CCN case. Sensitivity tests were performed to identify the impact of ice processes, radiation and large-scale influence on cloud-aerosol interactive processes, especially regarding surface rainfall amounts and characteristics (i.e., heavy or convective versus light or stratiform types). In addition, an inert tracer was included to follow the vertical redistribution of aerosols by cloud processes. We will also give a brief review from observational evidence on the role of aerosol on precipitation processes.
Atmospheric formic acid is severely underpredicted by models. A recent study proposed that this discrepancy can be resolved by abundant formic acid production from the reaction ( 1 ) between hydroxyl radical and methanediol derived from in-cloud formaldehyde processing and provided a chamber-experiment-derived rate constant, k 1 = 7.5 × 10 −12 cm 3 s −1 . High-level accuracy coupled cluster calculations in combination with E,J -resolved two-dimensional master equation analyses yield k 1 = (2.4 ± 0.5) × 10 −12 cm 3 s −1 for relevant atmospheric conditions ( T = 260–310 K and P = 0–1 atm). We attribute this significant discrepancy to HCOOH formation from other molecules in the chamber experiments. More importantly, we show that reversible aqueous processes result indirectly in the equilibration on a 10 min. time scale of the gas-phase reaction HCHO + H 2 O ⇌ HOCH 2 OH (2) with a HOCH 2 OH to HCHO ratio of only ca . 2%. Although HOCH 2 OH outgassing upon cloud evaporation typically increases this ratio by a factor of 1.5–5, as determined by numerical simulations, its in-cloud reprocessing is shown using a global model to strongly limit the gas-phase sink and the resulting production of formic acid. Based on the combined findings in this work, we derive a range of 1.2–8.5 Tg/y for the global HCOOH production from cloud-derived HOCH 2 OH reacting with OH. The best estimate, 3.3 Tg/y, is about 30 times less than recently reported. The theoretical equilibrium constant K eq (2) determined in this work also allows us to estimate the Henry’s law constant of methanediol (8.1 × 10 5 M atm −1 at 280 K).
Technical assistance continued in support of the Atmospheric Cloud Physics Laboratory is discussed. A study of factors affecting warm cloud formation showed that the time of formation during an arbitrary expansion is independent of carrier gas composition for ideal gases and independent of aerosol concentration for low concentrations of very small aerosols. Equipment and procedures for gravimetric evaluation of a precision saturator were laboratory tested. A numerical feasibility study was conducted for the stable levitation of charged solution droplets by an electric field in a one-g static diffusion chamber. The concept, operating principles, applications, limits, and sensitivity of the levitation technique are discussed.
Abstract Bjerknes compensation (BJC) refers to the anticorrelation observed between atmospheric and oceanic heat transport (AHT/OHT) variability, particularly on decadal to longer time scales that may be important to the predictability of the climate system. This study investigates the spread in BJC across fully coupled simulations of phase 6 of the Coupled Model Intercomparison Project (CMIP6) and critical processes (particularly related to sea ice and clouds) that may contribute to that spread. BJC on decadal to longer time scales is confirmed across all the simulations evaluated, and it is strongest in the Northern Hemisphere (NH) between 60° and 70°N. At these latitudes, BJC appears to be primarily driven by the exchange of turbulent fluxes (sensible and latent) in the Greenland, Iceland, and Barents Seas. Metrics to break down how sea ice and clouds uniquely modify the radiative balance of the polar atmosphere during anomalous OHT events are presented. These metrics quantify the impacts of sea ice and clouds on surface and top of atmosphere (latent, sensible, longwave, and shortwave radiative) energy fluxes. Cloud responses tend to counter the clear sky impacts over the Marginal Ice Zone (MIZ). It is further shown that the degree of BJC present in a simulation at high latitudes is heavily influenced by the sensitivity of the sea ice to OHT, which is most influential over the MIZ. These results are qualitatively robust across models and explain the intermodel spread in NH BJC in the preindustrial control experiment.