Modélisation de la coulée de l'érable à sucre (Acersaccharum Marsh.) à partir d'éléments météorologiques

1980 ◽  
Vol 10 (2) ◽  
pp. 152-157 ◽  
Author(s):  
André P. Plamondon ◽  
Pierre Y. Bernier
Keyword(s):  
Wind Speed ◽  
Air Temperature ◽  
Sap Flow ◽  
Sugar Maple ◽  
Climatic Conditions ◽  
Strongly Correlated ◽  
Efficiency Function ◽  
Global Efficiency ◽  
Daily Rate ◽  
Flow Cycle

It has already been shown that a relation exists between the daily rate of spring sap flow and the twig temperature of sugar maple. The authors first develop a method to calculate this temperature from radiation, wind speed, and air temperature. For each sap flow cycle, the values of four factors controlling the phenomenon are determined: the number of hours and degree-hours below 0 °C and above 0 °C. Each factor is then converted into an efficiency function. The combination of the four functions gives the global efficiency of the climatic conditions for each sap flow cycle. The flows calculated from the global efficiency are strongly correlated (r = 0.94) with the measured ones.

Effets des coupes d'éclaircie et des variations climatiques interannuelles sur la production et la teneur en sucre de la sève d'une érablière

1995 ◽  
Vol 25 (11) ◽  
pp. 1815-1820 ◽  
Author(s):  
David Pothier
Keyword(s):  
Sap Flow ◽  
Sugar Maple ◽  
Basal Area ◽  
Temperature Fluctuations ◽  
Winter Precipitation ◽  
Climatic Conditions ◽  
Sugar Concentration ◽  
Meteorological Variables ◽  
Strongly Correlated

A study was initiated in 1975 on a sugar maple (Acersaccharum Marsh.) stand of the Station forestière de Duchesnay (46°57′N, 71°39′W) to determine the effect of thinning on sap production of sugar maple. From 1975 to 1989, spring sap flow and sugar concentration were measured in 58 sample plots distributed in five blocks within which three intensities of thinning (0, 22, and 35% of the initial basal area) were applied. Thinning intensities only accounted for a small part of the variation in sap volume per tap and sap sugar concentration. However, more than 60% of the variation of these two sap characteristics was related to year-to-year variations. This suggests that sap yield and sap sugar concentration were largely controlled by the different climatic conditions that occurred during these years. Hence, sap yield was strongly correlated with the number of days characterized by temperature fluctuations around 0 °C during springtime and by winter precipitation. Sap sugar concentration was also correlated to the number of days with temperature fluctuating around 0 °C during springtime but all other tested meteorological variables failed to improve this relationship. While thinning intensities did not affect sap yield per tap and sugar concentration, sugar yield per hectare could be improved by thinning over the long term since it increased the potential number of taps per hectare.

scholarly journals Effects of Climatic Conditions on Sap Flow in Sugar Maple

1985 ◽  
Vol 61 (4) ◽  
pp. 303-307 ◽  
Author(s):  
Y. T. Kim ◽  
R. H. Leech
Keyword(s):  
Sap Flow ◽  
Acer Saccharum ◽  
Sugar Maple ◽  
Climatic Conditions ◽  
Climatic Factor

Temperature, sunlight and precipitation were studied to examine their influence on sugar maple (Acer saccharum Marsh) sap flow over a five-year period. Temperature was the most important climatic factor influencing the amount of sap flow. Sunlight also increased the sap flow, but rain one day before the sap collection reduced it.

Sublimation of snowpacks in subalpine conifer forests

1998 ◽  
Vol 28 (4) ◽  
pp. 501-513 ◽  
Author(s):  
R A Schmidt ◽  
C A Troendle ◽  
J R Meiman
Keyword(s):  
Wind Speed ◽  
Surface Structure ◽  
Air Temperature ◽  
Winter Season ◽  
Snow Surface ◽  
Average Difference ◽  
Weather Factors ◽  
Daily Rate ◽  
South Slope ◽  
Index Changes

