bluuebunny/crossref_metadata_2025 huggingface dataset:
Fluorescent biological aerosol particles over the central Pacific Ocean: covariation with ocean-surface biological activity indicators
Authors: Kawana Kaori , Matsumoto Kazuhiko , Taketani Fumikazu , Miyakawa Takuma , Kanaya Yugo
Published: February 2021

Abstract. Combining Waveband Integrated Bioaerosol Sensors and DNA staining techniques, online and offline shipboard observations of fluorescent aerosol particles in the atmosphere were carried out over the central Pacific Ocean during March 2019 to identify bioaerosols and determine their spatio-temporal distribution. To understand the origins of and processes associated with bioaerosols, we conducted correlation analyses of fluorescent particle number concentration, wind speed, and a variety of chemical and biological indicators, including concentrations of chlorophyll a, bacteria, marine organic gel particles such as Transparent Exopolymer Particles (TEPs) and Coomassie Stainable Particles (CSPs). Five-day backward trajectory analysis indicated that oceanic air masses were dominant between 6 and 18 March after which the influence of long-range transport from the continent of Asia was prominent. For the first period, we identified certain types of fluorescent particles as bioaerosols with marine origins, because their number concentrations were highly correlated with concentrations of TEPs and bacteria (R: 0.80–0.92) after considering the wind speed effect. For the second period, there was strong correlation between another type of fluorescent particles and CSPs irrespective of wind speed, implying that the fluorescent particles advected from land were mixed with those of marine origins. From the results of our correlation analysis, we developed equations to derive atmospheric bioaerosol number density in the marine atmosphere over the central Pacific Ocean from a combination of biogenic proxy quantities (chlorophyll a, TEPs and bacteria) and wind speed. We conclude that it is likely that TEPs were transported from the sea surface to the atmosphere together with bacteria to form fluorescent bioaerosols.
Measurement report: aerosol hygroscopic properties extended to 600 nm in the urban environment
Authors: Shen Chuanyang , Zhao Gang , Zhao Weilun , Tian Ping , Zhao Chunsheng
Published: February 2021

Abstract. Submicron particles larger than 300 nm dominate the
aerosol light extinction and mass concentration in the atmosphere. The water
uptake ability of this size range greatly influences the particle mass,
visibility degradation, and particle chemistry. However, most previous field
measurements on aerosol hygroscopicity are limited within 350 nm. In this
study, the size-resolved aerosol hygroscopic properties over an extended size
range (50–600 nm) at 85 % relative humidity were investigated in Beijing
winter from 27 November 2019 to 14 January 2020 using a humidity tandem
differential mobility analyzer (HTDMA) instrument. The corresponding aerosol
optical properties were also analyzed using the Mie scattering theory.
Results show that the averaged probability distribution of growth factor
(GF-PDF) is generally constituted by a more hygroscopic (MH) group and a
less hygroscopic (LH) group (including
hydrophobic). For the particles larger than 300 nm, there exists a large
fraction of LH group particles, resulting in an unexpected low
hygroscopicity. During the development of pollution, when particles are
gradually aged and accumulated, the bulk hygroscopicity above 300 nm is
enhanced significantly by the growth and expansion of the MH group. This
result is supported by previous chemical composition analysis, and we give
more direct and detailed evidence from the growth factor and mixing-state
aspects. Our calculations indicate that the optical contribution of
particles larger than 300 nm constitutes about two-thirds of the total aerosol
extinction. The large hygroscopic variation in aerosols above 300 nm will
influence the light degradation comparably with the increase in aerosol
loading in low-visibility haze events. Our studies highlight that the
hygroscopic properties above 300 nm are complex and vary greatly with
different pollution stages. Therefore more field measurements and
investigations need to be done in the future.
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.
Neapolitan volcanic area Tide Gauge Network (Southern Italy): Ground Displacements and Sea-Level Oscillations
Authors: Tammaro Umberto , Obrizzo Francesco , Riccardi Umberto , La Rocca Adriano , Pinto Salvatore , Brandi Giuseppe , Vertechi Enrico , Capuano Paolo
Published: February 2021

