bluuebunny/crossref_metadata_2025_split huggingface dataset:
Ambient nitro-aromatic compounds – biomass burning versus secondary formation in rural China
Authors: Salvador Christian Mark Garcia , Tang Rongzhi , Priestley Michael , Li Linjie , Tsiligiannis Epameinondas , Le Breton Michael , Zhu Wenfei , Zeng Limin , Wang Hui , Yu Ying , Hu Min , Guo Song , Hallquist Mattias 
Published: February 2021

Abstract. Nitro-aromatic compounds (NACs) were measured hourly at a rural site in
China during wintertime to monitor the changes due to local and regional
impacts of biomass burning (BB). Concurrent and continuous measurements of
the concentrations of 16 NACs in the gas and particle phases were performed
with a time-of-flight chemical ionization mass spectrometer (CIMS) equipped
with a Filter Inlet for
Gases and AEROsols (FIGAERO) unit using iodide as the
reagent ion. NACs accounted for <2 % of the mass concentration of
organic matter (OM) and total particulate matter (PM), but the total
particle mass concentrations of these compounds can reach as high as 1000 ng m−3 (299 ng m−3 avg), suggesting that they may contribute
significantly to the radiative forcing effects of atmospheric particles.
Levels of gas-phase NACs were highest during the daytime (15:00–16:00 local
time, LT), with a smaller night-time peak around 20:00 LT. Box-model
simulations showed that this occurred because the rate of NAC production
from gas-phase sources exceeded the rate of loss, which occurred mainly via
the OH reaction and to a lesser degree via photolysis. Data gathered during
extended periods with high contributions from primary BB sources (resulting
in 40 %–60 % increases in NAC concentrations) were used to characterize
individual NACs with respect to gas–particle partitioning and the
contributions of regional secondary processes (i.e. photochemical smog). On
days without extensive BB, secondary formation was the dominant source of
NACs, and NAC levels correlated strongly with the ambient ozone
concentration. Analyses of individual NACs in the regionally aged plumes
sampled on these days allowed precursors such as phenol and catechol to be
linked to their NAC derivatives (i.e. nitrophenol and nitrocatechol).
Correlation analysis using the high time resolution data and box-model
simulation results constrained the relationships between these compounds and
demonstrated the contribution of secondary formation processes. Furthermore,
13 of 16 NACS were classified according to primary or secondary formation
process. Primary emission was the dominant source (accounting for 60 %–70 %
of the measured concentrations) of 5 of the 16 studied NACs, but secondary
formation was also a significant source. Photochemical smog thus has
important effects on brown carbon levels even during wintertime periods
dominated by primary air pollution in rural China.
Cold cloud microphysical process rates in a global chemistry–climate model
Authors: Bacer Sara , Sullivan Sylvia C. , Sourdeval Odran , Tost Holger , Lelieveld Jos , Pozzer Andrea 
Published: February 2021

Abstract. Microphysical processes in cold clouds which act as sources or sinks of hydrometeors below 0 ∘C control the ice crystal number concentrations (ICNCs) and in turn the cloud radiative effects. Estimating the relative importance of the cold cloud microphysical process rates is of fundamental importance to underpin the development of cloud parameterizations for weather, atmospheric chemistry, and climate models and to compare the output with observations at different temporal resolutions. This study quantifies and investigates the ICNC rates of cold cloud microphysical processes by means of the chemistry–climate model EMAC (ECHAM/MESSy Atmospheric Chemistry) and defines the hierarchy of sources and sinks of ice crystals. Both microphysical process rates, such as ice nucleation, aggregation, and secondary ice production, and unphysical correction terms are presented.
Model ICNCs are also compared against a satellite climatology.
We found that model ICNCs are in overall agreement with satellite observations in terms of spatial distribution, although the values are overestimated, especially around high mountains.
The analysis of ice crystal rates is carried out both at global and at regional scales.
We found that globally the freezing of cloud droplets and convective detrainment over tropical land masses are the dominant sources of ice crystals, while aggregation and accretion act as the largest sinks. In general, all processes are characterized by highly skewed distributions. Moreover, the influence of (a) different ice nucleation parameterizations
and (b) a future global warming scenario on the rates has been analysed in two sensitivity studies. In the first, we found that the application of different parameterizations for ice nucleation changes the hierarchy of ice crystal sources only slightly.
In the second, all microphysical processes follow an upward shift in altitude and
an increase by up to 10 % in the upper troposphere towards the end of the 21st century.
Simulating compound weather extremes responsible for critical crop failure with stochastic weather generators
Authors: Pfleiderer Peter , Jézéquel Aglaé , Legrand Juliette , Legrix Natacha , Markantonis Iason , Vignotto Edoardo , Yiou Pascal 
Published: February 2021

