bluuebunny/crossref_metadata_2025 huggingface dataset:
A catastrophe risk model for current and future flooding in the UK
Authors: Bates Paul , Savage James , Wing Ollie , Quinn Niall , Sampson Christopher , Smith Andrew , Neal Jeff
Published: February 2023

We present a climate-conditioned catastrophe flood model for the UK that simulates pluvial, fluvial and coastal flood risks at 1 arc second spatial resolution (~20-25m). Hazard layers for ten different return periods are produced over the whole UK for historic, 2020, 2030, 2050 and 2070 conditions using the UKCP18 climate simulations. From these, monetary losses are computed for Great Britain only for five specific global warming levels (0.6, 1.1, 1.8, 2.5 and 3.3°C). The analysis contains a greater level of detail and nuance compared to previous work and represents our current best understanding of the UK’s changing flood risk landscape. Validation against national return period flood maps yielded Critical Success Index values in the range 0.6 to 0.78, and maximum water levels for the Carlisle 2005 flood were replicated to an RMSE of 0.41m without calibration. This level of skill is similar to local modelling with site specific data. Expected Annual Damage in 2020 was £730M, which compares favourably to the observed value of £714M reported by the Association of British Insurers. Previous UK flood loss estimates based on government data are ~3x higher and lie ~6-7 standard deviations away from the mean of our modelled loss distribution, which is plausibly centred on the observations. We estimate that UK 1% annual probability flood losses were ~6% greater in the average climate conditions of 2020 than for the period of historical river flow and rainfall observations (centred approximately on 1995) and can be kept to around ~8% if all countries’ COP26 2030 carbon emission reduction pledges and ‘net zero’ commitments are implemented in full. Implementing only the COP26 pledges increases UK 1% annual probability flood losses by ~23% above recent historical values, and potentially ~37% if climate sensitivity turns out to be higher than currently thought.
Evaluation of precipitation satellite products and ground-based radars during two case studies over France in 2022
Authors: Causse Antoine , Baray Jean-Luc , Planche Céline , Buisson Emmanuel
Published: February 2023

Precipitations are a crucial and extremely valuable source of water for humanity’s food production and for its own consumption but droughts or even floods can be potential causes of considerable damages to crops, infrastructures or properties and life-threatening situation. Precipitations are characterised by a high spatial and temporal variabilities. Hence, multiple rain gauges, precipitation radars and satellite-based estimates gridded datasets are necessary to quantify rain accumulation at local, regional and global scales.Rain gauges observations tend to observe the amount of precipitable water locally providing rain rates for an equivalent surface of less than 1 m². Weather radars estimate the rain fields over a surface at high spatio-temporal resolution (~1km for space and several minutes for the time). Finally, the satellite-related estimates of precipitation, mainly based on the estimates made by infrared (IR) and passive or active microwave (PMW or AMW) sensors, have been developed and studied in the last decades. Moreover, new innovative satellite skills provide rain estimates from the attenuation of broadband communication satellite link signals at Ka-band.This work evaluated the behaviour of two precipitation radar products: the French radar product PANTHERE and the pan-European radar mosaic product OPERA, and 11 satellite precipitation products: GHE, PDIR, IMERG Early v6, IMERG Late v6, CMORPH v0.x, CMORPH-RT v0.x, GSMaP-NRT v8, GSMaP-NRT-GC v8, GSMaP-NOW, GSMaP-NOW-GC and Databourg. This study has been performed against the observation made the RADOME rain gauge network with more than 500 stations over the French territory. All datasets are aggregated at hourly temporal resolution and are compared using a point-to-pixel method during two notable case studies: a 3-days April 2022 event and a 4-days June 2022 event. It is shown that radar products tend to be more reliable on the estimation of precipitation accumulation while PMW datasets tend to underestimate rain rates compared to the observations whereas IR datasets has the potential to overestimate these values.
How to study mechanism of avalanche on reservoir bank: a retrospective study
Authors: Li Yihang , Xu Xiangzhou
Published: February 2023

