scholarly journals Towards an operational database for real-time environmental monitoring and early warning systems

2017 ◽  
Vol 108 ◽  
pp. 2250-2259 ◽  
Author(s):  
Bartosz Balis ◽  
Marian Bubak ◽  
Daniel Harezlak ◽  
Piotr Nowakowski ◽  
Maciej Pawlik ◽  
...  
Keyword(s):  
Environmental Monitoring ◽  
Real Time ◽  
Early Warning ◽  
Early Warning Systems ◽  
Warning Systems ◽  
Monitoring And Early Warning

Observations on Zambia’s Crop Monitoring and Early Warning Systems

2014 ◽  
Vol 6 (3) ◽  
Author(s):  
Gelson Tembo ◽  
Bernadette Chimai ◽  
Nathan Tembo ◽  
Mukelabai Ndiyoi
Keyword(s):  
Early Warning ◽  
Early Warning Systems ◽  
Warning Systems ◽  
Crop Monitoring ◽  
Monitoring And Early Warning

scholarly journals P-wave picking for earthquake early warning: Refinement of a T pd method

2021 ◽  
Author(s):  
Masumi Yamada ◽  
Jim Mori
Keyword(s):  
Real Time ◽  
Early Warning ◽  
Arrival Time ◽  
Early Warning Systems ◽  
Earthquake Early Warning ◽  
P Wave ◽  
Warning Systems ◽  
Wave Detection ◽  
Earthquake Early Warning Systems ◽  
Wave Arrival

Summary Detecting P-wave onsets for on-line processing is an important component for real-time seismology. As earthquake early warning systems around the world come into operation, the importance of reliable P-wave detection has increased, since the accuracy of the earthquake information depends primarily on the quality of the detection. In addition to the accuracy of arrival time determination, the robustness in the presence of noise and the speed of detection are important factors in the methods used for the earthquake early warning. In this paper, we tried to improve the P-wave detection method designed for real-time processing of continuous waveforms. We used the new Tpd method, and proposed a refinement algorithm to determine the P-wave arrival time. Applying the refinement process substantially decreases the errors of the P-wave arrival time. Using 606 strong motion records of the 2011 Tohoku earthquake sequence to test the refinement methods, the median of the error was decreased from 0.15 s to 0.04 s. Only three P-wave arrivals were missed by the best threshold. Our results show that the Tpd method provides better accuracy for estimating the P-wave arrival time compared to the STA/LTA method. The Tpd method also shows better performance in detecting the P-wave arrivals of the target earthquakes in the presence of noise and coda of previous earthquakes. The Tpd method can be computed quickly so it would be suitable for the implementation in earthquake early warning systems.

scholarly journals African Rainfall Climatology Version 2 for Famine Early Warning Systems

2013 ◽  
Vol 52 (3) ◽  
pp. 588-606 ◽  
Author(s):  
Nicholas S. Novella ◽  
Wassila M. Thiaw
Keyword(s):  
Real Time ◽  
Early Warning ◽  
Correlation Coefficients ◽  
Global Precipitation Climatology Project ◽  
Early Warning Systems ◽  
Warning Systems ◽  
Telecommunication System ◽  
African Rainfall ◽  
Global Telecommunication System ◽  
Rainfall Climatology

AbstractThis paper describes a new gridded, daily 29-yr precipitation estimation dataset centered over Africa at 0.1° spatial resolution. Called the African Rainfall Climatology, version 2 (ARC2), it is a revision of the first version of the ARC. Consistent with the operational Rainfall Estimation, version 2, algorithm (RFE2), ARC2 uses inputs from two sources: 1) 3-hourly geostationary infrared (IR) data centered over Africa from the European Organisation for the Exploitation of Meteorological Satellites (EUMETSAT) and 2) quality-controlled Global Telecommunication System (GTS) gauge observations reporting 24-h rainfall accumulations over Africa. The main difference with ARC1 resides in the recalibration of all Meteosat First Generation (MFG) IR data (1983–2005). Results show that ARC2 is a major improvement over ARC1. It is consistent with other long-term datasets, such as the Global Precipitation Climatology Project (GPCP) and Climate Prediction Center (CPC) Merged Analysis of Precipitation (CMAP), with correlation coefficients of 0.86 over a 27-yr period. However, a marginal summer dry bias that occurs over West and East Africa is examined. Daily validation with independent gauge data shows RMSEs of 11.3, 13.4, and 14, respectively, for ARC2, Tropical Rainfall Measuring Mission Multisatellite Precipitation Analysis 3B42, version 6 (3B42v6), and the CPC morphing technique (CMORPH) for the West African summer season. The ARC2 RMSE is slightly higher for Ethiopia than those of CMORPH and 3B42v6. Both daily and monthly validations suggested that ARC2 underestimations may be attributed to the unavailability of daily GTS gauge reports in real time, and deficiencies in the satellite estimate associated with precipitation processes over coastal and orographic areas. However, ARC2 is expected to provide users with real-time monitoring of the daily evolution of precipitation, which is instrumental in improved decision making in famine early warning systems.

Monitoring and Early Warning Systems: Applications and Perspectives

2020 ◽  
pp. 1-21
Author(s):  
Nicola Casagli ◽  
Emanuele Intrieri ◽  
Tommaso Carlà ◽  
Federico Di Traglia ◽  
William Frodella ◽  
...  
Keyword(s):  
Early Warning ◽  
Early Warning Systems ◽  
Warning Systems ◽  
Monitoring And Early Warning

scholarly journals Early Warning Systems for Currency Crises with Real-Time Data

2019 ◽  
Vol 30 (4) ◽  
pp. 813-835 ◽  
Author(s):  
Tjeerd M. Boonman ◽  
Jan P. A. M. Jacobs ◽  
Gerard H. Kuper ◽  
Alberto Romero
Keyword(s):  
Real Time ◽  
Early Warning ◽  
Currency Crises ◽  
Early Warning Systems ◽  
Warning Systems ◽  
Time Data ◽  
Real Time Data
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