Choice of foraging patches by hill sheep given different opportunities to seek shelter and food

2001 ◽  
Vol 73 (3) ◽  
pp. 563-570 ◽  
Author(s):  
A.J. Duncan ◽  
R.W. Mayes ◽  
S.A. Young ◽  
C.S. Lamb ◽  
P. MacEachern
Keyword(s):  
Weather Condition ◽  
Thermal Conditions ◽  
Cold Weather ◽  
Windward Side ◽  
Small Scale ◽  
Observation Data ◽  
Patch Choice ◽  
Patch Use ◽  
Sward Height ◽  
Thermoneutral Zone

AbstractA patch choice experiment was conducted in which sheep were offered choices between patches of upland pasture which differed in their sward height and degree of shelter from the wind. Experimental plots (48 m ✕ 4 m) were divided into 4 m ✕ 4 m patches. Alternate patches were mown in advance of the experiment to create nominal sward heights of 4 and 6 cm. Portable shelters were erected on the windward side of alternate patches to reduce wind speed on sheltered patches by half. The four treatment combinations used to test the influence of sward height, shelter and their interaction on patch use were: patchy swards with and without shelters and uniform swards with and without shelters. Five adult sheep per treatment were observed while grazing the plots for 6 h/day on five occasions (days) in autumn. Patch choice was measured by video observation and using a patch marker technique. On none of the observation days was the weather condition sufficiently severe that animals were outside their thermoneutral zone. There was a strong influence of sward height on patch use with sheep spending 0·382 of their time on short swards when patchy swards were offered compared with 0·503 of their time on equivalent areas when swards were uniform. Thermal conditions did not influence patch choice with sheep spending an average of 0·442 of their time on equivalent patches whether they were sheltered or not. There was no interaction between sward conditions and thermal conditions on the amount of time spent on different patches. Data from the patch marker method supported observation data. The results confirm that sheep are resilient to extremes of cold weather commonly occurring at temperate latitudes and suggest that thermal constraints have minimal influence on the small-scale foraging movements of sheep, as long as they remain within their thermoneutral zone.

scholarly journals A High-Resolution (20 m) Simulation of Nighttime Low Temperature Inducing Agricultural Crop Damage with the WRF–LES Modeling System

Atmosphere ◽  
2021 ◽  
Vol 12 (12) ◽  
pp. 1562
Author(s):  
Ilseok Noh ◽  
Seung-Jae Lee ◽  
Seoyeon Lee ◽  
Sun-Jae Kim ◽  
Sung-Don Yang
Keyword(s):  
High Resolution ◽  
Low Temperature ◽  
Crop Damage ◽  
Cold Weather ◽  
Temperature Management ◽  
Small Scale ◽  
Observation Data ◽  
Agricultural Crop ◽  
Near Surface ◽  
Farm Scale

In Korea, sudden cold weather in spring occurs repeatedly every year and causes severe damage to field crops and fruit trees. Detailed forecasting of the daily minimum or suddenly decreasing temperature, closely related to the local topography, has been required in the farmer community. High-resolution temperature models based on empirical formulas or statistical downscaling have fundamental limitations, making it difficult to perform biophysical application and mechanism explanation on small-scale complex terrains. Weather Research and Forecasting–Large Eddy Simulation (WRF–LES) can provide a dynamically and physically scientific tool to be easily applied for farm-scale numerical weather predictions. However, it has been applied mainly for urban areas and in convective boundary layer studies until now. In this study, 20 m resolution WRF–LES simulation of nighttime near-surface temperature and wind was performed for two cold spring weather events that induced significant crop damages in the apple production area and the results were verified with automatic weather station observation data. The study showed that the maximum mean bias of temperature was −1.75 °C and the minimum was −0.68 °C in the spring, while the root mean square error varied between 2.13 and 3.00 °C. The minimum temperature and its duration significantly affected the crop damage, and the WRF–LES could accurately simulate both features. This implies that the application of WRF–LES, with proper nest-domain configuration and harmonized physical options, to the prediction of nighttime frost in rural areas has promising feasibility for orchard- or farm-scale frost prevention and low-temperature management.

