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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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At least 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2015

Improving Boundary-layer Turbulence and Cloud Processes in CAM with a Higher-order Turbulence Closure Scheme and ASR Measurement

In this study, a simplified intermediately prognostic higher-order turbulence closure (IPHOC) is implemented in the Community Atmosphere Model, version 5 (CAM5), to provide a consistent treatment of subgrid-scale cloud processes, except for deep convection. The planetary boundary layer (PBL) height is prognosticated to better resolve the discontinuity of temperature and moisture above the PBL top. Singlecolumn model tests show that fluxes of liquid water potential temperature and total water, cloud fraction, and liquid water content are improved with this approach. The simplified IPHOC package replaces the boundary layer dry and moist turbulence parameterizations, the shallow convection parameterization, and the liquid-phase part of the cloud macrophysics parameterization in CAM5. CAM5-IPHOC improves the simulation of the low-level clouds off the west coasts of continents and the storm track region in the Southern Hemisphere (SH). The transition from stratocumulus to cumulus clouds is more gradual. There are also improvements on the cloud radiative forcing, especially shortwave, in the subsidence regime. The improvements in the relationships among low cloud amount, surface relative humidity, lower tropospheric stability, and PBL depth are seen in some stratocumulus regions. CAM5-IPHOC, however, produces weaker precipitation at the South Pacific convergence zone than CAM5 because of less energy flux into the SH atmosphere. The more downward surface shortwave radiative cooling and the less top-of-theatmosphere longwave cloud radiative heating in the SH relative to the Northern Hemisphere explains the anomalous cooling and the lesser energy flux into the SH, which is related to the underestimate of extratropical middle/high clouds in the SH.

58 GEOSCIENCES↗
DOE OSTI2011

ISDAC Microphysics

Best estimate of cloud microphysical parameters derived using data collected by the cloud microphysical probes installed on the National Research Council (NRC) of Canada Convair-580 during ISDAC. These files contain phase, liquid and ice crystal size distributions (Nw(D) and Ni(D) respectively), liquid water content (LWC), ice water content (IWC), extinction of liquid drops (bw), extinction of ice crystals (bi), effective radius of water drops (rew) and of ice crystals (rei) and median mass diameter of liquid drops (Dmml) and of ice crystals (Dmmi) at 30 second resolution.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2013

In-Situ Microphysics from the RACORO IOP

These files were generated by Greg McFarquhar and Robert Jackson at the University of Illinois. Please contact mcfarq@atmos.uiuc.edu or rjackso2@atmos.uiuc.edu for more information or for assistance in interpreting the content of these files. We highly recommend that anyone wishing to use these files do so in a collaborative endeavor and we welcome queries and opportunities for collaboration. There are caveats associated with the use of the data which are difficult to thoroughly document and not all products for all time periods have been thoroughly examined. This is a value added data set of the best estimate of cloud microphysical parameters derived using data collected by the cloud microphysical probes installed on the Center for Interdisciplinary Remotely-Piloted Aircraft Studies (CIRPAS) Twin Otter during RACORO. These files contain best estimates of liquid size distributions N(D) in terms of droplet diameter D, liquid water content LWC, extinction of liquid drops beta, effective radius of cloud drops (re), total number concentration of droplets NT, and radar reflectivity factor Z at 1 second resolution.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Drizzle, Turbulence, and Density Currents Below Post Cold Frontal Open Cellular Marine Stratocumulus Clouds

