June-Yi Lee

Subtropical High predictability establishes a promising way for monsoon and tropical storm predictions

Monsoon rainfall and tropical storms (TSs) impose great impacts on society, yet their seasonal predictions are far from successful. The western Pacific Subtropical High (WPSH) is a prime circulation system affecting East Asian summer monsoon (EASM) and western North Pacific TS activities, but the sources of its variability and predictability have not been established. Here we show that the WPSH variation faithfully represents fluctuations of EASM strength (r = –0.92), the total TS days over the subtropical western North Pacific (r = –0.81), and the total number of TSs impacting East Asian coasts (r = –0.76) during 1979–2009. Our numerical experiment results establish that the WPSH variation is primarily controlled by central Pacific cooling/warming and a positive atmosphere-ocean feedback between the WPSH and the Indo-Pacific warm pool oceans. With a physically based empirical model and the state-of-the-art dynamical models, we demonstrate that the WPSH is highly predictable; this predictability creates a promising way for prediction of monsoon and TS. The predictions using the WPSH predictability not only yields substantially improved skills in prediction of the EASM rainfall, but also enables skillful prediction of the TS activities that the current dynamical models fail. Our findings reveal that positive WPSH–ocean interaction can provide a source of climate predictability and highlight the importance of subtropical dynamics in understanding monsoon and TS predictability.

Potential Predictability of Summer Mean Precipitation in a Dynamical Seasonal Prediction System with Systematic Error Correction

Potential predictability of summer mean precipitation over the globe is investigated using data obtained from seasonal prediction experiments for 21 yr from 1979 to 1999 using the Korea Meteorological Administration‐ Seoul National University (KMA‐SNU) seasonal prediction system. This experiment is a part of the Climate Variability and Predictability Program (CLIVAR) Seasonal Model Intercomparison Project II (SMIP II). The observed SSTs are used for the external boundary condition of the model integration; thus, the present study assesses the upper limit of predictability of the seasonal prediction system. The analysis shows that the tropical precipitation is largely controlled by the given SST condition and is thus predictable, particularly in the ENSO region. But the extratropical precipitation is less predictable due to the large contribution of the internal atmospheric processes to the seasonal mean. The systematic error of the ensemble mean prediction is particularly large in the subtropical western Pacific, where the air‐sea interaction is active and thus the two-tier approach of the present prediction experiment is not appropriate for correct predictions in the region. The statistical postprocessing method based on singular value decomposition corrects a large part of the systematic errors over the globe. In particular, about two-thirds of the total errors in the western Pacific are corrected by the postprocessing method. As a result, the potential predictability of the summer-mean precipitation is greatly enhanced over most of the globe by the statistical correction method; the 21-yr-averaged patterncorrelation value between the predictions and their observed counterparts is changed from 0.31 before the correction to 0.48 after the correction for the global domain and from 0.04 before the correction to 0.26 after the correction for the Asian monsoon and the western Pacific region.

Divergent global precipitation changes induced by natural versus anthropogenic forcing

As a result of global warming, precipitation is likely to increase in high latitudes and the tropics and to decrease in already dry subtropical regions. The absolute magnitude and regional details of such changes, however, remain intensely debated. As is well known from El Niño studies, sea-surface-temperature gradients across the tropical Pacific Ocean can strongly influence global rainfall. Palaeoproxy evidence indicates that the difference between the warm west Pacific and the colder east Pacific increased in past periods when the Earth warmed as a result of increased solar radiation. In contrast, in most model projections of future greenhouse warming this gradient weakens. It has not been clear how to reconcile these two findings. Here we show in climate model simulations that the tropical Pacific sea-surface-temperature gradient increases when the warming is due to increased solar radiation and decreases when it is due to increased greenhouse-gas forcing. For the same global surface temperature increase the latter pattern produces less rainfall, notably over tropical land, which explains why in the model the late twentieth century is warmer than in the Medieval Warm Period (around ad 1000–1250) but precipitation is less. This difference is consistent with the global tropospheric energy budget, which requires a balance between the latent heat released in precipitation and radiative cooling. The tropospheric cooling is less for increased greenhouse gases, which add radiative absorbers to the troposphere, than for increased solar heating, which is concentrated at the Earth’s surface. Thus warming due to increased greenhouse gases produces a climate signature different from that of warming due to solar radiation changes.

