The measurement and processing of high frequency acoustic backscatter profiles at multiple frequencies is an established technique for measuring suspended sediment load and equivalent mean particle size through the water column. The technique relies on the fact that the intensity of sound scattered by suspended particles is related not only to the particle size, but also the incident acoustic frequency. It is exploited by compact instruments that are deployed on seabed frames, vessels, and in laboratory flumes. However, one of the most significant influences on measurement accuracy comes from the presence of bubbles in the water column. Often found in suspended sediment study areas such as shallow wave-affected waters or highly turbulent flows, they can be of comparable acoustic cross-section to the suspended sediment particles and may dominate backscatter. Acoustic backscatter instrument calibrations and experimental measurements are typically carried out in a recirculating suspended sediment tower where, through careful design, a near homogeneous suspension can be established. Great attention is paid to the choice of fittings and recirculating pumps to ensure that no air is introduced into the flowing liquid, and lengthy periods of degassing are necessary to ensure no bubbles remain before measurements are taken. To tackle the problem of sediment backscatter signal contamination, a new research project is investigating how to detect and quantify bubbles present in sediment suspensions, with the aim of decomposing the backscatter signal into its sediment and bubble components. The first step in evaluating new acoustic techniques is to welcome back the bubble to the sediment tower from its long exile so it can become the focus of observations. The paper describes the recirculating suspended sediment tower and the newly introduced bubble generation and observation apparatus, which is being used to generate and observe controlled bubble populations. Bubble detection and measurement techniques are described, and initial results using a commercial acoustic backscatter profiler are presented.

Multi-frequency acoustic backscatter measurement can be used to observe spatial profiles of suspended sediment. The use of multiple frequencies helps to resolve mean particle size by exploiting the frequency-dependent relationship between scattering intensity and particle size. The AQUAscat acoustic backscatter profiler uses this principle to estimate mean particle size and concentration profiles with spatial resolution between 2.5 mm and 40 mm. The instrument is usually configured to acquire profiles of backscatter amplitude. However, an infrequently used setting on the standard instrument provides direct access to the quadrature sampled backscatter data stream, from which amplitude is normally calculated. By using the in-phase and quadrature sample data, the backscatter phase can also be calculated. The rate of phase change between profiles can then be related to the along-beam velocity of the scatterers. For a vertical beam, in the absence of vertical water motion, this is the settling velocity. This paper evaluates datasets and data processing approaches for estimating particle settling velocity. The experimental data is acquired with various types of laboratory generated suspensions, including glass spheres, sands, and flocculating mud. Besides extracting settling velocity data, the processing aim is to enhance the quality of acoustic backscatter data analysis.

Particle Image Velocimetry (PIV) is a proven technique for the observation of flow or particle motion in fluids. A pulsed laser is used to create a thin plane of light in the fluid, which typically contains a suspension of neutrally buoyant tracer particles. A high speed camera captures a sequence of images, which are processed to develop velocity vector fields from the particle motion. During a wider study into the observation of particle and bubble terminal velocity in water using an acoustic backscatter profiler in a recirculating sediment tower, the acoustic data appeared to reveal a more complex flow regime than expected. To verify the acoustic results, PIV was selected as a potential approach to monitor particle motion in the region of the tank where acoustic observations were being made. Review of available PIV equipment showed that even systems designed for educational use would be beyond the budget of the planned experimental program. A search of the cupboards yielded an alternative set of equipment with potential promise. A DIY laser level and an aging GoPro camera were pressed into action for a series of tests to investigate whether the combined equipment would be sufficiently sensitive and rapid to capture the particle motion satisfactorily. It would. This paper describes the equipment configuration and the range of measurements achieved. Results from data processed with the open source PIVlab software tool are presented in the context of validating acoustic measurements of particle terminal velocity.

