Quantifying the role of the large-scale circulation on European summer precipitation change View Full Text


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Article Info

DATE

2022-03-29

AUTHORS

Hylke de Vries, Geert Lenderink, Karin van der Wiel, Erik van Meijgaard

ABSTRACT

Regional climate projections indicate that European summer precipitation may change considerably in the future. Southern Europe can expect substantial drying while Northern Europe could actually become wetter. Model spread and internal variability in these projections are large, however, and unravelling the processes that underlie the changes is essential to get more confidence in these projections. Large-scale circulation change is one of the contributors to model spread. In this paper we quantify the role of future large-scale circulation changes to summer precipitation change, using a 16-member single-model ensemble obtained with the regional climate model RACMO2, forced by the global climate model EC-Earth2.3 and the RCP8.5 emission scenario. Using the method of circulation analogues three contributions to the future precipitation change are distinguished. The first is the precipitation change occurring without circulation change (referred to as the thermodynamic term). This contribution is characterised by a marked drying-to-wetting gradient as one moves north from the Mediterranean. The second contribution measures the effects of changes in the mean circulation. It has a very different spatial pattern and is closely related to the development of a region of high pressure (attaining its maximum west of Ireland) and the associated anti-cyclonic circulation response. For a large area east of Ireland including parts of western Europe, it is the major contributor to the overall drying signal, locally explaining more than 90% of the ensemble-mean change. In regions where the patterns overlap, the signal-to-noise ratio of the total change is either enhanced or reduced depending on their relative signs. Although the second term is expected to be particularly model dependent, the high-pressure region west of Ireland also appears in CMIP5 and CMIP6 ensemble-mean projections. The third contribution records the effects of changes in the circulation variability. This term has the smallest net contribution, but a relatively large uncertainty. The analogues are very good in partitioning the ensemble-mean precipitation change, but describe only up to 40% of the ensemble-spread. This demonstrates that other precipitation-drivers (SST, spring soil moisture etc.) will generally strongly influence trends in single climate realisations. This also re-emphasises the need for large ensembles or using alternative methods like the Pseudo Global Warming approach where signal to noise ratios are higher. Nevertheless, identifying the change mechanisms helps to understand the future uncertainties and differences between models. More... »

PAGES

2871-2886

References to SciGraph publications

  • 2018-06-30. The Influence of Arctic Amplification on Mid-latitude Weather and Climate in CURRENT CLIMATE CHANGE REPORTS
  • 2012-05-30. SST and circulation trend biases cause an underestimation of European precipitation trends in CLIMATE DYNAMICS
  • 2021-01-15. Anthropogenic intensification of short-duration rainfall extremes in NATURE REVIEWS EARTH & ENVIRONMENT
  • 2011-08-09. The RCP greenhouse gas concentrations and their extensions from 1765 to 2300 in CLIMATIC CHANGE
  • 2011-12-07. EC-Earth V2.2: description and validation of a new seamless earth system prediction model in CLIMATE DYNAMICS
  • 2017-09-16. Local-scale changes in mean and heavy precipitation in Western Europe, climate change or internal variability? in CLIMATE DYNAMICS
  • 2013-01-24. The influence of the North Sea on coastal precipitation in the Netherlands in the present-day and future climate in CLIMATE DYNAMICS
  • 2021-01-04. Contribution of climatic changes in mean and variability to monthly temperature and precipitation extremes in COMMUNICATIONS EARTH & ENVIRONMENT
  • 2020-03-30. Insights from Earth system model initial-condition large ensembles and future prospects in NATURE CLIMATE CHANGE
  • 2018-11-12. A first-of-its-kind multi-model convection permitting ensemble for investigating convective phenomena over Europe and the Mediterranean in CLIMATE DYNAMICS
  • 2011-11-25. Observed and simulated impacts of the summer NAO in Europe: implications for projected drying in the Mediterranean region in CLIMATE DYNAMICS
  • 2018-08-20. The influence of Arctic amplification on mid-latitude summer circulation in NATURE COMMUNICATIONS
  • 2006-04-06. Causes and uncertainty of future summer drying over Europe in CLIMATE DYNAMICS
  • 2017-05-15. Understanding the regional pattern of projected future changes in extreme precipitation in NATURE CLIMATE CHANGE
  • 2021-02-01. The first multi-model ensemble of regional climate simulations at kilometer-scale resolution part 2: historical and future simulations of precipitation in CLIMATE DYNAMICS
  • 2014-03-13. The key role of dry days in changing regional climate and precipitation regimes in SCIENTIFIC REPORTS
  • 2008-01-30. Intense coastal rainfall in the Netherlands in response to high sea surface temperatures: analysis of the event of August 2006 from the perspective of a changing climate in CLIMATE DYNAMICS
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