Nine cases of postcold frontal marine stratocumulus clouds exhibiting open cellular mesoscale organization are analyzed to characterize the drizzle, turbulence, and density currents below them. Data collected by the vertically pointing Doppler cloud radar and multiple lidars part of the Atmospheric Radiation Measurement (ARM) Eastern North Atlantic (ENA) site are used in these analyses. A total of 251 drizzle shafts passed over the site with 76 shafts sampled for more than 15 min by the vertically pointing instruments. On average the drizzle shafts were ~18 km wide with below-cloud drizzle water path of ~40 g m −2 , cloud base rain rate of 7.78 mm day −1 , and cloud base drizzle modal diameter of 393 μm. The widths of the drizzle shafts did not exhibit any relationship with the cloud base rain rate, below-cloud drizzle water path, and the total water removed from the cloud. The downdrafts in the lowest 500 m within the drizzle cells strengthened with increasing cloud base rain rates, while the updrafts within drizzle cells did not exhibit this behavior. On average, the surface air density, pressure, water vapor mixing ratio, and wind speed along the background wind during the drizzle shaft were higher by 1.88 g m −3 , 8.60 Pa, 0.24 g kg −1 , and 1.22 m s −1 , respectively, from their background values. On the other hand, the surface air temperature was lower by 0.43 K during the drizzle shaft than its background value. The coincident measurements highlight the drizzle-turbulence-surface coupling in these cloud systems.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2016

Regime dependence of cloud condensate variability observed at the Atmospheric Radiation Measurement Sites

Microphysical processes and cloud–radiation interaction occur on spatial scales of variability smaller than those represented explicitly in global weather forecasting and climate models. It is therefore necessary to parametrize the unresolved heterogeneity of humidity and cloud condensate in order to predict process rates accurately. Ground‐based observations from the Atmospheric Radiation Measurement sites located in various climatic regions of the world provide a source of high‐temporal‐resolution observations of cloud condensate. A number of different retrieval products for cloud condensate are assessed for the different geographical regions, years and seasons. The retrieval reliability varies with cloud type, but for cloud categories largely unaffected by precipitation a comparison across sites and longer time periods is possible. These observations confirm previously documented variability behaviour as a function of cloud fraction, but also reveal a systematic regime dependence that is not captured by existing parametrizations. Condensate variability measured as a fractional standard deviation (FSD) in warm boundary‐layer clouds is greater in the Tropics than in mid and high latitudes for scenes with comparable cloud type and fraction, with the observed FSD varying from 1.2 in the Tropics to 0.4 in the Arctic. A parametrization of the FSD of cloud liquid condensate based on the grid‐box mean total water amount and cloud fraction is formulated and shown to capture the observed range of FSD values better across different geographical sites and different seasons. The regime dependence of FSD for cirrus cloud is less pronounced than that for liquid clouds and is found largely to agree with FSD values previously derived from satellite observations.

Ahlgrimm, Maike↗
DOE OSTI2018

Characteristic Vertical Profiles of Cloud Water Composition in Marine Stratocumulus Clouds and Relationships With Precipitation

This study uses airborne cloud water composition measurements to characterize the vertical structure of air-equivalent mass concentrations of water-soluble species in marine stratocumulus clouds off the California coast. In this work, a total of 385 cloud water samples were collected in the months of July and August between 2011 and 2016 and analyzed for water-soluble ionic and elemental composition. Three characteristic profiles emerge: (i) a reduction of concentration with in-cloud altitude for particulate species directly emitted from sources below cloud without in-cloud sources (e.g., Cl - , Na + ); (ii) an increase of concentration with in-cloud altitude (e.g., NO 2 - , formate); and (iii) species exhibiting a peak in concentration in the middle of cloud (e.g., non-sea salt SO 4 2- , NO 3 - , organic acids). Vertical profiles of rainout parameters such as loss frequency, lifetime, and change in concentration with respect to time show that the scavenging efficiency throughout the cloud depth depends strongly on the thickness of the cloud. Thin clouds exhibit a greater scavenging loss frequency at cloud top, while thick clouds have a greater scavenging loss frequency at cloud base. The implications of these results for treatment of wet scavenging in models are discussed.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

