In the central Arctic Ocean the formation of clouds and their properties are sensitive to the availability of cloud condensation nuclei (CCN). The vapors responsible for new particle formation (NPF), ...potentially leading to CCN, have remained unidentified since the first aerosol measurements in 1991. Here, we report that all the observed NPF events from the Arctic Ocean 2018 expedition are driven by iodic acid with little contribution from sulfuric acid. Iodic acid largely explains the growth of ultrafine particles (UFP) in most events. The iodic acid concentration increases significantly from summer towards autumn, possibly linked to the ocean freeze-up and a seasonal rise in ozone. This leads to a one order of magnitude higher UFP concentration in autumn. Measurements of cloud residuals suggest that particles smaller than 30 nm in diameter can activate as CCN. Therefore, iodine NPF has the potential to influence cloud properties over the Arctic Ocean.
An infodemic is an overabundance of information-some accurate and some not-that occurs during an epidemic. In a similar manner to an epidemic, it spreads between humans via digital and physical ...information systems. It makes it hard for people to find trustworthy sources and reliable guidance when they need it.
A World Health Organization (WHO) technical consultation on responding to the infodemic related to the coronavirus disease (COVID-19) pandemic was held, entirely online, to crowdsource suggested actions for a framework for infodemic management.
A group of policy makers, public health professionals, researchers, students, and other concerned stakeholders was joined by representatives of the media, social media platforms, various private sector organizations, and civil society to suggest and discuss actions for all parts of society, and multiple related professional and scientific disciplines, methods, and technologies. A total of 594 ideas for actions were crowdsourced online during the discussions and consolidated into suggestions for an infodemic management framework.
The analysis team distilled the suggestions into a set of 50 proposed actions for a framework for managing infodemics in health emergencies. The consultation revealed six policy implications to consider. First, interventions and messages must be based on science and evidence, and must reach citizens and enable them to make informed decisions on how to protect themselves and their communities in a health emergency. Second, knowledge should be translated into actionable behavior-change messages, presented in ways that are understood by and accessible to all individuals in all parts of all societies. Third, governments should reach out to key communities to ensure their concerns and information needs are understood, tailoring advice and messages to address the audiences they represent. Fourth, to strengthen the analysis and amplification of information impact, strategic partnerships should be formed across all sectors, including but not limited to the social media and technology sectors, academia, and civil society. Fifth, health authorities should ensure that these actions are informed by reliable information that helps them understand the circulating narratives and changes in the flow of information, questions, and misinformation in communities. Sixth, following experiences to date in responding to the COVID-19 infodemic and the lessons from other disease outbreaks, infodemic management approaches should be further developed to support preparedness and response, and to inform risk mitigation, and be enhanced through data science and sociobehavioral and other research.
The first version of this framework proposes five action areas in which WHO Member States and actors within society can apply, according to their mandate, an infodemic management approach adapted to national contexts and practices. Responses to the COVID-19 pandemic and the related infodemic require swift, regular, systematic, and coordinated action from multiple sectors of society and government. It remains crucial that we promote trusted information and fight misinformation, thereby helping save lives.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, UILJ, UKNU, UL, UM, UPUK
Direct observations during intense warm‐air advection over the East Siberian Sea reveal a period of rapid sea‐ice melt. A semistationary, high‐pressure system north of the Bering Strait forced ...northward advection of warm, moist air from the continent. Air‐mass transformation over melting sea ice formed a strong, surface‐based temperature inversion in which dense fog formed. This induced a positive net longwave radiation at the surface while reducing net solar radiation only marginally; the inversion also resulted in downward turbulent heat flux. The sum of these processes enhanced the surface energy flux by an average of ~15 W m−2 for a week. Satellite images before and after the episode show sea‐ice concentrations decreasing from > 90% to ~50% over a large area affected by the air‐mass transformation. We argue that this rapid melt was triggered by the increased heat flux from the atmosphere due to the warm‐air advection.
