scholarly journals Atmospheric Error Correction of the Laser Beam Ranging

2014 ◽  
Vol 2014 ◽  
pp. 1-6 ◽  
Author(s):  
J. Saydi ◽  
A. Lotfalian ◽  
M. Abedi ◽  
J. Khalilzadeh ◽  
H. Saghafifar
Keyword(s):  
Laser Beam ◽  
Meteorological Data ◽  
Atmospheric Correction ◽  
Weather Conditions ◽  
Emission Angle ◽  
Laser Ranging ◽  
Atmospheric Effects ◽  
Atmospheric Models ◽  
Ranging Error ◽  
Surface Measurements

Atmospheric models based on surface measurements of pressure, temperature, and relative humidity have been used to increase the laser ranging accuracy by ray tracing. Atmospheric refraction can cause significant errors in laser ranging systems. Through the present research, the atmospheric effects on the laser beam were investigated by using the principles of laser ranging. Atmospheric correction was calculated for 0.532, 1.3, and 10.6 micron wavelengths through the weather conditions of Tehran, Isfahan, and Bushehr in Iran since March 2012 to March 2013. Through the present research the atmospheric correction was computed for meteorological data in base of monthly mean. Of course, the meteorological data were received from meteorological stations in Tehran, Isfahan, and Bushehr. Atmospheric correction was calculated for 11, 100, and 200 kilometers laser beam propagations under 30°, 60°, and 90° rising angles for each propagation. The results of the study showed that in the same months and beam emission angles, the atmospheric correction was most accurate for 10.6 micron wavelength. The laser ranging error was decreased by increasing the laser emission angle. The atmospheric correction with two Marini-Murray and Mendes-Pavlis models for 0.532 nm was compared.

scholarly journals Rain Erosion Maps for Wind Turbines Based on Geographical Locations: A Case Study in Ireland and Britain

2021 ◽  
Vol 7 (1) ◽  
Author(s):  
K. Pugh ◽  
M. M. Stack
Keyword(s):  
Wind Turbine ◽  
Western Europe ◽  
Meteorological Data ◽  
Turbine Blades ◽  
Weather Conditions ◽  
Annual Rainfall ◽  
Wind Turbine Blades ◽  
Weather Patterns ◽  
The Uk

AbstractErosion rates of wind turbine blades are not constant, and they depend on many external factors including meteorological differences relating to global weather patterns. In order to track the degradation of the turbine blades, it is important to analyse the distribution and change in weather conditions across the country. This case study addresses rainfall in Western Europe using the UK and Ireland data to create a relationship between the erosion rate of wind turbine blades and rainfall for both countries. In order to match the appropriate erosion data to the meteorological data, 2 months of the annual rainfall were chosen, and the differences were analysed. The month of highest rain, January and month of least rain, May were selected for the study. The two variables were then combined with other data including hailstorm events and locations of wind turbine farms to create a general overview of erosion with relation to wind turbine blades.

Statistical Analysis of Weather Effects on PM2.5

2012 ◽  
Vol 610-613 ◽  
pp. 1033-1040
Author(s):  
Wei Dai ◽  
Jia Qi Gao ◽  
Bo Wang ◽  
Feng Ouyang
Keyword(s):  
Statistical Analysis ◽  
Wind Speed ◽  
Relative Humidity ◽  
Statistical Methods ◽  
Predictive Analytics ◽  
Hypothesis Test ◽  
Meteorological Data ◽  
Weather Conditions ◽  
Statistical Distribution ◽  
Weather Effects

Effects of weather conditions including temperature, relative humidity, wind speed, wind and direction on PM2.5 were studied using statistical methods. PM2.5 samples were collected during the summer and the winter in a suburb of Shenzhen. Then, correlations, hypothesis test and statistical distribution of PM2.5 and meteorological data were analyzed with IBM SPSS predictive analytics software. Seasonal and daily variations of PM2.5 have been found and these mainly resulted from the weather effects.