ARM Data-Oriented Metrics and Diagnostics Package for Climate Model Evaluation

A Python-based metrics and diagnostics package is currently being developed by the U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) Infrastructure Team at Lawrence Livermore National Laboratory (LLNL) to facilitate the use of long-term, high-frequency measurements from the ARM Facility in evaluating the regional climate simulation of clouds, radiation, and precipitation. This metrics and diagnostics package computes climatological means of targeted climate model simulation and generates tables and plots for comparing the model simulation with ARM observational data. The Coupled Model Intercomparison Project (CMIP) model data sets are also included in the package to enable model intercomparison as demonstrated in Zhang et al. (2017). The mean of the CMIP model can serve as a reference for individual models. Basic performance metrics are computed to measure the accuracy of mean state and variability of climate models. The evaluated physical quantities include cloud fraction, temperature, relative humidity, cloud liquid water path, total column water vapor, precipitation, sensible and latent heat fluxes, and radiative fluxes, with plan to extend to more fields, such as aerosol and microphysics properties. Process-oriented diagnostics focusing on individual cloud- and precipitation-related phenomena are also being developed for the evaluation and development of specific model physical parameterizations. The version 1.0 package is designed based on data collected at ARM’s Southern Great Plains (SGP) Research Facility, with the plan to extend to other ARM sites. The metrics and diagnostics package is currently built upon standard Python libraries and additional Python packages developed by DOE (such as CDMS and CDAT). The ARM metrics and diagnostic package is available publicly with the hope that it can serve as an easy entry point for climate modelers to compare their models with ARM data. In this report, we first present the input data, which constitutes the core content of the metrics and diagnostics package in section 2, and a user's guide documenting the workflow/structure of the version 1.0 codes, and including step-by-step instruction for running the package in section 3.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

ARM data-oriented metrics and diagnostics package for climate model evaluation (ARM-DIAGS-V3) version 3

A Python-based metrics and diagnostics package is currently being developed by the ARM Infrastructure Team at Lawrence Livermore National Laboratory to facilitate the use of long-term high frequency measurements from the ARM program in evaluating the regional climate simulation of clouds, radiation, precipitation, and aerosols. This metrics and diagnostics package computes climatological means of targeted climate model simulation and generates tables and plots for comparing the model simulation with ARM observational data. The CMIP model data sets are also included in the package to enable model inter-comparison as demonstrated in Zhang et al. (2018) and Zhang et al. (2020). The mean of the CMIP model can be served as a reference for individual models. Basic performance metrics are computed to measure the accuracy of mean state and variability of climate models. The evaluated physical quantities include cloud fraction, temperature, relative humidity, cloud liquid water path, total column water vapor, precipitation, sensible and latent heat fluxes, aerosol optical depth, and radiative fluxes, with plan to extend to more fields, such as the evaluation of model simulated aerosol physicochemical properties and cloud microphysics properties. Process-oriented diagnostics focusing on aerosol, cloud, and precipitation-related phenomena are also being developed for the evaluation and development of specific model physical parameterizations. In addition to the Southern Great Plains (SGP), North Slope of Alaska (NSA) and Tropical Western Pacific (TWP) atmospheric observatories in the ARMDIAGS version 2.0, the version 3.0 package have extended to the data collected at the ARM Eastern North Atlantic (ENA) atmospheric observatory and the Observation and Modeling of the Green Ocean Amazon (GOAMAZON) field campaign. The metrics and diagnostics package are currently built upon standard Python libraries and additional Python packages developed by DOE (CDAT). The ARM metrics and diagnostic package is available publicly with the hope that it can serve as an easy entry point for climate modelers to compare their models with ARM data. In this report, we first provide an overview of major metrics in section 2. The input data, which constitutes the core content of the metrics and diagnostics package, is summarized in section 3. A user's guide documenting the workflow/structure of the version 3.0 codes and including step-by-step instruction for running the package is described in section 4.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2017

Biogenic, urban, and wildfire influences on the molecular composition of dissolved organic compounds in cloud water

