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At least 55 records · Page 3

Linking Synoptic Patterns to Cloud Properties and Local Circulations Over Southeastern Texas

This report classifies meteorological regimes in the southeastern Texas region to identify environmental conditions that favor sea-breeze induced convection. The classification is accomplished using a Self-Organizing Map (SOM) approach. We applied SOM to 10 years of 700-hPa geopotential height anomalies during the summer months from reanalysis data to distinguish three dominant synoptic regimes, with a continuum of transitional states between those. The primary regimes include: (a) a pre-trough regime associated with a synoptic trough, (b) a post-trough regime with upper-level northerly flow, and (c) an anticyclonic regime within the westward extent of the Bermuda High. We project the data from the Geostationary Operational Environmental Satellite and the Next Generation Weather Radar system onto each SOM node to investigate the characteristics of cloud and precipitation properties in different regimes. When southeastern Texas is positioned to the southwest quadrant of a maritime high pressure system, an increased cloud frequency is observed over the region during the afternoon hours due to significant moisture advection. A confluence of synoptic southerly flow and sea-breeze circulation commonly occurs in this regime. When a high pressure system is over southeastern Texas, the area is dominated by large-scale subsidence with weak pressure gradients and moderate precipitable water vapor. This weak synoptic forcing is favorable for the formation of a sea-breeze circulation. This is confirmed by an enhanced onshore flow and a decreased temperature at the surface in the early afternoon, as well as a sharp increase in radar echo top height.

54 ENVIRONMENTAL SCIENCES↗

Effects of coupling a stochastic convective parameterization with the Zhang–McFarlane scheme on precipitation simulation in the DOE E3SMv1.0 atmosphere model

Abstract. A stochastic deep convection parameterization is implemented into the US Department of Energy (DOE) Energy Exascale Earth System Model (E3SM) Atmosphere Model version 1.0 (EAMv1). This study evaluates its performance in simulating precipitation. Compared to the default model, the probability distribution function (PDF) of rainfall intensity in the new simulation is greatly improved. The well-known problem of “too much light rain and too little heavy rain” is alleviated, especially over the tropics. As a result, the contribution from different rain rates to the total precipitation amount is shifted toward heavier rain. The less frequent occurrence of convection contributes to suppressed light rain, while more intense large-scale and convective precipitation contributes to enhanced heavy total rain. The synoptic and intraseasonal variabilities of precipitation are enhanced as well to be closer to observations. The sensitivity of the rainfall intensity PDF to the model vertical resolution is examined. The relationship between precipitation and dilute convective available potential energy in the stochastic simulation agrees better with that in the Atmospheric Radiation Measurement (ARM) observations compared with the standard model simulation. The annual mean precipitation is largely unchanged with the use of the stochastic scheme except over the tropical western Pacific, where a moderate increase in precipitation represents a slight improvement. The responses of precipitation and its extremes to climate warming are similar with or without the stochastic deep convection scheme.

54 ENVIRONMENTAL SCIENCES↗

Study of Stratus-Lowering Marine-Fog Events Observed During C-FOG

Two stratus lowering marine fog events observed on 28 September and 04 October 2018 during the Coastal Fog (C-Fog) field campaign that took place offshore of Eastern Canada during 1 September to 6 October 2018 are described. In-situ, profiling and remote sensing observations were made at selected land sites in eastern Newfoundland (NL) and Nova Scotia (NS) as well as aboard the research vessel (R/V) Hugh R. Sharp that cruised in adjoining coastal waters. Synoptic scale analysis showed that both fog episodes were an outcome of the interaction between synoptic-scale surface level low-pressure systems and a contiguous high-pressure system. At the same time, back trajectories revealed that the bulk of the fog layer is formed due to differential advection. Here, the diameter of the fog droplets at the surface gradually decreased from the centre of the fog layer to its leading/trailing edges. The bimodal fog droplet diameter distribution with peaks at 5-10 µm and 20-25 µm provided clues on droplet collision and coalescence processes. The observed difference between microphysical variables and droplet distribution between the two fog events and within same fog layer may have been governed by atmospheric boundary layer conditions (e.g., humidity conditions and turbulence) prevailed in the fog layer. Overall, it is concluded that the life cycle of observed stratus-lowering coastal-fog episodes is dependent on synoptic conditions as well as atmospheric boundary layer characteristics such as stability, cloud top cooling and entrainment.

