The past 2 decades of research has demonstrated the value of co-production as a process that creates information that is usable to decision makers. However, research has also shown that those organizations that are already larger, more technically-capable, and located closer to the sources of new information are more likely to engage in co-production with boundary organizations. The question then arises of how smaller entities, who may actually have greater need for capacity, can benefit from investments in new science aimed at improving decision making for water management. In this project we conducted 5 case studies of the information use preferences and practices among small-scale water systems (small municipalities and Water Conservancy Districts) in the Upper Colorado River Basin to understand the opportunities and constraints for the uptake of new sources of information. Like previous work, results indicated that scale, skill, understandability, and lack of capacity limited the use of available information. Furthermore, entities did not engage in co-production with knowledge-related boundary organizations to any extent. However, small water providers did consistently mention the value of contact with other water systems in the area, and the value of being able to reach out to certain key individuals who were looked to as trusted sources of opinion on current information products and trends. Managers emphasized the importance of experience in operating a water system and involvement in operations as critical factors that engendered trust in these key individuals. Finally, certain water systems were seen as leaders in the local area, and constantly mentioned as sources of information and innovative ideas. These findings suggest the importance of both key individual practitioners in pioneering and disseminating new information, as well as more broadly the role of a community of practice in reaching small water providers. Implications for boundary organizations and emerging networks are discussed.

Mixed phase clouds, consisting of ice particles and super cooled liquid droplets, predominantly found in Arctic, are poorly represented in various climate models. A unique tethered balloon campaign carrying 4π radiometer, a cloud particle imager, and a meteorological package on board was conducted in Ny-Ålesund, Norway, located high in the Arctic at 78.91°N, 11.91°E during May-June 2008. The radiometric and cloud observations at 500nm and 800nm were collected during a month long experimental campaign. A state-of-the-art discrete ordinate radiative transfer model was used to estimate optimal cloud optical properties. These optical properties are contrasted with those of the cloud parameterization in the new NOAA-GFDL AM4 model that is presently being used in the Coupled Model Intercomparison Project 6 (CMIP6). The improved simulation of cloud optical properties will aid in understanding cloud radiation feedbacks and better representation of clouds in global climate model.

Key Points:  The HRRR model surface thermodynamic biases are seasonally dependent, presenting a systematic warm and dry bias during the warm season.  The primary locations of the summer warm and dry biases are over farmland, on days with optically thick clouds.  A hydrological bias underestimating of spring snow melt is consistent with subsequent summer warm and dry biases over farmland.

Access to accurate estimates of water withdrawal is requisite for urban planners as well as operators of critical infrastructure systems to make optimal operational decisions and investment plans to ensure reliable and affordable provisioning of water. Furthermore, identifying the key predictors of water withdrawal is important to regulators for promoting sustainable development policies to reduce water use. In this paper, we developed a rigorously evaluated predictive model, using statistical learning theory, to estimate state-level, per-capita water withdrawal as a function of various geographic, climatic and socio-economic variables. We then harnessed the data-driven predictive model to identify the key factors associated with high water-usage intensity among different sectors in the U.S. We analyzed the predictive accuracy of a range of parametric models (e.g., generalized linear models) and non-parametric, flexible learning algorithms (e.g., generalized additive models, multivariate adaptive regression splines and random forest). Our results identified irrigated farming, thermo-electric energy generation and urbanization as the most water-intensive anthropogenic activities, on a per-capita basis. Among the climate factors, precipitation was also found to be a key predictor of per-capita water withdrawal, with drier conditions associated with higher water withdrawals. Results of the first-order sensitivity analysis indicated changes between +/-10% in the future water withdrawal across the U.S., in response to precipitation changes, by the end of the 21st Century under the business-as-usual scenario. Overall, our study highlights the utility of leveraging statistical learning theory in developing data-driven models that can yield valuable insights related to the water withdrawal patterns across expansive geographical areas.