The correct simulation of fog and low stratus (FLS) is a difficult task for numerical weather prediction (NWP) models. The Swiss Plateau experiences many days with FLS in winter. Most NWP models employ terrain-following vertical coordinates. As a consequence, the typically flat cloud top is intersected by sloping coordinate surfaces above hilly terrain such as the Swiss Plateau. Horizontal advection across the sloping coordinate surfaces leads to spurious numerical diffusion which promotes erroneous FLS dissipation. To address this problem, we propose a new vertical coordinate formulation which features a local smoothing of the model levels. We demonstrate the positive impact of the new vertical coordinate formulation on a case study in detail and for a full month using the COSMO model. The improved vertical coordinate formulation is not yet sufficient to obtain perfect FLS forecasts, it is however a crucial aspect to consider on the way thereto.

In 2012, Aquatec launched an equipment award scheme for postgraduate students and early career scientists. Successful recipients with limited budgets gain free access to high quality subsea instrumentation for a laboratory or ‘eld campaign of up to three months, plus a travel grant to allow them to present their work at a conference. So far there have been 11 successful awardees who have applied from or deployed instruments in 13 countries spanning ’ve continents, in *umes, lakes, rivers, and coastal seas. In this paper, we present an overview of the most successful award projects. We also evaluate the impact of the scheme on the award recipients’ chosen project work and how it in*uenced their future career. The evaluation draws on analysis of the recipient study reports and the use of questionnaires and interviews. The scheme has also suffered the occasional setback. We attempt to identify some of the potential pitfalls of such a program, and highlight the key factors that lead not only to the best student experience, but also a positive outcome for the awarding company

South-east Asia is one of the most volcanically active places on Earth, with the majority of the volcanoes located in Indonesia and in the Philippines. Indochina (Myanmar, Cambodia, Laos, Thailand and Vietnam) also hosts a certain number of volcanoes that for several reasons (post-World War II conflicts, little accessibility due to dense vegetation, no significant historical activity recorded), have been little studied so far. Some of these volcanoes show evidence of recent (Quaternary) activity, therefore, a systematic assessment of the threat these volcanoes may pose to resident populations is needed in the region. A recent study on the inferred location of the Australasian meteorite impact (the largest known young meteorite on Earth) provided an unprecedented amount of data for the Bolaven Volcanic Field in Laos, in terms of geological mapping, location of vents, and over 30 absolute ages of lava flows and vents. On this basis, besides additional data obtained for this work, we used the Bolaven Volcanic Field as a case study, to assess the potential exposure of populations and infrastructure to lava flows in case of an eruption in the field. Key results suggest that an overall area of ~5500 km2 is potentially exposed to lava flows in case of eruption, including over 2000 km of roads, 400 km of power lines, two power stations and two dams, and over 500 km2 of agricultural lands, with the potential to affect about 300,000 people living in this area, and their main businesses (hydropower and coffee production). In addition, the abundance of water in this region may lead to life-threatening explosions from phreatomagmatic eruptions. Finally, based on the data available we provide a maximum estimate of the past eruption frequency of the field, which is approximately 10,400 years. Our study provides a number of techniques and approaches (remote sensing of potential sources and past flows, lava flow simulations and open-access exposure data) that can be used to assess hazards and exposure at other understudied volcanoes.

Regional transport has been identified as an important contributor to air pollution. Yet, understanding evolution of aerosol components associated with synoptic systems remains limited, particularly in China, where most of the measurement studies were conducted at ground-surface. In this study, an intensive campaign was designed with an aircraft measurement in Northeast China (NEC) together with ground-surface measurements in North China Plain (NCP), to investigate the role that the mid-latitude cyclone plays in transporting air pollution, specifically in changing aerosol components during the transport. During a flight on 30 July 2018, high concentrations of aerosols dominated by sulfate were observed in the free troposphere (FT), despite low aerosol loadings dominated by organics in the planetary boundary layer. Model simulations indicated that pollution in the lower free troposphere (LFT) was transported directly from North Hebei by warm and moist air masses, while pollution in the higher free troposphere (HFT) was influenced by the warm conveyor belt (WCB), which transported aerosols from the NCP and lifted them into the HFT. Both particulate nitrate and sulfate were formed productively due to strong emissions and high atmospheric oxidizing capacity in the NCP. During the transport, sulfate concentrations stayed relatively constant while nitrate decreased readily due to evaporation losses, resulting in an increasing contribution of sulfate but a decreasing contribution of nitrate to secondary aerosols along the transport path.

