Estimating wetness duration on maize ears from meteorological observations

1998 ◽  
Vol 78 (1) ◽  
pp. 149-154 ◽  
Author(s):  
P. S. Rao ◽  
T. J. Gillespie ◽  
A. W. Schaafsma
Keyword(s):  
Fungal Infections ◽  
Meteorological Data ◽  
Physical Models ◽  
Dew Point ◽  
Spatial And Temporal Variability ◽  
Threshold Models ◽  
Moderate Degree ◽  
Weather Station ◽  
Surface Wetness ◽  
Energy Balance Approach

The onset and cessation of surface wetness on maize ears were simulated with six models, using hourly meteorological data, to examine the linkage between wetness duration and possible forecasting of fungal infections that produce mycotoxins. Two threshold models (using relative humidity and dew point temperature), one regression model (using humidity and wind speed), and three physical models based on the energy balance approach, were compared. Also, spatial and temporal variability in wetness duration was measured and simulated at three sites located at distances up to 29 km from a central weather station. The estimated wetness values were compared with observations from cylindrical wetness sensors placed near ear level in maize canopies. The results relate to potential mycotoxin warning systems and indicate that threshold models can provide reasonable estimates of ear wetness duration in this region, that a comprehensive physical model can give superior estimates, and that wetness estimates made from a central weather station data can be extended to nearby crop fields with a moderate degree of confidence. Key words: epidemiology, mycotoxins, surface wetness models

scholarly journals Estimating leaf wetness duration over turfgrass, and in a 'Niagara Rosada' vineyard, in a subtropical environment

2008 ◽  
Vol 65 (spe) ◽  
pp. 10-17 ◽  
Author(s):  
Jorge Lulu ◽  
Paulo Cesar Sentelhas ◽  
Mário José Pedro Júnior ◽  
José Ricardo Macedo Pezzopane ◽  
Gabriel Constantino Blain
Keyword(s):  
High Accuracy ◽  
Training System ◽  
Dew Point ◽  
Classification And Regression Tree ◽  
Leaf Wetness ◽  
Good Precision ◽  
Weather Station ◽  
Leaf Wetness Duration ◽  
Confidence Index ◽  
Niagara Rosada

Leaf wetness duration (LWD) is a key parameter in agrometeorology because it is related to plant disease occurrence. As LWD is seldomly measured in a standard weather station it must be estimated to run warning systems for schedule chemical disease control. The objective of the present study was to estimate LWD over turfgrass considering different models with data from a standard weather station, and to evaluate the correlation between estimated LWD over turfgrass and LWD measured in a 'Niagara Rosada' vineyard, cultivated in a hedgerow training system, in Jundiaí, São Paulo State, Brazil. The wetness sensors inside the vineyard were located at the top of the plants, deployed at an inclination angle of 45º and oriented southwest, with three replications. The methods used to estimate LWD were: number of hours with relative humidity above 90% (NHRH > 90%), dew point depression (DPD), classification and regression tree (CART) and Penman-Monteith (PM). The CART model had the best performance to estimate LWD over turfgrass, with a good precision (R² = 0.82) and a high accuracy (d = 0.94), resulting in a good confidence index (c = 0.85). The results from this model also presented a good correlation with measured LWD inside the vineyard, with a good precision (R² = 0.87) and a high accuracy (d = 0.96), resulting in a high confidence index (c = 0.93), showing that LWD in a 'Niagara Rosada' vineyard can be estimated with data from a standard weather station.

scholarly journals Modelling the mass balance of northwest Spitsbergen glaciers and responses to climate change

1997 ◽  
Vol 24 ◽  
pp. 203-210 ◽  
Author(s):  
Kevin M. Fleming ◽  
Julian A. Dowdeswell ◽  
Johannes Oerlemans
Keyword(s):  
Climate Change ◽  
Mass Balance ◽  
Meteorological Data ◽  
Balance Model ◽  
Greenhouse Warming ◽  
Weather Station ◽  
Mass Balances ◽  
Area Distribution ◽  
Sensitivity Tests ◽  
Precipitation Increase