Abstract. In 2016, northern France experienced an unprecedented wheat crop loss. The cause of this event is not yet fully understood, and none of the most used crop forecast models were able to predict the event (Ben-Ari et al., 2018). However, this extreme event was likely due to a sequence of particular meteorological conditions, i.e. too few cold days in late autumn–winter and abnormally high precipitation during the spring season. Here we focus on a compound meteorological hazard (warm winter and wet spring) that could lead to a crop loss. This work is motivated by the question of whether the 2016 meteorological conditions were the most extreme possible conditions under current climate, and what the worst-case meteorological scenario would be with respect to warm winters followed by wet springs. To answer these questions, instead of relying on computationally intensive climate model simulations, we use an analogue-based importance sampling algorithm that was recently introduced into this field of research (Yiou and Jézéquel, 2020). This algorithm is a modification of a stochastic weather generator (SWG) that gives more weight to trajectories with more extreme meteorological conditions (here temperature and precipitation). This approach is inspired by importance sampling of complex systems (Ragone et al., 2017). This data-driven technique constructs artificial weather events by combining daily observations in a dynamically realistic manner and in a relatively fast way. This paper explains how an SWG for extreme winter temperature and spring precipitation can be constructed in order to generate large samples of such extremes.
We show that with some adjustments both types of weather events can be adequately simulated with SWGs, highlighting the wide applicability of the method. We find that the number of cold days in late autumn 2015 was close to the plausible minimum. However, our simulations of extreme spring precipitation show that considerably wetter springs than what was observed in 2016 are possible. Although the relation of crop loss in 2016 to climate variability is not yet fully understood, these results indicate that similar events with higher impacts could be possible in present-day climate conditions.
Dataset of Georeferenced Dams in South America (DDSA)
Authors: Paredes-Beltran Bolivar , Sordo-Ward Alvaro , Garrote Luis 
Published: February 2021

Abstract. Dams and their reservoirs generate major impacts on society and the environment. In general, its relevance relies on facilitating the management of water resources for anthropogenic purposes. However, dams could also generate many potential adverse impacts related to safety, ecology or biodiversity. These factors, as well as the additional effects that climate change could cause in these infrastructures and their surrounding environment, highlight the importance of dams and the necessity for their continuous monitoring and study. There are several studies examining dams both at regional and global scales; however, those that include the South America region focus mainly on the most renowned basins (primarily the Amazon basin), most likely due to the lack of records on the rest of the basins of the region. For this reason, a consistent database of georeferenced dams located in South America is presented: Dataset of Georeferenced Dams in South America (DDSA). It contains 1010 entries of dams with a combined reservoir volume of 1017  km3, and it is presented in the form of a list describing a total of 24 attributes that include the dams' names, characteristics, purposes and georeferenced locations. Also, hydrological information on the dams' catchments is also included: catchment area, mean precipitation, mean near-surface temperature, mean potential evapotranspiration, mean runoff, catchment population, catchment equipped area for irrigation, aridity index, residence time and degree of regulation. Information was obtained from public records, governments records, existing international databases and extensive internet research. Each register was validated individually and geolocated using public-access online map browsers, and then, hydrological and additional information was derived from a hydrological model computed using the HydroSHEDS (Hydrological data and maps based on SHuttle Elevation Derivatives at multiple Scales) dataset. With this database, we expect to contribute to the development of new research in this region. The database is publicly available at https://doi.org/10.5281/zenodo.4315647 (Paredes-Beltran et al., 2020).
Shyft v4.8: a framework for uncertainty assessment and distributed hydrologic modeling for operational hydrology
Authors: Burkhart John F. , Matt Felix N. , Helset Sigbjørn , Sultan Abdella Yisak , Skavhaug Ola , Silantyeva Olga 
Published: February 2021

Abstract. This paper presents Shyft, a novel hydrologic modeling software for streamflow forecasting
targeted for use in hydropower production environments and research. The software enables
rapid development and implementation in operational settings and the capability to perform
distributed hydrologic modeling with multiple model and forcing configurations. Multiple models
may be built up through the creation of hydrologic algorithms from a library of well-known
routines or through the creation of new routines, each defined for processes such as
evapotranspiration, snow accumulation and melt, and soil water response. Key to the design of
Shyft is an application programming interface (API) that provides access to all components of the
framework (including the individual hydrologic routines) via Python, while maintaining high
computational performance as the algorithms are implemented in modern C++. The API allows for
rapid exploration of different model configurations and selection of an optimal forecast
model. Several different methods may be aggregated and composed, allowing direct intercomparison
of models and algorithms. In order to provide enterprise-level software, strong focus is given
to computational efficiency, code quality, documentation, and test coverage. Shyft is released open-source under the GNU Lesser General Public License v3.0 and available at
https://gitlab.com/shyft-os (last access: 22 November 2020), facilitating effective cooperation between core developers, industry, and
research institutions.
Advanced parallel implementation of the coupled ocean–ice model FEMAO (version 2.0) with load balancing
Authors: Perezhogin Pavel , Chernov Ilya , Iakovlev Nikolay 
Published: February 2021

