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Kelvin–Helmholtz (KH) waves are remarkably common in deep stratiform precipitation systems associated with frontal disturbances, at least in the vicinity of complex terrain, as is evident from transects of vertical velocity and 2D circulation, obtained from a 3-mm airborne Doppler radar, the Wyoming Cloud Radar. The high range resolution of this radar (~40 m) allows detection and depiction of KH waves in fine detail. These waves are observed in a variety of wavelengths, depths, amplitudes, and turbulence intensities. Proximity rawinsonde data confirm that they are triggered in layers where the Richardson number is very small. Complex terrain may locally enhance wind shear, leading to KH instability. In some KH waves, the flow remains mostly laminar, while in other cases it breaks down into turbulence. KH waves are frequently locked to the terrain, and occur at various heights, including within the free troposphere, at the boundary layer top, and close to the surface. They are observed not only upwind of terrain barriers, as has been documented before, but also in the wake of steep terrain, where the waves can be highly turbulent. Vertical-plane dual-Doppler analyses of KH waves reveal the mixing of layers of differential momentum across the high-shear zone. Doppler radar data are used to explore the dynamics of KH waves, including the response of thermodynamic and kinematic variables above, below, and within the instability layer.

Over mountainous terrain, windward enhancement of stratiform precipitation results from a combination of warm-rain and ice-phase processes. In this study, ice-phase precipitation processes are investigated within frontal systems during the Olympic Mountains Experiment (OLYMPEX). An enhanced layer of radar reflectivity (ZH) above the melting level bright band (i.e., a secondary ZH maximum) is observed over both the windward slopes of the Olympic Mountains and the upstream ocean, with a higher frequency of occurrence and higher ZH values over the windward slopes indicating an orographic enhancement of ice-phase precipitation processes. Aircraft-based in situ observations are evaluated for the 01-02 and 03 December 2015 orographically-enhanced precipitation events. Above the secondary ZH maximum, the hydrometeors are primarily horizontally oriented dendritic and branched crystals. Within the secondary ZH maximum, there are high concentrations of large (> ~2 mm diameter) dendrites, plates, and aggregates thereof, with a significant degree of riming. In both events, aggregation and riming appear to be enhanced within a turbulent layer near sheared flow at the top of a low-level jet impinging on the terrain and forced to rise above the melting level. Based on windward ground sites at low-, mid-, and high-elevations, secondary ZH maxima periods during all of OLYMPEX are associated with increased rain rates and larger mass-weighted mean drop diameters compared to periods without a secondary ZH maximum. This result suggests that precipitation originating from secondary ZH maxima layers may contribute to enhanced windward precipitation accumulations through the formation of large, dense particles that accelerate fallout.

Using three years of observations from the Dual-Frequency Precipitation Radar (DPR) aboard the Global Precipitation Measurement (GPM) Core Observatory, properties of the cores of deep convection are examined. First, deep convective systems are selected, defined as GPM precipitation features with maximum 20-dBZ echo-top heights above 10 km. The cores of deep convection are described by the profiles of Ku- and Ka-band radar reflectivity at the location of the highest echo top in each deep convective system. Then the dual-frequency ratio (DFR) profile is derived by subtracting Ka-band from Ku-band radar reflectivity. It is found that values of DFR are larger over land than over ocean in general near the top of the convection, which is consistent with larger ice particles in stronger updrafts in continental convection. The magnitude of DFR at 12 km is positively correlated with the convection intensity indicated by 20- and 30-dBZ echo tops. The microphysical properties including volume-weighted mean diameter, ice water content, and total ice particle number concentration are derived using a simple lookup table approach. Under the same particle size distribution assumption, the cores of deep convection over land have larger ice particle size, higher ice water content, and lower particle concentration than those over ocean at levels above 10 km, but with some distinct regional variations.

In some prominent extreme precipitation and flash flood events, radar and rain gauge observations have suggested that the heaviest short-term rainfall accumulations (up to 177 mm h−1) were associated with supercells or mesovortices embedded within larger convective systems. In this research, we aim to identify the influence that rotation has on the storm-scale processes associated with heavy precipitation. Numerical model simulations conducted herein were inspired by a rainfall event that occurred in central Texas in October 2015 where the most extreme rainfall accumulations were collocated with meso-β-scale vortices. Five total simulations were performed to test the sensitivity of precipitation processes to rotation. A control simulation, based on a wind profile from the aforementioned event, was compared with two experiments with successively weaker low-level shear. With greater environmental low-level shear, more precipitation fell, in both a point-maximum and an area-averaged sense. Intense, rotationally induced low-level vertical accelerations associated with the dynamic nonlinear perturbation vertical pressure gradient force were found to enhance the low- to midlevel updraft strength and total vertical mass flux and allowed access to otherwise inhibited sources of moisture and CAPE in the higher-shear simulations. The dynamical accelerations, which increased with the intensity of the low-level shear, dominated over buoyant accelerations in the low levels and were responsible for inducing more intense low-level updrafts that were sustained despite a stable boundary layer.

This study examines Kelvin–Helmholtz (KH) waves observed by dual-polarization radar in several precipitating midlatitude cyclones during the Olympic Mountains Experiment (OLYMPEX) field campaign along the windward side of the Olympic Mountains in Washington State and in a strong stationary frontal zone in Iowa during the Iowa Flood Studies (IFloodS) field campaign. While KH waves develop regardless of the presence or absence of mountainous terrain, this study indicates that the large-scale flow can be modified when encountering a mountain range in such a way as to promote development of KH waves on the windward side and to alter their physical structure (i.e., orientation and amplitude). OLYMPEX sampled numerous instances of KH waves in precipitating clouds, and this study examines their effects on microphysical processes above, near, and below the melting layer. The dual-polarization radar data indicate that KH waves above the melting layer promote aggregation. KH waves centered in the melting layer produce the most notable signatures in dual-polarization variables, with the patterns suggesting that the KH waves promote both riming and aggregation. Both above and near the melting layer ice particles show no preferred orientation likely because of tumbling in turbulent air motions. KH waves below the melting layer facilitate the generation of large drops via coalescence and/or vapor deposition, increasing mean drop size and rain rate by only slight amounts in the OLYMPEX storms.

The structure of a melting layer associated with a mesoconvective system is examined using a combination of in situ aircraft measurements and a unique Doppler radar operated by the U.S. Navy that has a range resolution as fine as 0.5 m. Interest in this case was motivated by ground-based all-sky camera images that captured the transient development of midlevel billow cloud structures within a precipitating trailing stratiform cloud shield associated with a passing deep convective system. A sequence of high-fidelity time–height radar measurements taken of this storm system reveal that the movement of the billow cloud structure over the radar site corresponded with abrupt transitions in the observed low-level precipitation structure. Of particular note is an observed transition from stratiform to more periodic and vertically slanted rain shaft structures that both radar and aircraft measurements indicate have the same temporal periodicity determined to arise visually between successive billow cloud bands. Doppler, balloon, and aircraft measurements reveal these transient bands are associated with a shallow circulation field that resides just above the melting level in a layer of moist neutral stability and strong negative vertical wind shear. The nature of these circulations and their impact on the evolving precipitation field are described in the context of known nimbostratus cloud types.

