pinecone/core-2020-05-10-deduplication huggingface dataset:
A High-Latitude Convective Cloud Feedback and Equable Climates

A convective cloud feedback on extratropical surface temperatures is identified in a zonally averaged two-level atmospheric model. The model contains simplified parametrizations for convection, precipitation, and clouds, and a long-wave radiation scheme that explicitly depends on carbon dioxide, water vapour, and cloud fraction. The convective cloud feedback occurs if the extratropical surface temperature is increased enough to initiate strong atmospheric convection. This results in a change from low to high clouds and from negative to neutral or positive cloud radiative forcing, which further warms the surface and leads to more convection. This positive feedback activates as the CO2 concentration is increased and leads to a climate solution with high boundary-layer temperatures, convection at mid and high latitudes, and an Equator to Pole temperature difference that is reduced by 8-10 °C. The reduction in Equator to Pole temperature difference is due to changes in high-latitude local heat balance and occurs despite decreased meridional heat transport. The convective cloud feedback also leads to multiple equilibria and hysteresis with respect to CO2 and other model variables, although these results may be due to the simplicity of the model. The possible connection of the behaviour of the model at high CO2 with equable climates is considered.Earth and Planetary Science
Background error correlation length-scale estimates and their sampling statistics

WARNING : This is a preprint of an article accepted for publication in QUARTERLY JOURNAL OF THE ROYAL METEOROLOGICAL SOCIETY ref: Q. J. R. Meteorol. Soc. 134: 497–508 (2008) see the website for final version http://www.interscience.wiley.com/International audienceThis article presents different formulae to estimate correlation length-scales, and an evaluation of their qualities for practical diagnostic applications. In particular, two new and simple formulae are introduced, which only require the computation of correlation with a single point for a given direction. It is then shown in a 1D heterogeneous context that all formulations lead to similar realistic length-scale values, and that they represent geographical variations rather well. The estimation of length-scales within a finite ensemble is also studied. While a positive bias occurs when the ensemble size is too small, the standard deviation of the length-scale estimation is shown to be the main influence on the estimation error. The spatial structure of sampling noise is then diagnosed, and effects of spatial filtering techniques on the bias and standard deviation are illustrated. Finally, an ensemble of perturbed forecasts from a global NWP model is used, showing a real application example
A wavelet-based filtering of ensemble background-error variances

Background-error variances estimated from a small-size ensemble of data assimilations need to be filtered because of the associated sampling noise. Previous studies showed that objective spectral filtering is efficient in reducing this noise, while preserving relevant features to a large extent. However, since such filters are homogeneous, they tend to smooth small-scale structures of interest. In many applications, nonlinear thresholding of wavelet coefficients has proved to be an efficient technique for denoising signals. This algorithm proceeds by thresholding the wavelet coefficients of the noisy signal using an estimated threshold. This is equivalent to applying an adaptive local spatial filtering. A quasi-optimal value for the threshold can be computed from the noise variance. We show that the statistical properties of the sampling noise associated with the estimation of background-error variances can be used to calculate the noise level and the appropriate threshold value. This method is first applied to 1D academic examples, with emphasis on correlated and heterogeneous noises. This approach is shown to outperform the commonly used homogeneous filters, since it automatically adapts to the local structure of the signal. We also show that this technique compares favourably to a heterogeneous diffusion-based filter, with the advantage of requiring less trial-and-error tuning. These results are next confirmed in a more realistic 2D problem, using the Arome-France convective-scale model
Convective inhibition beneath an upper-level PV anomaly

Copyright @ 2008 Royal Meteorological SocietyUpper-level potential-vorticity (PV) anomalies reduce the convective stability of the troposphere through their impact on the vertical potential-temperature profile, thus reducing convective inhibition (CIN) and increasing convective available potential energy. Here, by contrast, we show the impact of a layer of stable air that was intrinsically linked with an upper-level PV anomaly and that increased CIN. This layer descended and tracked beneath the small upper-level PV anomaly, which in this case was a shallow upper-level trough. This low-humidity, relatively high-PV layer originated from the tropopause fold, generated by a breaking Rossby wave, which also produced the upper-level PV anomaly two days later. Despite conditions favourable for deep convection (as demonstrated by the development of a single storm), the CIN produced by this dry layer or lid was largely responsible for capping convection over much of southern England at around 2.5 km during the case presented here, which comes from the Convective Storm Initiation Project.This work is funded by the Natural Environment Research Council (NERC)
Modelling the diurnal cycle of tropical convection across the ‘grey zone’

