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Shengjun Zhang, Tim Li, Xuyang Ge, Melinda Peng, and Ning Pan

Abstract

A combined tropical cyclone dynamic initialization–three-dimensional variational data assimilation scheme (TCDI–3DVAR) is proposed. The specific procedure for the new initialization scheme is described as follows. First, a first-guess vortex field derived from a global analysis will be spun up in a full-physics mesoscale regional model in a quiescent environment. During the spinup period, the weak vortex is forced toward the observed central minimum sea level pressure (MSLP). The so-generated balanced TC vortex with realistic MSLP and a warm core is then merged into the environmental field and used in the subsequent 3DVAR data assimilation. The observation system simulation experiments (OSSEs) demonstrate that this new TC initialization scheme leads to much improved initial MSLP, warm core, and asymmetric temperature patterns compared to those from the conventional 3DVAR scheme. Forecasts of TC intensity with the new initialization scheme are made, and the results show that the new scheme is able to predict the “observed” TC intensity change, compared to runs with the conventional 3DVAR scheme or the TCDI-only scheme. Sensitivity experiments further show that the intensity forecasts with knowledge of the initial MSLP and wind fields appear more skillful than do the cases where the initial MSLP, temperature, and humidity fields are known. The numerical experiments above demonstrate the potential usefulness of the proposed new initialization scheme in operational applications. A preliminary test of this scheme with a navy operational model shows encouraging results.

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Minghong Zhang, Shuanglin Li, Jian Lu, and Renguang Wu

Abstract

This study examines the skills in simulating interannual variability of northwestern Pacific (NWP) summer climate in 12 atmospheric general circulation models (AGCMs) attending the Atmospheric Model Intercomparison Project phase 2 (AMIP II). The models show a wide range of skills, among those version 1 of the Hadley Centre Global Atmosphere Model (HadGAM1) showed the highest fidelity and thus may be a better choice for studying East Asian–NWP summer climate. To understand the possible causes for the difference among the models, five models {HadGAM1; ECHAM5; the Geophysical Fluid Dynamics Laboratory Atmosphere Model, version 2.1 (AM2.1); Model for Interdisciplinary Research on Climate 3.2, high-resolution version [MIROC3.2(hires)]; and the fourth-generation National Center for Atmospheric Research Community Atmosphere Model (CAM3)} that have various skill levels, ranging from the highest to the moderate to the minor, were selected for analyses. The simulated teleconnection of NWP summer climate with sea surface temperatures (SSTs) in the tropical Indian and Pacific Oceans was first compared. HadGAM1 reproduces suppressed (intensified) rainfall during El Niño (La Niña) events and captures well the remote connection with the tropical Indian Ocean, while the other models either underestimate [ECHAM5, AM2.1, MIROC3.2(hires)] or fail to reproduce (CAM3) these teleconnections. The Walker cell and diabatic heating were further compared to shed light on the underlying physical mechanisms for the difference. Consistent with the best performance in simulating interannual rainfall, HadGAM1 exhibits the highest-level skill in capturing the observed climatology of the Walker cell and diabatic heating. These results highlight the key roles of the model’s background climatology in the Walker cell and diabatic heating, thus providing important clues to improving the model’s ability.

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Feng Zhang, Zhongping Shen, Jiangnan Li, Xiuji Zhou, and Leiming Ma

Abstract

Although single-layer solutions have been obtained for the δ-four-stream discrete ordinates method (DOM) in radiative transfer, a four-stream doubling–adding method (4DA) is lacking, which enables us to calculate the radiative transfer through a vertically inhomogeneous atmosphere with multiple layers. In this work, based on the Chandrasekhar invariance principle, an analytical method of δ-4DA is proposed.

When applying δ-4DA to an idealized medium with specified optical properties, the reflection, transmission, and absorption are the same if the medium is treated as either a single layer or dividing it into multiple layers. This indicates that δ-4DA is able to solve the multilayer connection properly in a radiative transfer process. In addition, the δ-4DA method has been systematically compared with the δ-two-stream doubling–adding method (δ-2DA) in the solar spectrum. For a realistic atmospheric profile with gaseous transmission considered, it is found that the accuracy of δ-4DA is superior to that of δ-2DA in most of cases, especially for the cloudy sky. The relative errors of δ-4DA are generally less than 1% in both the heating rate and flux, while the relative errors of δ-2DA can be as high as 6%.

