Data_Sheet_1_Addressing on Abrupt Global Warming, Warming Trend Slowdown and Related Features in Recent Decades.pdf

• Main Author: Indrani Roy
• Format: Dataset
• Language: unknown
• Published: 2018
• Subjects: Solid Earth Sciences; Climate Science; Atmospheric Sciences not elsewhere classified; Exploration Geochemistry; Inorganic Geochemistry; Isotope Geochemistry; Organic Geochemistry; Geochemistry not elsewhere classified; Igneous and Metamorphic Petrology; Ore Deposit Petrology; Palaeontology (incl. Palynology); Structural Geology; Tectonics; Volcanology; Geology not elsewhere classified; Seismology and Seismic Exploration; Glaciology; Hydrogeology; Natural Hazards; Quaternary Environments; Earth Sciences not elsewhere classified; Evolutionary Impacts of Climate Change; Hiatus; Sun; Volcano; NAO; CMIP5; Indian; Pacific; aleutian low
• Online Access: https://doi.org/10.3389/feart.2018.00136.s001; https://figshare.com/articles/Data_Sheet_1_Addressing_on_Abrupt_Global_Warming_Warming_Trend_Slowdown_and_Related_Features_in_Recent_Decades_pdf/7146065

The puzzle of recent global warming trend slowdown has captured enough attention, though the underlying cause is still unexplained. This study addresses that area segregating the role of natural factors (the sun and volcano) to that from CO2 led linear anthropogenic contributions. It separates out a period 1976–1996 that covers two full solar cycles, where two explosive volcanos erupted during active phases of strong solar cycles. The similar period also matched the duration of abrupt global warming. It identifies that dominance of Central Pacific (CP) ENSO and associated water vapor feedback during that period play an important role. The possible mechanism could be initiated via a preferential alignment of NAO phase, generated by explosive volcanos. Inciting extratropical Rossby wave to influence the Aleutian Low, it has a modulating effect on CP ENSO. Disruption of Indian Summer Monsoon and ENSO during the abrupt warming period and a subsequent recovery thereafter can also be explained from that angle. Interestingly, CMIP5 model ensemble, and also individual models, fails to comply with such observation. It also explores possible areas where models miss important contributions due to natural drivers.