Mong-Ming Lu

Definition of South China Sea Monsoon Onset and Commencement of the East Asia Summer Monsoon

The climatological mean summer monsoon onset in the South China Sea (SCS) is a remarkably abrupt event. However, defining onset dates for individual years is noticeably controversial. The controversies and complications arise primarily from a number of factors: the intermittent southward intrusion of cold fronts into the northern SCS, the bogus onset in late April before the establishment of tropical monsoons over Indochina, and active intraseasonal oscillation. In this paper, a simple yet effective index, USCS, the 850-hPa zonal winds averaged over the central SCS (58‐158N and 1108‐1208E), is proposed for objectively defining the SCS monsoon onset. This onset index depicts not only the sudden establishment of the tropical southwesterly monsoon over the SCS but also the outbreak of the rainy season in the central-northern SCS. In this paper the East Asian summer monsoon (EASM) is defined as the broadscale summer monsoon over East Asia and the western North Pacific region (08‐408N, 1008‐1408E). It is shown that the seasonal transition of EASM can be objectively determined by the principal component of the dominant empirical orthogonal mode of the 850-hPa zonal winds, UEOF1. It is found that the local index USCS represents UEOF1 extremely well; thus, it can be used to determine both the SCS onset and the commencement of the broadscale EASM. The result suggests that the SCS summer monsoon onset indeed signifies the beginning of the summer monsoon over East Asia and the adjacent western Pacific Ocean. Evidence is also provided to show the linkage between the two salient phases of EASM: the local onset of the SCS monsoon and the local onset of the mei-yu (the rainy season in the Yangtze River and Huai River basin and southern Japan).

Vertical structure and physical processes of the Madden-Julian Oscillation: Exploring key model physics in climate simulations

Aimed at reducing deficiencies in representing the Madden-Julian oscillation (MJO) in general circulation models (GCMs), a global model evaluation project on vertical structure and physical processes of the MJO was coordinated. In this paper, results from the climate simulation component of this project are reported. It is shown that the MJO remains a great challenge in these latest generation GCMs. The systematic eastward propagation of the MJO is only well simulated in about one fourth of the total participating models. The observed vertical westward tilt with altitude of the MJO is well simulated in good MJO models but not in the poor ones. Damped Kelvin wave responses to the east of convection in the lower troposphere could be responsible for the missing MJO preconditioning process in these poor MJO models. Several process-oriented diagnostics were conducted to discriminate key processes for realistic MJO simulations. While large-scale rainfall partition and low-level mean zonal winds over the Indo-Pacific in a model are not found to be closely associated with its MJO skill, two metrics, including the low-level relative humidity difference between high- and low-rain events and seasonal mean gross moist stability, exhibit statistically significant correlations with the MJO performance. It is further indicated that increased cloud-radiative feedback tends to be associated with reduced amplitude of intraseasonal variability, which is incompatible with the radiative instability theory previously proposed for the MJO. Results in this study confirm that inclusion of air-sea interaction can lead to significant improvement in simulating the MJO.

A change in the relationship between tropical central Pacific SST variability and the extratropical atmosphere around 1990

A newly released reanalysis dataset covering the period 1979–2009 is analyzed to show that the sea surface temperature (SST) variability in the tropical central Pacific is more closely related to the SST variability in the tropical eastern Pacific before 1990 but more closely related to sea level pressure (SLP) variations associated with the North Pacific Oscillation (NPO) after 1990. Only during the period after 1990 can the NPO excite large SST variability in the tropical central Pacific. Related to this change, El Nino Southern Oscillation (ENSO) SST anomalies tend to spread from the eastern to central tropical Pacific before 1990 in a pattern resembling that associated with the Eastern Pacific (EP) type of ENSO, but are more closely connected to SST variability in the subtropical north Pacific after 1990 with a pattern resembling that of the Central Pacific (CP) type of ENSO. This study concludes that the increased influence of the NPO on the tropical Pacific is a likely reason for the increasing occurrence of the CP type of ENSO since 1990. An analysis of the mean atmospheric circulation during these two periods suggests that the increased NPO influence is associated with a strengthening Hadley circulation after 1990.

