ANNOUNCEMENTS
Fog over the Indian sub-continent, especially over the Indo-Gangetic Plains has immense interannual variability, which has enormous repercussions on daily life with considerable economic losses during the apex winter season. The preeminent objectives of the present research have been (i )To analyze the spatial and temporal variability of winter fog over the Indo-Gangetic plains; (ii) To configure a potent mesoscale numerical weather prediction (WRF) model using diverse parameterization schemes for winter fog prediction over the Indo Gangetic plains and (iii) To develop a reliable forecasting model to forecast fog occurrence, its intensity and duration based on mesoscale Numerical weather prediction model (WRF) over the Indo Gangetic plains of India.
In the pilot study, long-term ground observations of visibility and other meteorological parameters (1971-2010) has been analyzed over Ghaziabad city, National Capital Region (NCR) to comprehend the formation of fog phenomenon and its pertinence during winter months. The study proclaims that the maximum fog occurs during December (~23 days) followed by January (~21 days).In the last four decades, growing trend in the fog frequency has been observed for the months from October to February over the study area. The statistically significant increasing trend in fog occurrence has been observed from October-to-February during the study period at 95% confidence level. Further, it has also been observed that the magnitude of the trend is highest in the month of October, whereas, the average monthly fog frequency is highest during the month of December. Further, an attempt has also been made to forecast fog events using ARIMA model over the study region. The forecast value fetched for the next five years indicates that the numbers of fog days are going to increase further during the months from October-to-February in the forthcoming years. The study combined with the knowledge of meteorology and topography recommends that due to increase in the availability of fine particulates and rapid urbanization, fog formation may further escalate in the future and thus drastically perplex the social and economic activities over Ghaziabad, National Capital Region of India.
The outcome of the pilot study was further unfolded using the long-term ground observations of visibility and other meteorological parameters (1971-2015) to comprehend the formation of fog phenomena and its relevance during the apex winter months of January and December over the Indo-Gangetic Plains (IGP) of India. In order to ponder temporal variability, time series and trend analysis were carried out using Mann-Kendall Statistical test. Trend analysis executed using the Mann Kendall test accepts the alternate hypothesis with 95% confidence level that there exists a trend. Kendall tau’s statistics showed that there exists a positive correlation between time series and fog frequency. Further, Theil and Sen’s median slope estimate exhibited that the magnitude of the trend is positive. Magnitude is higher during January compared to December for entire IGP except in December when it is high over western IGP.
Every year, visibility reduces in dense and widespread fog over the Indo-Gangetic plains of India during the peak winter month of December and January. It is observed that during the peak winter months of December and January, the average fog frequency over the central IGP (Uttar Pradesh) is 24.35 % more than the average fog frequency over the west IGP (Punjab, Haryana, and Delhi).The average fog frequency has increased by 118 percent in the last four and half decades during the months of December and January over the IGP. It is found that the average fog frequency has increased by 116 percent over the central IGP and 280 percent over the west IGP, in the last four and half decades during the months of December and January. These results would offer the new perspective to counter fog perils that could be caused due to changing trends of fog.
A potent mesoscale numerical weather prediction (WRF) model has been configured using diverse parameterization schemes for winter fog forecast over the Indo Gangetic plains. A sensitivity analysis of the WRF model was done to determine the most appropriate combination of physical parameterization scheme for the fog prediction over the Indo-Gangetic plains. Principal component analysis of various meteorological parameters concludes that relative humidity, temperature, wind speed and sky state are the most benevolent variables for fog formations over IGP. The most appropriate combination of physical parameterization scheme over the Indo-Gangetic plains for meteorological elements favorable for fog includes - Micro-physics: WSM-6, Surface Layer: Monin- Obukhov (Janjic) Shine, Land surface: Unified NOAH land surface model, PBL: Mellor-Yamada-Janjic TKE scheme (MYJ) and CU Parameterization: GRELL Devenyi ensemble.
The study proffers a new FASF (Fog Analysis, Sensitivity, and Forecast) Model for comprehensive analysis, sensitivity, and forecast of fog events over a specified region in the Indo-Gangetic plains. In the first phase of this model long-term climatological fog data over many locations have been analyzed to adjudicate its characteristics and prevalent trend using various avant-garde statistical techniques. The analysis deliberation proclaimed that an alarming positive trend of fog frequency prevails over many locations of IGP. Hotspot and cluster analysis was conducted to identify the high fog prone zones using GIS and inferential statistical tools respectively. Hot spots on an average experience fog on 68.27% days during the peak winter months of December and January, it is followed by moderate and cold spots with 48.03% and 21.79% respectively. Similarly, central IGP experiences fog about 66.29% days, it is followed western IGP and Eastern IGP by with 41.94% and 33.06% respectively. During a second phase a sensitivity evaluation is conducted with different combination of parameterization schemes to determine the most appropriate combination for fog simulation over six locations across IGP and in the third and final phase, first the ARIMA model is used to prognosticate the number of fog days during the peak winter months of December and January in future . Thereafter, the Numerical model is used to predict the various meteorological parameters benevolent for fog forecast. Finally, the Hybrid model is developed and used for fog forecast over the study location. The outcome of the FASF model is validated with actual ground-based fog data using statistical techniques. Forecast Fog-gram generated using hybrid model shows remarkably encouraging results for fog occurrence/Nonoccurrence forecast. The enhanced accuracy in fog prediction using FASF model would offer a new perspective to take proactive measures in reducing the irreparable devastation that could be caused due to this hazardous fog events over the most productive and populated region of the Indian sub-continent. It is found that the forecast of fog occurrence and minimum visibility of the day using FASF model over the Indo-Gangetic plains are in reasonable agreement with those of actual observation. Therefore, the FASF model developed in the present study is quite useful to forecast fog over the Indo-Gangetic plains of India.
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