This effort to improve prediction of forest snowpack evaporation was aimed at understanding differences in winter snowpack among forested aspects. Theoretical arguments combined air temperature, humidity, wind speed, and radiation into a sublimation index. Monitoring weather factors and the mass of a 65-cm-diameter pan of snow set in a forest snowpack provided calibration of the index. Changes in snow surface structure caused a decrease with time in the empirical ratio of snowpack-to-index sublimation. This decrease was proportional to total sublimation since snowfall. We applied the model to compute daily snowpack sublimation on two adjacent forested slopes in central Colorado, U.S.A., during a 40-d accumulation period in March and April 1996. The estimate for both slopes combined was 0.52 mm/d, with sublimation from a south slope snowpack (0.61 mm/d) averaging 1.2 times that from an adjacent north-facing slope (0.43 mm/d). Extending the average difference of 0.18 mm/d through a winter season (150 d) would account for a 27-mm difference in snowpack water between the two aspects. Sublimation of 78 mm in a snow season, estimated from the combined average daily rate, represents about 20% of the normal peak water equivalent of these snowpacks. Effects of surface structure on snowpack sublimation should also apply to surfaces of snow intercepted by canopies.

scholarly journals Seasonal Climate Impacts on Vocal Activity in Two Neotropical Nonpasserines

Diversity ◽  
2021 ◽  
Vol 13 (7) ◽  
pp. 319
Author(s):  
Cristian Pérez-Granados ◽  
Karl-L. Schuchmann
Keyword(s):  
Air Temperature ◽  
Daily Rainfall ◽  
Climatic Conditions ◽  
Dry Season ◽  
Climate Impacts ◽  
Calling Behavior ◽  
Wet Season ◽  
Focal Species ◽  
Calling Activity ◽  
Vocal Activity

Climatic conditions represent one of the main constraints that influence avian calling behavior. Here, we monitored the daily calling activity of the Undulated Tinamou (Crypturellus undulatus) and the Chaco Chachalaca (Ortalis canicollis) during the dry and wet seasons in the Brazilian Pantanal. We aimed to assess the effects of climate predictors on the vocal activity of these focal species and evaluate whether these effects may vary among seasons. Air temperature was positively associated with the daily calling activity of both species during the dry season. However, the vocal activity of both species was unrelated to air temperature during the wet season, when higher temperatures occur. Daily rainfall was positively related to the daily calling activity of both species during the dry season, when rainfall events are scarce and seem to act as a trigger for breeding phenology of the focal species. Nonetheless, air temperature was negatively associated with the daily calling activity of the Undulated Tinamou during the wet season, when rainfall was abundant. This study improves our understanding of the vocal behavior of tropical birds and their relationships with climate, but further research is needed to elucidate the mechanisms behind the associations found in our study.

Modeling soil temperature using air temperature features in diverse climatic conditions with complementary machine learning models

2021 ◽  
Vol 185 ◽  
pp. 106158
Author(s):  
Maryam Bayatvarkeshi ◽  
Suraj Kumar Bhagat ◽  
Kourosh Mohammadi ◽  
Ozgur Kisi ◽  
M. Farahani ◽  
...  
Keyword(s):  
Machine Learning ◽  
Soil Temperature ◽  
Air Temperature ◽  
Climatic Conditions ◽  
Learning Models ◽  
Machine Learning Models

scholarly journals Changes in Air Temperature and Snow Cover in Winter in Poland

Atmosphere ◽  
2021 ◽  
Vol 12 (1) ◽  
pp. 68
Author(s):  
Arkadiusz M. Tomczyk ◽  
Ewa Bednorz ◽  
Katarzyna Szyga-Pluta
Keyword(s):  
Snow Cover ◽  
Air Temperature ◽  
Winter Season ◽  
Primary Objective ◽  
Climatic Conditions ◽  
Cover Depth ◽  
North Eastern ◽  
Northern Regions ◽  
Maximum Air Temperature ◽  
Snow Cover Depth

The primary objective of the paper was to characterize the climatic conditions in the winter season in Poland in the years 1966/67–2019/20. The study was based on daily values of minimum (Tmin) and maximum air temperature (Tmax), and daily values of snow cover depth. The study showed an increase in both Tmin and Tmax in winter. The most intensive changes were recorded in north-eastern and northern regions. The coldest winters were recorded in the first half of the analyzed multiannual period, exceptionally cold being winters 1969/70 and 1984/85. The warmest winters occurred in the second half of the analyzed period and among seasons with the highest mean Tmax, particularly winters 2019/20 and 1989/90 stood out. In the study period, a decrease in snow cover depth statistically significant in the majority of stations in Poland was determined, as well as its variability both within the winter season and multiannual.

scholarly journals Air pollution forecasting application based on deep learning model and optimization algorithm