Abstract. In this study, we investigate the oscillations of relative sea level through the analysis of tide gauge records about 10-year long collected in the Gulfs of Pozzuoli and Napoli (Southern Italy). The main goal of this study is to provide a suitable resolution model of the sea tides including low frequency (seiches), tidal bands and non-linear tides. The spectral analyses of the tide gauge records lead us to identify a number of seiche periods some of them already known from the literature and some other unknown. Furthermore, we target a non-conventional purpose of the tidal analysis, namely extracting from the tide gauge records the volcano-tectonic signal (vertical ground displacement) in the resurgent Campi Flegrei caldera. We suggest a method to filter out the volcano-tectonic signal (bradyseism) from the tide gauge records by deconvolving it from two records, one collected in the active volcanic area (Pozzuoli) and the other one collected in a tectonically stable station (Napoli), located beyond the caldera rim. Finally, we retrieve the relative mean sea level change in the Gulf of Naples and compare it with the trend found in five tide gauges spread along the Italian coast.
Smartphone pressure data: quality control and impact on atmospheric analysis
Authors: Li Rumeng , Zhang Qinghong , Sun Juanzhen , Chen Yun , Ding Lili , Wang Tian
Published: February 2021

Abstract. Smartphones are increasingly being equipped with
atmospheric measurement sensors providing huge auxiliary resources for
global observations. Although China has the highest number of cell phone
users, there is little research on whether these measurements provide useful
information for atmospheric research. Here, for the first time, we present
the global spatial and temporal variation in smartphone pressure
measurements collected in 2016 from the Moji Weather app. The data have an
irregular spatiotemporal distribution with a high density in urban areas, a
maximum in summer and two daily peaks corresponding to rush hours. With the
dense dataset, we have developed a new bias-correction method based on a
machine-learning approach without requiring users' personal information,
which is shown to reduce the bias of pressure observation substantially. The
potential application of the high-density smartphone data in cities is
illustrated by a case study of a hailstorm that occurred in Beijing in which
high-resolution gridded pressure analysis is produced. It is shown that the
dense smartphone pressure analysis during the storm can provide detailed
information about fine-scale convective structure and decrease errors from
an analysis based on surface meteorological-station measurements. This study
demonstrates the potential value of smartphone data and suggests some future
research needs for their use in atmospheric science.
Real-time measurement of radionuclide concentrations and its impact on inverse modeling of 106Ru release in the fall of 2017
Authors: Tichý Ondřej , Hýža Miroslav , Evangeliou Nikolaos , Šmídl Václav
Published: February 2021

Abstract. Low concentrations of 106Ru were detected across Europe
at the turn of September and October 2017. The origin of 106Ru
has still not been confirmed; however, current studies agree that
the release occurred probably near Mayak in the southern Urals. The
source reconstructions are mostly based on an analysis of concentration
measurements coupled with an atmospheric transport model. Since reasonable
temporal resolution of concentration measurements is crucial for proper
source term reconstruction, the standard 1-week sampling interval
could be limiting. In this paper, we present an investigation of the
usability of the newly developed AMARA (Autonomous Monitor of Atmospheric Radioactive Aerosol) and CEGAM (carousel gamma spectrometry) real-time monitoring
systems, which are based on the gamma-ray counting of aerosol filters and allow for determining the moment when 106Ru arrived at the monitoring site within approx. 1 h and detecting activity concentrations as low as several mBq m−3 in 4 h intervals.
These high-resolution data were used for inverse modeling of the 106Ru
release. We perform backward runs of the Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) atmospheric transport
model driven with meteorological data from the Global Forecast System
(GFS), and we construct a source–receptor sensitivity (SRS) matrix
for each grid cell of our domain. Then, we use our least squares with
adaptive prior covariance (LS-APC) method to estimate possible locations
of the release and the source term of the release. With Czech monitoring
data, the use of concentration measurements from the standard regime
and from the real-time regime is compared, and a better source reconstruction
for the real-time data is demonstrated in the sense of the location
of the source and also the temporal resolution of the source. The
estimated release location, Mayak, and the total estimated source
term, 237±107 TBq, are in agreement with previous studies. Finally,
the results based on the Czech monitoring data are validated with
the IAEA-reported (International Atomic Energy Agency) dataset with a much better spatial resolution, and
the agreement between the IAEA dataset and our reconstruction is demonstrated. In addition, we validated our findings also using the FLEXPART (FLEXible PARTicle dispersion) model coupled with meteorological analyses from the European Centre for Medium-Range Weather Forecasts (ECMWF).
On-line SPME derivatization for the sensitive determination of
multi-oxygenated volatile compounds in air
Authors: Borrás Esther , Tortajada-Genaro Luis A. , Ródenas Milagros , Vera Teresa , Speak Thomas , Seakins Paul , Shaw Marvin D. , Lewis Alastair C. , Muñoz Amalia
Published: February 2021

