Search Results

You are looking at 1 - 10 of 17 items for :

  • Seasonal effects x
  • Process-Oriented Model Diagnostics x
  • All content x
Clear All
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

-horizontal-resolution models ( Murakami et al. 2012b ; Knutson et al. 2013 ; Manganello et al. 2014 ; Bhatia et al. 2018 ; Bacmeister et al. 2018 ). Another common use of climate models is for TC dynamical forecasts on seasonal ( Vitart et al. 2001 ; Camargo and Barnston 2009 ; Manganello et al. 2016 ; Camp et al. 2019 ; G. Zhang et al. 2019 ; W. Zhang et al. 2019 ) and subseasonal time scales ( Lee et al. 2018 ; Camp et al. 2018 ; Gregory et al. 2019 ; Zhao et al. 2019 ). A recent review on this topic is

Restricted access
Zhe Feng, Fengfei Song, Koichi Sakaguchi, and L. Ruby Leung

consistent information on hydrologic hazards and impacts compared to traditional coarse resolution models ( Roberts et al. 2018 ). In the midlatitude, intense precipitation events are commonly associated with synoptic-scale disturbances such as extratropical cyclones and mesoscale disturbances such as tropical cyclones. In the contiguous United States (CONUS), mesoscale convective systems (MCSs), the largest form of deep convective storms, produce over 50% of annual and seasonal rainfall over large

Open access
Samson M. Hagos, L. Ruby Leung, Oluwayemi A. Garuba, Charlotte Demott, Bryce Harrop, Jian Lu, and Min-Seop Ahn

1. Introduction Understanding and quantifying the effects of global warming on regional hydrological cycles is one of the most important problems in climate science because of the societal implications. At global scale, atmospheric moisture increases with temperature under global warming at a rate that follows the Clausius–Clapeyron relationship of ~7% K −1 , while global precipitation increases at a much slower rate of ~2% K −1 ( Held and Soden 2006 ). This difference between the responses of

Open access
Xianan Jiang, Ángel F. Adames, Ming Zhao, Duane Waliser, and Eric Maloney

regulating this important form of variability. The MJO exhibits pronounced seasonality in its propagation characteristics. During boreal winter, the MJO is characterized by the equatorial eastward propagation ( Madden and Julian 1994 ). In contrast, it exhibits marked poleward movement over the Indian Ocean (IO) and western Pacific (WP) during summer with a relatively weak eastward-propagating component (e.g., Lau and Chan 1986 ; Hsu and Weng 2001 ; Jiang et al. 2004 ). Various theories have been

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

. Int. J. Climatol. , 36 , 2541 – 2554 , https://doi.org/10.1002/joc.4511 . 10.1002/joc.4511 Schott , F. A. , and J. P. McCreary , 2001 : The monsoon circulation of the Indian Ocean . Prog. Oceanogr. , 51 , 1 – 123 , https://doi.org/10.1016/S0079-6611(01)00083-0 . 10.1016/S0079-6611(01)00083-0 Seo , H. , S.-P. Xie , R. Murtugudde , M. Jochum , and A. J. Miller , 2009 : Seasonal effects of Indian Ocean freshwater forcing in a regional coupled model . J. Climate , 22

Full access
Alexis Berg and Justin Sheffield

hemisphere, considering seasonal values over June–August in the Northern Hemisphere and December–February in the Southern Hemisphere. To characterize SM–ET coupling, we analyze output of surface (top 10 cm; variable mrsos in the CMIP5 archive) soil moisture and evapotranspiration. We use surface soil moisture because it is more easily comparable across models, when correlated with surface fluxes, than total (column integrated) soil moisture, which reflects differences in soil depths between models. With

Full access
Fiaz Ahmed and J. David Neelin

°–70°W), and Atlantic Ocean (Atl) (25°N–25°S, 70°W–15°E). The tropical land regions were divided into seven major regions: India (5°–25°N, 75°–90°E), East Asia (15°–25°N, 105°–125°E), Maritime Continent (10°S–10°N, 95°–145°E), Australia (20°–10°S, 125°–145°E), South America (10°S–10°N, 75°–50°W), Argentina (25°–15°S, 75°–50°W), and West Africa (0°–15°N, 17°W–10°E). The land regions typify different regimes of tropical continental convection ( Xu and Zipser 2012 ) but are not seasonally distinguished

Full access
Daehyun Kim, Yumin Moon, Suzana J. Camargo, Allison A. Wing, Adam H. Sobel, Hiroyuki Murakami, Gabriel A. Vecchi, Ming Zhao, and Eric Page

1. Introduction Since the 1970s, it has been well known that global climate models (GCMs) are able to simulate vortices with characteristics similar to tropical cyclones (TCs; Manabe et al. 1970 ; Camargo and Wing 2016 ). As GCMs are also able to reproduce the relationship between TCs and El Niño–Southern Oscillation (ENSO), they have been used to develop dynamical TC seasonal forecasts ( Vitart and Stockdale 2001 ; Camargo and Barnston 2009 ). More recently, with the aid of rapid increases

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

closure is on average 80%. However, it ranges between 55% at the site Elsaler2 (irrigated cropland) and 93% at the neighboring site Elsaler, which is classified as a wetland, see Table 3 . Next, we evaluate the LSM ability to predict the evaporative fraction for a given day, cut into 10% bins. We find very low agreement of about 20% for the LSMs, see Fig. 3 . While the LSMs show seasonal variation in EF, the empirical benchmarks show rather constant EF across season and sites, since these have been

Open access
Allison A. Wing, Suzana J. Camargo, Adam H. Sobel, Daehyun Kim, Yumin Moon, Hiroyuki Murakami, Kevin A. Reed, Gabriel A. Vecchi, Michael F. Wehner, Colin Zarzycki, and Ming Zhao

1. Introduction The study of tropical cyclones (TCs) in climate models has long been difficult because of the conflict between the high resolution necessary to accurately simulate TCs and the need to perform long, global simulations. In recent years, however, enormous progress has been made in the ability of general circulation models (GCMs) to simulate TCs from subseasonal to seasonal and longer time scales ( Camargo and Wing 2016 ). Global forecast models have become a more reliable source of

Full access