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Stephen W. Nesbitt and Edward J. Zipser

Abstract

The Tropical Rainfall Measuring Mission (TRMM) satellite measurements from the precipitation radar and TRMM microwave imager have been combined to yield a comprehensive 3-yr database of precipitation features (PFs) throughout the global Tropics (±36° latitude). The PFs retrieved using this algorithm (which number nearly six million Tropicswide) have been sorted by size and intensity ranging from small shallow features greater than 75 km2 in area to large mesoscale convective systems (MCSs) according to their radar and ice scattering characteristics. This study presents a comprehensive analysis of the diurnal cycle of the observed precipitation features' rainfall amount, precipitation feature frequency, rainfall intensity, convective–stratiform rainfall portioning, and remotely sensed convective intensity, sampled Tropicswide from space.

The observations are sorted regionally to examine the stark differences in the diurnal cycle of rainfall and convective intensity over land and ocean areas. Over the oceans, the diurnal cycle of rainfall has small amplitude, with the maximum contribution to rainfall coming from MCSs in the early morning. This increased contribution is due to an increased number of MCSs in the nighttime hours, not increasing MCS areas or conditional rain rates, in agreement with previous works. Rainfall from sub-MCS features over the ocean has little appreciable diurnal cycle of rainfall or convective intensity. Land areas have a much larger rainfall cycle than over the ocean, with a marked minimum in the midmorning hours and a maximum in the afternoon, slowly decreasing through midnight. Non-MCS features have a significant peak in afternoon instantaneous conditional rain rates (the mean rain rate in raining pixels), and convective intensities, which differs from previous studies using rain rates derived from hourly rain gauges. This is attributed to enhancement by afternoon heating. MCSs over land have a convective intensity peak in the late afternoon, however all land regions have MCS rainfall peaks that occur in the late evening through midnight due to their longer life cycle. The diurnal cycle of overland MCS rainfall and convective intensity varies significantly among land regions, attributed to MCS sensitivity to the varying environmental conditions in which they occur.

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Daniel S. Harnos and Stephen W. Nesbitt

Abstract

Characteristics of over 15 000 tropical cyclone (TC) inner cores are evaluated coincidentally using 37- and 85-GHz passive microwave data to quantify the relative prevalence of cold clouds (i.e., deep convection and stratiform clouds) versus predominantly warm clouds (i.e., shallow cumuli and cumulus congestus). Results indicate greater presence of combined liquid and frozen hydrometeors associated with cold clouds within the atmospheric column for TCs undergoing subsequent rapid intensification (RI) or intensification. RI episodes compared to the full intensity change distribution exhibit approximately an order of magnitude increase for inner-core cold cloud frequency relative to warm cloud presence. Incorporation of an objective ring detection algorithm shows the robust presence of rings associated with hydrometeors for 85-GHz polarization corrected temperatures () and 37-GHz vertically polarized brightness temperatures () for differentiating RI with significance levels ≥99.99%, while 37-GHz false color rings of a combined cyan and pink appearance surrounding a region that is not cyan or pink lack statistical significance for discriminating RI against lesser intensification. Rings of depressed and enhanced tied to RI suggest the combined presence of liquid and frozen hydrometeors within the atmospheric column, indicative of cold clouds. The rings also exhibit preferences for those with collocated more widespread ice scattering signatures to be more commonly associated with RI and general intensification.

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Alison M. Anders and Stephen W. Nesbitt

Abstract

A Tropical Rainfall Measuring Mission (TRMM) climatology shows variability in surface precipitation rate–elevation relationships across the tropics. Vertical profiles of radar reflectivity and profiles of specific humidity and cross-barrier moisture fluxes during precipitation events from the Interim European Centre for Medium-Range Weather Forecasts Re-Analysis reveal four precipitation regimes with distinct precipitation mechanisms: 1) a tropical regime with a broad precipitation maximum at ~1500 m where convection is triggered by orographic lifting; 2) a trade winds regime with a near–sea level precipitation maximum dominated by forced ascent due to prevailing winds and the presence of dry air aloft; 3) a wet monsoon regime with a low-elevation precipitation maximum driven by efficient precipitation generation, large low-level cross-barrier moisture fluxes, and multiple convective modes; and 4) a dry monsoon regime with a high-elevation precipitation maximum reflecting intense convection and stratiform rain with a strong evaporation signature. In general, surface precipitation–elevation relationships across the tropics feature lower-elevation precipitation maxima relative to typical midlatitude regimes.

