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At least 109 records · Page 6

An Intercomparison of Large‐Eddy Simulations of a Convection Cloud Chamber Using Haze‐Capable Bin and Lagrangian Cloud Microphysics Schemes

Abstract Recent in situ observations show that haze particles exist in a convection cloud chamber. The microphysics schemes previously used for large‐eddy simulations of the cloud chamber could not fully resolve haze particles and the associated processes, including their activation and deactivation. Specifically, cloud droplet activation was modeled based on Twomey‐type parameterizations, wherein cloud droplets were formed when a critical supersaturation for the available cloud condensation nuclei (CCN) was exceeded and haze particles were not explicitly resolved. Here, we develop and adapt haze‐capable bin and Lagrangian microphysics schemes to properly resolve the activation and deactivation processes. Results are compared with the Twomey‐type CCN‐based bin microphysics scheme in which haze particles are not fully resolved. We find that results from the haze‐capable bin microphysics scheme agree well with those from the Lagrangian microphysics scheme. However, both schemes significantly differ from those from a CCN‐based bin microphysics scheme unless CCN recycling is considered. Haze particles from the recycling of deactivated cloud droplets can strongly enhance cloud droplet number concentration due to a positive feedback in haze‐cloud interactions in the cloud chamber. Haze particle size distributions are more realistic when considering solute and curvature effects that enable representing the complete physics of the activation process. Our study suggests that haze particles and their interactions with cloud droplets may have a strong impact on cloud properties when supersaturation fluctuations are comparable to mean supersaturation, as is the case in the cloud chamber and likely is the case in the atmosphere, especially in polluted conditions.

54 ENVIRONMENTAL SCIENCES↗

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↗

Retrieval of Polar Stratospheric Cloud Microphysical Properties from Lidar Measurements: Dependence on Particle Shape Assumptions

A retrieval algorithm has been developed for the microphysical analysis of polar stratospheric cloud (PSC) optical data obtained using lidar instrumentation. The parameterization scheme of the PSC microphysical properties allows for coexistence of up to three different particle types with size-dependent shapes. The finite difference time domain (FDTD) method has been used to calculate optical properties of particles with maximum dimensions equal to or less than 2 mu m and with shapes that can be considered more representative of PSCs on the scale of individual crystals than the commonly assumed spheroids. Specifically. these are irregular and hexagonal crystals. Selection of the optical parameters that are input to the inversion algorithm is based on a potential data set such as that gathered by two of the lidars on board the NASA DC-8 during the Stratospheric Aerosol and Gas Experiment 0 p (SAGE) Ozone Loss Validation experiment (SOLVE) campaign in winter 1999/2000: the Airborne Raman Ozone and Temperature Lidar (AROTEL) and the NASA Langley Differential Absorption Lidar (DIAL). The 0 microphysical retrieval algorithm has been applied to study how particle shape assumptions affect the inversion of lidar data measured in leewave PSCs. The model simulations show that under the assumption of spheroidal particle shapes, PSC surface and volume density are systematically smaller than the FDTD-based values by, respectively, approximately 10-30% and approximately 5-23%.

Reichardt, J.↗

A Comparison Of Cloud Microphysical Properties Derived Using VIRS 3.7 Micron and 1.6 Micron Data

One of the main objectives of the Clouds and the Earth's Radiant Energy System (CERES) project is the retrieval of cloud physical and microphysical properties simultaneously with observations of broadband radiative fluxes. These cloud parameter sare used for three main purposes: 1) to provide data for radiation-cloud climate feedback studies; 2) to provide scene identification data for the construction and application of angular distribution models; and 3) to be used as input to radiative transfer calculations of intra-atmospheric fluxes

