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

Hydrology: Glaciology (1863); 1863 Hydrology: Snow and ice (1827); 1854 Hydrology: Precipitation (3354)

[1] It is investigated to what extent multiannual accumulation time series from Greenland reflect dynamic and thermodynamic processes and how representative single accumulation series are for the entire ice sheet. Furthermore, it is examined whether accumulation is related to low-level atmospheric temperatures. For this purpose, two kinds of regression models are developed which linearly relate multiannual accumulation records to meteorological mean fields. Seven ice cores from north to central Greenland and the NCEP Reanalysis data are used for the period from 1948 to 1992. In order to reduce noise, the data are smoothed with a weighted 5-year running mean. The downscaling technique is based on a stepwise multiple linear regression. One group of regression models distinguishes between dynamic and thermodynamic atmospheric effects. For that reason, stream functions are used in a first step to describe the dynamically controlled accumulation, whereas the thermodynamically controlled accumulation is determined by temperature in a second step. For six of the ice cores, these regression models describe more than 56% of the variability of the smoothed accumulation series, confirming that they represent to a large extent atmospheric states. Multiannual accumulation variability is found to dominantly represent circulation variability. However, the circulation fields that are linked with accumulation show marked differences among the cores concerning the represented seasons, areas, and structures. Thus local accumulation generally represents only regional-scale climate features, which are probably to a great extent influenced by orography. Furthermore, regression models using only 700 hPa temperature as predictor show that a general linear relationship between accumulation and temperature does not exist over this 45-year time interval. Therefore paleoaccumulation rates derived from isotopic temperatures should be interpreted with caution. Moreover, it is not reasonable to describe accumulation by means of temperature in mass balance models for the Greenland ice sheet in decadal timescales

Geochemistry of a coral from Bermuda

We present a 55-year-long record (1928-1982) of Sr/Ca in a Bermuda coral (Diploria strigosa), which we use to reconstruct local twentieth century climate features. The clearest climate signal emerges for the late-year Sr/Ca. Although the coral was collected in shallow water (12 m), the correlation with station data is highest for temperatures at 50 m depth (r = -0.70), suggesting that local temperatures at the collection site are not representative for the sea surface temperatures in the adjacent open ocean. The most striking feature of the coral record is the persistent and significant correlation (r = -0.50) with the North Atlantic Oscillation (NAO) index. Field correlations of fall Sr/Ca with the winter sea level pressure (SLP) show the typical spatial NAO pattern. The stable relationship with the NAO shows that Sr/Ca in Bermuda corals is a suitable tool for the reconstruction of North Atlantic climate variability

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