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Abstract
A semi-objective procedure has been developed to modify mean sea level pressure and 1000–500 mb thickness using cloud vortex patterns obtained from satellite imagery. The method combines the previous work of Nagle and Hayden (1971) and Troup and Streten (1972), and is designed for operational use, particularly in the Southern Hemisphere. The method is capable of reproducing synoptic-scale structure which can be deduced from cloud data, but which is often difficult to incorporate in a numerical analysis system using “bogus” observations. Two case studies are used to illustrate its application: the first demonstrates the ability of the procedure to correct large-scale “first guess” errors, and the second compares results of a forecast/analysis cycle using this method with operational products of the National Meteorological Analysis Centre of the Australian Bureau of Meteorology.
Abstract
A semi-objective procedure has been developed to modify mean sea level pressure and 1000–500 mb thickness using cloud vortex patterns obtained from satellite imagery. The method combines the previous work of Nagle and Hayden (1971) and Troup and Streten (1972), and is designed for operational use, particularly in the Southern Hemisphere. The method is capable of reproducing synoptic-scale structure which can be deduced from cloud data, but which is often difficult to incorporate in a numerical analysis system using “bogus” observations. Two case studies are used to illustrate its application: the first demonstrates the ability of the procedure to correct large-scale “first guess” errors, and the second compares results of a forecast/analysis cycle using this method with operational products of the National Meteorological Analysis Centre of the Australian Bureau of Meteorology.
To test the impact of high-resolution Nimbus-6 sounding data on Australian region forecasts, two parallel analysis/forecast cycling experiments were carried out, using data for 14 days during August and September 1975. In one of these cycles, only conventional data and manual interpretation of satellite imagery were used as input, while the other cycle used conventional and Nimbus-6 sounding data. A manual mean sea level pressure analysis was used in each cycle to provide reference level information over the oceans.
Two series of 24 h limited area prognoses were prepared from these two sets of analyses, using the primitive equations prognosis model developed at the Australian Numerical Meteorology Research Centre. An average improvement in geopotential forecasts of more than 5 skill score points was achieved at all levels over the Australian continent when the Nimbus-6 data were included in the base analyses. Also, significant reductions were obtained in 24 h forecast root-mean-square (rms) temperature errors.
To test the impact of high-resolution Nimbus-6 sounding data on Australian region forecasts, two parallel analysis/forecast cycling experiments were carried out, using data for 14 days during August and September 1975. In one of these cycles, only conventional data and manual interpretation of satellite imagery were used as input, while the other cycle used conventional and Nimbus-6 sounding data. A manual mean sea level pressure analysis was used in each cycle to provide reference level information over the oceans.
Two series of 24 h limited area prognoses were prepared from these two sets of analyses, using the primitive equations prognosis model developed at the Australian Numerical Meteorology Research Centre. An average improvement in geopotential forecasts of more than 5 skill score points was achieved at all levels over the Australian continent when the Nimbus-6 data were included in the base analyses. Also, significant reductions were obtained in 24 h forecast root-mean-square (rms) temperature errors.
Abstract
Reconstructions of winter (December-February) sea level pressure (SLP) from western North American tree-ring chronologies are compared with a proxy record of winter severity in Japan derived from the historically documented freeze dates of Lake Suwa. The SLP reconstructions extend from 1602 to 1961 and freeze dates from 1443 to 1954. The instrumental and reconstructed SLP for the 20th century reveal two distinct circulation regimes (teleconnection patterns) over the North Pacific that appear to be associated with severe and mild winters and, consequently, with early and late freezing of the lake. The reconstructed SLP anomaly map for severe winters prior to 1683 shows a pattern similar to those in the instrumental and reconstructed records of the 20th century. The analysis reveals that the reliability of the reconstruction may vary with the configuration of the actual SLP pattern as the mild winter pattern is not as well reconstructed as the severe winter pattern. That result illustrates the importance of testing the reliability of a reconstruction within the context of the intended interpretation. This analysis demonstrates how different types of proxy climate data can be compared and verified.