Predictability of the Madden–Julian Oscillation in the Intraseasonal Variability Hindcast Experiment (ISVHE)*

The Madden‐Julian oscillation (MJO) represents a primary source of predictability on the intraseasonal time scalesanditsinfluenceextends fromseasonalvariationstoweatherand extreme events.While the lastdecadehas witnessed marked improvement in dynamical MJO prediction, an updated estimate of MJO predictability from a contemporary suite of dynamic models, in conjunction with an estimate of their corresponding prediction skill, is crucial for guiding future research and development priorities. In this study, the predictability of the boreal winter MJOis revisited based on the Intraseasonal Variability Hindcast Experiment (ISVHE), a set of dedicated extended-range hindcasts from eight different coupled models. Two estimates of MJO predictability are made, based on single-member and ensemble-mean hindcasts, giving values of 20‐30 days and 35‐45 days, respectively. Exploring the dependence of predictability on the phase of MJO during hindcast initiation reveals a slightly higher predictability for hindcasts initiated from MJO phases 2, 3, 6, or 7 in three of the models with higher prediction skill. The estimated predictability of MJO initiated in phases 2 and 3 (i.e., convection in Indian Ocean with subsequentpropagationacrossMaritimeContinent)beingequalto orhigherthanotherMJOphasesimplies that the so-called Maritime Continent prediction barrier may not actually be an intrinsic predictability limitation. For most of the models, the skill for single-member (ensemble mean) hindcasts is less than the estimated predictability limit by about 5‐10 days (15‐25 days), implying that significantly more skillful MJO forecasts can be afforded through further improvements of dynamical models and ensemble prediction systems (EPS).

The North Pacific as a Regulator of Summertime Climate over Eurasia and North America

Abstract The role of the North Pacific as a regulator of boreal summer climate over Eurasia and North America is investigated using observational data. Two summertime interannual climate modes associated with sea surface temperature (SST) variability in the North Pacific are identified. The first mode shows an elongated zone of warm (cold) SST anomalies in the central North Pacific along 40°N, with temporal variability significantly correlated with El Nino during the preceding spring, but its subsequent evolution is quite different from El Nino. The second mode exhibits a seesaw SST variation between the northern and southern North Pacific and is independent of El Nino. Both modes are linked to coherent SST anomalies over the North Atlantic, suggesting the presence of an “atmospheric bridge” linking the two extratropical oceans. Using the principal component of the most dominant mode as the North Pacific index (NPI), composite analyses show that the positive (negative) phase of NPI features a warm (cold) ...

Limitations of Seasonal Predictability for Summer Climate over East Asia and the Northwestern Pacific

AbstractPredictability of summer climate anomalies over East Asia and the northwestern Pacific is investigated using observations and a multimodel hindcast ensemble initialized on 1 May for the recent 20–30 yr. Summertime East Asia is under the influence of the northwestern Pacific subtropical high (PASH). The Pacific–Japan (PJ) teleconnection pattern, a meridional dipole of sea level pressure variability, affects the northwestern PASH. The forecast models generally capture the association of the PJ pattern with the El Nino–Southern Oscillation (ENSO).The Silk Road pattern, a wave train along the summer Asian jet, is another dominant teleconnection that influences the northwestern PASH and East Asia. In contrast to the PJ pattern, observational analysis reveals a lack of correlations between the Silk Road pattern and ENSO. Coupled models cannot predict the temporal phase of the Silk Road pattern, despite their ability to reproduce its spatial structure as the leading mode of atmospheric internal variabili...

