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  • Author or Editor: J. J. Gourley x
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Anita Nallapareddy
,
Alan Shapiro
, and
Jonathan J. Gourley

Abstract

A sudden increase in temperature during the nighttime hours accompanies the passages of some cold fronts. In some cold front–associated warming events, the temperature can rise by as much as 10°C and can last from a few minutes to several hours. Previous studies suggest that these events are due to the downward transport of warmer air by the strong and gusty winds associated with the cold-frontal passages. In this study, a climatology of nocturnal warming events associated with cold fronts was created using 6 yr of Oklahoma Mesonetwork (Mesonet) data from 2003 to 2008. Nocturnal warming events associated with cold-frontal passages occurred surprisingly frequently across Oklahoma. Of the cold fronts observed in this study, 91.5% produced at least one warming event at an Oklahoma Mesonet station. The winter months accounted for the most events (37.9%), and the summer months accounted for the fewest (3.8%). When normalized by the monthly number of cold-frontal passages, the winter months still had the most number of warming events. The number of warming events increased rapidly from 2300 to 0200 UTC; thereafter, the number of events gradually decreased. A spatial analysis revealed that the frequency of warming events decreased markedly from west to east across the state. In contrast, the average magnitude of the warming increased from west to east. In contrast to control periods (associated with cold-frontal passages without nocturnal warming events), warming events were associated with weaker initial winds and stronger initial temperature inversions. Moreover, the nocturnal temperature inversion weakened more during warming events than during control periods and the surface wind speeds increased more during warming events than during control periods. These results are consistent with previous studies that suggest the warming events are due to the “mixing out” of the nocturnal temperature inversion.

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N. Carr
,
P. E. Kirstetter
,
J. J. Gourley
, and
Y. Hong

Abstract

Precipitation events in which rainfall is generated primarily below the freezing level via warm-rain processes have traditionally presented a significant challenge for radar and satellite quantitative precipitation estimation (QPE) algorithms. It is possible to improve QPE in warm-rain events if they are correctly identified/classified as warm rain prior to precipitation estimation. Additionally, it is anticipated that classification schemes incorporating polarimetric radar data will be able to leverage precipitation microphysical information to better identify warm-rain precipitation events. This study lays the groundwork for the development of a polarimetric warm-rain classification algorithm by documenting the typical three-dimensional polarimetric characteristics associated with midlatitude warm-rain precipitation events. These characteristics are then compared with those observed in non-warm-rain events. Nearly all warm-rain precipitation events were characterized by lower median values of Z, Z DR, and K DP relative to the non-warm-rain convective cases. Furthermore, droplet coalescence was determined to be the dominant microphysical process in the majority of warm-rain events, while in non-warm-rain stratiform events, evaporation and breakup appeared to be the dominant (warm) microphysical processes. Most warm-rain events were also associated with sharp decreases in reflectivity, with height above the freezing level coincident with low echo-top heights and freezing-level Z DR values near 0, indicating limited ice- and mixed-phase precipitation growth processes. These results support the feasibility of a future polarimetric warm-rain identification algorithm.

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Pierre Tabary
,
Gianfranco Vulpiani
,
Jonathan J. Gourley
,
Anthony J. Illingworth
,
Robert J. Thompson
, and
Olivier Bousquet

Abstract

The differential phase (ΦDP) measured by polarimetric radars is recognized to be a very good indicator of the path integrated by rain. Moreover, if a linear relationship is assumed between the specific differential phase (K DP) and the specific attenuation (AH ) and specific differential attenuation (A DP), then attenuation can easily be corrected. The coefficients of proportionality, γH and γ DP, are, however, known to be dependent in rain upon drop temperature, drop shapes, drop size distribution, and the presence of large drops causing Mie scattering. In this paper, the authors extensively apply a physically based method, often referred to as the “Smyth and Illingworth constraint,” which uses the constraint that the value of the differential reflectivity Z DR on the far side of the storm should be low to retrieve the γ DP coefficient. More than 30 convective episodes observed by the French operational C-band polarimetric Trappes radar during two summers (2005 and 2006) are used to document the variability of γ DP with respect to the intrinsic three-dimensional characteristics of the attenuating cells. The Smyth and Illingworth constraint could be applied to only 20% of all attenuated rays of the 2-yr dataset so it cannot be considered the unique solution for attenuation correction in an operational setting but is useful for characterizing the properties of the strongly attenuating cells. The range of variation of γ DP is shown to be extremely large, with minimal, maximal, and mean values being, respectively, equal to 0.01, 0.11, and 0.025 dB °−1. Coefficient γ DP appears to be almost linearly correlated with the horizontal reflectivity (ZH ), differential reflectivity (Z DR), and specific differential phase (K DP) and correlation coefficient (ρ HV) of the attenuating cells. The temperature effect is negligible with respect to that of the microphysical properties of the attenuating cells. Unusually large values of γ DP, above 0.06 dB °−1, often referred to as “hot spots,” are reported for 15%—a nonnegligible figure—of the rays presenting a significant total differential phase shift (Δϕ DP > 30°). The corresponding strongly attenuating cells are shown to have extremely high Z DR (above 4 dB) and ZH (above 55 dBZ), very low ρ HV (below 0.94), and high K DP (above 4° km−1). Analysis of 4 yr of observed raindrop spectra does not reproduce such low values of ρ HV, suggesting that (wet) ice is likely to be present in the precipitation medium and responsible for the attenuation and high phase shifts. Furthermore, if melting ice is responsible for the high phase shifts, this suggests that K DP may not be uniquely related to rainfall rate but can result from the presence of wet ice. This hypothesis is supported by the analysis of the vertical profiles of horizontal reflectivity and the values of conventional probability of hail indexes.