Catchment-scale streamflow assessment in the paddy-dominated catchments using the available hydrological models is highly intricate due to the presence of significant ponding water during the rainy season and irrigation events. While the Soil and Water Assessment Tool (SWAT) and Variable Infiltration Capacity (VIC) model could be some suitable options for this, the model conceptualization, discretization of spatial domain, involved computational time, and these integrated effects on streamflow simulation are yet to be evaluated. Hence, this study evaluates the performances of the semi-distributed hydrologic response unit (HRU) based SWAT-pothole and grid-based VIC model for catchment-scale streamflow simulation; and subsequently, assesses the effect of the spatial domain representation of the catchment on the model computational requirement. The selected study is the 12,014 km2 Kangsabati River basin (KRB) of eastern India that consists of about 46% paddy land use with the tropical monsoon type climate having complex paddy field dynamics. SWAT is set up for the whole KRB using the add-in reservoir module; whereas the VIC model, due to the absence of reservoir module, is set up individually for the upstream river catchment and the downstream reservoir-catchment command. The SWAT setup consisted of 44 and 191 discrete sub-basins and HRUs, respectively. Conversely, the VIC setup resulted in 31 grids with 0.25°0.25° spatial discretization. The model simulation results reveal that the SWAT-pothole approach performed better with the Nash-Sutcliffe Efficiency (NSE) estimate of 0.79 than the standalone VIC model (NSE=0.68). However, the other water balance components, viz. evapotranspiration, baseflow, and percolation are far away from reality in both the models which could be attributed to the non-accountability of irrigation return flow by the SWAT-pothole model. The inferior water balance simulation in VIC could be aggravated due to the absence of crop management module and ignorance of explicit paddy land use class in a VIC grid. These findings highlight the future scope of including more dynamic spatial representation of paddy land use in the SWAT and VIC model domain for their application in other similar world river basins.

Surge-type glaciers are present in many cold environments in the world. These glaciers experience a dramatic increase in velocity over short time periods, the surge, followed by an extended period of slow movement, the quiescence. The detailed processes that control this intermittent behaviour remain elusive. We develop a machine learning framework to classify surge-type glaciers, based on their location, exposure, geometry, surface mass balance and runoff. We apply this approach to the Svalbard archipelago, a region with a relatively homogeneous climate. We compare the performance of logistic regression, random forest, and extreme gradient boosting (XGBoost) machine learning models that we apply to a newly combined database of glaciers in Svalbard. Based on the most accurate model, XGBoost, we compute surge probabilities along glacier centerlines and quantify the relative importance of several controlling features. Results show that the surface and bed slopes, ice thickness, glacier width, surface mass balance and runoff along glacier centerlines are the most significant features explaining surge probability for glaciers in Svalbard. A thicker and wider glacier with a low surface slope has a higher probability to be classified as surge-type, which is in good agreement with the existing theories of surging. Finally, we build a probability map of surge-type glaciers in Svalbard. Our methodology could be extended to classify surge-type glaciers in other areas of the world.