In this study, TRMM-observed precipitation in the tropics is decomposed according to the horizontal area of radar precipitation features, with special emphasis on large systems (rain area > 104 km2) that contribute roughly half of tropical rainfall. Statistical associations of rain-weighted radar precipitation feature (RPF) size distributions with atmospheric variables on the 1.5° grid of ERA-Interim data are explored. In one-predictor distributions, the association with total precipitable water vapor (TPWV) is the strongest, while relative humidity at low and midlevels and low-level wind shear are also positively related to large-RPF rain fraction. Standard CAPE and CIN variables computed from grid-mean thermodynamic profiles are only weakly related to the size of rain systems. Joint distributions over two variables are also reported. The relative importance of predictors varies over different regions. The eastern Pacific is distinctive for having large rain systems in environments with a moist boundary layer but a dry midtroposphere, with strong shallow wind shear and small CAPE. In contrast, the large-storm environment over the western Pacific is found to be moister in the whole troposphere, with relatively weaker wind shear and larger CAPE. Over tropical land, the Sahel and central Africa stand out as having a great fractional rainfall contributed by large RPFs. Their associated environment is characterized by lower TPWV but stronger shallow wind shear and larger CIN and CAPE, in comparison to the equatorial Amazon basin and the Maritime Continent. Based on these associations, statistical reconstructions of the geographical distribution of large-RPF rain fraction from grid-mean atmospheric predictors are attempted.

Convection-permitting numerical experiments using the Weather Research and Forecasting (WRF) Model are performed to examine the diurnal cycles of land and sea breeze and its related precipitation over the south China coastal region during the mei-yu season. The focus of the analyses is a 10-day simulation initialized with the average of the 0000 UTC gridded global analyses during the 2007–09 mei-yu seasons (11 May–24 June) with diurnally varying cyclic lateral boundary conditions. Despite differences in the rainfall intensity and locations, the simulation verified well against averages of 3-yr ground-based radar, surface, and CMORPH observations and successfully simulated the diurnal variation and propagation of rainfall associated with the land and sea breeze over the south China coastal region. The nocturnal offshore rainfall in this region is found to be induced by the convergence line between the prevailing low-level monsoonal wind and the land breeze. Inhomogeneity of rainfall intensity can be found along the coastline, with heavier rainfall occurring in the region with coastal orography. In the night, the mountain–plain solenoid produced by the coastal terrain can combine with the land breeze to enhance offshore convergence. In the daytime, rainfall propagates inland with the inland penetration of the sea breeze, which can be slowed by the coastal mountains. The cold pool dynamics also plays an essential role in the inland penetration of precipitation and the sea breeze. Dynamic lifting produced by the sea-breeze front is strong enough to produce precipitation, while the intensity of precipitation can be dramatically increased with the latent heating effect.

Two-dimensional video disdrometer (2DVD) data were analyzed from two equatorial Indian (Gan) and west Pacific Ocean (Manus) islands where precipitation is primarily organized by the intertropical convergence zone and the Madden–Julian oscillation (MJO). The 18 (3.5) months of 2DVD data from Manus (Gan) Island show that 1) the two sites have similar drop size distribution (DSD) spectra of liquid water content, median diameter, rain rate R, radar reflectivity z, normalized gamma number concentration Nw, and other integral rain parameters; 2) there is a robust Nw-based separation between convective (C) and stratiform (S) DSDs at both sites that produces consistent separation in other parameter spaces. The 2DVD data indicate an equatorial, maritime average C/S rainfall accumulation fraction (frequency) of 81/19 (41/59) at these locations. It is hypothesized that convective fraction and frequency estimates are slightly higher than previous radar-based studies, because the ubiquitous weak, shallow convection (

This paper presents analyses of the microphysical structure of comma head stratiform precipitation in 14 continental cyclones, focusing on fall streaks of hydrometeors produced by cloud-top convective generating cells. Data were obtained at temperatures between −4° and −45°C using in situ instrumentation and the W-band University of Wyoming Cloud Radar, all operated aboard the National Science Foundation/National Center for Atmospheric Research C-130. Analyses are presented first for a case study of one cyclone, followed by statistical analyses of the full dataset. Using radar-based objective classifications, the statistical percentile number concentrations averaged 1.9 times larger within the fall streaks compared to the regions between them, and the corresponding ice water content and median mass diameter values averaged 2.2 and 1.1 times larger. Ice-phase conditions were predominant within the stratiform precipitation, with deposition and aggregation the primary ice growth mechanisms. No distinct vertical velocity signatures were associated with the fall streaks, and similar ice growth mechanisms were common within and between them. Combined with observations of cloud-top generating cells in many of the same cyclones, these analyses provide a more complete description of the comma head microphysical structure and the physical processes producing precipitation. Whereas the generating cells are critical to nucleation and initial ice growth, the majority of ice growth (exceeding 90% of the median ice water contents in the case study) typically occurred below the generating-cell level, where enhanced moisture associated with synoptic-scale ascent was present.

This study uses Dynamics of the Madden–Julian Oscillation (DYNAMO) shipborne [Research Vessel (R/V) Roger Revelle] radar and Tropical Rainfall Measuring Mission (TRMM) Precipitation Radar (PR) datasets to investigate MJO-associated convective systems in specific organizational modes [mesoscale convective system (MCS) versus sub-MCS and linear versus nonlinear]. The Revelle radar sampled many “climatological” aspects of MJO convection as indicated by comparison with the long-term TRMM PR statistics, including areal-mean rainfall (6–7 mm day−1), convective intensity, rainfall contributions from different morphologies, and their variations with MJO phase. Nonlinear sub-MCSs were present 70% of the time but contributed just around 20% of the total rainfall. In contrast, linear and nonlinear MCSs were present 10% of the time but contributed 20% and 50%, respectively. These distributions vary with MJO phase, with the largest sub-MCS rainfall fraction in suppressed phases (phases 5–7) and maximum MCS precipitation in active phases (phases 2 and 3). Similarly, convective–stratiform rainfall fractions also varied significantly with MJO phase, with the highest convective fractions (70%–80%) in suppressed phases and the largest stratiform fraction (40%–50%) in active phases. However, there are also discrepancies between the Revelle radar and TRMM PR. Revelle radar data indicated a mean convective rain fraction of 70% compared to 55% for TRMM PR. This difference is mainly due to the reduced resolution of the TRMM PR compared to the ship radar. There are also notable differences in the rainfall contributions as a function of convective intensity between the Revelle radar and TRMM PR. In addition, TRMM PR composites indicate linear MCS rainfall increases after MJO onset and produce similar rainfall contributions to nonlinear MCSs; however, the Revelle radar statistics show the clear dominance of nonlinear MCS rainfall.

