Abstract. We describe the HadGEM2 family of climate configurations of the Met Office Unified Model, MetUM. The concept of a model "family" comprises a range of specific model configurations incorporating different levels of complexity but with a common physical framework. The HadGEM2 family of configurations includes atmosphere and ocean components, with and without a vertical extension to include a well-resolved stratosphere, and an Earth-System (ES) component which includes dynamic vegetation, ocean biology and atmospheric chemistry. The HadGEM2 physical model includes improvements designed to address specific systematic errors encountered in the previous climate configuration, HadGEM1, namely Northern Hemisphere continental temperature biases and tropical sea surface temperature biases and poor variability. Targeting these biases was crucial in order that the ES configuration could represent important biogeochemical climate feedbacks. Detailed descriptions and evaluations of particular HadGEM2 family memCorrespondence to: G. M. Martin (gill.martin@metoffice.gov.uk) bers are included in a number of other publications, and the discussion here is limited to a summary of the overall performance using a set of model metrics which compare the way in which the various configurations simulate present-day climate and its variability.

SUMMARYThree improvements to the representation of orography for use in numerical weather-and climate-prediction models are presented. The rst improvement is to replace the US Navy dataset with a new digitally generated dataset as the de nition of the true earth topography. There are large differences on all scales between the two datasets and these lead to large differences in the mean and subgrid-scale elds that are derived from them. The second improvement is to lter the mean and subgrid-scale orography (SSO) elds to remove grid-scale and neargrid-scale features and thus suppress forcing on scales that the model cannot treat well. The third improvement is to implement a new, simple parametrization of the effects of SSO in which the total surface pressure drag is calculated using the analytical expression for linear hydrostatic ow over a two-dimensional ridge in the absence of friction and rotation. The surface pressure drag is partitioned into gravity-wave and blocked-ow components that depend on the Froude number of the ow impinging on the SSO. The new scheme attributes about 70% of the total drag to ow blocking.These improvements have been incorporated into a new version of the Met Of ce Uni ed Model. A series of numerical weather-prediction experiments demonstrates that the introduction of the new SSO scheme is the most signi cant change. In particular, signi cant improvements to forecast skill, attributable to the SSO scheme's ow-blocking drag component, are found at low levels in the northern hemisphere and the Tropics for an extended northern hemisphere wintertime forecast trial. Furthermore, there are no signi cant degradations in skill at upper levels, in the southern hemisphere or for summertime trials.

Abstract. Currently, no extensive, near real time, global soil moisture observation network exists. Therefore, the Met Office global soil moisture analysis scheme has instead used observations of screen temperature and humidity. A number of new space-borne remote sensing systems, operating at microwave frequencies, have been developed that provide a more direct retrieval of surface soil moisture. These systems are attractive since they provide global data coverage and the horizontal resolution is similar to weather forecasting models. Several studies show that measurements of normalised backscatter (surface soil wetness) from the Advanced Scatterometer (ASCAT) on the meteorological operational (MetOp) satellite contain good quality information about surface soil moisture. This study describes methods to convert ASCAT surface soil wetness measurements to volumetric surface soil moisture together with bias correction and quality control. A computationally efficient nudging scheme is used to assimilate the ASCAT volumetric surface soil moisture data into the Met Office global soil moisture analysis. This ASCAT nudging scheme works alongside a soil moisture nudging scheme that uses observations of screen temperature and humidity. Trials, using the Met Office global Unified Model, of the ASCAT nudging scheme show a positive impact on forecasts of screen temperature and humidity for the tropics, North America and Australia. A comparison with in-situ soil moisture measurements from the US also indicates that assimilation of ASCAT surface soil wetness improves the soil moisture analysis. Assimilation of ASCAT surface soil wetness measurements became operational during July 2010.

Surface precipitation‐rate estimates derived from radar data are potentially of considerable value to high‐resolution Numerical Weather Prediction (NWP) models. This paper describes a scheme developed to assimilate precipitation rates derived from the UK weather radar network into the UK Met. Office Mesoscale Model, with the aim of improving the analysis and forecast of precipitation. It is based on ‘latent heat nudging’, in which the model profiles of latent heating are scaled by the ratio of observed and model precipitation rates. This causes the model to adjust so that the diagnosed precipitation rate agrees more closely with observations. The assimilation algorithm is outlined, and the results of a trial of the scheme are described. The scheme brings an increase in forecast skill for precipitation distribution in the first six to nine hours of the forecast, a conclusion supported both by objective verification against radar data and subjective assessment of 14 forecasts. The main benefit was found to occur in frontal cases. The scheme was implemented operationally on 16 April 1996. Copyright © 1997 Royal Meteorological Society

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