Determination of relative contribution of different meteorological elements on evaporation

The present study deals with influence of radiation, maximum temperature, hours of bright sunshine, relative humidity and surface wind on evaporation at Calcutta, Pune and New Delhi. Daily data from 1991-94 of January, May, June, July and October have been utilized. Direct and indirect influence of the weather factors have been determined through "path analysis" and discussed. Multiple regression equations have also been developed with evaporation as the dependent variable and the above five weather parameters as independent variables. The results reveal that radiation and maximum temperature are the two most important parameters which enhance evaporation. Most of their effect is direct though in some cases their interaction with relative humidity or wind also contribute significantly to evaporation. Humidity and surface wind, generally, do not significantly contribute directly to evaporation; their effect is manifested through interaction with maximum temperature, indirectly.

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Weather parameters vulnerability on tea production in north western Himalaya, India

Journal of Applied and Natural Science ◽

10.31018/jans.v8i4.1122 ◽

2016 ◽

Vol 8 (4) ◽

pp. 2262-2267

Author(s):

Parmod Verma ◽

Ranbir Singh Rana ◽

Ramesh Ramesh ◽

Ranu Pathania

Keyword(s):

Relative Humidity ◽

Minimum Temperature ◽

Positive Relationship ◽

Western Himalaya ◽

Green Leaf ◽

Maximum Temperature ◽

Leaf Yield ◽

Tea Production ◽

Weather Parameters ◽

June July

The study assessed the sensitivity of weather parameters with respect to total green leaf and two leaves and bud (T & B) productivity of tea crop {Camellia sinensis (L.) Kuntze}. The maximum temperature ranging from 20.0 to 29.0 oC during March, May, August and September showed positive relationship with values ranging from 0.26 to 3.38 and 0.22 to 3.22 for green leaf and T & B yield, respectively. Similarly, minimum temperature ranging from 9.1 to 20.0 oC during March and July to October found positive 0.001 to 2.93 and 0.28 to 2.91 for green leaf and T & B productivity, respectively. The mean monthly rainfall amounting 52.7 to 664.7 mm during March, May, July to October and 52.7 to 488.4 mm during June, July, September and October also showed positive sensitivity with values ranging from 0.03 to 0.33 and 0.007 to 0.35 for green leaf and T & B yield, respectively. The relative humidity ranging between 41.2 to 77.3% during April to May for green leaf yield (0.32 to 1.71) and during April to May and October for two leaf and bud yield (0.00 to 1.70) showed positive relationship. So, maximum and minimum temperature between 20.0 to 29.0 oC and 9.1 to 20.0 oC, respectively with rainfall of 52.7 to 488.4 mm and relative humidity 41.2 to 77.3% are the most beneficial weather parameters for tea cultivation at Palampur conditions.

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Seasonal abundance of Campoletis chlorideae Uchida (Hymenoptera:Ichneumonidae), A larval parasitoid of Helicoverpa armigera(Hubner) hardwick in chickpea

Legume Research - An International Journal ◽

10.18805/lr.v39i4.11260 ◽

2016 ◽

Vol 39 (4) ◽

Author(s):

A. Kuzhandhaivel Pillai ◽

S. Selvaraj ◽

Meena Agnihotri

Keyword(s):

Climate Change ◽

Relative Humidity ◽

Significant Negative Correlation ◽

Seasonal Abundance ◽

Maximum Temperature ◽

Weather Factors ◽

Campoletis Chlorideae ◽

Minimum Relative Humidity ◽

Larval Parasitoid ◽

Survival And Development

Climate change is likely to affect the insect host and the activity and abundance of biological control agents. Therefore, the present studies were conducted to understand the seasonal abundance of larval parasitoid, Campoletis chlorideae on chickpea at Pantnagar during the cropping season 2010-11 and 2011-12 revealed that the larval parasitoid exhibited its marked first appearance in 3rd standard meteorological week (SMW) and attained peak population in 7th (85.80%) and 8th (87.65%) SMW, respectively. Statistical analysis between the weather parameters and the population of the larval parasitoid showed a significant negative correlation with maximum temperature (r= - 0.698* and r= - 0.705*) and minimum temperature (r= - 0.706* and r= - 0.790*) whereas significant positive correlation with maximum relative humidity (r= 0.800** and r = 0.824**) and minimum relative humidity (r= 0.636* and r= 0.254) during 2010-11 and 2011-12, respectively. The results indicated that changes in weather factors as a result of climate change would have considerable influence on survival and development of C.chlorideae.

