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The Atmospheric Emitted Radiance Interferometer (AERI) was used to measure the infrared radiative properties and the temperature of the Gulf of Mexico during a 5-day oceanographic cruise in January 1995. The ocean skin temperature was measured with an accuracy believed to be better than 0.1 °C. The surface reflectivity/emissivity was determined as a function of view angle and sea state. The radiative properties are in good theoretical consistency with in situ measurements of ocean bulk temperature and the meteorological observations made from the oceanographic vessel. The AERI and in situ measurements provide a strong basis for accurate global specifications of sea surface temperature and ocean heat flux from satellites and ships.
The Atmospheric Emitted Radiance Interferometer (AERI) was used to measure the infrared radiative properties and the temperature of the Gulf of Mexico during a 5-day oceanographic cruise in January 1995. The ocean skin temperature was measured with an accuracy believed to be better than 0.1 °C. The surface reflectivity/emissivity was determined as a function of view angle and sea state. The radiative properties are in good theoretical consistency with in situ measurements of ocean bulk temperature and the meteorological observations made from the oceanographic vessel. The AERI and in situ measurements provide a strong basis for accurate global specifications of sea surface temperature and ocean heat flux from satellites and ships.
Abstract
A real-time, weather-adaptive three-dimensional variational data assimilation (3DVAR) system has been adapted for the NOAA Warn-on-Forecast (WoF) project to incorporate all available radar observations within a moveable analysis domain. The key features of the system include 1) incorporating radar observations from multiple Weather Surveillance Radars-1988 Doppler (WSR-88Ds) with NCEP forecast products as a background state, 2) the ability to automatically detect and analyze severe local hazardous weather events at 1-km horizontal resolution every 5 min in real time based on the current weather situation, and 3) the identification of strong circulation patterns embedded in thunderstorms. Although still in the early development stage, the system performed very well within the NOAA's Hazardous Weather Testbed (HWT) Experimental Warning Program during preliminary testing in spring 2010 when many severe weather events were successfully detected and analyzed. This study represents a first step in the assessment of this type of 3DVAR analysis for use in severe weather warnings. The eventual goal of this real-time 3DVAR system is to help meteorologists better track severe weather events and eventually provide better warning information to the public, ultimately saving lives and reducing property damage.
Abstract
A real-time, weather-adaptive three-dimensional variational data assimilation (3DVAR) system has been adapted for the NOAA Warn-on-Forecast (WoF) project to incorporate all available radar observations within a moveable analysis domain. The key features of the system include 1) incorporating radar observations from multiple Weather Surveillance Radars-1988 Doppler (WSR-88Ds) with NCEP forecast products as a background state, 2) the ability to automatically detect and analyze severe local hazardous weather events at 1-km horizontal resolution every 5 min in real time based on the current weather situation, and 3) the identification of strong circulation patterns embedded in thunderstorms. Although still in the early development stage, the system performed very well within the NOAA's Hazardous Weather Testbed (HWT) Experimental Warning Program during preliminary testing in spring 2010 when many severe weather events were successfully detected and analyzed. This study represents a first step in the assessment of this type of 3DVAR analysis for use in severe weather warnings. The eventual goal of this real-time 3DVAR system is to help meteorologists better track severe weather events and eventually provide better warning information to the public, ultimately saving lives and reducing property damage.
Abstract
As part of the Chesapeake Lighthouse and Aircraft Measurements for Satellites (CLAMS) experiment, 10 July–2 August 2001, off the central East Coast of the United States, the 14-channel NASA Ames Airborne Tracking Sunphotometer (AATS-14) was operated aboard the University of Washington’s Convair 580 (CV-580) research aircraft during 10 flights (∼45 flight hours). One of the main research goals in CLAMS was the validation of satellite-based retrievals of aerosol properties. The goal of this study in particular was to perform true over-ocean validations (rather than over-ocean validation with ground-based, coastal sites) at finer spatial scales and extending to longer wavelengths than those considered in previous studies. Comparisons of aerosol optical depth (AOD) between the Aerosol Robotic Network (AERONET) Cimel instrument at the Chesapeake Lighthouse and airborne measurements by AATS-14 in its vicinity showed good agreement with the largest r-square correlation coefficients at wavelengths of 0.38 and 0.5 μm (>0.99). Coordinated low-level flight tracks of the CV-580 during Terra overpass times permitted validation of over-ocean Moderate Resolution Imaging Spectroradiometer (MODIS) level 2 (MOD04_L2) multiwavelength AOD data (10 km × 10 km, nadir) in 16 cases on three separate days. While the correlation between AATS-14- and MODIS-derived AOD was weak with an r square of 0.55, almost 75% of all MODIS AOD measurements fell within the prelaunch estimated uncertainty range Δτ = ±0.03 ± 0.05τ. This weak correlation may be due to the small AODs (generally less than 0.1 at 0.5 μm) encountered in these comparison cases. An analogous coordination exercise resulted in seven coincident over-ocean matchups between AATS-14 and Multiangle Imaging Spectroradiometer (MISR) measurements. The comparison between AATS-14 and the MISR standard algorithm regional mean AODs showed a stronger correlation with an r square of 0.94. However, MISR AODs were systematically larger than the corresponding AATS values, with an rms difference of ∼0.06. AATS data collected during nine extended low-level CV-580 flight tracks were used to assess the spatial variability in AOD at horizontal scales up to 100 km. At UV and midvisible wavelengths, the largest absolute gradients in AOD were 0.1–0.2 per 50-km horizontal distance. In the near-IR, analogous gradients rarely reached 0.05. On any given day, the relative gradients in AOD were remarkably similar for all wavelengths, with maximum values of 70% (50 km)−1 and more typical values of 25% (50 km)−1. The implications of these unique measurements of AOD spatial variability for common validation practices of satellite data products and for comparisons to large-scale aerosol models are discussed.
