Here, we present new radio interferometer beamforming observations of lightning initiation using data from the Low Frequency Array (LOFAR). We show that the first lightning source in the flash increases exponentially in intensity by two orders of magnitude in 15 microseconds, while propagating 88 meters away from the initiation location at a constant speed of 4.8 ± 0.1 x 10^6 m/s. A second source replaces the first source at the initiation location, and subsequent propagation of the lightning leader follows. We interpret the first source to be a rapidly propagating and intensifying positive streamer discharge that subsequently produces a hot leader channel near the initiation point. How lightning initiates is one of the greatest unsolved problems in the atmospheric sciences, and these results shed light on this longstanding mystery.

The geodynamic evolution of the Western Mediterranean for the past 35My is a matter of debate. Present-day structure and composition of the lithosphere and sublithospheric mantle may help in constraining the geodynamic evolution of the region. We use an integrated geophysical-petrological modeling to derive and compare the present-day thermal, density and compositional structure of the lithosphere and sublithospheric mantle along two NNW-SSE oriented geo-transects crossing the back-arc Alboran and Algerian basins, from onshore Iberia to the northern Africa margin. The crust is constrained by seismic experiments and geological cross-sections, whereas seismic tomography models and mantle xenoliths constrain the upper mantle structure and composition. Results show a thick crust (37km and 30km) and a relative deep LAB (130km and 150km) underneath the HP/LT metamorphic units of the Internal Betics and Greater Kabylies, respectively, which contrast with the 16km thick magmatic crust of the Alboran Basin and the 10km thick oceanic crust of the Algerian Basin. The sharp change in lithosphere thickness, from the orogenic wedge to the back-arc basins, contrasts with the gentler lithosphere thickening towards the respective opposed margins. Our results confirm the presence of detached slabs ~400oC colder than upper mantle and a fertile composition than the continental lithospheric mantle beneath the External Betics and Saharan Atlas. Presence of detached quasi-vertical sublithospheric slabs dipping towards the SSE in the Betics and towards the NNW in the Kabylies and the opposed symmetric lithospheric structure support an opposite dipping subduction and retreat of two adjacent segments of the Jurassic Ligurian-Tethys realm.

Data assimilation (DA) has been applied to estimate the time-mean state such as annual mean surface temperature for paleoclimate reconstruction. There are two types of DA for this purpose: online-DA and offline-DA. The online-DA estimates the time-mean states and the initial conditions for the next DA cycles while the offline-DA only estimates the former. If there is sufficiently long predictability in the system of interest compared to the temporal resolution of the observations, online-DA is expected to outperform offline-DA by utilizing information in the initial conditions. However, previous studies failed to show the superiority of online-DA when time-averaged observations are assimilated, and the reason has not been investigated thoroughly. This study compares online-DA and offline-DA and investigates the relation to the predictability using an intermediate complexity general circulation model with perfect-model observing system simulation experiments. The result shows that the online-DA outperforms offline-DA when the length of predictability is longer than the averaging time of the observations. We also found that the longer the predictability, the more skillful the online-DA. Here, the ocean plays a crucial role in extending predictability, which helps online-DA to outperform offline-DA. Interestingly, the observations of near-surface air temperature over land are found to be highly valuable to update the ocean variables in the analysis steps, suggesting the importance to use cross-domain covariance information between the atmosphere and the ocean when online-DA is applied to reconstruct paleoclimate.

Storm surge barriers, levees, and other coastal flood defense megaprojects are currently being proposed as strategies to protect several U.S. cities against coastal storms and rising sea levels. However, social conflict and other political factors add a layer of complexity that casts doubt on their status as practical climate adaptation options. The specific mechanisms for why some projects do not progress beyond initial planning stages has remained unclear. Here we study the outcome of two U.S. Army Corps of Engineer (USACE) storm surge barrier proposals to explore the political reasons why some coastal flood protection megaprojects break ground in the U.S., while others do not. Using original archive research, we conclude that storm surge barriers are politically challenging climate adaptation options because of 1) modern environmental laws that provide avenues for expression of oppositional views within the decision process and 2) the allure of alternative options that are more aesthetically pleasing and cheaper and faster to implement. To better allocate public resources and the expertise of the USACE, future flood protection megaprojects should first achieve broad support from the public, NGOs, and elected officials before beginning serious planning. This support could be achieved through new innovative designs that simultaneously address adverse environmental impacts and provide co-benefits (e.g., recreation). New designs should be studied to better understand the level of protection offered and associated reliability so that the USACE has confidence in their use.

