21719 Article Several different time periods of the Atlantic Tradewind Ocean-Atmosphere Mesoscale Interaction Campaign (ATOMIC) are isolated for examining how the depiction of tradewind marine shallow cumuli in single-column models (SCMs) is affected by choices about model physics. The periods of interest are times when the NOAA Research Vessel Ronald H. Brown and research aircraft WP-3D Orion were collocated, enabling verification of initial conditions and large-scale forcing (advective) tendencies constructed using gridded data from the fifth generation ECMWF atmospheric reanalysis (ERA5). To demonstrate how this new ATOMIC test case can be used to guide model development, three parameterization suites of the NOAA Unified Forecast System are evaluated within the Common Community Physics Package Single Column Model (CCPP SCM). Calculations are also performed using a large-eddy simulation (LES) to further bridge the gap between observations and SCM output, all of which are separated into regimes of either relatively active (“cloudy”) or inactive (“clear”) marine shallow cumuli. In both regimes tested, the parameterization suites tend to: (a) generate an unrealistic skewed or bimodal distribution of cloud fraction, (b) overestimate light to moderate rain rates, (c) produce an erroneously cold and dry boundary layer, and (d) produce higher-than-observed cloud tops. Results show that modifying the treatment of cloud fraction as well as increasing spatial and temporal resolution help bring the SCM more in line with observations. In addition, evidence is found to suggest that some of the remaining model biases may stem from intrinsic differences in the spatio-temporal sampling properties of the observations versus SCM output. Plain Language Summary: This study uses observational data collected during the Atlantic Tradewind Ocean-Atmosphere Mesoscale Interaction Campaign (ATOMIC) to examine how well certain atmospheric model physics packages simulate tradewind marine shallow clouds in a simplified (single-column) modeling framework, which focuses on vertical physical processes within an air column. Several different time periods are chosen when NOAA's research ship and aircraft were both in the same location, so that the environmental conditions needing verification in that simplified modeling framework can be affirmed by observations to some extent. Discrepancies between the model and observations are found in cloud cover, rain rate, air properties near the surface, and cloud top. While part of these discrepancies may result from differences in how data was collected and averaged in time and space, adjustments in model cloud physics packages remain the most fundamental approach to addressing them. 2026-1 Journal of Advances in Modeling Earth Systems 18 e2024MS004814 0 10.1029/2024MS004814 Several different time periods of the Atlantic Tradewind Ocean-Atmosphere Mesoscale Interaction Campaign (ATOMIC) are isolated for examining how the depiction of tradewind marine shallow cumuli in single-column models (SCMs) is affected by choices about model physics. The periods of interest are times when the NOAA Research Vessel Ronald H. Brown and research aircraft WP-3D Orion were collocated, enabling verification of initial conditions and large-scale forcing (advective) tendencies constructed using gridded data from the fifth generation ECMWF atmospheric reanalysis (ERA5). To demonstrate how this new ATOMIC test case can be used to guide model development, three parameterization suites of the NOAA Unified Forecast System are evaluated within the Common Community Physics Package Single Column Model (CCPP SCM). Calculations are also performed using a large-eddy simulation (LES) to further bridge the gap between observations and SCM output, all of which are separated into regimes of either relatively active (“cloudy”) or inactive (“clear”) marine shallow cumuli. In both regimes tested, the parameterization suites tend to: (a) generate an unrealistic skewed or bimodal distribution of cloud fraction, (b) overestimate light to moderate rain rates, (c) produce an erroneously cold and dry boundary layer, and (d) produce higher-than-observed cloud tops. Results show that modifying the treatment of cloud fraction as well as increasing spatial and temporal resolution help bring the SCM more in line with observations. In addition, evidence is found to suggest that some of the remaining model biases may stem from intrinsic differences in the spatio-temporal sampling properties of the observations versus SCM output. Plain Language Summary: This study uses observational data collected during the Atlantic Tradewind Ocean-Atmosphere Mesoscale Interaction Campaign (ATOMIC) to examine how well certain atmospheric model physics packages simulate tradewind marine shallow clouds in a simplified (single-column) modeling framework, which focuses on vertical physical processes within an air column. Several different time periods are chosen when NOAA's research ship and aircraft were both in the same location, so that the environmental conditions needing verification in that simplified modeling framework can be affirmed by observations to some extent. Discrepancies between the model and observations are found in cloud cover, rain rate, air properties near the surface, and cloud top. While part of these discrepancies may result from differences in how data was collected and averaged in time and space, adjustments in model cloud physics packages remain the most fundamental approach to addressing them. Hu I.