Richard M. Forbes

Characteristics of high-resolution versions of the Met Office unified model for forecasting convection over the United Kingdom

With many operational centers moving toward order 1-km-gridlength models for routine weather forecasting, this paper presents a systematic investigation of the properties of high-resolution versions of the Met Office Unified Model for short-range forecasting of convective rainfall events. The authors describe a suite of configurations of the Met Office Unified Model running with grid lengths of 12, 4, and 1 km and analyze results from these models for a number of convective cases from the summers of 2003, 2004, and 2005. The analysis includes subjective evaluation of the rainfall fields and comparisons of rainfall amounts, initiation, cell statistics, and a scale-selective verification technique. It is shown that the 4- and 1-km-gridlength models often give more realistic-looking precipitation fields because convection is represented explicitly rather than parameterized. However, the 4-km model representation suffers from large convective cells and delayed initiation because the grid length is too long to correctly reproduce the convection explicitly. These problems are not as evident in the 1-km model, although it does suffer from too numerous small cells in some situations. Both the 4- and 1-km models suffer from poor representation at the start of the forecast in the period when the high-resolution detail is spinning up from the lower-resolution (12 km) starting data used. A scale-selective precipitation verification technique implies that for later times in the forecasts (after the spinup period) the 1-km model performs better than the 12- and 4-km models for lower rainfall thresholds. For higher thresholds the 4-km model scores almost as well as the 1-km model, and both do better than the 12-km model.

Assessment of the FOAM global data assimilation system for real-time operational ocean forecasting

Abstract An operational system to forecast the state of the global ocean a few days ahead has been implemented at the UK Met. Office (UKMO). The system, known as the Forecasting Ocean Assimilation Model (FOAM), consists of a 1°×1° resolution numerical ocean model driven by surface fluxes from the UKMO numerical weather prediction (NWP) suite and a modified successive correction data assimilation scheme for thermal observations. The assimilation scheme is assessed here in a series of 1-year integrations by comparison with ‘independent’ thermal profile observations and climatology. Assimilating temperature observations significantly reduces model errors in the upper ocean and results in temperature analyses that on average are closer to independent observations than climatology. The specific results depend on location and depth. The extent to which the data assimilation scheme is able to compensate for uncertainties in the surface forcing fluxes is also assessed by comparing integrations forced with climatological and NWP fluxes. Assimilating data is able to compensate for uncertainties in the surface heat forcing fluxes and significantly reduces the impact from uncertainties in the surface wind stress.

The Convective Storm Initiation Project

The Convective Storm Initiation Project (CSIP) is an international project to understand precisely where, when, and how convective clouds form and develop into showers in the mainly maritime environment of southern England. A major aim of CSIP is to compare the results of the very high resolution Met Office weather forecasting model with detailed observations of the early stages of convective clouds and to use the newly gained understanding to improve the predictions of the model. A large array of ground-based instruments plus two instrumented aircraft, from the U.K. National Centre for Atmospheric Science (NCAS) and the German Institute for Meteorology and Climate Research (IMK), Karlsruhe, were deployed in southern England, over an area centered on the meteorological radars at Chilbolton, during the summers of 2004 and 2005. In addition to a variety ofground-based remote-sensing instruments, numerous rawinsondes were released at one- to two-hourly intervals from six closely spaced sites. The Met Office weather radar network and Meteosat satellite imagery were used to provide context for the observations made by the instruments deployed during CSIP. This article presents an overview of the CSIP field campaign and examples from CSIP of the types of convective initiation phenomena that are typical in the United Kingdom. It shows the way in which certain kinds of observational data are able to reveal these phenomena and gives an explanation of how the analyses of data from the field campaign will be used in the development of an improved very high resolution NWP model for operational use.