Abstract Reservoir-bank avalanche is a common hydrogeological problem whether in China or other countries, and analysis for the mechanism of collapse on reservoir bank is an important issue in the field of disaster prevention and mitigation. This paper reviews the methods which had been used to study the mechanism of reservoir-bank avalanche, including field monitoring, field investigation, model or field experiment, and numerical simulation. In virtue of many advantages, e.g., high efficiency and automation, field monitoring has become a powerful tool in evaluating reservoir-bank collapse. Nevertheless, field monitoring is also subject to some external factors related to remote sensing technology, such as weather conditions, environment, and other factors. Field investigation has the characteristics of flexibility and maneuverability. However, a field investigation is a sampling method based the observation in the representative area, and the hazard information cannot be comprehensively obtained via field investigation in the study area. A common merit for the field monitoring and investigation is that data observed with the methods mentioned above may be used to calibrate the results of the model experiment and numerical simulation, but field monitoring or investigation are not applicable to track the process of bank collapse. Different from the monitoring or investigating method, an experiment of reservoir-bank collapse under closely monitored or controlled experimental conditions focuses on the regularities of bank collapse from a micro perspective. The model experiment may be conducted in a laboratory far away from the study area, and the experimental scenario may be freely designed if needed. Yet the researchers should consider the similarity of the cumulative effect while designing the downscaled model experiment for reservoir bank failure. Maybe it is easy to simulate and observe the complicated topographical conditions of bank collapse in the field experiment, because no change exists in the scale of the underlying surface and properties of erosion material. In fact, usually to make accurate observations and simulations is relatively difficult in the field. Numerical simulations have been widely used to analyze and predict the reservoir-bank avalanche from a macro perspective all over the world, whereas the result of the numerical simulation has to be verified with that obtained from monitoring, investigation or experiment. In summary, each research method presents its own characteristic set of advantages and limitations. Scientists may use an appropriate route for analysis according to objectives and contents of a specific project.Key words: Reservoir-bank avalanche; Field monitoring; Field investigation; Model experiment; Numerical simulation
Updated global radioxenon emission inventory from all types of nuclear facilities specific for the year 2014
Authors: Kalinowski Martin
Published: February 2023

This presentation summarizes the currently best available estimates of radioxenon emissions from all nuclear facilities for a specific year. It is a unique data set to be used in studies to enhance data analysis from the noble gas component of the International Monitoring System (IMS). Global radioactivity monitoring for the verification of the Comprehensive Nuclear-Test-Ban Treaty (CTBT) includes the four xenon isotopes 131mXe, 133Xe, 133mXe and 135Xe. These four isotopes are serving as important indicators of nuclear explosions. The state-of-the-art radioxenon emission inventory uses generic release estimates for each known nuclear facility. However, the release amount can vary by several orders of magnitude from year to year. The year 2014 was selected for a single year radioxenon emission inventory with minimized uncertainty. Whenever 2014 emissions reported by the facility operator are available these are incorporated into the 2014 emission inventory.This presentation summarizes this newly updated radioxenon emission inventory. It comprises all relevant nuclear facilities. For the three strong sources ANSTO (Australia), CNL (Canada), and IRE (Belgium), stack release data with a high time resolution are available. Annual emissions are provided for all other medial isotope production facilities, including new updates for the NIIAR facility (Russia) and the Karpov Institute (Russia). For nuclear power plants (NPP) in Europe and the USA the reported release for the whole year is applied in combination with information about their operational schedule. For all other NPPs the best estimates are used. The estimated releases of nuclear research reactor sources are included as well. For the first time, estimates were made for radioxenon releases from spallation neutron sources and from spent nuclear fuel reprocessing plants. The new emission data are compared with previous studies highlighting discrepancies which in many cases are as large as several orders of magnitude.The global radioxenon emission inventory for 2014 can be used for studies to estimate the contribution of this anthropogenic source to the observed ambient concentrations at IMS noble gas sensors to support CTBT monitoring activities, including calibration and performance assessment of the verification system as described in the Treaty as well as developing and validating methods for enhanced detection capabilities of signals that may indicate a nuclear test. One specific application is the 1st Nuclear Explosion Signal Screening Open Inter-Comparison Exercise that was announced end of 2021 and conducted in 2022. The emission inventory in combination with radioxenon observations at IMS stations may as well be used for global or regional atmospheric tracer studies and for the validation of atmospheric transport simulation methods.
Building a physics-constrained, fast and stable machine learning-based radiation emulator
Authors: Bertoli Guillaume , Schemm Sebastian , Ozdemir Firat , Perez Cruz Fernando , Szekely Eniko
Published: February 2023

Modelling the transfer of radiation through the atmosphere is a key component of weather and climate models. The operational radiation scheme in the Icosahedral Nonhydrostatic Weather and Climate Model (ICON) is ecRad. The radiation scheme ecRad is accurate but computationally expensive. It is operationally run in ICON on a grid coarser than the dynamical grid and the time step interval between two calls is significantly larger. This is known to reduce the quality of the climate prediction. A possible approach to accelerate the computation of the radiation fluxes is to use machine learning methods. Machine learning methods can significantly speed up computation of radiation, but they may cause climate drifts if they do not respect essential physical laws. In this work, we study random forest and neural network emulations of ecRad. We study different strategies to compare the stability of the emulations. Concerning the neural network, we compare loss functions with an additional energy penalty term and we observe that modifying the loss function is essential to predict accurately the heating rates. The random forest emulator, which is significantly faster to train than the neural network is used as a reference model that the neural network must outperform. The random forest emulator can become extremely accurate but the memory requirement quickly become prohibitive. Various numerical experiments are performed to illustrate the properties of the machine learning emulators.
Improvement of surface exchange coefficient parameterization and its application to regional numerical simulation
Authors: Zhang Xia , Chen Liang , Ma Zhuguo
Published: February 2023

