Development of intensity based fog climatological information system (daily and hourly) at IGI airport, New Delhi for use in fog forecasting and aviation

The main objective of the present paper is to make a microclimatological study of occurrence of fog of different intensities at Indira Gandhi International (IGI) airport, New Delhi which includes their date-wise climatological probabilities and their corresponding total number of hours of occurrence for 62-days of peak winter from 1st December to 31st January by using hourly visibility data for the period of 1981-2005. Their hourly climatology has been discussed separately for both months using same data for understanding their diurnal variations. Both the computations have been done to find most vulnerable periods with exact dates and timings when both duration and intensity of the fog are very high and hazardous for aviation. Corresponding 10-days and 3-hourly climatology of cumulative fog occurrences are computed to identify a period when fog related flight diversion risk is highest. For better understanding of their variability, dates of extreme hours of occurrences of a particular fog type amongst occurrences of all dates for the period during both months have also been documented. These climatological informations can be used by various airlines for planning flight operation and action for establishment of fog dissipation mechanism. Finally, fogprobability matrices of various intensities based on these climatological data have been presented with dates in first column and hours in the first row for all 62 days of December and January and for all 24 hours of each day giving date and hour wise climatological probability of their occurrences which can be used at IGI as climatological tool for forecasting of fog of various intensity and expected climatological period.

Micro-climatic study and trend analysis of fog characteristics at IGI airport New Delhi using hourly data (1981-2005)

Indira Gandhi International (IGI) airport, New Delhi where near about 675 flights on an averagedepart and arrive daily, is highly susceptible to dense fog occurrences during the winter season. In the present paper, anattempt has been made for development of an intensity based fog climatological information system for December andJanuary based on hourly visibility data of 25-years (1981-2005) recorded at IGI airport. Variations and trends if any werealso analyzed along with their extreme years and dates of occurrences. Data since 1964 were also used to find climaticjumps in the trend which includes various higher visibilities of no fog conditions. Besides various vital fog climatologicalinformation generated through the present study for use in aviation, the most important finding is the alarming increasingtrend of the dense fog (< 200m) occurrences in both the months up to as high as 10-20 times from 1960s in contrast tounusual drastic reduction of higher visibility hours to as low as one thirtieth to one fiftieth of hours which were observedin 1960s. Thus, finally making IGI airport, a unique airport in the world which hardly experiences good visibilityconditions (>5000m) in both the months. By considering the unexpected huge annual growth of 30% in both air trafficand passengers that India including IGI has presently been experiencing against the global average of 6%, such visibilitytrend also confirms that present flight disruptions and passengers sufferings in winter will be aggravated more severely indays to come unless CAT-III ILS implemented fully. Finally, we have computed further number of consecutive hours,spell periodicity, most favorable climatological timing of fog onset and fog dispersal based on various intensities for usein aviation and fog forecasting.

Fog climatology and stability index for Plovdiv 1991-2018

&lt;p&gt;Despite the continuous improvement of weather prediction fog diagnosis and forecasting remains a challenge with large economic losses for public services and in particular aviation where the cost of flight delays and rescheduling is estimated to hundreds of million euros per year. Today the operational fog forecasting is mainly done with &quot;in-house&quot; developed tools, which is understandable due to the fog life cycle peculiarity. The aim of this work is to investigate the fog climatology for Plovdiv, Bulgaria for the period 1991 - 2018 and to use it for calculation a threshold value of stability index, which can be implemented as an operational forecast tool. The climatology shows well-defined seasonal behavior of the fog and that the majority of the fog registrations are with horizontal visibility below 200 m. A 10-year moving average of the fog registrations time series shows a decrease after 2012. Stability index values for various visibility ranges are calculated and compared. In the last decade, there are major improvements in horizontal and spatial resolution, microphysics, and initial conditions of the Numerical Weather Prediction models. &amp;#160;However, fog forecasting remains a challenge due to the small scale of the phenomena and local effects, which can remain unresolved by the models. One fog case in January 2013 is selected for numerical weather prediction simulations with the WRF model for the city of Plovdiv. The reliability of the index is evaluated both with observations and model data. It was found that while the index with its site-specific threshold value well describes the fog evolution, the WRF model has large deviations in temperature compared to the observations during daytime.&lt;/p&gt;

Fog forecasting for Schiphol airport at sub-kilometre scale.

