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 Evaluation of Relationship Between Air Pollutant Concentration and Meteorological Elements in Winter Months

2014 ◽  
Vol 22 (1) ◽  
pp. 25-32 ◽  
Author(s):  
Andrzej Żyromski ◽  
Małgorzata Biniak-Pieróg ◽  
Ewa Burszta-Adamiak ◽  
Zenon Zamiar
Keyword(s):  
Air Quality ◽  
Wind Speed ◽  
Relative Humidity ◽  
Air Temperature ◽  
Winter Season ◽  
Air Pollutant ◽  
Pollutant Concentration ◽  
Pollution Monitoring ◽  
Air Pollution Monitoring ◽  
Meteorological Elements

Abstract The paper presents the evaluation of the relation between meteorological elements and air pollutants’ concentrations. The analysis includes daily concentrations of pollutants and variation of meteorological elements such as wind speed, air temperature and relative humidity, precipitation and total radiation at four monitoring stations located in the province of Lower Silesia in individual months of the winter half-year (November–April, according to hydrological year classification) of 2005–2009. Data on air quality and meteorological elements came from the results of research conducted in the automatic net of air pollution monitoring conducted in the range of the State Environment Monitoring. The effect of meteorological elements on analysed pollutant concentration was determined using the correlation and regression analysis at significance level α < 0.05. The occurrence of maximum concentration of NO, NO2, NOX, SO2 and PM10 occurred in the coldest months during winter season (January, February and December) confirmed the strong influence of “low emission” on air quality. Among the meteorological factors assessed wind speed was most often selected component in step wise regression procedure, then air temperature, less air relative humidity and solar radiation. In the case of a larger number of variables describing the pollution in the atmosphere, in all analyzed winter seasons the most common set of meteorological elements were wind speed and air temperature.

scholarly journals Revisiting Forest Effects on Winter Air Temperature and Wind Speed—New Open Data and Transfer Functions

Atmosphere ◽  
2021 ◽  
Vol 12 (6) ◽  
pp. 710
Author(s):  
Michael Klein ◽  
Jakob Garvelmann ◽  
Kristian Förster
Keyword(s):  
Wind Speed ◽  
Air Temperature ◽  
Transfer Functions ◽  
Linear Regression Analysis ◽  
Winter Season ◽  
Forest Edge ◽  
Late Winter ◽  
Spatial And Temporal Variability ◽  
Area Index ◽  
Study Sites

The diurnal cycle of both air temperature and wind speed is characterized by considerable differences, when comparing open site conditions to forests. In the course of this article, a new two-hourly, open-source dataset, covering a high spatial and temporal variability, is presented and analyzed. It contains air temperature measurements (128 station pairs (open/forest); six winter seasons; six study sites), wind speed measurements (64 station pairs; three winter seasons, four study sites) and related metadata in central Europe. Daily cycles of air temperature and wind speed, as well as further dependencies of the effective Leaf Area Index (effective LAI), the exposure in the context of forest effects, and the distance to the forest edge, are illustrated in this paper. The forest effects on air temperature can be seen particularly with increasing canopy density, in southern exposures, and in the late winter season, while wind speed depends on multiple factors such as effective LAI or the distance to the forest edge. New transfer functions, developed using linear and non-linear regression analysis, in a leave-one-out cross-validation, improve certain efficiency criteria (NSME; r2; RMSE; MAE) compared to existing transfer functions. The dataset enables multiple purposes and capabilities due to its diversity and sample size.

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.

scholarly journals Shade Levels, Wind Speed, and Wind Direction Influence Air Temperature in Mini-shadehouses

HortScience ◽  
1995 ◽  
Vol 30 (4) ◽  
pp. 862G-862
Author(s):  
S. Vladimirova ◽  
D.B. McConnell ◽  
R.A. Bucklin
Keyword(s):  
Wind Speed ◽  
Air Temperature ◽  
Wind Direction ◽  
Ground Level ◽  
Longitudinal Axis ◽  
Experimental Plot ◽  
Average Difference ◽  
The North ◽  
Light Levels ◽  
Air Temperatures

