First Rains: Fast-tracking multiscale prediction of rainfall onset across tropical and subtropical regional climates

When will the rains start? Vast regions of Earth's surface experience months-long dry periods before the start of the rainy season. Onset of these rains has defined the start of agricultural calendars for millennia, however, the rapid rate of climate change is upending cen-turies of local knowledge about the arrival of the first rains. Pre-onset heat extremes are amplifying and the risk of delayed onset is increasing as the planet warms to current CO2 levels; these are risks already committed to irrespective of future CO2 emission. Dire impacts on water, food, health and energy systems accompany such delays. First Rains sets out a research programme to fast-track advances in onset prediction and make the breakthroughs integral to unlocking robust climate adaptation in the face of fickle first rains.

Rainfall onset is a dramatic feature of (sub)tropical climates signalling a rapid regime switch from desiccated soils and skies to rain-filled atmospheres. This sharp switch between seasons is heralded by arrival of large thunderstorms. Timing of this arrival is critical for agricultural economies and yet it has rarely been a sole focus of prediction research programmes for over a decade. This lack in focus partly reflects numerical models that, until now, only estimated tropical thunderstorms. And yet, results from recent global monsoon theory advances point to increased delays of onset. Projections of delayed rainfall are most stark in southern Africa, the least studied of the regional monsoons. Critically, little research has engaged local forecast experts here in efforts to regionalise global theory. Gaps in both prediction science and dynamical theory continue to prevent provision of urgently needed decision-relevant onset metrics to climate adaptation efforts. However, cutting-edge new atmospheric models that directly simulate thunderstorms are now available, state-of-the-art observations provide the most comprehensive estimates the Earth System to date, and machine learning (ML) tools are providing powerful new ways to explore these data. These are the tools needed to close onset research gaps and deliver the urgently needed advance in onset prediction.

First Rains will pursue this goal from two fronts. New convective-scale atmospheric models will be rigorously trialled, in close collaboration with modelling centres, to determine new-found capabilities in predicting onset days to weeks in advance. Identified model weaknesses will be fed back to model developers. Careful diagnosis of convective-scale regional dynamics and predictability will ensure maximum benefit to the most at-risk countries. The second line of research will focus on improving characterisation of the spatio-temporal statistics of the first rains, which are more important for operational decisions than a single defined onset date. Innovative use of statistical ML algorithms will aid this onset characterisation in observations and models. Application of ML methods will also provide powerful ways to determine the most important sources of onset predictability in these data. These analyses of state-of-the-art Earth observations and convective-scale models will help determine prediction skill across forecast lead-times from days to months and point to targets for improving this skill further. Advancing the dynamical theory of regional to local-scale onset will unify the convective-scale modelling and observational analysis approaches.

The resulting breakthrough in fundamental prediction research will succeed in close collaboration with experts from countries most exposed to fickle first rains. The FLF +3 years will support uptake of the prediction advances into existing in-country climate adaptation and dissemination networks across the food-water-health nexus. First Rains will solve a fundamental prediction science problem and meet a long-standing and urgent societal need: generating climate information to enable effective adaptation to a warmer world.