There is a substantial gap between the current emissions of greenhouse gases and levels required for achieving the 2 and 1.5 °C temperature targets of the Paris Agreement. Understanding the implications of a temperature overshoot is thus an increasingly relevant research topic. Here we explore the carbon cycle feedbacks over land and ocean in the SSP5-3.4-OS overshoot scenario by using an ensemble of Coupled Model Intercomparison Project 6 Earth system models. Models show that after the CO2 concentration and air temperature peaks, land and ocean are decreasing carbon sinks from the 2040s and become sources for a limited time in the 22nd century. The decrease in the carbon uptake precedes the CO2 concentration peak. The early peak of ocean uptake stems from its dependency on the atmospheric CO2 growth rate. The early peak of the land uptake occurs due to a larger increase in ecosystem respiration than the increase in gross primary production, as well as due to a concomitant increase in land-use change emissions primarily attributed to the wide implementation of biofuel croplands. The carbon cycle feedback parameters amplify after the CO2 concentration and temperature peaks due to inertia of the Earth system so that land and ocean absorb more carbon per unit change in the atmospheric CO2 change (stronger negative feedback) and lose more carbon per unit temperature change (stronger positive feedback) compared to if the feedbacks stayed unchanged. The increased negative CO2 feedback outperforms the increased positive climate feedback. This feature should be investigated under other scenarios.

Many physical processes in the field of rock physics are influenced by the presence of fractures and microcracks. Therefore, intact rock samples are often used for reproducible experimental studies, and cracks are artificially created by various methods. For this, one possibility is the use of thermal treatments. In this work, twelve thermal treatments, differing in the applied maximum temperature and the applied cooling condition (slow versus fast cooling) are experimentally studied for dry Bianco Carrara marble under ambient conditions. Two sizes of cylindrical core samples are investigated to identify a potential size effect. As effective quantities on the core-scale, the bulk volume, the bulk density, and the P- and S-wave velocities, including shear wave splitting, are examined. To obtain a three-dimensional insight into the mechanisms occurring on the micro-scale level, micro X-Ray Computed Tomography (micro-XRCT) imaging is employed. For both cooling conditions, with increasing maximum temperature, the bulk volume increases, and the propagation velocities significantly drop. This behavior is amplified for fast cooling. The bulk volume increase is related to the initiated crack volume as micro-XRCT shows. Based on comprehensive measurements, a logarithmic relationship between the relative bulk volume change and the relative change of the ultrasound velocities can be observed. Although there is a size effect for fast cooling, the relationship found is independent of the sample size. Also the cooling protocol has almost no influence. A model is derived which predicts the relative change of the ultrasound velocities depending on the initiated relative bulk volume change.

A document by Saira Hamid. Click on the document to view its contents.

We present a book entitled “Machine Learning, Statistics, and Data Mining for Heliophysics,” an online and open source book available at helioml.org. This book includes a collection of interactive Jupyter notebooks, written in the programming language Python, that walks the reader through the process of applying machine learning, statistics, and data mining techniques on various kinds of solar and space physics data sets to reproduce published results. We consider this book to be a living document with frequent updates. Please contact us if you’d like to submit a chapter!

Vertical motions associated with mesoscale ocean eddies modulate the light and nutrient environment, stimulating phytoplankton biomass and chlorophyll anomalies. Populations within eddies may be trapped by the horizontal circulation or laterally diluted by mixing with surrounding waters. Conventionally, eddy boundaries are determined using Eulerian methods from daily satellite sea level anomaly fields. However, Eulerian methods do not delineate the bounds of trapped water masses, which is an important consideration when interpreting eddy-induced changes in chlorophyll concentration. Integrated Lagrangian particle tracking methods, on the other hand, more accurately identify coherent structure boundaries that trap fluid masses for time scales relevant to phytoplankton bloom evolution. From two decades of remote sensing observations in the North Pacific Subtropical Gyre, we compared coincident Eulerian and Lagrangian eddy atlases to assess the impact of eddy trapping on chlorophyll concentration. We found more positive chlorophyll anomalies within Lagrangian coherent vortices than in Eulerian eddy boundaries and outside-eddy waters. Yet, there are striking differences seasonally and regionally within the gyre. Chlorophyll is most enriched within coherent boundaries of the Hawaiian Lee eddies and in the region southeast of the Islands in fall and winter. Our results suggest that typical Eulerian analyses underestimate the role of mesoscale eddies in enhancing chlorophyll by not accounting for lateral mixing. Consequently, quantifying the contribution of mesoscale eddies toward open ocean primary production is more complex than previously assumed.