scholarly journals Low-Level Wind Shear Identification along the Glide Path at BCIA by the Pulsed Coherent Doppler Lidar

Atmosphere ◽  
2020 ◽  
Vol 12 (1) ◽  
pp. 50
Author(s):  
Hongwei Zhang ◽  
Xiaoying Liu ◽  
Qichao Wang ◽  
Jianjun Zhang ◽  
Zhiqiang He ◽  
...  
Keyword(s):  
Wind Shear ◽  
Vertical Direction ◽  
Small Scale ◽  
Observation Data ◽  
Doppler Lidar ◽  
Low Level ◽  
Glide Path ◽  
Coherent Doppler Lidar ◽  
Scanning Strategies ◽  
Meteorological Phenomenon

Low-level wind shear is usually to be a rapidly changing meteorological phenomenon that cannot be ignored in aviation security service by affecting the air speed of landing and take-off aircrafts. The lidar team in Ocean University of China (OUC) carried out the long term particular researches on the low-level wind shear identification and regional wind shear inducement search at Beijing Capital International Airport (BCIA) from 2015 to 2020 by operating several pulsed coherent Doppler lidar (PCDL) systems. On account of the improved glide path scanning strategy and virtual multiple wind anemometers based on the rang height indicator (RHI) modes, the small-scale meteorological phenomenon along the glide path and/or runway center line direction can be captured. In this paper, the device configuration, scanning strategies, and results of the observation data are proposed. The algorithms to identify the low-level wind shear based on the reconstructed headwind profiles data have been tested and proved based on the lidar data obtained from December 2018 to January 2019. High spatial resolution observation data at vertical direction are utilized to study the regional wind shear inducement at the 36L end of BCIA under strong northwest wind conditions.

scholarly journals Characteristics of Large-Scale Orographic Precipitation in a Linear Perspective

2011 ◽  
Vol 12 (1) ◽  
pp. 27-44 ◽  
Author(s):  
Michael Kunz
Keyword(s):  
Time Scales ◽  
Characteristic Time ◽  
Large Scale ◽  
Linear Perspective ◽  
Horizontal Wind ◽  
Small Scale ◽  
Orographic Precipitation ◽  
Observation Data ◽  
Horizontal Wind Speed ◽  
Precipitation Patterns

Abstract Simulations of orographic precipitation over the low mountain ranges of southwestern Germany and eastern France with two different physics-based linear precipitation models are presented. Both models are based on 3D airflow dynamics from linear theory and consider advection of condensed water and leeside drying. Sensitivity studies for idealized conditions and a real case study show that the amount and spatial distribution of orographic precipitation is strongly controlled by characteristic time scales for cloud and hydrometeor advection and background precipitation due to large-scale lifting. These parameters are estimated by adjusting the model results on a 2.5-km grid to observed precipitation patterns for a sample of 40 representative orography-dominated stratiform events (24 h) during a calibration period (1971–80). In general, the best results in terms of lowest rmse and bias are obtained for characteristic time scales of 1600 s and background precipitation of 0.4 mm h−1. Model simulations of a sample of 84 events during an application period (1981–2000) with fixed parameters demonstrate that both models are able to reproduce quantitatively precipitation patterns obtained from observations and reanalyses from a numerical model [Consortium for Small-scale Modeling (COSMO)]. Combining model results with observation data shows that heavy precipitations over mountains are restricted to situations with strong atmospheric forcings in terms of synoptic-scale lifting, horizontal wind speed, and moisture content.

