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At least 883 records · Page 49

The single scattering phase functions of Jupiter's clouds

The determination of the single scattering phase functions of Jupiter's clouds and a thin upper haze by Tomasko et al. was refined and extended to seven latitudes in blue and red light. The phase function is well-constrained by the Pioneer 10 and 11 photometric data sets. Multiple scattering models were computed to match the limb darkening at each latitude at up to 15 phase angles from 12 deg to 151 deg. Ground-based observations were used for absolute calibration and to extend the data to lower phase angles. The phase functions were parameterized using the double Henyey-Greenstein function. The three Henyey-Greenstein parameters and the single scattering albedo were determined using a non-linear least squares method for the haze and the clouds below. The phase functions derived for the northen zone and belt are remarkably similar to the phase functions of the corresponding regions in the south, with most of the differences in brightness of the northern and southern features resulting from minor differences in single scattering albedo. Analysis of the Equatorial Region is complicated by the presence of numerous small features, but the phase function required is generally similar to that seen in the more homogeneous regions. Details of the phase functions of the haze and clouds are presented, and the differences between the cloud phase functions at low and high latitudes in red and blue light are discussed.

Doose, L. R.↗

Atmospheric ice nucleation

Atmospheric ice nucleation is crucial for global precipitation and affects the structure, lifetime and reflectivity of clouds, thereby impacting climate. Ice nucleates in various ways from aerosol particles, termed ice-nucleating particles, over an extensive temperature and humidity range. Quantifying the kinetic and thermodynamic regimes of nucleation is necessary to relate fundamental physics to theoretically based predictions of ice formation for implementation in cloud and climate models. We review how the molecular picture of ice nucleation has advanced in recent years and consequential impacts on the interpretation and parameterization of ice nucleation. Advances include the role of interfacial free energy and pressure on ice nucleation rates, mobility regions of water that generate the critical ice nucleus, classical and non-classical pathways of nucleation, the type of ice polymorph that forms, the impact of solutes on freezing and the role of nanopores as surface features promoting ice nucleation. We also introduce currently debated and evaluated freezing parameterizations for application in model environments. Finally, we outline what we believe are the current needs for improving predictive understanding of ice nucleation.

54 ENVIRONMENTAL SCIENCES↗

The diurnal interaction between convection and peninsular-scale forcing over South Florida

One of the outstanding problems in modern meterology is that of describing in detail the manner in which larger scales of motion interact with, influence and are influenced by successively smaller scales of motion. The present investigation is concerned with a study of the diurnal evolution of convection, the interaction between the peninsular-scale convergence and convection, and the role of the feedback produced by the cloud-scale downdrafts in the maintenance of the convection. Attention is given to the analysis, the diurnal cycle of the network area-averaged divergence, convective-scale divergence, convective mass transports, and the peninsular scale divergence. The links established in the investigation between the large scale (peninsular), the mesoscale (network), and the convective scale (cloud) are found to be of fundamental importance to the understanding of the initiation, maintenance, and decay of deep precipitating convection and to its theoretical parameterization.

Cooper, H. J.↗

Numerical simulation of a subtropical squall line over the Taiwan Strait

The present 2D nonhydrostatic, time-dependent numerical cloud model, which is applied to the structure and development of a subtropical squall line observed during the Taiwan Area Mesoscale Experiment, includes (1) a parameterized ice-phase microphysical scheme, (2) longwave and shortwave radiative-transfer processes, and (3) heat and moisture fluxes from the ocean surface. A comparative study is made of the vertical transport of horizontal momentum and of the latent heat release by the simulated subtropical squall system, as well as the heat release of squall systems occurring in other geographic locations.

