bluuebunny/crossref_metadata_2025 huggingface dataset:
Evaluation of WRF physics ensemble performance in forecasting extreme precipitation events over Germany
Authors: Sotiropoulou Rafaella - Eleni P. , Stergiou Ioannis , Tagaris Efthimios
Published: February 2023

The effectiveness of numerical weather prediction models in forecasting precipitation and temperature extremes is highly dependent on the correct combination of the parameterization schemes as well as the grid resolutions used. For precipitation, the parameterization schemes of microphysics, cumulus and the planetary boundary layer are decisive for the correct forecast of the event. The WRF model is one of the most widely used numerical weather prediction models to estimate such extreme phenomena. In order to identify the optimal combination of these parameterizations for the European region, WRF is used here to simulate eight extreme precipitation events that occurred in the Schleswig–Holstein and Baden–Wurttemberg regions in Germany. The events were selected from the German Weather Service (DWD) catalog and exceeded DWD severe weather warning level 3 (i.e., precipitation > 40 mm/h – W3). A two-way nesting approach is used with 9 and 3 km spatial resolutions. The initial and boundary conditions are obtained from the ERA5 dataset at 0.25° × 0.25° resolution. To model each event, thirty different parameterization configurations were used, accounting for all possible combinations of five microphysics (MP), three cumulus (CU), and two planetary boundary layer (PBL) parameterization methods, yielding a total of 240 simulations. To determine the performance skill of each setup, the multi-criteria decision analysis Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) is employed. Six categorical and five statistical metrics are used as input in the TOPSIS algorithm to calculate each member's performance rank. The analysis conducted here revealed that an increase in the grid spatial resolution from 9 km to 3 km did not result in a substantial improvement in the accuracy of the forecast in time or in the estimation of precipitation intensity. When considering each event individually, the optimal combination, according to the TOPSIS ranking algorithm, is seasonally and geographically dependent, with specific members appearing more frequently in the top-ranking positions. When all events are treated as one to determine the best performing simulating members, the Morrison double-moment (MDM) scheme, along with the Grell-Freitas (GF) CU and the YSU PBL schemes, is found to be the most effective set up, followed by the WRF single-moment 5-class, along with the GF and the YSU schemes.
The double-ITCZ problem in CMIP6 and the influences of deep convection and model resolution
Authors: Zhao Shuyun , Ma Xinyu , Zhang Hua , Wang Wuke
Published: February 2023

The double Intertropical Convergence Zone (ITCZ) bias is an outstanding bias in many climate models. This work assesses the annual-mean double-ITCZ problem in the models participating in the Coupled Model Intercomparison Project Phase 6 (CMIP6) based on several quantitative indices. Within the forty-six CMIP6 models, nine models from mainland China are evaluated as a group to verify the effort of model development from one perspective. The double-ITCZ bias and its large inter-model spread still exist in CMIP6 models. The overall performance of the models from Chinese mainland is similar with all CMIP6 models. It is found that the top-five models with relatively low double-ITCZ biases can effectively restrain the frequency of deep convection and related sea surface temperature (SST) bias in the southeastern Pacific dry subsidence region, which highlights the necessity of improving convective physics in climate models. Impacts of model resolution on the double-ITCZ problem are examined by comparing the high- and low-resolution groups in CMIP6 and High Resolution Model Intercomparison Project (HighResMIP) historical experiments, respectively. Increased resolution in atmospheric models is found to be able to reduce the positive precipitation bias over the tropical southern Atlantic, and improve the simulation of deep convection frequency and convective precipitation ratio there. However, the double-ITCZ bias over the Pacific is not improved significantly by increased resolution.
35-years of aerosols-PBAPs research in Brazil: the need to think outside the Amazonian box
Authors: Mantoani Mauricio , Martins Jorge , Martins Leila , Carotenuto Federico , Šantl-Temkiv Tina , Morris Cindy , Rodrigues Fábio , Gonçalves Fábio
Published: February 2023

Whilst there is a consensus that aerosol particles and primary biological aerosol particles (PBAPs) play an important role in regulating the global climate, with aerosols-PBAPs research increasing lately in Brazil, information summarizing the available knowledge is limited. Here, we present a systematic review of research published during the last 35-years on aerosols-PBAPs in Brazil. A total of 212 studies encompassing 474 cases met the selection criteria. The Amazon rainforest was the most studied biome represented by 72% of cases, followed by the Atlantic Forest with 18%. Studies focusing on the Amazon rainforest mostly studied climate-related issues and aerosol physics, with less than 5% examining the biological identity of aerosols, whereas outside the Amazon rainforest this number reached 16%. In addition, more than half of the cases within Amazon (55%) were held at seven sampling sites only, but conclusions were mainly extrapolated to the entire biome. On the other hand, research beyond Amazon has mostly addressed temporal and biological characterization of PBAPs, and not only is it scattered, but also scarce. Regarding sampling effort, most cases (72%) have had less than 100 days of sampling, and 60% of them spanned less than half a year of study, confining research to one or two seasons at the most. Consequently, while research from different countries that conduce their studies within Brazil and scientific fields are focusing on the same area, inconsistences are slowing the progress of this research topic. We argue that scientists from different fields of research (e.g., biologists, physicists) and countries should work together to produce more detailed and complete assessments of aerosols-PBAPs in the country as a whole, particularly on regards to their biological identity, given their importance to global climate regulation.
Empirical Estimation of Daily Evaporation from Shallow Groundwater with a Temperature Coefficient
Authors: Gao Huibin , Ju Qin , Hao Zhenchun
Published: February 2023

