Person: Turco, Marco
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Turco, Marco
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Universidad de Murcia. Departamento de Física
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- PublicationOpen AccessOn the spin-up period in WRF simulations over Europe: trade-offs between length and seasonality(Wiley / American Geophysical Union, 2020-02-20) Jerez Rodríguez, Sonia; López Romero, José María; Turco, Marco; Lorente Plazas, Raquel; Gómez Navarro, Juan José; Jiménez Guerrero, Pedro; Montávez, Juan Pedro; Física; Facultades de la UMU::Facultad de Química; Facultades de la UMU::Facultad de BiologíaRegional climate models (RCMs) are usually initialized and driven through the boundaries of their limited area domain by data provided by global models (GCMs). The mismatch between the low-resolution GCM initial conditions and RCM’s high resolution introduces physical inconsistencies between the various components of the RCM. These inconsistencies can be resolved by running the RCM during a period that is considered unreliable: the spin-up period. There is no deterministic definition of the length that the spin-up period should have. Here we try to provide general guidelines that can be used to the advantage of the community. We base our analysis on Weather Research and Forecasting (WRF) simulations over a Euro-Cordex compliant domain and find that for 2-m temperature and precipitation, rather short spin-up periods (1 week) can be sufficient. Nevertheless, longer periods (6 months) are advisable, and start dates in non-winter months should be pursued, as this ensures a more realistic representation of the snow cover. Thus, the issue is not only about the spin-up length. As the soil subsystem evolves slowly and requires longer periods to reach equilibrium than the longest considered here (1 year), seasonality plays an important role in minimizing the impact of the unreliability of the soil initialization. Fortunately, except for goals where the deep soil-atmosphere feedbacks are critical, the lack of equilibrium between them can be ignored, as it seems to have little effect on the simulation of the atmospheric variables most frequently used in RCM studies.
- PublicationOpen AccessPopulation exposure to particulate-matter and related mortality due to the Portuguese wildfires in October 2017 driven by storm Ophelia(Elsevier, 2020-08-28) Augusto, Sofia; Ratola, Nuno; Tarín Carrasco, Patricia; Jiménez Guerrero, Pedro; Turco, Marco; Schuhmacher, Marta; Costa, Solange; Teixeira, J. P.; Costa, Carla; FísicaIn October 2017, hundreds of wildfires ravaged the forests of the north and centre of Portugal. The fires were fanned by strong winds as tropical storm Ophelia swept the Iberian coast, dragging up smoke (together with Saharan dust from north-western Africa) into higher western European latitudes. Here we analyse the long-range transport of particulate matter (PM10) and study associations between PM10 and short-term mortality in the Portuguese population exposed to PM10 due to the October 2017 wildfires, the worst fire sequence in the country over the last decades. We analysed space- and ground-level observations to track the smoke plume and dust trajectory over Portugal and Europe, and to access PM10 concentrations during the wildfires. The effects of PM10 on mortality were evaluated using satellite data for exposure and Poisson regression models. The smoke plume covered most western European countries (including Spain, France, Belgium and the Netherlands), and reached the United Kingdom, where the population was exposed in average to an additional PM10 level of 11.7 µg/m3 during seven smoky days (three with dust) in relation to the reference days (days without smoke or dust), revealing the impact of the wildfires on distant populations. In Portugal, the population was exposed in average to additional PM10 levels that varied from 16.2 to 120.6 µg/m3 in smoky days with dust and from 6.1 to 20.9 µg/m3 in dust-free smoky days. Results suggest that PM10 had a significant effect on the same day natural and cardiorespiratory mortalities during the month of October 2017. For every additional 10 µg/m3 of PM10, there was a 0.89% (95% confidence interval, CI, 0–1.77%) increase in the number of natural deaths and a 2.34% (95% CI, 0.99–3.66%) increase in the number of cardiorespiratory-related deaths. With rising temperatures and a higher frequency of storms due to climate change, PM from Iberian wildfires together with NW African dust will tend to be more often transported into Northern European countries, which may carry health threats to areas far from the ignition sites.
- PublicationOpen AccessA global probabilistic dataset for monitoring meteorological droughts(American Meteorological Society, 2020-10-09) Jerez Rodríguez, Sonia; Turco, Marco; Donat, Markus G.; Toreti, Andrea; Vicente-Serrano, Sergio M.; Doblas-Reyes, Francisco J.; FísicaAccurate and timely drought information is essential to move from postcrisis to preimpact drought-risk management. A number of drought datasets are already available. They cover the last three decades and provide data in near–real time (using different sources), but they are all “deterministic” (i.e., single realization), and input and output data partly differ between them. Here we first evaluate the quality of long-term and continuous climate data for timely meteorological drought monitoring considering the standardized precipitation index. Then, by applying an ensemble approach, mimicking weather/climate prediction studies, we develop Drought Probabilistic (DROP), a new global land gridded dataset, in which an ensemble of observation-based datasets is used to obtain the best near-real-time estimate together with its associated uncertainty. This approach makes the most of the available information and brings it to the end users. The highquality and probabilistic information provided by DROP is useful for monitoring applications, and may help to develop global policy decisions on adaptation priorities in alleviating drought impacts, especially in countries where meteorological monitoring is still challenging
- PublicationOpen AccessAn action-oriented approach to make the most of the wind and solar power complementarity(Wiley, American Geophysical Union, 2023-06-08) Jerez Rodríguez, Sonia; Barriopedro, David; López García, Alejandro; Lorente-Plazas, Raquel; Somoza Gimeno, Andrés Manuel; Turco, Marco; Carrillo, Judit; Trigo, Ricardo M.; FísicaSolar and wind power are called to play a main role in the transition toward decarbonized electricity systems. However, their integration in the energy mix is highly compromised due to the intermittency of their production caused by weather and climate variability. To face the challenge, here we present research about actionable strategies for wind and solar photovoltaic facilities deployment that exploit their complementarity in order to minimize the volatility of their combined production while guaranteeing a certain supply. The developed methodology has been implemented in an open-access step-wise model called CLIMAX. It first identifies regions with homogeneous temporal variability of the resources, and then determines the optimal shares of each technology over such regions. In the simplistic application performed here, we customize the model to narrow the monthly deviations of the total wind-plus-solar electricity production from a given curve (here, the mean annual cycle of the total production) across five European domains. For the current shares of both technologies, the results show that an optimal siting of the power units would reduce the standard deviation of the monthly anomalies of the total wind-plus-solar power generation by up to 20% without loss in the mean capacity factor as compared to a baseline scenario with an evenly spatial distribution of the installations. This result further improves (up to 60% in specific regions) if the total shares of each technology are also optimized, thus encouraging the use of CLIMAX for practical guidance of next-generation renewable energy scenarios.
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