As phytoplankton form the base of the marine food web, understanding the controls on their abundance is fundamental to understanding marine ecology and how it might be altered by global climate change. While many Earth System Models (ESMs) predict phytoplankton biomass, it is unclear whether they properly capture the mechanistic relationships that control this quantity in the real ocean. In this paper, we used Random Forest (RF) analysis to analyze the output of ESMs and observational datasets. We gathered information from 13 ESMs and two observational datasets. The target variable was phytoplankton carbon and the predictors included environmental parameters known to influence phytoplankton, such as nutrients, light, mixed layer depth, salinity, temperature, and upwelling. We examined three questions: (1) What fractions of variability in ESMs and observations can be linked to the large-scale environmental variables simulated by ESMs? (2) What are the dominant predictors and relationships affecting phytoplankton biomass? (3) How well do ESMs simulate phytoplankton carbon and do they simulate the relationships we see in observations? We show that about 88% to 96% of the variability in observational datasets and greater than 98% in the ESMs was accounted for by variables known to influence phytoplankton biomass from large-scale environmental variables. The dominant predictors in the observational datasets were dissolved iron and shortwave radiation. The dominant predictors in the ESMs were dissolved iron, shortwave radiation, and mixed layer depth. While relationships in most of the ESMs matched the general trends seen in the observations, significant quantitative differences were seen. While the assumption made by ESMs that large-scale environmental conditions control phytoplankton biomass appears to hold in the real world, much work remains to be done to ensure that ESMs properly represent these controls.

The Array of Things (AoT) is a collaborative effort among leading scientists, universities, local government and communities in Chicago to collect real-time data on the city’s environment, infrastructure, and activity for research and public use. The AoT is composed of nodes that will measure and sense the urban environment of Chicago and provide openly accessible data in near real time. One component of each node is the ChemSense board, which uses chemical sensors to measure five gas-phase species: ozone, nitrogen dioxide, carbon monoxide, sulfur dioxide and hydrogen sulfide. In addition, the ChemSense board provides information on total reducing gases and total oxidizing gases. The nodes also include meteorological information and cameras that will provide pedestrian and traffic counts using computer vision algorithms. Because the ChemSense boards rely on low-cost sensors, characterizing the sensor responses is critical to understanding the applicability of the AoT for urban air quality issues. As a first step, a node with the ChemSense board was installed at an EPA air quality monitoring site within the City of Chicago, which is run by the Cook County Department of Environment and Sustainability. The EPA site has Federal Reference Method monitors for ozone, nitrogen dioxide and sulfur dioxide. After collecting collocation data for seven months, the results are promising for ozone, but much less so for sulfur dioxide. For nitrogen dioxide, unexplained spikes not observed in the EPA data drive a poor fit. Results from the collocation project will be used to consider larger issues for characterizing the air quality component of the AoT.

Accurate mapping of urban infrastructure, specifically buildings, and extent is a high priority in addressing environmental and socioeconomic problems. Importantly, such mapping must account for the three-dimensionality (3D) of the urban environment that has traditionally been lacking (e.g., land cover and land use change—LCLUC—analyses often utilize two-dimensional satellite imagery). Undoubtedly, considerable development and change in urban areas takes place in the vertical dimension. Light detection and ranging (lidar) data provide the ability to map in 3D, but systematic data coverage both spatially and temporally is direly insufficient globally. Previous works have successfully implemented spaceborne radar data such as 1-km QuikSCAT data in lieu of lidar data to assess 3D urban build-up. Higher spatial resolution is required, though, to examine urban characteristics in detail. In this study, we test whether Sentinel-1 C-band Synthetic Aperture Radar (SAR) data can monitor 3D urban build-up in high spatial resolution (i.e. 40-m) in Detroit, Michigan, USA, 2015. Findings confirm, through comparison with aggregated 1-m lidar data, the utility of high spatial resolution SAR data for examination of urban built-up volume. Correlation and regression results show a strong linear relationship between SAR backscatter and lidar volume citywide. Moreover, SAR data, unlike coarser resolution radar data, can detect 3D anomalies over time (e.g., new building construction, building demolitions, etc.) further attesting to their utility for comprehensive 3D urban analyses a lower cost and higher repeatability over a much more extensive coverage compared to lidar data.

