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Abstract
An evaluation is made of techniques that have been or could be employed to determine the existence and nature of worldwide variations in atmospheric electric phenomena. In the course of a discussion of surface measurements, data from six sites on the surface of the earth are presented. The use of airborne vehicles in studies of global phenomena is discussed and results from soundings and transits are presented. It is concluded that, the use of instrumented aircraft is potentially the most promising technique to use, but that the expenditure of more care and effort than has been employed in the past is required if this potential is to be realized.
Abstract
An evaluation is made of techniques that have been or could be employed to determine the existence and nature of worldwide variations in atmospheric electric phenomena. In the course of a discussion of surface measurements, data from six sites on the surface of the earth are presented. The use of airborne vehicles in studies of global phenomena is discussed and results from soundings and transits are presented. It is concluded that, the use of instrumented aircraft is potentially the most promising technique to use, but that the expenditure of more care and effort than has been employed in the past is required if this potential is to be realized.
Abstract
TIROS photographs of cloud patterns in the vicinity of the jet stream are examined and compared with surface, upper air, and pilot-report data. It is found that with certain conditions of lighting and satellite attitude the northern edge of the cirrus cloud shield, which lies immediately south of the jet, can be easily identified by a shadow cast by the higher cloud deck on the lower underlying surface. This shadow identifies the cloud structure associated with the jet stream. Differences in texture and pattern also help to identify the northern limits of the high-level cirrus and thus aid in positioning the jet stream.
Abstract
TIROS photographs of cloud patterns in the vicinity of the jet stream are examined and compared with surface, upper air, and pilot-report data. It is found that with certain conditions of lighting and satellite attitude the northern edge of the cirrus cloud shield, which lies immediately south of the jet, can be easily identified by a shadow cast by the higher cloud deck on the lower underlying surface. This shadow identifies the cloud structure associated with the jet stream. Differences in texture and pattern also help to identify the northern limits of the high-level cirrus and thus aid in positioning the jet stream.
Abstract
An untended instrument to measure ocean surface heat flux has been developed for use in support of field experiments and the investigation of heat flux parameterization techniques. The sensing component of the Skin-Layer Ocean Heat Flux Instrument (SOHFI) consists of two simple thermopile heat flux sensors suspended by a fiberglass mesh mounted inside a ring-shaped surface float. These sensors make direct measurements within the conduction layer, where they are held in place by a balance between surface tension and float buoyancy. The two sensors are designed with differing solar absorption properties so that surface heat flux can be distinguished from direct solar irradiance. Under laboratory conditions, the SOHFI measurements agree well with calorimetric measurements (generally to within 10%). Performance in freshwater and ocean environments is discussed in a companion paper.
Abstract
An untended instrument to measure ocean surface heat flux has been developed for use in support of field experiments and the investigation of heat flux parameterization techniques. The sensing component of the Skin-Layer Ocean Heat Flux Instrument (SOHFI) consists of two simple thermopile heat flux sensors suspended by a fiberglass mesh mounted inside a ring-shaped surface float. These sensors make direct measurements within the conduction layer, where they are held in place by a balance between surface tension and float buoyancy. The two sensors are designed with differing solar absorption properties so that surface heat flux can be distinguished from direct solar irradiance. Under laboratory conditions, the SOHFI measurements agree well with calorimetric measurements (generally to within 10%). Performance in freshwater and ocean environments is discussed in a companion paper.
Abstract
The Skin-Layer Ocean Heat Flux Instrument (SOHFI) described by Sromovsky et al. (Part I, this issue) was field-tested in a combination of freshwater and ocean deployments. Solar irradiance monitoring and field calibration techniques were demonstrated by comparison with independent measurements. Tracking of solar irradiance diurnal variations appears to be accurate to within about 5% of full scale. Preliminary field tests of the SOHFI have shown reasonably close agreement with bulk aerodynamic heat flux estimates in freshwater and ocean environments (generally within about 20%) under low to moderate wind conditions. Performance under heavy weather suggests a need to develop better methods of submergence filtering. Ocean deployments and recoveries of drifting SOHFI-equipped buoys were made during May and June 1995, during the Combined Sensor Program of 1996 in the western tropical Pacific region, and in the Greenland Sea in May 1997. The Gulf Stream and Greenland Sea deployments pointed out the need for design modifications to improve resistance to seabird attacks. Better estimates of performance and limitations of this device require extended intercomparison tests under field conditions.
