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Special Issue "Agrometeorology: From Scientific Analysis to Operational Application"

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A special issue of Atmosphere (ISSN 2073-4433).

Deadline for manuscript submissions: closed (30 June 2013)

Special Issue Editors

Guest Editor
Prof. Dr. Josef Eitzinger

Institute of Meteorology of the Department of Water, Atmosphere and Environment, University of Natural Resources and Applied Life Sciences (BOKU), Vienna, Peter Jordan Str. 82, A-1190 Vienna, Austria
Website | E-Mail
Interests: agricultural meteorology; agroclimatology; microclimatology; remote sensing in agricultural meteorology; simulation models (agro-ecosystems, crops)
Guest Editor
Dr. Branislava Lalic

Faculty of Agriculture, University of Novi Sad, Serbia
E-Mail
Interests: modelling of forest-atmosphere interaction; Land-atmosphere processes (theory and modeling); boundary layer meteorology (theory and modeling); agrometeorological modelling; predicting the occurrence of plant diseases in agriculture; biometeorogical modelling
Guest Editor
Prof. Dr. Levent Saylan

Department of Meteorology, Istanbul Technical University, 34469 Maslak, Istanbul, Turkey
E-Mail
Interests: agricultural meteorology; microclimatology; impacts of climate change on agriculture; energy and gas exchange between land and atmosphere; crop growth simulation models; evapotranspiration, drought

Special Issue Information

Dear Colleagues,

Agrometeorology is an interdisciplinary holistic science forming a real bridge between physical and biological sciences and beyond. It is dealing with a complex system involving soil, plant, atmosphere, agricultural management options and others, which are interacting dynamically on various spatial and temporal scales. In specific, the fully coupled soil-plant-atmosphere system has to be well understood in order to develop reasonable operational applications or recommendations for stakeholders.
For these reasons a comprehensive analysis of cause-effect relationships and principles is necessary, that describe the influence of the state of the atmosphere, plants and soil on different aspects of agricultural production, as well as the nature and importance of feedbacks between these elements of the system.
Agrometeorological methods therefore use information and data from different key sciences such as soil physics and chemistry, hydrology, meteorology, crop and animal physiology and phenology, agronomy and others. Observed information is often combined in more or less complex models, focused on various components of system parts such as mass balances (i.e. soil carbon, nutrients and water), biomass production, crop growth and yield, crop or pest phenology in order to detect sensitivities or potential responses of the soil-biosphere-atmosphere system. However, model applications still involve many uncertainties, which call for further improvements of the description of system processes.
A better quality of operational applications at various scales (monitoring, forecasting, warning, recommendations, etc.) is crucial for stakeholders. For example, new methods for spatial applications involve GIS and Remote Sensing for spatial data presentation and generation. Further, tailor made products as well as information transfer are critical to allow effective management decisions in the short and long term. These should cover sustainability and enhancement strategies (including risk management, mitigation and adaptation) considering climate variability and change. We invite papers addressing these problems in the context of agrometeorological applications in “atmosphere” as an actual and important contribution to the state of the art.

Prof. Dr. Josef Eitzinger,
Dr. Branislava Lalic,
Prof. Dr. Levent Saylan
Guest Editors

Submission

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. Papers will be published continuously (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as 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 refereed through a 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 1000 CHF (Swiss Francs).

Keywords

  • agrometeorology
  • climate change
  • crop model
  • soil-plant-atmosphere processes
  • operational agrometeorology
  • monitoring, forecasting
  • water balance
  • carbon balance
  • phenology
  • pest
  • desease
  • agrometeorological indices
  • drought
  • weather extremes
  • stakeholders

Published Papers (6 papers)

