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Bin Wang, Renguang Wu, and Roger Lukas

Abstract

In this paper the amplitude-phase characteristics of the annual adjustment of the thermocline in the entire tropical Pacific Ocean are described and numerical experiments with a tropical ocean model are performed to assess the roles of the major wind systems in controlling the annual variation of the thermocline.

In the region between about 8°N and 10°S, the annual adjustment of the thermocline is controlled by both the Ekman pumping and equatorial wave propagation. The local wind stress forcing plays a dominant role in the central North Pacific (3°–8°N, 170°–120°W) where the thermocline exhibits the largest amplitude due to the prominent annual variation of the wind stress curl south of the ITCZ. In the equatorial central Pacific (2°N–5°S, 170°–120°W), the annual cycle also exhibits a pronounced unimodal seasonal variation (deepest in December and shallowest in May–June). This distinctive annual cycle results primarily from the adjustment of the waves, which are excited around 4°N, 110°W by the annual march of the ITCZ and excited in the equatorial western Pacific by the monsoon flows. The December maximum and May–June minimum then propagate westward in the off-equatorial waveguides along 5°N (3°–7°N) and 6°S (3°–9°S) to the western boundary. These annual Rossby waves are reflected at the western ocean boundary. The bimodal annual variation in the equatorial western Pacific is caused by the combined effects of the annual Rossby wave reflection and the monsoon westerly forcing during transitional seasons. The bimodal variations in the equatorial far eastern Pacific are determined by the remote forcing through the eastward propagation of Kelvin waves.

The thermocline variations in the North Pacific poleward of 8°N and in the South Pacific poleward of 10°S form approximately an annual seesaw oscillation with maximum depth occurring in May–June (October–November) and minimum in December (April–May) in the North (South) Pacific. These regions are characterized by an Ekman regime.

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Xudong Yin, Juanjuan Liu, and Bin Wang

Abstract

Model parameters can introduce significant uncertainties in climate simulations. Sensitivity analysis provides a way to quantify such uncertainties. Existing sensitivity analysis methods, however, cannot estimate the maximum sensitivity of the simulated climate to perturbations in multiple parameters. This study proposes the concept of nonlinear ensemble parameter perturbation (NEPP), which is independent of model initial conditions, to estimate the maximum effect of parameter perturbations on simulating Earth’s climate. The NEPP is obtained by solving a maximization problem, whose cost function is defined by the maximum deviation of a unique ensemble of short-term predictions with large enough members caused by parameter perturbations and whose optimal solution is obtained by an ensemble-based gradient approach. This method is used to investigate the effects of NEPP on the climate of the Lorenz-63 model and a complex climate model, the Grid-Point Atmospheric Model of IAP LASG, version 2 (GAMIL2). It is found that the NEPP is capable of estimating the maximum change in climate simulation caused by perturbations in multiple parameters when the Lorenz-63 model is used. With a low computational cost, the NEPP can cause remarkable changes in the climatology of GAMIL2. The results also illustrate that the effects of parameter perturbations on short-term weather predictions and those on long-term climate simulations are correlated.

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Chengsi Liu, Qingnong Xiao, and Bin Wang

Abstract

Applying a flow-dependent background error covariance (𝗕 matrix) in variational data assimilation has been a topic of interest among researchers in recent years. In this paper, an ensemble-based four-dimensional variational (En4DVAR) algorithm, designed by the authors, is presented that uses a flow-dependent background error covariance matrix constructed by ensemble forecasts and performs 4DVAR optimization to produce a balanced analysis. A great advantage of this En4DVAR design over standard 4DVAR methods is that the tangent linear and adjoint models can be avoided in its formulation and implementation. In addition, it can be easily incorporated into variational data assimilation systems that are already in use at operational centers and among the research community.

A one-dimensional shallow water model was used for preliminary tests of the En4DVAR scheme. Compared with standard 4DVAR, the En4DVAR converges well and can produce results that are as good as those with 4DVAR but with far less computation cost in its minimization. In addition, a comparison of the results from En4DVAR with those from other data assimilation schemes [e.g., 3DVAR and ensemble Kalman filter (EnKF)] is made. The results show that the En4DVAR yields an analysis that is comparable to the widely used variational or ensemble data assimilation schemes and can be a promising approach for real-time applications.