54 ENVIRONMENTAL SCIENCES↗

Quantifying long-term seasonal and regional impacts of North American fire activity on continental boundary layer aerosols and cloud condensation nuclei

An intimate knowledge of aerosol transport is essential in reducing the uncertainty of the impacts of aerosols on cloud development. Datasets from the U. S. Department of Energy (DOE) Atmospheric Radiation Measurement platform in the Southern Great Plains region (ARM-SGP) and the NASA Modern-Era Retrospective Analysis for Research and Applications, version 2 (MERRA-2) showed seasonal increases in aerosol loading and total carbon concentration during the spring and summer months (2008-2016) which was attributed to fire activity and smoke transport within North America. The monthly mean MERRA-2 surface carbonaceous aerosol mass concentration and ARM-SGP total carbon products were strongly correlated (R=0.82, p<0.01) along with a moderate correlation with the ARM-SGP cloud condensation nuclei (N CCN ) product (0.5, p~0.1). The monthly mean ARM-SGP total carbon and N CCN products were strongly correlated (0.7, p~0.01). An additional product denoting fire number and coverage taken from the National Interagency Fire Center (NIFC) showed a moderate correlation with the MERRA-2 carbonaceous product (0.45, p<0.01) during the 1981-2016 warm season months (March-September). With respect to meteorological conditions, the correlation between the NIFC fire product and MERRA-2 850 hPa isobaric height anomalies was lower (0.26, p~0.13) due to the variability in the frequency, intensity, and number of fires in North America. An observed increase in the isobaric height anomaly during the past decade may lead to frequent synoptic ridging and drier conditions with more fires, thereby potentially impacting cloud/precipitation processes and decreasing air quality.

54 ENVIRONMENTAL SCIENCES↗

Impacts of Synoptic-Scale Dynamics on Clouds and Radiation in High Southern Latitudes

High-latitudinal mixed-phase clouds significantly affect Earth's radiative balance. Observations of cloud and radiative properties from two field campaigns in the Southern Ocean and Antarctica were compared with two global climate model simulations. A cyclone compositing method was used to quantify “dynamics-cloud-radiation” relationships relative to the extratropical cyclone centers. Observations show larger asymmetry in cloud and radiative properties between western and eastern sectors at McMurdo compared with Macquarie Island. Most observed quantities at McMurdo are higher in the western (i.e., post-frontal) than the eastern (frontal) sector, including cloud fraction, liquid water path (LWP), net surface shortwave and longwave radiation (SW and LW), except for ice water path (IWP) being higher in the eastern sector. Here, the two models were found to overestimate cloud fraction and LWP at Macquarie Island but underestimate them at McMurdo Station. IWP is consistently underestimated at both locations, both sectors, and in all seasons. Biases of cloud fraction, LWP, and IWP are negatively correlated with SW biases and positively correlated with LW biases. The persistent negative IWP biases may have become one of the leading causes of radiative biases over the high southern latitudes, after correcting the underestimation of supercooled liquid water in the older model versions. By examining multi-scale factors from cloud microphysics to synoptic dynamics, this work will help increase the fidelity of climate simulations in this remote region.

58 GEOSCIENCES↗

Identifying synoptic controls on boundary layer thermodynamic and cloud properties in a regional forecast model

Although most of our understanding of boundary layer cloudiness is based on idealized, subtropical, barotropic marine environments, boundary layer clouds exist across a range of conditions. In this study, we use the Naval Research Laboratory's Coupled Ocean/Atmosphere Mesoscale Prediction System (COAMPS) and an automated cold-front-relative analysis framework to explore the boundary layer structure associated with low clouds across a transect through the cold front of a midlatitude synoptic cyclone. The model credibly captures boundary layer structure in line with conceptual models of midlatitude cyclones and ground-based observations at Graciosa Island in the Azores. The warm sector is conditionally unstable, with clouds that are too shallow and with too little liquid water, compared to cloud property retrievals from satellite and surface-based instruments. The cold-frontal region exhibits convection associated with weak stability and ascent. Northwest of the cold front, the boundary layer is well mixed, deeper, and capped by a strong inversion maintained by large-scale subsidence. Simulated clouds in frontal and post-frontal regions are mostly too thick, with too much liquid water and too little cloud base drizzle. The post-frontal clouds are associated with grid-scale updrafts, which appear to be the model's attempt to represent mesoscale organization of cellular convection typically observed in the cold sector of midlatitude cyclones. The deep, well-mixed post-frontal boundary layers and cloudiness are maintained by strong surface fluxes, as in cold air outbreaks. Our analysis framework serves as a unique approach to model verification, and our results offer insights into differences in boundary layer cloud behavior between subtropical and synoptic cold-sector regimes.

