scholarly journals Decadal trends in climate over India

MAUSAM ◽  
2021 ◽  
Vol 43 (1) ◽  
pp. 7-20
Author(s):  
H.N. SRIVASTAVA ◽  
B.N. DEWAN ◽  
S. K. DIKSHIT ◽  
G. S. PRAKASH RAO ◽  
S.S. SINGH ◽  
...  
Keyword(s):  
Atmospheric Pressure ◽  
Meteorological Parameters ◽  
Warming Trend ◽  
Annual Rainfall ◽  
Maximum Temperature ◽  
Data Series ◽  
Temperature Minimum ◽  
Decadal Variations ◽  
Almost All ◽  
Temperature Surface

Decadal variations of meteorological parameters, vig, temperature (surface air maximum temperature, minimum temperature and upper air up to middle troposphere), station level pressure and seasonal and annual rainfall are studied for the period 1901 to 1986 (upper air data available from 1951 onwards), Tests of significance applied to data series (stationwise as well as country as a whole) show that the temperatures are showing a decreasing trend in almost all the northern parts of the country (north of 23" N) and a rising trend in southern parts (south of 23"N), For the country as a whole, however, there is a small warming trend Atmospheric pressure shows a fall between second and third decades but does not indicate any significant change after 1930, Decadal analysis of seasonal (Jun-Sep) and annual rainfall indicates that the variations in rainfall are within the statistical limits.

scholarly journals Climatology at any point : A neural network solution

MAUSAM ◽  
2021 ◽  
Vol 64 (2) ◽  
pp. 231-250
Author(s):  
PULAK GUHATHAKURTA ◽  
AJIT TYAGI ◽  
B. MUKHOPADHYAY
Keyword(s):  
Neural Network ◽  
Atmospheric Pressure ◽  
Spatial Interpolation ◽  
Meteorological Parameters ◽  
Geographical Information ◽  
Maximum Temperature ◽  
Long Period ◽  
The Neural Network ◽  
Past Data ◽  
Advance Knowledge

lHkh mi;ksxdrkZvksa] ;kstuk cukus okyksa] vkink izca/ku dkfeZdksa] i;ZVu vkfn }kjk rkieku] vf/kdre rkieku] U;wure rkieku] ok;qeaMyh; nkc] o"kkZ vkfn tSls ekSle izkpyksa dh tyok;q foKku ij lwpukvksa dh mUur tkudkjh dh vR;kf/kd ek¡x jgh gSA fdlh LFkku fo'ks"k esa os/k’kkyk ds vHkko vkSj dHkh&dHkh nh?kZ vof/k ds igys ds vk¡dM+ksa dh vuqiyC/krk ds dkj.k ekSle foKku leqnk; ml LFkku fo’ks"k ds fy, visf{kr lwpukvksa dks miyC/k ugha djk ikrk gSA bl 'kks/k i= esa LFkkfud varosZ’ku ds {ks= esa U;wjy usVodZ ds rqyukRed u, vuqiz;ksx crk, x, gSaA iwjs ckjg eghuksa ds vf/kdre vkSj U;wure nksuksa rkiekuksa  ds fy, U;wjy usVodZ varosZ’ku fun’kZ fodflr fd, x, gSaA ;g ekWMy ml LFkku fo’ks"k ij lkekU; vf/kdre vkSj U;wure rkiekuksa dks rS;kj djus ds fy, lwpukvksa ds :i  esa v{kka’k] ns’kkUrj vkSj mUu;u tSlh HkkSxksfyd lwpukvksa dk mi;ksx djrk gSA varosZ’ku ds fy, LFkkfud ekWMyksa ds fu"iknuksa dh rqyuk vU; lkekU;r% iz;qDr i)fr ds lkFk dh xbZ gSA Advance knowledge of information on  climatology of meteorological parameters like temperature, maximum temperature, minimum temperature, atmospheric pressure, rainfall etc are of great demands from all the users, planners, disaster managements personals, tourism etc. The information is required at the place concerned but this cannot be fulfilled by the meteorological community due to absent of observatory at that place and also some time absent of past data of long period. The present paper has described a comparatively new application of the neural network in the field of spatial interpolation. Neural network interpolation models are developed for both maximum and minimum temperatures for all the twelve months. The model utilizes geographical information like latitude, longitude and elevation as inputs to generate normal maximum and minimum temperatures at a place. The performances of the models are compared with the other commonly used method for spatial interpolation.  

scholarly journals Recent trends in meteorological parameters over Jammu and Kashmir