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Research

Open AccessArticle Data Mining Methods to Generate Severe Wind Gust Models
Atmosphere 2014, 5(1), 60-80; doi:10.3390/atmos5010060
Received: 10 November 2013 / Revised: 12 December 2013 / Accepted: 18 December 2013 / Published: 13 January 2014
Cited by 1 | PDF Full-text (2236 KB) | HTML Full-text | XML Full-text
Abstract
Gaining knowledge on weather patterns, trends and the influence of their extremes on various crop production yields and quality continues to be a quest by scientists, agriculturists, and managers. Precise and timely information aids decision-making, which is widely accepted as intrinsically necessary for
[...] Read more.
Gaining knowledge on weather patterns, trends and the influence of their extremes on various crop production yields and quality continues to be a quest by scientists, agriculturists, and managers. Precise and timely information aids decision-making, which is widely accepted as intrinsically necessary for increased production and improved quality. Studies in this research domain, especially those related to data mining and interpretation are being carried out by the authors and their colleagues. Some of this work that relates to data definition, description, analysis, and modelling is described in this paper. This includes studies that have evaluated extreme dry/wet weather events against reported yield at different scales in general. They indicate the effects of weather extremes such as prolonged high temperatures, heavy rainfall, and severe wind gusts. Occurrences of these events are among the main weather extremes that impact on many crops worldwide. Wind gusts are difficult to anticipate due to their rapid manifestation and yet can have catastrophic effects on crops and buildings. This paper examines the use of data mining methods to reveal patterns in the weather conditions, such as time of the day, month of the year, wind direction, speed, and severity using a data set from a single location. Case study data is used to provide examples of how the methods used can elicit meaningful information and depict it in a fashion usable for management decision making. Historical weather data acquired between 2008 and 2012 has been used for this study from telemetry devices installed in a vineyard in the north of New Zealand. The results show that using data mining techniques and the local weather conditions, such as relative pressure, temperature, wind direction and speed recorded at irregular intervals, can produce new knowledge relating to wind gust patterns for vineyard management decision making. Full article
(This article belongs to the Special Issue Agrometeorology: From Scientific Analysis to Operational Application)
Open AccessArticle Water Vapor, Temperature and Wind Profiles within Maize Canopy under in-Field Rainwater Harvesting with Wide and Narrow Runoff Strips
Atmosphere 2013, 4(4), 428-444; doi:10.3390/atmos4040428
Received: 7 October 2013 / Revised: 6 November 2013 / Accepted: 13 November 2013 / Published: 29 November 2013
Cited by 1 | PDF Full-text (882 KB) | HTML Full-text | XML Full-text
Abstract
Micrometeorological measurements were used to evaluate heat and water vapor to describe the transpiration (Ev) and soil evaporation (Es) processes for wide and narrow runoff strips under in-field rainwater harvesting (IRWH) system. The resulting sigmoid-shaped water vapor (ea) in wide and
[...] Read more.
Micrometeorological measurements were used to evaluate heat and water vapor to describe the transpiration (Ev) and soil evaporation (Es) processes for wide and narrow runoff strips under in-field rainwater harvesting (IRWH) system. The resulting sigmoid-shaped water vapor (ea) in wide and narrow runoff strips varied in lower and upper parts of the maize canopy. In wide runoff strips, lapse conditions of ea extended from lowest measurement level (LP) to the upper middle section (MU) and inversion was apparent at the top of the canopy. The virtual potential temperature (θv) profile showed no difference in middle section, but the lower and upper portion (UP) had lower  in narrow, compared to wide, strips, and LP-UP changes of 0.6 K and 1.2 K were observed, respectively. The Ev and Es within the canopy increased the ea concentration as determined by the wind order of magnitude. The ea concentration reached peak at about 1.6 kPa at a range of wind speed value of 1.4–1.8 m∙s−1 and 2.0–2.4 m∙s−1 for wide and narrow treatments, respectively. The sparse maize canopy of the wide strips could supply more drying power of the air in response to atmospheric evaporative demand compared to narrow strips. This is due to the variation in air flow in wide and narrow runoff strips that change gradients in ea for evapotranspiration processes. Full article
(This article belongs to the Special Issue Agrometeorology: From Scientific Analysis to Operational Application)
Open AccessArticle Use of Traditional Weather/Climate Knowledge by Farmers in the South-Western Free State of South Africa: Agrometeorological Learning by Scientists
Atmosphere 2013, 4(4), 383-410; doi:10.3390/atmos4040383
Received: 3 September 2013 / Revised: 29 September 2013 / Accepted: 25 October 2013 / Published: 13 November 2013
Cited by 5 | PDF Full-text (347 KB) | HTML Full-text | XML Full-text
Abstract
The variety of natural indicators, associated with weather forecasting and climate prediction, as used by farmers in the South-Western Free State province of South Africa, is described. Most farmers in this area were not familiar with the application of weather forecasts/climate predictions for
[...] Read more.
The variety of natural indicators, associated with weather forecasting and climate prediction, as used by farmers in the South-Western Free State province of South Africa, is described. Most farmers in this area were not familiar with the application of weather forecasts/climate predictions for agricultural production, or with other science-based agrometeorological products. They relied almost fully on their experience and traditional knowledge for farming decision making. The indicators for traditional knowledge are demonstrated here in broad terms, relying on the stories and indications from observations and years of experience of their use by the farmers. These means of engagement with the natural environment, are skills not well understood by most scientists, but useful to the farmers. They range from the constellation of stars, animal behavior, cloud cover and type, blossoming of certain indigenous trees, appearance and disappearance of reptiles, to migration of bird species and many others. It is suggested that some short-term traditional forecasts/predictions may be successfully merged with science-based climate predictions. The traditional knowledge and its use, reported on in this paper, is what scientists learned from farmers. Berkes was right that scholars have wasted too much time and effort on a science versus traditional knowledge debate; we should reframe it instead as a science and traditional knowledge dialogue and partnership. The complications of a changing climate make this even more necessary. Full article
