Phenological model of bird cherry Padus racemosa with data assimilation

Abstract

The accuracy of the operational models can be improved by using observational data to shift the model state in a process called data assimilation. Here, a data assimilation approach using the temperature similarity to control the extent of extrapolation of point-like phenological observations is explored. A degree-day model is used to describe the spring phenology of the bird cherry Padus racemosa in the Baltic region in 2014. The model results are compared to phenological observations that are expressed on a continuous scale based on the BBCH code. The air temperature data are derived from a numerical weather prediction (NWP) model. It is assumed that the phenology at two points with a similar temperature pattern should be similar. The root mean squared difference (RMSD) between the time series of hourly temperature data over a selected time interval are used to measure the temperature similarity of any two points. A sigmoidal function is used to scale the RMSD into a weight factor that determines how the modelled and observed phenophases are combined in the data assimilation. The parameter space for determining the weight of observations is explored. It is found that data assimilation improved the accuracy of the phenological model and that the value of the point-like observations can be increased through using a weighting function based on environmental parameters, such as temperature.

The Phenological Growth Stages of Sapindus mukorossi According to BBCH Scale

“…Vegetative growth spanned three principal stages at our location in southern China: bud (00-09), leaf (10)(11)(12)(13)(14)(15)(16)(17)(18)(19) and shoot (31)(32)(33)(34)(35)(36)(37)(38)(39) development. The growth cycle of S. mukorossi differed from those of longan and lychee trees in southern China; these latter species have a period of dormancy in winter after completing the growth of shoot and then start the reproductive period in the spring of next year.…”

Journal article publishing in the social sciences and humanities: A comparison of Web of Science coverage for five European countries

“…In this study we use data about peer-reviewed publications from 2013 to 2016 that we collected from national databases in the Czech Republic (RIV), Poland (PBN), Slovakia (CREPČ), Flanders (VABB-SHW), and Norway (NSI). The authors of previous studies have described the need to use national databases as essential data sources for SSH-related analytics, data collection methodologies, definitions of publication types, and inclusion criteria in different countries [5,33,34].…”

“…For the purposes of this study, we use only data classified in three publications types: a) journal articles, b) monographs and edited books, and c) book chapters and conference proceedings. Details about each country's database and publication types were published in an earlier report [33]. Because national databases evolved in different historical and political settings and are unique in terms of scope, coverage, structure of publication types, and data availability, we must consider the context of data sources when interpreting the results.…”