40 research outputs found
Interactions between clouds and sea ice in the Arctic
The feedback between clouds and sea ice got more importance in the last years, because of the declining Arctic sea ice extent. Previous observations
show the formation of low clouds over newly formed open water. These low clouds are very important for the Arctic Energy Budget, because they warm the surface. This leads to increasing temperatures and stronger sea ice loss. To assess the relationship between sea ice cover and cloudiness, satellite observations by DARDAR were compared with both global climate reanalyses ERAâInterim and MACC. The analysis focuses on 2007 â 2010 and the relationship between different parameters from the different datasets. It is found that the reanalyses only poorly approximate the cloud cover in the Arctic. Consequently no strong correlation was found for the time period 2007 â 2010.Das WolkenâAlbedoâFeedback in der Arktis gewann in den letzten Jahren immer mehr an Bedeutung aufgrund des RĂŒckganges der MeereisflĂ€che.
Vorhergehende Arbeiten zeigten die Bildung von tiefer Bewölkung ĂŒber kĂŒrzlich aufgebrochenen Meereisstellen. Diese tiefen Wolken sind sehr wichtig fĂŒr das arktische Energiebudget, wegen des ErwĂ€rmens der OberflĂ€che. Daraus folgt ein Anstieg in der bodennahen Temperatur und ein verstĂ€rkter RĂŒckgang des Meereises. Um den Einfluss der Meereiskonzentration auf die Wolkenbildung zu untersuchen, werden in dieser Arbeit Satellitendaten von DARDAR mit den beiden globalen Klimareanalysen Eraâinterim und MACC verglichen. Analysiert werden Daten aus den Jahren 2007 bis 2010 und fĂŒr verschiedene OberflĂ€chenbedingungen werden Korrelationen der einzelnen DatensĂ€tze erstellt. Es hat sich gezeigt, dass die Darstellung der Wolkenbedeckung in der Arktis durch die Reanalyse Daten nicht geeignet ist. Aus diesem Grund wurden keine signifikanten Korrelationen in der Zeitspanne von 2007 bis 2010 gefunden
Analysis of diagnostic climate model cloud parameterisations using large-eddy simulations: Analysis of diagnostic climate model cloud parameterisations usinglarge-eddy simulations
Current climate models often predict fractional cloud cover on the basis of a diagnostic probability density function (PDF) describing the subgrid-scale variability of the total water specific humidity, qt, favouring schemes with limited complexity. Standard shapes are uniform or triangular PDFs the width of which is assumed to scale with the gridbox
mean qt or the grid-box mean saturation specific humidity, qs. In this study, the qt variability is analysed from large-eddy simulations for two stratocumulus, two shallow cumulus, and one deep convective cases. We find that in most cases, triangles are a better approximation to the simulated PDFs than uniform distributions. In two of the 24 slices examined, the actual distributions were so strongly skewed that the simple symmetric shapes could not capture the PDF at all. The distribution width for either shape scales acceptably well with both the mean value of qt and qs, the former being a slightly better choice. The qt variance is underestimated by the fitted PDFs, but overestimated by the existing parameterisations. While the cloud fraction is in general relatively well
diagnosed from fitted or parameterised uniform or triangular PDFs, it fails to capture cases with small partial cloudiness, and in 10 â 30% of the cases misdiagnoses clouds in clear skies or vice-versa. The results suggest choosing a parameterisation with a triangular shape, where the distribution width would scale with the grid-box mean qt using a scaling factor of 0.076. This, however, is subject to the caveat that the reference simulations examined here were partly for rather small domains and driven by idealised boundary conditions
Exploring Satellite-Derived Relationships between Cloud Droplet Number Concentration and Liquid Water Path Using a Large-Domain Large-Eddy Simulation
Important aspects of the adjustments to aerosol-cloud interactions can be examined using the relationship between cloud droplet number concentration (Nd) and liquid water path (LWP). Specifically, this relation can constrain the role of aerosols in leading to thicker or thinner clouds in response to adjustment mechanisms. This study investigates the satellite retrieved relationship between Nd and LWP for a selected case of mid-latitude continental clouds using high-resolution Large-eddy simulations (LES) over a large domain in weather prediction mode. Since the satellite retrieval uses the adiabatic assumption to derive the Nd, we have also considered adiabatic Nd (NAd) from the LES model for comparison. The joint histogram analysis shows that the NAd-LWP relationship in the LES model and the satellite is in approximate agreement. In both cases, the peak conditional probability (CP) is confined to lower NAd and LWP; the corresponding mean LWP (LWP) shows a weak relation with NAd. The CP shows a larger spread at higher NAd (>50 cmâ3), and the LWP increases non-monotonically with increasing NAd in both cases. Nevertheless, both lack the negative NAd-LWP relationship at higher NAd, the entrainment effect on cloud droplets. In contrast, the model simulated Nd-LWP clearly illustrates a much more nonlinear (an increase in LWP with increasing Nd and a decrease in LWP at higher Nd) relationship, which clearly depicts the cloud lifetime and the entrainment effect. Additionally, our analysis demonstrates a regime dependency (marine and continental) in the NAd-LWP relation from the satellite retrievals. Comparing local vs large-scale statistics from satellite data shows that continental clouds exhibit only a weak nonlinear NAd-LWP relationship. Hence a regime-based Nd-LWP analysis is even more relevant when it comes to warm continental clouds and their comparison to satellite retrievals
