COVID-19 is having a great impact on public health, mortality and economy worldwide, in spite of the efforts to prevent its epidemy. The SARS-CoV-2 genome is different from that of MERS-CoV and SARS-CoV, although also expected to spread differently according to meteorological conditions. Our main goal is to investigate the role of some meteorological variables on the expansion of this outbreak.In this study, an exponential model relating the number of accumulated confirmed cases and time was considered. The rate of COVID-19 spread, using as criterion the doubling time of the number of confirmed cases, was used as dependent variable in a linear model that took four independent meteorological variables: temperature, humidity, precipitation and wind speed. Only China cases were considered, to control both cultural aspects and containment policies. Confirmed cases and the 4 meteorological variables were gathered between January 23 and March 1 (39 days) for the 31 provinces of Mainland China. Several periods of time were sampled for each province, obtaining more than one value for the rate of disease progression.Two different periods of time were tested, of 12 and 15 days, along with 3 and 5 different starting points in time, randomly chosen. The median value for each meteorological variable was computed, using the same time period; models with > 0.75 were selected. The rate of progression and doubling time were computed and used to fit a linear regression model. Models were evaluated using = 0.05.. CC-BY 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not peer-reviewed)The copyright holder for this preprint . https: //doi.org/10.1101//doi.org/10. /2020 Results indicate that the doubling time correlates positively with temperature and inversely with humidity, suggesting that a decrease in the rate of progression of COVID-19 with the arrival of spring and summer in the north hemisphere. A 20ºC increase is expected to delay the doubling time in 1.8 days. Those variables explain 18% of the variation in disease doubling time; the remaining 82% may be related to containment measures, general health policies, population density, transportation or cultural aspects.

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Abstract. Due to its economic and nutritional value, the world production of chestnuts is increasing as new stands are being planted in various regions of the world. This work focuses on the relation between weather and annual chestnut production to model the role of weather, to assess the impacts of climate change and to identify appropriate locations for new groves. The exploratory analysis of chestnut production time series and the striking increase of production area have motivated the use for chestnut productivity. A large set of meteorological variables and remote sensing indices were computed and their role on chestnut productivity evaluated with composite and correlation analyses. These results allow for the identification of the variables cluster with a high correlation and impact on chestnut production. Then, different selection methods were used to develop multiple regression models able to explain a considerable fraction of productivity variance: (i) a simulation model (R 2 -value = 87 %) based on the winter and summer temperature and on spring and summer precipitation variables; and, (ii) a model to predict yearly chestnut productivity (R 2 -value of 63 %) with five months in advance, combining meteorological variables and NDVI. Goodness of fit statistic, cross validation and residual analysis demonstrate the model's quality, usefulness and consistency of obtained results.

The heat transfer characteristics from a circular cylinder immersed in power law fluids have been studied in the mixed convection regime when the imposed flow is oriented normal to the direction of gravity. The continuity, momentum, and thermal energy equations have been solved numerically using a second-order finite difference method to obtain the streamline, surface viscosity, and vorticity patterns, to map the temperature field near the cylinder and to determine the local and surface-averaged values of the Nusselt number. Overall, mixed convection distorts streamline and isotherm patterns and increases the drag coefficient as well as the rate of heat transfer from the circular cylinder. New results showing the complex dependence of all these parameters on power law index (n ) 0.6, 0.8, 1, 1.6), Prandtl number () 1,100), Reynolds number (1-30), and the Richardson number (0, 1, and 3) are presented herein. Over this range of conditions, the flow is assumed to be steady, as is the case for Newtonian fluids.