The Hikurangi Margin east of New Zealand’s North Island hosts an extensive gas hydrate province with numerous gas hydrate accumulations related to the faulted structure of the accretionary wedge. One such hydrate feature occurs in a small perched upper-slope basin known as Urutī Basin. We investigate this hydrate accumulation by combining a long-offset seismic line (10-km-long receiver array) with a grid of high-resolution seismic lines acquired with a 600-m-long hydrophone streamer. The long-offset data enable quantitative velocity analysis while the high-resolution data constrain the three-dimensional geometry of the hydrate accumulation. The sediments in Urutī Basin dip landward due to ongoing deformation of the accretionary wedge. These strata are clearly imaged in seismic data where they cross a distinct bottom simulating reflection (BSR) that dips, counterintuitively, in the opposite direction to the regional dip of the seafloor. BSR-derived heat flow estimates reveal a distinct heat flow anomaly that coincides spatially with the upper extent of a landward-verging thrust fault. We present a conceptual model of this gas hydrate system that highlights the roles of fault-controlled fluid flow at depth merging into strata-controlled fluid flow into the hydrate stability zone. The result is a layer-constrained accumulation of concentrated gas hydrate in the dipping strata. Our study provides new insight into the interplay between deep faulting, fluid flow and the shallow processes involved in gas hydrate formation.

Representing single or multi-layered mixed-phase clouds (MPCs) accurately in global climate models (GCMs) is critical for capturing climate sensitivity and Arctic amplification. Ice multiplication, or secondary ice production (SIP), can increase the ice crystal number concentration (ICNC) in MPCs by several orders of magnitude, affecting cloud properties and processes. Here, we propose a machine-learning approach, called Random Forest SIP (RaFSIP), to parameterize the effect of SIP on stratiform MPCs. The RaFSIP scheme uses few input variables available in models and considers rime splintering, ice-ice collisional break-up, and droplet-shattering, operating at temperatures between 0 and -25 ˚C. The training dataset for RaFSIP was derived from two-year pan-Arctic simulations with the Weather Research and Forecasting (WRF) model with explicit representations of SIP processes. The RaFSIP scheme was evaluated offline against WRF simulation outputs, then integrated within WRF. The parameterization exhibits stable performance over a simulation year, and reproduced predictions of ICNC with explicit microphysics to within a factor of 3. The coupled WRF-RaFSIP scheme can replicate regions of enhanced SIP and accurately map ICNCs and liquid water content, particularly at temperatures above -10 ˚C. Uncertainties related to the RaFSIP representation of MPCs marginally affected surface cloud radiative forcing in the Arctic, with radiative biases of lower than 3 Wm-2 compared to simulations with explicit SIP microphysics. Training from a few high-resolution model grid points did not limit the predictive skill of RaFSIP, with the approach opening up new avenues for model simplification and process description in GCMs by physics-guided machine learning algorithms.

The interior oceans of several icy moons are considered as “moderately rotating”. Observations suggest a larger heat transport around the poles than at the equator. Rotating Rayleigh-Bénard convection (RRBC) in planar configuration is known to show an enhanced heat transport compared to the non-rotating case for such “moderate” rotation. We investigate the potential for such a (polar) heat transport enhancement in these sub-glacial oceans by direct numerical simulations of RRBC in spherical geometry for Ra=106 and 0.7≤Pr≤4.38. We find an enhancement up to 28% in the “polar tangent cylinder”, which is globally compensated by a reduced heat transport at low latitudes. As a result, the polar heat transport can exceed the equatorial by up to 50%. The enhancement is mostly insensitive to different radial gravity profiles, but decreases for thinner shells. In general, polar heat transport and its enhancement in spherical RRBC follow the same principles as in planar RRBC.

Airborne Doppler radar observations of the wind field in the tropical cyclone boundary layer (TCBL) during the landfall of Hurricane Ida (2021) are examined here. Asymmetries in tangential and radial flow are governed by TC motion and vertical wind shear prior to landfall, while frictional effects dominate the asymmetry location during landfall. Strong TCBL inflow on the offshore-flow side of Ida occurs during landfall, while the location of the peak tangential wind at the top of the TCBL during this period is located on the onshore-flow side. A comparison of these observations with a numerical simulation of TC landfall shows many consistencies with the modeling study, though there are some notable differences that may be related to differences in the characteristics of the land surface between the simulation and the observations here.

