P8B.8 1 REAL-TIME IMPLEMENTATION OF REFRACTIVITY RETRIEVAL: PARTNERSHIP BETWEEN THE UNIVERSITY OF OKLAHOMA, NATIONAL SEVERE STORMS LABORATORY, AND THE RADAR OPERATIONS CENTER B. L. Cheong1 ,∗, R. D. Palmer1 , C. Curtis2 ,3 , K. Hondl3 , P. Heinselman2 ,3 , D. Zrnic3 , D. Forsyth3 , R. Murnan4 , R. Reed4 and R. Vogt4 1 School of Meteorology, University of Oklahoma, Norman, Oklahoma, USA 2 Cooperative Institute for Mesoscale Meteorological Studies, University of Oklahoma, Norman, Oklahoma, USA 3 NOAA/OAR National Severe Storm Laboratory, Norman, Oklahoma, USA 4 NWS NEXRAD Radar Operations Center, Norman, Oklahoma, USA ABSTRACT 1. INTRODUCTION High-resolution, near-surface refractivity measurements Until recently, moisture measurements were normally have the potential of becoming an important tool for only possible by in situ instruments. For example, the ra- operational forecasting and general scientific studies. diosonde network across the nation with approximately Access to measured refractivity fields with high spatial 50-100 km spacing performs hourly measurements. To and temporal resolution near the surface opens a new pursue further understanding and better prediction of paradigm for understanding the convective processes convective processes, e.g., convective precipitation and within the boundary layer. It has been shown via ad- its intensification, the existing surface instruments sim- vanced physical models that surface refractivity plays ply do not provide sufficient spatial and temporal reso- an important role in convective processes and, there- lution [Weckwerth and Parsons, 2003]. Fortunately, sur- fore, is expected to be valuable for forecasting the initi- face moisture is now possible to be retrieved remotely ation and intensity of convective precipitation. For this using radar echoes from ground targets [Fabry et al., project, the refractivity field is retrieved remotely us- 1997]. The relatively higher spatial and temporal res- ing S-band radars by measuring the returned phase olution, in comparison with the existing surface instru- from ground clutter. Pioneering work of Fabry et al. ments, opens up a new paradigm for surface moisture [1997] has demonstrated the usefulness of this tech- observations. nique. By adopting this refractivity retrieval concept, an independent real-time software platform has been de- Based on the work of Fabry et al. [1997], a separate veloped. The software was written with a modular de- platform to retrieve surface refractivity from the radar sign for portability and will be tested during the spring echoes from ground targets has been developed here 2007 storm season on two radars in Oklahoma. Both the at the University of Oklahoma. Real-time software has National Weather Radar Testbed – Phased Array Radar been built with a modular design for portability. This (NWRT PAR), supported by the National Severe Storm real-time software is being tested during the spring 2007 Laboratory (NSSL), and the WSR-88D weather radar storm season on two independent radars in Oklahoma. near Oklahoma City (KTLX), supported by the Radar Both the NWRT PAR, operated by the NSSL, and the Operations Center (ROC), will be used for this study. Us- WSR-88D weather radar near Oklahoma City (KTLX), ing the raw Level-I time series data from the radars, the operated by the Norman WFO and supported by the modular software platform will be used to process the Radar Operations Center ROC, are being used for this data in real-time for refractivity fields, which will be sent study. to the Norman Weather Forecast Office (WFO). The re- fractivity fields will be displayed through the Warning De- cision Support System - Integrated Information (WDSS- 2. OVERVIEW OF RADAR REFRACTIVITY RE- II) for evaluation. Working closely with the WFO fore- TRIEVAL (SAME AS P8B.9) casters, qualitative assessment procedures will be fol- lowed to evaluate the usefulness of the refractivity fields Refractive index, n, of a medium is defined as the ratio for operational forecasting. of the speed of light in a vacuum to the speed of light in the medium. For the air near the surface of the earth, ∗ Corresponding author address: Boon Leng Cheong, University of Oklahoma, School of Meteorology, 120 David L. Boren Blvd., Rm this number is typically around 1.003 and changes are −5 4640, Norman, OK 73072-7307; e-mail: [email protected] on the order of 10 [Bean and Dutton, 1968]. For con- P8B.8 2 venience, a derived quantity referred to as refractivity is OK Mesonet [Brock et al., 1995; McPherson et al., used in many scientific studies, and is mathematically 2007]. We will use this network to provide an estimate of formulated as follows the reference refractivity map. Under conditions where the spatial structure of refractivity is not complex, the 6 N = 10 (n − 1) (1) OK Mesonet allows us to