Abstract. Multi-oxygenated volatile organic compounds are important markers of air pollution and precursors of ozone and secondary aerosols in both polluted and remote environments. Herein, their accurate determination was enhanced. The approach was based on an automated system for active sampling and on-fiber derivatization coupled with GC-MS technique. The method capability was determined for different compound families, such as aldehydes, ketones, α-dicarbonyls, hydroxy-aldehydes, hydroxy-ketones and, carboxylic acids. A good accuracy (
Radar imaging with EISCAT 3D
Authors: Stamm Johann , Vierinen Juha , Urco Juan M. , Gustavsson Björn , Chau Jorge L.
Published: February 2021

Abstract. A new incoherent scatter radar called EISCAT 3D is being constructed in northern Scandinavia. It will have the capability to produce volumetric images of ionospheric plasma parameters using aperture synthesis radar imaging. This study uses the current design of EISCAT 3D to explore the theoretical radar imaging performance when imaging electron density in the E region and compares numerical techniques that could be used in practice. Of all imaging algorithms surveyed, the singular value decomposition with regularization gave the best results and was also found to be the most computationally efficient. The estimated imaging performance indicates that the radar will be capable of detecting features down to approximately 90×90 m at a height of 100 km, which corresponds to a ≈0.05∘ angular resolution. The temporal resolution is dependent on the signal-to-noise ratio and range resolution. The signal-to-noise ratio calculations indicate that high-resolution imaging of auroral precipitation is feasible. For example, with a range resolution of 1500 m, a time resolution of 10 s, and an electron density of 2×1011m-3, the correlation function estimates for radar scatter from the E region can be measured with an uncertainty of 5 %. At a time resolution of 10 s and an image resolution of 90×90 m, the relative estimation error standard deviation of the image intensity is 10 %. Dividing the transmitting array into multiple independent transmitters to obtain a multiple-input–multiple-output (MIMO) interferometer system is also studied, and this technique is found to increase imaging performance through improved visibility coverage. Although this reduces the signal-to-noise ratio, MIMO has successfully been applied to image strong radar echoes as meteors and polar mesospheric summer echoes. Use of the MIMO technique for incoherent scatter radars (ISRs) should be investigated further.
Predicting evapotranspiration from drone-based thermography – a method comparison in a tropical oil palm plantation
Authors: Ellsäßer Florian , Stiegler Christian , Röll Alexander , June Tania ,   Hendrayanto, Knohl Alexander , Hölscher Dirk
Published: February 2021

Abstract. For the assessment of evapotranspiration, near-surface airborne thermography
offers new opportunities for studies with high numbers of spatial replicates
and in a fine spatial resolution. We tested drone-based thermography and the
subsequent application of the DATTUTDUT energy balance model using the widely accepted eddy covariance technique as a reference
method. The study site was a mature oil palm plantation in lowland Sumatra,
Indonesia. For the 61 flight missions, latent heat flux estimates of the
DATTUTDUT (Deriving Atmosphere Turbulent Transport Useful To Dummies Using
Temperature) model with measured net radiation agreed well with eddy covariance
measurements (r2 = 0.85; MAE = 47; RMSE = 60) across
variable weather conditions and times of day. Confidence intervals for slope and
intercept of a model II Deming regression suggest no difference between
drone-based and eddy covariance methods, thus indicating interchangeability.
The DATTUTDUT model is sensitive to the configuration of the net radiation assessment. Overall, we
conclude that drone-based thermography with energy balance modeling is a
reliable method complementing available methods for evapotranspiration
studies. It offers promising, additional opportunities for fine grain and
spatially explicit studies.
Toward a global calibration for quantifying past oxygenation in
oxygen minimum zones using benthic Foraminifera
Authors: Tetard Martin , Licari Laetitia , Tachikawa Kazuyo , Ovsepyan Ekaterina , Beaufort Luc
Published: February 2021

