Ice Precipitation Research Articles

Comparison of the Morrison and WDM6 Microphysics Schemes in the WRF Model for a Convective Precipitation Event in Guangdong, China, Through the Analysis of Polarimetric Radar Data

Numerical weather prediction (NWP) models are indispensable for studying severe convective weather events. Research demonstrates that the outcomes of convective precipitation simulations are profoundly influenced by the choice between single or double-moment schemes for ice precipitation particles and the categorization of rimed ice. The advancement of dual-polarization radar has enriched the comparative validation of these simulations. This study simulated a convective event in Guangdong, China, from May 7 to 8, 2017, employing two bulk microphysical schemes (Morrison and WDM6) in the WRF v4.2 model. Each scheme was divided into two versions: one representing rimed ice particles as graupel (Mor_G, WDM6_G) and the other as hail (Mor_H, WDM6_H). The simulation results indicated negligible differences between the rimed ice set as graupel or hail particles, for both schemes. However, the Morrison schemes (Mor_G, Mor_H) depicted a more accurate raindrop size distribution below the 0 °C height level. A further analysis suggested that disparities between the Morrison and WDM6 schemes could be attributed to the intercept parameter (N0) setting for snow and graupel/hail in WDM6 scheme. The prescribed snow and graupel/hail N0 of WDM6 scheme might influence the melting processes, leading to a higher number concentration but a reduced mass-weighted diameter of raindrops. Reducing the intercept parameter for snow and graupel/hail in the WDM6 scheme could potentially enhance the simulation of convective precipitation. Conversely, the increase in N0 might deteriorate the precipitation simulation performance of the WDM6_G scheme, whereas the WDM6_H scheme exhibits minimal sensitivity to such changes.

Climate sensitivity of natural hazards processes in mountain regions: A fuzzy logic approach

Natural hazard processes, as an inherent component of mountain environments, react sensitively to global warming. The main drivers of these changes are alterations in the amount, intensity or type of precipitation, glacier melting, or thawing of permafrost ice. The hazard responses can involve a change in hazard intensity or frequency (increasing or decreasing), a shift in their location or, a shift from one type of hazard to another. As climate change impacts vary in space and time, this variability must be considered when planning measures to protect populations and infrastructure from hazardous processes. To support this, we developed a method for assessing the climate sensitivity of small individual rock releases and larger rockfall processes. The method is based on a fuzzy logic approach and uses highly resolved climate scenario data, allowing application on a regional or even larger scale.The application in a study area of 700 km2 in the central Valais (Switzerland) shows that the impacts of climate change on natural hazard processes can vary quite substantially across small spatial scales. Generally, an increase in rockfall frequency and magnitude is simulated under future warming scenarios, especially at higher altitudes. However, at lower elevations and on south-exposed slopes, a decrease in freeze-thaw cycles leads to a decrease in material availability. This knowledge is essential in discussions of how climate change should be considered in hazard and disaster management.

Land-sea contrast of vertical structure of precipitation over Sumatra revealed by GPM DPR observations

This study examines the land-sea contrast in the vertical structure of precipitation over Sumatra and its surrounding ocean using eight years (2014–2021) of dual-frequency precipitation radar (DPR) data from the Global Precipitation Measurement (GPM) mission. The study area is segmented into Ocean, Coast I (west coast), Land I (west of Barisan Mountains), Land II (east of Barisan Mountains), and Coast II (east coast). The effective reflectivity factor (Ze), rainfall rate (R), and two raindrop size distribution (DSD) parameters, namely the mass-weighted mean diameter (Dm) and the normalized intercept (Nw), were analyzed. Stratiform and deep convective rainfall were the most frequent types in Coast I, followed by Ocean, Land I, Land II, and Coast II. In contrast, shallow convective rainfall was the most common type in Ocean, followed by Coast I, Land I, Land II, and Coast II. The average rain top height (RTH) was found to be higher in Land II and Coast II than in Ocean, Coast I, and Land I, in accordance with the surface rainfall intensity pattern previously reported by other studies. Furthermore, the data on heavy ice precipitation demonstrated an increase from the ocean to the coast and land, with a significant number of instances observed in Land I, Land II, and Coast II, in addition to Coast I. This contrast in heavy ice precipitation and RTH influences DSD. The land-sea contrast of DSD is more pronounced for deep convective rains. Deep convective exhibited a lower frequency of large raindrops over the ocean than over the coast and land, as reflected in the Dm profile. Conversely, raindrop concentration, particularly small drops, was higher at sea. The percentage of Dm > 2 mm at sea was approximately 2%, rising to 4–6% in Land II and Coast II. The land-sea contrast in the vertical structure of precipitation over Sumatra exhibited apparent diurnal variation. Larger Dm and smaller Nw were observed over Land I and Coast I, particularly in the afternoon and evening, correlating with peak rainfall. This pattern aligns with heavy ice precipitation profiles, vertical relative humidity (RH), and wind profiles. This study highlights the complexities and potential discrepancies between vertical precipitation profiles and surface precipitation data, underscoring the nuanced nature of land-sea precipitation migration.