Abstract
The Skin-Layer Ocean Heat Flux Instrument (SOHFI) described by Sromovsky et al. (Part I, this issue) was field-tested in a combination of freshwater and ocean deployments. Solar irradiance monitoring and field calibration techniques were demonstrated by comparison with independent measurements. Tracking of solar irradiance diurnal variations appears to be accurate to within about 5% of full scale. Preliminary field tests of the SOHFI have shown reasonably close agreement with bulk aerodynamic heat flux estimates in freshwater and ocean environments (generally within about 20%) under low to moderate wind conditions. Performance under heavy weather suggests a need to develop better methods of submergence filtering. Ocean deployments and recoveries of drifting SOHFI-equipped buoys were made during May and June 1995, during the Combined Sensor Program of 1996 in the western tropical Pacific region, and in the Greenland Sea in May 1997. The Gulf Stream and Greenland Sea deployments pointed out the need for design modifications to improve resistance to seabird attacks. Better estimates of performance and limitations of this device require extended intercomparison tests under field conditions.
Abstract
During the last few decades, scientific capabilities for understanding and predicting weather and climate risks have advanced rapidly. At the same time, technological advances, such as the Internet, mobile devices, and social media, are transforming how people exchange and interact with information. In this modern information environment, risk communication, interpretation, and decision-making are rapidly evolving processes that intersect across space, time, and society. Instead of a linear or iterative process in which individual members of the public assess and respond to distinct pieces of weather forecast or warning information, this article conceives of weather prediction, communication, and decision-making as an interconnected dynamic system. In this expanded framework, information and uncertainty evolve in conjunction with people’s risk perceptions, vulnerabilities, and decisions as a hazardous weather threat approaches; these processes are intertwined with evolving social interactions in the physical and digital worlds. Along with the framework, the article presents two interdisciplinary research approaches for advancing the understanding of this complex system and the processes within it: analysis of social media streams and computational natural–human system modeling. Examples from ongoing research are used to demonstrate these approaches and illustrate the types of new insights they can reveal. This expanded perspective together with research approaches, such as those introduced, can help researchers and practitioners understand and improve the creation and communication of information in atmospheric science and other fields.
Abstract
During the last few decades, scientific capabilities for understanding and predicting weather and climate risks have advanced rapidly. At the same time, technological advances, such as the Internet, mobile devices, and social media, are transforming how people exchange and interact with information. In this modern information environment, risk communication, interpretation, and decision-making are rapidly evolving processes that intersect across space, time, and society. Instead of a linear or iterative process in which individual members of the public assess and respond to distinct pieces of weather forecast or warning information, this article conceives of weather prediction, communication, and decision-making as an interconnected dynamic system. In this expanded framework, information and uncertainty evolve in conjunction with people’s risk perceptions, vulnerabilities, and decisions as a hazardous weather threat approaches; these processes are intertwined with evolving social interactions in the physical and digital worlds. Along with the framework, the article presents two interdisciplinary research approaches for advancing the understanding of this complex system and the processes within it: analysis of social media streams and computational natural–human system modeling. Examples from ongoing research are used to demonstrate these approaches and illustrate the types of new insights they can reveal. This expanded perspective together with research approaches, such as those introduced, can help researchers and practitioners understand and improve the creation and communication of information in atmospheric science and other fields.
Abstract
Tropical cyclones (TCs) are a hazard to life and property and a prominent element of the global climate system; therefore, understanding and predicting TC location, intensity, and frequency is of both societal and scientific significance. Methodologies exist to predict basinwide, seasonally aggregated TC activity months, seasons, and even years in advance. It is shown that a newly developed high-resolution global climate model can produce skillful forecasts of seasonal TC activity on spatial scales finer than basinwide, from months and seasons in advance of the TC season. The climate model used here is targeted at predicting regional climate and the statistics of weather extremes on seasonal to decadal time scales, and comprises high-resolution (50 km × 50 km) atmosphere and land components as well as more moderate-resolution (~100 km) sea ice and ocean components. The simulation of TC climatology and interannual variations in this climate model is substantially improved by correcting systematic ocean biases through “flux adjustment.” A suite of 12-month duration retrospective forecasts is performed over the 1981–2012 period, after initializing the climate model to observationally constrained conditions at the start of each forecast period, using both the standard and flux-adjusted versions of the model. The standard and flux-adjusted forecasts exhibit equivalent skill at predicting Northern Hemisphere TC season sea surface temperature, but the flux-adjusted model exhibits substantially improved basinwide and regional TC activity forecasts, highlighting the role of systematic biases in limiting the quality of TC forecasts. These results suggest that dynamical forecasts of seasonally aggregated regional TC activity months in advance are feasible.