Tao, Wei-Kuo↗

Investigations of the dynamical evolution of protoplanetary nebulae

The spectral energy distributions (SED's) of all the known Class I (protostellar) sources in the Taurus molecular cloud were modelled. The Tereby, Shu, & Cassen (1984, TSC) density distribution for a rotating, infalling envelope was adopted. The radiative equilibrium temperature distribution from the spherical average of the TSC density distribution was calculated. The resulting spherically-symmetric temperature distribution then provides the source function to obtain the emergent spectrum at a given inclination angle i from the formal solution of the transfer equation, using the exact density (opacity) distribution. Results showed that the SED's of the protostar candidates in Taurus can be reproduced with TSC models having infall rates close to the values predicted by the theory of isothermal cloud collapse. Flat Spectrum T Tauri Stars were studied. The mid- to far-infrared fluxes of 'flat spectrum' T Tauri stars can be explained by radiative equilibrium emission from infalling dusty envelopes. This explanation indicated that models employing 'active' disks, in which the temperature distribution is a parameterized power law, should be invoked with caution. Infall also naturally explains the scattered light nebulae detected around many flat-spectrum sources. Results showed that the SED's of the protostar candidates in Taurus can be reproduced with TSC models having infall rates close to the values predicted by the theory of isothermal cloud collapse. Flattened infalling envelope models are also being studied.

Hartmann, Lee W.↗

Evaluating Mesoscale Convective Systems Over the US in Conventional and Multiscale Modeling Framework Configurations of E3SMv1

Organized mesoscale convective systems (MCSs) contribute a significant amount of precipitation in the Central and Eastern US during spring and summer, which impacts the availability of freshwater and flooding events. However, current global Earth system models cannot capture MCSs well and misrepresent the statistics of precipitation in the region. In this study, we investigate the representation of MCSs in three configurations of the Energy Exascale Earth System Model (E3SMv1) by tracking individual storms based on outgoing longwave radiation using a new application of TempestExtremes. Our results indicate that conventional parameterizations of convection, implemented in both low (LR; ~150 km) and high (HR; ~25 km) resolution configurations, fail to capture almost all MCS-like events, in-part because they underestimate high-level cloud ice associated with deep convection. On the other hand, the multiscale modeling framework (MMF; cloud-resolving models embedded in each grid-column of ~150 km resolution E3SMv1) configuration represents MCSs and their annual cycle better. Nevertheless, relative to observations, the E3SMv1-MMF spatial distribution of MCSs and associated precipitation is shifted eastward, and the diurnal timing is lagged. A comparison between the large-scale environment in E3SMv1-MMF and ERA5 reanalysis suggests that the biases during the summer in E3SMv1-MMF are associated with biases in low-level humidity and meridional moisture transport within the low-level jet. The fact that conventional parameterizations of convection, even with high-resolution, cannot capture MCSs over the US suggests that methods with explicit representation of kilometer-scale convective organization, such as the MMF, may be necessary for improving the simulation of these convective systems.

54 ENVIRONMENTAL SCIENCES↗

Strong Sensitivity of Simulated Biomass Burning Aerosol Transport and Radiative Effects Over the South Atlantic to Carbonaceous Aerosol Aging and Particle Density

Biomass burning aerosol (BBA) impacts climate through aerosol‐cloud‐radiation interactions, but models disagree on the sign and magnitude of BBA radiative effects. We quantify the sensitivity of BBA radiative effects and transport to three BBA‐relevant processes and properties: parameterized oxidative aging of organic aerosol (OA), a combined change to black carbon (BC) density and the method for calculating aerosol refractive index, and reduction in OA density. We evaluate Unified Model simulations against two aircraft campaigns from summer 2017 over the Southeast Atlantic. The model generally performs well, such that discrepancies between the observational data sets may sometimes limit the precision of the evaluation. Our newly developed aging parameterization reproduces observed OA:BC mass ratios well and allows modeled OA:BC to decrease with smoke age, but increases bias in aerosol extinction and changes the BBA radiative effect little (+0.12 W m -2 ). We calculate aerosol refractive index using either a volume‐weighted component average or the Maxwell‐Garnett (MG) mixing assumption, which represents BC as small inclusions in a host material. Compared to MG mixing, the volume‐weighted average refractive index and reduced BC density increase aerosol absorption, substantially increasing the total BBA radiative effect (+2.66 W m -2 ) and amount of BBA transported across the ocean through BC self‐lofting. Reducing OA density to better match literature values changes the total BBA radiative effect by −1.96 W m -2 . Changes to direct radiative effects exceed changes to cloud radiative effects. Our findings emphasize the sensitivity of aerosol radiative effects and transport to these processes and properties, which we suggest could be improved in climate models.