An energy-balance model is used to calculate mass balance and equilibrium-line altitudes (ELAs) on two northwest Spitsbergen glaciers, Austre Brøggerbreen and Midre Lovénbreen, whose mass balances are at present negative, and for which greater than 20 year records of mass-balance data are available. The model takes meteorological data, ice-mass area distribution with altitude, and solar radiation as inputs. Modelling uses mean daily meteorological data from a nearby weather station, adjusted for altitude. Average net balances modelled for 1980–89 using models tuned to the decade’s average were –0.44 and –0.47 m w.e. for Lovénbreen and Brøggerbreen, respectively, compared with the measured averages of –0.27 and –0.36 m. Sensitivity tests on glacier response to greenhouse warming predict a net balance change of –0.61 m year–1 per °C temperature rise relative to today, and a rise in ELA of 90 m °C–1. Modelling of Little lee Age conditions in Spitsbergen suggests that a 0.6°C cooling or a precipitation increase of 23% would yield zero net mass balance for Lovénbreen and that further cooling would increase net balance by 0.30 m year–1 °C–1. Set in the context of similar modelling of southern Norwegian, Alpine and Greenland ice masses, these results support the suggestion that glaciers with a maritime influence (i.e. higher accumulation) are most sensitive to climate change, implying a gradient towards decreasing sensitivity as accumulation decreases eastward and with altitude in Svalbard.

scholarly journals Impact Assessment for Building Energy Models Using Observed vs. Third-Party Weather Data Sets

2020 ◽  
Vol 12 (17) ◽  
pp. 6788 ◽  
Author(s):  
Eva Lucas Segarra ◽  
Germán Ramos Ruiz ◽  
Vicente Gutiérrez González ◽  
Antonis Peppas ◽  
Carlos Fernández Bandera
Keyword(s):  
Energy Demand ◽  
Meteorological Data ◽  
Building Energy ◽  
Third Party ◽  
Weather Data ◽  
Data Sets ◽  
Weather Station ◽  
Energy Models ◽  
The Impact ◽  
Energy Strategies

The use of building energy models (BEMs) is becoming increasingly widespread for assessing the suitability of energy strategies in building environments. The accuracy of the results depends not only on the fit of the energy model used, but also on the required external files, and the weather file is one of the most important. One of the sources for obtaining meteorological data for a certain period of time is through an on-site weather station; however, this is not always available due to the high costs and maintenance. This paper shows a methodology to analyze the impact on the simulation results when using an on-site weather station and the weather data calculated by a third-party provider with the purpose of studying if the data provided by the third-party can be used instead of the measured weather data. The methodology consists of three comparison analyses: weather data, energy demand, and indoor temperature. It is applied to four actual test sites located in three different locations. The energy study is analyzed at six different temporal resolutions in order to quantify how the variation in the energy demand increases as the time resolution decreases. The results showed differences up to 38% between annual and hourly time resolutions. Thanks to a sensitivity analysis, the influence of each weather parameter on the energy demand is studied, and which sensors are worth installing in an on-site weather station are determined. In these test sites, the wind speed and outdoor temperature were the most influential weather parameters.

scholarly journals Soil, snow, weather, and sub-surface storage data from a mountain catchment in the rain–snow transition zone

2013 ◽  
Vol 6 (2) ◽  
pp. 811-835 ◽  
Author(s):  
P. R. Kormos ◽  
D. Marks ◽  
C. J. Williams ◽  
H. P. Marshall ◽  
P. Aishlin ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Transition Zone ◽  
Soil Texture ◽  
Soil Depth ◽  
Meteorological Data ◽  
Dew Point ◽  
Soil Profiles ◽  
Data Set ◽  
Hydrologic Condition ◽  
Wide Range