Abstract
As part of the Chesapeake Lighthouse and Aircraft Measurements for Satellites (CLAMS) experiment, 10 July–2 August 2001, off the central East Coast of the United States, the 14-channel NASA Ames Airborne Tracking Sunphotometer (AATS-14) was operated aboard the University of Washington’s Convair 580 (CV-580) research aircraft during 10 flights (∼45 flight hours). One of the main research goals in CLAMS was the validation of satellite-based retrievals of aerosol properties. The goal of this study in particular was to perform true over-ocean validations (rather than over-ocean validation with ground-based, coastal sites) at finer spatial scales and extending to longer wavelengths than those considered in previous studies. Comparisons of aerosol optical depth (AOD) between the Aerosol Robotic Network (AERONET) Cimel instrument at the Chesapeake Lighthouse and airborne measurements by AATS-14 in its vicinity showed good agreement with the largest r-square correlation coefficients at wavelengths of 0.38 and 0.5 μm (>0.99). Coordinated low-level flight tracks of the CV-580 during Terra overpass times permitted validation of over-ocean Moderate Resolution Imaging Spectroradiometer (MODIS) level 2 (MOD04_L2) multiwavelength AOD data (10 km × 10 km, nadir) in 16 cases on three separate days. While the correlation between AATS-14- and MODIS-derived AOD was weak with an r square of 0.55, almost 75% of all MODIS AOD measurements fell within the prelaunch estimated uncertainty range Δτ = ±0.03 ± 0.05τ. This weak correlation may be due to the small AODs (generally less than 0.1 at 0.5 μm) encountered in these comparison cases. An analogous coordination exercise resulted in seven coincident over-ocean matchups between AATS-14 and Multiangle Imaging Spectroradiometer (MISR) measurements. The comparison between AATS-14 and the MISR standard algorithm regional mean AODs showed a stronger correlation with an r square of 0.94. However, MISR AODs were systematically larger than the corresponding AATS values, with an rms difference of ∼0.06. AATS data collected during nine extended low-level CV-580 flight tracks were used to assess the spatial variability in AOD at horizontal scales up to 100 km. At UV and midvisible wavelengths, the largest absolute gradients in AOD were 0.1–0.2 per 50-km horizontal distance. In the near-IR, analogous gradients rarely reached 0.05. On any given day, the relative gradients in AOD were remarkably similar for all wavelengths, with maximum values of 70% (50 km)−1 and more typical values of 25% (50 km)−1. The implications of these unique measurements of AOD spatial variability for common validation practices of satellite data products and for comparisons to large-scale aerosol models are discussed.
Clouds and the Earth’s Radiant Energy System (CERES) Cloud Radiative Swath (CRS) Edition 4 Data ProductAbstract
Satellite observations from Clouds and the Earth’s Radiant Energy System (CERES) radiometers have produced over two decades of world-class data documenting time–space variations in Earth’s top-of-atmosphere (TOA) radiation budget. In addition to energy exchanges among Earth and space, climate studies require accurate information on radiant energy exchanges at the surface and within the atmosphere. The CERES Cloud Radiative Swath (CRS) data product extends the standard Single Scanner Footprint (SSF) data product by calculating a suite of radiative fluxes from the surface to TOA at the instantaneous CERES footprint scale using the NASA Langley Fu–Liou radiative transfer model. Here, we describe the CRS flux algorithm and evaluate its performance against a network of ground-based measurements and CERES TOA observations. CRS all-sky downwelling broadband fluxes show significant improvements in surface validation statistics relative to the parameterized fluxes on the SSF product, including a ∼30%–40% (∼20%) reduction in SW↓ (LW↓) root-mean-square error (RMSΔ), improved correlation coefficients, and the lowest SW↓ bias over most surface types. RMSΔ and correlation statistics improve over five different surface types under both overcast and clear-sky conditions. The global mean computed TOA outgoing LW radiation (OLR) remains within <1% (2–3 W m−2) of CERES observations, while the global mean reflected SW radiation (RSW) is excessive by ∼3.5% (∼9 W m−2) owing to cloudy-sky computation errors. As we highlight using data from two remote field campaigns, the CRS data product provides many benefits for studies requiring advanced surface radiative fluxes.
