Abstract

The structure and evolution of a high-precipitation (HP) supercell thunderstorm is investigated using a three-dimensional, nonhydrostatic, cloud-scale numerical model (TASS). The model is initialized with a sounding taken from a mesoscale modeling study of the environment that produced the 28 November 1988 Raleigh tornadic thunderstorm. TASS produces a long-lived convective system that compares favorably with the observed Raleigh tornadic thunderstorm. The simulated storm evolves from a multicell-type storm to a multiple-updraft supercell storm. The storm complex resembles a hybrid multicell-supercell thunderstorm and is consistent with the conceptual model of cool season strong dynamic HP supercells that are characterized by shallow mesocyclones. The origin of rotation in this type of storm is often in the lowest levels.

Interactions between various cells in the simulated convective system are responsible for the transition to a supercellular structure. An intense low-level updraft core forms on the southwest flank of the simulated storm and moves over a region that is rich in vertical vorticity. The stretching of this preexisting vertical vorticity in the storm’s lowest levels is the most important vertical vorticity production mechanism during the initial stages of the main updraft’s development. Interactions with an extensive cold pool created by the storm complex are also important in producing vertical vorticity as the main updraft grows. Overall, the development of vorticity associated with the main updraft appears similar to nonsupercellular tornadic storms. However, classic supercell signatures are seen early in the simulation associated with other updrafts (e.g., formation of vortex couplet due to tilting of ambient horizontal vorticity, storm splitting, etc.) and are deemed important.

In the storm’s supercell stage, rotation is sustained in the lowest levels of the storm despite large amounts of precipitation located near and within the main mesocyclone. Pulsating downdrafts periodically invigorate the storm and the gust front never occludes, thus allowing the main updraft to persist for a prolonged period of time. The storm’s intensity is also maintained by frequent updraft mergers.

Abstract

A dataset consisting of one year of CloudSat Cloud Profiling Radar (CPR) near-surface radar reflectivity Z associated with dry snowfall is examined in this study. The CPR observations are converted to snowfall rates S using derived Z_e –S relationships, which were created from backscatter cross sections of various nonspherical and spherical ice particle models. The CPR reflectivity histograms show that the dominant mode of global near-surface dry snowfall has extremely light reflectivity values (∼3–4 dBZ_e ), and an estimated 94% of all CPR dry snowfall observations are less than 10 dBZ_e . The average conditional global snowfall rate is calculated to be about 0.28 mm h⁻¹, but is regionally highly variable as well as strongly sensitive to the ice particle model chosen. Further, ground clutter contamination is found in regions of complex terrain even when a vertical reflectivity continuity threshold is utilized. The potential of future multifrequency spaceborne radars is evaluated using proxy 35–13.6-GHz reflectivities and sensor specifications of the proposed Global Precipitation Measurement dual-frequency precipitation radar (DPR). It is estimated that because of its higher detectability threshold, only about 7%–1% of the near-surface radar reflectivity values and about 17%–4% of the total accumulation associated with global dry snowfall would be detected by a DPR-like instrument, but these results are very sensitive to the chosen ice particle model. These potential detection shortcomings can be partially mitigated by using snowfall-rate distributions derived by the CPR or other similar high-frequency active sensors.

Abstract

Using a 3-yr Global Precipitation Mission (GPM) Ku-band Precipitation Radar (KuPR) dataset, snow features (SFs) are defined by grouping the contiguous area of nonzero solid precipitation. The near-surface wet bulb temperatures calculated from ERA-Interim reanalysis data are used to verify that SFs are colder than 1°C to omit snowfall that melts before reaching the surface. The properties of SFs are summarized to understand the global distribution and characteristics of snow systems. The seasonal and diurnal variations of SFs and their properties are analyzed over Northern and Southern Hemispheric land and ocean separately.

To quantify the amount of snow missed by the GPM KuPR and the amount of snow underestimated by the CloudSat Cloud Profiling (CPR), 3-yr KuPR pixel-level data are compared with 4-yr CloudSat CPR observations. The overall underestimation of snowfall during heavy snow events by CPR is less than 3% compared to the combined CPR and KuPR estimates. KuPR underestimates about 52% of weak snow. Only a small percentage of SFs have sizes greater than 10 000 km² (0.35%), maximum near-surface reflectivity above 30 dBZ (5.1%), or echo top above 5 km (1.6%); however, they contribute 40%, 49.5%, or 30.4% of the global volumetric snow detected by KuPR. Snow in the Northern Hemisphere has stronger diurnal and seasonal variation compared to the Southern Hemisphere. Most of the SFs over the ocean are found with relatively smaller, less intense, and shallower echo tops than over land.

