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At least 217 records · Page 12

The Development of Midlatitude Cirrus Models for MODIS Using FIRE-I, FIRE-II, and ARM In Situ Data

Detailed in situ data from cirrus clouds have been collected during dedicated field Campaigns, but the use of the size and habit distribution data has been lagging in the development of more realistic cirrus scattering models. In this study, the authors examine the use of in situ cirrus data collected during three field campaigns to develop more realistic midlatitude cirrus microphysical models. Data are used from the First International Satellite Cloud Climatology Project (ISCCP) Regional Experiment (FIRE)-I (1986) and FIRE-II (1991) campaigns and from a recent Atmospheric Radiation Measurement (ARM) Program campaign held in March-April of 2000. The microphysical models are based on measured vertical distributions of both particle size and particle habit and are used to develop new scattering models for a suite of moderate-resolution imaging spectroradiometer (MODIS) bands spanning visible. near-infrared, and infrared wavelengths. The sensitivity of the resulting scattering properties to the underlying assumptions of the assumed particle size and habit distributions are examined. It is found that the near-infrared bands are sensitive not only to the discretization of the size distribution but also to the assumed habit distribution. In addition. the results indicate that the effective diameter calculated from a given size distribution tends to be sensitive to the number of size bins that are used to discretize the data and also to the ice-crystal habit distribution.

Nasiri, Shaima L.↗

Formation of Cirrus Clouds near the Tropical Tropopause and Their Implications for Stratospheric Humidity, Radiation Budgets, and Climate

Optically-thin cirrus clouds are a nearly ubiquitous feature of the transition layer between the tropical troposphere and stratosphere (known as the Tropical Tropopause Layer). Given their high occurrence frequency, these clouds have significant impacts on the Earth's radiation budget, with a particularly strong influence on the outgoing longwave radiation. Further, ice crystal growth and sedimentation in these clouds dehydrates air in the cold TTL to very low water vapor mixing ratios. Since transport from the troposphere into the stratosphere occurs primarily through the tropical tropopause and the Brewer-Dobson circulation transports air from the TTL throughout the stratosphere, cloud processes in the TTL cold trap essentially regulate the humidity of the entire stratosphere. It has been shown that even small changes in stratospheric humidity can have significant impacts on the Earth's radiation budget and climate, with magnitudes comparable to anthropogenic changes in greenhouse gases. The humidity of air crossing the TTL cold trap depends to first order on tropical tropopause temperatures, but also on deep convection reaching the TTL, large-scale transport (in balance with TTL radiative heating), atmospheric waves, and cloud microphysical processes. Gaps in our understanding of TTL transport and cloud processes motivated the NASA Airborne Tropical TRopopause EXperiment (ATTREX). ATTREX used the long-range (16,000 km), high-altitude (20 km) Global Hawk unmanned aircraft system equipped with twelve instruments measuring clouds, water vapor, meteorological conditions, chemical tracers, chemical radicals, and radiation. I will discuss the physics of TTL cirrus formation and the impact of these clouds on water vapor and radiation budgets, including new results emerging from the ATTREX measurements.

Jensen, Eric↗

Constraints on PSC Particle Microphysics Derived From Lidar Observations

Based on extensive T-matrix computations of light scattering by polydispersions of randomly oriented, rotationally symmetric nonspherical particles, we analyze existing lidar observations of polar stratospheric clouds (PSCs) and derive several constraints on PSC particle microphysical properties. We show that sharp-edged nonspherical particles (finite circular cylinders) exhibit less variability of lidar backscattering characteristics with particle size and aspect ratio than particles with smooth surfaces (spheroids). For PSC particles significantly smaller than the wavelength, the backscatter color index Alpha and the depolarization color index Beta are essentially shape-independent. Observations for type Ia PSCs can be reproduced by spheroids with aspect ratios larger than 1.2, oblate cylinders with diameter-to-length ratios greater than 1.6, and prolate cylinders with length-to-diameter ratios greater than 1.4. The effective equal-volume-sphere radius for type la PSCs is about 0.8 microns or larger. Type Ib PSCs are likely to be composed of spheres or nearly spherical particles with effective radii smaller than 0.8 microns. Observations for type II PSCs are consistent with large ice crystals (effective radius greater than 1 micron modeled as cylinders or prolate spheroids.