-K.. Chen X. Bengtsson L. Thompson E. J. Dias J. Tulich S. N. 21758 Article A data-driven dynamical filter is developed to characterize Madden-Julian Oscillation (MJO) variability, by representing tropical variability with nonorthogonal empirical-dynamical modes that allow for constructive and destructive interference. We find that two intraseasonal atmospheric modes, an “MJO-fast” mode ( 45 day period) and a newly identified “MJO-slow” mode ( 70 day period), alongside El Niño-Southern Oscillation modes that are not entirely removed by temporal filtering, explain nearly all observed Real-time Multivariate MJO (RMM) index-based variability. The fastest growing, and most predictable, MJO events are initiated primarily by the MJO-fast mode over the Indian Ocean, with subsequent progression across the Maritime Continent resulting from destructive and then constructive interference of the MJO-fast and MJO-slow modes. These events, which we demonstrate can be identified at forecast initialization time, are shown to be forecasts of opportunity in the ECMWF operational forecast model, with MJO skill extended by roughly a week compared to all other forecasts. Plain Language Summary: The Madden-Julian Oscillation (MJO) is a large area of organized tropical thunderstorms, flanked to the east and west by regions where these storms are unusually absent, that moves eastward along the equator from the Indian Ocean to the central tropical Pacific Ocean, over the course of 30–90 days. Its slow movement, and the atmospheric disturbances it drives in the extratropics, makes it a prime focus for improved prediction studies. In this work, we develop a data-driven method to characterize the MJO in terms of two east-west see-saw patterns, one that moves faster (once every 45 days) and one that moves slower (once every 70 days). These patterns combine to yield nearly all of the observed MJO phenomenon as defined by past methods, and how they combine can be used ahead of time to identify when MJO forecasts will be particularly skillful. In such cases, operational weather models like that of the ECMWF predict the MJO more skillfully by approximately 1 week than typical forecasts. 2026-1 Geophysical Research Letters 53 e2025GL118062 0 10.1029/2025GL118062 A data-driven dynamical filter is developed to characterize Madden-Julian Oscillation (MJO) variability, by representing tropical variability with nonorthogonal empirical-dynamical modes that allow for constructive and destructive interference. We find that two intraseasonal atmospheric modes, an “MJO-fast” mode ( 45 day period) and a newly identified “MJO-slow” mode ( 70 day period), alongside El Niño-Southern Oscillation modes that are not entirely removed by temporal filtering, explain nearly all observed Real-time Multivariate MJO (RMM) index-based variability. The fastest growing, and most predictable, MJO events are initiated primarily by the MJO-fast mode over the Indian Ocean, with subsequent progression across the Maritime Continent resulting from destructive and then constructive interference of the MJO-fast and MJO-slow modes. These events, which we demonstrate can be identified at forecast initialization time, are shown to be forecasts of opportunity in the ECMWF operational forecast model, with MJO skill extended by roughly a week compared to all other forecasts. Plain Language Summary: The Madden-Julian Oscillation (MJO) is a large area of organized tropical thunderstorms, flanked to the east and west by regions where these storms are unusually absent, that moves eastward along the equator from the Indian Ocean to the central tropical Pacific Ocean, over the course of 30–90 days. Its slow movement, and the atmospheric disturbances it drives in the extratropics, makes it a prime focus for improved prediction studies. In this work, we develop a data-driven method to characterize the MJO in terms of two east-west see-saw patterns, one that moves faster (once every 45 days) and one that moves slower (once every 70 days). These patterns combine to yield nearly all of the observed MJO phenomenon as defined by past methods, and how they combine can be used ahead of time to identify when MJO forecasts will be particularly skillful. In such cases, operational weather models like that of the ECMWF predict the MJO more skillfully by approximately 1 week than typical forecasts. Marsico D. H. Albers J. R. Newman M. Gehne M. Dias J. Sardeshmukh P. D. Kiladis G. N. LaJoie E. Wang Y. 21789 Article This paper presents physics improvements to the cool skin parameterization in the Coupled Ocean-Atmosphere Response Experiment (COARE) bulk flux algorithm. The principal improvement is adopting a specification of the ocean side mixing profile that combines molecular and turbulent diffusivities via a form that allows turbulent dissipation