Key Points
The importance of both large‐scale dynamics and local feedback for sea‐ice melt
The location of extra melt near the ice edge, due to the air‐mass transformation
The role of clouds, longwave radiation and turbulent heat flux for sea‐ice melt
Two consecutive cruises in the Weddell Sea, Antarctica, in winter 2013 provided the first direct observations of sea salt aerosol (SSA) production from blowing snow above sea ice, thereby validating ...a model hypothesis to account for winter time SSA maxima in the Antarctic. Blowing or drifting snow often leads to increases in SSA during and after storms. For the first time it is shown that snow on sea ice is depleted in sulfate relative to sodium with respect to seawater. Similar depletion in bulk aerosol sized ∼0.3–6 µm above sea ice provided the evidence that most sea salt originated from snow on sea ice and not the open ocean or leads, e.g. >90 % during the 8 June to 12 August 2013 period. A temporally very close association of snow and aerosol particle dynamics together with the long distance to the nearest open ocean further supports SSA originating from a local source. A mass budget estimate shows that snow on sea ice contains even at low salinity (<0.1 psu) more than enough sea salt to account for observed increases in atmospheric SSA during storms if released by sublimation. Furthermore, snow on sea ice and blowing snow showed no or small depletion of bromide relative to sodium with respect to seawater, whereas aerosol was enriched at 2 m and depleted at 29 m, suggesting that significant bromine loss takes place in the aerosol phase further aloft and that SSA from blowing snow is a source of atmospheric reactive bromine, an important ozone sink, even during winter darkness. The relative increase in aerosol concentrations with wind speed was much larger above sea ice than above the open ocean, highlighting the importance of a sea ice source in winter and early spring for the aerosol burden above sea ice. Comparison of absolute increases in aerosol concentrations during storms suggests that to a first order corresponding aerosol fluxes above sea ice can rival those above the open ocean depending on particle size. Evaluation of the current model for SSA production from blowing snow showed that the parameterizations used can generally be applied to snow on sea ice. Snow salinity, a sensitive model parameter, depends to a first order on snowpack depth and therefore was higher above first-year sea ice (FYI) than above multi-year sea ice (MYI). Shifts in the ratio of FYI and MYI over time are therefore expected to change the seasonal SSA source flux and contribute to the variability of SSA in ice cores, which represents both an opportunity and a challenge for the quantitative interpretation of sea salt in ice cores as a proxy for sea ice.
Numerical prediction of aerosol particle properties has become an important activity at many research and operational weather centers. This development is due to growing interest from a diverse set ...of stakeholders, such as air quality regulatory bodies, aviation and military authorities, solar energy plant managers, climate services providers, and health professionals. Owing to the complexity of atmospheric aerosol processes and their sensitivity to the underlying meteorological conditions, the prediction of aerosol particle concentrations and properties in the numerical weather prediction (NWP) framework faces a number of challenges. The modeling of numerous aerosol-related parameters increases computational expense. Errors in aerosol prediction concern all processes involved in the aerosol life cycle including (a) errors on the source terms (for both anthropogenic and natural emissions), (b) errors directly dependent on the meteorology (e.g., mixing, transport, scavenging by precipitation), and (c) errors related to aerosol chemistry (e.g., nucleation, gas–aerosol partitioning, chemical transformation and growth, hygroscopicity). Finally, there are fundamental uncertainties and significant processing overhead in the diverse observations used for verification and assimilation within these systems. Indeed, a significant component of aerosol forecast development consists in streamlining aerosol-related observations and reducing the most important errors through model development and data assimilation. Aerosol particle observations from satellite- and ground-based platforms have been crucial to guide model development of the recent years and have been made more readily available for model evaluation and assimilation. However, for the sustainability of the aerosol particle prediction activities around the globe, it is crucial that quality aerosol observations continue to be made available from different platforms (space, near surface, and aircraft) and freely shared. This paper reviews current requirements for aerosol observations in the context of the operational activities carried out at various global and regional centers. While some of the requirements are equally applicable to aerosol–climate, the focus here is on global operational prediction of aerosol properties such as mass concentrations and optical parameters. It is also recognized that the term “requirements” is loosely used here given the diversity in global aerosol observing systems and that utilized data are typically not from operational sources. Most operational models are based on bulk schemes that do not predict the size distribution of the aerosol particles. Others are based on a mix of “bin” and bulk schemes with limited capability of simulating the size information. However the next generation of aerosol operational models will output both mass and number density concentration to provide a more complete description of the aerosol population. A brief overview of the state of the art is provided with an introduction on the importance of aerosol prediction activities. The criteria on which the requirements for aerosol observations are based are also outlined. Assimilation and evaluation aspects are discussed from the perspective of the user requirements.
