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Now showing 1 - 5 of 5
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    Consecutive extreme flooding and heat wave in Japan: Are they becoming a norm?
    (Hoboken, NJ : Wiley, 2019) Wang, Simon S.-Y.; Kim, Hyungjun; Coumou, Dim; Yoon, Jin-Ho; Zhao, Lin; Gillies, Robert R.
    [No abstract available]
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    Tropical and mid-latitude teleconnections interacting with the Indian summer monsoon rainfall: a theory-guided causal effect network approach
    (Göttingen : Copernicus Publ., 2020) Di Capua, Giorgia; Kretschmer, Marlene; Donner, Reik V.; van den Hurk, Bart; Vellore, Ramesh; Krishnan, Raghavan; Coumou, Dim
    The alternation of active and break phases in Indian summer monsoon (ISM) rainfall at intraseasonal timescales characterizes each ISM season. Both tropical and mid-latitude drivers influence this intraseasonal ISM variability. The circumglobal teleconnection observed in boreal summer drives intraseasonal variability across the mid-latitudes, and a two-way interaction between the ISM and the circumglobal teleconnection pattern has been hypothesized. We use causal discovery algorithms to test the ISM circumglobal teleconnection hypothesis in a causal framework. A robust causal link from the circumglobal teleconnection pattern and the North Atlantic region to ISM rainfall is identified, and we estimate the normalized causal effect (CE) of this link to be about 0.2 (a 1 standard deviation shift in the circumglobal teleconnection causes a 0.2 standard deviation shift in the ISM rainfall 1 week later). The ISM rainfall feeds back on the circumglobal teleconnection pattern, however weakly. Moreover, we identify a negative feedback between strong updraft located over India and the Bay of Bengal and the ISM rainfall acting at a biweekly timescale, with enhanced ISM rainfall following strong updraft by 1 week. This mechanism is possibly related to the boreal summer intraseasonal oscillation. The updraft has the strongest CE of 0.5, while the Madden–Julian oscillation variability has a CE of 0.2–0.3. Our results show that most of the ISM variability on weekly timescales comes from these tropical drivers, though the mid-latitude teleconnection also exerts a substantial influence. Identifying these local and remote drivers paves the way for improved subseasonal forecasts.
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    Meridionally Extending Anomalous Wave Train over Asia During Breaks in the Indian Summer Monsoon
    ([Cham] : Springer International Publishing, 2019) Umakanth, Uppara; Vellore, Ramesh K.; Krishnan, R.; Choudhury, Ayantika Dey; Bisht, Jagat S.H.; Di Capua, Giorgia; Coumou, Dim; Donner, Reik V.
    Anomalous interactions between the Indian summer monsoon (ISM) circulation and subtropical westerlies are known to trigger breaks in the ISM on subseasonal time-scales, characterised by a pattern of suppressed rainfall over central-north India, and enhanced rainfall over the foothills of the central–eastern Himalayas (CEH). An intriguing feature during ISM breaks is the formation of a mid-tropospheric cyclonic circulation anomaly extending over the subtropical and mid-latitude areas of the Asian continent. This study investigates the mechanism of the aforesaid Asian continental mid-tropospheric cyclonic circulation (ACMCC) anomaly using observations and simplified model experiments. The results of our study indicate that the ACMCC during ISM breaks is part of a larger meridional wave train comprising of alternating anticyclonic and cyclonic anomalies that extend poleward from the monsoon region to the Arctic. A lead–lag analysis of mid-tropospheric circulation anomalies suggests that the meridional wave-train generation is linked to latent heating (LH) anomalies over the CEH foothills, Indo-China, and the Indian landmass during ISM breaks. By conducting sensitivity experiments using a simplified global atmospheric general circulation model forced with satellite-derived three-dimensional LH, it is demonstrated that the combined effects of the enhanced LH over the CEH foothills and Indo-China and decreased LH over the Indian landmass during ISM breaks are pivotal for generating the poleward extending meridional wave train and the ACMCC anomaly. At the same time, the spatial extent of the mid-latitude cyclonic anomaly over Far-East Asia is also influenced by the anomalous LH over central–eastern China. While the present findings provide interesting insights into the role of LH anomalies during ISM breaks on the poleward extending meridional wave train, the ACMCC anomaly is found to have important ramifications on the daily rainfall extremes over the Indo-China region. It is revealed from the present analysis that the frequency of extreme rainfall occurrences over Indo-China shows a twofold increase during ISM break periods as compared to active ISM conditions. © 2019, The Author(s).
