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Suzana J. Camargo, Claudia F. Giulivi, Adam H. Sobel, Allison A. Wing, Daehyun Kim, Yumin Moon, Jeffrey D. O. Strong, Anthony D. Del Genio, Maxwell Kelley, Hiroyuki Murakami, Kevin A. Reed, Enrico Scoccimarro, Gabriel A. Vecchi, Michael F. Wehner, Colin Zarzycki, and Ming Zhao

models (P3, P4, P5, and P10). Only three models are not tracked with either of these algorithms: P1, P2, and P6. To explore the sensitivity of our results to the tracking algorithm, we will show in the online supplement a few key figures grouped by tracking algorithm. b. Data We compare the models’ environmental fields with those produced by the European Centre for Medium-Range Weather Forecasts (ECMWF) interim reanalysis (ERA-Interim) dataset ( Dee et al. 2011 ), which is available from 1979 to the

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Douglas E. Miller and Zhuo Wang

Atlantic and impact weather and climate over eastern North America and western Europe ( Hurrell 1995 ; Scaife et al. 2008 ). The NAO is a regional manifestation of the Arctic Oscillation (AO), or the northern annular mode (NAM), which is considered the dominant mode of variability in the Northern Hemisphere extratropics ( Thompson and Wallace 1998 ). Previous studies (e.g., DeWeaver and Nigam 2000 ; Hurrell et al. 2003 ) suggested that the internal dynamics of the atmosphere, particularly eddy

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Alexis Berg and Justin Sheffield

of the twenty-first century (2071–2100) under scenario RCP8.5. Figure 6a shows an important aspect of model uncertainties in future projections of summertime climate; across the CMIP5 ensemble, models that are warmer in summer under present-day climate conditions tend to project larger warming in the future over large swaths of the land surface: northern United States and Canada, eastern Europe, central Asia, northern Australia, the Amazon, and parts of sub-Saharan Africa. This positive

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Eric D. Maloney, Andrew Gettelman, Yi Ming, J. David Neelin, Daniel Barrie, Annarita Mariotti, C.-C. Chen, Danielle R. B. Coleman, Yi-Hung Kuo, Bohar Singh, H. Annamalai, Alexis Berg, James F. Booth, Suzana J. Camargo, Aiguo Dai, Alex Gonzalez, Jan Hafner, Xianan Jiang, Xianwen Jing, Daehyun Kim, Arun Kumar, Yumin Moon, Catherine M. Naud, Adam H. Sobel, Kentaroh Suzuki, Fuchang Wang, Junhong Wang, Allison A. Wing, Xiaobiao Xu, and Ming Zhao

and complementary to other efforts such as European Earth System Model Bias Reduction and Assessing Abrupt Climate Change (EMBRACE) project/Earth System Model eValuation Tool (ESMValTool) and Coordinated Set of Model Evaluation Capabilities (CMEC) that use open-source software packages for multimodel evaluation. Because most other efforts have thus far largely emphasized basic performance metrics for models, the MDTF effort described here is complementary and advantageous to these other efforts as

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Toward a Systematic Evaluation of Warm Conveyor Belts in Numerical Weather Prediction and Climate Models. Part I: Predictor Selection and Logistic Regression Model

Julian F. Quinting and Christian M. Grams

wintertime blocking frequency over the Atlantic–European sector ( Matsueda 2009 ; Quinting and Vitart 2019 ). Furthermore, the structure and propagation of upper-level Rossby waves have been shown to be systematically misrepresented in several NWP models ( Gray et al. 2014 ; Quinting and Vitart 2019 ). Since the representation of blocking is closely related to the representation of upper-level Rossby waves (e.g., Altenhoff et al. 2008 ; Martínez-Alvarado et al. 2018 ), it would be worthwhile to

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Alexis Berg and Justin Sheffield

fraction of transpiration increases while the fraction of soil evaporation decreases over most of these regions ( Figs. 8d–f ). Exceptions to this pattern include parts of Europe, northeast China, and the eastern United States, where it is the fraction of soil evaporation that increases (although transpiration still increases in absolute terms). Absolute increases in all three components are consistent with increases in precipitation in these regions. This precipitation-driven behavior also explains

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Maik Renner, Axel Kleidon, Martyn Clark, Bart Nijssen, Marvin Heidkamp, Martin Best, and Gab Abramowitz

, . 10.1016/j.agrformet.2005.04.001 Moderow , U. , and Coauthors , 2009 : Available energy and energy balance closure at four coniferous forest sites across Europe . Theor. Appl. Climatol. , 98 , 397 – 412 , . 10.1007/s00704-009-0175-0 Monin , A. S. , and A. M. Obukhov , 1954 : Basic laws of turbulent mixing in the atmosphere near the ground . Tr. Akad. Nauk SSSR Geofiz. Inst , 24 , 163 – 187

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James F. Booth, Young-Oh Kwon, Stanley Ko, R. Justin Small, and Rym Msadek

the similarities between Figs. 10f and 10b , especially off the U.S. East Coast, the Labrador Sea, and northwestern Europe, as a strong indication that model biases in T DIFF create biases in momentum mixing and these impact the surface storm tracks. Similar results are not apparent in multimodel mean biases for the North Pacific (not shown). However, biases in the multimodel mean T DIFF are negligible there. This might also explain the lack of significance in the model-to-model correlations

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Motoki Nagura, J. P. McCreary, and H. Annamalai

al. 2008 ). Surface winds are obtained from the European Centre for Medium-Range Weather Forecast (ECMWF) interim reanalysis (ERA-Interim; Dee et al. 2011 ). Horizontal grid intervals are 1° × 1° for WOA13 and OAFlux, 2.5° × 2.5° for GPCP rain, and 1.5° × 1.5° for the ERA-Interim reanalysis. The time series we use for each dataset extend from 1979 to 2015 for GPCP rainfall and the ERA-Interim reanalysis, 1984 to 2009 for OAFlux surface heat flux, and 1985 to 2014 for OAFlux evaporative flux

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Fiaz Ahmed and J. David Neelin

, respectively. 2. Data Vertical profiles of temperature and specific humidity, as well as surface variables including surface pressure, 2-m temperature, and dewpoint temperature, were all obtained from the European Centre for Medium-Range Weather Forecasts (ECMWF) interim reanalysis (ERA-Interim; Dee et al. 2011 ), four times daily at 0.25° grid spacing for a period spanning from September 2001 to December 2014. Concurrent values of precipitation were obtained from version 7 of the 3B42 Tropical Rainfall

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