scholarly journals An overview of rain attenuation research in Bangladesh

2021 ◽  
Vol 23 (2) ◽  
pp. 902
Author(s):  
Md Abdus Samad ◽  
Md. Razu Ahmed ◽  
Syed Zahidur Rashid
Keyword(s):  
Signal To Noise Ratio ◽  
Model Development ◽  
Rain Attenuation ◽  
Climatic Conditions ◽  
Telecommunication Networks ◽  
60 Ghz ◽  
Attenuation Model ◽  
Frequency Bands ◽  
Backbone Networks ◽  
June July

The demands of shifting to the operating frequency of wireless telecommunication systems at new higher frequency bands increase as day by day the necessity to transfer more data volume through wireless networks. Bangladesh has launched its first satel-lite, Bangabandhu-1, with 40 communication channels in the C and Ku frequency bands. Besides, a huge volume of terrestrial microwave backbone networks suffer from fading during rain across the country. Bangladesh experiences heavy rainfall in June-July-August. The rain has a remarkable impact on deteriorating the signal-to-noise ratio at the receiver end. To implement the 5G network, 2.6–60 GHz frequency bands are promising. However, the propagated waves in these bands are prone to fadedue to rain. Unfortunately, the rain attenuation model developed for other climatic conditions can not be used readily without customization. In this regard, to maintain quality telecommunication networks, proper rain attenuation model development is crucial. This work reviews rain attenuation research in Bangladesh, global research trends and the research scope to manage rain attenuation.

scholarly journals Optimized Merging of Search Coil and Fluxgate Data for MMS

2016 ◽  
Author(s):  
David Fischer ◽  
Werner Magnes ◽  
Christian Hagen ◽  
Ivan Dors ◽  
Mark W. Chutter ◽  
...  
Keyword(s):  
High Speed ◽  
Signal To Noise Ratio ◽  
Model Development ◽  
Frequency Bands ◽  
Search Coil ◽  
Precise Knowledge ◽  
Combining Data ◽  
Unity Gain ◽  
Magnetospheric Multiscale Mission ◽  
Compensation Approach

Abstract. The Magnetospheric Multiscale mission (MMS) targets the characterization of fine scale current structures in the Earth's tail and magnetopause. The high speed of these structures, when traversing one of the MMS spacecraft, creates magnetic field signatures that cross the sensitive frequency bands of both search coil and fluxgate magnetometers. Higher data quality for analysis of these events can be achieved by combining data from both instrument types and using the frequency bands with best sensitivity and signal to noise ratio from both sensors. This can be achieved by a model based frequency 20 compensation approach which requires the precise knowledge of instrument gain and phase properties. We discuss relevant aspects of the instrument design, the ground calibration activities, describe the model development and explain the application on in-flight data. Finally, we show the precision of this method by comparison of inflight data. It confirms unity gain and a time difference of less than 100 μs between the different magnetometer instruments.

scholarly journals Optimized merging of search coil and fluxgate data for MMS

2016 ◽  
Vol 5 (2) ◽  
pp. 521-530 ◽  
Author(s):  
David Fischer ◽  
Werner Magnes ◽  
Christian Hagen ◽  
Ivan Dors ◽  
Mark W. Chutter ◽  
...  
Keyword(s):  
High Speed ◽  
Signal To Noise Ratio ◽  
Model Development ◽  
Flight Data ◽  
Frequency Bands ◽  
Search Coil ◽  
Precise Knowledge ◽  
Combining Data ◽  
Magnetospheric Multiscale Mission ◽  
Compensation Approach

Abstract. The Magnetospheric Multiscale mission (MMS) targets the characterization of fine-scale current structures in the Earth's tail and magnetopause. The high speed of these structures, when traversing one of the MMS spacecraft, creates magnetic field signatures that cross the sensitive frequency bands of both search coil and fluxgate magnetometers. Higher data quality for analysis of these events can be achieved by combining data from both instrument types and using the frequency bands with best sensitivity and signal-to-noise ratio from both sensors. This can be achieved by a model-based frequency compensation approach which requires the precise knowledge of instrument gain and phase properties. We discuss relevant aspects of the instrument design and the ground calibration activities, describe the model development and explain the application on in-flight data. Finally, we show the precision of this method by comparison of in-flight data. It confirms unity gain and a time difference of less than 100 µs between the different magnetometer instruments.

DROUGHT OCCURRENCE UNDER LITHUANIAN CLIMATIC CONDITIONS

2015 ◽  
Author(s):  
Laima TAPARAUSKIENĖ ◽  
Veronika LUKŠEVIČIŪTĖ
Keyword(s):  
Meteorological Data ◽  
Standardized Precipitation Index ◽  
Vegetation Period ◽  
Climatic Conditions ◽  
Precipitation Record ◽  
Calculation Step ◽  
Drought Conditions ◽  
The Standardized Precipitation Index ◽  
June July

This study provides the analysis of drought conditions of vegetation period in 1982-2014 year in two Lithuanian regions: Kaunas and Telšiai. To identify drought conditions the Standardized Precipitation Index (SPI) was applied. SPI was calculated using the long-term precipitation record of 1982–2014 with in-situ meteorological data. Calculation step of SPI was taken 1 month considering only vegetation period (May, June, July, August, September). The purpose of investigation was to evaluate the humidity/aridity of vegetation period and find out the probability of droughts occurrence under Lithuanian climatic conditions. It was found out that according SPI results droughts occurred in 14.5 % of all months in Kaunas region and in 15.8 % in Telšiai region. Wet periods in Kaunas region occurred in 15.8 %, and in Telšiai region occurrence of wet periods was – 18.8 % from all evaluated months. According SPI evaluation near normal were 69.7 % of total months during period of investigation in Kaunas and respectively – 65.5 % in Telšiai. The probability for extremely dry period under Lithuania climatic conditions are pretty low – 3.0 % in middle Lithuania and 2.4 % in western part of Lithuania.

