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Mrinal K. Biswas, Jun A. Zhang, Evelyn Grell, Evan Kalina, Kathryn Newman, Ligia Bernardet, Laurie Carson, James Frimel, and Georg Grell


The Developmental Testbed Center (DTC) tested two convective parameterization schemes in the Hurricane Weather Research and Forecasting (HWRF) Model and compared them in terms of performance of forecasting tropical cyclones (TCs). Several TC forecasts were conducted with the scale-aware Simplified Arakawa Schubert (SAS) and Grell–Freitas (GF) convective schemes over the Atlantic basin. For this sample of over 100 cases, the storm track and intensity forecasts were superior for the GF scheme compared to SAS. A case study showed improved storm structure for GF when compared with radar observations. The GF run had increased inflow in the boundary layer, which resulted in higher angular momentum. An angular momentum budget analysis shows that the difference in the contribution of the eddy transport to the total angular momentum tendency is small between the two forecasts. The main difference is in the mean transport term, especially in the boundary layer. The temperature tendencies indicate higher contribution from the microphysics and cumulus heating above the boundary layer in the GF run. A temperature budget analysis indicated that both the temperature advection and diabatic heating were the dominant terms and they were larger near the storm center in the GF run than in the SAS run. The above results support the superior performance of the GF scheme for TC intensity forecast.

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Prakash Pithani, Sachin D. Ghude, R. K. Jenamani, Mrinal Biswas, C. V. Naidu, Sreyashi Debnath, Rachana Kulkarni, Narendra G. Dhangar, Chinmay Jena, Anupam Hazra, R. Phani, P. Mukhopadhyay, Thara Prabhakaran, Ravi S. Nanjundiah, and M. Rajeevan


A Winter Fog Experiment (WiFEX) was conducted to study the genesis of fog formation between winters 2016–17 and 2017–18 at Indira Gandhi International Airport (IGIA), Delhi, India. To support the WiFEX field campaign, the Weather Research and Forecasting (WRF) Model was used to produce real-time forecasts at 2-km horizontal grid spacing. This paper summarizes the performance of the model forecasts for 43 very dense fog episodes (visibility < 200 m) and preliminary evaluation of the model against the observations. Similarly, near-surface liquid water content (LWC) from models and continuous visibility observations are used as a metric for model evaluation. Results show that the skill score is relatively promising for the hit rate with a value of 0.78, whereas the false alarm rate (0.19) and missing rate (0.32) are quite low. This indicates that the model has reasonable predictive accuracy, and the performance of the real-time forecast is better for both dense fog events and no-fog events. For success cases, the model accurately captured the near-surface meteorological conditions, particularly the low-level moisture, wind fields, and temperature inversion. In contrast, for failed cases, the WRF Model shows large error in near-surface relative humidity and temperature compared to the observations, although it captures temperature inversions reasonably well. Our results also suggest that the model is able to capture the variability in fog onset for consecutive fog events. Errors in near-surface variables during failed cases are found to be affected by the errors in the initial conditions taken from the Indian Institute of Tropical Meteorology Global Forecasting System (IITM-GFS) spectral model forecast. Further evaluation of the operational forecasts for dense fog cases indicates that the error in predicting fog onset stage is relatively large (mean error of 4 h) compared to the dissipation stage.

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Syed Ismail, Richard A. Ferrare, Edward V. Browell, Gao Chen, Bruce Anderson, Susan A. Kooi, Anthony Notari, Carolyn F. Butler, Sharon Burton, Marta Fenn, Jason P. Dunion, Gerry Heymsfield, T. N. Krishnamurti, and Mrinal K. Biswas


The Lidar Atmospheric Sensing Experiment (LASE) on board the NASA DC-8 measured high-resolution profiles of water vapor and aerosols, and cloud distributions in 14 flights over the eastern North Atlantic during the NASA African Monsoon Multidisciplinary Analyses (NAMMA) field experiment. These measurements were used to study African easterly waves (AEWs), tropical cyclones (TCs), and the Saharan air layer (SAL). These LASE measurements represent the first simultaneous water vapor and aerosol lidar measurements to study the SAL and its interactions with AEWs and TCs. Three case studies were selected for detailed analysis: (i) a stratified SAL, with fine structure and layering (unlike a well-mixed SAL), (ii) a SAL with high relative humidity (RH), and (iii) an AEW surrounded by SAL dry air intrusions. Profile measurements of aerosol scattering ratios, aerosol extinction coefficients, aerosol optical thickness, water vapor mixing ratios, RH, and temperature are presented to illustrate their characteristics in the SAL, convection, and clear air regions. LASE extinction-to-backscatter ratios for the dust layers varied from 35 ± 5 to 45 ± 5 sr, well within the range of values determined by other lidar systems. LASE aerosol extinction and water vapor profiles are validated by comparison with onboard in situ aerosol measurements and GPS dropsonde water vapor soundings, respectively. An analysis of LASE data suggests that the SAL suppresses low-altitude convection. Midlevel convection associated with the AEW and transport are likely responsible for high water vapor content observed in the southern regions of the SAL on 20 August 2008. This interaction is responsible for the transfer of about 7 × 1015 J (or 8 × 103 J m−2) latent heat energy within a day to the SAL. Initial modeling studies that used LASE water vapor profiles show sensitivity to and improvements in model forecasts of an AEW.

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