In addition, experiments were carried out to test the sensitivities of EnKF and En4DVAR, whose background error covariance is estimated from the same ensemble forecasts. The experiments indicated that En4DVAR obtained reasonably sound analysis even with larger observation error, higher observation frequency, and more unbalanced background field.

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Lijuan Li, Bin Wang, and Guang J. Zhang

Abstract

The weak response of surface shortwave cloud radiative forcing (SWCF) to El Niño over the equatorial Pacific remains a common problem in many contemporary climate models. This study shows that two versions of the Grid-Point Atmospheric Model of the Institute of Atmospheric Physics (IAP)/State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics (LASG) (GAMIL) produce distinctly different surface SWCF response to El Niño. The earlier version, GAMIL1, underestimates this response, whereas the latest version, GAMIL2, simulates it well. To understand the causes for the different SWCF responses between the two simulations, the authors analyze the underlying physical mechanisms. Results indicate the enhanced stratiform condensation and evaporation in GAMIL2 play a key role in improving the simulations of multiyear annual mean water vapor (or relative humidity), cloud fraction, and in-cloud liquid water path (ICLWP) and hence in reducing the biases of SWCF and rainfall responses to El Niño due to all of the improved dynamical (vertical velocity at 500 hPa), cloud amount, and liquid water path (LWP) responses. The largest contribution to the SWCF response improvement in GAMIL2 is from LWP in the Niño-4 region and from low-cloud cover and LWP in the Niño-3 region. Furthermore, as a crucial factor in the low-cloud response, the atmospheric stability change in the lower layers is significantly influenced by the nonconvective heating variation during La Niña.

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Wen Xing, Bin Wang, and So-Young Yim

Abstract

Considerable year-to-year variability of summer rainfall exposes China to threats of frequent droughts and floods. Objective prediction of the summer rainfall anomaly pattern turns out to be very challenging. As shown in the present study, the contemporary state-of-the-art dynamical models’ 1-month-lead prediction of China summer rainfall (CSR) anomalies has insignificant skills. Thus, there is an urgent need to explore other ways to improve CSR prediction. The present study proposes a combined empirical orthogonal function (EOF)–partial least squares (PLS) regression method to offer a potential long-lead objective prediction of spatial distribution of CSR anomalies. The essence of the methodology is to use PLS regression to predict the principal component (PC) of the first five leading EOF modes of CSR. The preceding December–January mean surface temperature field [ST; i.e., SST over ocean and 2-m air temperature (T2m) over land] is selected as the predictor field for all five PCs because SST and snow cover, which is reflected by 2-m air temperature, are the most important factors that affect CSR and because the correlation between each mode and ST during winter is higher than in spring. The 4-month-lead forecast models are established by using the data from 1979 to 2004. A 9-yr independent forward-rolling prediction is made for the latest 9 yr (2005–13) as a strict forecast validation. The pattern correlation coefficient skill (0.32) between the observed and the 4-month-lead predicted patterns during the independent forecast period of 2005–13 is significantly higher than the dynamic models’ 1-month-lead hindcast skill (0.04), which indicates that the EOF–PLS regression is a useful tool for improving the current seasonal rainfall prediction. Issues related to the EOF–PLS method are also discussed.

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Xiouhua Fu, Bin Wang, and Tim Li

Abstract

Atmosphere–ocean coupling was found to play a critical role in simulating the mean Asian summer monsoon and its climatological intraseasonal oscillation (CISO) in comparisons of the results from a stand-alone ECHAM4 atmospheric general circulation model (AGCM) and a coupled ECHAM4–ocean [Wang–Li–Fu (WLF)] model. The stand-alone simulation considerably overestimates the equatorial Indian Ocean rainfall and underestimates monsoon rainfall near 15°N, particularly over the eastern Arabian Sea and the Bay of Bengal. Upon coupling with an ocean model, the simulated monsoon rainfall becomes more realistic with the rainbelt near 15°N (near the equator) intensified (reduced). These two rainbelts are connected by the northward-propagating CISOs that are significantly enhanced by the air–sea interactions.

