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Ali Tokay, David A. Short, Christopher R. Williams, Warner L. Ecklund, and Kenneth S. Gage

Abstract

The motivation for this research is to move in the direction of improved algorithms for the remote sensing of rainfall, which are crucial for meso- and large-scale circulation studies and climate applications through better determinations of precipitation type and latent heating profiles. Toward this end a comparison between two independent techniques, designed to classify precipitation type from 1) a disdrometer and 2) a 915-MHz wind profiler, is presented, based on simultaneous measurements collected at the same site during the Intensive Observing Period of the Tropical Ocean Global Atmosphere Coupled Ocean–Atmosphere Response Experiment. Disdrometer-derived quantities such as differences in drop size distribution parameters, particularly the intercept parameter N 0 and rainfall rate, were used to classify rainfall as stratiform or convective. At the same time, profiler-derived quantities, namely, Doppler velocity, equivalent reflectivity, and spectral width, from Doppler spectra were used to classify precipitation type in four categories: shallow convective, deep convective, mixed convective–stratiform, and stratiform.

Overall agreement between the two algorithms is found to be reasonable. Given the disdrometer stratiform classification, the mean profile of reflectivity shows a distinct bright band and associated large vertical gradient in Doppler velocity, both indicators of stratiform rain. For the disdrometer convective classification the mean profile of reflectivity lacks a bright band, while the vertical gradient in Doppler velocity below the melting level is opposite to the stratiform case. Given the profiler classifications, in the order shallow–deep–mixed–stratiform, the composite raindrop spectra for a rainfall rate of 5 mm h−1 show an increase in D 0, the median volume diameter, consistent with the dominant microphysical processes responsible for drop formation. Nevertheless, the intercomparison does reveal some limitations in the classification methodology utilizing the disdrometer or profiler algorithms in isolation. In particular, 1) the disdrometer stratiform classification includes individual cases in which the vertical profiles appear convective, but these usually occur at times when the disdrometer classification is highly variable; 2) the profiler classification scheme also appears to classify precipitation too frequently as stratiform by including cases that have small vertical Doppler velocity gradients at the melting level but no bright band; and 3) the profiler classification scheme includes a category of mixed (stratiform–convective) precipitation that has some features in common with deep convection (e.g., enhanced spectral width above the melting level) but other features in common with stratiform precipitation (e.g., well-developed melting layer signature). Comparison of the profiler-derived vertical structure with disdrometer-determined rain rates reveals that almost all cases of rain rates greater than 10 mm h−1 are convective. For rain rates less than 5 mm h−1 all four profiler-determined precipitation classes are well represented.

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Leah R. Williams, Jeffrey A. Manion, David M. Golden, and Margaret A. Tolbert

Abstract

Increasing evidence from field, modeling, and laboratory studies suggests that heterogeneous reactions on stratospheric sulfate aerosol particles may contribute to global ozone depiction. Using a Knudsen cell reactor technique, the authors have studied the uptake, reactivity, and solubility of several trace atmospheric species on cold sulfuric acid surfaces representative of stratospheric aerosol particles. The results suggest that the heterogeneous conversion of N2O5 to HNO3 is fast enough to significantly affect the partitioning of nitrogen species in the global stratosphere and thus contribute to global ozone depletion. The hydrolysis of ClONO2 is slower and unlikely to be important under normal conditions at midlatitudes. The solubilities of HCl and HNO3 in sulfuric acid down to 200 K were found to be quite low. For HCl, this means that little HCl is available for reaction on the surfaces of stratospheric sulfate aerosol particles. The low solubility of HNO3 means that this product of heterogeneous reactions will enter the gas phase, and the denitrification observed in polar regions is unlikely to occur in the global stratosphere.

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John R. Mecikalski, John K. Williams, Christopher P. Jewett, David Ahijevych, Anita LeRoy, and John R. Walker

Abstract

The Geostationary Operational Environmental Satellite (GOES)-R convective initiation (CI) algorithm predicts CI in real time over the next 0–60 min. While GOES-R CI has been very successful in tracking nascent clouds and obtaining cloud-top growth and height characteristics relevant to CI in an object-tracking framework, its performance has been hindered by elevated false-alarm rates, and it has not optimally combined satellite observations with other valuable data sources. Presented here are two statistical learning approaches that incorporate numerical weather prediction (NWP) input within the established GOES-R CI framework to produce probabilistic forecasts: logistic regression (LR) and an artificial-intelligence approach known as random forest (RF). Both of these techniques are used to build models that are based on an extensive database of CI events and nonevents and are evaluated via cross validation and on independent case studies. With the proper choice of probability thresholds, both the LR and RF techniques incorporating NWP data produce substantially fewer false alarms than when only GOES data are used. The NWP information identifies environmental conditions (as favorable or unfavorable) for the development of convective storms and improves the skill of the CI nowcasts that operate on GOES-based cloud objects, as compared with when the satellite IR fields are used alone. The LR procedure performs slightly better overall when 14 skill measures are used to quantify the results and notably better on independent case study days.

