Choraghe et al. (2021), based on a study of the recovery phase of the SYM-H index of 31 extreme geomagnetic storms, have recently concluded that the hyperbolic decay function is only able to explain the complete recovery phase of about one third of events and that both the exponential or the hyperbolic decay functions fail to explain the late recovery phase of storms. Furthermore, they propose a linear function to model the late recovery phase and claim that the proposed model could throw new light on the relative importance of different physical processes involved during the complete recovery phase of extreme storms. We assert that \citeA{Choraghe} conclusions regarding the recovery phase of extreme storms analysis are incorrect and in particular are based on a misunderstanding of the nature of the evolution of the SYM-H index and the energy balance of the ring current.

Production of food in space via photosynthetic crops similar to the ones we use on Earth requires profligate use of resources that will be in short supply in early long duration space missions. We demonstrate that production of bulk calories via chemotrophic single cell organisms is 2 to 3 orders of magnitude less expensive in terms of energy, volume, and water usage than via photosynthetic crops. In addition we survey the history and current state of the art in production of food from non-photosynthetic single cell organisms.

Deeper flows through bedrock in mountain watersheds could be important but lack of data to characterize bedrock properties and link flow paths to snow-dynamics limits understanding. To address data scarcity, we combine a previously published integrated hydrologic model of a snow-dominated, headwater basin with a new method for dating baseflow age using dissolved gas tracers SF, N, Ar. The original flow model produces shallow groundwater flow (median depth 6 m), very young stream water and is unable to reproduce observed SF concentrations. To match the observed gas data, bedrock permeability is increased to allow a larger fraction of deeper groundwater flow (median depth 110 m). Results indicate that interannual variability in baseflow age (3-12 y) is dictated by the volume of seasonal interflow. Deeper groundwater flow remains stable (11.7±0.7 y) as a function of the ratio of recharge to bedrock hydraulic conductivity (R/K), where recharge is dictated by long-term climate and land use. With sensitivity experiments, we show that information gleaned from gas tracer data to increase bedrock hydraulic conductivity effectively moves this alpine basin away from shallow, topographically controlled groundwater flow with baseflow age relatively insensitive to water inputs (high R/K), and closer toward recharge-controlled conditions, in which a small shift toward a drier future with less snow accumulation will alter the groundwater flow system and increase baseflow age (low R/K). Work stresses the need to explore alternative methods characterizing bedrock properties in mountain basins to better quantify deeper groundwater flow and predict their hydrologic response to change.

Gravity wave activity in the lower and middle atmosphere of Mars during the global dust storm of 2018 has been studied for the first time using a high-resolution (gravity wave resolving) general circulation model. Dust storm simulations were compared with those utilizing the climatological distribution of dust in the absence of storms. Both scenarios are based on observations of the dust optical depth by the Mars Climate Sounder instrument on board the Mars Reconnaissance Orbiter. The modeling reveals a reduction of the wave activity by a factor of two or more in the lower atmosphere, which qualitatively agrees with recent observations. It is associated with a decline of gravity wave generation due to baroclinic and convective stabilization of the Martian troposphere induced by the increased amount of airborne aerosols during the storm. Contrary to the decrease of GW activity in the lower atmosphere, wave energy and momentum fluxes in the middle atmosphere increase by approximately the same factor. This enhancement of gravity wave activity is caused by the changes in the large-scale circulation, most importantly in the mean zonal wind, which facilitate vertical wave propagation by allowing for a greater portion of gravity wave harmonics originated in the lower atmosphere to avoid filtering on their way to upper layers.

Inter-annual sea-level variations of up to 20 mm are superimposed upon the global average sea-level rise (~3 mm/yr) from human-caused global warming. These variations affect the degree of coastal flooding, and related damage, during the highest annual tides. Along the Atlantic coast of the United States, such inter-annual sea-level variations have been attributed to several atmospheric and oceanographic processes. In the present analysis, detrended tide gauge data isolate inter-annual interannual variations that can be reconstructed using Fourier analysis of a limited number of coefficients based on frequencies of lunar orbit ( and precessions) combined with . Although a causal relationship between such forcings and extreme sea levels remains elusive, the reconstructions may provide an effective method for projections of occurrence of extreme sea levels. Two reconstructions project that anomalously high sea levels may occur in the late 2020s, mid 2050s, early 2060s, early 2070s and late 2090s.

