ALBERT

Description: In this study we are focusing on the retrieval of quantitative precipitation estimates using C-band dual polarization radar installed at southern tip of India. Knowledge of spatial variability of precipitation would be helpful to better understand the dynamics of mesoscale cloud systems. A popular approach is to use doppler weather radar (DWR) data to obtain precipitation using some relationships. Usually power-law type relationships (Z = aR〈sup〉b〈/sup〉) between the rain rate (R) reflectivity (Z) are widely used for retrieval of rainfall. But Z-R relations have a great degree of uncertainty because of the large scatter in the Z-R scatter diagram which is usually used to obtain the Z-R relation. To overcome this issue, we have tried other relations between rain rate and polarimetric variables [e.g., Z〈sub〉h〈/sub〉, Z〈sub〉dr〈/sub〉, rho, K〈sub〉dp〈/sub〉]. we have adopted the T-matrix formulation to calculate the values of Z〈sub〉h〈/sub〉, Z〈sub〉dr〈/sub〉, rho, K〈sub〉dp〈/sub〉 for different 1-minute DSDs observed from optical disdrometer during pre-monsoon [Mar-Apr-May] of 2016, 2017, 2019, 2020, 2021. Then we have obtained relations between rain rate and different combinations of polarimetric variables [e.g., R(Z〈sub〉h〈/sub〉), R(K〈sub〉dp〈/sub〉), R(Z〈sub〉h〈/sub〉, Z〈sub〉dr〈/sub〉), R(K〈sub〉dp〈/sub〉, Z〈sub〉dr〈/sub〉)]. Further we evaluated them using the data of 2018 from the polarimetric DWR to find the best estimate among them. We have also tried a machine learning (ML) model to obtain precipitation estimate. Though the overall performance of different estimates is close to each other, there is hint that the ML model might be more useful in heavy precipitation.

Description: The study investigates the hydrometeor characteristics of stratiform precipitation over High altitude Cloud Physics Observatory, in Southern Western Ghats using collocated observation and high-resolution spectral bin microphysics (WRF-SBM) full model. Stratiform precipitating systems identified with Bright Band (BB) signatures are selected for the analysis i.e., 11〈sup〉th〈/sup〉-12〈sup〉th〈/sup〉, 20〈sup〉th〈/sup〉, and 21〈sup〉st〈/sup〉 of October 2021. The numerical simulations reproduced temporal characteristics (total duration of ~8 hours), of the BB event on 11 Oct 2021. However, the simulation underestimated the duration of ~2 hours for the event of 21 October 2021, and also the model pre-simulated (~one hour) the event on 21 October 2021 with an underestimated reflectivity of 〈20 dBZ below the melting layer. The simulated melting layer height is around 5 km with maximum radar reflectivity of 40 dBZ which is approximately 10 dBZ higher than the observation. The microphysical analysis of BB event on 11 October 2021, shows low graupel concentration above 0-degree isotherm level and high snow mixing ratio, undergoes a microphysical process that led to the raindrops. The simulation shows comparatively high concentrations of supercooled drops at upper levels in form of ice columns, plates, (in range 0.1-0.2 mm), and a small concentration of graupel (around 0.3 mm) near the melting layer. The raindrop size distribution shows the bimodal distribution with overestimation at 4 km. However, at the surface level, the large (〉2 mm) drops are underestimated and smaller (〈2mm) drops are overestimated. The variation in snow mass spectra and resultant changes in graupel contributes to modification in rainfall.