In traditional practice, weather forecasts typically span up to two weeks, while climate forecasts begin at the seasonal timescale and extend further. Consequently, there exists a gap between weather and climate predictions in the subseasonal to seasonal (S2S) range. There is a growing demand within operational prediction and application communities for forecasts that bridge this gap, providing predictions between daily weather forecasts and seasonal climate outlooks. A global model with an unstructured grid mesh is utilized for this study to examine the forecast skill. Additionally, ensemble forecasting is taken into account, which involves running multiple simulations with slightly different initial conditions to capture uncertainties in the forecast. These ensemble forecasts are integrated for a period of 23 to 27 days, allowing for an extended prediction window beyond the typical forecast horizon. Results indicate that the model can give reasonable predictions on the development of a super Typhoon at lead times up to 10 days ahead of its peak intensity. Signal of a heat wave in southern China associated with the subsidence heating from TC outflow was also predicted reasonably well, despite variability among members existed due to disparity in the predicted TC tracks. Additionally, we carried out sensitivity tests on the use of radiation schemes on model cloud fraction. It is also found that the use of Xu and Randall generates more realistic cloud cover than Sundqvist, and resulting in greatly improving the evolution of synoptic scale weather systems over the western North Pacific consequentially.

Impacts of urban land cover and anthropogenic heat (AH) on extreme local rainfall over the coastal PRD megacity region during boreal summer are investigated by conducting numerical experiments using the Weather Research and Forecasting (WRF) model coupled with a single-layer urban canopy model (SLUCM). To examine the relative importance of land cover change vs the presence of AH, three numerical experiments corresponding to different levels of urbanization in the PRD area were designed: one with cropland covering the whole region, one with urban land cover but zero AH, and one with urban land cover and a strong diurnal maximum of 300Wm-2 of AH in the model simulations. Results show that the increase of accumulated rainfall in the urban area is much more sensitive to the intensity of AH than the mere change of surface properties. Urbanization with intense AH can enhance both the intensity and frequency of extreme rainfall, which can be attributed to higher surface temperature (of about 3.5 to 4oC), higher convective available potential energy (CAPE), and lower convective inhibition (CIN), thus creating an environment more conducive to strong convection over the urban areas. Moreover, enhanced rainfall is supported by moisture supply from the South China Sea and increased water vapor flux convergence over the PRD city area. The amount of moisture flux converging over the coastal megacity area was found to depend on the direction of prevailing background wind.

In the context of the human-induced warming climate, a greater amount of water vapor will be hold in the atmosphere, leading to more-intense precipitation extremes on global scale. However, there is no consensus yet on how much changes in those extremes are attributable to human influences on a regional basis. In this study, human-influenced variations in frequency and intensification of precipitation extremes over the South China (SC) Pearl River Delta (PRD) region are quantitatively assessed using the cloud-resolving Weather Research and Forecasting (WRF) model based on the reversed pseudo global warming (PGW) method. Forty extreme precipitation (95th percentile) events that occurred in different seasons for 1998-2018 over the PRD region are identified and dynamically downscaled by the WRF. The model was forced with present and counterfactual initial and boundary conditions, with the latter being derived by subtracting the CMIP5 7-model ensemble mean changes from ERA-Interim reanalysis. As inferred from these global models, the 1000-500 hPa tropospheric temperature has warmed by ~0.9 (0.8) ℃ over PRD (SC) due to human influences. Preliminary results show that such human-induced warming can lead to about 20% or more increase in the frequency of daily rainfall in PRD, with the greater enhancement in non-rainy season events. Human impacts also intensify the 95th percentile of PRD daily rainfall by around 12% (8%) in the non-rainy (rainy) season. This super-CC increase of non-rainy season cases probably implies the possible dynamic feedbacks, in addition to moisture-related thermodynamic effect in human-influenced extreme precipitation variations.

Capturing TC intensity change remains a great challenge for most state-of-the-art operational forecasting systems. Recent studies found the TC intensity forecasts are sensitive to three-dimensional ocean dynamics and air-sea interface processes beneath extreme winds. By performing a series of numerical simulations based on hierarchical Atmosphere–Wave–Ocean (AWO) coupling configurations, we showed how atmosphere-ocean and atmosphere-sea wave coupling can affect the intensity of super typhoon Mangkhut (2018). The AWO coupled model can simulate TC-related strong winds, oceanic cold wake, and wind waves with high fidelity. With atmosphere-ocean (AO) coupling implemented, the simulated maximum surface wind speed is reduced by 7 m/s compared to the atmosphere-only run, due to TC-induced oceanic cold wakes in the former experiment. In the fully coupled AWO simulations, the wind speed deficit can be completely compensated by the wave-air coupling effect. Further analyses showed that, in the AWO experiment, two mechanisms contribute to the improvement of TC intensity. First, in the high wind scenario (>28m/s), the surface drag coefficient reaches an asymptotic level, assisting extreme wind speed to be maintained within the eyewall. Second, the wind speed distribution is modulated and becomes broader; higher wind within the TC area helps to offset the negative effect due to leveling off of the heat exchange coefficient as wind speed increases. Overall, the simulated TC in the AWO run can extract 8-9% more total heat energy from the ocean to maintain its strength, compared to that from the AO experiment.

This study compares the impacts of global warming and intense anthropogenic heat (AH) on extreme hourly precipitation over the Pearl River Delta (PRD) megacity, located in coastal South China. Using the cloud-resolving Weather Research and Forecasting (WRF) model coupled with the single-layer urban canopy model (SLUCM), three downscaling experiments were carried out: the first (second) having zero (300W/m2 as diurnal maximum) AH values prescribed over PRD urban grids, under the same current climate conditions. The third experiment with AH=300W/m2 under future projected climate representative concentration pathway (RCP) 8.5. Boundary conditions were derived from PRD extreme rainfall episodes, identified from the Geophysical Fluid Dynamics Laboratory Earth System Model (GFDL-ESM2M) historical and RCP8.5 runs. Global warming forcing leads to ~20 to more than 100% increase in the probability of hourly precipitation with the magnitude of 20-100mm/hr over urban locations. The enhancements from intense AH forcing were similar. However, two types of forcings have distinct signatures in modulating the thermodynamic environment. Warming due to AH is limited to the lowest 1km above ground, while global warming warms up the whole troposphere. Intense AH results in enhanced convective available potential energy (CAPE) and reduced convective inhibition (CIN) within the megacity, allowing convection to be triggered more easily and with more vigor. On the other hand, global warming enhances both CAPE and CIN, over both urban and rural areas. Our results highlight the different physical mechanisms of AH and global warming in exacerbating extreme urban rainfall, despite their having similar impacts on the rainfall intensity.