Abstract. In this paper, we present a parallel version of the finite-element model of the Arctic Ocean (FEMAO) configured for the White Sea and based on MPI technology. This model consists of two main parts: an ocean dynamics model and a surface ice dynamics model. These parts are very different in terms of the number of computations because the complexity of the ocean part depends on the bottom depth, while that of the sea-ice component does not. In the first step, we decided to locate both submodels on the same CPU cores with a common horizontal partition of the computational domain. The model domain is divided into small blocks, which are distributed over the CPU cores using Hilbert-curve balancing. Partitioning of the model domain is static (i.e., computed during the initialization stage). There are three baseline options: a single block per core, balancing of 2D computations, and balancing of 3D computations. After showing parallel acceleration for particular ocean and ice procedures, we construct the common partition, which minimizes joint imbalance in both submodels. Our novelty is using arrays shared by all blocks that belong to a CPU core instead of allocating separate arrays for each block, as is usually done. Computations on a CPU core are restricted by the masks of non-land grid nodes and block–core correspondence. This approach allows us to implement parallel computations into the model that are as simple as when the usual decomposition to squares is used, though with advances in load balancing. We provide parallel acceleration of up to 996 cores for the model with a resolution of 500×500×39 in the ocean component and 43 sea-ice scalars, and we carry out a detailed analysis of different partitions on the model runtime.
A model for interpreting the deformation mechanism of reservoir landslides in the Three Gorges Reservoir area, China
Authors: Zou Zongxing , Tang Huiming , Criss Robert E. , Hu Xinli , Xiong Chengren , Wu Qiong , Yuan Yi 
Published: February 2021

Abstract. Landslides whose slide surface is gentle near the toe and
relatively steep in the middle and rear part are common in the Three Gorges
Reservoir area, China. The mass that overlies the steep part of the slide
surface is termed the “driving section”, and that which overlies the gentle
part of the slide surface is termed the “resisting section”. A
driving–resisting model is presented to elucidate the deformation mechanism
of reservoir landslides of this type, as exemplified by Shuping landslide.
More than 13 years of field observations that include rainfall, reservoir
level, and deformation show that the displacement velocity of Shuping
landslide depends strongly on the reservoir level but only slightly on
rainfall. Seepage modeling shows that the landslide was destabilized
shortly after the reservoir was first impounded to 135 m, which initiated a
period of steady deformation from 2003 to 2006 that was driven by buoyancy
forces on the resisting section. Cyclical water level fluctuations in
subsequent years also affected slope stability, with annual “jumps” in
displacement coinciding with drawdown periods that produce outward seepage
forces. In contrast, the inward seepage force that results from rising
reservoir levels stabilizes the slope, as indicated by decreased
displacement velocity. Corrective transfer of earth mass from the driving
section to the resisting section successfully reduced the deformation of
Shuping landslide and is a feasible treatment for huge reservoir landslides
in similar geological settings.
Simulating historical flood events at the continental scale: observational validation of a large-scale hydrodynamic model
Authors: Wing Oliver E. J. , Smith Andrew M. , Marston Michael L. , Porter Jeremy R. , Amodeo Mike F. , Sampson Christopher C. , Bates Paul D. 
Published: February 2021

Abstract. Continental–global-scale flood hazard models simulate design floods, i.e. theoretical flood events of a given probability. Since they output phenomena unobservable in reality, large-scale models are typically compared to more localised engineering models to evidence their accuracy. However, both types of model may share the same biases and so not validly
illustrate their predictive skill. Here, we adapt an existing continental-scale design flood framework of the contiguous US to simulate historical flood events. A total of 35 discrete events are modelled and compared to observations of flood extent, water level, and inundated buildings. Model performance was highly variable, depending on the flood event chosen and validation data used. While all events were accurately replicated in terms of flood extent, some modelled water levels deviated substantially from those measured in the field. Despite this, the model generally replicated the observed flood events in the context of terrain data vertical accuracy, extreme discharge measurement uncertainties, and observational field data errors. This analysis highlights the continually improving fidelity of large-scale flood hazard models, yet also evidences the need for considerable advances in the accuracy of routinely collected field and high-river flow data in order to interrogate flood inundation models more comprehensively.
Properties of surface water masses in the Laptev and the East Siberian seas in summer 2018 from in situ and satellite data
Authors: Tarasenko Anastasiia , Supply Alexandre , Kusse-Tiuz Nikita , Ivanov Vladimir , Makhotin Mikhail , Tournadre Jean , Chapron Bertrand , Boutin Jacqueline , Kolodziejczyk Nicolas , Reverdin Gilles 
Published: February 2021

