During the month of June 2015, the South Asian (or Southwest) monsoon advanced steadily from the southern to the northwestern states of India. The progression of the monsoon had an apparent effect on the relative strength of convective storm downbursts that occurred during June and July 2015. A convective downburst prediction algorithm, involving the Microburst Windspeed Potential Index (MWPI) and a satellite-derived three-band microburst risk product, and applied with meteorological geostationary satellite (KALPANA-1 VHRR and METEOSAT-7) and MODIS Aqua data, was evaluated and found to effectively indicate relative downburst intensity in both pre-monsoon and monsoon environments over various regions of India. The MWPI product, derived from T574L64 Global Forecast System (NGFS) model data, is being generated in real-time by National Center for Medium Range Weather Forecasting (NCMRWF), Ministry of Earth Sciences, India. The validation process entailed direct comparison of measured downburst-related wind gusts at airports and India Meteorological Department (IMD) observatories to adjacent MWPI values calculated from GFS and India NGFS model datasets. Favorable results include a statistically significant positive correlation between MWPI values and proximate measured downburst wind gusts with a confidence level near 100%. Case studies demonstrate the influence of the South Asian monsoon on convective storm environments and the response of the downburst prediction algorithm.
A suite of products has been developed and evaluated to assess hazards presented by convective storm downbursts
derived from the current generation of Geostationary Operational Environmental Satellite (GOES) (13-15). The existing
suite of GOES downburst prediction products employs the GOES sounder to calculate risk based on conceptual models
of favorable environmental profiles for convective downburst generation. A diagnostic nowcasting product, the
Microburst Windspeed Potential Index (MWPI), is designed to infer attributes of a favorable downburst environment: 1)
the presence of large convective available potential energy (CAPE), and 2) the presence of a surface-based or elevated
mixed layer with a steep temperature lapse rate and vertical relative humidity gradient. These conditions foster intense
convective downdrafts upon the interaction of sub-saturated air in the elevated or sub-cloud mixed layer with the storm
precipitation core. This paper provides an updated assessment of the MWPI algorithm, presents recent case studies
demonstrating effective operational use of the MWPI product over the Atlantic coastal region, and presents validation
results for the United States Great Plains and Mid-Atlantic coastal region. In addition, an application of the brightness
temperature difference (BTD) between GOES imager water vapor (6.5μm) and thermal infrared (11μm) channels that
identifies regions where downbursts are likely to develop, due to mid-tropospheric dry air entrainment, will be outlined.