Mixed-phase Precipitation Research Articles

Should We Conserve Entropy or Energy when Computing CAPE with Mixed-Phase Precipitation Physics?

Abstract The rapidly increasing resolution of global atmospheric reanalysis and climate model datasets necessitates finding methods for computing convective available potential energy (CAPE) both efficiently and accurately. To this end, this article compares two common methods for computing CAPE which conserve either energy or entropy. Inaccuracies in these computations arise from both physical and numerical errors. For instance, computing CAPE with entropy conserved results in physical errors from nonequilibrium phase transitions but minimizes numerical errors because solutions are analytic at each height. In contrast, computing CAPE with energy conserved avoids these physical errors, but accumulates numerical errors that are grid-resolution-dependent because the numerical integration of a differential equation is required. Analysis of CAPE computed with large databases of soundings from the tropical Amazon and midlatitude storm environments shows that physical errors from the entropy method are typically 1%–3% as large as CAPE, which is comparable to the numerical errors from conserving energy with grid spacing of 25 and 250 m using explicit first-order and second-order integration schemes, respectively. Errors in entropy-based CAPE calculations are also insensitive to vertical grid spacing, in contrast to energy-based calculations whose error strongly scales with the grid spacing. It is shown that entropy-based methods are advantageous when intercomparing datasets with differing vertical resolution because they produce accurate and reasonably fast results that are insensitive to grid resolution, whereas a second-order energy-based method is advantageous when analyzing data with a consistent vertical resolution because of its superior computational efficiency. Significance Statement Convective available potential energy (CAPE) is a measure of instability in the atmosphere that helps forecasters and researchers understand when and where thunderstorms will form. The purpose of this article is to identify the most efficient and accurate methods for computing CAPE. Two methods are considered here, one that relates to the entropy (a measure of thermodynamic disorder) of an air parcel and one that relates to the energy of an air parcel. Results indicate that the entropy method is most accurate and insensitive to the resolution of the data used for the calculation (which can vary considerably), whereas the energy method uses the least computation time.

Vertical structures and microphysical mechanisms of winter precipitation over the southwestern mountainous area of China

The vertical structures and microphysical processes of winter precipitation were investigated using comprehensive observations of three PARSIVELs and one MRR during January–March 2022 over the southwestern mountainous area of China. Twelve precipitation events were classified into four precipitation categories, including solid-phase precipitation, mixed-phase precipitation, light liquid-phase precipitation and heavy liquid-phase precipitation. Statistics reveal that, the majority of winter precipitation originates from snowflakes, with significantly higher precipitation top altitudes in liquid-phase precipitation compared to solid-phase and mixed-phase precipitation. Among the four different precipitation categories, there are distinct layers in which different microphysical processes dominate. For solid-phase precipitation, there is single solid-phase layer with few phase-type transitions, increased reflectivity (Ze) and precipitation rate (R) above 2.1 km altitude are likely affected by deposition and aggregation growth of snowflakes, increased fall velocity (Vf) and dispersed spectral width (Vsw) below 2.1 km altitude might suggest that most snowflakes rime into graupel and a few snowflakes melt. For mixed-phase precipitation, there are two distinct phase-type layers with weak phase-type transitions; in solid-phase layer (above 2.1 km altitude), accompanied by decreased Ze and R, decreased (increased) proportion of liquid-phase/mixed-phase hydrometeors above (below) 4.5 km altitude is likely attributed to refreezing/sublimation with fragmentation (sublimation); in mixed-phase layer (below 2.1 km altitude), significantly increased Vf and more dispersed Vsw suggest that snowflakes rime/melt into graupel, mixed-phase and liquid-phase hydrometeors. Although both light and heavy liquid-phase precipitation are divided into three distinct phase-type layers with remarkable phase-type transitions, significant differences exist in their vertical structures: first, heavy liquid-phase precipitation exhibits substantially higher precipitation top altitudes and a greater abundance of supercooled hydrometeors, resulting more active microphysical processes and noticeable increases of Ze and R at all altitudes; second, in melting layer, Ze in light liquid-phase precipitation initially increases and then decreases, known as bright band signature, however, Ze in heavy liquid-phase precipitation continuously increases due to enhanced melting and collision processes; third, in liquid-phase layer, both Ze and R in light liquid-phase precipitation show decreasing trends due to evaporation or break-up process, while Ze and R in heavy liquid-phase precipitation show remarkable increasing trends attributed to collision coalescence processes. Moreover, there are significant differences in ground particle size distributions, with small-size high-concentration hydrometeors in solid-phase precipitation, medium-size medium-concentration hydrometeors in mixed-phase precipitation, small-size low-concentration hydrometeors in light liquid-phase precipitation, and large-size high-concentration hydrometeors in heavy liquid-phase precipitation, resulting different Z-R relationships among the four precipitation categories.

