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The capability of assimilating surface PM10 (particulate matter with diameters less than 10 µm) observations has been developed within the National Centers for Environmental Prediction Gridpoint Statistical Interpolation three‐dimensional variational (3DVAR) data assimilation (DA) system. It provides aerosol analyses for the Goddard Chemistry Aerosol Radiation and Transport aerosol scheme within the Weather Research and Forecasting/Chemistry model. Control and assimilation experiments were performed for June 2011 over China to explore in detail the impact of assimilating surface PM10. In the assimilation experiment, analyses were produced every 6 h to adjust the mass concentrations of different aerosol species. The statistical results from two parallel experiments demonstrate that the assimilation of surface PM10 observations can significantly reduce the uncertainty of initial aerosol fields and effectively improve the subsequent aerosol forecasts for at least 12 h. However, the benefit from the assimilation of PM10 diminishes rapidly with forecast range. Process analysis for PM10 formation indicates that the rapidly diminishing DA impact on aerosol forecasts, especially in early forecast hours, was dominated by vertical mixing with an additional contribution from advection. Both processes were mainly related to unbalanced aerosol fields in the horizontal and vertical after assimilating surface observations. These findings illustrate the importance of adjusting aerosol emission rates and the initial aerosol vertical profile.

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Due to the extremely low latency, events have been recently exploited to supplement lost information for motion deblurring. Existing approaches largely rely on the perfect pixelwise alignment between intensity images and events, which is not always fulfilled in the real world. To tackle this problem, we propose a novel coarse-to-fine framework, named NETwork of Event-based motion Deblurring with STereo event and intensity cameras (St-EDNet), to recover high-quality images directly from the misaligned inputs, consisting of a single blurry image and the concurrent event streams. Specifically, the coarse spatial alignment of the blurry image and the event streams is first implemented with a cross-modal stereo matching module without the need for ground-truth depths. Then, a dual-feature embedding architecture is proposed to gradually build the fine bidirectional association of the coarsely aligned data and reconstruct the sequence of the latent sharp images. Furthermore, we build a new dataset with STereo Event and Intensity Cameras (StEIC), containing real-world events, intensity images, and dense disparity maps. Experiments on real-world datasets demonstrate the superiority of the proposed network over state-of-the-art methods. The code and dataset are available at https://mingyuan-lin.github.io/St-ED web/.

Abstract. El Niño has two different flavors, eastern Pacific (EP) and central Pacific (CP) El Niños, with different global teleconnections. However, their different impacts on the interannual carbon cycle variability remain unclear. Here we compared the behaviors of interannual atmospheric CO 2 variability and analyzed their terrestrial mechanisms during these two types of El Niños, based on the Mauna Loa (MLO) CO 2 growth rate (CGR) and the Dynamic Global Vegetation Model's (DGVM) historical simulations. The composite analysis showed that evolution of the MLO CGR anomaly during EP and CP El Niños had three clear differences: (1) negative or neutral precursors in the boreal spring during an El Niño developing year (denoted as "yr0"), (2) strong or weak amplitudes, and (3) durations of the peak from December (yr0) to April during an El Niño decaying year (denoted as "yr1") compared to October (yr0) to January (yr1) for a CP El Niño, respectively. The global land-atmosphere carbon flux (F TA ) simulated by multi-models was able to capture the essentials of these characteristics. We further found that the gross primary productivity (GPP) over the tropics and the extratropical Southern Hemisphere (Trop + SH) generally dominated the global F TA variations during both El Niño types. Regional analysis showed that during EP El Niño events significant anomalous carbon uptake caused by increased precipitation and colder temperatures, corresponding to the negative precursor, occurred between 30 • S and 20 •

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