Does the Signal-to-Noise Paradox Exist in Subseasonal Predictions?

2021 ◽  
Author(s):  
Wei Zhang ◽  
Baoqiang Xiang ◽  
Ben Kirtman ◽  
Emily Becker
Keyword(s):  
Signal To Noise Ratio ◽  
Current Model ◽  
Model Development ◽  
Coupled Model ◽  
Seasonal Prediction ◽  
Signal To Noise ◽  
Model Framework ◽  
Noise Ratio ◽  
Decadal Climate ◽  
New Generation

<p>One of the emerging topics in climate prediction is the issue of the so-called “signal-to-noise paradox”, characterized by too small signal-to-noise ratio in current model predictions that cannot reproduce the realistic signal. Recent studies have suggested that seasonal-to-decadal climate can be more predictable than ever expected due to the paradox. But no studies, to the best of our knowledge, have been focused on whether the signal-to-noise paradox exists in subseasonal predictions. The present study seeks to address the existence of the paradox in subseasonal predictions based on (i) coupled model simulations participating in phase 5 and phase 6 of the Coupled Model Intercomparison Project (CMIP5 and CMIP6, respectively), and (ii) subseasonal hindcast outputs from the Subseasonal Experiment (SubX) and the Subseasonal-to-Seasonal Prediction (S2S) projects. Of particular interest is the possible existence of the paradox in the new generation of GFDL SPEAR model, through the diagnosis of which may help identify potential issues in the new forecast system to guide future model development and initialization. Here we investigate the paradox issue using two methods: the ratio of predictable component defined as the ratio of predictable component in the real world to the signal-to-noise ratio in models and the persistence/dispersion characteristics estimated from a Markov model framework. The preliminary results suggest a potentially widespread occurrence of the signal-to-noise paradox in subseasonal predictions, further implying some room for improvement in future ensemble-based subseasonal predictions.</p>

Effect of pre-utilisation and harvest time on the quantity and quality of fodder on extensive pastures

2010 ◽  
Vol 58 (2) ◽  
pp. 185-193 ◽  
Author(s):  
M. Bajnok ◽  
L. Szemán ◽  
J. Tasi
Keyword(s):  
Festuca Arundinacea ◽  
Dry Matter ◽  
Weather Conditions ◽  
Climatic Conditions ◽  
Energy Concentration ◽  
List Type ◽  
Regeneration Period ◽  
Yield And Quality ◽  
June July

No significant studies have yet been reported in Central Europe on the yield and quality of winter harvest pastures. The aim of the research was to collect information about the effect of pre-utilisation (June, July and August) and winter harvest date (November, December, January) on the quantity and quality of fodder from Festuca arundinacea stands. The dry matter, energy, ADF, ADL and ergosterol contents of the yield were examined and it was found that: 1. A shorter regeneration period between harvests resulted in lower dry matter levels, but also in a higher energy concentration and lower ergosterol concentration. 2. The yield and energy concentrations decreased, whereas the ADF, ADL and ergosterol concentrations increased as the winter progressed. 3. Fodder harvested in November produced the best results in terms of yield quantity and quality. The highest yield and energy values were thus achieved by harvesting in November, regardless of pre-utilisation. Despite the cold and the long period of snow cover, the energy values of samples harvested in December and January showed no significant decrease. The weather conditions were more important for fodder quantity and quality than the frequency or date of harvesting. Thus, under the continental climatic conditions in Hungary, extensive utilisation, until late November or early December, is recommended.

scholarly journals A physically based rain attenuation model for terrestrial links

Radio Science ◽  
2017 ◽  
Vol 52 (8) ◽  
pp. 972-980 ◽  
Author(s):  
R. Ghiani ◽  
L. Luini ◽  
A. Fanti
Keyword(s):  
Rain Attenuation ◽  
Attenuation Model ◽  
Physically Based

scholarly journals Recognition method of radar intra-pulse modulation type based on signal square spectrum bandwidth ratio

2021 ◽  
Vol 2021 (1) ◽  
Author(s):  
Dongmei Li ◽  
Zhiyuan Xu ◽  
Lei Gu ◽  
Lanxiang Zhu
Keyword(s):  
Signal To Noise Ratio ◽  
Signal Reconstruction ◽  
Noise Signal ◽  
Reconstruction Error ◽  
Information Warfare ◽  
60 Ghz ◽  
Bandwidth Utilization ◽  
Pulse Modulation ◽  
Electronic Warfare ◽  
Time Frequency

AbstractThe twenty-first century is the era of electronic warfare and information warfare. The focus is of the battle between all parties. CEEMD can link the time domain and frequency domain, describe the two-dimensional time–frequency characteristics of the signal, and draw the time–frequency diagram of the signal, so as to reduce the noise signal and improve the signal-to-noise ratio of the signal. The purpose of this paper was to study how to adjust the signal square spectrum bandwidth ratio in the subject of identifying the intra-pulse modulation of radar, so as to solve the problem of identifying the type of radar intra-pulse modulation. The experimental results in this paper show that the decomposition result of EEMD is incomplete and the signal reconstruction error is larger. Compared with the previous two methods, not only the CEEMD method can effectively suppress modal aliasing, but also the decomposition result is complete; the signal reconstruction error is very small, and the decomposition results close to ideal value. The interleaving filter with a bandwidth ratio of 1:2 can divide the 100 GHz channel spacing into asymmetric output spectra with bandwidths greater than 60 GHz and 30 GHz, which effectively improves the current mix of 10 Gb/s and 40 Gb/s The bandwidth utilization of the system illustrates the success of the simulation experiment.

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