Arctic Cloud‐Base Ice Precipitation Properties Retrieved Using Bayesian Inference

AbstractCloud‐climate feedbacks are still the greatest source of uncertainty in current climate projections. Arctic clouds, which are predominantly stratiform and supercooled, often long‐lived, and nearly continuously precipitate ice particles, contribute roughly 10% of the uncertainty attributed to the global cloud feedback. This Arctic cloud uncertainty is driven by incomplete observational and theoretical knowledge required to estimate and explain the state and active processes occurring in those clouds. A focus on ice precipitation properties at Arctic cloud base rather than the surface deconfounds the product of cloud condensate sink processes from the influence of the atmospheric thermodynamic state below cloud base, rendering cloud‐base properties a more appealing target for inference and evaluation of model simulations. Here I describe an inverse model for the estimation of cloud base ice precipitation properties over Utqiagvik, North Slope of Alaska, using the synthesis of ground‐based radar and lidar measurements. By leveraging a Markov Chain Monte Carlo algorithm as the core of the inverse model, a wide range of particle size distributions are sampled, and different combinations of ice habit models are examined, both of which are typically fixed in other retrieval methods. Results show intriguing links between different cloud base thermodynamic and ice precipitation properties. Apparent ice number concentration enhancements at temperatures of −5 and −15°C suggest possible secondary ice production (SIP). The analysis alludes to an overestimation of SIP occurrence and intensity, especially in studies relying only on radar or lidar measurements. Finally, reflectivity‐dependent ice precipitation rate and ice water content parameterizations are presented.

Seasonal Differences of Precipitation and Microphysical Characteristics over the Asian Monsoon Region Using Spaceborne Dual-Frequency Precipitation Radar

Abstract This study aimed to reveal the seasonal climatic variations in the microphysical properties of precipitation over the Asian monsoon region. We used the Dual-Frequency Precipitation Radar satellite product aboard the Global Precipitation Measurement Mission Core Observatory for 8 years from 2014 to 2021 to statistically analyze the mass-weighted mean diameter (Dm) and frequency of heavy ice precipitation (graupel and hail). The results showed statistically significant seasonal changes. The microphysical characteristics of large Dm and frequent heavy ice precipitation were observed over the Indian subcontinent and Indochina Peninsula in the premonsoon season and over the western Himalayan region in the mature-monsoon season, which can be related to the intense and deeply developed precipitation systems. The relationship between precipitation rate and Dm was also examined. The results indicated that changes in Dm were not caused only by changes in precipitation rate but were probably induced by changes in precipitation characteristics. In terms of the relationship between the microphysical properties, heavy ice precipitation particles in the upper atmosphere above the melting layer were observed more frequently as Dm near the surface increased. We also studied lower-atmospheric instability by investigating the vertical gradients of the dry and moist static energies. The results indicated that instability properties were different; dry and wet instabilities were dominant in the premonsoon and monsoon seasons, respectively, consistent with the results of the precipitation characteristics. Significance Statement The purpose of this study was to reveal seasonal variations in precipitation microphysical characteristics, such as precipitation particle size and the existence of graupel and hail in the upper atmosphere, by climatological analysis over the Asian monsoon region. In previous studies, microphysical characteristics have mainly been addressed using ground-based observations. However, more sampling is needed to expand our understanding of climatological perspectives; therefore, we used recently available satellite observations. As a result, we found that precipitation particles at the surface were larger, and more graupel and hail existed in clouds in the premonsoon season when less precipitation was observed, compared to the mature-monsoon season when precipitation amount and frequency were abundant.