to suppress turbulence near the interface. The turbulence is also scaled with the viscous friction velocity, since the stress input to waves is not realized continuously as turbulence at the interface but only intermittently at localized regions where the waves are breaking. Additional improvements include adopting a newer specification of the solar absorption profile in the ocean and incorporating the impacts of the rain sensible heat flux. The new parameterization is tuned to published observations of cool skin from a series of cruises and a recent publication of the turbo-molecular mixing term deduced for observations of gas fluxes. Data from three recent ship-based field programs, particularly the Propagation of Intraseasonal Oscillations in the Maritime Continent Region (PISTON) experiment, with radiometric sea surface and floating near-surface temperature sensors as well as high-quality air-sea flux measurements were analyzed to evaluate the model. The improvements led to modest decreases in the nonsolar cool skin (∼16%) and in the solar heating contribution, both principally in light winds. The new model better reproduced mean nighttime cool skin amplitudes and was somewhat better than the previous COARE v3.6 model at reproducing the mean diurnal cycle. Overall, cool skin predictions for a large cruise database were reduced by ∼0.01°C. Plain Language Summary: The very surface of the ocean is usually cooler than the water just below because of an overall transfer of heat from the ocean to the air above and the damping of turbulence near the interface. This paper presents an update to a model commonly used to estimate the size of this so-called “cool skin” for determining the net heat flux. The improvement introduces damped turbulent mixing in addition to the traditional molecular diffusion within the skin layer. The new model also includes new treatments for how solar radiation is absorbed near the ocean surface and the heat exchange associated with falling rain. The model is tuned with and tested against observations of the surface and near-surface temperature and corresponding heat flux from recent ocean research cruises. The changes result in slightly reduced estimates of the magnitude of the surface cooling and better agreement with the observations than the previous version of the model. 2026-1 Journal of Geophysical Research: Oceans 131 e2025JC023539 0 10.1029/2025JC023539 This paper presents physics improvements to the cool skin parameterization in the Coupled Ocean-Atmosphere Response Experiment (COARE) bulk flux algorithm. The principal improvement is adopting a specification of the ocean side mixing profile that combines molecular and turbulent diffusivities via a form that allows turbulent dissipation to suppress turbulence near the interface. The turbulence is also scaled with the viscous friction velocity, since the stress input to waves is not realized continuously as turbulence at the interface but only intermittently at localized regions where the waves are breaking. Additional improvements include adopting a newer specification of the solar absorption profile in the ocean and incorporating the impacts of the rain sensible heat flux. The new parameterization is tuned to published observations of cool skin from a series of cruises and a recent publication of the turbo-molecular mixing term deduced for observations of gas fluxes. Data from three recent ship-based field programs, particularly the Propagation of Intraseasonal Oscillations in the Maritime Continent Region (PISTON) experiment, with radiometric sea surface and floating near-surface temperature sensors as well as high-quality air-sea flux measurements were analyzed to evaluate the model. The improvements led to modest decreases in the nonsolar cool skin (∼16%) and in the solar heating contribution, both principally in light winds. The new model better reproduced mean nighttime cool skin amplitudes and was somewhat better than the previous COARE v3.6 model at reproducing the mean diurnal cycle. Overall, cool skin predictions for a large cruise database were reduced by ∼0.01°C. Plain Language Summary: The very surface of the ocean is usually cooler than the water just below because of an overall transfer of heat from the ocean to the air above and the damping of turbulence near the interface. This paper presents an update to a model commonly used to estimate the size of this so-called “cool skin” for determining the net heat flux. The improvement introduces damped turbulent mixing in addition to the traditional molecular diffusion within the skin layer. The new model also includes new treatments for how solar radiation is absorbed near the ocean surface and the heat exchange associated with falling rain. The model is tuned with and tested against observations of the surface and near-surface temperature and corresponding heat flux from recent ocean research cruises. The changes result in slightly reduced estimates of the magnitude of the surface cooling and better agreement with the observations than the previous version of the model. Fairall C. W. Thompson E. J. Bariteau L. Wick G. A. Minnett P. J. Szczodrak G. Jessup A. T. Witte C.