11-Year Warm Cloud Modification Experiment in Maharashtra State, India
A. S. R. Murty et. al
Abstract
A warm cloud modification experiment was carried out in an area of 4800 Sq.Km in the Pune region,India, during the 11-summer monsoon (June-September) seasons (1973-74, 1976, 1979-86). A double-area cross-over design with area randomization was adopted and an instrumented aircraft was used for seeding and cloud physical measurements. Finely pulverised salt (sodium chloride) particles were released into the monsoon clouds (cumulus and stratocumulus) during aircraft penetrations into the clouds at a height of 200-300 m above the cloud-base. The warm cloud responses to salt seeding are found to be critically dependent on the cloud physical characteristics e.g., vertical thickness and liquid water content. Clouds with vertical thickness greater than 1 km, LWC greater than 0.5 gm/cubic m when seeded with salt particles (modal diameter 10 micro m, concentration 1 per litre of cloud air) produced increase in rainfall of 24 per cent significant at 4 per cent level. Shallow clouds (vertical thickness less than 1 km, LWC less than 0.5 gm/cubic m) when seeded showed tendency for dissipation. The cloud physical observations made in not-seeded (control) and seeded (target) clouds have provided some useful evidence to test the applicability of the warm cloud modification hypothesis. The results of the cloud model computations suggested that moderate convergence at the cloud-base is essential for the cloud growth and development of precipitation in the real world. Hygroscopic particle seeding of warm clouds under favourable dynamical conditions (convergence at the cloud-base level) may result in the acceleration of the collision-coalescence process resulting in the enhancement of rainfall.
Create a lesson
Related papers
Morphology-based retrieval of local wave parameters and phase shifts in satellite-observed atmospheric disturbances
Yuriy Klymenko, Alla Fedorenko, Evgen Kryuchkov et al.
Parametric wave spectrum models for prediction of Stokes drift profiles
W. Erick Rogers, Yalin Fan, Luis Zamudio et al.
Evaluating LLMs for Translating Legacy Fortran Atmospheric Physics to GPU-Accelerated JAX
Iris Linck, John Dennis, John Schreck et al.
legoESM: a modular, differentiable, multiscale, AI-ready Earth system model built with AI agents
Pierre Gentine, Dhruv Balwada, Aytaç Paçal et al.
A Physics-Constrained Implicit Profile Network for Continuous Reconstruction of Tropical Cyclone Near-Surface Wind Profiles
Jian Ma, Yilin Yang, Robert Rogers et al.
A Graph Neural Network for Global Daily Fire Radiative Power Prediction at Medium-Range Lead Times
Li Zhang, Jun Wang, Isidora Jankov et al.