We assess the ability of neural network emulators of physical parametrization schemes in numerical weather prediction models to aid in the construction of linearised models required by 4D-Var data assimilation. Neural networks can be differentiated trivially, and so if a physical parametrization scheme can be accurately emulated by a neural network then its tangent-linear and adjoint versions can be obtained with minimal effort, compared with the standard paradigms of manual or automatic differentiation of the model code. Here we demonstrate this idea by emulating the non-orographic gravity wave drag parametrization scheme in an atmospheric model with a neural network, and deriving its tangent-linear and adjoint models. We demonstrate that these neural network-derived tangent-linear and adjoint models not only pass the standard consistency tests but also can be used successfully to do 4D-Var data assimilation. This technique holds the promise of significantly easing maintenance of tangent-linear and adjoint codes in weather forecasting centres, if accurate neural network emulators can be constructed.

We present a characterization of transient-large-amplitude (TLA) geomagnetic disturbances that occurred at six stations of the Magnetometer Array for Cusp and Cleft Studies throughout 2015. TLA events are defined as one or more short-timescale (< 60 seconds) dB/dt signature with magnitude > 6 nT/s. A semi-automated dB/dt search algorithm was developed to identify TLA events in ground magnetometer data and used to identify 40 TLA dB/dt events. We demonstrate the existence of large-amplitude dB/dt with timescale less than 10 seconds in nine of the events. The association of these events to sudden commencements is relatively weak, rather the events are more likely to occur in relation to substorm onsets. However, 15% of TLA events show no direct association to geomagnetic storms, substorms or nighttime magnetic impulse events.

Arctic precipitation (PG) that occurs as rainfall (Pr) or snowfall (Ps) depending on the prevailing climatic conditions results in seasonally specific hydrological events. Climate change can affect the PG- and permafrost-originated water (Pi) regimes, resulting in change to ecohydrological processes. However, the relative influences of source waters (i.e., Pr, Ps, and Pi) on terrestrial hydrological processes have not yet been fully established. Here, we report the development and implementation of a numerical water tracer model designed to quantify changes in the storages and fluxes of the source waters and the hydrogen and oxygen isotopic tracers associated with hydrometeorological events. The presented tracer model was used to illustrate the spatiotemporal variability of the tracers in the surface–subsurface system of a deciduous needleleaf boreal forest, and to separate the contribution rates of the tracer waters to evapotranspiration (ET). Although Ps accounted for 14%–40% of ET and the subcomponents, the contribution rates to soil evaporation and transpiration were significant only during the spring season. The major source water for soil moisture was Pr, which accounted for 80.1% of ET and showed an increasing trend. Additionally, Pr also accounted for 85.7% of transpiration. Under the present conditions of warming permafrost, Pi demonstrated negligibly low impact on ET. The tracer model was shown capable of quantifying the contribution rates of tracer waters to ET, highlighting the advantages of the tracer model for similar quantitative separation regarding future climate change.

A method is presented for retrieving temperature and composition from 150-350 km in Earth’s thermosphere using total number density measurements made via EUV solar occultations by the PROBA2/LYRA instrument. Systematic and random uncertainties are calculated and found to be less than 5% for the temperature measurements and 5-20% for the composition measurements. Regression coefficients relating both temperature and the [O]/[N2] abundance ratio with EUV irradiance at 150, 275 and 350 km are reported. Additionally, it is shown that the altitude where [O] equals [N2] decreases with increasing solar EUV irradiance, an effect attributed to thermal expansion. Temperatures from 2010 to 2017 are compared with estimates from the MSIS empirical model and show good agreement at the dawn terminator but LYRA is markedly cooler at the dusk terminator, with the MSIS-LYRA temperature difference increasing with solar activity. Anthropogenic cooling can explain this discrepancy at periods of lower solar activity, but the divergence of temperature with increasing solar activity remains unexplained. LYRA measurements of the exospheric sensitivity to EUV irradiance are compared with contemporaneous measurements made at Mars, showing that the exospheric temperature at Mars is approximately half as sensitive to EUV variability as that of Earth.

