Most atmospheric models consider radiative transfer only in the vertical direction (1D), as 3D radiative transfer calculations are too costly. Thereby, horizontal transfer of radiation is omitted, resulting in incorrect surface radiation fields. The horizontal spreading of diffuse radiation results in darker cloud shadows, whereas it increases the surface radiation in clear sky patches (cloud enhancement). In this study, we developed a simple method to account for the horizontal transfer of diffuse radiation. We spatially filter the surface diffuse radiation field with a Gaussian filter, which is conceptually simple and computationally efficient. We applied the filtering to the results of Large-Eddy Simulations for two summer days in Cabauw, the Netherlands, on which shallow cumulus clouds formed during the day. We obtained the optimal filter size by matching the simulation results with detailed high-quality observations (1Hz). Without the filtering, cloud enhancements are not captured, and the probability distribution of global radiation is unimodal, whereas the observed distribution is bimodal. After filtering, the probability distribution of global radiation is bimodal and cloud enhancements are simulated, in line with the observations. We found that small changes in the filter width do not strongly influence the results. Furthermore, we showed that the width of the filter can be parameterized as a linear function of e.g. the cloud cover. Hence, this work presents a proof-of-concept for our method to come to more realistic surface irradiances by filtering diffuse radiation at the surface.

A document by Jon Vandegriff. Click on the document to view its contents.

To study the role of the Atlantic meridional overturning circulation (AMOC) in climate change, we perform an abrupt CO2–doubling experiment using a coupled atmosphere-ocean- ice model with a simple geometry that separates the ocean into small and large basins. As in observations and high-end climate models, the small basin exhibits a MOC and warms at a faster rate than the large basin. In our set-up, this contrast in heat storage rates is 0.6 ± 0.1 W/m^2, and we argue that this is due to the small basin MOC. However, the MOC weakens significantly, yet this has little impact on the small basin’s heat storage rate. We find this is due to the effects of both compensating warming patterns and interbasin heat transports. Thus, although the presence of a MOC is important for enhanced heat storage, MOC weakening is surprisingly unimportant.

High-resolution seafloor mapping provides insights into the dynamics of past ice-sheets/ice-shelves on high-latitude continental margins. Geological/geophysical studies in the Arctic Ocean suggest widespread Pleistocene ice grounding on the Chukchi–East Siberian continental margin. However, flow directions, timing, and behavior of these ice masses are not yet clear due to insufficient data. We present a combined seismostratigraphic and morphobathymetric analysis of the Chukchi Rise off the northwestern Chukchi margin using the densely acquired sub-bottom profiler (SBP) and multibeam echosounder (MBES) data. Comparison with deeper airgun seismic records shows that the SBP data cover most of the glaciogenic stratigraphy possibly spanning ca. 0.5–1 Ma. Based on the stratigraphic distribution and geometry of acoustically transparent glaciogenic diamictons, the lateral and vertical extent of southern-sourced grounded ice became smaller over time. The older deposits are abundant as debris lobes on the slope contributing to a large trough mouth fan, whereas younger till wedges are found at shallower depths. MBES data show two sets of mega-scale lineations indicating at least two fast ice-streaming events of different ages. Contour-parallel recessional morainic ridges mark a stepwise retreat of the grounded ice margin, likely controlled by rising sea levels during deglaciation(s). The different inferred directions of ice advances and retreats reflect complex geomorphic settings on the borderland. The overall picture shows that the Chukchi Rise was an area of intense interaction(s) of different ice-sheets/ice-shelves. In addition to glaciogenic deposits, we identify a number of related or preceding seabed features including mounds, gullies/channels, and sediment waves.