Local identification of persistent cold air pool conditions in the Great Hungarian Plain

Időjárás ◽  
2021 ◽  
Vol 125 (2) ◽  
pp. 167-192
Author(s):  
Karolina Szabóné André ◽  
Judit Bartholy ◽  
Rita Pongrácz ◽  
József Bór
Keyword(s):  
Meteorological Data ◽  
Weather Conditions ◽  
Reanalysis Data ◽  
Weather Event ◽  
Cold Air ◽  
Great Hungarian Plain ◽  
Winter Time ◽  
Heat Deficit ◽  
Local Detection ◽  
Hungarian Plain

Cold air pool (CAP) is a winter-time, anticyclonic weather event: a cold air layer confined by the topography and warm air aloft. If its duration is more than one day, then it is called persistent cold air pool (PCAP). CAPs are mainly examined in small basins and valleys. Fewer studies pay attention to PCAPs in much larger basins (with an area of more than 50 000 km2), and it is not evident how effective the existing numerical definitions are in cases of extensive PCAP events. A possible method of identifying PCAPs in a large basin is to identify PCAP weather conditions at different measuring sites across the basin. If there are PCAP weather conditions at most of the sites, then it is likely to be an extensive PCAP. In this work, we examine which of the documented CAP definitions can be used for reliable local detection of CAP conditions. Daily weather reports and meteorological data from two locations in the 52 000 km2 sized Great Hungarian Plain have been used to obtain a reference set of days with PCAP weather conditions during two consecutive winter months. Several numerical CAP definitions were compared for their performance in recognizing the presence of PCAP weather conditions using radiosonde measurements and reanalysis data. The lowest error was produced by using the heat deficit (HD) method. So this is considered the most suitable method for local identification of PCAPs in the Great Hungarian Plain.

A hierarchy of atmospheric effects and laser beam detection

2014 ◽  
Author(s):  
John Stephen deGrassie ◽  
Stephen Hammel
Keyword(s):  
Laser Beam ◽  
Atmospheric Effects

Meteorological study for Gangotri Glacier and its comparison with other high altitude meteorological stations in central Himalayan region

2007 ◽  
Vol 38 (1) ◽  
pp. 59-77 ◽  
Author(s):  
Pratap Singh ◽  
Umesh K. Haritashya ◽  
Naresh Kumar
Keyword(s):  
High Altitude ◽  
Meteorological Data ◽  
Weather Conditions ◽  
Meteorological Station ◽  
Himalayan Region ◽  
Valley Wind ◽  
Maximum Rainfall ◽  
Garhwal Himalayas ◽  
Wind Speeds ◽  
Gangotri Glacier

In spite of the vital role of high altitude climatology in melting of snow and glaciers, retreat or advancement of glaciers, flash floods, erosion and sediment transport, etc., weather conditions are not much studied for the high altitude regions of Himalayas. In this study, a comprehensive meteorological analysis has been made for the Gangotri Meteorological Station (Bhagirathi Valley, Garhwal Himalayas) using data observed for four consecutive melt seasons (2000–2003) covering a period from May to October for each year. The collected meteorological data includes rainfall, temperature, wind speed and direction, relative humidity, sunshine hours and evaporation. The results and their distribution over the different melt seasons were compared with available meteorological records for Dokriani Meteorological Station (Dingad Valley, Garhwal Himalayas) and Pyramid Meteorological Station (Khumbu Valley, Nepal Himalayas). The magnitude and distribution of temperature were found to be similar for different Himalayan regions, while rainfall varied from region to region. The influence of the monsoon was meagre on the rainfall in these areas. July was recorded to be the warmest month for all the regions and, in general, August had the maximum rainfall. For all the stations, daytime up-valley wind speeds were 3 to 4 times stronger than the nighttime down-valley wind speeds. It was found that the Gangotri Glacier area experienced relatively low humidity and high evaporation rates as compared to other parts of the Himalayas. Such analysis reveals the broad meteorological characteristics of the high altitude areas of the Central Himalayan region.

scholarly journals Meteorology in field artillery ballistic calculations

2021 ◽  
Vol 2090 (1) ◽  
pp. 012149
Author(s):  
M Mendel
Keyword(s):  
Atmospheric Pressure ◽  
Open Space ◽  
Meteorological Parameters ◽  
Meteorological Data ◽  
Armed Forces ◽  
Weather Conditions ◽  
Atmospheric Conditions ◽  
Area Of Interest ◽  
Single Probe ◽  
Atmospheric Data

Abstract The most important meteorological data are:ambient temperature, precipitation quantity, air humidity, amount and type of clouds, atmospheric pressure, wind direction and speed, visibility, weather phenomena. These coefficients impact the effectiveness of various combat activities, especially those conducted in an open space. Knowledge of future weather conditions is essential for planning the location, calculating times, choice of means, and other aspects relevant to the upcoming operations. Taking weather conditions into account is vital, specifically when it comes to planning combat operations, where the accuracy in cooperation is of paramount importance. Rocket forces and artillery is a particular type of armed forces where weather conditions are critical. The effectiveness of artillery depends on ballistic calculation precision, and so knowledge of atmospheric conditions is fundamental. Atmospheric data are collected from sounding using a single probe attached to a balloon. It is generally known that particular meteorological parameters change in a smooth spatial manner depending on various coefficients. Information about the atmosphere collected by a single probe may be insufficient, due to the possibility of a balloon drifting away from the area of interest, and the calculations are based on data received from its probe. In this paper, I will suggest a method for preparing artillery use meteorologically, which takes into account the distribution of particular meteorological coefficients over a given area.

