pinecone/core-2020-05-10-deduplication huggingface dataset:
Quantile forecast discrimination ability and value

While probabilistic forecast verification for categorical forecasts is well
established, some of the existing concepts and methods have not found their
equivalent for the case of continuous variables. New tools dedicated to the
assessment of forecast discrimination ability and forecast value are introduced
here, based on quantile forecasts being the base product for the continuous
case (hence in a nonparametric framework). The relative user characteristic
(RUC) curve and the quantile value plot allow analysing the performance of a
forecast for a specific user in a decision-making framework. The RUC curve is
designed as a user-based discrimination tool and the quantile value plot
translates forecast discrimination ability in terms of economic value. The
relationship between the overall value of a quantile forecast and the
respective quantile skill score is also discussed. The application of these new
verification approaches and tools is illustrated based on synthetic datasets,
as well as for the case of global radiation forecasts from the high resolution
ensemble COSMO-DE-EPS of the German Weather Service
On the predictability of extremes: Does the butterfly effect ever decrease?

This is the peer reviewed version of the following article: Sterk, A. E., Stephenson, D. B., Holland, M. P. and Mylne, K. R. (2015), On the predictability of extremes: Does the butterfly effect ever decrease?. Quarterly Journal of the Royal Meteorological Society, which has been published in final form at http://dx.doi.org/10.1002/qj.2627. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Self-Archiving: http://olabout.wiley.com/WileyCDA/Section/id-820227.html#termsThis study investigates whether or not predictability always decreases for more extreme events. Predictability is measured by the Mean Squared Error (MSE), estimated here from the difference of pairs of ensemble forecasts, conditioned on one of the forecast variables (the 'pseudo-observation') exceeding a threshold. Using an exchangeable linear regression model for pairs of forecast variables, we show that the MSE can be decomposed into the sum of three terms: a threshold-independent constant, a mean term that always increases with threshold, and a variance term that can either increase, decrease, or stay constant with threshold. Using the generalised Pareto distribution to model wind speed excesses over a threshold, we show that MSE always increases with threshold at sufficiently high threshold. However, MSE can be a decreasing function of threshold at lower thresholds but only if the forecasts have finite upper bounds. The methods are illustrated by application to daily wind speed forecasts for London made using the 24 member Met Office Global and Regional Ensemble Prediction System from 1 January 2009 to 31 May 2011. For this example, the mean term increases faster than the variance term decreases with increasing threshold, and so predictability decreases for more extreme events.Engineering and Physical Sciences Research Council (EPSRC)Netherlands Organisation for Scientific Research (NWO
Waxing and Waning of Observed Extreme Annual Tropical Rainfall

We begin by providing observational evidence that the probability of
encountering very high and very low annual tropical rainfall has increased
significantly in the recent decade (1998-present) as compared to the preceding
warming era (1979-1997). These changes over land and ocean are spatially
coherent and comprise of a rearrangement of very wet regions and a systematic
expansion of dry zones. While the increased likelihood of extremes is
consistent with a higher average temperature during the pause (as compared to
1979-1997), it is important to note that the periods considered are also
characterized by a transition from a relatively warm to cold phase of the El
Nino Southern Oscillation (ENSO). To further probe the relation between
contrasting phases of ENSO and extremes in accumulation, a similar comparison
is performed between 1960-1978 (another extended cold phase of ENSO) and the
aforementioned warming era. Though limited by land-only observations, in this
cold-to-warm transition, remarkably, a near-exact reversal of extremes is noted
both statistically and geographically. This is despite the average temperature
being higher in 1979-1997 as compared to 1960-1978. Taken together, we propose
that there is a fundamental mode of natural variability, involving the waxing
and waning of extremes in accumulation of global tropical rainfall with
different phases of ENSO.Comment: 9 pages, 7 figure
Quasi-geostrophic dynamics in the presence of moisture gradients

The derivation of a quasi-geostrophic (QG) system from the rotating shallow
water equations on a midlatitude beta-plane coupled with moisture is presented.
Condensation is prescribed to occur whenever the moisture at a point exceeds a
prescribed saturation value. It is seen that a slow condensation time scale is
required to obtain a consistent set of equations at leading order. Further,
since the advecting wind fields are geostrophic, changes in moisture (and
hence, precipitation) occur only via non-divergent mechanisms. Following
observations, a saturation profile with gradients in the zonal and meridional
directions is prescribed. A purely meridional gradient has the effect of
slowing down the dry Rossby waves, through a reduction in the "equivalent
gradient" of the background potential vorticity. A large scale unstable moist
mode results on the inclusion of a zonal gradient by itself, or in conjunction
with a meridional moisture gradient. For gradients that are are representative
of the atmosphere, the most unstable moist mode propagates zonally in the
direction of increasing moisture, matures over an intraseasonal timescale and
has small phase speed.Comment: 9 pages, 8 figures, Quarterly Journal of the Royal Meteorological
  Society, DOI:10.1002/qj.2644, 201
A data-driven method for the stochastic parametrisation of subgrid-scale
  tropical convective area fraction

