scholarly journals Monitoring the Short-term Variations in the Stability of the Nigerian GNSS CORS Diurnal Coordinates

2021 ◽  
Vol 5 (2) ◽  
pp. 545-554
Author(s):  
M. Moses ◽  
S. Bawa ◽  
I. Nzelibe ◽  
E.A. Akomolafe ◽  
B. Samson
Keyword(s):  
Time Series ◽  
Network Services ◽  
Reference Network ◽  
Observation Data ◽  
Short Term ◽  
Diverse Range ◽  
The Stability ◽  
Coordinate Changes ◽  
Monitoring Module ◽  
Python Programming

Positioning, based on GNSS reference network technology, is becoming a routine operation within and outside the spatial industry. The expanding user base and diverse range of applications employing this technology can impose significant expectations on the providers of reference network services. In positioning and navigation, the requirement for high accurate coordinate estimates cannot be over-emphasized. This is ensured by the provision of accurate and reliable corrections from the zero-order GNSS reference stations. It is therefore expedient to study the diurnal coordinates of such stations to guarantee reliable information for positioning and navigation applications. In this study, observation data from the Nigerian permanent GNSS continuously operating reference stations located at different states around Nigeria was processed. The hourly and diurnal (daily) coordinate solutions obtained were analysed for the purpose of monitoring the short-term stability of the network coordinates using a two-year (2012-2013) test data. The daily precise point positioning results were processed, analysed, and presented as coordinate time series using RTKPLOT. Python programming language was used to write custom modules to visualize the time series graphs at 30 seconds epochs in order to determine points and epochs where and when the condition for stability defaulted. The stations; FPNO, GEMB, and MDGR were found to be most stable in the Easting component; GEMB and MDGR were the most stable in the Northing component while in the Up component the station GEMB was the most stable. The outcome of the study will assist in detecting stations that are non-operational, performing diurnal PPP processing to detect stations that are unstable, and reporting reference stations that experience sudden coordinate changes. The developed monitoring module can be implemented by the reference stations operators as an automated program for setting up an intelligent alert system to trigger a warning whenever there is unexpected coordinate breach.

scholarly journals A SLR Pre-Processing Algorithm Based on Satellite Signature Effect

2021 ◽  
Vol 11 (19) ◽  
pp. 8880
Author(s):  
Bowen Guan ◽  
Cunbo Fan ◽  
Ning An ◽  
Ricardo Cesar Podesta ◽  
Dra Ana Pacheco ◽  
...  
Keyword(s):  
Mean Value ◽  
Observation Data ◽  
Short Term ◽  
Error Sources ◽  
Effect Model ◽  
The Mean ◽  
The Stability ◽  
First Time ◽  
Satellite Signature Effect

As one of the major error sources, satellite signature effect should be reduced or even erased from the distribution of the post-fit residuals to improve the ranging precision. A simulation of satellite signature effect removal process for normal point algorithm is conducted based on a revised model of satellite response, which fully considers the structural and distribution characteristics of retroreflectors. In order to eliminate both long-term and short-term satellite signature effect, a clipping method for SLR data processing is proposed by defining the clipping location as 5.6 mm away from the mean value of the long-term fit residuals to select effective returns for normal points. The results indicate that, compared to normal points algorithm, the RMS per NP of LAGEOS-1 observation data processed by the clipping method is reduced from 62.90 ± 9.9 mm to 56.07 ± 4.69 mm, and the stability of RMS is improved 53%. This study improves the satellite signature effect model and simulates the fluctuation of normal points caused by satellite signature effect for the first time. The new method based on the simulation of satellite signature effect has stronger robustness and applicability, which can further minimize the influence of satellite signature effect on the SLR production and significantly improve the data property.

scholarly journals ANALISIS PENGARUH VARIABEL MAKROEKONOMI DAN COUNTRY RISK TERHADAP INVESTASI PORTOFOLIO ASING DI INDONESIA

2018 ◽  
Vol 7 (2) ◽  
pp. 135
Author(s):  
Halifah Hadi ◽  
Hasdi Aimon ◽  
Dewi Zaini Putri
Keyword(s):  
Economic Growth ◽  
Time Series ◽  
Time Series Data ◽  
Country Risk ◽  
Growth Effect ◽  
Series Data ◽  
Short Term ◽  
Correction Model ◽  
The Stability

The reseach aims to explain the effect of country risk and variabels macroeconomics to the foreign portofolio invesment in Indonesia in short term and long term. The analysis takes time series time series data from 2006 quarter 1 through 2016 quarter 4by using Error Correction Model (ECM). The source of data are Badan Pusat Statistik, Bank Indonesia, FX Sauder and World Bank. The result are in the short term the exchange rate and economic growth effect the shock that will influence the foreign portofolio invesment. In the long trem the inflation, interst rate, money supply and country risk influence on foreign portofolio invesment significanly. The suggestion in this research is, the goverment sould keep the stability balance of payment in Indonesia .Any change, the condition of  balance of payments effect appreciation and depreciation to Rupiah. To increase the economic growth in Indonesia, goverment could increasing the fiscal income and PMDN realization that will  increase the enterprises productivity.