A methodology is proposed to investigate the scale dependence of the predictability of precipitation patterns at the mesoscale. By applying it to two or more precipitation fields, either modeled or observed, a decorrelation scale can be defined such that all scales smaller than are fully decorrelated. For precipitation forecasts from a radar data–assimilating storm-scale ensemble forecasting (SSEF) system, is found to increase with lead time, reaching 300 km after 30 h. That is, for , the ensemble members are fully decorrelated. Hence, there is no predictability of the model state for these scales. For , the ensemble members are correlated, indicating some predictability by the ensemble. When applied to characterize the ability to predict precipitation as compared to radar observations by numerical weather prediction (NWP) as well as by Lagrangian persistence and Eulerian persistence, increases with lead time for most forecasting methods, while it is constant (300 km) for non–radar data–assimilating NWP. Comparing the different forecasting models, it is found that they are similar in the 0–6-h range and that none of them exhibit any predictive ability at meso-γ and meso-β scales after the first 2 h. On the other hand, the radar data–assimilating ensemble exhibits predictability of the model state at these scales, thus causing a systematic difference between corresponding to the ensemble and corresponding to model and radar. This suggests that either the ensemble does not have sufficient spread at these scales or that the forecasts suffer from biases.

The representation of the Madden–Julian oscillation (MJO) is still a challenge for numerical weather prediction and general circulation models (GCMs) because of the inadequate treatment of convection and the associated interactions across scales by the underlying cumulus parameterizations. One new promising direction is the use of the stochastic multicloud model (SMCM) that has been designed specifically to capture the missing variability due to unresolved processes of convection and their impact on the large-scale flow. The SMCM specifically models the area fractions of the three cloud types (congestus, deep, and stratiform) that characterize organized convective systems on all scales. The SMCM captures the stochastic behavior of these three cloud types via a judiciously constructed Markov birth–death process using a particle interacting lattice model. The SMCM has been successfully applied for convectively coupled waves in a simplified primitive equation model and validated against radar data of tropical precipitation. In this work, the authors use for the first time the SMCM in a GCM. The authors build on previous work of coupling the High-Order Methods Modeling Environment (HOMME) NCAR GCM to a simple multicloud model. The authors tested the new SMCM-HOMME model in the parameter regime considered previously and found that the stochastic model drastically improves the results of the deterministic model. Clear MJO-like structures with many realistic features from nature are reproduced by SMCM-HOMME in the physically relevant parameter regime including wave trains of MJOs that organize intermittently in time. Also one of the caveats of the deterministic simulation of requiring a doubling of the moisture background is not required anymore.

This study investigates the convective population and environmental conditions during three MJO events over the central Indian Ocean in late 2011 using measurements collected from the Research Vessel (R/V) Roger Revelle deployed in Dynamics of the MJO (DYNAMO). Radar-based rainfall estimates from the Revelle C-band radar are first placed in the context of larger-scale Tropical Rainfall Measuring Mission (TRMM) rainfall data to demonstrate that the reduced Revelle radar range captured the MJO convective evolution. Time series analysis and MJO phase-based composites of Revelle measurements both support the “recharge–discharge” MJO theory. Time series of echo-top heights indicate that convective deepening during the MJO onset occurs over a 12–16-day period. Composite statistics show evident recharging–discharging features in convection and the environment. Population of shallow/isolated convective cells, SST, CAPE, and the lower-tropospheric moisture increase (recharge) substantially approximately two to three phases prior to the MJO onset. Deep and intense convection and lightning peak in phase 1 when the sea surface temperature and CAPE are near maximum values. However, cells in this phase are not well organized and produce little stratiform rain, possibly owing to reduced shear and a relatively dry upper troposphere. The presence of deep convection leads the mid- to upper-tropospheric humidity by one to two phases, suggesting its role in moistening these levels. During the MJO onset (i.e., phase 2), the mid- to upper troposphere becomes very moist, and precipitation, radar echo-top heights, and the mesoscale extent of precipitation all increase and obtain peak values. Persistent heavy precipitation in these active periods helps reduce the SST and dry/stabilize (or discharge) the atmosphere.

The impact of the collisional warm-rain microphysical processes on the polarimetric radar variables is quantified using a coupled microphysics–electromagnetic scattering model. A one-dimensional bin-microphysical rain shaft model that resolves explicitly the evolution of the drop size distribution (DSD) under the influence of collisional coalescence and breakup, drop settling, and aerodynamic breakup is coupled with electromagnetic scattering calculations that simulate vertical profiles of the polarimetric radar variables: reflectivity factor at horizontal polarization ZH, differential reflectivity ZDR, and specific differential phase KDP. The polarimetric radar fingerprint of each individual microphysical process is quantified as a function of the shape of the initial DSD and for different values of nominal rainfall rate. Results indicate that individual microphysical processes (collisional processes, evaporation) display a distinctive signature and evolve within specific areas of ZH–ZDR and ZDR–KDP space. Furthermore, a comparison of the resulting simulated vertical profiles of the polarimetric variables with radar and disdrometer observations suggests that bin-microphysical parameterizations of drop breakup most frequently used are overly aggressive for the largest rainfall rates, resulting in very “tropical” DSDs heavily skewed toward smaller drops.

This paper describes an analysis of multiyear satellite datasets that subdivide two halves (faster and slower) of the space–time spectral signal peaks corresponding to convectively coupled equatorial waves such as Kelvin and inertia–gravity waves [n = 0 eastward inertia–gravity wave (EIGn0 wave), and n = 1 and n = 2 westward inertia–gravity waves (WIGn1 and WIGn2 waves, respectively)]. The faster (slower) component of an equatorial wave is defined as that which has a spectral signal peak in the regions with deeper (shallower) equivalent depths. The data obtained from the Tropical Rainfall Measuring Mission (TRMM) precipitation radar (TRMM-PR) are composited around space–time-filtered equatorial-belt data from the TRMM-3B42 rainfall product to separately estimate the convective and stratiform rainfall modulations. Results indicate that the faster components of WIGn1 and WIGn2 waves modulate convective rain relatively more (and stratiform rain relatively less) than their slower counterparts. For Kelvin and EIGn0 waves, however, there is no significant difference in the rainfall modulation between their faster and slower components. A space–time cospectral analysis of the satellite-retrieved rainfall and moisture shows that in the spectral regions corresponding to WIGn1 and WIGn2 waves, precipitation is significantly correlated with low-level moisture but not with midlevel moisture. In contrast, significant coherence between rainfall and moisture at these levels is found in the spectral regions corresponding to the Kelvin and EIGn0 waves. These results may bear on different convection–wave coupling mechanisms for these “divergent” waves (stratiform instability versus moisture–stratiform instability).

