Assessing the impact of observations on a local numerical fog prediction system

Abstract

ABSTRACT:As poor visibility conditions have great influence on air traffic, a need exists for accurate, updated fog and low-cloud forecasts. COBEL-ISBA, a boundary-layer one-dimensional numerical model, has been developed for the very short-term forecasting of fog and low clouds. This forecasting system assimilates the information from a local observation system designed to provide details on the state of the surface boundary layer, as well as that of the fog and low-cloud layers. This article aims to assess the influence of each component of the observation system on the initial conditions and lowvisibility forecasts. The objective is to obtain a quantitative assessment of the impact on numerical fog forecasts of using a reduced (for smaller-sized airports) or enhanced (using a sodar) set of observations. We first used simulated observations, and focused on modelling the atmosphere before fog formation and then on simulating the life-cycle of fog and low clouds. Within this framework, we also estimated the impact of using a sodar to estimate the thickness of the cloud layer. We showed that the radiative flux observations were the most important of all in cloudy conditions, and that the measurement mast did not have to be higher than 10 m. Using either a sodar or radiative flux to estimate the optical thickness of a cloud layer gave the same scores. Using both of them together did not significantly improve the forecast. Simulations with real observations over a winter of simulations confirmed these findings.

Adaptation of a particle filtering method for data assimilation in a 1D numerical model used for fog forecasting

“…The bias was also reduced in the lower part of the domain for temperature after 1 h of the forecast and for specific humidity over the whole domain after 1 h of the forecast. The smaller bias shows that the initialization of ISBA and the interface between COBEL and ISBA worked better with the new algorithm then with the operational set-up, since it was shown by previous studies (Rémy and Bergot, 2009) that a faulty initialization of ISBA is a cause of increasing forecast bias on temperature and specific humidity close to the ground. Figure 9 shows the RMSE of PART50 as a percentage of REF's RMSE for temperature and specific humidity, and also the bias difference between the two experiments for FOG.…”

“…Two sets of simulated observations were made: one for the study of clear-sky nights and of shallow-fog situations (NEAR-FOG), and the other for the study of frequent and deep fogs (FOG). (Rémy and Bergot, 2009, provide more details on how the simulated observations were generated. ).…”

“…Modelling the life cycle of fog involves interactions between many parametrizations: turbulence, microphysics, radiative scheme, and surface-atmosphere exchanges. This stresses the importance of working with accurate initial conditions; the quality of the COBEL-ISBA forecasts depends much on the initial conditions Roquelaure and Bergot, 2007;Rémy and Bergot, 2009). As fog modelling involves numerous threshold processes, the model is strongly nonlinear.…”

A Persistent Fog Event Involving Heavy Pollutants in Yancheng Area of Jiangsu Province

“…is is why accurate forecasts of fog and haze have become an important issue. e observation [6,7] and modelling [8,9] of dense fog have been studied in recent years. Several dynamic, thermal, and water vapor conditions including the layered structure of thermal inversion, the increase of temperature in the ground layer after sunrise, and the vertical transmission of heat, momentum, and water vapor caused by turbulent mixing have been found that trigger to dense fog [1,10,11].…”

Relationship between optical extinction and liquid water content in fogs

“…Observations are thus lacking for validating model simulations (Bergot, 2013). Real-time LWC observation could have a significant impact on fog predictions (Rémy and Bergot, 2009). In this work, the possibility of measuring the LWC with a lidar is based on the existence of a relationship between the LWC and the optical extinction in fogs.…”