Calculation of Agro-Climatic Factors from Global Climatic Data
Abstract
:Featured Application
Abstract
1. Introduction
2. Related Works
2.1. Temperature-Related Agro-Climatic Factors
2.2. Solar Radiation-Related Agro-Climatic Factors
2.3. Water-Cycle Related Agro-Climatic Factors
2.4. Comprehensive Studies
- The average number of frost days from the years 1981–2010 (number of days with the minimum daily temperature below 0 °C) and the average number of ice days (number of days with the maximum daily temperature below 0 °C).
- The late frost risk (the map shows the occurrence of a minimum daily temperature below 0 °C for five consecutive days with an average daily temperature above 10 °C in a row) and the late significant frost risk (daily temperatures below 0 °C for five consecutive days with an average daily temperature above 15 °C in a row expressed as a percentage of years in the reference period when this condition occurred for 1 or more days).
- Also, maps focused on high temperatures are produced: Extremes—temperature above 35 °C in July, tropical days (average annual number of days with the maximum daily air temperature above 30 °C), risk of temperature stress—degree of alertness (the map shows the average number of days with temperature index > = 27 °C), risk of hot or/and dry periods.
- Next, a map of the length of the growing summer season demonstrates the average length of the growing summer (continuous period with an average daily temperature above 15 °C). A map of the length of the growing season shows the length of the growing season (continuous period with an average daily temperature above 5 °C).
- Also, precipitation data are processed, and average annual precipitation, daily total precipitation over 5 mm, daily total precipitation over 10 mm, average total precipitation in summer maps are created. The Institute has developed many maps focused on deficits and changes in water storage, for example, changes in a landscape water regime, changes in a landscape water regime during the growing period (April-September). These changes were calculated as the difference between precipitation and reference evapotranspiration during the whole year or season.
2.5. Common Grounds for Agro-Climatic Factors Calculation
- The previous works calculate agro-climatic factors mostly from data of local weather stations-the used input climate data are usually not global. Therefore, our approach aims to evaluate global climatic data suitability.
- The inverse distance weighted interpolation (IDW) is generally used as an interpolation method. Therefore it is used in our study as well.
- The calculations are often just briefly indicated, not described in detail. Therefore we aim to describe each agro-climatic factor in detail (see the link to GitHub provided in Supplementary Materials).
- Isopleths are commonly used to visualize the calculated agro-climatic factors. Thus we follow the same approach.
- Calculated for a set of the year but hard to repeat as it is not running as an on-demand service. On the contrary, algorithms that we publish allow everybody to recalculate the factors on demand.
- From air temperature: Frost-free periods, growing degree units, heat stress units, number of (optimal) growing degree days,
- From soil temperature: The nitrogen application window,
- From incident sunlight: Accumulated solar radiation,
- From precipitation, evapotranspiration, and runoff data: Water balance.
3. Materials and Methods
3.1. Materials
3.1.1. ERA5-Land Hourly Data from 1981 to Present
3.1.2. ERA5 Ensemble of Data Assimilations (ERA5 EDA)
3.1.3. Case Study Area in Kojčice
3.1.4. Case Study Area in the Pilsen Region
3.2. Methods
3.2.1. Frost-Free Periods
3.2.2. Crop Growth-Related Temperatures
3.2.3. Uncertainty of Input Variables
3.2.4. Uncertainty of Calculated Agro-Climatic Factors
4. Results
4.1. Uncertainty of Input Temperatures
4.2. Accuracy of the Global Climatic Data Evaluated Using In-Situ Sensors
4.3. Uncertainty of Calculated Agro-Climatic Factors
5. Findings and Discussion
6. Conclusions
Supplementary Materials
Author Contributions
Funding
Conflicts of Interest
Appendix A
References
- Meteoblue. Meteoblue: History+. 2020. Available online: https://www.meteoblue.com/en/historyplus (accessed on 21 May 2020).
- National Oceanic and Atmospheric Administration (NOAA). When to Expect Your Last Spring Freeze. 2010. Available online: https://www.ncdc.noaa.gov/news/when-expect-your-last-spring-freeze (accessed on 21 May 2020).
- The Old Farmer’s Almanac. Yankee Publishing Inc. 2020. Available online: https://www.almanac.com/ (accessed on 21 May 2020).
- Ustrnul, Z.; Wypych, A.; Winkler, J.A.; Czekierda, D. Late spring freezes in Poland in relation to atmospheric circulation. Quaest. Geogr. 2014, 33, 165–172. [Google Scholar] [CrossRef] [Green Version]
- Index to Degree-Day Data and Maps of USA. 2009. Available online: http://pnwpest.org/US/ (accessed on 21 May 2020).