Liu, Li↗

Single-Scattering Properties of Melting Precipitation for GPM Passive Microwave and Radar Remote Sensing Applications

Over the past two decades, detailed computational simulations of the intricate three dimensional structures of ice-phase crystals and aggregates of those crystals have been developed. The microwave single-scattering properties of these simulated ice particles have been computed and used to improve quantitative estimates of snow rates and to better deRne the vertical structure of snow water contents in deep convective systems, as derived from satellite-borne passive microwave and/or radar remote sensing measurements. The same icephase particles have more recently been used as the starting point for simulations of melting precipitation using computational melting methods. In the current study, a heuristic melting method, as well as a physically-based melting procedure based on smoothed-particle hydrodynamics, are applied to ice particle models to describe the full evolution of the particles from dry snow to liquid drops. The discrete dipole approximation is utilized to calculate the single-scattering properties of the mixed-phase particles throughout the melting process. Then, the properties of the particles are “mapped” into simpliRed microphysical simulations of particle size spectra in the melting layers of stratiform, precipitating clouds. The bulk single-scattering properties of the melting layers and the sensitivity of their properties to modeling assumptions are explored, and the implications for combined radar-radiometer precipitation remote sensing from GPM are discussed.

William S Olson↗

The Microwave Radiative Properties of Falling Snow Derived from Nonspherical Ice Particle Models. Part II: Initial Testing Using Radar, Radiometer and In Situ Observations

In this study, two different particle models describing the structure and electromagnetic properties of snow are developed and evaluated for potential use in satellite combined radar-radiometer precipitation estimation algorithms. In the first model, snow particles are assumed to be homogeneous ice-air spheres with single-scattering properties derived from Mie theory. In the second model, snow particles are created by simulating the self-collection of pristine ice crystals into aggregate particles of different sizes, using different numbers and habits of the collected component crystals. Single-scattering properties of the resulting nonspherical snow particles are determined using the discrete dipole approximation. The size-distribution-integrated scattering properties of the spherical and nonspherical snow particles are incorporated into a dual-wavelength radar profiling algorithm that is applied to 14- and 34-GHz observations of stratiform precipitation from the ER-2 aircraft-borne High-Altitude Imaging Wind and Rain Airborne Profiler (HIWRAP) radar. The retrieved ice precipitation profiles are then input to a forward radiative transfer calculation in an attempt to simulate coincident radiance observations from the Conical Scanning Millimeter-Wave Imaging Radiometer (CoSMIR). Much greater consistency between the simulated and observed CoSMIR radiances is obtained using estimated profiles that are based upon the nonspherical crystal/aggregate snow particle model. Despite this greater consistency, there remain some discrepancies between the higher moments of the HIWRAP-retrieved precipitation size distributions and in situ distributions derived from microphysics probe observations obtained from Citation aircraft underflights of the ER-2. These discrepancies can only be eliminated if a subset of lower-density crystal/aggregate snow particles is assumed in the radar algorithm and in the interpretation of the in situ data.