Abstract. Oxygen Minimum Zones (OMZs) are oceanic areas largely depleted in dissolved oxygen, nowadays considered in expansion in the face of global warming. Their ecological and economic consequences are being debated. The investigation of past OMZ conditions allows us to better understand biological and physical mechanisms responsible for their variability with regards to climate change, carbon pump and carbonate system. To investigate the relationship between OMZ expansion and global climate changes during the late Quaternary, quantitative oxygen reconstructions are needed, but are still in their early development. Here, past bottom water oxygenation (BWO) was quantitatively assessed through a new, fast, semi-automated, and taxonfree morphometric analysis of benthic foraminiferal tests, developed and calibrated using Eastern North Pacific (ENP) and the Eastern South Pacific (ESP) OMZs samples. This new approach is based on an average size and circularity index for each sample. This method, as well as two already published micropalaeontological approaches based on benthic foraminiferal assemblages variability and porosity investigation of a single species, were here calibrated based on availability of new data from 23 core tops recovered along an oxygen gradient (from 0.03 to 1.79 mL.L−1) from the ENP, ESP, AS (Arabian Sea) and WNP (Western North Pacific, including its marginal seas) OMZs. Global calibrated transfer functions are thus herein proposed for each of these methods. These micropalaeontological reconstruction approaches were then applied on a paleorecord from the ENP OMZ to examine the consistency and limits of these methods, as well as the relative influence of bottom and pore waters on these micropalaeontological tools. Both the assemblages and morphometric approaches (that is also ultimately based on the ecological response of the complete assemblage and faunal succession according to BWO) gave similar and consistent past BWO reconstructions, while the porosity approach (based on a single species and its unique response to a mixed signal of bottom and pore waters) shown ambiguous estimations.
CO2 emissions from peat-draining rivers regulated by water pH
Authors: Klemme Alexandra , Rixen Tim , Müller-Dum Denise , Müller Moritz , Notholt Justus , Warneke Thorsten
Published: February 2021

Abstract. Southeast Asian peatlands represent a globally significant carbon store that is destabilized by deforestation and the transformation into plantations, causing high carbon dioxide (CO2) emissions from peat soils and increased leaching rates of peat carbon into rivers. While global model studies assumed that CO2 emissions from peat-draining rivers would be high, estimates based on field data suggest they are only moderate. In this study we offer an explanation for this phenomenon and show that carbon decomposition is hampered by the low pH in peat-draining rivers, which limits CO2 production in and emissions from these rivers. We find an exponential pH limitation that shows good agreement with laboratory measurements from high latitude peat soils. Additionally, our results suggest that enhanced input of carbonate minerals increase CO2 emissions from peat-draining rivers by counteracting the pH limitation. As such inputs of carbonate minerals occur due to human activities like deforestation of river catchments, liming in plantations and enhanced weathering projects, our study points out an important feedback mechanism of those practices.
Evolution of mean ocean temperature in Marine Isotope Stages 5-4
Authors: Shackleton Sarah , Menking James A. , Brook Edward , Buizert Christo , Dyonisius Michael N. , Petrenko Vasilii V. , Baggenstos Daniel , Severinghaus Jeffrey P.
Published: February 2021