Southeast Atlantic↗

Modeling Land-Atmosphere Coupling at Cloud-Resolving Scale Within the Multiple Atmosphere Multiple Land (MAML) Framework in SP-E3SM

Representing subgrid variabilities of land surface processes and their upscaled effects is crucial for global climate modeling. Here, we implement a Multiple Atmosphere Multiple Land (MAML) framework in the superparamaterized version of E3SM (SP32 E3SM) to explicitly simulate the subgrid variabilities of land states and fluxes at cloud-resolving scale and their interactions with atmosphere. Comparing to the standard SP-E3SM in which all the atmospheric columns of the cloud resolving model embedded within the global atmospheric model grid interact with the same land surface (i.e., Multiple Atmosphere Single Land (MASL)), the impact of MAML on the strength of land-atmosphere coupling is limited, partly because the current implementation mainly facilitates one-way coupling between the cloud-resolving model and the land surface model. Despite such limitation, MAML increases the surface latent heat flux at the expense of sensible heat flux, and increases precipitation in India, Amazon, and Central Africa, reducing the model dry bias compared to the standard SP-E3SM. By employing a normalized gross moist stability (NGMS) diagnostic framework, we find that the increase in precipitation minus evaporation (PE) is primarily driven by the change in large-scale moisture convergence, particularly by the increase of water vapor in the lower atmosphere, while the local effect of total surface energy flux plays a minor role in the P-E change. More specifically, MAML changes the surface energy partitioning (evaporative fraction), increases the atmosphere water vapor, and further increases P-E by decreasing the NGMS. Finally, future development in the MAML framework is discussed.

54 ENVIRONMENTAL SCIENCES↗

Evaluation of present-day extreme precipitation over the United States: an inter-comparison of convection and dynamic permitting configurations of E3SMv1

Abstract Accurate simulation of the present-day characteristics of mean and extreme precipitation at regional scales remains a challenge for Earth system models, which is due in part to deficiencies in model physics such as convective parameterization (CP), and coarse resolution. High horizontal resolution (HR, ∼25 km) and multiscale modeling framework (MMF, i.e. replacing conventional CP with embedded km-scale cloud-resolving models) are two promising directions that could help improve the interaction between subgrid-scale physical processes and large-scale climate. Here, we evaluate simulated extreme precipitation over the United States (US) across three configurations (i.e. low-resolution [LR], HR, and MMF) of the Energy Exascale Earth System Model (E3SMv1) and intercompare them against two gridded observation datasets (climate prediction center daily US precipitation and integrated multi-satellite retrievals for global precipitation measurement). We assess the model’s ability to simulate very heavy seasonal precipitation (illustrated by the difference between the 99th and 90th percentile values) as well as the spatial distributions of several extreme precipitation indices defined by the expert team on climate change detection and indices. Our results show that both the dry (i.e. consecutive dry days (CDD)) and wet (i.e. consecutive wet days, maximum 5 day precipitation, and very wet days) extremes evaluated herein show some improvement as well as degradation with MMF and HR relative to LR. These results vary across seasons and US subregions. For instance, only the very heavy precipitation of winter is improved with MMF and HR. Both configurations alleviate the well-known drizzling bias evident in LR across both winter and summer in many parts of the US, largely due to the overall improvement in intensity and frequency of precipitation. Additionally, our results suggest that while E3SMv1-MMF has higher intensity rates when it does rain, it has too many CDD during the summer, contributing to a low mean precipitation bias.