We present the results of simulations carried out with the Met Office Unified Model at 12, 4 and 1.5 km resolution for a large region centred on West Africa using several different representations of the convection processes. These span a range of resolutions from much coarser than the size of the convection processes to cloud-system-resolving and thus encompass the intermediate ‘grey zone’. The diurnal cycle in the extent of convective regions in the models is tested against observations from the Geostationary Earth Radiation Budget instrument on Meteosat-8. By this measure, the two best-performing simulations are a 12 km model without convective parametrization, using Smagorinsky-style subgrid-scale mixing in all three dimensions, and a 1.5 km simulation with two-dimensional Smagorinsky mixing. Of these, the 12 km model produces a better match to the magnitude of the total cloud fraction but the 1.5 km one results in better timing for its peak value. The results suggest that the previously reported improvement in the representation of the diurnal cycle of convective organization in the 4 km model compared with the standard 12 km configuration is principally a result of the convection scheme employed rather than the improved resolution per se. The details of this result and implications for high-resolution model simulations are discussed
Cascades, backscatter and conservation in numerical models of two‐dimensional turbulence

The equations governing atmospheric flow imply transfers of energy and potential enstrophy between scales. Accurate simulation of turbulent flow requires that numerical models, which have finite resolution and truncation errors, adequately capture these interscale transfers, particularly between resolved and unresolved scales. It is therefore important to understand how accurately these transfers are modelled in the presence of scale‐selective dissipation or other forms of subgrid model. Here, the energy and enstrophy cascades in numerical models of two‐dimensional turbulence are investigated using the barotropic vorticity equation.  Energy and enstrophy transfers in spectral space due to truncated scales are calculated for a high‐resolution reference solution and for several explicit and implicit subgrid models at coarser resolution. The reference solution shows that enstrophy and energy are removed from scales very close to the truncation scale and energy is transferred (backscattered) into the large scales. Some subgrid models are able to capture the removal of enstrophy from small scales, though none are scale‐selective enough; however, none are able to capture accurately the energy backscatter.  We propose a scheme that perturbs the vorticity field at each time step by the addition of a particular vorticity pattern derived by filtering the predicted vorticity field. Although originally conceived as a parametrization of energy backscatter, this scheme is best interpreted as an energy ‘fixer’ that attempts to repair the damage to the energy spectrum caused by numerical truncation error and an imperfect subgrid model. The proposed scheme improves the energy and enstrophy behaviour of the solution and, in most cases, slightly reduces the root mean square vorticity errors
On the definition of a moist-air potential vorticity

A new potential vorticity is derived by using a specific entropy formulation
expressed in terms of a moist-air entropy potential temperature. The new
formulation is compared with Ertel's version and with others based on virtual
and equivalent potential temperatures. The new potential vorticity is subject
to conservative properties ensured by the Second Law applied to the moist-air
material derivatives. It is shown that the upper tropospheric and stratospheric
(dry) structures are nearly the same as those obtained with Ertel's component.
Moreover, new structures are observed in the low troposphere, with negative
values associated with moist frontal regions. The negative values are observed
in the frontal regions where slantwise convection instabilities may take place,
but they are smaller than those observed with the equivalent potential
vorticity. The main purpose of the article is to diagnose the behaviour of the
new potential vorticity from numerical output generated by the ARPEGE NWP
model, with the help of isobaric charts and vertical cross-sections. Two
inversion methods are suggested. The first method could be based on the
invertibility principle verified by the virtual potential vorticity, with a
possibility to control and modify separately potential vorticity components in
the (dry) upper and (moist) lower atmospheric levels. The other method may
consist of an inversion process directly applied to the new moist-air entropy
potential vorticity, because the negative values and the solenoidal term are
smaller than those observed with equivalent potential vorticity, as shown by
numerical evaluations.Comment: Submitted to the Q. J. R. Meteorol. Soc. in August 2012. Accepted in
  April 2013. Early view on the QJRMS site
  http://onlinelibrary.wiley.com/doi/10.1002/qj.2182/abstract. 24 pages, 10
  color figures. V2: add the arXiv links of Marquet (2011), Geleyn and Marquet
  (2012) and Marquet and Geleyn (2013
Twentieth century North Atlantic jet variability

