Multi-model assessment of the late-winter extra-tropical response to El Niño and La Niña

El Niño-Southern Oscillation (ENSO) is known to affect the Northern Hemisphere tropospheric circulation in late-winter (January-March), but whether El Niño and La Niña lead to symmetric impacts and with the same underlying dynamics remains unclear, particularly in the North Atlantic. Three state-of-the-art atmospheric models forced by symmetric anomalous sea surface temperature (SST) patterns, mimicking strong ENSO events, are used to robustly diagnose symmetries and asymmetries in the extra-tropical ENSO response. Asymmetries arise in the sea-level pressure (SLP) response over the North Pacific and North Atlantic, as the response to La Niña tends to be weaker and shifted westward with respect to that of El Niño. The difference in amplitude can be traced back to the distinct energy available for the two ENSO phases associated with the non-linear diabatic heating response to the total SST field. The longitudinal shift is embedded into the large-scale Rossby wave train triggered from the tropical Pacific, as its anomalies in the upper troposphere show a similar westward displacement in La Niña compared to El Niño. To fully explain this shift, the response in tropical convection and the related anomalous upper-level divergence have to be considered together with the climatological vorticity gradient of the subtropical jet, i.e. diagnosing the tropical Rossby wave source. In the North Atlantic, the ENSO-forced SLP signal is a well-known dipole between middle and high latitudes, different from the North Atlantic Oscillation, whose asymmetry is not indicative of distinct mechanisms driving the teleconnection for El Niño and La Niña

Multi-model assessment of the impact of soil moisture initialization on mid-latitude summer predictability

Land surface initial conditions have been recognized as a potential source of predictability in sub-seasonal to seasonal forecast systems, at least for near-surface air temperature prediction over the mid-latitude continents. Yet, few studies have systematically explored such an influence over a sufficient hindcast period and in a multi-model framework to produce a robust quantitative assessment. Here, a dedicated set of twin experiments has been carried out with boreal summer retrospective forecasts over the 1992–2010 period performed by five different global coupled ocean–atmosphere models. The impact of a realistic versus climatological soil moisture initialization is assessed in two regions with high potential previously identified as hotspots of land–atmosphere coupling, namely the North American Great Plains and South-Eastern Europe. Over the latter region, temperature predictions show a significant improvement, especially over the Balkans. Forecast systems better simulate the warmest summers if they follow pronounced dry initial anomalies. It is hypothesized that models manage to capture a positive feedback between high temperature and low soil moisture content prone to dominate over other processes during the warmest summers in this region. Over the Great Plains, however, improving the soil moisture initialization does not lead to any robust gain of forecast quality for near-surface temperature. It is suggested that models biases prevent the forecast systems from making the most of the improved initial conditions.The authors thank Jeff Knight (Met Office Hadley Centre) for his constructive comments on earlier versions of this manuscript. The research leading to these results received funding from the European Union Seventh Framework Programme (FP7/2007–2013) SPECS project (Grant Agreement Number 308378) and H2020 Framework Programme IMPREX project (Grant Agreement Number 641811). Constantin Ardilouze was also supported by the BSC Centro de Excelencia Severo Ochoa Programme.Peer ReviewedPostprint (author's final draft

Current and emerging developments in subseasonal to decadal prediction

Weather and climate variations of subseasonal to decadal timescales can have enormous social, economic and environmental impacts, making skillful predictions on these timescales a valuable tool for decision makers. As such, there is a growing interest in the scientific, operational and applications communities in developing forecasts to improve our foreknowledge of extreme events. On subseasonal to seasonal (S2S) timescales, these include high-impact meteorological events such as tropical cyclones, extratropical storms, floods, droughts, and heat and cold waves. On seasonal to decadal (S2D) timescales, while the focus remains broadly similar (e.g., on precipitation, surface and upper ocean temperatures and their effects on the probabilities of high-impact meteorological events), understanding the roles of internal and externally-forced variability such as anthropogenic warming in forecasts also becomes important. The S2S and S2D communities share common scientific and technical challenges. These include forecast initialization and ensemble generation; initialization shock and drift; understanding the onset of model systematic errors; bias correct, calibration and forecast quality assessment; model resolution; atmosphere-ocean coupling; sources and expectations for predictability; and linking research, operational forecasting, and end user needs. In September 2018 a coordinated pair of international conferences, framed by the above challenges, was organized jointly by the World Climate Research Programme (WCRP) and the World Weather Research Prograame (WWRP). These conferences surveyed the state of S2S and S2D prediction, ongoing research, and future needs, providing an ideal basis for synthesizing current and emerging developments in these areas that promise to enhance future operational services. This article provides such a synthesis

