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- Author or Editor: B. Solheim x
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Abstract
The accuracy of the Global Positioning System (GPS) as an instrument for measuring the integrated water vapor content of the atmosphere has been evaluated by comparison with concurrent observations made over a 14-day period by radiosonde, microwave water vapor radiometer (WVR), and Very Long Baseline Interferometry (VLBI). The Vaisala RS-80 A-HUMICAP radiosondes required a correction to the relative humidity readings (provided by Vaisala) to account for packaging contamination; the WVR data required a correction in order to be consistent with the wet refractivity formulation of the VLBI, GPS, and radiosondes. The best agreement of zenith wet delay (ZWD) among the collocated WVR, radiosondes, VLBI, and GPS was for minimum elevations of the GPS measurements below 10°. After corrections were applied to the WVR and radiosonde measurements, WVR, GPS, and VLBI (with 5° minimum elevation angle cutoff) agreed within ∼6 mm of ZWD [1 mm of precipitable water vapor (PWV)] when the differences were averaged, while the radiosondes averaged ∼6 mm of ZWD lower than the WVR. After the removal of biases between the techniques, the VLBI and GPS scales differ by less than 3%, while the WVR scale was ∼5% higher and the radiosonde scale was ∼5% lower. Estimates of zenith wet delay by GPS receivers equipped with Dorne–Margolin choke ring antennas were found to have a strong dependence on the minimum elevation angle of the data. Elevation angle dependent phase errors for the GPS antenna/mount combination can produce ZWD errors of greater than 30 mm over a few hour interval for typical GPS satellite coverage. The VLBI measurements of ZWD are independent of minimum elevation angle and, based on known error sources, appear to be the most accurate of the four techniques.
Abstract
The accuracy of the Global Positioning System (GPS) as an instrument for measuring the integrated water vapor content of the atmosphere has been evaluated by comparison with concurrent observations made over a 14-day period by radiosonde, microwave water vapor radiometer (WVR), and Very Long Baseline Interferometry (VLBI). The Vaisala RS-80 A-HUMICAP radiosondes required a correction to the relative humidity readings (provided by Vaisala) to account for packaging contamination; the WVR data required a correction in order to be consistent with the wet refractivity formulation of the VLBI, GPS, and radiosondes. The best agreement of zenith wet delay (ZWD) among the collocated WVR, radiosondes, VLBI, and GPS was for minimum elevations of the GPS measurements below 10°. After corrections were applied to the WVR and radiosonde measurements, WVR, GPS, and VLBI (with 5° minimum elevation angle cutoff) agreed within ∼6 mm of ZWD [1 mm of precipitable water vapor (PWV)] when the differences were averaged, while the radiosondes averaged ∼6 mm of ZWD lower than the WVR. After the removal of biases between the techniques, the VLBI and GPS scales differ by less than 3%, while the WVR scale was ∼5% higher and the radiosonde scale was ∼5% lower. Estimates of zenith wet delay by GPS receivers equipped with Dorne–Margolin choke ring antennas were found to have a strong dependence on the minimum elevation angle of the data. Elevation angle dependent phase errors for the GPS antenna/mount combination can produce ZWD errors of greater than 30 mm over a few hour interval for typical GPS satellite coverage. The VLBI measurements of ZWD are independent of minimum elevation angle and, based on known error sources, appear to be the most accurate of the four techniques.
Abstract
A new approach of coordinated global and regional climate modeling is presented. It is applied to the Canadian Centre for Climate Modelling and Analysis Regional Climate Model (CanRCM4) and its parent global climate model CanESM2. CanRCM4 was developed specifically to downscale climate predictions and climate projections made by its parent global model. The close association of a regional climate model (RCM) with a parent global climate model (GCM) offers novel avenues of model development and application that are not typically available to independent regional climate modeling centers. For example, when CanRCM4 is driven by its parent model, driving information for all of its prognostic variables is available (including aerosols and chemical species), significantly improving the quality of their simulation. Additionally, CanRCM4 can be driven by its parent model for all downscaling applications by employing a spectral nudging procedure in CanESM2 designed to constrain its evolution to follow any large-scale driving data. Coordination offers benefit to the development of physical parameterizations and provides an objective means to evaluate the scalability of such parameterizations across a range of spatial resolutions. Finally, coordinating regional and global modeling efforts helps to highlight the importance of assessing RCMs’ value added relative to their driving global models. As a first step in this direction, a framework for identifying appreciable differences in RCM versus GCM climate change results is proposed and applied to CanRCM4 and CanESM2.