Ice particles; Radiances; Radiative transfer; Airc↗

Microphysical Properties of Tropical Tropopause Layer Cirrus

Pervasive cirrus clouds in the tropical tropopause layer (TTL) play an important role in determining the composition of stratospheric air through dehydration of tropospheric air entering the stratosphere. This dehydration affects Earth's energy budget and climate, yet uncertainties remain regarding the microphysical processes that govern TTL cirrus. TTL cirrus were sampled with the NASA Global Hawk UAV for over 30 hr in the Western Pacific in 2014 during the Airborne Tropical TRopopause EXperiment. In situ measurements by a Fast Cloud Droplet Probe and Hawkeye probe (combination Fast Cloud Droplet Probe, Two‐Dimensional Stereo optical array probe, and Cloud Particle Imager) provided particle concentrations and sizing between 1‐ and 1,280‐μm diameter and high resolution images for habit identification. We present the variability in ice concentrations, size distributions, and habits as functions of temperature, altitude, and time since convective influence. Observed ice particles were predominantly small and quasi‐spheroidal in shape, with the percentage of quasi‐spheroids increasing with decreasing temperature. In comparison to the large fraction of the population consisting of quasi‐spheroids, faceted habits (columns, plates, rosettes, and budding rosettes) constituted a smaller percentage of the overall population and exhibited the opposite correlation with temperature. The trend of higher percentages of faceted crystals occurring at warmer temperatures may be due to diffusional growth or aggregation as particles descend through cloud, and/or the more rapid diffusional growth rate at warmer temperatures. Sampling was typically well away from deep convection, however, and very few aggregates were observed, so the trend of higher percentages of faceted habits is likely attributable to diffusional growth.

Woods, Sarah↗

Ice Nucleating Particles, Aerosols and Clouds over the Higher Latitude Southern Ocean

Improved understanding of aerosol-cloud-precipitation interactions is a key goal of the DOE-ASR program. Ice Nucleating Particles (INPs) are rare aerosol particles that trigger ice formation in clouds. By doing so they may initiate precipitation in clouds, and this impacts cloud lifetime. Nowhere may the role of INPs be manifested so dramatically as in the Southern Ocean (SO). This vast region was the focus of the DOE-ARM MARCUS (Measurement of Aerosols, Radiation and CloUds over the Southern Oceans) and MICRE (Macquarie Island Cloud and Radiation Experiment) campaigns. In the SO, a deficit of INPs has been a leading hypothesis for why liquid clouds persist, which underlays the bias of global climate models in predicting excess shortwave radiation reaching the ocean surface between 55°S and Antarctica. In this study, we used the 6-month acquisition of INP data on four MARCUS cruises from Hobart, Tasmania, to Antarctica, and the single-location full annual INP cycle observed in MICRE, to gain a holistic, quantitative picture of the INP number concentrations as a function of temperature and their variability over SO latitudes from 43°S to Antarctica. Augmenting initial processing of filter collections of aerosol particles during MARCUS and MICRE, additional freezing studies following thermal treatment (to removes INPs associated with microbes) and peroxide treatment (to remove all organics), as well as ionic chemistry and total organic carbon analysis, were applied to samples to improve time and space resolution, and differentiate marine from terrestrial contributions. We also performed Next Generation Sequencing to determine that bacterial composition can tag periods of enhanced and degraded marine organic INPs and the relative lack of occurrence of land-sourced bio-particles. Through these and other analyses, INP data were categorized into representative source types (e.g., marine versus terrestrially-influenced). The products of our analyses are being used to parameterize ice formation for use in numerical modeling studies to determine if, and when, ocean-derived INPs control the microphysical composition and radiative balance of SO clouds in a manner not presently captured by global models. The specific objectives and approaches proposed were largely accomplished, including: 1) Additional and value-added chemical and biological analyses of archived samples of aerosols were completed to categorize and quantify INP types and concentrations over the SO. 2) Analyses were completed to place INP data in meteorological and aerosol context. 3) Sea spray aerosol INPs were demonstrated to dominate the SO region in all but episodic events. 4) New parameterizations for INP sources relevant to the SO were constructed. 5) Collaborative modeling studies demonstrating the crucial role of INPs in determining cloud radiative and precipitation properties were conducted with MARCUS and MICRE partners. Collaborative publication submissions in this regard ensued within the two year study. This work will advance the science of interactions of aerosols, clouds and precipitation, to improve their representation in regional and global climate models. Results have informed representation of primary ice crystal nucleation, give inference to the role of secondary processes, and improve investigations of aerosol influences on clouds via ice nucleation over SO high latitudes and similar vast ocean regions. Application will improve representation of such interactions for clouds in both regional and global climate models. The data base and analyses methods applied will continue to serve research studies in the future.