Land-atmosphere energy and moisture exchange can strongly influence local and regional climate changes. However, high uncertainties exist in the representation of land-atmosphere interactions in numerical models and the coupling strength between land and atmosphere is largely overestimated, in which the determination of surface exchange coefficient is one of the main problems. Here, we show the improvements from a dynamic vegetation-type-dependent exchange scheme in the offline Noah land surface model with multi-parameterization options and the Weather Research and Forecasting model when applied to China. Compared to the default schemes, the dynamic exchange scheme significantly reduces land-atmosphere coupling strength overestimations, and comparisons to flux tower observations reveal its capability to better match observed surface energy and water variations. In particular, the above remarkable improvements produced by the dynamic exchange scheme primarily occur in areas covered with short vegetation. The improved version benefits from the treatment of the roughness length for heat. Further, land-surface processes play significant roles in cloud formation and precipitation generation by affecting local planetary boundary layer profiles. The dynamical exchange scheme could narrow the positive discrepancies in the simulated precipitation. Using 3-km-resolution convection-permitting models for three heavy precipitation cases, the dynamic coupling simulations could achieve the closest agreement with the field observations, especially the intensity and location of the heaviest rainfall during the precipitation process. Overall, our findings highlight the applicability of the dynamic scheme as a better physical alternative to the current treatment of surface exchange processes in atmosphere coupling models and could help achieve more accurate simulations.
Using zonal surface heat flux asymmetry to reveal new features of Southern Ocean air-sea interaction
Authors: Josey Simon , Grist Jeremy , Mecking Jennifer , Moat Ben , Schulz Eric
Published: February 2023

New results on Southern Ocean heat exchange and wind forcing are presented with a focus on zonal asymmetry between surface ocean heat gain in the Atlantic/Indian sector and heat loss in the Pacific sector. The asymmetry arises from an intersector variation in the humidity gradient between the sea surface and near surface atmosphere. This gradient increases by 60% in the Pacific sector enabling a 20 Wm-2 stronger latent heat loss compared to the Atlantic/Indian sector. A new zonal asymmetry metric is used for intercomparison of atmospheric reanalyses and CMIP6 climate simulations. CMIP6 has weaker Atlantic/Indian sector heat gain compared to the reanalyses primarily due to Indian Ocean sector differences. The potential for surface flux buoys to provide an observation-based counterpart to the asymmetry metric is explored. Over the past decade, flux buoys have been deployed at two sites (south of Tasmania and upstream of Drake Passage). The data record provided by these moorings is assessed and an argument developed for a third buoy to sample the Atlantic/Indian sector of the asymmetry metric. In addition, we assess evidence that the main westerly wind belt has strengthened and moved southward in recent decades using the ERA5 reanalysis. We find only marginal evidence of a southward broadening of the belt in the Atlantic /Indian sector and northward broadening in the Pacific sector and that the latitude of maximum wind speed remains essentially unchanged.
Calibration of the SWAT Hydrological Model with the Particle Swarm Optimization Technique
Authors: Çakır Fatmanur , Elçi Alper , Somay-Altaş Melis
Published: February 2023

Hydrological models are important tools for management of water resources at the basin scale. However, the outputs of these models might come with significant inaccuracies, often due to uncertainties in model parameters. One of the biggest challenges in working with a hydrological model is that these models require rigorous calibration, validation, and uncertainty analysis. In recent years, there has been an increase in the use of heuristic optimization techniques in water resources research. These techniques can yield more accurate and more reliable modeling results by searching the global optimum of multiple model parameter sets.This study describes the application of a heuristic optimization method, the Particle Swarm Optimization (PSO), on a hydrological model, the Soil and Water Assessment Tool (SWAT). The model is applied to the Fetrek Stream watershed in western Turkiye, which is under environmental stress due to excessive groundwater abstraction and pollution from numerous wastewater discharges. The model includes data related to 41 point sources, and two inflowing tributaries. The model is configured with 8 sub-basins, and 484 hydrologic response units. Hydrological fluxes are obtained for a 30-year simulation period. The sensitivities of the model parameters and uncertainties of model results are investigated. PSO is used to calibrate sensitive model parameters, followed by a comparison with the calibration outcome using the SUFI-2 (Sequential Uncertainty Fitting) algorithm, which is the usual choice in calibrating SWAT models. The performances of both optimization approaches are evaluated with the Kling-Gupta Efficiency (KGE), the regression coefficient (R2), and the bias percentage  (PBIAS) Model results are presented with their associated prediction uncertainties in the form of the so-called p-factor and r-factor statistics, which represent envelopes of good model solutions. The results show that the PSO approach can achieve satisfactory results on a monthly time-scale thereby offering an alternative calibration with less parameters and a wider interval of the 95% prediction uncertainty.This study is supported by the PRIMA program under grant agreement No: 2024 Project TRUST (management of industrial Treated wastewater ReUse as mitigation measures to water Scarcity in climaTe change context in two Mediterranean regions). The PRIMA program is supported by the European Union.
The benefit of textural features for SAR-based tropical forest disturbance mapping
Authors: Balling Johannes , Herold Martin , Reiche Johannes
Published: February 2023