MAUSAM ◽  
2021 ◽  
Vol 61 (3) ◽  
pp. 369-382
Author(s):  
A. K. JASWAL ◽  
G. S. PRAKASA RAO
Keyword(s):  
Relative Humidity ◽  
Minimum Temperature ◽  
Meteorological Parameters ◽  
Cloud Amount ◽  
The State ◽  
Annual Rainfall ◽  
Maximum Temperature ◽  
Jammu And Kashmir ◽  
Total Cloud Amount ◽  
Increasing Trends

Annual trends of meteorological parameters temperature, rainfall, relative humidity and clouds for ten stations in Jammu and Kashmir during the period 1976-2007 were studied. Trend analysis shows that temperatures are increasing over the state with significant increase in maximum temperature in the Kashmir region (+0.04 to                +  0.05° C/year) and minimum temperature in the Jammu region (+0.03 to + 0.08° C/year). The diurnal temperature range (DTR) is increasing over Kashmir region due to higher increasing trends in the maximum temperature while the strong increasing trends in the minimum temperature are contributing more towards the decrease in DTR over the Jammu region. Annual rainfall and rainy days trends are decreasing in both the regions of the state except at Jammu where rainfall trend is significantly increasing (+12.05 mm/year). Day-time relative humidity trends are mixed while total cloud amount trends are decreasing over Kashmir region and increasing over Jammu region. The effects of urbanization in the last two decades are more pronounced in Jammu region and this is strongly expressed in minimum temperature over the region. The warming trends observed over Jammu and Kashmir state during the period of study need further investigation in relation to variability of atmospheric circulation over North India.

scholarly journals Seasonal and Weather Effects on Rheumatoid Arthritis: Myth or Reality?

2020 ◽  
Vol 2020 ◽  
pp. 1-5
Author(s):  
Hamida Azzouzi ◽  
Linda Ichchou
Keyword(s):  
Rheumatoid Arthritis ◽  
Regression Analysis ◽  
Linear Regression ◽  
Multiple Linear Regression ◽  
Atmospheric Pressure ◽  
Meteorological Parameters ◽  
Linear Regression Analysis ◽  
Multiple Linear Regression Analysis ◽  
Maximum Temperature ◽  
Tender Joint Count

Introduction. Many of our rheumatic patients report that weather and seasons affect their symptoms. Objective. The purpose of this study was to examine the effect of meteorological parameters within seasons on rheumatoid arthritis (RA) symptoms. Methods. A retrospective longitudinal study from July 2017 to August 2018 was conducted. Data from three consultations for three seasons were collected and included a tender and swollen joint count, a disease activity score for 28 joints (DAS28), and patient’s pain assessment from their computerized medical record. The weather conditions (minimum and maximum temperature, precipitation, humidity, atmospheric pressure, and wind speed) registered during the same day of consultation for each patient were obtained. Then, the statistical correlation between each meteorological parameter and RA parameters was determined using the multiple linear regression analysis. Results. The data of 117 patients with a mean age of 50.45 ± 12.17 years were analyzed. The mean DAS28 at baseline was 2.44 ± 0.95. The winter in Oujda is cold (average temperature between 10°C and15°C) compared to summer (24.5°C–32.7°C). The spring is wetter with a 71% average humidity. Overall, the tender joint count was significantly correlated with hygrometry (p=0.027) in winter. A similar result was obtained in summer with precipitation (p=0.003). The pain intensity in the summer was negatively correlated with minimum temperatures and atmospheric pressure. However, there was no correlation between meteorological parameters and disease objective parameters for all seasons. Multiple linear regression analysis showed that weather parameters appeared to explain the variability in four RA predictors in the summer. No significant associations were observed in the spring. Conclusion. Our study supported the physicians’ assumption regarding the effect of climate on pain in RA patients.

scholarly journals Estimated length of soybean phenological stages

2016 ◽  
Vol 37 (4) ◽  
pp. 1871 ◽  
Author(s):  
Ana Paula Rockenbach ◽  
Braulio Otomar Caron ◽  
Velci Queiróz de Souza ◽  
Elvis Felipe Elli ◽  
Douglas Machado de Oliveira ◽  
...  
Keyword(s):  
Meteorological Parameters ◽  
Thermal Time ◽  
Maximum Temperature ◽  
Temperature Minimum ◽  
Full Bloom ◽  
Phenological Stages ◽  
Potential Yield ◽  
Average Temperature ◽  
Growth Habits ◽  
Santa Maria