Observations of tropical convection from precipitation radar and the
concurring large-scale atmospheric state at two locations (Darwin and
Kwajalein) are used to establish effective stochastic models to parameterise
subgrid-scale tropical convective activity. Two approaches are presented which
rely on the assumption that tropical convection induces a stationary
equilibrium distribution. In the first approach we parameterise convection
variables such as convective area fraction as an instantaneous random
realisation conditioned on the large-scale vertical velocities according to a
probability density function estimated from the observations. In the second
approach convection variables are generated in a Markov process conditioned on
the large-scale vertical velocity, allowing for non-trivial temporal
correlations. Despite the different prevalent atmospheric and oceanic regimes
at the two locations, with Kwajalein being exposed to a purely oceanic weather
regime and Darwin exhibiting land-sea interaction, we establish that the
empirical measure for the convective variables conditioned on large-scale
mid-level vertical velocities for the two locations are close. This allows us
to train the stochastic models at one location and then generate time series of
convective activity at the other location. The proposed stochastic
subgrid-scale models adequately reproduce the statistics of the observed
convective variables and we discuss how they may be used in future
scale-independent mass-flux convection parameterisations.Comment: accepted for publication in Quarterly Journal of the Royal
  Meteorological Society (QJRMS) (2015
Seasonal surface urban energy balance and wintertime stability simulated using three land-surface models in the high-latitude city Helsinki

The performance of three urban land surface models, run in offline mode, with their default external parameters, is evaluated for two distinctly different sites in Helsinki: Torni and Kumpula. The former is a dense city centre site with 22% vegetation, while the latter is a suburban site with over 50% vegetation. At both locations the models are compared against sensible and latent heat fluxes measured using the eddy covariance technique, along with snow depth observations. The cold climate experienced by the city causes strong seasonal variations that include snow cover and stable atmospheric conditions.

Most of the time the three models are able to account for the differences between the study areas as well as the seasonal and diurnal variability of the energy balance components. However, the performances are not systematic across the modelled components, season and surface type. The net all-wave radiation is well simulated, with the greatest uncertainties related to snowmelt timing, when the fraction of snow cover has a key role, particularly in determining the surface albedo. For the turbulent fluxes, more variation between the models is seen which can partly be explained by the different methods in their calculation and partly by surface parameter values. For the sensible heat flux, simulation of wintertime values was the main problem, which also leads to issues in predicting near-surface stabilities particularly at the dense city centre site. All models have the most difficulties in simulating latent heat flux. This study particularly emphasizes that improvements are needed in the parameterization of anthropogenic heat flux and thermal parameters in winter, snow cover in spring and evapotranspiration in order to improve the surface energy balance modelling in cold climate cities.status: publishe
A test case for the inviscid shallow-water equations on the sphere

Partial support for this work was provided through the National Science Foundation award AGS-1333029.A numerically converged solution to the inviscid global shallow-water equations for a predefined time interval is documented to provide a convenient benchmark for model validation. The solution is based on the same initial conditions as a previously documented solution for the viscous equations. The solution is computed using two independent numerical schemes, one a pseudospectral scheme based on an expansion in spherical harmonics and the other a finite-volume scheme on a cubed-sphere grid. Flow fields and various integral norms are documented to facilitate model comparison and validation. Attention is drawn to the utility of the potential vorticity supremum as a convenient and sensitive test of numerical convergence, in which the exact value is known a priori over the entire time interval.PostprintPeer reviewe
Validation of eight atmospheric reanalyses in the Antarctic Peninsula region

Eight atmospheric reanalyses were compared against observed vertical profiles of temperature, specific humidity and wind speed collected by two research aircraft in February–March 2010 in the Antarctic Peninsula region. These data offered a rare possibility to validate reanalyses against independent in-situ data which have not been assimilated into the reanalyses. The reanalyses had generally too moist profiles with too low wind speeds, but otherwise the errors in the reanalyses had large spatial differences. On the eastern side of the peninsula, the near-surface temperatures were largely overestimated. None of the reanalysis outperformed the others in all variables, at all altitudes and on both sides of the peninsula. Generally, NCEP-CFSR and MERRA had the smallest errors in temperature profiles, JRA-55 had marginally the most accurate specific humidity profiles and NCEP-CFSR had the best wind profiles. The reanalyses were coherent, although biased, on the western side of the Antarctic Peninsula, but on the eastern side the spread was large. All the reanalyses underestimated the variability between the individual profiles of temperature and wind speed. The modern reanalyses with a sufficient spatial resolution and an adequate data assimilation method outperformed the others, especially on the eastern sid
The influence of diabatic heating in the South Pacific Convergence Zone on Rossby wave propagation and the mean flow

