In situ observations of cloud properties made by airborne probes play a critical role in ice cloud research through their role in process studies, parameterization development, and evaluation of simulations and remote sensing retrievals. To determine how cloud properties vary with environmental conditions, in situ data collected during different field projects processed by different groups must be used. However, because of the diverse algorithms and codes that are used to process measurements, it can be challenging to compare the results. Therefore it is vital to understand both the limitations of specific probes and uncertainties introduced by processing algorithms. Since there is currently no universally accepted framework regarding how in situ measurements should be processed, there is a need for a general reference that describes the most commonly applied algorithms along with their strengths and weaknesses. Methods used to process data from bulk water probes, single-particle light-scattering spectrometers and cloud-imaging probes are reviewed herein, with emphasis on measurements of the ice phase. Particular attention is paid to how uncertainties, caveats, and assumptions in processing algorithms affect derived products since there is currently no consensus on the optimal way of analyzing data. Recommendations for improving the analysis and interpretation of in situ data include the following: establishment of a common reference library of individual processing algorithms, better documentation of assumptions used in these algorithms, development and maintenance of sustainable community software for processing in situ observations, and more studies that compare different algorithms with the same benchmark datasets.

A Bayesian algorithm to retrieve profiles of cloud ice water content (IWC), ice particle size (<i>D</i>_me), and relative humidity from millimeter-wave/submillimeter-wave radiometers is presented. The first part of the algorithm prepares an a priori file with cumulative distribution functions (CDFs) and empirical orthogonal functions (EOFs) of profiles of temperature, relative humidity, three ice particle parameters (IWC, <i>D</i>_me, distribution width), and two liquid cloud parameters. The a priori CDFs and EOFs are derived from CloudSat radar reflectivity profiles and associated ECMWF temperature and relative humidity profiles combined with three cloud microphysical probability distributions obtained from in situ cloud probes. The second part of the algorithm uses the CDF/EOF file to perform a Bayesian retrieval with a hybrid technique that uses Monte Carlo integration (MCI) or, when too few MCI cases match the observations, uses optimization to maximize the posterior probability function. The very computationally intensive Markov chain Monte Carlo (MCMC) method also may be chosen as a solution method. The radiative transfer model assumes mixtures of several shapes of randomly oriented ice particles, and here random aggregates of hexagonal plates, spheres, and dendrites are used for tropical convection. A new physical model of stochastic dendritic snowflake aggregation is developed. The retrieval algorithm is applied to data from the Compact Scanning Submillimeter-wave Imaging Radiometer (CoSSIR) flown on the ER-2 aircraft during the Tropical Composition, Cloud and Climate Coupling (TC4) experiment in 2007. Example retrievals with error bars are shown for nadir profiles of IWC, <i>D</i>_me, and relative humidity, and nadir and conical scan swath retrievals of ice water path and average <i>D</i>_me. The ice cloud retrievals are evaluated by retrieving integrated 94 GHz backscattering from CoSSIR for comparison with the Cloud Radar System (CRS) flown on the same aircraft. The rms difference in integrated backscattering is around 3 dB over a 30 dB range. A comparison of CoSSIR retrieved and CRS measured reflectivity shows that CoSSIR has the ability to retrieve low-resolution ice cloud profiles in the upper troposphere

Abstract. In situ measurements of ice crystal concentrations and sizes made with aircraft instrumentation over the past two decades have often indicated the presence of numerous relatively small (<50 μm diameter) crystals in cirrus clouds. Further, these measurements frequently indicate that small crystals account for a large fraction of the extinction in cirrus clouds. The fact that the instruments used to make these measurements, such as the Forward Scattering Spectrometer Probe (FSSP) and the Cloud Aerosol Spectrometer (CAS), ingest ice crystals into the sample volume through inlets has led to suspicion that the indications of numerous small-crystals could be artifacts of large-crystal shattering on the instrument inlets. We present new aircraft measurements in anvil cirrus sampled during the Tropical Composition, Cloud, and Climate Coupling (TC4) campaign with the 2-Dimensional Stereo (2D-S) probe, which detects particles as small as 10 μm. The 2D-S has detector "arms" instead of an inlet tube, and therefore is expected to be less susceptible to shattering artifacts than instruments such as CAS. In addition, particle inter-arrival times are used to identify and remove shattering artifacts that occur even with the 2D-S probe. The number of shattering artifacts identified by the 2D-S interarrival time analysis ranges from a negligible contribution to an order of magnitude or more enhancement in apparent ice concentration over the natural ice concentration, depending on the abundance of large crystals and the natural small-crystal concentration. The 2D-S measurements in tropical anvil cirrus suggest that natural small-crystal concentrations are typically one to two orders of magnitude lower than those inferred from CAS. The strong correlation between the CAS/2D-S ratio of small-crystal concentrations and large-crystal concentration suggests that the discrepancy is likely caused by shattering of large crystals on the CAS inlet. We argue that past measurements with CAS in cirrus with large crystals present may contain errors due to crystal shattering, and past conclusions derived from these measurements may need to be revisited. Further, we present correlations between CAS spurious concentration and 2D-S large-crystal mass from spatially uniform anvil cirrus sampling periods as an approximate guide for estimating quantitative impact of large-crystal shattering on CAS concentrations in previous datasets. We use radiative transfer calculations to demonstrate that in the maritime anvil cirrus sampled during TC4, small crystals indicated by 2D-S contribute relatively little to cloud extinction, radiative forcing, or radiative heating in the anvils, regardless of anvil age or vertical location in the clouds. While 2D-S ice concentrations in fresh anvil cirrus may often exceed 1 cm−3, and are observed to exceed 10 cm−3 in turrets, they are typically ~0.1 cm−3 and rarely exceed 1 cm−3 (<1.4% of the time) in aged anvil cirrus. It appears that the numerous small crystals detrained from convective updrafts do not persist in the anvil cirrus sampled during TC-4. We hypothesize that isolated occurrences of higher ice concentrations in aged anvil cirrus are caused by ice nucleation driven by gravity waves.