Streamflow monitoring is very important for planning and management of water resources in watersheds, and their prediction accuracy is crucial for decision-making. The Niger River Basin is a transboundary resource, shared by nine West African Countries and Algeria and, a large portion of the population rely on the basin for rain-fed agriculture and hydropower. Over the years, the basin’s streamflow regime has been altered due to climate change, drought, desertification and establishment of Dams. This research describes a novel Deep Learning framework comprised of Bidirectional-Long Short-Term Memory (LSTM) requiring Antecedent Precipitation Index (API) and meteorological variables, preprocessed using Normal Quantile Transform (NQT) as input drivers and, compared with the Soil and Water Assessment Tool (SWAT+) for streamflow prediction. NQT-API-LSTM which considers catchment wetness and seasonality, was forced with reanalyzed climate (1979–2021) while, SWAT+ was driven with biophysical data and reanalyzed climate (2010–2020). The very high performance of both NQT-API-LSTM and SWAT+ models showed the models were reliable and can predict regulated flows with reasonable certainty. However, NQT-API-LSTM outperformed SWAT+ at Lokoja watershed and, realistically captured the influence of seasonal climate and regional groundwater dynamics from upstream catchments including the Sahara Desert on the Benue, Guinean, Sahelian and Sudan Flood. Overall, NQT-API-LSTM could be used successfully for watershed-scale streamflow prediction without the need for continuous ground support data, a benefit for sparsely gauged West African River Basins, while SWAT+ could be used as an alternative, particularly, to evaluate the watershed’s response to land use/land cover changes.

Surface ozone regulation policies rely heavily on air quality models, such as CAMx, as important guiding tools. Comparison with observations is crucial to validating a model’s ability to represent ozone production chemistry. Identifying factors influencing surface ozone formation is complicated because ozone photochemical production rates are non-linearly dependent on concentrations of precursors such as nitrogen oxides (NOx) and volatile organic compounds (VOCs). We compare ozone production regimes (OPRs) identified from satellite observations and model simulations, as defined by the ratio of column formaldehyde to nitrogen dioxide (FNR, HCHO/NO2). We perform CAMx simulations for June-July-August 2016 over the Contiguous United States (CONUS) and compared these outputs against two OMI NO2and HCHO retrievals. Our analysis spans diurnal and altitudinal variations of OPRs, offering important insights for effective policy formulation. At the time of the OMI overpass (~1:30 PM LT), OPR is NOx-limited over most of the CONUS, as determined from OMI column ratios. Analysis of CAMx column ratios shows similar results. In contrast, more regions are VOC-limited when we constrain our ratio to within the Planetary Boundary Layer (PBL). In the morning (~9 AM LT), the CAMx PBL column ratios shift towards VOC-limited regime. We highlight areas of the CONUS for which satellite measurements of FNR may not be an accurate indicator of near-surface OPRs. Air quality regulations based on satellite observations should consider the diurnal variations of surface OPRs and assess how well their ratios represent near-surface OPR. Our results have implications for interpretation of TEMPO data for policy relevant applications.

Challenges in remote sensing, including remote sensing of vegetation, include the spectral characterization of objects over space and time. One key aspect for this characterization involves the geometry of data acquisition and positional relationships between light source, the target and the remote sensor. Several configurations of goniometers have been used to acquire spectral data as a function of this geometry and this strategy has been particularly efficient when applied to the study of short canopies (e.g., grasses). Tall canopies present logistical challenges when conducting these analyses, which can be resolved by replacing physical structures (rails) with flying systems capable to conform to different canopy geometries and data acquisition requirements. This work (the Droniometer Experiment) investigates anisotropies of a forest using radiometrically calibrated images from a multispectral camera (MicaSense RedEdge) mounted on a rotary-wing unmanned aerial system programmed to follow a planned flight that simulates data acquisition by a goniometer assembled over tall canopy. The experiment used multiple planned flights, conducted to represent changes in illumination, considering sun azimuth and elevation (multiple flights per day and over the course of months). Multi-angle data acquisition was addressed by controlling aircraft position and camera pitch at regular intervals. This work presents the integration of the droniometer system, including platform and camera requirements and control, data acquisition and processing, and analyses of results for target/vegetation characterization and to support information extraction and multi-angle remote sensing. A radiative transfer model, the Soil Canopy Observation, Photochemistry and Energy fluxes (SCOPE) was used for comparative analysis and to further describe anisotropies in spectral responses of tall canopies.

