Status of numerical models
Clouds in the operational Met Office mesoscale model
An overview of current numerical modelsNumerical models will never be able to represent individual clouds, so the atmosphere is split up into boxes, of typical size 50 to 200 km in the horizontal and 1 km in the vertical, and clouds within the box are represented by prognostic variables such as:
(ii) Average water content (liquid and ice)
and within a decade
Size is currently prescribed, with different liquid droplet size for marine and continental clouds, and an ice particle size which varies with temperature. Cloud overlap affects radiation and precipitation efficiency. A vertical stack of grid boxes partially filled with cloud which is continuous in the vertical is assumed to be maximally overlapped, but if they are separated by cloud free layers then overlap is assumed to be random. A further issue not yet addressed is the degree of overlap of cloud inhomogeneities within a grid box.
In the project the following variables will be observed and compared with values held in the operational models or values diagnosed from the model variables:
(ii) Cloud overlap and the overlap of cloud inhomogeneities
(iv) Droplet size
(v) Optical depth and emissivity
(vii) Ice particle size
(viii) Optical Depth
(xi) Ice water content
(xii) Liquid Water content
At the ECMWF seminar on Key Sub-grid parameterisation issues in NWP, 3-8 September 2001, the issue of sub-grid cloud variability was identified as the major difficulty needing attention if forecasts are to be improved.
To this we may add the representation of layers of supercooled clouds. These are quite common, have an important radiative effect and yet most models cannot represent them. For example, the ECMWF model represents the liquid water fraction in clouds by a simple temperature function, so that all clouds at 0°C, and the fraction falls monotonically to zero at -22°C.Currently we have virtually no observations of ice water content of clouds and yet this variable is crucial for the earth's radiative balance and for the production of precipitation. Very little is known about the frequency or characteristics of mixed phase clouds.
Each site is equipped with radar, lidar and a suite of passive instrumentation. The observations will be used in the evaluation of four operational numerical models, and to demonstrate the role that could be played by an operational network of cloud remote sensing stations. We will also be exploiting the extensive existing datasets from numerous observational campaigns that have already taken place.
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