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Nicole J. Schiffer and Stephen W. Nesbitt

Abstract

This study uses an improved surge identification method to examine composites of 29 yr of surface observations and reanalysis data alongside 10 yr of satellite precipitation data to reveal connections between flow, thermodynamic parameters, and precipitation, both within and outside of the North American monsoon (NAM) region, associated with Gulf of California (GoC) moisture surges. The North American Regional Reanalysis (NARR), examined using composites of flow during all detected moisture surges at Yuma, Arizona, and so-called wet and dry surges (those producing anomalously high and low precipitation, respectively, over Arizona and New Mexico), show markedly different flow and moisture patterns that ultimately lead to the differing observed precipitation distributions in the region. Wet surges tend to be associated with moister precursor air masses over the southwestern United States, have a larger contribution of enhanced easterly cross–Sierra Madre Occidental (SMO) moisture transport, and tend to result from a transient cyclonic disturbance tracking across northern Mexico. Dry surges tend to be associated with a more southerly tracking disturbance, are associated with less convection over the SMO, and tend to be associated with a drier presurge air mass over Arizona and New Mexico.

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Stephen W. Nesbitt, Edward J. Zipser, and Christian D. Kummerow

Abstract

An evaluation of the version-5 precipitation radar (PR; algorithm 2A25) and Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI; algorithm 2A12) rainfall products is performed across the Tropics in two ways: 1) by comparing long-term TRMM rainfall products with Global Precipitation Climatology Centre (GPCC) global rain gauge analyses and 2) by comparing the rainfall estimates from the PR and TMI on a rainfall feature-by-feature basis within the narrow swath of the PR using a 1-yr database of classified precipitation features (PFs). The former is done to evaluate the overall biases of the TMI and PR relative to “ground truth” to examine regional differences in the estimates; the latter allows a direct comparison of the estimates with the same sampling area, also identifying relative biases as a function of storm type. This study finds that the TMI overestimates rainfall in most of the deep Tropics and midlatitude warm seasons over land with respect to both the GPCC gauge analysis and the PR (which agrees well with the GPCC gauges in the deep Tropics globally), in agreement with past results. The PR is generally higher than the TMI in midlatitude cold seasons over land areas with gauges. The analysis by feature type reveals that the TMI overestimates relative to the PR are due to overestimates in mesoscale convective systems and in most features with 85-GHz polarization-corrected temperature of less than 250 K (i.e., with a significant optical depth of precipitation ice). The PR tended to be higher in PFs without an ice-scattering signature of less than 250 K. Normalized for a subset of features with a large rain volume (exceeding 104 mm h−1 km2) independent of the PF classification, features with TMI > PR in the Tropics tended to have a higher fraction of stratiform rainfall, higher IR cloud tops, more intense radar profiles and 85-GHz ice-scattering signatures, and larger rain areas, whereas the converse is generally true for features with PR > TMI. Subtropical-area PF bias characteristics tended not to have such a clear relationship (especially over the ocean), a result that is hypothesized to be due to the influence of more variable storm environments and the presence of frontal rain. Melting-layer effects in stratiform rain and a bias in the ice-scattering–rain relationship were linked to the TMI producing more rainfall than the PR. However, noting the distinct characteristic biases Tropics-wide by feature type, this study reveals that accounting for regime-dependent biases caused by the differing horizontal and vertical morphologies of precipitating systems may lead to a reduction in systematic relative biases in a microwave precipitation algorithm.

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Timothy J. Lang, Stephen W. Nesbitt, and Lawrence D. Carey

Abstract

Three methodologies for correcting the radar reflectivity factor (Z H) in the presence of partial beam blockage are implemented, compared, and evaluated using a polarimetric radar dataset from the North American Monsoon Experiment (NAME) in northwestern Mexico. One methodology uses simulated interactions between radar beams and digital terrain maps, while the other two invoke the self-consistency of polarimetric radar measurands in rainfall, and the relative insensitivity of a specific differential phase to beam blockage. While the different methodologies often agree to within 1–2 dB, significant disagreements can occur in regions of sharp azimuthal gradients in beam blockage patterns, and in areas where the terrain-caused radar clutter map is complex. These disagreements may be mitigated by the use of additional radar data to develop the polarimetric correction techniques, by a more sophisticated terrain-beam interaction model, or by a higher-resolution digital terrain map. Intercomparisons between ground radar data and Tropical Rainfall Measuring Mission satellite overpasses suggest that all of the methodologies can correct mean Z H to within the expected uncertainty of such intercomparisons (1–1.5 dB). The polarimetric correction methods showed good results even in severely blocked regions (>10 dB reduction). The results suggest the possibility that all of the techniques may be valid approaches to correcting partial beam blockage, and within that context relative advantages and disadvantages of each technique are discussed. However, none of the techniques can correct radar data when weak echoes are reduced to noise by strong blocks, thus leading to biases in corrected Z H and rainfall climatologies.