As part of the Norwegian SI-ARCTIC Program, in late summer of 2014 and 2015 acoustic data (18, 38 and 120 kHz) for the estimation of the distribution and abundance of zooplankton and fish were collected from regions west and north of Svalbard, to examine high latitude epipelagic and mesopelagic scattering structures. The deep scattering layer biological constituents were determined from vertical and oblique hauls with zooplankton nets and pelagic trawls. There was strong patchy scattering in the upper part of the epipelagic zone (<50 m) throughout the area due to 0-group fish that were particularly abundant west of the Spitsbergen Archipelago and by copepods, krill, and amphipods. The distinct Off-shelf deep scattering layer (DSL) occurred between 200 and 600 m and contained a range of larger longer lived organisms (mesopelagic fish and macrozooplankton). In eastern Fram Strait, the DSL also included larger fish close to the shelf/slope break that were associated with Warm Atlantic Water moving north towards the Arctic Ocean, but switched to dominance by species having weaker scattering signatures further offshore. The Weighted Mean Depths of the DSL were deeper (WMD >440 m) in the Arctic habitat north of Svalbard compared to those south in the Fram Strait west of Svalbard (WMD ~400 m) and the mesopelagic nautical area scattering coefficient was a factor of approximately 6-10 lower around Svalbard compared to the areas in the south-eastern part of the Norwegian Sea ~62º30’N. The DSL displayed a clear ascending and descending diel movement. The high-light WMD with respect to backscattered energy was statistically deeper than the low-light WMD for the locations studied. This behavior of the DSL was consistent both when the sun was continuously above the horizon and after it started to set on 1 September, and both in open water and sea ice covered waters.

Elevated nitrate concentrations in German water bodies are a widespread problem, potentially resulting from a long history of excess nitrogen (N) inputs. Here, we investigated long-term (1950-2014) N dynamics across 89 German catchments using a process-based model. Results showed that the mean fractions of N surplus (excess) exported to the river, removed by denitrification, accumulated in the soil zone, and accumulated in groundwater across all catchments are 27%, 58%, 14%, and 1%, respectively. Dissolved inorganic N in groundwater could affect the stream N levels over decades as indicated by long groundwater transit times. A cluster identified four catchment groups with distinct archetypal long-term N transport and retention dynamics, which can be partly linked to the catchments’ topographic and geological conditions. This hints at underlying mechanisms that explain spatial differences in the fate of diffuse N inputs to catchments and opens the possibility for better-targeted management

We present a reinterpretation of a geological section in the Tampico-Misantla oil province made with the purpose of selecting and evaluating possible sites to implement a Geological CO2 Storage (GCS) in the Jurassic sedimentary units. Specific parameters of the reservoir such as porosity, permeability, fluid content, temperature, and overburden pressure were estimated from a database of drilled oil wells, core descriptions, laboratory tests, and analogue outcrop descriptions. Previous data indicated porosity values ranging from 6% to 12%, and relatively low permeability values <0.001 mD for calcareous sand and clay-silty bearing layers. Reinterpretation of a geological section involving the main lithostratigraphic units, from Cenozoic sediments to Jurassic metamorphic rocks, was made based on geological maps, geological contacts, and seismic data. Petrophysical properties were obtained from well logs available (Neutron, DTCO, Gamma Ray, Resistivity) and compared with laboratory measurements in cores from wells and outcrops. A model of regional petrophysical facies for the reservoir and seal units was developed by using selected physical properties in relation with the regional geological context. Five petrophysical facies distributed across the study area were identified in the reservoir including calcareous sands, quartz bearing sandstone and quartz bearing conglomerates for the reservoir, and bituminous shales and limestone for the shale units covering the reservoir. Permeability and porosity values at the reservoir scale were estimated from well logs using methods available in the literature and then compared with the laboratory tests. Two porosity estimations were computed from well logs: Neutron porosity (NPHI) and Sonic Porosity (PHITS) with results ranging from 0.1 % to 16%. Estimated permeability yielded a range of 0.001 mD to 15 mD. The results suggest that the Jurassic units are a suitable reservoir since geological traps and specific depositional facies distributed in the basin have the required porosity and permeability values suggested for efficient CO2 storage.

