The Added Value of Large-Eddy and Storm-Resolving Models for Simulating Clouds and Precipitation

More than one hundred days were simulated over very large domains with fine (0.156 km to 2.5 km) grid spacing for realistic conditions to test the hypothesis that storm (kilometer) and large-eddy (hectometer) resolving simulations would provide an improved representation of clouds and precipitation in atmospheric simulations. At scales that resolve convective storms (storm-resolving for short), the vertical velocity variance becomes resolved and a better physical basis is achieved for representing clouds and precipitation. Similarly to past studies we found an improved representation of precipitation at kilometer scales, as compared to models with parameterized convection. The main precipitation features (location, diurnal cycle and spatial propagation) are well captured already at kilometer scales, and refining resolution to hectometer scales does not substantially change the simulations in these respects. It does, however, lead to a reduction in the precipitation on the time-scales considered – most notably over the ocean in the tropics. Changes in the distribution of precipitation, with less frequent extremes are also found in simulations incorporating hectometer scales. Hectometer scales appear to be more important for the representation of clouds, and make it possible to capture many important aspects of the cloud field, from the vertical distribution of cloud cover, to the distribution of cloud sizes, and to the diel (daily) cycle. Qualitative improvements, particularly in the ability to differentiate cumulus from stratiform clouds, are seen when one reduces the grid spacing from kilometer to hectometer scales. At the hectometer scale new challenges arise, but the similarity of observed and simulated scales, and the more direct connection between the circulation and the unconstrained degrees of freedom make these challenges less daunting. This quality, combined with already improved simulation as compared to more parameterized models, underpins our conviction that the use and further development of storm-resolving models offers exciting opportunities for advancing understanding of climate and climate change

Raman lidar water vapor profiling over Warsaw, Poland

Water vapor mixing ratio and relative humidity profiles were derived from the multi-wavelength Raman PollyXT lidar at the EARLINET site in Warsaw, using the Rayleigh molecular extinction calculation based on atmospheric temperature and pressure from three different sources: i) the standard atmosphere US 62, ii) the Global Data Assimilation System (GDAS) model output, and iii) the WMO 12374 radiosoundings launched at Legionowo. With each method, 136 midnight relative humidity profiles were obtained for lidar observations from July 2013 to August 2015. Comparisons of these profiles showed in favor of the latter method (iii), but it also indicated that the other two data sources could replace it, if necessary. Such use was demonstrated for an automated retrieval of water vapor mixing ratio from dusk until dawn on 19/20 March 2015; a case study related to an advection of biomass burning aerosol from forest fires over Ukraine. Additionally, an algorithm that applies thresholds to the radiosounding relative humidity profiles to estimate macro-physical cloud vertical structure was used for the first time on the Raman lidar relative humidity profiles. The results, based on a subset of 66 profiles, indicate that below 6 km cloud bases/tops can be successfully obtained in 53% and 76% cases from lidar and radiosounding profiles, respectively. Finally, a contribution of the lidar derived mean relative humidity to cloudy conditions within the range of 0.8 to 6.2 km, in comparison to clear-sky conditions, was estimated

The Added Value of Large-Eddy and Storm-Resolving Models for Simulating Clouds and Precipitation

More than one hundred days were simulated over very large domains with fine (0.156 km to 2.5 km) grid spacing for realistic conditions to test the hypothesis that storm (kilometer) and large-eddy (hectometer) resolving simulations would provide an improved representation of clouds and precipitation in atmospheric simulations. At scales that resolve convective storms (storm-resolving for short), the vertical velocity variance becomes resolved and a better physical basis is achieved for representing clouds and precipitation. Similarly to past studies we found an improved representation of precipitation at kilometer scales, as compared to models with parameterized convection. The main precipitation features (location, diurnal cycle and spatial propagation) are well captured already at kilometer scales, and refining resolution to hectometer scales does not substantially change the simu-lations in these respects. It does, however, lead to a reduction in the precipitation on the time-scales considered – most notably over the ocean in the tropics. Changes in the distribution of precipitation, with less frequent extremes are also found in simulations incorporating hectometer scales. Hectometer scales appear to be more important for the representation of clouds, and make it possible to capture many important aspects of the cloud field, from the vertical distribution of cloud cover, to the distribution of cloud sizes, and to the diel (daily) cycle. Qualitative improvements, particularly in the ability to differentiate cumulus from stratiform clouds, are seen when one reduces the grid spacing from kilometer to hectometer scales. At the hectometer scale new challenges arise, but the similarity of observed and simulated scales, and the more direct connection between the circula-tion and the unconstrained degrees of freedom make these challenges less daunting. This quality, combined with already improved simulation as compared to more parameterized models, underpins our conviction that the use and further development of storm-resolving models offers exciting opportunities for advancing understanding of climate and climate change