Seismic instruments placed outside of spatially extensive hazard zones can be used to rapidly sense a range of mass movements. However, it remains challenging to automatically detect specific events of interest. Benford's law, which states that first non-zero-digit of given datasets follow a specific probability distribution, can provide a computationally cheap approach to identifying anomalies in large datasets and potentially be used for event detection. Here, we select raw seismic signals to derive the first-digit distribution. The seismic signals generated by debris flows, landslides, lahars, and glacier-lake-outburst floods follow Benford's law, while those generated by ambient noise, rockfalls, and bedload transports do not. Focusing on debris flows, our Benford's-law-based detector is comparable to an existing random forest method for the Illgraben, Switzerland, but requires only single station data and three non-dimensional parameters. We suggest this computationally cheap, novel technique offers an alternative for event recognition and potentially for real-time warnings.

The Central American Dry Corridor experienced five consecutive years of drought from 2015 to 2019. Here, we find that the severity of this drought was driven primarily by rainfall deficits in July-August. To determine if the magnitude of this event was outside the range of natural variability, we apply a statistical resampling method to observations that emulates internal climate variability. Our analyses show that droughts similar to the 2015-2019 event are possible, although extremely rare, even without anthropogenic influences. Persistent droughts in our ensemble are consistently linked to positive anomalies of the Caribbean Low-Level Jet. We also examine the effects of temperature on soil moisture during this drought using the Palmer Drought Severity Index and show that anthropogenic warming increases the likelihood of severe deficits. Multi-year droughts are likely to worsen by the end of the 21st century due to the compound effects of anthropogenic climate change.

This study investigates how climate sensitivity depends upon the spatial pattern of radiative forcing. Sensitivity experiments using a coupled ocean-atmosphere model were conducted by adding anomalous incoming solar radiation over the entire globe, Northern Hemisphere mid-latitudes, Southern Ocean, and tropics, respectively, with both positive and negative perturbation considered. The varied forcing patterns led to highly divergent climate sensitivities, with extratropical forcing inducing significantly more global-mean temperature change compared to tropical forcing. This dependence is particularly strong over the Southern Hemisphere, where the climate is nearly twice as sensitive to Southern Ocean forcing as tropical forcing. This dependence of climate sensitivity on the location of radiative forcing stems from covariations between lapse rate feedback, cloud feedback and tropospheric stability. These results contrast with the conventional SST-pattern effect in which tropical surface temperature changes regulate the climate sensitivity, and has important implications for geoengineering and understanding the mechanisms of paleoclimate change.

A document by Lei Yang. Click on the document to view its contents.

Phytoplankton primary productivity (PP) varies significantly over environmental gradients, particularly in physically-dynamic systems such as estuaries and coastal seas. As the Changjiang River runoff peaks during summer time, large environmental gradients appear in both the Changjiang estuary and adjacent East China Sea (ECS), likely driving significant variability in PP. As satellite models of PP often underperform in coastal waters, we aimed to develop a novel approach for net PP estimation in such a dynamic environment. Parallel in situ measurements of Fast Repetition Rate (FRR) fluorometry and carbon (C) uptake rates were conducted for the first time in this region during two summer cruises in 2019 and 2021. A series of 13C-incubations (n=31) were performed, with measured PP ranging from ~6 - 1700 mgC m-3 d-1. Net PP values were significantly correlated with salinity (r = 0.45), phytoplankton chlorophyll a (Chl-a, r = 0.88), Photosystem II (PSII) functional absorption cross-section (, r = -0.76) and maximum PSII quantum yield (, r = 0.59). Stepwise regression analysis showed that Chl-a and were the strongest predictors of net PP. A generalized additive model (GAM) was also used to estimate net PP considering nonlinear effects of Chl-a and . We demonstrate that GAM outperforms linear modelling approaches in predicting net PP in this study, as evidenced by a lower root mean square error (~140 vs. 250 mgC m-3 d-1). Our novel approach provides a high resolution means to examine carbon cycling dynamics in this important region.

A document by Zechao Zhuo. Click on the document to view its contents.

