FAIRness of micrometeorological data and responsible research and innovation: an open framework for climate research

During the 20th century, the atmospheric science community became one of the major "big data" sources, and micrometeorological measurements are an important part of it. This trend is still going strong, supported by networks of so-called "unconventional" measurements and SMART technologies (citizen weather networks and meteorological instruments on different mobile devices, for example). The potential weakness of data coming from such diverse sources is the lack of findability, accessibility, interoperability, and reusability (FAIR). The opportunity for improvement is "to define a minimal set of related but independent and separable guiding principles and practices, which enable both machines and humans to find access, interoperate and reuse research data and metadata" (PwC EU Services, 2018). Enhanced FAIRness of micrometeorological data strongly supports almost all main pillars of Responsible Research and Innovation (RRI), particularly in STEM and STEM-related fields, leaving room for different levels of accessibility since FAIRness does not imply Open data status. In a case study, an initial FAIRness assessment is performed for micrometeorological data measured in an orchard within the Forecasting and Reporting Service for Plant Protection of the Republic of Serbia (PIS) observational network

Seasonal forecasting of green water components and crop yields of winter wheat in Serbia and Austria

A probabilistic crop forecast based on ensembles of crop model output (CMO) estimates offers a myriad of possible realizations and probabilistic forecasts of green water components (precipitation and evapotranspiration), crop yields and green water footprints (GWFs) on monthly or seasonal scales. The present paper presents part of the results of an ongoing study related to the application of ensemble forecasting concepts for agricultural production. The methodology used to produce the ensemble CMO using the ensemble seasonal weather forecasts as the crop model input meteorological data without the perturbation of initial soil or crop conditions is presented and tested for accuracy, as are its results. The selected case study is for winter wheat growth in Austria and Serbia during the 2006–2014 period modelled with the SIRIUS crop model. The historical seasonal forecasts for a 6-month period (1 March-31 August) were collected for the period 2006–2014 and were assimilated from the European Centre for Medium-range Weather Forecast and the Meteorological Archival and Retrieval System. The seasonal ensemble forecasting results obtained for winter wheat phenology dynamics, yield and GWF showed a narrow range of estimates. These results indicate that the use of seasonal weather forecasting in agriculture and its applications for probabilistic crop forecasting can optimize field operations (e.g., soil cultivation, plant protection, fertilizing, irrigation) and takes advantage of the predictions of crop development and yield a few weeks or months in advance

Agricultural Meteorology and Climatology

Agricultural Meteorology and Climatology is an introductory textbook for meteorology and climatology courses at faculties of agriculture and for agrometeorology and agroclimatology courses at faculties whose curricula include these subjects. Additionally, this book may be a useful source of information for practicing agronomists and all those interested in different aspects of weather and climate impacts on agriculture. In times when scientific knowledge and practical experience increase exponentially, it is not a simple matter to prepare a textbook. Therefore we decided not to constrain Agricultural Meteorology and Climatology by its binding pages. Only a part of it is a conventional textbook. The other part includes numerical examples (easy-to-edit worksheets) and recommended additional reading available on-line in digital form. To keep the reader's attention, the book is divided into three sections: Basics, Applications and Agrometeorological Measurements with Numerical Examples

An Approach for Calculation of Turbulent Transfer Coefficient for Momentum inside Vegetation Canopies

A method for calculating the profile of turbulent transfer coefficient for momentum inside a vegetation canopy for use in land surface schemes is presented. It is done through the following steps. First, an equation for the turbulent transfer coefficient for momentum inside a vegetation canopy using the “sandwich” approach for its representation is derived. Second, it is examined analytically to determine whether its solution is always positive. Third, the equation for the turbulent transfer coefficient is solved numerically, using an iterative procedure for calculating the attenuation factor in the expression for the wind speed inside a vegetation canopy that is assumed to be a linear combination of an exponential function and a logarithmic function. The proposed method is tested using 1) the observations for the wind profiles in a Japanese larch plantation and a pine forest and 2) the outputs for surface fluxes and total soil water content obtained by the Land–Air Parameterization Scheme (LAPS) with the forcing data and observations in a soybean field at the Caumont site in France during the 1986 growing season. Also, a test is performed that compares the proposed method with the method for calculating the turbulent transfer coefficients for momentum inside a vegetation canopy commonly used in land surface schemes

Variability in the water footprint of arable crop production across European regions

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Exchange of greenhouse gases between biosphere and atmosphere

<p>The concentrations and fluxes of greenhouse gases (GHG) in the land-atmosphere system are controlled by complex interactions between emissions, turbulent transfer, dry deposition and chemical transformations. The forest canopy can significantly affect turbulent fluxes between the atmosphere, the canopy crown and the understory where most of the sinks or sources of mass and energy are located. Exchange processes depend on canopy homogeneity and isotropy, as well as morphological, aerodynamic and thermal characteristics. Therefore, it is anticipated that the forest canopy structure will play a significant role in the exchange of GHG species.</p

Agricultural Meteorology and Climatology

Agricultural Meteorology and Climatology is an introductory textbook for meteorology and climatology courses at faculties of agriculture and for agrometeorology and agroclimatology courses at faculties whose curricula include these subjects. Additionally, this book may be a useful source of information for practicing agronomists and all those interested in different aspects of weather and climate impacts on agriculture. In times when scientific knowledge and practical experience increase exponentially, it is not a simple matter to prepare a textbook. Therefore we decided not to constrain Agricultural Meteorology and Climatology by its binding pages. Only a part of it is a conventional textbook. The other part includes numerical examples (easy-to-edit worksheets) and recommended additional reading available on-line in digital form. To keep the reader\u27s attention, the book is divided into three sections: Basics, Applications and Agrometeorological Measurements with Numerical Examples