Abstract

In this study, mechanisms of cell regeneration, development, and propagation within a two-dimensional multicell storm are investigated using a numerical cloud model. The cell regeneration is explained by the advection mechanism. The following processes occur periodically during cell regeneration: (i) Near the edge of the gust front, the gust front updraft is formed by low-level convergence ahead of the gust front near the surface. (ii) The upper portion of the gust front updraft grows by midlevel inflow since the gust front propagates faster than the basic wind. (iii) The growing cell tends to produce and is flanked by strong compensating downdrafts. The upstream downdraft tends to cut off the growing cell from the gust front updraft. It is found that the period of cell regeneration is inversely proportional to the midlevel, strong relative wind speed. This advection mechanism is different from that proposed by Yang and Houze, which views the rearward propagating cell as gravity waves generated by the quasi-steady updraft moving through the ambient flow.

Cell development and propagation within a two-dimensional multicell storm may be described in terms of two distinctive modes: (i) a growing mode and (ii) a propagating mode. When a growing cell reaches its maximum intensity, it splits and then propagates downstream without amplification. The dynamics of cell development and propagation is explained here by critical level argument. For the growing mode there is growth because of a conditionally unstable environment leading to steering level propagation, while for the propagating mode there is no growth because of a more stable environment leading to propagation relative to the flow (i.e., absence of critical level). It is found that the phase relationship between w′ and θ′ (w′ and u′) in the growing mode is different from that in the propagating mode and can be explained by the dominance of latent heating in the thermodynamic equation. The propagating mode is dominated by horizontal advection. The propagating mode exhibits gravity wave properties and propagates faster than the growing mode.

Abstract

This paper presents a new, purely physical approach to simulate ice-particle scattering at microwave frequencies. Temperature-dependent ice particle size distributions measured by aircraft in midlatitude frontal systems are used to represent the distribution of precipitation-sized frozen hydrometeors above the freezing level through derived radar reflectivity–snow water content (Z–M) relationships. The discrete dipole approximation is employed to calculate optical properties of selected types of idealized nonspherical ice particles (hexagonal columns, four-arm rosettes, and six-arm rosettes). Based on those assumptions, passive microwave optical properties are calculated using radar observations from Gotland Island in the Baltic Sea. These forward-simulated brightness temperatures are compared with observed data from both the Advanced Microwave Scanning Radiometer (AMSR-E) and the Advanced Microwave Sounding Unit-B (AMSU-B). Results show that the new ice scattering/microphysics model is able to generate brightness temperatures that are consistent with AMSR and AMSU-B observations of two light-winter-precipitation cases. The overall differences among the various ice-habit results at 89 GHz are generally not that expansive, whereas the AMSU-B 150-GHz comparisons show increased sensitivity to ice-particle shapes.

Abstract

A new method to derive radar reflectivity–snow rate (Z_e –S) relationships from scattering properties of different ice particle models is presented. Three statistical Z_e –i relationships are derived to characterize the best estimate and uncertainties due to ice habit. The derived relationships are applied to CloudSat data to derive near-surface snowfall retrievals. Other uncertainties due to various method choices, such as vertical continuity tests, the near-surface reflectivity threshold used for choosing snowfall cases, and correcting for attenuation, are also explored on a regional and zonally averaged basis. The vertical continuity test in particular is found to have interesting regional effects. Although it appears to be useful for eliminating ground clutter over land, it also masks out potential lake-effect-snowfall cases over the Southern Ocean storm-track region. The choice of reflectivity threshold is found to significantly affect snowfall detection but is insignificant in terms of the mean snowfall rate. The use of an attenuation correction scheme can increase mean snowfall rates by ∼20%–30% in some regions. The CloudSat-collocated Advanced Microwave Scanning Radiometer (AMSR)-derived liquid water path is also analyzed, and significant amounts of cloud liquid water are often present in snowfall cases in which surface temperature is below freezing, illustrating the need to improve the arbitrary model-derived surface temperature criterion used to select “dry” snowfall cases. Precipitation measurements from conventional surface weather stations across Canada are used in an initial attempt to evaluate CloudSat snowfall retrievals. As expected, evaluation with ground-based data is fraught with difficulties. Encouraging results are found at a few stations, however—in particular, those located at very high latitudes.

Abstract

An observation-based study is presented that utilizes aircraft data from the 2003 Wakasa Bay Advanced Microwave Scanning Radiometer Precipitation Validation Campaign to assess recent advances in the modeling of microwave scattering properties of nonspherical ice particles in the atmosphere. Previous work has suggested that a triple-frequency (Ku–Ka–W band) reflectivity framework appears capable of identifying key microphysical properties of snow, potentially providing much-needed constraints on significant sources of uncertainty in current snowfall retrieval algorithms used for microwave remote sensing instruments. However, these results were based solely on a modeling framework. In contrast, this study considers the triple-frequency approach from an observational perspective using airborne radar observations from the Wakasa Bay field campaign. After accounting for several challenges with the observational dataset, such as beam mismatching and attenuation, observed dual-wavelength ratio results are presented that confirm both the utility of a multifrequency approach to snowfall retrieval and the validity of the unique signatures predicted by complex aggregate ice particle scattering models. This analysis provides valuable insight into the microphysics of frozen precipitation that can in turn be applied to more readily available single- and dual-frequency systems, providing guidance for future precipitation retrieval algorithms.