Intensification of the Agulhas Leakage (AL) during glacial terminations has long been proposed as a necessary mechanism for reverting the Atlantic Meridional Overturning Circulation (AMOC) to its interglacial mode. However, lack of records showing the downstream evolution of AL signal and substantial temporal differences between AL intensification and resumption of deep‐water convection have cast doubt on the importance of this mechanism to the AMOC. Here, we analyze a combination of new and previously published data relating to Mg/Ca‐derived temperatures and ice volume‐corrected seawater δ18O records (δ18OIVC‐SW, as a proxy for relative changes in ocean salinity), which demonstrate propagation of AL signal via surface and thermocline waters to the western South Atlantic (Santos Basin) during Termination II and the early Last Interglacial. The saline AL waters were temporally stored in the upper subtropical South Atlantic until they were abruptly released in two stages into the North Atlantic via surface and thermocline waters at ca. 129 and 123 ka BP, respectively. Accounting for age model uncertainties, these two stages are coeval with the resumption of convection in the Labrador and Nordic seas during the Last Interglacial. We propose a mechanism whereby both active AL and a favorable ocean‐atmosphere configuration in the tropical Atlantic were required to allow flux of AL waters into the North Atlantic, where they then contributed to enhancing the AMOC during the Last Interglacial period. Our results provide a framework that connects AL strengthening to the AMOC intensifications that followed glaciations.

We revisited the June, 2010 - October, 2011 Guy-Greenbrier earthquake sequence in central Arkansas using PhaseNet, a deep neural network trained to pick P and S arrival times. We applied PhaseNet to continuous waveform data and used phase association and hypocenter relocation to locate nearly 90,000 events. Our catalog suggests that the sequence consists of two adjacent earthquake sequences on the same fault and that the second sequence may be associated with the wastewater disposal well to the west of the Guy-Greenbrier Fault, rather than the wells to the north and the east that were previously implicated. We find that each sequence is comprised of many small clusters that exhibit diffusion along the fault at shorter time scales. Our study demonstrates that machine learning based earthquake catalog development is now feasible and will yield new insights into earthquake behavior.

International frameworks for climate mitigation that build from national actions have been developed under the United National Framework Convention on Climate Change and advanced most recently through the Paris Climate Agreement. In parallel, sub-national actors have set greenhouse gas (GHG) reduction goals and developed corresponding climate mitigation plans. Within the U.S., multi-state coalitions have formed to facilitate coordination of related science and policy. Here, utilizing the forum of the NASA Carbon Monitoring System’s Multi-State Working Group (MSWG), we collected and reviewed climate mitigation plans for 11 states in the Regional Greenhouse Gas Initiative (RGGI) region of the Eastern U.S. For each state we reviewed the 1) policy framework for climate mitigation, 2) GHG reduction goals, 3) inclusion of forest carbon in the state’s climate action plan, 4) existing science used to estimate forest carbon, and 5) stated needs for carbon monitoring science. Across the region, we found important differences across all categories. While all states have GHG reduction goals and framework documents, nearly three-quarters of all states do not account for forest carbon when planning GHG reductions; those that do account for forest carbon use a variety of scientific methods with various levels of planning detail and guidance. We suggest that a common, efficient, standardized forest carbon monitoring system would provide important benefits to states and the geographic region as a whole. In addition, such a system would allow for more effective transparency and progress tracking to support state, national, and international efforts to increase ambition and implementation of climate goals.