Shallow groundwater evaporation (Eg) is a major component of the hydrological cycle, especially in semiarid and arid locations. Existing Eg estimation processes mainly rely on three approaches: direct measurements, numerical models, and empirical methods. Empirical methods are more commonly used in practical applications due to good performances with more accessible inputs and simple forms. However, most of commonly used empirical methods can only weakly represent Eg variations along the soil depth and do not consider the energy driver. Therefore, a temperature coefficient was proposed and incorporated into two preferred empirical models to characterize the impacts of soil temperature and air temperature lags on Eg. The method was evaluated using in situ daily data obtained from nonweighing bare soil lysimeters. The results indicated that the models that considered the temperature gradient variable (T) conformed to the changes in the actual Eg values with depth more appropriately than the original models, accompanied by 4.3%–8.8% accuracy improvements overall. Shallow groundwater evaporation Eg was found to be influenced by the water table depth (H), T, and pan evaporation (E0) in descending order, and strong interactions were found between H and T. Moreover, bias of Eg measurement results from precipitation was investigated; measurements from dry days without precipitation revealed the actual Eg process, the relative errors in the cumulative Eg values derived at different depths demonstrated a positive relationship with infiltration recharge, and the errors related to precipitation induced 6.7%–8.3% Eg underestimations. These results contribute to a better understanding of evaporative losses from shallow groundwater and the typical Eg situation that occurs simultaneously with recharge, and they provide promising perspectives for corresponding integrated hydrologic modeling research.
Modeling and sensitivity study of wet scavenging models for the Fukushima accident using 1-km-resolution meteorological field data
Authors: Zhuang Shuhan , Dong Xinwen , Xu Yuhan , Fang Sheng
Published: February 2023

Wet scavenging modeling remains a challenge of the atmospheric transport of 137Cs following the Fukushima Daiichi Nuclear Power Plant accident, which significantly influences the detailed spatiotemporal 137Cs distribution. Till now, numerous wet deposition schemes have been proposed for 137Cs, but it is often difficult to evaluate them consistently, due to the limited resolution of meteorological field data and detailed differences in model implementations. This study evaluated the detailed behavior of 25 combinations of in- and below-cloud wet scavenging models in the framework of the Weather Research and Forecasting-Chemistry model, using high-resolution (1 km × 1 km) meteorological input. The above implementation enables consistent evaluation with great details, revealing complex local behaviors of these combinations. The 1-km-resolution simulations were compared with simulations obtained previously using 3-km-resolution meteorological field data, with respect to the rainfall pattern of the east Japan during the accident, atmospheric concentrations acquired at the regional SPM monitoring sites and the total ground deposition. The capability of these models in reproducing local-scale observations were also investigated with a local-scale observations at the Naraha site, which his only 17.5 km from the Fukushima Daiichi Nuclear Power Plant. The performance of the ensemble mean was also evaluated. Results revealed that the 1-km simulations better reproduce the cumulative rainfall pattern during the Fukushima accident than those revealed by the 3-km simulations, but showing with spatiotemporal variability in accuracy. And rainfall below 1 mm/h is critical for the simulation accuracy. Those single-parameter wet deposition models that rely solely on the rainfall showed improvements in performance in the 1-km simulations relative to that in the 3-km simulations, because of the improved rainfall simulation in the 1-km results. Those multiparameter models that rely on both cloud and rainfall showed more robust performance in both the 3-km and -1km simulations, and the Roselle–Mircea model presented the best performance among the 25 models considered. Besides rainfall, wind transport showed substantial influence on the removal process of atmospheric 137Cs, and it was nonnegligible even during periods in which wet deposition was dominant. The ensemble mean of the 1-km simulations better reproduces the high deposition area and the total deposition amount is closer to the observations than the 3-km simulation. At the local scale, the 1-km-resolution simulations effectively reproduced the 137Cs concentrations observed at the Naraha site, but with deviations in peak timing, mainly because of biased wind direction. These findings indicate the necessity of a multi-parameter model for robust regional-scale wet deposition simulation and a refined wind and dispersion model for local-scale simulation of 137Cs concentration.
A journey to a cold seep: a paired teaching video lesson on how scientists study methane in the Arctic Ocean
Authors: Aune Vibeke , Panieri Giuliana , Mohadjer Solmaz
Published: February 2023

