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.

Abstract

The advent of Internet-2 and effective data compression techniques facilitates the economic transmission of base-level radar data from the Weather Surveillance Radar-1988 Doppler (WSR-88D) network to users in real time. The native radar spherical coordinate system and large volume of data make the radar data processing a nontrivial task, especially when data from several radars are required to produce composite radar products. This paper investigates several approaches to remapping and combining multiple-radar reflectivity fields onto a unified 3D Cartesian grid with high spatial (≤1 km) and temporal (≤5 min) resolutions. The purpose of the study is to find an analysis approach that retains physical characteristics of the raw reflectivity data with minimum smoothing or introduction of analysis artifacts. Moreover, the approach needs to be highly efficient computationally for potential operational applications. The appropriate analysis can provide users with high-resolution reflectivity data that preserve the important features of the raw data, but in a manageable size with the advantage of a Cartesian coordinate system.

Various interpolation schemes were evaluated and the results are presented here. It was found that a scheme combining a nearest-neighbor mapping on the range and azimuth plane and a linear interpolation in the elevation direction provides an efficient analysis scheme that retains high-resolution structure comparable to the raw data. A vertical interpolation is suited for analyses of convective-type echoes, while vertical and horizontal interpolations are needed for analyses of stratiform echoes, especially when large vertical reflectivity gradients exist. An automated brightband identification scheme is used to recognize stratiform echoes. When mosaicking multiple radars onto a common grid, a distance-weighted mean scheme can smooth possible discontinuities among radars due to calibration differences and can provide spatially consistent reflectivity mosaics. These schemes are computationally efficient due to their mathematical simplicity. Therefore, the 3D multiradar mosaic scheme can serve as a good candidate for providing high-spatial- and high-temporal-resolution base-level radar data in a Cartesian framework in real time.

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.

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.

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.

Abstract

Uncertainty in quantitative precipitation forecasts (QPFs) from numerical weather prediction (NWP) models manifests in errors in the amounts of rainfall, storm structure, storm location, and timing, among other precipitation characteristics. In flash flood forecasting applications, errors in the QPFs can translate into significant uncertainty in forecasts of surface water flows and their impacts. In particular, the QPF errors in location and structure result in errors on flow paths, which can be highly detrimental in identifying locations susceptible to flash flood impacts. To account for this type of uncertainty, the neighboring pixel ensemble technique (NPET) was devised and implemented as a postprocessing algorithm of deterministic or ensemble outputs from a distributed hydrologic model. The aim of the technique is to address displaced hydrologic responses resulting from location biases in QPFs using a probabilistic approach. NPET identifies a sampling region surrounding each forecast pixel and builds an ensemble of surface water flow values considering the pixel’s physiographic similarities. The probabilistic information produced with NPET can be calibrated through a set of tunable parameters that are adjusted to account for NWP-specific QPF error characteristics. The utility of NPET is demonstrated for the Ellicott City flash flood event on 27 May 2018, using products and tools routinely used in the U.S. National Weather Service for warning operations. Results from this case demonstrate that NPET effectively conveys uncertainty information about QPF precipitation location in a hydrologic context.

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.

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.

Abstract

Characterization of the error associated with satellite rainfall estimates is a necessary component of deterministic and probabilistic frameworks involving spaceborne passive and active microwave measurements for applications ranging from water budget studies to forecasting natural hazards related to extreme rainfall events. The authors focus here on the relative error structure of Tropical Rainfall Measurement Mission (TRMM) precipitation radar (PR) quantitative precipitation estimation (QPE) at the ground by comparison of 2A25 products with reference values derived from NOAA/NSSL’s ground radar–based National Mosaic and QPE system (NMQ/Q2). The primary contribution of this study is to compare the new 2A25, version 7 (V7), products that were recently released as a replacement of version 6 (V6). Moreover, the authors supply uncertainty estimates of the rainfall products so that they may be used in a quantitative manner for applications like hydrologic modeling. This new version is considered superior over land areas and will likely be the final version for TRMM PR rainfall estimates. Several aspects of the two versions are compared and quantified, including rainfall rate distributions, systematic biases, and random errors. All analyses indicate that V7 is in closer agreement with the reference rainfall compared to V6.

Abstract

The differential phase (Φ_DP) 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 (A_H ) and specific differential attenuation (A _DP), then attenuation can easily be corrected. The coefficients of proportionality, γ_H 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 (Z_H ), 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 Z_H (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.