Cloud penetrating Synthetic Aperture Radar (SAR) imagery has proven effective for tropical forest monitoring at national and pan-tropical scales. Current SAR-based disturbance detection methods rely on identifying decreased post-disturbance backscatter values as an indicator of forest disturbances. However, these methods suffer from a major shortcoming, as they show omission errors and delayed detections for some disturbance types (e.g., logging or fires). Here, post-disturbance debris or tree remnants result in stable SAR backscatter values similar to those of stable forest. Despite fairly stable backscatter values we hypothesize that different orientation and arrangement of tree remnants lead to an increased heterogeneity of adjacent disturbed pixels. Increased heterogeneity can be quantified by textural features. We assessed six Gray-Level Co-Occurrence Matrix (GLCM) textural features utilizing Sentinel-1 C-band SAR time series. We used a pixel-based probabilistic change detection algorithm to detect forest disturbances based on each GLCM feature and compared them against forest disturbances detected using only backscatter data. We further developed a method to combine both backscatter and GLCM features to detect forest disturbances. GLCM Sum Average (SAVG) performed best out of the tested GLCM features. Omission errors were reduced of up to 36% and the timeliness of detections was improved of up to 30 days by applying the combination method of backscatter and GLCM SAVG. Test sites characterized by large unfragmented disturbance patches (e.g., large-scale clearings, fires and mining) showed the greatest spatial and temporal improvement. A GLCM kernel size of 5 leads to the best trade-off of improving timeliness of detections and reducing omission errors while not introducing commission errors. The robustness of the developed method was verified for a variety of natural and human-induced forest disturbance types in the Amazon Biome. Our results show that combined SAR-based textural features and backscatter can overcome omission errors caused by post-disturbance tree remnants. Combining textural features and backscatter can support law enforcement activities by improving spatial and temporal accuracy of operational SAR-based disturbance monitoring and alerting systems.
Monitoring temperature at the ocean seafloor with fibre optic cables and DAS
Authors: Pelaez Quiñones Julián , Sladen Anthony , Ponte Aurelien , Lior Itzhak , Ampuero Jean-Paul , Rivet Diane , Meulé Samuel , Bouchette Frédéric , Pairaud Ivane , Coyle Paschal
Published: February 2023

Ocean water temperature measurements are fundamental to atmospheric and ocean sciences. Obtaining them, however, often comes along with major experimental and logistic challenges. Except for the uppermost ocean surface temperature, which can be measured from satellites, temperature data of the ocean is often poorly sampled or nonexistent, especially in deep-water regions. Although Distributed Acoustic Sensing (DAS) technology has become popular because its high sensitivity to strains and mechanical vibrations, our work focuses on its usage on tens-of-kilometer-long underwater fibre-optic (FO) telecommunication cables to measure temperature anomalies at the seafloor at millikelvin (mK) sensitivity. This is possible because of the lack of dominant strain signals at frequencies less than about ∼1 mHz, as well as the poor coupling of the fibre with these signals while remaining highly sensitive to slow ambient temperature variations that locally affect its optical path length. DAS allows us to observe significant temperature anomalies at the continental shelf and slope of the Mediterranean sea, South of Toulon, France over periods of several days, with variability remaining relatively low at the deep ocean. By means of this approach, oceanic processes such as near-inertial internal waves and upwelling can be monitored at unprecedented detail.Our observations are validated with oceanographic in-situ sensors and alternative Distributed Fibre Optic Sensing (DFOS) technologies established for temperature sensing. We outline key advantages of DAS thermometry over the aforementioned sensors in terms of spatial coverage, sensitivity, versatility and highest attainable frequency. At the current state of the art, DAS can only measure temperature anomalies as opposed to absolute temperature, a drawback that could be compensated via single temperature calibration measurements.
An information-theoretic approach for evaluating catchment scale process relationships
Authors: Reghunath Gowri , Mujumdar Pradeep P.
Published: February 2023

