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- Author or Editor: George Kallos x
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Abstract
During the past 20 years, organized experimental campaigns as well as continuous development and implementation of air-pollution modeling have led to significant gains in the understanding of the paths and scales of pollutant transport and transformation in the greater Mediterranean region (GMR). The work presented in this paper has two major objectives: 1) to summarize the existing knowledge on the transport paths of particulate matter (PM) in the GMR and 2) to illustrate some new findings related to the transport and transformation properties of PM in the GMR. Findings from previous studies indicate that anthropogenically produced air pollutants from European sources can be transported over long distances, reaching Africa, the Atlantic Ocean, and North America. The PM of natural origin, like Saharan dust, can be transported toward the Atlantic Ocean and North America mostly during the warm period of the year. Recent model simulations and studies in the area indicate that specific long-range transport patterns of aerosols, such as the transport from Asia and the Indian Ocean, central Africa, or America, have negligible or at best limited contribution to air-quality degradation in the GMR when compared with the other sources. Also, new findings from this work suggest that the imposed European Union limits on PM cannot be applicable for southern Europe unless the origin (natural or anthropogenic) of the PM is taken into account. The impacts of high PM levels in the GMR are not limited only to air quality, but also include serious implications for the water budget and the regional climate. These are issues that require extensive investigation because the processes involved are complex, and further model development is needed to include the relevant physicochemical processes properly.
Abstract
During the past 20 years, organized experimental campaigns as well as continuous development and implementation of air-pollution modeling have led to significant gains in the understanding of the paths and scales of pollutant transport and transformation in the greater Mediterranean region (GMR). The work presented in this paper has two major objectives: 1) to summarize the existing knowledge on the transport paths of particulate matter (PM) in the GMR and 2) to illustrate some new findings related to the transport and transformation properties of PM in the GMR. Findings from previous studies indicate that anthropogenically produced air pollutants from European sources can be transported over long distances, reaching Africa, the Atlantic Ocean, and North America. The PM of natural origin, like Saharan dust, can be transported toward the Atlantic Ocean and North America mostly during the warm period of the year. Recent model simulations and studies in the area indicate that specific long-range transport patterns of aerosols, such as the transport from Asia and the Indian Ocean, central Africa, or America, have negligible or at best limited contribution to air-quality degradation in the GMR when compared with the other sources. Also, new findings from this work suggest that the imposed European Union limits on PM cannot be applicable for southern Europe unless the origin (natural or anthropogenic) of the PM is taken into account. The impacts of high PM levels in the GMR are not limited only to air quality, but also include serious implications for the water budget and the regional climate. These are issues that require extensive investigation because the processes involved are complex, and further model development is needed to include the relevant physicochemical processes properly.
Abstract
In this study, the authors investigate the use of high-resolution simulations from the Weather Research and Forecasting Model (WRF) for evaluating satellite rainfall biases of flood-inducing storms in mountainous areas. A probability matching approach is applied to evaluate a power-law relationship between satellite-retrieved and WRF-simulated rain rates over the storm domain. Satellite rainfall in this study is from the NOAA Climate Prediction Center morphing technique (CMORPH). Results are presented based on analyses of five heavy precipitation events that induced flash floods in northern Italy and southern France complex terrain basins. The WRF-based adjusted CMORPH rain rates exhibited improved error statistics against independent radar rainfall estimates. The authors show that the adjustment procedure reduces the underestimation of high rain rates, thus moderating the magnitude dependence of CMORPH rainfall bias. The Heidke skill score for the WRF-based adjusted CMORPH was consistently higher for a range of rain rate thresholds. This is an indication that the adjustment procedure ameliorates the satellite rain rates to provide a better estimation. Results also indicate that the low rain detection of CMORPH technique is also identifiable in the WRF–CMORPH comparison; however, the adjustment procedure herein does not incorporate this effect on the satellite rainfall bias adjustment.
Abstract
In this study, the authors investigate the use of high-resolution simulations from the Weather Research and Forecasting Model (WRF) for evaluating satellite rainfall biases of flood-inducing storms in mountainous areas. A probability matching approach is applied to evaluate a power-law relationship between satellite-retrieved and WRF-simulated rain rates over the storm domain. Satellite rainfall in this study is from the NOAA Climate Prediction Center morphing technique (CMORPH). Results are presented based on analyses of five heavy precipitation events that induced flash floods in northern Italy and southern France complex terrain basins. The WRF-based adjusted CMORPH rain rates exhibited improved error statistics against independent radar rainfall estimates. The authors show that the adjustment procedure reduces the underestimation of high rain rates, thus moderating the magnitude dependence of CMORPH rainfall bias. The Heidke skill score for the WRF-based adjusted CMORPH was consistently higher for a range of rain rate thresholds. This is an indication that the adjustment procedure ameliorates the satellite rain rates to provide a better estimation. Results also indicate that the low rain detection of CMORPH technique is also identifiable in the WRF–CMORPH comparison; however, the adjustment procedure herein does not incorporate this effect on the satellite rainfall bias adjustment.