Impact of soil moisture on summer climate predictability over mid-latitudes

Les épisodes de sécheresse et de canicule qui frappent épisodiquement les régions tempérées ont des conséquences préjudiciables sur les plans sanitaire, économique, social et écologique. Afin de pouvoir enclencher des stratégies de préparation et de prévention avec quelques semaines ou mois d'anticipation, les attentes sociétales en matière de prévision sont élevées, et ce d'autant plus que les projections climatiques font craindre la multiplication de ces épisodes au cours du 21ème siècle. Néanmoins, la saison d'été est la plus difficile à prévoir aux moyennes latitudes. Les sources connues de prévisibilité sont plus ténues qu'en hiver et les systèmes de prévision climatique actuels peinent à représenter correctement les mécanismes de téléconnexion associés. Un nombre croissant d'études a mis en évidence un lien statistique dans certaines régions entre l'humidité du sol au printemps et les températures et précipitations de l'été qui suit. Ce lien a été partiellement confirmé dans des modèles numériques de climat mais de nombreuses interrogations subsistent. L'objectif de cette thèse est donc de mieux comprendre le rôle joué par l'humidité du sol sur les caractéristiques et la prévisibilité du climat de l'été dans les régions tempérées. Grâce notamment au modèle couplé de circulation générale CNRM-CM, nous avons mis en œuvre des ensembles de simulations numériques qui nous ont permis d'évaluer le degré de persistance des anomalies d'humidité du sol printanière. En effet, une longue persistance est une condition nécessaire pour que ces anomalies influencent le climat à l'échelle de la saison, via le processus d'évapotranspiration de la surface. En imposant dans notre modèle des conditions initiales et aux limitées idéalisées d'humidité du sol, nous avons mis en évidence des régions du globe pour lesquelles l'état moyen et la variabilité des températures et des précipitations en été sont particulièrement sensibles à ces conditions. C'est notamment le cas sur une grande partie de l'Europe et de l'Amérique du nord, y compris à des latitudes élevées. Pour toutes ces régions, l'humidité du sol est une source prometteuse de prévisibilité potentielle du climat à l'horizon saisonnier, bien que de fortes incertitudes demeurent localement sur le degré de persistance de ses anomalies. Une expérience de prévisibilité effective coordonnée avec plusieurs systèmes de prévision montre qu'une initialisation réaliste de l'humidité du sol améliore la prévision de températures estivales principalement dans le sud-est de l'Europe. Dans d'autres régions, comme l'Europe du Nord, le désaccord des modèles provient de l'incertitude sur la persistance des anomalies d'humidité du sol. En revanche, sur les Grandes Plaines américaines, aucun modèle n'améliore ses prévisions qui restent donc très médiocres. La littérature ainsi que nos évaluations de sensibilité du climat à l'humidité du sol ont pourtant identifié cette région comme un "hotspot" du couplage entre l'humidité du sol et l'atmosphère. Nous supposons que l'échec de ces prévisions est une conséquence des forts biais chauds et secs présents dans tous les modèles sur cette région en été, qui conduisent à un dessèchement excessif des sols. Pour le vérifier, nous avons développé une méthode qui corrige ces biais au cours de l'intégration des prévisions avec CNRM-CM6. Les prévisions qui en résultent sont nettement améliorées sur les Grandes Plaines. La compréhension de l'origine des biais continentaux en été et leur réduction dans les prochaines générations de modèles de climat sont des étapes essentielles pour tirer le meilleur parti de l'humidité du sol comme source de prévisibilité saisonnière dans les régions tempérées.Severe heat waves and droughts that episodically hit temperate regions have detrimental consequences on health, economy and society. The design and deployment of efficient preparedness strategies foster high expectations for the prediction of such events a few weeks or months ahead. Their likely increased frequency throughout the 21st century, as envisaged by climate projections, further emphasizes these expectations. Nevertheless, the summer season is the most difficult to predict over mid-latitudes. Well-known sources of predictability are weaker than in winter and current climate prediction systems struggle to adequately represent associated teleconnection mechanisms. An increasing number of studies have shown a statistical link over some regions between spring soil moisture and subsequent summer temperature and precipitation. This link has been partly confirmed in climate numerical models, but many questions remain. The purpose of this PhD thesis is to better understand the role played by soil moisture onthe characteristics and predictability of the summer climate in temperate regions. By means of the CNRM-CM coupled general circulation model, we have designed a range of numerical simulations which help us evaluate the persistence level of spring soil moisture anomalies. Indeed, a long persistence is a necessary condition for these anomalies to influence the climate at the seasonal scale, through the process of evapotranspiration. By imposing in our model idealized initial and boundary soil moisture conditions, we have highlighted areas of the globe for which the average state and the variability of temperatures and precipitation in summer is particularly sensitive to these conditions. This is the case in particular for Europe and North America, including over high latitudes. Soil moisture is therefore a promising source of potential seasonal climate predictability for these regions, although the persistence of soil moisture anomalies remains locally very uncertain. An effective predictability coordinated experiment, bringing together several prediction systems, shows that a realistic soil moisture initialization improves the forecast skill of summer temperatures mainly over southeast Europe. In other regions, such as Northern Europe, the disagreement between models comes from uncertainty about the persistence of soil moisture anomalies. On the other hand, over the American Great Plains, even the forecasts with improved soil moisture initialization remain unsuccessful. Yet, the literature as well as our assessment of climate sensitivity to soil moisture have identified this region as a "hotspot" of soil moisture - atmosphere coupling. We assume that the failure of these predictions relates to the strong hot and dry bias present in all models over this region in summer, which leads to excessive soil drying. To verify this assumption, we developed a method that corrects these biases during the forecast integration based on the CNRM-CM6 model. The resulting forecasts are significantly improved over the Great Plains. Understanding the origin of continental biases in the summer and reducing them in future generations of climate models are essential steps to making the most of soil moisture as a source of seasonal predictability in temperate region