Potential quantum advantage for simulation of fluid dynamics
Numerical simulation of turbulent fluid dynamics needs to either parameterize
turbulence-which introduces large uncertainties-or explicitly resolve the
smallest scales-which is prohibitively expensive. Here we provide evidence
through analytic bounds and numerical studies that a potential quantum
exponential speedup can be achieved to simulate the Navier-Stokes equations
governing turbulence using quantum computing. Specifically, we provide a
formulation of the lattice Boltzmann equation for which we give evidence that
low-order Carleman linearization is much more accurate than previously believed
for these systems and that for computationally interesting examples. This is
achieved via a combination of reformulating the nonlinearity and accurately
linearizing the dynamical equations, effectively trading nonlinearity for
additional degrees of freedom that add negligible expense in the quantum
solver. Based on this we apply a quantum algorithm for simulating the
Carleman-linerized lattice Boltzmann equation and provide evidence that its
cost scales logarithmically with system size, compared to polynomial scaling in
the best known classical algorithms. This work suggests that an exponential
quantum advantage may exist for simulating fluid dynamics, paving the way for
simulating nonlinear multiscale transport phenomena in a wide range of
disciplines using quantum computing
Recommended from our members
Radiative forcing of climate change from the Copernicus reanalysis of atmospheric composition
Radiative forcing provides an important basis for understanding and predicting global climate changes, but its quantification has historically been done independently for different forcing agents, involved observations to varying degrees, and studies have not always included a detailed analysis of uncertainties. The Copernicus Atmosphere Monitoring Service reanalysis is an optimal combination of modelling and observations of atmospheric composition. It provides a unique opportunity to rely on observations to quantify the monthly and spatially resolved global distributions of radiative forcing consistently for six of the largest forcing agents: carbon dioxide, methane, tropospheric ozone, stratospheric ozone, aerosol-radiation interactions, and aerosol-cloud interactions. These radiative forcing estimates account for adjustments in stratospheric temperatures, but do not account for rapid adjustments in the troposphere. On a global average and over the period 2003â2017, stratospherically adjusted radiative forcing of carbon dioxide has averaged +1.89 W mâ2 (5-95% confidence interval: 1.50 to 2.29 W mâ2) relative to 1750 and increased at a rate of 18% per decade. The corresponding values for methane are +0.46 (0.36 to 0.56) W mâ2 and 4% per decade, but with a clear acceleration since 2007. Ozone radiative forcing averages +0.32 (0 to 0.64) W mâ2, almost entirely contributed by tropospheric ozone since stratospheric ozone radiative forcing is only +0.003 W mâ2. Aerosol radiative forcing averages â1.25 (â1.98 to â0.52) W mâ2, with aerosol-radiation interactions contributing â0.56 W mâ2 and aerosol-cloud interactions contributing â0.69 W mâ2 to the global average. Both have been relatively stable since 2003. Taking the six forcing agents together, there no indication of a sustained slowdown or acceleration in the rate of increase in anthropogenic radiative forcing over the period. These ongoing radiative forcing estimates will monitor the impact on the Earthâs energy budget of the dramatic emission reductions towards net-zero that are needed to limit surface temperature warming to the Paris Agreement temperature targets. Indeed, such impacts should be clearly manifested in radiative forcing before being clear in the temperature record. In addition, this radiative forcing dataset can provide the input distributions needed by researchers involved in monitoring of climate change, detection and attribution, interannual to decadal prediction, and integrated assessment modelling. The data generated by this work are available at https://doi.org/10.24380/ads.1hj3y896 (Bellouin et al., 2020)
Recommended from our members
The effect of rapid adjustments to halocarbons and N2O on radiative forcing
Rapid adjustments occur after initial perturbation of an external climate driver (e.g., CO2) and involve changes in, e.g. atmospheric temperature, water vapour and clouds, independent of sea surface temperature changes. Knowledge of such adjustments is necessary to estimate effective radiative forcing (ERF), a useful indicator of surface temperature change, and to understand global precipitation changes due to different drivers. Yet, rapid adjustments have not previously been analysed in any detail for certain compounds, including halocarbons and N2O. Here we use several global climate models combined with radiative kernel calculations to show that individual rapid adjustment terms due to CFC-11, CFC-12 and N2O are substantial, but that the resulting flux changes approximately cancel at the top-of-atmosphere due to compensating effects. Our results further indicate that radiative forcing (which includes stratospheric temperature adjustment) is a reasonable approximation for ERF. These CFCs lead to a larger increase in precipitation per kelvin surface temperature change (2.2â±â0.3%âKâ1) compared to other well-mixed greenhouse gases (1.4â±â0.3%âKâ1 for CO2). This is largely due to rapid upper tropospheric warming and cloud adjustments, which lead to enhanced atmospheric radiative cooling (and hence a precipitation increase) and partly compensate increased atmospheric radiative heating (i.e. which is associated with a precipitation decrease) from the instantaneous perturbation