- Meteotemplate. Isle of Grain Weather. 2020. Available online: https://www.iogweather.org.uk/template/plugins/mapsUK/index.php (accessed on 21 May 2020).
- Environmental Indicators: Growing Degree Days. 2017. Available online: http://archive.stats.govt.nz/browse_for_stats/environment/environmental-reporting-series/environmental-indicators/Home/Atmosphere-and-climate/growing-degree-days.aspx (accessed on 21 May 2020).
- The Geography of Transport Systems: Length of Growing Period (LGP), in Days. 2010. Available online: https://transportgeography.org/?page_id=12891 (accessed on 21 May 2020).
- UNEP Environmental Data Explorer—The Environmental Database (Search | Map | Graph | Download). 2006. Available online: http://geodata.grid.unep.ch/ (accessed on 21 May 2020).
- Hollinger, S.E.; Angel, J.R. Illinois Agronomy Handbook: Weather and Crops. 2012. Available online: http://extension.cropsciences.illinois.edu/handbook/pdfs/chapter01.pdf (accessed on 21 May 2020).
- Pathak, T.; Hubbard, K.; Shulski, M. Soil Temperature: A Guide for Planting Agronomic and Horticulture Crops in Nebraska; University of Nebraska: Lincoln, NE, USA, 2012. [Google Scholar]
- SolarGIS. Global Solar Atlas. 2020. Available online: https://globalsolaratlas.info/map (accessed on 21 May 2020).
- Giusti, M. ERA5: Dataset Documentation. 2019. Available online: https://confluence.ecmwf.int/display/CKB/ERA5 (accessed on 21 May 2020).
- Afonin, A.N.; Greene, S.L.; Dzyubenko, N.I.; Frolov, A.N. (Eds.) Interactive Agricultural Ecological Atlas of Russia and Neighboring Countries. Economic Plants and their Diseases, Pests and Weeds. 2008. Available online: http://www.agroatlas.ru (accessed on 21 May 2020).
- Bishop, J.K.B.; Rossow, W.B.; Dutton, E.G. Surface solar irradiance from the International Satellite Cloud Climatology Project 1983–1991. J. Geophys. Res. 1997, 102, 6883–6910. [Google Scholar] [CrossRef]
- Markovic, S.; Luka, B.; Cerekovic, N.; Kljajić, N.; Rudan, N. Rainfall Analyses and Water Deficit during Growing Season in Banja Luka Region. Int. Congr. Ecol. Ecol. Spectr. 2012, 4167, 1167–1176. [Google Scholar]
- Geography, A.L. The Water Balance. 2016. Available online: https://www.alevelgeography.com/water-balance/ (accessed on 21 May 2020).
- El Dorado Weather: Australia Yearly Rainfall Averages. 2010. Available online: https://www.eldoradoweather.com/forecast/australia/australia-yearly-rainfall.html (accessed on 21 May 2020).
- Canada.ca: Agroclimatic Atlas of Canada. 1976. Available online: http://sis.agr.gc.ca/cansis/publications/manuals/1976-acac/index.html (accessed on 21 May 2020).
- Globální Klimatické Modely | Klimatická Změna v České Republice. 2020. Available online: https://www.klimatickazmena.cz/cs/metodika/globalni-klimaticke-modely/ (accessed on 21 May 2020). (In Czech).
- Adisa, O.M.; Botai, C.M.; Botai, J.O.; Hassen, A.; Darkey, D.; Tesfamariam, E.; Adisa, A.F.; Adeola, A.M.; Ncongwane, K.P. Analysis of agro-climatic parameters and their influence on maize production in South Africa. Theor. Appl. Climatol. 2018, 134, 991–1004. [Google Scholar] [CrossRef]
- Trnka, M.; Olesen, J.E.; Kersebaum, K.C.; Skjelvåg, A.O.; Eitzinger, J.; Seguin, B.; Peltonen-Sainio, P.; Rötter, R.; Iglesias, A.; Orlandini, S.; et al. Agroclimatic conditions in Europe under climate change. Glob. Chang. Biol. 2011, 17, 2298–2318. [Google Scholar] [CrossRef] [Green Version]
- Copernicus Climate Change Service (C3S): C3S ERA5-Land Reanalysis. 2019. Available online: https://cds.climate.copernicus.eu/cdsapp#!/home (accessed on 19 May 2020).