Impact de l'humidité du sol sur la prévisibilité du climat estival aux moyennes latitudes

Severe heat waves and droughts that episodically hit temperate regions have detrimental consequences on health, economy and society. The design and deployment of efficient preparedness strategies foster high expectations for the prediction of such events a few weeks or months ahead. Their likely increased frequency throughout the 21st century, as envisaged by climate projections, further emphasizes these expectations. Nevertheless, the summer season is the most difficult to predict over mid-latitudes. Well-known sources of predictability are weaker than in winter and current climate prediction systems struggle to adequately represent associated teleconnection mechanisms. An increasing number of studies have shown a statistical link over some regions between spring soil moisture and subsequent summer temperature and precipitation. This link has been partly confirmed in climate numerical models, but many questions remain.The purpose of this PhD thesis is to better understand the role played by soil moisture on the characteristics and predictability of the summer climate in temperate regions. By means of the CNRM-CM coupled general circulation model, we have designed a range of numerical simulations which help us evaluate the persistence level of spring soil moisture anomalies. Indeed, a long persistence is a necessary condition for these anomalies to influence the climate at the seasonal scale, through the process of evapotranspiration. By imposing in our model idealized initial and boundary soil moisture conditions, we have highlighted areas of the globe for which the average state and the variability of temperatures and precipitation in summer is particularly sensitive to these conditions. This is the case in particular for Europe and North America, including over high latitudes. Soil moisture is therefore a promising source of potential seasonal climate predictability for these regions, although the persistence of soil moisture anomalies remains locally very uncertain.An effective predictability coordinated experiment, bringing together several prediction systems, shows that a realistic soil moisture initialization improves the forecast skill of summer temperatures mainly over southeast Europe. In other regions, such as Northern Europe, the disagreement between models comes from uncertainty about the persistence of soil moisture anomalies. On the other hand, over the American Great Plains, even the forecasts with improved soil moisture initialization remain unsuccessful. Yet, the literature as well as our assessment of climate sensitivity to soil moisture have identified this region as a "hotspot" of soil moisture - atmosphere coupling. We assume that the failure of these predictions relates to the strong hot and dry bias present in all models over this region in summer, which leads to excessive soil drying. To verify this assumption, we developed a method that corrects these biases during the forecast integration based on the CNRM-CM6 model. The resulting forecasts are significantly improved over the Great Plains. Understanding the origin of continental biases in the summer and reducing them in future generations of climate models are essential steps to making the most of soil moisture as a source of seasonal predictability in temperate regions.Les épisodes de sécheresse et de canicule qui frappent épisodiquement les régions tempérées ont des conséquences préjudiciables sur les plans sanitaire, économique, social et écologique. Afin de pouvoir enclencher