Research on Atmospheric Rivers (ARs) has focused primarily on AR (thermo)dynamics and hydrological impacts over land. However, the evolution and potential role of nearshore air-sea fluxes during landfalling ARs are not well documented. Here, we examine synoptic evolutions of nearshore latent heat flux (LHF) during strong late-winter landfalling ARs (1979–2017) using 138 over-shelf buoys along the U. S. west coast. Composite evolutions show that ARs typically receive upward (absolute) LHF from the coastal ocean. LHF is small during landfall due to weak air-sea humidity gradients but is strongest (30–50 W/m^2 along the coast) 1–3 days before/after landfall. During El Niño winters, southern-coastal LHF strengthens, coincident with stronger ARs. A decomposition of LHF reveals that sea surface temperature (SST) anomalies modulated by the El Niño—Southern Oscillation dominate interannual LHF variations under ARs, suggesting a potential role for nearshore SST and LHF influencing the intensity of landfalling ARs.

Sea levels in the Western North Pacific (WNP) are presented with anomalous intraseasonal variations. This study examines the response of sea level in the WNP to the atmospheric Intraseasonal Oscillation modes, namely the Madden-Julian Oscillation (MJO) and the Boreal Summer Intraseasonal Oscillation (BSISO), using the 25 years (1993-2017) of satellite altimetry and barotropic model output. In winter, the MJO has significant effects on the component of sea level due to the instant wind and atmospheric pressure effects (high-frequency), showing an eastward propagation pattern in most regions, with the strongest effects in the western marginal seas. The MJO-associated pattern of dynamical (low-frequency) component of sea level propagates southward, with the significant effects mostly in the tropics. In summer, the BSISO-associated pattern of the high-frequency component of sea level moves from southwest to northeast, with the largest anomalies in the middle of WNP (20{degree sign}N-30{degree sign}N), while the strongest BSISO effects on the low-frequency component are detectable mostly in the coasts of China and east of the Philippines. The MJO and BSISO can also modulate the probability of extreme sea level events. In winter, during phases 2-5, MJO increases the chance of extreme high events in the high-frequency component of sea level by 100-200% in the western coasts and the tropics. In summer, in BSISO phases 6-7, the chance of extreme high events in the high-frequency component of sea level is enhanced by >300% in the South China Sea and east of the Philippines.

This work presents a new approach to defining drought, establishing an empirical relationship between historical droughts (and wet spells) documented in impact reports, and a broad range of observed drought-related climate features. A Random Forest (RF) algorithm was trained to identify the particular combinations of predictors – such as precipitation, soil moisture and potential evapotranspiration – that led to categorical, documented drought or non-drought events. Unlike traditional drought definitions, the new RF drought indicator combines meteorological, hydrological, agricultural, and socioeconomic drought, providing drought information for all impacted sectors. The metric also quantifies the conditional probability of drought (rather than being threshold-based), considering multiple climate features and their interactive effect, and can be used for forecasting. The approach was validated out-of-sample across several random selections of training and testing datasets, and demonstrated better predictive capabilities than commonly used drought indicators in a range of performance metrics. Furthermore, it showed a comparable performance to the (expert elicitation-based) US Drought Monitor (USDM) which is the current state-of-the-art record of historical drought in the USA. As well as providing an alternative historical drought indicator to USDM, the RF approach offers additional advantages by being automated, by providing drought information at the grid-scale, and by having predictive capacity. As a proof-of-concept case, the RF drought indicator was trained on Texan climate data and droughts, and validated in all Texas ecoregions. However, the introduced approach can be easily implemented to develop a RF drought indicator for new regions if adequate information on historical droughts is available.

Previous studies have estimated that 25% to 35% of Amazonian precipitation comes from evapotranspiration (ET) within the basin. However, due to simplifying assumptions of traditional models, these studies primarily focus on large spatial and temporal scales. In this work we use the Weather Research and Forecast (WRF) regional climate model with the added capability of water vapor tracers to track the moisture from Amazonian ET at the native WRF resolution. The tracers reveal that the well-mixed assumption of simpler models does not hold, as local ET is more efficiently rained out of the atmospheric column than remote sources of moisture, particularly in the eastern part of the basin. Recycled precipitation shows a strong annual and semi-annual signal, associated with the passage of the Inter-Tropical Convergence Zone. The tracers also reveal a strong diurnal cycle of Amazonian water vapor related to the diurnal cycle of ET, convective precipitation and advected moisture. ET increases from early morning into the afternoon, some of this moisture is rained out through convective storms in the early evening, while later in the night strong winds associated with the South American Low Level Jet advect moisture downwind. Visualizing the Amazonian water vapor highlights its diurnal beating pattern and suggests that the Amazon has “younger” water than other regions in the globe, with very efficient recycling of local moisture.