Comparison of Microphysics Schemes on WRF-HAILCAST Model to Study Hailstone in Aeronautics (Case Study: Hail Strike on AirAsia A320-200, November 16, 2018)

A hail strike is caused by the hail phenomenon, an aviation accident caused by environmental factors. Hail is a type of extreme weather in the form of precipitation ice grains which is generally caused by cumulonimbus clouds. Research on hail modeling can be carried out using the Weather Research Forecasting Hail Forecast (WRF-HAILCAST), which can model the structure, dynamics, microphysics, hailstone distribution, and estimate the maximum diameter of the hailstone. In this study, the hail modeling that caused the hail strike on the AirAsia A320-200 aircraft on November 16, 2018, was carried out using the WRF-HAILCAST model with six different microphysics schemes. This study compares the results of the microphysics scheme on the WRF-HAILCAST model in hail modeling. The results of this study indicated that each microphysics scheme produces a different outcome. Generally, the spatial and temporal distribution of the entire scheme could indicate the presence of convective clouds reaching 40–55 dBZ. Each scheme showed the microphysical processes of clouds consisting of different hydrometeor particles. However, only MY2 and NSSL showed the presence of supercooled water, and those schemes could estimate maximum diameter hailstone worth 25.8 mm and 13.2 mm. So, NSSL is the best microphysics scheme in this study.DOI: 10.17977/um024v8i12023p020

Determination of Total Column of Trichlorofluoromethane in the Atmosphere Considering the Effect of Amorphous Water Ice Precipitation on the Spectrometer Detector

Determination of Total Column of Trichlorofluoromethane in the Atmosphere Considering the Effect of Amorphous Water Ice Precipitation on the Spectrometer Detector

ICE-CAMERA: a flatbed scanner to study inland Antarctic polar precipitation

Abstract. Studying precipitation at very high latitudes is difficult because of the harsh environmental conditions that limit the external activity of humans and instruments, especially in the polar winter. The direct monitoring of ice crystal habits and size distribution in Antarctic precipitation is important for the validation of the algorithms used for retrieving precipitation from ground-based and satellite-borne radar instruments and for the improvement of the climatological modelling of polar areas. This paper describes an automated device (ICE-CAMERA) specifically developed for the imaging, measurement, and classification of ice precipitation on the Antarctic high plateau. The instrument gives detailed information on precipitation on an hourly basis. The article provides a description of the device and its image processing software. Starting in 2014, the instrument has operated almost unattended all year round at Concordia station, Antarctica (75∘ S, 123∘ E, 3220 m altitude).

Precipitation Microphysics of Tropical Cyclones over Northeast China in 2020

Landfalling tropical cyclones (TCs) in Northeast China are rare because of the region’s high latitude (>40°N). In 2020, Northeast China was affected by three TCs within half a month—the first time on record. We used the Global Precipitation Measurement orbital dataset to study the precipitation microphysics during the TC period in Northeast China in 2020 (2020-TC), and during September in this region from 2014 to 2019 (hereafter September 2014–September 2019). FY-4A was used to provide cloud top height (CTH). The results show that, compared with September 2014–September 2019, the 2020-TC precipitation has stronger precipitation ice productivity, weaker deposition efficiency, stronger riming, and stronger coalescence processes. The storm top height (STH), CTH, and the difference between the two (CTH-STH) are indicative of the near-surface droplet size distribution (DSD), but there are differences: STH and CTH-STH both correlate significantly with mean mass-weighted drop diameter, whereas only the positive correlation between CTH and normalized drop concentration parameter passes the significance test. These results reveal for the first time the precipitation microphysics of landfalling TCs in Northeast China, and allow discussion of the validity of convective intensity indicators from the perspective of DSD.