CMIP5 model simulations of the impacts of the two types of El Niño on the U.S. winter temperature

PUBLICATIONS Journal of Geophysical Research: Atmospheres RESEARCH ARTICLE 10.1002/2013JD021064 Key Points: • CMIP5 models simulate U.S. winter response to EP ENSO well but not to CP ENSO • The performance difference is due to different OLR response induced by two ENSOs • The two types of ENSO initiate differ- ent wavetrain patterns in the NH Correspondence to: J.-Y. Yu, jyyu@uci.edu Citation: Zou, Y., J.-Y. Yu, T. Lee, M.-M. Lu, and S. T. Kim (2014), CMIP5 model simula- tions of the impacts of the two types of El Nino on the U.S. winter temperature, J. Geophys. Res. Atmos., 119, doi:10.1002/2013JD021064. Received 20 OCT 2013 Accepted 22 FEB 2014 Accepted article online 27 FEB 2014 CMIP5 model simulations of the impacts of the two types of El Nino on the U.S. winter temperature Yuhao Zou 1 , Jin-Yi Yu 1 , Tong Lee 2 , Mong-Ming Lu 3 , and Seon Tae Kim 4 Department of Earth System Science, University of California, Irvine, California, USA, 2 Jet Propulsion Laboratory, California Institute of Technology, Pasadena, California, USA, 3 Research and Development Center, Central Weather Bureau, Taipei, Taiwan, 4 Marine and Atmospheric Research, CSIRO, Aspendale, Victoria, Australia Abstract Thirty Coupled Model Intercomparison Project phase 5 (CMIP5) preindustrial simulations are examined to contrast impacts of the two types of El Nino on the U.S. winter temperatures. The CMIP5 models are found more capable of simulating the observed eastern Pacific (EP) El Nino impacts (a warm northeast, cold southwest pattern over the U.S.) but less capable of simulating the observed central Pacific (CP) El Nino impacts (a warm northwest, cold southeast pattern). During EP El Nino, sea surface temperature (SST) anomalies influence the Walker circulation giving rise to a basin-wide pattern of outgoing longwave radiation (OLR) anomalies. The modeled atmospheric responses to the EP El Nino are thus less sensitive to the detailed structure of the simulated SST anomalies and can be well simulated by most of the CMIP5 models. In contrast, the SST anomalies during the CP El Nino affect the strength of the Walker circulation less effectively than the EP El Nino. OLR anomalies are local, rather than basin wide. The modeled atmospheric responses to the CP El Nino therefore depend more on how realistically the CP El Nino SST anomalies are simulated in the models. As a result, the CP El Nino’s impact on the U.S. winter temperature, controlled by the atmospheric wave train response to the OLR forcing, is less well simulated by the CMIP5 models. This conclusion is supported by an examination of the Pacific North American and tropical/Northern Hemisphere patterns produced by the CMIP5 models in response to the two types of El Nino. 1. Introduction The impacts of El Nino on the United States (U.S.) climate have been extensively studied over the past few decades [e.g., Ropelewski and Halpert, 1986, 1989; Kiladis and Diaz, 1989; Livezey et al., 1997; Dettinger et al., 1998; Mo and Higgins, 1998; Montroy et al., 1998; Cayan et al., 1999; Larkin and Harrison, 2005, and many others]. For the winter climate, El Nino’s impact has traditionally been described as a north-south anomaly pattern with the winter being colder and wetter than normal in the southern U.S. and warmer and drier than normal in the northern U.S. This conventional view has been revised in recent years amid the increasing recognition that there exist different types or flavors of El Nino events [Larkin and Harrison, 2005; Ashok et al., 2007; Yu and Kao, 2007; Guan and Nigam, 2008; Kao and Yu, 2009; Kug et al., 2009]. Two particular types have been emphasized: an eastern Pacific (EP) type that has its sea surface temperature (SST) anomalies located off the South American coast and a central Pacific (CP) type that has the anomalies confined around the International Date Line [Yu and Kao, 2007; Kao and Yu, 2009]. Weng et al. [2009], for example, noticed that EP El Nino events increase rainfall in the western U.S. by shifting the polar jet stream equatorward, while CP El Nino events increase the rainfall there by shifting the Intertropical Convergence Zone poleward. Mo [2010] contrasted the impacts of El Nino on air temperature and precipitation over the U.S. during the period 1915–1960 when the EP type dominated and the period 1962–2006 when the CP type became increasingly dominant. She noted that the EP El Nino produces a north-south contrast pattern in the U.S. winter temperature variations, while the CP El Nino produces an east-west contrast pattern. Yu and Zou [2013] showed that the CP El Nino enhances the typical drying effect of El Nino over the northern U.S. but weakens the wetting effect over the southern U.S. These and other recent studies [e.g., Sheffield et al., 2013; Xu et al., 2013; Liang et al., 2014] support the assertion that the EP and CP El Nino have different impacts on the U.S. climate. Yu et al. [2012b] developed a way to identify the El Nino impacts of the two types using two indices that they called CP and EP indices. By regression analyses with these two indices, they showed that the El Nino impact ZOU ET AL. ©2014. American Geophysical Union. All Rights Reserved.