54 ENVIRONMENTAL SCIENCES↗

The effects of small ice crystals on the infrared radiative properties of cirrus clouds

The effects of nonspherical small ice crystals on the IR radiative properties of cirrus clouds are investigated utilizing light scattering properties of spheroidal particles. Employing the anomalous diffraction theory for spheres and results from the exact spheroid scattering program, efficient parameterization equations are developed for calculations of the absorption and scattering properties for small ice crystals. Parameterization formulas are developed for large ice crystals employing results computed from the geometric ray-tracing method and the Fraunhofer diffraction theory for hexagonal crystals and spheroids.

Takano, Y.↗

Simulation of the Aerosol Size Distribution Using a Neural Network Surrogate for the Modal Aerosol Module (MAM7)

One objective of atmospheric simulations is to quantify the distribution of aerosols and their properties. Accurate parameterizations of the processes governing aerosol mass, particle number, and particle size distribution are important for predicting the Earth’s net radiative balance and aerosol-cloud interactions. The Modal Aerosol Module (MAM7) is a two-moment aerosol model that simulates mass, number, and size distribution of seven modes comprised of internally mixed aerosol species. The two-moment scheme adds significant computational expense but allows for the prediction of varying particle size distribution relative to the bulk method which predicts only total mass. In this work, we developed a neural network surrogate model for MAM7 (MAMnet) to predict the aerosol number concentration in NASA’s Global Earth Observing System (GEOS) without adding prohibitive computational expense. MAMnet, can be driven by output from a single moment, mass-based, aerosol scheme (Goddard Chemistry Aerosol and Radiation model (GOCART)) or from reanalysis products (Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2)). MAMnet was trained using number concentrations from a 5-year GEOS/MAM7 simulation at 1-degree horizontal resolution and using the total mass calculated across modes as inputs, as well as temperature and air density. The model architecture for MAMnet was based on AlexNet, the 2012 winner of the ImageNet Large Scale Visual Recognition Challenge. While some modifications were necessary to accommodate our problem, important aspects of the network were preserved. MAMnet was able to reproduce zonal dynamics and spatial distributions of the aerosol number concentration however predictability in the upper troposphere was poor.

Katherine H Breen↗

Anatomy of a Summertime Convective Event over the Arabian Region

This study investigates the structure and evolution of a summertime convective event that occurred on 14 July 2015 over the Arabian region. We use the WRF Model with 1-km horizontal grid spacing and test three PBL parameterizations: the Mellor–Yamada–Nakanishi–Niino (MYNN) scheme; the Asymmetrical Convective Model, version 2, (ACM2) scheme; and the quasi-normal scale-elimination (QNSE) scheme. Convection initiates near the Al Hajar Mountains of northern Oman at around 1100 local time (LT; 0700 UTC) and propagates northwestward. A nonorographic convective band along the west coast of the United Arab Emirates (UAE) develops after 1500 LT as a result of the convergence of cold pools with the sea breeze from the Arabian Gulf. The model simulation employing the QNSE scheme simulates the convection initiation and propagation well. Although the MYNN and ACM2 simulations show convective initiation near the Al Hajar Mountains, they fail to simulate the development of the convective band along the UAE west coast. The MYNN run simulates colder near-surface temperatures and a weaker sea breeze, whereas the ACM2 run simulates a stronger sea breeze but a drier lower troposphere. Sensitivity simulations using horizontal grid spacings of 9 and 3 km show that lower-resolution runs develop broader convective structures and weaker cold pools and horizontal wind divergence, affecting the development of convection along the west coast of the UAE. The 1-km run using the QNSE PBL scheme realistically captures the sequence of events that leads to the moist convection over the UAE and adjacent mountains.

