Spatial Variability and Long-Term Trend in the Occurrence Frequency of Heatwave and Tropical Night in Korea

2019 ◽  
Vol 55 (1) ◽  
pp. 101-114 ◽  
Author(s):  
Nakbin Choi ◽  
Myong-In Lee
Keyword(s):  
Spatial Variability ◽  
Occurrence Frequency ◽  
Term Trend ◽  
Tropical Night ◽  
Long Term Trend

scholarly journals Polar stratospheric cloud climatology based on CALIPSO spaceborne lidar measurements from 2006 to 2017

2018 ◽  
Vol 18 (15) ◽  
pp. 10881-10913 ◽  
Author(s):  
Michael C. Pitts ◽  
Lamont R. Poole ◽  
Ryan Gonzalez
Keyword(s):  
Standard Deviation ◽  
Relative Standard Deviation ◽  
Occurrence Frequency ◽  
The Arctic ◽  
Term Trend ◽  
Relative Standard ◽  
Lidar Measurements ◽  
Spatial Volume ◽  
Long Term Trend

Abstract. The Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) on the CALIPSO (Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations) satellite has been observing polar stratospheric clouds (PSCs) from mid-June 2006 until the present. The spaceborne lidar profiles PSCs with unprecedented spatial (5 km horizontal×180 m vertical) resolution and its dual-polarization capability enables classification of PSCs according to composition. Nearly coincident Aura Microwave Limb Sounder (MLS) measurements of the primary PSC condensables (HNO3 and H2O) provide additional constraints on particle composition. A new CALIOP version 2 (v2) PSC detection and composition classification algorithm has been implemented that corrects known deficiencies in previous algorithms and includes additional refinements to improve composition discrimination. Major v2 enhancements include dynamic adjustment of composition boundaries to account for effects of denitrification and dehydration, explicit use of measurement uncertainties, addition of composition confidence indices, and retrieval of particulate backscatter, which enables simplified estimates of particulate surface area density (SAD) and volume density (VD). The over 11 years of CALIOP PSC observations in each v2 composition class conform to their expected thermodynamic existence regimes, which is consistent with previous analyses of data from 2006 to 2011 and underscores the robustness of the v2 composition discrimination approach. The v2 algorithm has been applied to the CALIOP dataset to produce a PSC reference data record spanning the 2006–2017 time period, which is the foundation for a new comprehensive, high-resolution climatology of PSC occurrence and composition for both the Antarctic and Arctic. Time series of daily-averaged, vortex-wide PSC areal coverage versus altitude illustrate that Antarctic PSC seasons are similar from year to year, with about 25 % relative standard deviation in Antarctic PSC spatial volume at the peak of the season in July and August. Multi-year average, monthly zonal mean cross sections depict the climatological patterns of Antarctic PSC occurrence in latitude–altitude and also equivalent-latitude–potential-temperature coordinate systems, with the latter system better capturing the microphysical processes controlling PSC existence. Polar maps of the multi-year mean geographical patterns in PSC occurrence frequency show a climatological maximum between longitudes 90∘ W and 0∘, which is the preferential region for forcing by orography and upper tropospheric anticyclones. The climatological mean distributions of particulate SAD and VD also show maxima in this region due to the large enhancements from the frequent ice clouds. Stronger wave activity in the Northern Hemisphere leads to a more disturbed Arctic polar vortex, whose evolution and lifetime vary significantly from year to year. Accordingly, Arctic PSC areal coverage is distinct from year to year with no “typical” year, and the relative standard deviation in Arctic PSC spatial volume is >100 % throughout most of the season. When PSCs are present in the Arctic, they most likely occur between longitudes 60∘ W and 90∘ E, which is consistent with the preferential location of the Arctic vortex. Comparisons of CALIOP v2 and Michelson Interferometer for Passive Atmospheric Sounding (MIPAS) Antarctic PSC observations show excellent correspondence in the overall spatial and temporal evolution, as well as for different PSC composition classes. Climatological patterns of CALIOP v2 PSC occurrence frequency in the vicinity of McMurdo Station, Antarctica, and Ny-Ålesund, Spitsbergen, are similar in nature to those derived from local ground-based lidar measurements. To investigate the possibility of longer-term trends, appropriately subsampled and averaged CALIOP v2 PSC observations from 2006 to 2017 were compared with PSC data during the 1978–1989 period obtained by the spaceborne solar occultation instrument SAM II (Stratospheric Aerosol Measurement II). There was good consistency between the two instruments in column Antarctic PSC occurrence frequency, suggesting that there has been no long-term trend. There was less overall consistency between the Arctic records, but it is very likely due to the high degree of interannual variability in PSCs rather than a long-term trend.

scholarly journals Predation on livestock by an expanding reintroduced lynx population: long-term trend and spatial variability

2001 ◽  
Vol 38 (3) ◽  
pp. 674-687 ◽  
Author(s):  
P. Stahl ◽  
J.M. Vandel ◽  
V. Herrenschmidt ◽  
P. Migot
Keyword(s):  
Spatial Variability ◽  
Term Trend ◽  
Long Term Trend

NAEP Trends: Main NAEP vs. Long-Term Trend

2010 ◽  
Author(s):  
Albert E. Beaton ◽  
James R. Chromy
Keyword(s):  
Term Trend ◽  
Long Term Trend

Environmental behavior and potential driving force of bisphenol A in the Elbe River: A long-term trend study

2020 ◽  
pp. 143251
Author(s):  
Zhenyu Huang ◽  
Pei Hua ◽  
Zhenyu Wang ◽  
Ruifei Li ◽  
Liang Dong ◽  
...  
Keyword(s):  
Bisphenol A ◽  
Driving Force ◽  
Environmental Behavior ◽  
Elbe River ◽  
Trend Study ◽  
Term Trend ◽  
The Elbe River ◽  
Long Term Trend

Estimation and Long-term Trend Analysis of Surface Solar Radiation in Antarctica: A Case Study of Zhongshan Station

2021 ◽  
Author(s):  
Zhaoliang Zeng ◽  
Zemin Wang ◽  
Minghu Ding ◽  
Xiangdong Zheng ◽  
Xiaoyu Sun ◽  
...  
Keyword(s):  
Solar Radiation ◽  
Trend Analysis ◽  
Surface Solar Radiation ◽  
Term Trend ◽  
Zhongshan Station ◽  
Long Term Trend
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