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We identified precipitating systems from May to August 2016 using data from the Global Precipitation Measurement mission Dual-frequency Precipitation Radar instrument. Then, using this set of cases, Himawari-8 10.4-μm brightness temperature data from before and after each precipitation event were used to identify three life stages of clouds: a developing stage, a mature stage, and a dissipating stage. Using statistical analysis and two case studies, we show that the precipitating systems at different life stages of the clouds have different systematic properties, including the area of precipitation, the convective ratio, the rain-top height, and the brightness temperature. The developing systems had the largest convective ratio, whereas the dissipating systems had the largest area of precipitation. The life stage of the cloud also influenced the vertical structure of the precipitation. The microphysical processes within each stage were unique, leading to various properties of the droplets in precipitation. The developing systems had large, but sparse, droplets; the mature systems had large and dense droplets; and the dissipating systems had small and sparse droplets. Our results suggest that the different properties of precipitating systems in each life cycle stage of clouds are linked to the cloud water content and the upward motion of air.

Three striking and impactful extreme cold weather events successively occurred across East Asia and North America during the mid-winter of 2020/21. These events open a new window to detect possible underlying physical processes. The analysis here indicates that the occurrences of the three events resulted from integrated effects of a concurrence of anomalous thermal conditions in three oceans and interactive Arctic-lower latitude atmospheric circulation processes, which were linked and influenced by one major sudden stratospheric warming (SSW). The North Atlantic warm blob initiated an increased poleward transient eddy heat flux, reducing the Barents-Kara seas sea ice over a warmed ocean and disrupting the stratospheric polar vortex (SPV) to induce the major SSW. The Rossby wave trains excited by the North Atlantic warm blob and the tropical Pacific La Nina interacted with the Arctic tropospheric circulation anomalies or the tropospheric polar vortex to provide dynamic settings, steering cold polar air outbreaks. The long memory of the retreated sea ice with the underlying warm ocean and the amplified tropospheric blocking highs from the midlatitudes to the Arctic intermittently fueled the increased transient eddy heat flux to sustain the SSW over a long time period. The displaced or split SPV centers associated with the SSW played crucial roles in substantially intensifying the tropospheric circulation anomalies and moving the jet stream to the far south to cause cold air outbreaks to a rarely observed extreme state. The results have significant implications for increasing prediction skill and improving policy decision making to enhance resilience in “One Health, One Future”.

The North Pacific storm track (NPST) is a high-frequency area of extratropical cyclones and an important channel for water vapor and energy transfer between low and mid–high latitudes. Previous weather and dynamic studies in this region have made significant progress, but due to the lack of ocean surface rainfall observation data, there is a lack of statistical research on precipitation in this area. In this study, statistical research on the spatiotemporal distribution characteristics of NPST rainfall was conducted based on GPM DPR (Global Precipitation Measurement Dual-frequency Precipitation Radar) observation data and ERA5 atmospheric parameters, and analysis and explanations are provided based on the atmospheric parameters. The study found that, compared to low-pressure systems, pressure gradients have a greater impact on cyclone activity and rainfall distribution. This feature, along with the meridional distribution of high atmospheric water vapor in the North Pacific Ocean and low in the north, collectively leads to the offset of high-frequency rainfall areas relative to storm tracks. The distribution of sea surface temperatures in the North Pacific Ocean affects the zonal distribution of storm tracks, causing weather disturbances and precipitation along the storm tracks to exhibit a northward extension from west to east. This study deepens our understanding of the role of NPST in global-scale water vapor and energy balance, and is of great significance for improving the prediction accuracy of climate models with respect to rainfall generated by extratropical cyclones.

Urban expansion and climate change can considerably influence the regional thermal environment. In this study, the effects of changes in land cover type and vegetation coverage (referred to as LU for short), gridded anthropogenic heat (AH) emission and future climate change on atmospheric thermal environment in a Chinese megacity, Hefei, are investigated by Weather Research and Forecasting (WRF)/Urban Canopy Model (UCM) model. It is found that the increase of surface sensible heat in old urban areas is contributed by AH emission, while that in new urban areas is attributed to LU change. The LU change in new urban areas can lead to the decreased latent heat flux due to the reduction of vegetation coverage and the increase of impervious land surface. The contribution of LU change to the summer UHI intensity is about 0.76 ℃, and AH emission to that is about 0.17 ℃. The combined effects of LU change and AH emission in old urban areas are greater than those in new urban areas, leading to changes in daily mean 2-m air temperature, 2-m relative humidity (RH), and heat index in old (new) urban areas to be 1.08 ℃ (0.75 ℃), – 5.93% (– 4.96%), and 2.77 ℃ (1.76 ℃), respectively. At the end of the twenty-first century, the urban air temperature under RCP 4.5 (RCP 8.5) scenario is 0.7 ℃ (3 ℃) higher than that at present.