The knowledge generated through scientific research in the Arctic Ocean is often done with little input or communication with the public. In particular, school communities have few opportunities to engage in and contribute to knowledge generation and sharing related to the Arctic Ocean.To address this issue, the 2022 AKMA OceanSenses expedition (11-23 May) brought together scientists and teachers to co-create educational materials that are scientifically accurate and pedagogically engaging. Here, we present an educational video about methane activity in the Arctic Ocean. The video follows a pedagogical model known as paired teaching. This approach enables scientists and teachers to create and instruct virtual lessons and activities that are carried out under the guidance of in-class teachers in school classrooms. The video is designed to be viewed in short segments. In each segment, the video scientist asks questions that will be explored through hands-on activities and group discussions under the guidance of the classroom teacher in between segments.The video introduces students to methane and gas hydrates, their geographical distribution, and global significance. These topics are taught through lively discussions and observation-based exercises where students work together to relate scientific datasets to discover processes that produce methane and gas hydrates. The video and supporting materials are freely available on the YouTube channel of the European Geoscience Union (https://youtu.be/k0awmdQQlTA).   
Improving the accuracy of rapid Earth Orientation Parameters with the "ResLearner" machine learning method
Authors: Kiani Shahvandi Mostafa , Dill Robert , Dobslaw Henryk , Mishra Siddhartha , Soja Benedikt
Published: February 2023

Determination of Earth Orientation Parameters (EOP) with utmost accuracy requires the combination of various data sources from different space geodetic techniques, some of which requiring long processing time. This results in a latency of up to several weeks by which the so-called final EOP are released. Since some of the important applications, including satellite navigation and orientation of deep space telescopes, require instantaneous EOP information, the so-called rapid determination and also prediction of EOP are needed. International Earth Rotation and Reference Systems Service (IERS) provides rapid EOP by using the most recent Global Positioning System (GPS) and Very Long Baseline Interferometry (VLBI) 24-hour and intensive sessions data. However, there are some discrepancies between these rapid data and the final, most accurate EOP. In order to reduce these discrepancies and achieve more accurate rapid EOP, we focus on applying machine learning algorithms for polar motion components (xp, yp) and dUT1=UT1-UTC. We focus on a window of 63 days with 31 day predictions to the past and 31 day predictions to the future.We devise a new algorithm called ResLearner, which is a machine learning method based on multilayer perceptrons trying to learn the differences between rapid and final EOP data. We use informative features such as Effective Angular Momentum (EAM) data (both the observations provided by GFZ and the 14-day forecasts provided by ETH Zurich), tides, Liouville equation for (xp, yp), and a linear relation between dUT1 and the axial components of EAM.We use ResLearner in the context of Deep Ensembles in order to derive the uncertainty in the estimations. We also address the so-called unmixing and self-calibration problems. The former enables us to unravel the causes behind the discrepancies between rapid and final EOP as provided by IERS, while the latter could help us reduce these erroneous effects. We train the algorithms on both the IERS and Jet Propulsion Laboratory (JPL) final EOP data. Our ResLearner method can consistently reduce the discrepancies between rapid and final EOP across all days. The improvement in accuracy is up to 55%. We observe some unexpected behaviour related to day 0 of prediction, in which the accuracy of the IERS is significantly better than the immediately preceding or following values. Our unmixing algorithm shows that this behaviour is probably related to erroneous, non-linear effects of EAM at day 0, and also semi-diurnal, diurnal, long-period retrograde and prograde, and zonal tides. Using our self-calibration algorithm for EAM, we can slightly improve the prediction performance by up to 14%.Finally, we provide the improved rapid EOP data publicly, operationally, and on a daily basis, on the ETH Zurich prediction center website at https://gpc.ethz.ch/EOP/Rapid/
Evaluating diffuse wavefield and its applications in seismic imaging
Authors: Yang Bo , Meng Haoran , Gu Ning , Liu Xin , Chen Xiaofei
Published: February 2023

The cross-correlation of ambient seismic noise data can be utilized to image subsurface geological structures from ambient noise fields at local, regional, and global scales by extracting Green's functions between seismograph pairs. Precise extraction of empirical Green's functions from the cross-correlations of noise records requires that the seismic wavefield be fully diffuse. This requires the coefficients of the eigenfunction expansion of the seismic records to satisfy the statistical characteristics derived by Weaver and Lobkis (2004) in the time domain. Due to the complexities of the Earth media and noise sources, it is not feasible to obtain accurate eigenfunctions with the corresponding coefficients and adopt these statistical characteristics to evaluate actual seismic data. To resolve this issue, we derive the equivalent expressions in the frequency domain with dimensionless evaluation criteria without requiring the eigenfunctions. The evaluation of random noise, wind-induced vibrations, car- and air-traffic-excited ground motions, earthquakes, and continuous ambient seismic noise records confirms the validity of our evaluation method. We further apply the method to the widely used preprocessing procedures of ambient noise imaging techniques by examining time-domain normalization and spectral whitening operations of earthquake waveforms, thus quantitatively demonstrating how these procedures down-weight the non-diffuse component and improve the degree of waveform diffuseness (as shown in Figure 1). As an application, we select the coda wave signals generated by road traffic and earthquakes that satisfy the diffuse wavefield characteristics and extract the higher-order surface wave dispersion curves from 20-100 s seismic recordings without performing preprocessing procedures. Compared with the traditional surface wave processing process, our method is highly efficient, does not require long recording time and preprocessing such as normalization and whitening, and can be widely used in evaluating diffuse wavefield, imaging subsurface velocity and attenuation structures, and monitoring the temporal changes with high temporal resolution.
Heavy precipitation events where there’s no rain: Saharan rainfall climatology and its relationship with cyclones
Authors: Armon Moshe , de Vries Andries Jan , Marra Francesco , Peleg Nadav , Wernli Heini
Published: February 2023