According to TRMM and GPM satellite precipitation composites, a broad maritime area over the far eastern Tropical Pacific and western Colombia houses one of the rainiest spots on Earth. This study aims to present a suite of mechanistic drivers that help create such a world-record breaking rainy spot. Previous research has shown that this oceanic and nearly-continental precipitation maximum has a strong early morning precipitation peak and development of a high density of mesoscale convective systems. We examined new and unique observational evidence highlighting the role of both dynamical and thermodynamical drivers in the activation and duration of organized convection. Results show the existence of a rather large combination of mechanisms, including: (1) dynamics of the Choco (ChocoJet) and Caribbean Low-Level Jets along their confluence zone, including the Panama semi-permanent low; (2) land breeze favors ChocoJet deceleration offshore, enhancing the nighttime and early morning low-level convergence; (3) vertical wind shear and tilting of vertical wind shear into vorticity lines that interact with convective outflows; (4) action of mid-level gravity waves, which support the strong diurnal variability; (5) mesoscale convective vortices related to subsidence in the stratiform region in long lasting MCSs reinforcing (3); and (6) the likely role of land surface-atmosphere interactions and the rainforest over western Colombia. This study emphasizes the multi-scale environmental processes associated with the formation of one of the rainiest spots on Earth and showcases new observations gathered during the Organization of Tropical East Pacific Convection (OTREC; August-September, 2019) which support the outlined mechanisms.

In Arctic winter and spring 2020, the stratospheric temperatures were exceptionally low for a long time period and the polar vortex was very stable. As a consequence, significant ozone depletion occurred in Northern polar regions in spring 2020. Here, we present simulations by the Chemical Lagrangian Model of the Stratosphere (CLaMS) that addresses the development of chlorine compounds and ozone in the polar stratosphere in 2020. The simulation is able to reproduce relevant observations which is shown by comparisons with MLS, ACE-FTS and OMI data. Although the concentration of chlorine and bromine compounds in the polar stratosphere has decreased by more than 10% compared to the peak values around the year 2000, the meteorological conditions in winter and spring 2020 caused an unprecedented ozone depletion. The simulated lowest ozone mixing ratio was around 0.05 ppmv and the ozone depletion in the vortex core in the lower stratosphere reached 133 Dobson Units, which is more than the loss in the years 2011 and 2016 that had the largest Arctic ozone depletion so far.

A vast majority of marine geological research is based on academic seismic data collected with single-channel systems or short-offset multi-channel seismic cables, which often lack reflection moveout for conventional velocity analysis. Consequently, our understanding of earth processes often relies on seismic time sections, which hampers quantitative analysis in terms of depth, formation thicknesses, or dip angles of faults. In order to overcome these limitations, we present a robust diffraction extraction scheme that models and adaptively subtracts the reflected wavefield from the data. We use diffractions to estimate insightful wavefront attributes and perform wavefront tomography to obtain laterally resolved seismic velocity information in depth. Using diffraction focusing as a quality control tool, we perform an interpretation-driven refinement to derive a geologically plausible depth-velocity-model. In a final step, we perform depth migration to arrive at a spatial reconstruction of the shallow crust. Further, we focus the diffracted wavefield to demonstrate how these diffraction images can be used as physics-guided attribute maps to support the identification of faults and unconformities. We demonstrate the potential of this processing scheme by its application to a seismic line from the Santorini-Amorgos Tectonic Zone, located on the Hellenic Volcanic Arc, which is notorious for its catastrophic volcanic eruptions, earthquakes, and tsunamis. The resulting depth image allows a refined fault pattern delineation and, for the first time, a quantitative analysis of the basin stratigraphy. We conclude that diffraction-based data analysis is a decisive factor, especially when the acquisition geometry of seismic data does not allow conventional velocity analysis.