Organic aerosol formation and transformation occurs within aqueous aerosol and cloud droplets, yet little is known about the composition of high molecular weight organic compounds in cloud water. Cloud water samples collected at Whiteface Mountain, New York, during August-September 2014 were analyzed by ultra-high-resolution mass spectrometry to investigate the molecular composition of dissolved organic carbon, with a focus on sulfur- and nitrogen-containing compounds. Organic molecular composition was evaluated in the context of cloud water inorganic ion concentrations, pH, and total organic carbon concentrations to gain insights into the sources and aqueous-phase processes of the observed high molecular weight organic compounds. Cloud water acidity was positively correlated with the average oxygen : carbon ratio of the organic constituents, suggesting the possibility for aqueous acid-catalyzed (prior to cloud droplet activation or during/after cloud droplet evaporation) and/or radical (within cloud droplets) oxidation processes. Many tracer compounds recently identified in laboratory studies of bulk aqueous-phase reactions were identified in the cloud water. Organosulfate compounds, with both biogenic and anthropogenic volatile organic compound precursors, were detected for cloud water samples influenced by air masses that had traveled over forested and populated areas. Oxidation products of long-chain (C 10-12 ) alkane precursors were detected during urban influence. Influence of Canadian wildfires resulted in increased numbers of identified sulfur-containing compounds and oligomeric species, including those formed through aqueous-phase reactions involving methylglyoxal. Light-absorbing aqueous-phase products of syringol and guaiacol oxidation were observed in the wildfire-influenced samples, and dinitroaromatic compounds were observed in all cloud water samples (wildfire, biogenic, and urban-influenced). Overall, the cloud water molecular composition depended on air mass source influence and reflected aqueous-phase reactions involving biogenic, urban, and biomass burning precursors.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2017

Quantification of marine aerosol subgrid variability and its correlation with clouds based on high‐resolution regional modeling

Abstract One limitation of most global climate models (GCMs) is that with the horizontal resolutions they typically employ, they cannot resolve the subgrid variability (SGV) of clouds and aerosols, adding extra uncertainties to the aerosol radiative forcing estimation. To inform the development of an aerosol subgrid variability parameterization, here we analyze the aerosol SGV over the southern Pacific Ocean simulated by the high‐resolution Weather Research and Forecasting model coupled to Chemistry. We find that within a typical GCM grid, the aerosol mass subgrid standard deviation is 15% of the grid‐box mean mass near the surface on a 1 month mean basis. The fraction can increase to 50% in the free troposphere. The relationships between the sea‐salt mass concentration, meteorological variables, and sea‐salt emission rate are investigated in both the clear and cloudy portion. Under clear‐sky conditions, marine aerosol subgrid standard deviation is highly correlated with the standard deviations of vertical velocity, cloud water mixing ratio, and sea‐salt emission rates near the surface. It is also strongly connected to the grid box mean aerosol in the free troposphere (between 2 km and 4 km). In the cloudy area, interstitial sea‐salt aerosol mass concentrations are smaller, but higher correlation is found between the subgrid standard deviations of aerosol mass and vertical velocity. Additionally, we find that decreasing the model grid resolution can reduce the marine aerosol SGV but strengthen the correlations between the aerosol SGV and the total water mixing ratio (sum of water vapor, cloud liquid, and cloud ice mixing ratios).

Lin, Guangxing↗
DOE OSTI2018

Final Technical Report: Moving ASR Cloud Microphysical Retrievals Beyond the Vertical Column

