Search

Dynamical prediction of monsoon rainfall has been an important topic and a long-standing issue in both research and operational community. This paper provides a comprehensive evaluation of the subseasonal-to-seasonal (S2S) prediction skill of the East Asian summer monsoon (EASM) rainfall using the hindcast record from the Beijing Climate Center Climate System Model, BCC CSM1.1m, during the period 1983–2019. The model exhibits reasonable skills for predicting the EASM rainfall at all lead times with the skill dropping dramatically from the shortest lead time of about 2 weeks (LM0) to 1-month lead (LM1), and then fluctuating remarkably throughout 2-month to 12-month lead times. Over the EASM domain, the rapid decline of the S2S rainfall prediction skill from LM0 to LM1 is mainly caused by the inferior skills over Central China in July and over Northeast China in August. Composite analysis based on hindcast records suggest that these inferior skills are directly tied to the model's difficulties in capturing above-normal precipitation over eastern Central China and Northeast China in the respective months, which are further shown to be associated with anomalous weakening and meridional movement of the Northwestern Pacific subtropical high and the activity of large-scale teleconnection pattern hard to be predicted over northeastern Asia in summer, respectively. These findings inform the intrinsic limits of the S2S predictability of the EASM rainfall by a dynamical model, and strongly suggest that the level of confidence placed upon S2S forecasts should be stratified by large-scale circulation anomalies known to significantly affect the prediction skill, e.g., the subtropical high and high-latitude teleconnection patterns for summer monsoon rainfall prediction in this region. [ABSTRACT FROM AUTHOR]

Thunderstorms are usually accompanied by heavy precipitation and other disasters. Therefore, it is very important to study the thermodynamic and dynamic mechanisms that control the occurrence and development of storms. However, the relatively coarse resolution of the reanalysis may limit the evaluation and application of its derived convective parameters at regional and local scales, especially in high mountains. Given that the effect of grid averaging on ERA5 can be well-reflected in the monthly mean, the paper proposes a methodological framework to achieve the statistical downscaling of convective parameters (SDCP). After the convection-related variables are decomposed, we introduce a multi-scale geographically weighted regression (MGWR) model and take the Normalized Difference Vegetation Index (NDVI) and the Digital Elevation Model (DEM) as explanatory variables to improve the spatial resolution of monthly-scale convective parameters. The convective parameters chosen for the downscaling experiments are closely related to thunderstorm occurrence, involving instability, moisture, and wind shear. ERA5 and SDCP datasets' quality is evaluated based on measurements available from 11 radiosonde stations over 10 years. We also explore the climatology of thunderstorm environments and the corresponding trends. The results show that the accuracy of the SDCP data obtains additional added value in complex-terrain areas. Compared with ERA5, the downscaled results have a finer spatial structure. A strong but spatially and scale-varying relationship exists between the monthly mean convective parameter and the resampled NDVI and DEM. Considering the very high predictive ability of the MGWR model, the performance of the SDCP algorithm mainly depends on the accuracy of the ERA5 data. Our study demonstrates the possibility of high spatial resolution land surface features observed by remote sensing satellites in improving the spatial resolution of thermodynamic parameters. [ABSTRACT FROM AUTHOR]

Seasonal precipitation and temperature predictions with global climate models that are developed based on the ocean–atmosphere interactions, contribute to the water resources management and hazard mitigation. To date, multi-model ensemble seasonal climate prediction systems, such as North American multi-model ensemble (NMME), are an effective way to provide useful forecast information a few months ahead especially over regions with strong ocean–atmosphere coupling. Previous studies have evaluated the skill of NMME hindcasts worldwide, however, whether the NMME real-time forecasts perform as well as the hindcasts and how the decadal variability in ocean-atmospheric teleconnections affect the prediction skill remain unclear. In this paper, based on precipitation and temperature datasets from nine models of NMME, the evaluation of forecast skills during hindcast (1982–2010) and real-time forecast (2011–2020) periods is carried out in the Yangtze River basin over China. Results show that although selecting an appropriate time frame for the calculation of climatology can reduce errors of real-time prediction, but the real-time prediction skills are lower than hindcast skills in the Yangtze River basin, with anomaly correlation decreased by 14–51% (38–75%) and error increased by 30–31% (51–55%) for seasonal precipitation (temperature) predictions up to the sixth lead-season, and the skill decrease is larger at longer leads. The failure in representing the decadal variations of ocean-atmospheric teleconnection (especially the association with Indian Ocean surface temperature) during the real-time forecast period can partly explain the decline in the prediction skills. Our findings suggest that a better grasp of decadal variability is needed to improve the real-time climate predictions. [ABSTRACT FROM AUTHOR]