2021 ◽  
Author(s):  
Azim Heydari ◽  
Meysam Majidi Nezhad ◽  
Davide Astiaso Garcia ◽  
Farshid Keynia ◽  
Livio De Santoli
Keyword(s):  
Air Pollution ◽  
Wind Speed ◽  
Power Plant ◽  
Air Temperature ◽  
Short Term Memory ◽  
Combined Cycle ◽  
Short Term ◽  
Term Memory ◽  
Proposed Model ◽  
Long Short Term Memory

AbstractAir pollution monitoring is constantly increasing, giving more and more attention to its consequences on human health. Since Nitrogen dioxide (NO2) and sulfur dioxide (SO2) are the major pollutants, various models have been developed on predicting their potential damages. Nevertheless, providing precise predictions is almost impossible. In this study, a new hybrid intelligent model based on long short-term memory (LSTM) and multi-verse optimization algorithm (MVO) has been developed to predict and analysis the air pollution obtained from Combined Cycle Power Plants. In the proposed model, long short-term memory model is a forecaster engine to predict the amount of produced NO2 and SO2 by the Combined Cycle Power Plant, where the MVO algorithm is used to optimize the LSTM parameters in order to achieve a lower forecasting error. In addition, in order to evaluate the proposed model performance, the model has been applied using real data from a Combined Cycle Power Plant in Kerman, Iran. The datasets include wind speed, air temperature, NO2, and SO2 for five months (May–September 2019) with a time step of 3-h. In addition, the model has been tested based on two different types of input parameters: type (1) includes wind speed, air temperature, and different lagged values of the output variables (NO2 and SO2); type (2) includes just lagged values of the output variables (NO2 and SO2). The obtained results show that the proposed model has higher accuracy than other combined forecasting benchmark models (ENN-PSO, ENN-MVO, and LSTM-PSO) considering different network input variables. Graphic abstract

Estimation of snowmelt volume using air temperature and wind speed

1995 ◽  
Vol 21 (5) ◽  
pp. 497-500 ◽  
Author(s):  
Masahiko Hasebe ◽  
Takanori Kumekawa
Keyword(s):  
Wind Speed ◽  
Air Temperature

Review on Renewable Energy Potential in Australian Subtropical Region (Central and North Queensland)

2011 ◽  
Vol 347-353 ◽  
pp. 3846-3855 ◽  
Author(s):  
Ali Baniyounes ◽  
Gang Liu ◽  
M. G. Rasul ◽  
M. M. K. Khan
Keyword(s):  
Renewable Energy ◽  
Wind Speed ◽  
Spatial Databases ◽  
Cost Effective ◽  
Climatic Conditions ◽  
Energy Resources ◽  
Climatic Data ◽  
Renewable Energy Resources ◽  
Subtropical Region ◽  
Energy Potential

In Australia the future demand for energy is predicted to increase rapidly. Conventional energy resources soaring prices and environmental impact have increased the interest in renewable energy technology. As a result of that the Australian government is promoting renewable energy; such as wind, geothermal, solar and hydropower. These types of energy are believed to be cost-effective and environmentally friendly. Renewable energy availability is controlled by climatic conditions such as solar radiation, wind speed and temperature. This paper aims to assess the potential of renewable energy resources, in particular wind and solar energy in an Australian subtropical region (Central and North Queensland) namely, Gladstone, Emerald, Rockhampton, Yeppoon, Townsville, and Cairns. Analysis is done by using the latest statistical state of Queensland energy information, along with measured data history of wind speed, solar irradiations, air temperature, relative humidity, and atmospheric pressure for those sites. This study has also shown that national assessments of solar and wind energy potential can be improved by improving local climatic data assessments using spatial databases of Central and North Queensland areas.

Main engine of transport ship inlet air cooling by ejector chiller

2020 ◽  
Vol 5 (3) ◽  
pp. 33-48
Author(s):  
Roman M. Radchenko1 ◽  
◽  
Dariusz Mikielewicz2 ◽  
Mykola I. Radchenko1 ◽  
Victoria S. Kornienko1 ◽  
...  
Keyword(s):  
Diesel Engine ◽  
Fuel Consumption ◽  
Air Temperature ◽  
Temperature Drop ◽  
Climatic Conditions ◽  
Air Cooling ◽  
Slow Speed ◽  
Exhaust Gases ◽  
Transport Ship ◽  
Main Engine

The efficiency of cooling the air at the inlet of marine slow speed diesel engine turbocharger by ejector chiller utilizing the heat of exhaust gases and scavenge air were analyzed. The values of air temperature drop at the inlet of engine turbocharger and corresponding decrease in fuel consumption of the engine at varying climatic conditions on the route line Odesa-Yokogama- Odesa were evaluated.

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