Abstract. A comprehensive hydroclimatic data set is presented for the 2011 water year to improve understanding of hydrologic processes in the rain-snow transition zone. This type of dataset is extremely rare in scientific literature because of the quality and quantity of soil depth, soil texture, soil moisture, and soil temperature data. Standard meteorological and snow cover data for the entire 2011 water year are included, which include several rain-on-snow events. Surface soil textures and soil depths from 57 points are presented as well as soil texture profiles from 14 points. Meteorological data include continuous hourly shielded, unshielded, and wind corrected precipitation, wind speed, air temperature, relative humidity, dew point temperature, and incoming solar and thermal radiation data. Sub-surface data included are hourly soil moisture data from multiple depths from 7 soil profiles within the catchment, and soil temperatures from multiple depths from 2 soil profiles. Hydrologic response data include hourly stream discharge from the catchment outlet weir, continuous snow depths from one location, intermittent snow depths from 5 locations, and snow depth and density data from ten weekly snow surveys. Though it represents only a single water year, the presentation of both above and below ground hydrologic condition makes it one of the most detailed and complete hydro-climatic datasets from the climatically sensitive rain-snow transition zone for a wide range of modeling and descriptive studies. Data are available at doi:10.1594/PANGAEA.819837.

Comparison between forecasts of reference evapotranspiration and ETo values calculated using data from different climatic conditions

2020 ◽  
Author(s):  
Ghaieth Ben Hamouda ◽  
Francesca Ventura ◽  
Daniele Zaccaria ◽  
Khaled M. Bali ◽  
Richard L. Snyder
Keyword(s):  
Reference Evapotranspiration ◽  
Irrigation Management ◽  
Climatic Conditions ◽  
Physical Models ◽  
Dew Point ◽  
Water Losses ◽  
Plant Canopies ◽  
Crucial Component ◽  
And Performance ◽  
Using Data

<p>Evapotranspiration is the transfer of water from the earth's surface to the atmosphere. It comprises the sum of water losses to atmosphere due to the processes of evaporation of moisture from soil, water bodies and wet plant canopies, and the transpiration of water from plants. Forecasts of this crucial component of the hydrologic cycle can be very valuable for growers, farm managers, irrigation practitioners, water resource planners and managers, and reservoir operators for their planning, allocation, delivery and scheduling decisions, as well as to hydrologic scientists for research purposes. Verifying the reliability of models’ forecasts is among the critical tasks for development and performance evaluation of physical models. In fact, the verification allows understanding the models’ behavior, and evaluating their applicability and dependability. The US National Weather Service (NWS) has released a product that provides forecasts of reference evapotranspiration (FRET) at 2.5-km grid resolution for the entire continental US. In this study, a comparison is made between ETo estimates from FRET and ETo values calculated by the California Irrigation Management Information System (CIMIS) for 68 days during summer 2019. Both the FRET forecasts and ETo values were obtained from NWS and CIMIS, respectively, on the basis of 15 CIMIS locations that are representative of different climatic conditions in California. In addition, air temperature, dew point temperature, relative humidity, wind speed, and vapor pressure deficit (VPD) data were also collected/calculated from the NWS and CIMIS websites to analyze the sensitivity of FRET forecasts to predictions of these parameters. All FRET forecasts were performed with timescales of 1, 3, 5 and 7 days. Statistical indices were calculated to assess the dependability of FRET values. They showed a good correlation of the FRET model outputs with CIMIS ETo data, with some differences depending on the climatic characteristics of selected weather stations’ locations, suggesting that FRET data could be valuable for anticipating near-future water demand and improve irrigation management in California.</p>

Realization and use of a digital portable Weather Station - An integrated example of technological applications of low cost and high quality professional hardware platforms for innovative laboratory teaching in the classroom

2020 ◽  
Author(s):  
Pietro Crimi
Keyword(s):  
Communication Networks ◽  
Meteorological Data ◽  
Low Cost ◽  
Online Communication ◽  
Lower Troposphere ◽  
Mobile Systems ◽  
Advanced Technology ◽  
Weather Data ◽  
Weather Station ◽  
Laboratory Teaching

