Weather In Agriculture: Accuracy Promotes Success
Agriculture weather is critical for securing the yield of most field crops. However, farmers and landowners who rely on publicly available agriculture weather data often find that the forecasts made by these sources don’t match up with what they see in their fields. This disparity might result in heavy losses, especially when severe weather strikes unexpectedly. Therefore, growers should only use agriculture weather forecasts that have been carefully compiled, specifically for their fields, using data from meteo stations, sensors, and satellites.
Concept And Importance Of Weather In Agriculture
When we remark on the crucial role of weather in agriculture, we are not exaggerating; in fact, we may be understating its significance. If you want to maximize your agricultural output and increase crop yields, you must work in conjunction with the meteo conditions.
Weather has a significant impact on the prevalence of pests and diseases, the availability of water, and the amount of fertilizer needed to grow crops. Farmers rely on climate patterns and weather forecasting in agriculture to determine which crops to cultivate and when to sow them. The majority of farming techniques depend on favorable meteorological conditions. As an illustration, precision irrigation relies on the amount of rain that falls on a field, soil solarization requires high temperatures, etc.
Climate change and agriculture are intertwined in crucial ways. If temperatures rise, farmers may be able to reap the benefits of growing crops suited to their climate or move to growing crops more suited to warmer regions. If the increased temperature is higher than optimal for a given crop, however, agriculture production will suffer. In general, it may become more challenging to cultivate crops in the same manner and locations as a result of climate change .
Farmers most frequently use short-range forecasts, which are predictions made between 1 and 7 days in advance. In the meantime, medium-range (up to a month), long-range (up to a year), and hazardous weather forecasts for agriculture can all be extremely helpful in field activity planning. Even though severe weather can come abruptly, wreaking havoc on crops and even impacting the viability of seeds in storage, local meteorological forecasts help farmers prepare for these events, minimizing or even eliminating their harmful effects.
How Does Weather Affect Agriculture?
Most crops grown in fields rely entirely on rain and sunshine for their survival. Meteo conditions also affect the well-being and food availability of livestock.
Agriculture losses from severe weather can be devastating. High temperatures, low rainfall, flooding, and sudden freezes negatively affect crops, particularly during the most vulnerable stages of plant growth, such as seed germination. Studies have shown that drought is typically a major reason for decreased grain yields and economic losses on farms .
Indirect effects of weather on agriculture crops include shifts in soil processes, dynamics of nitrogen uptake, and the spread of pest populations. Soil erosion and nutrient deficiency due to heavy rain and the opposite phenomenon, soil salinization during the dry spell, are all examples of the indirect impact of weather on agriculture.
With all of the potential direct and indirect effects of meteo conditions, agriculture producers should plan ahead of time and count on accurate and dependable data.
Why Is Public Weather Station Data Insufficient For Agricultural Needs?
Given the significance of agricultural weather forecast accuracy, it’s easy to see why companies and organizations in this sector are so eager to acquire the best available information. With multiple open-access public sources, it may seem that they might just pick one to obtain their desired agricultural meteorological reports. However, big players in the agriculture industry prefer reliable agricultural weather stations and data providers for one main reason: accurate data helps them increase profits while spending less.
Generally, meteorological stations covering a certain territory around them are the source of global weather data for agriculture monitoring, and the bigger the distance, the less accurate the forecast is. Typical forecasting models allow for prognoses based on specific conditions and their combinations. However, such suggestions are far from precise and cannot always assist in making the right decisions or insuring risks in agriculture.
Say, for instance, that a certain field’s crops don’t receive adequate moisture despite the fact that rain is forecast for the area. This is an example of why public weather data is insufficient for agriculture.
Accuracy And “Hyperlocality” Of Weather Data in EOSDA Crop Monitoring
In order to provide accurate meteorological forecasts for players in the agriculture industry, EOSDA Crop Monitoring has teamed up with Meteomatics to offer meteorology analytics. Precision is achieved by:
- global network of sensors and stations supplemented by satellite data;
- closer, more concentrated areas of operation;
- local topographic examination and study;
- advanced data-processing algorithm;
- unique high-resolution (spatial and temporal) datasets with a hyperlocal focus;
- merging results from several prediction models to produce the most reliable information.
The breadth of indications provided by shared-resource agricultural weather assessments is often insufficient for agronomists’ needs.
Agriculturally relevant variables include the sum of active temperatures, hourly precipitation, and cloud cover percentage; however, these metrics are not accessible on every resource. Additionally, the availability of these criteria does not guarantee their precision for agriculture. At the end of the day, it’s dependent on the model used to extrapolate data from meteo stations. Data accuracy decreases as model resolution decreases.
With a precision of up to 90 meters, the Meteomatics weather monitoring model is extremely accurate for agriculture. Furthermore, Meteomatics offers historical weather dating back to 1979, whereas most open-source tools only go back to the present day.