We explore the mantle density structure of the northeast Atlantic region using constrained linear inversion of the satellite gravity gradient data based on statistical prior information and assuming a Gaussian model. The uncertainty of residual gravity gradient signal is characterized by covariance matrix obtained using geostatistical analysis of controlled-source seismic data. The forward modelling of the gravity gradients in the 3D reference crustal model is performed using a global spherical harmonics analysis. We estimate the model covariance function in the radial and angular directions using a variogram method. We compute volumetric gravity gradient kernels for a spherical shell covering the northeast Atlantic region down to the upper limit of the mantle transition zone (410 km depth). The solution of the linear inverse problem in the form the mean density model follows a least-squares approach. The results indicate a direct relationship between the seismic velocity and density anomalies in the Iceland-Jan Mayen region, Greenland and the Norwegian passive margin. The predicted low-density anomalies at the depth of 100-150 km underneath the northeast Atlantic Ocean are correlated with the distribution of Cenozoic underwater volcanoes and seamount-like features of the seafloor.

In this letter, we present for the first time simultaneously measured electron and gamma ray spectra of TGE. We also demonstrate how the measurement of the energy spectra of TGE particles can help to understand the charge structure of the thundercloud. We introduce two main scenarios that can support the initiation of the relativistic runaway avalanches (RREA) in the thundercloud. One of the scenarios includes the emergence of the lower positive charged layer (LPCR). The LPCR is a short-living charge structure sitting on hydrometeors, which exhibit accidental charge reversals depending on temperature changes. LPCR can sustain a positive (downwards directed) near-surface electric field for several minutes, before falling down with precipitation. Comparison of energy spectra of electrons and gamma rays makes it possible to scrutinize the LPCR emergence and estimate the height where the strong electric field that originates the RREA declines.

In this study, a new high-latitude empirical model is introduced, named for Auroral energy Spectrum and High-Latitude Electric field variabilitY (ASHLEY). This model aims to improve specifications of soft electron precipitations and electric field variability that are not well represented in existing high-latitude empirical models. ASHLEY consists of three components, ASHLEY-A, ASHLEY-E and ASHLEY-Evar, which are developed based on the electron precipitation and bulk ion drift measurements from the Defense Meteorological Satellite Program (DMSP) satellites during the most recent solar cycle. On the one hand, unlike most existing high-latitude electron precipitation models, which have assumptions about the energy spectrum of incident electrons, the electron precipitation component of ASHLEY, ASHLEY-A, provides the differential energy fluxes in the 19 DMSP energy channels under different geophysical conditions without making any assumptions about the energy spectrum. It has been found that the relaxation of spectral assumptions significantly improves soft electron precipitation specifications with respect to a Maxwellian spectrum (up to several orders of magnitude). On the other hand, ASHLEY provides consistent mean electric field and electric field variability under different geophysical conditions by ASHLEY-E and ASHLEY-Evar components, respectively. This is different from most existing electric field models which only focus on the large-scale mean electric field and ignore the electric field variability. Furthermore, the consistency between the electric field and electron precipitation is better taken into account in ASHLEY.

Tropopause-penetrating overshooting convection (OC) can transport tropospheric air into and affect the composition of the lower stratosphere. During the warm season, OC occurs frequently over the contiguous United States, and the transport of plumes from these events is modulated by the flow over North America, which throughout June to August is characterized by a large-scale anticyclone in the upper troposphere and lower stratosphere. This study uses data from the Next Generation Weather Radar (NEXRAD) and the ERA5 reanalysis to locate OC during May–August of 2008 to 2020. Evidence of convective transport is found well above the 380 K isentrope, which is the top of the “lowermost stratosphere” and also the top of the stratospheric middleworld. By initializing massless particles within the volume of OC above the tropopause, we perform trajectory calculations to simulate the transport of OC plumes. With three-dimensional diabatic trajectory modeling in isentropic coordinates using winds from ERA5, we quantify the confinement within the anticyclone and the number of trajectories transported into the tropical and extratropical stratosphere. By evaluating the trajectory residence time in the North American region, we find that July exhibits the strongest confinement, with about a quarter of trajectories staying in the region for more than 11 days. It is shown that, together with sufficient injection height, convective injection that occurs south of the jet and/or into anticyclonic regimes increases the chances of air remaining in the stratosphere. After 30 days, 45% of all air masses injected above the tropopause remain in the global stratosphere.