Abstract
Satellite observations from Clouds and the Earth’s Radiant Energy System (CERES) radiometers have produced over two decades of world-class data documenting time–space variations in Earth’s top-of-atmosphere (TOA) radiation budget. In addition to energy exchanges among Earth and space, climate studies require accurate information on radiant energy exchanges at the surface and within the atmosphere. The CERES Cloud Radiative Swath (CRS) data product extends the standard Single Scanner Footprint (SSF) data product by calculating a suite of radiative fluxes from the surface to TOA at the instantaneous CERES footprint scale using the NASA Langley Fu–Liou radiative transfer model. Here, we describe the CRS flux algorithm and evaluate its performance against a network of ground-based measurements and CERES TOA observations. CRS all-sky downwelling broadband fluxes show significant improvements in surface validation statistics relative to the parameterized fluxes on the SSF product, including a ∼30%–40% (∼20%) reduction in SW↓ (LW↓) root-mean-square error (RMSΔ), improved correlation coefficients, and the lowest SW↓ bias over most surface types. RMSΔ and correlation statistics improve over five different surface types under both overcast and clear-sky conditions. The global mean computed TOA outgoing LW radiation (OLR) remains within <1% (2–3 W m−2) of CERES observations, while the global mean reflected SW radiation (RSW) is excessive by ∼3.5% (∼9 W m−2) owing to cloudy-sky computation errors. As we highlight using data from two remote field campaigns, the CRS data product provides many benefits for studies requiring advanced surface radiative fluxes.
Abstract
Research funded by the U.S. Department of Energy's Atmospheric Radiation Measurement (ARM) program has led to significant improvements in longwave radiative transfer modeling over the last decade. These improvements, which have generally come in small incremental changes, were made primarily in the water vapor self- and foreign-broadened continuum and the water vapor absorption line parameters. These changes, when taken as a whole, result in up to a 6 W m−2 improvement in the modeled clear-sky downwelling longwave radiative flux at the surface and significantly better agreement with spectral observations. This paper provides an overview of the history of ARM with regard to clear-sky longwave radiative transfer, and analyzes remaining related uncertainties in the ARM state-of-the-art Line-by-Line Radiative Transfer Model (LBLRTM).
A quality measurement experiment (QME) for the downwelling infrared radiance at the ARM Southern Great Plains site has been ongoing since 1994. This experiment has three objectives: 1) to validate and improve the absorption models and spectral line parameters used in line-by-line radiative transfer models, 2) to assess the ability to define the atmospheric state, and 3) to assess the quality of the radiance observations that serve as ground truth for the model. Analysis of data from 1994 to 1997 made significant contributions to optimizing the QME, but is limited by small but significant uncertainties and deficiencies in the atmospheric state and radiance observations. This paper concentrates on the analysis of QME data from 1998 to 2001, wherein the data have been carefully selected to address the uncertainties in the 1994–97 dataset. Analysis of this newer dataset suggests that the representation of self-broadened water vapor continuum absorption is 3%–8% too strong in the 750–1000 cm−1 region. The dataset also provides information on the accuracy of the self- and foreign-broadened continuum absorption in the 1100–1300 cm−1 region. After accounting for these changes, remaining differences in modeled and observed downwelling clear-sky fluxes are less than 1.5 W m−2 over a wide range of atmospheric states.
Abstract
Research funded by the U.S. Department of Energy's Atmospheric Radiation Measurement (ARM) program has led to significant improvements in longwave radiative transfer modeling over the last decade. These improvements, which have generally come in small incremental changes, were made primarily in the water vapor self- and foreign-broadened continuum and the water vapor absorption line parameters. These changes, when taken as a whole, result in up to a 6 W m−2 improvement in the modeled clear-sky downwelling longwave radiative flux at the surface and significantly better agreement with spectral observations. This paper provides an overview of the history of ARM with regard to clear-sky longwave radiative transfer, and analyzes remaining related uncertainties in the ARM state-of-the-art Line-by-Line Radiative Transfer Model (LBLRTM).