scholarly journals ROUTINE, EXTREME AND ENGINEERING METEOROLOGY ANALYSIS FOR KARACHI COASTAL AREA

2020 ◽  
Vol 4 (1) ◽  
pp. 15-22
Author(s):  
Muhammad Taqui ◽  
Jabir Hussain Syed ◽  
Ghulam Hassan Askari
Keyword(s):  
Climate Change ◽  
Coastal Area ◽  
Meteorological Parameters ◽  
Meteorological Data ◽  
Weather Conditions ◽  
Meteorological Station ◽  
Annual Precipitation ◽  
Maximum Temperature ◽  
Intergovernmental Panel ◽  
Interdisciplinary Field

Pakistan’s largest city, Karachi, which is industrial centre and economic hub needs focus in research and development of every field of Engineering, Science and Technology. Urbanization and industrialization is resulting bad weather conditions which prolongs until a climate change. Since, Meteorology serves as interdisciplinary field of study, an analytical study of real and region-specific meteorological data is conducted which focuses on routine, extreme and engineering meteorology of metropolitan city Karachi. Results of study endorse the meteorological parameters relationship and establish the variability of those parameters for Karachi Coastal Area. The rise of temperature, decreasing trend of atmospheric pressure, increment in precipitation and fall in relative humidity depict the effects of urbanization and industrialization. The recorded extreme maximum temperature of 45.50C (on June 11, 1988) and the extreme minimum temperature of 4.5 0C(on January 1, 2007) is observed at Karachi south meteorological station. The estimated temperature rise in 32 years is 0.9 0C, which is crossing the Intergovernmental Panel on Climate Change (IPCC) predicted/estimated limit of 2oC rise per century. The maximum annual precipitation of 487.0mm appearing in 1994 and the minimum annual precipitation of 2.5mm appearing in 1987 is observed at same station which is representative meteorological station for Karachi Coast. Further Engineering meteorological parameters for heating ventilation air condition (HVAC) system design for industrial purpose are deduced as supporting data for coastal area site study for industrial as well as any follow-up engineering work in the specified region.

scholarly journals A parameterization of Long-Continuing-Current (LCC) lightning in the lightning submodel LNOX (version 3.0) of the Modular Earth Submodel System (MESSy, version 2.54)

2021 ◽  
Author(s):  
Francisco Javier Pérez-Invernón ◽  
Heidi Huntrieser ◽  
Patrick Jöckel ◽  
Francisco J. Gordillo-Vázquez
Keyword(s):  
Meteorological Data ◽  
Space Station ◽  
Low Frequency ◽  
Electrical Current ◽  
Pressure Level ◽  
Convective Precipitation ◽  
Atmospheric Models ◽  
Optical Instruments ◽  
Current Flows ◽  
Imaging Sensor

Abstract. Lightning flashes can produce a discharge in which a continuing electrical current flows for more than 40 ms. This type of flashes are proposed to be the main precursors of lightning-ignited wildfires and also to trigger sprite discharges in the mesosphere. However, lightning parameterizations implemented in global atmospheric models do not include information about the continuing electrical current of flashes. The continuing current of lightning flashes cannot be detected by conventional lightning location systems. Instead, these so-called Long-Continuing-Current (LCC) flashes are commonly observed by Extreme Low Frequency (ELF) sensors and by optical instruments located in space. Previous reports of LCC lightning flashes tend to occur in winter and oceanic thunderstorms, which suggests a connection between weak convection and the occurrence of this type of discharge. In this study, we develop a parameterization of LCC lightning flashes based on a climatology derived from optical lightning measurements reported by the Lightning Imaging Sensor (LIS) on-board the International Space Station (ISS) between March 2017 and March 2020. We use meteorological data from reanalyses to find a global parameterization that uses the vertical velocity at 450 hPa pressure level as a proxy for the ratio of LCC to typical lightning in thunderstorms. We implement this parameterization into the LNOX submodel of the Modular Earth Submodel System (MESSy) for usage within the EMAC model, and compare the observed and the simulated climatologies of LCC lightning flashes using six different lightning parameterizations. We find that the best agreement between the simulated and the observed spatial distribution is obtained when using a novel combined lightning parameterization based on the cloud top height over land and on the convective precipitation over ocean.

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