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Weather Factors Associated with Development of Sorghum Ergot in the Texas Panhandle

Plant Disease ◽

10.1094/pd-90-0717 ◽

2006 ◽

Vol 90 (6) ◽

pp. 717-722 ◽

Cited By ~ 9

Author(s):

F. Workneh ◽

C. M. Rush

Keyword(s):

Relative Humidity ◽

Weather Conditions ◽

Maximum Temperature ◽

Hybrid Seed Production ◽

Weather Factors ◽

Inoculum Level ◽

Minimum Relative Humidity ◽

Hourly Temperature ◽

Texas Panhandle ◽

Claviceps Africana

Since its first introduction in 1997, sorghum ergot, caused by Claviceps africana, has been observed yearly in the Texas Panhandle, where it has caused occasional epidemics in hybrid-seed production fields. To determine the effect of weather factors on ergot severity, inoculation experiments were conducted in 2003 and 2004 using sequentially planted sorghum plants. Sorghum flowers were inoculated with three inoculum concentrations (1 × 104, 1 × 105, or 1 × 106 spores/ml) prepared from infected sorghum panicles producing fresh honeydew. Each year, inoculations were conducted several times during sorghum flowering periods so that time of inoculations would coincide with different weather conditions. Weather variables (temperature, relative humidity, wind speed, precipitation, and radiation) were collected using an onsite weather station. Infected and uninfected florets were counted 8 to 13 days after inoculation, and the percentage of infected florets per sorghum panicle (severity) was determined. In both years, temperature and relative humidity were the predominant factors responsible for variations in sorghum ergot severity with all inoculum densities. Relationship between ergot severity and each of the two variables depended on inoculum density. Measurable infection occurred at a maximum temperature of 34°C with 1 × 106 spores/ml, while there was little or no infection at 30°C with 1 × 104 spore/ml. Cumulative departures from minimum relative humidity and maximum temperature infection thresholds 12, 18, 24, 36, 48, and 72 h after inoculation were calculated and regressed against ergot severity for each inoculum level. Cumulative departures of hourly temperature and relative humidity from maximum temperature and minimum relative humidity infection thresholds 18 and 24 h after inoculation were best related to sorghum ergot severity (R 2 = 89 and 91; P < 0001, respectively). Models based on these two time-durations then were used in predicting a regional site-specific ergot severity potential using radar-estimated rainfall.

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Influence of weather factors, soil temperature and moisture on collar rot disease of betel vine (Piper betle L.) under coastal saline zone of West Bengal

Journal of Agrometeorology ◽

10.54386/jam.v23i4.148 ◽

2021 ◽

Vol 23 (4) ◽

pp. 428-434

Author(s):

PRABIR KUMAR GARAIN ◽

BHOLANATH MONDAL ◽

SUBRATA DUTTA

Keyword(s):