Abstract
Tropical cyclones (TCs) are a hazard to life and property and a prominent element of the global climate system; therefore, understanding and predicting TC location, intensity, and frequency is of both societal and scientific significance. Methodologies exist to predict basinwide, seasonally aggregated TC activity months, seasons, and even years in advance. It is shown that a newly developed high-resolution global climate model can produce skillful forecasts of seasonal TC activity on spatial scales finer than basinwide, from months and seasons in advance of the TC season. The climate model used here is targeted at predicting regional climate and the statistics of weather extremes on seasonal to decadal time scales, and comprises high-resolution (50 km × 50 km) atmosphere and land components as well as more moderate-resolution (~100 km) sea ice and ocean components. The simulation of TC climatology and interannual variations in this climate model is substantially improved by correcting systematic ocean biases through “flux adjustment.” A suite of 12-month duration retrospective forecasts is performed over the 1981–2012 period, after initializing the climate model to observationally constrained conditions at the start of each forecast period, using both the standard and flux-adjusted versions of the model. The standard and flux-adjusted forecasts exhibit equivalent skill at predicting Northern Hemisphere TC season sea surface temperature, but the flux-adjusted model exhibits substantially improved basinwide and regional TC activity forecasts, highlighting the role of systematic biases in limiting the quality of TC forecasts. These results suggest that dynamical forecasts of seasonally aggregated regional TC activity months in advance are feasible.
Abstract
The objective of the North American Land Data Assimilation System (NLDAS) is to provide best-available estimates of near-surface meteorological conditions and soil hydrological status for the continental United States. To support the ongoing efforts to develop data assimilation (DA) capabilities for NLDAS, the results of Gravity Recovery and Climate Experiment (GRACE) DA implemented in a manner consistent with NLDAS development are presented. Following previous work, GRACE terrestrial water storage (TWS) anomaly estimates are assimilated into the NASA Catchment land surface model using an ensemble smoother. In contrast to many earlier GRACE DA studies, a gridded GRACE TWS product is assimilated, spatially distributed GRACE error estimates are accounted for, and the impact that GRACE scaling factors have on assimilation is evaluated. Comparisons with quality-controlled in situ observations indicate that GRACE DA has a positive impact on the simulation of unconfined groundwater variability across the majority of the eastern United States and on the simulation of surface and root zone soil moisture across the country. Smaller improvements are seen in the simulation of snow depth, and the impact of GRACE DA on simulated river discharge and evapotranspiration is regionally variable. The use of GRACE scaling factors during assimilation improved DA results in the western United States but led to small degradations in the eastern United States. The study also found comparable performance between the use of gridded and basin-averaged GRACE observations in assimilation. Finally, the evaluations presented in the paper indicate that GRACE DA can be helpful in improving the representation of droughts.
Abstract
The objective of the North American Land Data Assimilation System (NLDAS) is to provide best-available estimates of near-surface meteorological conditions and soil hydrological status for the continental United States. To support the ongoing efforts to develop data assimilation (DA) capabilities for NLDAS, the results of Gravity Recovery and Climate Experiment (GRACE) DA implemented in a manner consistent with NLDAS development are presented. Following previous work, GRACE terrestrial water storage (TWS) anomaly estimates are assimilated into the NASA Catchment land surface model using an ensemble smoother. In contrast to many earlier GRACE DA studies, a gridded GRACE TWS product is assimilated, spatially distributed GRACE error estimates are accounted for, and the impact that GRACE scaling factors have on assimilation is evaluated. Comparisons with quality-controlled in situ observations indicate that GRACE DA has a positive impact on the simulation of unconfined groundwater variability across the majority of the eastern United States and on the simulation of surface and root zone soil moisture across the country. Smaller improvements are seen in the simulation of snow depth, and the impact of GRACE DA on simulated river discharge and evapotranspiration is regionally variable. The use of GRACE scaling factors during assimilation improved DA results in the western United States but led to small degradations in the eastern United States. The study also found comparable performance between the use of gridded and basin-averaged GRACE observations in assimilation. Finally, the evaluations presented in the paper indicate that GRACE DA can be helpful in improving the representation of droughts.