Abstract. Deglaciations are characterized by relatively fast and near-synchronous changes in ice sheet volume, ocean temperature, and atmospheric greenhouse gas concentrations, but glacial inceptions occur more gradually. Understanding the evolution of ice sheet, ocean, and atmospheric conditions from interglacial to glacial maximum provides important insight into the interplay of these components of our climate system. Using noble gas measurements in ancient ice samples, we reconstruct mean ocean temperature (MOT) from 74 to 59.5 ka BP, covering the Marine Isotope Stage (MIS) 5-4 boundary, MIS 4, and part of the MIS 4-3 transition. Comparing this MOT reconstruction to previously published MOT reconstructions from the last glacial cycle, we find that the majority of interglacial-glacial ocean cooling occurred across MIS 5, and MOT reached full glacial levels by MIS 4 (−2.7 ± 0.3 °C relative to the Holocene). Comparing MOT to contemporaneous records of CO2 and benthic 𝛿18O, we find that ocean cooling and the solubility pump can explain most of the CO2 drawdown and increase in 𝛿18O across MIS 5. The timing of ocean warming and cooling in our record indicates that millennial scale climate variability plays a crucial role in setting mean ocean temperature during this interval, as seen during other periods, such as the last deglaciation.
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.
A new view of heat wave dynamics and predictability over the eastern Mediterranean
Authors: Hochman Assaf , Scher Sebastian , Quinting Julian , Pinto Joaquim G. , Messori Gabriele
Published: February 2021

Abstract. Skillful forecasts of extreme weather events have a major
socioeconomic relevance. Here, we compare two complementary approaches to
diagnose the predictability of extreme weather: recent developments in
dynamical systems theory and numerical ensemble weather forecasts. The
former allows us to define atmospheric configurations in terms of their
persistence and local dimension, which provides information on how the atmosphere evolves
to and from a given state of interest. These metrics may be used as proxies
for the intrinsic predictability of the atmosphere, which only depends on
the atmosphere's properties. Ensemble weather forecasts provide information on the
practical predictability of the atmosphere, which partly depends on the
performance of the numerical model used. We focus on heat waves affecting
the eastern Mediterranean. These are identified using the climatic stress
index (CSI), which was explicitly developed for the summer weather
conditions in this region and differentiates between heat waves (upper
decile) and cool days (lower decile). Significant differences are found
between the two groups from both the dynamical systems and the numerical
weather prediction perspectives. Specifically, heat waves show relatively
stable flow characteristics (high intrinsic predictability) but
comparatively low practical predictability (large model spread and error). For
500 hPa geopotential height fields, the intrinsic predictability of heat waves is
lowest at the event's onset and decay. We relate these results to the
physical processes governing eastern Mediterranean summer heat waves:
adiabatic descent of the air parcels over the region and the geographical
origin of the air parcels over land prior to the onset of a heat wave. A
detailed analysis of the mid-August 2010 record-breaking heat wave provides
further insights into the range of different regional atmospheric
configurations conducive to heat waves. We conclude that the dynamical
systems approach can be a useful complement to conventional numerical
forecasts for understanding the dynamics and predictability of eastern
Mediterranean heat waves.
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).
A restructured and updated global soil respiration database (SRDB-V5)
Authors: Jian Jinshi , Vargas Rodrigo , Anderson-Teixeira Kristina , Stell Emma , Herrmann Valentine , Horn Mercedes , Kholod Nazar , Manzon Jason , Marchesi Rebecca , Paredes Darlin , Bond-Lamberty Ben
Published: February 2021

Abstract. Field-measured soil respiration (RS, the soil-to-atmosphere CO2 flux) observations were compiled into a global soil
respiration database (SRDB) a decade ago, a resource that has been widely used by the biogeochemistry community to advance our understanding of
RS dynamics. Novel carbon cycle science questions require updated and augmented global information with better interoperability among
datasets. Here, we restructured and updated the global RS database to version SRDB-V5. The updated version has all previous fields
revised for consistency and simplicity, and it has several new fields to include ancillary information (e.g., RS measurement time,
collar insertion depth, collar area). The new SRDB-V5 includes published papers through 2017 (800 independent studies), where total observations
increased from 6633 in SRDB-V4 to 10 366 in SRDB-V5. The SRDB-V5 features more RS data published in the Russian and Chinese scientific
literature and has an improved global spatio-temporal coverage and improved global climate space representation. We also restructured the database so
that it has stronger interoperability with other datasets related to carbon cycle science. For instance, linking SRDB-V5 with an hourly timescale
global soil respiration database (HGRsD) and a community database for continuous soil respiration (COSORE) enables researchers to explore new questions. The updated SRDB-V5 aims to be a data
framework for the scientific community to share seasonal to annual field RS measurements, and it provides opportunities for the
biogeochemistry community to better understand the spatial and temporal variability in RS, its components, and the overall carbon
cycle. The database can be downloaded at https://github.com/bpbond/srdb and will be made available in the Oak Ridge National Laboratory's Distributed Active Archive Center (ORNL DAAC). All data and code to reproduce the results in this study can be found at https://doi.org/10.5281/zenodo.3876443 (Jian and Bond-Lamberty, 2020).
Observations from the NOAA P-3 aircraft during ATOMIC
Authors: Pincus Robert , Fairall Chris W. , Bailey Adriana , Chen Haonan , Chuang Patrick Y. , de Boer Gijs , Feingold Graham , Henze Dean , Kalen Quinn T. , Kazil Jan , Leandro Mason , Lundry Ashley , Moran Ken , Naeher Dana A. , Noone David , Patel Akshar J. , Pezoa Sergio , PopStefanija Ivan , Thompson Elizabeth J. , Warnecke James , Zuidema Paquita
Published: February 2021