The Sahara is the largest and perhaps the driest desert in the world. This desert however, has not always been this dry. In fact, it is presumed that a few thousand years ago it was much wetter. Moreover, it is projected that, by the end of the 21st century, the Sahara will exhibit the strongest relative increase in precipitation outside the polar regions. To better grasp this information, however, we need to answer some questions: wetter than what? What is the present-day rainfall climatology of the Sahara and what are the synoptic conditions during rainstorms in the desert?Currently, rainstorms in the Sahara are considered a rare phenomenon. However, rain-bearing cyclones intruding from wetter neighboring regions are possible, and can lead to heavy precipitation events (HPEs) which cause hazardous desert floods. When rainfall occurs, the chances for it to be observed and measured at the ground are close to zero due to the scarcity of rain gauges and the small scale of the precipitation systems. Consequently, the characteristics of rainfall during Saharan rainstorms were seldom analyzed, especially at the scale of the whole desert. In this study, we use high-resolution satellite precipitation estimates (IMERG) and meteorological reanalysis (ERA5) to (a) identify thousands of HPEs that occurred over the Sahara in the past 21 years, (b) characterize rainfall properties during these events, and (c) identify the governing atmospheric conditions on HPE-days, with a focus on surface cyclones.Our results show that HPEs may occur throughout the entire Sahara. Summer events happen mainly in the southern Sahara. They tend to be short-lived (on average ~12 h) and small in size (~8000 km2), with high-intensity convective rainfall. Conversely, winter HPEs occur primarily in the northern and western parts of the desert, they are longer (~16 h) and larger (15,000 km2) and produce higher rainfall volumes with lower rainfall intensities. When associated with cyclones (29% of events), HPEs exhibit 15% lower rainfall intensities, and 46% higher volumes. This is likely due to a much greater (+64%) areal extent. Our analysis compensates the small number of events at each location with the huge area of the desert, so that a HPE is observed on average every second day. The high-resolution datasets we use enable us to characterize small-size events, with substantial implications for the local scales. Hopefully, such an analysis can serve as a starting point to cope with natural hazards and better understand the future of HPEs in the Sahara.
Testing the space-for-time substitution on the temperature sensitivity of terrestrial vegetation
Authors: Fan Naixin , Forkel Matthias , Carvalhais Nuno
Published: February 2023

Space-for-time substitution has been used to infer long-term ecological processes such as vegetation dynamics, turnover of species, nutrient cycling, etc. The theory of space-for-time substitution was established to understand temporal processes from contemporary spatial patterns or gradients due to the lack of long-term temporal observations on the response of vegetation to climate change. However, the validity of this theory has been largely debated mostly due to the fact that the fundamental assumption, a climate or an environmental driver of the spatial gradient also drive its temporal change, has not been systematically tested. There is still lack of quantitative understanding of the interaction between climate and vegetation at different spatial and temporal scales. In this study, we used global observations of spatiotemporal changes in several proxies of vegetation (e.g., NDVI) to investigate the link between space and time in the responses of vegetation to climate. We show that the temperature sensitivities of vegetation derived from large scale spatial gradient (space) are highly correlated with the temporal temperature sensitivity (time). Our goal of this study is not only providing quantitively analysis on the spatiotemporal linkage in terrestrial vegetation but also to provide a broader perspective on the methodology that links space and time in understanding the variability of global vegetation. 
Parameter transferability of a distributed hydrological model to droughts
Authors: Bruno Giulia , Duethmann Doris , Avanzi Francesco , Alfieri Lorenzo , Libertino Andrea , Gabellani Simone
Published: February 2023

