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Hua Song, Wuyin Lin, Yanluan Lin, Audrey B. Wolf, Roel Neggers, Leo J. Donner, Anthony D. Del Genio, and Yangang Liu

Abstract

This study evaluates the performances of seven single-column models (SCMs) by comparing simulated surface precipitation with observations at the Atmospheric Radiation Measurement Program Southern Great Plains (SGP) site from January 1999 to December 2001. Results show that although most SCMs can reproduce the observed precipitation reasonably well, there are significant and interesting differences in their details. In the cold season, the model–observation differences in the frequency and mean intensity of rain events tend to compensate each other for most SCMs. In the warm season, most SCMs produce more rain events in daytime than in nighttime, whereas the observations have more rain events in nighttime. The mean intensities of rain events in these SCMs are much stronger in daytime, but weaker in nighttime, than the observations. The higher frequency of rain events during warm-season daytime in most SCMs is related to the fact that most SCMs produce a spurious precipitation peak around the regime of weak vertical motions but rich in moisture content. The models also show distinct biases between nighttime and daytime in simulating significant rain events. In nighttime, all the SCMs have a lower frequency of moderate-to-strong rain events than the observations for both seasons. In daytime, most SCMs have a higher frequency of moderate-to-strong rain events than the observations, especially in the warm season. Further analysis reveals distinct meteorological backgrounds for large underestimation and overestimation events. The former occur in the strong ascending regimes with negative low-level horizontal heat and moisture advection, whereas the latter occur in the weak or moderate ascending regimes with positive low-level horizontal heat and moisture advection.

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Weiqing Han, Peter J. Webster, Jia-Lin Lin, W. T. Liu, Rong Fu, Dongliang Yuan, and Aixue Hu

Abstract

Satellite and in situ observations in the equatorial Atlantic Ocean during 2002–03 show dominant spectral peaks at 40–60 days and secondary peaks at 10–40 days in sea level and thermocline within the intraseasonal period band (10–80 days). A detailed investigation of the dynamics of the intraseasonal variations is carried out using an ocean general circulation model, namely, the Hybrid Coordinate Ocean Model (HYCOM). Two parallel experiments are performed in the tropical Atlantic Ocean basin for the period 2000–03: one is forced by daily scatterometer winds from the Quick Scatterometer (QuikSCAT) satellite together with other forcing fields, and the other is forced by the low-passed 80-day version of the above fields. To help in understanding the role played by the wind-driven equatorial waves, a linear continuously stratified ocean model is also used.

Within 3°S–3°N of the equatorial region, the strong 40–60-day sea surface height anomaly (SSHA) and thermocline variability result mainly from the first and second baroclinic modes equatorial Kelvin waves that are forced by intraseasonal zonal winds, with the second baroclinic mode playing a more important role. Sharp 40–50-day peaks of zonal and meridional winds appear in both the QuikSCAT and Pilot Research Moored Array in the Tropical Atlantic (PIRATA) data for the period 2002–03, and they are especially strong in 2002. Zonal wind anomaly in the central-western equatorial basin for the period 2000–06 is significantly correlated with SSHA across the equatorial basin, with simultaneous/lag correlation ranging from −0.62 to 0.74 above 95% significance. Away from the equator (3°–5°N), however, sea level and thermocline variations in the 40–60-day band are caused largely by tropical instability waves (TIWs).

On 10–40-day time scales and west of 10°W, the spectral power of sea level and thermocline appears to be dominated by TIWs within 5°S–5°N of the equatorial region. The wind-driven circulation, however, also provides a significant contribution. Interestingly, east of 10°W, SSHA and thermocline variations at 10–40-day periods result almost entirely from wind-driven equatorial waves. During the boreal spring of 2002 when TIWs are weak, Kelvin waves dominate the SSHA across the equatorial basin (2°S–2°N). The observed quasi-biweekly Yanai waves are excited mainly by the quasi-biweekly meridional winds, and they contribute significantly to the SSHA and thermocline variations in 1°–5°N and 1°–5°S regions.

