interannual variability of atmospheric circulation statistics
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Dept. Commerce, National Oceanic and Atmospheric Administration, Environmental Research Laboratories, Geophysical Fluid Dynamic Laboratory, for sale by the Supt. of Docs., U.S. Govt. Print. Off. , Princeton, N.J, Washington
Atmospheric circulation -- Statistics, Atmospheric circulation -- Charts, diagrams
|Statement||Abraham H. Oort ; Geophysical Fluid Dynamics Laboratory|
|Series||NOAA professional paper ; 8, NOAA professional paper -- 8|
|Contributions||Environmental Research Laboratories (U.S.), Geophysical Fluid Dynamics Laboratory (U.S.)|
|The Physical Object|
|Pagination||iii, 76 p. :|
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This study examines the variability and long-term trends of atmospheric circulation over the Chukchi and Beaufort Seas using the ECMWF Interim Re-Analysis (ERA-Interim) for the period – Because of the mobility of the BSH through the year, EOF analysis is applied to the sea level pressure (SLP) field in order to investigate the Cited by: Get this from a library.
The interannual variability of atmospheric circulation statistics. [Abraham H Oort; Geophysical Fluid Dynamics Laboratory (U.S.),]. 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.
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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].
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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.
Also, it was shown that the observed interannual variability of seasonal statistics (including extremes) can be better reproduced by using 12‐hourly, rather than seasonal, data in statistical downscaling. This stresses the importance of availability of higher‐resolution data from climate model outputs.
GMMIP simulations on global monsoon interannual variability show higher skill than historical simulations Institute of Atmospheric Physics, Chinese Academy of Sciences. The reconstructed Southern California precipitation record contains interannual variability in the 2‐ to 7‐year band that could be driven by changes in tropical Pacific ENSO variability and/or the strength of the ENSO teleconnection modulated by extratropical pressure systems.
Rodríguez, J.M.; Milton, S.F. East Asian Summer Atmospheric Moisture Transport and Its Response to Interannual Variability of the West Pacific Subtropical High: An Evaluation of the Met Office Unified Model.
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Atmosphere10, Regional Climate of China is the first volume to present the latest research findings gained over the last decade which has greatly advanced our knowledge of the regional climate researches in China.
A distinctive feature of the volume is that it is based on an integration of researches by using the advanced technologies, such as field observation and experiment, satellite information and. Using meteorological observation data and NCEP/NCAR (National Centers for Environmental Prediction/National Center for Atmospheric Research) reanalysis data, the impacts of the atmospheric circulation pattern on the interannual variability of haze-fog in northern China in January are studied by means of statistical methods.
The results showed that the Eurasian teleconnection (EU) at the Previous studies explain the impact of ENSO on haze based on the fact that ENSO modulates some of these meteorological factors (e.g., precipitation anomalies or atmospheric circulation anomalies), without strictly examining whether the interannual haze variability is driven by these meteorological factors (S.
Li et al., ; Zhao et al., ). A. Mapande, C. Reason, Links between rainfall variability on intraseasonal and interannual scales over western Tanzania and regional circulation and SST patterns, Meteorology and Atmospheric Physics, /s, 89,(), ().
The large interannual variability (IAV) of global atmospheric carbon dioxide (CO 2) growth rate originates primarily from variations in CO 2 uptake by pantropical terrestrial ecosystems, whose carbon balance is basically controlled by climate fluctuations of water availability and heat stress related to precipitation and temperature anomalies (Beer et alBallantyne et alAhlström.
Previous analyses of ENSO and rainfall variability (e.g., Gershunov and Barnett, ; Englehart and Douglas, ; Gutzler et al., ) have found a distinct change in statistics of interannual variability before and afterwhen Pacific Ocean SSTs and the atmospheric circulation shifted in association with the PDO (Graham, ; Mantua.
Interannual variability of cyclones that are generated over the eastern Asian continent and passed over the Yellow, Bohai, and East China seas (YBE cyclones) in spring is analyzed using reanalysis datasets for the period of – Possible causes for the variability are also discussed.
Results show that the number of YBE cyclones exhibits significant interannual variability with a period. the statistics have a distinctive annual cycle that should be recognized in the analysis; rather than simply ana-lyze the seasons separately, we employ a cyclostation-ary EOF (CSEOF) analysis (Kim and North ).
This provides a rather different perspective on interannual variability, and perhaps one that may be of value in other applications. Systematic differences in NCEP tropopause statistics are observed between the presatellite (–) and postsatellite (–) periods, precluding the use of the reanalyses for the study of multidecadal variability.
Interannual anomalies in tropical average radiosonde and NCEP data show variations of order ±1–2 K over the period. Enter search terms. Keep search filters New search. Advanced search. These weather conditions are largely affected by large-scale atmospheric circulation anomalies with strong interannual variability, such as the East Asian Winter Monsoon (EAWM), Arctic sea ice and sea surface temperature anomalies in the northwestern Pacific (Wang et alWu et alPei et al ).
Although both meteorological. Increasing greenhouse gas concentrations are expected to enhance the interannual variability of summer climate in Europe 1,2,3 and other mid.
Mark C. Serreze, Andrew P. Barrett, Alex D. Crawford, Rebecca A. Woodgate, Monthly Variability in Bering Strait Oceanic Volume and Heat Transports, Links to Atmospheric Circulation and Ocean Temperature, and Implications for Sea Ice Conditions, Journal of Geophysical Research: Oceans, /JC,12, (), ().Understanding the variability of heat waves and their relation to the large‐scale circulation and SST forcing can be important for predicting the short‐term regional climate extremes (e.g., Della‐Marta et al., ; Marshall et al., ).
By linking each of the dominant modes with the large‐scale atmospheric circulation, it is.The interannual variability of rainfall over the Indian subcontinent, the African Sahel, and the Nordeste region of Brazil have been evaluated in 32 models for the period as part of the.
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