Eissner, Jordan M. [Univ. of Kansas, Lawrence, KS ↗

Redshift evolution of the underlying type Ia supernova stretch distribution

The detailed nature of type Ia supernovae (SNe Ia) remains uncertain, and as survey statistics increase, the question of astrophysical systematic uncertainties arises, notably that of the evolution of SN Ia populations. We study the dependence on redshift of the SN Ia SALT2.4 light-curve stretch, which is a purely intrinsic SN property, to probe its potential redshift drift. The SN stretch has been shown to be strongly correlated with the SN environment, notably with stellar age tracers. We modeled the underlying stretch distribution as a function of redshift, using the evolution of the fraction of young and old SNe Ia as predicted using the SNfactory dataset, and assuming a constant underlying stretch distribution for each age population consisting of Gaussian mixtures. We tested our prediction against published samples that were cut to have marginal magnitude selection effects, so that any observed change is indeed astrophysical and not observational in origin. In this first study, there are indications that the underlying SN Ia stretch distribution evolves as a function of redshift, and that the age drifting model is a better description of the data than any time-constant model, including the sample-based asymmetric distributions that are often used to correct Malmquist bias at a significance higher than 5σ. The favored underlying stretch model is a bimodal one, composed of a high-stretch mode shared by both young and old environments, and a low-stretch mode that is exclusive to old environments. The precise effect of the redshift evolution of the intrinsic properties of a SN Ia population on cosmology remains to be studied. The astrophysical drift of the SN stretch distribution does affect current Malmquist bias corrections, however, and thereby the distances that are derived based on SN that are affected by observational selection effects. We highlight that this bias will increase with surveys covering increasingly larger redshift ranges, which is particularly important for the Large Synoptic Survey Telescope.

79 ASTRONOMY AND ASTROPHYSICS↗

Collapse of magnetized white dwarfs as site of heavy-element formation and kilonova signal

We present the first end-to-end calculation connecting the accretion-induced collapse (AIC) of a magnetized, rapidly rotating white dwarf to observable kilonova signatures, combining two-dimensional (2D) general-relativistic neutrino-magnetohydrodynamic simulations, followed by radiation hydrodynamics with in-situ nuclear network and 2D Monte Carlo radiative transfer with spatially resolved heating rates. Unlike all previous unmagnetized AIC models – which predicted proton-rich, $^{56}$Ni-dominated ejecta – strong magnetic fields eject ${\approx }\, 0.2\, \mathrm{ M}_\odot$ of neutron-rich material ($\langle Y_e \rangle \sim 0.24$) on dynamical time-scales, before neutrino irradiation can raise the electron fraction, enabling strong r-process nucleosynthesis up to and beyond the third peak. The resulting kilonova is lanthanide-rich ($X_{\rm lan} \approx 8~{{\ \rm per\ cent}}$) and dominated by near-infrared emission. We compute synthetic light curves in the Large Synoptic Survey Telescope and J ames Webb Space Telescope bands and find striking agreement, without parameter tuning, between the observations of AT 2023vfi/GRB 230307A and our broadband light curves for polar viewing angles. These results establish magnetized AIC as a viable channel for heavy r-process element production and a compelling progenitor candidate for long-duration gamma-ray bursts with kilonova signatures.