Soil Moisture ◽

Relative Humidity ◽

Soil Temperature ◽

Disease Incidence ◽

Maximum Temperature ◽

Piper Betle ◽

Weather Factors ◽

Collar Rot ◽

Minimum Relative Humidity ◽

Rot Disease

A study was conducted to find out the influence of weather factors, soil temperature and soil moisture on the incidence of Sclerotium rolfsii Sacc. induced collar rot disease in betelvine (Piper betle L.), during 2016 to 2018. Fourteen soil and weather factors, taken from the agrometeorological observatory located at instructional farm of Ramkrishna Ashram Krishi Vigyan Kendra, Nimpith and recorded from a nearby betelvine boroj, were subjected to multiple regression, binary logistic regression and canonical discriminant analysis to develop a suitable disease forewarning model. The binary logistic model, Y(0/1) = 5.899 + 0.865 (Tmax) – 0.569 (SM) + 0.097 (BRHmin) was able to predict the disease risk with 78 per cent accuracy and correctly classified 94 per cent of cases during model validation in 2018. The weekly averages of maximum temperature (Tmax), soil moisture (SM) and minimum relative humidity inside the boroj (BRHmin) were found to be the most significant predictors of disease incidence, in this model. The soil moisture at 69 - 72 per cent of field capacity, minimum temperature of 25 - 27oC, maximum temperature of 33 - 36oC, average soil temperature of 28 - 30oC, minimum relative humidity of 60 - 72 per cent inside the boroj and maximum relative humidity of 83 - 89 per cent inside the boroj were found to be highly congenial for collar rot disease incidence in betelvine under coastal saline zone of West Bengal.

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Seasonality of Non-SARS, Non-MERS Coronaviruses and the Impact of Meteorological Factors

Pathogens ◽

10.3390/pathogens10020187 ◽

2021 ◽

Vol 10 (2) ◽

pp. 187

Author(s):

Olympia E. Anastasiou ◽

Anika Hüsing ◽

Johannes Korth ◽

Fotis Theodoropoulos ◽

Christian Taube ◽

...

Keyword(s):

Logistic Regression ◽

Relative Humidity ◽

Cloud Cover ◽

Detection Rate ◽

Logistic Regression Model ◽

Meteorological Factors ◽

Seasonal Pattern ◽

Weather Factors ◽

Immunosuppressed Patients ◽

Immunocompetent Patients

Background: Seasonality is a characteristic of some respiratory viruses. The aim of our study was to evaluate the seasonality and the potential effects of different meteorological factors on the detection rate of the non-SARS coronavirus detection by PCR. Methods: We performed a retrospective analysis of 12,763 respiratory tract sample results (288 positive and 12,475 negative) for non-SARS, non-MERS coronaviruses (NL63, 229E, OC43, HKU1). The effect of seven single weather factors on the coronavirus detection rate was fitted in a logistic regression model with and without adjusting for other weather factors. Results: Coronavirus infections followed a seasonal pattern peaking from December to March and plunged from July to September. The seasonal effect was less pronounced in immunosuppressed patients compared to immunocompetent patients. Different automatic variable selection processes agreed on selecting the predictors temperature, relative humidity, cloud cover and precipitation as remaining predictors in the multivariable logistic regression model, including all weather factors, with low ambient temperature, low relative humidity, high cloud cover and high precipitation being linked to increased coronavirus detection rates. Conclusions: Coronavirus infections followed a seasonal pattern, which was more pronounced in immunocompetent patients compared to immunosuppressed patients. Several meteorological factors were associated with the coronavirus detection rate. However, when mutually adjusting for all weather factors, only temperature, relative humidity, precipitation and cloud cover contributed independently to predicting the coronavirus detection rate.

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Relation of the maximum temperature and relative humidity close to the insemination with the tropical milking criollo heifer’s gestation in three seasons

Tropical Animal Health and Production ◽

10.1007/s11250-020-02430-3 ◽

2020 ◽

Vol 53 (1) ◽

Author(s):

Froylan Rosales-Martínez ◽

Adalberto Rosendo-Ponce ◽

César Cortez-Romero ◽

Jaime Gallegos-Sánchez ◽

Juan M. Cuca-García ◽

...

