DoGMA: Evaluating Dust forecasting over the eastern Mediterranean Area
The EUFAR DOGMA project aimed to investigate the properties of dust clouds in the Mediterranean region using airborne in-situ measurements on board the DLR Falcon aircraft.
Dust is the most abundant aerosol at the greater Mediterranean region. Apart from the air quality implications, dust is also a significant climate and weather
modulator. Dust aerosols are very efficient ice nuclei (IN), and they play an important role in heterogeneous cloud glaciation. Introducing a dust based ice
nucleation parameterization in NMM-DREAM model allows the calculation of dust IN activation and the related impacts in cloud properties. However, in order to
properly assess the modification of cloud properties due to dust contamination one should first evaluate the model performance with regards to the basic
parameters that participate in these processes.
The main objectives of this project are to
1. Measure temperature and humidity profiles inside the elevated dust layers
2. Examine the concentration of airborne dust particles and their size distribution (fine to coarse ratio) over the greater E Mediterranean region.
3. Assess the accuracy of dust concentration forecasting in NMM-DREAM and investigate the ice glaciation capabilities of the model.
The methodology proposed to carry out the experiment is mainly based on observations of Saharan mineral dust plumes. During spring, these plumes are usually
accompanied by cloud formations often leading to stormy weather and severe precipitations including wet deposition of dust. These clouds are affected by dust
and their properties are altered depending on dust concentration and sizes. Aircraft measurements of the meteorological and aerosol parameters inside the dust
layers will be used to evaluate the performance of NMM-DREAM forecast fields. Model interpretation and assessment of the simulations will be performed
together with space-borne and aircraft lidar profiles, ground photometers and ground chemical/size characterization of dust.
The anticipated outputs from this work include the improvement of our knowledge on dust processes and the validation of dust modeling results that will increase
our confident on these products over this particular area.