The relationships between deformation and erosion in transpressive systems are still poorly understood. Here, we present a new set of analog models to investigate how the tectonic and surface processes present at transpressive plate boundaries interact to shape topography. The experimental setup comprised a 2 x 1 x 0.5 m3 plexiglass box fit with a plexiglass board cut to 20º obliquity. A motor pulled a mylar sheet beneath the board to generate a velocity discontinuity at the interface. We loaded a ~5 cm thick layer of a granular material onto the board and sheet composed of 40 wt. % silica powder, 40 wt. % glass microbeads, and 20 wt. % PVC powder (cf. CMII in Reitano et al., 2020, doi: 10.5194/esurf-8-973-2020). This setup allows deformation to nucleate at the velocity discontinuity and naturally form a transpressional wedge. The model was monitored with digital cameras and a laser scanner to conduct particle image velocimetry and digital elevation model analysis, respectively. To explore surface processes associated with mass transport and erosion, we used a sprinkler system that casts a uniform mist across the model surface. We allowed ~1 cm of relief (equivalent to ~10 cm of convergence) to form before misting began to ensure the formation of realistic drainage networks. Before misting, experiments evolved in 3 stages: 1) distributed strain, 2) strike-slip faulting along synthetic structures, and 3) uplift and formation of a wedge along bivergent thrust structures. After misting, strike-slip deformation was still fully partitioned to synthetic structures and thrust sheets propagated in the prowedge direction. As the experiment continued, sub-longitudinal drainage systems formed with their orientation controlled by synthetic structures. Strike-slip displacement along these structures interrupted transverse streams, which ultimately captured the sub longitudinal systems. On the retrowedge, a longitudinal basin formed along a coalesced extensional structure, which also was later captured by transverse channels. These and other interactions between fault structures and channel networks provide insight into erosion and mass transport in transpressional systems and the nature of the complex reorganization of stream networks in response to deformation.

Quantifying warming of the Earth’s climate system since the late 19th century and the ratio of regional to global warming are required when examining implications of Paris Agreement global warming targets. To estimate these terms reliably, the limitations in quality and length of observed records, differences between climate models and observations, and different results dependent on temporal and forcing contexts must be taken into account. Here we use observational datasets currently available back to 1860 and the latest set of global climate model simulations from CMIP5/6 to examine the warming of Australia in the past and projected future. We find that Australia has warmed by 1.5 °C (1.3–1.8 °C) during 1850 - 2019, at a ratio of ~1.4 times the global warming of ~1.1 °C. Models generally produce a lower ratio of Australian to global warming than in observations, which may be related to model biases or internal climate variability.

Shifts in Southern Ocean (SO, 40-85S) shortwave (SW) cloud feedback (SWFB) towards more positive values are the dominant contributor to higher effective climate sensitivity (ECS) in Coupled Model Intercomparison Project phase 6 (CMIP6) models. The positive shift in SWFB in CMIP6 global climate model (GCMs) can be traced back to the greater reduction in low cloud cover and the weaker cloud liquid water response to warming in the SO. To evaluate how realistic the CMIP6 cloud response is, we connect the SO SWFB to changes in column-integrated liquid water mass (LWP) and the susceptibility of albedo to LWP in 50 CMIP5 and CMIP6 GCMs. In turn, we predict the responses of SO LWP to warming using a cloud-controlling factor (CCF) model. The combination of the CCF model and radiative susceptibility explains about 50% of the variance in the GCM-simulated SWFB in the SO. Observations of SW radiation fluxes, LWP, and reanalysis of CCFs are used to constrain the SO SWFB. This yields a constrained response of SO LWP to warming of 2.89-4.41 gm-2K-1, relative to the total GCM range of -0.48-9.33 gm-2K-1. The susceptibility of albedo to LWP is constrained to be 0.41-0.86 (kgm-2)-1, relative to the GCM range of 0.23-3.62 (kgm-2)-1, where albedo is unitless. The overall constraint on the contribution of SO SWFB to global cloud feedback is -0.19-0.05 Wm-2K-1, relative to GCM range of -0.28-0.27 Wm-2K-1. In summary, observations suggest a moderate negative to weak positive SO SWFB.