58 GEOSCIENCES↗

Direct Comparisons Between GPM-DPR and CloudSat Snowfall Retrievals

Two spaceborne radars currently in orbit enable the sampling of snowfall near the surface and throughout the atmospheric column, namely, CloudSat’s Cloud Profiling Radar (CPR) and the Global Precipitation Measurement mission’s Dual-Frequency Precipitation Radar (GPM-DPR). In this paper, a direct comparison of the CPR’s 2C-SNOW-PROFILE (2CSP), the operational GPM-DPR algorithm (2ADPR) and a neural network (NN) retrieval applied to the GPM-DPR data is performed using coincident observations between both radars. Examination of over 3500 profiles within moderate to strong precipitation (Ka band ≥ 18 dBZ) show that the NN retrieval provides the closest retrieval of liquid equivalent precipitation rate R immediately above the melting level to the R retrieved just below the melting layer, agreeing within 5%. Meanwhile, 2CSP retrieves a maximum value of R at −15°C, decreases by 35% just above the melting layer, and is about 50% smaller than the GPM-DPR retrieved R below the melting layer. CPR-measured reflectivity shows median reduction of 2–3 dB from −15° to −2.5°C, likely the reason for the 2CSP retrieval reduction of R . Two case studies from NASA field campaigns [i.e., Olympic Mountains Experiment (OLYMPEX) and Investigation of Microphysics and Precipitation for Atlantic Coast-Threatening Snowstorms (IMPACTS)] provide analogs to the type of precipitating systems found in the comparison between retrieval products. For the snowfall events that GPM-DPR can observe, this work suggests that the 2CSP retrieval is likely underestimating the unattenuated reflectivity, resulting in a potential negative, or low, bias in R . Future work should investigate how frequently the underestimated reflectivity profiles occur within the CPR record and quantify its potential effects on global snowfall accumulation estimation.

Atmosphere↗

Convective Influence on the Humidity and Clouds in the Tropical Tropopause Layer During Boreal Summer

The impact of convection on the humidity and clouds in the tropical tropopause layer (TTL) during boreal summer 2007 is investigated in simulations of detailed cloud microphysical processes and their effects on the water vapor (H2O) profile along backward trajectories from the 379 K potential temperature (100‐hPa pressure) surface. Convective influence is determined by tracing the trajectories through time‐dependent fields of satellite‐based convective cloud top height. The simulated H2O mixing ratios at the 100‐hPa level and cloud occurrence fractions in the middle to upper (16–18 km) TTL exhibit a pronounced maximum over the Asian monsoon region as in observations; these local enhancements are virtually absent in the simulation without convection, indicating that convection is the dominant driver of the localized H2O and cloud maxima in the Asian summer monsoon region. Convection moistens the 100‐hPa level by 0.6 ppmv (~15%) averaged over the 10°S–50°N domain and increases tropical (10°S–30°N) mean cloud occurrence in the middle to upper TTL by ~170%. Nearly all of the convective enhancements in H2O and clouds are due to the effect of convective saturation; convectively detrained ice crystals have negligible impact. Parcels are most frequently hydrated by deep convection in the southern sector of the Asian monsoon anticyclone and subsequently dehydrated downstream of convection to the west, shifting the locations of final dehydration northwest of the cold temperature region in the northern Tropics. Infrequent, extreme deep convective systems (cloud tops exceeding 380 K) have a disproportionately large effect on TTL humidity and clouds.

Humidity↗

The Cloud Radar System

Improvement in our understanding of the radiative impact of clouds on the climate system requires a comprehensive view of clouds including their physical dimensions, dynamical generation processes, and detailed microphysical properties. To this end, millimeter vave radar is a powerful tool by which clouds can be remotely sensed. The NASA Goddard Space Flight Center has developed the Cloud Radar System (CRS). CRS is a highly sensitive 94 GHz (W-band) pulsed-Doppler polarimetric radar that is designed to fly on board the NASA high-altitude ER-2 aircraft. The instrument is currently the only millimeter wave radar capable of cloud and precipitation measurements from above most all clouds. Because it operates from high-altitude, the CRS provides a unique measurement perspective for cirrus cloud studies. The CRS emulates a satellite view of clouds and precipitation systems thus providing valuable measurements for the implementation and algorithm validation for the upcoming NASA CloudSat mission that is designed to measure ice cloud distributions on the global scale using a spaceborne 94 GHz radar. This paper describes the CRS instrument and preliminary data from the recent Cirrus Regional Study of Tropical Anvils and Cirrus Layers - Florida Area Cirrus Experiment (CRYSTAL-FACE). The radar design is discussed. Characteristics of the radar are given. A block diagram illustrating functional components of the radar is shown. The performance of the CRS during the CRYSTAL-FACE campaign is discussed.

