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<jats:title>Abstract</jats:title><jats:p>The Asian Monsoonal rainfall accounts for the majority of annual regional precipitation in East and South Asia and could be remotely regulated by El Niño‐Southern Oscillation (ENSO). Besides, several paleoclimate records and simulations have indicated solar signals in the Asian Monsoon, implying the impact of solar activity on the regional monsoon precipitation. By conducting multi‐linear regression analysis to the solar irradiance forced single‐forcing experiment in the last millennium, this study presents the comparison of solar and ENSO effects on monsoonal precipitation in South and East Asia during early summer (May–June). Increased total solar irradiance during high solar activity years tends to trigger a favorable environment for developing monsoon onset, leading to more precipitation against ENSO‐related patterns over Southeast and South Asia before peak‐summer (July–August). The result supports reconstructed terrestrial records and underlines considerable influences of the solar cycle on the variation of the Asian Summer Monsoon.</jats:p>

<jats:title>Abstract</jats:title><jats:p>Pelagic tunicates (salps, pyrosomes) and fishes generate jelly falls and/or fecal pellets that sink roughly 10 times faster than bulk oceanic detritus, but their impacts on biogeochemical cycles in the ocean interior are poorly understood. Using a coupled physical‐biogeochemical model, we find that fast‐sinking detritus decreased global net primary production and surface export, but increased deep sequestration and transfer efficiency in much of the extratropics and upwelling zones. Fast‐sinking detritus generally decreased total suboxic and hypoxic volumes, reducing a “large oxygen minimum zone (OMZ)” bias common in global biogeochemical models. Newly aerobic regions at OMZ edges exhibited reduced transfer efficiencies in contrast with global tendencies. Reductions in water column denitrification resulting from improved OMZs improved simulated nitrate deficits relative to phosphate. The carbon flux to the benthos increased by 11% with fast‐sinking detritus from fishes and pelagic tunicates, yet simulated benthic fluxes remained on the lower end of observation‐based estimates.</jats:p>

<jats:title>Abstract</jats:title><jats:p>Sulfate aerosol greatly contributes to wintertime haze pollution in emission‐intensive regions like the North China Plain (NCP) in China. Fast sulfate increase and accumulation are usually recorded during winter haze; however, the multiphase oxidation of sulfur dioxide (SO<jats:sub>2</jats:sub>) and the physical processes affecting near‐surface sulfate are not fully understood. By combining in situ observations and numerical simulations, we found that high sulfur oxidation ratios (&gt;0.6) under heavily polluted conditions are associated with low clouds and fog over NCP, induced by the moist southerly airflow. Thick low clouds and high SO<jats:sub>2</jats:sub> levels in NCP provide a reaction environment for sulfate production. The sulfate production rate in cloud water can reach 0.5–1.3 μg m<jats:sup>−3</jats:sup> h<jats:sup>−1</jats:sup>. The results demonstrate that the vertical mixing of sulfate generated within the cloud water to the surface plays a significant role in rapid sulfate production, highlighting the importance of understanding cloud‐water processes in haze pollution.</jats:p>

<jats:title>Abstract</jats:title><jats:p>In some areas of Antarctica, blue‐colored bare ice is exposed at the surface. These blue ice areas (BIAs) can trap meteorites or old ice and are vital for understanding the climatic history. By combining multi‐sensor remote sensing data (MODIS, RADARSAT‐2, and TanDEM‐X) in a deep learning framework, we map blue ice across the continent at 200‐m resolution. We use a novel methodology for image segmentation with “noisy” labels to learn an underlying “clean” pattern with a neural network. In total, BIAs cover ca. 140,000 km<jats:sup>2</jats:sup> (∼1%) of Antarctica, of which nearly 50% located within 20 km of the grounding line. There, the low albedo of blue ice enhances melt‐water production and its mapping is crucial for mass balance studies that determine the stability of the ice sheet. Moreover, the map provides input for fieldwork missions and can act as constraint for other geophysical mapping efforts.</jats:p>

<jats:title>Abstract</jats:title><jats:p>This study examines the impact of ocean advection and surface freshwater flux on the non‐seasonal, upper‐ocean salinity variability in two climate model simulations with eddy‐resolving and eddy‐parameterized ocean components (HR and LR, respectively). We assess the realism of each simulation by comparing their sea surface salinity (SSS) variance with satellite and Argo float estimates. In the extratropics, the HR variance is about five times larger than that in LR and agrees with Argo. In turn, the extratropical satellite SSS variance is smaller than that from HR and Argo by about a factor of two, potentially caused by the insufficient resolution of radiometers to capture mesoscale features and their low sensitivity to SSS in cold waters. Using a simplified salinity conservation equation for the upper‐50‐m ocean, we find that the advection‐driven variance in HR is, on average, 10 times larger than the surface flux‐driven variance, reflecting the action of mesoscale processes.</jats:p>

<jats:title>Abstract</jats:title><jats:p>We show that ModE‐Sim, a global ensemble of atmospheric model simulations that uses observed ocean boundary conditions and radiative forcings providing 36 members with daily climate information can be used to in‐depth analyze the known spatial and temporal variability of heatwaves in the Northern Hemisphere and Australia during the past 160 years. It can also be used to study actual past extreme events like heatwaves during the El Nino 1877/1878. To analyze past heatwaves we use a novel approach of a transient baseline climatology and compare to different observational data sets. Furthermore, we analyze sea surface temperature anomalies during the most extreme heatwave summers in North America, Europe and Australia and identify the most prominent anomaly patterns over the Subpolar North Atlantic and in the Central Pacific. Using a large ensemble of forced simulations, like ModE‐Sim can consequently contribute to a better understanding of preindustrial heatwaves, their decadal variability and their driving mechanisms.</jats:p>