Supercell Thunderstorm Charge Structure Variability and Influences on Spatial Lightning Flash Relationships with the Updraft

Abstract Relationships between lightning flashes and thunderstorm kinematics and microphysics are important for applications such as nowcasting of convective intensity. These relationships are influenced by cloud electrification structures and have been shown to vary in anomalously electrified thunderstorms. This study addresses transitional relationships between active charge structure and lightning flash location in the context of kinematic and microphysical updraft characteristics during the development of an anomalously electrified supercell thunderstorm in the Tennessee Valley on 10 April 2009. The initial charge structure within the updraft was characterized as an anomalous dipole in which positive charge was inferred in regions of precipitation ice (i.e., graupel and hail) and negative charge was inferred in regions of cloud ice (i.e., aggregates and ice crystals). During subsequent development of the anomalous charge structure, additional minor charge layers as well as evidence of increasing horizontal complexity were observed. Microphysical and kinematic characteristics of the charge structure also evolved to include increasing observations of negative charge in precipitation ice regions, indicating the emergence of more prominent normal charging alongside dominant anomalous charging. Simultaneously, lightning flash initiation locations were also increasingly observed in regions of faster updrafts and stronger horizontal gradients in updraft speed. It is suggested that continuous variability in charging behavior over mesogamma spatial scales influenced the evolution of lightning flash locations with respect to the updraft structure. Further work is necessary to determine how this variability may impact lightning flash relationships, including lightning flash rate, with bulk microphysical and kinematic characteristics and related applications.

Arctic sea level variability from high-resolution model simulations and implications for the Arctic observing system

Abstract. Two high-resolution model simulations are used to investigate the spatiotemporal variability of the Arctic Ocean sea level. The model simulations reveal barotropic sea level variability at periods of < 30 d, which is strongly captured by bottom pressure observations. The seasonal sea level variability is driven by volume exchanges with the Pacific and Atlantic oceans and the redistribution of the water by the wind. Halosteric effects due to river runoff and evaporation minus precipitation ice melting/formation also contribute in the marginal seas and seasonal sea ice extent regions. In the central Arctic Ocean, especially the Canadian Basin, the decadal halosteric effect dominates sea level variability. The study confirms that satellite altimetric observations and Gravity Recovery and Climate Experiment (GRACE) could infer the total freshwater content changes in the Canadian Basin at periods longer than 1 year, but they are unable to depict the seasonal and subseasonal freshwater content changes. The increasing number of profiles seems to capture freshwater content changes since 2007, encouraging further data synthesis work with a more complicated interpolation method. Further, in situ hydrographic observations should be enhanced to reveal the freshwater budget and close the gaps between satellite altimetry and GRACE, especially in the marginal seas.

New Empirical Formulation for the Sublimational Breakup of Graupel and Dendritic Snow

Abstract Ice fragments are generated by sublimation of ice particles in subsaturated conditions in natural clouds. Conceivably, such sublimational breakup would be expected to cause ice multiplication in natural clouds. Any fragment that survives will grow to become ice precipitation that may sublimate and fragment further. As a first step toward assessing this overlooked process, a formulation is proposed for the number of ice fragments from sublimation of ice particles for an atmospheric model. This is done by amalgamating laboratory observations from previously published studies. The concept of a “sublimated mass activity spectrum” for the breakup is applied to the dataset. The number of ice fragments is determined by the relative humidity over ice and the initial size of the parent ice particles. The new formulation applies to dendritic crystals and heavily rimed particles only. Finally, a thought experiment is performed for an idealized scenario of subsaturation with in-cloud descent. Scaling analysis yields an estimate of an ice enhancement ratio of about 5 (10) within a weak deep convective downdraft of about 2 m s−1, for an initial monodisperse population of dendritic snow (graupel) particles of 3 L−1 and 2 mm. During descent, there is a dynamic equilibrium between continual emission of fragments and their depletion by sublimation. A simplified bin microphysics parcel model exhibits this dynamical quasi equilibrium, consistent with the thought experiment. The fragments have average lifetimes of around 90 and 70 s for dendrites and graupel, respectively. Sublimational breakup is predicted to cause significant secondary ice production.