Abstract
Reconstructions of winter (December-February) sea level pressure (SLP) from western North American tree-ring chronologies are compared with a proxy record of winter severity in Japan derived from the historically documented freeze dates of Lake Suwa. The SLP reconstructions extend from 1602 to 1961 and freeze dates from 1443 to 1954. The instrumental and reconstructed SLP for the 20th century reveal two distinct circulation regimes (teleconnection patterns) over the North Pacific that appear to be associated with severe and mild winters and, consequently, with early and late freezing of the lake. The reconstructed SLP anomaly map for severe winters prior to 1683 shows a pattern similar to those in the instrumental and reconstructed records of the 20th century. The analysis reveals that the reliability of the reconstruction may vary with the configuration of the actual SLP pattern as the mild winter pattern is not as well reconstructed as the severe winter pattern. That result illustrates the importance of testing the reliability of a reconstruction within the context of the intended interpretation. This analysis demonstrates how different types of proxy climate data can be compared and verified.
Abstract
Results are presented from the Actinic Flux Determination from Measurements of Irradiance (ADMIRA) campaign to measure spectral global UV irradiance and actinic flux at the ground, beneath an atmosphere well defined by supporting measurements. Actinic flux is required to calculate photolysis rates for atmospheric chemistry, yet most spectral UV measurements are of irradiance. This work represents the first part of a project to provide algorithms for converting irradiances to actinic fluxes with specified uncertainties. The campaign took place in northern Greece in August 2000 and provided an intercomparison of UV spectroradiometers measuring different radiation parameters, as well as a comprehensive radiation and atmospheric dataset. The independently calibrated spectroradiometers measuring irradiance and actinic flux agreed to within 5%, while measurements of spectral direct irradiance differed by 9%. Relative agreement for all parameters proved to be very stable during the campaign. A polarization problem in the Brewer spectrophotometer was identified as a problem in making radiance distribution measurements with this instrument. At UV wavelengths actinic fluxes F were always greater than the corresponding irradiance E by a factor between 1.4 and 2.6. The value of the ratio F : E depended on wavelength, solar zenith angle, and the optical properties of the atmosphere. Both the wavelength and solar zenith angle dependency of the ratio decreased when the scattering in the atmosphere increased and the direct beam proportion of global irradiance decreased, as expected. Two contrasting days, one clear and one with higher aerosol and some cloud, are compared to illustrate behavior of the F : E ratio.
Abstract
Results are presented from the Actinic Flux Determination from Measurements of Irradiance (ADMIRA) campaign to measure spectral global UV irradiance and actinic flux at the ground, beneath an atmosphere well defined by supporting measurements. Actinic flux is required to calculate photolysis rates for atmospheric chemistry, yet most spectral UV measurements are of irradiance. This work represents the first part of a project to provide algorithms for converting irradiances to actinic fluxes with specified uncertainties. The campaign took place in northern Greece in August 2000 and provided an intercomparison of UV spectroradiometers measuring different radiation parameters, as well as a comprehensive radiation and atmospheric dataset. The independently calibrated spectroradiometers measuring irradiance and actinic flux agreed to within 5%, while measurements of spectral direct irradiance differed by 9%. Relative agreement for all parameters proved to be very stable during the campaign. A polarization problem in the Brewer spectrophotometer was identified as a problem in making radiance distribution measurements with this instrument. At UV wavelengths actinic fluxes F were always greater than the corresponding irradiance E by a factor between 1.4 and 2.6. The value of the ratio F : E depended on wavelength, solar zenith angle, and the optical properties of the atmosphere. Both the wavelength and solar zenith angle dependency of the ratio decreased when the scattering in the atmosphere increased and the direct beam proportion of global irradiance decreased, as expected. Two contrasting days, one clear and one with higher aerosol and some cloud, are compared to illustrate behavior of the F : E ratio.