<p>As part of the innovation in the laboratory teaching of Natural Sciences, an experimental path of learning of Atmospheric Sciences and Microclimates is proposed in continuation and evolution, which was presented with a poster at the GIFT workshop 2017, an experience of project, construction and use of a mobile and portable Weather Station with digital features.By identifying the main parameters that measure the physical characteristics of the lower troposphere and the corresponding sensors responsible for detecting instantaneous weather data, a project was developed for the construction of a mini weather station with an assembly system of modular electronic components in "open source" , such as those of the "Arduino" platform (series of electronic boards equipped with a microcontroller). In this way, a device for controlling the main weather parameters (temperature, atmospheric pressure, relative humidity, ...) in real time in any part of the territory was achieved relatively quickly and easily. The hardware platform in pre-assembled version, with specific microcontrollers and USB interface for connections to the most advanced computer devices, together with the sensors, which can be acquired through the online network, allow you to create a completely inexpensive but absolutely professional, effective and efficient weather mobile system as well as easily transportable in various external and internal environments. The subsequent data collection, through visualization with advanced technology display and fast and online communication networks, by means of applications for mobile systems (tablets and smartphones), integrated by field observations, define the instantaneous weather and to process meteorological data in statistical terms with simple operations and graphs.</p>

A first attempt to model an Artificial Ice Reservoir (Ice Stupa) using a simple energy balance approach

2020 ◽  
Author(s):  
Suryanarayanan Balasubramanian ◽  
Martin Hoelzle ◽  
Michael Lehning ◽  
Sonam Wangchuk ◽  
Johannes Oerlemans ◽  
...  
Keyword(s):  
Water Mass ◽  
Meteorological Data ◽  
Physical Processes ◽  
Discharge Data ◽  
One Dimensional ◽  
Vapour Diffusion ◽  
Alternate Model ◽  
Energy Balance Approach ◽  
Fresh Water Resource ◽  
Model Scenarios

<div> <div> <p>Artificial Ice Reservoirs (AIRs, also called icestupas) have been successful in storing water during winter and releasing the water during spring and summer. Therefore, they can be seen as a vital fresh water resource for irrigation in dry environments. Many different forms of AIRs do exist and not many studies have tried to model theses ice structures.<br>We will present simulations of the most important physical processes that causes the formation and melt of AIRs using one dimensional equations governing the heat transfer, vapour diffusion and water transport of a phase changing water mass. For validation, an AIR was constructed in Schwarzsee region in the Canton of Fribourg, Switzerland. Meteorological data in conjunction with fountain discharge data was measured. According to the model, the Schwarzsee AIR was able to store and discharge 850 litres or  3.7 percent of all the water sprayed over a duration of 41 days. Alternate model scenarios will also be presented to show how this freezing efficiency can be increased.</p> </div> </div>

Glaciers in the High Arctic and recent environmental change

1995 ◽  
Vol 352 (1699) ◽  
pp. 321-334 ◽  
Keyword(s):  
Mass Balance ◽  
Climate Warming ◽  
Meteorological Data ◽  
Ice Cores ◽  
High Arctic ◽  
Ice Age ◽  
Geological Evidence ◽  
Recent Climate ◽  
Severnaya Zemlya ◽  
Energy Balance Approach

High Arctic climate change over the last few hundred years includes the relatively cool Little Ice Age (LIA), followed by warming over the last hundred years or so. Meteorological data from the Eurasian High Arctic (Svalbard, Franz Josef Land, Severnaya Zemlya) and Canadian High Arctic islands are scarce before the mid-20th century, but longer records from Svalbard and Greenland show warming from about 1910-1920. Logs of Royal Navy ships in the Canadian Northwest Passage in the 1850s indicate temperatures cooler by 1-2.5 °C during the LIA. Other evidence of recent trends in High Arctic temperatures and precipitation is derived from ice cores, which show cooler temperatures (by 2-3 °C) for several hundred years before 1900, with high interdecadal variability. The proportion of melt layers in ice cores has also risen over the last 70-130 years, indicating warming. There is widespread geological evidence of glacier retreat in the High Arctic since about the turn of the century linked to the end of the LIA. An exception is the rapid advance of some surge-type ice masses. Mass balance measurements on ice caps in Arctic Canada, Svalbard and Severnaya Zemlya since 1950 show either negative or near-zero net balances, suggesting glacier response to recent climate warming. Glacier-climate links are modelled using an energy balance approach to predict glacier response to possible future climate warming, and cooler LIA temperatures. For Spitsbergen glaciers, a negative shift in mass balance of about 0.5 m a -1 is predicted for a 1 °C warming. A cooling of about 0.6 °C, or a 23% precipitation increase, would produce an approximately zero net mass balance. A ‘greenhouse-induced’ warming of 1 °C in the High Arctic is predicted to produce a global sea-level rise of 0.063 mm a -1 from ice cap melting.