<jats:title>Abstract</jats:title><jats:p>Melting of ice shelves can energize a wide range of ocean currents, from three‐dimensional turbulence to relatively large‐scale boundary currents. Here, we conduct high‐resolution simulations of the western Amundsen Sea to show that submesoscale eddies are prevalent inside ice shelf cavities. The simulations indicate energetic submesoscale eddies at the top and bottom ocean boundary layers, regions with sharp topographic slopes and strong lateral buoyancy gradients. These eddies play a substantial role in the vertical and lateral (along‐isopycnal) heat advection toward the ice shelf base, enhancing the basal melting in all simulated cavities. In turn, the meltwater provides strong buoyancy gradients that energize the submesoscale variability, forming a positive loop that could affect the overall efficiency of heat exchange between the ocean and the ice shelf cavity. Our study implies that submesoscale‐induced enhancement of basal melting may be a ubiquitous process that needs to be parameterized in coarse‐resolution climate models.</jats:p>

<jats:title>Abstract</jats:title><jats:p>CIRBE (Colorado Inner Radiation Belt Experiment), a 3U CubeSat, was launched on 15 April 2023 into a sun synchronous orbit (97.4° inclination and 509 km altitude). The sole science payload onboard is REPTile‐2 (Relativistic Electron and Proton Telescope integrated little experiment—2), an advanced version of REPTile which operated in space between 2012 and 2014. REPTile‐2 has 60 channels for electrons (0.25–6 MeV) and 60 channels for protons (6.5–100 MeV). It has been working well, capturing detailed dynamics of the radiation belt electrons, including several orders of magnitude enhancements of the outer belt electrons after an intense magnetic storm, multiple “wisps”‐ an electron precipitation phenomenon associated with human‐made very low frequency (VLF) waves in the inner belt, and “drift echoes” of 0.25–1.4 MeV electrons across the entire inner belt and part of the outer belt. These new observations provide opportunities to test the understanding of the physical mechanisms responsible for these features.</jats:p>

<jats:title>Abstract</jats:title><jats:p>This study shows that geostationary satellites are critical to estimate the accurate cloud feedback strength over the tropical western Pacific (TWP). Cloud feedback strength was calculated by the simultaneous relation between cloud cover and sea surface temperature (SST) over the TWP [120°E–170°E, 20°S–20°N]. During 2011–2018, the cloud cover was obtained by geostationary earth orbit satellite (GEO) and low‐level earth orbit satellite (LEO) (<jats:italic>A</jats:italic><jats:sup>GEO</jats:sup>, <jats:italic>A</jats:italic><jats:sup>LEO</jats:sup>), and the NOAA's all‐sky SST (<jats:italic>T</jats:italic><jats:sub>o</jats:sub>) was weighted with the clear‐sky fraction observed by GEO and LEO (<jats:italic>T</jats:italic><jats:sub>w</jats:sub><jats:sup>GEO</jats:sup>; <jats:italic>T</jats:italic><jats:sub>w</jats:sub><jats:sup>LEO</jats:sup>). The linear regression coefficients between clouds and SST are very different: −7.93%K<jats:sup>−1</jats:sup> (<jats:italic>A</jats:italic><jats:sup>GEO</jats:sup>/<jats:italic>T</jats:italic><jats:sub>w</jats:sub><jats:sup>G</jats:sup><jats:sup>EO</jats:sup>), −6.94%K<jats:sup>−1</jats:sup> (<jats:italic>A</jats:italic><jats:sup>LEO</jats:sup>/<jats:italic>T</jats:italic><jats:sub>w</jats:sub><jats:sup>GEO</jats:sup>), −1.35%K<jats:sup>−1</jats:sup> (<jats:italic>A</jats:italic><jats:sup>GEO</jats:sup>/<jats:italic>T</jats:italic><jats:sub>w</jats:sub><jats:sup>LEO</jats:sup>), −0.69%K<jats:sup>−1</jats:sup> (<jats:italic>A</jats:italic><jats:sup>LEO</jats:sup>/<jats:italic>T</jats:italic><jats:sub>w</jats:sub><jats:sup>LEO</jats:sup>), −0.02 %K<jats:sup>−1</jats:sup> (<jats:italic>A</jats:italic><jats:sup>GEO</jats:sup>/<jats:italic>T</jats:italic><jats:sub>o</jats:sub>), and −0.50 %K<jats:sup>−1</jats:sup> (<jats:italic>A</jats:italic><jats:sup>LEO</jats:sup>/<jats:italic>T</jats:italic><jats:sub>o</jats:sub>). Among these, only the <jats:italic>T</jats:italic><jats:sub>w</jats:sub><jats:sup>GEO</jats:sup> values provided a valid cloud feedback signal. This is because GEO's field of view is large enough to simultaneously capture cloud cover over the entire TWP.</jats:p>

<jats:p>No abstract is available for this article.</jats:p>