MHD↗

Regime-based aerosol–cloud interactions from CALIPSO-MODIS and the Energy Exascale Earth System Model version 2 (E3SMv2) over the Eastern North Atlantic

This study investigates aerosol-cloud interactions in marine boundary layer (MBL) clouds using an advanced deep-learning-driven synoptic-regime-based framework, combining satellite data (CALIPSO vertically resolved aerosol extinction and MODIS cloud properties) with 1° nudged Energy Exascale Earth System Model version 2 (E3SMv2) simulation over the Eastern North Atlantic (ENA; ∼10°×10°, 2006–2014). The E3SMv2 captures observed seasonal variations in cloud droplet number concentrations (N d ) and liquid water path (LWP), though it systematically underestimates N d . We then partition ENA meteorology into four synoptic regimes (Pre-Trough, Post-Trough, Ridge, Trough) via a deep-learning clustering of ERA5 reanalysis fields, enabling regime-dependent aerosol-cloud interactions analyses. Both satellite and E3SMv2 exhibit an inverted-V LWP-N d relationship. In Post-Trough and Ridge regimes, the satellite shows stronger negative LWP-N d sensitivities than in Pre-Trough regime. The Trough regime displays a muted satellite LWP response. In comparison, the model predicts more exaggerated LWP responses across regimes, with LWP increasing too quickly at low N d and decreasing more sharply at high N d , especially in Pre-Trough and Trough regimes. These exaggerated model LWP sensitivities may stem from uncertainties in representing drizzle processes, entrainment, and turbulent mixing. As for N d susceptibility to aerosols, N d increases with MBL aerosol extinction in both datasets, but the simulated aerosol-cloud interactions appear oversensitive to meteorological conditions. Overall, E3SMv2 better captures aerosol effects under regimes that favor stratiform clouds (Post-Trough, Ridge), but performance deteriorates for regimes with deeper, dynamically complex clouds (Trough), highlighting the need for improved representations of those cloud processes in climate models.

Environmental sciences↗

Evaluating seasonal and regional distribution of snowfall in regional climate model simulations in the Arctic

In this study, we investigate how the regional climate model HIRHAM5 reproduces the spatial and temporal distribution of Arctic snowfall when compared to CloudSat satellite observations during the examined period of 2007–2010. For this purpose, both approaches, i.e., the assessments of the surface snowfall rate (observation-to-model) and the radar reflectivity factor profiles (model-to-observation), are carried out considering spatial and temporal sampling differences. The HIRHAM5 model, which is constrained in its synoptic representation by nudging to ERA-Interim, represents the snowfall in the Arctic region well in comparison to CloudSat products. The spatial distribution of the snowfall patterns is similar in both identifying the southeastern coast of Greenland and the North Atlantic corridor as regions gaining more than twice as much snowfall as the Arctic average, defined here for latitudes between 66 and 81°N. Excellent agreement (difference less than 1%) in the Arctic-averaged annual snowfall rate between HIRHAM5 and CloudSat is found, whereas ERA-Interim reanalysis shows an underestimation of 45% and significant deficits in the representation of the snowfall rate distribution. From the spatial analysis, it can be seen that the largest differences in the mean annual snowfall rates are an overestimation near the coastlines of Greenland and other regions with large orographic variations as well as an underestimation in the northern North Atlantic Ocean. To a large extent, the differences can be explained by clutter contamination, blind zone or higher resolution of CloudSat measurements, but clearly HIRHAM5 overestimates the orographic-driven precipitation. The underestimation of HIRHAM5 within the North Atlantic corridor south of Svalbard is likely connected to a poor description of the marine cold air outbreaks which could be identified by separating snowfall into different circulation weather type regimes. By simulating the radar reflectivity factor profiles from HIRHAM5 utilizing the Passive and Active Microwave TRAnsfer (PAMTRA) forward-modeling operator, the contribution of individual hydrometeor types can be assessed. Looking at a latitude band at 72–73°N, snow can be identified as the hydrometeor type dominating radar reflectivity factor values across all seasons. The largest differences between the observed and simulated reflectivity factor values are related to the contribution of cloud ice particles, which is underestimated in the model, most likely due to the small sizes of the particles. The model-to-observation approach offers a promising diagnostic when improving cloud schemes, as illustrated by comparison of different schemes available for HIRHAM5.