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Zhe Li, Dawen Yang, Yang Hong, Jian Zhang, and Youcun Qi

Abstract

Understanding spatiotemporal rainfall patterns in mountainous areas is of great importance for prevention of natural disasters such as flash floods and landslides. There is little knowledge about rainfall variability over historically underobserved complex terrains, however, and especially about the variations of hourly rainfall. In this study, the spatiotemporal variations of hourly rainfall in the Three Gorges region (TGR) of China are investigated with gauge and newly available radar data. The spatial pattern of hourly rainfall has been examined by a number of statistics, and they all show that the rainfall variations are time-scale and location dependent. In general, the northern TGR receives more-intense and longer-duration rainfall than do other parts of the TGR, and short-duration storms could occur in most of the TGR. For temporal variations, the summer diurnal cycle shifts from a morning peak in the west to a late-afternoon peak in the east while a mixed pattern of two peaks exists in the middle. In statistical terms, empirical model–based estimation indicates that the correlation scale of hourly rainfall is about 40 km. Further investigation shows that the correlation distance varies with season, from 30 km in the warm season to 60 km in the cold season. In addition, summer rainstorms extracted from radar rainfall data are characterized by short duration (6–8 h) and highly localized patterns (5–17 and 13–36 km in the minor and major directions, respectively). Overall, this research provides quantitative information about the rainfall regime in the TGR and shows that the combination of gauge and radar data is useful for characterizing the spatiotemporal pattern of storm rainfall over complex terrain.

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Zongjian Ke, Peiqun Zhang, Wenjie Dong, and Laurent Li

Abstract

Seasonal climate prediction, in general, can achieve excellent results with a multimodel system. A relevant calibration of individual models and an optimal combination of individual models are the key elements leading to this success. However, this commonly used approach appears to be insufficient to remove the intermodel systematic errors (IMSE), which represent similar error properties in individual models after their calibration. A new postprocessing method is proposed to correct the IMSE and to increase the prediction skill. The first step consists of carrying out a diagnosis on the calibrated errors before constructing the multimodel ensemble. In contrast to previous studies, the calibrated errors here are treated directly as the investigation target, and temporal correlation coefficients between the calibrated errors and other meteorological variables are calculated. In the second stage, mathematical and statistical tools are applied in an effort to forecast the IMSE in individual models. Then, the IMSE are removed from the calibrated results and the new corrected data are used to construct the multimodel ensemble. The hindcast of the European Union–funded Development of a European Multimodel Ensemble System for Seasonal-to-Interannual Prediction (DEMETER) multimodel system is used to test the method. The simulated Southern Oscillation index is used to diagnose and to correct the calibrated errors of the simulated precipitation. The prediction qualities of the corrected data are assessed and compared with those of the uncorrected dataset. The results show that it is feasible to improve seasonal precipitation prediction by forecasting and correcting the IMSE. This improvement is visible not only for the individual models, but also for the multimodel ensemble.

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Wei Zhang, Bing Fu, Melinda S. Peng, and Tim Li

Abstract

This study investigates the classification of developing and nondeveloping tropical disturbances in the western North Pacific (WNP) through the C4.5 algorithm. A decision tree is built based on this algorithm and can be used as a tool to predict future tropical cyclone (TC) genesis events. The results show that the maximum 800-hPa relative vorticity, SST, precipitation rate, divergence averaged between 1000- and 500-hPa levels, and 300-hPa air temperature anomaly are the five most important variables for separating the developing and nondeveloping tropical disturbances. This algorithm also unravels the thresholds of the five variables (i.e., 4.2 × 10−5 s−1 for maximum 800-hPa relative vorticity, 28.2°C for SST, 0.1 mm h−1 for precipitation rate, −0.7 × 10−6 s−1 for vertically averaged convergence, and 0.5°C for 300-hPa air temperature anomaly). Six rules are derived from the decision tree. The classification accuracy of this decision tree is 81.7% for the 2004–10 cases. The hindcast accuracy for the 2011–13 dataset is 84.6%.

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Liang Wang, Dan Li, Ning Zhang, Jianning Sun, and Weidong Guo

Abstract

Urban heat islands (UHIs) are caused by a multitude of changes induced by urbanization. However, the relative importance of biophysical and atmospheric factors in controlling the UHI intensity remains elusive. In this study, we quantify the magnitude of surface UHIs (SUHIs), or surface urban cool islands (SUCIs), and elucidate their biophysical and atmospheric drivers on the basis of observational data collected from one urban site and two rural grassland sites in and near the city of Nanjing, China. Results show that during the daytime a strong SUCI effect is observed when the short grassland site is used as the reference site whereas a moderate SUHI effect is observed when the tall grassland is used as the reference site. We find that the former is mostly caused by the lower aerodynamic resistance for convective heat transfer at the urban site and the latter is primarily caused by the higher surface resistance for evapotranspiration at the urban site. At night, SUHIs are observed when either the short or the tall grassland site is used as the reference site and are predominantly caused by the stronger release of heat storage at the urban site. In general, the magnitude of SUHI is much weaker, and even becomes SUCI during daytime, with the short grassland site being the reference site because of its larger aerodynamic resistance. The study highlights that the magnitude of SUHIs and SUCIs is mostly controlled by urban–rural differences of biophysical factors, with urban–rural differences of atmospheric conditions playing a minor role.

