Diagnostic scripts and processed lifecycle composites for convective rainfall over Hong Kong
Year: 2026
Type: software
Abstract: I. OVERVIEWThis repository contains the core MATLAB diagnostic analysis scripts and processed composite datasets supporting the study: "A Vertically Resolved Lifecycle Diagnostic Framework Identifies Robust Thermodynamic-Dynamic Controls on Convective Rainfall Intensity in a Subtropical Monsoon Region" by Moufeng Wan, Hui Su, and Pak Wai Chan, submitted to Journal of Geophysical Research: Atmospheres. The framework identifies universal preconditioning and onset characteristics by integrating thermodynamic (IRH, Moist Static Energy) and dynamical (divergence, vertical velocity, vertical wind shear) atmospheric profiles from ERA5 reanalysis across five rainfall intensity categories and four seasons. II. CONTENTS1. Code (`diagnostic_lifecycle_compositing.m`): - Computes layer-resolved Integrated Relative Humidity (IRH) across eight pressure cut-offs (1000-925 hPa to 1000-150 hPa). - Computes Moist Static Energy (MSE) and its vertical gradients (ΔMSE_1 for low-level conditional instability; ΔMSE_2 for mid-level stratification). - Implements the 5-node precipitation event (PE) lifecycle compositing algorithm (BR12-BR1 -> BR0 -> DR_max -> AR0 -> AR1-AR12) using a non-parametric bootstrap approach (n=1500 replicates) for 95% confidence intervals. - Extracts and standardizes kinematic fields: horizontal divergence, vertical velocity, and bulk vertical wind shear (deep and low layers). 2. Data (`PE_statistics_seasonal.mat` / `PE_statistics_seasonal_Fig.mat`): - Structured MATLAB datasets containing grid-averaged maximum hourly rainfall rates across five percentiles (R1 to R5). - Seasonal no-rain (NR) climatological baselines and diurnal cycle statistics. - 19 years of processed multi-variable composites for Hong Kong across DJF, MAM, JJAS, and ON seasons.
Authors: Wan, Moufeng, Su, Hui, Chan, Pak Wai
Language: English
Subfield: Atmospheric Science
Field: Earth and Planetary Sciences
Domain: Physical Sciences
SDG: Climate action
Open Access status: green
OpenAlex ID: W7225600355