Abstract
Accurate estimation of snow mass is important for the characterization of the hydrological cycle at different space and time scales. For effective water resources management, accurate estimation of snow storage is needed. Conventionally, snow depth is measured at a point, and in order to monitor snow depth in a temporally and spatially comprehensive manner, optimum interpolation of the points is undertaken. Yet the spatial representation of point measurements at a basin or on a larger distance scale is uncertain. Spaceborne scanning sensors, which cover a wide swath and can provide rapid repeat global coverage, are ideally suited to augment the global snow information. Satellite-borne passive microwave sensors have been used to derive snow depth (SD) with some success. The uncertainties in point SD and areal SD of natural snowpacks need to be understood if comparisons are to be made between a point SD measurement and satellite SD. In this paper three issues are addressed relating satellite derivation of SD and ground measurements of SD in the northern Great Plains of the United States from 1988 to 1997. First, it is shown that in comparing samples of ground-measured point SD data with satellite-derived 25 × 25 km2 pixels of SD from the Defense Meteorological Satellite Program Special Sensor Microwave Imager, there are significant differences in yearly SD values even though the accumulated datasets showed similarities. Second, from variogram analysis, the spatial variability of SD from each dataset was comparable. Third, for a sampling grid cell domain of 1° × 1° in the study terrain, 10 distributed snow depth measurements per cell are required to produce a sampling error of 5 cm or better. This study has important implications for validating SD derivations from satellite microwave observations.
Abstract
Accurate estimation of snow mass is important for the characterization of the hydrological cycle at different space and time scales. For effective water resources management, accurate estimation of snow storage is needed. Conventionally, snow depth is measured at a point, and in order to monitor snow depth in a temporally and spatially comprehensive manner, optimum interpolation of the points is undertaken. Yet the spatial representation of point measurements at a basin or on a larger distance scale is uncertain. Spaceborne scanning sensors, which cover a wide swath and can provide rapid repeat global coverage, are ideally suited to augment the global snow information. Satellite-borne passive microwave sensors have been used to derive snow depth (SD) with some success. The uncertainties in point SD and areal SD of natural snowpacks need to be understood if comparisons are to be made between a point SD measurement and satellite SD. In this paper three issues are addressed relating satellite derivation of SD and ground measurements of SD in the northern Great Plains of the United States from 1988 to 1997. First, it is shown that in comparing samples of ground-measured point SD data with satellite-derived 25 × 25 km2 pixels of SD from the Defense Meteorological Satellite Program Special Sensor Microwave Imager, there are significant differences in yearly SD values even though the accumulated datasets showed similarities. Second, from variogram analysis, the spatial variability of SD from each dataset was comparable. Third, for a sampling grid cell domain of 1° × 1° in the study terrain, 10 distributed snow depth measurements per cell are required to produce a sampling error of 5 cm or better. This study has important implications for validating SD derivations from satellite microwave observations.
Abstract
The second phase of the North American Monsoon Experiment (NAME) Model Assessment Project (NAMAP2) was carried out to provide a coordinated set of simulations from global and regional models of the 2004 warm season across the North American monsoon domain. This project follows an earlier assessment, called NAMAP, that preceded the 2004 field season of the North American Monsoon Experiment. Six global and four regional models are all forced with prescribed, time-varying ocean surface temperatures. Metrics for model simulation of warm season precipitation processes developed in NAMAP are examined that pertain to the seasonal progression and diurnal cycle of precipitation, monsoon onset, surface turbulent fluxes, and simulation of the low-level jet circulation over the Gulf of California. Assessment of the metrics is shown to be limited by continuing uncertainties in spatially averaged observations, demonstrating that modeling and observational analysis capabilities need to be developed concurrently. Simulations of the core subregion (CORE) of monsoonal precipitation in global models have improved since NAMAP, despite the lack of a proper low-level jet circulation in these simulations. Some regional models run at higher resolution still exhibit the tendency observed in NAMAP to overestimate precipitation in the CORE subregion; this is shown to involve both convective and resolved components of the total precipitation. The variability of precipitation in the Arizona/New Mexico (AZNM) subregion is simulated much better by the regional models compared with the global models, illustrating the importance of transient circulation anomalies (prescribed as lateral boundary conditions) for simulating precipitation in the northern part of the monsoon domain. This suggests that seasonal predictability derivable from lower boundary conditions may be limited in the AZNM subregion.