An Airborne Multifrequency Microwave Analysis of Precipitation within Two Winter Cyclones

Abstract NASA’s Investigation of Microphysics and Precipitation for Atlantic Coast-Threatening Snowstorms (IMPACTS) field campaign gathered data using “satellite-simulating” (albeit with higher-resolution data than satellites currently provide) and in situ aircraft to study snowstorms, with an emphasis on banding. This study used three IMPACTS microwave instruments—two passive and one active—chosen for their sensitivity to precipitation microphysics. The 10–37-GHz passive frequencies were well suited for detecting light precipitation and differentiating rain intensities over water. The 85–183-GHz frequencies were more sensitive to cloud ice, with higher cloud tops manifesting as lower brightness temperatures, but this did not necessarily correspond well to near-surface precipitation. Over land, retrieving precipitation information from radiometer data is more difficult, requiring increased reliance on radar to assess storm structure. A dual-frequency ratio (DFR) derived from the radar’s Ku- and Ka-band frequencies provided greater insight into storm microphysics than reflectivity alone. Areas likely to contain mixed-phase precipitation (often the melting layer/bright band) generally had the highest DFR, and high-altitude regions likely to contain ice usually had the lowest DFR. The DFR of rain columns increased toward the ground, and snowbands appeared as high-DFR anomalies. Significance Statement Winter precipitation was studied using three airborne microwave sensors. Two were passive radiometers covering a broad range of frequencies, while the other was a two-frequency radar. The radiometers did a good job of characterizing the horizontal structure of winter storms when they were over water, but struggled to provide detailed information about winter storms when they were over land. The radar was able to provide vertically resolved details of storm structure over land or water, but only provided information at nadir, so horizontal structure was less well described. The combined use of all three instruments compensated for individual deficiencies, and was very effective at characterizing overall winter storm structure.

Microphysical Insights From Dual Polarization Spectral Observations in Updraft and Mixed-Phase Precipitation

Microphysical Insights From Dual Polarization Spectral Observations in Updraft and Mixed-Phase Precipitation

Aircraft observation of fast initiation of mixed phase precipitation in convective cloud over the Tibetan Plateau

The Tibetan Plateau is known as the water tower of Southeast Asia, and precipitation processes on the Tibetan Plateau is complex, especially in convective cloud precipitation. Many remote sensing and ground observations have been analyzed, but the in-situ measurements of cloud microphysical characteristics are rare. Here we present aircraft observations of the microphysics of convective clouds over the Qinghai Tibet Plateau in China. These results show the microphysical structure of convective clouds and the triggering characteristics of precipitation in summer in Tibet. The vertical profile of July 9th was selected for a detailed analysis of microphysical characteristics. Mixed phase precipitation was initiated above the 7000 m above sea level over the TP, which is only about 500 m above cloud base height. Riming was the dominant precipitation forming process over the TP, leading to graupel formation, which was the primary form of precipitation of the convective clouds. Although the dust was a large fraction of the overall aerosols over the TP during the flights, it was not likely a major contribution to the early ice formation because of the temperature limit of the Ice Nuclei (IN) parameterization. The secondary ice process (SIP) appears to be the main source of ice crystals.