Hydrological responses of a catchment evolve due to the complex interactions between various climate inputs and landscape characteristics. Such interactions and the resulting hydrological processes need to be adequately understood to explicitly describe the catchment’s behaviour and process dynamics. Hydrological modelling serves as a powerful tool to strengthen the understanding of such complex process interactions. Conventional hydrological modelling practices focus on calibrating the model outputs with an aim only to match the observed discharge at stream gauge locations. This procedure might not adequately capture the process interactions and the underlying causalities, especially in catchments exhibiting strong non-linear hydrological process relationships. While getting the streamflow right, there is a chance that the other hydrological processes may be wrongly captured, i.e., getting the right calibration results for the wrong reasons. In this study, information-theoretic measures such as Shannon Entropy, Mutual Information and Transfer Entropy are used to understand the process relationships simulated using a physically based hydrological model. The grid-based Variable Infiltration Capacity (VIC) model is employed at a spatial resolution of 0.25 x 0.25-degree over the Cauvery river basin in peninsular India at a daily time scale. Entropy measures are applied to the major hydrological processes such as rainfall, surface runoff, actual evapotranspiration and baseflow, which are simulated using the model, and their relationships are evaluated using non-linear correlation metrics. The study also proposes an entropy-based calibration framework for improving the model efficiency in simulating the catchment water balance. This work highlights the advantages of using information-theoretic measures over conventional methods in evaluating hydrological process relationships, especially in catchments manifesting strong non-linear hydrological behaviour.
A Programming Model for Geospatial Machine-Learning with Scalability in Hybrid Multiclouds
Authors: Tatsubori Michiaki , Kimura Daiki , Moriyama Takao , Simumba Naomi , Ishikawa Tatsuya
Published: February 2023

While deep machine learning approaches are getting pervasively used in remote sensing and modeling the earth, difficulties due to the size of satellite data are always pains for scientists in implementing such experiential software. We present a programming model for geospatial machine learning based on TorchGeo and PyTorch, which are getting the de fact standards in programming with PyTorch/Python.  TorchGeo is open-sourced and designed to make it simple for remote sensing experts to explore machine learning solutions. Our objective is to allow machine-learning programs using TorchGeo to scale leveraging proprietary high-performance computing (HPC) and multicloud HPC resources, from ones notebook. One of key technologies specifically needed in geospatial machine learning is the smart integration of peta-scale data services and data-distributed parallel frameworks.  We implement such a platform as a part of IBM Research Geospatial Discovery Network (GDN) and experiment segmentation tasks such as flood detection from satellite data to show its scalability.
Understanding changes in West African monsoon precipitation in response to increased CO2
Authors: Mutton Harry , Chadwick Robin , Collins Matthew , Lambert Hugo
Published: February 2023

Projections of future West African monsoon (WAM) precipitation change in response to increased greenhouse gases are uncertain, and an improved understanding of the drivers of WAM precipitation change is needed to help aid model development and better inform adaptation policies in the region. Here, we address two of these drivers: the direct radiative effect of increased CO2 (referring to the impact of increased CO2 in the absence of SST changes), and the impact of a uniform SST warming. Atmosphere only models are used to investigate the response, finding that these two drivers have opposing impacts on WAM precipitation. In response to the direct radiative effect, an increase in precipitation is caused by a northward shift and a weakening of the shallow meridional circulation over West Africa, advecting less dry air into the monsoon rainband. In contrast, the uniform SST warming causes a decrease in precipitation due to a strengthening of the shallow meridional circulation and enhanced moisture gradients between the moist monsoon airmass and the dry desert airmass. These changes in the shallow meridional circulation are shown to be caused by large scale temperature changes as well as the more localised impact of a soil moisture feedback mechanism over the Sahel. It is then shown that the processes discussed are relevant to the intermodel uncertainty in WAM projections across a range of CMIP6 models.
Evidence for Large Increases in Clear-Air Turbulence over the Past Four Decades
Authors: Williams Paul D. , Prosser Mark C. , Marlton Graeme J. , Harrison R. Giles
Published: February 2023

Clear-air turbulence (CAT) is hazardous to aircraft and is projected to intensify in response to future climate change. However, our understanding of past CAT trends is currently limited, being derived largely from outdated reanalysis data. Here we analyse CAT trends globally during 1979–2020 in a modern reanalysis dataset using 21 diagnostics. We find clear evidence of large increases around the globe at aircraft cruising altitudes. For example, at an average point over the North Atlantic, the total annual duration of light-or-greater CAT increased by 17% from 466.5 hours in 1979 to 546.8 hours in 2020, with even larger relative changes for moderate-or greater CAT (increasing by 37% from 70.0 hours to 96.1 hours) and severe-or-greater CAT (increasing by 55% from 17.7 hours to 27.4 hours). Our study represents the best evidence yet that CAT has increased over the past four decades.
Detecting the occurrence of preferential flow in soils with stable water isotopes
Authors: Pyschik Jonas , Weiler Markus
Published: February 2023

