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Alvaro de la Cámara
,
François Lott
,
Valérian Jewtoukoff
,
Riwal Plougonven
, and
Albert Hertzog

Abstract

The austral stratospheric final warming date is often predicted with substantial delay in several climate models. This systematic error is generally attributed to insufficient parameterized gravity wave (GW) drag in the stratosphere around 60°S. A simulation with a general circulation model [Laboratoire de Météorologie Dynamique zoom model (LMDZ)] with a much less pronounced bias is used to analyze the contribution of the different types of waves to the dynamics of the final warming. For this purpose, the resolved and unresolved wave forcing of the middle atmosphere during the austral spring are examined in LMDZ and reanalysis data, and a good agreement is found between the two datasets. The role of parameterized orographic and nonorographic GWs in LMDZ is further examined, and it is found that orographic and nonorographic GWs contribute evenly to the GW forcing in the stratosphere, unlike in other climate models, where orographic GWs are the main contributor. This result is shown to be in good agreement with GW-resolving operational analysis products. It is demonstrated that the significant contribution of the nonorographic GWs is due to highly intermittent momentum fluxes produced by the source-related parameterizations used in LMDZ, in qualitative agreement with recent observations. This yields sporadic high-amplitude GWs that break in the stratosphere and force the circulation at lower altitudes than more homogeneously distributed nonorographic GW parameterizations do.

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Riwal Plougonven
,
Valérian Jewtoukoff
,
Alvaro de la Cámara
,
François Lott
, and
Albert Hertzog

Abstract

The relationship between gravity wave momentum fluxes and local wind speed is investigated for oceanic regions at high southern latitudes during austral spring. The motivation is to better describe the gravity wave field by identifying a simple relationship between gravity waves and the large-scale flow. The tools used to describe the gravity waves are probability density functions of the gravity wave momentum fluxes. Three independent datasets covering high latitudes in the Southern Hemisphere springtime are analyzed: simulations with a mesoscale model, analyses from the European Centre for Medium-Range Weather Forecasts, and observations from superpressure balloons of the Concordiasi campaign in 2010. A remarkably robust relation is found, with stronger momentum fluxes much more likely in regions of strong winds. The tails of the probability density functions are well described as lognormal. The median momentum flux increases linearly with background wind speed: for winds stronger than 50 m s−1, the median gravity wave momentum fluxes are about 4 times larger than for winds weaker than 10 m s−1. From model output, this relation is found to be relevant from the tropopause to the midstratosphere at least. The flux dependence on wind speed shows a somewhat steeper slope at higher altitude. Several different processes contribute to this relation, involving both the distribution of sources and the effects of propagation and filtering. It is argued that the location of tropospheric sources is the main contributor in the upper troposphere and lowermost stratosphere and that lateral propagation into regions of strong winds becomes increasingly important above.

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Naveen Goutham
,
Riwal Plougonven
,
Hiba Omrani
,
Alexis Tantet
,
Sylvie Parey
,
Peter Tankov
,
Peter Hitchcock
, and
Philippe Drobinski

Abstract

Owing to the increasing share of variable renewable energies in the electricity mix, the European energy sector is becoming more weather sensitive. In this regard, skillful subseasonal predictions of essential climate variables can provide considerable socioeconomic benefits to the energy sector. The aim of this study is therefore to improve the European subseasonal predictions of 100-m wind speed and 2-m temperature, which we achieve through statistical downscaling. We employ redundancy analysis (RDA) to estimate spatial patterns of variability from large-scale fields that allow for the best prediction of surface fields. We compare explanatory powers between the patterns obtained using RDA against those derived using principal component analysis (PCA), when used as predictors in multilinear regression models to predict surface fields, and show that the explanatory power of the former is superior to that of the latter. Subsequently, we employ the estimated relationship between RDA patterns and surface fields to produce statistical probabilistic predictions of gridded surface fields using dynamical ensemble predictions of RDA patterns. We finally demonstrate how a simple combination of dynamical and statistical predictions of surface fields significantly improves the accuracy of subseasonal predictions of both variables over a large part of Europe. We attribute the improved accuracy of these combined predictions to improvements in reliability and resolution.

Open access
Naveen Goutham
,
Riwal Plougonven
,
Hiba Omrani
,
Sylvie Parey
,
Peter Tankov
,
Alexis Tantet
,
Peter Hitchcock
, and
Philippe Drobinski

Abstract

Subseasonal forecasts of 100-m wind speed and surface temperature, if skillful, can be beneficial to the energy sector as they can be used to plan asset availability and maintenance, assess risks of extreme events, and optimally trade power on the markets. In this study, we evaluate the skill of the European Centre for Medium-Range Weather Forecasts’ subseasonal predictions of 100-m wind speed and 2-m temperature. To the authors’ knowledge, this assessment is the first for the 100-m wind speed, which is an essential variable of practical importance to the energy sector. The assessment is carried out on both forecasts and reforecasts over European domain gridpoint wise and also by considering several spatially averaged domains, using several metrics to assess different attributes of forecast quality. We propose a novel way of synthesizing the continuous ranked probability skill score. The results show that the skill of the forecasts and reforecasts depends on the choice of the climate variable, the period of the year, and the geographical domain. Indeed, the predictions of temperature are better than those of wind speed, with enhanced skill found for both variables in the winter relative to other seasons. The results also indicate significant differences between the skill of forecasts and reforecasts, arising mainly due to the differing ensemble sizes. Overall, depending on the choice of the geographical domain and the forecast attribute, the results show skillful predictions beyond 2 weeks, and in certain cases, up to 6 weeks for both variables, thereby encouraging their implementation in operational decision-making.

