A Radar Wind Analysis System for Nowcast Applications

Qin Xu,Qingyun Zhao,Shun Liu,Li Wei,Kang Nai,Robert M Rabin

doi:10.1155/2015/264515

Abstract

A radar wind analysis system (RWAS) has been developed for nowcast applications. By ingesting real-time wind observations from operational WSR-88D radars and surface mesonet, this system can produce and display real-time vector winds at each selected vertical level or on each conical surface of radar scans superimposed on radar reflectivity or radial-velocity images. An early version of the system has been evaluated and used to provide real-time winds to drive high-resolution emergency response dispersion models. This paper presents the detailed formulations of background error correlation functions used in each of the three steps of vector wind analysis performed in the RWAS and the method of solution used in each step of vector wind analysis. The performances of the RWAS are demonstrated by illustrative examples.

Highlights

Built upon the recent successes derived from the Collaborative Radar Acquisition Field Test (Kelleher et al [1]), a suite of real-time capabilities has been developed at the National Severe Storms Laboratory (NSSL) to process and display NEXRAD level II data through high speed internet (Lakshmanan et al [2])
This paper aims to present the detailed formulations of background error correlation functions and the method of solution used in each step of the vector wind analysis in the upgraded radar wind analysis system (RWAS)
The early stand-alone version of radar wind analysis system (RWAS) developed at NSSL is upgraded with extended capabilities to analyze radial-velocity observations from multiple radars, while the initial background wind field is no longer zero but extracted from the nearest operational model predictions by interpolating the predicted wind fields in time and space to the analysis grid in an enlarged mesoscale domain (800 × 800 × 10 km3)

Summary

Introduction

Built upon the recent successes derived from the Collaborative Radar Acquisition Field Test (Kelleher et al [1]), a suite of real-time capabilities has been developed at the National Severe Storms Laboratory (NSSL) to process and display NEXRAD level II data through high speed internet (Lakshmanan et al [2]). The random horizontal vector fields of background wind errors normalized by their standard deviation are traditionally assumed to be horizontally homogeneous and isotropic over local (or regional) areas in the widely used statistical interpolation and three-dimensional variational techniques for large-scale and synoptic-scale atmospheric data analyses (Daley [13]). This assumption is likely to be less valid at the mesoscale and storm-scale, but it is still adopted commonly and implicitly along with the statistical interpolation and three-dimensional variational techniques in mesoscale data analysis.

Objectives

Methods

Conclusion