The non-hydrostatic global variable resolution model (MPAS-atmosphere) is used to conduct the simulations for the South Asian Summer monsoon season (June, July, and August) in 2015 with a refinement over the Tibetan Plateau (TP) at the convection-permitting scale (4 km). Two experiments with different topographical datasets, complex (4-km) and smooth (60-km) topography, are designed to investigate the impacts of topographical complexity on moisture transport and precipitation. Compared with the observations and reanalysis data, the simulation can successfully capture the general features of key meteorological fields over the TP despite slightly underestimating the inflow through the southern TP. The results indicate that the complex topography can decrease the inward and outward moisture transport, ultimately increasing the total net moisture transport into the TP by ∼11%. The impacts of complex topography on precipitation are negligible over the TP, but the spatial distributions of precipitation over the Himalayas are significantly modulated. With the inclusion of complex topography, the sharper southern slopes of the Himalayas shift the lifted airflow and hence precipitation northward compared to the smooth topography. In addition, more small-scale valleys are resolved by the inclusion of complex topography, which serve as channels for moisture transport across the Himalayas, further favoring a northward shift of precipitation. Overall, the difference between the two experiments with different topography datasets is mainly attributed to their differing representation of the degree of the southern slopes of the Himalayas and the extent to which the valleys are resolved.

Scientific research and engineering practice often require the modeling and decomposition of nonlinear systems. The dynamic mode decomposition (DMD) is a novel Koopman-based technique that effectively dissects high-dimensional nonlinear systems into periodically distinct constituents on reduced-order subspaces. As a novel mathematical hatchling, the DMD bears vast potentials yet an equal degree of unknown. This effort investigates the nuances of DMD sampling with an engineering-oriented emphasis. It aimed at elucidating how sampling range and resolution affect the convergence of DMD modes. We employed the most classical nonlinear system in fluid mechanics as the test subject—the turbulent free-shear flow over a prism—for optimal pertinency. We numerically simulated the flow by the dynamic-stress Large-Eddies Simulation with Near-Wall Resolution. With the large-quantity, high-fidelity data, we parametrized and identified four global convergence states: Initialization , Transition , Stabilization , and Divergence with increasing sampling range. Results showed that Stabilization is the optimal state for modal convergence, in which DMD output becomes independent of the sampling range. The Initialization state also yields sufficient accuracy for most system reconstruction tasks. Moreover, defying popular beliefs, over-sampling causes algorithmic instability: as the temporal dimension, n , approaches and transcends the spatial dimension, m (i.e., m  <  n ), the output diverges and becomes meaningless. Additionally, the convergence of the sampling resolution depends on the mode-specific dynamics, such that the resolution of 15 frames per cycle for target activities is suggested for most engineering implementations. Finally, a bi-parametric study revealed that the convergence of the sampling range and resolution are mutually independent.

Satellite microwave instruments have different field of views (FOVs) in different channels. A direct average technique (“direct method”) is frequently used to generate gridded datasets in the earth science community. A large FOV will measure radiance from outside the area of a designated grid cell. Thus, the direct method will lead to errors in a measurement over a grid cell because some pixels covering areas outside of the cell are involved in the averaging process. The Backus-Gilbert method (BG method) is proposed and demonstrated to minimize those uncertainties. Three sampling resolutions (6.5 km × 6.0 km, 11.5 km × 6.0 km, 13.0 km × 6.0 km) are analyzed based on the scanning characteristics of the Global Precipitation Measurement (GPM) Microwave Imager (GMI) 18.9-GHz channel. Brightness temperatures (TBs) at 0.5 km × 0.5 km resolution over eastern China are used to obtain synthetic 18.9-GHz TBs at the three sampling resolutions. The direct and BG methods are both applied to create a 25 km × 25 km gridded dataset and their related uncertainties are analyzed. Results indicate the error variances with the direct method are 3.00, 3.68 and 4.99 K 2 at the three sampling resolutions, respectively. By contrast, the BG method leads to a much smaller error variance than the direct method, especially over areas with a large TB gradient. Two GMI orbital measurements are applied to verify the BG method for gridding process is reliable. The BG method could be utilized for general purpose of creating a gridded dataset.

