Correction: Impact of the Benguela coastal low-level jet on the southeast tropical Atlantic SST bias in a regional ocean model - Jaison Kurian; Pin Li; Ping Chang; Christina M. Patricola-DiRosario; Justin Small (Climate Dynamics, 2026)

Effects of grid spacing on high-frequency precipitation variance in coupled high-resolution global ocean–atmosphere models - Charles X. Light; Brian K. Arbic; Paige E. Martin; Laurent Brodeau; J. Thomas Farrar; Stephen M. Griffies; Ben P. Kirtman; Lucas C. Laurindo; Dimitris Menemenlis; Andrea Molod; Arin D. Nelson; Ebenezer Nyadjro; et al. (Climate Dynamics, 2022)
High-frequency precipitation variance is calculated in 12 different free-running (non-data-assimilative) coupled high resolution atmosphere–ocean model simulations, an assimilative coupled atmosphere–ocean weather forecast model, and an assimilative reanalysis. The results are compared with results from satellite estimates of precipitation and rain gauge observations. An analysis of irregular sub-daily fluctuations, which was applied by Covey et al. (Geophys Res Lett 45:12514–12522, 2018. https://doi.org/10.1029/2018GL078926 ) to satellite products and low-resolution climate models, is applied here to rain gauges and higher-resolution models. In contrast to lower-resolution climate simulations, which Covey et al. (2018) found to be lacking with respect to variance in irregular sub-daily fluctuations, the highest-resolution simulations examined here display an irregular sub-daily fluctuation variance that lies closer to that found in satellite products. Most of the simulations used here cannot be analyzed via the Covey et al. (2018) technique, because they do not output precipitation at sub-daily intervals. Thus the remainder of the paper focuses on frequency power spectral density of precipitation and on cumulative distribution functions over time scales (2–100 days) that are still relatively “high-frequency” in the context of climate modeling. Refined atmospheric or oceanic model grid spacing is generally found to increase high-frequency precipitation variance in simulations, approaching the values derived from observations. Mesoscale-eddy-rich ocean simulations significantly increase precipitation variance only when the atmosphere grid spacing is sufficiently fine (< 0.5°). Despite the improvements noted above, all of the simulations examined here suffer from the “drizzle effect”, in which precipitation is not temporally intermittent to the extent found in observations.

Global oscillatory modes in high-end climate modeling and reanalyses - Yizhak Feliks; Justin Small; Michael Ghil (Climate Dynamics, 2021)
Interannual oscillatory modes, atmospheric and oceanic, are present in several large regions of the globe. We examine here low-frequency variability (LFV) over the entire globe in the Community Earth System Model (CESM) and in the NCEP-NCAR and ECMWF ERA5 reanalyses. Multichannel singular spectrum analysis (MSSA) is applied to these three datasets. In the fully coupled CESM1.1 model, with its resolution of $$0.1 × 0.1$$ 0.1 × 0.1 degrees in the ocean and $$0.25 × 0.25$$ 0.25 × 0.25 degrees in the atmosphere, the fields analyzed are surface temperatures, sea level pressures and the 200-hPa geopotential. The simulation is 100-year long and the last 66 yr are used in the analysis. The two statistically significant periodicities in this IPCC-class model are 11 and 3.4 year. In the NCEP-NCAR reanalysis, the fields of sea level pressure and of 200-hPa geopotential are analyzed at the available resolution of $$2.5 × 2.5$$ 2.5 × 2.5 degrees over the 68-years interval 1949–2016. Oscillations with periods of 12 and 3.6 years are found to be statistically significant in this dataset. In the ECMWF ERA5 reanalysis, the 200-hPa geopotential field was analyzed at its resolution of $$0.25 × 0.25$$ 0.25 × 0.25 degrees over the 71-years interval 1950–2020. Oscillations with periods of 10 and 3.6 years are found to be statistically significant in this third dataset. The spatio-temporal patterns of the oscillations in the three datasets are quite similar. The spatial pattern of these global oscillations over the North Pacific and North Atlantic resemble the Pacific Decadal Oscillation and the LFV found in the Gulf Stream region and Labrador Sea, respectively. We speculate that such regional oscillations are synchronized over the globe, thus yielding the global oscillatory modes found herein, and discuss the potential role of the 11-year solar-irradiance cycle in this synchronization. The robustness of the two global modes, with their 10–12 and 3.4–3.6 years periodicities, also suggests potential contributions to predictability at 1–3 years horizons.

Impact of the Benguela coastal low-level jet on the southeast tropical Atlantic SST bias in a regional ocean model - Jaison Kurian; Pin Li; Ping Chang; Christina M. Patricola-DiRosario; Justin Small (Climate Dynamics, 2021)

On the control of subantarctic stratification by the ocean circulation - R. Justin Small; Alice K. DuVivier; Daniel B. Whitt; Matthew C. Long; Ian Grooms; William G. Large (Climate Dynamics, 2021)

Comparing inferences derived from microsatellite and RADseq datasets: a case study involving threatened bull trout - Justin Bohling; Maureen Small; Jennifer Von Bargen; Amelia Louden; Patrick DeHaan (Conservation Genetics, 2019)

Atmosphere surface storm track response to resolved ocean mesoscale in two sets of global climate model experiments - R. Justin Small; Rym Msadek; Young-Oh Kwon; James F. Booth; Colin Zarzycki (Climate Dynamics, 2019)

Storm track response to ocean fronts in a global high-resolution climate model - R. Justin Small; Robert A. Tomas; Frank O. Bryan (Climate Dynamics, 2014)

Turbulent heat fluxes during an intense cold-air outbreak over the Kuroshio Extension Region: results from a high-resolution coupled atmosphere–ocean model - Tommy G. Jensen; Timothy J. Campbell; Richard A. Allard; Richard Justin Small; Travis A. Smith (Ocean Dynamics, 2011)

Intraseasonal variability in the far-east pacific: investigation of the role of air–sea coupling in a regional coupled model - R. Justin Small; Shang-Ping Xie; Eric D. Maloney; Simon P. de Szoeke; Toru Miyama (Climate Dynamics, 2011)