Small and Full-Scale Modeling for the Application of Wall Solar Chimneys

2016 ◽  
Author(s):  
David Park ◽  
Francine Battaglia
Keyword(s):  
Natural Ventilation ◽  
Velocity Ratio ◽  
Thermal Conditions ◽  
Ambient Air ◽  
Full Scale ◽  
Scale Model ◽  
Small Scale ◽  
Solar Chimney ◽  
Window Position ◽  
Pi Theorem

A solar chimney is a natural ventilation technique that has a potential to save energy consumption as well as to maintain the air quality in the building. However, studies of buildings are often challenging due to their large sizes. The objective of the current study was to determine relationships between small- and full-scale solar chimney system models. In the current work, computational fluid dynamics (CFD) was utilized to model different building sizes with a solar chimney system, where the computational model was validated with the experimental study of Mathur et al. The window, which controls entrainment of ambient air, was also studied to determine the effects of window position. Correlations for average velocity ratio and non-dimensional temperature were consistent regardless of window position. Buckingham pi theorem was employed to further non-dimensionalize the important variables. Regression analysis was conducted to develop a mathematical model to predict a relationship among all of the variables, where the model agreed well with simulation results with an error of 2.33%. The study demonstrated that the flow and thermal conditions in larger buildings can be predicted from the small-scale model.

Development of a Predictive Equation for Ventilation in a Wall-Solar Chimney System

2017 ◽  
Vol 139 (3) ◽  
Author(s):  
David Park ◽  
Francine Battaglia
Keyword(s):  
Mathematical Model ◽  
Relative Error ◽  
Natural Ventilation ◽  
Thermal Conditions ◽  
Ambient Air ◽  
Maximum Error ◽  
Scale Model ◽  
Small Scale ◽  
Maximum Relative Error ◽  
Solar Chimney

A solar chimney is a natural ventilation technique that has potential to save energy consumption as well as to maintain the air quality in a building. However, studies of buildings are often challenging due to their large sizes. The objective of this study was to determine the relationships between small- and full-scale solar chimney system models. Computational fluid dynamics (CFD) was employed to model different building sizes with a wall-solar chimney utilizing a validated model. The window, which controls entrainment of ambient air for ventilation, was also studied to determine the effects of window position. A set of nondimensional parameters were identified to describe the important features of the chimney configuration, window configuration, temperature changes, and solar radiation. Regression analysis was employed to develop a mathematical model to predict velocity and air changes per hour, where the model agreed well with CFD results yielding a maximum relative error of 1.2% and with experiments for a maximum error of 3.1%. Additional wall-solar chimney data were tested using the mathematical model based on random conditions (e.g., geometry, solar intensity), and the overall relative error was less than 6%. The study demonstrated that the flow and thermal conditions in larger buildings can be predicted from the small-scale model, and that the newly developed mathematical equation can be used to predict ventilation conditions for a wall-solar chimney.

Global carbon and water exchange during drought reflects adaptation of rooting depth to climate and topography

2021 ◽  
Author(s):  
Benjamin Stocker ◽  
Shersingh Tumber-Davila ◽  
Alexandra Konings ◽  
Rob Jackson
Keyword(s):  
Remote Sensing ◽  
Snow Accumulation ◽  
Rooting Depth ◽  
Small Scale ◽  
Observation Data ◽  
Systematic Bias ◽  
Thermal Infrared Remote Sensing ◽  
Near Surface ◽  
Rooting Zone ◽  
Zone Water