Auroral brightness and color ratio imagery, captured using the Juno mission’s Ultraviolet Spectrograph, display intense emissions poleward of Jupiter’s northern main emission, and these are split into two distinctly different spectral or “color ratio” regimes. The most poleward region, designated the “swirl region” by Grodent et al. (2003), exhibits a high color ratio, while low color ratio emissions are found within the collar around the swirl region but still poleward of the main emission. We confirm the apparent strong magnetospheric local time control within the polar collar (Grodent et al., 2003), with the dusk side bright “active region” emissions extending from ~11 to 22 hr of magnetospheric local time. These bright emissions dim by at least an order of magnitude between ~0 and 11 hr magnetospheric local time, in the midnight to dawn side “dark region”. This magnetospheric local time structure holds true even when the entire northern oval is located on the night side of the planet (in ionospheric local time), a geometry unstudied prior to Juno, as it is unobservable from Earth. The swirl region brightens at ionospheric dawn (~5-7 ionospheric local time) and diminishes or completely disappears at ionospheric local times of ~20 to 22 hrs. Finally, the southern auroral polar emissions appear to share all of the local time dependencies of its northern counterpart, but at a reduced intensity.

The aquatic vegetation patch plays a significant role on sediment net deposition in the vegetated channels. Particularly, the flow is decelerated at the leading edge of a patch that tends to induce vertical updraft, that is, a diverging flow region, in which vegetation greatly affects the pattern of sediment net deposition. This study focuses on the simulation of the sediment net deposition in the whole vegetation patch region through an innovative random displacement model, a Lagrange method, with a probability-based boundary condition instead of the reflection or sorption boundary at the channel bottom. The probability model of deposition and resuspension is proposed according to the flow field characteristics in the different regions of the vegetation patch. The variation of the sediment deposition and resuspension with the turbulent kinetic energy is analyzed to illustrate the effect of the turbulence induced by vegetation, represented by the dimensionless turbulent kinetic energy (ψ), on the sediment deposition and resuspension. The sediment deposition predicted by the proposed model agrees well with the experimental measurements. Results show that the effect of vegetation on the sediment deposition and resuspension motions begins to prevail when the vegetation-induced ψ is larger than its threshold, ψ *. Although the experimental data are limited, the threshold of ψ is predicted to be within 6.8 to 10 according to the simulation results. As the turbulent kinetic energy increases, the deposition probability decreases continuously when ψ>ψ *.

We analyze two preindustrial experiments from the Community Earth System Model version 2 (CESM2) to characterize the impact of sea ice physics on regional differences in coastal sea ice production around Antarctica and the resulting impact on the ocean and atmosphere. The experiment in which sea ice is a “mushy” mixture of solid ice and brine has a substantial increase in coastal sea ice frazil and snow ice production that is accompanied by decreasing congelation growth and increasing bottom melt. With mushy ice physics, the subsurface ocean is denser and saltier, there is a statistically significant increase in Antarctic Bottom Water Formation by ~0.5 Sv, but differences in ocean biogeochemistry are minimal and only in regions where the summer ice state differs. While there are no significant changes in the atmospheric circulation, using “mushy” ice physics results in decreased turbulent heat flux, atmospheric convection, and low level cloud cover.

A physics-based earthquake simulator should reproduce first-order empirical power-law behaviors of magnitudes and clustering. However, sequences exhibiting these laws have only been produced in discrete and low-dimension continuum simulations. We show that the same emergence also occurs in 3-D continuum simulations. Our model approximates a strike-slip fault system slipping under rate-and-state friction. We produce spatiotemporally clustered earthquake sequences exhibiting characteristic Gutenberg-Richter scaling as well as empirical inter-event time distribution. With fault interaction, partial ruptures emerge when seismogenic width W over characteristic nucleation length L∞ is larger than 16.24, but none occurs without fault interaction. The mainshock recurrence times of individual faults remain quasi-periodic and fit a Brownian passage time distribution. The system mainshock recurrence time has a short-term Omori-type decay, indicating a 22% chance of mainshock clustering. These results show that physics-based multi-cycle models adequately reflect observed statistical signatures and show practical potential for long-term hazard assessment and medium-term forecasting.

