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Abstract
The stratospheric quasi-biennial oscillation (QBO) in zonal wind, temperature and column ozone has been successfully modeled in a two-dimensional dynamical/chemical model by the introduction of a parameterization scheme to model the transfer of momentum to the zonal flow associated with the damping of vertically propagating Kelvin and Rossby-gravity waves. The largest amplitudes of the observed QBO in column ozone are found in high latitudes and this must be taken into account in any explanation of the increased depletion of ozone in the southern polar spring during the 1980s. A strong QBO signal in column ozone is evident in the model at all latitudes. The largest anomalies of approximately 20 DU are present at high latitudes. The equatorial ozone QBO is out of phase with the mid- and high-latitude ozone QBO. A positive (negative) ozone anomaly at the equator coincides with the presence of equatorial westerlies (easterlies) at 50 mb, in good agreement with observations. The modeled zonal wind at the equator varies from +20 m s−1 to −18 m s−1 at 25 km. The period of the modeled QBO is just over 2 yr throughout the model run except for one event when the period extends to almost 3 yr. This anomalously long period is explained in terms of the strong interaction between the modeled QBO and the seasonal cycle; in particular, the timing of the westerly phase of the QBO is influenced by the presence of the modeled semiannual oscillation (SAO). In view of this model behavior a mechanism is proposed to explain the large variability in the period of the observed QBO.
Abstract
The stratospheric quasi-biennial oscillation (QBO) in zonal wind, temperature and column ozone has been successfully modeled in a two-dimensional dynamical/chemical model by the introduction of a parameterization scheme to model the transfer of momentum to the zonal flow associated with the damping of vertically propagating Kelvin and Rossby-gravity waves. The largest amplitudes of the observed QBO in column ozone are found in high latitudes and this must be taken into account in any explanation of the increased depletion of ozone in the southern polar spring during the 1980s. A strong QBO signal in column ozone is evident in the model at all latitudes. The largest anomalies of approximately 20 DU are present at high latitudes. The equatorial ozone QBO is out of phase with the mid- and high-latitude ozone QBO. A positive (negative) ozone anomaly at the equator coincides with the presence of equatorial westerlies (easterlies) at 50 mb, in good agreement with observations. The modeled zonal wind at the equator varies from +20 m s−1 to −18 m s−1 at 25 km. The period of the modeled QBO is just over 2 yr throughout the model run except for one event when the period extends to almost 3 yr. This anomalously long period is explained in terms of the strong interaction between the modeled QBO and the seasonal cycle; in particular, the timing of the westerly phase of the QBO is influenced by the presence of the modeled semiannual oscillation (SAO). In view of this model behavior a mechanism is proposed to explain the large variability in the period of the observed QBO.
Abstract
The main field activities of the Coordinated Airborne Studies in the Tropics (CAST) campaign took place in the west Pacific during January–February 2014. The field campaign was based in Guam (13.5°N, 144.8°E), using the U.K. Facility for Airborne Atmospheric Measurements (FAAM) BAe-146 atmospheric research aircraft, and was coordinated with the Airborne Tropical Tropopause Experiment (ATTREX) project with an unmanned Global Hawk and the Convective Transport of Active Species in the Tropics (CONTRAST) campaign with a Gulfstream V aircraft. Together, the three aircraft were able to make detailed measurements of atmospheric structure and composition from the ocean surface to 20 km. These measurements are providing new information about the processes influencing halogen and ozone levels in the tropical west Pacific, as well as the importance of trace-gas transport in convection for the upper troposphere and stratosphere. The FAAM aircraft made a total of 25 flights in the region between 1°S and 14°N and 130° and 155°E. It was used to sample at altitudes below 8 km, with much of the time spent in the marine boundary layer. It measured a range of chemical species and sampled extensively within the region of main inflow into the strong west Pacific convection. The CAST team also made ground-based measurements of a number of species (including daily ozonesondes) at the Atmospheric Radiation Measurement Program site on Manus Island, Papua New Guinea (2.1°S, 147.4°E). This article presents an overview of the CAST project, focusing on the design and operation of the west Pacific experiment. It additionally discusses some new developments in CAST, including flights of new instruments on board the Global Hawk in February–March 2015.
Abstract
The main field activities of the Coordinated Airborne Studies in the Tropics (CAST) campaign took place in the west Pacific during January–February 2014. The field campaign was based in Guam (13.5°N, 144.8°E), using the U.K. Facility for Airborne Atmospheric Measurements (FAAM) BAe-146 atmospheric research aircraft, and was coordinated with the Airborne Tropical Tropopause Experiment (ATTREX) project with an unmanned Global Hawk and the Convective Transport of Active Species in the Tropics (CONTRAST) campaign with a Gulfstream V aircraft. Together, the three aircraft were able to make detailed measurements of atmospheric structure and composition from the ocean surface to 20 km. These measurements are providing new information about the processes influencing halogen and ozone levels in the tropical west Pacific, as well as the importance of trace-gas transport in convection for the upper troposphere and stratosphere. The FAAM aircraft made a total of 25 flights in the region between 1°S and 14°N and 130° and 155°E. It was used to sample at altitudes below 8 km, with much of the time spent in the marine boundary layer. It measured a range of chemical species and sampled extensively within the region of main inflow into the strong west Pacific convection. The CAST team also made ground-based measurements of a number of species (including daily ozonesondes) at the Atmospheric Radiation Measurement Program site on Manus Island, Papua New Guinea (2.1°S, 147.4°E). This article presents an overview of the CAST project, focusing on the design and operation of the west Pacific experiment. It additionally discusses some new developments in CAST, including flights of new instruments on board the Global Hawk in February–March 2015.