Anthropogenic subsurface urban heat islands (SUHIs) in groundwater under cities are known worldwide. SUHIs are potentially threats to springs because much spring fauna, like trout, amphipods, and rare plants, is cold stenothermal. The city of Minneapolis, Minnesota, USA, has a SUHI documented by the temperature of an underground spring, dubbed “Little Minnehaha Falls,” inside Schieks Cave, which is located 23 m below the central core of the city. In 2000 the temperature of that spring was elevated 11°C above regional background groundwater temperatures (8°C) at this latitude (45°N). A thermometric survey of the cave and nearby tunnel seepages in 2007 found that an abandoned drill-hole through the bedrock ceiling of the cave was discharging groundwater with a temperature of 17.9°C. By comparison, groundwater in the deep water-table below the cave was closer to natural background temperatures for the region. The unusually warm groundwater was thereby localized to the strata above the cave. This is the strongest signal of anthropogenic groundwater warming in the state of Minnesota and is attributed to vertical heat conduction from basements and pavements. Minneapolis is unique among SUHIs in that a cave forms a natural collection gallery deep below the city surface, whereas the literature is almost exclusively based on data from observation wells.

Over-the-horizon radar (OTHR) systems operating in the high-frequency (HF) band (3-30MHz) are unique in their ability to detect targets at extreme ranges, offering cost-effective large area surveillance. Due to their reliance on the reflective nature of the ionosphere in this band, OTHR systems are extremely sensitive to ionospheric conditions and can expect significant variations in operational performance. At high latitudes, the presence of auroral enhancements in the E-Region electron density can substantially modify the coverage area and frequency management of OTHR systems. In this study, HF raytracing is utilized to investigate these impacts for a hypothetical radar under different auroral conditions simulated using the Empirical Canadian High Arctic Ionospheric Model (E-CHAIM). Aurora were seen to increase maximum useable frequency (MUF) from 8.5 MHz to 26 MHz whilst also reducing median available target range from 2541 km to 1226 km, for the greatest differences. Target interception showed large variations in path coverage of between 33-115% and 0-107% for two flight paths tested with precipitation toggled. Two distinct propagation modes were observed with aurora, noted as the F-E ducted and Auroral E-modes. Long-range coverage provided by the auroral F-E ducted mode was of limited capacity with low solar activity due to the reduced NmF2. F-mode propagation transitioned to the dominating Auroral E-mode between Auroral Electrojet (AE) index values of 50- and 200-nT. The significant variations in both frequency and coverage observed within this study highlight some aspects of the importance of considering aurora in OTHR modelling and design.

China’s lunar exploration missions have developed and progressed for more than 13 years. In these missions, Precise Orbit determination (POD) guarantees successful execution of Chang’e missions, and the basis for further scientific investigations using radio science data; for example, recovering the lunar gravity field to explore the inner structure and detect craters to study the evolutionary history of the moon. This paper briefly reviews the Chang’e series mission orbit and tracking measurements. We reprocessed the tracking data and comprehensively summarized the evolution in POD accuracy and the tracking system precision from the Chang’e 1 to Chang’e 4 missions. Our results show that the accuracy of Chang’e 5T1 Doppler measurements reach about 0.35 mm/s and the two-way range measurements 0.2 m, with respect to 1.1 mm/s and 1.6 m for Chang’e 1. The Chang’e 4 relay satellite achieved POD accuracy at the meter level, in contrast to the half-kilometer level accuracy achieved during the Chang’e 1 mission. We can clearly see that the POD performance and precision of the Chang’e spacecraft are continuously improving. This research is a reference for future Chinese Lunar missions, as well as Chinese Mars and asteroid explorations.

Near-field observations of tsunami waves generated by the Mw9.2 1964 Alaska earthquake reveal a complex relationship between coseismic slip and the tsunami wavefield in the source area. The documented times and amplitudes of first arrivals, measured runup heights and inundation areas along the coasts of the Kenai Peninsula and Kodiak Island show that secondary splay faults played an important role in generating destructive tsunami waves. We find that a splay fault extending to about 150°W is required to fit tsunami first arrivals on the Kenai Peninsula, but that the splay fault did not rupture along the entire length of the Kenai Peninsula. This extent supports the connection of splay faulting to a persistent Prince William Sound asperity. Our results also show that the contribution of coseismic horizontal displacements into the initial tsunami wave field does not change the pattern of tsunami arrivals much, but increases the amplitude. The coseismic deformation model of Suito and Freymueller (2009) explains the pattern of tsunami arrivals in the Kodiak Island region well, indicating that it provides a good estimate of slip on the megathrust in the Kodiak asperity. The sensitivity of the near-field arrival information to the coseismic slip model shows that such data are important in distinguishing between slip on splay faults and on the megathrust, and in discriminating between competing slip models.