Clouds of all types play important roles in atmospheric heating, surface heating and emission of radiation, hence energy, to space. Clouds not only affect atmospheric heating via their impacts on solar and terrestrial radiation, they also release kinetic energy to the atmosphere when they form and they extract kinetic energy from the atmosphere when they evaporate. To understand the impacts of clouds on weather and climate, one must be able to make accurate observations of the amount of water associated with them and the impact of this water on atmospheric and surface heating rates. One important cloud type is liquid water clouds. Liquid clouds are often found in the boundary layers of Earth at altitudes from just above the surface to approximately 2000 m above it, at a variety of temperatures, including temperatures below the freezing point of liquid water (0 °C). As a result, they are important constituents over the world’s oceans as well as over cold, ice-covered surfaces such as in the Arctic. Observationally estimating the total amount of liquid contained in a column through a liquid water cloud can now be accomplished to acceptable accuracies (except for the thinnest, lowest liquid containing clouds) using instruments called passive microwave radiometers. However, observationally determining the spatial distribution of liquid within these columns has proven to be difficult. The focus of this project was on the application of two radars operating at two different frequencies to retrieve the distribution of liquid water within columns passing through liquid water clouds. Motivation in this project for using two different radars operating at different frequencies is that as overlapping (in space) beams from the two radars pass through the same column of liquid water cloud absorption of power from one beam (the 94-GHz beam) is greater than absorption of power from the other beam (the 35-GHz beam). Therefore, the difference in returned powers between the two radar beams with distance from the radars is proportional to the amount of liquid water that the two beams have passed through. Therefore, one can use the differences in power between the two beams with distance through a liquid water cloud to determine the distribution of liquid water throughout the cloud. The two radars used in this study are the Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) Program Ka-band Scanning ARM Cloud Radar (Ka-SACR) and the W-band Scanning ARM Cloud Radar (W-SACR). When this projected started in 2013, the Ka- and W-band SACRs were new technology, state-of-the-art sensors. To put together a sufficiently diverse and big set of test cases for the study, data from the SACRs deployed to NSA, SGP, TCAP and MAGIC were used, leading to a test set composed of 65 hours of suitable data spread over approximately 17 case study days. Using the Ka- and W-band SACR data from the case study periods, vertical distributions of liquid water content through liquid water clouds were retrieved. Because there are no other data sets with which to compare the retrievals, distributions of liquid water through a column were summed and compared to the total amounts of liquid water obtained by retrievals applied to passive microwave radiometer observations. The total amounts of liquid water (in units of millimeters, or the thickness in millimeters of the total liquid water in a vertical column if allowed to pool at the bottom of the column) between the two retrievals agreed to within 0.060 mm with a standard deviation of 0.31 mm, or to within 0.016 mm with a standard deviation of 0.12 mm once outliers were removed. The standard deviation of 0.12 mm was fairly independent of the total amount of liquid water in the clouds, indicating that retrieval errors were larger for clouds with smaller amounts of liquid in them. Errors in the retrieved total amounts of liquid were also found to be sensitive to the a priori information that was fed into the retrieval approach. Overall, standard deviations of 0.12 mm are sufficient for some cloud studies but for radiation studies standard deviations on the order of 0.02 mm need to be achieved for clouds with the lowest amounts of liquid water. Many modifications to the retrieval approach were tested subsequently in an attempt to reduce the standard deviations relative to the radiometer retrievals below 0.12 mm but none of them worked reliably. We decided to wait until the DOE ARM Program deployed its second generation SACR2s to its NSA and ENA sites for further retrieval evaluation. The SACR2s were engineered to better synchronize data between the Ka- and W-band radars, reducing potential sources of noise for radar retrieval of liquid water distributions within clouds. The SACR2s have improved in reliability recently and the system deployed to ENA is best positioned to provide the data to advance research on this path. This will be an ongoing research activity beyond the project because of the promise in SACR2 data from the DOE ARM ENA Facility.

