GRL

Climate models suffer from longstanding precipitation biases, much of which has been attributed to their atmospheric component owing to unrealistic parameterizations. Here we investigate precipitation biases in 37 Atmospheric Model Intercomparison Project Phase 6 (AMIP6) models, focusing on the Indo-Pacific region during boreal summer. These models remain plagued by considerable precipitation biases, especially over regions of strong precipitation. In particular, 22 models overestimate the Asian-Pacific monsoon precipitation, while 28 models underestimate the southern Indian Ocean Intertropical Convergence Zone precipitation. The inter-model spread in summer precipitation is decomposed into Empirical Orthogonal Functions (EOFs). The leading EOF mode features an anomalous anticyclone circulation spanning the Indo-northwest Pacific oceans, which we show is energized by barotropic conversion from the confluence of the background monsoonal westerlies and trade-wind easterlies. Our results suggest precipitation biases in atmospheric models, though caused by unrealistic parameterizations, are organized by dynamical feedbacks of the mean flow.

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.

The South Asian summer monsoon strongly modulates regional temperature and humidity. While extreme dry heat peaks in the pre-monsoon season, recent literature suggests that extreme humid heat can continue to build throughout the monsoon season. Here we explore the influence of monsoon onset and subseasonal precipitation variability on the occurrence of extreme wet bulb temperatures (Tw) across South Asia. We find that extreme Tw events often occur on rainy days during the monsoon season. However, the influence of precipitation on Tw varies with the background climatology of surface specific humidity. In climatologically drier areas, positive Tw anomalies tend to occur when precipitation increases due to either early onset or wet spells during the monsoon. In contrast, in climatologically humid areas, positive Tw anomalies occur during periods of suppressed precipitation, including both delayed onset and dry spells during the monsoon.

Seismic surveys along subduction zones have identified anomalously high ratio of P- to S-wave velocity (V P /V S ) in the subducting oceanic crust that are possibly due to the presence of pore water. Such interpretations postulate that the pore structure is homogeneous at the scale of the seismic wavelength. Here we present the first statistical evidence of a heterogeneous pore structure in oceanic crust at scales larger than laboratory samples. The spatial correlation of measured bulk density profiles of the crustal section of the Samail ophiolite suggests that the pore structure is heterogeneous at scales smaller than ∼1 m. Wave-induced fluid flow cannot follow the loading during the seismic wave propagation at this estimated heterogeneity, which implies that fluid-filled microscopic pores and cracks have a limited impact on the observed high V P /V S anomalies in the subducting oceanic crust. Large-scale cracks may therefore play an important role in shaping these anomalies.

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 (L ∼ 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.

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 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, for a dominant influence of the driving Global Climate Models for projecting changes in the frequency, and for 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.

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.

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.

Ultra-low-frequency (ULF) waves emerge as pivotal factors in elucidating the mechanisms that drive the intricate dynamics of radiation belt electrons within the plasmasphere and plasmaspheric plumes. Utilizing THEMIS data from September 2012 to September 2017, we conducted a comprehensive statistical analysis of Pc4-5 ULF waves within and outside the plasmaspheric plume. Our findings reveal a distinctive dawn-dusk asymmetry in occurrence rate and wave power of poloidal mode waves in the absence of the plume, resembling the toroidal mode asymmetry observed. Poloidal mode waves exhibit a higher likelihood of formation within the plume, while the toroidal mode waves show the opposite trend, contributing to the elevated dusk-side occurrence rate of poloidal mode waves. Moreover, both wave modes within the plume demonstrate lower peak frequencies compared to waves outside the plume. The global distribution of wave power within the plume suggests higher power at noon than on the dusk side.

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.

Subtle bedrock depressions called gnammas allow the water in ephemeral pools to maintain contact with bare rock, thus serving as natural rock-weathering experiments. Following filling by precipitation, evaporation is often assumed to be the sole process of water loss from gnammas. We evaluated this assumption by monitoring evolving stable isotope compositions of gnamma waters hosted in granite of Colorado's Front Range. Surprisingly, we found that a significant fraction of the water was lost by seepage through the underlying bedrock. Seepage dominated, with only 10%–20% loss by evaporation. We propose a conceptual model of gnamma formation in which enhanced weathering of the bedrock beneath the gnamma increases the water holding capacity and permeability of the underlying rock that in turn promotes efficient water loss through seepage and further weathering of the surrounding rock. This model has implications for bare-rock weathering and hence the evolution of landscapes over geologic timescales.