Abstract
The second phase of the North American Monsoon Experiment (NAME) Model Assessment Project (NAMAP2) was carried out to provide a coordinated set of simulations from global and regional models of the 2004 warm season across the North American monsoon domain. This project follows an earlier assessment, called NAMAP, that preceded the 2004 field season of the North American Monsoon Experiment. Six global and four regional models are all forced with prescribed, time-varying ocean surface temperatures. Metrics for model simulation of warm season precipitation processes developed in NAMAP are examined that pertain to the seasonal progression and diurnal cycle of precipitation, monsoon onset, surface turbulent fluxes, and simulation of the low-level jet circulation over the Gulf of California. Assessment of the metrics is shown to be limited by continuing uncertainties in spatially averaged observations, demonstrating that modeling and observational analysis capabilities need to be developed concurrently. Simulations of the core subregion (CORE) of monsoonal precipitation in global models have improved since NAMAP, despite the lack of a proper low-level jet circulation in these simulations. Some regional models run at higher resolution still exhibit the tendency observed in NAMAP to overestimate precipitation in the CORE subregion; this is shown to involve both convective and resolved components of the total precipitation. The variability of precipitation in the Arizona/New Mexico (AZNM) subregion is simulated much better by the regional models compared with the global models, illustrating the importance of transient circulation anomalies (prescribed as lateral boundary conditions) for simulating precipitation in the northern part of the monsoon domain. This suggests that seasonal predictability derivable from lower boundary conditions may be limited in the AZNM subregion.
Abstract
A major oceanographic field experiment is described, which is designed to observe, quantify, and understand the creation and dispersal of weakly stratified fluid known as “mode water” in the region of the Gulf Stream. Formed in the wintertime by convection driven by the most intense air–sea fluxes observed anywhere over the globe, the role of mode waters in the general circulation of the subtropical gyre and its biogeo-chemical cycles is also addressed. The experiment is known as the CLIVAR Mode Water Dynamic Experiment (CLIMODE). Here we review the scientific objectives of the experiment and present some preliminary results.
Abstract
A major oceanographic field experiment is described, which is designed to observe, quantify, and understand the creation and dispersal of weakly stratified fluid known as “mode water” in the region of the Gulf Stream. Formed in the wintertime by convection driven by the most intense air–sea fluxes observed anywhere over the globe, the role of mode waters in the general circulation of the subtropical gyre and its biogeo-chemical cycles is also addressed. The experiment is known as the CLIVAR Mode Water Dynamic Experiment (CLIMODE). Here we review the scientific objectives of the experiment and present some preliminary results.
Abstract
Air quality and heat are strong health drivers, and their accurate assessment and forecast are important in densely populated urban areas. However, the sources and processes leading to high concentrations of main pollutants, such as ozone, nitrogen dioxide, and fine and coarse particulate matter, in complex urban areas are not fully understood, limiting our ability to forecast air quality accurately. This paper introduces the Clean Air for London (ClearfLo; www.clearflo.ac.uk) project’s interdisciplinary approach to investigate the processes leading to poor air quality and elevated temperatures.
Within ClearfLo, a large multi-institutional project funded by the U.K. Natural Environment Research Council (NERC), integrated measurements of meteorology and gaseous, and particulate composition/loading within the atmosphere of London, United Kingdom, were undertaken to understand the processes underlying poor air quality. Long-term measurement infrastructure installed at multiple levels (street and elevated), and at urban background, curbside, and rural locations were complemented with high-resolution numerical atmospheric simulations. Combining these (measurement–modeling) enhances understanding of seasonal variations in meteorology and composition together with the controlling processes. Two intensive observation periods (winter 2012 and the Summer Olympics of 2012) focus upon the vertical structure and evolution of the urban boundary layer; chemical controls on nitrogen dioxide and ozone production—in particular, the role of volatile organic compounds; and processes controlling the evolution, size, distribution, and composition of particulate matter. The paper shows that mixing heights are deeper over London than in the rural surroundings and that the seasonality of the urban boundary layer evolution controls when concentrations peak. The composition also reflects the seasonality of sources such as domestic burning and biogenic emissions.
Abstract
Air quality and heat are strong health drivers, and their accurate assessment and forecast are important in densely populated urban areas. However, the sources and processes leading to high concentrations of main pollutants, such as ozone, nitrogen dioxide, and fine and coarse particulate matter, in complex urban areas are not fully understood, limiting our ability to forecast air quality accurately. This paper introduces the Clean Air for London (ClearfLo; www.clearflo.ac.uk) project’s interdisciplinary approach to investigate the processes leading to poor air quality and elevated temperatures.
