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R. A. Roebeling and E. van Meijgaard

Abstract

The evaluation of the diurnal cycle of cloud amount (CA) and cloud condensed water path (CWP) as predicted by climate models receives relatively little attention, mostly because of the lack of observational data capturing the diurnal cycle of such quantities. The Spinning Enhanced Visible and Infrared Imager (SEVIRI) onboard the geostationary Meteosat-8 satellite is the first instrument able to provide accurate information on diurnal cycles during daylight hours of cloud properties over land and ocean surfaces. This paper evaluates the daylight cycle of CA and CWP as predicted by the Regional Atmospheric Climate Model version 2 (RACMO2), using corresponding SEVIRI retrievals. The study is done for Europe using hourly cloud properties retrievals from SEVIRI during the summer months from May to September 2004.

The results of this study show that SEVIRI-retrieved daylight cycles of CA and CWP provide a powerful tool for identifying climate model deficiencies. Over Europe the SEVIRI retrievals of cloud condensed water paths comprise about 80% liquid water and about 20% ice water. The daylight cycles of CA and CWP from SEVIRI show large spatial variations in their mean values and time of daily maximum and daytime-normalized amplitude. In general, RACMO2 overestimates CWP by about 30% and underestimates CA by about 20% as compared to SEVIRI. The largest amplitudes are observed in the Mediterranean and northern Africa. For the greater part of the ocean and coastal areas the time of daily maximum CWP is found during morning, whereas over land this maximum is found after local solar noon. These features are reasonably well captured by RACMO2. In the Mediterranean and continental Europe RACMO2 tends to predict maximum CWP associated with convection to occur about two hours earlier than SEVIRI indicates.

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M. R. van den Broeke, N. P. M. van Lipzig, and E. van Meijgaard

Abstract

Output of a regional atmospheric climate model is used to quantify the average January and July momentum budget of the atmospheric boundary layer (ABL) over the East Antarctic ice sheet and the surrounding oceans. Results are binned in nine elevation intervals over the ice sheet and six distance intervals over the ocean. In January, when surface cooling is weak, the large-scale pressure gradient force dominates the ABL momentum budget. In July, under conditions of strong surface cooling, a shallow katabatic jet develops over the gentle slopes of the interior ice sheet and a strong, deep jet over the steep coastal slopes. In the coastal regions the ABL thickens considerably, caused by the piling up of cold air over the adjacent sea ice and ice shelves. This represents the main opposing force for the katabatic winds. Horizontal and vertical advection are generally small. In the cross-slope direction the momentum budget represents a simple balance between surface drag and Coriolis turning. Intraseasonal variability of the large-scale wind field in the ABL can be explained in terms of the strength of the polar vortex, the background baroclinicity, and the topography of the ice sheet. Subsidence is found over the interior ice sheet and rising motion in the coastal zone, reflecting the acceleration and deceleration of the katabatic circulation. However, vertical velocities are generally small, because the downslope mass flux in the ABL is confined to a shallow layer below the wind speed maximum.

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Reinout Boers, Fred Bosveld, Henk Klein Baltink, Wouter Knap, Erik van Meijgaard, and Wiel Wauben

Abstract

A dataset of 9 years in duration (2009–17) of clouds and radiation was obtained at the Cabauw Experimental Site for Atmospheric Research (CESAR) in the Netherlands. Cloud radiative forcings (CRF) were derived from the dataset and related to cloud cover and temperature. Also, the data were compared with RCM output. Results indicate that there is a seasonal cycle (i.e., winter, spring, summer, and autumn) in longwave (CRF-LW: 48.3, 34.4, 30.8, and 38.7 W m−2) and shortwave (CRF-SW: −23.6, −60.9, −67.8, and −32.9 W m−2) forcings at CESAR. Total CRF is positive in winter and negative in summer. The RCM has a cold bias with respect to the observations, but the model CRF-LW corresponds well to the observed CRF-LW as a result of compensating errors in the difference function that makes up the CRF-LW. The absolute value of model CRF-SW is smaller than the observed CRF-SW in summer, mostly because of albedo differences. The majority of clouds from above 2 km are present at the same time as low clouds, so the higher clouds have only a small impact on CRF whereas low clouds dominate their values. CRF-LW is a function of fractional cloudiness. CRF-SW is also a function of fractional cloudiness, if the values are normalized by the cosine of solar zenith angle. Expressions for CRF-LW and CRF-SW were derived as functions of temperature, fractional cloudiness, and solar zenith angle, indicating that CRF is the largest when fractional cloudiness is the highest but is also large for low temperature and high sun angle.

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P. Bechtold, S. K. Krueger, W. S. Lewellen, E. van Meijgaard, C.-H. Moeng, D. A. Randall, A. van Ulden, and S. Wang

Several one-dimensional (ID) cloud/turbulence ensemble modeling results of an idealized nighttime marine stratocumulus case are compared to large eddy simulation (LES). This type of model intercomparison was one of the objects of the first Global Energy and Water Cycle Experiment Cloud System Study boundary layer modeling workshop held at the National Center for Atmospheric Research on 16–18 August 1994.

Presented are results obtained with different 1D models, ranging from bulk models (including only one or two vertical layers) to various types (first order to third order) of multilayer turbulence closure models. The ID results fall within the scatter of the LES results. It is shown that ID models can reasonably represent the main features (cloud water content, cloud fraction, and some turbulence statistics) of a well-mixed stratocumulus-topped boundary layer.

Also addressed is the question of what model complexity is necessary and can be afforded for a reasonable representation of stratocumulus clouds in mesoscale or global-scale operational models. Bulk models seem to be more appropriate for climate studies, whereas a multilayer turbulence scheme is best suited in mesoscale models having at least 100- to 200-m vertical resolution inside the boundary layer.

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S. Crewell, H. Bloemink, A. Feijt, S. G. García, D. Jolivet, O. A. Krasnov, A. van Lammeren, U. Löhnert, E. van Meijgaard, J. Meywerk, M. Quante, K. Pfeilsticker, S. Schmidt, T. Scholl, C. Simmer, M. Schröder, T. Trautmann, V. Venema, M. Wendisch, and U. Willén

Clouds cause uncertainties in the determination of climate sensitivity to either natural or anthropogenic changes. Furthermore, clouds dominate our perception of the weather, and the relatively poor forecast of cloud and precipitation parameters in numerical weather prediction (NWP) models is striking. In order to improve modeling and forecasting of clouds in climate and NWP models the BALTEX BRIDGE Campaign (BBC) was conducted in the Netherlands in August/September 2001 as a contribution to the main field experiment of the Baltic Sea Experiment (BALTEX) from April 1999 to March 2001 (BRIDGE). The complex cloud processes, which involve spatial scales from less than 1 mm (condensation nuclei) to 1000 km (frontal systems) require an integrated measurement approach. Advanced remote sensing instruments were operated at the central facility in Cabauw, Netherlands, to derive the vertical cloud structure. A regional network of stations was operated within a 100 km × 100 km domain to observe solar radiation, cloud liquid water path, cloud-base temperature, and height. Aircraft and tethered balloon measurements were used to measure cloud microphysical parameters and solar radiation below, in, and above the cloud. Satellite measurements complemented the cloud observations by providing the spatial structure from above. In order to better understand the effect of cloud inhomogeneities on the radiation field, three-dimensional radiative transfer modeling was closely linked to the measurement activities. To evaluate the performance of dynamic atmospheric models for the cloudy atmosphere four operational climate and NWP models were compared to the observations. As a first outcome of BBC we demonstrate that increased vertical resolution can improve the representation of clouds in these models.

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