Wind farm icing loss forecast pertinent to winter extremes

The 2021 Texas power crisis has highlighted the vulnerability of the power system under wind extremes, particularly with the increasing penetration of energy resources that depend on weather conditions (e.g., wind energy). The current wind power forecast models do not effectively consider the impact of such extreme weather events. In the present study, we provide a fast and robust statistical model developed using ten years of utility-scale turbine data at the Eolos Wind Energy Research Station to forecast the icing losses under such weather conditions. This model covers different cold climate impacts, including precipitation icing, frost contamination, and low-temperature effect. This model has been assessed using three large-scale (>100 MW) wind farm data involving turbines with different capacities and from different manufacturers across multiple geographic regions. Notably, the model has been used to predict the wind power losses in Texas (>91% of total wind installation in Texas) during the 2021 Texas power crisis. The proposed model can be easily integrated into the existing wind farm and power grid operations, allowing the power system operators to develop more appropriate and pinpointed plans to balance the severe and sudden energy deficits and increase the system integrity under winter extremes.

Improving the representation of aggregation in a two-moment microphysical scheme with statistics of multi-frequency Doppler radar observations

Abstract. Aggregation is a key microphysical process for the formation of precipitable ice particles. Its theoretical description involves many parameters and dependencies among different variables that are either insufficiently understood or difficult to accurately represent in bulk microphysics schemes. Previous studies have demonstrated the valuable information content of multi-frequency Doppler radar observations to characterize aggregation with respect to environmental parameters such as temperature. Comparisons with model simulations can reveal discrepancies, but the main challenge is to identify the most critical parameters in the aggregation parameterization, which can then be improved by using the observations as constraints. In this study, we systematically investigate the sensitivity of physical variables, such as number and mass density, as well as the forward-simulated multi-frequency and Doppler radar observables, to different parameters in a two-moment microphysics scheme. Our approach includes modifying key aggregation parameters such as the sticking efficiency or the shape of the size distribution. We also revise and test the impact of changing functional relationships (e.g., the terminal velocity–size relation) and underlying assumptions (e.g., the definition of the aggregation kernel). We test the sensitivity of the various components first in a single-column “snowshaft” model, which allows fast and efficient identification of the parameter combination optimally matching the observations. We find that particle properties, definition of the aggregation kernel, and size distribution width prove to be most important, while the sticking efficiency and the cloud ice habit have less influence. The setting which optimally matches the observations is then implemented in a 3D model using the identical scheme setup. Rerunning the 3D model with the new scheme setup for a multi-week period revealed that the large overestimation of aggregate size and terminal velocity in the model could be substantially reduced. The method presented is expected to be applicable to constrain other ice microphysical processes or to evaluate and improve other schemes.

Examining Conditions Supporting the Development of Anomalous Charge Structures in Supercell Thunderstorms in the Southeastern United States

AbstractHypotheses regarding favorable conditions for anomalous charging have primarily resulted from studies within the Great Plains region of the United States, where the efficiency of warm precipitation processes is thought to be fundamental. Rare observations of anomalous charge structures in the Southeastern region challenge existing conceptual models used to explain anomalous charging. As a rigorous evaluation of conditions that support anomalous charge structures, environmental characteristics and bulk kinematic and microphysical properties of two normal and two anomalous supercell thunderstorms observed in the Southeast were compared. Within the anomalous supercells, greater quantities of precipitation ice were identified at higher altitudes and colder temperatures, suggesting a greater depth of riming growth and increased vertical transport of rimed hydrometeors. Deeper anomalous supercell updrafts were larger and stronger in the upper mixed‐phase and glaciated regions. However, normal supercells were characterized by more robust low‐level updrafts, resulting in comparable warm cloud residence times that suggested warm precipitation processes were not necessarily less efficient in the anomalous supercells. Indications of enhanced mixed‐phase liquid water content in favor of anomalous charging were observed in the anomalous supercells, though contrasts in related environmental parameters were not as large as observed in other comparative studies. Anomalous supercell environments were characterized by increased instability, shallower warm cloud depth, as well as lower relative humidity in the 700–500 mb layer. Evidence of impacts from dry air in anomalous storm structures suggested that water vapor content may have affected particle‐scale charge transfer in support of anomalous charge structure development.