Coarse sea spray inhibits lightning

The known effects of thermodynamics and aerosols can well explain the thunderstorm activity over land, but fail over oceans. Here, tracking the full lifecycle of tropical deep convective cloud clusters shows that adding fine aerosols significantly increases the lightning density for a given rainfall amount over both ocean and land. In contrast, adding coarse sea salt (dry radius > 1 μm), known as sea spray, weakens the cloud vigor and lightning by producing fewer but larger cloud drops, which accelerate warm rain at the expense of mixed-phase precipitation. Adding coarse sea spray can reduce the lightning by 90% regardless of fine aerosol loading. These findings reconcile long outstanding questions about the differences between continental and marine thunderstorms, and help to understand lightning and underlying aerosol-cloud-precipitation interaction mechanisms and their climatic effects.

Southern Ocean Precipitation Characteristics Observed From CloudSat and Ground Instrumentation During the Macquarie Island Cloud & Radiation Experiment (MICRE): April 2016 to March 2017

AbstractA 1‐year blended surface precipitation data set using Parsivel disdrometer, surface W‐band radar, and tipping bucket measurements is produced for the Macquarie Island Cloud and Radiation Experiment (MICRE) and compared with retrievals from CloudSat (spaceborne 94 GHz radar). Surface precipitation was observed 44% ± 4% of the time between April 2016 and March 2017. Precipitation composed primarily of small particles (diameter <1 mm) occurred about 36% ± 2% of the time, constituting 10% of total accumulation. Remaining precipitation contained enough large particles such that the disdrometer could be used to identify the precipitation type as rain, ice, snow or wet snow. Seasonal and annual statistics on frequency of occurrence and accumulation for each precipitation type observed during MICRE are presented. Most ice and mixed phase precipitation was shallow, originating at a height of 3 km or lower, and occurred most often when Macquarie Island was to the northwest of the nearest cyclonic low‐pressure center. In contrast, rain was more often deep and occurred most frequently when the island was to the southeast of cyclonic lows. A weak diurnal cycle in frequency and mean rate was present with a minimum between 12:00 and 14:00 local time and maximum between 03:00 and 06:00 local time. The CloudSat 2C‐Precip‐Column product missed the lightest precipitation (because the near‐surface reflectivity is <−15 dBZ) and overestimated total liquid precipitation and occurrence of mixed phase precipitation, but captured reasonably well the distribution of rain rates for rates >0.5 mm/hr.

Atmospheric rivers and associated precipitation patterns during the ACLOUD and PASCAL campaigns near Svalbard (May–June 2017): case studies using observations, reanalyses, and a regional climate model

Abstract. Recently, a significant increase in the atmospheric moisture content has been documented over the Arctic, where both local contributions and poleward moisture transport from lower latitudes can play a role. This study focuses on the anomalous moisture transport events confined to long and narrow corridors, known as atmospheric rivers (ARs), which are expected to have a strong influence on Arctic moisture amounts, precipitation, and the energy budget. During two concerted intensive measurement campaigns – Arctic CLoud Observations Using airborne measurements during polar Day (ACLOUD) and the Physical feedbacks of Arctic planetary boundary layer, Sea ice, Cloud and AerosoL (PASCAL) – that took place at and near Svalbard, three high-water-vapour-transport events were identified as ARs, based on two tracking algorithms: the 30 May event, the 6 June event, and the 9 June 2017 event. We explore the temporal and spatial evolution of the events identified as ARs and the associated precipitation patterns in detail using measurements from the French (Polar Institute Paul Emile Victor) and German (Alfred Wegener Institute for Polar and Marine Research) Arctic Research Base (AWIPEV) in Ny-Ålesund, satellite-borne measurements, several reanalysis products (the European Centre for Medium-Range Weather Forecasts (ECMWF) Re-Analysis (ERA) Interim (ERA-Interim); the ERA5 reanalysis; the Modern-Era Retrospective analysis for Research and Applications, version 2 (MERRA-2); the Climate Forecast System version 2 (CFSv2); and the Japanese 55-Year Reanalysis (JRA-55)), and the HIRHAM regional climate model version 5 (HIRHAM5). Results show that the tracking algorithms detected the events differently, which is partly due to differences in the spatial and temporal resolution as well as differences in the criteria used in the tracking algorithms. The first event extended from western Siberia to Svalbard, caused mixed-phase precipitation, and was associated with a retreat of the sea-ice edge. The second event, 1 week later, had a similar trajectory, and most precipitation occurred as rain, although mixed-phase precipitation or only snowfall occurred in some areas, mainly over the coast of north-eastern Greenland and the north-east of Iceland, and no differences were noted in the sea-ice edge. The third event showed a different pathway extending from the north-eastern Atlantic towards Greenland before turning south-eastward and reaching Svalbard. This last AR caused high precipitation amounts on the east coast of Greenland in the form of rain and snow and showed no precipitation in the Svalbard region. The vertical profiles of specific humidity show layers of enhanced moisture that were concurrent with dry layers during the first two events and that were not captured by all of the reanalysis datasets, whereas the HIRHAM5 model misrepresented humidity at all vertical levels. There was an increase in wind speed with height during the first and last events, whereas there were no major changes in the wind speed during the second event. The accuracy of the representation of wind speed by the reanalyses and the model depended on the event. The objective of this paper was to build knowledge from detailed AR case studies, with the purpose of performing long-term analysis. Thus, we adapted a regional AR detection algorithm to the Arctic and analysed how well it identified ARs, we used different datasets (observational, reanalyses, and model) and identified the most suitable dataset, and we analysed the evolution of the ARs and their impacts in terms of precipitation. This study shows the importance of the Atlantic and Siberian pathways of ARs during spring and beginning of summer in the Arctic; the significance of the AR-associated strong heat increase, moisture increase, and precipitation phase transition; and the requirement for high-spatio-temporal-resolution datasets when studying these intense short-duration events.