Direct geological information in Antarctica is limited to ice free regions along the coast, high mountain ranges or isolated nunataks. Therefore, indirect methods are required to reveal subglacial geology and heterogeneities in crustal properties, which are critical steps towards interpreting geological history. We present a 3D crustal model of density and susceptibility distribution in the Wilkes Subglacial Basin and the Transantarctic Mountains (TAM) based on joint inversion of airborne gravity and magnetic data. The applied “variation of information” technique enforces a coupling between gravity and magnetic sources to give an enhanced inversion result. Our model reveals a large-scale body located in the interior of the Wilkes Subglacial Basin interpreted as a batholithic intrusive structure, as well as a linear dense body at the margin of the Terre Adélie Craton. Density and susceptibility relationships are used to inform the interpretation of petrophysical properties and the reconstruction of the origin of those crustal blocks. The petrophysical relationship indicates that the postulated batholitic intrusion is granitic, but independent from the Granite Harbour Igneous Complex previous described in the TAM area. Emplacement of a large volume of intrusive granites can potentially elevate local geothermal heat flow significantly. Finally, we present a tectonic evolution sketch based on the inversion results, which includes development of a passive continental margin with seaward dipping basalt horizons and magmatic underplating followed by two distinct intrusion events in the Wilkes Subglacial Basin with Pan-African ages (700 - 551 Ma) and Ross ages (550 - 450 Ma).

The Outer Continental Shelf of the Gulf of Mexico (GOM) is populated with numerous oil and natural gas (ONG) platforms which produce NOx (NOx = NO + NO2), a major component of air pollution. The Bureau of Ocean Energy Management (BOEM) is mandated to ensure that the air quality of coastal states is not degraded by these emissions. As part of a NASA-BOEM collaboration, we conducted a satellite data-based analysis of nitrogen dioxide (NO2) patterns and trends in the GOM. Data from the OMI and TROPOMI sensors were used to obtain 18+ year records of tropospheric column (TrC) NO2 in three GOM regions: 1) Houston urban area, 2) near shore area off the Louisiana coast, and a 3) deepwater area off the Louisiana coast. The 2004-2022 time series show a decreasing trend for the urban (-0.027 DU/decade) and near shore (-0.0022 DU/decade) areas, and an increasing trend (0.0019 DU/decade) for the deepwater area. MERRA-2 wind and TROPOMI NO2 data were used to reveal several NO2 hotspots (up to 25% above background values) under calm wind conditions near individual platforms. The NO2 signals from these deepwater platforms and the high density of shallow water platforms closer to shore were confirmed by TrC NO2 anomalies of up to 10%, taking into account the monthly TrC NO2 climatology over the GOM. The results presented in this study establish a baseline for future estimates of emissions from the ONG hotspots and provide a methodology for analyzing NO2 measurements from the new geostationary TEMPO instrument.

Because they are conceptually unable to consider events at the sub-annual scale, probabilistic flood analyses based on annual maxima (AM) underestimate the actual frequency of frequent floods (with return periods under 5 years), so that peaks-over-threshold (POT) approaches should be preferred. While this has been acknowledged for decades, frequent floods are still estimated too often using AM, probably because the procedure is simpler, and AM series are longer and easier to obtain. However, the negative bias incurred when performing flood frequency with AM can be severe. This affects fields such as river restoration, stream ecology, and fluvial geomorphology, which require a correct characterization of frequent floods. Using hundreds of U.S. watersheds with natural flow regimes, across different climatic and geomorphic conditions, we systematically study the variability in how AM frequency analyses underestimate frequent floods, finding clear spatial patterns. Exploiting the duality between the Generalized Extreme Value and the Generalized Pareto distributions (used for modeling AM and POT, respectively), we identify the drivers of frequent-flood underestimation, studying the influence of the distributions’ shapes. In turn, with the support of an optimal feature-selection technique, we determine the physical drivers explaining underestimation, from a wide spectrum of basin descriptors, investigating their linkages with the distributional characteristics that affect underestimation. A theoretical relationship is derived to infer the underestimation rate, allowing for post-hoc correction of AM-predicted frequent floods, without the need to perform POT frequency analyses. However, this approach underperforms at sites with mixed flood populations.

Taking advantage of a large ensemble of Convection Permitting-Regional Climate Models on a pan-Alpine domain and of an object-oriented dedicated analysis, this study aims to investigate future changes in the high-impact fall Mediterranean Heavy Precipitation Events at high warming levels. We identify a robust multi-model agreement for an increased frequency from central Italy to the northern Balkans combined with a substantial extension of the affected areas, a dominant influence of the driving Global Climate Models for projecting changes in the frequency, an increase in intensity, area, volume and severity over the French Mediterranean. However, large quantitative uncertainties persist despite the use of convection-permitting models, with no clear agreement in frequency changes over southeastern France and a large range of plausible changes in events’ properties, including for the most intense events. Model diversity and international coordination are still needed to provide policy-relevant climate information regarding precipitation extremes.