54 ENVIRONMENTAL SCIENCES↗

Enabling Catalog Simulations of Transient and Variable Sources Based on LSST Cadence Strategies

The American Astronomical Society. All rights reserved.. The Large Synoptic Survey Telescope (LSST) project will conduct a 10 year multi-band survey starting in 2022. Observing strategies for this survey are being actively investigated, and the science capabilities can be best forecasted on the basis of simulated strategies from the LSST Operations Simulator (OpSim). This paper describes the way in which OpSim simulates a stochastic realization of the sequence of LSST pointings over the survey duration, and is based on a model of the observatory (including telescope) and historical data of observational conditions. OpSim outputs contain a record of each simulated pointing of the survey along with a complete characterization of the pointing in terms of observing conditions, and some useful quantities derived from the characteristics of the pointing. Thus, each record can be efficiently used to derive the properties of observations of all astrophysical sources found in that pointing. However, in order to obtain the time series of observations (light curves) of a set of sources, it is often more convenient to compute all observations of an astrophysical source, and iterate over sources. In this document, we describe the open source python package OpSimSummary, which allows for a convenient reordering. The objectives of this package are to provide users with an Application Programming Interface for accessing all such observations and summarizing this information in the form of intermediate data products usable by third party software such as SNANA, thereby also bridging the gap between official LSST products and preexisting simulation codes.

79 ASTRONOMY AND ASTROPHYSICS↗

TRACER Perspectives on Gulf-Breeze and Bay-Breeze Circulations and Coastal Convection

Abstract This study explores gulf-breeze circulations (GBCs) and bay-breeze circulations (BBCs) in Houston–Galveston, investigating their characteristics, large-scale weather influences, and impacts on surface properties, boundary layer updrafts, and convective clouds. The results are derived from a combination of datasets, including satellite observations, ground-based measurements, and reanalysis datasets, using machine learning, changepoint detection method, and Lagrangian cell tracking. We find that anticyclonic synoptic patterns during the summer months (June–September) favor GBC/BBC formation and the associated convective cloud development, representing 74% of cases. The main Tracking Aerosol Convection Interactions Experiment (TRACER) site located close to the Galveston Bay is influenced by both GBC and BBC, with nearly half of the cases showing evident BBC features. The site experiences early frontal passages ranging from 1040 to 1630 local time (LT), with 1300 LT being the most frequent. These fronts are stronger than those observed at the ancillary site which is located further inland from the Galveston Bay, including larger changes in surface temperature, moisture, and wind speed. Furthermore, these fronts trigger boundary layer updrafts, likely promoting isolated convective precipitating cores that are short lived (average convective lifetime of 63 min) and slow moving (average propagation speed of 5 m s −1 ), primarily within 20–40 km from the coast.

54 ENVIRONMENTAL SCIENCES↗

Tuning the Legacy Survey of Space and Time (LSST) Observing Strategy for Solar System Science

Abstract The Vera C. Rubin Observatory is expected to start the Legacy Survey of Space and Time (LSST) in early to mid-2025. This multiband wide-field synoptic survey will transform our view of the solar system, with the discovery and monitoring of over five million small bodies. The final survey strategy chosen for LSST has direct implications on the discoverability and characterization of solar system minor planets and passing interstellar objects. Creating an inventory of the solar system is one of the four main LSST science drivers. The LSST observing cadence is a complex optimization problem that must balance the priorities and needs of all the key LSST science areas. To design the best LSST survey strategy, a series of operation simulations using the Rubin Observatory scheduler have been generated to explore the various options for tuning observing parameters and prioritizations. We explore the impact of the various simulated LSST observing strategies on studying the solar system’s small body reservoirs. We examine what are the best observing scenarios and review what are the important considerations for maximizing LSST solar system science. In general, most of the LSST cadence simulations produce ±5% or less variations in our chosen key metrics, but a subset of the simulations significantly hinder science returns with much larger losses in the discovery and light-curve metrics.

