Detection and Tracking of Tropical Convective Storms Based on Globally Gridded Precipitation Measurements: Algorithm and Survey over the Tropics

Abstract

This paper is the first attempt to document a simple convection tracking method based on the IMERG precipitation product to generate an IMERG-based Convection Tracking (IMERG-CT) dataset. Up to now precipitation datasets have been Eulerian accumulations. Now with IMERG-CT, we can estimate total rainfall based on Lagrangian accumulations, which is a very important step in diagnosing cloud-precipitation process following the evolution of air masses. Convection tracking algorithms have traditionally been developed based on brightness temperature (Tb) from satellite infrared (IR) retrievals. However, vigorous rainfall can be produced by warm-topped systems in moist environment, which cannot be captured by traditional IR-based tracking but is observed in IMERG-CT. Therefore, an advantage of IMERG-CT is its ability to include the previously missing information of shallow clouds that grow into convective storms, which provides us more complete lifecycle records of convective storms than traditional IR-based tracking does. This study also demonstrates the utility of IMERG-CT through investigating various properties of convective systems in terms of the evolution before and after peak precipitation rate and amount. For example, composite analysis reveals a link between evolution of precipitation and convective development: the signature of stratiform anvils remaining after the storm has produced the maximum rainfall, as average Tb stays almost constant for 5 hours after the peak of precipitation. Our study highlights the importance of joint analysis of cloud and precipitation data in time sequence, which helps elucidate the underlying dynamic processes producing tropical rainfall and its resultant effects on the atmospheric thermodynamics.

Convective Organization and 3D Structure of Tropical Cloud Systems deduced from Synergistic A-Train Observations and Machine Learning

“…The cloud system concept allows to link the convective core and anvil properties and therefore a process-oriented evaluation of parameterizations in climate models (Stubenrauch et al, 2019). In agreement with earlier studies (e. g. Schumacher and Houze, 2003;Roca et al, 2014, Takahashi et al, 2021, we found that the rain intensity is maximum after the first development of anvils and that deeper convection leads to larger heavy rain areas. These results also confirm the quality of the ML derived precipitation rate classification.…”

“…According to Takahashi et al (2021), using a convection-tracking analysis on data from Intergrated Multisatellite Retrievals for GPM (IMERG), the fraction of precipitating cores (adjacent grid cells with a rain rate > 5 mm/hr) within precipitation systems (adjacent grid cells with rain rate > 0.5 mm/hr) first increases and then decreases during the evolution of these systems.…”

“…Our data do not provide the absolute system life time, but the convective core fraction within a system indicates the maturity stage in a normalized life cycle. We also know that the coldest systems have also a tendency to live the longest (e. g. Rossow and Pearl, 2007;Takahashi et al, 2021). Figure 7 presents the evolution during the life cycle of a) the strong rain area relative to the precipitating area within single core MCSs and b) the precipitating area relative to the whole MCS area.…”

Properties of Mesoscale Convective Systems Throughout Their Lifetimes Using IMERG, GPM, WWLLN, and a Simplified Tracking Algorithm

“…Recently, Takahashi et al. (2021) have used IMERG to develop a convection‐tracking algorithm. Overall, IMERG precipitation estimates have been found to be reasonable (e.g., Tan et al., 2018) and capture many well‐known areas of heavy precipitation, such as the oceanic intertropical convergence zone (ITCZ) and orographically enhanced precipitation in India, the Philippines, and Papua New Guinea (Liu, 2016).…”

“…These high spatial and temporal resolution data are useful since they can provide estimates of precipitation on a near global scale and allow precipitation events to be observed throughout their lifetimes. Recently, Takahashi et al (2021) have used IMERG to develop a convection-tracking algorithm. Overall, IMERG precipitation estimates have been found to be reasonable (e.g., Tan et al, 2018) and capture many well-known areas of heavy precipitation, such as the oceanic intertropical convergence zone (ITCZ) and orographically enhanced precipitation in India, the Philippines, and Papua New Guinea (Liu, 2016).…”