Measured and modeled vertical structure of precipitation during mixed-phase event near the West Coast of the Antarctic Peninsula

Precipitation structures are easy to detect, however, the mesoscale atmospheric processes which they reflect are challenging to understand in Polar Regions and hard to model numerically. Currently, the spatial distribution of precipitation can be tracked at the resolution of minutes and seconds. For this purpose, the researchers at the Ukrainian Antarctic Akademik Vernadsky station employ several near-ground measurement systems and the Micro Rain Radar for remote vertical measurements. Measurements show stochastic precipitation variability caused by turbulence, precipitation bands related to the atmospheric processes of its formation, phase transition (melting) zones, and wind shears. The time scale of bands in the stratiform precipitation typically varied in the range of 5—15 minutes and corresponded to the 2—15 km spatial scale of atmospheric circulations according to the modeled parameters of the atmosphere. The Polar Weather Research and Forecast (Polar WRF) model was used to reveal the general atmospheric conditions. We also tested and evaluated its ability to reproduce small structures. A simple method based on typical model variables is proposed to identify the precipitation melting layer in the simulation data, similar to that determined by radars. The results were satisfyingly consistent with the position of the 0 °C isotherm in the model and with the radar measurements. In addition, the method highlighted supercooled mixed-phase precipitation. Modeling showed good results for large-scale processes like atmospheric fronts and general air mass features in the case study. However, even at the 1 km resolution the simulation reproduced thin mesoscale precipitation features smoothly, which sometimes looks unrealistic. As for other precipitation peculiarities, like band inclination, melting layer position, and mixed-phase zones, the Polar WRF model demonstrates high consistency with observations. The model can describe the atmospheric conditions except for the investigation of precipitation-initiating mechanisms, which still is a challenge for modeling at a small scale.

Automated precipitation monitoring with the Thies disdrometer: biases and ways for improvement