Characteristics of the precipitation in rainy season over the steep Himalayas and adjacent regions, including four selected sectors of the flat Gangetic Plains (FGP), foothills of the Himalayas (FHH), the steep slope of the southern Himalayas (SSSH), and the Himalayan–Tibetan Plateau tableland (HTPT), are investigated using collocated satellite datasets from the TRMM PR and VIRS at pixel level during May–August of 1998–2012. Results indicate that the rain frequency increases significantly from the FGP via FHH to the lower elevations of the SSSH (~ 2.5 km), then decreases as the elevation further increases up to the HTPT, and reaches the minimum over the HTPT. Along with such spatial variation of the rain frequency, mean rain rates (RRs) are the heaviest over the FGP (4 mm h−1) and the FHH (5.5 mm h−1), medium over the SSSH (2–4 mm h−1), and the weakest over the HTPT (less than 2 mm h−1). More than 60% of precipitation over the FGP, FHH, and HTPT is produced by ice-phase topped clouds, while more than 70% over the SSSH is from mixed-phase topped clouds.Analysis suggests that the highest rain frequency over the SSSH in rainy season may be caused by a strong upward motion over the SSSH as warm moist air monsoon flow interacting with the terrain of the Himalayas, while the heaviest RR over the FHH may result from low-level convergence where the air flow is blocked by the SSSH. The elevation and relief effects have linear relationships with precipitation over the south sub-region of the SSSH, which indicates that both effects play important roles on precipitation over complex plateau topography.

Based on 10 years precipitation data from Tropical Rainfall Measurement Mission （TRMM） Multi-satellite Precipitation Analysis （TMPA） 3B42 and the best track data from China Meteorological Administration （CMA）, the seasonal, monthly and annual contribution of tropical cyclone （TC） precipitation to the total rainfall are analyzed over the Western North Pacific （WNP） during 1998 to 2007 from May to December. The results show that： （1） TC seasonal rainfall contribution ranges from 4% in inland regions to above 40% in ocean-regions of 15°N-25°N. TCs at higher categories contribute much more to the total precipitation. （2） On monthly scale, TCs contribute 60% to the total rainfall regionally during whole TC season, which is the maximum contribution. The peak contribution of TC rainfall averaged in multi-months of the ten years occurs in August （28%） over the whole ocean impacted by TC and in December （23%） over the whole land impacted by TC, respectively. （3） On annual scale, the maximum contribution of TC precipitation to the total rainfall are in 2004 （-30%） over ocean and in 1998 （-20%） over land, respectively. （4） The contribution of TC precipitation to the total rainfall increases 6% （decreases 6%） in El Nino （La Nifia） years compared with neutral years.

This study aimed to investigate the correlation between anti-phospholipase A2 receptor (PLA2R) levels in serum and urine with clinical parameters, particularly albuminuria, in patients with idiopathic membranous nephropathy (IMN). We retrospectively analyzed data from 30 patients with biopsy-proven PLA2R-related IMN diagnosed between 2016 and 2022 at two medical centers. Serum and urine anti-PLA2R antibody levels were measured using enzyme-linked immunosorbent assay (ELISA). We assessed the correlation between antibody levels and clinical parameters, including plasma albumin, 24-hour urine protein quantification, and estimated glomerular filtration rate (eGFR). Patients were staged according to the Ehrenreich-Churg classification. Serum anti-PLA2R antibody levels showed a significant negative correlation with plasma albumin (r = -0.469, P < 0.05), whereas urine anti-PLA2R antibody levels exhibited a weak, but significant, positive correlation with 24-hour urine protein excretion (r = 0.362, P = 0.049). Patients with higher serum anti-PLA2R antibody titers had significantly lower plasma albumin levels (20.63 ± 4.79 g/L) compared to those with lower titers (27.71 ± 6.78 g/L) (P < 0.05). Conversely, patients with higher urine anti-PLA2R antibody titers had significantly higher 24-hour urine protein quantification (9.22 ± 4.17 g) compared to those with lower titers (5.32 ± 3.09 g) (P < 0.05). In patients with IMN, serum anti-PLA2R antibody concentrations are inversely associated with plasma albumin, while urine anti-PLA2R antibody levels are positively associated with 24-hour urine protein quantification. These findings suggest that combined assessment of serum and urine anti-PLA2R antibody levels may provide valuable insights into disease activity and albuminuria in IMN. Further studies with larger cohorts are needed to validate these findings and explore their potential clinical implications.