Hydrological models often do not simulate properly streamflow (Q) during droughts, because of a poor representation of the interactions among precipitation deficits, actual evapotranspiration (ET), and terrestrial water storage anomalies (TWSA) during these periods. However, there is little research comprehensively evaluating model skills during droughts of varying intensity in a spatially distributed way. To shed further light into these drops in model skills and step toward more robust models in an anthropogenic era and a changing climate, we evaluated Q, ET, and TWSA simulations during moderate and severe droughts, and we tested if calibrating during a moderate drought could enhance model performances during a severe one. We applied the distributed hydrological model Continuum over the heavily human-affected Po river basin in northern Italy and the period 2010 – 2022. Moreover, we exploited independent ground- and remote sensing-based datasets to evaluate the temporal and spatial variability of Q, ET, and TWSA monthly simulations across the whole basin and 38 sub-catchments. Model performances for Q across the study sub-catchments were comparable during both wet years (2014 and 2020, mean KGE = 0.59±0.32) and moderate droughts (2012 and 2017, mean KGE = 0.55±0.25). Further, Continuum simulated well Q for the basin outlet even during a severe drought (KGE = 0.82 in 2022), while its performances generally decreased among the sub-catchments (mean KGE = 0.18±0.69 in 2022). In general, the model well represented ET and TWSA seasonality over the study area, and a decline in TWSA over the more recent years. Yet, during the severe 2022 drought we detected an increased uncertainty in ET anomalies, especially in human-affected croplands, that could explain the Q performance drop along with an increased anthropogenic disturbance. Including a moderate drought (2017) in the calibration period did not lead to a significant improvement in model skills during the severe event (mean KGE = 0.18±0.63 for Q during 2022), meaning that the severe 2022 drought was fairly unique for the study area both in terms of hydrological processes and human disturbance on them. By unveiling an increase in model uncertainty during a severe drought and possible causes for it, our findings are relevant to assess and possibly enhance model robustness in a changing climate and the anthropogenic era for adequate water management, disaster risk reduction, and climate change adaptation.
Arc splitting and back-arc spreading evolution: the control of hydration and melts
Authors: Gomes Ana , Balázs Attila , Gerya Taras
Published: February 2023

While there has been a lot of work focusing on improving our understanding of divergent and convergent plate boundaries, the complex nature of the back-arc region, where convergent margins transition into large-scale extension in the upper plate, is yet to be investigated fully. Indeed, why and how extensional basins open near the boundaries between convergent plates, followed by their tectonic inversion, have long been outstanding questions in plate tectonics.Here we investigate a wide range of factors that influence the development of back-arc extension using 2D thermo-mechanical code I2VIS employing visco-plastic rheologies, hydration and dehydration processes, melting and surface processes. We systematically vary several parameters to determine their roles and respective importance, including a)  fluid and melt induced weakening, b) upper plate geothermal gradient and c) amount of sediment in the accretionary wedge. The fluid and melt induced weakening is implemented by using the Mohr–Coulomb yield criterion that limits the creep viscosity, altogether yielding an effective visco-plastic rheology, and controlled via the melt/fluid pore fluid pressure parameters, λfluid and λmelt. The upper plate geothermal gradient is controlled by the parameter TMoho . Finally, the amount of sediment in the accretionary wedge is changed through the parameter Sedlev, which controls the minimum y-coordinate sediments can occupy, throughout the model. The higher the Sedlev, the less the height of sediment that can accumulate in the accretionary wedge.Our extensive series of high-resolution models led to the following conclusions:a) a higher upper plate geothermal gradient predictably leads to a more ductile rheology, which then results in an initial wider rift, followed by enhanced melting and earlier arc splitting; 
b) higher erosion and sedimentation rates lead to increasing hydration of the mantle wedge and enhancing mantle melting, and decreasing the stress transfer from the lower to the upper plate; 
c) λfluid controls arc rifting to a greater extent, relative to λmelt, and for λfluid smaller than 0.2, arc rifting occurs. This means that the fluid induced weakening has to be high, in order to produce arc rifting.
These initial results suggest that the upper plate geotherm has the highest magnitude effects in modulating arc rifting, but fluid and melt induced weakening are also major controls in rift development, in the sense that they regulate whether it happens at all, or not. The height of the accretionary wedge works with the fluid weakening of the upper plate, facilitating arc rifting. 
Phosphorous losses in flood events in a Mediterranean agroforestry catchment: effects of rainfall characteristics and land use
Authors: Ramos Maria Concepción , Lizaga Ivan , Gaspar Leticia , Navas Ana
Published: February 2023

Runoff generated after rainfall of high magnitude and/or with high intensity transport soil and sediments that finally reach rivers and water bodies affecting water quality. All land uses can contribute to the problem, but in particular croplands are considered important nonpoint sources of phosphorous losses. The aim of this research was to evaluate the phosphorus delivery and transport after flood events in an agroforestry catchment, in which woodland and cropland are the dominant land uses. To this purpose sediments were collected in five trap MATs distributed across the catchment. A total of 20 sampling campaigns were carried out during five years, in which rainfall events of different characteristics (total precipitation and intensity) were recorded.  Besides P concentration, particle size and other properties such as soil organic matter (SOM), low frequency magnetic susceptibility (χLF) and Ti concentrations were analysed in the sediment trapped in the MATs to relate them to the provenance of the sediment.  The rainfall events recorded in each campaign were analysed and the campaigns were grouped using a cluster analysis taken into account the characteristics of the collected sediments. The study reveals a P enrichment in the sediments compared to the soils under all land uses, with the greatest P concentration associated to sediment rich in clay and SOM. However, the sediment showed lower χLF than the soils. P losses were higher at the catchment outlet than at the headwaters. These results are explained by two main factors: the higher water volumes accumulated at the outlet and the greater contribution of cropland to P losses compared to the other land uses, since cropland occupies a greater area at the outlet of the catchment. Our findings also confirmed the clear influence of the precipitation concentration on P losses, which suggest that under the increase of events of high intensity projected under climate change scenarios, the mobilisation of P and its loss, in particular from croplands will increase, which could exacerbate water pollution.
Time-series Boosting in Ensemble Modelling of Real-Time Flood Forecasting Application
Authors: Piadeh Farshad , Piadeh Farzad , Behzadian Kourosh
Published: February 2023