High resolution and accurate rainfall information is essential to modeling and predicting hydrological processes. Crowdsourced personal weather stations (PWSs) have become increasingly popular in recent years and can provide dense spatial and temporal resolution in rainfall estimates. However, their usefulness is limited due to a lack of trust in crowdsourced data compared to traditional data sources. Using crowdsourced PWSs data without an evaluation of its trustworthiness can result in inaccurate rainfall estimates as PWSs may be poorly maintained or incorrectly sited. In this study, we advance the Reputation System for Crowdsourced Rainfall Networks (RSCRN) to bridge this trust gap by assigning dynamic trust scores to the PWSs. Using rainfall data collected from 18 PWSs in two dense clusters in Houston, Texas USA as a case study, the results show that using RSCRN-derived trust scores can increase the accuracy of 15-min PWS rainfall estimates when compared to rainfall observations recorded at city’s high-fidelity rainfall stations. Overall, RSCRN rainfall estimates improved for 77% (48 out of 62) of the analyzed storm events, with a median RMSE improvement of 27.3%. Compared to an existing PWS quality control method, results showed that while 13 (21%) storm events had the same performance, RSCRN improved rainfall estimates for 78% of the remaining storm events (38 out of 49), with a median RMSE improvement of 13.4%. Using RSCRN-derived trust scores can make the rapidly growing network of PWSs a more useful resource for urban flood management, greatly improving knowledge of rainfall patterns in areas with dense PWSs.

From the heated debates over the airborne transmission of the novel coronavirus to the abrupt Earth system changes caused by the sudden lockdowns, the dire circumstances resulting from the coronavirus disease 2019 (COVID-19) pandemic has brought the field of GeoHealth to the forefront of visibility in science and policy. The pandemic has inadvertently provided an opportunity to study how human response has impacted the Earth system, how the Earth system may impact the pandemic, and the capacity of GeoHealth to inform real-time policy. The lessons learned throughout our responses to the COVID-19 pandemic are shaping the future of GeoHealth.

On 15 January 2022, the Hunga Tonga-Hunga Ha’apai submarine volcano erupted violently and triggered a giant atmospheric shock wave and tsunami. The exact mechanism of this extraordinary eruptive event, its size and magnitude are not well understood yet. In this work, we analyze data from the nearest ground-based receivers of Global Navigation Satellite System (GNSS) to explore the ionospheric total electron content (TEC) response to this event. We show that the ionospheric response consists of a giant TEC increase followed by a strong long-lasting depletion. We observe that the explosive event of 15 January 2022 began at 04:05:54UT and consisted of at least 5 explosions. Based on the ionospheric TEC data, we estimate the energy released during the main major explosion to be between 9 and 37 Megatons in TNT equivalent. This is the first detailed analysis of the eruption sequence scenario and the timeline from ionospheric TEC observations.