Both local and remote air–sea interactions in the tropical Indian and Pacific Oceans contribute to better simulation of the Asian summer monsoon. The local impact is primarily due to negative feedback between SST and convection. The excessive rainfall near the equatorial Indian Ocean reduces (increases) the downward solar radiation (upward latent heat flux). These changes of surface heat fluxes cool the sea surface upon coupling, thus reducing local rainfall. The cooling of the equatorial Indian Ocean drives an anticyclonic Rossby wave response and enhances the meridional land–sea thermal contrast. Both strengthen the westerly monsoon flow and monsoon rainfall around 15°N. The local negative feedback also diminishes the excessive CISO variability in the equatorial Indian Ocean that appeared in the stand-alone atmospheric run. The remote impact stems from the reduced rainfall in the western Pacific Ocean. The overestimated rainfall (easterly wind) in the western North (equatorial) Pacific cools the sea surface upon coupling, thus reducing rainfall in the tropical western Pacific. This reduced rainfall further enhances the Indian monsoon rainfall by strengthening the Indian–Pacific Walker circulation. These results suggest that coupling an atmospheric model with an ocean model can better simulate Asian summer monsoon climatology.

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Jian Cao, Bin Wang, and Libin Ma

Abstract

Investigation of global monsoon (GM) responses to external forcings is instrumental for understanding its formation mechanism and projected future changes. Coupled climate model experiments are performed to assess how the individual and full Last Glacial Maximum (LGM) forcings change GM precipitation. Under the full LGM forcing, the annual and local summer-mean GM precipitation are reduced by 8.5% and 10.8%, respectively, compared to the results in the preindustrial control run; and the reduction of Northern Hemisphere (NH) summer monsoon (NHSM) precipitation is twice as large as its Southern Hemisphere (SH) counterpart (SHSM). The NH–SH asymmetric response is mainly caused by the monsoon circulation change–induced moisture convergence rather than the reduction of moisture content, but the root cause is the continental ice sheet forcing. The NHSM precipitation changes dramatically differ among various single-forcing experiments, while this is not the case for their SH counterparts. The moisture budget analysis indicates the NHSM is dynamically oriented, but SHSM is thermodynamically oriented. The markedly different NHSM circulation changes are caused by different forcing-induced sea surface temperature (SST) patterns, including the North Atlantic cooling pattern forced by the continental ice sheet, the mega–La Niña–like pattern resulting from the greenhouse gas forcing, and the Indian Ocean dipole–like SST pattern caused by the land–sea configuration forcing. Moreover, the distinctive change of “monsoonality” in the Australian–Indonesian monsoon is predominantly forced by the exposure of the land shelf, which enhances precipitation during early summer (November–December) but weakens it in the rest of the year.

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Tianjun Zhou, Bo Wu, and Bin Wang

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The authors evaluate the performances of 11 AGCMs that participated in the Atmospheric Model Intercomparison Project II (AMIP II) and that were run in an AGCM-alone way forced by historical sea surface temperature covering the period 1979–99 and their multimodel ensemble (MME) simulation of the interannual variability of the Asian–Australian monsoon (AAM). The authors explore to what extent these models can reproduce two observed major modes of AAM rainfall for the period 1979–99, which account for about 38% of the total interannual variances. It is shown that the MME SST-forced simulation of the seasonal rainfall anomalies reproduces the first two leading modes of variability with a skill that is comparable to the NCEP/Department of Energy Global Reanalysis 2 (NCEP-2) in terms of the spatial patterns and the corresponding temporal variations as well as their relationships with ENSO evolution. Both the biennial tendency and low-frequency components of the two leading modes are captured reasonably in MME. The skill of AMIP simulation is seasonally dependent. December–February (DJF) [July–August (JJA)] has the highest (lowest) skill. Over the extratropical western North Pacific and South China Sea, where ocean–atmosphere coupling may be critical for modeling the monsoon rainfall, the MME fails to demonstrate any skill in JJA, while the reanalysis has higher skills. The MME has deficiencies in simulating the seasonal phase of two anticyclones associated with the first mode, which are not in phase with ENSO forcing in observations but strictly match that of Niño-3.4 SST in MME. While the success of MME in capturing essential features of the first mode suggests the dominance of remote El Niño forcing in producing the predictable portion of AAM rainfall variability, the deficiency in capturing the seasonal phase implies the importance of local air–sea coupling effects. The first mode generally concurs with the turnabout of El Niño; meanwhile, the second mode is driven by La Niña at decaying stage. Multimodel intercomparison shows that there are good relationships between the simulated climatology and anomaly in terms of the degree of accuracy.