&lt;p&gt;Fog is a critical weather phenomenon for safety and operations in aviation. Unfortunately, the forecasting of radiation fog remains challenging due to the numerous physical processes that play a role and their complex interactions, in addition to the vertical and horizontal resolution of the numerical models. In this study we evaluate the performance of the Weather Research and Forecasting (WRF) model for a radiation fog event at Schiphol Amsterdam Airport (The Netherlands) and further develop the model towards a 100 m grid spacing. Hence we introduce high resolution land use and land elevation data. In addition we study the role of gravitational droplet settling, advection of TKE, top-down diffusion caused by strong radiative cooling at the fog top. Finally the impact of heat released by the terminal areas on the fog formation is studied. The model outcomes are evaluated against 1-min weather observations near multiple runways at the airport.&lt;/p&gt;&lt;p&gt;Overall we find the WRF model shows an reasonable timing of the fog onset and is well able to reproduce the visibility and meteorological conditions as observed during the case study. The model appears to be relatively insensitive to the activation of the individual physical processes. An increased spatial resolution to 100 m generally results in a better timing of the fog onset differences up to three hours, though not for all runways. The effect of the refined landuse dominates over the effect of refined elevation data. The modelled fog dissipation systematically occurs 3-4 h hours too early, regardless of physical processes or spatial resolution. Finally, the introduction of heat from terminal buildings delays the fog onset with a maximum of two hours, an overestimated visibility of 100-200 m and a decrease of the LWC with 0.10-0.15 g/kg compared to the reference.&lt;/p&gt;

A Preliminary Impact Study of Wind on Assimilation and Forecast Systems into the One-Dimensional Fog Forecasting Model COBEL-ISBA over Morocco

The assimilation impact of wind data from aircraft measurements (AMDAR), surface synoptic observations (SYNOP) and 3D numerical weather prediction (NWP) mesoscale model, on short-range numerical weather forecasting (up to 12 h) and on the assimilation system, using the one-dimensional fog forecasting model COBEL-ISBA (Code de Brouillard à l’Échelle Locale-Interactions Soil Biosphere Atmosphere), is studied in the present work. The wind data are extracted at Nouasseur airport, Casablanca, Morocco, over a winter period from the national meteorological database. It is the first time that wind profiles (up to 1300 m) are assimilated in the framework of a single-column model. The impact is assessed by performing NWP experiments with data denial tests, configured to be close to the operational settings. The assimilation system estimates the flow-dependent background covariances for each run of the model and takes the cross-correlations between temperature, humidity and wind components into account. When assimilated into COBEL-ISBA with an hourly update cycle, the wind field has a positive impact on temperature and specific humidity analysis and forecasts accuracy. Thus, a superior fit of the analysis background fields to observations is found when assimilating AMDAR without NWP wind data. The latter has shown a detrimental impact in all experiments. Besides, wind assimilation gave a clear improvement to short-range forecasts of near-surface thermodynamical parameters. Although, assimilation of SYNOP and AMDAR wind measurements slightly improves the probability of detection of fog but also increases the false alarms ratio by a lower magnitude.

Assessing the Impact of Surface and Wind Profiler Data on Fog Forecasting Using WRF 3DVAR: An OSSE Study on a Dense Fog Event over North China

Because fog is a high-impact weather phenomenon, there has been increased demand for its accurate prediction. Both surface data and wind profiler data possess great potential for improved fog prediction. This study aimed to quantitatively assess the impact of surface and wind profiler data on fog prediction in terms of their spatial resolutions and distributions and also to assess the relative effect of these two types of observations. A dense fog event in northern China that occurred on 20 February 2007 was studied using the Weather Research and Forecasting (WRF) Model’s three-dimensional variational data assimilation (3DVAR) system with observing system simulation experiments (OSSE). The results indicated that the incorporation of surface data has an obvious positive impact on fog forecasts, especially with respect to effective assimilation of automated weather station data. Dense planetary boundary layer (PBL) wind profilers are more beneficial for fog forecasting than troposphere wind profilers, and an even spatial distribution over a large region is superior to a localized distribution. Surface data show greater benefit for fog forecasting than wind profiler data, with a 6.6% increase of skill score as a result of the improvement of near-surface thermal stratification. Moreover, combining both types of data greatly enhances fog predictive skill, with a 13.6% increase in skill score relative to the experiment assimilating only surface data, as a result of better dynamically balanced fields of thermodynamic and kinematic variables within the PBL with the assimilation of PBL wind profiler data.