Ultimately, hyperlocal weather tracking is crucial in agriculture. Several Meteomatics sources that are relevant to agriculture are used to provide the meteorological data for EOSDA Crop Monitoring:
- records from meteo stations (networks of national stations and some other providers);
- evidence from weather models (ECMWF, ECMWF-ERA5, DWD-ICON, MF-Arome, GFS, HRRR, UKMO, Ensembles, and more);
- radar readings (data on precipitation gathered by radar networks all over the world);
- information gathered by satellites (Himawari-8, Meteosat, GOES-16, and GOES-17).
Using EOSDA Crop Monitoring software, agriculture producers can monitor the current climatic conditions of each field separately, including temperature and cloud cover. Further, such important indicators as humidity, wind speed and direction, and precipitation are also available. For ease of use, the platform allows selecting either metric or imperial measurements.
EOSDA Crop Monitoring provides highly reliable agricultural weather reports since they compile data from multiple sources, not just the one closest to the questioned field. The analytics are based on complicated algorithms that choose the most relevant resources among radar, satellites, sensors, and meteorological stations. Furthermore, the algorithm analyzes local topographic peculiarities and uses adiabatic corrections for elevation discrepancies between the stations and the area of interest. The applied techniques give the highest data precision for smart farming.
EOSDA Crop Monitoring
Fields analytics tool with access to high-resolution satellite images for remote problem areas identification!
Weather Tracking Feature On EOSDA Crop Monitoring
For large companies with a stake in agriculture, EOSDA Crop Monitoring provides a flexible and user-friendly hub for all their data collection and analysis needs. You can get meteorological information in a few different ways, including through an online web-based platform, a mobile app, or an API. Whatever approach you choose, you’ll have access to a historical meteorological record, a 14-day forecast, and real-time weather conditions for your fields.
In addition to the current conditions presented in the “Weather Today” section, EOSDA Crop Monitoring also offers agriculture weather forecasts for the next 14 days. These forecasts help reduce or prevent losses from weather-related disasters. Also, they have substantial financial and social benefits for agricultural businesses.
Actively using real-time meteorological data and forecasts, agricultural cooperatives optimize their field operations for irrigation and planting. This helps reduce costs while producing stronger, healthier plants.
Agriculture stakeholders can use EOSDA Crop Monitoring to find out about past temperatures and precipitation (daily and accumulated), as well as current conditions in the field and accurate forecasts for the next two weeks. The platform can provide charts of historical weather and help track its impact on agriculture for every five years, all the way back to 1979 (with or without the comparison).
This allows agribusinesses and agri-related companies to better understand the climate patterns that have developed in a specific area. Looking back at historical patterns and trends, we may make educated guesses about what crops will thrive in the future.
Agricultural consultants will find the data beneficial when providing weather-related advisory services in agriculture to their clients. Banking institutions and insurance companies can better calculate weather index insurance for agriculture if they have access to historical weather data. Also, methods based on machine learning can reveal meteorological insights that can help insurers come up with new products that are likely to make agriculture much safer.
EOSDA Crop Monitoring As An All-In-One Agro-Needs Software
EOSDA Crop Monitoring’s weather tracking technology in agriculture is closely interconnected with other data significant for crop development. Vegetation indices and growth stage modeling, also available in the tool, greatly facilitate weighted agriculture decisions. Alongside other factors, the modeling is based on the use of weather in precision agriculture, e.g., the temperature regime.
Agriculture success strongly depends on three major factors: soil fertility, meteorological conditions, and quality planting material. While selecting vibrant species or improving soil fertility is relatively easy, managing meteorological risks turns out to be the biggest and most difficult challenge. Meteo extremities like hail, flood, severe cold, or heat can ruin the crops in a single day, and a reliable forecast promotes a decent response. EOSDA Crop Monitoring alerts farmers to the meteorological dangers of frost and droughts.
Another issue to consider in agriculture is that one-degree temperature discrepancies with the forecast within a day have little effect on vegetation. However, plants are seriously impacted by accumulated events like unfavorable soil temperature, continuous waterlogging, and prolonged heat or cold stress. For this reason, agribusiness stakeholders have to take into account both daily meteorological conditions and accumulated values within a week or two.
EOSDA Crop Monitoring provides all the required data types for credible weather analytics in agriculture, thus, contributing to farming success. Start monitoring your fields with us today.
About the author:
Natalia Ivanchuk holds a Master’s degree in Applied Mathematics (2013) from the National University of Water and Environmental Engineering. She is an author of 60+ scientific publications, monographs, and other scientific works.
In 2019, she successfully defended a thesis, “Mathematical modeling of filtration processes in soil environments taking into account the influence of elements of engineering structures” and earned the Candidate of Technical Sciences degree.
Currently, Natalia is an Associate Professor at the Department of Computer Sciences and Applied Mathematics at the National University of Water and Environmental Engineering in Rivne, Ukraine. She teaches different programming languages (C++, C#, JS, among others) at the said university.
Natalia is actively engaged in scientific research related to the practical application of new programming algorithms. Programming is also something she likes to do in her spare time.
Her expertise and constant desire to learn and perfect her programming skills, especially in working with Python, has been most beneficial for EOS Data Analytics.
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