TY - GEN
T1 - Pattern Recognition Through Empirical Mode Decomposition for Temperature Time Series Between 1986 and 2019 in Mexico City Downtown for Global Warming Assessment
AU - Orozco-del-Castillo, Mauricio Gabriel
AU - Hernández-Gómez, Jorge J.
AU - Yañez-Casas, Gabriela Aurora
AU - Moreno-Sabido, Mario Renán
AU - Couder-Castañeda, Carlos
AU - Medina, Isaac
AU - Novelo-Cruz, Raúl
AU - Enciso-Aguilar, Mauro Alberto
N1 - Publisher Copyright:
© 2019, Springer Nature Switzerland AG.
PY - 2019
Y1 - 2019
N2 - Global warming is a real threat for the survival of life on Earth in the following 80 years. The effects of Global Warming are particularly harmful for inhabitants of very saturated urban settlements, which is the case of Mexico City. In this work, we analyse temperature time series from Mexico City Downtown, taken hourly between 1986 and 2019. The gaps in the time series were interpolated through the kriging method. Then, temporal tendencies and main frequencies were obtained through Empirical Mode Decomposition. The first frequency mode reveals a clear increasing tendency driven by Global Warming, which for 2019 was of 0.72 C above a 30-year baseline period mean between 1986 and 2016. Furthermore, the shorter periods identified in the first intrinsic mode functions are likely driven by the solar activity periods. It remains to find the origin of the smallest identified periods in the time series (<0.36 years).
AB - Global warming is a real threat for the survival of life on Earth in the following 80 years. The effects of Global Warming are particularly harmful for inhabitants of very saturated urban settlements, which is the case of Mexico City. In this work, we analyse temperature time series from Mexico City Downtown, taken hourly between 1986 and 2019. The gaps in the time series were interpolated through the kriging method. Then, temporal tendencies and main frequencies were obtained through Empirical Mode Decomposition. The first frequency mode reveals a clear increasing tendency driven by Global Warming, which for 2019 was of 0.72 C above a 30-year baseline period mean between 1986 and 2016. Furthermore, the shorter periods identified in the first intrinsic mode functions are likely driven by the solar activity periods. It remains to find the origin of the smallest identified periods in the time series (<0.36 years).
KW - AI
KW - Artificial Intelligence
KW - Climate Change
KW - EMD
KW - Empirical Mode Decomposition
KW - Global Warming
KW - Mexico City
KW - Pattern recognition
KW - Temperature increase
KW - Time series
UR - http://www.scopus.com/inward/record.url?scp=85076178587&partnerID=8YFLogxK
U2 - 10.1007/978-3-030-33229-7_5
DO - 10.1007/978-3-030-33229-7_5
M3 - Contribución a la conferencia
AN - SCOPUS:85076178587
SN - 9783030332280
T3 - Communications in Computer and Information Science
SP - 45
EP - 60
BT - Telematics and Computing - 8th International Congress, WITCOM 2019, Proceedings
A2 - Mata-Rivera, Miguel Felix
A2 - Zagal-Flores, Roberto
A2 - Barría-Huidobro, Cristian
PB - Springer
T2 - 8th International Congress on Telematics and Computing, WITCOM 2019
Y2 - 4 November 2019 through 8 November 2019
ER -