Young, David F.↗

A Comparison of Cloud Microphysical and Optical Properties during TOGA-COARE

The impact of cirrus clouds on climate is an issue of research interest currently. Whether cirrus clouds heat or cool the Earth-atmosphere system depends on the cloud shortwave albedo and infrared reflectance and absorptance. These in turn are determined by the size distribution, phase, and composition of particles in the clouds. The TOGA-COARE campaign presented an excellent opportunity to study cirrus clouds and their influence on climate. In this campaign, a microphysics instrument package was flown aboard the DC-8 aircraft at medium altitudes in cirrus clouds. This package included a 2D Greyscale Cloud Particle Probe, a Forward Scattering Spectrometer Aerosol Probe, and an ice crystal replicator. At the same time the ER-2 equipped with a radiation measurement system flew coordinated flight tracks above the DC-8 at very high altitude. The radiation measurement made were short and long wave fluxes, as well as narrowband fluxes, both upwelling and downwelling. In addition LIDAR data is available. The existence of these data sets allows for a the comparison of radiation measurement with microphysical measurements. For example, the optical depth and effective radius retrieved from the ER-2 radiation measurements can be compared to the microphysical data. Conversely, the optical properties and fluxes produced by the clouds can be calculated from the microphysical measurements and compared to those measured aboard the ER-2. The assumptions required to make these comparisons are discussed. Typical microphysical results show a prevalence of micron-sized particles, in addition to the cloud particles that exceed 100 mm. The large number of small particles or "haze" cause the effective cloud radii to shift to smaller sizes, leading to changes in optical parameters.

Strawa, A. W.↗

Atmospheric State, Cloud Microphysics & Radiative Flux

These data contain atmospheric thermodynamics, cloud properties, radiative fluxes and radiative heating rates. The data represent a characterization of the physical state of the atmospheric column compiled on a five-minute temporal and 90m vertical grid. Sources for this information include raw measurements, cloud property and radiative retrievals, retrievals and derived variables from other third-party sources, and radiative calculations using the derived quantities.

54 ENVIRONMENTAL SCIENCES↗

Sensitivity of Multispectral Imager Liquid Water Cloud Microphysical Retrievals to the Index of Refraction

A cloud property retrieved from multispectral imagers having spectral channels in the shortwave infrared (SWIR) and/or midwave infrared (MWIR) is the effective particle radius (CER), a radiatively relevant weighting of the cloud particle size distribution. The physical basis of the CER retrieval is the dependence of SWIR/MWIR cloud reflectance on the cloud particle single scattering absorption, which in turn depends on the complex index of refraction of bulk liquid water (or ice) in addition to the cloud particle size. There is a general consistency in the choice of the liquid water index of refraction by the cloud remote sensing community, largely due to the few available independent datasets and compilations. Here we examine the sensitivity of CER retrievals to the available laboratory index of refraction datasets in the SWIR and MWIR using the retrieval software package that produces NASA’s standard MODIS/VIIRS continuity cloud products. The sensitivity study incorporates two laboratory index of refraction datasets that include measurements at supercooled water temperatures, one in the SWIR [Kou et al., 1993] and one in the MWIR [Wagner et al., 2005]. Neither has been broadly utilized in the cloud remote sensing community. It is shown that these two new datasets can significantly change CER retrievals (e.g., 1-2 μm) relative to common datasets used by the community. Further, index of refraction data for a 265 K water temperature results in more consistent retrievals between the two spectrally distinct 2.2 μm atmospheric window channels on MODIS and VIIRS. As a result, the 265 K values from the SWIR and MWIR index of refraction datasets were adopted for use in the production version of the continuity cloud product. The results indicate the need to better understand temperature-dependent bulk water absorption and uncertainties in these spectral regions.

