[1] This paper provides a first overview of the performance of state-of-the-art global climate models participating in the Coupled Model Intercomparison Project Phase 5 (CMIP5) in simulating climate extremes indices defined by the Expert Team on Climate Change Detection and Indices (ETCCDI), and compares it to that in the previous model generation (CMIP3). For the first time, the indices based on daily temperature and precipitation are calculated with a consistent methodology across multimodel simulations and four reanalysis data sets (ERA40, ERA-Interim, NCEP/NCAR, and NCEP-DOE) and are made available at the ETCCDI indices archive website. Our analyses show that the CMIP5 models are generally able to simulate climate extremes and their trend patterns as represented by the indices in comparison to a gridded observational indices data set (HadEX2). The spread amongst CMIP5 models for several temperature indices is reduced compared to CMIP3 models, despite the larger number of models participating in CMIP5. Some improvements in the CMIP5 ensemble relative to CMIP3 are also found in the representation of the magnitude of precipitation indices. We find substantial discrepancies between the reanalyses, indicating considerable uncertainties regarding their simulation of extremes. The overall performance of individual models is summarized by a “portrait” diagram based on root-mean-square errors of model climatologies for each index and model relative to four reanalyses. This metric analysis shows that the median model climatology outperforms individual models for all indices, but the uncertainties related to the underlying reference data sets are reflected in the individual model performance metrics.

https://agupubs.onlinelibrary.wiley.com/doi/pdf/10.1002/jgrd.50203

Climate extremes indices in the CMIP5 multimodel ensemble: Part 1. Model evaluation in the present climate

Robust evidence exists that certain extreme weather and climate events, especially daily temperature and precipitation extremes, have changed in regard to intensity and frequency over recent decade...

https://royalsocietypublishing.org/doi/pdf/10.1098/rstb.2016.0135

Extreme weather and climate events with ecological relevance: a review.

It has been predicted, by theory and models, that heavy precipitation will increase with climate change and this is now being seen in observations Emergence of signals such as this will enable testing of predictions, which should increase confidence in them Environmental phenomena are often observed first, and then explained quantitatively The complexity of processes, the range of scales involved, and the lack of first principles make it challenging to predict conditions beyond the ones observed Here we use the intensification of heavy precipitation as a counterexample, where seemingly complex and potentially computationally intractable processes manifest themselves to first order in simple ways: heavy precipitation intensification is now emerging in the observed record across many regions of the world, confirming both theory and model predictions made decades ago As the anthropogenic climate signal strengthens, there will be more opportunities to test climate predictions for other variables against observations and across a hierarchy of different models and theoretical concepts

Observed heavy precipitation increase confirms theory and early models

Climate change, impacts and vulnerability in Europe 2012. An indicator-based report

This paper surveys the current state of knowledge regarding large-scale meteorological patterns (LSMPs) associated with short-duration (less than 1 week) extreme precipitation events over North America. In contrast to teleconnections, which are typically defined based on the characteristic spatial variations of a meteorological field or on the remote circulation response to a known forcing, LSMPs are defined relative to the occurrence of a specific phenomenon—here, extreme precipitation—and with an emphasis on the synoptic scales that have a primary influence in individual events, have medium-range weather predictability, and are well-resolved in both weather and climate models. For the LSMP relationship with extreme precipitation, we consider the previous literature with respect to definitions and data, dynamical mechanisms, model representation, and climate change trends. There is considerable uncertainty in identifying extremes based on existing observational precipitation data and some limitations in analyzing the associated LSMPs in reanalysis data. Many different definitions of “extreme” are in use, making it difficult to directly compare different studies. Dynamically, several types of meteorological systems—extratropical cyclones, tropical cyclones, mesoscale convective systems, and mesohighs—and several mechanisms—fronts, atmospheric rivers, and orographic ascent—have been shown to be important aspects of extreme precipitation LSMPs. The extreme precipitation is often realized through mesoscale processes organized, enhanced, or triggered by the LSMP. Understanding of model representation, trends, and projections for LSMPs is at an early stage, although some promising analysis techniques have been identified and the LSMP perspective is useful for evaluating the model dynamics associated with extremes.

/pdf/north-american-extreme-temperature-events-and-related-large-1mzz6ojjpv.pdf

North American extreme temperature events and related large scale meteorological patterns: a review of statistical methods, dynamics, modeling, and trends

This paper focuses primarily on extremes in the historical instrumental period We consider a range of phenomena, including temperature and precipitation extremes, tropical and extra-tropical storms, hydrological extremes, and transient extreme sea-level events We also discuss the extent to which detection and attribution research has been able to link observed changes to external forcing of the climate system Robust results are available that detect and often attribute changes in frequency and intensity of temperature extremes to external forcing There is also some evidence that on a global scale, precipitation extremes have intensified due to forcing However, robustly detecting and attributing forced changes in other important extremes, such as tropical and extratropical storms or drought remains challenging

/pdf/climate-extremes-challenges-in-estimating-and-understanding-3apmcei3eh.pdf

Climate Extremes: Challenges in Estimating and Understanding Recent Changes in the Frequency and Intensity of Extreme Climate and Weather Events

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Climate Extremes: Challenges in Estimating and Understanding Recent Changes in the Frequency and Intensity of Extreme Climate and Weather Events