Improving QPE Over Complex Terrain Using Cloud-to-ground Lightning Data

Quantitative precipitation estimation (QPE) has traditionally been carried out using weather radars and rain gauges networks. Every one of these techniques has its own strenghts and weaknesses and none per se provides an accurate areal precipitation estimation. Authors have suggested the search for new remote sensing alternatives to retrieve QPE such as satellite and lightning, especially over regions with poor sensor coverage such as montanious terrain. Over the last 20 years, the relationship between lightning and rainfall has been studied with more intensity and although this relation can vary depending on the geographic region, meteorological conditions, and nature of precipitation among others, it can provide retrievals at high space and time resolutions.

In this presentation, we present the results of estimating convective precipitation by using cloud-to-ground lightning occurrences over the southwest U.S. and northwest Mexico at high space and time resolutions (5 km 5 minutes) by employing two models: one seasonal and the other dynamic. We will show that this methodology can be useful to estimate preciptiation over areas of poor sensor coverage and/or complex terrain.