The Arctic climate is changing dramatically, especially in terms of sea ice loss, with potentially large downstream impacts on the Nordic Seas and the North Atlantic Ocean. The East Greenland Current (EGC) transports substantial amounts of freshwater (in liquid and solid states) southward along the east Greenland continental slope. To increase our understanding of the drivers of surface salinity changes in the interior Nordic Seas, we investigate the diversion of freshwater from the EGC into the Nordic Seas. To this end, we analyse the outcomes of an ocean model hindcast for the period 1973-2004 with a horizontal resolution of 0.25 degree. We find that sea ice contributes large amounts of freshwater to the interior Nordic Seas. On an interannual time scale, this sea ice diversion has a high and significant correlation with surface salinity in the Greenland and Iceland Seas (correlation < -0.7). On a seasonal time scale, the model hindcast and observations demonstrate a clear signal in surface salinity: a lateral migration of the Polar Front position occurring along all of east Greenland. In the model hindcast, these lateral shifts in the front are consistent with seasonal changes in the westward wind-driven Ekman transport. Thus, this climate model study indicates that there are two main causes of seasonal and interannual surface salinity changes; wind-driven Ekman transport and sea ice diversion from the EGC, respectively.

The mid-Proterozoic (~1.8–0.8 Ga) is characterized by low atmospheric oxygen and pervasive oceanic anoxia, with transient oxygenations. One of the prominent oxygenation events happened at ~1.57 Ga, during which atmospheric O2 may have reached ≥4% present atmospheric level (PAL) and thus promoted the evolution of multi-cellular eukaryotes. The causes for this oxygenation event, however, remained unknown. Here, we report the result of δ202Hg and ∆199Hg, P concentration, Rb/Al, and eNd(t) across this oxygenation interval in the Gaoyuzhuang Formation of North China. The positive δ202Hg, eNd(t), and negative Δ199Hg shifts, and the accompanied peaks in Rb/Al, P and I/(Ca+Mg) suggest that this oxygenation was likely resulted from enhanced weathering of intermediate to mafic rocks, which may have promoted primary production via increasing P influx to the ocean and led to the rise in oxygen levels. The data indicate that enhanced weathering input can trigger transient oxygenation events during the mid-Proterozoic.

The 13 km SHiELD (System for High-resolution prediction on Earth-to-Local Domains) global model that is under development at the Geophysical Fluid Dynamics Laboratory (GFDL) and runs in near real time, produced outstanding tropical cyclone track forecasts during the 2021 Atlantic hurricane season, compared to both the upgraded National Weather Service Global Forecast System (GFSv16), the Hurricane Weather Research and Forecasting (HWRF) model and the European Centre for Medium-Range Weather Forecast Integrated Forecasting System (IFS). SHiELD’s average track forecast errors were 10% and 15% less than the GFSv16 and HWRF, respectively, for the 3-5 day forecast lead times. SHiELD’s track forecast skill was comparable to the National Hurricane Center’s official forecast at several forecast lead times, and approached 70% skill relative to the Climatology and Persistence Model (CLIPER) at 3 and 4 days. Similar improvements were found in the western Pacific basin in 2021, with improvements also seen in the eastern Pacific at days 4 and 5. Improved performance was also found in the 2019 Atlantic hurricane season, with neutral performance in 2020, when SHiELD was run retrospectively from the GFSv16 initial conditions. Distribution of the spatial errors and biases showed that in both the 2021 Atlantic hurricane season and the previous two years, the largest track forecast errors from both SHiELD and GFSv16 occurred in the subtropical eastern Atlantic, associated with a distinct northeast bias. Analysis indicated that some of the excessive north bias in the GFSv16 is associated with lower geopotential height fields compared to those in SHiELD.

The climate of the southwestern North America has experienced profound changes between wet and dry phases over the past 200 kyr. To better constrain the timing, magnitude and paleoenvironmental impacts of these changes in hydroclimate, we conducted a multiproxy biomarker study from samples collected from a new 76 m sediment core (SLAPP-SRLS17) drilled in Searles Lake, California. Here, we use biomarkers and pollen to reconstruct vegetation, lake conditions and climate. We find that δD values of long chain n-alkanes are dominated by glacial to interglacial changes that match nearby Devils Hole calcite δ18O variability, suggesting both archives predominantly reflect precipitation isotopes. However, precipitation isotopes do not simply covary with evidence for wet-dry changes in vegetation and lake conditions, indicating a partial disconnect between large scale atmospheric circulation tracked by precipitation isotopes and landscape moisture availability. Increased crenarchaeol production and decreased evidence for methane cycling reveal a 10 kyr interval of a fresh, productive and well-mixed lake during Termination II, corroborating evidence for a paleolake highstand from shorelines and spillover deposits in downstream Panamint Basin during the end of the penultimate (Tahoe) glacial (140–130 ka). At the same time brGDGTs yield the lowest temperature estimates (mean months above freezing = 9 ± 3°C) of the 200 kyr record. These limnological conditions are not replicated elsewhere in the 200 kyr record, suggesting that the Heinrich stadial 11 highstand was wetter than that during the last glacial maximum and Heinrich 1 (18–15 ka).