Open access
Aurélien Podglajen
,
T. Paul Bui
,
Jonathan M. Dean-Day
,
Leonhard Pfister
,
Eric J. Jensen
,
M. Joan Alexander
,
Albert Hertzog
,
Bernd Kärcher
,
Riwal Plougonven
, and
William J. Randel

Abstract

The contribution of turbulent mixing to heat and tracer transport in the tropical tropopause layer (TTL) is poorly constrained, partly owing to a lack of direct observations. Here, the authors use high-resolution (20 Hz) airborne measurements to study the occurrence and properties of small-scale (<100 m) wind fluctuations in the TTL (14–19 km) over the tropical Pacific. The fluctuations are highly intermittent and appear localized within shallow (100 m) patches. Furthermore, active turbulent events are more frequent at low altitude, near deep convection, and within layers of low gradient Richardson number. A case study emphasizes the link between the turbulent events and the occurrence of inertio-gravity waves having small horizontal or vertical scale. To evaluate the impact of the observed fluctuations on tracer mixing, their characteristics are examined. During active events, they are in broad agreement with inertial-range turbulence theory: the motions are close to 3D isotropic and the spectra follow a −5/3 power-law scaling. The diffusivity induced by turbulent bursts is estimated to be on the order of 10−1 m2 s−1 and increases from the top to the bottom of the TTL (from ~2 × 10−2 to ~3 × 10−1 m2 s−1). Given the uncertainties involved in the estimate, this is in reasonable agreement (about a factor of 3–4 lower) with the parameterized turbulent diffusivity in ERA-Interim, but it disagrees with other observational estimates from radar and radiosondes. The magnitude of the consequent vertical transport depends on the altitude and the tracer; for the species considered, it is generally smaller than that induced by the mean tropical upwelling.

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Ulrich Achatz
,
M. Joan Alexander
,
Erich Becker
,
Hye-Yeong Chun
,
Andreas Dörnbrack
,
Laura Holt
,
Riwal Plougonven
,
Inna Polichtchouk
,
Kaoru Sato
,
Aditi Sheshadri
,
Claudia Christine Stephan
,
Annelize van Niekerk
, and
Corwin J. Wright

Abstract

Atmospheric predictability from subseasonal to seasonal time scales and climate variability are both influenced critically by gravity waves (GW). The quality of regional and global numerical models relies on thorough understanding of GW dynamics and its interplay with chemistry, precipitation, clouds, and climate across many scales. For the foreseeable future, GWs and many other relevant processes will remain partly unresolved, and models will continue to rely on parameterizations. Recent model intercomparisons and studies show that present-day GW parameterizations do not accurately represent GW processes. These shortcomings introduce uncertainties, among others, in predicting the effects of climate change on important modes of variability. However, the last decade has produced new data and advances in theoretical and numerical developments that promise to improve the situation. This review gives a survey of these developments, discusses the present status of GW parameterizations, and formulates recommendations on how to proceed from there.

Open access
Christopher G. Kruse
,
M. Joan Alexander
,
Lars Hoffmann
,
Annelize van Niekerk
,
Inna Polichtchouk
,
Julio T. Bacmeister
,
Laura Holt
,
Riwal Plougonven
,
Petr Šácha
,
Corwin Wright
,
Kaoru Sato
,
Ryosuke Shibuya
,
Sonja Gisinger
,
Manfred Ern
,
Catrin I. Meyer
, and
Olaf Stein

Abstract

Four state-of-the-science numerical weather prediction (NWP) models were used to perform mountain wave (MW)-resolving hindcasts over the Drake Passage of a 10-day period in 2010 with numerous observed MW cases. The Integrated Forecast System (IFS) and the Icosahedral Nonhydrostatic (ICON) model were run at Δx ≈ 9 and 13 km globally. The Weather Research and Forecasting (WRF) Model and the Met Office Unified Model (UM) were both configured with a Δx = 3-km regional domain. All domains had tops near 1 Pa (z ≈ 80 km). These deep domains allowed quantitative validation against Atmospheric Infrared Sounder (AIRS) observations, accounting for observation time, viewing geometry, and radiative transfer. All models reproduced observed middle-atmosphere MWs with remarkable skill. Increased horizontal resolution improved validations. Still, all models underrepresented observed MW amplitudes, even after accounting for model effective resolution and instrument noise, suggesting even at Δx ≈ 3-km resolution, small-scale MWs are underresolved and/or overdiffused. MW drag parameterizations are still necessary in NWP models at current operational resolutions of Δx ≈ 10 km. Upper GW sponge layers in the operationally configured models significantly, artificially reduced MW amplitudes in the upper stratosphere and mesosphere. In the IFS, parameterized GW drags partly compensated this deficiency, but still, total drags were ≈6 times smaller than that resolved at Δx ≈ 3 km. Meridionally propagating MWs significantly enhance zonal drag over the Drake Passage. Interestingly, drag associated with meridional fluxes of zonal momentum (i.e., u υ ¯ ) were important; not accounting for these terms results in a drag in the wrong direction at and below the polar night jet.

Significance Statement

This study had three purposes: to quantitatively evaluate how well four state-of-the-science weather models could reproduce observed mountain waves (MWs) in the middle atmosphere, to compare the simulated MWs within the models, and to quantitatively evaluate two MW parameterizations in a widely used climate model. These models reproduced observed MWs with remarkable skill. Still, MW parameterizations are necessary in current Δx ≈ 10-km resolution global weather models. Even Δx ≈ 3-km resolution does not appear to be high enough to represent all momentum-fluxing MW scales. Meridionally propagating MWs can significantly influence zonal winds over the Drake Passage. Parameterizations that handle horizontal propagation may need to consider horizontal fluxes of horizontal momentum in order to get the direction of their forcing correct.

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