Dense acquisition are more and more available in exploration and earthquake seismology. Tomographic approaches can now consider not only travel times but also the wavefront itself across the seismic network (Zhang and Thurber, 2003; Yuan et al., 2016). For dense controlled-source seismic experiments, double differences of travel times between receivers in a common-shot gather (resp between sources in a common-receiver gather) are estimated, namely the horizontal component of the slowness vector at source and receiver positions designed as slopes. These slopes associated with the two-way traveltimes are interpreted as a reflection/diffraction from a small reflector segment or diffractor are used in tomographic inversion (Lambaré, 2008; Tavakoli F. et al., 2017). Picking of locally-coherent events leads to dense volumetric dataset and hence higher-resolution tomographic results (Guillaume et al., 2008). The reflection setting introduces implicitly another class of unknowns which are scatterer positions. Resulting inverse problem is awkward due to the intrinsic coupling between velocities and scatterer positions. The first choice alternates positions and wavespeeds. The second performs the joint estimation of the two parameter classes. The third one relies on the projection of the scatterer positions subspace onto the wavespeed subspace leading to a reduced-space inversion. This reduced-space formulation can be implemented in the slope tomography using adjoint-state method. Two focusing equations, which depend on two observables among the three available ones (two-way traveltime and one slope in 2D), gives exact solutions of positions which are injected as constraints in the slope tomography (Chauris et al., 2002). These constraints explicitly enforce the positions in the velocity estimation problem, which reduces now to a mono-variate inverse problem by minimization of single-slope residuals, not yet used. 2D synthetic (see figure) and real data case studies show faster convergence toward more accurate minimizer achieved by this variable projection method compared to the alternated and joint strategies. This method, which can be extended to 3D configurations, draws also interesting perspective for the joint hypocenter-velocity inversion problem in earthquake seismology.

Remotely sensed land surface temperature (LST) enables global modelling and monitoring carbon dioxide (CO2) fluxes from peatlands. We aimed to provide the first overview of the LST potential for monitoring ecosystem respiration (Reco) in disturbed (drained and extracted) peatlands. We used chamber measured data (2017–2020) from five disturbed and two intact northern peatlands and LST data from Landsat 7, 8, and MODIS missions. First, we studied the strength of relationships between fluxes and their in-situ drivers: thermal and moisture conditions. Second, we examined the association between LST and in-situ temperatures. Third, we compared chamber measured Reco with the modelled Reco based on (i) in-situ measured surface temperature and (ii) MODIS LST. In-situ temperatures were a stronger driver of CO2 fluxes in disturbed sites (Spearman correlation R=0.8–0.9) than in intact ones (R=0.5–0.7). LST had a higher association with in-situ measured temperatures (mean R=0.74 for MODIS) in disturbed sites and weaker in the intact peatlands (mean R=0.34 for Landsat and 0.36 for MODIS). Reco models driven by MODIS LST and in-situ surface temperature yielded similar accuracy: R-squared was 0.26, 0.64, 0.65 and 0.28, 0.68, 0.58 for intact, drained and extracted sites, correspondingly. Therefore, LST has a great potential to be utilized in Reco models as a proxy of thermal regime in disturbed and intact northern peatlands.

Aerosol particles undergo physical and chemical changes during cloud processes. In this work, we quantified the changes in aerosol mixing state using a particle-resolved model. To this end, we coupled the particle-resolved aerosol model PartMC-MOSAIC with the aqueous chemistry module CAPRAM 2.4 and designed cloud parcel simulations that mimicked several cloud cycles that a particle population may be exposed to in an urban environment. Aqueous-phase chemistry during these cloud cycles affected aerosol mixing state and the particles’ potential to act as cloud condensation nuclei (CCN) significantly, with the largest differences after the first cloud cycle. The mean size and total dry mass of the population increased by 24% and 219%, respectively, after the first cycle, while the increments were only 5% and 38% after the fourth cycle. The formation of ammonium sulfate and nitrate were responsible for those changes. Cloud processing increased the internally mixed state of all particle populations, with the mixing state index increasing from 50 to 83 percentage points after four cloud cycles. The CCN concentrations for supersaturations lower than 0.23% increased. For example, for supersaturation levels of 0.02%, the CCN concentration increased from 25 to 547 cm-3. Brownian coagulation led to an increase of the CCN/CN ratio for supersaturation levels higher than 0.2%. The ratio increased by 4.1% at the supersaturation level 0.5%. Total number concentration and CCN concentration decreased by 5.9% and 1.7%, respectively, when Brownian coagulation is considered. These findings highlight the complex influence of cloud processing on particle properties.