Mixed‐Phase Clouds and Precipitation in Southern Ocean Cyclones and Cloud Systems Observed Poleward of 64°S by Ship‐Based Cloud Radar and Lidar

AbstractMixed‐phase clouds (MPCs), composed of both liquid and ice, are prevalent in Southern Ocean cyclones. A characterization of these clouds on fine vertical scales is required in order to understand the microphysical processes within these clouds, and for model and satellite evaluations over this region. We investigated three examples of cloud systems collected by ship‐mounted remote‐sensing instruments adjacent to East Antarctica at latitudes between 64°S and 69°S. These cases allow us to examine the properties of midlevel MPCs, with cloud tops between 2 and 6 km. Midlevel MPCs contain multiple layers of supercooled liquid water (SLW) embedded within ice during the passage of cyclones. SLW layers are capped by strong temperature inversions and are observed at temperatures as low as −31°C. Convective generating cells (GCs) are present inside supercooled liquid‐topped midlevel MPCs. The horizontal extent, vertical extent, and maximum upward Doppler velocity of these GCs were 0.6–3.6 km, 0.7–1.0 km, and 0.5–1.0 m s−1, respectively, and are consistent with observations from previous lower‐latitude studies. Ice precipitation is nearly ubiquitous, except in the thinnest clouds at the trailing end of the observed systems. Seeding of lower SLW layers from above leads to periods with either larger ice particles or greater ice precipitation rates. Periods of supercooled drizzle lasting up to 2 h were observed toward the end of two of the three cyclone systems. This supercooled drizzle turns into predominantly ice precipitation as the result of seeding by ice clouds located above the precipitating SLW layer.

The Effects of Ice Habit on Simulated Orographic Snowfall

AbstractMany factors are at play in determining the amount and distribution of mountain snowfall that is predicted by weather models; among them is the influence of assumed ice habit on snowfall distribution. Ice habit is necessarily greatly simplified in microphysics schemes and uncertainty remains in how best to model ice processes. In this study we simulate a Sierra Nevada snowfall event driven by an extratropical cyclone in February 2014. We have simulated the storm with four fixed habit types as well as with an ice habit scheme that is variable in time and space. In contrast to some previous studies, we found substantially smaller sensitivity of total accumulated precipitation amount and negligible changes in spatial distribution to the ice habit specification. The reason for smaller sensitivity seems to be linked to strong aggregation of ice crystals in the model. Nonetheless, while changes in total accumulated precipitation were small, changes in accumulated ice hydrometeors were larger. The variable-habit simulation produced up to 37% more ice precipitation than any of the fixed-habit simulations with an average increase of 14%. The variable-habit simulation led to a maximization of ice growth in the atmosphere and, subsequently, ice accumulation at the surface. This result points to the potential importance of accounting for the time and space variation of ice crystal properties in simulations of orographic precipitation.