MODIS↗

Investigation of liquid cloud microphysical properties of deep convective systems: 1. Parameterization raindrop size distribution and its application for stratiform rain estimation

Abstract To investigate liquid‐phase ( T > 3°C) cloud and precipitation microphysical properties within Deep Convective Systems (DCSs), eight DCS cases sampled by the University of North Dakota Citation II research aircraft during Midlatitude Continental Convective Clouds Experiment were selected. A full spectrum of raindrop size distribution (DSD) was constructed from 120 µm to 4000 µm through a combination of two‐dimensional cloud probe (120 to 900 µm) and High Volume Precipitation Spectrometer (900 to 4000 µm) data sets. A total of 1126 five second DSDs have been used to fit to Gamma and Exponential functions within the stratiform rain (SR) regions of DCSs. The Gamma shape μ Γ and slope λ Γ parameters are then compared with those derived from surface disdrometer measurements. The similar μ Γ ‐ λ Γ relationships but different μ Γ and λ Γ value ranges from two independent platforms at different elevations may represent the real nature of DSD shape information in clouds and at the surface. To apply the exponentially fitted DSD parameters to precipitation estimation using Next Generation Weather Radar (NEXRAD) radar reflectivity factor Z e , the terms N 0 E and λ E have been parameterized as a function of Z e using an empirical N 0 E ‐ λ E relationship. The averaged SR rain rate retrieved from this study is almost identical to the surface measurements, while the NEXRAD Q2 precipitation is twice as large. The comparisons indicate that the new DSD parameterization scheme is robust, while the Q2 SR precipitation estimation based on Marshall‐Palmer Z‐R relationship, where a constant DSD intercept parameter ( N 0 E ) was assumed, needs to be improved for heavy precipitation cases.

Wang, Jingyu↗

A Satellite-Based Estimate of Combustion Aerosol Cloud Microphysical Effects over the Arctic Ocean

Climate predictions for the rapidly changing Arctic are highly uncertain, largely due to a poor understanding of the processes driving cloud properties. In particular, cloud fraction (CF) and cloud phase (CP) have major impacts on energy budgets, but are poorly represented in most models, often because of uncertainties in aerosol–cloud interactions. Here, we use over 10 million satellite observations coupled with aerosol transport model simulations to quantify large scale microphysical effects of aerosols on CF and CP over the Arctic Ocean during polar night, when direct and semi-direct aerosol effects are minimal. Combustion aerosols over sea ice are associated with very large (~10W/sq.m) differences in longwave cloud radiative effects at the sea ice surface. However, co-varying meteorological changes on factors such as CF likely explain the majority of this signal. For example, combustion aerosols explain at most 40% of the CF differences between the full dataset and the clean-condition subset, compared to between 57% and 91% of the differences that can be predicted by co-varying meteorology. After normalizing for meteorological regime, aerosol microphysical effects have small but significant impacts on CF, CP, and precipitation frequency on an Arctic-wide scale. These effects indicate that dominant aerosol–cloud microphysical mechanisms are related to the relative fraction of liquid-containing clouds, with implications for a warming Arctic.

Zamora, Lauren M.↗

Cloud microphysics of the giant planets

The characteristic time constants for the atmospheres of the giant planets were compared for the purpose of finding analogs for clouds in the atmospheres of these planets among the several types of cloud systems found on earth. The NH3 clouds on Jupiter and Saturn were found to be weakly precipitating systems, similar to the thicker cirrus clouds on earth, while the H2O clouds were found to be much more massive than the water clouds on earth. The CH4 and H2O clouds on Uranus and Neptune are completely unlike any cloud on earth, being 10 to 100 times more massive than the densest water clouds on earth. It is concluded that, while the microphysical characteristics of the clouds on Jupiter and Saturn are comparable to those of terrestrial stratus and cumulus clouds, the massive clouds on Uranus and Neptune reach conditions unlike anything on earth.