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Juan Li, Bin Wang, and Young-Min Yang

Abstract

The distinctive monsoon climate over East Asia, which is affected by the vast Eurasian continent and Pacific Ocean basin and the high-altitude Tibetan Plateau, provides arguably the best testbed for evaluating the competence of Earth system climate models. Here, a set of diagnostic metrics, consisting of 14 items and 7 variables, is specifically developed. This physically intuitive set of metrics focuses on the essential features of the East Asian summer monsoon (EASM) and East Asian winter monsoon (EAWM), and includes fields that depict the climatology, the major modes of variability, and unique characteristics of the EASM. The metrics are applied to multimodel historical simulations derived from 20 models that participated in phases 3 and 5 of the Coupled Model Intercomparison Project (CMIP3 and CMIP5, respectively), along with the newly developed Nanjing University of Information Science and Technology Earth System Model, version 3. The CMIP5 models show significant improvements over the CMIP3 models in terms of the simulated East Asian monsoon circulation systems on a regional scale, major modes of EAWM variability, the monsoon domain and precipitation intensity, and teleconnection associated with the heat source over the Philippine Sea. Clear deficiencies persist from CMIP3 to CMIP5 with respect to capturing the major modes of EASM variability, as well as the relationship between the EASM and ENSO during El Niño developing and decay phases. The possible origins that affect models’ performance are also discussed. The metrics provide a tool for evaluating the performance of Earth system climate models, and facilitating the assessment of past and projected future changes of the East Asian monsoon.

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Hiroyuki Murakami, Bin Wang, and Akio Kitoh

Abstract

Projected future changes in tropical cyclone (TC) activity over the western North Pacific (WNP) under the Special Report on Emissions Scenarios (SRES) A1B emission scenario were investigated using a 20-km-mesh, very-high-resolution Meteorological Research Institute (MRI)–Japan Meteorological Agency (JMA) atmospheric general circulation model. The present-day (1979–2003) simulation yielded reasonably realistic climatology and interannual variability for TC genesis frequency and tracks.

The future (2075–99) projection indicates (i) a significant reduction (by about 23%) in both TC genesis number and frequency of occurrence primarily during the late part of the year (September–December), (ii) an eastward shift in the positions of the two prevailing northward-recurving TC tracks during the peak TC season (July–October), and (iii) a significant reduction (by 44%) in TC frequency approaching coastal regions of Southeast Asia.

The changes in occurrence frequency are due in part to changes in large-scale steering flows, but they are due mainly to changes in the locations of TC genesis; fewer TCs will form in the western portion of the WNP (west of 145°E), whereas more storms will form in the southeastern quadrant of the WNP (10°–20°N, 145°–160°E). Analysis of the genesis potential index reveals that the reduced TC genesis in the western WNP is due mainly to in situ weakening of large-scale ascent and decreasing midtropospheric relative humidity, which are associated with the enhanced descent of the tropical overturning circulation. The analysis also indicates that enhanced TC genesis in the southeastern WNP is due to increased low-level cyclonic vorticity and reduced vertical wind shear. These changes appear to be critically dependent on the spatial pattern of future sea surface temperature; therefore, it is necessary to conduct ensemble projections with a range of SST spatial patterns to understand the degree and distribution of uncertainty in future projections.

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