The Walker circulation connects the regions with deep atmospheric convection in the western tropical Pacific to the shallow-convection, tropospheric subsidence, and stratocumulus cloud decks of the eastern Pacific. Although important to many elements of the Earth system such as tropical precipitation, and cloud feedback processes, interactions between large-scale tropical circulations and these cloud systems are still not well understood. The purpose of this study is to better understand the multi-scale interactions between the Walker circulation, cloud systems, and interactive radiation. To do this we simulate a mock-Walker Circulation with a full-physics General Circulation Model (GCM) using idealized boundary conditions. Our experiments use a doubly-periodic domain with grid-spacing of 1, 2, 25, and 100km. We thus span the range from General Circulation Models (GCMs) to Cloud-system Resolving Models (CRMs). Our model is derived from the Geophysical Fluid Dynamics Laboratory (GFDL) atmospheric GCM (AM4.0). Our GCM-like experiments have a large low-level cloud fraction while the CRM-like experiments have more upper-level clouds. This difference leads to opposite atmospheric responses to changes in the longwave cloud radiative effect (LWCRE). Active LWCRE lead to increased precipitation for our GCMs, but decreased precipitation for our CRMs. The LWCRE leads to a narrower rising branch of the circulation and substantially increases the fraction of precipitation from the large-scale cloud parameterization. Decreasing the grid-spacing to 1km and 2km results in stronger overturning circulations, more condensate aloft, and less precipitation. This work demonstrates that a mock-Walker circulation is a useful generalization of RCE that includes a large-scale circulation.

Surface waves modify upper ocean dynamics through Stokes drift related processes. Representation of these processes at either resolved or parameterized scales in an ocean model depends on accurate estimation of Stokes drift profiles. Stokes drift estimated from a discrete wave spectrum is compared to Stokes drift approximations as a monochromatic profile based on bulk surface wave parameters, and to two additional super-exponential functional forms. The impact of these different methods on resolved-scale ocean processes is examined in the context of two test-bed cases of a wave-current coupled system: (1) a shallow water inlet test case and (2) an idealized deep water hurricane case. In case (1), tidal currents can modify the waves and significantly affect Stokes drift computed from the wave spectrum. In both cases, large deviations in ocean current response are produced when the Stokes drift is approximated monochromatically from bulk wave parameters, rather than from integration over the wave spectra. Deep water simulations using the two super-exponential approximations are in better agreement with those estimated from wave spectra than are those using the monochromatic, exponential profile based on bulk wave parameters. In order to represent the impact of Stokes drift at resolved scales, we recommend that for studies of nearshore processes and brief deep water events, like wave-current interactions under storms, the Stokes drift should be calculated from full wave spectra. For long simulations of open ocean dynamics, methods using super-exponential profiles to represent equilibrium wind seas might be sufficient, but appear to be marginally more computationally efficient.

In this paper, we study the variations of the solar-wind parameters (solar wind velocity, plasma density, and IMF-Bz component) and the Earth’s disturbance storm-time index (Dst), in relation to cosmic ray flux measurements from 8 neutron monitor stations distributed over Canada, Russia, Finland, and Greenland, during 3 intense geomagnetic storms occurred during the 24th solar cycle (March 16-18, 2015, June 21-23, 2015, and September 7-9, 2017). The wavelet analysis of the Forbush decrease seen in the cosmic ray intensity reveals the clear evolution of the classical two-step process, and with a peak period of approximately 2.1 h. The correlation-delay analyses show a very strong correlation (~0.9) between the relative count rate changes cosmic ray intensity and the indices of solar wind velocity and Dst. We obtain similar time-delay responses to the solar wind velocity for all the cases (~4 hours), but large discrepancies are seen for the Dst index between the storms. We therefore recommend not using the Dst index for predicting Forbush decreases. Finally, we employ the resulting delay-times to parameterize the Forbush decreases in terms of solar wind, and we obtain a predictive model with R2 parameter of an approximate value of 0.8. Moreover, we observe a possible dependence on solar wind proton density which modulates the magnitude of Forbush decreases under similar solar wind velocity conditions. Our results verify the suitability of using solar wind parameters to predict Forbush decreases in the cosmic ray flux.