scholarly journals Determining the Optimal Spatial Distribution of Weather Station Networks for Hydrological Modeling Purposes Using RCM Datasets: An Experimental Approach

2014 ◽  
Vol 15 (1) ◽  
pp. 517-526 ◽  
Author(s):  
Richard Arsenault ◽  
François Brissette
Keyword(s):  
River Basin ◽  
Optimization Algorithm ◽  
Water Resource Management ◽  
Hydrological Modeling ◽  
Climate Model ◽  
Meteorological Data ◽  
High Density ◽  
Limiting Factor ◽  
Weather Station ◽  
Weather Stations

Abstract In many hydrological studies, the main limiting factor in model performance is the low meteorological data quality. In some cases, no meteorological records even exist. Installing weather stations becomes a necessity in these areas when water resource management becomes an issue. The objective of this study is to propose a new experimental and exploratory method for determining the optimal density of a weather station network when being used for long-term hydrological modeling. Data from the Canadian Regional Climate Model at 15-km resolution (CRCM15) were used to create a virtual network of stations with long and complete series of meteorological data over the Toulnustouc River basin in central Québec, Canada. The weather stations to be fed to HSAMI, Hydro-Québec's lumped rainfall–runoff hydrological model, were selected in order to minimize the number of stations while maintaining the best hydrological performance possible using a multi-objective optimization algorithm. It was shown that the number of stations making up the network on the Toulnustouc River basin should be at least two but not higher than four. If the stations are positioned optimally, there is little to no gain to be made with a denser network. The optimization algorithm clearly identified that combinations of two or three stations can result in better hydrological performance than if a high-density network was fed to the model. Thus, the major conclusion of this study is that if weather stations are positioned at optimal locations, a very few number of them are required to model runoff with as good as or better performance than when a high-density network is used.

scholarly journals High-Resolution Monthly Precipitation Fields (1913–2015) over a Complex Mountain Area Centred on the Forni Valley (Central Italian Alps)

2018 ◽  
Vol 2018 ◽  
pp. 1-17 ◽  
Author(s):  
Golzio Alessio ◽  
Crespi Alice ◽  
Irene Maria Bollati ◽  
Senese Antonella ◽  
Guglielmina Adele Diolaiuti ◽  
...  
Keyword(s):  
High Resolution ◽  
Meteorological Data ◽  
Monthly Precipitation ◽  
Weather Station ◽  
Italian Alps ◽  
Mountain Area ◽  
Mountain Environments ◽  
Set Up ◽  
Precipitation Records ◽  
Good Agreement

Mountain environments are extremely influenced by climate change but are also often affected by the lack of long and high-quality meteorological data, especially in glaciated areas, which limits the ability to investigate the acting processes at local scale. For this reason, we checked a method to reconstruct high-resolution spatial distribution and temporal evolution of precipitation. The study area is centred on the Forni Glacier area (Central Italian Alps), where an automatic weather station is present since 2005. We set up a model based on monthly homogenised precipitation series and we spatialised climatologies and anomalies on a 30-arc-second-resolution DEM, using Local Weighted Linear Regression (LWLR) and Regression Kriging (RK) of precipitation versus elevation, in order to test the most suitable approach for this complex terrain area. The comparison shows that LWLR has a better reconstruction ability for winter while RK slightly prevails during summer. The results of precipitation spatialisation were compared with station observations and with data collected at the weather station on Forni Glacier, which were not used to calibrate the model. A very good agreement between observed and modelled precipitation records was pointed out for most station sites. The agreement is lower, but encouraging, for Forni Glacier station data.

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