Carlson, Barbara E.↗

Mixed-phase orographic cloud microphysics during StormVEx and IFRACS

Wintertime mixed-phase orographic cloud (MPC) measurements were conducted at the Storm Peak Laboratory (SPL) during the Storm Peak Lab Cloud Property Validation Experiment (StormVEx) and Isotopic Fractionation in Snow (IFRACS) programs in 2011 and 2014, respectively. The data include 92 h of simultaneous measurements of supercooled liquid cloud droplet and ice particle size distributions (PSDs). Average cloud droplet number concentration (CDNC), droplet size (NMD), and liquid water content (LWC) were similar in both years, while ice particle concentration (Ni) and ice water content (IWC) were higher during IFRACS. The consistency of the liquid cloud suggests that SPL is essentially a cloud chamber that produces a consistent cloud under moist, westerly flow during the winter. A variable cloud condensation nuclei (CCN)-related inverse relationship between CDNC and NMD strengthened when the data were stratified by LWC. Some of this variation is due to changes in cloud base height below SPL. While there was a weak inverse correlation between LWC and IWC in the data as a whole, a stronger relationship was demonstrated for a case study on 9 February 2014 during IFRACS. A minimum LWC of 0.05 g m–3 showed that the cloud was not completely glaciated on this day. Erosion of the droplet distribution at high IWC was attributed to the Wegener–Bergeron–Findeisen process as the high IWC was accompanied by a 10-fold increase in Ni. A relationship between large cloud droplet concentration (25–35 µm) and small ice particles (75–200 µm) under cold (<–8 °C) but not warm (>–8 °C) conditions during IFRACS suggests primary ice particle production by contact or immersion freezing. The effect of blowing snow was evaluated from the relationship between wind speed and Ni and by comparing the relative (percent) ice particle PSDs at high and low wind speeds. These were similar, contrary to expectation for blowing snow. However, the correlation between wind speed and ice crystal concentration may support this explanation for high crystal concentrations at the surface. Secondary processes could have contributed to high crystal concentrations but there was no direct evidence to support this. Further experimental work is needed to resolve these issues.

54 ENVIRONMENTAL SCIENCES↗

Application of TRMM PR and TMI Measurements to Assess Cloud Microphysical Schemes in the MM5 Model for a Winter Storm

Seen by the human eye, precipitation particles are commonly drops of rain, flakes of snow, or lumps of hail that reach the ground. Remote sensors and numerical models usually deal with information about large collections of rain, snow, and hail (or graupel --also called soft hail ) in a volume of air. Therefore, the size and number of the precipitation particles and how particles interact, evolve, and fall within the volume of air need to be represented using physical laws and mathematical tools, which are often implemented as cloud and precipitation microphysical parameterizations in numerical models. To account for the complexity of the precipitation physical processes, scientists have developed various types of such schemes in models. The accuracy of numerical weather forecasting may vary dramatically when different types of these schemes are employed. Therefore, systematic evaluations of cloud and precipitation schemes are of great importance for improvement of weather forecasts. This study is one such endeavor; it pursues quantitative assessment of all the available cloud and precipitation microphysical schemes in a weather model (MM5) through comparison with the observations obtained by National Aeronautics and Space Administration (NASA) s and Japan Aerospace Exploration Agency (JAXA) s Tropical Rainfall Measuring Mission (TRMM) precipitation radar (PR) and microwave imager (TMI). When satellite sensors (like PR or TMI) detect information from precipitation particles, they cannot directly observe the microphysical quantities (e.g., water species phase, density, size, and amount etc.). Instead, they tell how much radiation is absorbed by rain, reflected away from the sensor by snow or graupel, or reflected back to the satellite. On the other hand, the microphysical quantities in the model are usually well represented in microphysical schemes and can be converted to radiative properties that can be directly compared to the corresponding PR and TMI observations. This study employs this method to evaluate the accuracy of the simulated radiative properties by the MM5 model with different microphysical schemes. It is found that the representations of particle density, size, and mass in the different schemes in the MM5 model determine the model s performance when predicting a winter storm over the eastern Pacific Ocean. Schemes lacking moderate density particles (i.e. graupel), with snow flakes that are too large, or with excessive mass of snow or graupel lead to degraded prediction of the radiative properties as observed by the TRMM satellite. This study demonstrates the uniqueness of the combination of both an active microwave sensor (PR) and passive microwave sensor (TMI) onboard TRMM on assessing the accuracy of numerical weather forecasting. It improves our understanding of the physical and radiative properties of different types of precipitation particles and provides suggestions for better representation of cloud and precipitation processes in numerical models. It would, ultimately, contribute to answering questions like "Why did it not rain when the forecast says it would?"