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George Duffy, Greg Mcfarquhar, Stephen W. Nesbitt, and Ralf Bennartz

Abstract

The retrieval of the mass-weighted mean diameter (D m) is a fundamental component of spaceborne precipitation retrievals. The Dual-Frequency Precipitation Radar (DPR) on the Global Precipitation Measurement (GPM) satellite is the first satellite to use dual-wavelength ratio measurements—the quotient of radar reflectivity factors (Z) measured at Ku and Ka wavelengths—to retrieve D m. While it is established that DWR, being theoretically insensitive to changes in ice crystal mass and concentration, can provide a superior retrieval of D m compared to Z-based retrievals, the benefits of this retrieval have yet to be directly observed or quantified. In this study, DWR–D m and ZD m relationships are empirically generated from collocated airborne radar and in situ cloud particle probe measurements. Data are collected during nine intensive observation periods (IOPs) from three experiments representing different locations and times of year. Across IOPs with varying ice crystal concentrations, cloud temperatures, and storm types, ZD m relationships vary considerably while the DWR–D m relationship remains consistent. This study confirms that a DWR–D m relationship can provide a more accurate and consistent D m retrieval than a ZD m relationship, quantified by a reduced overall RMSE (0.19 and 0.25 mm, respectively) and a reduced range of biases between experiments (0.11 and 0.32 mm, respectively).

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Ole Peters, J. David Neelin, and Stephen W. Nesbitt

Abstract

Size distributions and other geometric properties of mesoscale convective systems (MCSs), identified as clusters of adjacent pixels exceeding a precipitation threshold in satellite radar images, are examined with respect to a recently identified critical range of water vapor. Satellite microwave estimates of column water vapor and precipitation show that the onset of convection and precipitation in the tropics can be described as a phase transition, where the rain rate and likelihood of rainfall suddenly increase as a function of water vapor. This is confirmed in Tropical Rainfall Measuring Mission radar data used here. Percolation theory suggests that cluster properties should be highly sensitive to changes in the density of occupied pixels, which here translates into a rainfall probability, which in turn sensitively depends on the water vapor. To confirm this, clusters are categorized by their prevalent water vapor. As expected, mean cluster size and radius of gyration strongly increase as the critical water vapor is approached from below. In the critical region one finds scale-free size distributions spanning several orders of magnitude. Large clusters are typically from the critical region: at low water vapor most clusters are small, and supercritical water vapor values are too rare to contribute much. The perimeter of the clusters confirms previous observations in satellite, field, and model data of robust nontrivial scaling. The well-known area–perimeter scaling is fully compatible with the quantitative prediction from the plausible null model of gradient percolation, where the accessible hull is a fractal object with dimension 4/3.

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Randy J. Chase, Stephen W. Nesbitt, and Greg M. McFarquhar

Abstract

With the launch of the Global Precipitation Measurement Dual-Frequency Precipitation Radar (GPM-DPR) in 2014, renewed interest in retrievals of snowfall in the atmospheric column has occurred. The current operational GPM-DPR retrieval largely underestimates surface snowfall accumulation. Here, a neural network (NN) trained on data that are synthetically derived from state-of-the-art ice particle scattering models and measured in situ particle size distributions (PSDs) is used to retrieve two parameters of the PSD: liquid equivalent mass-weighted mean diameter Dml and the liquid equivalent normalized intercept parameter Nwl. Evaluations against a test dataset showed statistically significantly improved ice water content (IWC) retrievals relative to a standard power-law approach and an estimate of the current GPM-DPR algorithm. Furthermore, estimated median percent errors (MPE) on the test dataset were −0.7%, +2.6%, and +1% for Dml, Nwl, and IWC, respectively. An evaluation on three case studies with collocated radar observations and in situ microphysical data shows that the NN retrieval has MPE of −13%, +120%, and +10% for Dml, Nwl, and IWC, respectively. The NN retrieval applied directly to GPM-DPR data provides improved snowfall retrievals relative to the default algorithm, removing the default algorithm’s ray-to-ray instabilities and recreating the high-resolution radar retrieval results to within 15% MPE. Future work should aim to improve the retrieval by including PSD data collected in more diverse conditions and rimed particles. Furthermore, different desired outputs such as the PSD shape parameter and snowfall rate could be included in future iterations.

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Robert J. Trapp, Geoffrey R. Marion, and Stephen W. Nesbitt

Abstract

Strong to violent tornadoes cause a disproportionate amount of damage, in part because the width and length of a tornado damage track are correlated to tornado intensity (as now estimated through enhanced Fujita scale ratings). The tendency expressed in the observational record is that the most intense tornadoes are often the widest. Herein the authors explore the simple hypothesis that wide intense tornadoes should form more readily out of wide rotating updrafts. This hypothesis is based on an application of Kelvin’s circulation theorem, which is used to argue that the large circulation associated with a wide intense tornado is more plausibly associated with a wide mesocyclone. Because a mesocyclone is, strictly speaking, a rotating updraft, the mesocyclone width should increase with increasing updraft width. A simple mathematical model that is quantified using observations of mesocyclones supports this hypothesis, as do idealized numerical simulations of supercellular thunderstorms.

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