The effect of the environment on individual clouds makes it difficult to isolate the signal of the aerosol indirect effect, particularly at larger spatial and temporal scales. This study uses observations from the Tropical Rainfall Measuring Mission (TRMM), CloudSat, and Aqua satellites to identify convective cloud systems in clean and dirty environments. The Moderate Resolution Imaging Spectroradiometer (MODIS) aerosol index is collocated with radar precipitation features (RPFs) from TRMM and congestus cloud features (CFs) from CloudSat. The Interim ECMWF Re-Analysis (ERA-Interim) is interpolated to identify the environmental profile surrounding each feature. Regions in Africa, the Amazon, the Atlantic Ocean, and the southwestern United States are examined. TRMM features in the Africa and Amazon regions are more intense and have higher lightning flash rates under dirty background conditions. RPFs in the southwestern United States are more intense under clean background conditions. The Atlantic region shows little difference in intensity. The differences found in the mean thermodynamic profile for RPFs forming in clean and dirty environments could explain these differences in convective intensity.Congestus identified with CloudSat show smaller differences between clouds forming in clean and dirty environments in Africa and the Amazon. Congestus in clean environments have higher reflectivities and generally larger widths, but no trend is seen in cloud-top height. The signal of the aerosol indirect effect is so small that it is very difficult to detect confidently using these methods. The environment must be considered in any study of the aerosol indirect effect, because important environmental changes can occur as aerosols are introduced to an air mass.

Three-dimensional radar reflectivity fields from a dual-wavelength Doppler polarimetric radar (S-PolKa) deployed in the equatorial Indian Ocean are used to evaluate the composition of the population of convective cloud elements during active phases of the MJO. Rainfall in active periods was intermittent, occurring in 11 episodes of about 2–4 days, separated by several nonrainy days. Data for these 2-day periods were composited relative to the time of maximum rainfall. Analysis of the S-PolKa data shows the makeup of the convective population during the rainfall episodes. Four types of echo structures were analyzed statistically for the 11 rainfall episodes: shallow convective echoes (SCE), deep convective cores (DCC), wide convective echo cores (WCC), and broad stratiform (BSR) echo regions. SCE and DCC events were most frequent before the maximum rainfall, with the peak frequency of SCE leading that of DCCs. WCCs were most frequent during the rainfall maximum, and BSR regions were most frequent in the later part of the rainfall episode. Composited ECMWF Interim Re-Analysis (ERA-Interim) data and 3-hourly atmospheric soundings indicate that the 2–4-day episodes were related to the passage of equatorial waves. In the early part of a rainfall episode, the wave-passage conditions were unstable, favoring deep penetrating convective elements, while in the later period the wave divergence profile was commensurate with convective systems in late anvil-producing stages. These results support the stretched building-block notion of the life cycle of tropical convection and confirm satellite-based interpretations of SCE, DCC, WCC, and BSR statistics in the composition of the convective population.

This study uses ground-based dual-Doppler radar and surface observations to document the structural and surface features of the arc-shaped radar echoes (ASREs) evident along an outer rainband of Typhoon Longwang as it approached northern Taiwan on 1 October 2005. The particular aim of this study is to explore the possible distinction between the present case, previously documented tropical cyclone rainbands (TCRs), and squall lines. The dual-Doppler-derived fields show that the leading precipitation of the studied ASREs exhibited a convective nature with a sharp horizontal gradient of reflectivity and a significant vertical extent. The regions behind the leading convection were characterized by band-relative rear-to-front flow at low levels and were associated with a broader area of stratiform precipitation. The deep layer of front-to-rear flow extending from the surface to the upper troposphere was generally present ahead of the ASREs. This flow appears to be lifted upward at and immediately ahead of the leading edge of the low-level rear-to-front flow to form rearward-tilting updrafts. These airflow patterns are similar to those of the convective region of squall lines but differ fundamentally from those of previously documented TCRs that were located closer to the inner core of cyclones. The detailed analyses of surface fluctuations during the passage of one of the studied ASREs further show an abrupt pressure rise (2 mb), a temperature drop (4°C), and a pronounced deceleration of inflow air coincident with the leading heavy precipitation. The evaluation presented suggests that the convectively generated cold pool may be important in influencing the structures and propagation of the studied ASREs.

In a Lagrangian frame of reference, the accuracy of rainfall systems predicted by nowcasting algorithms can be improved by incorporating the growth and decay of the rainfall. The scale dependence of predictability of growth and decay of continental-scale precipitating systems is studied with the help of the U.S. national radar composites. The growth and decay of precipitating systems is estimated in a time interval τ by correcting the precipitation image for advection and rotation at time t + τ with respect to the precipitation image at time t and then subtracting the former from the latter. Results show that the two-dimensional correlation of growth and decay has an elliptical structure, indicating that growth and decay is nonisotropic. The probability density function of precipitation intensities and of growth and decay follows a Gaussian distribution. The scale-dependence analysis of growth and decay patterns indicates that the growth and decay of rainfall may be predictable up to about 2 h for scales larger than 250 km.

Equatorial atmospheric waves in the upper troposphere and lower stratosphere (UTLS), excited by latent heating, are investigated by using a global spectral model. The latent heating profiles are derived from the 3-hourly Tropical Rainfall Measuring Mission (TRMM) rain rates, which include both convective- and stratiform-type profiles. The type of heating profile is determined based on an intensity of the surface rain rate. Latent heating profiles over stratiform rain regions, estimated from the TRMM Precipitation Radar (PR) product, are applied to derive the stratiform-type latent heating profiles from the gridded rain rate data. Monthly zonal-mean latent heating profiles derived from the rain rates appear to be reasonably comparable with the TRMM convective/stratiform heating product. A broad spectrum of Kelvin, mixed Rossby–gravity (MRG), equatorial Rossby (ER), and inertia–gravity waves are generated in the model. Particularly, equatorial waves (Kelvin, ER, and MRG waves) of zonal wavenumbers 1–5 appear to be dominant in the UTLS. In the wavenumber–frequency domain, the equatorial waves have prominent spectral peaks in the range of 12–200 m of the equivalent depth, while the spectral peaks of the equatorial waves having shallower equivalent depth ( The horizontal and vertical structures of the simulated equatorial waves (Kelvin, ER, and MRG waves) are in a good agreement with the equatorial wave theory and observed wave structure. In particular, comparisons of the simulated Kelvin waves and the High Resolution Dynamics Limb Sounder (HIRDLS) satellite observation are discussed.