54 ENVIRONMENTAL SCIENCES↗

Tropical Cirrus in Global Storm-Resolving Models: 1. Role of Deep Convection

Pervasive cirrus clouds in the upper troposphere and tropical tropopause layer (TTL) influence the climate by altering the top-of-atmosphere radiation balance and stratospheric water vapor budget. These cirrus are often associated with deep convection, which global climate models must parameterize and struggle to accurately simulate. By comparing high-resolution global storm-resolving models from the Dynamics of the Atmospheric general circulation Modeled On Non-hydrostatic Domains (DYAMOND) intercomparison that explicitly simulate deep convection to satellite observations, we assess how well these models simulate deep convection, convectively generated cirrus, and deep convective injection of water into the TTL over representative tropical land and ocean regions. The DYAMOND models simulate deep convective precipitation, organization, and cloud structure fairly well over land and ocean regions, but with clear intermodel differences. All models produce frequent overshooting convection whose strongest updrafts humidify the TTL and are its main source of frozen water. Intermodel differences in cloud properties and convective injection exceed differences between land and ocean regions in each model. We argue that, with further improvements, global storm-resolving models can better represent tropical cirrus and deep convection in present and future climates than coarser-resolution climate models. To realize this potential, they must use available observations to perfect their ice microphysics and dynamical flow solvers.

54 ENVIRONMENTAL SCIENCES↗

A Lagrangian Study of the Transition from Shallow to Deep Convection Using ASR Observations and Les Simulations (Final Report)

With the support from this grant, we have made the following accomplishments. We have found that a formula for fractional entrainment rate, a key aspect for parameterization moist convection, that works for both shallow and deep convection, which provide a promising direction for unified treatment of entrainment for both shallow and deep convection. We also examined the formulation of vertical velocity and showed that the effect of non-hydrostatic pressure and entrainment on vertical velocity are not constants, as assumed in past studies, but can be computed using a simple model for the cloudy updrafts. These results also apply to both deep and shallow convection, which opens the door for a more physically based parameterization of the updraft vertical velocity. We have also conducted extensive analysis of the RACORO aircraft data and have published the results in Wei et al. (2020). We have made extensive effort scrutinizing the data in detail and examining the various hypotheses with the aid of the LES simulations. This was the first application of the modified Paluch diagram on modern aircraft data and the first comprehensive analysis of mixing in clouds using real data (instead of only LES output) in a very long time. These analyses enhanced the science return of the ASR aircraft measurements. This grant also supported a study of the collisions among cold pools and an effort to build parameterizations of moist convection using tools developed in control theory.

42 ENGINEERING↗

A diagnostic study of vertical fluxes in cumulus clouds using model output data

Midlatitude supercell, Florida sea-breeze convection, and tropical squall line simulations were performed using the Colorado State University Regional Atmospheric Modeling System which employed the non-hydrostatic, fully compressible, equations with parameterized microphysics. The time evolution of the vertical velocity variance (VVV) is especially interesting since it is a measure of the strength of convection. This variance exhibits striking similarities when analyzed for the aforementioned cases which may indicate that all convection is fundamentally similar. Vertical mass and moisture covariances appear strongly linked to VVV, so it may be the appropriate variable on which to base a hybrid cumulus parameterization scheme.

Weissbluth, M. J.↗

Artificial Neural Network (ANN) Surface Longwave and Shortwave Fluxes Trained on CERES Observations

The Clouds and Earth’s Radiant Energy System (CERES) project provides satellite-based observations of the radiative fluxes and clouds systems. CERES climate quality data products typically take several months of calibration and validation before release to the public. The Fast Longwave and Shortwave Radiative Flux (FLASHFlux) data product was developed to provide key data for the applied sciences and educational users within a week of observation. FLASHFlux achieves this by using simplified calibration, an operational meteorological product from Global Modeling and Assimilation Office (GMAO), and its own surface parameterizations model. The CERES FLASHFlux provides two data products: 1) an hourly Level 2 Single Scanner Footprint (SSF) data separately for Terra and NOAA-20 observations, and 2) a daily Level 3 Time Interpolated and Spatially Averaged (TISA) 1o x 1o gridded data that combines Terra and NOAA-20 observations. Currently, FLASHFlux uses the Langley Parameterized Shortwave Algorithm (LPSA) and Langley Parameterized Longwave Algorithm (LPLA) to derive its surface fluxes (Kratz et al., 2010; Gupta et al, 2001). A new Machine Learning (ML) based approach using Artificial Neural Networks to derive Surface Longwave (LW) & Shortwave (SW) fluxes based on training data from the CERES Clouds Radiative Swath (CRS) product is being investigated to replace LPSA and LPLA in the SSF surface flux products. One of the biggest hurdles in training ML model is model fitting. To overcome the problem of overfitting we use feature engineering that helps in finding the important feature and remove features that are irrelevant to the model. In our training we employed the Leave-One-Feature-Out Importance (LOFO) to evaluate the significance of each feature in our training. We intercompare ANN fluxes against surface fluxes produced from the Fu-Liou model in CRS and the LPSA/LPLA in FLASHFlux SSF. Furthermore, we validated ANN derived fluxes to the Baseline Surface Radiation Network (BSRN).