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Kenneth S. Gage, Christopher R. Williams, Paul E. Johnston, Warner L. Ecklund, Robert Cifelli, Ali Tokay, and David A. Carter

Abstract

The National Oceanic and Atmospheric Administration’s Aeronomy Laboratory has modified a standard 915-MHz profiler for use as a precipitation profiler in support of Tropical Rainfall Measuring Mission ground validation field campaigns. This profiler was modified to look vertically with a fixed dish antenna. It was operated during the Texas and Florida Underflights Experiment (TEFLUN) A in south Texas in April–May 1998 and during TEFLUN B in central Florida in August–September 1998. Collocated with the profiler was a Distromet, Inc., RD-69 Joss–Waldvogel disdrometer in Texas and Florida and a two-dimensional video disdrometer in Florida. The disdrometers are used to calibrate the profiler at the lowest range gates. At higher altitudes, the calibrated profiler reflectivities are compared with observations made by scanning radars such as the Weather Surveillance Radar-1988 Doppler in Dickinson, Texas, and Melbourne, Florida, and the S-band Doppler dual-polarization radar in Florida. The authors conclude that it is possible to use profilers as transfer standards to calibrate and to validate the reflectivities measured by the scanning radars.

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James M. Kurdzo, Earle R. Williams, David J. Smalley, Betty J. Bennett, David C. Patterson, Mark S. Veillette, and Michael F. Donovan

Abstract

Chaff is a radar countermeasure typically used by military branches in training exercises around the United States. Chaff within view of the S-band WSR-88D beam can appear prominently on radar users’ displays. Knowledge of chaff characteristics is useful for radar users to discriminate between chaff and weather echoes and for automated algorithms to do the same. The WSR-88D network provides dual-polarimetric capabilities across the United States, leading to the collection of a large database of chaff cases. This database is analyzed to determine the characteristics of chaff in terms of the reflectivity factor and polarimetric variables on large scales. Particular focus is given to the dynamics of differential reflectivity Z DR in chaff and its dependence on height. In contrast to radar observations of chaff for a single event, this study is able to reveal a repeatable and new pattern of radar chaff observations. A discussion about the observed characteristics is presented, and hypotheses for the observed Z DR dynamics are put forth.

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Earle R. Williams, David J. Smalley, Michael F. Donovan, Robert G. Hallowell, Kenta T. Hood, Betty J. Bennett, Raquel Evaristo, Adam Stepanek, Teresa Bals-Elsholz, Jacob Cobb, Jaclyn Ritzman, Alexei Korolev, and Mengistu Wolde

Abstract

The organized behavior of differential radar reflectivity (ZDR) is documented in the cold regions of a wide variety of stratiform precipitation types occurring in both winter and summer. The radar targets and attendant cloud microphysical conditions are interpreted within the context of measurements of ice crystal types in laboratory diffusion chambers in which humidity and temperature are both stringently controlled. The overriding operational interest here is in the identification of regions prone to icing hazards with long horizontal paths. Two predominant regimes are identified: category A, which is typified by moderate reflectivity (from 10 to 30 dBZ) and modest +ZDR values (from 0 to +3 dB) in which both supercooled water and dendritic ice crystals (and oriented aggregates of ice crystals) are present at a mean temperature of −13°C, and category B, which is typified by small reflectivity (from −10 to +10 dBZ) and the largest +ZDR values (from +3 to +7 dB), in which supercooled water is dilute or absent and both flat-plate and dendritic crystals are likely. The predominant positive values for ZDR in many case studies suggest that the role of an electric field on ice particle orientation is small in comparison with gravity. The absence of robust +ZDR signatures in the trailing stratiform regions of vigorous summer squall lines may be due both to the infusion of noncrystalline ice particles (i.e., graupel and rimed aggregates) from the leading deep convection and to the effects of the stronger electric fields expected in these situations. These polarimetric measurements and their interpretations underscore the need for the accurate calibration of ZDR.