<p>The rooting zone water storage capacity (S) defines the total amount of water available to plants for transpiration during rain-free periods. Thereby, S determines the sensitivity of carbon and water exchanges between the land surface and the atmosphere, controls the sensitivity of ecosystem functioning to progressive drought conditions, and mediates feedbacks between soil moisture and near-surface air temperatures. While being a central quantity for water-carbon-climate coupling, S is inherently difficult to observe. Notwithstanding scarcity of observations, terrestrial biosphere and Earth system models rely on the specification of S either directly or indirectly through assuming plant rooting depth.</p><p>Here, we model S based on the assumption that plants size their rooting depth to maintain function under the expected maximum cumulative water deficit (CWD), occurring with a return period of 40 years (CWD<sub>X40</sub>), following Gao et al. (2014). CWD<sub>X40</sub> is “translated” into a rooting depth by accounting for the soil texture. CWD is defined as the cumulative evapotranspiration (ET) minus precipitation, where ET is estimated based on thermal infrared remote sensing (ALEXI-ET), and precipitation is from WATCH-WFDEI, modified by accounting for snow accumulation and melt. In contrast to other satellite remote sensing-based ET products, ALEXI-ET makes no a priori assumption about S and, as our evaluation shows, exhibits no systematic bias with increasing CWD. It thus provides a robust observation of surface water loss and enables estimation of S with global coverage at 0.05° (~5 km) resolution.</p><p>Modelled S and its variations across biomes is largely consistent with observed rooting depth, provided as ecosystem-level maximum estimates by Schenk et al. (2002), and a recently compiled comprehensive plant-level dataset. In spite of the general agreement of modelled and observed rooting depth across large climatic gradients, comparisons between local observations and global model predictions are mired by a scale mismatch that is particularly relevant for plant rooting depth, for which the small-scale topographical setting and hydrological conditions, in particular the water table depth, pose strong controls.</p><p>To resolve this limitation, we investigate the sensitivity of photosynthesis (estimated by sun-induced fluorescence, SIF), and of the evaporative fraction (EF, defined as ET over net radiation) to CWD. By employing first principles for the constraint of rooting zone water availability on ET and photosynthesis, it can be derived how their sensitivity to the increasing CWD relates to S. We make use of this relationship to provide an alternative and independent estimate of S (S<sub>dSIF</sub> and S<sub>dEF</sub>), informed by Earth observation data, to which S, modelled using CWD<sub>X40</sub>, can be compared. Our comparison reveals a strong correlation (R<sup>2</sup>=0.54) and tight consistency in magnitude between the two approaches for estimating S. </p><p>Our analysis suggests adaptation of plant structure to prevailing climatic conditions and drought regimes across the globe and at catchment scale and demonstrates its implications for land-atmosphere exchange. Our global high-resolution mapping of S reveals contrasts between plant growth forms (grasslands vs. forests) and a discrepant importance across the landscape of plants’ access to water stored at depth, and enables an observation-informed specification of S in global models.</p>

scholarly journals Performance and applicability of a 2.5-D ice-flow model in the vicinity of a dome

2016 ◽  
Vol 9 (7) ◽  
pp. 2301-2313 ◽  
Author(s):  
Olivier Passalacqua ◽  
Olivier Gagliardini ◽  
Frédéric Parrenin ◽  
Joe Todd ◽  
Fabien Gillet-Chaulet ◽  
...  
Keyword(s):  
Flow Model ◽  
Three Dimensional ◽  
Thermal Conditions ◽  
Observation Data ◽  
Flow Tube ◽  
Ice Flow ◽  
Linear Temperature ◽  
Ice Surface ◽  
Scanning Window ◽  
D Model

Abstract. Three-dimensional ice flow modelling requires a large number of computing resources and observation data, such that 2-D simulations are often preferable. However, when there is significant lateral divergence, this must be accounted for (2.5-D models), and a flow tube is considered (volume between two horizontal flowlines). In the absence of velocity observations, this flow tube can be derived assuming that the flowlines follow the steepest slope of the surface, under a few flow assumptions. This method typically consists of scanning a digital elevation model (DEM) with a moving window and computing the curvature at the centre of this window. The ability of the 2.5-D models to account properly for a 3-D state of strain and stress has not clearly been established, nor their sensitivity to the size of the scanning window and to the geometry of the ice surface, for example in the cases of sharp ridges. Here, we study the applicability of a 2.5-D ice flow model around a dome, typical of the East Antarctic plateau conditions. A twin experiment is carried out, comparing 3-D and 2.5-D computed velocities, on three dome geometries, for several scanning windows and thermal conditions. The chosen scanning window used to evaluate the ice surface curvature should be comparable to the typical radius of this curvature. For isothermal ice, the error made by the 2.5-D model is in the range 0–10 % for weakly diverging flows, but is 2 or 3 times higher for highly diverging flows and could lead to a non-physical ice surface at the dome. For non-isothermal ice, assuming a linear temperature profile, the presence of a sharp ridge makes the 2.5-D velocity field unrealistic. In such cases, the basal ice is warmer and more easily laterally strained than the upper one, the walls of the flow tube are not vertical, and the assumptions of the 2.5-D model are no longer valid.