Preferential flow in soils and hillslopes may transport water faster than the soil matrix. These features activate quickly during precipitation events, increase infiltration and vertical pathways can play an important role in runoff generation. However, preferential pathways are difficult to identify as common techniques (e.g. piezometer, soil moisture sensors, hillslope trenches) do not sufficiently represent the spatial scale and frequency of these features and other approaches (e.g. dye patterns) are labour intensive and heavily invasive.Here, we present a method to derive locations of preferential flow only by using vertical stable water isotope profiles in soils. In four catchments, we each drilled 120 soil cores (1-3m) and analysed the stable isotope composition of the soil water in 10-20cm increments to derive depth profiles. Visually selecting profiles with similar isotopic seasonality patterns not influenced by preferential flow, we determined a reference isotope profile for each catchment using a LOESS regression. These represent a soil profile only influenced by vertical matrix infiltration. To account for differences in soil conductivity and porosity, the reference profiles were scaled by depths to each profile. Locations where the measured profile deviates significantly from the reference, we assume an influence of vertical or lateral preferential flow.With this method we found evidence for preferential flowpaths in all catchments. Especially in the alpine catchment with highly heterogeneous soils many profiles showed distinct preferential flow features. There, some profiles also indicate multiple, vertically independent pathways. The depth at which these pathways occurred were highly variable, even at neighbouring profiles.Overall our results demonstrate the feasibility to assess preferential flow only using soil water isotope profiles while also underlining the large spatial and vertical variability of preferential flowpaths at the hillslope and catchment scale.
Dryland land crop yield sensitivity to drought in Botswana: Development ofstatistical tools based on satellite remote sensing, observation and climate models foruse in risk assessment
Authors: Matsuokwane Manyothwane Tshepho , Mengistu Tsidu Gizaw
Published: February 2023

AbstractAssessing agricultural drought is of great importance as it is viewed as the most serious problem in mostcountries in terms of food security, economy, and social stability. Various drought indices have beendeveloped in order to describe the characteristics of drought such as severity, extent, frequency andduration. These indices can be classified into two categories: ground-based and remotely-sensed indices.Ground-based drought indices are more accurate but limited in coverage, while remote sensing droughtindices cover large areas but have poor precision. Therefore there is need to apply advanced data fusionmethods based on satellite data and ground-based drought indices to fill this gap. However there is a lagtime between drought events and the impacts they cause.Due to the semi arid conditions of Botswana, the country is prone to the occurrence of droughts and hasa great influence on agriculture and economy of the country at large. In order to monitor droughts inBotswana this paper proposes that it is necessary to link the pre meteorological observations and theconsequential vegetation drought. This is neededed for effective monitoring of agricultural drought andearly warning. In this study, MODIS reflectance data and data from recent satellites such as landsat OLI,Sentinel will be used to discover relationships between vegetative drought and meteorological droughtusing vegetation condition index (VCI) derived from NDVI and NDWI, and meteorological droughtderived from SPI and SPEI in Botswana. Dataset derived from Soil Moisture Active Passive (SMAP)will be used to generate %soil moisture content. The %moisture content will be compared withexperimental results from the field. Pearson correlation analyses were performed between single remotesensing drought indices and in-situ drought indices, NDVI and SPEI. Preliminary studies show that VCIderived from NDWI (VCI-2) over Southern District of Botswana can be used as an approach to monitorand provide early warnings. However, there is weak correlation SPEI and VCI-1 and VCI-2 rangingfrom -1 to 0.2.
Field measurements of organic and inorganic composition in the Rambouillet Forest during ACROSS campaign
Authors: Bachelier Fanny , Xue Chaoyang , Houny Jérôme , McGillen Max , Kukui Alexandre , Grosselin Benoit , Mellouki Abdelwahid , Daële Véronique
Published: February 2023

Rambouillet Forest is a large forested location, situated about 50km from central Paris. It covers some 200km² and contains mainly a mix of oak and pine trees. Its size and proximity towards Paris makes it an interesting site to study the interaction between polluted air masses and biogenic emissions and the impact on air quality in areas surrounding polluted cities. The ACROSS (Atmospheric ChemistRy Of the Suburban forest) campaign represents a large international collaboration between various French, European and American institutes, which aims to further characterize these interactions. For our contribution, different instruments from ICARE and LPC2E CNRS Orléans performed in-situ measurements in this forest during June and July of 2022, including: VOCs/ BVOCs (GC-MS/FID); oxidants (OH radicals, CIMS); oxidant precursors (NOx, NOy, Ecophysics, CAPS, LOPAP); and highly oxidized products (orbitrap). In general, data coverage for all instrumentation was high throughout the campaign, furthermore this instrumentation was calibrated and characterized under field condition where possible. These observations represent a broad look at the composition of the forested environment, and contain information on organic emissions, their oxidized products, oxidants and oxidant precursors. We therefore anticipate that these measurements will contribute significantly to the understanding of the atmospheric chemistry operating during the ACROSS campaign.
Sensitivity of EQBO’s boreal winter teleconnections and surface impacts to SSWs
Authors: Butler Amy , Elsbury Dillon , Peings Yannick , Magnusdottir Gudrun
Published: February 2023