Past and projected changes in global hydroclimate in Earth system models have been examined. The Budyko framework that relates the partitioning of precipitation into evaporation to a location’s aridity has been modified to account for the effect of interannual terrestrial water storage and compared to traditional methods. The new formulation better fits climate model data over most of the globe. Old and new formulations are used to quantify changes in the spatial patterns of hydroclimate based locally on year-to-year variations water and energy cycle variables. Focus is on multi-model median responses to changing climate. The changes in hydroclimate from preindustrial to recent historical (1965-2014) conditions often have different patterns and characteristics than changes due only to increasing CO2. For simulations with gradually increasing CO2, differing model treatments of vegetation are found specifically to have categorically different impacts on hydroclimate, particularly altering the relationship between aridity and the fraction of precipitation contributing to evaporation in models that predict vegetation changes. Models that predict vegetation phenology have consistently different responses to increasing CO2 than models that do not. Dynamic vegetation models show more widespread but less consistent differences than other models, perhaps reflecting their less mature state. Nevertheless, there is clearly sensitivity to vegetation that illustrates the importance of including the representation of biospheric shifts in Earth system models.

Streams play a critical role in attenuating the excess reactive nitrogen generated from human activities. These systems can consequently also emit significant amounts of N2O, a potent greenhouse gas. Models and manipulative experiments now suggest that hydrology regulates the balance between nitrogen removal and N2O production. We aimed to empirically test this hypothesis by measuring changes in the concentration and isotopic composition of NO3- (δ18O, δ15N) and N2O (δ18O, δ15N, site preference) in hyporheic sediments and surface water of a 30 m reach over eight days of falling stream discharge (2.7 to 1.8 m3 s-1). The stream was persistently heterotrophic (productivity/respiration: 0.005 - 0.2), while changes in conductivity, δ18O-H2O, and 222Rn indicated that hyporheic mixing decreased and net groundwater inputs increased as discharge declined. The shallow groundwater had high inorganic N concentrations (2 – 10 mg l-1), but increased groundwater inputs could not fully explain the concurrent increases in NO3- (1 – 3 mg N l-1) and N2O (700 to 1000 % saturation) in the surface water. Biologically, rather than solely hydrologically, regulated stream nitrogen export was confirmed by changes in N2O and NO3- isotopic composition. However, isotope patterns indicated that nitrification, not denitrification, increased surface water NO3- and N2O concentrations as hyporheic exchange decreased. These findings empirically demonstrate how flow dynamics regulate biological NO3- production as well as transport, with implications for predicting aquatic N2O emissions.

The Sixth Phase of the Coupled Model Intercomparison Project (CMIP6) provides the long-term soil moisture (SM) products and this study conducts a comprehensive assessment of SM products of multiple CMIP6 model simulations over conterminous China. Both near-surface (0-10 cm) SM simulations from 40 models and root-zone (0-100 cm) SM from 25 models are compared with a set of station measurements in the growing season (April to September) for 1992-2013 in term of magnitude, spatial and temporal variability, and the long-term trend and interannual variability of near-surface SM for 1961-2014 are further evaluated with an offline land surface modeling dataset. Simulations from most models broadly capture the spatial characteristics of observation and the multi-model mean (MME) well reproduces seasonal variations over majority regions regardless of large-spread across models. Models from the same institution likely manifest similar performances and the land surface scheme plays a dominant role in the SM reproduction. The majority of models well simulate the overall drying trend in China as a whole and the signs of SM trend are highly consistent across models, but the areas with significant wetting/drying trends vary with models. The spatial patterns of SM interannual variability are model-dependent in term of spatial patterns. MME is overall superior to the simulations of individual model and may have potential applications in the future research. The heterogeneity SM performances across models reveal the complexity in modeling land surface variables, suggesting the need for improving representations of land surface processes in the coupled models.

