Dominant Modes of Subseasonal Variability of East Asian Summertime Surface Air Temperature and Their Predictions

Dominant Modes of Subseasonal Variability of East Asian Summertime Surface Air Temperature and... AbstractSubseasonal variability of surface air temperature (SAT) over East Asia is analyzed using the NCEP–NCAR reanalysis of 34 Northern Hemisphere extended summers. An empirical orthogonal function (EOF) analysis is performed with pentad SAT data to identify the leading modes of subseasonal SAT variability. The first (EOF1) and second (EOF2) modes, which together account for about 35% of the total variance, correspond to a monopole structure of SAT anomaly in the whole East Asian region and a dipole structure with opposite signs of variability over the north and south East Asian continent, respectively. Lead–lag regressions are calculated in order to analyze how the large-scale atmospheric circulation evolves in association with the development of the leading SAT modes. An eastward propagation of the Rossby wave from the midlatitude Atlantic Ocean is observed about three pentads before EOF1. EOF2 is influenced by both the tropical Madden–Julian oscillation (MJO) and a midlatitude wave train. These results indicate that there is potential for prediction of the dominant SAT modes on the subseasonal time scale. The subseasonal prediction of the two dominant modes is further evaluated in the operational monthly forecasting system of Environment and Climate Change Canada (ECCC). The model shows a better forecast skill than the persistence forecast. The strength of the subseasonal signal in initial conditions impacts the forecast skill. The forecasts starting with strong EOF in the initial condition are more skillful than those initialized with weak EOF. The findings in the study contribute to improving the understanding of the subseasonal variability and SAT subseasonal forecasting in East Asia. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Journal of Climate American Meteorological Society

Dominant Modes of Subseasonal Variability of East Asian Summertime Surface Air Temperature and Their Predictions

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Publisher
American Meteorological Society
Copyright
Copyright © American Meteorological Society
ISSN
1520-0442
D.O.I.
10.1175/JCLI-D-17-0368.1
Publisher site
See Article on Publisher Site

Abstract

AbstractSubseasonal variability of surface air temperature (SAT) over East Asia is analyzed using the NCEP–NCAR reanalysis of 34 Northern Hemisphere extended summers. An empirical orthogonal function (EOF) analysis is performed with pentad SAT data to identify the leading modes of subseasonal SAT variability. The first (EOF1) and second (EOF2) modes, which together account for about 35% of the total variance, correspond to a monopole structure of SAT anomaly in the whole East Asian region and a dipole structure with opposite signs of variability over the north and south East Asian continent, respectively. Lead–lag regressions are calculated in order to analyze how the large-scale atmospheric circulation evolves in association with the development of the leading SAT modes. An eastward propagation of the Rossby wave from the midlatitude Atlantic Ocean is observed about three pentads before EOF1. EOF2 is influenced by both the tropical Madden–Julian oscillation (MJO) and a midlatitude wave train. These results indicate that there is potential for prediction of the dominant SAT modes on the subseasonal time scale. The subseasonal prediction of the two dominant modes is further evaluated in the operational monthly forecasting system of Environment and Climate Change Canada (ECCC). The model shows a better forecast skill than the persistence forecast. The strength of the subseasonal signal in initial conditions impacts the forecast skill. The forecasts starting with strong EOF in the initial condition are more skillful than those initialized with weak EOF. The findings in the study contribute to improving the understanding of the subseasonal variability and SAT subseasonal forecasting in East Asia.

Journal

Journal of ClimateAmerican Meteorological Society

Published: Apr 1, 2018

References

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