The use of modeling is a trend for agronomic science that aims to detect factors that could limit the growing practices and influence the potential yield of some crops. The objective of this study was to calculate the accumulated thermal time and estimate the phenological stages length of three soybean cultivars in two crop years, using agronomic models associated to meteorological variables. Two experiments were conducted in a field at the Agroclimatology Laboratory (LAGRO) of the Federal University of Santa Maria/UFSM, campus of Frederico Westphalen/RS, Brazil during the 2012/2013 and 2013/2014 crop years. A randomized block in a factorial scheme 6x3 with six spatial arrangements (45, crossed, 20, 20x40, 20x60 and 20x80 cm) and three cultivars with different cycles and growth habits (BMX Ativa RR/determinate, BMX Turbo RR/indeterminate and BMX Potência RR/indeterminate) with three replications were used for the experimental design. Sowing was held on 11/28/2012 and 12/02/2013. The assessed phenological stages were sowing-emergence; emergence – final vegetative; final vegetative – full bloom; full bloom – physiological maturity. The duration of each stage was related to meteorological parameters: maximum temperature, minimum temperature, average temperature, rainfall, solar radiation, and thermal time. Air temperature influences soybean growth and development. The accumulated thermal time varies between years and among cultivars, and it is the main contributor to the estimated duration of the phenological stages.

scholarly journals AnANN Model Trained on Regional Data in the Prediction of Particular Weather Conditions

2021 ◽  
Vol 11 (11) ◽  
pp. 4757
Author(s):  
Aleksandra Bączkiewicz ◽  
Jarosław Wątróbski ◽  
Wojciech Sałabun ◽  
Joanna Kołodziejczyk
Keyword(s):  
Atmospheric Pressure ◽  
Real Life ◽  
Real Data ◽  
Weather Conditions ◽  
Maximum Temperature ◽  
Air Masses ◽  
Weather Forecasts ◽  
Life Problems ◽  
The World ◽  
The City

Artificial Neural Networks (ANNs) have proven to be a powerful tool for solving a wide variety of real-life problems. The possibility of using them for forecasting phenomena occurring in nature, especially weather indicators, has been widely discussed. However, the various areas of the world differ in terms of their difficulty and ability in preparing accurate weather forecasts. Poland lies in a zone with a moderate transition climate, which is characterized by seasonality and the inflow of many types of air masses from different directions, which, combined with the compound terrain, causes climate variability and makes it difficult to accurately predict the weather. For this reason, it is necessary to adapt the model to the prediction of weather conditions and verify its effectiveness on real data. The principal aim of this study is to present the use of a regressive model based on a unidirectional multilayer neural network, also called a Multilayer Perceptron (MLP), to predict selected weather indicators for the city of Szczecin in Poland. The forecast of the model we implemented was effective in determining the daily parameters at 96% compliance with the actual measurements for the prediction of the minimum and maximum temperature for the next day and 83.27% for the prediction of atmospheric pressure.

Predictions of Current Attachment at Thermionic Cathode for TIG Arcs

2008 ◽  
Vol 580-582 ◽  
pp. 319-322 ◽  
Author(s):  
Manabu Tanaka ◽  
Kentaro Yamamoto ◽  
Tashiro Shinichi ◽  
John J. Lowke
Keyword(s):  
Melting Point ◽  
Work Function ◽  
Atmospheric Pressure ◽  
The Other ◽  
Numerical Calculations ◽  
Maximum Temperature ◽  
Arc Plasma ◽  
Melting Points ◽  
Thermionic Cathode ◽  
Uniform Current

Study of current attachment at thermionic cathode for TIG arc at atmospheric pressure is attempted from numerical calculations of arc-electrodes unified model. The calculations show that the maximum temperature of arc plasma close to the cathode tip for W-2% ThO2 reaches 19,000 K and it is the highest value in comparison with the other temperatures for W-2% La2O3 and W-2% CeO2, because the current attachment at the cathode tip is constricted by a centralized limitation of liquid area of ThO2 due to its higher melting point. The calculations also show that, in cases of W- 2% La2O3 and W-2% CeO2, the liquid areas of La2O3 and Ce2O3 are widely expanded at the cathode tip due to their lower melting points and then produce uniform current attachments at the cathode. It is concluded that the current attachment at thermionic cathode is strongly dependent on work function, melting point and Richardson constant of emitter materials.

