Analysis of the Spatiotemporal Behavior of Precipitation in South Korea Based on EOF and CSEOF Analyses

In this study, EOF analysis and CSEOF analysis were applied to major ASOS precipitation data in Korea to evaluate the spatiotemporal variability of precipitation in Korea. It was concluded that both EOF and CSEOF analyses are appropriate for identifying the spatiotemporal characteristics of precipitation in Korea. In particular, the CSEOF analysis method was able to interpret the temporal, cyclic behavior of precipitation data in detail. Both EOF and CSEOF showed that the first component explained the variance of most of the raw data. From the first EOF to the third EOF, the authors identified the average precipitation characteristics in Korea, precipitation characteristics according to latitude, and the phenomenon estimated by the mountain effect. The first CSEOF was characterized by precipitation in summer and winter in Korea, the second CSEOF was characterized by latitude and local precipitation, and the third CSEOF was characterized by varied and complex variation in precipitation.

Statistical Downscaling of Wintertime Temperatures over South Korea

Reanalysis data have global coverage and faithfully render large-scale phenomena. On the other hand, regional and small-scale characteristics of atmospheric variability are poorly resolved. In an attempt to improve reanalysis data for regional use, a statistical downscaling strategy is developed based on cyclostationary empirical orthogonal function (CSEOF) analysis. The developed algorithm is applied to the National Centers for Environmental Prediction–National Center for Atmospheric Research (NCEP–NCAR) reanalysis data and to the European Centre for Medium-Range Weather Forecast (ECMWF) Interim Re-Analysis (ERA-Interim) data in order to produce winter temperatures at 60 Korea Meteorological Administration (KMA) stations over the Korean Peninsula. The developed downscaling algorithm is evaluated by predicting winter daily temperatures from 17 November to 16 March for 35 years (1979–2014). For validating the downscaling algorithm the jackknife method is used, in which winter daily temperature is predicted over a 1-yr period not used for training. This procedure is repeated for the entire data period. The mean and variance of the resulting downscaled temperatures match reasonably well with those of the KMA measurements. Validation based on correlation and error variance shows that the temperatures at 60 KMA stations are faithfully reproduced based on coarse reanalysis data. The utility of this technique for downscaling model predictions based on future scenarios is also addressed.

A New Perspective on the Climate Prediction of Asian Summer Monsoon Precipitation

A new paradigm for climate (one month and longer) prediction is developed and is applied to the 5-day-averaged Asian summer monsoon (ASM) precipitation. The foundation of the method is to identify climate signals (deterministic components) that constitute the ASM system and predict the temporal fluctuations of the amplitudes (stochastic components) of the individual signals. Climate signals were identified via cyclostationary empirical orthogonal function (CSEOF) analysis of the Xie–Arkin pentad precipitation in this study and include the annual cycle, El Niño/La Niña, and the intraseasonal oscillations of the 40–50-day period band (the Madden–Julian oscillation). Prediction is much facilitated by forecasting the slowly undulating amplitude time series of each climate signal rather than the raw precipitation data directly. The new prediction method results in reasonable forecasts of the pentad precipitation for the test period of 1999–2001. Specifically, the propagation of the intraseasonal oscillations is predicted successfully 60 days in advance. The performance of the new method is significantly better than persistence and that of conventional prediction methods in which raw data is predicted directly.

Interannual Variability of Patterns of Atmospheric Mass Distribution

Using the 40-yr European Centre for Medium-Range Weather Forecasts (ECMWF) Re-Analysis (ERA-40) for 1958 to 2001, adjusted for bias over the southern oceans prior to 1979, an analysis is made of global patterns of monthly mean anomalies of atmospheric mass, which is approximately conserved globally. It differs from previous analyses of atmospheric circulation by effectively area weighting surface or sea level pressure that diminishes the role of high latitudes. To examine whether global patterns of behavior exist requires analysis of all seasons together (as opposite seasons occur in each hemisphere). Empirical orthogonal function (EOF) analysis, R-mode varimax-rotated EOF analysis, and cyclostationary EOF (CSEOF) analysis tools are used to explore patterns and variability on interannual and longer time scales. Clarification is given of varimax terminology and procedures that have been previously misinterpreted. The dominant global monthly variability overall is associated with the Southern Hemisphere annular mode (SAM), which is active in all months of the year. However, it is not very coherent from month to month and exhibits a great deal of natural unforced variability. The third most important pattern is the Northern Hemisphere annular mode (NAM) and associated North Atlantic Oscillation (NAO), which is the equivalent Northern Hemisphere expression. Neither of these is really a global mode, although they covary on long time scales in association with tropical or external forcing. For monthly data, the second mode is coherent with Niño-3.4 sea surface temperatures and thus corresponds to El Niño–Southern Oscillation (ENSO), which is truly global in extent. It exhibits more coherent evolution with time and projects strongest onto the interannual variability, where it stands out by far as the dominant mode in the CSEOF analysis. The CSEOF analysis extracts the patterns phase locked with annual cycle and reveals their evolution throughout the year. Standard EOF and varimax analyses are not able to evolve with time of year unless the analysis is stratified by season. Varimax analysis is able to extract the SAM, NAM, and ENSO modes very well, however.

Regional Heat Sources and the Active and Break Phases of Boreal Summer Intraseasonal (30–50 Day) Variability*

The boreal summer intraseasonal variability (BSISV) associated with the 30–50-day mode is represented by the coexistence of three components: poleward propagation of convection over the Indian and tropical west Pacific longitudes and eastward propagation along the equator. The hypothesis that the three components influence each other has been investigated using observed outgoing longwave radiation (OLR), NCEP–NCAR reanalysis, and solutions from an idealized linear model. The null hypothesis is that the three components are mutually independent. Cyclostationary EOF (CsEOF) analysis is applied on filtered OLR to extract the life cycle of the BSISV. The dominant CsEOF mode is significantly tied to the observed spatial rainfall pattern associated with the active/break phases over the Indian subcontinent. The components of the heating patterns from CsEOF analysis serve as prescribed forcings for the dry version of the linear model. This allows one to investigate the possible roles that the regional heat sources and sinks play in driving the large-scale monsoon circulation at various stages of the BSISV life cycle. To understand the interactive nature between convection and circulation, the moist version of the model is forced with intraseasonal SST anomalies. The linear models reproduce the major features of the BSISV seen in the reanalysis. The linear model suggests three new findings: (i) The circulation anomalies that develop as a Rossby wave response to suppressed convection over the equatorial Indian Ocean associated with the previous break phase of the BSISV results in low-level convergence and tropospheric moisture enhancement over the equatorial western Indian Ocean and helps trigger the next active phase of the BSISV. (ii) The development of convection over the tropical west Pacific forces descent anomalies to the west. This, in conjunction with the weakened cross-equatorial flow due to suppressed convective anomalies over the equatorial Indian Ocean, reduces the tropospheric moisture over the Arabian Sea and promotes westerly wind anomalies that do not recurve over India. As a result the low-level cyclonic vorticity shifts from India to Southeast Asia and break conditions are initiated over India. (iii) The circulation anomalies forced by equatorial Indian Ocean convective anomalies significantly influence the active/break phases over the tropical west Pacific. The model solutions support the hypothesis that the three components of the BSISV influence each other but do not imply that such an influence is responsible for the space–time evolution of the BSISV. Further, the applicability of the model results to the observed system is constrained by the assumption that linear interactions are sufficient to address the BSISV and that air–sea interaction and transient forcing are excluded.