Global versus Local MJO Forecast Skill of the ECMWF Model during DYNAMO

AbstractThis study introduces a concept of global versus local forecast skill of the Madden–Julian oscillation (MJO). The global skill, measured by a commonly used MJO index [the Real-time Multivariate MJO (RMM)], evaluates the model’s capability of forecasting global patterns of the MJO, with an emphasis on the zonal wind fields. The local skill is measured by a method of tracking the eastward propagation of MJO precipitation. It provides quantitative information of the strength, propagation speed, and timing of MJO precipitation in a given region, such as the Indian Ocean. Both global and local MJO forecast skills are assessed for ECMWF forecasts of three MJO events during the 2011–12 Dynamics of the MJO (DYNAMO) field campaign. Characteristics of error growth differ substantially between global and local MJO forecast skills, and between the three MJO quantities (strength, speed, and timing) of the local skill measure. They all vary considerably among the three MJO events. Deterioration in global foreca...

On the Representation of High-Latitude Boundary Layer Mixed-Phase Cloud in the ECMWF Global Model

AbstractSupercooled liquid water (SLW) layers in boundary layer clouds are abundantly observed in the atmosphere at high latitudes, but remain a challenge to represent in numerical weather prediction (NWP) and climate models. Unresolved processes such as small-scale turbulence and mixed-phase microphysics act to maintain the liquid layer at cloud top, directly affecting cloud radiative properties and prolonging cloud lifetimes. This paper describes the representation of supercooled liquid water in boundary layer clouds in the European Centre for Medium-Range Weather Forecasts (ECMWF) global NWP model and in particular the change from a diagnostic temperature-dependent mixed phase to a prognostic representation with separate cloud liquid and ice variables. Data from the Atmospheric Radiation Measurement site in Alaska and from the CloudSat/Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) satellite missions are used to evaluate the model parameterizations. The prognostic scheme s...

The Impact of Low Clouds on Surface Shortwave Radiation in the ECMWF Model

AbstractThe long-term measurement records from the Atmospheric Radiation Measurement site on the Southern Great Plains show evidence of a bias in the ECMWF model’s surface irradiance. Based on previous studies, which have suggested that summertime shallow clouds may contribute to the bias, an evaluation of 146 days with observed nonprecipitating fair-weather cumulus clouds is performed. In-cloud liquid water path and effective radius are both overestimated in the model with liquid water path dominating to produce clouds that are too reflective. These are compensated by occasional cloud-free days in the model such that the fair-weather cumulus regime overall does not contribute significantly to the multiyear daytime mean surface irradiance bias of 23 W m−2. To further explore the origin of the bias, observed and modeled cloud fraction profiles over 6 years are classified and sorted based on the surface irradiance bias associated with each sample pair. Overcast low cloud conditions during the spring and fal...

Improving the Representation of Low Clouds and Drizzle in the ECMWF Model Based on ARM Observations from the Azores

AbstractIn this study, the representation of marine boundary layer clouds is investigated in the ECMWF model using observations from the Atmospheric Radiation Measurement (ARM) mobile facility deployment to Graciosa Island in the North Atlantic. Systematic errors in the occurrence of clouds, liquid water path, precipitation, and surface radiation are assessed in the operational model for a 19-month-long period. Boundary layer clouds were the most frequently observed cloud type but were underestimated by 10% in the model. Systematic but partially compensating surface radiation errors exist and can be linked to opposing cloud cover and liquid water path errors in broken (shallow cumulus) and overcast (stratocumulus) low-cloud regimes, consistent with previously reported results from the continental ARM Southern Great Plains (SGP) site. Occurrence of precipitation is overestimated by a factor of 1.5 at cloud base and by a factor of 2 at the surface, suggesting deficiencies in both the warm-rain formation and...

