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Abstract
Supercooled 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 shows a more realistic cloud structure, with an SLW layer at cloud top and ice falling out below. However, because of the limited vertical and horizontal resolution and uncertainties in the parameterization of physical processes near cloud top, the change leads to an overall reduction in SLW water with a detrimental impact on shortwave and longwave radiative fluxes, and increased 2-m temperature errors over land. A reduction in the ice deposition rate at cloud top significantly improves the SLW occurrence and radiative impacts, and highlights the need for improved understanding and parameterization of physical processes for mixed-phase cloud in large-scale models.
Abstract
Supercooled 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 shows a more realistic cloud structure, with an SLW layer at cloud top and ice falling out below. However, because of the limited vertical and horizontal resolution and uncertainties in the parameterization of physical processes near cloud top, the change leads to an overall reduction in SLW water with a detrimental impact on shortwave and longwave radiative fluxes, and increased 2-m temperature errors over land. A reduction in the ice deposition rate at cloud top significantly improves the SLW occurrence and radiative impacts, and highlights the need for improved understanding and parameterization of physical processes for mixed-phase cloud in large-scale models.
Abstract
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.
Abstract
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.
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 of ground-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.
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 of ground-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.