Han, Mei↗

The potential effects of volcanic aerosols on cirrus cloud microphysics

The potential impact of volcanic aerosols on nucleation of ice crystals in upper tropospheric cirrus clouds is examined from a microphysical perspective. The sulfuric acid aerosols which form in the stratosphere are presumably transported into the troposphere by sedimentation and tropopause folding. The tropospheric volcanic aerosol size distribution is estimated from 10-micron lidar backscatter and in situ measurements. Microphysical simulations suggest that at temperatures below about -50 C the concentration of ice crystals which nucleate may be as much as a factor of 5 larger when volcanic aerosols are present. The simulations suggest that the presence of volcanic aerosols may increase the net radiative forcing (surface warming) of certain types of cirrus near the tropopause by as much as 8 W/sq m. Further observations are required to determine whether these effects actually occur, and their global impact.

Jensen, Eric J.↗

MLS and CALIOP Cloud Ice Measurements in the Upper Troposphere: A Constraint from Microwave on Cloud Microphysics

This study examines the consistency and microphysics assumptions among satellite ice water content (IWC) retrievals in the upper troposphere with collocated A-Train radiances from Microwave Limb Sounder (MLS) and lidar backscatters from Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP). For the cases in which IWC values are small (less than 10mg m(exp-23)), the cloud ice retrievals are constrained by both MLS 240- and 640- GHz radiances and CALIOP 532-nm backscatter beta(532). From the observed relationships between MLS cloud-induced radiance T(sub cir) and the CALIOP backscatter integrated gamma532 along the MLS line of sight, an empirical linear relation between cloud ice and the lidar backscatter is found: IWC/beta532=0.58+/-0.11. This lidar cloud ice relation is required to satisfy the cloud ice emission signals simultaneously observed at microwave frequencies, in which ice permittivity is relatively well known. This empirical relationship also produces IWC values that agree well with the CALIOP, version 3.0, retrieval at values, less than 10mg m(exp-3). Because the microphysics assumption is critical in satellite cloud ice retrievals, the agreement found in the IWC-beta532 relationships increase fidelity of the assumptions used by the lidar and microwave techniques for upper-tropospheric clouds.

ice water content↗

Simulations of Winter Arctic Clouds and Associated Radiation Fluxes Using Different Cloud Microphysics Schemes in the Polar WRF: Comparisons With CloudSat, CALIPSO, and CERES

Clouds are important for the Arctic climate, but simulating such clouds with numerical models is still challenging. The accuracy of model clouds has not been sufficiently examined due to the harsh Arctic environment obstructing cloud observations, especially during Arctic winters experiencing polar nights. This study compares the Arctic winter clouds simulated by a weather forecast model to cloud observations from active (lidar and radar) satellite instruments. The model successfully produced cloud patterns similar to the satellite observations. However, the choice of the cloud physics module in the model can modify the amount of cloud water significantly enough to affect the simulated surface climate.

54 ENVIRONMENTAL SCIENCES↗

Cloud microphysical properties from multispectral reflectance measurements

Images as well as statistical properties of the cloud optical thickness and effective particle radius derived from reflected solar radiation measurements at 0.75, 1.65, and 2.16 micron are presented. The remote-sensing-derived cloud optical thickness and effective radius are compared with the values inferred from nearly simultaneous in situ microphysical measurements obtained from an aircraft. A good spatial correlation is observed for both the optical thickness and effective radius, it is noted that the remote sensing has a tendency to overestimate the effective radius; the optical thickness is overestimated for small optical thicknesses and underestimated for large optical thicknesses. The marginal probability density functions of optical thickness and effective radius are derived from the remote-sensing results and discussed.

King, Michael D.↗