Abstract
A new approach of coordinated global and regional climate modeling is presented. It is applied to the Canadian Centre for Climate Modelling and Analysis Regional Climate Model (CanRCM4) and its parent global climate model CanESM2. CanRCM4 was developed specifically to downscale climate predictions and climate projections made by its parent global model. The close association of a regional climate model (RCM) with a parent global climate model (GCM) offers novel avenues of model development and application that are not typically available to independent regional climate modeling centers. For example, when CanRCM4 is driven by its parent model, driving information for all of its prognostic variables is available (including aerosols and chemical species), significantly improving the quality of their simulation. Additionally, CanRCM4 can be driven by its parent model for all downscaling applications by employing a spectral nudging procedure in CanESM2 designed to constrain its evolution to follow any large-scale driving data. Coordination offers benefit to the development of physical parameterizations and provides an objective means to evaluate the scalability of such parameterizations across a range of spatial resolutions. Finally, coordinating regional and global modeling efforts helps to highlight the importance of assessing RCMs’ value added relative to their driving global models. As a first step in this direction, a framework for identifying appreciable differences in RCM versus GCM climate change results is proposed and applied to CanRCM4 and CanESM2.
On 20 February 2001, a converted Russian ICBM delivered Odin, a small Swedish satellite, into low Earth orbit. One of the sensors onboard is a small Canadian spectrometer called OSIRIS. By measuring scattered sunlight from Earth's horizon, or limb, OSIRIS is able to deduce the abundance of trace gases and particles from the upper troposphere into the lower thermosphere. Designed and built on a modest budget, OSIRIS has exceeded not only its 2-yr lifetime but also all expectations. With more than a decade of continuous data, OSIRIS has recorded over 1.8 million limb scans. The complexities associated with unraveling scattered light in order to convert OSIRIS spectra into highquality geophysical profiles have forced the OSIRIS team to develop leading-edge algorithms and computer models. These profiles are being used to help address many science questions, including the coupling of atmospheric regions (e.g., stratosphere–troposphere exchange) and the budgets and trends in ozone, nitrogen, bromine, and other species. One specific example is the distribution and abundance of upper-tropospheric, lightning-produced reactive nitrogen and ozone. Arguably OSIRIS's most important contributions come from its aerosol measurements, including detection and characterization of subvisual cirrus and polar stratospheric and mesospheric clouds. OSIRIS also provides a unique view of the stratospheric aerosol layer, and it is able to identify and track perturbations from volcanic activity and biomass burning.
On 20 February 2001, a converted Russian ICBM delivered Odin, a small Swedish satellite, into low Earth orbit. One of the sensors onboard is a small Canadian spectrometer called OSIRIS. By measuring scattered sunlight from Earth's horizon, or limb, OSIRIS is able to deduce the abundance of trace gases and particles from the upper troposphere into the lower thermosphere. Designed and built on a modest budget, OSIRIS has exceeded not only its 2-yr lifetime but also all expectations. With more than a decade of continuous data, OSIRIS has recorded over 1.8 million limb scans. The complexities associated with unraveling scattered light in order to convert OSIRIS spectra into highquality geophysical profiles have forced the OSIRIS team to develop leading-edge algorithms and computer models. These profiles are being used to help address many science questions, including the coupling of atmospheric regions (e.g., stratosphere–troposphere exchange) and the budgets and trends in ozone, nitrogen, bromine, and other species. One specific example is the distribution and abundance of upper-tropospheric, lightning-produced reactive nitrogen and ozone. Arguably OSIRIS's most important contributions come from its aerosol measurements, including detection and characterization of subvisual cirrus and polar stratospheric and mesospheric clouds. OSIRIS also provides a unique view of the stratospheric aerosol layer, and it is able to identify and track perturbations from volcanic activity and biomass burning.