Abstract
Of the boundary conditions that affect the simulation of convective precipitation, soil moisture is one of the most important. In this study, we explore the impact of the soil moisture on convective precipitation, and factors affecting it, through an extensive numerical experiment based on four convective precipitation events that caused moderate to severe flooding in the Gard region of southern France. High-spatial-resolution (1 km) weather simulations were performed using the integrated atmospheric model Regional Atmospheric Modeling System/Integrated Community Limited Area Modeling System (RAMS/ICLAMS). The experimental framework included comparative analysis of five simulation scenarios for each event, in which we varied the magnitude and spatial distribution of the initial volumetric water content using realistic soil moisture fields with different spatial resolution. We used precipitation and surface soil moisture from radar and satellite sensors as references for the comparison of the sensitivity tests. Our results elucidate the complexity of the relationship between soil moisture and convective precipitation, showing that the control of soil water content on partitioning land surface heat fluxes has significant impacts on convective precipitation. Additionally, it is shown how different soil moisture conditions affect the modeled microphysical structure of the clouds, which translates into further changes in the magnitude and distribution of precipitation.
Abstract
Of the boundary conditions that affect the simulation of convective precipitation, soil moisture is one of the most important. In this study, we explore the impact of the soil moisture on convective precipitation, and factors affecting it, through an extensive numerical experiment based on four convective precipitation events that caused moderate to severe flooding in the Gard region of southern France. High-spatial-resolution (1 km) weather simulations were performed using the integrated atmospheric model Regional Atmospheric Modeling System/Integrated Community Limited Area Modeling System (RAMS/ICLAMS). The experimental framework included comparative analysis of five simulation scenarios for each event, in which we varied the magnitude and spatial distribution of the initial volumetric water content using realistic soil moisture fields with different spatial resolution. We used precipitation and surface soil moisture from radar and satellite sensors as references for the comparison of the sensitivity tests. Our results elucidate the complexity of the relationship between soil moisture and convective precipitation, showing that the control of soil water content on partitioning land surface heat fluxes has significant impacts on convective precipitation. Additionally, it is shown how different soil moisture conditions affect the modeled microphysical structure of the clouds, which translates into further changes in the magnitude and distribution of precipitation.
Abstract
Flash floods develop over small spatiotemporal scales, an attribute that makes their predictability a particularly challenging task. The serious threat they pose for human lives, along with damage estimates that can exceed one billion U.S. dollars in some cases, urge toward more accurate forecasting. Recent advances in computational science combined with state-of-the-art atmospheric models allow atmospheric simulations at very fine (i.e., subkilometer) grid scales, an element that is deemed important for capturing the initiation and evolution of flash flood–triggering storms. This work provides some evidence on the relative gain that can be expected from the adoption of such subkilometer model grids. A necessary insight into the complex processes of these severe incidents is provided through the simulation of three flood-inducing heavy precipitation events in the Alps for a range of model grid scales (0.25, 1, and 4 km) with the Regional Atmospheric Modeling System–Integrated Community Limited Area Modeling System (RAMS–ICLAMS) atmospheric model. A distributed hydrologic model [Kinematic Local Excess Model (KLEM)] is forced with the various atmospheric simulation outputs to further evaluate the relative impact of atmospheric model resolution on the hydrologic prediction. The use of a finer grid is beneficial in most cases, yet there are events where the improvement is marginal. This underlines why the use of finer scales is a step in the right direction but not a solitary component of a successful flash flood–forecasting recipe.
Abstract
Flash floods develop over small spatiotemporal scales, an attribute that makes their predictability a particularly challenging task. The serious threat they pose for human lives, along with damage estimates that can exceed one billion U.S. dollars in some cases, urge toward more accurate forecasting. Recent advances in computational science combined with state-of-the-art atmospheric models allow atmospheric simulations at very fine (i.e., subkilometer) grid scales, an element that is deemed important for capturing the initiation and evolution of flash flood–triggering storms. This work provides some evidence on the relative gain that can be expected from the adoption of such subkilometer model grids. A necessary insight into the complex processes of these severe incidents is provided through the simulation of three flood-inducing heavy precipitation events in the Alps for a range of model grid scales (0.25, 1, and 4 km) with the Regional Atmospheric Modeling System–Integrated Community Limited Area Modeling System (RAMS–ICLAMS) atmospheric model. A distributed hydrologic model [Kinematic Local Excess Model (KLEM)] is forced with the various atmospheric simulation outputs to further evaluate the relative impact of atmospheric model resolution on the hydrologic prediction. The use of a finer grid is beneficial in most cases, yet there are events where the improvement is marginal. This underlines why the use of finer scales is a step in the right direction but not a solitary component of a successful flash flood–forecasting recipe.
