Theodore M. Giannaros

WRF-LTNGDA

This study introduces WRF-LTNGDA, a lightning data assimilation technique implemented in the Weather Research and Forecasting (WRF) model. This technique employs lightning for improving the representation of convection by means of controlling the triggering of the models convection parameterization scheme. The development and implementation of WRF-LTNGDA was carried out in a framework that could easily allow for its exploitation in real-time forecasting activities. The assimilation algorithm was evaluated over eight precipitation events that took place in Greece in the years 2010-2013. Results clearly show that lightning forcing has a positive impact on model performance. The conducted analysis revealed that the employment of WRF-LTNGDA induces statistically significant improvements in precipitation verification scores, especially for high rainfall accumulations. Separate examination of one of the eight case studies highlighted the overall better agreement between the modelled and observed spatial distribution of precipitation when lightning data assimilation was applied, than in the control simulation. WRF-LTNGDA: a lightning data assimilation technique for the WRF model.WRF-LTNGDA is evaluated over eight case studies in Greece.Lightning assimilation improves precipitation prediction.WRF-LTNGDA can be used for real-time weather forecasting applications.

Evaluation of thermal bioclimate based on observational data and numerical simulations: an application to Greece

The evaluation of thermal bioclimate can be conducted employing either observational or modeling techniques. The advantage of the numerical modeling approach lies in that it can be applied in areas where there is lack of observational data, providing a detailed insight on the prevailing thermal bioclimatic conditions. However, this approach should be exploited carefully since model simulations can be frequently biased. The aim of this paper is to examine the suitability of a mesoscale atmospheric model in terms of evaluating thermal bioclimate. For this, the numerical weather prediction Weather Research and Forecasting (WRF) model and the radiation RayMan model are employed for simulating thermal bioclimatic conditions in Greece during a 1-year time period. The physiologically equivalent temperature (PET) is selected as an index for evaluating thermal bioclimate, while synoptic weather station data are exploited for verifying model performance. The results of the present study shed light on the strengths and weaknesses of the numerical modeling approach. Overall, it is shown that model simulations can provide a useful alternative tool for studying thermal bioclimate. Specifically for Greece, the WRF/RayMan modeling system was found to perform adequately well in reproducing the spatial and temporal variations of PET.

Operational forecasting of human-biometeorological conditions

This paper presents the development of an operational forecasting service focusing on human-biometeorological conditions. The service is based on the coupling of numerical weather prediction models with an advanced human-biometeorological model. Human thermal perception and stress forecasts are issued on a daily basis for Greece, in both point and gridded format. A user-friendly presentation approach is adopted for communicating the forecasts to the public via the worldwide web. The development of the presented service highlights the feasibility of replacing standard meteorological parameters and/or indices used in operational weather forecasting activities for assessing the thermal environment. This is of particular significance for providing effective, human-biometeorology-oriented, warnings for both heat waves and cold outbreaks.

Study of the impact of natural sources on the air quality – Evaluation of a natural emissions model

A Natural Emissions MOdel (NEMO) driven by the meteorology of the Weather Research and Forecasting (WRF) model has been used in order to estimate particle emissions from windblown dust, sea salt and primary biological aerosol particles (PBAPs) as well as Biogenic Volatile Organic Compounds (BVOCs) emissions from vegetation. NEMO is applied on a 30km spatial resolution grid, which covers Europe for the year 2009. NEMO emissions results of dust, sea salt and BVOCs were incorporated in a photochemical modelling system consisted of the WRF model and the Comprehensive Air Quality model with extensions (CAMx). Anthropogenic emissions data have been taken by the Netherlands Organization (TNO). The modelling system is implemented for different emission scenarios, which concern the exclusion of natural sources in the simulations in order to study their impact on the European air quality. A model evaluation indicated a good model performance.