Study of GPS instrumental bias and TEC estimations from GPS stations in Thailand

Author(s):  
Athiwat Chiablaem ◽  
Watid Phakphisut ◽  
Pomchai Supnithi
Keyword(s):  
2008 ◽  
Vol 8 (5) ◽  
pp. 1391-1402 ◽  
Author(s):  
M. Scherer ◽  
H. Vömel ◽  
S. Fueglistaler ◽  
S. J. Oltmans ◽  
J. Staehelin

Abstract. This paper presents an updated trend analysis of water vapour in the lower midlatitude stratosphere from the Boulder balloon-borne NOAA frostpoint hygrometer measurements and from the Halogen Occulation Experiment (HALOE). Two corrections for instrumental bias are applied to homogenise the frostpoint data series, and a quality assessment of all soundings after 1991 is presented. Linear trend estimates based on the corrected data for the period 1980–2000 are up to 40% lower than previously reported. Vertically resolved trends and variability are calculated with a multi regression analysis including the quasi-biennal oscillation and equivalent latitude as explanatory variables. In the range of 380 to 640 K potential temperature (≈14 to 25 km), the frostpoint data from 1981 to 2006 show positive linear trends between 0.3±0.3 and 0.7±0.1%/yr. The same dataset shows trends between −0.2±0.3 and 1.0±0.3%/yr for the period 1992 to 2005. HALOE data over the same time period suggest negative trends ranging from −1.1±0.2 to −0.1±0.1%/yr. In the lower stratosphere, a rapid drop of water vapour is observed in 2000/2001 with little change since. At higher altitudes, the transition is more gradual, with slowly decreasing concentrations between 2001 and 2007. This pattern is consistent with a change induced by a drop of water concentrations at entry into the stratosphere. Previously noted differences in trends and variability between frostpoint and HALOE remain for the homogenised data. Due to uncertainties in reanalysis temperatures and stratospheric transport combined with uncertainties in observations, no quantitative inference about changes of water entering the stratosphere in the tropics could be made with the mid latitude measurements analysed here.


1988 ◽  
Vol 130 ◽  
pp. 569-569
Author(s):  
Arlin P. S. Crotts

SummaryIf voids like those seen in the low z galaxy distribution existed in the H I distribution at z ≈ 2, then high quality QSO spectra, with many Ly-α forest lines per unit z, could be used to discern the voids from the usual random fluctuations in observed number density of lines (≡ n). Several such spectra have been obtained, and these show evidence for gaps in the Ly-α distribution on scales of 20 to 50 h−1Mpc (comoving coordinates, with h = H0/66.7 km s−1Mpc−1, assuming q0 = 0.1). These results are summarized in the table below. All QSO spectra with a line-of-sight n of Ly-α lines n > 80 per unit z and total number of lines N > 40 known to the author are included (except that of PKS 2000-330 [c.f. Carswell and Rees 1987], which is broken into five separate segments of Ly-α forest by gaps in the data and a broad absorption line). Excluded are portions of these spectra where n falls more than 25% below the mean due to instrumental bias. For each of these the distribution of gaps between nearest-neighbor Ly-α redshifts is computed as a function of gap size. If the distribution of redshifts were Poisson, the distribution of gaps should be a decreasing exponential function of gap size. For the two best spectra, large deviations from an exponential are found in the range of 20 to 50 h−1Mpc (in the other four cases, it should be noted that a large number of gaps of such sizes are still expected from Poisson fluctuations). The probability that such deviations are statistically consistent with an exponential distribution is shown in the fifth column of the table.


2020 ◽  
Author(s):  
Leena Leppänen ◽  
Juan Ignazio Lopez-Moreno ◽  
Bartłomiej Luks ◽  
Ladislav Holko ◽  
Ghislain Picard ◽  
...  

<p>Manually collected snow data can be considered as ground truth for many applications, such as climatological or hydrological studies. Water equivalent of snow cover (SWE) can be manually measured by using a snow tube or snow cylinder to extract a snow core and measure the bulk density of the core by weighing it. Different snow core samplers and scales are used, but they all use the same measurement principle. However, there are various sources of uncertainty that have not been quantified in detail. To increase the understanding of these errors, different manual SWE measurement devices used across Europe were evaluated within the framework of the COST Action ES1404 HarmoSnow. Two field campaigns were organized in different environments to quantify uncertainties when measuring snow depth, snow bulk density and SWE with core samplers. The 1<sup>st</sup> field campaign in 2017 in Iceland focused on measurement differences attributed to different instrumentation compared with the natural variability in the snowpack, and the 2<sup>nd</sup> field campaign in 2018 in Finland focused on device comparison and on the separation of the different sources of variability. To our knowledge, such a comparison has not previously been conducted in terms of the number of device and different environments.</p><p>During the 1<sup>st</sup> campaign, repeated measurements were taken along two 20 m long snow trenches to distinguish snow variability measured at the plot and at the point scale. The results revealed a much higher variability of SWE at the plot scale, resulting from both natural variability and instrument bias, compared to repeated measurements at the same spot, resulting mostly from error induced by observers or a high variability in the snow depth. Snow Micro Pen sampling showed that the snowpack was very homogeneous for the 2<sup>nd</sup> campaign, which allowed for the disregarding of the natural variability of the snowpack properties and the focus to be on separating between instrumental bias and error induced by observers. Results confirmed that instrumental bias exceeded both the natural variability and the error induced by observers, even when observers performed measurements with snow core samplers they were not formally trained on. Under such measurement conditions, the uncertainty in bulk snow density estimation is about 5% for an individual instrument and is close to 10% among different instruments. The results showed that the devices provided slightly different uncertainties since they were designed for different snow conditions. The aim of this comparison was not to provide a definitive estimation of uncertainty for manual SWE measurements, but to illustrate the role of the different uncertainty sources.</p>


2011 ◽  
Vol 4 (4) ◽  
pp. 5569-5595
Author(s):  
X. Muth ◽  
M. Schneebeli ◽  
A. Berne

Abstract. Accurate positioning of data collected by a weather radar is of primary importance for their appropriate georeferencing, which in turn makes it possible to combine those with additional sources of information (topography, land cover maps, meteorological simulations from numerical weather models to list a few). This issue is especially acute for mobile radar systems, for which accurate and stable levelling might be difficult to ensure. The sun is a source of microwave radiation, which can be detected by weather radars and used for the accurate positioning of the radar data. This paper presents a technique based on the sun echoes to quantify and hence correct for the instrumental errors which can affect the pointing accuracy of radar antenna. The proposed method is applied to data collected in the Swiss Alps using a mobile X-band radar system. The obtained instrumental bias values are evaluated by comparing the locations of the ground echoes predicted using these bias estimates with the observed ground echo locations. The very good agreement between the two confirms the good accuracy of the proposed method.


Authorea ◽  
2019 ◽  
Author(s):  
Ignacio Lopez Moreno ◽  
Leena Lepp nen ◽  
Bart omiej Luks ◽  
Ladislav Holko ◽  
Ghislain Picard ◽  
...  

2020 ◽  
Vol 34 (14) ◽  
pp. 3120-3133
Author(s):  
J. Ignacio López‐Moreno ◽  
Leena Leppänen ◽  
Bartłomiej Luks ◽  
Ladislav Holko ◽  
Ghislain Picard ◽  
...  

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