During the Arctic Clouds in Summer Experiment (ACSE) in summer 2014 a weeklong period of warm-air advection over melting sea ice, with the formation of a strong surface temperature inversion and ...dense fog, was observed. Based on an analysis of the surface energy budget, we formulated the hypothesis that, because of the airmass transformation, additional surface heating occurs during warm-air intrusions in a zone near the ice edge. To test this hypothesis, we explore all cases with surface inversions occurring during ACSE and then characterize the inversions in detail. We find that they always occur with advection from the south and are associated with subsidence. Analyzing only inversion cases over sea ice, we find two categories: one with increasing moisture in the inversion and one with constant or decreasing moisture with height. During surface inversions with increasing moisture with height, an extra 10–25 W m−2 of surface heating was observed, compared to cases without surface inversions; the surface turbulent heat flux was the largest single term. Cases with less moisture in the inversion were often cloud free and the extra solar radiation plus the turbulent surface heat flux caused by the inversion was roughly balanced by the loss of net longwave radiation.
Celotno besedilo
Dostopno za:
BFBNIB, DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Surface turbulent exchanges play a key role on sea ice dynamics, on ocean and sea ice heat budgets and on the polar atmosphere. Uncertainties in parameterizations of surface turbulent fluxes are ...mostly held by the transfer coefficients and estimates of those transfer coefficients from field data are required for parameterization development. Measurement errors propagate through the computation of transfer coefficients and contribute to its total error together with the uncertainties in the empirical stability functions used to correct for stability effects. Here we propose a methodology to assess their contributions individually to each coefficient estimate as well as the total drag coefficient uncertainty and we apply this methodology on the example of the SHEBA campaign. We conclude that for most common drag coefficient values (between
1.0
×
10
-
3
and
2.5
×
10
-
3
), the relative total uncertainty ranges from 25 and 50
%
. For stable or unstable conditions with a stability parameter
|
ζ
|
>
1
on average, the total uncertainty in the neutral drag coefficient exceeds the neutral drag coefficient value itself, while for
|
ζ
|
<
1
the total uncertainty is around 25
%
of the drag coefficient. For closer-to-neutral conditions, this uncertainty is dominated by measurement uncertainties in surface turbulent momentum fluxes which should therefore be the target of efforts in uncertainty reduction. We also propose an objective data-screening procedure for field data, which consists of retaining data for which the relative error on neutral drag coefficient does not exceed a given threshold. This method, in addition to the commonly used flux quality control procedure, allows for a reduction of the drag coefficient dispersion compared to other data-screening methods, which we take as an indication of better dataset quality.
