scholarly journals Spatio-temporal modelling of lightning climatologies for complex terrain

2017 ◽  
Vol 17 (3) ◽  
pp. 305-314 ◽  
Author(s):  
Thorsten Simon ◽  
Nikolaus Umlauf ◽  
Achim Zeileis ◽  
Georg J. Mayr ◽  
Wolfgang Schulz ◽  
...  
Keyword(s):  
Complex Terrain ◽  
Generalized Additive Models ◽  
Weather Prediction ◽  
Geographical Location ◽  
Eastern Alps ◽  
Spatial Effect ◽  
Additive Models ◽  
Seasonal Effect ◽  
Altitude Effect ◽  
North West

Abstract. This study develops methods for estimating lightning climatologies on the day−1 km−2 scale for regions with complex terrain and applies them to summertime observations (2010–2015) of the lightning location system ALDIS in the Austrian state of Carinthia in the Eastern Alps. Generalized additive models (GAMs) are used to model both the probability of occurrence and the intensity of lightning. Additive effects are set up for altitude, day of the year (season) and geographical location (longitude/latitude). The performance of the models is verified by 6-fold cross-validation. The altitude effect of the occurrence model suggests higher probabilities of lightning for locations on higher elevations. The seasonal effect peaks in mid-July. The spatial effect models several local features, but there is a pronounced minimum in the north-west and a clear maximum in the eastern part of Carinthia. The estimated effects of the intensity model reveal similar features, though they are not equal. The main difference is that the spatial effect varies more strongly than the analogous effect of the occurrence model. A major asset of the introduced method is that the resulting climatological information varies smoothly over space, time and altitude. Thus, the climatology is capable of serving as a useful tool in quantitative applications, i.e. risk assessment and weather prediction.

scholarly journals Spatio-temporal smoothing of lightning climatologies

2016 ◽  
Author(s):  
Thorsten Simon ◽  
Nikolaus Umlauf ◽  
Achim Zeileis ◽  
Georg J. Mayr ◽  
Wolfgang Schulz ◽  
...  
Keyword(s):  
Generalized Additive Models ◽  
Weather Prediction ◽  
Geographical Location ◽  
Eastern Alps ◽  
Spatial Effect ◽  
Additive Models ◽  
Seasonal Effect ◽  
Altitude Effect ◽  
Temporal Smoothing ◽  
Spatio Temporal

Abstract. This study develops methods for estimating lightning climatologies on the d-1 km-2 scale for regions with complex terrain and applies them to summertime observations (2010–2015) of the lightning location system ALDIS in the Austrian state of Carinthia in the Eastern Alps. Generalized additive models (GAMs) are used to model both the probability of occurrence and the intensity of lightning. Additive effects are set up for altitude, day of the year (season) and geographical location (longitude/latitude). The performance of the models is verified by 6-fold cross-validation. The altitude effect of the occurrence model suggests higher probabilities of lightning for locations on higher elevations. The seasonal effect peaks in mid July. The spatial effect models several local features, but there is a pronounced minimum in the Northwest and a clear maximum in the Eastern part of Carinthia. The estimated effects of the intensity model reveal similar features, though they are not equal. Main difference is that the spatial effect varies more strongly than the analogous effect of the occurrence model. A major asset of the introduced method is that the resulting climatological information vary smoothly over space and time. Thus, the climatology is capable to serve as a useful tool in quantitative applications, i.e., risk assessment and weather prediction.

scholarly journals Sardine potential habitat and environmental forcing off western Portugal

2010 ◽  
Vol 67 (8) ◽  
pp. 1553-1564 ◽  
Author(s):  
Juan P. Zwolinski ◽  
Paulo B. Oliveira ◽  
Victor Quintino ◽  
Yorgos Stratoudakis
Keyword(s):  
Chlorophyll A ◽  
Seasonal Pattern ◽  
Generalized Additive Models ◽  
Additive Models ◽  
Seasonal Effect ◽  
Oceanic Circulation ◽  
Environmental Forcing ◽  
Potential Habitat ◽  
The North ◽  
Spatio Temporal

Abstract Zwolinski, J. P., Oliveira, P. B., Quintino, V., and Stratoudakis, Y. 2010. Sardine potential habitat and environmental forcing off western Portugal. – ICES Journal of Marine Science, 67: 1553–1564. Relationships between sardine (Sardina pilchardus) distribution and the environment off western Portugal were explored using data from seven acoustic surveys (spring and autumn of 2000, 2001, 2005, and spring 2006). Four environmental variables (salinity, temperature, chlorophyll a, and acoustic epipelagic backscatter other than fish) were related to the acoustic presence and density of sardine. Univariate quotient analysis revealed sardine preferences for waters with high chlorophyll a content, low temperature and salinity, and low acoustic epipelagic backscatter. Generalized additive models depicted significant relationships between the environment and sardine presence but not with sardine density. Maps of sardine potential habitat (SPH) built upon the presence/absence models revealed a clear seasonal effect in the across-bathymetry and alongshelf extension of SPH off western Portugal. During autumn, SPH covered a large part of the northern Portuguese continental shelf but was almost absent from the southern region, whereas in spring SPH extended farther south but was reduced to a narrow band of shallow coastal waters in the north. This seasonal pattern agrees with the spatio-temporal variation of primary production and oceanic circulation described for the western Iberian shelf.