Racette, Paul↗

Satellite Remote Sensing of Tropical Precipitation and Ice Clouds for GCM Verification

This project, supported by the NASA New Investigator Program, has primarily been funding a graduate student, Darren McKague. Since August 1999 Darren has been working part time at Raytheon, while continuing his PhD research. Darren is planning to finish his thesis work in May 2001, thus some of the work described here is ongoing. The proposed research was to use GOES visible and infrared imager data and SSM/I microwave data to obtain joint distributions of cirrus cloud ice mass and precipitation for a study region in the Eastern Tropical Pacific. These joint distributions of cirrus cloud and rainfall were to be compared to those from the CSU general circulation model to evaluate the cloud microphysical amd cumulus parameterizations in the GCM. Existing algorithms were to be used for the retrieval of cloud ice water path from GOES (Minnis) and rainfall from SSM/I (Wilheit). A theoretical study using radiative transfer models and realistic variations in cloud and precipitation profiles was to be used to estimate the retrieval errors. Due to the unavailability of the GOES satellite cloud retrieval algorithm from Dr. Minnis (a co-PI), there was a change in the approach and emphasis of the project. The new approach was to develop a completely new type of remote sensing algorithm - one to directly retrieve joint probability density functions (pdf's) of cloud properties from multi-dimensional histograms of satellite radiances. The usual approach is to retrieve individual pixels of variables (i.e. cloud optical depth), and then aggregate the information. Only statistical information is actually needed, however, and so a more direct method is desirable. We developed forward radiative transfer models for the SSM/I and GOES channels, originally for testing the retrieval algorithms. The visible and near infrared ice scattering information is obtained from geometric ray tracing of fractal ice crystals (Andreas Macke), while the mid-infrared and microwave scattering is computed with Mie scattering. The radiative transfer is performed with the Spherical Harmonic Discrete Ordinate Method (developed by the PI), and infrared molecular absorption is included with the correlated k-distribution method. The SHDOM radiances have been validated by comparison to version 2 of DISORT (the community "standard" discrete-ordinates radiative transfer model), however we use SHDOM since it is computationally more efficient.

Evans, K. Franklin↗

Measurements of upper troposheric humidity at low temperatures during CRYSTAL-FACE

Aircraft condensation trails (contrails) and thin cirrus were studied by instruments on the NASA WB-57F high-altitude aircraft during contrails and optically thing cirrus are contrasted by different levels of supersaturation with respect to ice. During the July 13, 2002, flight of the WB-57F aircraft intercepted visible contrails produced by both the WB-57F and ER-2 aircraft. These contrails were located immediately below the local tropopause, where ambient temperatures were very low (-76 degree C). The contrails were clearly indicated by an abrupt increase in NO and a simultaneous, abrupt decrease in ice supersaturation. With in the contrail, the relative humidity was close to 130% with respect to ice, higher than expected from theory. Outside the contrails was a persistent layer of subvisible currus extending from approximately 13 to 15 km altitude. This layer was characterized y significant supersaturations because the ambient concentrations of ice particles were insufficient to significantly deplete the ice supersaturation. We will discuss in situ measurements and models simulations of humidity.

water vapor↗

Towards an Optimal Estimation Retrieval of Cirrus Cloud Optical and Microphysical Properties Using Hyperspectral Shortwave Instruments and A Fast Radiative Transfer Algorithm