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Jonathan J. Gourley
,
Pierre Tabary
, and
Jacques Parent du Chatelet

Abstract

A polarimetric method is devised to correct for attenuation effects at C band on reflectivity ZH and differential reflectivity Z DR measurements. An operational cross-correlation analysis is used to derive advection vectors and to displace echoes over a 5-min time step. These advected echoes are then compared with observations valid at the same time. The method assumes that the mean change in the intrinsic ZH and Z DR over a 5-min period when considering 1–2 h of observations over the entire radar umbrella is approximately zero. Correction coefficients are retrieved through the minimization of a cost function that links observed decreases in ZH and Z DR due to attenuation effects with increases in differential phase shift (ΦDP). The retrieved coefficients are consistent with published values for the typical ranges of temperatures and drop sizes encountered at midlatitudes, even when Mie scattering effects are present. Measurements of ZH and Z DR corrected using retrieved coefficients are compared with raw measurements and to measurements adjusted by mean coefficients found in the literature. The empirical retrieval method shows improvement over using mean correction coefficients based on comparisons of ZH from neighboring, unattenuated radars, disdrometer measurements, and analysis of ZH and Z DR as a function of ΦDP.

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Yixin Wen
,
Yang Hong
,
Guifu Zhang
,
Terry J. Schuur
,
Jonathan J. Gourley
,
Zac Flamig
,
K. Robert Morris
, and
Qing Cao

Abstract

Ground-based polarimetric weather radar is arguably the most powerful validation tool that provides physical insight into the development and interpretation of spaceborne weather radar algorithms and observations. This study aims to compare and resolve discrepancies in hydrometeor retrievals and reflectivity observations between the NOAA/National Severe Storm Laboratory “proof of concept” KOUN polarimetric Weather Surveillance Radar-1988 Doppler (WSR-88D) and the spaceborne precipitation radar (PR) on board NASA’s Tropical Rainfall Measuring Mission (TRMM) platform. An intercomparison of PR and KOUN melting-layer heights retrieved from 2 to 5 km MSL shows a high correlation coefficient of 0.88 with relative bias of 5.9%. A resolution volume–matching technique is used to compare simultaneous TRMM PR and KOUN reflectivity observations. The comparisons reveal an overall bias of <0.2% between PR and KOUN. The bias is hypothesized to be from non-Rayleigh scattering effects and/or errors in attenuation correction procedures applied to Ku-band PR measurements. By comparing reflectivity with respect to different hydrometeor types (as determined by KOUN’s hydrometeor classification algorithm), it is found that the bias is from echoes that are classified as rain–hail mixture, wet snow, graupel, and heavy rain. These results agree with expectations from backscattering calculations at Ku and S bands, but with the notable exception of dry snow. Comparison of vertical reflectivity profiles shows that PR suffers significant attenuation at lower altitudes, especially in convective rain and in the melting layer. The attenuation correction performs very well for both stratiform and convective rain, however. In light of the imminent upgrade of the U.S. national weather radar network to include polarimetric capabilities, the findings in this study will potentially serve as the basis for nationwide validation of space-based precipitation products and also invite synergistic development of coordinated space–ground multisensor precipitation products.

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Qing Cao
,
Yang Hong
,
Jonathan J. Gourley
,
Youcun Qi
,
Jian Zhang
,
Yixin Wen
, and
Pierre-Emmanuel Kirstetter

Abstract

This study presents a statistical analysis of the vertical structure of precipitation measured by NASA–Japan Aerospace Exploration Agency’s (JAXA) Tropical Rainfall Measuring Mission (TRMM) precipitation radar (PR) in the region of southern California, Arizona, and western New Mexico, where the ground-based Next-Generation Radar (NEXRAD) network finds difficulties in accurately measuring surface precipitation because of beam blockages by complex terrain. This study has applied TRMM PR version-7 products 2A23 and 2A25 from 1 January 2000 to 26 October 2011. The seasonal, spatial, intensity-related, and type-related variabilities are characterized for the PR vertical profile of reflectivity (VPR) as well as the heights of storm, freezing level, and bright band. The intensification and weakening of reflectivity at low levels in the VPR are studied through fitting physically based VPR slopes. Major findings include the following: precipitation type is the most significant factor determining the characteristics of VPRs, the shape of VPRs also influences the intensity of surface rainfall rates, the characteristics of VPRs have a seasonal dependence with strong similarities between the spring and autumn months, and the spatial variation of VPR characteristics suggests that the underlying terrain has an impact on the vertical structure. The comprehensive statistical and physical analysis strengthens the understanding of the vertical structure of precipitation and advocates for the approach of VPR correction to improve surface precipitation estimation in complex terrain.

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Jonathan J. Gourley
,
Yang Hong
,
Zachary L. Flamig
,
Li Li
, and
Jiahu Wang

Abstract

Rainfall products from radar, satellite, rain gauges, and combinations have been evaluated for a season of record rainfall in a heavily instrumented study domain in Oklahoma. Algorithm performance is evaluated in terms of spatial scale, temporal scale, and rainfall intensity. Results from this study will help users of rainfall products to understand their errors. Moreover, it is intended that developers of rainfall algorithms will use the results presented herein to optimize the contribution from available sensors to yield the most skillful multisensor rainfall products.

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