\ud
Long records of the latitude and speed of the North Atlantic eddy-driven jet stream since 1871 are presented from the newly available Twentieth Century Reanalysis. These jet variations underlie the variability associated with patterns such as the North Atlantic Oscillation (NAO) and have considerable societal impact through variations in the prevailing westerly winds. While the NAO combines variations in the latitude and speed of the jet, these two characteristics are shown to have quite different seasonal cycles and interannual variability, suggesting that they may have different dynamical influences.\ud
\ud
\ud
In general, the features exhibited in shorter records are shown to be robust, for example the strong skewness of the NAO distribution. Related to this is a clear multimodality of the jet latitude distribution, which suggests the existence of preferred positions of the jet. Decadal variations in jet latitude are shown to correspond to changes in the occurrence of these preferred positions. However, it is the speed rather than the latitude of the jet that exhibits the strongest decadal variability, and in most seasons this is clearly distinct from a white-noise representation of the seasonal means. When viewed in this longer term context, the variations of recent decades do not appear unusual and recent values of jet latitude and speed are not unprecedented in the historical record
Modelling of Local Length-Scale Dynamics and Isotropizing Deformations: Formulation in Natural Coordinate System

We propose an algorithm to model anisotropic correlation functions using an approach based on the deformation of locally isotropic ones. In a previous work, a set of equations that allow to calculate the desired deformation was derived for a flat coordinates system. However this strategy is not adapted for curved geometry as the sphere (regional and global atmospheric models), where it is suitable to state the local isotropy in terms of the local Riemannian metric.This paper introduces the theoretical background to deal explicitly with natural coordinate systems leading to a formulation adapted with the Riemannian metric. It results that the isotropizing deformation is obtained from the resolution of coupled non-linear equations depending on the geometry. This procedure is illustrated within a 2D setting
Variance estimation for Brier Score decomposition

This is the author accepted manuscript. The final version is available from Wiley via the DOI in this record.The Brier Score is a widely-used criterion to assess the quality of probabilistic predictions of binary events. The expectation value of the Brier Score can be decomposed into the sum of three components called reliability, resolution, and uncertainty which characterize different forecast attributes. Given a dataset of forecast probabilities and corresponding binary verifications, these three components can be estimated empirically. Here, propagation of uncertainty is used to derive expressions that approximate the sampling variances of the estimated components. Variance estimates are provided for both the traditional estimators, as well as for refined estimators that include a bias correction. Applications of the derived variance estimates to artificial data illustrate their validity, and application to a meteorological prediction problem illustrates a possible use case. The observed increase of variance of the bias-corrected estimators is discussed
Primary and successive events in the Madden–Julian Oscillation

Conventional analyses of the MJO tend to produce a repeating cycle, such that any particular feature cannot be unambiguously attributed to the current or previous event. We take advantage of the sporadic nature of the MJO and classify each observed Madden-Julian (MJ) event as either primary, with no immediately preceding MJ event, or successive, which does immediately follow a preceding event. 40% of MJ events are primary events. Precursor features of the primary events can be unambiguously attributed to that event. A suppressed convective anomaly grows and decays in situ over the Indian Ocean, prior to the start of most primary MJ events. An associated mid-tropospheric temperature anomaly destabilises the atmosphere, leading to the generation of the active MJ event. Hence, primary MJ events appear to be thermodynamically triggered by a previous dry period, although stochastic forcing may also be important. Other theories predict that boundary-layer convergence, humidity, propagation of dynamical structures around the Equator, sea surface temperatures, and lateral forcing by extratropical transients may all be important in triggering an event. Although precursor signals from these mechanisms are diagnosed from reanalysis and satellite observational data in the successive MJ events, they are all absent in the primary MJ events. Hence, it appears that these apparent precursor signals are part of the MJO once it is established, but do not play a role in the spontaneous generation of the MJO. The most frequent starting location of the primary events is the Indian Ocean, but over half of them start elsewhere, from the maritime continent to the western Pacific
Evaluation of ECMWF medium-range ensemble forecasts of precipitation for river basins

Providing probabilistic forecasts using Ensemble Prediction Systems has become increasingly popular in both the meteorological and hydrological communities. Compared to conventional deterministic forecasts, probabilistic forecasts may provide more reliable forecasts of a few hours to a number of days ahead, and hence are regarded as better tools for taking uncertainties into consideration and hedging against weather risks. It is essential to evaluate performance of raw ensemble forecasts and their potential values in forecasting extreme hydro-meteorological events. This study evaluates ECMWF's medium-range ensemble forecasts of precipitation over the period 1 January 2008 to 30 September 2012 on a selected midlatitude large-scale river basin, the Huai river basin (ca. 270 000 km2) in central-east China. The evaluation unit is sub-basin in order to consider forecast performance in a hydrologically relevant way. The study finds that forecast performance varies with sub-basin properties, between flooding and non-flooding seasons, and with the forecast properties of aggregated time steps and lead times. Although the study does not evaluate any hydrological applications of the ensemble precipitation forecasts, its results have direct implications in hydrological forecasts should these ensemble precipitation forecasts be employed in hydrology
Fair scores for ensemble forecasts

