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[1] Arid and semi-arid areas of the Loess Plateau over northwestern China are one of the dust aerosol source regions featured by its unique underlying surface. These areas, suffering the severe aridity trend in past decades, are also known as the transitional zone of climate and ecosystem change. To better understand the basic characteristics of the land surface energy budget, seasonal and diurnal variations of moisture and heat flux over this region, field observations collected at the Semi-Arid Climate and Environment Observatory of Lanzhou University (SACOL, 35°57′N, 104°08′E, Elev. 1965.8 ) occurred in winter as the snow cover. The highest surface albedo was also found in winter as a result of the snow cover. Surface albedo was lower in the growing season (wet season) due to the larger vegetation fraction and wetter soil. The components of the land surface energy budget varied seasonally except for the surface soil heat flux, and all showed strong diurnal cycles. Net radiation increased from winter to summer and decreased from summer to winter associated with the variation of DSR. Sensible (latent) heat flux was the main consumer of the available energy in winter and spring (summer and autumn). The energy imbalance problem was also identified. When the soil heat storage in the surface soil and vegetation canopy was neglected, the energy imbalance ratio was about 22%. While given the surface heat storage calculated by the thermal diffusion equation and correction method (TDEC), the imbalance ratio was only 14%. Furthermore, taking the soil heat storage into account, this ratio was only 8% in spring, and 15% in summer and autumn. Compared with the bare surface layer in spring, it is likely that a part of energy was stored in the vegetation canopy in summer and autumn. In addition, the sensible and latent heat fluxes over different land surface types of the Loess Plateau are analyzed. Sensible and latent heat fluxes are utterly different substantially over those different underlying surfaces due to the factors such as vegetation, precipitation, and soil moisture.

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The El Niño-Southern Oscillation (ENSO) has been shown to manifest as primarily two types, the eastern Pacific (EP) type and central Pacific (CP) type, in terms of the zonal positions of the sea surface temperature (SST) anomalies. This study focuses on examining the predictability of the two types of ENSO by developing statistical models for their corresponding Niño indices, which have their own distinct key precursors. The results show that the statistical predictability of the Niño indices representing the two types of ENSO primarily originates from the preceding variations in the equatorial Pacific upper-ocean heat content and the surface zonal wind stress, which intrinsically reflect the zonally uniform and contrasted thermocline patterns, respectively. The traditional Niño3 and Niño4 indices are more predictive than the Niño indices of the EP and CP ENSO types; however, all the indices are subject to predictability barriers with different timings and intensities, which might be weakened by introducing additional external precursors. The EP ENSO indices have overall higher skills than the CP indices, in which the statistical model has much higher skill scores than persistence forecast for the EP ones while it does less for the CP ones. We demonstrate that the precursors outside the tropical Pacific, e.g., the Indian Ocean Dipole, North Pacific oscillation, North American dipole, and Southern Hemispheric SST modes, except the northern tropical Atlantic SST, as suggested in previous studies, only make limited contributions to improving the prediction skills of the two ENSO types at specific initial months and leads compared to a benchmark model built using the equatorial Pacific heat content and zonal wind stress indices. This is primarily because these precursors have already transferred most of their signals into the variation of the two indices in the benchmark model. We further show that conditionally adding the northern tropical Atlantic SST precursor to the benchmark could provide considerable additional prediction skill scores for both types of ENSO and weaken the intensity of the ENSO predictability barriers that occur during boreal spring-summer.

In the boreal winter, the Arctic Oscillation (AO) evidently acts to influence surface air temperature (SAT) anomalies in China. This study reveals a large intraseasonal variation in the relationship between the winter AO and southern China SAT anomalies. Specifically, a weak in-phase relationship occurs in December, but a significant out-of-phase relationship occurs in January and February. The authors show that the linkage between the AO and southern China SAT anomalies strongly depends on the AO-associated changes in the Middle East jet stream (MEJS) and that such an AO-MEJS relationship is characterized by a significant difference between early and middle-to-late winter. In middle-to-late winter, the Azores center of high pressure anomalies in the positive AO phase usually extends eastward and yields a significantly anomalous upper-level convergence over the Mediterranean Sea, which can excite a Rossby wave train spanning the Arabian Sea and intensify the MEJS. In early winter, however, the Azores center of the AO is apparently shifted westward and is mainly confined to the Atlantic Ocean; in this case, the associated change in the MEJS is relatively weak. Both observational diagnoses and experiments based on a linearized barotropic model suggest that the MEJS is closely linked to the AO only when the latter generates considerable upper-level convergence anomalies over the Mediterranean Sea. Therefore, the different impacts of the AO on the MEJS and the southern China SAT anomalies between early and middle-to-late winter are primarily attributed to the large intraseasonal zonal migrations of the Azores center of the AO.

A record-breaking heat wave hit the Yangtze River valley during the boreal summer of 2022, and caused severe social and economic losses. One prominent feature of this long-lived heat event was its persistence and abnormal intensification in August. This study investigated the physical mechanisms be responsible for the intensification of this heat event in late summer under the background of a La Niña event. The prolonged heat event was directly related to the intensification and westward extension of the western North Pacific subtropical high, which can be attributed to the synergistic effects of an anomalous western North Pacific anticyclone and the eastward extension of the South Asian high in the upper troposphere. The anomalous anticyclone in the western North Pacific, which was induced by negative sea surface temperature anomalies in the central tropical Pacific, strengthened in August. The positive sea surface temperature anomaly in the western Pacific warm pool and enhanced in-situ convection led to anomalous high pressure over the Yangtze River valley via the local meridional circulation. Atmospheric convergence and descending motion over the Yangtze River valley was amplified in August as a result of the zonal shift in the South Asian high from the Iranian Plateau to the Tibetan Plateau. The Silk Road pattern index of August 2022 was the lowest since the 1990s. The abnormal negative phase of the Silk Road pattern contributed to both the zonal shift in the South Asian high and the westward extension of the western North Pacific subtropical high, which led to the abnormal intensification of the heat event over the Yangtze River valley in August 2022.