<p>Sand and Dust Storms (SDS) are extreme meteorological phenomena that can be associated with high amounts of atmospheric mineral dust. SDS are an essential element of the Earth&#8217;s natural biogeochemical cycles but are also caused in part by human-induced drivers including climate change, unsustainable land management, and water use; in turn, SDS contribute to climate change and air pollution. Over the last few years, there has been an increasing need for SDS accurate information and predictions, particularly over desert regions as the Sahara and in the Middle East and regions affected by long-range dust transport as Europe, to support early warning systems, and preparedness and mitigation plans in addition to growing interest from diverse stakeholders in the aviation sector, including airlines, airports, engine manufacturers, as well as the military. SDS affect aviation operations mainly through reduced visibility and several types of mechanical effects that impact different parts of the aircraft (Clarkson and Simpson 2017); these have significant mid- to long-term implications for issues such as engine and aircraft maintenance, airport operations and resilience, and flight route planning and optimization.&#160;</p><p>In this contribution, we will present ongoing efforts on utilizing desert dust modelling products based on the MONARCH chemical weather prediction system and satellite observational constraint (P&#233;rez et al, 2011; Di Tomaso et al., 2017) as the basis to understand the short- and long-term risks of operating in risky sand and dust environments. We will introduce two types of examples of the use of SDS information. First, a long-term assessment for Northern Africa, the Middle East and Europe of the SDS-threats surrounding visibility and aircraft/engine exposure to dust, based on a 10-year MONARCH dust reanalysis in the context of the EU ERA4CS DustClim project. We will subsequently revise the benefits of using daily dust forecasts based on MONARCH (the reference operational model of the WMO Barcelona Dust Forecast Center, https://dust.aemet.es/) for the early prediction of extreme events as the ones occurred in March 2018 in the Eastern Mediterranean and in February 2020 in the Canary Islands.</p><p><strong>Acknowledgement </strong></p><p>The authors acknowledge the DustClim project which is part of ERA4CS, an ERA-NET. COST Action inDust (CA16202) and the WMO SDS-WAS Regional Center are also acknowledged. We are thankful to T. Bolic for her suggestions and ideas regarding resilience of the aviation sector to SDS.</p><p><strong>References </strong></p><p>Clarkson, R., and Simpson, H., 2017: Maximising Airspace Use During Volcanic Eruptions: Matching Engine Durability against Ash Cloud Occurrence, NATO STO AVT-272 Specialists Meeting on &#8220;Impact of Volcanic Ash Clouds on Military Operations&#8221; Volume: 1.</p><p>Di Tomaso et al., (2017): Assimilation of MODIS Dark Target and Deep Blue observations in the dust aerosol component of NMMB-MONARCH version 1.0, Geosci. Model Dev., 10, 1107-1129, doi:10.5194/gmd-10-1107-2017.</p><p>P&#233;rez et al.,: An online mineral dust aerosol model for meso to global scales: Model description, annual simulations and evaluation, Atmos. Chem. Phys., 11, 13001-13027, doi: 10.5194/acp-11-13001-2011, 2011.</p><p>Votsis et al., (2020), Operational risks of sand and dust storms in aviation and solar energy: the DustClim approach, FMI's Climate Bulletin: Research Letters 1/2020, DOI: 10.35614/ISSN-2341-6408-IK-2020-02-RL.</p>
Temporal analysis of Sand and Dust Storms (SDS) between the years 2003 and 2017 in the Central Asia