- Yang, X. ERA5-Land: Data Documentation. 2020. Available online: https://confluence.ecmwf.int/display/CKB/ERA5-Land (accessed on 19 May 2020).
- European Centre for Medium-Range Weather Forecasts (ECMWF): ERA5-Land. 2020. Available online: https://www.ecmwf.int/en/era5-land (accessed on 19 May 2020).
- European Centre for Medium-Range Weather Forecasts (ECMWF): IFS Documentation CY45R1. 2018. Available online: https://www.ecmwf.int/en/elibrary/18714-part-iv-physical-processes (accessed on 19 May 2020).
- Hennermann, K. ERA5: Uncertainty Estimation. 2020. Available online: https://confluence.ecmwf.int/display/CKB/ERA5%3A+uncertainty+estimation (accessed on 19 May 2020).
- Isaksen, L.; Bonavita, M.; Buizza, R.; Fisher, M.; Haseler, J.; Leutbecher, M.; Raynaud, L. Ensemble of Data Assimilations at ECMWF; ECMWF: Reading, UK, 2010; Available online: https://www.ecmwf.int/en/elibrary/10125-ensemble-data-assimilations-ecmwf (accessed on 19 May 2020). [CrossRef]
- Valeš, J. JiriVales/Agroclimatic-Factors: Algorithms of Creation Agroclimatic Factors from Climatic Dataset ERA5-Land (Necdf Files), GitHub, Inc. 2020. Available online: https://github.com/JiriVales/agroclimatic-factors/wiki (accessed on 21 May 2020).
- E-Infrastructure of the Project European e-Infrastructure for Extreme Data Analytics in Sustainable Development (EUXDAT). 2020. Available online: https://test.euxdat.eu/ (accessed on 21 May 2020).
- Geslin, H.; Holzberg, I.A.; Mason, B. Protection against Frost Damage (Report of a Working Group of the Commission for Agricultural Meteorology), World Meteorological Organization (WMO). 1963. Available online: https://library.wmo.int/index.php?lvl=notice_display&id=5363#.XyKxBCgzaUl (accessed on 21 May 2020).
- Shroyer, J.P.; Mikesell, M.E.; Paulsen, G.M. Spring Freeze Injury to Kansas Wheat. Cooperative Extension Service, Kansas State University. 1995. Available online: https://bookstore.ksre.ksu.edu/pubs/C646.pdf (accessed on 13 August 2020).
- Ahrens, C.D. Meteorology Today, 8th ed.; Brooks/Cole Publishing: Belmont, CA, USA, 2006; ISBN 0-49501162-2. [Google Scholar]
- Haby, J. Which Months of the Year Are Typically Coldest? 2004. Available online: https://www.theweatherprediction.com/habyhints3/980/ (accessed on 19 May 2020).
- National Centers for Environmental Information (NCEI). Meteorological Versus Astronomical Seasons. 2016. Available online: https://www.ncei.noaa.gov/news/meteorological-versus-astronomical-seasons (accessed on 19 May 2020).
- Shepard, D. A two-dimensional interpolation function for irregularly-spaced data. In Proceedings of the 1968 ACM National Conference, New York, NY, USA, 27–29 August 1968; pp. 517–524. [Google Scholar] [CrossRef]
- Kraak, M.J.; Koussoulakou, A. A Visualization Environment for the Space-Time-Cube. In Developments in Spatial Data Handling; Springer: Berlin/Heidelberg, Germany, 2005. [Google Scholar] [CrossRef]
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Jedlička, K.; Valeš, J.; Hájek, P.; Kepka, M.; Pitoňák, M. Calculation of Agro-Climatic Factors from Global Climatic Data. Appl. Sci. 2021, 11, 1245. https://doi.org/10.3390/app11031245
Jedlička K, Valeš J, Hájek P, Kepka M, Pitoňák M. Calculation of Agro-Climatic Factors from Global Climatic Data. Applied Sciences. 2021; 11(3):1245. https://doi.org/10.3390/app11031245
Chicago/Turabian StyleJedlička, Karel, Jiří Valeš, Pavel Hájek, Michal Kepka, and Martin Pitoňák. 2021. "Calculation of Agro-Climatic Factors from Global Climatic Data" Applied Sciences 11, no. 3: 1245. https://doi.org/10.3390/app11031245
APA StyleJedlička, K., Valeš, J., Hájek, P., Kepka, M., & Pitoňák, M. (2021). Calculation of Agro-Climatic Factors from Global Climatic Data. Applied Sciences, 11(3), 1245. https://doi.org/10.3390/app11031245