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Atmosphere
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ICT-Based High-Resolution Weather and Climate Research for an Early-Warning System...
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ICT-Based High-Resolution Weather and Climate Research for an Early-Warning System for Agricultural Disasters

A special issue of Atmosphere (ISSN 2073-4433). This special issue belongs to the section "Meteorology".

Deadline for manuscript submissions: 20 November 2024 | Viewed by 2708

Special Issue Editors

Dr. Seung-Jae Lee

E-Mail Website
Guest Editor
National Center for AgroMeteorology (NCAM), Seoul 08826, Republic of Korea
Interests: earth system modeling; numerical weather prediction; regional climate simulation; land-air-water-life interaction; user-customized data processing
Special Issues, Collections and Topics in MDPI journals
Dr. Kyo-Moon Shim

E-Mail Website
Guest Editor
National Institute of Agricultural Sciences, Wanju 55365, Republic of Korea
Interests: agro-meteorology; agro-meteorological services; agricultural disasters; climate change; disaster prevention
Dr. Byong-Lyol Lee

E-Mail Website
Guest Editor
National Center for AgroMeteorology (NCAM), Suwon 16200, Republic of Korea
Interests: agronomy; field crop science; agricultural ecology

Special Issue Information

Dear Colleagues,

Meteorological and climatological disasters such as heavy rainfall, floods, droughts, and typhoons threaten the stable supply of agricultural products and the income of farmers. Overall, the frequency and intensity of such disasters are increasing under the changing climate. We aim to reduce the damage caused by natural hazards through adopting preventative measures including greenhouse cultivation. A more complete system with efficient disaster-reduction capability is required to mitigate the impact of extreme weather. The development of climate-smart agriculture can help reduce the impact of natural hazards on food production systems and improve the livelihoods of farming communities. Specifically, the further development of disaster prevention technology is required in important crop-production areas. Such technology should provide pre-disaster warnings and facilitate the identification of disaster-affected areas and aid in conducting post-disaster surveys for the rehabilitation of crops. Disaster prevention technology can also be used to clarify the critical conditions of different crops and growth periods, estimate the probability of crop losses, and establish a complete knowledge database of crop disasters.

In this Special Issue, we will emphasize concepts and practices related to reducing agricultural weather disaster risks through systematic efforts to analyze and reduce the causal factors of disasters. This Special Issue will include articles on the sensible management of crops and the environment using innovative disaster prevention technologies, setup of the early-warning systems which send SNS messages to farmers, and evaluation of vulnerability to cultivation and economic losses as a result of disasters. In particular, we invite information and communication technology vendors to demonstrate the latest products for environmental monitoring and crop disaster (or cultivation) warning systems. We hope this collection of articles will aid in expanding climate smart agriculture and reducing the impact of natural hazards on food production systems through a multidimensional discussion.

Dr. Seung-Jae Lee
Dr. Kyo-Moon Shim
Dr. Byong-Lyol Lee
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Atmosphere is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • agrometeorological disaster
  • early-warning system
  • weather risk index
  • farmstead-specific weather data
  • high-resolution weather and climate model
  • downscaling and upscaling
  • agrometeorological service
  • crop phenology
  • diseases and insects
  • frost
  • hail
  • wind gusts
  • heavy rainfall
  • drought

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Published Papers (2 papers)

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Research

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16 pages, 9567 KiB  
Article
Using the Multiple-Sensor-Based Frost Observation System (MFOS) for Image Object Analysis and Model Prediction Evaluation in an Orchard
by Su Hyun Kim, Seung-Min Lee and Seung-Jae Lee
Atmosphere 2024, 15(8), 906; https://doi.org/10.3390/atmos15080906 - 29 Jul 2024
Viewed by 677
Abstract
Accurate frost observations are crucial for developing and validating frost prediction models. In 2022, the multi-sensor-based automatic frost observation system (MFOS), including an RGB camera, a thermal infrared camera, a leaf wetness sensor (LWS), LED lighting, and three glass plates, was developed to [...] Read more.
Accurate frost observations are crucial for developing and validating frost prediction models. In 2022, the multi-sensor-based automatic frost observation system (MFOS), including an RGB camera, a thermal infrared camera, a leaf wetness sensor (LWS), LED lighting, and three glass plates, was developed to replace the naked-eye observation of frost. The MFOS, herein installed and operated in an apple orchard, provides temporally high-resolution frost observations that show the onset, end, duration, persistence, and discontinuity of frost more clearly than conventional naked-eye observations. This study introduces recent additions to the MFOS and presents the results of its application to frost weather analysis and forecast evaluation in an orchard in South Korea. The NCAM’s Weather Research and Forecasting (WRF) model was employed as a weather forecast model. The main findings of this study are as follows: (1) The newly added image-based object detection capabilities of the MFOS helped with the extraction and quantitative comparison of surface temperature data for apples, leaves, and the LWS. (2) The resolution matching of the RGB and thermal infrared images was made successful by resizing the images, matching them according to horizontal movement, and conducting apple-centered averaging. (3) When applied to evaluate the frost-point predictions of the numerical weather model at one-hour intervals, the results showed that the MFOS could be used as a much more objective tool to verify the accuracy and characteristics of frost predictions compared to the naked-eye view. (4) Higher-resolution and realistic land-cover and vegetation representation are necessary to improve frost forecasts using numerical grid models based on land–atmosphere physics. Full article
(This article belongs to the Special Issue ICT-Based High-Resolution Weather and Climate Research for an Early-Warning System for Agricultural Disasters)
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Review

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15 pages, 5307 KiB  
Review
Farmstead-Specific Weather Risk Prediction Technique Based on High-Resolution Weather Grid Distribution
by Dae-Jun Kim, Jin-Hee Kim, Eun-Jeong Yun, Dae Gyoon Kang and Eunhye Ban
Atmosphere 2024, 15(1), 116; https://doi.org/10.3390/atmos15010116 - 18 Jan 2024
Viewed by 1175
Abstract
In recent years, the importance and severity of weather-related disasters have escalated, attributed to rising temperatures and the occurrence of extreme weather events due to global warming. The focus of disaster management has shifted from crisis management (e.g., repairing and recovering from damage [...] Read more.
In recent years, the importance and severity of weather-related disasters have escalated, attributed to rising temperatures and the occurrence of extreme weather events due to global warming. The focus of disaster management has shifted from crisis management (e.g., repairing and recovering from damage caused by natural disasters) to risk management (e.g., prediction and preparation) while concentrating on early warning, thanks to the development of media and communication conditions. The Rural Development Administration (Korea) has developed the “early warning service for weather risk management in the agricultural sector” that detects weather risks for crops from high-resolution weather information in advance and provides customized information to respond to possible disaster risks in advance in response to the increasing number of extreme weather events. The core technology of this service is damage prediction technology that determines the overall agricultural weather risk level by quantifying the current growth stage of cultivated crops and the probability of possible weather disasters according to the weather conditions of the farm. Agrometeorological disasters are damages caused by weather conditions that can affect crops and can be predicted by estimating the probability of damage that may occur from the interaction between hazardous weather and crop characteristics. This review introduces the classification of possible weather risks by their occurrence mechanisms, based on the developmental stage of crops and prediction techniques that have been developed or applied to date. The accumulated crop growth and weather risk information is expected to be utilized as support material for farming decision-making, which helps farmers proactively respond to crop damage due to extreme weather events by providing highly reliable disaster forecasts through the advancement of prediction technology. Full article
(This article belongs to the Special Issue ICT-Based High-Resolution Weather and Climate Research for an Early-Warning System for Agricultural Disasters)
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