Convective Precipitation Estimation in Complex Terrain by using Cloud-to-ground Lightning

Convective Precipitation Estimation in complex Terrain by using cloud-to-ground lightning With its own strengths and weakneses, rain gauge networks have been used for Quantitative Precipitation Estimation (QPE). Although gauges are an accurate precipitation measurement, they are a point measurement for QPE that depends on the density of the network, which is typically low. Weather radars on the other hand, suffer from weaknesses in the Z-R callibration relationship, precipitation evaporation, terrain blockage in montainous areas. Because none of these common techniques are free of errors, alternatives have been proposed for QPE, for example, satellites, disdrometers and lightning. The relationship between lightning and precipitation has been studied for more than 30 years. Lightning has been used as an indicator of precipitation, but not as an actual estimator. In this presentation, we discuss the use of a recursive method for QPE by using lightning over SW U.S. where poor radar coverage is evident. Taking as a base, a seasonally fixed model that considers time and space neighbors over a grid, a kalman filter is run to estimate precipitation by using cloud-to-ground lightning occurrences including regions where the radar cannot measure precipitation. At a five kilometer and 5 minutes space/time resolution, precipitation estimates by the kalman dynamic model improves precipitation estimation obtained just from the seasonally fixed model. In this presentation, we describe the algorithm used and present results for the years 2009 and 2010.