Bangladesh is one of the most vulnerable countries of the world in the event of climate change due to its unique geographical location. This study assessed the impact of climate change on precipitation and temperature extremes over Bangladesh from Coupled Model Intercomparison Project Phase 6 (CMIP6) models under four SSP-RCP (Shared Socioeconomic Pathway-Representative Concentration Pathway) scenarios (SSP126, SSP245, SSP370, and SSP585). At first quantile mapping (QM) method was employed to produce bias-corrected daily data. Then the future changes in climate extremes were assessed using a subset of extreme temperature and precipitation indices devised by the Expert Team on Climate Change Detection and Indices (ETCCDI). For the assessment of precipitation extremes, Consecutive Wet Days (CWD), Number of days with rainfall greater than 10mm (R10mm), Wet Days Precipitation (R95p), total annual rainfall (PRCPTOT), annual maximum 1-day precipitation (Rx1day), and annual maximum 5-day precipitation (Rx5day) have been utilized while for the temperature extremes, frequency of hot days (TX90p) and cool days (TX10p) have been used. The results from the probability density function (PDF) of most of the precipitation indices show rightward shifting in the future indicating a tendency toward wetter conditions. However, the magnitudes of change were different for the selected CMIP6 Global Climate Models (GCMs). The projected increase in CWD is greater over the south-western region of the country while the projected increase in PRCPTOT is greater over the north-eastern region of the country under all scenarios. R10mm shows the highest increase for the SSP585. In response to climate change, the TX90p shows a general increase in this century. However, the frequency of cool days is projected to decrease for most of the SSP scenarios. The results from these analyses present an opportunity to understand the impact of climate change on extreme events in Bangladesh and thus may help the local decision-makers in policy-making, disaster management, and infrastructure planning.

Experiments with six CMIP6 models were used to assess the climate feedback parameter for net historical, historical greenhouse gas (GHG) and anthropogenic aerosol forcings. The net radiative feedback is found to be more amplifying (higher effective climate sensitivity) for aerosol than GHG forcing, and hence also more amplifying for net historical (GHG + aerosol) than GHG only. We demonstrate that this difference is consistent with their different latitudinal distributions. Historical aerosol forcing is most pronounced in northern extratropics, where the boundary layer is decoupled from the free troposphere, so the consequent temperature change is confined to low altitude and causes low-level cloud changes. This is caused by change in stability which also affects upper-tropospheric clearsky emission, both affecting shortwave and longwave radiative feedbacks. This response is a feature of extratropical forcing generally, regardless of its sign or hemisphere.

As the Arctic climate rapidly warms, there is a critical need for understanding variability and change in the Arctic carbon cycle, but a lack of long-term observations has hindered progress. This work analyzes and interprets measurements of atmospheric carbon dioxide (CO2) mixing ratios from long-term on-ice measurements (the O-Buoy Network), as well as coastal observatories from 2009-2016. The on-ice measurements show smaller seasonal amplitudes when compared to the coastal observatories, in contrast to the general observation of poleward increases of seasonal cycle amplitude. Average on-ice mixing ratios were lower than their coastal counterparts during the winter and spring months, contradicting the expectation that wintertime presents a poleward increasing gradient of CO2. We compare the observations to CO2; simulated in an updated version of the GEOS-Chem 3-D chemical transport model, which includes new tracers of airmass history and CO2; sources and sinks. The model reproduces the observed features of the seasonal cycle and shows that terrestrial biosphere fluxes and synoptic transport explain most CO2; variability over the surface of the Arctic Ocean. Interannually, the coastal observations were more comparable in overall CO2; growth than concurrent measurements over sea ice. We find evidence indicating the presence of ocean gas exchange in and around sea ice during periods where this growth discrepancy occurs. Periods with large spatial gradients are examined, showing that release of CO2; from Arctic waters in years with low sea ice concentration could possibly contribute to the greater interannual increase of CO2; over sea ice compared to land.

