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The Atmospheric Radiation Measurement (ARM) Mobile Facility (AMF) was recently developed to enable collection of detailed climate data in locations not currently sampled by ARM's five fixed sites. The AMF includes a comprehensive suite of active and passive remote sensors, including cloud radar, that sample the atmosphere in a narrow column above its location. Surface radiation, aerosols, and fluxes are also measured and there is an ancillary measurement facility to help quantify local gradients. The AMF is deployed at no cost to the principal investigator or institution for periods from six months to one year on the basis of an international proposal competition judged by a nonpartisan board. The proposal to ARM that led to the initial international deployment of the AMF in Niamey, Niger, was titled “Radiative Atmospheric Divergence Using the AMF, GERB Data, and AMMA Stations (RADAGAST).” This paper provides a description of the instruments that compose the AMF, its charter, a description of its deployment in support of RADAGAST, and examples of data that have been collected in Africa.
The Atmospheric Radiation Measurement (ARM) Mobile Facility (AMF) was recently developed to enable collection of detailed climate data in locations not currently sampled by ARM's five fixed sites. The AMF includes a comprehensive suite of active and passive remote sensors, including cloud radar, that sample the atmosphere in a narrow column above its location. Surface radiation, aerosols, and fluxes are also measured and there is an ancillary measurement facility to help quantify local gradients. The AMF is deployed at no cost to the principal investigator or institution for periods from six months to one year on the basis of an international proposal competition judged by a nonpartisan board. The proposal to ARM that led to the initial international deployment of the AMF in Niamey, Niger, was titled “Radiative Atmospheric Divergence Using the AMF, GERB Data, and AMMA Stations (RADAGAST).” This paper provides a description of the instruments that compose the AMF, its charter, a description of its deployment in support of RADAGAST, and examples of data that have been collected in Africa.
Abstract
The longwave radiation emitted by the atmosphere toward the surface [downward longwave radiation (DLR)] is a crucial factor in the exchange of energy between the earth surface and the atmosphere and in the context of radiation-induced climate change. Accurate modeling of this quantity is therefore a fundamental prerequisite for a reliable simulation and projection of the surface climate in coupled general circulation models (GCM).
DLR climatologies calculated in a number of GCMs and in a model in assimilation mode (reanalysis) are analyzed using newly available data from 45 worldwide distributed observation sites of the Global Energy Balance Archive (GEBA) and the Baseline Surface Radiation Network (BSRN). It is shown that substantial biases are present in the GCM-calculated DLR climatologies, with the GCMs typically underestimating the DLR (estimated here to be approximately 344 W m−2 globally). The biases are, however, not geographically homogeneous, but depend systematically on the prevailing atmospheric conditions. The DLR is significantly underestimated particularly at observation sites with cold and dry climates and thus little DLR emission. This underestimation gradually diminishes toward sites with more moderate climates; at sites with warm or humid atmospheric conditions and strong DLR emission, the GCM-calculated DLR is in better agreement with the observations or even overestimates them. This is equivalent to creating an excessively strong meridional gradient of DLR in the GCMs.
The very same tendencies are independently found in stand-alone calculations with the GCM radiation codes in isolation, using observed atmospheric profiles of temperature and humidity for cloud-free conditions as input to the radiation schemes. A significant underestimation of DLR is calculated by the radiation schemes when driven with clear-sky atmospheric profiles of temperature and humidity representative for cold and dry climates, whereas the DLR is no longer underestimated by the radiation schemes with prescribed clear-sky profiles representative for a hot and humid atmosphere. This suggests that the biases in the GCM-calculated DLR climatologies are predominantly induced by problems in the simulated emission of the cloud-free atmosphere.
The same biases are also found in the DLR fluxes calculated by the European Centre for Medium-Range Weather Forecasts (ECMWF) model in assimilation mode (reanalysis), in which the biases in the atmospheric thermal and humidity structure are minimized. This gives further support that the biases in the DLR are not primarily due to errors in the model-predicted atmospheric temperature and humidity profiles that enter the radiative transfer calculations, but rather are due to the radiation schemes themselves. A particular problem in these schemes is the accurate simulation of the thermal emission from the cold, dry, cloud-free atmosphere.
