scholarly journals Abrupt climate change detection based on heuristic segmentation algorithm

2005 ◽  
Vol 54 (11) ◽  
pp. 5494
Author(s):  
Feng Guo-Ling ◽  
Gong Zhi-Qiang ◽  
Dong Wen-Jie ◽  
Li Jian-Ping
Keyword(s):  
Climate Change ◽  
Change Detection ◽  
Segmentation Algorithm ◽  
Abrupt Climate Change ◽  
Climate Change Detection

The applicability of research on moving cut data-approximate entropy on abrupt climate change detection

2015 ◽  
Vol 124 (1-2) ◽  
pp. 475-486 ◽  
Author(s):  
Hongmei Jin ◽  
Wenping He ◽  
Qunqun Liu ◽  
Jinsong Wang ◽  
Guolin Feng
Keyword(s):  
Climate Change ◽  
Change Detection ◽  
Approximate Entropy ◽  
Abrupt Climate Change ◽  
Climate Change Detection

scholarly journals Atmospheric Climate Change Detection by Radio Occultation Data Using a Fingerprinting Method

2011 ◽  
Vol 24 (20) ◽  
pp. 5275-5291 ◽  
Author(s):  
Bettina C. Lackner ◽  
Andrea K. Steiner ◽  
Gabriele C. Hegerl ◽  
Gottfried Kirchengast
Keyword(s):  
Climate Change ◽  
Change Detection ◽  
Confidence Level ◽  
Geopotential Height ◽  
Radio Occultation ◽  
Lower Stratosphere ◽  
Quality Data ◽  
Climate Change Signal ◽  
High Quality ◽  
Climate Change Detection

Abstract The detection of climate change signals in rather short satellite datasets is a challenging task in climate research and requires high-quality data with good error characterization. Global Navigation Satellite System (GNSS) radio occultation (RO) provides a novel record of high-quality measurements of atmospheric parameters of the upper-troposphere–lower-stratosphere (UTLS) region. Because of characteristics such as long-term stability, self calibration, and a very good height resolution, RO data are well suited to investigate atmospheric climate change. This study describes the signals of ENSO and the quasi-biennial oscillation (QBO) in the data and investigates whether the data already show evidence of a forced climate change signal, using an optimal-fingerprint technique. RO refractivity, geopotential height, and temperature within two trend periods (1995–2010 intermittently and 2001–10 continuously) are investigated. The data show that an emerging climate change signal consistent with the projections of three global climate models from the Coupled Model Intercomparison Project cycle 3 (CMIP3) archive is detected for geopotential height of pressure levels at a 90% confidence level both for the intermittent and continuous period, for the latter so far in a broad 50°S–50°N band only. Such UTLS geopotential height changes reflect an overall tropospheric warming. 90% confidence is not achieved for the temperature record when only large-scale aspects of the pattern are resolved. When resolving smaller-scale aspects, RO temperature trends appear stronger than GCM-projected trends, the difference stemming mainly from the tropical lower stratosphere, allowing for climate change detection at a 95% confidence level. Overall, an emerging trend signal is thus detected in the RO climate record, which is expected to increase further in significance as the record grows over the coming years. Small natural changes during the period suggest that the detected change is mainly caused by anthropogenic influence on climate.

scholarly journals Constraining uncertainties in climate models using climate change detection techniques

2000 ◽  
Vol 27 (4) ◽  
pp. 569-572 ◽  
Author(s):  
Chris E. Forest ◽  
Myles R. Allen ◽  
Peter H. Stone ◽  
Andrei P. Sokolov
Keyword(s):  
Climate Change ◽  
Change Detection ◽  
Climate Models ◽  
Detection Techniques ◽  
Climate Change Detection
Sign in / Sign up

Export Citation Format

Share Document