Keyword(s):

Relative Humidity ◽

Maximum Temperature

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Intensification of Tilted Tropical Cyclones Over Relatively Cool and Warm Oceans in Idealized Numerical Simulations

Journal of the Atmospheric Sciences ◽

10.1175/jas-d-21-0051.1 ◽

2021 ◽

Author(s):

David A. Schecter

Keyword(s):

Relative Humidity ◽

Tropical Cyclones ◽

Inner Core ◽

Structural Parameters ◽

Deep Convection ◽

Surface Wind ◽

Vertical Wind Shear ◽

Surface Wind Speed ◽

Cloud Resolving Model ◽

Complete Alignment

Abstract A cloud resolving model is used to examine the intensification of tilted tropical cyclones from depression to hurricane strength over relatively cool and warm oceans under idealized conditions where environmental vertical wind shear has become minimal. Variation of the SST does not substantially change the time-averaged relationship between tilt and the radial length scale of the inner core, or between tilt and the azimuthal distribution of precipitation during the hurricane formation period (HFP). By contrast, for systems having similar structural parameters, the HFP lengthens superlinearly in association with a decline of the precipitation rate as the SST decreases from 30 to 26 °C. In many simulations, hurricane formation progresses from a phase of slow or neutral intensification to fast spinup. The transition to fast spinup occurs after the magnitudes of tilt and convective asymmetry drop below certain SST-dependent levels following an alignment process explained in an earlier paper. For reasons examined herein, the alignment coincides with enhancements of lower–middle tropospheric relative humidity and lower tropospheric CAPE inward of the radius of maximum surface wind speed rm. Such moist-thermodynamic modifications appear to facilitate initiation of the faster mode of intensification, which involves contraction of rm and the characteristic radius of deep convection. The mean transitional values of the tilt magnitude and lower–middle tropospheric relative humidity for SSTs of 28-30 °C are respectively higher and lower than their counterparts at 26 °C. Greater magnitudes of the surface enthalpy flux and core deep-layer CAPE found at the higher SSTs plausibly compensate for less complete alignment and core humidification at the transition time.

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Empirical Equations to Estimate Evapotranspiration in Mosul City

Tikrit Journal of Engineering Sciences ◽

10.25130/tjes.27.4.10 ◽

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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Homogeneity Test and Correction of Daily Temperature and Precipitation Data (1978–2015) in North China

Advances in Meteorology ◽

10.1155/2018/4712538 ◽

2018 ◽

Vol 2018 ◽

pp. 1-17 ◽

Cited By ~ 3

Author(s):

Lingling Shen ◽

Li Lu ◽

Tianjie Hu ◽

Runsheng Lin ◽

Ji Wang ◽

...

Keyword(s):

Large Scale ◽

North China ◽

Maximum Temperature ◽

Homogeneity Test ◽

Climate Data ◽

Average Temperature ◽

Temperature And Precipitation ◽

Daily Data ◽

Before And After ◽

Annual Average Temperature

Homogeneity of climate data is the basis for quantitative assessment of climate change. By using the MASH method, this work examined and corrected the homogeneity of the daily data including average, minimum, and maximum temperature and precipitation during 1978–2015 from 404/397 national meteorological stations in North China. Based on the meteorological station metadata, the results are analyzed and the differences before and after homogenization are compared. The results show that breakpoints are present pervasively in these temperature data. Most of them appeared after 2000. The stations with a host of breakpoints are mainly located in Beijing, Tianjin, and Hebei Province, where meteorological stations are densely distributed. The numbers of breakpoints in the daily precipitation series in North China during 1978–2015 also culminated in 2000. The reason for these breakpoints, called inhomogeneity, may be the large-scale replacement of meteorological instruments after 2000. After correction by the MASH method, the annual average temperature and minimum temperature decrease by 0.04°C and 0.06°C, respectively, while the maximum temperature increases by 0.01°C. The annual precipitation declines by 0.96 mm. The overall trends of temperature change before and after the correction are largely consistent, while the homogeneity of individual stations is significantly improved. Besides, due to the correction, the majority series of the precipitation are reduced and the correction amplitude is relatively large. During 1978–2015, the temperature in North China shows a rise trend, while the precipitation tends to decrease.

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