Search Results

You are looking at 1 - 10 of 55 items for

  • Author or Editor: JONATHAN J. GOURLEY x
  • Refine by Access: All Content x
Clear All Modify Search
Jonathan J. Gourley and Humberto Vergara

Abstract

New operational tools for monitoring flash flooding based on radar quantitative precipitation estimates (QPEs) have become available to U.S. National Weather Service forecasters. Herman and Schumacher examined QPE exceedance thresholds for several tools and compared them to each other, to flash flood reports (FFRs), and to flash flood warnings. The Next Generation Radar network has been updated with dual-polarization capabilities since the publication of Herman and Schumacher, which has changed the characteristics of the derived QPEs. Updated thresholds on Multi-Radar Multi-Sensor version 12 products that are associated to FFRs are provided and thus can be used as guidance by the operational forecasting community and other end-users of the products.

Restricted access
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.

Full access
Jonathan J. Gourley and Chris M. Calvert

Abstract

During stratiform precipitation, hydrometeors within the melting layer increase backscatter to radar. This layer can persist at a nearly constant height for hours and can lead to serious radar-based overestimates in accumulated surface rainfall. Sophisticated precipitation algorithms of the present and near future are beginning to identify regions where there is contaminated reflectivity in order to make corrections to the data. An automated algorithm that operates on full-resolution Weather Surveillance Radar-1988 Doppler (WSR-88D) reflectivity data (i.e., archive level II) to identify the height and depth of the bright band for every volume scan has been developed. Results from the algorithm are compared with 0°C heights from nearby radiosonde observations and from model analyses for three different regions in the United States. In addition, reflectivity observations from an independent, vertically pointing radar situated in complex terrain are compared with results from the brightband algorithm operating on WSR-88D data. The output from the brightband algorithm matches observations well. A case is presented to show how the radar-observed brightband heights can be used to identify regions in precipitation products where radar is sampling within the melting layer and therefore may be subject to overestimation. Improved monitoring of the bright band, because of the comparatively high temporal resolution of the radar observations, results from application of the algorithm. The algorithm output can provide guidance to forecasters who are using radar-based quantitative precipitation estimates to issue advisories and warnings. Moreover, the melting-layer observations can be used with a digital elevation model to map the approximate rain–snow line.

Full access
Jonathan J. Gourley and Baxter E. Vieux

Abstract

A major goal in quantitative precipitation estimation and forecasting is the ability to provide accurate initial conditions for the purposes of hydrologic modeling. The accuracy of a streamflow prediction system is dependent upon how well the initial hydrometeorological states are characterized. A methodology is developed to objectively and quantitatively evaluate the skill of several different precipitation algorithms at the scale of application—a watershed. Thousands of hydrologic simulations are performed in an ensemble fashion, enabling an exploration of the model parameter space. Probabilistic statistics are then utilized to compare the relative skill of hydrologic simulations produced from the different precipitation inputs to the observed streamflow. The primary focus of this study is to demonstrate a methodology to evaluate precipitation algorithms that can be used to supplement traditional radar–rain gauge analyses. This approach is appropriate for the evaluation of precipitation estimates or forecasts that are intended to serve as inputs to hydrologic models.

Full access
Jonathan J. Gourley, Anthony J. Illingworth, and Pierre Tabary

Abstract

A major limitation of improved radar-based rainfall estimation is accurate calibration of radar reflectivity. In this paper, the authors fully automate a polarimetric method that uses the consistency between radar reflectivity, differential reflectivity, and the path integral of specific differential phase to calibrate reflectivity. Complete instructions are provided such that this study can serve as a guide for agencies that are upgrading their radars with polarimetric capabilities and require accurate calibration. The method is demonstrated using data from Météo-France’s operational C-band polarimetric radar. Daily averages of the calibration of radar reflectivity are shown to vary by less than 0.2 dB. In addition to achieving successful calibration, a sensitivity test is also conducted to examine the impacts of using different models relating raindrop oblateness to diameter. It turns out that this study highlights the suitability of the raindrop shape models themselves. Evidence is shown supporting the notion that there is a unique model that relates drop oblateness to diameter in midlatitudes.

Full access
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.