Abstract. This paper describes observations obtained during the Atlantic Tradewind Ocean-Atmosphere Mesoscale Interaction Campaign (ATOMIC) by the US National Oceanic and Atmospheric Administration's (NOAA) Lockheed WP-3D Orion research aircraft based on the island of Barbados during the period Jan 17–Feb 11 2020. The aircraft obtained 95 hours of observations over eleven flights, many of which were coordinated with the NOAA research ship R/V Ronald H. Brown and autonomous platforms deployed from the ship. Each flight contained a mixture of sampling strategies including: high-altitude circles with frequent dropsonde deployment to characterize the large-scale environment; slow descents and ascents to measure the distribution of water vapor and its isotopic composition; stacked legs aimed at sampling the microphysical and thermodynamic state of the boundary layer; and offset straight flight legs for observing clouds and the ocean surface with remote sensing instruments and the thermal structure of the ocean with in situ sensors dropped from the plane. The characteristics of the it in situ observations, expendable devices, and remote sensing instrumentation are described, as is the processing used in deriving estimates of physical quantities. Data archived at the National Center for Environmental Information include flight-level data such as aircraft navigation and basic thermodynamic information (https://doi.org/10.25921/7jf5-wv54); high-accuracy measurements of water vapor concentration from an isotope analyzer (https://doi.org/10.25921/c5yx-7w29); profiles of sea water temperature made with Airborne eXpendable BathyThermographs (AXBTs, https://doi.org/10.25921/pe39-sx75); profiles of radar reflectivity, Doppler velocity, and spectrum width from a nadir-looking W-band (94 GHz) radar (https://doi.org/10.25921/n1hc-dc30); estimates of cloud presence, the cloud top location, and the cloud-top radar reflectivity and temperature, along with estimates of 10-m wind speed obtained from remote sensing instruments operating in the microwave and thermal infrared spectral regions (https://doi.org/10.25921/x9q5-9745); and ocean surface wave characteristics from a Wide Swath Radar Altimeter (https://doi.org/10.25921/qm06-qx04). Data are provided as netCDF files following Climate and Forecast conventions.
Autonomous-underwater-vehicle-based marine multicomponent self-potential method: observation scheme and navigational correction
Authors: Zhu Zhongmin , Shen Jinsong , Tao Chunhui , Deng Xianming , Wu Tao , Nie Zuofu , Wang Wenyi , Su Zhaoyang
Published: February 2021

Abstract. Marine self-potential (SP) investigation is an effective method to study
deep-sea hydrothermal vents and seafloor sulfide deposits. At present, one
of the commonly used marine self-potential systems is a towed array of
electrodes. Large noises are recorded when great changes in electrode
distance and array attitude occur due to the complex seafloor topography. In
this paper, a new multicomponent electrical field observation system based on an
autonomous underwater vehicle (AUV) was introduced for the
measurement of seafloor self-potential signals. The system was tested in a
lake, and the multicomponent self-potential data were collected from there. Observed
data involve the navigational information of the AUV, which could be corrected
using a rotation transform. After navigational correction, measured data can
recover the location of the artificial source using self-potential
tomography. The experimental results showed that the new SP system can be
applied to marine SP observations, providing an efficient and low-noise SP
acquisition method for marine resources and environmental investigations.
Development of WRF/CUACE v1.0 model and its preliminary application in simulating air quality in China
Authors: Zhang Lei , Gong Sunling , Zhao Tianliang , Zhou Chunhong , Wang Yuesi , Li Jiawei , Ji Dongsheng , He Jianjun , Liu Hongli , Gui Ke , Guo Xiaomei , Gao Jinhui , Shan Yunpeng , Wang Hong , Wang Yaqiang , Che Huizheng , Zhang Xiaoye
Published: February 2021