Abstract
The Convective Transport of Active Species in the Tropics (CONTRAST) experiment was conducted from Guam (13.5°N, 144.8°E) during January–February 2014. Using the NSF/NCAR Gulfstream V research aircraft, the experiment investigated the photochemical environment over the tropical western Pacific (TWP) warm pool, a region of massive deep convection and the major pathway for air to enter the stratosphere during Northern Hemisphere (NH) winter. The new observations provide a wealth of information for quantifying the influence of convection on the vertical distributions of active species. The airborne in situ measurements up to 15-km altitude fill a significant gap by characterizing the abundance and altitude variation of a wide suite of trace gases. These measurements, together with observations of dynamical and microphysical parameters, provide significant new data for constraining and evaluating global chemistry–climate models. Measurements include precursor and product gas species of reactive halogen compounds that impact ozone in the upper troposphere/lower stratosphere. High-accuracy, in situ measurements of ozone obtained during CONTRAST quantify ozone concentration profiles in the upper troposphere, where previous observations from balloonborne ozonesondes were often near or below the limit of detection. CONTRAST was one of the three coordinated experiments to observe the TWP during January–February 2014. Together, CONTRAST, Airborne Tropical Tropopause Experiment (ATTREX), and Coordinated Airborne Studies in the Tropics (CAST), using complementary capabilities of the three aircraft platforms as well as ground-based instrumentation, provide a comprehensive quantification of the regional distribution and vertical structure of natural and pollutant trace gases in the TWP during NH winter, from the oceanic boundary to the lower stratosphere.
Abstract
The Convective Transport of Active Species in the Tropics (CONTRAST) experiment was conducted from Guam (13.5°N, 144.8°E) during January–February 2014. Using the NSF/NCAR Gulfstream V research aircraft, the experiment investigated the photochemical environment over the tropical western Pacific (TWP) warm pool, a region of massive deep convection and the major pathway for air to enter the stratosphere during Northern Hemisphere (NH) winter. The new observations provide a wealth of information for quantifying the influence of convection on the vertical distributions of active species. The airborne in situ measurements up to 15-km altitude fill a significant gap by characterizing the abundance and altitude variation of a wide suite of trace gases. These measurements, together with observations of dynamical and microphysical parameters, provide significant new data for constraining and evaluating global chemistry–climate models. Measurements include precursor and product gas species of reactive halogen compounds that impact ozone in the upper troposphere/lower stratosphere. High-accuracy, in situ measurements of ozone obtained during CONTRAST quantify ozone concentration profiles in the upper troposphere, where previous observations from balloonborne ozonesondes were often near or below the limit of detection. CONTRAST was one of the three coordinated experiments to observe the TWP during January–February 2014. Together, CONTRAST, Airborne Tropical Tropopause Experiment (ATTREX), and Coordinated Airborne Studies in the Tropics (CAST), using complementary capabilities of the three aircraft platforms as well as ground-based instrumentation, provide a comprehensive quantification of the regional distribution and vertical structure of natural and pollutant trace gases in the TWP during NH winter, from the oceanic boundary to the lower stratosphere.
The Climate Absolute Radiance and Refractivity Observatory (CLARREO) mission will provide a calibration laboratory in orbit for the purpose of accurately measuring and attributing climate change. CLARREO measurements establish new climate change benchmarks with high absolute radiometric accuracy and high statistical confidence across a wide range of essential climate variables. CLARREO's inherently high absolute accuracy will be verified and traceable on orbit to Système Internationale (SI) units. The benchmarks established by CLARREO will be critical for assessing changes in the Earth system and climate model predictive capabilities for decades into the future as society works to meet the challenge of optimizing strategies for mitigating and adapting to climate change. The CLARREO benchmarks are derived from measurements of the Earth's thermal infrared spectrum (5–50 μm), the spectrum of solar radiation reflected by the Earth and its atmosphere (320–2300 nm), and radio occultation refractivity from which accurate temperature profiles are derived. The mission has the ability to provide new spectral fingerprints of climate change, as well as to provide the first orbiting radiometer with accuracy sufficient to serve as the reference transfer standard for other space sensors, in essence serving as a “NIST [National Institute of Standards and Technology] in orbit.” CLARREO will greatly improve the accuracy and relevance of a wide range of space-borne instruments for decadal climate change. Finally, CLARREO has developed new metrics and methods for determining the accuracy requirements of climate observations for a wide range of climate variables and uncertainty sources. These methods should be useful for improving our understanding of observing requirements for most climate change observations.