The splitting of the plates with SN strikes was attributed to the maximum principal stress field accumulated by the rotation of the Earth. The course of the plate breakup is as follows: any plate has to undergo 5 stages before breaking up; the 5 stages own each tectonic system; the strikes of these 5 tectonic systems gradually deflect 15° towards the rotation axis of the Earth; and after entering the 5th stage, the plate will normally be broken up. This model is supported by experiments and verified using real data from the China Plate, deriving some important conclusions. The five-stage model of plate breakup can explain the linear characteristics of rift valleys and oceanic ridges, which other hypotheses in terms of mantle convection, hot-spots and mantle plumes cannot be explained. Theoretically, the significance of this study might be its filling in gaps in the field of plate tectonics. In addition, this model unexpectedly came to a relatively simple account of why Mars and Venus do not look as our Earth has an entire plate breakup and subsequent florid biological world, mainly because of the 5° deviation between Earth and Mars (or Venus) in the direction of the resultant force that their lithospheric plates have gone through, respectively. The 5° deviation created our distinctive Earth and human beings. Throughout the Solar System, almost all planets are regular spheres except our Earth, which may be why humans is so lonely!

Pacific-Panthalassa plate tectonics back to Jurassic times are recognized as the most challenging on Earth to reconstruct, due partly to a large (>9000 km length) unconstrained area between the Pacific and Laurasia (now NE Asia) during the Early Jurassic. We built four contrasted NW Pacific-Panthalassa global plate reconstructions and assimilated their velocity fields into global geodynamic models. We compare our predicted mantle structure, synthetic geoid and dynamic topography to Earth observations. P-wave tomographic filtering of predicted mantle structures allowed for more explicit comparisons to global tomography. Plate reconstructions that include intra-oceanic subduction in NW Pacific-Panthalassa fit better to the observed geoid and residual topography, challenging the Andean-style subduction along East Asia. Our geodynamic models predict significant SE-ward lateral slab advections within the NW Pacific basin lower mantle (~2500 km from Mesozoic times to present), which can confound “vertical slab sinking”-style restorations of past subduction zone locations.

Arctic sea ice has substantially changed over the past four decades, with a large decrease in sea-ice area and volume. The exact causes of these changes are not entirely known. In our study, we make use of the Swedish Meteorological and Hydrological Institute Large Ensemble (SMHI-LENS). This ensemble consists of 50 members realized with the EC-Earth3 global climate model and covers the period 1970-2100. We apply the Liang-Kleeman information flow method to analyze the cause-effect relationships between Arctic sea ice and its potential drivers. We show that recent and future changes in Arctic sea ice are mainly driven by air and sea-surface temperatures and ocean heat transport. Conversely, changes in Arctic sea ice also considerably impact temperature and ocean heat transport. Finally, we find a progressive decrease in the influence of sea-ice area and volume on air temperature and ocean heat transport through the twenty-first century.

Attaining a comprehensive and reliable water balance of snow-dominated alpine catchments is fundamental for a holistic representation of the hydrological and hydrogeological processes. A major limitation to the elaboration of this balance in alpine terrain is the difficultly of data acquisition as well as the limited presence of meteorological stations. Remotely sensed data can provide valuable information for the balance elaboration at a regional scale. We exploited Sentinel-satellite data to estimate the groundwater storage for one hydrologic year in an extensive Alpine catchment located in northern Italy. Evapotranspiration (ET) and Snow Water Equivalent (SWE) were estimated once weekly with the combined use of Sentinel data, at a spatial resolution of 20 m and 30 m, respectively. Finally, the groundwater storage was estimated by means of the residual water balance approach. The results show that the adopted satellite-based methods allow obtaining consistent and physically realistic values to describe the groundwater storage dynamics, with a relatively low uncertainty (36%). For the studied hydrologic year, a positive storage occurred only in the snowmelt period and the overall storage was negative, leading to a lowering of the groundwater level in the floodplain. In addition, the influence of physiographic parameters (altitude, slope, and aspect) and the seasonal conditions on the estimates of ET and snow-depth were investigated. For SWE estimates, an altitude-dependent effect and a lower accuracy in the snowmelt phase were observed. Finally, the estimated values of ET and the SWE-linked components were verified for a gauged tributary valley with negligible groundwater storage.