Kelvin–Helmholtz waves were observed by the Twin Lakes, Oklahoma (KTLX), Weather Surveillance Radar-1988 Doppler (WSR-88D); the Norman, Oklahoma (KOUN), polarimetric WSR-88D; and the polarimetric Collaborative Adaptive Sensing of the Atmosphere (CASA) radars on 30 November 2006 during a winter storm in central Oklahoma. The life cycle and structure of the waves are analyzed from the radar data, and the nearby atmospheric conditions are examined. The initial perturbations associated with the waves are first evident only in the radars’ radial velocity fields. As the waves mature, perturbations become discernable in the reflectivity factor Z and spectrum width (SW) fields of both radars, and in the differential reflectivity Zdr and, to a lesser extent, the cross-correlation coefficient ρhv fields of KOUN. As the waves break and begin to dissipate, the perturbations subside. A dual-Doppler analysis is synthesized to examine the kinematic structure of the waves and to relate the polarimetric observations to the kinematics. It is determined that Z and Zdr are enhanced in regions of upward motion (wave crests), and ρhv is reduced in the same vicinity and near the base of the wave circulations. Vertical velocity perturbations transport horizontal momentum upward and downward, inducing horizontal wind perturbations that are approximately 90° out of phase and downstream from their corresponding vertical velocity perturbations. Perturbations in Z, Zdr, and ρhv are observed in the vicinity of wave crests while SW perturbations occur predominately in and just upstream from wave troughs. It is determined that perturbations in the polarimetric variables are a result of the waves modifying local precipitation microphysics. Perturbations in Z and Zdr are hypothesized to be the result of columnar ice crystal generation whereas those in ρhv likely result from the mixing of ice crystals of various shapes and sizes. Perturbations in SW are a result of turbulent motions likely associated with wave breaking and downward advection of a strong shear layer.

Shallow marine trade wind cumuli are one of the most prevalent cloud types in the tropical atmosphere. Understanding how precipitation forms within these clouds is necessary to advance our knowledge concerning their role in climate. This paper presents a statistical analysis of the characteristic heights and times at which precipitation in trade wind clouds passes through distinct stages in its evolution as defined by the equivalent radar reflectivity factor at horizontal polarization ZH, the differential reflectivity ZDR, and the spatial correlation between and averages of these variables. The data were obtained during the Rain in Cumulus over the Ocean (RICO) field campaign by the National Center for Atmospheric Research (NCAR) S-band dual-polarization (S-Pol) Doppler radar, the National Science Foundation (NSF)–NCAR C130 aircraft, and soundings launched near the radar. The data consisted of 76 trade cumuli that were tracked from early echo development through rainout on six days during RICO. Trade wind clouds used in the statistical analyses were segregated based on giant condensation nuclei (GCN) measurements made during low-level aircraft flight legs on the six days. This study found that the rate of precipitation formation in shallow marine cumulus was unrelated to the GCN concentration in the ambient environment. Instead, the rate at which precipitation developed in the clouds appeared to be related to the mesoscale forcing as suggested by the cloud organization. Although GCN had no influence on the rate of precipitation development, the data suggest that they do contribute to a modification of the rain drop size distribution within the clouds. With very few exceptions, high threshold values of ZDR were found well above cloud base on days with high GCN concentrations. On the days that were exceptions, these threshold values were almost always achieved near cloud base.

Cloud-nucleating aerosols emitted from mainland China have the potential to influence cloud and precipitation systems that propagate through the region of the East China Sea. Both simulations from the Spectral Radiation-Transport Model for Aerosol Species (SPRINTARS) and observations from the Moderate Resolution Imaging Spectroradiometer (MODIS) reveal plumes of pollution that are transported into the East China Sea via frontal passage or other offshore flow. Under such conditions, satellite-derived precipitation estimates from the Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI) and Precipitation Radar (PR) frequently produce discrepancies in rainfall estimates that are hypothesized to be a result of aerosol modification of cloud and raindrop size distributions. Cloud-resolving model simulations were used to explore the impact of aerosol loading on three identified frontal-passage events in which the TMI and PR precipitation estimates displayed large discrepancies. Each of these events was characterized by convective and stratiform elements in association with a frontal passage. Area-averaged time series for each event reveal similar monotonic cloud and rain microphysical responses to aerosol loading. The ratio in the vertical distribution of cloud water to rainwater increased. Cloud droplet concentration increased and the mean diameters decreased, thereby reducing droplet autoconversion and collision–coalescence growth. As a result, raindrop concentration decreased, while the drop mean diameter increased; furthermore, average rainwater path magnitude and area fraction both decreased. The average precipitation rate fields reveal a complex modification of the timing and spatial coverage of rainfall. This suggests that the warm-rain microphysical response to aerosols, in addition to the precipitation life cycle, microphysical feedbacks, and evaporative effects, play an important role in determining surface rainfall.

In previous work, it was argued that a source of radar coherent scatter occurs in the direction perpendicular to the direction of wave propagation because of the presence of grids of enhanced particle concentrations with spatial periodicities in resonance with the radar wavelength. While convincing, the evidence thus far has been indirect. In this work the authors now present direct observations of radar coherent backscattered signals in precipitation in the direction of wave propagation. The theory is developed for the cross-correlation function of the complex amplitudes in the direction of propagation calculated for nearest neighbor range bins. Data are analyzed in snow and in rain. The results agree with the earlier conclusions in the previous work, namely that coherent scatter occurs in both rain and snow, that it is larger in snow than it is in rain, and that it can be significant at times.

S-band radar surveillance scans of precipitating shallow convection are analyzed. The scans are complied from 52 days of near-continuous measurements in the winter trades of the North Atlantic during the Rain in Cumulus over the Ocean (RICO) field campaign. After being analyzed and filtered to exclude spurious returns, the scans are segmented to identify contiguous returns, or echoes. The echo size and reflectivity statistics are then analyzed. A new normalization method is developed to account for biases associated with the nonuniformity in the native radar grid. The echo area distribution robustly exhibits power-law scaling up until sizes of about 10 km2, with a scaling exponent of about −1.1. At larger sizes the scaling behavior breaks down and varies more markedly across subsamples of the data. Conditional sampling suggests that the scaling behavior of the larger echoes does, however, approach that of the smaller echoes as echo coverage increases, which supports the idea of a limiting distribution. Departures from this limiting distribution are argued to reflect finite size effects, modulated by the presence of a capping inversion whose height and strength varies across the samples.