The Climate Absolute Radiance and Refractivity Observatory (CLARREO) mission will provide a calibration laboratory in orbit for the purpose of accurately measuring and attributing climate change. CLARREO measurements establish new climate change benchmarks with high absolute radiometric accuracy and high statistical confidence across a wide range of essential climate variables. CLARREO's inherently high absolute accuracy will be verified and traceable on orbit to Système Internationale (SI) units. The benchmarks established by CLARREO will be critical for assessing changes in the Earth system and climate model predictive capabilities for decades into the future as society works to meet the challenge of optimizing strategies for mitigating and adapting to climate change. The CLARREO benchmarks are derived from measurements of the Earth's thermal infrared spectrum (5–50 μm), the spectrum of solar radiation reflected by the Earth and its atmosphere (320–2300 nm), and radio occultation refractivity from which accurate temperature profiles are derived. The mission has the ability to provide new spectral fingerprints of climate change, as well as to provide the first orbiting radiometer with accuracy sufficient to serve as the reference transfer standard for other space sensors, in essence serving as a “NIST [National Institute of Standards and Technology] in orbit.” CLARREO will greatly improve the accuracy and relevance of a wide range of space-borne instruments for decadal climate change. Finally, CLARREO has developed new metrics and methods for determining the accuracy requirements of climate observations for a wide range of climate variables and uncertainty sources. These methods should be useful for improving our understanding of observing requirements for most climate change observations.
Abstract
The largest uncertainty in the historical radiative forcing of climate is caused by changes in aerosol particles due to anthropogenic activity. Sophisticated aerosol microphysics processes have been included in many climate models in an effort to reduce the uncertainty. However, the models are very challenging to evaluate and constrain because they require extensive in situ measurements of the particle size distribution, number concentration, and chemical composition that are not available from global satellite observations. The Global Aerosol Synthesis and Science Project (GASSP) aims to improve the robustness of global aerosol models by combining new methodologies for quantifying model uncertainty, to create an extensive global dataset of aerosol in situ microphysical and chemical measurements, and to develop new ways to assess the uncertainty associated with comparing sparse point measurements with low-resolution models. GASSP has assembled over 45,000 hours of measurements from ships and aircraft as well as data from over 350 ground stations. The measurements have been harmonized into a standardized format that is easily used by modelers and nonspecialist users. Available measurements are extensive, but they are biased to polluted regions of the Northern Hemisphere, leaving large pristine regions and many continental areas poorly sampled. The aerosol radiative forcing uncertainty can be reduced using a rigorous model–data synthesis approach. Nevertheless, our research highlights significant remaining challenges because of the difficulty of constraining many interwoven model uncertainties simultaneously. Although the physical realism of global aerosol models still needs to be improved, the uncertainty in aerosol radiative forcing will be reduced most effectively by systematically and rigorously constraining the models using extensive syntheses of measurements.
Abstract
The largest uncertainty in the historical radiative forcing of climate is caused by changes in aerosol particles due to anthropogenic activity. Sophisticated aerosol microphysics processes have been included in many climate models in an effort to reduce the uncertainty. However, the models are very challenging to evaluate and constrain because they require extensive in situ measurements of the particle size distribution, number concentration, and chemical composition that are not available from global satellite observations. The Global Aerosol Synthesis and Science Project (GASSP) aims to improve the robustness of global aerosol models by combining new methodologies for quantifying model uncertainty, to create an extensive global dataset of aerosol in situ microphysical and chemical measurements, and to develop new ways to assess the uncertainty associated with comparing sparse point measurements with low-resolution models. GASSP has assembled over 45,000 hours of measurements from ships and aircraft as well as data from over 350 ground stations. The measurements have been harmonized into a standardized format that is easily used by modelers and nonspecialist users. Available measurements are extensive, but they are biased to polluted regions of the Northern Hemisphere, leaving large pristine regions and many continental areas poorly sampled. The aerosol radiative forcing uncertainty can be reduced using a rigorous model–data synthesis approach. Nevertheless, our research highlights significant remaining challenges because of the difficulty of constraining many interwoven model uncertainties simultaneously. Although the physical realism of global aerosol models still needs to be improved, the uncertainty in aerosol radiative forcing will be reduced most effectively by systematically and rigorously constraining the models using extensive syntheses of measurements.
