Meteorological Parameter Studies During 6 December 2016 Indonesia Earthquake (Mw 6.5)

2019 ◽  
pp. 175-190
Author(s):  
Pranab Hazra ◽  
Suman Paul ◽  
Shreya Chatterjee ◽  
Anindita Chandra
Keyword(s):  
Meteorological Parameter

Experimental and Theoretical Studies on Performance of GSHP Combined with Free Cooling System

2013 ◽  
Vol 368-370 ◽  
pp. 1232-1236
Author(s):  
Wei Xue Cao ◽  
Ru Chang ◽  
Can Zhang ◽  
Qiu Li Zhang
Keyword(s):  
Cooling Tower ◽  
Cooling System ◽  
Meteorological Parameter ◽  
Economic Benefits ◽  
Ground Source Heat Pump ◽  
Combined System ◽  
Climate Zones ◽  
Ground Source ◽  
Free Cooling ◽  
Experimental And Theoretical Studies

Ground-Source Heat Pump systems and tower cooling system have been studied in this paper individually by experiment and simulation using TRNSYS, the influencing factors such as meteorological parameter, cooling tower and subunit construction was analyzed. Results show that the combined system has ability to meet the cooling requirements in II building climate zones, the combined system will have energy-saving and obvious economic benefits by working through the year.

scholarly journals Modelling in Human Biometeorology: Spatial-Temporal Analysis of Thermal Indices

2021 ◽  
Vol 8 (1) ◽  
pp. 28
Author(s):  
Andreas Matzarakis ◽  
Marcel Gangwisch ◽  
Tim Herbert
Keyword(s):  
Meteorological Parameters ◽  
Meteorological Parameter ◽  
Temporal Analysis ◽  
Wave Radiation ◽  
Thermal Indices ◽  
Spatial And Temporal Scales ◽  
Mitigation And Adaptation ◽  
Radiation Fluxes ◽  
Scale Models ◽  
Radiant Temperature

The issue of the quantification of thermal comfort or heat stress on humans is in vogue nowadays. This is evident for indices, which are trying to quantify these effects. Most known indices are PET, modified PET, SET*, PT and UTCI. All thermal indices require the same thermo-physiological and meteorological parameters. Air temperature, air humidity, wind speed, and short and long wave radiation fluxes in terms of mean radiant temperature are the required meteorological parameters. For human thermo-physiology, information about heat production and clothing are required. The meteorological parameters have to be available in appropriate spatial and temporal scales depending on the target and the specific issues demanded. The appropriate spatial and temporal resolution data cannot only be delivered by measurement stations. Meso and micro scale models, which compute meteorological parameter and thermal indices, can be helpful in the development of mitigation and adaptation strategies in the era of climate change.

scholarly journals Relationship Between Phenological and Meteorological Data as an Important Input Into Spring Barley Phenological Model

2019 ◽  
Vol 67 (3) ◽  
pp. 679-688
Author(s):  
Lenka Hájková ◽  
Martin Možný ◽  
Věra Kožnarová ◽  
Lenka Bartošová ◽  
Zdeněk Žalud
Keyword(s):  
Meteorological Data ◽  
Spring Barley ◽  
Meteorological Parameter ◽  
Grain Filling ◽  
Phenological Stage ◽  
Phenological Stages ◽  
Phenological Model ◽  
Average Value ◽  
Precipitation Total ◽  
Grain Filling Period

In this study, phenological and meteorological data have been used to interpret the relationship and influence of weather on current phenological stages of spring barley. The analyses were focused mainly on the stages closely connected with yield and grain filling period – tillering (BBCH 21), heading (BBCH 55) and yellow ripeness (BBCH 85). The aims of this paper were to: (1) calculate the trend in phenological development of spring barley from CHMI phenological stations in period 1991 – 2012 at different climatic zones; (2) evaluate the trend in number of days between phenological stages; (3) evaluate the sums of growing degree days above threshold above 5 °C (GDD) and precipitation totals to phenophase onset calculated since the phenological stage of emergence (BBCH 10); (4) calculate Pearson’s correlation coefficient (PCC) between phenological stage and meteorological parameter. The highest positive PCC was found between GDD and phenological stages of heading and yellow ripeness at Doksany and Strážnice stations situated in lowlands. The average value of GDD to phenological stage heading is within the range from 418.4 to 500.1 °C. The sums of precipitation totals fluctuate from 73.9 mm (Doksany station) to 123.2 mm (Chrastava station). The results of this study suggest that GDD can be a more suitable parameter for phenological model of spring barley development than precipitation total.