Drought is a prominent feature of Hawaii’s climate, however, the biological, ecological, cultural, and socioeconomic impacts of drought in Hawaii are not well understood. This paper provides a comprehensive synthesis of impacts of past droughts in Hawaii that we integrate with a geospatial analysis of drought characteristics (duration, frequency, severity, and geographic extent) using a newly developed 93-year (1920-2012) gridded Standardized Precipitation Index (SPI) dataset. The synthesis examines past droughts classified into five categories: meteorological, agricultural, hydrological, ecological, and socioeconomic drought. Results show that drought duration, magnitude, and frequency have all increased significantly, consistent with trends found in other Pacific Islands. Most droughts, though not all, were associated with El Nino events, and the two worst droughts in the past century were 1998-2002 and 2007-2012. The most severe drought in the record (2007-2012) had the greatest impacts on Hawaii Island, whereas the islands of Oahu and Kauai experienced more severe drought conditions during the 1998-2002 event. Both droughts exerted a large and quantifiable impact on the agricultural sector, and although anecdotal evidence points to strong impacts on ecological and socioeconomic sectors, more research is needed to understand drought impacts to these sectors. This synthesis is an example of how coupling quantitative SPI analysis with economic and ecological impacts can provide the historical context needed to better understand future drought projections, and will contribute to more effective policy and management of natural, cultural, hydrological, and agricultural resources.

Temperature and density in the upper Martian atmosphere, above ~100 km, are key diagnostic parameters to study processes of the species’ escape, investigate the impact of solar activity, model the atmospheric circulation, and plan spacecraft descent or aerobraking maneuvers. In this paper, we report vertical profiling of carbon dioxide (CO2) density and temperature from the Atmospheric Chemistry Suite (ACS) solar occultations onboard the ExoMars Trace Gas Orbiter (TGO). A strong CO2 absorption band near 2.7 μm observed by the middle infrared spectrometric channel (ACS MIR) allows the retrieval of the atmospheric thermal structure in a large altitude range, from 20 to 180 km. We present the latitudinal and seasonal climatology of the thermal structure for 1.5 Martian years (MYs), from the middle of MY 34 to the end of MY 35. The results show the variability of distinct atmospheric layers, such as a mesopause (derived from 70 to 150 km) and homopause, changing from 80-90 km at aphelion to 100-110 km at perihelion. Some short-term homopause fluctuations are also observed depending on the dust activity.

The growth of data recorded by dense seismic arrays has stimulated the development of new array-based receiver function (RF) imaging techniques. This study examines the feasibility and performance of the least-squares migration (LSM) method, a state-of-art technique used in exploration seismology, to lithospheric imaging using teleseismic RFs. Taking advantage of a pair of forward (de-migration) and adjoint (migration) operators, the LSM casts migration as a regularized least-squares optimization problem. We employ the Split-step Fourier method to design the two operators and conduct wavefield propagation in heterogeneous media. Synthetic tests with models containing various Moho geometries demonstrate that LSM enables resolving interfaces at a higher resolution than conventional migration. Then LSM is applied to teleseismic data recorded by the Hi-CLIMB array deployed on the Tibetan Plateau. Considering the irregular and noisy recordings from field acquisition, we adopt signal processing algorithms, including the Radon transform and Singular Spectrum Analysis filter, to regularize the wavefields and precondition the RFs. The proposed workflow produces a significantly improved subsurface image than conventional methods, revealing new observations of 1) two well-defined interfaces at the base of the crust and 2) gently dipping mantle discontinuities extending continuously from the Lhasa Block to the Qiangtang Block. These structures could represent the imbricated Indian and Tibetan crust underlain by the underthrusting Indian lithosphere, implying that the Indian collisional front extends as far north as the Bangong-Nujiang suture. Overall, our study offers a new high-resolution RF imaging tool and inspires the future development of advanced array processing workflows.

Bays within eastern boundary upwelling systems (EBUS) are ecological hot-spots featuring a diverse range of spatio-temporal dynamics. At the EBUSs’ poleward limit, upwelling occurs in short-lived (<1 week) pulses modulated by synoptic wind variability. The circulations in long, narrow bays can respond to these fluctuations within few hours. The short-term biological response to these pulses was investigated in two of these bays (Rias Baixas, NW-Iberia) with a two-week quasi-synoptic spatio-temporal survey in the summer 2018. A four-day-long upwelling pulse caused deep, nutrient-rich isopycnals to rise into the euphotic zone inside the bays, triggering a rapid (~1.7 days) nutrient uptake and formation of a subsurface chlorophyll maximum (~3.8 days). The phytoplankton biomass was transported rapidly toward deep, offshore waters when the winds weakened. These results suggest that high productivity in narrow bays is controlled by the transient exposure of deep, nutrient-rich waters to light during upwelling pulses.

