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Abstract Studying convection, which is one of the least understood physical mechanisms in the tropical atmosphere, is very important for weather and climate predictions of extreme events such as storms, hurricanes, monsoons, floods and hail. Collecting more observations to do so is critical. It is also a challenge. The OTREC (Organization of Tropical East Pacific Convection) field project took place in the summer of 2019. More than thirty scientists and twenty students from the US, Costa Rica, Colombia, México and UK were involved in collecting observations over the ocean (East Pacific and Caribbean) and land (Costa Rica, Colombia). We used the NSF NCAR Gulfstream V airplane to fly at 13 kilometers altitude sampling the tropical atmosphere under diverse weather conditions. The plane was flown in a ‘lawnmower’ pattern and every 10 minutes deployed dropsondes that measured temperature, wind, humidity and pressure from flight level to the ocean. Similarly, over the land we launched radiosondes, leveraged existing radars and surface meteorological networks across the region, some with co-located Global Positioning System (GPS) receivers and rain sensors, and installed a new surface GPS meteorological network across Costa Rica, culminating in an impressive systematic data set that when assimilated into weather models immediately gave better forecasts. We are now closer than ever in understanding the environmental conditions necessary for convection as well as how convection influences extreme events. The OTREC data set continues to be studied by researchers all over the globe. This article aims to describe the lengthy process that precedes science breakthroughs. 

Abstract Moist static energy (MSE) budgets and gross moist stability (GMS) have been widely used as a diagnostic tool to study the evolution of moisture and convection at different time scales. However, use of GMS is limited at shorter time scales because many points in the tropics have close-to-zero large-scale vertical motion at a given time. This is particularly true in the case of convective life cycles, which have been shown to exist with noise-like ubiquity throughout the tropics at intraseasonal time scales. This study proposes a novel phase angle–based framework as a process-level diagnostic tool to study the MSE budgets during these cycles. Using the GMS phase plane, a phase angle parameter is defined, which converts the unbound GMS into a finite ranged variable. The study finds that the convective life cycles are closely linked to evolution of moisture and effectively behave as moisture recharge–discharge cycles. Convective cycles in different datasets are studied using TOGA COARE, a mix of different satellite products and ERA-Interim. Analysis of the MSE budget reveals that the cyclic behavior is a result of transitions between wet and dry equilibrium states and is similar across different regions. Further, vertical and horizontal advection of MSE are found to act as the primary drivers behind this variability. In contrast, nonlinearities in the radiative and surface flux feedbacks are found to resist the convective evolution. A linearized model consistent with moisture mode dynamics is able to replicate the recharge–discharge cycle variability in TOGA COARE data. Significance Statement In the tropics, variability of moisture and rainfall are closely linked to each other. Through this study we aim to better understand the evolution of moisture in observed daily time series data. We present a novel phase angle–based diagnostic tool to represent and study the energy budget of the system at this time resolution. Our results suggest that similar processes and mechanisms are relevant across different regions and at different scales in the tropics with moisture dynamics being important for these processes. Further, a key role is played by the energy transport associated with the large-scale circulation that drives moisture evolution in a cyclic pattern.