Abstract. The intensity and phase of precipitation at the ground surface can have important implications not only for meteorological and hydrological situations but also in terms of hazards and risks. In the field, Thies disdrometers are sometimes used to monitor the quantity and nature of precipitation with high temporal resolution and very low maintenance and thus provide valuable information for the management of meteorological and hydrological risks. Here, we evaluate the Thies disdrometer with respect to precipitation detection, as well as the estimation of precipitation intensity and phase at a pre-alpine site in Switzerland (1060 m a.s.l.), using a weighing precipitation gauge (OTT pluviometer) and a two-dimensional video disdrometer (2DVD) as a reference. We show that the Thies disdrometer is well suited to detect even light precipitation, reaching a hit rate of around 95 %. However, the instrument tends to systematically underestimate rainfall intensities by 16.5 %, which can be related to a systematic underestimation of the number of raindrops with diameters between 0.5 and 3.5 mm. During snowfall episodes, a similar underestimation is observed in the particle size distribution (PSD), which is, however, not reflected in intensity estimates, probably due to a compensation by snow density assumptions. To improve intensity estimates, we test PSD adjustments (to the 2DVD) and direct adjustments of the resulting intensity estimates (to the OTT pluviometer), the latter of which are able to successfully reduce the systematic deviations during rainfall in the validation period. For snowfall, the combination of the 2DVD and the OTT pluviometer seems promising as it allows for improvement of snow density estimates, which poses a challenge to all optical precipitation measurements. Finally, we show that the Thies disdrometer and the 2DVD agree well insofar as the distinction between rain and snowfall is concerned, such that an important prerequisite for the proposed correction methods is fulfilled. Uncertainties mainly persist during mixed-phase precipitation or low precipitation intensities, where the assignment of precipitation phase is technically challenging, but less relevant for practical applications. We conclude that the Thies disdrometer is suitable not only to estimate precipitation intensity but also to distinguish between rain and snowfall. The Thies disdrometer therefore seems promising for the improvement of precipitation monitoring and the nowcasting of discharge in pre-alpine areas, where considerable uncertainties with respect to these quantities are still posing a challenge to decision-making.

Synergetic Use of the WSR-88D Radars, GOES-R Satellites, and Lightning Networks to Study Microphysical Characteristics of Hurricanes

AbstractThis study analyzes the microphysics and precipitation pattern of Hurricanes Harvey (2017) and Florence (2018) in both the eyewall and outer rainband regions. From the retrievals by a satellite red–green–blue scheme, the outer rainbands show a strong convective structure while the inner eyewall has less convective vigor (i.e., weaker upper-level reflectivities and electrification), which may be related to stronger vertical wind shear that hinders fast vertical motions. The WSR-88D column-vertical profiles further confirm that the outer rainband clouds have strong vertical motion and large ice-phase hydrometeor formation aloft, which correlates well with 3D Lightning Mapping Array source counts in height and time. From the results from this study, it is determined that the inner eyewall region is dominated by warm rain, whereas the external rainband region contains intense mixed-phase precipitation. External rainbands are defined here as those that reside outside of the main hurricane circulation, associated with surface tropical storm wind speeds. The synergy of satellite and radar dual-polarization parameters is instrumental in distinguishing between the key microphysical features of intense convective rainbands and the warm-rain-dominated eyewall regions within the hurricanes. Substantial amounts of ice aloft and intense updrafts in the external rainbands are indicative of heavy surface precipitation, which can have important implications for severe weather warnings and quantitative precipitation forecasts. The novel part of this study is to combine ground-based radar measurement with satellite observations to study hurricane microphysical structure from surface to cloud top so as to fill in the gaps between the two observational techniques.

Atmospheric ice nuclei concentration measurements over a high altitude-station in the Western Ghats, India

Abstract Mixed-phase and ice clouds play a significant role in modulating the Indian summer monsoon rainfall, and modeling studies suggest that inaccurate representation of ice nucleating particles (INP) is one of the factors, which have resulted in a deficiency in the prediction of cloud properties and hydrological cycle. We do not understand the ice nucleation mechanisms to represent the ice formation in the model, and therefore more INP measurements at various supercooled temperatures are needed. This study reports for the first time real-time INP concentration at a high altitude station in the Western Ghats region of India, and these results will be used to constrain the ice nucleation parameterizations in the model. The variation of INP for any particular cloud condition can have strong microphysical responses of mixed-phase precipitation formation processes. Also, to improve the representation of heterogeneous ice nucleation, INP measurements of various types of aerosols commonly observed over the Indian region are needed. This study presents, the INP concentrations and daily concentration of non-refractory chemical composition (organics, sulfate, nitrate, ammonium, and chloride), cloud condensation nuclei (CCN), and aerosol size distribution. Spectrometer for Ice Nuclei (SPIN) was operated to measure INP concentration at the mountain site from August to December 2018. INP measurements were performed at three different temperatures (−25, −30, and − 34 °C) in the immersion freezing mode relevant for mixed-phase cloud conditions. The average INP concentrations approximately varied from 0.18 to 12.4 L−1, 0.39 to 24 L−1, 1.1 to 40.2 L−1 at −25, −30, and − 34 °C, respectively. These concentrations are within the concentrations reported in the literature from different regions across the globe. The air mass back trajectory analysis showed that continental air mass contains more INP compared to maritime air mass. The information on INP concentration and chemical characteristics of aerosol will help to improve heterogeneous ice nucleation parameterization in numerical models.