des stratégies de préparation et de prévention avec quelques semaines ou mois d'anticipation, les attentes sociétales en matière de prévision sont élevées, et ce d'autant plus que les projections climatiques font craindre la multiplication de ces épisodes au cours du 21ème siècle. Néanmoins, la saison d'été est la plus difficile à prévoir aux moyennes latitudes. Les sources connues de prévisibilité sont plus ténues qu'en hiver et les systèmes de prévision climatique actuels peinent à représenter correctement les mécanismes de téléconnexion associés. Un nombre croissant d'études a mis en évidence un lien statistique dans certaines régions entre l'humidité du sol au printemps et les températures et précipitations de l'été qui suit. Ce lien a été partiellement confirmé dans des modèles numériques de climat mais de nombreuses interrogations subsistent.L'objectif de cette thèse est donc de mieux comprendre le rôle joué par l'humidité du sol sur les caractéristiques et la prévisibilité du climat de l'été dans les régions tempérées. Grâce notamment au modèle couplé de circulation générale CNRM-CM, nous avons mis en oeuvre des ensembles de simulations numériques qui nous ont permis d'évaluer le degré de persistance des anomalies d'humidité du sol printanière. En effet, une longue persistance est une condition nécessaire pour que ces anomalies influencent le climat à l'échelle de la saison, via le processus d'évapotranspiration de la surface. En imposant dans notre modèle des conditions initiales et aux limites idéalisées d'humidité du sol, nous avons mis en évidence des régions du globe pour lesquelles l'état moyen et la variabilité des températures et des précipitations en été sont particulièrement sensibles à ces conditions. C'est notamment le cas sur une grande partie de l'Europe et de l'Amérique du nord, y compris à des latitudes élevées. Pour toutes ces régions, l'humidité du sol est une source prometteuse de prévisibilité potentielle du climat à l'horizon saisonnier, bien que de fortes incertitudes demeurent localement sur le degré de persistance de ses anomalies.Une expérience de prévisibilité effective coordonnée avec plusieurs systèmes de prévision montre qu'une initialisation réaliste de l'humidité du sol améliore la prévision de températures estivales principalement dans le sud-est de l'Europe. Dans d'autres régions, comme l'Europe du Nord, le désaccord des modèles provient de l'incertitude sur la persistance des anomalies d'humidité du sol. En revanche, sur les Grandes Plaines américaines, aucun modèle n'améliore ses prévisions qui restent donc très médiocres. La littérature ainsi que nos évaluations de sensibilité du climat à l'humidité du sol ont pourtant identifié cette région comme un "hotspot" du couplage entre l'humidité du sol et l'atmosphère. Nous supposons que l'échec de ces prévisions est une conséquence des forts biais chauds et secs présents dans tous les modèles sur cette région en été, qui conduisent à un dessèchement excessif des sols. Pour le vérifier, nous avons développé une méthode qui corrige ces biais au cours de l'intégration des prévisions avec CNRM-CM6. Les prévisions qui en résultent sont nettement améliorées sur les Grandes Plaines. La compréhension de l'origine des biais continentaux en été et leur réduction dans les prochaines générations de modèles de climat sont des étapes essentielles pour tirer le meilleur parti de l'humidité du sol comme source de prévisibilité saisonnière dans les régions tempérées

Impact of initializing the soil with a thermally and hydrologically balanced state on subseasonal predictability