Abstract. Variability of surface water masses of the Laptev and the East Siberian seas in August–September 2018 is studied using in situ and satellite data. In situ data were collected during the ARKTIKA-2018 expedition and then complemented with satellite-derived sea surface temperature (SST), salinity (SSS), sea surface height, wind speed, and sea ice concentration. The estimation of SSS fields is challenging in high-latitude regions, and the precision of soil moisture and ocean salinity (SMOS) SSS retrieval is improved by applying a threshold on SSS weekly error. For the first time in this region, the validity of DMI (Danish Meteorological Institute) SST and SMOS SSS products is thoroughly studied using ARKTIKA-2018 expedition continuous thermosalinograph measurements and conductivity–temperature–depth (CTD) casts. They are found to be adequate to describe large surface gradients in this region. Surface gradients and mixing of the river and the sea water in the ice-free and ice-covered areas are described with a special attention to the marginal ice zone at a synoptic scale. We suggest that the freshwater is pushed northward, close to the marginal ice zone (MIZ) and under the sea ice, which is confirmed by the oxygen isotope analysis. The SST-SSS diagram based on satellite estimates shows the possibility of investigating the surface water mass transformation at a synoptic scale and reveals the presence of river water on the shelf of the East Siberian Sea. The Ekman transport is calculated to better understand the pathway of surface water displacement on the shelf and beyond.
Tropospheric eddy feedback to different stratospheric conditions in idealised baroclinic life cycles
Authors: Rupp Philip , Birner Thomas 
Published: February 2021

Abstract. A pronounced signature of stratosphere–troposphere coupling is a robust negative anomaly in the surface northern annular mode (NAM) following sudden stratospheric warming (SSW) events, consistent with an equatorward shift in the tropospheric jet. It has previously been pointed out that tropospheric synoptic-scale eddy feedbacks, mainly induced by anomalies in the lowermost extratropical stratosphere, play an important role in creating this surface NAM signal. Here, we use the basic set-up of idealised baroclinic life cycles to investigate the influence of stratospheric conditions on the behaviour of tropospheric synoptic-scale eddies. Particular attention is given to the enhancement of the tropospheric eddy response by surface friction and the sensitivity to wind anomalies in the lower stratosphere. We find systems that include a tropospheric jet only (modelling post-SSW conditions) to be characterised by an equatorward shift in the tropospheric jet in the final state of the life cycle, relative to systems that include a representation of the polar vortex (mimicking more undisturbed stratospheric wintertime conditions), consistent with the observed NAM response after SSWs. The corresponding relative surface NAM signal is increased if the system includes surface friction, presumably due to a direct coupling of the eddy field at tropopause level to the surface winds. We further show that the jet shift signal observed in our experiments is mainly caused by changes in the zonal wind structure of the lowermost stratosphere, while changes in the wind structure of the middle and upper stratosphere have almost no influence.
Set-point optimization in wind farms to mitigate effects of flow blockage induced by atmospheric gravity waves
Authors: Lanzilao Luca , Meyers Johan 
Published: February 2021

Abstract. Recently, it has been shown that flow blockage in large wind farms may lift up the top of the boundary layer, thereby triggering atmospheric gravity waves in the inversion layer and in the free atmosphere. These waves impose significant pressure gradients in the boundary layer, causing detrimental consequences in terms of a farm's efficiency. In the current study, we investigate the idea of controlling the wind farm in order to mitigate the efficiency drop due to wind-farm-induced gravity waves and blockage. The analysis is performed using a fast boundary layer model which divides the vertical structure of the atmosphere into three layers. The wind-farm drag force is applied over the whole wind-farm area in the lowest layer and is directly proportional to the wind-farm thrust set-point distribution. We implement an optimization model in order to derive the thrust-coefficient distribution, which maximizes the wind-farm energy extraction. We use a continuous adjoint method to efficiently compute gradients for the optimization algorithm, which is based on a quasi-Newton method. Power gains are evaluated with respect to a reference thrust-coefficient distribution based on the Betz–Joukowsky set point. We consider thrust coefficients that can change in space, as well as in time, i.e. considering time-periodic signals. However, in all our optimization results, we find that optimal thrust-coefficient distributions are steady; any time-periodic distribution is less optimal. The (steady) optimal thrust-coefficient distribution is inversely related to the vertical displacement of the boundary layer. Hence, it assumes a sinusoidal behaviour in the streamwise direction in subcritical flow conditions, whereas it becomes a U-shaped curve when the flow is supercritical. The sensitivity of the power gain to the atmospheric state is studied using the developed optimization tool for almost 2000 different atmospheric states. Overall, power gains above 4 % were observed for 77 % of the cases with peaks up to 14 % for weakly stratified atmospheres in critical flow regimes.