Cirrus cloud retrieval products (here, cloud optical depth, effective particle size, and cloud top height) are important inputs into numerical weather and climate models. Uncertainties in such retrieval products, as a matter of course, propagate downstream, impacting model calculations. Improvements in high-quality global cirrus cloud optical and microphysical data products from satellite observations are needed to understand and reduce retrieval uncertainties. Hyperspectral shortwave instruments produce high-resolution and information-dense spectra, thus offering the opportunity to reduce uncertainties in retrieval products. We are in the process of developing a retrieval that uses the very fast Principal Component Radiative Transfer Model in the solar spectral region (PCRTM-Solar) in the forward model calculations. This retrieval will use measured reflectances from the NASA Earth Surface Mineral Dust Source Investigation (EMIT) and the forthcoming Climate Absolute Radiance and Refractivity Observatory Pathfinder (CLARREO-Pathfinder) instruments. In this manuscript we present progress towards a reference retrieval employing a widely used, verified, accurate, yet computationally slower radiative transfer modeling technique. The reference retrieval, while too slow for using the complete hyperspectral measurement, will allow us to study the behavior of retrieval products and help us verify results from our in-development fast retrieval. Both retrievals will use the optimal estimation retrieval framework. In this manuscript we present results from an uncertainty analysis considering three uncertainty sources for a cirrus cloud retrieval in the form of error covariance matrices: reflectance uncertainty due to water vapor, the reflectance uncertainty due to ice crystal scattering assumptions, and the instrument measurement uncertainty. Results show that the uncertainty due to habit selection is the largest, while that due to water vapor is at most 0.6% relative to channel reflectance. As a first step, the retrieval is being designed for single layer ice clouds over open ocean water.

Cirrus cloud↗

Dynamical Conditions of Ice Supersaturation and Ice Nucleation in Convective Systems: A Comparative Analysis Between in Situ Aircraft Observations and WRF Simulations

Occurrence frequency and dynamical conditions of ice supersaturation (ISS, where relative humidity with respect to ice (RHi) greater than 100%) are examined in the upper troposphere around convective activity. Comparisons are conducted between in situ airborne observations and the Weather Research and Forecasting model simulations using four double-moment microphysical schemes at temperatures less than or or equal to -40degdegC. All four schemes capture both clear-sky and in-cloud ISS conditions. However, the clear-sky (in-cloud) ISS conditions are completely (significantly) limited to the RHi thresholds of the Cooper parameterization. In all of the simulations, ISS occurrence frequencies are higher by approximately 3-4 orders of magnitude at higher updraft speeds (greater than 1 m s(exp -1) than those at the lower updraft speeds when ice water content (IWC) greater than 0.01 gm(exp -3), while observations show smaller differences up to approximately 1-2 orders of magnitude. The simulated ISS also occurs less frequently at weaker updrafts and downdrafts than observed. These results indicate that the simulations have a greater dependence on stronger updrafts to maintain/generate ISS at higher IWC. At lower IWC (less than or equal or 0.01 gm(exp -3), simulations unexpectedly show lower ISS frequencies at stronger updrafts. Overall, the Thompson aerosol-aware scheme has the closest magnitudes and frequencies of ISS greater than 20% to the observations, and the modified Morrison has the closest correlations between ISS frequencies and vertical velocity at higher IWC and number density. The Cooper parameterization often generates excessive ice crystals and therefore suppresses the frequency and magnitude of ISS, indicating that it should be initiated at higher ISS (e.g.,lees than or equal to 25%).

D’Alessandro, John J.↗

Ice and Supercooled Liquid Water Distributions over the Southern Ocean based on In Situ Observations and Climate Model Simulations