Accurate soil moisture initial conditions in dynamical subseasonal forecast systems are known to improve the temperature forecast skill regionally, through more realistic water and energy fluxes at the land-atmosphere interface. Recently, results from a multi-model coordinated experiment have provided evidence of the primal contribution of the initial surface and subsurface soil temperature over the Tibetan Plateau for capturing a hemispheric scale atmopsheric teleconnection leading to improved subseasonal forecasts. Yet, both the soil temperature and water content are key components of the soil enthalpy and we hypothesize that properly initializing one of them without modifying the other in a consistent manner can alter the soil thermal equilibrium, thereby potentially reducing the benefit of land initial conditions on subsequent atmospheric forecasts. This study builds on the protocol of the above-mentioned multi-model experiment, by testing three different land initialization strategies in an Earth system model. Results of this pilot study suggest that a better mass and energy balance in land initial conditions of the Tibetan Plateau triggers a wave train which propagates through the northern hemisphere mid-latitudes, resulting in an improved large scale circulation and temperature anomalies over multiple regions of the globe. While this study is based on a single case, it strongly advocates for enhanced attention towards preserving the soil energy equilibrium at initialization to make the most of land as a driver of atmospheric extended-range predictability

Impact of initializing the soil with a thermally and hydrologically balanced state on subseasonal predictability

Accurate soil moisture initial conditions in dynamical subseasonal forecast systems are known to improve the temperature forecast skill regionally, through more realistic water and energy fluxes at the land-atmosphere interface. Recently, results from a multi-model coordinated experiment have provided evidence of the primal contribution of the initial surface and subsurface soil temperature over the Tibetan Plateau for capturing a hemispheric scale atmopsheric teleconnection leading to improved subseasonal forecasts. Yet, both the soil temperature and water content are key components of the soil enthalpy and we hypothesize that properly initializing one of them without modifying the other in a consistent manner can alter the soil thermal equilibrium, thereby potentially reducing the benefit of land initial conditions on subsequent atmospheric forecasts. This study builds on the protocol of the above-mentioned multi-model experiment, by testing three different land initialization strategies in an Earth system model. Results of this pilot study suggest that a better mass and energy balance in land initial conditions of the Tibetan Plateau triggers a wave train which propagates through the northern hemisphere mid-latitudes, resulting in an improved large scale circulation and temperature anomalies over multiple regions of the globe. While this study is based on a single case, it strongly advocates for enhanced attention towards preserving the soil energy equilibrium at initialization to make the most of land as a driver of atmospheric extended-range predictability

Sub-chapter 3.4.4. Seasonal forecast of droughts and water resources

Introduction Forecasting the upcoming season is a fundamentally different scientific issue from forecasting the weather over the next few days. Due to the intrinsically chaotic nature of the atmosphere, the predictability of temperature, winds, precipitation or pressure systems is typically limited to 10 days. Seasonal forecasts therefore set out to provide an outlook on statistical averages of climatic variables at ranges from one month to a year, and rely on large-scale, more slowly-evolvin..

Flow dependence of wintertime subseasonal prediction skill over Europe

International audienceAbstract. Issuing skillful forecasts beyond the typical horizon of weather predictability remains a challenge actively addressed by the scientific community. This study evaluates winter subseasonal reforecasts delivered by the CNRM and ECMWF dynamical systems and identifies that the level of skill for predicting temperature in Europe varies fairly consistently in both systems. In particular, forecasts initialized during positive North Atlantic Oscillation (NAO) phases tend to be more skillful over Europe at week 3 in both systems. Composite analyses performed in an atmospheric reanalysis, a long-term climate simulation and both forecast systems unveil very similar temperature and sea-level pressure patterns 3 weeks after NAO conditions. Furthermore, regressing these fields onto the 3-weeks-prior NAO index in a reanalysis shows consistent patterns over Europe but also other regions of the Northern Hemisphere extratropics, thereby suggesting a lagged teleconnection, related to either the persistence or recurrence of the positive and negative phases of the NAO. This teleconnection, conditioned to the intensity of the initial NAO phase, is well captured by forecast systems. As a result, it is a key mechanism for determining a priori confidence in the skill of wintertime subseasonal forecasts over Europe as well as other parts of the Northern Hemisphere

Multimodel Forecasting of Precipitation at Subseasonal Timescales Over the Southwest Tropical Pacific

International audienc