In desert regions like the Middle East (ME), dust has a profound impact on the environment, climate, air quality, and solar devices. The size of dust particles determines the extent of these effects. Dust deposition (DD) measurements show that coarse dust particles with geometric radius r > 10 μm comprise most of the deposited mass. Still, these particles are not represented in the current models that are tuned to fit the observed aerosol visible optical depth (AOD). As a result, the existing models and reanalysis products underestimate DD and dust emission (DE) almost three times. This is the first study to constrain the dust simulations by both AOD and DD measurements to quantify the effect of coarse and fine dust using the WRF-Chem model. We found that, on average, coarse dust contributes less than 10% to dust shortwave (SW) radiative forcing (RF) at the surface but comprises more than 70% of DE. Annual mean net RF over the Arabian Peninsula and regional seas locally reaches -25 W m-2. Airborne fine dust particles with radii r < 3 μm are mainly responsible for the significant dimming (5-10%) of solar radiation, cooling the surface and hampering solar energy production. However, dust mass deposition is primarily linked to coarse particles, decreasing the efficiency of Photovoltaic panels by 2-5% per day. Therefore, incorporating coarse dust in model simulations and data assimilation would improve the overall description of the dust mass balance and its impact on environmental systems and solar devices.

Magnetosheath jets constitute a significant coupling effect between the solar wind (SW) and the magnetosphere of the Earth. In order to investigate the effects and forecasting of these jets, we present the first-ever statistical study of the jet production during large-scale SW structures like coronal mass ejections (CMEs), stream interaction regions (SIRs) and high speed streams (HSSs). Magnetosheath data from Time History of Events and Macroscale Interactions during Substorms (THEMIS) spacecraft between January 2008 to December 2020 serve as measurement source for jet detection. Two different jet definitions were used to rule out statistical biases induced by our jet detection method. For the CME and SIR+HSS lists, we used lists provided by literature and expanded on incomplete lists using OMNI data to cover the time range of May 1996 to December 2020. We find that the number and total time of observed jets decrease when CME-sheaths hit the Earth. The number of jets is lower throughout the passing of the CME-magnetic ejecta (ME) and recovers quickly afterwards. On the other hand, the number of jets increases during SIR and HSS phases. We discuss a few possibilities to explain these statistical results.

The Arctic Ocean receives a large supply of dissolved organic matter (DOM) from its catchment and shelf sediments, which can be traced across much of the basin’s upper waters. This signature can potentially be used as a tracer. On the shelf, the combination of river discharge and sea-ice formation, modifies water densities and mixing considerably. These waters are a source of the halocline layer that covers much of the Arctic Ocean, but also contain elevated levels of DOM. Here we demonstrate how this can be used as a supplementary tracer and contribute to evaluating ocean circulation in the Arctic. A fraction of the organic compounds that DOM consists of fluoresce and can be measured using in-situ fluorometers. When deployed on autonomous platforms these provide high temporal and spatial resolution measurements over long periods. The results of an analysis of data derived from several Ice Tethered Profilers (ITPs) offer a unique spatial coverage of the distribution of DOM in the surface 800m below Arctic sea-ice. Water mass analysis using temperature, salinity and DOM fluorescence, can clearly distinguish between the contribution of Siberian terrestrial DOM and marine DOM from the Chukchi shelf to the waters of the halocline. The findings offer a new approach to trace the distribution of Pacific waters and its export from the Arctic Ocean. Our results indicate the potential to extend the approach to separate freshwater contributions from, sea-ice melt, riverine discharge and the Pacific Ocean.

Plate reconstructions show that the plume feeding today’s Icelandic volcanism passed beneath the continental lithosphere of Greenland between 50 and 100 million years ago. While there has been ample volcanism on the margins of Greenland, both on the west and the east coasts, the thickness of the Greenland craton prevented surface eruptions within Greenland, leaving details of the plume track unclear. However, the passage of the plume is expected to leave a scar in the lower continental lithosphere of Greenland, where the hot plume material interacts with and erodes the stiff cratonic root. This interaction should cause increased surface heat flux and reduced lithosphere thickness along the plume track, and can potentially be constrained by observations that constrain heat flux (e.g., magnetic data and ice flow rates) and lithospheric structure (e.g., seismic tomography and magnetotelluric modeling). While most seismic tomography models indicate that there might be an east-west trending corridor of reduced lithosphere thickness, recent heat flux maps inferred from magnetic data show a northwest-southeast trending anomaly of high heat flux, suggesting an alternative direction of the passage of the Iceland plume. In order to resolve the discrepancy between the suggested hotspot tracks, we use numerical models to investigate how the surface heat flux would evolve in response to the passage of a plume beneath thick cratonic lithosphere. Our work focuses both on the temporal evolution (e.g. the onset and duration), and the shape of the heat flux anomaly, as well as lithospheric thinning related to convective erosion of the cratonic root by hot plume material. We show that both the onset and the duration of the heat flux anomaly, as well as the degree of lithosphere thinning, depend on various parameters, especially the viscosity structure of lithosphere and asthenosphere and the plume strength. A comparison between observations from Greenland and our model predictions should provide new and better constraints on the subsurface structure of Greenland, and how it was modified by its interaction with the Iceland plume.