58 GEOSCIENCES↗
DOE OSTI2012

Indirect radiative forcing by ion-mediated nucleation of aerosol

A clear understanding of particle formation mechanisms is critical for assessing aerosol indirect radiative forcing and associated climate feedback processes. Recent studies reveal the importance of ion-mediated nucleation (IMN) in generating new particles and cloud condensation nuclei (CCN) in the atmosphere. Here we implement for the first time a physically based treatment of IMN into the Community Atmosphere Model version 5. Our simulations show that, compared to globally averaged results based on binary homogeneous nucleation (BHN), the presence of ionization (i.e., IMN) halves H2SO4 column burden, but increases the column integrated nucleation rate by around one order of magnitude, total particle number burden by a factor of ~ 3, CCN burden by ~ 10% (at 0.2% supersaturation) to 65% (at 1.0% supersaturation), and cloud droplet number burden by ~ 18%. Compared to BHN, IMN increases cloud liquid water path by 7.5%, decreases precipitation by 1.1%, and increases total cloud cover by 1.9%. This leads to an increase of total shortwave cloud radiative forcing by 3.67 W/m2 (more negative) and longwave cloud forcing by 1.78 W/m2 (more positive), resulting in a -1.9 W/m2 net change in cloud radiative forcing associated with IMN. The significant impacts of ionization on global aerosol formation, CCN abundance, and cloud radiative forcing may provide an important physical mechanism linking the global energy balance to various processes affecting atmospheric ionization, which should be properly represented in climate models.

aerosol↗
DOE OSTI2019

Sensitivity to Physical and Numerical Aspects of Large-Eddy Simulation of Stratocumulus

Abstract A series of numerical experiments where both physical and numerical model parameters are varied with respect to a reference setup is used to investigate the physics of a stratocumulus cloud and the performance of a large-eddy simulation (LES) model. The simulations show a delicate balance of physical processes with some sensitivities amplified by numerical model features. A strong feedback between cloud liquid, cloud-top radiative cooling, and turbulence leads to slow grid convergence of the turbulent fluxes. For a methodology that diagnoses cloud liquid from conserved variables, small errors in the total water amount result in large liquid water errors, which are amplified by the cloud-top radiative cooling leading to large variations of buoyancy forcing. In contrast, when the liquid–radiation–buoyancy feedback is not present in simulations without radiation, the turbulence structure of the boundary layer remains essentially identical for grid resolutions between 20 and 1.25 m. The present runs suggest that the buoyancy reversal instability significantly enhances the entrainment rate. Even though cloud-top radiative cooling is regarded as a key attribute of stratocumulus, the present simulations suggest that surface fluxes and surface shear significantly contribute to the total turbulent kinetic energy. Turbulence spectra exhibit inertial range scaling away from the confinement effects of the surface and inversion. Fine grid resolution LESs agree with observations, especially with respect to cloud liquid and vertical velocity variance, and exhibit grid convergence without any model tuning or ad hoc model choices.

Matheou, Georgios↗
DOE OSTI2015

Long-lifetime ice particles in mixed-phase stratiform clouds: Quasi-steady and recycled growth

Lagrangian ice particle tracking is applied in both a 3-D time dependent velocity field produced by a Large Eddy Simulation cloud model and in a 2-D idealized field. It is found that more than 10% of ice particles have lifetimes longer than 1.5 hours, much longer than the large eddy turnover time or the time for a crystal to fall through the depth of a non-turbulent cloud. An analysis of trajectories in a 2-D idealized field shows that there are two types of long lifetime ice particles: quasi-steady and recycled growth. For quasi-steady growth, ice particles are suspended in the updraft velocity region for a long time. For recycled growth, ice particles are trapped in the large-eddy structures, and whether ice particles grow or evaporate depends on the ice relative humidity profile within the boundary layer. Some ice particles can grow after each cycle in the trapping region, until they are too large to be trapped, and thus have long lifetimes. Here, the relative contribution of the recycled ice particles to the cloud mean ice water content depends on both the dynamic and thermodynamic properties of the mixing layer. In particular, the total ice water content of a mixed phase cloud in a decoupled boundary layer can be much larger than that in a fully coupled boundary layer.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2012

Supercooled liquid water Estimation Tool

The Cloud Supercooled liquid water Estimation Tool (SEET) is a user driven Graphical User Interface (GUI) that estimates cloud supercooled liquid water (SLW) content in terms of vertical column and total mass from Moderate resolution Imaging Supercooled liquid water Estimation Tool Spectroradiometer (MODIS) spatially derived cloud products and realistic vertical cloud parameterizations that are user defined. It also contains functions for post-processing of the resulting data in tabular and graphical form.

