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This study assesses the midsummer precipitation prediction over eastern China by the dynamic downscaling method. Based on the Climate Forecast System version 2 of the National Centers for Environmental Prediction and the Weather Research and Forecasting Model, the prediction performance of global and regional models on the July precipitation over eastern China is further analyzed by hindcast experiments from 1982 to 2010 and prediction experiments from 2011 to 2021. The results suggest that the regional model forced by the global model can noticeably improve the prediction skill for precipitation in eastern China, especially in the region from the South of North China to the Yangtze River Basin, referred as the northern China in this paper. In addition, we perform a diagnostic analysis of the reason for the improvement of the model prediction skill. The results indicate that the high resolution of the regional model and the refinement of physical process parameterizations contribute to improving the simulation ability for the East Asian atmospheric circulation pattern, heat flux, especially for the meridional teleconnection pattern in East Asia and the sensible heat flux in the northern China, thus further improving precipitation prediction. [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]

Numerous circulation indices have been applied in practical climate services focused on regional precipitation. It is beneficial to identify the most influential or decisive indices, but this is difficult with conventional correlation analyses because of the underlying nonlinear mechanisms for precipitation. This paper demonstrates a set of the most influential indices for July–August precipitation in North China, based on the recursive random forest (RRF) method. These decisive circulation indices include the Polar–Eurasia teleconnection, North African subtropical high ridge position, India–Burma trough, Antarctic Oscillation, Northern Hemisphere polar vortex central latitude, North Atlantic Oscillation, and western Pacific subtropical high northern boundary position. Some of these factors have been recognized as directly influential to the regional precipitation, for example, those of the northwestern Pacific subtropical high; however, some are not easily understood. Decision tree (DT) models using these indices were developed to facilitate composite analyses to explain the RRF results. Taking one of the most interesting DT rules as an example, when the North African subtropical high ridge position is sufficiently far south, an anomalous anticyclone occurs in the upstream and an anomalous cyclone in the downstream of North China. This is unfavorable for northward moisture transport in eastern China and hence causes less precipitation in North China than climatology. The present results are not only helpful for improving diagnostic models of regional precipitation, but also enlightening for exploring how global climate change could impact a region by modulating large-scale circulation patterns. [ABSTRACT FROM AUTHOR]

Wang, X.; Jiang, R.; Xie, J.; Zhao, Y.; Li, F., and Zhu, J., 2019. Multiscale variability of precipitation and their teleconnection with large-scale climate anomalies: A case study of Xi'an city, China. In: Guido-Aldana, P.A. and Mulahasan, S. (eds.), Advances in Water Resources and Exploration. Journal of Coastal Research, Special Issue No. 93, pp. 417–426. Coconut Creek (Florida), ISSN 0749-0208. The changes of precipitation affect the urban rainstorm waterlogging and water resources management, which have important influences on the sustainable development of society. The primary objective of the paper is to provide theoretical basis for local water resources management and disaster prevention and reduction by analyzing the multiscale variability of precipitation and their teleconnection with large-scale climate anomalies in Xi'an city of China. The change characteristics of precipitation and extreme precipitation indices were investigated using Mann-Kendall test, Spearman's rank correlation and wavelet analysis. The cross wavelet transform and wavelet coherence were used to explore the correlations between the precipitation and large-scale teleconnection indices such as Arctic Oscillation (AO), Southern Oscillation Index (SOI), El Niño-Southern Oscillation (ENSO) and sunspot. Results indicate that: the precipitation was mainly concentrated in summer, followed by autumn. The annual, seasonal and monthly precipitation except June and August had decreasing trends, and the magnitudes of precipitation decrease were more pronounced in spring, April and November. The change patterns varied for extreme precipitation indices. The temporal variation in extreme precipitation indices indicated that the extreme precipitation events had mainly increased during 1971-1990 and 1991-2017, and decreased during 1951-1970 and 1951-2017, especially, increased more pronounced during 1991-2017 and decreased more pronounced during 1951-1970. The precipitation exhibited a fluctuant change from increase to decrease, then increase to decrease and finally increase trends, and there was an abrupt change point in 1965. The annual precipitation had statistically significant cycles of 3-5 year and 7-10 year at 5% significance level. The large-scale teleconnection indices affected the precipitation in Xi'an city. The phase differences between precipitation and teleconnection indices including AO and SOI were in-phase dominated, and anti-phase dominated between precipitation and teleconnection indices including ENSO and sunspot, indicating that the AO and SOI exerted positive climate impacts on the precipitation and vice-versa for ENSO and sunspot. [ABSTRACT FROM AUTHOR]