Harmful algal blooms (HAB; Karenia brevis) occurrences have been reported from the coastal waters of Charlotte County in southwest Florida. We developed multivariate regression models that relate reported (January 2010 to October 2017) bloom occurrences to observations extracted from archival remote sensing data (Moderate Resolution Imaging Spectroradiometer [MODIS]) to accomplish the following: (1) identify factors controlling HAB propagation, (2) predict algal bloom distribution (same day, and 1, 2, and 3 days in advance), and (3) develop fully automated system for data distribution via a web-based GIS platform. These tasks were accomplished through three main steps: (1) automatic downloading and processing of daily MODIS products using SeaDAS software to extract relevant remote sensing variables (euphotic depth, wind direction, ocean chlorophyll three-band algorithm for MODIS [Chlorophyll a OC3M], wind speed, chlorophyll a Generalized Inherent Optical Property [GIOP], Fluorescence Line Height [Flh], diffused attenuation coefficient for downwelling irradiance at 490 nanometer [Kd_490], chlorophyll a Garver-Siegel- Maritorena [GSM], Turbidity index, Particulate backscattering coefficient at 547 nm [bbp_547_giop] and sea surface temperature [SST]), (2) development and calibration of multivariate regression models using relevant remote sensing and static variable (distance from river mouth, bathymetry) inputs for same day mapping and forecasting of HAB occurrences, and (3) automated posting of model outputs on a web-based GIS (http://mgs.geology.wmich.edu/bloom/). Findings include: (1) the variables most indicative of the timing of bloom propagation are bathymetry, euphotic depth, wind direction, sea surface temperature [SST], chlorophyll a [OC3M] and distance from the river mouth, and (2) the model predictions were successful at 90% for same day mapping and 65%, 72% and 71% for the one, two and three days in advance predictions, respectively.

During summer, the Southern Ocean is largely unaffected by anthropogenic emissions, which makes this region an ideal place to investigate marine natural aerosol sources and processes. A better understanding of natural aerosol is key to constrain the preindustrial aerosol state and reduce the aerosol radiative forcing uncertainty in global climate models. We report the concentrations of gaseous sulfuric acid, iodic acid, and methanesulfonic acid (MSA) together with a characterization of new particle formation (NPF) events over a large stretch of the Southern Ocean. Measurements were conducted on board the Russian icebreaker Akademik Tryoshnikov from January to March 2017. Iodic acid is characterized by a particular diurnal cycle with reduced concentration around noon, suggesting a lower formation yield when solar irradiance is higher. Gaseous MSA does not have a diurnal cycle and measured concentrations in gas and condensed phase are compatible with this species being primarily produced via heterogeneous oxidation of dimethyl sulfide and subsequent partitioning into the gas phase. We also found that NPF in the boundary layer is mainly driven by sulfuric acid but it occurred very rarely over the vast geographical area probed and did not contribute to the CCN budget in a directly observable manner. Despite the near absence of NPF events in the boundary layer, Aitken mode particles were frequently measured, supporting the hypothesis of a free tropospheric source. Iodic acid and MSA were not found to participate in nucleation, however, MSA may contribute to aerosol growth via heterogeneous formation in the aqueous phase.

