by U.S. Dept. of Commerce, National Oceanic and Atmospheric Administration, for sale by the Supt. of Docs., U.S. Govt. Print. Off.] in Rockville, Md, [Washington .
Written in English
Bibliography: p. 30.
|Statement||Abraham H. Oort.|
|Series||NOAA professional paper ; 8, NOAA professional paper ;, 8.|
|LC Classifications||GC1 .U42c no. 8, QC880.4.A8 .U42c no. 8|
|The Physical Object|
|Pagination||iii, 76 p. :|
|Number of Pages||76|
|LC Control Number||78600539|
We speculate that interannual atmospheric circulation variability associated with SFW events may have a practical bearing upon weather and climate prediction. Acknowledgments The study was supported by the NSF Climate and Large-Scale Dynamics Program under Grant ATM (under the U.S. CLIVAR Program) and NASA’s Living with a Star Cited by: This study examines seasonal AR variation and interannual variability of summertime ARs over the NWP by using both long-term (since ) global reanalysis and high-resolution historical (since ) atmospheric general circulation model (AGCM) by: The fake below-ground meridional wind (FBGMW) exists in reanalysis products which is not present in the real atmosphere and should be removed before calculating the mass stream function (MSF). In this study, the impacts of FBGMW on Hadley circulation (HC) in terms of climatology, interannual variability, and long-term trends were investigated using five reanalysis data sets based on three Author: Jianbo Cheng, Zhihang Xu, Xiaoya Hou. The main objective of the workshop was to address this question by assessing the current state of knowledge on predictability of seasonal and interannual climate variability and to investigate various possibilities for its prediction.
The interannual variation in the onset of the summer rainy season was characterized by abrupt changes in these factors of atmospheric circulation patterns during onset[−1]–onset. Thus, these factors greatly influence the onset timing and process of the summer rainy season. The suppressed variability of TIW agreed well between the two sets, but amplification of the variability was somewhat underestimated in SODA (underestimation was also found in a general circulation model output; Menkes et al. ). Nonetheless, correlation between TIWV from SODA and from Tropical Ocean and Global Atmosphere (TOGA)–TAO was 0. The atmospheric circulation response to sea surface temperature (SST) anomalies is a crucial part of the tropical air–sea interaction. Therefore, understanding the changes in the atmospheric circulation response to SST anomalies is key to understanding the changes in tropical climate variability. An index measuring the variability of MAT intensity is defined, which reveals significant interannual and interdecadal variations of the trough. On interannual time scales, the variation of MAT is significantly associated with the North Atlantic Oscillation, a southeastward propagating stationary wave that possibly originates from the.
T.N. Krishnamurti is Professor of Meteorology at Florida State University. He obtained his PhD in at the University of Chicago. His research interests are in the following areas: high resolution hurricane forecast (tracks, landfall, and intensity), monsoon forecasts on short, medium range, and monthly time scale and studies of interseasonal and interannual variability of the tropical. Through the changes in the atmospheric circulation, IOD influences the world climate [e.g., Saji and Yamagata, b]. For example, the IOD influences the Southern Oscillation in the Pacific [Behera and Yamagata, ], rainfall variability during the Indian summer monsoon [Behera et al., ; Ashok et al., ], the summer climate condition. S.G. Philander, in Encyclopedia of Ocean Sciences (Second Edition), The Atmosphere. The atmospheric circulation in low latitudes corresponds mainly to direct thermal circulations driven by convection over the regions with the highest surface temperatures. Moisture-bearing trade winds converge onto these regions where the air rises in cumulus towers that provide plentiful rainfall locally. The effect of atmospheric circulation on temperature variability and trends in Finland in – is studied using a trajectory-based method. On the average 81% of the detrended interannual variance of monthly mean temperatures is explained by the start points of the three-dimensional trajectories, with the best performance in autumn and winter.