Groundwater development will provide a more stable water source and enhance food security. Sustainable groundwater development requires collecting and analyzing data produced at global and national levels and disseminating that data and knowledge to end users such as States, NGOs, municipalities, businesses, and agropastoralists in a format that is useful for planning and decision-making. In developing countries, analyzing in situ measurements to de can be challenging due to sparsity of data and lack of tools and expertise. To address these problems we have developed a web-based geospatial tool that ingests in situ water level measurements and performs temporal and spatial interpolation to build interactive animated maps, time series plots, and long-term aquifer depletion curves. We use machine learning to find correlations among Earth observation data, such as precipitation or soil moisture, with water level data and perform more accurate interpolation. This approach ensures that scarce in situ data are used as effectively and accurately as possible. This tool helps water managers gain a better understanding of groundwater resources and determine how aquifers are responding to groundwater development, droughts, and climate change.

Changes in ocean heat content are a critical element of climate change, with the oceans containing about 90% of the excess heat stored in the climate system (60% in the upper 700 db). Estimates of these changes are sensitive to horizontal mapping of the sparse historical data and errors in eXpendable BathyThermograph data. Here we show that they are also sensitive to the vertical interpolation of sparsely sampled data through the water column. We estimate, using carefully constructed vertical interpolation methods with high-quality hydrographic (bottle and CTD) data, the observationally based upper ocean heat content increase (thermosteric sea level rise) from 1956 to 2020 is 285 Zeta Joules (0.55 mm yr-1), 14% (14%) larger than estimates relying on simple but biased linear interpolation schemes. The underestimates have a clear spatial pattern with their maximum near 15ºN and 12ºS, near the maxima in the curvature of the temperature depth profile.

Accurate descriptions of natural fault surfaces and associated fault rocks are important for understanding fault zone processes and properties. Slickensides–grooved polished surfaces that record displacement and wear along faults– develop measurable roughness and characteristic microstructures during fault slip. We quantify the roughness of natural slickensides from three different fault surfaces by calculating the surfaces power spectra and height distributions and analyze the microstructures formed above and below the slickensides. Slickenside surfaces exhibit anisotropic self-affine roughness with corresponding mean Hurst exponents in directions parallel– 0.53±0.07– and perpendicular –0.6±0.1– to slip, consistent with reports from other fault surfaces. Additionally, surfaces exhibit non-Gaussian height distributions, with their skewness and kurtosis roughness parameters having noticeable dependence on the scale of observation. Below the surface, microstructural analyses reveal that S-C-C’ fabrics develop adjacent to a C-plane-parallel principal slip zone characterized by a sharp decrease in clast size and a thin (≤100 µm) nanoparticulate-rich principal slip surface (PSS). These microstructures are present in most analyzed samples suggesting they commonly form during slickenside development regardless of lithology or tectonic setting. Our results suggest that 1) PSS likely arise by progressive localization along weaker oriented fabrics 2) deformation along PSS’s is energetic enough to comminute the rocks into nanometric grains, and 3) fault geometry can be further characterized by studying the height distributions of fault surfaces, which are likely to impact stress distributions and frictional responses along faults.