The changes of precipitation affect the urban rainstorm waterlogging and water resources management, which have important influences on the sustainable development of society. The primary objective of the paper is to provide theoretical basis for local water resources management and disaster prevention and reduction by analyzing the multiscale variability of precipitation and their teleconnection with large-scale climate anomalies in Xi'an city of China. The change characteristics of precipitation and extreme precipitation indices were investigated using Mann-Kendall test, Spearman's rank correlation and wavelet analysis. The cross wavelet transform and wavelet coherence were used to explore the correlations between the precipitation and large-scale teleconnection indices such as Arctic Oscillation (AO), Southern Oscillation Index (SOI), El Niño- Southern Oscillation (ENSO) and sunspot. Results indicate that: the precipitation was mainly concentrated in summer, followed by autumn. The annual, seasonal and monthly precipitation except June and August had decreasing trends, and the magnitudes of precipitation decrease were more pronounced in spring, April and November. The change patterns varied for extreme precipitation indices. The temporal variation in extreme precipitation indices indicated that the extreme precipitation events had mainly increased during 1971-1990 and 1991-2017, and decreased during 1951-1970 and 1951-2017, especially, increased more pronounced during 1991-2017 and decreased more pronounced during 1951-1970. The precipitation exhibited a fluctuant change from increase to decrease, then increase to decrease and finally increase trends, and there was an abrupt change point in 1965. The annual precipitation had statistically significant cycles of 3-5 year and 7-10 year at 5% significance level. The large-scale teleconnection indices affected the precipitation in Xi'an city. The phase differences between precipitation and teleconnection indices including AO and SOI were in-phase dominated, and anti-phase dominated between precipitation and teleconnection indices including ENSO and sunspot, indicating that the AO and SOI exerted positive climate impacts on the precipitation and vice-versa for ENSO and sunspot. [ABSTRACT FROM AUTHOR]

The influence of urbanization on regional precipitation is one of the most important issues in hydrology. This paper selected the North Haihe Basin as the study area and explored the connection between summer precipitation and urbanization index (URBI) based on satellite precipitation and nighttime lights datasets. A moving spatial percentage anomaly method (MSP) was used to signify the local induced enhancement of precipitation (LIEP). Local indicators of spatial association (LISA) clustering for LIEP and URBI based on Bivariate Moran's I coupled with digital elevation model (DEM) segmentation was used to separate the impacts caused by urbanization and terrain uplifting, and thus, the regions of interest (ROI) where the urban induced enhancement of precipitation (UIEP) plays a dominant role were located. A geographically weighted regression (GWR) model was used to reveal the spatial variation of the sensitivity of UIEP to URBI within the ROI. Pearson correlation and cross-wavelet analyses (XWT) were adopted to investigate the teleconnection between UIEP and climate anomalies, using Niño3.4 and SOI as indices. The results indicated that: (1) Urbanization effects on precipitation spatial variation in the upstream mountainous area would be hidden away by topographic factors. (2) From the perspective of the basin, the highest urbanization level areas have the Lowest LIEP, while the suburban areas have the highest LIEP, and the rural areas are in the middle. (3) The UIEP and the URBI are generally negatively correlated within ROI. (4) UIEP versus Niño3.4 and SOI both show a significant common high-power period at a time scale of 2 years. This work can help comprehensively understand the hydrological response to urbanization. [ABSTRACT FROM AUTHOR]