While concept of boosting ensemble data mining techniques has been recently attracted a lot of attention for flood forecasting, mainly on non-urbanised river basins or reservoirs [1,2], time-series boosting, i.e., contribution of last timestep prediction to the next forecasting model is a new era, especially for real-time operation of flood forecasting models in the shape of early warning systems.This study aims to provide time-series boosting for ensemble flood forecasting model through adding forecasted water level of one timestep before as an input of training base models to previous proposed rainfall feature, especially rainfall duration, intensity, evidence of past rainfall and season occurrence [3]. Several weak learner data mining techniques are developed for various forecast lead times and recorded in data cube structure that can be used for developing time-series boosted ensemble model. This novel model was tested for real case study of Hanwell urban drainage systems located in the west London, UK for a period of 20 years data with 15min intervals. Confusion matrix is employed for performance assessment and the model is compared by conventional benchmark gradient boosted models.Results shows the added feature can significantly increase the accuracy of overflow detection of all developed base models, especially for longer timesteps. More specifically, adding the new feature to the model can increase the accuracy rate from 84% for the best developed base model to 93% in 3hrs-ahead predictions. More importantly, the model can decrease underestimation miss rate from 45% to only 21% for the same forecast lead time. Furthermore, new time-series boosted ensemble model can noticeably increase overflow detection rate, where hit rate increase from 78% to 88% in 3hrs-ahead predictions. Overall, the concept of time-series boosted ensemble modelling can overcome the problem of missing and false alarm of real-time operation by adding the previous situation of catchment to the forecasting procedure.References[1] Jarajapu, D., Rathinasamy, M., Agarwal, A., Bronstert, A. (2022). Design flood estimation using extreme Gradient Boosting-based on Bayesian optimization, Journal of Hydrology, 613(A), 128341.[2] Piadeh, F., Behzadian, K., Alani, A. (2022). A critical review of real-time modelling of flood forecasting in urban drainage systems. Journal of Hydrology, 607, 127476.[3] Piadeh, F., Behzadian, K., Alani, A.M. (2022). Multi-Step Flood Forecasting in Urban Drainage Systems Using Time-series Data Mining Techniques. Water Efficiency Conference, West Indies, Trinidad and Tobago. repository.uwl.ac.uk/id/eprint/9690 [Accessed 31/12/2022].
Modelling the trends and drivers of the CO2 seasonal cycle amplitude in northern high latitudes
Authors: Cai Wenjia , Prentice Iain Colin
Published: February 2023

Seasonal variations in  atmospheric carbon dioxide (CO2) reflect the responses of terrestrial ecosystems to environmental variations. Accurate estimation of the spatial distribution of global CO2 fluxes would improve our ability to close the global carbon budget and predict the effect of climate change on the terrestrial carbon sink. A large increase in the seasonal cycle amplitude (SCA) of CO2 in northern high latitudes since the 1950s has been observed. However current vegetation models generally fail to reproduce the magnitude of this increase, while the underlying mechanisms are still debated. Using an eco-evolutionary optimality model (the P model) we simulated global gridded atmosphere-ecosystem CO2 exchange from the 1950s onwards and converted the results to atmospheric CO2 concentration variations using the global chemistry-transport model TM5. Our modelled global CO2 flux and derived carbon sink are comparable with that derived from TRENDY models as used in the Global Carbon Project’s annual assessment. The P model could capture the trend of SCA in northern high latitudes, as shown both at remote monitoring stations and in aircraft campaigns. We evaluated the contribution of potential drivers in SCA trends, including atmospheric CO2, climate, land use change and agricultural practices. Our analysis demonstrated that a parameter-sparse model can capture the observed CO2 SCA trend and provide useful insights for carbon cycle dynamics.
Modeling Secondary Ice Processes on a midlatitude squall line
Authors: Gao Jie , Xue Huiwen
Published: February 2023