Characterizing the radiative impacts of precipitating snow in the ECMWF Integrated Forecast System global model

Global weather and climate models often exclude the effects of precipitating hydrometeors and convective core mass on radiative fluxes. In particular, many models split the ice phase into separate “cloud ice” and “snow” categories representing the smaller and larger ice particles, respectively; a separation that is generally not well defined in observations. A version of the European Centre for Medium-Range Weather Forecasts (ECMWF) global numerical weather prediction model which includes the radiative effects of cloud liquid, cloud ice, and precipitating snow is used to investigate the impact of including and excluding the radiative effects of the precipitating snow category. The results show that exclusion of precipitating snow in the radiation calculations leads to differences in the shortwave and longwave radiative fluxes of 5–15 W m−2 in strongly precipitating and convective areas. These differences are of the same order of magnitude as the systematic errors in the model compared to satellite observations. Corresponding biases in the radiative heating profiles are on the order of 0.15 K d−1. The results imply that precipitating snow should be included in the radiative calculations in all weather and climate models in the context of improving model fidelity and reducing compensating errors.

Using satellite and reanalysis data to evaluate the representation of latent heating in extratropical cyclones in a climate model

Extratropical cyclones are a key feature of the weather in the extratropics, which climate models need to represent in order to provide reliable projections of future climate. Extratropical cyclones produce significant precipitation and the associated latent heat release can play a major role in their development. This study evaluates the ability of a climate model, HiGEM, to represent latent heating in extratropical cyclones. Remote sensing data is used to investigate the ability of both the climate model and ERA-Interim (ERAI) reanalysis to represent extratropical cyclone cloud features before latent heating itself is assessed. An offline radiance simulator, COSP, and the ISCCP and CloudSat datasets are used to evaluate comparable fields from HiGEM and ERAI. HiGEM is found to exhibit biases in the cloud structure of extratropical cyclones, with too much high cloud produced in the warm conveyor belt region compared to ISCCP. Significant latent heating occurs in this region, derived primarily from HiGEM’s convection scheme. ERAI is also found to exhibit biases in cloud structure, with more clouds at lower altitudes than those observed in ISCCP in the warm conveyor belt region. As a result, latent heat release in ERAI is concentrated at lower altitudes. CloudSat indicates that much precipitation may be produced at too low an altitude in both HiGEM and ERAI, particularly ERAI, and neither capture observed variability in precipitation intensity. The potential vorticity structure in composite extratropical cyclones in HiGEM and ERAI is also compared. A more pronounced tropopause ridge evolves in HiGEM on the leading edge of the composite as compared to ERAI. One future area of research to be addressed is what impact these biases in the representation of latent heating have on climate projections produced by HiGEM. The biases found in ERAI indicate caution is required when using reanalyses to study cloud features and precipitation processes in extratropical cyclones or using reanalysis to evaluate climate models’ ability to represent their structure.

Katabatic winds diminish precipitation contribution to the Antarctic ice mass balance

Significance Precipitation over Antarctica remains largely unknown, despite its crucial role in the surface mass balance of the Antarctic ice sheet. Using unprecedented observations covering an entire year, this work describes a previously unknown mechanism that leads to the sublimation of a large fraction of snowfall in the lower atmosphere, resulting from the interaction of precipitation and katabatic winds. Snowfall sublimation in the atmosphere, caused by katabatic winds, is in the order of 35% in the margins of East Antarctica. This process critically affects the interpretation of satellite-based remote sensing observations close to the ground and suggests that snowfall sublimation in a warming climate may counterbalance the expected increase of precipitation. Snowfall in Antarctica is a key term of the ice sheet mass budget that influences the sea level at global scale. Over the continental margins, persistent katabatic winds blow all year long and supply the lower troposphere with unsaturated air. We show that this dry air leads to significant low-level sublimation of snowfall. We found using unprecedented data collected over 1 year on the coast of Adélie Land and simulations from different atmospheric models that low-level sublimation accounts for a 17% reduction of total snowfall over the continent and up to 35% on the margins of East Antarctica, significantly affecting satellite-based estimations close to the ground. Our findings suggest that, as climate warming progresses, this process will be enhanced and will limit expected precipitation increases at the ground level.