Abstract
The weather and climate greatly affect socioeconomic activities on multiple temporal and spatial scales. From a climate perspective, atmospheric and ocean characteristics have determined the life, evolution, and prosperity of humans and other species in different areas of the world. On smaller scales, the atmospheric and sea conditions affect various sectors such as civil protection, food security, communications, transportation, and insurance. It becomes evident that weather and ocean forecasting is high-value information highlighting the need for state-of-the-art forecasting systems to be adopted. This importance has been acknowledged by the authorities of Saudi Arabia entrusting the National Center for Meteorology (NCM) to provide high-quality weather and climate analytics. This led to the development of a numerical weather prediction (NWP) system. The new system includes weather, wave, and ocean circulation components and has been operational since 2020 enhancing the national capabilities in NWP. Within this article, a description of the system and its performance is discussed alongside future goals.
Abstract
The weather and climate greatly affect socioeconomic activities on multiple temporal and spatial scales. From a climate perspective, atmospheric and ocean characteristics have determined the life, evolution, and prosperity of humans and other species in different areas of the world. On smaller scales, the atmospheric and sea conditions affect various sectors such as civil protection, food security, communications, transportation, and insurance. It becomes evident that weather and ocean forecasting is high-value information highlighting the need for state-of-the-art forecasting systems to be adopted. This importance has been acknowledged by the authorities of Saudi Arabia entrusting the National Center for Meteorology (NCM) to provide high-quality weather and climate analytics. This led to the development of a numerical weather prediction (NWP) system. The new system includes weather, wave, and ocean circulation components and has been operational since 2020 enhancing the national capabilities in NWP. Within this article, a description of the system and its performance is discussed alongside future goals.
In this paper, the performance of two commonly used regional-scale Eulerian photochemical modeling systems, namely, RAMS/UAM-V and MM5/SAQM, from the regulatory or operational perspective, is examined. While the Urban Airshed Model with Variable Grid (UAM-V) is driven with the meteorological fields derived from the Regional Atmospheric Model System (RAMS), the San Joaquin Valley Air Quality Model (SAQM) used the meteorological fields derived from the Pennsylvania State University–National Center for Atmospheric Research Mesoscale Model Version 5 (MM5). The model's performance in reproducing the observed ozone air quality over the eastern United States is evaluated for three typical high-ozone episodic events that occurred during 16–20 June, 12–16 July, and 30 July–2 August of 1995. The prevailing meteorological conditions associated with these three episodes are characterized by a slow eastward-moving high pressure system, westerly and southwesterly low-level jets, stable boundary layers, and the Appalachian lee-side trough. The results suggest that the performance of RAMS/UAM-V and MM5/SAQM systems in reproducing the observed ozone concentrations is comparable when model outputs are averaged over all simulated days. For different emissions reduction (i.e., volatile organic compound and nitrogen oxide controls) options, the response of both modeling systems, in terms of changes in ozone levels, was directionally similar, but the magnitude of ozone improvement differed from individual episode days at individual grid cells.
In this paper, the performance of two commonly used regional-scale Eulerian photochemical modeling systems, namely, RAMS/UAM-V and MM5/SAQM, from the regulatory or operational perspective, is examined. While the Urban Airshed Model with Variable Grid (UAM-V) is driven with the meteorological fields derived from the Regional Atmospheric Model System (RAMS), the San Joaquin Valley Air Quality Model (SAQM) used the meteorological fields derived from the Pennsylvania State University–National Center for Atmospheric Research Mesoscale Model Version 5 (MM5). The model's performance in reproducing the observed ozone air quality over the eastern United States is evaluated for three typical high-ozone episodic events that occurred during 16–20 June, 12–16 July, and 30 July–2 August of 1995. The prevailing meteorological conditions associated with these three episodes are characterized by a slow eastward-moving high pressure system, westerly and southwesterly low-level jets, stable boundary layers, and the Appalachian lee-side trough. The results suggest that the performance of RAMS/UAM-V and MM5/SAQM systems in reproducing the observed ozone concentrations is comparable when model outputs are averaged over all simulated days. For different emissions reduction (i.e., volatile organic compound and nitrogen oxide controls) options, the response of both modeling systems, in terms of changes in ozone levels, was directionally similar, but the magnitude of ozone improvement differed from individual episode days at individual grid cells.
