Dynamical downscaling is an important approach to obtaining fine-scale weather and climate information. However, dynamical downscaling simulations are often degraded by biases in the large-scale forcing itself. We constructed a bias-corrected global dataset based on 18 models from the Coupled Model Intercomparison Project Phase 6 (CMIP6) and the European Centre for Medium-Range Weather Forecasts Reanalysis 5 (ERA5) dataset. The bias-corrected data have an ERA5-based mean climate and interannual variance, but with a non-linear trend from the ensemble mean of the 18 CMIP6 models. The dataset spans the historical time period 1979–2014 and future scenarios (SSP245 and SSP585) for 2015–2100 with a horizontal grid spacing of (1.25° × 1.25°) at six-hourly intervals. Our evaluation suggests that the bias-corrected data are of better quality than the individual CMIP6 models in terms of the climatological mean, interannual variance and extreme events. This dataset will be useful for dynamical downscaling projections of the Earth’s future climate, atmospheric environment, hydrology, agriculture, wind power, etc.

We have investigated changes of western North Pacific land-falling tropical cyclone (TC) characteristics due to warmer climate conditions, using the pseudo-global-warming (PGW) technique. Historical simulations of three intense TCs making landfall in Pearl River Delta (PRD) were first conducted using the Weather Research and Forecasting (WRF) model. The same cases were then re-simulated by superimposing near- (2015–2039) and far- (2075–2099) future temperature and humidity changes onto the background climate; these changes were derived from the Coupled Model Intercomparison Project phase 5 (CMIP5) multi-model projections according to the Representative Concentration Pathway (RCP) 8.5 scenario. Peak intensities of TCs (maximum surface wind in their lifetimes) are expected to increase by ~ (3) 10% in the (near) far future. Further experiments indicate that surface warming alone acts to intensify TCs by enhancing sea surface heat flux, while warmer atmosphere acts in the opposite way by increasing the stability. In the far future, associated storm surges are also estimated to increase by about 8.5%, computed by the Sea, Lake, and Overland Surges from Hurricanes (SLOSH) model. Combined with sea level rise and estimated land vertical displacement, TC-induced storm tide affecting PRD will increase by ~1 m in the future 2075–2099 period.

Future projections of the eastern-Pacific (EP) and central-Pacific (CP) types of El Niño in the twenty-first century, as well as their associated tropical circulation and precipitation variability, are investigated using historical runs and representative concentration pathway 8.5 (RCP8.5) simulations from 31 coupled models in phase 5 of the Coupled Model Intercomparison Project (CMIP5). As inferred from CMIP5 models that best capture both El Niño flavors, EP El Niño sea surface temperature (SST) variability will become weaker in the future climate, while no robust change of CP El Niño SST is found. Models also reach no consensus on the future change of relative frequency from CP to EP El Niño. However, there are robust changes in the tropical overturning circulation and precipitation associated with both types of El Niño. Under a warmer climate, magnitudes of precipitation anomalies during EP El Niño are projected to increase, presenting significant enhancement of the dry (wet) signal over the western (central–eastern) Pacific. This is consistent with an accelerated hydrological cycle in the deep tropics; hence, a “wet get wetter” picture appears under global warming, accompanied by a weakened anomalous Walker circulation. For CP El Niño, drier-than-normal conditions will be intensified over the tropical central–eastern Pacific in the future climate, with stronger anomalous sinking related to the strengthened North Pacific local Hadley cell. These results suggest that, besides the enhanced basic-state hydrological cycle over the tropics, other elements, such as the anomalous overturning circulation, might also play a role in determining the ENSO precipitation response to a warmer background climate.

