Catálogo de publicaciones - revistas

<jats:title>Abstract</jats:title><jats:p>To improve the forecast accuracy of numerical weather prediction, it is essential to obtain better initial conditions by combining simulations and available observations via data assimilation. It has been known that a part of observations degrade the forecast accuracy. Detecting and discarding such detrimental observations via proactive quality control (PQC) could improve the forecast accuracy. However, conventional methods for diagnosing observation impacts require future observations as a reference state and PQC cannot be real‐time in general. This study proposes using machine learning (ML) trained by a time series of analyses to obtain a reference state without future observations and enable real‐time ML‐based PQC. This study presents proof‐of‐concept using a low‐dimensional dynamical system. The results indicate that ML‐based and model‐based estimates of observation impacts are generally consistent. Furthermore, ML‐based real‐time PQC successfully improves the forecast accuracy compared to a baseline experiment without PQC.</jats:p>

<jats:title>Abstract</jats:title><jats:p>Craters on Mars are a window into Mars' past and the time they were emplaced. Because the crust is heated and shocked during impact, craters can demagnetize or magnetize the crust depending on the presence or absence of a dynamo field at the time of impact. This concept has been used to constrain dynamo timing. Here, we investigate magnetic anomalies associated with craters larger than 150 km. We find that most of those craters, independent of age, exhibit demagnetization signatures in the form of a central magnetic low. We demonstrate a statistically significant association between such signatures and craters, and hypothesize that the excavation of strongly magnetic crustal material may be an important contribution to the dominance of demagnetized craters. This finding implies that the simple presence or absence of crater demagnetization signatures is not a reliable indicator for the activity of the Martian dynamo during or after crater formation.</jats:p>

<jats:title>Abstract</jats:title><jats:p>Induced seismicity represents a negative drawback during subsurface exploitation for geothermal energy production. Understanding the triggering mechanisms of induced earthquakes can help implement effective seismic hazard mitigation actions. Among the triggering mechanisms, the pore fluid pressure is of primary importance. Here we provide a static picture of the excess pore fluid pressure at the hypocenters of a seismic sequence induced at the deep geothermal field in St. Gallen, Switzerland, in July 2013. We find that in addition to the Coulomb static stress change, fluids play a key role in promoting the sequence. The estimated excess pore fluid pressure for approximately half of the earthquakes is higher than the injection pressure necessary during the well control phase to fight the unexpected gas kick, that accidently occurred during field operations when a trap of overpressured gas was broken.</jats:p>

<jats:title>Abstract</jats:title><jats:p>Radial diffusion (RD) induced by ULF waves can contribute to particle acceleration and scattering. Past global simulations that incorporate RD often use dipole magnetic fields, which could not realistically reveal the role of RD. To better understand the effects of RD and identify whether a background magnetic field model matters in understanding the ring current dynamics in response to RD, we simulate a storm event with different magnetic configurations using a global kinetic ring current model. Results indicate that RD can effectively diffuse protons of hundreds of keV to inner regions (<jats:italic>L</jats:italic> ∼ 3.5), especially in recovery phase. Comparisons with in‐situ observations demonstrate that simulations with TS05 overall capture both the intensity and variations of proton fluxes with the aid of RD, whereas that with a dipole field significantly overestimates low‐L region fluxes. This study implies adopting realistic magnetic fields is important for correctly interpreting the role of RD.</jats:p>

<jats:title>Abstract</jats:title><jats:p>Dipolarization fronts (DFs) are widely believed to host energy conversion processes. However, which mechanism is responsible for the energy conversion is still obscure. Using data from the Magnetospheric Multiscale mission, a current sheet is observed at a DF. This current sheet is caused by interchange instability bending the edge of the DF. Inside the current sheet, Hall electromagnetic field, super Alfvénic electron jets, demagnetization of ions and electrons, strong energy conversion, and steady ion flow and temperature are observed, indicating an electron‐only reconnection at the DF. The duskward plasma flow, which may be deflected by the DF, compresses the bent edges of the DF. As a result, the width of the current sheet between two adjacent bent edges of the DF reduces, and then reconnection begins. Our observations give direct evidence that magnetic reconnection results in energy conversion at a DF.</jats:p>