Potential of Passive Microwave around 183 GHz for Snowfall Detection in the Arctic

This study evaluates the potential use of the Microwave Humidity Sounder (MHS) for snowfall detection in the Arctic. Using two years of colocated MHS and CloudSat observations, we develop an algorithm that is able to detect up to 90% of the most intense snowfall events (snow water path ≥400 g m−2 and 50% of the weak snowfall rate events (snow water path ≤50 g m−2. The brightness temperatures at 190.3 GHz and 183.3 ± 3 GHz, the integrated water vapor, and the temperature at 2 m are identified as the most important variables for snowfall detection. The algorithm tends to underestimate the snowfall occurrence over Greenland and mountainous areas (by as much as −30%), likely due to the dryness of these areas, and to overestimate the snowfall occurrence over the northern part of the Atlantic (by up to 30%), likely due to the occurrence of mixed phase precipitation. An interpretation of the selection of the variables and their importance provides a better understanding of the snowfall detection algorithm. This work lays the foundation for the development of a snowfall rate quantification algorithm.

An improved self-consistent approach to attenuation correction for C-band polarimetric radar measurements and its impact on quantitative precipitation estimation

Attenuation correction of measured reflectivity (ZH) and differential reflectivity (ZDR) is critical in short-wavelength radar applications, especially during extreme precipitation events such as heavy rain. This paper develops an improved self-consistent approach (improved ZPHI method) for attenuation correction in practical environment. In particular, a non-negative constraint is imposed on the specific attenuation, which is inferred from the monotonic increasing characteristic of differential propagation phase (ΦDP). The copolar correlation coefficient (ρHV) is used to partition the ΦDP profiles into independent range segments, which are featured by different hydrometeor phases such as liquid rain or mixed-phase precipitation. Additional minimization constraint is imposed on the cost function of the difference between preprocessed ΦDP and reconstructed ΦDPto ensure its appropriate convergence. In addition, an exponential ZDR − ZH relation derived from local raindrop size distribution (DSD) data is applied in the procedure of ZDR correction. Polarimetric measurements from a C-band radar (CPOL) in Hangzhou of China during two extreme precipitation events are used to demonstrate the improved attenuation correction method. DSD observations from disdrometers and radar data from a nearby system operating at non-attenuated frequency (i.e., S-band) at Huangshan Mountain are used to evaluate the attenuation correction performance. This paper also studies the impact of attenuation correction on the radar-derived quantitative precipitation estimation (QPE) product, through cross-comparison with rain gauge observations. Results show that the polarimetric observations from CPOL radar are effectively enhanced and more consistent with collocated S-band measurements and the simulated radar moments based on DSD data. Hourly rainfall products derived from R(ZH) and R(ZH,ZDR) are significantly improved, which are comparable to R(KDP) after attenuation correction.

OceanRAIN, a new in-situ shipboard global ocean surface-reference dataset of all water cycle components

OceanRAIN—the Ocean Rainfall And Ice-phase precipitation measurement Network—provides in-situ along-track shipboard data of precipitation, evaporation and the resulting freshwater flux at 1-min resolution over the global oceans from June 2010 to April 2017. More than 6.83 million minutes with 75 parameters from 8 ships cover all routinely measured atmospheric and oceanographic state variables along with those required to derive the turbulent heat fluxes. The precipitation parameter is based on measurements of the optical disdrometer ODM470 specifically designed for all-weather shipboard operations. The rain, snow and mixed-phase precipitation occurrence, intensity and accumulation are derived from particle size distributions. Additionally, microphysical parameters and radar-related parameters are provided. Addressing the need for high-quality in-situ precipitation data over the global oceans, OceanRAIN-1.0 is the first comprehensive along-track in-situ water cycle surface reference dataset for satellite product validation and retrieval calibration of the GPM (Global Precipitation Measurement) era, to improve the representation of precipitation and air-sea interactions in re-analyses and models, and to improve understanding of water cycle processes over the global oceans.