The Greenland Ice Sheet discharges ice to the ocean through hundreds of outlet glaciers. Recent acceleration of Greenland outlet glaciers has been linked to both oceanic and atmospheric drivers. Here, we leverage temporally dense observations, regional climate model output, and newly developed time series analysis tools to assess the most important forcings causing ice flow variability at one of the largest Greenland outlet glaciers, Helheim Glacier, from 2009 to 2017. We find that ice speed correlates most strongly with catchment-integrated runoff at seasonal to interannual scales, while multi-annual flow variability correlates most strongly with multi-annual terminus variability. The multiple relevant time scales and the influence of subglacial topography on Helheim Glacier’s dynamics highlight different regimes that can inform modeling and forecasting of its future. Notably, our results suggest that the recent terminus history observed at Helheim is a response to, rather than the cause of, upstream changes.

This study investigates the spontaneous self-aggregation of convection in non-rotating Radiative-Convective Equilibrium (RCE) simulations performed by the CNRM-CM6-1 General Circulation Model within the framework of the RCE Model Intercomparison Project (RCEMIP). In this model, the level of convection self-aggregation at equilibrium, as quantified by metrics based on moisture or moist static energy, strongly increases with sea surface temperature (SST). As it gets warmer, the troposphere gets drier, high cloud cover diminishes in dry regions, the top of high cloud rises and their thickness increases in moist regions, and low cloud cover increases. At high SSTs, the large-scale circulation exhibits a shallow component, stronger than its deep counterpart. The transition towards self-aggregation has a similar first 20-day phase for all SSTs within the 295-305-K range. It primarily involves radiative positive feedback processes. Then, for SSTs above approximately 300 K, a new, slower, transition towards higher levels of self-aggregation occurs. It is concomitant with a shift from a top-heavy to a more bottom-heavy large-scale circulation, a strengthening of the shallow circulation and a reduced mobility of convective aggregates. This second transition is mostly driven by the dry regions, still involves longwave radiative positive feedbacks, but also advective positive feedbacks in the driest regions. It is argued that boundary-layer radiative cooling difference between moist and dry regions, which is stronger at high SSTs, is instrumental in this second phase of self-aggregation. The sensitivity of deep convection to environmental dry air also likely acts as a positive feedback on the system.

The flow of CO2 foam for mobility control in porous media is dictated by the foam texture, or bubble density, which is commonly expressed as the number of bubbles per unit of flowing gas. In most high-pressure laboratory studies of foam in porous media, the local foam texture cannot be determined due to opaque flow systems. Here, we unlock real-time foam texture dynamics at high pressure (100 bar) by utilizing a realistic pore network with an extended field of view. We identified snap-off as the dominant foam generation mechanism, with additional fining of foam texture caused by backward foam propagation. Foam coalescence during continuous CO2 injection resulted in large gas channels parallel to the general flow direction that reduced the overall foam apparent viscosity. A large fraction of the CO2 foam remained trapped (X_t > 0.97) and stationary in pores to divert CO2 flow and increase sweep efficiency. The gas mobility was calculated from the fraction of trapped bubbles at the pore-scale, and the apparent foam viscosity was in agreement with similar injection test performed at core-scale. Hence, improved understanding of CO2 foam texture evolution (n_f) can strengthen the validation of numerical foam models for physical upscaling of flow phenomena, instrumental in the development of field scale implementation of CO2 foam for in carbon utilization and storage applications.