Surface ozone (O₃) is an important air pollutant and greenhouse gas. Land use and land cover is one of the critical factors influencing ozone, in addition to anthropogenic emissions and climate. Land use and land cover change (LULCC) can on the one hand affect ozone “biogeochemically”, i.e., via dry deposition and biogenic emissions of volatile organic compounds (VOCs). LULCC can on the other hand alter regional- to large-scale climate through modifying albedo and evapotranspiration, which can lead to changes in surface temperature, hydrometeorology, and atmospheric circulation that can ultimately impact ozone “biogeophysically”. Such biogeophysical effects of LULCC on ozone are largely understudied. This study investigates the individual and combined biogeophysical and biogeochemical effects of LULCC on ozone and explicitly examines the critical pathway for how LULCC impacts ozone pollution. A global coupled atmosphere–chemistry–land model is driven by projected LULCC from the present day (2000) to the future (2050) under RCP4.5 and RCP8.5 scenarios, focusing on the boreal summer. Results reveal that when considering biogeochemical effects only, surface ozone is predicted to have slight changes by up to 2 ppbv maximum in some areas due to LULCC. It is primarily driven by changes in isoprene emission and dry deposition counteracting each other in shaping ozone. In contrast, when considering the combined effect of LULCC, ozone is more substantially altered by up to 5 ppbv over several regions in North America and Europe under RCP4.5, reflecting the importance of biogeophysical effects on ozone changes. In boreal and temperate mixed forests with intensive reforestation, enhanced net radiation and sensible heat induce a cascade of hydrometeorological feedbacks that generate warmer and drier conditions favorable for higher ozone levels. In contrast, reforestation in subtropical broadleaf forests has minimal impacts on boundary-layer meteorology and ozone air quality. Furthermore, significant ozone changes are also found in regions with only modest LULCC, which can only be explained by “remote” biogeophysical effects. A likely mechanism is that reforestation induces a circulation response, leading to reduced moisture transport and ultimately warmer and drier conditions in the surrounding regions with limited LULCC. We conclude that the biogeophysical effects of LULCC are important pathways through which LULCC influences ozone air quality both locally and in remote regions even without significant LULCC. Overlooking the effects of hydrometeorological changes on ozone air quality may cause underestimation of the impacts of LULCC on ozone pollution.

Performances of the Model for Prediction Across Scales-Atmosphere (MPAS-A) in predicting and the Weather Research and Forecasting (WRF) model in simulating western North Pacific (WNP) tropical cyclone (TC) tracks and intensities have been compared. Parallel simulations of the same historical storms that made landfall over southern China, namely, TCs Hope (1979), Gordon (1989), Koryn (1993), Imbudo (2003), Dujuan (2003), Molave (2009), Hato (2017) and Mangkhut (2018), were carried out using WRF and MPAS-A, with initial conditions (and, for WRF, lateral boundary conditions as well) taken from ERA-interim. For MPAS-A, the model was integrated using a standard 60-to-3-km variable-resolution global grid mesh and also on 160-to-2-km grids customized to cover the TC tracks with the highest resolution mesh. The WRF model was integrated using a 15-km/3-km nested domain. No TC bogus scheme was applied when initializing the MPAS-A and WRF simulations. It was found that while TC tracks were reasonably captured by the two models configured variously, the storm intensities were underestimated in general. Given MPAS-A runs were initial value predictions whereas WRF runs were dynamically downscaled from ERA-interim, the finding that MPAS-A has comparable (or slightly better) performance as (than) WRF is noteworthy. To further examine the sensitivity of the MPAS-A TC forecasts to the initial data, additional experiments were carried out for TCs Molave and Hope using ERA5 reanalysis as initial conditions. The ERA5 initialized runs showed significant (slight) improvement in intensity (track) evolution, suggesting that the underestimated TC intensity is likely related to inferior representation of storms in the ERA-interim initial fields. Furthermore, additional runs using another customized 60-to-2-km mesh showed a reasonable improvement in capturing the TC tracks, suggesting that the track forecast accuracy of MPAS-A in TC can be sensitive to the grid resolution in the coarsest part of the variable-resolution mesh used.