P C Sawaengphokhai↗

Applying Advanced Ground-Based Remote Sensing in the Southeast Asian Maritime Continent to Characterize Regional Proficiencies in Smoke Transport Modeling

This work describes some of the most extensive ground-based observations of the aerosol profile collected in Southeast Asia to date, highlighting the challenges in simulating these observations with a mesoscale perspective. An 84-h WRF Model coupled with chemistry (WRF-Chem) mesoscale simulation of smoke particle transport at Kuching, Malaysia, in the southern Maritime Continent of Southeast Asia is evaluated relative to a unique collection of continuous ground-based lidar, sun photometer, and 4-h radiosonde profiling. The period was marked by relatively dry conditions, allowing smoke layers transported to the site unperturbed by wet deposition to be common regionally. The model depiction is reasonable overall. Core thermodynamics, including landsea-breeze structure, are well resolved. Total model smoke extinction and, by proxy, mass concentration are low relative to observation. Smoke emissions source products are likely low because of undersampling of fires in infrared sun-synchronous satellite products, which is exacerbated regionally by endemic low-level cloud cover. Differences are identified between the model mass profile and the lidar profile, particularly during periods of afternoon convective mixing. A static smoke mass injection height parameterized for this study potentially influences this result. The model does not resolve the convective mixing of aerosol particles into the lower free troposphere or the enhancement of near-surface extinction from nighttime cooling and hygroscopic effects.

Aerosols; Air quality; Lidars/Lidar observations; ↗

The Role of In-Cloud Wet Removal in Simulating Aerosol Vertical Profiles and Cloud Radiative Forcing

Among the physical processes controlling aerosol vertical profiles, in-cloud wet removal is of utmost importance while its representation in global climate models (GCMs) is crude. In this study, we implement into the Community Atmosphere Model version 6 (CAM6) a physically based aerosol wet removal parameterization scheme that explicitly treats aerosol activation, removal and resuspension. Evaluation against in-situ observations shows that the default scheme substantially overestimates the upper tropospheric black carbon (BC) and sea salt mass. Our physically based scheme reduces BC and sea salt mass by a factor of 10 and 1,000, respectively, in better agreement with observations. Also, the new scheme slightly increases number of aerosol particles between 12 nm and 4.8 μm in diameter, thereby mitigating the aerosol number underestimation in the default scheme. Our new scheme reduces the overestimation of coarse-mode aerosol (0.5–4.8 μm) number. Overall, the aerosol property changes (mass decrease and number increase) reduce the cloud condensation nuclei (CCN) concentration at low supersaturation (i.e., 0.02% and 0.1%), and increase CCN at high supersaturations (i.e., 0.5% and 1%). Consequently, the global annual mean cloud liquid water path increases by 1.89 g m -2 and the ice water path increases by 0.51 g m -2 . The global annual mean shortwave, longwave, and net cloud radiative forcing change by -1.06, 0.57, and -0.48 W m -2 , respectively. Further improvement is needed to reflect the real physics that the removal efficiencies for aerosol mass and number are disproportionate and to advect cloud-borne (activated) aerosols for a complete aerosol lifecycle.

54 ENVIRONMENTAL SCIENCES↗