In studying problems like plant-soil-microbe interactions in environmental biogeochemistry and ecology, one usually has to quantify and model how substrates control the growth of, and interaction among, biological organisms. To address these substrate-consumer relationships, many substrate kinetics and growth rules have been developed, including the famous Monod kinetics for single substrate-based growth, Liebig’s law of the minimum for multiple-nutrient co-limited growth, etc. However, the mechanistic basis that leads to these various concepts and mathematical formulations and the implications of their parameters are often quite uncertain. Here we show that an analogy based on Ohm’s law in electric circuit theory is able to unify many of these different concepts and mathematical formulations. In this Ohm’s law analogy, a resistor is defined by a combination of consumers’ and substrates’kinetic traits. In particular, the resistance is equal to the mean first passage time that has been used by renewal theory to derive the Michaelis-Menten kinetics under substrate replete conditions for a single substrate as well as the predation rate of individual organisms. We further show that this analogy leads to important insights on various biogeochemical problems, such as (1) multiple-nutrient co-limited biological growth, (2) denitrification, (3) fermentation under aerobic conditions, (4) metabolic temperature sensitivity, and (5) the accuracy of Monod kinetics for describing bacterial growth. We expect our approach will help both modelers and non-modelers to better understand and formulate hypotheses when studying certain aspects of environmental biogeochemistry and ecology.

This study investigates the occurrence of mixed-phase clouds (MPC) over the Southern Ocean (SO) using space- and surface-based lidar and radar observations. The occurrence of supercooled clouds is dominated by geometrically thin (< 1km) layers that are rarely MPC. We diagnose layers that are geometrically thicker than 1 km to be MPC approximately 65%, and 4% of the time from below by surface remote sensors and from above by orbiting remote sensors, respectively. We examine the discrepancy in MPC as diagnosed from the below and above. From above, we find that MPC occurrence has a gradient associated with the Antarctic Polar Front near 55°S with the rare occurrence of satellite-derived MPC south of that latitude. In contrast, surface sensors find MPC in 33% of supercooled layers. We infer that space-based lidar cannot identify the occurrence of MPC except when secondary ice-forming processes operate in convection that is sufficiently strong to loft ice crystals to cloud tops. We conclude that the CALIPSO phase statistics of MPC have a severe low bias in MPC occurrence. Based on surface-based statistics, we present a parameterization of the frequency of MPC as a function of cloud top temperature that differs substantially from that used in recent climate model simulations.

Natural and non-natural factors have combined effects on the trajectory of COVID-19 pandemic, but it is difficult to make them separate. To address this problem, a two-stepped methodology is proposed. First, a compound natural factor (CNF) model is developed via assigning weight to each of seven investigated natural factors, i.e., temperature, humidity, visibility, wind speed, barometric pressure, aerosol and vegetation in order to show their coupling relationship with the COVID-19 trajectory. Onward, the empirical distribution based framework (EDBF) is employed to iteratively optimize the coupling relationship between trajectory and CNF to express the real interaction. In addition, the collected data is considered from the backdate, i.e., about 23 days—which contains 14-days incubation period and 9-days invalid human response time—due to the non-availability of prior information about the natural spreading of virus without any human intervention(s), and also lag effects of the weather change and social interventions on the observed trajectory due to the COVID-19 incubation period; Second, the optimized CNF-plus-polynomial model is used to predict the future trajectory of COVID-19.Results revealed that aerosol and visibility show the higher contribution to transmission, wind speed to death, and humidity followed by barometric pressure dominate the recovery rates, respectively. Consequently, the average effect of environmental change to COVID-19 trajectory in China is minor in all variables, i.e., about -0.3%, +0.3% and +0.1%, respectively. In this research, the response analysis of COVID-19 trajectory to the compound natural interactions presents a new prospect on the part of global pandemic trajectory to environmental changes.