Secondary ice processes (SIPs) can produce ice crystals with a number concentration much higher than that of ice nucleating particles (INPs) in mixed-phase clouds, and therefore influence cloud glaciation and precipitation. But the role of SIPs in midlatitude continental mesoscale convective systems (MCSs) such as squall lines is still unknown. This study investigates the relative importance of rime splintering, freezing drop shattering, and collision breakup in the mature stage of a squall line case in North China on 18 August 2020 using the WRF model. The simulations show that collision breakup has the most pronounced effect on ice production, and rime splintering plays a secondary role. It is because ice multiplication from SIPs can feedback to collision breakup and rime splintering in different ways. Collision breakup has a positive feedback because the numerous snow and graupel from SIPs in turn promote a higher collision breakup rate, while rime splintering is limited by itself and also limited by collision breakup because the weaker riming due to the two SIPs leads to a lower rime splintering rate. Freezing drop shattering has a negligible effect on ice production because there are few large droplets in the mature stage. Collision breakup can also redistribute surface precipitation in the squall line, which decreases in the convective region and increases in the stratiform region. The influence of aerosols as CCN and INPs on SIPs is further studied. Preliminary simulation results show that the effects of aerosol concentration on the rate of SIPs and anvil ice concentration are nonlinear. The mechanism remains to be analyzed.
Evaluation of the Semi-Arid Region Groundwater Storage Potential for Solapur Region, Maharashtra, India
Authors: Patil Yuvraj , Landage Amarsinh
Published: February 2023

Groundwater storage potential is defined as the total amount of permanent storage that exists in the aquifers. The significance of groundwater storage potential is effectively concerned with climate-related impacts on groundwater resources. The current demand for groundwater for societal needs will hasten the depletion rate of the regional groundwater potential. The present research employs a groundwater modelling tool called MODFLOW to estimate the regional groundwater sensitivity, potential and conceptual simulations of groundwater flow in the study region. The groundwater levels of the Solapur region from 2010 to 2021 were used to investigate the region's groundwater potential, along with other parameters, viz., aquifer type and hydraulic conductivity in both vertical and horizontal directions. The groundwater level shows a sensitive response to the rainfall intensity, but the unconsolidated materials have greater water depths regardless of the season. Consolidated material formations show lower available water depths, irrespective of the season. The simulated results of the study show that the regional groundwater depths are sensitive to hydraulic conductivity in both horizontal and vertical directions. The zone budget's findings shows that the regional inflow and outflow are nearly equal. The study replicates that the Solapur area is semi-arid. As a consequence, this research is relevant to all semi-arid places where groundwater is becoming the dominant source of social requirements. Such a study would be useful for appropriate planning and management of groundwater for future requirements.Keywords: Groundwater level, Rainfall, Geology, Modflow, Zone budget. 
Exceptional decrease of Indian Ocean carbon uptake in 2015-2016 due to a remote effect of El Niño
Authors: Liao Enhui , Lu Wenfang
Published: February 2023

The Indian Ocean experienced an extremely anomalous carbon flux with a magnitude of 0.1 PgC/yr in 2015-2016 according two pCO2-based data products and MOM6 model simulations. However, the Indian Ocean Dipole (IOD) climate mode cannot well explain the anomalous interannual variability. We show that the Indian Ocean carbon flux anomaly is remotely driven by the extreme 2015-2016 El Niño which is the strongest El Niño in the 21st century. The El Niño is able to drive a basin-scale warming and high dissolved inorganic carbon (DIC) anomaly in the southeastern tropical Indian Ocean which increase ocean pCO2 and weaken the ocean carbon sink in the Indian Ocean. The basin-scale warming is induced by a more shortwave radiation and less latent heat flux loss in the Indian Ocean which is originated from El Niño through cloud-radiation-SST feedback and wind-evaporation-SST (WES) feedback. The high DIC in the southeastern tropical Indian Ocean is induced by a less dilution of weakened the fresh Indonesia Through Flow (ITF) and reduced freshwater flux associated with El Niño. The ocean carbon response to El Niño remote effect is different from IOD. This study complements the understanding of air-sea CO2 flux interannual variability in the Indian Ocean.
Enormously large tippers observed in South-West of China. Can realistic 3-D modeling reproduce them?
Authors: Xu Shan , Chen Chaojian , Kuvshinov Alexey , Kruglyakov Mikhail , Rigaud Rafael , Hu Xiangyun
Published: February 2023

Vertical magnetic transfer functions (tippers) observed at a global/continental net of geomagnetic observatories can be used to image the electrical conductivity structure of the Earth down to a depth of around 200 km. We estimated tippers at 54 geomagnetic observatories across China, aiming eventually to invert them in terms of subsurface three-dimensional (3-D) conductivity distribution. Strikingly, we obtained enormously large tippers at three inland observatories in southwest China. Large tippers are often observed at coastal observatories due to the high lateral conductivity contrast between resistive continental bedrock and conductive seawater. However, tippers at those mentioned above observatories appeared to be a few times larger than coastal tippers. Moreover, as far as we know, such large tippers (reaching value 3) were never reported in any region of the world. We perform 3-D electromagnetic simulations mimicking the geological setting of the region and demonstrate that the enormously large tippers are feasible and can be attributed to a current channelling. 
The potential of machine learning to solve the single step inversion problem in ambient noise tomography
Authors: Fone Joseph , Rawlinson Nicholas
Published: February 2023