Accurate and reliable predictions and an understanding of future changes in the stratosphere are major aspects of the subject of climate change. Simulating the interaction between chemistry and climate is of particular importance, because continued increases in greenhouse gases and a slow decrease in halogen loading are expected. These both influence the abundance of stratospheric ozone. In recent years a number of coupled chemistry–climate models (CCMs) with different levels of complexity have been developed. They produce a wide range of results concerning the timing and extent of ozone-layer recovery. Interest in reducing this range has created a need to address how the main dynamical, chemical, and physical processes that determine the long-term behavior of ozone are represented in the models and to validate these model processes through comparisons with observations and other models. A set of core validation processes structured around four major topics (transport, dynamics, radiation, and stratospheric chemistry and microphysics) has been developed. Each process is associated with one or more model diagnostics and with relevant datasets that can be used for validation. This approach provides a coherent framework for validating CCMs and can be used as a basis for future assessments. Similar efforts may benefit other modeling communities with a focus on earth science research as their models increase in complexity.
Accurate and reliable predictions and an understanding of future changes in the stratosphere are major aspects of the subject of climate change. Simulating the interaction between chemistry and climate is of particular importance, because continued increases in greenhouse gases and a slow decrease in halogen loading are expected. These both influence the abundance of stratospheric ozone. In recent years a number of coupled chemistry–climate models (CCMs) with different levels of complexity have been developed. They produce a wide range of results concerning the timing and extent of ozone-layer recovery. Interest in reducing this range has created a need to address how the main dynamical, chemical, and physical processes that determine the long-term behavior of ozone are represented in the models and to validate these model processes through comparisons with observations and other models. A set of core validation processes structured around four major topics (transport, dynamics, radiation, and stratospheric chemistry and microphysics) has been developed. Each process is associated with one or more model diagnostics and with relevant datasets that can be used for validation. This approach provides a coherent framework for validating CCMs and can be used as a basis for future assessments. Similar efforts may benefit other modeling communities with a focus on earth science research as their models increase in complexity.
Abstract
One primary goal of annual Spring Forecasting Experiments (SFEs), which are coorganized by NOAA’s National Severe Storms Laboratory and Storm Prediction Center and conducted in the National Oceanic and Atmospheric Administration’s (NOAA) Hazardous Weather Testbed, is documenting performance characteristics of experimental, convection-allowing modeling systems (CAMs). Since 2007, the number of CAMs (including CAM ensembles) examined in the SFEs has increased dramatically, peaking at six different CAM ensembles in 2015. Meanwhile, major advances have been made in creating, importing, processing, verifying, and developing tools for analyzing and visualizing these large and complex datasets. However, progress toward identifying optimal CAM ensemble configurations has been inhibited because the different CAM systems have been independently designed, making it difficult to attribute differences in performance characteristics. Thus, for the 2016 SFE, a much more coordinated effort among many collaborators was made by agreeing on a set of model specifications (e.g., model version, grid spacing, domain size, and physics) so that the simulations contributed by each collaborator could be combined to form one large, carefully designed ensemble known as the Community Leveraged Unified Ensemble (CLUE). The 2016 CLUE was composed of 65 members contributed by five research institutions and represents an unprecedented effort to enable an evidence-driven decision process to help guide NOAA’s operational modeling efforts. Eight unique experiments were designed within the CLUE framework to examine issues directly relevant to the design of NOAA’s future operational CAM-based ensembles. This article will highlight the CLUE design and present results from one of the experiments examining the impact of single versus multicore CAM ensemble configurations.
Abstract
One primary goal of annual Spring Forecasting Experiments (SFEs), which are coorganized by NOAA’s National Severe Storms Laboratory and Storm Prediction Center and conducted in the National Oceanic and Atmospheric Administration’s (NOAA) Hazardous Weather Testbed, is documenting performance characteristics of experimental, convection-allowing modeling systems (CAMs). Since 2007, the number of CAMs (including CAM ensembles) examined in the SFEs has increased dramatically, peaking at six different CAM ensembles in 2015. Meanwhile, major advances have been made in creating, importing, processing, verifying, and developing tools for analyzing and visualizing these large and complex datasets. However, progress toward identifying optimal CAM ensemble configurations has been inhibited because the different CAM systems have been independently designed, making it difficult to attribute differences in performance characteristics. Thus, for the 2016 SFE, a much more coordinated effort among many collaborators was made by agreeing on a set of model specifications (e.g., model version, grid spacing, domain size, and physics) so that the simulations contributed by each collaborator could be combined to form one large, carefully designed ensemble known as the Community Leveraged Unified Ensemble (CLUE). The 2016 CLUE was composed of 65 members contributed by five research institutions and represents an unprecedented effort to enable an evidence-driven decision process to help guide NOAA’s operational modeling efforts. Eight unique experiments were designed within the CLUE framework to examine issues directly relevant to the design of NOAA’s future operational CAM-based ensembles. This article will highlight the CLUE design and present results from one of the experiments examining the impact of single versus multicore CAM ensemble configurations.