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Hainan Gong, Lin Wang, Wen Zhou, Wen Chen, Renguang Wu, Lin Liu, Debashis Nath, and Marco Y.-T. Leung

Abstract

This study revisits the northern mode of East Asian winter monsoon (EAWM) variation and investigates its response to global warming based on the ERA dataset and outputs from phase 5 of the Coupled Model Intercomparison Project (CMIP5) models. Results show that the observed variation in East Asian surface air temperature (EAT) is tightly coupled with sea level pressure variation in the expanded Siberian high (SH) region during boreal winter. The first singular value decomposition (SVD) mode of the EAT and SH explains 95% of the squared covariance in observations from 1961 to 2005, which actually represents the northern mode of EAWM variation. Meanwhile, the first SVD mode of the EAT and SH is verified to be equivalent to the first empirical orthogonal function mode (EOF1) of the EAT and SH, respectively. Since the leading mode of the temperature variation is significantly influenced by radiative forcing in a rapidly warming climate, for reliable projection of long-term changes in the northern mode of the EAWM, we further employ the EOF1 mode of the SH to represent the northern mode of EAWM variation. The models can well reproduce this coupling between the EAT and SH in historical simulations. Meanwhile, a robust weakening of the northern mode of the EAWM is found in the RCP4.5 scenario, and with stronger warming in the RCP8.5 scenario, the weakening of the EAWM is more pronounced. It is found that the weakening of the northern mode of the EAWM can contribute 6.7% and 9.4% of the warming trend in northern East Asian temperature under the RCP4.5 and RCP8.5 scenarios, respectively.

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Zhangkang Shu, Jianyun Zhang, Junliang Jin, Lin Wang, Guoqing Wang, Jie Wang, Zhouliang Sun, Ji Liu, Yanli Liu, Ruimin He, Cuishan Liu, and Zhenxin Bao

Abstract

We evaluated 24-h control forecast products from The International Grand Global Ensemble center over the 10 first-class water resource regions of Mainland China in 2013–2018 from the perspective of precipitation processes (continuous) and precipitation events (discrete). We evaluated the forecasts from the China Meteorological Administration (CMA), the Centro de Previsão de Tempo e Estudos Climáticos (CPTEC), the Canadian Meteorological Centre (CMC), the European Centre for Medium-Range Weather Forecasts (ECMWF), the Japan Meteorological Agency (JMA), the Korea Meteorological Administration (KMA), the United Kingdom Met Office (UKMO), and the National Centers for Environmental Prediction (NCEP). We analyzed the differences among the numerical weather prediction (NWP) models in predicting various types of precipitation events and showed the spatial variations in the quantitative precipitation forecast efficiency of the NWP models over Mainland China. Meanwhile, we also combined four hydrological models to conduct meteo-hydrological runoff forecasting in three typical basins and used Bayesian model averaging (BMA) method to perform the ensemble forecast of different scenarios. Our results showed that the models generally underestimate and overestimate precipitation in northwestern China and southwestern China, respectively. This tendency became increasingly clear as the lead time rose. Each model has a high reliability for the forecast of no-rain and light rain in the next 10 days, whereas the NWP model only has high reliability on the next day for moderate and heavy rain events. In general, each model showed different capabilities of capturing various precipitation events. For example, the CMA and CMC forecasts had a better prediction performance for heavy rain but greater errors for other events. The CPTEC forecast performed well for long lead times for no-rain and light rain but had poor predictability for moderate and heavy rains. The KMA, UKMO, and NCEP forecasts performed better for no-rain and light rain. However, their forecasting ability was average for moderate and heavy rain. Although the JMA model performed better in terms of errors and accuracy, it seriously underestimated heavy rain events. The extreme rainstorm and flood forecast results of the coupled JMA model should be treated with caution. Overall, the ECMWF had the most robust performance. Discrepancies in the forecasting effects of various models on different precipitation events vary with the lead time and region. When coupled with hydrological models, NWP models not only control the accuracy of runoff prediction directly but also increase the difference among the prediction results of different hydrological models with the increase in NWP error significantly. Among all the single models, ECMWF, JMA, and NCEP have better effects than the other models. Moreover, the ensemble forecast based on BMA is more robust than the single model, which can improve the quality of runoff prediction in terms of accuracy and reliability.

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Si Gao, Wei Zhang, Jia Liu, I.-I. Lin, Long S. Chiu, and Kai Cao