Changes in the Tropical Pacific SST Trend from CMIP3 to CMIP5 and Its Implication of ENSO

This study assesses the changes in the tropical Pacific Ocean sea surface temperature (SST) trend and ENSO amplitude by comparing a historical run of the World Climate Research Programme Coupled Model Intercomparison Project (CMIP) phase-5 multimodel ensemble dataset (CMIP5) and the CMIP phase-3 dataset (CMIP3). The results indicate that the magnitude of the SST trend in the tropical Pacific basin has been significantly reduced from CMIP3 to CMIP5, which may be associated with the overestimation of the response to natural forcing and aerosols by including Earth system models in CMIP5. Moreover, the patterns

Asian summer monsoon rainfall predictability: a predictable mode analysis

Abstract To what extent the Asian summer monsoon (ASM) rainfall is predictable has been an important but long-standing issue in climate science. Here we introduce a predictable mode analysis (PMA) method to estimate predictability of the ASM rainfall. The PMA is an integral approach combining empirical analysis, physical interpretation and retrospective prediction. The empirical analysis detects most important modes of variability; the interpretation establishes the physical basis of prediction of the modes; and the retrospective predictions with dynamical models and physics-based empirical (P–E) model are used to identify the “predictable” modes. Potential predictability can then be estimated by the fractional variance accounted for by the “predictable” modes. For the ASM rainfall during June–July–August, we identify four major modes of variability in the domain (20°S–40°N, 40°E–160°E) during 1979–2010: (1) El Niño-La Nina developing mode in central Pacific, (2) Indo-western Pacific monsoon-ocean coupled mode sustained by a positive thermodynamic feedback with the aid of background mean circulation, (3) Indian Ocean dipole mode, and (4) a warming trend mode. We show that these modes can be predicted reasonably well by a set of P–E prediction models as well as coupled models’ multi-model ensemble. The P–E and dynamical models have comparable skills and complementary strengths in predicting ASM rainfall. Thus, the four modes may be regarded as “predictable” modes, and about half of the ASM rainfall variability may be predictable. This work not only provides a useful approach for assessing seasonal predictability but also provides P–E prediction tools and a spatial-pattern-bias correction method to improve dynamical predictions. The proposed PMA method can be applied to a broad range of climate predictability and prediction problems.

Improved simulation of two types of El Niño in CMIP5 models

Using the coupled general circulation models (CGCMs) participating in phases 3 and 5 of the Coupled Model Intercomparison Project (CMIP3 and CMIP5), simulations of the two types of El Ni˜ no event are evaluated. Previous studies using CMIP3 models pointed out that most of

Assessment of the APCC coupled MME suite in predicting the distinctive climate impacts of two flavors of ENSO during boreal winter

Forecast skill of the APEC Climate Center (APCC) Multi-Model Ensemble (MME) seasonal forecast system in predicting two main types of El Niño-Southern Oscillation (ENSO), namely canonical (or cold tongue) and Modoki ENSO, and their regional climate impacts is assessed for boreal winter. The APCC MME is constructed by simple composite of ensemble forecasts from five independent coupled ocean-atmosphere climate models. Based on a hindcast set targeting boreal winter prediction for the period 1982–2004, we show that the MME can predict and discern the important differences in the patterns of tropical Pacific sea surface temperature anomaly between the canonical and Modoki ENSO one and four month ahead. Importantly, the four month lead MME beats the persistent forecast. The MME reasonably predicts the distinct impacts of the canonical ENSO, including the strong winter monsoon rainfall over East Asia, the below normal rainfall and above normal temperature over Australia, the anomalously wet conditions across the south and cold conditions over the whole area of USA, and the anomalously dry conditions over South America. However, there are some limitations in capturing its regional impacts, especially, over Australasia and tropical South America at a lead time of one and four months. Nonetheless, forecast skills for rainfall and temperature over East Asia and North America during ENSO Modoki are comparable to or slightly higher than those during canonical ENSO events.