Association of Taiwan’s Rainfall Patterns with Large-Scale Oceanic and Atmospheric Phenomena

A 50-year (1960–2009) monthly rainfall gridded dataset produced by the Taiwan Climate Change Projection and Information Platform Project was presented in this study. The gridded data (5 × 5 km) displayed influence of topography on spatial variability of rainfall, and the results of the empirical orthogonal functions (EOFs) analysis revealed the patterns associated with the large-scale sea surface temperature variability over Pacific. The first mode (65%) revealed the annual peaks of large rainfall in the southwestern mountainous area, which is associated with southwest monsoons and typhoons during summertime. The second temporal EOF mode (16%) revealed the rainfall variance associated with the monsoon and its interaction with the slopes of the mountain range. This pattern is the major contributor to spatial variance of rainfall in Taiwan, as indicated by the first mode (40%) of spatial variance EOF analysis. The second temporal EOF mode correlated with the El Nino Southern Oscillation (ENSO). In particular, during the autumn of the La Nina years following the strong El Nino years, the time-varying amplitude was substantially greater than that of normal years. The third temporal EOF mode (7%) revealed a north-south out-of-phase rainfall pattern, the slowly evolving variations of which were in phase with the Pacific Decadal Oscillation. Because of Taiwan’s geographic location and the effect of local terrestrial structures, climate variability related to ENSO differed markedly from other regions in East Asia.

A Source of AGCM Bias in Simulating the Western Pacific Subtropical High: Different Sensitivities to the Two Types of ENSO

AbstractThis study reveals a possible cause of model bias in simulating the western Pacific subtropical high (WPSH) variability via an examination of an Atmospheric Model Intercomparison Project (AMIP) simulation produced by the atmospheric general circulation model (AGCM) developed at Taiwan’s Central Weather Bureau (CWB). During boreal summer, the model overestimates the quasi-biennial (2–3 yr) band of WPSH variability but underestimates the low-frequency (3–5 yr) band of variability. The overestimation of the quasi-biennial WPSH sensitivity is found to be due to the model’s stronger sensitivity to the central Pacific El Nino–Southern Oscillation (CP ENSO) that has a leading periodicity in the quasi-biennial band. The model underestimates the low-frequency WPSH variability because of its weaker sensitivity to the eastern Pacific (EP) ENSO that has a leading periodicity in the 3–5-yr band. These different model sensitivities are shown to be related to the relative strengths of the mean Hadley and Walker ...