Macro- and microphysical properties of single-layer stratiform mixed-phase clouds are derived from multiple years of lidar, radar, and radiosonde observations. Measurements were made as part of the Mixed-Phase Arctic Clouds Experiment (MPACE) and the Study of Environmental Arctic Change (SEARCH) in Barrow, Alaska, and Eureka, Nunavut, Canada, respectively. Single-layer mixed-phase clouds occurred between 4% and 26% of the total time observed, varying with season and location. They had mean cloud-base heights between ∼700 and 2100 m and thicknesses between ∼200 and 700 m. Seasonal mean cloud optical depths ranged from 2.2 up. The clouds existed at temperatures of ∼242–271 K and occurred under different wind conditions, depending on season. Utilizing retrievals from a combination of lidar, radar, and microwave radiometer, mean cloud microphysical properties were derived, with mean liquid effective diameters estimated from 16 to 49 μm, mean liquid number densities on the order of 104–105 L−1, and mean water contents estimated between 0.07 and 0.28 g m−3. Ice precipitation was shown to have mean ice effective diameters of 50–125 μm, mean ice number densities on the order of 10 L−1, and mean water contents estimated between 0.012 and 0.031 g m−3. Mean cloud liquid water paths ranged from 25 to 100 g m−2. All results are compared to previous studies, and potential retrieval errors are discussed. Additionally, seasonal variation in macro- and microphysical properties was highlighted. Finally, fraction of liquid water to ice mass was shown to decrease with decreasing temperature.

Cloud and precipitation simulated using the three-dimensional (3D) Goddard Cumulus Ensemble (GCE) model are compared to Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI) and Precipitation Radar (PR) rainfall measurements and Clouds and the Earth’s Radiant Energy System (CERES) single scanner footprint (SSF) radiation and cloud retrievals. Both the model simulation and retrieved parameters are based upon observations made during the South China Sea Monsoon Experiment (SCSMEX) field campaign. The model-simulated cloud and rain systems are evaluated by systematically examining important parameters such as the surface rain rate, convective/stratiform percentage, rain profiles, cloud properties, and precipitation efficiency. It is demonstrated that the GCE model is capable of simulating major convective system development and reproduces the total surface rainfall amount as compared to rainfall estimated from the SCSMEX sounding network. The model yields a slightly higher total convective rain/stratiform rain ratio than the TMI and PR observations. The GCE rainfall spectrum exhibits a greater contribution from heavy rains than those estimated from PR or TMI observations. In addition, the GCE simulation produces much greater amounts of snow and graupel than the TRMM retrievals. The model’s precipitation efficiency of convective rain is close to the observations, but the precipitation efficiency of stratiform rain is much lower than the observations because of large amounts of slowly falling simulated snow and graupel. Compared to observations, the GCE produces more compact areas of intense convection and less anvil cloud, which are consistent with a smaller total cloud fraction and larger domain-averaged outgoing longwave radiation.

A method of analyzing radar data is developed and applied to determine whether the X-band radar reflectivity evolution of clouds observed during summertime on the northeast Florida coast during the Small Cumulus Microphysics Study (SCMS) shows distinct differences in precipitation development that can be associated with the clouds’ maritime or continental characteristics. For this study, the entire National Center for Atmospheric Research CP2 radar dataset from SCMS was examined, and 38 clouds were used. For these clouds the evolution in X-band radar reflectivity, from the clouds’ earliest detection through precipitation, was clearly documented and met specific requirements concerning the clouds’ location relative to the coastline and direction of movement. Since cloud condensation nuclei (CCN) and giant and ultragiant nuclei (GN) measurements were not available for the specific clouds used in this study, proxies were used to partition the clouds into four groups based on the cloud location and direction of movement. Specifically, it was assumed that clouds forming over the ocean during onshore flow had maritime characteristics (group 1: low CCN, high GN), clouds forming over land during onshore flow would have modified maritime characteristics (group 2: high CCN, high GN), clouds forming over land during offshore flow would have continental characteristics (group 3: high CCN, low GN), and clouds forming over the ocean during offshore flow would have modified continental characteristics (group 4: high CCN, high GN). These assumptions are based on past measurements presented by Sax and Hudson. Then, these populations were statistically compared using the nonparametric multiresponse permutation procedure developed by Mielke et al. A comparison of groups 1 and 2 provided a test of the role of CCN concentrations in precipitation development in these cloud populations. A comparison of groups 3 and 4 provided a test of the role of GN concentrations in precipitation development in these cloud populations. The two cloud populations that were disjoint at a statistically significant level were groups 1 and 2. For these groups, the analysis showed that the median characteristic total water content of the truly maritime clouds (group 1) was about half that of the modified maritime clouds (group 2) at the time of precipitation formation. The characteristic time to precipitation formation was about 60% smaller for the truly maritime clouds. Thus, the characteristic reflectivity threshold for precipitation development was reached at a much lower altitude above cloud base in a much faster time in the truly maritime clouds. This result supports the conclusions of Hudson and Yum that precipitation development in the SCMS clouds was primarily controlled by CCN concentrations rather than GN concentrations.

Directionally averaged time series of precipitation rates for eight warm seasons (1996–2003) over the continental United States derived from Next Generation Weather Radar (NEXRAD) measurements are analyzed using spectral decomposition methods. For the latitudinally averaged data, in addition to previously identified diurnal and semidiurnal cycles, the temporal spectra show cross-scale self-similarity and periodicity. This property is revealed by a power-law scaling with an exponent of −4/3 for the frequency band higher than semidiurnal and −3/4 for the 1–3-day band. For the longitudinally averaged series the scaling exponent for the frequency band higher than semidiurnal changes from −4/3 to −5/3 revealing anisotropic properties. The dominant periods and propagation speeds display temporal variability on about 1/2, 1, 4, 11, and 25 days. Composite patterns describing periods of 5 days) patterns propagate westward suggesting the influence of large-scale waves, and both dominant periods and propagation speeds show marked interannual variability. The implied dependence between propagation and mean-flow for

Predictability of precipitation is examined from storm to synoptic scales through an experimental approach using continent-scale radar composite images. The lifetime of radar reflectivity patterns in Eulerian and Lagrangian coordinates is taken as a measure of predictability. The results are stratified according to scale, location, and time in order to determine how predictability depends on these parameters. Three companion papers give a detailed description of the methodology, and present results are obtained for 143 hours of North American warm season rainfall with emphasis on lifetime, scale dependence, optimum smoothing of forecast fields, and predictability in terms of probabilistic rainfall rates. This paper discusses the sources of forecast uncertainty and extends the analysis to a total of 1424 hours of rainfall. In a Lagrangian persistence framework the predictability problem can be separated into a component associated with growth of precipitation and a component associated with changes in the storm motion field. The role of changes in the motion field turned out to be small but not negligible. A stratification of lifetime according to location reveals the regions with high predictability and significant nonstationary storm motion. This work is of high practical significance for three reasons: First, Lagrangian persistence of radar patterns was proved to have skill for probabilistic precipitation nowcasting. The discussion of the sources of uncertainty provides a guideline for further improvements. Second, a scale- and location-dependent benchmark is obtained against which the progress of other precipitation forecasting techniques can be evaluated. And, third, the experimental approach to predictability presented in this paper is a valuable contribution to the fundamental question of predictability of precipitation.