Abstract
The longwave radiation emitted by the atmosphere toward the surface [downward longwave radiation (DLR)] is a crucial factor in the exchange of energy between the earth surface and the atmosphere and in the context of radiation-induced climate change. Accurate modeling of this quantity is therefore a fundamental prerequisite for a reliable simulation and projection of the surface climate in coupled general circulation models (GCM).
DLR climatologies calculated in a number of GCMs and in a model in assimilation mode (reanalysis) are analyzed using newly available data from 45 worldwide distributed observation sites of the Global Energy Balance Archive (GEBA) and the Baseline Surface Radiation Network (BSRN). It is shown that substantial biases are present in the GCM-calculated DLR climatologies, with the GCMs typically underestimating the DLR (estimated here to be approximately 344 W m−2 globally). The biases are, however, not geographically homogeneous, but depend systematically on the prevailing atmospheric conditions. The DLR is significantly underestimated particularly at observation sites with cold and dry climates and thus little DLR emission. This underestimation gradually diminishes toward sites with more moderate climates; at sites with warm or humid atmospheric conditions and strong DLR emission, the GCM-calculated DLR is in better agreement with the observations or even overestimates them. This is equivalent to creating an excessively strong meridional gradient of DLR in the GCMs.
The very same tendencies are independently found in stand-alone calculations with the GCM radiation codes in isolation, using observed atmospheric profiles of temperature and humidity for cloud-free conditions as input to the radiation schemes. A significant underestimation of DLR is calculated by the radiation schemes when driven with clear-sky atmospheric profiles of temperature and humidity representative for cold and dry climates, whereas the DLR is no longer underestimated by the radiation schemes with prescribed clear-sky profiles representative for a hot and humid atmosphere. This suggests that the biases in the GCM-calculated DLR climatologies are predominantly induced by problems in the simulated emission of the cloud-free atmosphere.
The same biases are also found in the DLR fluxes calculated by the European Centre for Medium-Range Weather Forecasts (ECMWF) model in assimilation mode (reanalysis), in which the biases in the atmospheric thermal and humidity structure are minimized. This gives further support that the biases in the DLR are not primarily due to errors in the model-predicted atmospheric temperature and humidity profiles that enter the radiative transfer calculations, but rather are due to the radiation schemes themselves. A particular problem in these schemes is the accurate simulation of the thermal emission from the cold, dry, cloud-free atmosphere.
Abstract
Two altocumulus clouds, which formed at a temperature of −30°C, were sampled using the NCAR King Air aircraft and coincident lidar during the 1986 FIRE cirrus experiment in Wisconsin. The clouds were structurally and thermodynamically similar to stratocumulus, with extensive cloudtop entrainment, a capping temperature inversion, and a dry layer above.
The microphysical and radiative properties of both clouds were characterized and modeled numerically. Calculations of droplet concentration and mean diameter profiles compare favorably with the measurements when entrainment effects are incorporated in the model.
Radiative transfer calculations suggest radiation played an important role in driving convection in the more dynamically unstable of the two clouds. A simple model shows that radiative cooling causes sufficient negative buoyancy in cloudtop parcels to produce convective instability and to reproduce the observed downdraft velocities. Entrainment of warmer, drier air near cloudtop is shown to partially counteract the radiatively induced negative buoyancy in the downdrafts.
Abstract
Two altocumulus clouds, which formed at a temperature of −30°C, were sampled using the NCAR King Air aircraft and coincident lidar during the 1986 FIRE cirrus experiment in Wisconsin. The clouds were structurally and thermodynamically similar to stratocumulus, with extensive cloudtop entrainment, a capping temperature inversion, and a dry layer above.
The microphysical and radiative properties of both clouds were characterized and modeled numerically. Calculations of droplet concentration and mean diameter profiles compare favorably with the measurements when entrainment effects are incorporated in the model.
Radiative transfer calculations suggest radiation played an important role in driving convection in the more dynamically unstable of the two clouds. A simple model shows that radiative cooling causes sufficient negative buoyancy in cloudtop parcels to produce convective instability and to reproduce the observed downdraft velocities. Entrainment of warmer, drier air near cloudtop is shown to partially counteract the radiatively induced negative buoyancy in the downdrafts.