Full access
Jessica M. Erlingis, Jonathan J. Gourley, and Jeffrey B. Basara

Abstract

This study uses backward trajectories derived from North American Regional Reanalysis data for 19 253 flash flood reports during the period 2007–13 published by the National Weather Service to assess the origins of air parcels for flash floods in the conterminous United States. The preferred flow paths for parcels were evaluated seasonally and for six regions of interest: the West Coast, Arizona, the Front Range of the Rocky Mountains, Flash Flood Alley in south-central Texas, the Missouri Valley, and the Appalachians. Parcels were released from vertical columns in the atmosphere at times and locations where there were reported flash floods; these were traced backward in time for 5 days. The temporal and seasonal cycles of flood events in these regions are also explored. The results show the importance of trajectories residing for long periods over oceanic regions such as the Gulf of Mexico and the Caribbean Sea. The flow is generally unidirectional with height in the lower layers of the atmosphere. The trajectory paths from oceanic genesis regions to inland hotspots and their orientation with height provide clues that can assist in the diagnosis of impending flash floods. Part II of this manuscript details the land–atmosphere interactions along the trajectory paths.

Full access
Katja Friedrich, Urs Germann, Jonathan J. Gourley, and Pierre Tabary

Abstract

Radar reflectivity (Z h), differential reflectivity (Z dr), and specific differential phase (K dp) measured from the operational, polarimetric weather radar located in Trappes, France, were used to examine the effects of radar beam shielding on rainfall estimation. The objective of this study is to investigate the degree of immunity of K dp-based rainfall estimates to beam shielding for C-band radar data during four typical rain events encountered in Europe. The rain events include two cold frontal rainbands with average rainfall rates of 7 and 17 mm h−1, respectively, and two summertime convective rain events with average rainfall rates of 11 and 22 mm h−1.

The large effects of beam shielding on rainfall accumulation were observed for algorithms using Z h and Z dr with differences of up to ∼2 dB (40%) compared to a K dp-based algorithm over a power loss range of 0–8 dB. This analysis reveals that Z dr and K dp are not affected by partial beam shielding. Standard reflectivity corrections based on the degree of beam shielding would have overestimated rainfall rates by up to 1.5 dB for less than 40% beam shielding and up to 3 dB for beam shielding less than 75%. The investigation also examined the sensitivity of beam shielding effects on rainfall rate estimation to (i) axis–ratio parameterization and drop size distribution, (ii) methods used to smooth profiles of differential propagation phase (ϕ dp) and estimate K dp, and (iii) event-to-event variability. Although rainfall estimates were sensitive to drop size distribution and axis–ratio parameterization, differences between Z h- and K dp-based rainfall rates increased independently from those parameters with amount of shielding. Different approaches to smoothing ϕ dp profiles and estimating K dp were examined and showed little impact on results.

Full access
Heather M. Grams, Pierre-Emmanuel Kirstetter, and Jonathan J. Gourley

Abstract

Satellite-based precipitation estimates are a vital resource for hydrologic applications in data-sparse regions of the world, particularly at daily or longer time scales. With the launch of a new generation of high-resolution imagers on geostationary platforms such as the Geostationary Operational Environmental Satellite series R (GOES-R), an opportunity exists to advance the detection and estimation of flash-flood-scale precipitation events from space beyond what is currently available. Because visible and infrared sensors can only observe cloud-top properties, many visible- and infrared-band-based rainfall algorithms attempt to first classify clouds before deriving a rain rate. This study uses a 2-yr database of cloud-top properties from proxy Advanced Baseline Imager radiances from GOES-R matched to surface precipitation types from the Multi-Radar Multi-Sensor (MRMS) system to develop a naïve Bayesian precipitation type classifier for the four major types of precipitation in MRMS: stratiform, convective, tropical, and hail. Evaluation of the naïve Bayesian precipitation type product showed a bias toward classifying convective and stratiform at the expense of tropical and hail. The tropical and hail classes in MRMS are derived based on the vertical structure and magnitude of radar reflectivity, which may not translate to an obvious signal at cloud top for a satellite-based algorithm. However, the satellite-based product correctly classified the hail areas as being convective in nature for the vast majority of missed hail events.

Full access
Kenneth W. Howard, Jonathan J. Gourley, and Robert A. Maddox

Abstract

Radar measurement uncertainties associated with storm top, cloud top, and other height measurements are well recognized; however, the authors feel the resulting impacts on the trends of storm features are not as well documented or understood by some users of the WSR-88D system. Detailed examination of radar-measured life cycles of thunderstorms occurring in Arizona indicates substantial limitations in the WSR-88D’s capability to depict certain aspects of storm-height attribute evolution (i.e., life cycle) accurately. These inherent limitations are illustrated using a vertical reflectivity structure model for the life cycle of a simple, “single-pulse” thunderstorm. The life cycle of this simple storm is “scanned” at varying ranges and translation speeds. The results show that radar-determined trends are often substantially different from those of the model storm and that in extreme cases the radar-detected storm and the model storm can have trends in storm-top height of opposite sign. Caution is clearly required by both the operational and research users of some products derived from operational WSR-88D data.

Full access