79 ASTRONOMY AND ASTROPHYSICS↗

Vertical Structure of Clouds and Precipitation During Arctic Cold–Air Outbreaks and Warm–Air Intrusions: Observations From COMBLE

The Arctic is marked by deep intrusions of warm, moist air, alternating with outbreaks of cold air down to lower latitudes. The typical vertical structure of clouds and precipitation during these two synoptic weather extremes is examined at a coastal site at 69°N in Norway. The Norwegian Sea is a corridor for warm-air intrusions (WAIs) and frequently witnesses cold-air outbreaks (CAOs). This study uses data from profiling radar, lidar, and microwave radiometer, radiosondes and other probes that were collected during the CAOs in the Marine Boundary Layer Experiment (COMBLE) between 1 December 2019 and 31 May 2020. Marine CAOs are defined in terms of thermal instability relative to the sea surface temperature, and WAIs in terms of equivalent potential temperature stratification between the surface and 850 hPa. Cloud structures in CAOs are convective, driven by strong surface heat fluxes over a long fetch of open water, with cloud tops rarely exceeding 6 km above sea level. The mostly open-cellular convection produces intermittent moderately-heavy precipitation at the observational site, notwithstanding the low precipitable water vapor (PWV). In contrast, WAIs are marked by high values of PWV and integrated vapor transport. Here, WAI clouds are synoptically driven, stratiform, with cloud tops often exceeding 5 km, sometimes layered, and generally producing persistent precipitation that can be heavier than in CAOs.

54 ENVIRONMENTAL SCIENCES↗

DSCOVR/EPIC-derived global hourly and daily downward shortwave and photosynthetically active radiation data at 0.1° × 0.1° resolution

Downward shortwave radiation (SW) and photosynthetically active radiation (PAR) play crucial roles in Earth system dynamics. Spaceborne remote sensing techniques provide a unique means for mapping accurate spatiotemporally continuous SW–PAR, globally. However, any individual polar-orbiting or geostationary satellite cannot satisfy the desired high temporal resolution (sub-daily) and global coverage simultaneously, while integrating and fusing multisource data from complementary satellites/sensors is challenging because of co-registration, intercalibration, near real-time data delivery and the effects of discrepancies in orbital geometry. The Earth Polychromatic Imaging Camera (EPIC) on board the Deep Space Climate Observatory (DSCOVR), launched in February 2015, offers an unprecedented possibility to bridge the gap between high temporal resolution and global coverage and characterize the diurnal cycles of SW–PAR globally. In this study, we adopted a suite of well-validated data-driven machine-learning models to generate the first global land products of SW–PAR, from June 2015 to June 2019, based on DSCOVR/EPIC data. The derived products have high temporal resolution (hourly) and medium spatial resolution (0.1°×0.1°), and they include estimates of the direct and diffuse components of SW–PAR. We used independently widely distributed ground station data from the Baseline Surface Radiation Network (BSRN), the Surface Radiation Budget Network (SURFRAD), NOAA's Global Monitoring Division and the U.S. Department of Energy's Atmospheric System Research (ASR) program to evaluate the performance of our products, and we further analyzed and compared the spatiotemporal characteristics of the derived products with the benchmarking Clouds and the Earth's Radiant Energy System Synoptic (CERES) data. We found both the hourly and daily products to be consistent with ground-based observations (e.g., hourly and daily total SWs have low biases of -3.96 and -0.71 W m -2 and root-mean-square errors (RMSEs) of 103.50 and 35.40 W m -2 , respectively). The developed products capture the complex spatiotemporal patterns well and accurately track substantial diurnal, monthly, and seasonal variations in SW–PAR when compared to CERES data. They provide a reliable and valuable alternative for solar photovoltaic applications worldwide and can be used to improve our understanding of the diurnal and seasonal variabilities of the terrestrial water, carbon and energy fluxes at various spatial scales.

54 ENVIRONMENTAL SCIENCES↗

Survey-wide asteroid discovery with a high-performance computing enabled non-linear digital tracking framework

Modern astronomical surveys detect asteroids by linking together their appearances across multiple images taken over time. This approach faces limitations in detecting faint asteroids and handling the computational complexity of trajectory linking. Here, we present a novel method that adapts “digital tracking” – traditionally used for short-term linear asteroid motion across images – to work with large-scale synoptic surveys such as the Vera Rubin Observatory Legacy Survey of Space and Time (Rubin/LSST). Our approach combines hundreds of sparse observations of individual asteroids across their non-linear orbital paths to enhance detection sensitivity by several magnitudes. To address the computational challenges of processing massive data sets and dense orbital phase spaces, we developed a specialized high-performance computing architecture. We demonstrate the effectiveness of our method through experiments that take advantage of the extensive computational resources at Lawrence Livermore National Laboratory. This work enables the detection of significantly fainter asteroids in existing and future survey data, potentially increasing the observable asteroid population by orders of magnitude across different orbital families, from near-Earth objects (NEOs) to Kuiper belt objects (KBOs).