Characterization of hydrometeors and precipitation over the Indian monsoon region using aircraft measurements

In-situ observations of cloud microphysical properties, carried out over different parts of Indian sub-continent using an instrumented research aircraft during Phase-I of Cloud Aerosol Interaction and Precipitation Enhancement EXperiment (CAIPEEX) from June to September 2009, were studied. Different cloud probes were used to characterize the hydrometeor and precipitation types in the monsoon clouds. The results revealed that all liquid phase hydrometeors were present at temperatures −12 °C to 15 °C. Most of the presence of rain drops were found in the liquid water content (LWC) range from 0.5 to 2 g/m3. In general, rain drops are initiated when the droplet effective radius (Re) exceeded 12 μm. Rain dominated at the tops of young growing convective clouds even at temperatures colder than −10 °C. Mixed phase hydrometeors were present at temperatures from −2 °C to −18 °C. The cases where mixed phase precipitation occurred at temperatures warmer than about −7 °C were associated with influx of transported dust aerosol at the upper (supercooled) region of these cloud systems. Ice only hydrometeors were found at temperatures extending from −10 °C to −22 °C. Most of the monsoon rain is produced by warm and cold cloud/mixed-phase processes in the cloud. The combined Re from two different cloud probes is useful for validation of satellite derived cloud microphysical parameter.

The Microphysical Roles of Lower-Tropospheric versus Midtropospheric Aerosol Particles in Mature-Stage MCS Precipitation

Abstract Simulations of two leading-line, trailing-stratiform mesoscale convective system (MCS) events that occurred during the Midlatitude Continental Convective Clouds Experiment (MC3E) have been used to understand the relative microphysical impacts of lower- versus midtropospheric aerosol particles (APs) on MCS precipitation. For each MCS event, four simulations were conducted in which the initial vertical location and concentrations of cloud droplet nucleating APs were varied. These simulations were used to determine the precipitation response to AP vertical location. Importantly, the total integrated number and mass of the initial aerosol profiles used in the sensitivity simulations remained constant, such that differences in the simulations could be directly attributable to changes in the vertical location of cloud droplet nucleating APs. These simulations demonstrate that lower-tropospheric APs largely influenced the precipitation response directly rearward of the leading cold pool boundary. However, farther rearward in the MCS, the relative impact of lower- versus midtropospheric APs largely depended on the MCS structure, which varied between the two events because of differences in line-normal wind shear. Midtropospheric APs were able to activate new cloud droplets in the midtropospheric levels of convective updrafts and to enhance mixed-phase precipitation through increased cloud riming, and this microphysical pathway had a more significant impact on mixed-phase precipitation in weaker line-normal wind shear conditions. This result exposes the importance of properly representing midtropospheric APs when assessing aerosol effects on clouds. This study also demonstrates the utility of assessing aerosol effects within the different regions of MCSs.

An Analysis of Coordinated Observations from NOAA’s Ronald H. Brown Ship and G-IV Aircraft in a Landfalling Atmospheric River over the North Pacific during CalWater-2015