<jats:title>Abstract</jats:title><jats:p>An array of atmospheric profile observations consists of three‐dimensional vectors representing pressure, temperature, and humidity, with each profile forming a continuous curve in this three‐dimensional space. In this paper, the Signature method, which can quantify a profile's curve, was adopted for the atmospheric profiles, and the accuracy of profile representations was investigated. The description of profiles by the signature was confirmed with adequate accuracy. The machine‐learning‐based model, developed using the signature, exhibited a high level of annual accuracy with minimal absolute mean differences in temperature and water vapor mixing ratio (&lt;2.0 K or g kg<jats:sup>−1</jats:sup>). Notably, the model successfully captured the vertical structure and atmospheric instability, encompassing drastic variations in water vapor and temperature, even during intense rainfall. These results indicate the Signature method can comprehensively describe the vertical profile with information on how ordered values are correlated. This concept would potentially improve the representation of the atmospheric vertical structure.</jats:p>

<jats:title>Abstract</jats:title><jats:p>In around 1990, significant shifts occurred in the spatial pattern and temporal evolution of the El Niño‐Southern Oscillation (ENSO), with these shifts showing asymmetry between El Niño and La Niña phases. El Niño transitioned from the Eastern Pacific (EP) to the Central Pacific (CP) type, while La Niña's multi‐year (MY) events increased. These changes correlated with shifts in ENSO dynamics. Before 1990, El Niño was influenced by the Tropical Pacific (TP) ENSO dynamic, shifting to the Subtropical Pacific (SP) ENSO dynamic afterward, altering its spatial pattern. La Niña was influenced by the SP ENSO dynamic both before and after 1990 and has maintained the CP type. The strengthened SP ENSO dynamic since 1990, accompanied by enhanced precipitation efficiency during La Niña, make it easier for La Niña to transition into MY events. In contrast, there is no observed increase in precipitation efficiency during El Niño.</jats:p>

<jats:title>Abstract</jats:title><jats:p>The February 2023 Turkey‐Syria Earthquake doublet ruptured multiple segments of the East Anatolian Fault (EAF) Zone. Dominating seismicity focal mechanism shifted dramatically from strike‐slip to normal‐faulting after the doublet. To better understand this shift, here we derived a comprehensive 3D co‐seismic displacement field and performed the stress analysis. Abundant space geodetic data were used to generate high‐resolution 3D surface displacement, which provide tight constraints on fault geometry, slip distribution and stress field. Together with stress inversion from aftershock focal mechanisms, we show that the principal stress direction rotation in the region with the most normal‐faulting aftershocks is the staggering 29°. The induced heterogenous stress may explain the shift of the dominant focal mechanism toward normal faulting. We suggest that the extensional horsetail splay faults, likely formed through geologic time scale related to the releasing bend on the EAF, are the hosts of most of the normal faulting aftershocks.</jats:p>

<jats:title>Abstract</jats:title><jats:p>There has been an acceleration of groundwater loss in the Great Basin (GB) of the western U.S. as determined from total water storage (TWS) measurements from the GRACE/FO satellite missions. From 2002 to 2023, there was a loss of TWS in the GB of ∼68.7 km<jats:sup>3</jats:sup> which is more than six times the current volume of the Lake Mead Reservoir. In this arid/semi‐arid region, groundwater is the primary factor contributing to the decade‐scale decline in TWS. Stronger declining trends are found in the western versus the eastern GB. Snow loading is the major cause of seasonal fluctuations of TWS in the GB. Despite annual replenishment of groundwater by snow, the downward trend persists even in notable snow years. Likely causes include declining snow mass, upstream water diversions and increased evaporation/sublimation due to increasing temperatures. Dire consequences for humans and wildlife are associated with this large loss of groundwater.</jats:p>

<jats:title>Abstract</jats:title><jats:p>The hyporheic zone is a hotspot for biogeochemical cycling where interactions with mineral metals preserve the release and biodegradation of organic matter (OM). A small fraction of OM can still be exchanged between localized sediments and the overlying water column, and recent evidence suggests there exists a longitudinal structuring in sediment dissolved OM (DOM) chemistry across the continental United States (CONUS). In this study, we tested a hypothesis that water extractable sediment DOM chemistry could be explained by sediment metal contents and integrative watershed scale features at the CONUS scale. Crowdsourced samples were characterized for high resolution mass spectrometry and coupled with sediment metals determined via x‐ray fluorescence as well as with land cover and soil elemental information obtained from national databases. Our results highlight weak relationships between DOM chemistry and elemental composition at the CONUS scale indicating limited transferability of organo‐metal linkages into multi‐scale hydrobiogeochemical models.</jats:p>