The Geology teaching and learning processes should be carried out through the interaction of different learning environments, inside the classroom and outdoors. Practical activities are a methodological strategy widely suggested by the Portuguese Ministry of Education for the Geology teaching whose aim is to promote the development of skills (knowledge, ability and attitudes) denying the idea that the subjects of this science are complex and far from the students’ academic interests and needs. This work presents some formal and non-formal education practical activities (e.g. laboratory and fieldwork, mineral fairs, national contests), developed throughout the last year in Sé School, a small school in the north of Portugal, with students of the different grades (Kindergarten to high school).

The Indian subcontinent is one of the hotspots of deadly heat stress. Several attribution studies have shown increasing trends in heatwaves and its linkage with dry spells over South Asia. However, very few studies have investigated concurrent or successive (lagged d-day) occurrence of humid heat stress (high temperature compounded by humidity) and precipitation extremes within a short time window. Using gauge-based observation records of the last five decades, we have analyzed the concurrence of extreme wet bulb temperature, Tw and peak rain events in 9 urban locations of India, distributed over climatologically heterogeneous regions. We find a larger fraction of the population is exposed to a significant increase (more than 1% and up to 2.5%/decade) in mean and extreme Tw (around 1%/decade) in several sites than solely accounting dry-bulb temperature trends. This prompted us to analyze the compound hazard associated with storm events preceded by extreme Tw (assessed through ≥ 95 – 98.5th percentile exceedances and annual maxima series) up to a week of occurrence of the event. Considering synchronicity between two drivers (extreme Tw and peak rain), we demonstrate cities located across the western half of the country showed positive dependence, whereas those located over the eastern half show negative dependence. While negative correlation suggests the concurrence of dry and hot episodes, the positive correlation suggests robust amplification in precipitation extremes. This is confirmed by the large upper tail distributions of peak rain events during the core monsoon season (June – September) to locations showing positive dependence. Based on extreme Tw-precipitation sensitivity, we propose compound heat stress – rain-induced flood hazard model for densely populated areas. Understanding drivers of peak runoff responses would benefit risk management, insurance, and flash flood forecast, devising flood resilience under climate change.

Air-sea flux variability has contributions from both ocean and atmosphere at different spatio-temporal scales. Atmospheric synoptic scales and the air-sea turbulent heat flux that they drive are well represented in climate models, but ocean mesoscales and their associated variability are often not well resolved due to non-eddy-resolving spatial resolutions of current climate models. We deploy a physics-based stochastic subgrid-scale parameterization for ocean density, that reinforces the lateral density variations due to oceanic eddies, and examine its effect on air-sea heat flux variability in a comprehensive coupled climate model. The stochastic parameterization substantially modifies sea surface temperature (SST) and latent heat flux (LHF) variability and their correlations, primarily at scales near the resolution of the ocean model grid. Changes in the SST-LHF anomaly correlations indicate that the ocean-intrinsic component of the air-sea heat flux variability improves with respect to the satellite observational product, especially in western boundary current extensions.

A direct comparison of hydrometeor types (HMT) from state-of-the-art hydrometeor classification schemes (HMC) with modelled hydrometeors (ICOL-LAM, operational weather predictions model of the German Weather Service) is challenging, e.g. due to different HMT definitions and numbers and difficulties to identify dominant types in mixtures of hydrometeors. A comparison of published HMCs even revealed significant differences between the membership functions used for the same hydrometeor types (Figure 1), emphasizing again the high uncertainty in scattering simulations for ice hydrometeors because of their complex geometries, dielectric properties, and largely unknown size and orientation distributions. The HMCs were applied to perturbed polarimetric variables observed by the X-band Radar in Bonn (BoXPol) to test their robustness against measurement errors and show that especially in the regions with solid precipitation misclassification in hydrometeor typing occurs often. Thus, a dual strategy to evaluate the hydrometeor type representation in ICON-LAM is presented: i) Classification after clustering of the data is assumed to reduce the sensitivity of the decision to the uncertainty of scattering simulations. First an agglomerative hierarchical clustering of the radar pixels based on their similarity in multi-dimensional polarimetric signatures is applied, and afterwards for each identified cluster a comparison of the distributions of polarimetric moments with scattering simulations or membership functions for different HMT is performed. ii) A direct comparison of multivariate simulated and observed distributions of polarimetric moments. These comparisons will be performed for different heights and/or space-time subsets, and for clusters with similar HMT in the model and the observations as identified with the advanced radar-based hydrometeor classification scheme. Results for a set of case studies observed with the polarimetric X-band radar composite in Bonn, Germany, will be presented.