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Xiuzhong Li, Yijun He, Biao Zhang, and Chenqing Fan

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In this study, a rotating frequency-modulated continuous wave (FMCW) radar is installed on an aircraft to retrieve the sea wave spectra. Because the aircraft attitude angles produce the incorrect antenna gain used in the radar equation, the incorrect normalized radar cross section (NRCS) of the sea surface will be acquired. To eliminate the effect of the angles, a three-dimensional matrix of the radar antenna gain is constructed by means of coordinate transformation and interpolation, based on a large set of configurations of the aircraft attitude angles (roll, pitch, etc.). With the application of the matrix, the NRCS of the sea surface is corrected and the calculating time is reduced. Then the sea surface mean square slope (MSS) is obtained from the echoes of the airborne wave spectrometer. Considering a weak periodicity of MSS due to low sea state, four images are presented to show the variation of the MSS after aircraft attitude angle correction. The results indicate that the accurate incidence angle of the antenna beam center is critical for retrieving the sea surface MSS, and that the magnitude of the MSS from three cycles of radar echoes can be changed by as much as 40% within 5° of the attitude angles. Furthermore, the MSS becomes more periodic and regular after correction.

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Guijun Han, Xinrong Wu, Shaoqing Zhang, Zhengyu Liu, and Wei Li

Abstract

Coupled data assimilation uses a coupled model consisting of multiple time-scale media to extract information from observations that are available in one or more media. Because of the instantaneous exchanges of information among the coupled media, coupled data assimilation is expected to produce self-consistent and physically balanced coupled state estimates and optimal initialization for coupled model predictions. It is also expected that applying coupling error covariance between two media into observational adjustments in these media can provide direct observational impacts crossing the media and thereby improve the assimilation quality. However, because of the different time scales of variability in different media, accurately evaluating the error covariance between two variables residing in different media is usually very difficult. Using an ensemble filter together with a simple coupled model consisting of a Lorenz atmosphere and a pycnocline ocean model, which characterizes the interaction of multiple time-scale media in the climate system, the impact of the accuracy of coupling error covariance on the quality of coupled data assimilation is studied. Results show that it requires a large ensemble size to improve the assimilation quality by applying coupling error covariance in an ensemble coupled data assimilation system, and the poorly estimated coupling error covariance may otherwise degrade the assimilation quality. It is also found that a fast-varying medium has more difficulty being improved using observations in slow-varying media by applying coupling error covariance because the linear regression from the observational increment in slow-varying media has difficulty representing the high-frequency information of the fast-varying medium.

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Li Zhang, Bolan Gan, Lixin Wu, Wenju Cai, and Hao Ma

Abstract

Two-way coupling between sea surface temperature (SST) variations in the midlatitude southern oceans and changes of synoptic-scale (2–8 day) eddy activities in the lower and upper troposphere throughout the year is investigated based on lagged maximum covariance analysis using reanalysis datasets from 1951 to 2000. Results show a strong seasonal dependence of the coupling, as characterized by the most prominent one in austral midsummer (January). On one hand, SST variations in austral late spring (primarily October) are likely to influence storm tracks in the following January. That is, significant warm SST anomalies in the western midlatitude areas of South Atlantic and south Indian Ocean could result in the systematic strengthening of the low-level and upper-level eddy activities, which is presumably attributed to the coherent intensification of the SST front and the lower-tropospheric baroclinicity. Particularly, interannual variability (a spectral peak at 4 yr) of SST in the western midlatitude South Atlantic in October could play a predominant role in driving the corresponding variability of the Southern Hemisphere storm tracks three months later. The timing of the discernible response of storm tracks is also discussed based on the preliminary results of sensitivity experiments. On the other hand, the strengthened eddy activities in January continue to induce the dipolelike patterns of SST anomalies in the midlatitude southern oceans. Those SST response patterns are, to the first order, determined by changes of the net surface heat flux. The anomalous Ekman advections in part driven by the storm-track changes also contribute to SST anomalies in the southern subtropical South Atlantic and the western midlatitude South Pacific.

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