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Validation of boreal summer tropical–extratropical causal links in seasonal forecasts

Urheber*innen
/persons/resource/dicapua

Di Capua,  Giorgia
Potsdam Institute for Climate Impact Research;

/persons/resource/coumou

Coumou,  Dim
Potsdam Institute for Climate Impact Research;

van den Hurk,  Bart
External Organizations;

Weisheimer,  Antje
External Organizations;

Turner,  Andrew G.
External Organizations;

/persons/resource/Reik.Donner

Donner,  Reik V.
Potsdam Institute for Climate Impact Research;

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29192oa.pdf
(Verlagsversion), 11MB

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Zitation

Di Capua, G., Coumou, D., van den Hurk, B., Weisheimer, A., Turner, A. G., Donner, R. V. (2023): Validation of boreal summer tropical–extratropical causal links in seasonal forecasts. - Weather and Climate Dynamics, 4, 3, 701-723.
https://doi.org/10.5194/wcd-4-701-2023


Zitierlink: https://publications.pik-potsdam.de/pubman/item/item_29192
Zusammenfassung
Much of the forecast skill in the mid-latitudes on seasonal timescales originates from deep convection in the tropical belt. For boreal summer, such tropical–extratropical teleconnections are less well understood compared to winter. Here we validate the representation of boreal summer tropical–extratropical teleconnections in a general circulation model in comparison with observational data. To characterise variability between tropical convective activity and mid-latitude circulation, we identify the South Asian monsoon (SAM)–circumglobal teleconnection (CGT) pattern and the western North Pacific summer monsoon (WNPSM)–North Pacific high (NPH) pairs as the leading modes of tropical–extratropical coupled variability in both reanalysis (ERA5) and seasonal forecast (SEAS5) data. We calculate causal maps based on the Peter and Clark momentary conditional independence (PCMCI) causal discovery algorithm, which identifies causal links in a 2D field, to show the causal effect of each of these patterns on circulation and convection in the Northern Hemisphere. The spatial patterns and signs of the causal links in SEAS5 closely resemble those seen in ERA5, independent of the initialisation date of SEAS5. By performing a subsampling experiment (over time), we analyse the strengths of causal links in SEAS5 and show that they are qualitatively weaker than those in ERA5. We identify those regions for which SEAS5 data well reproduce ERA5 values, e.g. the southeastern USA, and highlight those where the bias is more prominent, e.g. North Africa and in general tropical regions. We demonstrate that different El Niño–Southern Oscillation phases have only a marginal effect on the strength of these links. Finally, we discuss the potential role of model mean-state biases in explaining differences between SEAS5 and ERA5 causal links.