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What is Weather?

What is Weather?

Hot Weather Concreting

Hot Weather Concreting

Concreting at elevated temperatures accelerates the hydration process, leading to quicker setting but potentially reducing the long-term strength of the concrete structure. Additionally, low air humidity fosters rapid moisture loss from the concrete, resulting in reduced workability, pronounced plastic shrinkage, and a higher likelihood of crazing.
Mitigating the heat increase in concrete can be economically achieved by shading aggregate stockpiles to prevent heating from solar radiation,...

Cold Weather Concreting

Cold Weather Concreting

When freshly poured concrete is exposed to freezing temperatures before it has set, the water within the concrete can freeze. This expansion disrupts the setting process, delays chemical reactions necessary for hardening, and increases the volume of pores within the hardened concrete, which weakens its overall structure. If the concrete manages to reach an appreciable strength before it freezes, the damage can be somewhat mitigated.
To counteract the negative impacts of cold weather, ensuring...

Predicting Molecular Geometry

Predicting Molecular Geometry

VSEPR Theory for Determination of Electron Pair Geometries

Prediction Intervals

Prediction Intervals

The interval estimate of any variable is known as the prediction interval. It helps decide if a point estimate is dependable.
However, the point estimate is most likely not the exact value of the population parameter, but close to it. After calculating point estimates, we construct interval estimates, called confidence intervals or prediction intervals. This prediction interval comprises a range of values unlike the point estimate and is a better predictor of the observed sample value, y.

Masonry in Cold and Hot Weather Conditions

Masonry in Cold and Hot Weather Conditions

In cold weather, masonry construction requires specific precautions to ensure mortar does not freeze before curing, as this can significantly weaken its strength and watertightness. Mortar temperature should be maintained between 60°F and 80°F to support proper hydration and curing. Below 40°F, mortar water must be heated, but should not exceed 120°F as high temperatures can reduce mortar's compressive and bond strength.
Other key practices include keeping masonry units...

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Related Experiment Video

Updated: Jan 30, 2026

Untargeted Liquid Chromatography-Mass Spectrometry-Based Metabolomics Analysis of Wheat Grain

Untargeted Liquid Chromatography-Mass Spectrometry-Based Metabolomics Analysis of Wheat Grain

Published on: March 13, 2020

A Threshold-Based Weather Model for Predicting Stripe Rust Infection in Winter Wheat.

Moussa El Jarroudi¹, Louis Kouadio², Clive H Bock³

¹Department of Environmental Sciences and Management, Université de Liège, Arlon, B-6700 Belgium.

|January 26, 2019

Summary

A new weather model predicts wheat stripe rust (Puccinia striiformis f. sp. tritici) epidemics. It identifies optimal conditions like high humidity and specific temperatures, aiding fungicide application timing.

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Last Updated: Jan 30, 2026

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Published on: November 3, 2011

Area of Science:

Plant Pathology
Agricultural Meteorology
Crop Science

Background:

Wheat stripe rust, caused by Puccinia striiformis f. sp. tritici, poses a significant global threat to wheat production.
Favorable environmental conditions can lead to substantial yield losses in wheat crops due to stripe rust infections.

Purpose of the Study:

To develop a threshold-based weather model for predicting wheat stripe rust epidemics.
To identify critical weather variables and their optimal ranges for wheat stripe rust development.

Main Methods:

Utilized meteorological data from 1999-2015 across three Luxembourg wheat-growing sites.
Employed Monte Carlo simulations to characterize favorable weather conditions using the Dennis model.
Developed a predictive model based on optimal combinations of temperature, relative humidity, and rainfall during the May-June infection period.

Main Results:

Identified optimal conditions for stripe rust development: relative humidity >92%, 4°C < temperature < 16°C for ≥4 continuous hours, and rainfall ≤0.1 mm.
The model achieved high prediction accuracy with probabilities of detection ≥0.90 and false alarm ratios ≤0.38.
Critical success indexes ranged from 0.63 to 1, indicating robust predictive performance.

Conclusions:

The developed threshold-based weather model accurately predicts wheat stripe rust infection events.
This model can be integrated into operational warning systems to guide timely fungicide applications.
The methodology shows potential for application to other fungal diseases and geographical locations.