AbstractTo gain a more complete observational understanding of atmospheric rivers (ARs) over the data-sparse open ocean, a diverse suite of mobile observing platforms deployed on NOAA’s R/V Ronald H. Brown (RHB) and G-IV research aircraft during the CalWater-2015 field campaign was used to describe the structure and evolution of a long-lived AR modulated by six frontal waves over the northeastern Pacific during 20–25 January 2015. Satellite observations and reanalysis diagnostics provided synoptic-scale context, illustrating the warm, moist southwesterly airstream within the quasi-stationary AR situated between an upper-level trough and ridge. The AR remained offshore of the U.S. West Coast but made landfall across British Columbia where heavy precipitation fell. A total of 47 rawinsondes launched from the RHB provided a comprehensive thermodynamic and kinematic depiction of the AR, including uniquely documenting an upward intrusion of strong water vapor transport in the low-level moist southwesterly flow during the passage of frontal waves 2–6. A collocated 1290-MHz wind profiler showed an abrupt frontal transition from southwesterly to northerly flow below 1 km MSL coinciding with the tail end of AR conditions. Shipborne radar and disdrometer observations in the AR uniquely captured key microphysical characteristics of shallow warm rain, convection, and deep mixed-phase precipitation. Novel observations of sea surface fluxes in a midlatitude AR documented persistent ocean surface evaporation and sensible heat transfer into the ocean. The G-IV aircraft flew directly over the ship, with dropsonde and radar spatial analyses complementing the temporal depictions of the AR from the RHB. The AR characteristics varied, depending on the location of the cross section relative to the frontal waves.

Examination of Mixed-Phase Precipitation Forecasts from the High-Resolution Rapid Refresh Model Using Surface Observations and Sounding Data

Abstract Accurate prediction of mixed-phase precipitation remains challenging for numerical weather prediction models even at high resolution and with a sophisticated explicit microphysics scheme and diagnostic algorithm to designate the surface precipitation type. Since mixed-phase winter weather precipitation can damage infrastructure and produce significant disruptions to air and road travel, incorrect surface precipitation phase forecasts can have major consequences for local and statewide decision-makers as well as the general public. Building upon earlier work, this study examines the High-Resolution Rapid Refresh (HRRR) model’s ability to forecast the surface precipitation phase, with a particular focus on model-predicted vertical temperature profiles associated with mixed-phase precipitation, using upper-air sounding observations as well as the Automated Surface Observing Systems (ASOS) and Meteorological Phenomena Identification Near the Ground (mPING) observations. The analyses concentrate on regions of mixed-phase precipitation from two winter season events. The results show that when both the observational and model data indicated mixed-phase precipitation at the surface, the model represents the observed temperature profile well. Overall, cases where the model predicted rain but the observations indicated mixed-phase precipitation generally show a model surface temperature bias of <2°C and a vertical temperature profile similar to the sounding observations. However, the surface temperature bias was ~4°C in weather systems involving cold-air damming in the eastern United States, resulting in an incorrect surface precipitation phase or the duration (areal coverage) of freezing rain being much shorter (smaller) than the observation. Cases with predicted snow in regions of observed mixed-phase precipitation present subtle difference in the elevated layer with temperatures near 0°C and the near-surface layer.

Polarimetric Signatures of Midlatitude Warm-Rain Precipitation Events

AbstractPrecipitation events in which rainfall is generated primarily below the freezing level via warm-rain processes have traditionally presented a significant challenge for radar and satellite quantitative precipitation estimation (QPE) algorithms. It is possible to improve QPE in warm-rain events if they are correctly identified/classified as warm rain prior to precipitation estimation. Additionally, it is anticipated that classification schemes incorporating polarimetric radar data will be able to leverage precipitation microphysical information to better identify warm-rain precipitation events. This study lays the groundwork for the development of a polarimetric warm-rain classification algorithm by documenting the typical three-dimensional polarimetric characteristics associated with midlatitude warm-rain precipitation events. These characteristics are then compared with those observed in non-warm-rain events. Nearly all warm-rain precipitation events were characterized by lower median values of Z, ZDR, and KDP relative to the non-warm-rain convective cases. Furthermore, droplet coalescence was determined to be the dominant microphysical process in the majority of warm-rain events, while in non-warm-rain stratiform events, evaporation and breakup appeared to be the dominant (warm) microphysical processes. Most warm-rain events were also associated with sharp decreases in reflectivity, with height above the freezing level coincident with low echo-top heights and freezing-level ZDR values near 0, indicating limited ice- and mixed-phase precipitation growth processes. These results support the feasibility of a future polarimetric warm-rain identification algorithm.