Abstract

Tropical cyclone (TC) intensity prediction, especially in the warning time frame of 24–48 h and for the prediction of rapid intensification (RI), remains a major operational challenge. Sea surface temperature (SST) based empirical or theoretical maximum potential intensity (MPI) is the most important predictor in statistical intensity prediction schemes and rules derived by data mining techniques. Since the underlying SSTs during TCs usually cannot be observed well by satellites because of rain contamination and cannot be produced on a timely basis for operational statistical prediction, an ocean coupling potential intensity index (OC_PI), which is calculated based on pre-TC averaged ocean temperatures from the surface down to 100 m, is demonstrated to be important in building the decision tree for the classification of 24-h TC intensity change ΔV 24, that is, RI (ΔV 24 ≥ 25 kt, where 1 kt = 0.51 m s−1) and non-RI (ΔV 24 < 25 kt). Cross validations using 2000–10 data and independent verification using 2011 data are performed. The decision tree with the OC_PI shows a cross-validation accuracy of 83.5% and an independent verification accuracy of 89.6%, which outperforms the decision tree excluding the OC_PI with corresponding accuracies of 83.2% and 83.9%. Specifically for RI classification in independent verification, the former decision tree shows a much higher probability of detection and a lower false alarm ratio than the latter example. This study is of great significance for operational TC RI prediction as pre-TC OC_PI can skillfully reduce the overestimation of storm potential intensity by traditional SST-based MPI, especially for the non-RI TCs.

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Yun Lin, Yuan Wang, Bowen Pan, Jiaxi Hu, Yangang Liu, and Renyi Zhang

Abstract

A continental cloud complex, consisting of shallow cumuli, a deep convective cloud (DCC), and stratus, is simulated by a cloud-resolving Weather Research and Forecasting Model to investigate the aerosol microphysical effect (AME) and aerosol radiative effect (ARE) on the various cloud regimes and their transitions during the Department of Energy Routine Atmospheric Radiation Measurement Aerial Facility Clouds with Low Optical Water Depths Optical Radiative Observations (RACORO) campaign. Under an elevated aerosol loading with AME only, a reduced cloudiness for the shallow cumuli and stratus resulted from more droplet evaporation competing with suppressed precipitation, but an enhanced cloudiness for the DCC is attributed to more condensation. With the inclusion of ARE, the shallow cumuli are suppressed owing to the thermodynamic effects of light-absorbing aerosols. The responses of DCC and stratus to aerosols are monotonic with AME only but nonmonotonic with both AME and ARE. The DCC is invigorated because of favorable convection and moisture conditions at night induced by daytime ARE, via the so-called aerosol-enhanced conditional instability mechanism. The results reveal that the overall aerosol effects on the cloud complex are distinct from the individual cloud types, highlighting that the aerosol–cloud interactions for diverse cloud regimes and their transitions need to be evaluated to assess the regional and global climatic impacts.

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Fan Wu, Xiaopeng Cui, Da-Lin Zhang, Dongxia Liu, and Dong Zheng

Abstract

In this study, the spatiotemporal characteristics of cloud-to-ground (CG) and intracloud (IC) lightning flashes observed by Surveillance et Alerte Foudre par Interférometrie Radioélectrique (SAFIR)-3000 over the Beijing metropolitan region (BMR) during 2005–07 were investigated. The results showed the presence of 299 lightning days with 241 688 flashes, most of which were IC lightning flashes. Only 19% of the total flashes were CG lightning flashes; 14% of these CG flashes were positive. Most lightning activity occurred during the summer months (June–August), with a major diurnal peak around 1900 Beijing standard time (BST) and a secondary peak around 2300 BST. Spatial variations in flash density and lightning days both exhibited an obvious southeastwardly increasing pattern, with higher flash densities or more lightning days occurring in the southeastern plains and lower values distributed on the northwestern mountains. The Z ratio (IC/CG lightning flashes) exhibited a similar spatial pattern, but the percentage of positive CG lightning flashes showed an almost opposite pattern. The results also showed significant topographic effects on the spatiotemporal variations in lightning activity. That is, flash counts on the northeastern and southwestern mountains peaked in the afternoon, whereas those on the southeastern plains peaked in the late night to early morning, which could be attributed to the propagation of thunderstorms from the mountains to the plains. The results showed that the SAFIR-3000 lightning data are more useful than CG lightning data alone for forecasting the development and propagation of thunderstorms over the BMR.

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Maochong Shi, Changsheng Chen, Qichun Xu, Huichan Lin, Guimei Liu, Hui Wang, Fang Wang, and Jinhui Yan