The Quasi-Biennial Oscillation (QBO) is known to influence the boreal winter surface circulation. The QBO affects extratropical surface circulation and temperature over Asia as well as the North Atlantic and Europe. While these surface responses are undoubtedly associated with the QBO, it is less clear whether they arise solely due to modulations in the frequency of extreme stratospheric events such as sudden stratospheric warmings (SSWs) or due to other pathways of the QBO. SSWs rapidly evolve in the stratosphere but can initiate persistent hemispheric scale surface temperature and circulation responses and hence, may account for some of the surface response to the QBO. While not reproduced in climate models, reanalysis tends to show that the frequency of SSW is higher during easterly QBO (EQBO), which could suggest the SSW do in fact account for some of the EQBO surface response. However, the QBO has multiple pathways to influence boreal winter surface conditions and hence may affect surface conditions independently of SSWs.Here, we study the teleconnections and extratropical surface responses to EQBO by prescribing EQBO in an ensemble of branched simulations derived from a control simulation run without a QBO. The EQBO branched simulations, which run with repeating annual cycles of sea surface temperatures and sea ice, reproduce many of the observed EQBO teleconnections and surface impacts. After subsampling the branched runs for memberswith and without SSWs, it becomes clear that SSWs are necessary to fully realize both the polar and subtropical routes of EQBO influence. However, there are regions such as east Asia where the surface circulation is able to be modulated by the EQBO even in the absence of SSWs.
The added value of regional climate simulations at kilometre-scale resolution to describe daily wind speed: the CORDEX FPS-Convection multi-model ensemble runs over the Alps
Authors: Molina María Ofelia , Careto Joao , Gutiérrez Claudia , Sánchez Enrique , Soares Pedro
Published: February 2023

In the recent past, the increase in computational resources allowed researchers to run simulations at increasingly horizontal and time resolutions. One such project is the World Climate Research Program’s Coordinated Regional Downscaling Experiments Flagship Pilot Studies (FPS) on convective phenomena. This FPS encompasses a set of simulations driven by the ERA-Interim reanalysis for the period from 2000-2009 (hindcast) and by the Coupled Model Intercomparison Project Phase 5 Global models for the 1996-2005 period (historical). Most models feature a horizontal resolution of 2.2 to 3 km, nested in an intermediate resolution of 12-25 km. An extended Alpine domain is considered for the simulations, due to the complexity of the mountain system together with heavy precipitation events, a large observational network and the high population density of the area. This initiative aims to build first-of-its-kind ensemble climate experiments of convective-permitting models to investigate convective processes over Europe and the Mediterranean.  In this study, the Distribution Added Value metric is used to determine the improvement of the representation of all available FPS hindcast and historical simulations for the daily mean wind speed. The analysis is performed on normalized empirical probability distributions and considers station observation data as a reference. The use of a normalized metric allows for spatial comparison among the different altitudes and seasons. This approach permits a direct assessment of the added value between the higher resolution convection-permitting regional climate model simulations against their global driving simulations and respective coarser resolution Regional Model counterparts. Although the complexity of such simulations, those not always reveal an added value. In general, results show that models add value to their reanalysis or forcing global model, but the nature and magnitude of the improvement on the representation of wind speed vary depending on the model, the spatial distribution and the season. 
Impact of rapid deforestation and conversion of traditional agricultural practices into food crop production on land and water degradation: a case study from Mayotte Island, Indian Ocean, France (2011-2022)
Authors: Foucher Anthony , Evrard Olivier , Rabiet Laura , Cerdan Olivier , Landemaine Valentin , Vitter Maxime , Desprats Jean-François
Published: February 2023

During the last twenty years, Mayotte island (France, Comoros archipelago) has experienced an explosion of population (+80% between 2002 and 2021, taking the official population into account only) leading to a deforestation and a decline in traditional agricultural practices (mahorais garden) in favor of intensive food crop monocultures (e.g. banana, manioc…). These changes in land use are at the origin of an acceleration of erosion dynamics and an excessive transfer of sediments to water bodies downstream. In addition to land degradation, sediment transfers contribute to the filling of reservoirs devoted to supplying drinking water, to the deterioration of the lagoon and to a general loss of biodiversity.The inertia, trajectory and the sources of this erosion remain poorly documented despite the acceleration of this land use evolution during the last 10 years. In this study, we propose a retro-observation of sedimentary fluxes and sources of sediment based on the analysis of sedimentary archives collected in one of the main reservoirs of the island (Dzoumogné reservoir, 22 ha) along with the development of a sediment tracing approach (associating radionuclide measurements, elemental geochemistry, organic matter and color analyses) in order to reconstruct the evolution of erosion rates and sources of since 2011.The first results reveal the occurrence of two periods of erosion acceleration between 2013 and 2015, and then after 2019. The first increase (+140% of erosion rates, from 3.5 to 8.5 t ha-1 yr-1) occurred during a period of deforestation, which induced an opening of the landscape (e.g. creation of unpaved roads). The second acceleration phase took place during the most recent period of agriculture expansion associated with an intensification of agricultural practices (+115% of erosion rates, from 3 t ha-1 yr-1 in 2017 to 6.5 t ha-1 yr-1 in 2020). The sediment accumulated in the reservoir between 2011 and 2021mostly originated from subsurface sources (bank erosion, unpaved roads, gullied soils) and intensive cultivation (e.g., in 2021, 35% of sediment originated from unpaved roads, channel banks, landslides and 27% from intensive cultivation) while forests that are less exposed to erosion only supplied a limited contribution to sediment (<18%). As land use changes are expected to continue in the coming years, understanding the factors controlling the erosion dynamics and the supply of sediment sources are of prime importance in order to implement effective conservation measures and to protect the land and water resources.
Estimation of anthropogenic and volcanic SO2 emissions from satellite data in the presence of snow/ice on the ground
Authors: Fioletov Vitali , McLinden Chris , Griffin Debora , Krotkov Nickolay , Li Can , Joiner Joanna , Theys Nicolas , Carn Simon
Published: February 2023