The prevalence of precipitation from polar supercooled clouds

Abstract. Supercooled clouds substantially impact polar surface energy budgets, but large-scale models often underestimate their occurrence, which motivates accurately establishing metrics of basic processes. An analysis of long-term measurements at Utqiaġvik, Alaska, and McMurdo Station, Antarctica, combines lidar-validated use of soundings to identify supercooled cloud layers and colocated ground-based profiling radar measurements to quantify cloud base precipitation. We find that more than 85 % (75 %) of sampled supercooled layers are precipitating over the Arctic (Antarctic) site, with more than 75 % (50 %) precipitating continuously to the surface. Such high frequencies can be reconciled with substantially lesser spaceborne estimates by considering differences in radar hydrometeor detection sensitivity. While ice precipitation into supercooled clouds from aloft is common, we also find that the great majority of supercooled cloud layers without ice falling into them are themselves continuously generating precipitation. Such sustained primary ice formation is consistent with continuous activation of immersion-mode ice-nucleating particles (INPs), suggesting that supercooled cloud formation is a principal gateway to ice formation at temperatures greater than ∼-38 ∘C over polar regions. The prevalence of weak precipitation fluxes is also consistent with supercooled cloud longevity and with well-observed and widely simulated case studies. An analysis of colocated microwave radiometer retrievals suggests that weak precipitation fluxes can be nonetheless consequential to moisture budgets for supercooled clouds owing to small liquid water paths. The results here also demonstrate that the observed abundance of mixed-phase clouds can vary substantially with instrument sensitivity and methodology. Finally, we suggest that these ground-based precipitation rate statistics offer valuable guidance for improving the representation of polar cloud processes in large-scale models.

Radar-Based Bayesian Estimation of Ice Crystal Growth Parameters within a Microphysical Model

Abstract The potential for polarimetric Doppler radar measurements to improve predictions of ice microphysical processes within an idealized model–observational framework is examined. In an effort to more rigorously constrain ice growth processes (e.g., vapor deposition) with observations of natural clouds, a novel framework is developed to compare simulated and observed radar measurements, coupling a bulk adaptive-habit model of vapor growth to a polarimetric radar forward model. Bayesian inference on key microphysical model parameters is then used, via a Markov chain Monte Carlo sampler, to estimate the probability distribution of the model parameters. The statistical formalism of this method allows for robust estimates of the optimal parameter values, along with (non-Gaussian) estimates of their uncertainty. To demonstrate this framework, observations from Department of Energy radars in the Arctic during a case of pristine ice precipitation are used to constrain vapor deposition parameters in the adaptive habit model. The resulting parameter probability distributions provide physically plausible changes in ice particle density and aspect ratio during growth. A lack of direct constraint on the number concentration produces a range of possible mean particle sizes, with the mean size inversely correlated to number concentration. Consistency is found between the estimated inherent growth ratio and independent laboratory measurements, increasing confidence in the parameter PDFs and demonstrating the effectiveness of the radar measurements in constraining the parameters. The combined Doppler and polarimetric observations produce the highest-confidence estimates of the parameter PDFs, with the Doppler measurements providing a stronger constraint for this case.

Evaluation of Different Storm Parameters as the Proxies for Gridded Total Lightning Flash Rates: A Convection-Allowing Model Study

Lightning simulation is important for a variety of applications, including lightning forecast, atmospheric chemical simulation, and lightning data assimilation. In this study, the potential of five storm parameters (graupel volume, precipitation ice mass, radar echo volume, maximum updraft, and updraft volume) to be used as the proxy for the diagnosis of gridded total lightning flash rates has been investigated in a convection-allowing model. A mesoscale convective system occurred in the Guangdong province of China was selected as the test case. Radar data assimilation was used to improve the simulation accuracy of the convective clouds, hence providing strong instantaneous correlations between observed and simulated storm signatures. The areal coverage and magnitude of the simulated lightning flash rates were evaluated by comparing to those of the total lightning observations. Subjective and the Fractions Skill Score (FSS) evaluations suggest that all the five proxies tested in this study are useful to indicate general tendencies for the occurrence, region, and time of lightning at convection-allowing scale (FSS statistics for the threshold of 1 flash per 9 km2 per hour were around 0.7 for each scheme). The FSS values were decreasing as the lightning flash rate thresholds used for FSS computation increased for all the lightning diagnostic schemes with different proxies. For thresholds from 1 to 3 and 16 to 20 flashes per 9 km2 per hour, the graupel contents related schemes achieved higher FSS values compared to the other three schemes. For thresholds from 5 to 15 flashes per 9 km2 per hour, the updraft volume related scheme yielded the largest FSS. When the thresholds of lightning flash rates were greater than 13 flashes per 9 km2 per hour, the FSS values were below 0.5 for all the lightning diagnostic schemes with different proxies.