The effect of four shade levels (47%, 63%, 80%, and 91%) on air temperature was evaluated using 24 arch-shaped, open-ended shadestructures oriented with their longitudinal axis in north–south direction. The mini-shadehouses were 80 × 185 × 80 cm (width × length × height). Six replicates per treatment (shade level) were randomly assigned within the experimental plot. Light levels were measured using Sunceram solar cells. Copper-Constantan thermocouples were installed 60 cm from ground level and 20 cm from the north entrance. The experiment was initiated in July 1994 and terminated in Oct. 1994. Data from 20 consecutive days in August were analyzed. Eighty percent shade had the highest air temperature; however, the average difference between 47%, 63%, and 91% shade was less than 1C. Wind direction and speed affected air temperature with north or south winds correlated with highest temperatures. Analysis of the data shows averaged air temperatures differed by ≤1C for all shade levels. Consequently, these structures may be used for replicated research studies involving plant growth.

scholarly journals The ground-level ozone concentration is inversely correlated with the number of COVID-19 cases in Warsaw, Poland

2021 ◽  
Author(s):  
Oskar Wiśniewski ◽  
Wiesław Kozak ◽  
Maciej Wiśniewski
Keyword(s):  
Wind Speed ◽  
Ozone Concentration ◽  
Inverse Correlation ◽  
Ground Level ◽  
Viral Agent ◽  
The Novel ◽  
Weather Factors ◽  
Ground Level Ozone ◽  
The Many ◽  
The Impact

AbstractCOVID-19, which is a consequence of infection with the novel viral agent SARS-CoV-2, first identified in China (Hubei Province), has been declared a pandemic by the WHO. As of September 10, 2020, over 70,000 cases and over 2000 deaths have been recorded in Poland. Of the many factors contributing to the level of transmission of the virus, the weather appears to be significant. In this work, we analyze the impact of weather factors such as temperature, relative humidity, wind speed, and ground-level ozone concentration on the number of COVID-19 cases in Warsaw, Poland. The obtained results show an inverse correlation between ground-level ozone concentration and the daily number of COVID-19 cases.

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

scholarly journals The Influence of the Madden–Julian Oscillation on Canadian Wintertime Surface Air Temperature

2009 ◽  
Vol 137 (7) ◽  
pp. 2250-2262 ◽  
Author(s):  
Hai Lin ◽  
Gilbert Brunet
Keyword(s):  
Air Temperature ◽  
Wave Train ◽  
Winter Season ◽  
Surface Air Temperature ◽  
Madden Julian Oscillation ◽  
Eastern Canada ◽  
Central Pacific ◽  
Sea Level Pressure ◽  
The Indian Ocean ◽  
Rossby Wave Train

Using the homogenized Canadian historical daily surface air temperature (SAT) for 210 relatively evenly distributed stations across Canada, the lagged composites and probability of the above- and below-normal SAT in Canada for different phases of the Madden–Julian oscillation (MJO) in the winter season are analyzed. Significant positive SAT anomalies and high probability of above-normal events in the central and eastern Canada are found 5–15 days following MJO phase 3, which corresponds to an enhanced precipitation over the Indian Ocean and Maritime Continent and a reduced convective activity near the tropical central Pacific. On the other hand, a positive SAT anomaly appears over a large part of northern and northeastern Canada about 5–15 days after the MJO is detected in phase 7. An analysis of the evolution of the 500-hPa geopotential height and sea level pressure anomalies indicates that the Canadian SAT anomaly is a result of a Rossby wave train associated with the tropical convection anomaly of the MJO. Hence, the MJO phase provides useful information for the extended-range forecast of Canadian winter surface air temperature. This result also provides an important reference for numerical model verifications.

Empirical Equations to Estimate Evapotranspiration in Mosul City

2020 ◽  
Vol 27 (4) ◽  
pp. 98-102
Author(s):  
Haqqi Yasin ◽  
Luma Abdullah
Keyword(s):  
Wind Speed ◽  
Relative Humidity ◽  
Air Temperature ◽  
Reference Evapotranspiration ◽  
Sunshine Duration ◽  
Food And Agriculture ◽  
Food And Agriculture Organization ◽  
Daily Data ◽  
Daily Sunshine ◽  
Measured Wind Speed

Average daily data of solar radiation, relative humidity, wind speed and air temperature from 1980 to 2008 are used to estimate the daily reference evapotranspiration in the Mosul City, North of Iraq. ETo calculator software with the Penman Monteith method standardized by the Food and Agriculture Organization is used for calculations. Further, a nonlinear regression approach using SPSS Statistics is utilized to drive the daily reference evapotranspiration relationships in which ETo is function to one or more of the average daily air temperature, actual daily sunshine duration, measured wind speed at 2m height and relative humidity

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