The two step inversion of ambient noise surface wave data is common practice due to its convenience and reliability of imaging structures that are consistent with other observations. It is performed by taking the inter station dispersion curves produced by cross-correlation of ambient noise and performing individual 2D travel time tomographic inversions to produce maps of phase and/or group velocity for Rayleigh and/or love waves and whichever frequencies and modes have been extracted from the ambient noise data. These maps are then sampled in discrete points to produce location based dispersion curves known as pseudo-dispersion curves. These pseudo-dispersion curves are then inverted for 1D velocity structure. The issue with this method is the many separate inversions that are performed are entirely separate from one another with no regularisation applied to the final 3D model only in the individual steps. This can lead to artefacts in the model, particularly in areas of low data coverage, as the pseudo-dispersion curves can have unphysical spikes and velocity changes and so often produce unrealistic 1D models. Post processing can partially remedy this, such as smoothing the final model, but it does not go all the way to solving the problem. Single step inversions are also possible. The forward problem involves taking the 3D model and sampling it in discrete locations and computing dispersion curves which can be converted into 2D maps of phase/group velocity etc. Then using some Eikonal solver the travel time between stations can be calculated. These calculated travel times are then used with the measured travel times extracted from ambient noise to perform an inversion. This obtains a 3D model directly from the observed dispersion curves with regularisation built into whichever inversion scheme being used. This is often much more computationally expensive than the two step as the forward problem is expensive and needs to be computed many times in a typical inversion scheme. In this preliminary study we investigate the potential of using neural networks to assist in the single step inversion process by training networks to perform the forward and inverse problems in single step tomography of interstation dispersion curves. This may result in significant speed ups in these processes or lead to different ways of approaching the one step process. To examine the potential of this we investigate possible efficient sampling algorithms to produce synthetic training data sets as well as network architectures that produce the most accurate mapping of model parameters to the data and vice versa.
Radar Sounding Waveform Fitting for Roughness parameters estimation
Authors: Gambacorta Letizia , Mastrogiuseppe Marco , Seu Roberto
Published: February 2023

SHARAD (Shallow Radar) and MARSIS (Mars advanced Radar for subsurface and ionosphere sounding) are two low frequency sounder radars in orbit around Mars whose aim is to assess the distribution of on-ground and buried water, to provide the material composing its crust and to study its topography at global scale. The estimation of dielectric properties using radar data, can be pursued by means of different methods, including a parametric data inversion approach. Our method provides for the estimation of surface permittivity and loss tangent by exploiting the ratio between the return powers from the surface and the subsurface at different frequencies. As the roughness of the surface as well as the subsurface, affects  the returned power, inversion techniques are often applied  on moderately flat surfaces, where the power loss due to roughness can be considered negligible.In this work we present an approach for the estimation of surface roughness properties and power loss compensation via waveform fitting, whose shape is modified in relation to the  characteristics of the surface impinged by the emitted electromagnetic wave. Such fitting procedure exploits a large-scale roughness model for the power return obtained under the Kirchhoff approximation hypotheses and comprising both the coherent and the non-coherent components of the scattered field. Our method allows to estimate the roughness regime of the selected area in terms of height standard deviation and root mean squared slope and therefore to compensate for  power losses in relation with the estimated parameters.The performances of the fitting procedure are tested using a ray-tracing simulator of the range-compressed SHARAD and MARSIS received signal. As a fist step we applied the analysis on isotropic gaussian surfaces with different roughness characteristics showing the possibility to recover the power lost due to roughness effects. Moreover, the analysis will be performed on MOLA simulated products to represent MARS surface and finally, will be applied to SHARAD real data acquired over the volcanic region of Elysium Planitia.
Validation of a subglacial hydrology model with analytical and semi-analytical solutions
Authors: Schmiedel Jeremie , Sayag Roiy
Published: February 2023

Subglacial hydrology is a key component in ice sheet dynamics. The presence of subglacial water at the ice-bed interface can significantly reduce basal friction and facilitate rapid ice flow, which could lead to the formation of surges and ice streams. The action of the subglacial network on ice flow is simulated by a range of numerical models. Validating these models is essential to ensure that the important physical processes are included, and that the numerical methods provide accurate solutions. In addition to field measurements, which are challenging to obtain at the ice-bed interface, a common validation technique includes inter-comparison with other numerical models. Even though such a technique is beneficial, it does not provide an equivalent validation as exact solutions. Here we present analytical and semi-analytical solutions for confined and unconfined flows in porous layers to validate subglacial hydrology models, which are based on an effective porous medium (EPM) approach. We then apply them to validate the confined-unconfined aquifer scheme (CUAS) model. We find that the numerical results are consistent with the analytical solutions, which provides more confidence that CUAS accurately solves the hydrology equations. Because of their generality, our solutions are readily applicable to other subglacial hydrology models that are based on an EPM approach. We anticipate that a validated hydrology model with our solutions can achieve more credible results in subglacial network simulations.