Examination of the early radar echo histories of several vigorous, cumulus clouds in northeast Colorado and northwest Kansas, with sensitive, dual-polarization radar, reveals the formation of millimeter-sized water drops at about the same time that the conventional, first precipitation echo (from ice) forms aloft. The early, positive ZDR values appear in the vicinity of the 0°C level (the radar data do not specify height accurately) and soon extend both above and below it. Positive ZDR is found within and to the upwind side of the updraft, separate from the conventional first precipitation echoes, which appear first at higher altitude, generally downwind of the updraft core, and have no significantly positive ZDR. Big, liquid drops were not expected this early in the formation of continental cumulus. The early presence of supercooled water drops larger than cloud droplets may be a significant factor in the glaciation of these clouds. The kind of early radar coverage illustrated here would be a priceless adjunct to aircraft studies of precipitation formation in cumulus. Microphysical data from aircraft must be interpreted with numerical models in order to deduce (or verify) the processes, and such models require the kind of early data illustrated here, both for initialization and verification.

A physically intuitive and computationally simple precipitation mapping algorithm has been developed for use with the airborne Advanced Microwave Precipitation Radiometer (AMPR). The algorithm is based on microwave emission and scattering properties of precipitation. Specifically, emission by liquid water allows increasing brightness temperatures at low frequencies to be interpreted as increasing rain rates. Scattering by large hydrometeors (particularly graupel and hail) causes relative minima in the brightness temperatures, with progressively larger hydrometeors scattering progressively longer wavelengths. The vigor of convection is therefore ascertained according to which wavelengths are being significantly scattered. The combination of emission and scattering information from four microwave channels is used to assign a precipitation category, which is related to the liquid rain rate, the vertical extent of precipitation, and the vigor of convection. The qualitative precipitation categories output by the passive microwave algorithm have been verified using coincident radar (ER-2 Doppler Radar - EDOP) and electric field measurements (Lightning Instrument Package - LIP). These coincident measurements can subsequently be used to quantify rain rates, hydrometeor contents, and vertical profiles that are typical for each precipitation category. This algorithm has been developed using an airborne platform. Comparisons are being made with other airborne, satellite, and ground-based radar and radiometer data. This technique shows promise both as a research tool and potentially as a real-time analysis tool, which could be applied to either traditional or uninhabited aerial vehicles.

The threat of flooding from landfalling tropical cyclones is a function of the local variation in rain rate and rain accumulation. To date, these have been inferred from single-frequency radar reflectivity measurements. However, the Tropical Rainfall Measuring Mission experience has confirmed that one of the main difficulties in retrieving rain profiles using a single-frequency radar is the unknown raindrop size distribution (DSD). A dual-frequency radar such as the one planned for the upcoming Global Precipitation Measurement (GPM) core satellite is expected to help sort out at least part of this DSD-induced ambiguity. However, the signature of precipitation at 14 GHz does not differ greatly from its signature at 35 GHz (the GPM radar frequencies). To determine the extent of the vertical variability of the DSD in tropical systems and to quantify the effectiveness of a dual-frequency radar in resolving this ambiguity, several different models of DSD shape are considered and used to estimate the rain-rate and mean-diameter profiles from the measurements made by Jet Propulsion Laboratory’s (JPL’s) airborne second generation precipitation radar (PR-2) over Hurricanes Gabrielle and Humberto during the Fourth Convection and Moisture Experiment (CAMEX-4) in September 2001. It turns out that the vertical structures of the rain profiles retrieved from the same measurements under different DSD assumptions are similar, but the profiles themselves are quantitatively significantly different.

Observations from the East Pacific Investigation of Climate (EPIC) 2001 field campaign are well suited for exploring the relationships among the diurnal cycle, mesoscale (10–100 km) structure, and precipitation in the stratocumulus region in the southeast Pacific. Meteorological time series and observations from a scanning C-band radar, vertically pointing cloud radar, and ceilometer, as well as satellite data, are used to show that drizzle is associated with increased variability in cloud and boundary layer properties compared to nondrizzling periods. The stratocumulus-topped boundary layer is typically well mixed at night, transitioning to less well mixed in the afternoon, with drizzle most frequently occurring in the early morning. Coherent patches of drizzle, or “cells,” can have large areas with radar reflectivities of greater than 5 dBZ of up to about 100 km2. Individual cells have long lifetimes, up to 2 h, and appear to be replenished by moisture in the boundary layer.

The application of polarimetric radar data to the retrieval of raindrop size distribution parameters and rain rate in samples of convective and stratiform rain types is presented. Data from the Colorado State University (CSU), CHILL, NCAR S-band polarimetric (S-Pol), and NASA Kwajalein radars are analyzed for the statistics and functional relation of these parameters with rain rate. Surface drop size distribution measurements using two different disdrometers (2D video and RD-69) from a number of climatic regimes are analyzed and compared with the radar retrievals in a statistical and functional approach. The composite statistics based on disdrometer and radar retrievals suggest that, on average, the two parameters (generalized intercept and median volume diameter) for stratiform rain distributions lie on a straight line with negative slope, which appears to be consistent with variations in the microphysics of stratiform precipitation (melting of larger, dry snow particles versus smaller, rimed ic...

Satellite-derived brightness temperature has been used to estimate tropical precipitation. Ricciardulli and Garcia applied it to quantify forcing of atmospheric waves that are excited by tropical cumulus convection and propagate into the middle atmosphere. Because of the broad coverage of the satellite data, this method provides exclusively dense information on wave forcing and is especially valuable for middle-atmosphere modeling. However, the validity of the method has not been investigated, which is done in this study using radar-derived precipitation during the Tropical Ocean and Global Atmosphere Coupled Ocean–Atmosphere Response Experiment (TOGA COARE) field experiment. The method is shown to overestimate the variance of precipitation so that the wave forcing derived with it is too strong. The overestimation is most severe at coarse resolution, reaching nearly an order of magnitude at a grid scale of 2°, which is comparable to typical resolutions of current global climate models. Although t...