Carbon-capture and sequestration (CCS) in geologic reservoirs is one strategy for reducing anthropogenic CO2 emissions from large-scale point-source emitters. Recent developments have shown that basalt reservoirs are highly effective for permanent mineral trapping on the basis of CO2-water-rock interactions, which result in the formation of carbonate minerals. However, the injection of super-critical CO2 into the subsurface causes a disturbance in the pressure, temperature, and chemical systems within the target reservoir. How the ambient conditions change in response to a CO2 injection ultimately affects the transport and fate of the injected CO2. Understanding the behavior and transport of CO2 within a geologic reservoir is a difficult problem that is only exacerbated by heterogeneities within the reservoir, for example, permeability can be highly heterogeneous and exhibits significant control on the movement of CO2. The non-isothermal effects that accompany a CO2 injection are also affected by heterogeneous reservoir properties. These non-isothermal effects can lead to significant changes in temperature in both the reservoir water and rock, which can also affect the injectivity and movement of the CO2. This study is focused on gaining a better understanding of the non-isothermal effects of a CO2 injection and how the changes in temperature will affect the movement and reactivity of the CO2, as well as investigate the efficacy of using temperature as a proxy for CO2 breakthrough in the subsurface. iTOUGH2 eco2n is utilized to simulate CO2 injections into a 1D radially symmetric domain over a range of permeabilities, porosities, and salinities. Preliminary results indicate that for a modest CO2 injection rate of 31,500 metric tons/year the exothermic dissolution of CO2 can cause a temperature increase of up to 3.6oC at the edges of the CO2 plume and the Joule-Thomson effect can cause a decrease in temperature up to 10oC near the injection well. Additionally, results from this study indicate that the thermal effects of a CO2 injection, namely the heat of dissolution associated with a large-scale CO2 injection may be an effective MMV strategy for monitoring CO2 breakthrough.

Under persistent eutrophication of European water bodies and a changing climate, there is an increasing need to evaluate mitigation measures for reducing nutrient losses from agricultural catchments. In this study, we set up a daily discharge and water quality model in Hydrological Predictions of the Environment for two contrasting agricultural catchments in Sweden to forecast the impacts of future climate trajectories on nutrient loads. The model predicted a slight increase in inorganic nitrogen (IN) and total phosphorus (TP) loads under RCP2.6, likely due to precipitation-driven mobilisation. Under RCP4.5 and RCP8.5, the IN loads were forecasted to decrease from 16%-26% and 21%-50% respectively, most likely due to temperature-driven increases in denitrification and evapotranspiration. No distinct trends in TP loads were observed. A 50% decrease in nutrient loads, as targeted by the European Green Deal, was backcasted using a combination of mitigation scenarios, including i) a 20% reduction in mineral fertiliser, ii) introducing cover crops, and iii) stream mitigation by increasing the size of floodplains and wetlands. Target TP load reductions could only be achieved by stream mitigation, which is likely due to legacy effects and secondary mobilisation within agricultural streams. Target IN load reductions were backcasted with a combination of stream mitigation, fertiliser reduction, and cover crops, wherein the required measures depended on the climate. Overall, the diverging responses of nutrients to climate change and mitigation scenarios indicate that water quality management needs to be tailored to the catchment characteristics, and to the spatial and time specific effects of climate change.

The physical circulation of the Southern Ocean sets the surface concentration and thus air-sea exchange of CO2. However, we have a limited understanding of the three-dimensional circulation that brings deep carbon-rich waters to the surface. Here, we introduce and analyze a novel high-resolution ocean model simulation with active biogeochemistry and online Lagrangian particle tracking. We focus our attention on a subset of particles with high dissolved inorganic carbon (DIC) that originate below 1000 m and eventually upwell into the surface mixed layer. We find that 71% of the DIC-enriched water upwelling across 1000 m is concentrated near topographic features, which occupy just 33% of the Antarctic Circumpolar Current. Once particles upwell to the surface mixed layer, their DIC decorrelates on timescales of ~1.5 months—an order of magnitude longer than their residence time. Our results show that Southern Ocean bathymetry plays a key role in delivering carbon-rich waters to the surface.