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    Assessing changes in risk of amplified planetary waves in a warming world
    (Hoboken, NJ : Wiley, 2019) Huntingford, Chris; Mitchell, Dann; Kornhuber, Kai; Coumou, Dim; Osprey, Scott; Allen, Myles
    Summer weather extremes are often associated with high-amplitude atmospheric planetary waves (Petoukhov et al., 2013). Such conditions lead to stationary weather patterns, triggering heat waves and sometimes prolonged intense rainfall. These wave events, referred to as periods of Quasi-Resonant Amplification (QRA), are relatively rare though and hence provide only a few data points in the meteorological record to analyse. Here, we use atmospheric models coupled to boundary conditions that have evolved slowly (i.e., climate), to supplement measurements. Specifically we assess altered probabilities of resonant episodes by employing a unique massive ensemble of atmosphere-only climate simulations to populate statistical distributions of event occurrence. We focus on amplified waves during the two most extreme European heat waves on record, in years 2003 and 2015 (Russo et al., 2015). These years are compared with other modelled recent years (1987–2011), and critically against a modelled world without climate change. We find that there are differences in the statistical characteristics of wave event likelihood between years, suggesting a strong dependence on the known and prescribed Sea Surface Temperature (SST) patterns. The differences are larger than those projected to have occurred under climate change since the pre-industrial period. However, this feature of small differences since pre-industrial is based on single large ensembles, with members consisting of a range of estimates of SST adjustment from pre-industrial to present. Such SST changes are from projections by a set of coupled atmosphere–ocean (AOGCM) climate models. When instead an ensemble for pre-industrial estimates is subdivided into simulations according to which AOGCM the SST changes are based on, we find differences in QRA occurrence. These differences suggest that to reliably estimate changes to extremes associated with altered amplification of planetary waves, and under future raised greenhouse gas concentrations, likely requires reductions in any spread of future modelled SST patterns. © 2019 The Authors. Atmospheric Science Letters published by John Wiley & Sons Ltd on behalf of the Royal Meteorological Society.
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    The influence of aggregation and statistical post‐processing on the subseasonal predictability of European temperatures
    (Weinheim [u.a.] : Wiley, 2020) Straaten, Chiem; Whan, Kirien; Coumou, Dim; Hurk, Bart; Schmeits, Maurice
    The succession of European surface weather patterns has limited predictability because disturbances quickly transfer to the large-scale flow. Some aggregated statistics, however, such as the average temperature exceeding a threshold, can have extended predictability when adequate spatial scales, temporal scales and thresholds are chosen. This study benchmarks how the forecast skill horizon of probabilistic 2-m temperature forecasts from the subseasonal forecast system of the European Centre for Medium-Range Weather Forecasts (ECMWF) evolves with varying scales and thresholds. We apply temporal aggregation by rolling-window averaging and spatial aggregation by hierarchical clustering. We verify 20 years of re-forecasts against the E-OBS dataset and find that European predictability extends at maximum into the fourth week. Simple aggregation and standard statistical post-processing extend the forecast skill horizon with two and three skilful days on average, respectively. The intuitive notion that higher levels of aggregation capture large-scale and low-frequency variability and can therefore tap into extended predictability holds in many cases. However, we show that the effect can be saturated and that there exist regional optimums beyond which extra aggregation reduces the forecast skill horizon. We expect such windows of predictability to result from specific physical mechanisms that only modulate and extend predictability locally. To optimize subseasonal forecasts for Europe, aggregation should thus be limited in certain cases.