The South Pacific Convergence Zone (SPCZ) is a northwest-southeast oriented precipitation band over the South Pacific Ocean. Latent heat release from condensation leads to substantial diabatic heating, which has potentially large impacts on local and global climate. The influence of this diabatic heating within the SPCZ is investigated using the Intermediate General Circulation Model (IGCM4). Precipitation in the SPCZ has been shown to be triggered by transient Rossby waves that originate in the Australian subtropical jet and are refracted towards the equatorial eastern Pacific. A Rossby wave triggers a SPCZ 'convective event', with associated diabatic heat release and vortex stretching. Consequently, the Rossby wave is dissipated in the SPCZ region. These features are simulated well in a control integration of IGCM4. In an experiment, convective heating is prescribed to its 'climatological' value in the SPCZ region during the Rossby wave 'events' and dynamic forcing from Rossby waves is decoupled from the usual thermodynamic response. In this experiment Rossby waves over the SPCZ region are not dissipated, confirming the vortex stretching mechanism from previous studies. Furthermore, the change in Rossby wave propagation has an impact on momentum transport. Overall, the effect of the Rossby wave-induced convection in the SPCZ is to decrease the strength of the Pacific subtropical jet and the equatorial eastern Pacific upper-tropospheric westerlies, by about 2-6 m s-1. Following these changes to the basic state, two potential feedbacks in the SPCZ and larger Pacific climate system are suggested: increased SPCZ convection due to the enhancement of negative zonal stretching deformation in the SPCZ region and decreased equatorward refraction of Rossby waves into the westerly duct leading to less SPCZ 'events'. As the convective events in the SPCZ have a significant impact on Pacific mean climate, it is crucial that the SPCZ is represented correctly in climate models
An Energy Conserving Restoration Scheme for the Shallow Water Equations.

This is the peer reviewed version of the article, which has been published in final form at DOI 10.1002/qj.2713. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Self-Archiving.The numericalmethods that solve the governing equations in an atmospheric dynamical core are designed to dissipate potential enstrophy and prevent the buildup of kinetic energy at the grid scale. A side effect of this is the dissipation of total energy which should be conserved. Energy fixers are used in climate models to replace the dissipated energy by modifying the temperature in the thermodynamic equation, and stochastic backscatter schemes have also been developed for use in weather prediction models. Here, we present the first steps towards designing a deterministic energy conserving restoration scheme that considers the conversion of kinetic energy to heat, replacing kinetic energy lost due to model error, and the backscatter of kinetic energy. The energy conserving restoration scheme (ECRS) is presented in the context of the shallow water equations on the sphere. It is designed to be used with any existing shallow water equation scheme (called the preliminary scheme) which can adequately dissipate potential enstrophy, and in this paper we use a semi-implicit semi-Lagrangian (SISL) scheme. For each prognostic variable a spatial pattern is chosen; this is added to the preliminary scheme solution, and the amount added is calculated to ensure energy conservation. Results from short-termtest cases show that ECRS and SISL have very similar error norms. For long-term simulations ECRS conserves energy to a good approximation whereas SISL dissipates energy.Office of Science, U.S. Department of Energ
Data-assimilation by delay-coordinate nudging

A new nudging method for data assimilation, delay-coordinate nudging, is
presented. Delay-coordinate nudging makes explicit use of present and past
observations in the formulation of the forcing driving the model evolution at
each time-step. Numerical experiments with a low order chaotic system show that
the new method systematically outperforms standard nudging in different model
and observational scenarios, also when using an un-optimized formulation of the
delay-nudging coefficients. A connection between the optimal delay and the
dominant Lyapunov exponent of the dynamics is found based on heuristic
arguments and is confirmed by the numerical results, providing a guideline for
the practical implementation of the algorithm. Delay-coordinate nudging
preserves the easiness of implementation, the intuitive functioning and the
reduced computational cost of the standard nudging, making it a potential
alternative especially in the field of seasonal-to-decadal predictions with
large Earth system models that limit the use of more sophisticated data
assimilation procedures.Comment: minor changes, 10 pages, to appear in Q. J. R. Meteorol. So
3D cut-cell modelling for high-resolution atmospheric simulations

