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There is evidence of an increased frequency of rapid intensification events of tropical cyclones (TCs) in global offshore regions. This will not only result in increased peak wind speeds but may lead to more intense heavy precipitation events, leading to flooding in coastal regions. Therefore, high impacts are expected for urban agglomerations in coastal regions such as the densely populated Pearl River Delta (PRD) in China. Regional climate models (RCMs) such as the Weather Research and Forecasting (WRF) model are state-of-the-art tools commonly applied to predict TCs. However, typhoon simulations are connected with high uncertainties due to the high number of parameterization schemes of relevant physical processes (including possible interactions between the parameterization schemes) such as cumulus (CU) and microphysics (MP), as well as other crucial model settings such as domain setup, initial times, and spectral nudging. Since previous studies mostly focus on either individual typhoon cases or individual parameterization schemes, in this study a more comprehensive analysis is provided by considering four different typhoons of different intensity categories with landfall near the PRD, i.e. Typhoon Neoguri (2008), Typhoon Hagupit (2008), Typhoon Hato (2017), and Typhoon Usagi (2013), as well as two different schemes for CU and MP, respectively. Moreover, the impact of the model initialization and the driving data is studied by using three different initial times and two spectral nudging settings. Compared with the best-track reference data, the results show that the four typhoons show some consistency. For track bias, nudging only horizontal wind has a positive effect on reducing the track distance bias; for intensity, compared with a model explicitly resolving cumulus convection, i.e. without cumulus parameterization (CuOFF; nudging potential temperature and horizontal wind; late initial time), using the Kain–Fritsch scheme (KF; nudging only horizontal wind; early initial time) configuration shows relatively lower minimum sea level pressures and higher maximum wind speeds, which means stronger typhoon intensity. Intensity shows less sensitivity to two MP schemes compared with the CuOFF, nudging, and initial time settings. Furthermore, we found that compared with the CuOFF, using the KF scheme shows a relatively larger latent heat flux and higher equivalent potential temperature, providing more energy to typhoon development and inducing stronger TCs. This study could be used as a reference to configure WRF with the model's different combinations of schemes for historical and future TC simulations and also contributes to a better understanding of the performance of principal TC structures. [ABSTRACT FROM AUTHOR]

The regional drought predictability is strongly influenced by teleconnections factors. Among them, El Niño-Southern Oscillation (ENSO) is important to drought occurrence. However, it is still not fully understood how the probability of regional droughts corresponding to different ENSO regimes varies with time lags. In this study, the event-based coincidence analysis (ECA) is employed to statistically derive the relationships regarding time information and magnitude between conventional ENSO (c-ENSO)/ENSO Modoki (ENSO_M) episodes and drought events. The standardized precipitation evapotranspiration index (SPEI) based on station-records is used to determine meteorological droughts. Our study focuses on the largest freshwater lake of China, Poyang Lake basin (PLB), as severe droughts have occurred there frequently. Results indicate that the summer-autumn continuous drought dominates the severe droughts, with a frequent onset in August/September, and a cessation in October/November. The likelihood of drought occurrence is highest during cool phases of c-ENSO (CEN), followed by warm ENSO_M (WEM), warm c-ENSO (WEN), and cool ENSO_M (CEM). The influence of WEN/WEM on droughts is statistically significant mostly for a time lag of 10 months, whereas CEN/CEM shows no lagged influence. Furthermore, the variability of the 850 hPa wind anomalies during different ENSO episodes at various time lags is corresponding to the lagged influence of ENSO on droughts. The development and persistence of droughts is resulting from strengthened northeasterly wind anomalies over the PLB. Our findings demonstrate that the ENSO anomalies are early warning signals of droughts and hence can be beneficial for increasing the drought predictivity • A novel statistical framework to quantify the probability of droughts responding to ENSO with varied time lags is developed. • The influence of WEN/WEM on the droughts in the PLB is statistically significant mostly for a time lag of 10 months. • The strengthened northeasterly wind anomalies over the PLB likely results in the development of ENSO-induced droughts. [ABSTRACT FROM AUTHOR]

Intense precipitation events frequently occur in the Hanjiang River Basin (HRB) in China, causing major economic losses and affecting human security. Accurate precipitation simulations are sensitive to the choice of physical schemes in numerical weather prediction models. Therefore, in this study the performance of the different combinations of physical schemes in the Weather Research and Forecasting (WRF) model was investigated for the HRB. Five intense precipitation events in summer during the period 2008–2011 were selected. For simulating each intense precipitation event, an 18-member multi-physics ensemble was designed by using three cumulus (CU) schemes and four microphysics (MP) schemes. The temporal dynamics and spatial patterns of the simulated precipitation were evaluated systematically by a comparison to the China precipitation analysis reference data. A quantitative analysis using the Euclidean distance metric to synthesize the evaluation results was performed. The performed uncertainty analysis suggests that the skill of precipitation simulation is more sensitive to the choice of the CU scheme and less sensitive to the choice of the MP scheme. Our analysis shows that a suitable WRF physical configuration consists of Kain-Fritsch and WRF Single-Moment 6-class, which reaches a performance similar to that of the ensemble mean method. To our knowledge, this multi-physics ensemble study is the first effort to comprehensively evaluate the applicability of the WRF model to intense precipitation simulations over the HRB. Therefore, this study potentially contributes to the improvement of climate simulations for central China. • Cumulus schemes have primary impact on intense precipitation simulation while microphysics schemes have secondary impact. • A suitable WRF physical configuration is the combinations of the KF and WSM6 schemes. • This study potentially contributes to the improvement of climate simulations for central China. [ABSTRACT FROM AUTHOR]

Lateral terrestrial water flow contributes to the Earth system dynamics by redistributing the moisture fluxes at the land surface. Fully coupled atmospheric-hydrological modeling, which considers the lateral hydrological processes, is increasingly used to investigate the land-atmosphere interactions. Planetary boundary layer (PBL) parameterizations which depict vertical energy and mass exchanges from the surface to lower atmosphere are pivotal to atmosphere modeling applications. This study aims at quantitatively evaluating to what extend the PBL scheme influences land-atmosphere interactions and how it impacts the regional climate modeling by coupled atmospheric-hydrological modeling approach. In this case study, the hydrologically enhanced version of the Weather Research and Forecasting modeling WRF-Hydro is used as fully coupled atmospheric-hydrological modeling experiment, and the standard WRF modeling is used as the control experiment. The regional simulation is applied to the Heihe river basin, an endorheic basin located in northwest China. The atmospheric modeling is configured at convection permitting scale 3 km, and the lateral terrestrial water processes are resolved at 300 m fine hydrological sub-grid. An ensemble of WRF/WRF-Hydro simulations is produced by varying the PBL scheme (YSU, MYJ, ACM2) for three continuous years from 2008-2010. The sensitivity of land-atmosphere interactions is evaluated with a regional precipitation recycling analysis and a three-dimensional atmospheric moisture tracing method (E-tagging). The interannual variability of the regional water budgets and land-atmosphere interactions are quantified with the model ensemble. We find a low precipitation recycling and a clearly positive soil moisture-precipitation feedback triggered by lateral terrestrial water flow in the study area. Lateral terrestrial water flow increases the local precipitation recycling irrespective of the modeling variability obtained with the different PBL parameterizations. The robust impact of lateral terrestrial water flow on local precipitation recycling indicates that the fully coupled modeling should be applied for climate projections. [ABSTRACT FROM AUTHOR]