Atmospheric drag is one of the primary sources of error in the orbit determination and prediction of satellites in the low altitude LEO regime. Accurate modeling of the drag force is limited by uncertainties in the atmospheric density model used in the filter and the assumption of a constant drag coefficient, the so-called ‘cannonball’ model. Over the last two decades, various advances in density and drag-coefficient modeling have been made possible through the development of empirical and physics-based dynamical calibration techniques and machine-learning methods respectively. But even with high-fidelity models for density and drag coefficient, systematic uncertainties can remain in both due to the lack of temporal and spatial resolution of data and insufficient knowledge of parameters that feed into these models. In this work, we develop an estimation-based Fourier expansion model that can provide corrections to the nominal values of density and drag coefficient during the orbit determination process. In an earlier work (Ray et al., 2018), we demonstrated improved orbit prediction performance over the standard cannonball model with Fourier series expansions of the drag coefficient in body frame and orbit frame of a satellite. Whereas a body-fixed Fourier model captures the dependence of the drag coefficient on satellite attitude, the orbit-fixed model corrects for periodic changes in the gas-surface interaction in orbit. Since changes in the gas-surface interaction parameters in orbit are highly correlated with atmospheric density, any existing errors in the density are absorbed in the estimated orbit-fixed coefficients. Here, we derive a body-orbit Fourier model such that the orbit-fixed terms provide corrections for combined error variations of density and drag coefficient in orbit while the body-fixed terms account for the drag coefficient attitude dependence. We analyze the performance of the proposed approach with various atmospheric models such as NRLMSISE-00 (Picone et al., 2002), JB08 (Bowman et al., 2008), HASDM (Storz et al., 2002) and densities derived by Mehta et al. (2017) for varying geomagnetic conditions for the GRACE satellite.

Due to its eccentric orbit, Mercury experiences varying gravitational pull from the Sun along its orbit, leading to periodic surface tidal deformation. The previous measurement of Mercury’s tidal h2 by Bertone et al. (2021) is based on minimizing height differences at cross-overs of the Mercury Laser Altimeter (MLA) profiles. However, this method can suffer from significant interpolation errors. In this study, we apply an alternative approach, which is based on the co-registration of reprocessed MLA profiles. For the reprocessing, we account for the pointing aberration and incorporate an updated spacecraft orbit model. Within the study region of 77°N to 84°N, we obtain a tidal h2 of 0.92±0.51 (3-σ). This value is compatible with current interior structure and rheology models, but significantly smaller than the previous estimate of 1.55±0.65 (3-σ). When combined with recent tidal k2 estimates, our measurement favors a small to medium-sized inner core.

Understanding catchment controls on catchment solute export is a prerequisite for water quality management. StorAge Selection (SAS) functions encapsulate essential information about catchment functioning in terms of discharge selection preference and solute export dynamics. However, they lack information on the spatial origin of solutes when applied at the catchment scale, thereby limiting our understanding of the internal (subcatchment) functioning. Here, we parameterized SAS functions in a spatially explicit way to understand the internal catchment responses and transport dynamics of reactive dissolved nitrate (N-NO3). The model was applied in a nested mesoscale catchment (457 km²), consisting of a mountainous partly forested, partly agricultural subcatchment, a middle-reach forested subcatchment, and a lowland agricultural subcatchment. The model captured flow and nitrate concentration dynamics not only at the catchment outlet but also at internal gauging stations. Results reveal disparate subsurface mixing dynamics and nitrate export among headwater and lowland subcatchments. The headwater subcatchment has high seasonal variation in subsurface mixing schemes and younger water in discharge, while the lowland subcatchment has less pronounced seasonality in subsurface mixing and much older water in discharge. Consequently, nitrate concentration in discharge from the headwater subcatchment shows strong seasonality, whereas that from the lowland subcatchment is stable in time. The temporally varying responses of headwater and lowland subcatchments alternates the dominant contribution to nitrate export in high and low-flow periods between subcatchments. Overall, our results demonstrate that the spatially explicit SAS modeling provides useful information about internal catchment functioning, helping to develop or evaluate spatial management practices.

We present detailed 3-D images of whole mantle P-wave velocity structure beneath Southeast Asia and surrounding regions. The results are obtained by applying an updated global tomographic method to invert ~8 million P, pP, PP, PcP, and Pdiff arrival times from 23,587 earthquakes recorded at 14,136 stations distributed all over the world. Our tomographic model reveals a continuous, thin low-velocity (low-V) zone from the surface to the core-mantle boundary beneath the Hainan hotspot, which may reflect the Hainan plume that exists in the whole mantle. Beneath the Australian slab that has subducted into the lower mantle, a strong low-V anomaly is detected, which may reflect subslab hot mantle upwelling (SHMU) due to return flow of the slab subduction. Our model also shows the distinct shape of subducted slabs in the upper mantle and slab remnants in the lower mantle. In particular, a hole in the subducting Australian slab is revealed at depths of 280–430 km beneath eastern Java. The low-V anomaly in the mantle wedge above the Australian slab is connected with the SHMU through the slab hole, suggesting that mixture of the island arc magma and the SHMU may have caused huge eruptions of the Tambora and Rinjani volcanoes in eastern Java.