Abstract

A combined active/passive modeling system that converts CloudSat observations to simulated microwave brightness temperatures (T_B ) is used to assess different ice particle models under precipitating conditions. Simulation results indicate that certain ice models (e.g., low-density spheres) produce excessive scattering and implausibly low simulated T_B s for stratiform precipitation events owing to excessive derived ice water paths (IWPs), while other ice models produce unphysical T_B depressions due to the combined effects of elevated derived IWP and excessive particle size distribution–averaged extinction. An ensemble of nonspherical ice particle models, however, consistently produces realistic results under most circumstances and adequately captures the radiative properties of frozen hydrometeors associated with precipitation—with the possible exception of very high IWP events. Large derived IWP uncertainties exceeding 60% are also noted and may indicate IWP retrieval accuracy deficiencies using high-frequency passive microwave observations. Simulated T_B uncertainties due to the ice particle model ensemble members approach 9 (5) K at 89 (157) GHz for high ice water path conditions associated with snowfall and ∼2–3 (∼1–2) K under typical stratiform rain conditions. These uncertainties, however, display considerable variability owing to ice water path, precipitation type, satellite zenith angle, and frequency. Comparisons between 157-GHz simulations and observations under precipitating conditions produce low biases (<1.5 K) and high correlations, but lower-frequency channels display consistent negative biases of 3–4 K in precipitating regions. Sample error correlations and covariance matrices for select microwave frequencies also show strong functional relationships with ice water path and variability depending on precipitation type.

Abstract

The prevailing snowfall regimes at two Scandinavian sites, Haukeliseter, Norway, and Kiruna, Sweden, are documented using ground-based in situ and remote sensing methods. Micro Rain Radar (MRR) profiles indicate three distinct snowfall regimes occur at both sites: shallow, deep, and intermittent snowfall. The shallow snowfall regime produces the lowest mean snowfall rates and radar echo tops are confined below 1.5 km above ground level (AGL). Shallow snowfall occurs under areas of large-scale subsidence with a moist boundary layer and dry air aloft. The atmospheric ridge coinciding with shallow snowfall is highly anomalous over Haukeliseter but is more common in Kiruna where shallow snowfall was frequently observed. The shallow snowfall particle size distributions (PSDs) are broad with lower particle concentrations than other regimes, especially small particles. Deep snowfall events exhibit MRR profiles that extend above 2 km AGL and tend to be associated with weak low pressure and high relative humidity throughout the troposphere. The PSDs in deep events are narrower with high concentrations of small particles. Increasing MRR reflectivity toward the surface suggests aggregation as a possible growth process during deep snowfall events. The heaviest mean snowfall rates are associated with intermittent events that are characterized by deep MRR profiles but have variations in intensity and height. The intermittent regime is associated with anomalous, deep low pressure along the coast of Norway and enhanced relative humidity at lower levels. The PSDs reveal high concentrations of small and large particles. The analysis reveals that there are unique characteristics of shallow, deep, and intermittent snowfall regimes that are common between the sites.

Abstract

The first observationally based near-global shallow cumuliform snowfall census is undertaken using multiyear CloudSat Cloud Profiling Radar observations. CloudSat snowfall observations and snowfall rate estimates from the CloudSat 2C-Snow Water Content and Snowfall Rate (2C-SNOW-PROFILE) product are partitioned between shallow cumuliform and nimbostratus cloud structures by utilizing coincident cloud category classifications from the CloudSat 2B-Cloud Scenario Classification (2B-CLDCLASS) product. Shallow cumuliform (nimbostratus) snowfall events comprise about 36% (59%) of snowfall events in the CloudSat snowfall dataset. The remaining 5% of snowfall events are distributed between other categories. Distinct oceanic versus continental trends exist between the two major snowfall categories, as shallow cumuliform snow-producing clouds occur predominantly over the oceans. Regional differences are also noted in the partitioned dataset, with over-ocean regions near Greenland, the far North Atlantic Ocean, the Barents Sea, the western Pacific Ocean, the southern Bering Sea, and the Southern Hemispheric pan-oceanic region containing distinct shallow snowfall occurrence maxima exceeding 60%. Certain Northern Hemispheric continental regions also experience frequent shallow cumuliform snowfall events (e.g., inland Russia), as well as some mountainous regions. CloudSat-generated snowfall rates are also partitioned between the two major snowfall categories to illustrate the importance of shallow snow-producing cloud structures to the average annual snowfall. While shallow cumuliform snowfall produces over 50% of the annual estimated surface snowfall flux regionally, about 18% (82%) of global snowfall is attributed to shallow (nimbostratus) snowfall. This foundational spaceborne snowfall study will be utilized for follow-on evaluative studies with independent model, reanalysis, and ground-based observational datasets to characterize respective dataset biases and to better quantify CloudSat snowfall detection and quantitative snowfall estimate uncertainties.