Abstract. The development of chemical transport models with advanced physics
and chemical schemes could improve air-quality forecasts. In this study, the
China Meteorological Administration Unified Atmospheric Chemistry
Environment (CUACE) model, a comprehensive chemistry module incorporating
gaseous chemistry and a size-segregated multicomponent aerosol algorithm,
was coupled to the Weather Research and Forecasting (WRF) framework with chemistry (WRF-Chem)
using an interface procedure to build the WRF/CUACE v1.0 model. The latest
version of CUACE includes an updated aerosol dry deposition scheme and the
introduction of heterogeneous chemical reactions on aerosol surfaces. We
evaluated the WRF/CUACE v1.0 model by simulating PM2.5, O3,
NO2, and SO2 concentrations for January, April, July, and October
(representing winter, spring, summer and autumn, respectively) in 2013,
2015, and 2017 and comparing them with ground-based observations. Secondary
inorganic aerosol simulations for the North China Plain (NCP), Yangtze River
Delta (YRD), and Sichuan Basin (SCB) were also evaluated. The model captured well
the variations of PM2.5, O3, and NO2 concentrations
in all seasons in eastern China. However, it is difficult to accurately
reproduce the variations of air pollutants over SCB, due to
its deep basin terrain. The simulations of SO2 were generally
reasonable in the NCP and YRD with the bias at −15.5 % and 24.55 %,
respectively, while they were poor in the Pearl River Delta (PRD) and SCB. The sulfate and nitrate
simulations were substantially improved by introducing heterogeneous chemical
reactions into the CUACE model (e.g., change in bias from −95.0 % to
4.1 % for sulfate and from 124.1 % to 96.0 % for nitrate in the NCP).
Additionally, The WRF/CUACE v1.0 model was revealed with better performance
in simulating chemical species relative to the coupled Fifth-Generation Penn
State/NCAR Mesoscale Model (MM5) and CUACE model. The development of the
WRF/CUACE v1.0 model represents an important step towards improving
air-quality modeling and forecasts in China.
The Meridionally Averaged Model of Eastern Boundary Upwelling Systems (MAMEBUSv1.0)
Authors: Moscoso Jordyn E. , Stewart Andrew L. , Bianchi Daniele , McWilliams James C.
Published: February 2021

Abstract. Eastern boundary upwelling systems (EBUSs) are physically and biologically active regions of the ocean with substantial impacts on ocean biogeochemistry, ecology, and global fish catch. Previous studies have used models of varying complexity to study EBUS dynamics, ranging from minimal two-dimensional (2-D) models to comprehensive regional and global models. An advantage of 2-D models is that they are more computationally efficient and easier to interpret than comprehensive regional models, but their key drawback is the lack of explicit representations of important three-dimensional processes that control biology in upwelling systems. These processes include eddy quenching of nutrients and meridional transport of nutrients and heat. The authors present the Meridionally Averaged Model of Eastern Boundary Upwelling Systems (MAMEBUS) that aims at combining the benefits of 2-D and 3-D approaches to modeling EBUSs by parameterizing the key 3-D processes in a 2-D framework. MAMEBUS couples the primitive equations for the physical state of the ocean with a nutrient–phytoplankton–zooplankton–detritus model of the ecosystem, solved in terrain-following coordinates. This article defines the equations that describe the tracer, momentum, and biological evolution, along with physical parameterizations of eddy advection, isopycnal mixing, and boundary layer mixing. It describes the details of the numerical schemes and their implementation in the model code, and provides a reference solution validated against observations from the California Current. The goal of MAMEBUS is to facilitate future studies to efficiently explore the wide space of physical and biogeochemical parameters that control the zonal variations in EBUSs.
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.