Empirical statistical downscaling with EPISODES in Austria

2021 ◽  
Author(s):  
Theresa Schellander-Gorgas ◽  
Frank Kreienkamp ◽  
Philip Lorenz ◽  
Christoph Matulla ◽  
Janos Tordai
Keyword(s):  
Time Series ◽  
Linear Regression ◽  
Statistical Downscaling ◽  
Climate Impact ◽  
Coarse Grid ◽  
Climate Projections ◽  
Observation Data ◽  
Short Term ◽  
High Quality ◽  
Data Set

<p>EPISODES is an empirical statistical downscaling (ESD) method, which has been initiated and developed by the German Weather Service (DWD). Having resulted in good evaluation scores for Germany, the methodology it is also set-up and adapted for Austria at ZAMG and, hence, for an alpine territory with complex topography.</p><p>ESD methods are sparing regarding computational costs compared to dynamical downscaling models. Due to this advantage ESD can be applied in a short time frame and in a demand-based manner. It enables, e.g., processing ensembles of downscaled climate projections, which can be assessed either as stand-alone data set or to enhance ensembles based on dynamical methods. This helps improve the robustness of climatological statements for the purpose of climate impact research.</p><p>Preconditions for achieving high-quality results by EPISODES are long-term, temporally consistent observation data sets and a best possible realistic reproduction of relevant large-scale weather conditions by the GCMs. Given these requirements, EPISODES produces high-quality multivariate and spatially/temporally consistent synthetic time series on regular grids or station locations. The output is provided for daily time steps and, at maximum, for the resolution of underlying observation data.</p><p>The EPISODES method consists on mainly two steps: At first stage, univariate time series are produced on a coarse grid based on the analogue method and linear regression. It means that coarse scale atmospheric conditions of each single day as described by the GCM projections are assigned to a selection of at most similar daily weather situations of the observed past. From this selection new values are determined by linear regression for each day.</p><p>The second stage of the EPISODES method works like a weather generator. Short-term anomalies based on first stage results, on the one hand, and on observations, on the other hand, are matched selecting the most similar day for all used meteorological parameters and coarse grid points at the same time. Together with the high-resolution climatological background of observations and the climatological shift as described by GCM projections the short-term variability are combined to synthetic daily values for each target grid point. This approach provides the desired characteristics of the downscaled climate projections such as multivariability and spatio-temporal consistency.</p><p>Recent EPISODES evaluation results for daily precipitation and daily mean temperature are presented for the Austrian federal territory. Performance of the EPISODES ensemble will also be discussed in relation to existing ensembles based on dynamical methods which have already been widely used in climate impact studies in Austria: EURO-CORDEX and ÖKS15.</p>

DEVELOPMENT OF STREAMFLOW DROUGHT INDICES IN THE MORAVA RIVER BASIN

2020 ◽  
Author(s):  
Ondrej Ledvinka ◽  
◽  
Pavel Coufal ◽  
Keyword(s):  
Time Series ◽  
Kendall Test ◽  
Drought Indices ◽  
Drought Period ◽  
Left Hand ◽  
Low Flows ◽  
Current Period ◽  
Catchment Size ◽  
Morava River ◽  
The Stability

The territory of Czechia currently suffers from a long-lasting drought period which has been a subject of many studies, including the hydrological ones. Previous works indicated that the basin of the Morava River, a left-hand tributary of the Danube, is very prone to the occurrence of dry spells. It also applies to the development of various hydrological time series that often show decreases in the amount of available water. The purpose of this contribution is to extend the results of studies performed earlier and, using the most updated daily time series of discharge, to look at the situation of the so-called streamflow drought within the basin. 46 water-gauging stations representing the rivers of diverse catchment size were selected where no or a very weak anthropogenic influences are expected and the stability and sensitivity of profiles allow for the proper measurement of low flows. The selected series had to cover the most current period 1981-2018 but they could be much longer, which was considered beneficial for the next determination of the development direction. Various series of drought indices were derived from the original discharge series. Specifically, 7-, 15- and 30-day low flows together with deficit volumes and their durations were tested for trends using the modifications of the Mann– Kendall test that account for short-term and long-term persistence. In order to better reflect the drivers of streamflow drought, the indices were considered for summer and winter seasons separately as well. The places with the situation critical to the future water resources management were highlighted where substantial changes in river regime occur probably due to climate factors. Finally, the current drought episode that started in 2014 was put into a wider context, making use of the information obtained by the analyses.