Effect of environment factors on milk production and lactation length under different seasons in crossbred cattle

2015 ◽  
Author(s):  
S.S. Mote ◽  
D.S. Chauhan* and Nilotpal Ghosh1
Keyword(s):  
Milk Yield ◽  
Minimum Temperature ◽  
Summer Season ◽  
Climatic Variables ◽  
Coefficient Of Determination ◽  
Maximum Temperature ◽  
Temperature Minimum ◽  
Crossbred Cattle ◽  
Lactation Length ◽  
Significant Regression

The study was undertaken to evaluate the effect of different macro climatic variables on lactation milk yield and lactation length of Holdeo (Holstein Friesian x Deoni) crossbred cattle. Milk data of 145 Holdeo crossbred cows with 619 lactation records and the meteorological data over a period of 15 years (1995-2009) were obtained from Cattle Cross Breeding Project, Vasantrao Naik Marathwada Krishi Vidyapeeth, Parbhani and University Meteorological Observatory, respectively. It was observed that maximum temperature has significant correlation with lactation milk yield; whereas maximum temperature, minimum temperature, sunshine hours and wind speed have significant correlation with lactation length. Regression analysis indicated that all the climatic variables except minimum temperature exhibited significant regression results with lactation milk yield, and maximum temperature, minimum temperature and maximum humidity have significant regression results with lactation length. All the climatic variables considered in the study accounted for 75 % and 65 % direct variation on lactation milk yield and lactation length, respectively, as verified by the value of coefficient of determination (R2). It was observed that lactation milk yield (1136.56 + 21.04 kg.) and lactation length (295.29 + 5.51 days) were highest among the cows calved during winter season as compared to rainy and summer season. All the climatic variables considered in the study accounted for 57% , 56 % and 48 % direct variation on milk yield and 68% , 53 % and 46 % direct variation on lactation length in rainy, winter and summer season, respectively, as verified by the value of coefficient of determination (R2). This research indicated that crossbred cows were sensitive to seasonal changes on their lactation performance. The optimum ranges of temperature; humidity and THI for better performance of crossbred in subtropical region of India were found to be 19-26 oC, 52-66 % and 65-68 %, respectively.

Changing Work and Work-Related Travel and the Impact of Covid-19

2021 ◽  
Vol 47 (3) ◽  
pp. 336-354
Author(s):  
Kiron Chatterjee ◽  
Fiona Crawford
Keyword(s):  
Health Outcomes ◽  
Digital Age ◽  
Data Series ◽  
Work Related ◽  
Policy Interventions ◽  
Working Practices ◽  
Key Features ◽  
The Uk ◽  
Almost All ◽  
The Impact

The nature of work was undergoing dramatic change before the pandemic as the digital age continued to transform all sectors of society. In this paper we describe pre-pandemic trends in types of work, the workforce and working arrangements in the UK. We show how these changes were having gradual yet significant impacts on commuting and other work-related travel which were apparent in national travel data series. Key features of these impacts were increasing diversification and flexibility in work travel. We bring together findings on how working practices and travel have been altered by the pandemic and report expectations and opinions on its longer-term legacies. The pandemic has accelerated pre-pandemic trends and led to a shift in how work is performed for almost all sectors of the economy – but grasping the opportunity for this to contribute to deep carbon reductions from transport and to improve equity and health outcomes will require carefully directed policy interventions.

Thermal Hydraulic Analysis of Severe Accident in PFBR

2010 ◽  
Author(s):  
K. Velusamy ◽  
P. Chellapandi ◽  
G. R. Raviprasan ◽  
P. Selvaraj ◽  
S. C. Chetal
Keyword(s):  
Atmospheric Pressure ◽  
Fluid Dynamic ◽  
Hydraulic Modeling ◽  
Severe Accident ◽  
Maximum Temperature ◽  
Maximum Pressure ◽  
Dynamic Calculation ◽  
Thermal Hydraulic Modeling ◽  
Thermal Hydraulic Analysis ◽  
Design Pressure

During a core disruptive accident (CDA), the amount of primary sodium that can be released to Reactor Containment Building (RCB) in Prototype Fast Breeder Reactor (PFBR) is estimated to be 350 kg/s, by a transient fluid dynamic calculation. The pressure and temperature evolutions inside RCB, due to consequent sodium fire have been estimated by a constant burning rate model, accounting for heat absorption by RCB wall, assuming RCB isolation based on area gamma monitors. The maximum pressure developed is 7000 Pa. In case RCB isolation is delayed, then the final pressure inside RCB reduces below atmospheric pressure due to cooling of RCB air. The negative pressure that can be developed is estimated by dynamic thermal hydraulic modeling of RCB air / wall to be −3500 Pa. These investigations were useful to arrive at the RCB design pressure. Following CDA, RCB is isolated for 40 days. During this period, the heat added to RCB is dissipated to atmosphere only by natural convection. Considering all the possible routes of heat addition to RCB, evolution of RCB wall temperature has been predicted using HEATING5 code. It is established that the maximum temperature in RCB wall is less than the permissible value.

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