Changing climate has altered the trends and variability of precipitation and temperature globally and thereby increasing the risk of natural and social disasters, especially in coastal climatic transitional zones such as the Huaihe river basin (HRB). This paper applies the Empirical Quantile Mapping (EQM) method for bias correction and systematically evaluates the performance of the 30 Global climate models (GCMs) of the Coupled Model Intercomparison Project phase 6 (CMIP6) in simulating precipitation and temperature over the Huaihe river basin (HRB) for 1979–2014. A suitable multi-model ensemble subset (BMME) is selected based on the Euclidean Distance (ED) synthetic metric. Results show that in comparison to the baseline period 1995–2014, precipitation (temperature) over HRB is projected to increase at the rate of around 15 mm/decade (0.1 °C/decade), 16 mm/decade (0.3 °C/decade), 20 mm/decade (0.5 °C/decade), and 15 mm/decade (0.6 °C/decade) for the period 2015–2100, under Shared Socioeconomic Pathways SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5, respectively. In the long-term (2081–2100), the annual precipitation is projected to increase by 32%, 27%, 35%, and 26%, under the four scenarios, respectively. The temperature is projected to remain stable or slightly decrease under SSP1-2.6 (2 °C) and SSP2-4.5 (3 °C), while will keep rising and increasing by 6 °C under SSP5-8.5 and by 4 °C under SSP3-7.0 by 2100. The isotherm and isohyet are projected to shift northwest from southeastern coastal China to inland in the future, which is likely associated with the northwestward shift of the western Pacific anticyclone in summer. [ABSTRACT FROM AUTHOR]

In early summer 2020, eastern China was hit by record-breaking Meiyu rainfall. The anomalous western Pacific subtropical high (WPSH) played a crucial role in this event. This paper exposes the abnormal features of the WPSH and its related vertical circulations and reveals its dynamical causes in this period, from the perspective of the three-pattern decomposition of global atmospheric circulation (3P-DGAC). Analyzing the anomalous spatial patterns of the three stream functions R, H, and W of the horizontal, meridional, and zonal circulations defined by the 3P-DGAC, we discovered that the WPSH described by R at 850 hPa was intensified and westward from the horizontal circulation. For the vertical circulations, the local meridional circulation along East Asia expressed by H manifested an abnormal downdraft at 20° N, which was beneficial to strengthening the WPSH. The zonal circulation in the tropical Pacific represented by W was anomalously far to the west, which was related to the westward extension of the WPSH. Then, to uncover the causes of the anomalous WPSH from the dynamics, we used the vorticity equation based on the 3P-DGAC and found that the negative relative vorticity advection anomaly over the western Pacific played a key role in this event. Due to the positive sea surface temperature (SST) anomaly and enhanced convection over the Maritime Continent (MC), local vertical circulations at low latitudes were significantly activated. The intense local meridional circulation along East Asia carried the relative vorticity from the MC to the western Pacific and strengthened the WPSH. The ascending branch of the zonal circulation in the tropical Pacific moved westward, which may favor the westward extension of the WPSH. This study represents a promising step in revealing the three-dimensional (3D) structure and internal dynamics of anomalous WPSH. [ABSTRACT FROM AUTHOR]

This paper investigates the causes for the interdecadal change in the relationships between early and late summer precipitation over South China (SC). It is found that the correlations of the precipitation over SC between June and August shift from weak positive in 1979–1995 to significantly negative in 1996–2019. Further analysis demonstrates that the distinct evolution of sea surface temperature (SST) pattern between the two periods accounts for the interdecadal variations of their relationships. Although the warming of the tropical western Indian Ocean (WIO) in June favors increasing precipitation over the SC via enhancing the Northwest Pacific Subtropical High (NWPSH) during the whole period, the associated SST anomalies in August are rather different between the two periods. Specifically, the WIO warming in June corresponds to slightly positive anomalies over the tropical central-eastern Pacific in August during the 1979–1995, which has weak impact on the NWPSH and results in a weak precipitation correlation between June and August. However, the WIO warming in June corresponds to La Niña's rapid development in August during the 1996–2019, which favors the enhancement of the NWPSH via increasing the regional Hadley circulation. Due to the climatologically northward movement of NWPSH from June to August, the enhanced NWPSH in August acts to decrease the precipitation over SC, causing a significantly negative correlation between precipitation in June and August. Overall, the distinct evolution of tropical SST pattern is the key factor inducing the change of the relationships between June and August precipitation in the two periods. [ABSTRACT FROM AUTHOR]

Mesoscale convective systems (MCSs) are important warm-season precipitation systems in eastern China. However, our knowledge of their climatology and capability in their simulation is still insufficient. This paper examines their characteristics over the 2008–2017 warm seasons using convection-permitting climate simulations (CPCSs) with a 3-km grid spacing that explicitly resolves MCSs, as well as a high-resolution gauge-satellite merged precipitation product. An object-based tracking algorithm is applied to identify MCSs. Results indicate that the MCS genesis and occurrence are closely related to the progression of the East Asian monsoon and are modulated by the underlying topography. On average, about 243 MCSs are observed each season and contribute 19% and 47% to total and extreme warm-season precipitation. The climatological attributes and variabilities are reasonably reproduced in the CPCS. The major model deficiencies are excessive small MCS occurrence and overmuch MCS rainfall, consequently overestimating the precipitation contributions, whereas observational uncertainties may play a role too. Both the observed and simulated MCS precipitation feature a nocturnal or morning maximum and an eastward delayed diurnal peak east of the Tibetan Plateau, in contrast to the dominant afternoon peak of non-MCS precipitation. The favorable comparison with observations demonstrates the capability of CPCSs in simulating MCSs in the Asian monsoon climate, and its usefulness in projecting the future changes of MCSs under global warming. The finding that non-MCS precipitation is responsible for the high biased afternoon precipitation provides helpful guidance for further model improvement. [ABSTRACT FROM AUTHOR]