Aggregation prone regions in antibody sequences raised against Vibrio cholerae: A bioinformatic approach

2020 ◽  
Vol 15 ◽  
Author(s):  
Zakia Akter ◽  
Anamul Haque ◽  
Md. Sabir Hossain ◽  
Firoz Ahmed ◽  
Md Asiful Islam
Keyword(s):  
Vibrio Cholerae ◽  
Binding Sites ◽  
Bioinformatic Analysis ◽  
Antigen Binding ◽  
Short Term ◽  
Protein Database ◽  
The Stability ◽  
Bioinformatic Approach ◽  
Self Aggregation ◽  
Complementarity Determining Region

Background: Cholera, a diarrheal illness causes millions of deaths worldwide due to large outbreaks. Monoclonal antibody used as therapeutic purposes of cholera are prone to be unstable due to various factors including self-aggregation. Objectives: In this bioinformatic analysis, we identified the aggregation prone regions (APRs) of different immunogens of antibody sequences (i.e., CTB, ZnM-CTB, ZnP-CTB, TcpA-CT-CTB, ZnM-TcpA-CT-CTB, ZnP-TcpA-CT-CTB, ZnM-TcpA, ZnP-TcpA, TcpA-CT-TcpA, ZnM-TcpA-CT-TcpA, ZnP-TcpA-CT-TcpA, Ogawa, Inaba and ZnM-Inaba) raised against Vibrio cholerae. Methods: To determine APRs in antibody sequences that were generated after immunizing Vibrio cholerae immunogens on Mus musculus, a total of 94 sequences were downloaded as FASTA format from a protein database and the algorithms such as Tango, Waltz, PASTA 2.0, and AGGRESCAN were followed to analyze probable APRs in all of the sequences. Results: A remarkably high number of regions in the monoclonal antibodies were identified to be APRs which could explain a cause of instability/short term protection of anticholera vaccine. Conclusion: To increase the stability, it would be interesting to eliminate the APR residues from the therapeutic antibodies in a such way that the antigen binding sites or the complementarity determining region loops involved in antigen recognition are not disrupted.

scholarly journals Short-term household load forecasting based on Long- and Short-term Time-series network

2021 ◽  
Vol 7 ◽  
pp. 58-64
Author(s):  
Xifeng Guo ◽  
Ye Gao ◽  
Yupeng Li ◽  
Di Zheng ◽  
Dan Shan
Keyword(s):  
Time Series ◽  
Load Forecasting ◽  
Short Term

scholarly journals Sea Ice Concentration Products over Polar Regions with Chinese FY3C/MWRI Data

2021 ◽  
Vol 13 (11) ◽  
pp. 2174
Author(s):  
Lijian Shi ◽  
Sen Liu ◽  
Yingni Shi ◽  
Xue Ao ◽  
Bin Zou ◽  
...  
Keyword(s):  
Time Series ◽  
Sea Ice ◽  
Ocean Circulation ◽  
The Arctic ◽  
Retrieval Algorithm ◽  
Atmospheric Effects ◽  
Observation Data ◽  
Long Time Series ◽  
Ice Concentration ◽  
Long Time

Polar sea ice affects atmospheric and ocean circulation and plays an important role in global climate change. Long time series sea ice concentrations (SIC) are an important parameter for climate research. This study presents an SIC retrieval algorithm based on brightness temperature (Tb) data from the FY3C Microwave Radiation Imager (MWRI) over the polar region. With the Tb data of Special Sensor Microwave Imager/Sounder (SSMIS) as a reference, monthly calibration models were established based on time–space matching and linear regression. After calibration, the correlation between the Tb of F17/SSMIS and FY3C/MWRI at different channels was improved. Then, SIC products over the Arctic and Antarctic in 2016–2019 were retrieved with the NASA team (NT) method. Atmospheric effects were reduced using two weather filters and a sea ice mask. A minimum ice concentration array used in the procedure reduced the land-to-ocean spillover effect. Compared with the SIC product of National Snow and Ice Data Center (NSIDC), the average relative difference of sea ice extent of the Arctic and Antarctic was found to be acceptable, with values of −0.27 ± 1.85 and 0.53 ± 1.50, respectively. To decrease the SIC error with fixed tie points (FTPs), the SIC was retrieved by the NT method with dynamic tie points (DTPs) based on the original Tb of FY3C/MWRI. The different SIC products were evaluated with ship observation data, synthetic aperture radar (SAR) sea ice cover products, and the Round Robin Data Package (RRDP). In comparison with the ship observation data, the SIC bias of FY3C with DTP is 4% and is much better than that of FY3C with FTP (9%). Evaluation results with SAR SIC data and closed ice data from RRDP show a similar trend between FY3C SIC with FTPs and FY3C SIC with DTPs. Using DTPs to present the Tb seasonal change of different types of sea ice improved the SIC accuracy, especially for the sea ice melting season. This study lays a foundation for the release of long time series operational SIC products with Chinese FY3 series satellites.

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