(This article belongs to the Special Issue Agrometeorology: From Scientific Analysis to Operational Application)
Open AccessArticle A Methodology to Infer Crop Yield Response to Climate Variability and Change Using Long-Term Observations
Atmosphere 2013, 4(4), 365-382; doi:10.3390/atmos4040365
Received: 31 August 2013 / Revised: 4 October 2013 / Accepted: 8 October 2013 / Published: 8 November 2013
Cited by 6 | PDF Full-text (846 KB) | HTML Full-text | XML Full-text
Abstract
A new methodology to extract crop yield response to climate variability and change from long-term crop yield observations is presented in this study. In contrast to the existing first-difference approach (FDA), the proposed methodology considers that the difference in value between crop yields
[...] Read more.
A new methodology to extract crop yield response to climate variability and change from long-term crop yield observations is presented in this study. In contrast to the existing first-difference approach (FDA), the proposed methodology considers that the difference in value between crop yields of two consecutive years reflects necessarily the contributions of climate and management conditions, especially at large spatial scales where both conditions may vary significantly from one year to the next. Our approach was applied to remove the effect of non-climatic factors on crop yield and, hence, to isolate the effect of the observed climate change between 1961 and 2006 on three widely crops grown in three Mediterranean countries—namely wheat, corn and potato—using national-level crop yield observations’ time-series. Obtained results show that the proposed methodology provides us with a ground basis to improve substantially our understanding of crop yield response to climate change at a scale that is relevant to large-scale estimations of agricultural production and to food security analyses; and therefore to reduce uncertainties in estimations of potential climate change effects on agricultural production. Furthermore, a comparison of outputs of our methodology and FDA outputs yielded a difference in terms of maize production in Egypt, for example, that exceeds the production of some neighbouring countries. Full article
(This article belongs to the Special Issue Agrometeorology: From Scientific Analysis to Operational Application)
Open AccessArticle Extension Agrometeorology as the Answer to Stakeholder Realities: Response Farming and the Consequences of Climate Change
Atmosphere 2013, 4(3), 237-253; doi:10.3390/atmos4030237
Received: 29 June 2013 / Accepted: 13 August 2013 / Published: 20 August 2013
Cited by 7 | PDF Full-text (231 KB) | HTML Full-text | XML Full-text
Abstract
Extension agrometeorology is applied in agrometeorological extension work to advice and serve farmers. In agrometeorology, response farming has been developed decades ago. Climate change complicates response farming, but does not alter it. This paper reports on new operationalization of that response farming in
[...] Read more.
Extension agrometeorology is applied in agrometeorological extension work to advice and serve farmers. In agrometeorology, response farming has been developed decades ago. Climate change complicates response farming, but does not alter it. This paper reports on new operationalization of that response farming in new educational commitments in agroclimatology. It is explained how “Science Field Shops” are an example in Indonesia. This was based on a thorough analysis of what climate change means for farmers in Asia. For Africa, we report on eying the training of agrometeorological extension trainers (“product intermediaries”) in West Africa, based on a thorough analysis of what climate change means for farmers in Africa. We also compare experience with reaching farmers in South Africa and farmer communities in Zambia, as new forms of supporting response farming, all under conditions of a changing climate. The paper, for the first time, connects results from four different programs the senior author is taking part in. There is first and foremost the need for training material to make it possible for the product intermediaries to participate in training extension intermediaries. This should, particularly, bring new knowledge to farmers. With what is presently available and with new approaches, climate extension should be developed and tested with farmers in ways that improve farmer preparedness and decision making. Full article
(This article belongs to the Special Issue Agrometeorology: From Scientific Analysis to Operational Application)
Open AccessArticle Spatio-Temporal Analysis of Droughts in Semi-Arid Regions by Using Meteorological Drought Indices
Atmosphere 2013, 4(2), 94-112; doi:10.3390/atmos4020094
Received: 27 February 2013 / Revised: 25 March 2013 / Accepted: 12 April 2013 / Published: 25 April 2013
Cited by 7 | PDF Full-text (1815 KB) | HTML Full-text | XML Full-text
Abstract
Six meteorological drought indices including percent of normal (PN), standardized precipitation index (SPI), China-Z index (CZI), modified CZI (MCZI), Z-Score (Z), the aridity index of E. de Martonne (I) are compared and evaluated for assessing spatio-temporal dynamics of droughts in six climatic regions
[...] Read more.
Six meteorological drought indices including percent of normal (PN), standardized precipitation index (SPI), China-Z index (CZI), modified CZI (MCZI), Z-Score (Z), the aridity index of E. de Martonne (I) are compared and evaluated for assessing spatio-temporal dynamics of droughts in six climatic regions in Iran. Results indicated that by consideration of the advantages and disadvantages of the mentioned drought predictors in Iran, the Z-Score, CZI and MCZI could be used as a good meteorological drought predictor. Depending on the month, the length of drought and climatic conditions of the region, they are an alternative to the SPI that has limitations both because of only a few available long term data series in Iran and its complex structure. Full article
(This article belongs to the Special Issue Agrometeorology: From Scientific Analysis to Operational Application)

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