Prediction of Meiyu rainfall in Taiwan by multi-lead physical–empirical models

Taiwan is located at the dividing point of the tropical and subtropical monsoons over East Asia. Taiwan has double rainy seasons, the Meiyu in May–June and the Typhoon rains in August–September. To predict the amount of Meiyu rainfall is of profound importance to disaster preparedness and water resource management. The seasonal forecast of May–June Meiyu rainfall has been a challenge to current dynamical models and the factors controlling Taiwan Meiyu variability has eluded climate scientists for decades. Here we investigate the physical processes that are possibly important for leading to significant fluctuation of the Taiwan Meiyu rainfall. Based on this understanding, we develop a physical–empirical model to predict Taiwan Meiyu rainfall at a lead time of 0- (end of April), 1-, and 2-month, respectively. Three physically consequential and complementary predictors are used: (1) a contrasting sea surface temperature (SST) tendency in the Indo-Pacific warm pool, (2) the tripolar SST tendency in North Atlantic that is associated with North Atlantic Oscillation, and (3) a surface warming tendency in northeast Asia. These precursors foreshadow an enhanced Philippine Sea anticyclonic anomalies and the anomalous cyclone near the southeastern China in the ensuing summer, which together favor increasing Taiwan Meiyu rainfall. Note that the identified precursors at various lead-times represent essentially the same physical processes, suggesting the robustness of the predictors. The physical empirical model made by these predictors is capable of capturing the Taiwan rainfall variability with a significant cross-validated temporal correlation coefficient skill of 0.75, 0.64, and 0.61 for 1979–2012 at the 0-, 1-, and 2-month lead time, respectively. The physical–empirical model concept used here can be extended to summer monsoon rainfall prediction over the Southeast Asia and other regions.

Analysis of space–time patterns of rainfall events during 1996–2008 in Yilan County (Taiwan)

Understanding local precipitation patterns is essential to water resource management and flood mitigation. Precipitation patterns can vary in space and time depending on factors from different spatial scales such as local topographical changes and macroscopic atmospheric circulation. This study applied the two-stage classification method to distinguish the space–time patterns of local precipitations in the two identified distinct synoptic conditions, i.e. summer and autumn, from 24 gauges during 1996–2008 in Yilan County, Taiwan. The proposed method classifies the synoptic and local conditions for the space–time rainfall patterns by using K-means coupled with empirical orthogonal function analysis, and hierarchical ascending clustering method respectively. The proposed two-stage classification method considers not only the magnitude and the space–time distribution of rainfall events, but also the associated synoptic conditions. The results identified three primary patterns of extreme and two patterns of normal events in both seasons. Regarding the extreme events from typhoons, wind directions and the frontal accompanied effect are major contributors to the magnitude and spatial distribution of rainfall events in the summer and autumn, respectively. Spatiotemporal covariance structures are used to characterize the variability of normal events, showing the increasing frequency of wide spatial and temporal ranges from the summer to autumn. In summary, the proposed classification analysis provides patterns associated with distinct underlying physical mechanisms and space–time characteristics. The general characteristics of rainfall patterns can provide insights for the hydrological modeling of local catchments under different climatic scenarios.

A space-time typhoon trajectories analysis in the vicinity of Taiwan

Abstract Tropical cyclones are one of the most serious natural disasters in northwestern Pacific Ocean. In general, an average of three to four typhoons invades the vicinity of Taiwan annually, which brings heavy rainfalls and strong winds resulting in disasters including flooding, mudflows, and landslides, leading to severe damage to economies and casualties. Studies show that different tracks of typhoon can cause distinct spatio-temporal patterns of rainfall events at different regions of Taiwan. As a result, understanding the trajectories of tropical cyclones and their relationship to climatic variables at global scale is crucial for hydrological modeling and disaster migration in Taiwan, especially under the conditions of climate change. This study applied a probabilistic curve clustering technique, which is based on a regression mixture model, to classify the best tracks of typhoons across the area within 6° around Taiwan during the period of 1951–2009. For the purposes of modeling and forecasting the typhoon trajectories, the track cluster is performed separately in different seasons due to their distinct driving forces to typhoon movements. A generalized linear model (GLM) is used to characterize the relationship between the identified typhoon tracks and the dominant climate features derived from NCEP reanalysis data. Results showed the six major typhoon tracks in the vicinity of Taiwan for different seasons respectively. The result of GLM cross validation showed that the frequency of typhoon tracks passing cross Taiwan in summer can significantly depend upon with two empirical orthogonal functions (EOFs) of sea level pressure, and the third EOF of sea surface temperature.