On the Climatological Use of Radar Data Mosaics: Possibilities and Challenges

Abstract

occurrence, formation, and decay? What is the climatology of severe weather? Answers to these 28 questions have value on their own and also invariably trigger more questions about the processes 29 causing these patterns as well as suggest some answers. They also have considerable pedagogical 30 value to illustrate in the classroom the impacts on precipitation of different processes such as 31 sea-land breezes, topography, and seasons. 32In this work, U.S. mosaics of radar data from 1996 to 2015 are used to demonstrate the 33 possibilities offered by such a data set. Three topics are touched: a) climatologies and daily 34 cycles of precipitation and convection, and what they can teach us about precipitation 35 mechanisms; b) the spatial and temporal distribution of the appearance and occurrence of 36convection, and what it reveals on the importance of surface terrain properties for these events; 37 and c) the power and challenges of looking for a small signal in even such a large dataset using 38 the influence of weekly activity cycles and of cities on precipitation as an illustration. 39 CAPSULE 40Where the radar climatology of weather echoes is used to reveal how surface properties 41 shape precipitation occurrence and to explore the ease or difficulty to unambiguously detect 42 these effects. 43 3 Precipitation climatology and radars 44Radar has historically transformed the way we study storms thanks to its ability to take 45 frequent and regular 3-D measurements even through clouds and precipitation. As a result, it is 46 commonly used both operationally for weather surveillance as well as for research to help 47 understand the dynamics and microphysical processes of atmospheric phenomena (Atlas et al. 48 1990; Wakimoto and Srivastava 2003; Fabry 2015). 49The first national Doppler radar network in the world was deployed in the United States 50 in the mid-1990s. More importantly, a framework and process for monitoring and maintaining 51 radar data quality was implemented and adhered to since. From late 1995 onwards, the 52 reflectivity data from all these radars have been made into national mosaics by a variety of 53 actors, including private companies, research institutes, and the National Weather Service itself. 54A unique dataset now exists to study radar echoes collected by the same radars over a period of 55 more than 20 years (and counting) over the contiguous United States. 56Though country-wide climatological information on precipitation exists, for example 57 from the US Climate Normals (Applequist et al. 2012, Arguez et al. 2012, the information 58 available is not as rich as it could be. As an illustration, we challenge all readers to find the 59 These questions both complicate the interpretation of a radar echo climatology and can also be 88 partially answered by it (see the sidebar on Data, Processing, and Quality Issues for some 89 details). In parallel, radar has unique strengths, in particular for measuring the coverage and 90 instantaneous intensity of precipitation, more so than for quant...

Where, When, and Why Did It Rain during PECAN?

“…7a) and 0100-1300 UTC nighttime ( Fig. 7b) accumulated precipitation fields show that most of the PECAN precipitation fell over the nighttime hours, consistent with previous long-term studies (e.g., Kincer 1916;Ahijevych et al 2004;Fabry et al 2017). The nighttime precipitation was most prevalent in the northeast of the radar domain, similar to the total rainfall distribution of Fig.…”

“…A minimum in precipitation was located in western Kansas and north-central Oklahoma. This PECAN 2015 QPE pattern was similar to the 15-yr radar climatological precipitation record presented in Fabry et al (2017).…”

“…It has been known for more than a century that the diurnal pattern of summertime precipitation in the U.S. Great Plains has a strong nocturnal maximum (e.g., Kincer 1916;Bleeker and Andre 1951;Wallace 1975;Easterling and Robinson 1985;Heideman and Fritsch 1988;Colman 1990;Carbone et al 2002;Fabry et al 2017). Maddox (1980) used satellite imagery to show that this nocturnal precipitation was largely attributed to long-lived (.12 h) and large (.100 000 km 2 ) systems, termed mesoscale convective complexes (MCCs).…”

A Radar-Based Climatology of Mesoscale Convective Systems in the United States

“…This study uses two primary datasets: an archive of National Operational Weather Radar (NOWrad) images and the stage IV hourly precipitation analysis (Lin and Mitchell 2005). The NOWrad dataset is a CONUSwide mosaic of composite reflectivity with approximately 2-km spatial resolution that can be used to generate objective climatologies for precipitation events of interest (Fabry et al 2017). The values of each grid point represent a proxy of the column-maximum instantaneous rainfall rate measured in units of dBZ (reflectivity).…”

Estimation of Hourly Rainfall during Typhoons Using Radar Mosaic-Based Convolutional Neural Networks

“…A radar is commonly used for both weather surveillance and research to help meteorologists understand the dynamics and microphysical processes of atmospheric phenomena [16]. Radar reflectivity is a measure of the fraction of electromagnetic waves reflected by precipitation particles (e.g., rain, snow, or hail).…”