A document by Antoine Lucas. Click on the document to view its contents.

The recovery of the thermosphere after a strong geomagnetic storm on 12 May 2021 is investigated using lower and middle thermospheric temperature (Tdisk), ratio of atomic oxygen and molecular nitrogen column densities (O/N2), cooling due to Nitric Oxide (NO), and model simulations. The peak influence of the geomagnetic storm lasted about five hours and generated latitudinal gradients in Tdisk and O/N2. Following the storm, the latitudinal gradient in temperature recovered faster compared to that of O/N2. Measured NO-cooling rate and simulated NO-densities are enhanced on the storm day compared to a quiet-day, consistent with a rapid recovery in temperatures. Based on this, we conclude that the faster recovery of the Tdisk latitudinal gradient is driven by the combined effect of NO cooling and strong thermal conductivity. Furthermore, the slower recovery of the O/N2 latitudinal gradients can be attributed to the lack of poleward advection after the storm.

The Earth surface Mineral dust source InvesTigation (EMIT) is a remote visible to shortwave infrared (VSWIR) imaging spectrometer that will map the mineralogy of Earth's mineral dust forming regions. EMIT was launched to the International Space Station in July 2022, beginning a year-long mission. This article describes the EMIT spectroradiometric calibration and on-orbit validation experiments. EMIT achieves several notable firsts for an instrument of its class. It demonstrates successful on-orbit adjustments of Focal Plane Array (FPA) alignment with sub-micron precision. It offers spectral uniformity better than 98%. Optical artifacts in the measurement channels are at least three orders of magnitude below the primary signal. EMIT consists of just six optical elements, no shutter, and no onboard calibration systems. With this simple and efficient design, EMIT satisfies the stringent needs for the next generation of VSWIR imaging spectrometers.

The Korean Collision Belt originally constituted a single coherent southwards-thinning tectonic wedge formed by accretion of the Qinling-type Barrovian metamorphic Jingok and Samgot units (Yeoncheon Complex) and Taean Formation onto the Sino–Korean Craton’s southern extension (Precambrian Gyeonggi Massif) while being underthrust by the South China Block. Detailed structural geological study and 40Ar/39Ar laser-probe dating of 47 mineral single-grain and 2 whole-rock samples with both syn-collisional peak metamorphic and retrograde mineral assemblages reveal a prolonged tectonic evolution from the Devono–Carboniferous pre-collisional stage (375–370 Ma; ~315 Ma) to the Midde–Late Jurassic reactivation of the Permian–Triassic wedge during the second major exhumation phase of the Gyeonggi Massif (194–165 Ma). The latest Permian to Late Triassic main orogeny comprises three distinct correlated tectono-metamorphic phases. Essentially concordant (pseudo-)plateau ages (255.2–249.9 ± 0.4–0.9 Ma, 1σ) for main-phase-fabric-forming muscovite and biotite in the garnet, staurolite and kyanite zones and discordant late-stage andalusite-quartz veins (Jingok Unit) show fast cooling during exhumation from ~30 km to ≤12.5 km. Hornblendes (248.8–247.0 ± 0.6–1.6 Ma, 1σ) in the underlying higher-grade metamorphic, deeper underthrust Samgot Unit show later cooling. Fabric asymmetry implies cooling and age differences stem from (S)SE-ward exhumation along low-angle ductile normal faults. Incipient exhumation of mid-Triassic eclogites (Hongseong Belt) induced strong tectono-metamorphic reworking of the overriding plate (242–237 Ma; Yeoncheon Complex, Taean Formation, Gyeonggi Massif). Structurally downwards increasing resetting of mica (225–220 Ma), retrogression and overprinting by top-to the-north post-main-phase-shear constrains the Gyeonggi Massif’s further exhumation and cooling. Key Points:Korean Collision Belt: a southwards-tapering tectonic wedge with discrete tectono-metamorphic phases at 255–247, 245–237, 225–220 Ma255–247 Ma: fast cooling, rapid exhumation, top-to-SE normal shear; 225–220 Ma: downwards increase retrogression, top-to-N normal shear245–237 Ma: strong reworking; exhumation mid-Triassic eclogite; 194–165 Ma: final metamorphic reactivation and top-to-N normal shear