Within ClearfLo, a large multi-institutional project funded by the U.K. Natural Environment Research Council (NERC), integrated measurements of meteorology and gaseous, and particulate composition/loading within the atmosphere of London, United Kingdom, were undertaken to understand the processes underlying poor air quality. Long-term measurement infrastructure installed at multiple levels (street and elevated), and at urban background, curbside, and rural locations were complemented with high-resolution numerical atmospheric simulations. Combining these (measurement–modeling) enhances understanding of seasonal variations in meteorology and composition together with the controlling processes. Two intensive observation periods (winter 2012 and the Summer Olympics of 2012) focus upon the vertical structure and evolution of the urban boundary layer; chemical controls on nitrogen dioxide and ozone production—in particular, the role of volatile organic compounds; and processes controlling the evolution, size, distribution, and composition of particulate matter. The paper shows that mixing heights are deeper over London than in the rural surroundings and that the seasonality of the urban boundary layer evolution controls when concentrations peak. The composition also reflects the seasonality of sources such as domestic burning and biogenic emissions.
Abstract
The NASA Convective Processes Experiment - Cabo Verde (CPEX-CV) field campaign took place in September 2022 out of Sal Island, Cabo Verde. A unique payload aboard the NASA DC-8 aircraft equipped with advanced remote sensing and in situ instrumentation, in conjunction with radiosonde launches and satellite observations, allowed CPEX-CV to target the coupling between atmospheric dynamics, marine boundary layer properties, convection, and the dust-laden Saharan Air Layer in the data-sparse tropical East Atlantic region. CPEX-CV provided measurements of African Easterly Wave environments, diurnal cycle impacts on convective lifecycle, and several Saharan dust outbreaks, including the highest dust optical depth observed by the DC-8 interacting with what would become Tropical Storm Hermine. Preliminary results from CPEX-CV underscore the positive impact of dedicated tropical East Atlantic observations on downstream forecast skill, including sampling environmental forcings impacting the development of several non-developing and developing convective systems such as Hurricanes Fiona and Ian. Combined airborne radar, lidar, and radiometer measurements uniquely provide near-storm environments associated with convection on various spatiotemporal scales and, with in situ observations, insights into controls on Saharan dust properties with transport. The DC-8 also collaborated with the European Space Agency to perform coordinated validation flights under the Aeolus spaceborne wind lidar and over the Mindelo ground site, highlighting the enhanced sampling potential through partnership opportunities. CPEX-CV engaged in professional development through dedicated team building exercises that equipped the team with a cohesive approach for targeting CPEX-CV science objectives and promoted active participation of scientists across all career stages.
Abstract
The NASA Convective Processes Experiment - Cabo Verde (CPEX-CV) field campaign took place in September 2022 out of Sal Island, Cabo Verde. A unique payload aboard the NASA DC-8 aircraft equipped with advanced remote sensing and in situ instrumentation, in conjunction with radiosonde launches and satellite observations, allowed CPEX-CV to target the coupling between atmospheric dynamics, marine boundary layer properties, convection, and the dust-laden Saharan Air Layer in the data-sparse tropical East Atlantic region. CPEX-CV provided measurements of African Easterly Wave environments, diurnal cycle impacts on convective lifecycle, and several Saharan dust outbreaks, including the highest dust optical depth observed by the DC-8 interacting with what would become Tropical Storm Hermine. Preliminary results from CPEX-CV underscore the positive impact of dedicated tropical East Atlantic observations on downstream forecast skill, including sampling environmental forcings impacting the development of several non-developing and developing convective systems such as Hurricanes Fiona and Ian. Combined airborne radar, lidar, and radiometer measurements uniquely provide near-storm environments associated with convection on various spatiotemporal scales and, with in situ observations, insights into controls on Saharan dust properties with transport. The DC-8 also collaborated with the European Space Agency to perform coordinated validation flights under the Aeolus spaceborne wind lidar and over the Mindelo ground site, highlighting the enhanced sampling potential through partnership opportunities. CPEX-CV engaged in professional development through dedicated team building exercises that equipped the team with a cohesive approach for targeting CPEX-CV science objectives and promoted active participation of scientists across all career stages.