In-Situ Validation of Water Quality Algorithms and Monitoring of Irish Lakes using Sentinel 2 Imagery

2020 ◽  
Author(s):  
Sita Karki ◽  
Kevin French ◽  
Valerie McCarthy ◽  
Jennifer Hanafin ◽  
Eleanor Jennings ◽  
...  
Keyword(s):  
Water Quality ◽  
Time Window ◽  
Atmospheric Correction ◽  
European Space Agency ◽  
Weather Condition ◽  
Water Bodies ◽  
Observation Data ◽  
Field Validation ◽  
Field Samples ◽  
Sentinel 2

<p>Through Remote Sensing of Irish Surface Water (INFER) project, we are validating the algorithms to measure the  water quality using Sentinel 2 imagery, which comprises of two European Space Agency (ESA) terrestrial satellites with combined temporal resolution of 5 days. The project is focused on selection of optimal algorithms that will be applicable in Irish context in relation to the high cloud cover and relatively small sizes of the water bodies. The current procedure entails collection of reflectance data from the lakes during the Sentinel overpass as it helps to identify the correct atmospheric correction algorithm. Field radiometry tasks were carried out using TRIOS RAMSES radiometers. Standard field procedures were employed for acquiring glint free reflectance from the water bodies.</p><p>Historical data collected from the 11 lakes, which had field bathymetry survey data, were analysed in order to determine the influence of environmental conditions on the quality of samples. Based on the analysis, recommendations to collect field samples from areas deeper than 10 m and 30 m away from the shoreline were provided in order to avoid the reflectance from the bottom and the surrounding topography. A site selection process was undertaken during the spring of 2019 to shortlist appropriate sites for field validation of satellite-derived products. A total of fifteen lakes were identified for field validation based on several criteria so as to ensure lakes with varying size, depth, trophic status and Water Framework Directive (WFD) status . In addition, a timetable for proposed sampling was established by drawing up a timetable of satellite passes starting from summer of 2019. C2RCC and Acolite processors are being used to compute the chlorophyll and turbidity from identified lakes. Considering the fast changing weather condition of Ireland, it was difficult to obtain the exact overlap between the sentinel overpass and the field sampling. In order to address this issue, the field samples collected within 10 days from the sensor overpass were considered for the field validation. Study of the satellite derived water chemistry data showed that the data collected outside of that time window may not represent the natural fluctuation that occurs in the water bodies.</p><p>The end product of this project is the web platform with the access to Sentinel 2 MSI data products where users can visualize the water quality products for Ireland. This platform will promote the use of earth observation data for inland water quality monitoring and would enable sustainable utilization of the water resources.</p>

Influence of Cold Weather on Compressive Strength in High Performance with Silica Fume

2014 ◽  
Vol 627 ◽  
pp. 445-448 ◽  
Author(s):  
Young Il Jang ◽  
Wan Shin Park ◽  
Sun Woong Kim ◽  
Song Hui Yun ◽  
Hyun Do Yun ◽  
...  
Keyword(s):  
Compressive Strength ◽  
Silica Fume ◽  
High Performance ◽  
Mechanical Performance ◽  
High Performance Concrete ◽  
Weather Condition ◽  
Weather Conditions ◽  
Cold Weather ◽  
Binder Ratio ◽  
Hot Weather

This paper addresses the influence of cold weather on the compressive strength of high performance concrete with silica fume under different curing days. Test variables of this study are weather condition (5°C, -5°C and-15°C) and different curing days (7days and 28 days). In this work, the specimen was designed a water-binder ratio of 0.34. One batches of concrete were prepared for each mixing hour, and the compressive strength of cylindrical concrete specimens was measured after 7 and 28 days. Test results for concrete compressive strength show that the concrete’s best mechanical performance occurred when there was the least difference between ambient temperature and concrete temperature, that is, during the later hours of the day in hot weather conditions.

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