The occurrence frequency and rainfall production of mesoscale convective systems (MCSs) relative to smaller groups of convective clouds over the tropical oceans is not well known. Eighty days of shipboard radar data collected during the recent Tropical Ocean Global Atmosphere Coupled Ocean–Atmosphere Response Experiment (TOGA COARE) were used to provide a detailed view of convection in the western Pacific warm pool, a region of global climatological significance. The aim of this study was to document the frequency of occurrence, rainfall production, and depth of convection observed during TOGA COARE within a simple and meaningful framework of convective horizontal organization. Organization was characterized in terms of the horizontal scale and morphology of convective systems. Precipitation events were defined based on whether they attained the length scale of an MCS, and on whether convection was organized into lines. About four-fifths of rainfall during COARE was associated with MCS-scale squa...

In preparation for the launch of TRMM, new algorithms must be created that take advantage of the combined data from radar and microwave radiometers that will be on board the satellite. A microwave radiative transfer algorithm with a one-dimensional cloud model is created that incorporates data from radar and radiometers using data obtained from TCM-90 and TOGA COARE flown over the western Pacific in 1990 and 1993, respectively. A hybrid cloud model (HCM) was developed using observations from TOGA COARE, TCM-90, and other field projects. The HCM is a physically based model that is not “tuned” by limited “ground truth.” Therefore, the HCM incorporated new microphysical data based on observations of clouds. Cloud observations changed the HCM in four ways. First, stratiform clouds with low rain rates were shown to have a low cloud liquid water content (

The second WetNet Precipitation Intercomparison Project (PIP-2) evaluates the performance of 20 satellite precipitation retrieval algorithms, implemented for application with Special Sensor Microwave/Imager (SSM/I) passive microwave (PMW) measurements and run for a set of rainfall case studies at full resolution‐instantaneous space‐timescales. The cases are drawn from over the globe during all seasons, for a period of 7 yr, over a 608N‐ 178S latitude range. Ground-based data were used for the intercomparisons, principally based on radar measurements but also including rain gauge measurements. The goals of PIP-2 are 1) to improve performance and accuracy of different SSM/I algorithms at full resolution‐instantaneous scales by seeking a better understanding of the relationship between microphysical signatures in the PMW measurements and physical laws employed in the algorithms; 2) to evaluate the pros and cons of individual algorithms and their subsystems in order to seek optimal ‘‘front-end’’ combined algorithms; and 3) to demonstrate that PMW algorithms generate acceptable instantaneous rain estimates. It is found that the bias uncertainty of many current PMW algorithms is on the order of 630%. This level is below that of the radar and rain gauge data specially collected for the study, so that it is not possible to objectively select a best algorithm based on the ground data validation approach. By decomposing the intercomparisons into effects due to rain detection (screening) and effects due to brightness temperature‐rain rate conversion, differences among the algorithms are partitioned by rain area and rain intensity. For ocean, the screening differences mainly affect the light rain rates, which do not contribute significantly to area-averaged rain rates. The major sources of differences in mean rain rates between individual algorithms stem from differences in how intense rain rates are calculated and the maximum rain rate allowed by a given algorithm. The general method of solution is not necessarily the determining factor in creating systematic rain-rate differences among groups of algorithms, as we find that the severity of the screen is the dominant factor in producing systematic group differences among land algorithms, while the input channel selection is the dominant factor in producing systematic group differences among ocean algorithms. The significance of these issues are examined through what is called ‘‘fan map’’ analysis. The paper concludes with a discussion on the role of intercomparison projects in seeking improvements to algorithms, and a suggestion on why moving beyond the ‘‘ground truth’’ validation approach by use of a calibration-quality forward model would be a step forward in seeking objective evaluation of individual algorithm performance and optimal algorithm design.

Based on the fundamental relationship involving the interaction of microwave radiation with precipitation, microwave-based satellite precipitation estimates hold the most promise for quantitative rain estimation from space. At present, the low-resolution channels onboard the DMSP Special Sensor Microwave Imager (SSM/I) are sampled with a spatial resolution several times larger than the scale at which rainfall is generated in typical convective rainbands. Aircraft-based instruments can provide views of the detailed microwave radiometric characteristics of precipitating clouds. In this manuscript, the authors present coincident finescale (1–3-km resolution) collocated aircraft radiometric and aircraft precipitation radar measurements collected during the 1993 Tropical Ocean Global Atmosphere Coupled Ocean–Atmosphere Response Experiment in the western Pacific Ocean. By intentionally degrading the resolution of the aircraft datasets from their native resolution to that of current and future spaceborn...

The variational Doppler radar analysis system developed in part I of this study is tested on a Florida airmass storm observed during the Convection and Precipitation/ Electrification Experiment. The 3D wind, temperature, and microphysical structure of this storm are obtained by minimizing the difference between the radar-observed radial velocities and rainwater mixing ratios (derived from reflectivity) and their model predictions. Retrieval experiments are carried out to assimilate information from one or two radars. The retrieved fields are compared with measurements of two aircraft penetrating the storm at different heights. The retrieved wind, thermodynamical, and microphysical fields indicate that the minimization converges to a solution consistent with the input velocity and rainwater fields. The primary difference between using single-Doppler and dual-Doppler information is the reduction of the peak strength of the storm on the order of 10% when information from only one radar is provided. ...

In this study, 600 h of vertically pointing X-band radar data and 50 h of UHF boundary layer wind profiler data were processed and analyzed to characterize quantitatively the structure and the causes of the radar signature from melting precipitation. Five classes of vertical profiles of reflectivity in rain were identified, with three of them having precipitation undergoing a transition between the solid and liquid phase. Only one of them, albeit the most common, showed a radar brightband signature. In-depth study of the bright band and its dependence on precipitation intensity reveals that the ratio of the brightband peak reflectivity to the rainfall reflectivity is constant at 8 dB below 0.5 mm h−1 and then increases to reach 13 dB at 2.5 mm h−1 and 16 dB at 5 mm h−1. The equivalent reflectivity factor of snow just above the melting layer is on average 1–2 dB below the reflectivity of rain just below the melting layer, independent of precipitation intensity. The classical brightband explanation...

In the first part of this paper, the characteristics of microburst-producing storms are examined with a three-dimensional cloud model using soundings from the Cooperative Huntsville Meteorological Experiment (COHMEX). With a grid resolution of 500 m, it is shown that the general characteristics of observed vertical velocities, vertical draft sizes, water contents, radar reflectivities, and surface outflow strengths can be simulated. In addition, observed microburst precursors such as midlevel convergence and descending precipitation cores can also be simulated. Using a grid resolution of 250 m, the observed structure of a particularly well-documented storm on 20 July 1986 during COHMEX is simulated, including a hail shaft 1–2 km wide that descended to the ground. In the second part of this paper, the influence of microphysical processes in the production of low-level downdrafts in simulated COHMEX storms is investigated. It is shown that low-level downdrafts are in some cases stronger and deeper ...