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.

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 (<2.0 K or g kg−1). 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.

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.

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 km3 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.

Changes in the volume transport of Atlantic water into the Arctic Ocean can affect the heat and mass balance in the central Arctic Ocean. To understand the impacts of Arctic storms on the inflow through Fram Strait, we implemented the NEMO ocean model for the Arctic Ocean, to simulate the decadal variations of the water volume transport through Fram Strait. The simulations suggest that the water inflow tends to be weaker in the decades of the 1960 and 2010s but stronger in the 1980s. The decadal variation is associated with decadal variability of the storm density in the Greenland Sea. When there is an increased storm density near Fram Strait, the southerly wind anomalies dominate the Atlantic water pathway. As a response, there is an increased Atlantic inflow through Fram Strait.

Vegetation Optical Depth (VOD) has emerged as a valuable metric to quantify water stress on vegetation's carbon uptake from a remote sensing perspective. However, existing spaceborne microwave remote sensing platforms face limitations in capturing the diurnal VOD variations and global products lack site-level validation against plant physiology. To address these challenges, we leveraged the Global Navigation Satellite System (GNSS) L-band microwave signal, measuring its attenuation by the canopy of a temperate broadleaf forest using a pair of GNSS receivers. This approach allowed us to collect continuous VOD observations at a sub-hourly scale. We found a significant seasonal-scale correlation between VOD and leaf water potential. The VOD diurnal amplitude is affected by soil moisture, plant transpiration and leaf surface water. Additionally, VOD can help independently estimate plant transpiration. Our findings pave the way for a deeper understanding of response of the vegetation to water stress at finer temporal scales.

The elimination of rain evaporation in the planetary boundary layer (PBL) has been found to lead to convective self-aggregation (CSA) even without radiative feedback, but the precise mechanisms underlying this phenomenon remain unclear. We conducted cloud-resolving simulations with two domain sizes and progressively reduced rain evaporation in the PBL. Surprisingly, CSA only occurred when rain evaporation was almost completely removed. The additional convective heating resulting from the reduction of evaporative cooling in the moist patch was found to be the trigger, thereafter a dry subsidence intrusion into the PBL in the dry patch takes over and sets CSA in motion. Temperature and moisture anomalies oppose each other in their buoyancy effects, hence explaining the need for almost total rain evaporation removal. We also found radiative cooling and not cold pools to be the leading cause for the comparative ease of CSA to take place in the larger domain.

Understanding variations in catchment evapotranspiration (E C) is critical as it directly affects water availability for humans and ecosystems. Previous studies found increases in E C in Central Europe over recent decades, but fixed study periods may not fully reveal inter-decadal hydroclimatological variability. We performed a multi-temporal trend analysis of water balance-derived E C for 461 German catchments and the period 1964–2019. We accounted for previously often neglected changes in storage and uncertainties in precipitation. E C generally increased throughout Germany during 1970s–2000s (>2 mm year−2), while it showed milder changes and decreases afterward. These variations were robust to uncertainties in precipitation (median relative uncertainty of 26%) and broadly coherent with sparse plot-scale data. Variations in E C were related with variations in precipitation and radiation, with a potentially increasing influence of precipitation after 2000s. These findings provide a reference for synthesizing current knowledge on variations in E C and their uncertainties.

In airborne data or model outputs, clouds are often defined using information about Liquid Water Content (LWC). Unfortunately LWC is not enough to retrieve information about the dynamical boundary of the cloud, that is, volume of turbulent air around the cloud. In this work, we propose an algorithmic approach to this problem based on a method used in time series analysis of dynamical systems, namely Recurrence Plot (RP) and Recurrence Quantification Analysis (RQA). We construct RPs using time series of turbulence kinetic energy, vertical velocity and temperature fluctuations as variables important for cloud dynamics. Then, by studying time series of laminarity (LAM), a variable which is calculated using RPs, we distinguish between turbulent and non-turbulent segments along a horizontal flight leg. By selecting a single threshold of this quantity, we are able to reduce the number of subjective variables and their thresholds used in the definition of the dynamical cloud boundary.