Three climate models are evaluated using in situ airborne observations from the Southern Ocean Clouds, Radiation, Aerosol Transport Experimental Study (SOCRATES) campaign. The evaluation targets cloud phases, microphysical properties, thermodynamic conditions, and aerosol indirect effects from –40°C to 0°C. Compared with 580-s averaged observations (i.e., 100 km horizontal scale), the Community Atmosphere Model version 6 (CAM6) shows the most similar result for cloud phase frequency distribution and allows more liquid-containing clouds below –10°C compared with its predecessor—CAM5. The Energy Exascale Earth System Model (E3SM) underestimates (overestimates) ice phase frequencies below (above) –20°C. CAM6 and E3SM show liquid and ice water contents (i.e., LWC and IWC) similar to observations from –25°C to 0°C, but higher LWC and lower IWC than observations at lower temperatures. Simulated in-cloud RH shows higher minimum values than observations, possibly restricting ice growth during sedimentation. As number concentrations of aerosols larger than 500 nm (Na 500 ) increase, observations show increases of LWC, IWC, liquid, and ice number concentrations (N liq , N ice ). Number concentrations of aerosols larger than 100 nm (Na 100 ) only show positive correlations with LWC and N liq . From –20°C to 0°C, higher aerosol number concentrations are correlated with lower glaciation ratio and higher cloud fraction. From –40°C to –20°C, large aerosols show positive correlations with glaciation ratio. CAM6 shows small increases of LWC and N liq with Na 500 and Na 100 . E3SM shows small increases of N ice with Na 500 . Altogether, CAM6 and E3SM underestimate aerosol indirect effects on ice crystals and supercooled liquid droplets over the Southern Ocean.

54 ENVIRONMENTAL SCIENCES↗

Winter QPF Sensitivities to Snow Parameterizations and Comparisons to NASA CloudSat Observations

Steady increases in computing power have allowed for numerical weather prediction models to be initialized and run at high spatial resolution, permitting a transition from larger scale parameterizations of the effects of clouds and precipitation to the simulation of specific microphysical processes and hydrometeor size distributions. Although still relatively coarse in comparison to true cloud resolving models, these high resolution forecasts (on the order of 4 km or less) have demonstrated value in the prediction of severe storm mode and evolution and are being explored for use in winter weather events . Several single-moment bulk water microphysics schemes are available within the latest release of the Weather Research and Forecast (WRF) model suite, including the NASA Goddard Cumulus Ensemble, which incorporate some assumptions in the size distribution of a small number of hydrometeor classes in order to predict their evolution, advection and precipitation within the forecast domain. Although many of these schemes produce similar forecasts of events on the synoptic scale, there are often significant details regarding precipitation and cloud cover, as well as the distribution of water mass among the constituent hydrometeor classes. Unfortunately, validating data for cloud resolving model simulations are sparse. Field campaigns require in-cloud measurements of hydrometeors from aircraft in coordination with extensive and coincident ground based measurements. Radar remote sensing is utilized to detect the spatial coverage and structure of precipitation. Here, two radar systems characterize the structure of winter precipitation for comparison to equivalent features within a forecast model: a 3 GHz, Weather Surveillance Radar-1988 Doppler (WSR-88D) based in Omaha, Nebraska, and the 94 GHz NASA CloudSat Cloud Profiling Radar, a spaceborne instrument and member of the afternoon or "A-Train" of polar orbiting satellites tasked with cataloguing global cloud characteristics. Each system provides a unique perspective. The WSR-88D operates in a surveillance mode, sampling cloud volumes of Rayleigh scatterers where reflectivity is proportional to the sixth moment of the size distribution of equivalent spheres. The CloudSat radar provides enhanced sensitivity to smaller cloud ice crystals aloft, as well as consistent vertical profiles along each orbit. However, CloudSat reflectivity signatures are complicated somewhat by resonant Mie scattering effects and significant attenuation in the presence of cloud or rain water. Here, both radar systems are applied to a case of light to moderate snowfall within the warm frontal zone of a cold season, synoptic scale storm. Radars allow for an evaluation of the accuracy of a single-moment scheme in replicating precipitation structures, based on the bulk statistical properties of precipitation as suggested by reflectivity signatures.