NASA and the FAA conducted two flight campaigns to quantify onboard weather radar measurements with in-situ measurements of high concentrations of ice crystals found in deep convective storms. The ultimate goal of this research was to improve the understanding of high ice water content (HIWC) and develop onboard weather radar processing techniques to detect regions of HIWC ahead of an aircraft to enable tactical avoidance of the potentially hazardous conditions. Both HIWC RADAR campaigns utilized the NASA DC-8 Airborne Science Laboratory equipped with a Honeywell RDR-4000 weather radar and in-situ microphysical instruments to characterize the ice crystal clouds. The purpose of this paper is to summarize how these campaigns were conducted and highlight key results. The first campaign was conducted in August 2015 with a base of operations in Ft. Lauderdale, Florida. Ten research flights were made into deep convective systems that included Mesoscale Convective Systems (MCS) near the Gulf of Mexico and Atlantic Ocean, and Tropical Storms Danny and Erika near the Caribbean Sea. The radar and in-situ measurements from these ten flights were analyzed and correlations defined. Key results included 1) derived relationships between radar reflectivity factor (RRF), Ice Water Content (IWC), and ice particle size distributions, 2) characterization of HIWC conditions at the-50°C and other flight levels, and 3) verification of pilot observations, such as low radar reflectivity factor and pitot and total air temperature (TAT) anomalies. This data set also enabled new pilot radar HIWC detection algorithms to be developed and tested. A second campaign was conducted in August 2018 to test proposed HIWC radar detection algorithms within a new set of storm systems. Seven research flights were conducted from bases of operations in Ft. Lauderdale, Florida; Palmdale, California; and Kona, Hawaii. Flights were made into convective systems over the Gulf of Mexico and into an eastern-Pacific tropical system that developed into Hurricane Lane. Using a new, NASA-developed radar processing technique called "Swerling", regions of HIWC were identified, and estimates of IWC were produced, at distances up to 60 Nm ahead of the NASA DC-8. Subsequently, the DC-8 flew through these regions to acquire the insitu measurements to verify the radar-based IWC estimates.

Coincident radar data with Doppler radar measurements at X, Ku, Ka, and W bands on the NASA ER-2 aircraft overflying the NASA P3 aircraft acquiring in-situ microphysical measurements are used to characterize the relationship between radar measurements and ice microphysical properties. The data were obtained from the Investigation of Microphysics and Precipitation for Atlantic Coast-Threatening Snowstorms (IMPACTS. Direct measurements of the condensed water content as well as coincident Doppler radar measurements were acquired, facilitating improved estimates of ice particle mass, a variable that is an underlying factor for calculating and therefore retrieving the radar reflectivity (Ze), median mass diameter (Dm), particle terminal velocity, and snowfall rate (S). The relationship between the measured ice water content (IWC) and that calculated from the particle size distributions (PSD) using relationships developed in earlier studies, and between the calculated and measured radar reflectivity at the four radar wavelengths, are quantified. Relationships are derived between the measured IWC and properties of the PSD, Dm, Ze at the four radar wavelengths and the dual-wavelength ratio. Because IWC and Ze are measured directly, the coefficients in the mass-dimensional relationship that best match both the IWC and Ze are derived. The relationships developed here, and the mass-dimensional relationship that uses both the measured IWC and Ze to find a best match for both variables, can be used in studies that characterize the properties of wintertime snow clouds.