Secondary organic aerosols (SOA) are formed from oxidation of hundreds of volatile organic compounds (VOCs) emitted from anthropogenic and natural sources. Accurate predictions of this chemistry are key for air quality and climate studies due to the large contribution of organic aerosols to submicron aerosol mass. Currently, only explicit models, such as the Generator for Explicit Chemistry and Kinetics of Organics in the Atmosphere (GECKO-A), can fully represent the chemical processing of thousands of organic species. However, their extreme computational cost prohibits their use in current chemistry-climate models, which rely on simplified empirical parameterizations to predict SOA concentrations. Recent applications of atmospheric chemistry emulation with machine learning (ML) applied to the simpler chemical mechanisms of tropospheric ozone have shown its ability to produce realistic predictions and significantly reduce the computational cost. This study proves that ML can accurately emulate SOA formation from an explicit chemistry model for several precursors with 100 to 100,000 times speedup over GECKO-A, making it computationally usable in a chemistry-climate model. To train the ML emulator, we generated thousands of GECKO-A box simulations sampled from a broad range of initial environmental conditions, and focused on the chemistry of three representative SOA precursors: the oxidation by OH of two anthropogenic (toluene, dodecane), and one biogenic VOC (alpha-pinene). We compare fully-connected and recurrent neural network methods and use an ensemble approach to quantify their underlying uncertainty and robustness. The SOA predictions generally remain stable over a simulation period of 5 days with an approximate error of 2-8\%.

Current three-dimensional, data-based models for the terrestrial exosphere have been derived from measurements of optically thin Lyman-alpha (Ly-α) emissions scattered by neutral hydrogen atoms. Such models are only valid for the middle exospheric region (3-8 Earth radii geocentric distances) since the orbital paths of the space-based platforms used to acquire Ly-α radiance were located within the exosphere, thus precluding the proper detection of the faint outer exospheric emission. Notwithstanding, accurate specifications of density distributions beyond 8 RE are needed to support comprehensive studies of the solar-terrestrial interactions. Two upcoming missions, the Solar wind Magnetosphere-Ionosphere Link Explorer (SMILE) and the Lunar Environment Heliospheric X-ray Imager (LEXI), will image the Earth’s magnetosheath in soft X-rays, and neutral densities are crucial to extract ion distributions through inversion of the acquired images. This work develops a technique to estimate the Earth’s outer exospheric density distributions using far-ultraviolet wide-field data acquired by the Lyman-Alpha Imaging Camera (LAICA) onboard the Proximate Object Close Flyby with Optical Navigation mission. Our approach formulates an inverse problem based on the linearity between measurements of scattered Ly-α flux and the local atomic hydrogen density, which is solved using the Bayesian approach known as Maximum a posteriori estimation. We use the LAICA image to derive global, 3-D hydrogen density distributions at 6-35 RE geocentric distances. We find that the spatial structure of the outer exosphere agrees well with the predictions of radiation pressure theory. Further, we find that the mean hydrogen density at 10 RE subsolar point is 26.51 atoms/cm3.

Many researchers have studied the terrestrial water cycle at global and local scales, determining the reasons for its change over time, space, and changing climates. However, event-wise analysis in a higher frequency variability (e.g., daily scale) of surface water flow and the associated complexity in its change remains unexplored. We define magnitude and duration for wet and dry phases of CaMa-Flood simulated discharge (forced by 10 CMIP6 model runoffs) for two future scenarios (SSP126 and SSP585) and compare them with their respective historical scenario to unravel the intricacies accompanied by shifts in discharge under climate change. We found a substantial wet-dry asymmetricity in magnitude and duration shifts, particularly for extreme events. Further, these asymmetric shifts are more prominent for the dry phase than the wet phase for the duration of events, whereas magnitude shifts in the wet phase are more pronounced than the dry phase. There is an intensification of magnitude and duration of moderate events for both dry and wet phases, while for extreme events increase in wet phase magnitude and duration is complemented by a decrease in dry phase changes. Additionally, the discharge shifts are associated with relatively homogenous magnitude-duration shifts for the dry phase than the wet phase, particularly for extreme events. Our research reveals a rather voluminous wet-phase shift than dry-phase shifts but lengthier dry-phase shifts than wet-phase shifts for warmer climates in the future that tend to intensify with additional warming for most regions of the world.