The construction sector serves as a vital pillar from both social and economic standpoints, fulfilling essential housing needs and contributing significantly to economic growth. However, its environmental impact is notable, manifesting through the release of substantial greenhouse gas emissions, ultimately leading to detrimental environmental consequences, such as global warming and ozone depletion. The global construction industry is a significant contributor, accounting for a substantial 39% of the world's greenhouse gas emissions. Civil construction, particularly in developing countries like India, holds a pronounced economic role. To address environmental concerns, the adoption of sustainable construction practices becomes imperative, not only to curtail greenhouse gas emissions but also to conserve finite resources. Developing economies are compelled to embark on large-scale civil construction and energy production ventures, accentuating the criticality of transitioning to a low-carbon economy, though this poses challenges in the process. To identify potential mitigation opportunities, comprehending the contributions of the construction industry and related activities is vital. Thus, the present study seeks to quantify the overall carbon material footprint of the construction sector in India, with a focus on identifying key contributing supply chains, industries, and products. To achieve this, extensive economy-wide input-output analysis is conducted utilizing economic input-output transaction tables jointly by the Central Statistical Organization (CSO) and Planning Commission. This comprehensive approach enables detailed sector disaggregation refined analysis, and facilitates benchmarking. To assess GHG emissions, the study develops a model based on input-output and process-based life cycle assessment principles. The significance of this in-depth analysis is to provide critical insights for reducing construction-related greenhouse gas emissions in developing countries. The outcome will aid in prioritizing future emissions reduction endeavors, directing targeted solutions toward improving the overall environmental performance of the construction industries.

The British Oceanographic Data Centre (BODC) celebrated its 50th anniversary in 2019. It holds data collected from 1773 to the present day. Holdings are multidisciplinary, heterogeneous data reflecting the full range of disciplines, platforms, temporal and spatial fieldwork scales typically encountered in oceanographic research and monitoring. These collections vary in granularity and contain data which are at different stages of curation ranging from raw data to standardised data products. BODC need to improve data services to meet the developing the expectations of the research community. These include the FAIR data principles, TRUSTed repository guidelines and CoreTrustSeal accreditation. This is a significant challenge within the constraints of resource available (both financial and human). The initial focus for BODC is making holdings citable with the following aspirations: Application of DOIs to data at the point of receipt by BODC. Publication of data papers and publication of DOIs for data products. Application of persistent identifiers to low level data granules where DOIs are not feasible. Application of persistent identifiers to datasets included in BODC API services and versioning of these data. Work with organisations or groups who include data curated by BODC in their products to enable the provenance of data to be unambiguous. Work with communities on joint data papers where BODC are a partner organisation. This will enable each type of data served by BODC to be unambiguously citable. The initial effort is being directed towards the application of DOIs to data submissions and publication of data papers for BODC curated data products.

Lakes and wetlands are natural sources and have an important role for hydrological cycle. They are also affected by climate change and anthropogenic activities such as precipitation regime, diminishing water bodies, uncontrolled groundwater extraction, drainage and irrigation channels, agricultural activities and discharge of domestic and industrial waste. For this reasons monitoring the lake surface areas are very crucial. In this paper; the Seyfe Lake was selected as a case study. The study area is located at the southern part of the Seyfe basin with a catchment area of 1447 km2 in Central Anatolia. Seyfe Lake wetland is located in a closed basin. The lake area and its surroundings is a Ramsar site and have the status of Grade 1 Natural Site and Protected Natural Area. This study aimed to evaluate the spatio-temporal changes of the surface area of Seyfe Lake by using Geographical Information Systems (GIS) and remote sensing techniques. For this purpose Landsat (MSS, TM, ETM+, OLİ/TIRS) satellite images used for a period between 1987 and 2020. A total of 34 images were processed and, using unsupervised classification method, water body was extracted according to the spectral information of the image bands and the historical change of the lake surface area was calculated by using Image Analysis Function of ArcGIS 10.6.1 software. In addition to these satellite images, long-term hydrometeorological data and field observations were analyzed to determine the changes of the Seyfe Lake surface area and understand the effects of climate change and antropojenic activities. According to the old and recent satellite images of Seyfe Lake area, the persisting shrinkage of lake area and diminishing of the water resources over the years in the Seyfe Lake basin still continue. Maximum and minumum surface area of the lake was calculated 43 km2 and 18 km2 respectively during 1987-2020. In August 2008; the lake area is completely dried. Nowadays the 58% of the lake area is dried up. These variations could probably be related with the antropogenic effects and climatic changes in the study area. As a result, Satellite based techniques might provide a historical data to identify changes on the lake surface area. Remote sensing techniques are also effective to evaluate temporal and spatial changes on water resources resulted by human activities and local climate change. In-situ observation and hydrogeological monitoring are another important tools to support findings of remote sensing study. Keywords: Spatio-temporal change, Wetland, Seyfe Lake, Unsupervised Classification, Remote Sensing