scholarly journals Analysis of Big Game Fishing Catches of Blue Marlin (Makaira nigricans) in the Madeira Archipelago (Eastern Atlantic) and Factors that Affect Its Presence

2021 ◽  
Vol 13 (16) ◽  
pp. 8975
Author(s):  
Roi Martinez-Escauriaza ◽  
Pablo Pita ◽  
Maria Lídia Ferreira de Gouveia ◽  
Nuno Manuel Abreu Gouveia ◽  
Eduardo Teixeira ◽  
...  
Keyword(s):  
Generalized Additive Models ◽  
Additive Models ◽  
Seasonal Effect ◽  
Success Rates ◽  
Usual Practice ◽  
Blue Marlin ◽  
Makaira Nigricans ◽  
Madeira Archipelago ◽  
The Status ◽  
June July

The archipelago of Madeira (Portugal) is one of the main European big game fishing locations, where the main target species is the blue marlin (Makaira nigricans). Catch data for these fish were used to analyze their presence over the years, estimate their average weights, and calculate annual fishing success rates. The results showed a marked seasonal effect, with higher average catch rates in summer (June–July), suggesting a migration from the equatorial waters they inhabit at the beginning of the year to northern areas when the waters become warmer. The influences of some environmental factors were analyzed using generalized additive models, and it was observed that the occurrence of blue marlin may be influenced by water temperature, wind, rain, and atmospheric pressure. This fishery did not register a high mortality rate in blue marlin specimens due to the usual practice of catch and release; individuals captured in this fishery can be used as a source of information that allows for follow-up on the status of the blue marlin population in the region.

scholarly journals Predicting Malaria Transmission Dynamics in Dangassa, Mali: A Novel Approach Using Functional Generalized Additive Models

2020 ◽  
Vol 17 (17) ◽  
pp. 6339
Author(s):  
François Freddy Ateba ◽  
Manuel Febrero-Bande ◽  
Issaka Sagara ◽  
Nafomon Sogoba ◽  
Mahamoudou Touré ◽  
...  
Keyword(s):  
Wind Speed ◽  
Malaria Incidence ◽  
Generalized Additive Models ◽  
Community Health Center ◽  
Additive Model ◽  
Additive Models ◽  
Functional Regression ◽  
Novel Approach ◽  
Malaria Incidence Rate ◽  
Mean Wind Speed

Mali aims to reach the pre-elimination stage of malaria by the next decade. This study used functional regression models to predict the incidence of malaria as a function of past meteorological patterns to better prevent and to act proactively against impending malaria outbreaks. All data were collected over a five-year period (2012–2017) from 1400 persons who sought treatment at Dangassa’s community health center. Rainfall, temperature, humidity, and wind speed variables were collected. Functional Generalized Spectral Additive Model (FGSAM), Functional Generalized Linear Model (FGLM), and Functional Generalized Kernel Additive Model (FGKAM) were used to predict malaria incidence as a function of the pattern of meteorological indicators over a continuum of the 18 weeks preceding the week of interest. Their respective outcomes were compared in terms of predictive abilities. The results showed that (1) the highest malaria incidence rate occurred in the village 10 to 12 weeks after we observed a pattern of air humidity levels >65%, combined with two or more consecutive rain episodes and a mean wind speed <1.8 m/s; (2) among the three models, the FGLM obtained the best results in terms of prediction; and (3) FGSAM was shown to be a good compromise between FGLM and FGKAM in terms of flexibility and simplicity. The models showed that some meteorological conditions may provide a basis for detection of future outbreaks of malaria. The models developed in this paper are useful for implementing preventive strategies using past meteorological and past malaria incidence.

The Relationship between Mobility and COVID-19 in Germany: Modeling Case Occurrence using Apple's Mobility Trends Data

2021 ◽  
Author(s):  
Mark David Walker ◽  
Mihály Sulyok
Keyword(s):  
Generalized Additive Models ◽  
Information Criterion ◽  
Additive Models ◽  
Online Data ◽  
German Government ◽  
Explanatory Variables ◽  
Mobility Data ◽  
Community Mobility ◽  
The Relationship ◽  
Potential Use

Abstract Background Restrictions on social interaction and movement were implemented by the German government in March 2020 to reduce the transmission of coronavirus disease 2019 (COVID-19). Apple's “Mobility Trends” (AMT) data details levels of community mobility; it is a novel resource of potential use to epidemiologists. Objective The aim of the study is to use AMT data to examine the relationship between mobility and COVID-19 case occurrence for Germany. Is a change in mobility apparent following COVID-19 and the implementation of social restrictions? Is there a relationship between mobility and COVID-19 occurrence in Germany? Methods AMT data illustrates mobility levels throughout the epidemic, allowing the relationship between mobility and disease to be examined. Generalized additive models (GAMs) were established for Germany, with mobility categories, and date, as explanatory variables, and case numbers as response. Results Clear reductions in mobility occurred following the implementation of movement restrictions. There was a negative correlation between mobility and confirmed case numbers. GAM using all three categories of mobility data accounted for case occurrence as well and was favorable (AIC or Akaike Information Criterion: 2504) to models using categories separately (AIC with “driving,” 2511. “transit,” 2513. “walking,” 2508). Conclusion These results suggest an association between mobility and case occurrence. Further examination of the relationship between movement restrictions and COVID-19 transmission may be pertinent. The study shows how new sources of online data can be used to investigate problems in epidemiology.

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