Advection-Based Adjustment of Radar Measurements

Abstract

When making radar-based precipitation products, a radar measurement is commonly taken to represent the geographical location vertically below the contributing volume of the measurement sample. However, when wind is present during the fall of the hydrometeors, precipitation will be displaced horizontally from the geographical location of the radar measurement. Horizontal advection will introduce discrepancies between the radar-measured and ground level precipitation fields. The significance of the adjustment depends on a variety of factors related to the characteristics of the observed precipitation as well as those of the desired end product. In this paper the authors present an advection adjustment scheme for radar precipitation observations using estimated hydrometeor trajectories obtained from the High-Resolution Limited-Area Model (HIRLAM) MB71 NWP model data. They use the method to correct the operational Finnish radar composite and evaluate the significance of precipitation advection in typical Finnish conditions. The results show that advection distances on the order of tens of kilometers are consistently observed near the edge of the composite at ranges of 100-250 km from the nearest radar, even when using a low elevation angle of 0.38. The Finnish wind climatology suggests that approximately 15% of single radar measurement areas are lost on average when estimating ground level rainfall if no advection adjustment is applied. For the Finnish composite, area reductions of approximately 10% have been observed, while the measuring area is extended downstream by a similar amount. Advection becomes increasingly important at all ranges in snowfall with maximum distances exceeding 100 km.

Correcting for wind drift in high resolution radar rainfall products: a feasibility study

“…The data are adjusted in situ and output in the same polar format. This is in contrast to the work of Mittermaier et al (2004) and of Lauri et al (2012), who apply corrections to radar CAPPIs (constant-altitude PPIs) and Cartesian composites respectively.…”

“…The fall time for this path is calculated and the reflectivity measurement from the appropriate time placed at the surface. A prognostic approach is described in detail by Lauri et al (2012) and illustrated in their Fig. 4.…”

“…The authors propose a correction for fall streak profile in the snow layer using Met Office mesoscale model wind profiles. A similar algorithm is tested on the Finnish operational rain rate composite by Lauri et al (2012), which extends the original wind drift model to the melting and liquid layers, using a simple drop fall speed profile to calculate total displacements. Neither algorithm is assessed for accuracy on a fine scale grid.…”

Remote Sensing

“…Hogan and Kew (2005) and Kalesse et al (2016) showed how in situations when vertical wind shear is observed, the evolution of snow particles should be tracked along slanted fall streaks instead of considering vertical profiles. Other studies used the principle to observe hydrometeors with high spatial resolution (Collier 1999) or to improve radar-derived rainfall estimations (Mittermaier et al 2004;Lack and Fox 2007;Lauri et al 2012). Kalesse et al (2016) assumed that the ice-formation process is stationary during cloud observation, and only additional information about the horizontal wind field is needed in order to follow particles through a cloud.…”

Measuring Snow with Weather Radar

“…to the runway half an hour later. Lauri et al (2012) have discussed the effect of advection in snowfall measurement.…”