Constraining the Twomey effect from satellite observations: issues and perspectives
The Twomey effect describes the radiative forcing
associated with a change in cloud albedo due to an increase
in anthropogenic aerosol emissions. It is driven by the perturbation
in cloud droplet number concentration (1Nd; ant)
in liquid-water clouds and is currently understood to exert
a cooling effect on climate. The Twomey effect is the key
driver in the effective radiative forcing due to aerosolâcloud
interactions, but rapid adjustments also contribute. These
adjustments are essentially the responses of cloud fraction
and liquid water path to 1Nd; ant and thus scale approximately
with it. While the fundamental physics of the influence
of added aerosol particles on the droplet concentration
(Nd) is well described by established theory at the particle
scale (micrometres), how this relationship is expressed at the
large-scale (hundreds of kilometres) perturbation, 1Nd; ant,
remains uncertain. The discrepancy between process understanding
at particle scale and insufficient quantification at
the climate-relevant large scale is caused by co-variability of
aerosol particles and updraught velocity and by droplet sink
processes. These operate at scales on the order of tens of metres at which only localised observations are available and at
which no approach yet exists to quantify the anthropogenic
perturbation. Different atmospheric models suggest diverse
magnitudes of the Twomey effect even when applying the
same anthropogenic aerosol emission perturbation. Thus, observational
data are needed to quantify and constrain the
Twomey effect. At the global scale, this means satellite data.
There are four key uncertainties in determining 1Nd; ant,
namely the quantification of (i) the cloud-active aerosol â the
cloud condensation nuclei (CCN) concentrations at or above
cloud base, (ii) Nd, (iii) the statistical approach for inferring
the sensitivity of Nd to aerosol particles from the satellite
data and (iv) uncertainty in the anthropogenic perturbation
to CCN concentrations, which is not easily accessible from
observational data. This review discusses deficiencies of current
approaches for the different aspects of the problem and
proposes several ways forward: in terms of CCN, retrievals
of optical quantities such as aerosol optical depth suffer from
a lack of vertical resolution, size and hygroscopicity information,
non-direct relation to the concentration of aerosols,
difficulty to quantify it within or below clouds, and the problem
of insufficient sensitivity at low concentrations, in addition
to retrieval errors. A future path forward can include
utilising co-located polarimeter and lidar instruments, ideally
including high-spectral-resolution lidar capability at two
wavelengths to maximise vertically resolved size distribution
information content. In terms of Nd, a key problem is the lack
of operational retrievals of this quantity and the inaccuracy of
the retrieval especially in broken-cloud regimes. As for the
Nd-to-CCN sensitivity, key issues are the updraught distributions
and the role of Nd sink processes, for which empirical
assessments for specific cloud regimes are currently the best
solutions. These considerations point to the conclusion that past studies using existing approaches have likely underestimated
the true sensitivity and, thus, the radiative forcing due
to the Twomey effect
Eastern Pacific Emitted Aerosol Cloud Experiment
Aerosolâcloudâradiation interactions are widely held to be the largest single source of uncertainty in climate model projections of future radiative forcing due to increasing anthropogenic emissions. The underlying causes of this uncertainty among modeled predictions of climate are the gaps in our fundamental understanding of cloud processes. There has been significant progress with both observations and models in addressing these important questions but quantifying them correctly is nontrivial, thus limiting our ability to represent them in global climate models. The Eastern Pacific Emitted Aerosol Cloud Experiment (E-PEACE) 2011 was a targeted aircraft campaign with embedded modeling studies, using the Center for Interdisciplinary Remotely-Piloted Aircraft Studies (CIRPAS) Twin Otter aircraft and the research vessel Point Sur in July and August 2011 off the central coast of California, with a full payload of instruments to measure particle and cloud number, mass, composition, and water uptake distributions. EPEACE used three emitted particle sources to separate particle-induced feedbacks from dynamical variability, namely 1) shipboard smoke-generated particles with 0.05â1-ÎŒm diameters (which produced tracks measured by satellite and had drop composition characteristic of organic smoke), 2) combustion particles from container ships with 0.05â0.2-ÎŒm diameters (which were measured in a variety of conditions with droplets containing both organic and sulfate components), and 3) aircraft-based milled salt particles with 3â5-ÎŒm diameters (which showed enhanced drizzle rates in some clouds). The aircraft observations were consistent with past large-eddy simulations of deeper clouds in ship tracks and aerosolâ cloud parcel modeling of cloud drop number and composition, providing quantitative constraints on aerosol effects on warm-cloud microphysics