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Christopher R. Williams, V. N. Bringi, Lawrence D. Carey, V. Chandrasekar, Patrick N. Gatlin, Ziad S. Haddad, Robert Meneghini, S. Joseph Munchak, Stephen W. Nesbitt, Walter A. Petersen, Simone Tanelli, Ali Tokay, Anna Wilson, and David B. Wolff
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Christopher R. Williams, V. N. Bringi, Lawrence D. Carey, V. Chandrasekar, Patrick N. Gatlin, Ziad S. Haddad, Robert Meneghini, S. Joseph Munchak, Stephen W. Nesbitt, Walter A. Petersen, Simone Tanelli, Ali Tokay, Anna Wilson, and David B. Wolff
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A. Park Williams, Richard Seager, Max Berkelhammer, Alison K. Macalady, Michael A. Crimmins, Thomas W. Swetnam, Anna T. Trugman, Nikolaus Buenning, Natalia Hryniw, Nate G. McDowell, David Noone, Claudia I. Mora, and Thom Rahn

Abstract

In 2011, exceptionally low atmospheric moisture content combined with moderately high temperatures to produce a record-high vapor pressure deficit (VPD) in the southwestern United States (SW). These conditions combined with record-low cold-season precipitation to cause widespread drought and extreme wildfires. Although interannual VPD variability is generally dominated by temperature, high VPD in 2011 was also driven by a lack of atmospheric moisture. The May–July 2011 dewpoint in the SW was 4.5 standard deviations below the long-term mean. Lack of atmospheric moisture was promoted by already very dry soils and amplified by a strong ocean-to-continent sea level pressure gradient and upper-level convergence that drove dry northerly winds and subsidence upwind of and over the SW. Subsidence drove divergence of rapid and dry surface winds over the SW, suppressing southerly moisture imports and removing moisture from already dry soils. Model projections developed for the fifth phase of the Coupled Model Intercomparison Project (CMIP5) suggest that by the 2050s warming trends will cause mean warm-season VPD to be comparable to the record-high VPD observed in 2011. CMIP5 projections also suggest increased interannual variability of VPD, independent of trends in background mean levels, as a result of increased variability of dewpoint, temperature, vapor pressure, and saturation vapor pressure. Increased variability in VPD translates to increased probability of 2011-type VPD anomalies, which would be superimposed on ever-greater background VPD levels. Although temperature will continue to be the primary driver of interannual VPD variability, 2011 served as an important reminder that atmospheric moisture content can also drive impactful VPD anomalies.

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Christopher R. Williams, V. N. Bringi, Lawrence D. Carey, V. Chandrasekar, Patrick N. Gatlin, Ziad S. Haddad, Robert Meneghini, S. Joseph Munchak, Stephen W. Nesbitt, Walter A. Petersen, Simone Tanelli, Ali Tokay, Anna Wilson, and David B. Wolff

Abstract

Rainfall retrieval algorithms often assume a gamma-shaped raindrop size distribution (DSD) with three mathematical parameters N w, D m, and μ. If only two independent measurements are available, as with the dual-frequency precipitation radar on the Global Precipitation Measurement (GPM) mission core satellite, then retrieval algorithms are underconstrained and require assumptions about DSD parameters. To reduce the number of free parameters, algorithms can assume that μ is either a constant or a function of D m. Previous studies have suggested μ–Λ constraints [where Λ = (4 + μ)/D m], but controversies exist over whether μ–Λ constraints result from physical processes or mathematical artifacts due to high correlations between gamma DSD parameters. This study avoids mathematical artifacts by developing joint probability distribution functions (joint PDFs) of statistically independent DSD attributes derived from the raindrop mass spectrum. These joint PDFs are then mapped into gamma-shaped DSD parameter joint PDFs that can be used in probabilistic rainfall retrieval algorithms as proposed for the GPM satellite program. Surface disdrometer data show a high correlation coefficient between the mass spectrum mean diameter D m and mass spectrum standard deviation σ m. To remove correlations between DSD attributes, a normalized mass spectrum standard deviation is constructed to be statistically independent of D m, with representing the most likely value and std representing its dispersion. Joint PDFs of D m and μ are created from D m and . A simple algorithm shows that rain-rate estimates had smaller biases when assuming the DSD breadth of than when assuming a constant μ.

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