Asteroid discovery↗

Airborne Lidar Measurements of XCO 2 in Synoptically Active Environment and Associated Comparisons With Numerical Simulations

Frontal boundaries have been shown to cause large changes in CO 2 mole-fractions, but clouds and the complex vertical structure of fronts make these gradients difficult to observe. It remains unclear how the column average CO 2 dry air mole-fraction (XCO 2 ) changes spatially across fronts, and how well airborne lidar observations, data assimilation systems, and numerical models without assimilation capture XCO 2 frontal contrasts (ΔXCO 2 , i.e., warm minus cold sector average of XCO 2 ). We demonstrated the potential of airborne Multifunctional Fiber Laser Lidar (MFLL) measurements in heterogeneous weather conditions (i.e., frontal environment) to investigate the ΔXCO 2 during four seasonal field campaigns of the Atmospheric Carbon and Transport-America (ACT-America) mission. Most frontal cases in summer (winter) reveal higher (lower) XCO 2 in the warm (cold) sector than in the cold (warm) sector. During the transitional seasons (spring and fall), no clear signal in ΔXCO 2 was observed. Intercomparison among the MFLL, assimilated fields from NASA's Global Modeling and Assimilation Office (GMAO), and simulations from the Weather Research and Forecasting-—Chemistry (WRF-Chem) showed that (a) all products had a similar sign of ΔXCO 2 though with different levels of agreement in ΔXCO 2 magnitudes among seasons; (b) ΔXCO 2 in summer decreases with altitude; and (c) significant challenges remain in observing and simulating XCO 2 frontal contrasts. A linear regression analyses between ΔXCO 2 for MFLL versus GMAO, and MFLL versus WRF-Chem for summer-2016 cases yielded a correlation coefficient of 0.95 and 0.88, respectively. The reported ΔXCO 2 variability among four seasons provide guidance to the spatial structures of XCO 2 transport errors in models and satellite measurements of XCO 2 in synoptically-active weather systems.

54 ENVIRONMENTAL SCIENCES↗

Contrasting characteristics of open- and closed-cellular stratocumulus cloud in the eastern North Atlantic

Abstract. Extensive regions of marine boundary layer cloud impact the radiative balance through their significant shortwave albedo while having little impact on outgoing longwave radiation. Despite this importance, these cloud systems remain poorly represented in large-scale models due to difficulty in representing the processes that drive their life cycle and coverage. In particular, the mesoscale organization and cellular structure of marine boundary clouds have important implications for the subsequent cloud feedbacks. In this study, we use long-term (2013–2018) observations from the Atmospheric Radiation Measurement (ARM) Facility's Eastern North Atlantic (ENA) site on Graciosa Island, Azores, Portugal, to identify cloud cases with open- or closed-cellular organization. More than 500 h of each organization type are identified. The ARM observations are combined with reanalysis and satellite products to quantify the cloud, precipitation, aerosol, thermodynamic, and large-scale synoptic characteristics associated with these cloud types. Our analysis shows that both cloud organization populations occur during similar sea surface temperature conditions, but the open-cell cases are distinguished by stronger cold-air advection and large-scale subsidence compared to the closed-cell cases, consistent with their formation during cold-air outbreaks. We also find that the open-cell cases were associated with deeper boundary layers, stronger low-level winds, and higher rain rates compared to their closed-cell counterparts. Finally, raindrops with diameters larger than 1 mm were routinely recorded at the surface during both populations, with a higher number of large drops during the open-cellular cases. The similarities and differences noted herein provide important insights into the environmental and cloud characteristics during varying marine boundary layer cloud mesoscale organization and will be useful for the evaluation of model simulations for ENA marine clouds.

54 ENVIRONMENTAL SCIENCES↗