scholarly journals Estimation of Rainfall-Runoff Relationship and Correlation of Runoff with Infiltration Capacity and Temperature Over East Singhbhum District of Jharkhand

2019 ◽  
Vol 9 (2) ◽  
pp. 461-466
Keyword(s):  
Land Surface ◽  
Pearson Correlation ◽  
Meteorological Parameter ◽  
Research Work ◽  
Soil Surface ◽  
Graphical Analysis ◽  
Annual Runoff ◽  
Annual Rainfall ◽  
Rainfall Runoff ◽  
Infiltration Capacity

In meteorology, Precipitation is any product of the condensation of atmospheric water vapor that falls under the gravity, the rainfall being the principal form of precipitation in India. Rainfall is the most important meteorological parameter for hydrology, as it controls the other processes such as infiltration, runoff, detention storage, and evapotranspiration. When precipitation falls over a catchment area, these processes have to be satisfied before precipitation water becomes runoff. Infiltration is the vertically downward flow of rainfall into ground/underground through percolation inside the soil surface and depends on soil-type, porosity, and permeability. Runoff is the flow of rainwater over the land surface that happens when there is an excess of precipitation over an area. Runoff is produced when the rainwater exceeds the infiltration capacity of the soil. The most important relationships for any watershed are the relationship between rainfall and runoff. This relationship depends on some factors such as characteristics of rainfall, runoff, and infiltration. Though the abovementioned factors have a major impact on the volume of runoff, a consistent correlation between rainfall-runoff enables us to increase more confidence in sufficient time for the formulation of appropriate decision making for the local authority. The present research work was undertaken to analyze the correlation between annual rainfall and annual runoff for the years 1901-2018 over Jamshedpur of East Singhbhum district, Jharkhand. Further in this study, the correlation between infiltration and annual runoff was analyzed over the same area and the same data period. Correlation between temperature and annual runoff was also found. Through the graphical analysis, it was found that the value of annual rainfall and runoff are strongly correlated.As the value of the Pearson correlation coefficient (r) is almost equal to +1 which is a nearly perfect positive correlation, signifies that both variables move in the same direction. It also signifies that the two variables being compared have a perfect positive relationship; that means these two are strongly related. Through the study, it was also found that the infiltration and runoff are largely correlated. There was practically no correlation found between the values of temperature and runoff over the years.

scholarly journals The Accumulated Winter Season Severity Index (AWSSI)

2015 ◽  
Vol 54 (8) ◽  
pp. 1693-1712 ◽  
Author(s):  
Barbara E. Mayes Boustead ◽  
Steven D. Hilberg ◽  
Martha D. Shulski ◽  
Kenneth G. Hubbard
Keyword(s):  
Snow Depth ◽  
Meteorological Parameter ◽  
Winter Season ◽  
Weather Conditions ◽  
Severity Index ◽  
Winter Weather ◽  
Site Specific ◽  
Teleconnection Patterns ◽  
Temperature And Precipitation ◽  
Parallel Index

AbstractThe character of a winter can be defined by many of its features, including temperature averages and extremes, snowfall totals, snow depth, and the duration between onset and cessation of winter-weather conditions. The accumulated winter season severity index incorporates these elements into one site-specific value that defines the severity of a particular winter, especially when examined in the context of climatological values for that site. Thresholds of temperature, snowfall, and snow depth are assigned points that accumulate through the defined winter season; a parallel index uses temperature and precipitation to provide a snow proxy where snow data are unavailable or unreliable. The results can be analyzed like any other meteorological parameter to examine relationships to teleconnection patterns, determine trends, and create sector-specific applications, as well as to analyze an ongoing winter or any individual winter season to place its severity in context.

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