Molthan, Andrew↗

Cloud Microphysics in Hurricane Outflows: Observations in 'Bonnie' (1998) at 12 km Altitude

The water balance of a hurricane is controlled by boundary layer inflow, near vertical motion in the eyewall causing coalescence precipitation at above and residual ice precipitation at below freezing temperatures, and cirrus outflow at below -40 C aloft. In this paper we address the question of efficiency of water removal by this cirrus outflow which is important for the release of latent heat at high altitudes and its role in the dynamic flow at that level. During NASA's 1998 Convection and Moisture Experiment campaign we acquired microphysical outflow data in order to (1) determine the release and redistribution of latent heat near the top of hurricanes, (2) aid in TRMM algorithm development for remote sensing of precipitation, and (3) determine the optical/radiative characteristics of hurricane outflow. The data were acquired with Particle Measuring Systems two dimensional imaging spectrometers. On 23 August and again during the hurricane's landfall on 26 August, 1998, the NASA DC-8 aircraft penetrated hurricane 'Bonnie' four times each near 200 hPa pressure altitude. The eye crossing times were determined by (1) zero counts of cloud particles, (2) approximately 5 C increases in static and potential temperatures, and (3) minima in speeds and changes of direction of horizontal winds. The vertical winds showed shear between -6 m per second and +4 m per second and tangential winds approached 30 m per second in the eyewall. The particle volumes in the eyewall (determined by the pixels the particles shadowed in the direction of flight [x-direction] and normally to it by the number of diodes that they shadowed [y-direction]) ranged between 0.5 and 5.0 cubic centimeters per cubic meter. With a particle density near 0.2 g per cubic centimeter (determined from in situ melting and evaporation on a surface collector), the 1.0 g per meter corresponding mass of cloud ice ranged between 0.27 and 2.7 g per kilograms yielding horizontal fluxes between 8.1 and 81 g per square meters per second. The outflow ice was concentrated in crystals of a modal size of 190 micrometers. The particle size distributions were heavily skewed toward sizes with 98% of all cirrus particles smaller than the modal size comprising, however, only 20% of the mass. Thus the smaller than modal size particles dominantly affected the optical/radiative characteristics of the cloud, whereas the larger than modal size crystals determined the ice mass, hence dominated latent heating. Questions to be addressed relate to the origin of individual ice particles as the hurricane evolved and the likelihood of pristine and aggregate particle formation under the complicated conditions of rotation and outflow in the eyewall.

Pueschel, Rudolf F.↗

A Comprehensive Machine Learning Study to Classify Precipitation Type over Land from Global Precipitation Measurement Microwave Imager (GPM-GMI) Measurements

Precipitation type is a key parameter used for better retrieval of precipitation characteristics as well as to understand the cloud–convection–precipitation coupling processes. Ice crystals and water droplets inherently exhibit different characteristics in different precipitation regimes (e.g., convection, stratiform), which reflect on satellite remote sensing measurements that help us distinguish them. The Global Precipitation Measurement (GPM) Core Observatory’s microwave imager (GMI) and dual-frequency precipitation radar (DPR) together provide ample information on global precipitation characteristics. As an active sensor, the DPR provides an accurate precipitation type assignment, while passive sensors such as the GMI are traditionally only used for empirical understanding of precipitation regimes. Using collocated precipitation type flags from the DPR as the “truth”, this paper employs machine learning (ML) models to train and test the predictability and accuracy of using passive GMI-only observations together with ancillary information from a reanalysis and GMI surface emissivity retrieval products. Out of six ML models, four simple ones (support vector machine, neural network, random forest, and gradient boosting) and the 1-D convolutional neural network (CNN) model are identified to produce 90–94% prediction accuracy globally for five types of precipitation (convective, stratiform, mixture, no precipitation, and other precipitation), which is much more robust than previous similar effort. One novelty of this work is to introduce data augmentation (subsampling and bootstrapping) to handle extremely unbalanced samples in each category. A careful evaluation of the impact matrices demonstrates that the polarization difference (PD), brightness temperature (Tc) and surface emissivity at high-frequency channels dominate the decision process, which is consistent with the physical understanding of polarized microwave radiative transfer over different surface types, as well as in snow and liquid clouds with different microphysical properties. Furthermore, the view-angle dependency artifact that the DPR’s precipitation flag bears with does not propagate into the conical-viewing GMI retrievals. This work provides a new and promising way for future physics-based ML retrieval algorithm development.

machine learning/artificial intelligence↗