Green Bay is a large freshwater estuarine system that drains one-third of the Lake Michigan basin. The International Joint Commission designated southern Green Bay as an area of concern (AOC) in the 1980s due to ecosystem degradation including eutrophication, harmful algal blooms (HABs), hypoxia, lost or altered habitat, and reduced water quality. Restoration studies have found excessive nutrient loading and release of toxic materials, primarily produced in farmlands and industrial units, to be major drivers of Green Bay environmental/ecological issues. The Green Bay geomorphology and restricted mixing is a barrier to the efficient transport of sediments (as well as the accompanying nutrients and contaminants), acting as a retention basin for Lake Michigan. The purposes of this research were to: a) use the existing database of hydrodynamic, wave, and sediment field data to develop a three-dimensional (3D) predictive model of sediment transport in Lake Michigan, with an emphasis in Green Bay; b) use the sediment transport model to contribute to understanding ecological and environmental problems in the bay, and to recommend long-term solutions to those problems; and c) analyze summer patterns of circulation, wave action, current and wave-induced bottom shear stress, thermal structure, and sediment transport in Lake Michigan, with special attention to Green Bay.

The effects of precipitation (Pr) and evapotranspiration (ET) on soil moisture play an essential role in the land-atmosphere system. Here we evaluate multimodel differences of these effects within the Coupled Model Intercomparison Project Phase 5 (CMIP5) compared to Soil Moisture Active Passive (SMAP) products in the frequency domain. The variability of surface soil moisture (SSM), Pr, and ET within three frequency bands (7 ~ 30 days, 30 ~ 90 days, and 90 ~ 365 days) after normalization is quantified using Fourier transform. We then analyze the impact of ET and Pr on SSM variability based on a transfer function assuming these variables with a linear time-invariant (LTI) system. For the simulated effects of ET and Pr on SSM variability, models underestimate them in the two higher frequency bands and overestimate them in the lowest frequency band but show better estimates in transitional zones between dry and wet climates. Besides, the effects on SSM by Pr and ET are found to be different across the three frequency bands, and models underestimate the one of Pr and ET as the dominant factor controlling SSM variability in each frequency band. This study identifies the spatiotemporal distribution of the CMIP5 model deficiencies in simulating ET and Pr effects on SSM. Overcoming these deficiencies could improve the interpretability and predictability of Earth system models in simulating interactions among the three variables.

At the international level, the term “water security” (WS) has gained increasing attention in recent decades. At the operational level, WS is assessed using tools that define the concept using a variety of dimensions and sub-dimensions, with qualitative and quantitative indicators and parameters. The breadth of tools and concepts is an obstacle to the operationalization of the concept of water security (WS). Clearly we need a range of diverse data to evaluate water security (WS). However, there are several barriers to designing an optimal Data Gathering Strategy (DGS). Such a strategy must strike a balance between a wide range of competing and overlapping data requirements and characteristics including: resources, information, and impact. The conceptual aim of the framework can be summarised as shifting the focus of the DGS from a “data to information approach” to a “data to action approach”. The specific aims of this paper are to: identify the key issues that should be addressed in designing a Data Gathering Strategy for Water Security (DGSxWS); communicate the key issues with a clear conceptual framework; and suggest approaches and activities that could help water practitioners in dealing with the issues identified.