Early versions of satellite nadir-viewing UV SO2 data products assumed snow-free surface conditions. Snow covered terrain, with its high reflectance in the UV, typically enhances satellite sensitivity to boundary layer pollution. However, a significant fraction of high-quality cloud-free measurements over snow is currently excluded from analyses.  This leads to increasing the uncertainties of the satellite emissions estimates and introducing potential seasonal biases due to the lack of data in winter months for some high-latitudinal sources. In this study, we investigated how OMI and TROPOMI satellite SO2 measurements over snow-covered surfaces could be used to improve the annual emissions reported in our SO2 emissions catalogue (version 2, Fioletov et al., 2023). Although only 100 out of 759 sources listed in the catalogue have 10% or more of the observations over snow, for 40 high-latitude sources more than 30% of measurements suitable for emission calculations were made over snow-covered surfaces. For example, in the case of Norilsk, the world’s largest SO2 emissions point source, annual emissions estimates in the SO2 catalogue were based only on 3-4 summer months, while addition of data for snow conditions extends that period to 7 months. Emissions in the SO2 catalogue were based on satellite measurements of SO2 slant column densities (SCDs) that were converted to vertical column densities (VCDs) using site-specific clear-sky air mass factors (AMFs), calculated for snow-free conditions. The same approach was applied to measurements with snow on the ground whereby a new set of constant, site-specific, clear-sky with snow AMFs was created, and these were applied to the measured SCDs. Annual emissions were then estimated for each source considering (i) only snow-free days, (ii) only clear-sky with snow days and (iii) a merged dataset (snow and no snow conditions). For individual sources, the difference between emissions estimated for snow and snow-free conditions is within ±20% for three quarters of smelters and oil and gas sources, and with practically no systematic bias. This is excellent consistency given that there is typically a 3-5 times difference between AMFs for snow and snow-free conditions. For coal-fired power plants, however, emissions estimated for snow conditions are on average 25% higher than for no snow conditions; this difference is likely real and due to larger production (consumption of coal) and emissions in wintertime. Reference:Fioletov, V. E., McLinden, C. A., Griffin, D., Abboud, I., Krotkov, N., Leonard, P. J. T., Li, C., Joiner, J., Theys, N., and Carn, S.: Version 2 of the global catalogue of large anthropogenic and volcanic SO2 sources and emissions derived from satellite measurements, Earth Syst. Sci. Data, 15, 75–93, https://doi.org/10.5194/essd-15-75-2023, 2023.
Nature-Based Features: developing a framework to shift them from risky investments to reliable and robust solutions
Authors: Olszewski Jennifer , Kucharski John , Smith Matthew , Abellera Marriah , Steissberg Todd
Published: February 2023

Nature-based features (NNBFs) have emerged over the past two decades as tools to leverage natural processes that provide a range of functions from flood reduction to pollutant removal. Despite their growing popularity, a notable gap remains between our understanding of internal NNBF processes and our ability to design NNBFs for specific objectives (e.g., x% reduction of peak storm flow, x% nitrogen reduction) by leveraging such processes. NNBF benefits are, as a result, difficult to quantify, making them a riskier investment compared to tried-and-true grey infrastructure alternatives. This knowledge gap must be filled if we want to design effective and sustainable NNBFs that are viewed on equal footing with grey infrastructure. This presentation will discuss the development of a non-tidal constructed wetland model for the purpose of evaluating design suitability across a range of performance metrics. This model, written in MATLAB, couples hydrologic, hydraulic, and water quality modules. It also allows the user to adjust the constructed wetland configuration (i.e., shape, area, grid cell water depths, vegetation placement, etc.) to maximize specific performance objectives including flood control, wildlife habitat, and water quality. Current efforts are also underway to build upon this design model concept to (1) expand to tidal wetland environments like salt marshes, (2) incorporate vegetation growth/death and morphologic processes, and (3) to incorporate future uncertainty into the design process to support the development of robust and sustainable NNBFs across a range of potential futures and landscape contexts. The overall aim of this work is to develop a framework that allows engineers and policy-makers to evaluate NNBF performance on level footing with grey infrastructure alternatives.