scholarly journals GPS Meteorology : Error in the estimation of precipitable water by ground based GPS system in some meso-scale thunderstorms - A case study

MAUSAM ◽  
2021 ◽  
Vol 71 (2) ◽  
pp. 175-186
Author(s):  
PUVIARASAN N ◽  
YADAV RAMASHRAY ◽  
GIRI R K ◽  
SINGH VIRENDRA
Keyword(s):  
Atmospheric Condition ◽  
Mapping Function ◽  
Precipitable Water ◽  
Heavy Rain ◽  
Gps Receiver ◽  
Squall Lines ◽  
Gps Satellites ◽  
Gps System ◽  
Gps Station

Remote sensing by ground based GPS receivers provide continuous and accurate measurement of precipitable water (PW) of an order of 1.5 mm comparable to radiosondes and water vapour radiometers.  In the present work we have examined the amount of PW variation in three thunderstorms accompanied with rain shower that occurred over the GPS station.  In all the three thunderstorms event heavy rain was reported.  However on comparison of observed rainfall with GPS estimated precipitable water (hourly) in real time, it is observed that among the three, in one event the amount of precipitable water (PW) is much less (~20mm) for the same amount of rainfall.  After analysing and taken into account various source of error, we suspect that in a mesoscale thunderstorms or squall lines associated with heavy rainfall, discrepancies arise because the wet mapping functions that used to map the wet delay at any angle to the zenith do not represent the localized atmospheric condition particularly for narrow towering thunder clouds and non-availability of GPS satellites in the zenith direction.  On the other hand for the larger thunder cells the atmosphere is very nearly azimuthally symmetric with respect to GPS receiver, the error due to the wet mapping function is minimal.

Satellite Differential Code Bias Estimated Using EGYNET: A Local Egyptian Permanent Network

2020 ◽  
Vol 19 (6) ◽  
pp. 453-459
Author(s):  
Mohammed A. Abid ◽  
Ashraf Mousa
Keyword(s):  
Gps Data ◽  
Gps Receiver ◽  
Gps Receivers ◽  
Differential Code Bias ◽  
Gps Satellites ◽  
Four Seasons ◽  
Algorithm Operation ◽  
Code Bias ◽  
Comparison Of The Results ◽  
Gps Station

This paper proposes to determine the GPS satellites DCB using nine GPS receivers located in the middle of Egypt. During four seasons and 36 days characterized by quiet geomagnetism, the performance of the proposed method is examined. The dual GPS data selected is used and applied to the GPS receiver chain notes. The Bernese program V.5 is used to estimate DCBs from the data of a single GPS station where the results of the algorithm operation are compared to the CODE DCB data and the main differences in GLONASS data are recorded. According to the comparison of the results between the proposed method and the currently existing methods, it can be shown that the accuracy of the DCB estimates is at a level of about 0.31 and 0.17 ns.

scholarly journals Ionic Runoff as a Way to Determine the Degree of Karst Denudation (Case Study Jasov Plateau, Slovak Karst, Slovakia)

Water ◽  
2021 ◽  
Vol 13 (11) ◽  
pp. 1449
Author(s):  
Alena Gessert ◽  
Imrich Sládek ◽  
Veronika Straková ◽  
Mihály Braun ◽  
Enikő Heim ◽  
...  
Keyword(s):  
Heavy Rain ◽  
Similar Amount ◽  
Karst Water ◽  
Karst Spring ◽  
Snow Melting ◽  
Flow Rates ◽  
Karst Springs ◽  
Degree Of Protection ◽  
Episodic Events

Estimation of the catchment area of a karst spring is not possible in all areas for various reasons. The Slovak Karst is protected by the highest degree of protection and karst springs are used as a source of drinking water for the second largest city in Slovakia, Košice. From this reason, no results on ionic runoff or chemical denudation have been published from this area and the most appropriate way to obtain information about the denudation rate is to determine the ionic runoff. This paper provides an overview of ionic runoff results based on sampling and analysis of karst water from six springs in the period November 2013–October 2016 (three hydrological years) and periodic measurements. Springs have significantly fluctuated flow rates from 0 L/s in summer and autumn up to 192 L/s, and episodic events during the snow melting and heavy rain in the spring of 2013 are also known (more than 380 L/s). The total value of ionic runoff for the area of 40,847 m3/y.km2 is comparable with the Vracanska Plateau in Bulgaria, which lies at a similar altitude and with a similar amount of precipitation.

Impact of radar data assimilation on simulations of precipitable water with the Harmonie model: A case study over Cyprus

2021 ◽  
Vol 253 ◽  
pp. 105473
Author(s):  
Serguei Ivanov ◽  
Silas Michaelides ◽  
Igor Ruban ◽  
Demetris Charalambous ◽  
Filippos Tymvios
Keyword(s):  
Data Assimilation ◽  
Precipitable Water ◽  
Radar Data ◽  
Radar Data Assimilation

scholarly journals The Use of Laser Precipitation Monitor (LPM) of Disdrometer and Weather Radar to Determine the Microphysics Characteristics of Extreme Rainfall in Jakarta. (Jakarta Flood Case Study February 25, 2020)