This is the author accepted manuscript. The final version is available from the publisher via the DOI in this record.The notion of fair scores for ensemble forecasts was introduced recently to
reward ensembles whose members behave as though they and the verifying
observation are sampled from the same distribution. In the case of forecasting
binary outcomes, a characterization is given of a general class of fair scores
for ensembles that are interpreted as random samples. This is also used to
construct classes of fair scores for ensembles that forecast multi-category and
continuous outcomes. The usual Brier, ranked probability, and continuous
ranked probability scores for ensemble forecasts are shown to be unfair,
while adjusted versions of these scores are shown to be fair. A definition of
fairness is also proposed for ensembles whose members are interpreted as
being dependent, and it is shown that fair scores exist only for some forms of
dependence
An analysis of the observed low-level structure of rapidly intensifying and mature hurricane Earl (2010)

The article of record as published may be located at http://dx.doi.org/10.1002/qj.2283We examine dynamic and thermodynamic aspects of Atlantic hurricane Earl (2010) during
its intensification and mature phases over four days of intensive measurements. During
this period, Earl underwent an episode of rapid intensification, maturity, secondary eyewall
replacement, re-intensification and the early part of its decline. The observations are used
to appraise elements of a new model for tropical-cyclone intensification.
The results affirm the conventional (vortex interior) and boundary-layer spin-up
mechanisms that form dynamical elements of the azimuthally averaged view of the
new intensification model. The averagemaximum tangential winds beneath the eyewall are
found to exceed the gradient wind by between 20 and 60%. The results suggest also that
the gradient wind balance approximation in the low-level vortex interior above the strong
inflow layer may not be as accurate in the inner-core region of a tropical cyclone during
its intensification as has been widely held. An analysis of the low-level thermodynamic
structure affirms the radial increase of moist equivalent potential temperature, θe, with
decreasing radius during the intensification process, a necessary ingredient of the newmodel
for maintaining convective instability in the presence of a warming upper troposphere.
An unanticipated finding is the discovery of an unmixed boundary layer in terms of θe
within several hundred kilometres of the vortex centre. In the inner-core region, this
finding is not consistent with the axisymmetric eruption of the boundary layer into the
eyewall unless there are non-conservative (eddy) processes acting to modify the entropy of
ascending air.We acknowledge NASA and Ramesh Kakar for their support of the GRIP experiment. MTM acknowledges the support of NSF AGS-0733380 and NASA grants NNH09AK561, NNG11PK021 and NNG09HG031. JAZ acknowledges the support from NOAA’s Hurricane Forecast and Improvement Program (HFIP)
Energy- and enstrophy-conserving schemes for the shallow-water
  equations, based on mimetic finite elements

This paper presents a family of spatial discretisations of the nonlinear
rotating shallow-water equations that conserve both energy and potential
enstrophy. These are based on two-dimensional mixed finite element methods and
hence, unlike some finite difference methods, do not require an orthogonal
grid. Numerical verification of the aforementioned properties is also provided.Comment: 25 pages, 14 figures, submitted to QJRMS; parts of sections 3 and 4
  rewritten for clarification, assorted typo fixe
On the influence of model nonlinearity and localization on ensemble Kalman smoothing

Ensemble-based Kalman smoother algorithms extend ensemble Kalman filters\ud
to reduce the estimation error of past model states utilizing observational\ud
information from the future. Like the filters they extend, current smoothing\ud
algorithms are optimal only for linear models. However, the ensemble methods\ud
are typically applied with high-dimensional nonlinear models, which also\ud
require the application of localization in the data assimilation. In this paper,\ud
the influence of the model nonlinearity and of the application of localization\ud
on the smoother performance is studied. Numerical experiments show that\ud
the observational information can be successfully utilized over smoothing lags\ud
several times the error doubling time of the model. Localization limits the\ud
smoother lag by spatial decorrelation. However, if the localization is well tuned,\ud
the usable lag of the smoother, and hence the usable amount of observational\ud
information, is maximized. The localization reduces the estimation errors of\ud
the smoother even more than those of the filter. As the smoother reuses the\ud
transformation matrix of the filter, it profits stronger from increases of the\ud
ensemble size than the filter. With respect to inflation and localization, the\ud
experiments also show that the same configuration that yields the smallest\ud
estimation errors for the filter without smoothing also results in the smallest\ud
errors of the smoothed states. Thus, smoothing only adds the lag as a further\ud
tunable parameter