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The Qilian Mountains (QMs) act as the "water tower" of the Hexi Corridors, playing an important role in the regional ecosystem security and economic development. Therefore, it is of great significance to understand the spatiotemporal characteristics of precipitation in the QMs. This study evaluated the performance of 21 models of phase 6 of the Coupled Model Intercomparison Project (CMIP6) from 1959 to 1988 based on ERA5 and in situ datasets. In addition, the precipitation changing trend from 2015 to 2100 was projected according to four shared socioeconomic pathways (SSPs): namely, SSP126, SSP245, SSP370, and SSP585. The results have shown the following: (1) all CMIP6 models could reflect the same precipitation changing trend, based on the observed datasets (−2.01 mm·10a−1), which was slightly lower than that of ERA5 (2.82 mm·10a−1). Multi-mode ensemble averaging (MME) showed that the projected precipitation-change trend of the four scenarios was 5.73, 9.15, 12.23, and 16.14 mm·10a−1, respectively. (2) The MME and ERA5 showed the same precipitation spatial pattern. Also, during the period 1959–1988, the MME in spring, summer, autumn and winter was 130.07, 224.62, 95.96, and 29.07 mm, respectively, and that of ERA5 was 98.57, 280.77, 96.85, and 22.64 mm, respectively. The largest precipitation difference in summer was because of strong convection and variable circulation. (3) From 2015 to 2100, the snow-to-rain ratio was between 0.1 and 1.1, and the snow-to-rain ratio climate tendency rate was concentrated in the range of −10~0.1 mm·10a−1. Both of these passed the significance test (p < 0.05). The projected rainfall of all four SSPs all showed an increasing trend with values of 6.20, 11.31, 5.64, and 20.41 mm·10a−1, respectively. The snowfall of the four SSPs all showed a decreasing trend with values of 0.42, 2.18, 3.34, and 4.17 mm·10a−1, respectively. [ABSTRACT FROM AUTHOR]

Simple Summary: Multiple myeloma (MM) is characterized by the presence of systemic clinical manifestations. Among them, pneumonia accounts for a significant cause of morbidity and mortality, highlighting an urgent need to explore possible susceptibility and potential mechanisms of pneumonia in MM. Recently, the gut–lung axis has emphasized the relevance of gut microbiota and pneumonia, indicating that the compromised function of gut microbiota may be susceptible to pneumonia. It has been previously shown that intestinal Klebsiella pneumonia enriches in MM patients and promotes MM progression in our previous work. In addition, host metabolism has been identified as a key regulator of MM. However, what role the altered gut microbiota plays in MM with pneumonia remains unknown. In this study, we explored the association between gut microbiota and MM with pneumonia. This is the first study to identify and elucidate the function of gut microbiota involved in MM with pneumonia. Pneumonia accounts for a significant cause of morbidity and mortality in multiple myeloma (MM) patients. It has been previously shown that intestinal Klebsiella pneumonia (K. pneumonia) enriches in MM and promotes MM progression. However, what role the altered gut microbiota plays in MM with pneumonia remains unknown. Here, we show that intestinal K. pneumonia is significantly enriched in MM with pneumonia. This enriched intestinal K. pneumonia links to the incidence of pneumonia in MM, and intestinal colonization of K. pneumonia contributes to pneumonia in a 5TGM1 MM mice model. Further targeted metabolomic assays reveal the elevated level of glutamine, which is consistently increased with the enrichment of K. pneumonia in MM mice and patients, is synthesized by K. pneumonia, and leads to the elevated secretion of TNF-α in the lung normal fibroblast cells for the higher incidence of pneumonia. Inhibiting glutamine synthesis by establishing glnA-mutated K. pneumonia alleviates the incidence of pneumonia in the 5TGM1 MM mice model. Overall, our work proposes that intestinal K. pneumonia indirectly contributes to pneumonia in MM by synthesizing glutamine. Altogether, we unveil a gut–lung axis in MM with pneumonia and establish a novel mechanism and a possible intervention strategy for MM with pneumonia. [ABSTRACT FROM AUTHOR]

Landfalling tropical cyclones (TCs) in Northeast China are rare because of the region's high latitude (>40°N). In 2020, Northeast China was affected by three TCs within half a month—the first time on record. We used the Global Precipitation Measurement orbital dataset to study the precipitation microphysics during the TC period in Northeast China in 2020 (2020-TC), and during September in this region from 2014 to 2019 (hereafter September 2014–September 2019). FY-4A was used to provide cloud top height (CTH). The results show that, compared with September 2014–September 2019, the 2020-TC precipitation has stronger precipitation ice productivity, weaker deposition efficiency, stronger riming, and stronger coalescence processes. The storm top height (STH), CTH, and the difference between the two (CTH-STH) are indicative of the near-surface droplet size distribution (DSD), but there are differences: STH and CTH-STH both correlate significantly with mean mass-weighted drop diameter, whereas only the positive correlation between CTH and normalized drop concentration parameter passes the significance test. These results reveal for the first time the precipitation microphysics of landfalling TCs in Northeast China, and allow discussion of the validity of convective intensity indicators from the perspective of DSD. [ABSTRACT FROM AUTHOR]

This paper uses the median-of-means (MOM) method to estimate the parameters of the nonlinear regression models and proves the consistency and asymptotic normality of the MOM estimator. Especially when there are outliers, the MOM estimator is more robust than nonlinear least squares (NLS) estimator and empirical likelihood (EL) estimator. On this basis, we propose hypothesis testing Statistics for the parameters of the nonlinear regression models using empirical likelihood method, and the simulation performance shows the superiority of MOM estimator. We apply the MOM method to analyze the top 50 data of GDP of China in 2019. The result shows that MOM method is more feasible than NLS estimator and EL estimator. [ABSTRACT FROM AUTHOR]

The daily fields from three reanalysis datasets are utilized to explore the subseasonal influence of teleconnection patterns on the surface air temperature (SAT) over southern China. Due to the similarity of the results from the different datasets, the ensemble mean is then used in this study. After applying the false discovery rate to the significance test, the composite results reveal that positive Western Pacific (WP) events, East Atlantic (EA) events, Scandinavian (SCA) events, and Eastern Atlantic/Western Russia (EAWR) events are the teleconnection events that have an influence on SAT anomalies over southern China. The timing of inducing significant SAT anomalies over southern China is similar among positive WPevents, EA events and EAWR events, i.e., approximately the first 5-day period after their peak day. In contrast, SCA events exert a lagged significant influence on SAT, i.e., during approximately the second 6-day period after their peak day. Therefore, considering that significant circulation anomalies generally begin to appear at least 4 days before the peak day, these teleconnection events could be used as subseasonal predictors for SAT anomalies over southern China. [ABSTRACT FROM AUTHOR]