Temperature trends in the skin/surface, mid-troposphere and low stratosphere near Korea from satellite and ground measurements - Yoo, Jung-Moon; Won, Young-In; Cho, Young-Jun; Jeong, Myeong-Jae; Shin, Dong-Bin; Lee, Suk-Jo; Lee, Yu-Ri; Oh, Soo-Min; Ban, Soo-Jin (Asia-Pacific journal of atmospheric sciences, 2011)
Various types of satellite (AIRS/AMSU, MODIS) and ground measurements are used to analyze temperature trends in the four vertical layers (skin/surface, mid-troposphere, and low stratosphere) around the Korean Peninsula (123–132°E, 33–44°N) during the period from September 2002 to August 2010. The ground-based observations include 72 Surface Meteorological Stations (SMSs), 6 radiosonde stations (RAOBs), 457 Automatic Weather Stations (AWSs) over the land, and 5 buoy stations over the ocean. A strong warming (0.052 K yr −1 ) at the surface, and a weak warming (0.004∼0.010 K yr −1 ) in the mid-troposphere and low stratosphere have been found from satellite data, leading to an unstable atmospheric layer. The AIRS/AMSU warming trend over the ocean surface around the Korean Peninsula is about 2.5 times greater than that over the land surface. The ground measurements from both SMS and AWS over the land surface of South Korea also show a warming of 0.043∼0.082 K yr −1 , consistent with the satellite observations. The correlation average (r = 0.80) between MODIS skin temperature and ground measurement is significant. The correlations between AMSU and RAOB are very high (0.91∼0.95) in the anomaly time series, calculated from the spatial averages of monthly mean temperature values. However, the warming found in the AMSU data is stronger than that from the RAOB at the surface. The opposite feature is present above the mid-troposphere, indicating that there is a systematic difference. Warming phenomena (0.012∼0.078 K yr −1 ) are observed from all three data sets (SMS, AWS, MODIS), which have been corroborated by the coincident measurements at five ground stations. However, it should also be noted that the observed trends are subject to large uncertainty as the corresponding 95% confidence intervals tend to be larger than the observed signals due to large thermal variability and the relatively short periods of the satellitebased temperature records. The EOF analysis of monthly mean temperature anomalies indicates that the tropospheric temperature variability near Korea is primarily linked to the Arctic Oscillation (AO), and secondarily to ENSO (El Niño and Southern Oscillation). However, the low stratospheric temperature variability is mainly associated with Southern Oscillation and then additionally with Quasi-Biennial Oscillation (QBO). Uncertainties from the different spatial resolutions between satellite data are discussed in the trends.