Tsunamis generated by large earthquake-induced displacements of the ocean floor can lead to tragic consequences for coastal communities. Ionospheric measurements of Co-Seismic Disturbances (CIDs) offer a unique solution to characterize an earthquake’s tsunami potential in Near-Real-Time (NRT) since CIDs can be detected within 15 min of a seismic event. However, the detection of CIDs relies on human experts, which currently prevents the deployment of ionospheric methods in NRT. To address this critical lack of automatic procedure, we designed a machine-learning based framework to (1) classify ionospheric waveforms into CIDs and noise, (2) pick CID arrival times, and (3) associate arrivals across a satellite network in NRT. Machine-learning models (random forests) trained over an extensive ionospheric waveform dataset show excellent classification and arrival-time picking performances compared to existing detection procedures, which paves the way for the NRT imaging of surface displacements from the ionosphere.

Coastal cities are exposed to multiple flood drivers such as extreme coastal high tide, storm surge, and extreme river discharge. The interaction among these flood drivers may cause compound flooding events, which could exacerbate social and economic consequences. Climate change can put greater pressure on these areas by increasing the frequency and intensity of coastal and riverine flooding. In this study, a bivariate compound flooding risk assessment method is developed to incorporate sea level rise (SLR) and nonstationary river discharge conditions. Extreme sea water level (SWL) and river stage are identified using the peak-over-threshold method, and subsequently, pairs of extremes are selected when both SWL and river stage exceed their defined thresholds within ±1 day from each other. A copula-based approach is then used to estimate the joint distribution and return period of compound coastal riverine flooding by incorporating nonstationarity into the marginal distributions of extreme SWL and river stage. The future flood risk is assessed using the notation of failure probability, which here refers to (1) the probability of occurrence of at least one major coastal or riverine flooding for a given design life (i.e., total flood risk); and (2) the probability of occurrence of at least one compound major coastal riverine flooding for a given design life (i.e., compound flood risk). Compound flood risk assessment is conducted at 26 paired NOAA-USGS stations along the Contiguous United States coast with long‐term observed data and defined flood thresholds. The results indicate that in some regions the joint return period of coastal/riverine flooding are substantially lower when considering the projected future hydroclimate conditions and SLR. The importance impact of future SLR and hydroclimate conditions is discussed regionally in terms of changes in the frequency of compound major coastal riverine flooding events.

Observations using Arecibo Observatory’s highly sensitive Incoherent Scattering Radar (AO-ISR) show ionospheric descending layers from as high as $\sim$400 km, much higher than earlier studies, with continuity down to 90 km. The AO-ISR was operated to observe the ion-line and plasma-line with coded-long-pulse for high temporal and spatial resolution of 35/10 seconds and 300 m, respectively, during 01-06 February 2019. We found multiple layering structures descending from 400 km to 90 km in all these six days. These layers are traditionally called intermediate descending layers (IDLs) ($>$130 km and below F-peak), upper semi-diurnal daytime $\&$ nighttime layers (110 km-130 km), and lower diurnal layers($<$110 km). We have denoted the new daytime descending layers above the hmF2 as top-side descending layers (TDLs). All these layers are collectively named ion descending layers (IonDLs) since all of them are connected with some discontinuity at the F1-peak (i.e., 170 km), except for the daytime lower-diurnal layer. The most pronounced IonDLs occur in the twilight times. IonDLs mainly occur in shear zones of the vertical ion drifts and are favored by downward ion drifts, and their descent speeds increase with increasing altitude. The estimated phase velocities of the waves in the F-region are comparable with the descending speed of the IonDLs. Furthermore, IonDLs/IDLs occur with and without spread-F events but intensified spread-F events raise their beginning altitude. The TDLs and IDLs are driven by gravity waves with time periods of 1.5-4 hours.

Subglacial models represent moulins as cylinders or cones, but field observations suggest the upper part of moulins in the Greenland Ice Sheet have more complex shapes. These more complex shapes should cause englacial water storage within moulins to vary as a function of depth, a relationship not currently accounted for in models. Here, we use a coupled englacial--subglacial conduit model to explore how moulin shape affects depth-dependent moulin water storage and water pressure dynamics within a subglacial channel. We simulate seven different moulin shapes across a range of moulin sizes. We find that the englacial storage capacity at the water level is the main control over the daily water level oscillation range and that depth-varying changes in englacial water storage control the temporal shape of this oscillation. Further, the cross-sectional area of the moulin within the daily oscillation range, but not above or below this range, controls pressures within the connected subglacial channel. Specifically, large cross-sectional areas can dampen daily to weekly oscillations that occur in the surface meltwater supply. Our findings suggest that further knowledge of the shape of moulins around the equilibrium water level would improve englacial storage parameterization in subglacial hydrological models and aid predictions of hydro-dynamic coupling.