derive an accurate reference refractivity map. Refractivity is related to meteorological parameters as shown below [Bean and Dutton, 1968] A flowchart of refractivity retrieval algorithm is provided in Figure 1. First, a map of reference phase measure- p 5 e N = 77.6 +3.73 × 10 (2) ments from the radar, associated with the time of the T T 2 reference refractivity from OK Mesonet are collected. where p represents the air pressure in hectopascal In general, we would like the structure of the field to (hPa), T represents the absolute air temperature in be relatively simple, so that the coarse sampling of the Kelvin (K) and e represents the vapor pressure in hPa. Mesonet can be used to produce an accurate reference The first term in equation (2) is proportional to pressure refractivity map. During normal scanning time, a map of p and is, therefore, related to the air density. The sec- phase measurement is obtained and subsequently used ond term is proportional to vapor pressure e, which is to derive a map of phase difference from the reference. dominated by moisture. Near the surface of the earth Then, regions without good ground targets (based on with relatively warm temperatures, most of the spatial ground clutter coverage and its quality) are masked out variability in N results from the change in the second to retain only those phase measurements that are use- term. ful for refractivity retrieval. A process of spatial interpo- lation and smoothing is applied to this masked phase- In theory, given that the received phase from stationary difference map in order to fill the map. By computing ra- targets is a path-integrated function of the refractive in- dial derivatives (refer to Equation (5)) of this smoothed dex, which is described as follows phase-difference map, refractivity change can be ob- 4πf r tained. Another smoothing is applied to this refractivity φ(r)= − n(γ)dγ (3) change map to reduce the inherent uncertainty in the c Z0 measurement and derivative operation. Finally, abso- where f represents the frequency, c represents the lute refractivity can be obtained by adding the reference speed of light (299,792,458 m s−1) and r is the range. In refractivity map to the refractivity change map. practice, the radar wavelength that is on the order of cm and n ≈ 1, so the phase wraps many times within a res- Phase measurement for a Phase measurement during olution volume depth which makes deriving refractivity map of reference phase operation time Phase Change ∆φ (rad) directly from a single scan (Equation (3)) problematic. 0 2 40 To mitigate this phase wrapping problem, Fabry et al. Reno Oklahoma City A map of phase difference: 20 Processed ∆φ (rad) KTLX Sh [1997] proposed that the change of refractivity between 0 2 KOUN/PAR 0 Norman 40 two scans can be obtained instead, i.e., Reno kasha Oklahoma City Purcell 20 KTLX Sh 0 20 40 KOUN/PAR Image processing: 0 Norman ∆φ(r) = φ(r, t1) − φ(r, t0) clutter quality, masking, smoothing kasha Purcell Refractivity Change ∆N 4πf r 0 10 20 − − 0 20 40 40 = [n(γ,t1) n(γ,t0)] dγ. (4) Reno Oklahoma City c Z 20 0 KTLX Radial gradient Sh KOUN/PAR 0 Norman kasha If the refractivity field of the reference scan (t0) is known, Purcell the measurement of the change of refractivity allows us 0 20 40 to obtain the absolute refractivity map simply by adding the difference to the reference map. By performing a Figure 1: Procedure of refractivity retrieval range derivative in equation (3), it can be shown that d 4πf [φ(r, t1) − φ(r, t0)] = − [n(r, t1) − n(r, t0)] . dr c 3. REAL-TIME DATA PROCESSING, COMMUNICA- (5) TION, AND DISPLAY where measurement at time t0 is referred to as the ref- erence, i.e., reference phase and reference refractivity. Real-time data processing software for refractivity re- Fortunately for our studies, Oklahoma has a reliable, trieval has been developed here at the University of Ok- high-quality network of surface stations, known as the lahoma. It is designed in a modular architecture in order P8B.8 3 to provide flexible portability. Such an architecture al- AT THE RADAR lows for the application of the processing software from Data Interface one radar to another with minimal changes. In addition, it also unifies the software changes or upgrades for dif- Pre-processing Refractivity Retrieval ferent radars. Raw I/Q Generation of The data flow from the raw I/Q time series to the fully Level II Products processed radar products, which will be presented to the user (weather forecasters) for product evaluation is Communication Communication shown in Figure 2. The raw time series data are in- Software Communication Link Software gested into the processing software through the raw data interface, which can be one that has been stan- AT THE NWC dardized, e.g, SIGMET’s RVP-8, or one that is com- WDSS-II Server pletely designed in-house.