Recently, recurrent deep networks have shown promise to harness newly available satellite-sensed data for long-term soil moisture projections. However, to be useful in forecasting, deep networks must also provide uncertainty estimates. Here we evaluated Monte Carlo dropout with an input-dependent data noise term (MCD+N), an efficient uncertainty estimation framework originally developed in computer vision, for hydrologic time series predictions. MCD+N simultaneously estimates a heteroscedastic input-dependent data noise term (a trained error model attributable to observational noise) and a network weight uncertainty term (attributable to insufficiently-constrained model parameters). Although MCD+N has appealing features, many heuristic approximations were employed during its derivation, and rigorous evaluations and evidence of its asserted capability to detect dissimilarity were lacking. To address this, we provided an in-depth evaluation of the scheme’s potential and limitations. We showed that for reproducing soil moisture dynamics recorded by the Soil Moisture Active Passive (SMAP) mission, MCD+N indeed gave a good estimate of predictive error, provided that we tuned a hyperparameter and used a representative training dataset. The input-dependent term responded strongly to observational noise, while the model term clearly acted as a detector for physiographic dissimilarity from the training data, behaving as intended. However, when the training and test data were characteristically different, the input-dependent term could be misled, undermining its reliability. Additionally, due to the data-driven nature of the model, the two uncertainty terms are correlated. This approach has promise, but care is needed to interpret the results.

The 17 May 2012 M4.8 Timpson earthquake is the largest known earthquake in eastern Texas. It is suspected to have been induced by wastewater injection from two nearby, high-volume wells. Its cataloged aftershocks form a NW-SE trend, which unlike other induced earthquakes sequences, is unfavorably oriented for failure in the local stress field. To understand this, we enriched the catalog using PhaseNet, a deep-learning-based picker followed by double-difference relocation with cross-correlation-based differential traveltimes. We clustered the aftershocks based on waveform similarity. Most of the seismicity falls into two-clusters, which define a complex fault structure of two parallel subfaults that are more favorably oriented than the overall trend. We inferred from waveform similarity that the sequence initiated on the northern subfault with a M3.9 foreshock and M4.8 mainshock, then extended to the southern subfault with a M4.1 aftershock, and was finally reactivated on the northern subfault with two more M4 events.

The mesosphere and lower thermosphere (MLT) region is dominated globally by dynamics at various scales: planetary waves, tides, gravity waves, and stratified turbulence. The latter two can co-exist and be significant at horizontal scales less than 500 km, scales that are difficult to measure. This study presents a recently deployed multi-static specular meteor radar system, SIMONe Peru, which can be used to observe these scales. The radars are positioned at and around the Jicamarca Radio Observatory, which is located at the magnetic equator. Besides presenting preliminary results of typically reported large scale features, like the dominant diurnal tide at low latitudes, we show results on selected days of spatially and temporally resolved winds obtained with two methods based on: (a) estimation of mean wind and their gradients (gradient method), and (b) an inverse theory with Tikhonov regularization (regularized wind field inversion method). The gradient method allows improved MLT vertical velocities and, for the first time, low-latitude wind field parameters such as horizontal divergence and relative vorticity. The regularized wind field inversion method allows the estimation of spatial structure within the observed area and has the potential to outperform the gradient method, in particular when more detections are available or when fine adaptive tuning of the regularization factor is done. SIMONe Peru adds important information at low latitudes to currently scarce MLT continuous observing capabilities. Results contribute to studies of the MLT dynamics at different scales inherently connected to lower atmospheric forcing and E-region dynamo related ionospheric variability.