Owing to the recent, rapid development of computer technology, the resolution
of atmospheric numerical models has increased substantially. With the use of
next-generation supercomputers, atmospheric simulations using horizontal grid
intervals of O(100) m or less will gain popularity. At such high resolution
more of the steep gradients in mountainous terrain will be resolved, which may
result in large truncation errors in those models using terrain-following
coordinates. In this study, a new 3D Cartesian coordinate non-hydrostatic
atmospheric model is developed. A cut-cell representation of topography based
on finite-volume discretization is combined with a cell-merging approach, in
which small cut-cells are merged with neighboring cells either vertically or
horizontally. In addition, a block-structured mesh-refinement technique is
introduced to achieve a variable resolution on the model grid with the finest
resolution occurring close to the terrain surface. The model successfully
reproduces a flow over a 3D bell-shaped hill that shows a good agreement with
the flow predicted by the linear theory. The ability of the model to simulate
flows over steep terrain is demonstrated using a hemisphere-shaped hill where
the maximum slope angle is resolved at 71 degrees. The advantage of a locally
refined grid around a 3D hill, with cut-cells at the terrain surface, is also
demonstrated using the hemisphere-shaped hill. The model reproduces smooth
mountain waves propagating over varying grid resolution without introducing
large errors associated with the change of mesh resolution. At the same time,
the model shows a good scalability on a locally refined grid with the use of
OpenMP.Comment: 19 pages, 16 figures. Revised version, accepted for publication in
  QJRM
Probabilistic temperature forecasting based on an ensemble AR
  modification

To address the uncertainty in outputs of numerical weather prediction (NWP)
models, ensembles of forecasts are used. To obtain such an ensemble of
forecasts the NWP model is run multiple times, each time with different
formulations and/or initial or boundary conditions. To correct for possible
biases and dispersion errors in the ensemble, statistical postprocessing models
are frequently employed. These statistical models yield full predictive
probability distributions for a weather quantity of interest and thus allow for
a more accurate assessment of forecast uncertainty. This paper proposes to
combine the state of the art Ensemble Model Output Statistics (EMOS) with an
ensemble that is adjusted by an AR process fitted to the respective error
series by a spread-adjusted linear pool (SLP) in case of temperature forecasts.
The basic ensemble modification technique we introduce may be used to simply
adjust the ensemble itself as well as to obtain a full predictive distribution
for the weather quantity. As demonstrated for temperature forecasts of the
European Centre for Medium-Range Weather Forecasts (ECMWF) ensemble, the
proposed procedure gives rise to improved results upon the basic (local) EMOS
method.Comment: 18 pages, 4 figures, 5 table
Assimilation of 3D radar reflectivities with an ensemble Kalman filter on the convective scale

An ensemble data assimilation system for 3D radar reflectivity data is introduced for the convection-permitting numerical weather prediction model of the COnsortium for Small-scale MOdelling (COSMO) based on the Kilometre-scale ENsemble Data Assimilation system (KENDA), developed by Deutscher Wetterdienst and its partners. KENDA provides a state-of-the-art ensemble data assimilation system on the convective scale for operational data assimilation and forecasting based on the Local Ensemble Transform Kalman Filter (LETKF). In this study, the Efficient Modular VOlume RADar Operator is applied for the assimilation of radar reflectivity data to improve short-term predictions of precipitation. Both deterministic and ensemble forecasts have been carried out. A case-study shows that the assimilation of 3D radar reflectivity data clearly improves precipitation location in the analysis and significantly improves forecasts for lead times up to 4 h, as quantified by the Brier Score and the Continuous Ranked Probability Score. The influence of different update rates on the noise in terms of surface pressure tendencies and on the forecast quality in general is investigated. The results suggest that, while high update rates produce better analyses, forecasts with lead times of above 1 h benefit from less frequent updates. For a period of seven consecutive days, assimilation of radar reflectivity based on the LETKF is compared to that of DWD's current operational radar assimilation scheme based on latent heat nudging (LHN). It is found that the LETKF competes with LHN, although it is still in an experimental phase
Equatorial superrotation in Held & Suarez-like flows with weak
  equator-to-pole surface temperature gradient

Equatorial superrotation under zonally-symmetric thermal forcing is
investigated in a setup close to that of the classic Held & Suarez (1994)
setup. In contrast to the behaviour in the classic setup, a transition to
equatorial superrotation occurs when the equator-to-pole surface equilibrium
entropy gradient is weakened. Two factors contribute to this transition: 1) the
reduction of breaking Rossby waves from the mid-latitude that decelerate the
equatorial flow and 2) the presence of barotropic instability in the equatorial
region, providing stirring to accelerate the equatorial flow. In the latter,
Kelvin waves excited by instability near the equator generate and maintain the
superrotation. However, the superrotation is unphysically enhanced if
simulations are under-resolved and/or over-dissipated.Comment: 15 pages, 14 figures, accepted for publication in QJRM