Abstract

An analysis of the water level and current data taken in Qiongzhou Strait in the South China Sea (SCS) over the last 37 years (1963 to 1999) was made to examine the characteristics of tidal waves and residual flow through the strait and their roles in the seasonal variation of the SCS circulation. The observations reveal that Qiongzhou Strait is an area where opposing tidal waves interact and a source of water transport to the Gulf of Beibu (Gulf of Tonkin), SCS. A year-round westward mean flow with a maximum speed of 10–40 cm s−1 is found in Qiongzhou Strait. This accounts for water transport of 0.2–0.4 Sv and 0.1–0.2 Sv into the Gulf of Beibu in winter–spring and summer–autumn, respectively. The outflow from Qiongzhou Strait may cause up to 44% of the gulf water to be refreshed each season, suggesting that it has a significant impact on the seasonal circulation in the Gulf of Beibu. This finding is in contrast to our current understanding that the seasonal circulation patterns in the South China Sea are primarily driven by seasonal winds. Several numerical experiments were conducted to examine the physical mechanisms responsible for the formation of the westward mean flow in Qiongzhou Strait. The model provides a reasonable simulation of semidiurnal and diurnal tidal waves in the strait and the predicted residual flow generally agrees with the observed mean flow. An analysis of the momentum equations indicates that the strong westward flow is driven mainly by tidal rectification over variable bottom topography. Both observations and modeling suggest that the coastal physical processes associated with tidal rectification and buoyancy input must be taken into account when the mass balance of the SCS circulation is investigated, especially for the regional circulation in the Gulf of Beibu.

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Ching-Sen Chen, Yi-Leng Chen, Che-Ling Liu, Pay-Liam Lin, and Wan-Chin Chen

Abstract

The seasonal variations of heavy rainfall days over Taiwan are analyzed using 6-yr (1997–2002) hourly rainfall data from about 360 rainfall stations, including high-spatial-resolution Automatic Rainfall and Meteorological Telemetry System stations and 25 conventional stations. The seasonal variations and spatial variations of nontyphoon and typhoon heavy rainfall occurrences (i.e., the number of rainfall stations with rainfall rate >15 mm h−1 and daily accumulation >50 mm) are also analyzed. From mid-May to early October, with abundant moisture, potential instability, and the presence of mountainous terrain, nontyphoon heavy rainfall days are frequent (>60%), but only a few stations recorded extremely heavy rainfall (>130 mm day−1) during the passage of synoptic disturbances or the drifting of mesoscale convective systems inland. During the mei-yu season, especially in early June, these events are more widespread than in other seasons. The orographic effects are important in determining the spatial distribution of heavy rainfall occurrences with a pronounced afternoon maximum, especially during the summer months under the southwesterly monsoon flow. After the summer–autumn transition, heavy rainfall days are most frequent over northeastern Taiwan under the northeasterly monsoon flow. Extremely heavy rainfall events (>130 mm day−1) are infrequent during the winter months because of stable atmospheric stratification with a low moisture content. Typhoon heavy rainfall events start in early May and become more frequent in late summer and early autumn. During the analysis period, heavy rainfall occurrences are widespread and dominated by extremely heavy rainfall events (>130 mm day−1) on the windward slopes of the storm circulations. The spatial distribution of typhoon heavy rainfall occurrences depends on the typhoon track with very little diurnal variation.

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Xuezhi Tan, Thian Yew Gan, Shu Chen, Daniel E. Horton, Xiaohong Chen, Bingjun Liu, and Kairong Lin

Abstract

Both large-scale atmospheric circulation and moisture content in the atmosphere govern regional precipitation. We partition recent changes in mean, heavy, and extreme precipitation for all seasons over Canada to changes in synoptic circulation patterns (dynamic changes) and in atmospheric moisture conditions (thermodynamic changes) using 500-hPa geopotential height and precipitation data over 1979–2014. Using the self-organizing map (SOM) cluster analysis, we identify statistically significant trends in occurrences of certain synoptic circulation patterns over the Canadian landmass, which have dynamically contributed to observed changes in precipitation totals and occurrence of heavy and extreme precipitation events over Canada. Occurrences of circulation patterns such as westerlies and ridges over western North America and the North Pacific have considerably affected regional precipitation over Canada. Precipitation intensity and occurrences of precipitation extremes associated with each SOM circulation pattern also showed statistically significant trends resulting from thermodynamic changes in the atmospheric moisture supply for precipitation events. A partition analysis based on the thermodynamic–dynamic partition method indicates that most (~90%) changes in mean and extreme precipitation over Canada resulted from changes in precipitation regimes occurring under each synoptic circulation pattern (thermodynamic changes). Other regional precipitation changes resulted from changes in occurrences of synoptic circulation patterns (dynamic changes). Because of the high spatial variability of precipitation response to changes in thermodynamic and dynamic conditions, dynamic contributions could offset thermodynamic contributions to precipitation changes over some regions if thermodynamic and dynamic contributions are in opposition to each other (negative or positive), which would result in minimal changes in precipitation intensity and occurrences of heavy and extreme precipitation events.

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