A Cloud Condensation Model on Insoluble Nuclei Validated with Radiosonde and Ceilometer Data: Implications for Dust based Rainfall Forecasting

TL;DR

This paper presents a validated cloud condensation model for insoluble nuclei using radiosonde and ceilometer data, enhancing dust-related rainfall forecasting by determining dust particle activation thresholds.

Contribution

It introduces a novel comparative analysis method that transforms radiosonde data into simulated signals to validate cloud condensation on insoluble nuclei.

Findings

Model accurately predicts dust particle activation thresholds.

Improves parameterization of cloud formation in weather models.

Enhances rainfall forecasting in dust-prone regions.

Abstract

This study introduces and validates a cloud condensation model on insoluble nuclei using a novel comparative analysis of simultaneous radiosonde and ceilometer data. A transformation of the radiosonde's temperature and relative humidity profiles into a simulated optical backscatter signal is implemented via the model, which includes a critical rate-limiting activation step. By comparing this simulated signal with the ceilometer's measured data, the model can determine the minimum effective size of dust particles required to act as cloud condensation nuclei. This approach has direct implications for improving the parameterization of cloud formation in local weather models, particularly for rainfall forecasting in dust-prone arid and semi-arid regions.