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  • Author or Editor: Andrea Borrelli x
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Andrea Alessandri
,
Andrea Borrelli
,
Silvio Gualdi
,
Enrico Scoccimarro
, and
Simona Masina

Abstract

This study investigates the predictability of tropical cyclone (TC) seasonal count anomalies using the Centro Euro-Mediterraneo per i Cambiamenti Climatici–Istituto Nazionale di Geofisica e Vulcanologia (CMCC-INGV) Seasonal Prediction System (SPS). To this aim, nine-member ensemble forecasts for the period 1992–2001 for two starting dates per year were performed. The skill in reproducing the observed TC counts has been evaluated after the application of a TC location and tracking detection method to the retrospective forecasts. The SPS displays good skill in predicting the observed TC count anomalies, particularly over the tropical Pacific and Atlantic Oceans. The simulated TC activity exhibits realistic geographical distribution and interannual variability, thus indicating that the model is able to reproduce the major basic mechanisms that link the TCs’ occurrence with the large-scale circulation. TC count anomalies prediction has been found to be sensitive to the subsurface assimilation in the ocean for initialization. Comparing the results with control simulations performed without assimilated initial conditions, the results indicate that the assimilation significantly improves the prediction of the TC count anomalies over the eastern North Pacific Ocean (ENP) and northern Indian Ocean (NI) during boreal summer. During the austral counterpart, significant progresses over the area surrounding Australia (AUS) and in terms of the probabilistic quality of the predictions also over the southern Indian Ocean (SI) were evidenced. The analysis shows that the improvement in the prediction of anomalous TC counts follows the enhancement in forecasting daily anomalies in sea surface temperature due to subsurface ocean initialization. Furthermore, the skill changes appear to be in part related to forecast differences in convective available potential energy (CAPE) over the ENP and the North Atlantic Ocean (ATL), in wind shear over the NI, and in both CAPE and wind shear over the SI.

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Stefano Materia
,
Andrea Borrelli
,
Alessio Bellucci
,
Andrea Alessandri
,
Pierluigi Di Pietro
,
Panagiotis Athanasiadis
,
Antonio Navarra
, and
Silvio Gualdi

Abstract

The impact of land surface and atmosphere initialization on the forecast skill of a seasonal prediction system is investigated, and an effort to disentangle the role played by the individual components to the global predictability is done, via a hierarchy of seasonal forecast experiments performed under different initialization strategies. A realistic atmospheric initial state allows an improved equilibrium between the ocean and overlying atmosphere, increasing the model predictive skill in the ocean. In fact, in regions characterized by strong air–sea coupling, the atmosphere initial condition affects forecast skill for several months. In particular, the ENSO region, eastern tropical Atlantic, and North Pacific benefit significantly from the atmosphere initialization. On the mainland, the effect of atmospheric initial conditions is detected in the early phase of the forecast, while the quality of land surface initialization affects forecast skill in the following seasons. Winter forecasts in the high-latitude plains benefit from the snow initialization, while the impact of soil moisture initial state is particularly effective in the Mediterranean region and central Asia.

However, the initialization strategy based on the full value technique may not be the best choice for land surface, since soil moisture is a strongly model-dependent variable: in fact, initialization through land surface reanalysis does not systematically guarantee a skill improvement. Nonetheless, using a different initialization strategy for land, as opposed to atmosphere and ocean, may generate inconsistencies. Overall, the introduction of a realistic initialization for land and atmosphere substantially increases skill and accuracy. However, further developments in the procedure for land surface initialization are required for more accurate seasonal forecasts.

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Panos J. Athanasiadis
,
Alessio Bellucci
,
Leon Hermanson
,
Adam A. Scaife
,
Craig MacLachlan
,
Alberto Arribas
,
Stefano Materia
,
Andrea Borrelli
, and
Silvio Gualdi

Abstract

Primarily as a response to boundary forcings, certain components of the atmospheric intraseasonal variability are potentially predictable. Particularly referring to the extratropics, the current generation of seasonal forecasting systems is making advancements in predicting these components by realistically initializing many components of the climate system, using higher resolution and utilizing large ensemble sizes.

The operational seasonal prediction system of the Met Office (UKMO) and the corresponding system of the Centro Euro-Mediterraneo sui Cambiamenti Climatici (CMCC) are analyzed in terms of their representation of different aspects of extratropical low-frequency variability. The UKMO system achieves unprecedented high scores in predicting the winter mean phase of the North Atlantic Oscillation (NAO; correlation 0.62) and the Pacific–North American pattern (PNA; correlation 0.82). The CMCC system, despite its smaller ensemble size and coarser resolution, also exhibits significant skill (0.42 for NAO, 0.51 for PNA). Low-frequency variability is underrepresented in both models, particularly in the eastern North Atlantic. Consequently, their intrinsic variability patterns (sectoral EOFs) are somewhat different from the observed patterns.

Regarding the representation of wintertime Northern Hemisphere blocking, after bias correction both systems exhibit a realistic climatology of blocking frequency. In this assessment, instantaneous blocking and large-scale persistent blocking events are identified using daily geopotential height fields at 500 hPa. The blocking signature on the circulation and the dependence of blocking frequency on the NAO are also quite realistic for both systems. Finally, the Met Office system exhibits significant skill in predicting the winter mean frequency of blocking that relates to the NAO.

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Panos J. Athanasiadis
,
Alessio Bellucci
,
Adam A. Scaife
,
Leon Hermanson
,
Stefano Materia
,
Antonella Sanna
,
Andrea Borrelli
,
Craig MacLachlan
, and
Silvio Gualdi

Abstract

Significant predictive skill for the mean winter North Atlantic Oscillation (NAO) and Arctic Oscillation (AO) has been recently reported for a number of different seasonal forecasting systems. These findings are important in exploring the predictability of the natural system, but they are also important from a socioeconomic point of view, since the ability to predict the wintertime atmospheric circulation anomalies over the North Atlantic well ahead in time will have significant benefits for North American and European countries.

In contrast to the tropics, for the mid latitudes the predictive skill of many forecasting systems at the seasonal time scale has been shown to be low to moderate. The recent findings are promising in this regard, suggesting that better forecasts are possible, provided that key components of the climate system are initialized realistically and the coupled models are able to simulate adequately the dominant processes and teleconnections associated with low-frequency variability. It is shown that a multisystem approach has unprecedented high predictive skill for the NAO and AO, probably largely due to increasing the ensemble size and partly due to increasing model diversity.

Predicting successfully the winter mean NAO does not ensure that the respective climate anomalies are also well predicted. The NAO has a strong impact on Europe and North America, yet it only explains part of the interannual and low-frequency variability over these areas. Here it is shown with a number of different diagnostics that the high predictive skill for the NAO/AO indeed translates to more accurate predictions of temperature, surface pressure, and precipitation in the areas of influence of this teleconnection.

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