Analysis of the Life Cycle of Extratropical Cyclone Precipitation Based on the Global Precipitation Measurement Mission

Midlatitude precipitation is predominantly caused by extratropical cyclones. The large-scale circulation of a storm has a strong influence on the characteristics of the precipitation generated, but the latent heating associated with forming precipitation can also influence storm circulation. The details of these interactions have mainly come from case studies and numerical models, because of lack of high quality data in both the spatial and temporal domain. NASA’s Global Precipitation Mission has made an effort to change this, and we use that data here to address the question: what is the most likely temporal evolution of precipitation during the life cycle of an extratropical cyclone. Using Lagrangian tracking, we identify extratropical cyclones in reanalysis. Then, we co-locate the cyclone tracks with precipitation data from the Integrated Multi-satellitE Retrievals for GPM (IMERG) data product, to generate cyclone-centered composites. By utilizing the Lagrangian tracks, we can sort the cyclone-centered composites based on cyclone life cycle, which we define using the storm’s wind speed. We find that storm-centered area-average precipitation peaks 18-hours prior to the wind speed maximum. Furthermore, even 2-days prior to peak wind speed, the area-average precipitation is greater than at the time the storm is the strongest. We repeat the analysis using sea level pressure as the metric for storm strength, and find a similar result. We also carry out the analysis using GPCP, which is daily, and find a consistent result. The analysis supports the theoretical role of in-storm latent heating leading to storm intensification. However, it may also be the case that our result simply reflects the fact that storms typically move poleward as they intensify, and at higher latitudes the air is cooler, which makes heavy rain rates less likely. Subsetting tests for cyclones in the southern hemisphere are used to determine the most likely explanation of the timing of the precipitation maximum relative to the storm strength maximum.