Eddy-driven zonal jets and Rossby waves are common features of planetary atmospheres and oceans, organising the large-scale flow and influencing the dispersion and transport of material tracers and constituents. In the presence of relatively weak friction and forcing, zonal jets form a dominant component of the flow in a regime known as “zonostrophic”, characterized by strongly anisotropic energy spectra and the formation of slowly evolving systems of alternating zonal jets. This regime is characterized by two scales, Lβ ~ (Πε/β3)1/5 and LR ~ (Urms/β)1/2, where Πε is the transfer rate of the inverse energy cascade and β is the radial gradient of the Coriolis parameter. Their ratio is known as the zonostrophy index, Rβ = LR/Lβ. Zonal jets become discernible at Rβ ≥ 1.5 but are much stronger for Rβ > 2. Achieving such high values of Rβ in a laboratory is non-trivial, however. The atmospheres of gas giant planets are probably well within such a regime with Rβ ~ 5 [Galperin et al. Icarus 2014], though the Earth’s atmosphere and oceans are in a more friction-dominated state where Rβ ~ 1.5 – 1.8. In this study we have investigated the flow obtained in a rapidly rotating fluid on a topographic beta-plane in a cylindrical tank, subject to localised, periodic mechanical forcing along a radius. The experiments were carried out in the 5 m diameter rotating tank at the Turlab facility in Turin, Italy under the European High-Performance Infrastructures in Turbulence (EUHiT) programme. Velocity measurements were obtained using PIV in a horizontal plane a short distance below the free surface, while discrete particles floating on the surface were tracked to obtained their Lagrangian trajectories. The flow exhibited the spontaneous formation of persistent zonal jets, nonlinear topographic Rossby waves and intense vortical eddies (see image below). The large-scale flow was found to lie within the zonostrophic regime with Rβ ≥ 2.4. Diagnostics indicate the presence of an anisotropic dual (inverse/direct) KE cascade. The KE spectrum, however, seems unexpectedly consistent with recent f-plane turbulence models based on Quasi-Normal Scale Elimination [Galperin & Sukoriansky Phys. Rev. Fluids 2020], the implications of which will be discussed in the presentation.

We explore seasonal mass oscillations by continental water storage in Southeast Asia and Himalayan arc region using continuous Global Positioning System (cGPS) measurements and satellite data from the Gravity Recovery and Climate Experiment (GRACE). While the interaction between seasonally induced non-tectonic and tectonic deformation along the Himalayan plate boundary is still debated, we propose that tectonic deformation along this plate boundary can be significantly influenced by the deformation induced by the non-tectonic hydrological loading cycles. We suggest that the substantially higher transient displacements above the base of the seismogenic zone indicate a role of changes in aseismic slip rate on the deep megathrust that may be controlled by seasonal hydrological loading. We invoke modulation of aseismic slip on the megathrust down-dip of the seismogenic zone due to a fault resonance process induced by the seasonal stress changes. This process modulates mid-crustal ramp associated micro-seismicity and influences the timing of Central Himalayan earthquakes.