A method of estimating dissipation rates from a vertically pointing Doppler lidar with high temporal and spatial resolution has been evaluated by comparison with independent measurements derived from ...a balloon-borne sonic anemometer. This method utilizes the variance of the mean Doppler velocity from a number of sequential samples and requires an estimate of the horizontal wind speed. The noise contribution to the variance can be estimated from the observed signal-to-noise ratio and removed where appropriate. The relative size of the noise variance to the observed variance provides a measure of the confidence in the retrieval. Comparison with in situ dissipation rates derived from the balloon-borne sonic anemometer reveal that this particular Doppler lidar is capable of retrieving dissipation rates over a range of at least three orders of magnitude. This method is most suitable for retrieval of dissipation rates within the convective well-mixed boundary layer where the scales of motion that the Doppler lidar probes remain well within the inertial subrange. Caution must be applied when estimating dissipation rates in more quiescent conditions. For the particular Doppler lidar described here, the selection of suitably short integration times will permit this method to be applicable in such situations but at the expense of accuracy in the Doppler velocity estimates. The two case studies presented here suggest that, with profiles every 4 s, reliable estimates of Greek Lunate Epsilon can be derived to within at least an order of magnitude throughout almost all of the lowest 2 km and, in the convective boundary layer, to within 50%. Increasing the integration time for individual profiles to 30 s can improve the accuracy substantially but potentially confines retrievals to within the convective boundary layer. Therefore, optimization of certain instrument parameters may be required for specific implementations.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, UILJ, UKNU, UL, UM, UPUK
Forecasts with the European Centre for Medium‐Range Weather Forecasts' numerical weather prediction model are evaluated using an extensive set of observations from the Arctic Ocean 2018 expedition on ...the Swedish icebreaker Oden. The atmospheric model (Cy45r1) is similar to that used for the ERA5 reanalysis (Cy41r2). The evaluation covers 1 month, with the icebreaker moored to drifting sea ice near the North Pole; a total of 125 forecasts issued four times per day were used. Standard surface observations and 6‐hourly soundings were assimilated to ensure that the initial model error is small. Model errors can be divided into two groups. First, variables related to dynamics feature errors that grow with forecast length; error spread also grows with time. Initial errors are small, facilitating a robust evaluation of the second group; thermodynamic variables. These feature fast error growth for 6–12 hr, after which errors saturates; error spread is roughly constant. Both surface and near‐surface air temperatures are too warm in the model. During the summer both are typically above zero in spite of the ongoing melt; however, the warm bias increases as the surface freezes. The warm bias is due to a too warm atmosphere; errors in surface sensible heat flux transfer additional heat from the atmosphere to the surface. The lower troposphere temperature error has a distinct vertical structure: a substantial warm bias in the lowest few 100 m and a large cold bias around 1 km; this structure features a significant diurnal cycle and is tightly coupled to errors in the modelled clouds. Clouds appear too often and in a too deep layer of the lower atmosphere; the lowest clouds essentially never break up. The largest error in cloud presence is aligned with the largest cold bias at around 1 km.
The average temperature error as a function of height in ECMWF/IFS forecasts for the central Arctic mirror the average errors in cloud occurrence almost perfectly, leading us to hypothesize that the cold bias around 1 km and the warm‐biased boundary layer are connected to the overestimation of clouds in the lower troposphere. The evaluation was done based on extensive data collected in the central Arctic and is based on 125 operational forecasts over a full month, spanning the end of the summer melt season and the beginning of the autumn freeze.
Several recent studies have utilized a Haar wavelet covariance transform to provide automated detection of the boundary layer top from lidar backscatter profiles by locating the maximum in the ...covariance profiles. This approach is effective where the vertical gradient in the backscatter is small within and above the boundary layer, and where the inversion is sharp and well defined. These near-ideal conditions are often not met, particularly under stable stratification where the inversion may be deep and is sometimes ill defined, and vertical gradients are common. Here the effects of vertical gradients and inversion depth on the covariance transform are examined. It is found that a significant dilation-dependent bias in the determination of the boundary layer top may result when using the published method. An alternative approach is developed utilizing multiple wavelet dilations, and is capable of identifying both the upper and lower limits of the backscatter transition zone associated with the inversion while remaining insensitive to mean vertical gradients in the background signal. This approach enables more detailed information on the small-scale structure of the inversion and entrainment zone to be retrieved than is possible using existing techniques. PUBLICATION ABSTRACT
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, UILJ, UKNU, UL, UM, UPUK
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