Roskovensky, John↗
DOE OSTI2015

Investigation of the marine boundary layer cloud and CCN properties under coupled and decoupled conditions over the Azores

Here, six coupled and decoupled marine boundary layer (MBL) clouds were chosen from the 19 month Atmospheric Radiation Measurement Mobile Facility data set over the Azores. Thresholds of liquid water potential temperature difference Δθ L < 0.5 K (>0.5 K) and total water mixing ratio difference Δq t < 0.5 g/kg (>0.5 g/kg) below the cloud base were used for selecting the coupled (decoupled) cases. A schematic diagram was given to demonstrate the coupled and decoupled MBL vertical structures and how they associate with nondrizzle, virga, and rain drizzle events. Out of a total of 2676 5 min samples, 34.5% were classified as coupled and 65.5% as decoupled, 36.2% as nondrizzle and 63.8% as drizzle (47.7% as virga and 16.1% as rain), and 33.4% as daytime and 66.6% as nighttime. The decoupled cloud layer is deeper (0.406 km) than coupled cloud layer (0.304 km), and its liquid water path and cloud droplet effective radius (r e ) values (122.1 gm -2 and 13.0 µm) are higher than coupled ones (83.7 gm -2 and 10.4 µm). Conversely, decoupled stratocumuli have lower cloud droplet number concentration (N d ) and surface cloud condensation nucleus (CCN) concentration (N CCN ) (74.5 cm -3 and 150.9 cm -3 ) than coupled stratocumuli (111.7 cm -3 and 216.4 cm -3 ). The linear regressions between r e and N d with N CCN have demonstrated that coupled r e and N d strongly depend on N CCN and have higher correlations (-0.56 and 0.59) with N CCN than decoupled results (-0.14 and 0.25). The MBL cloud properties under nondrizzle and virga drizzle conditions are similar to each other but significantly different to those of rain drizzle.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2014

Investigating ice nucleation in cirrus clouds with an aerosol-enabled Multiscale Modeling Framework

In this study, an aerosol-dependent ice nucleation scheme [Liu and Penner, 2005] has been implemented in an aerosol-enabled multi-scale modeling framework (PNNL MMF) to study ice formation in upper troposphere cirrus clouds through both homogeneous and heterogeneous nucleation. The MMF model represents cloud scale processes by embedding a cloud-resolving model (CRM) within each vertical column of a GCM grid. By explicitly linking ice nucleation to aerosol number concentration, CRM-scale temperature, relative humidity and vertical velocity, the new MMF model simulates the persistent high ice supersaturation and low ice number concentration (10 to 100/L) at cirrus temperatures. The low ice number is attributed to the dominance of heterogeneous nucleation in ice formation. The new model simulates the observed shift of the ice supersaturation PDF towards higher values at low temperatures following homogeneous nucleation threshold. The MMF models predict a higher frequency of midlatitude supersaturation in the Southern hemisphere and winter hemisphere, which is consistent with previous satellite and in-situ observations. It is shown that compared to a conventional GCM, the MMF is a more powerful model to emulate parameters that evolve over short time scales such as supersaturation. Sensitivity tests suggest that the simulated global distribution of ice clouds is sensitive to the ice nucleation schemes and the distribution of sulfate and dust aerosols. Simulations are also performed to test empirical parameters related to auto-conversion of ice crystals to snow. Results show that with a value of 250 μm for the critical diameter, Dcs, that distinguishes ice crystals from snow, the model can produce good agreement to the satellite retrieved products in terms of cloud ice water path and ice water content, while the total ice water is not sensitive to the specification of Dcs value.

54 ENVIRONMENTAL SCIENCES↗