We present a statistical investigation of the effects of interplanetary magnetic field (IMF) on hemispheric asymmetry in auroral currents. Nearly six years of magnetic field measurements from Swarm A and C satellites are analyzed. Bootstrap resampling is used to remove the difference in the number of samples and IMF conditions between the local seasons and the hemispheres. Currents are stronger in Northern Hemisphere (NH) than Southern Hemisphere (SH) for IMF B$y^+$ in NH (B$y^-$ in SH) in most local seasons under both signs of IMF B$z$. For B$y^-$ in NH (B$y^+$ in SH), the hemispheric difference in currents is small except in local winter when currents in NH are stronger than in SH. During B$y^+$ and B$z^+$ in NH (B$y^-$ and B$z^+$ in SH), the largest hemispheric asymmetry occurs in local winter and autumn when the NH/SH ratio of field-aligned current (FAC) is 1.18$\pm$0.09 in winter and 1.17$\pm$0.09 in autumn. During B$y^+$ and B$z^-$ in NH (B$y^-$ and B$z^-$ in SH), the largest asymmetry is observed in local autumn with NH/SH ratio of 1.16$\pm$0.07 for FAC. We also find an explicit B$y$ effect on auroral currents in a given hemisphere: on average B$y^+$ in NH and B$y^-$ in SH causes larger currents than vice versa. The explicit B$y$ effect on divergence-free (DF) current during IMF B$z^+$ is in very good agreement with the B$y$ effect on the cross polar cap potential (CPCP) from the Super Dual Auroral Radar Network (SuperDARN) dynamic model except at SH equinox and NH summer.

Atmospheric rivers (ARs) are responsible for the vast majority (approximately 88%) of flood damage in the Western U.S, an annual average of USD$1.1 billion. Here, using historical flood insurance data, we investigate the genesis characteristics of damaging ARs in the Western U.S. ARs exceeding USD$20 million in damage (90th percentile), are shown to travel further across the Pacific Ocean, with median genesis locations 8° to 27° longitude further westward compared to typical ARs. Identifying regions of preferential genesis of damaging ARs elicit important implications for AR observation campaigns, highlighting distant regions not currently considered for AR reconnaissance. The genesis of damaging ARs is associated with elevated upper-level zonal wind speeds along with deeper cyclonic anomalies, most pronounced for Washington and Oregon ARs. Linking AR dynamics and lifecycle characteristics to economic damage provides an opportunity for impact-based forecasting of ARs prior to landfall, supporting efforts to mitigate extreme flood damages.

Electrostatic solitary waves (ESWs) are a type of nonlinear time-domain plasma structure (TDS) generally defined by bipolar electric fields and propagation parallel to the local magnetic field. Formation mechanisms for TDSs in the magnetosphere have been studied extensively and are associated with plasma boundary layers and the braking of bursty bulk flows (BBFs). However, the rapid timescales over which these TDSs occur (< 2 ms) make them infeasible to count by eye over large time periods. Furthermore, high-cadence data are not always available. The Solitary Wave Detector (SWD) on NASA’s Magnetospheric Multiscale (MMS) mission quantifies the occurrence and amplitude of TDS throughout the constellation’s orbit; analysis of burst (65 kS/s) parallel electric field data indicates that the SWD captures appx. 60% of all bipolar TDS encountered in the tail region, enabling large-scale examination of their occurrence. Maps of TDS occurrence rates during several years of the MMS mission were generated from SWD data, showing enhanced TDS density in the tail region between 6-9 Re; enhance occurrence in or near shocks; and an unexpected enhancement in the dawn side of the tail and in the radiation belt.

Observational data from the past century show a weakening trend in summer monsoon over the Indian subcontinent. This is possibly attributed to the reduced land–sea contrast resulting from the Indian Ocean warming under the rapid increase of greenhouse gases in the atmosphere. In contrast, speleothem records indicate that the Indian summer monsoon was stronger during the last interglacial (LIG) warm period than it is today. Using climate model simulations, we show that orbital forcing effect during the LIG, as well as related ocean feedbacks, led to warming in the Eurasian continent and cooling in the Indian Ocean basin. This amplified the land–sea contrast in the region and intensified the Indian summer monsoon. Although the LIG is often portrayed as a potential analogue of future climate, our study shows that the Indian monsoon responded differently to the LIG warming period than it does to current climate warming.