2021 ◽  
Vol 893 (1) ◽  
pp. 012017
Author(s):  
I D G A Putra ◽  
A Sopaheluwakan ◽  
B P Adi ◽  
K A Sudama ◽  
J Rizal ◽  
...  
Keyword(s):  
Extreme Rainfall ◽  
Weather Radar ◽  
Heavy Rain ◽  
Maximum Diameter ◽  
Convective Clouds ◽  
Data Volume ◽  
Accumulated Rainfall ◽  
The One ◽  
The Relationship

Abstract Heavy rains on February 24, 2020, caused flooding in most parts of Jakarta and its surroundings. The one-day observation of accumulated rainfall from the Laser Precipitation Monitor (LPM) was recorded at 358.6 mm/day at the Kemayoran station on February 25, 2020, at 00.00 UTC (07.00 Jakarta Time). In this study, analysis of the microphysical characteristics of extreme rainfall using LPM installed at Kemayoran meteorology station and weather radar at Cengkareng meteorology station with a spatial radius of 250 km. LPM is used to measure the diameter of the raindrops, the velocity of falling raindrops, LPM reflectivity, and the amount of accumulated rainfall with time resolution per minute and stored in excel data format. While the weather radar is used to measure the reflectivity spatially and temporally in the data volume format (.vol). The method used is, first, to find the relationship between LPM reflectivity and the amount of LPM rainfall with regression analysis. Second, the radar reflectivity is converted into estimated rainfall intensity for the Jakarta area and its surroundings. The results of this study found a relationship between LPM reflectivity (X) and rainfall accumulation LPM (Y) to form a regression relationship with the formula Y = 0.013X with R2 = 0.3777. Based on the record of the LPM time series, the peak of rainfall occurred at 18.17 UTC with 1000 raindrops, the maximum fall speed was 10 m/s, and the maximum diameter is 8.5 millimeters. Based on the results of microphysical measurements of LPM, spatial plots, and vertical cross-section radar, it can be concluded that flooding in Jakarta is due to heavy rain from convective clouds.

scholarly journals Comments on “Incorporating the Effects of Moisture into a Dynamical Parameter: Moist Vorticity and Moist Divergence”

2016 ◽  
Vol 31 (4) ◽  
pp. 1393-1396 ◽  
Author(s):  
David M. Schultz ◽  
Thomas Spengler
Keyword(s):  
Relative Humidity ◽  
Potential Vorticity ◽  
Single Case ◽  
Heavy Rain ◽  
Relative Vorticity ◽  
Dynamical Parameter ◽  
Accumulated Rainfall ◽  
Moist Potential Vorticity ◽  
Model Precipitation

Abstract In a recent article, Qian et al. introduced the quantities moist vorticity and moist divergence to diagnose locations of heavy rain. These quantities are constructed by multiplying the relative vorticity and divergence by relative humidity to the power k, where k = 10 in their article. Their approach is similar to that for the previously constructed quantity generalized moist potential vorticity. This comment critiques the approach of Qian et al., demonstrating that the moist vorticity, moist divergence, and by extension generalized moist potential vorticity are flawed mathematically and meteorologically. Raising relative humidity to the 10th power is poorly justified and is based on a single case study at a single time. No meteorological evidence is presented for why areas of moist vorticity and moist divergence should overlap with regions of 24-h accumulated rainfall. All three quantities have not been verified against the output of precipitation directly from the model nor is the approach of combining meteorological quantities into a single parameter appropriate in an ingredients-based forecasting approach. Researchers and forecasters are advised to plot the model precipitation directly and employ an ingredients-based approach, rather than rely on these flawed quantities.

Topographic amplification of crustal subsidence by the rainwater load of the 2018 heavy rain in SW Japan

2021 ◽  
Author(s):  
Syachrul Arief
Keyword(s):  
Water Vapor ◽  
Precipitable Water ◽  
Heavy Rain ◽  
Satellite System ◽  
Rain Gauge ◽  
Precipitable Water Vapor ◽  
Surface Load ◽  
Rain Area ◽  
Movement Data ◽  
Sw Japan

<p>The huge amount of water vapor in the atmosphere caused disastrous heavy rain and floods in early July 2018 in SW Japan. Here I present a comprehensive space geodetic study of water brought by this heavy rain done by using a dense network of Global Navigation Satellite System (GNSS) receivers. </p><p>First, I reconstruct sea level precipitable water vapor above land region on the heavy rain. The total amount of water vapor derived by spatially integrating precipitable water vapor on land was ~25.8 Gt, which corresponds to the bucket size to carry water from ocean to land. I then compiled the precipitation measured with a rain radar network. The data showed the total precipitation by this heavy rain as ~22.11 Gt.</p><p>Next, I studied the crustal subsidence caused by the rainwater as the surface load. The GNSS stations located under the heavy rain area temporarily subsided 1-2 centimeters and the subsidence mostly recovered in a day. Using such vertical crustal movement data, I estimated the distribution of surface water in SW Japan. </p><p>The total amount of the estimated water load on 6 July 2018 was ~68.2 Gt, which significantly exceeds the cumulative on-land rainfalls of the heavy rain day from radar rain gauge analyzed precipitation data. I consider that such an amplification of subsidence originates from the selective deployment of GNSS stations in the concave places, e.g. along valleys and within basins, in the mountainous Japanese Islands.</p>

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