A quality measurement experiment (QME) for the downwelling infrared radiance at the ARM Southern Great Plains site has been ongoing since 1994. This experiment has three objectives: 1) to validate and improve the absorption models and spectral line parameters used in line-by-line radiative transfer models, 2) to assess the ability to define the atmospheric state, and 3) to assess the quality of the radiance observations that serve as ground truth for the model. Analysis of data from 1994 to 1997 made significant contributions to optimizing the QME, but is limited by small but significant uncertainties and deficiencies in the atmospheric state and radiance observations. This paper concentrates on the analysis of QME data from 1998 to 2001, wherein the data have been carefully selected to address the uncertainties in the 1994–97 dataset. Analysis of this newer dataset suggests that the representation of self-broadened water vapor continuum absorption is 3%–8% too strong in the 750–1000 cm−1 region. The dataset also provides information on the accuracy of the self- and foreign-broadened continuum absorption in the 1100–1300 cm−1 region. After accounting for these changes, remaining differences in modeled and observed downwelling clear-sky fluxes are less than 1.5 W m−2 over a wide range of atmospheric states.
Abstract
A ground-based Fourier transform spectrometer has been developed to measure the atmospheric downwelling infrared radiance spectrum at the earth's surface with high absolute accuracy. The Atmospheric Emitted Radiance Interferometer (AERI) instrument was designed and fabricated by the University of Wisconsin Space Science and Engineering Center (UW-SSEC) for the Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) Program. This paper emphasizes the key features of the UW-SSEC instrument design that contribute to meeting the AERI instrument requirements for the ARM Program. These features include a highly accurate radiometric calibration system, an instrument controller that provides continuous and autonomous operation, an extensive data acquisition system for monitoring calibration temperatures and instrument health, and a real-time data processing system. In particular, focus is placed on design issues crucial to meeting the ARM requirements for radiometric calibration, spectral calibration, noise performance, and operational reliability. The detailed performance characteristics of the AERI instruments built for the ARM Program are described in a companion paper.
Abstract
A ground-based Fourier transform spectrometer has been developed to measure the atmospheric downwelling infrared radiance spectrum at the earth's surface with high absolute accuracy. The Atmospheric Emitted Radiance Interferometer (AERI) instrument was designed and fabricated by the University of Wisconsin Space Science and Engineering Center (UW-SSEC) for the Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) Program. This paper emphasizes the key features of the UW-SSEC instrument design that contribute to meeting the AERI instrument requirements for the ARM Program. These features include a highly accurate radiometric calibration system, an instrument controller that provides continuous and autonomous operation, an extensive data acquisition system for monitoring calibration temperatures and instrument health, and a real-time data processing system. In particular, focus is placed on design issues crucial to meeting the ARM requirements for radiometric calibration, spectral calibration, noise performance, and operational reliability. The detailed performance characteristics of the AERI instruments built for the ARM Program are described in a companion paper.
Abstract
The Atmospheric Emitted Radiance Interferometer (AERI) instrument was developed for the Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) Program by the University of Wisconsin Space Science and Engineering Center (UW-SSEC). The infrared emission spectra measured by the instrument have the sensitivity and absolute accuracy needed for atmospheric remote sensing and climate studies. The instrument design is described in a companion paper. This paper describes in detail the measured performance characteristics of the AERI instruments built for the ARM Program. In particular, the AERI systems achieve an absolute radiometric calibration of better than 1% (3σ) of ambient radiance, with a reproducibility of better than 0.2%. The knowledge of the AERI spectral calibration is better than 1.5 ppm (1σ) in the wavenumber range 400– 3000 cm−1.
Abstract
The Atmospheric Emitted Radiance Interferometer (AERI) instrument was developed for the Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) Program by the University of Wisconsin Space Science and Engineering Center (UW-SSEC). The infrared emission spectra measured by the instrument have the sensitivity and absolute accuracy needed for atmospheric remote sensing and climate studies. The instrument design is described in a companion paper. This paper describes in detail the measured performance characteristics of the AERI instruments built for the ARM Program. In particular, the AERI systems achieve an absolute radiometric calibration of better than 1% (3σ) of ambient radiance, with a reproducibility of better than 0.2%. The knowledge of the AERI spectral calibration is better than 1.5 ppm (1σ) in the wavenumber range 400– 3000 cm−1.
The American Meteorological Society (AMS) held its Seventh Symposium on Education in conjunction with the 78th AMS Annual Meeting. The theme of the symposium was “Atmospheric and Oceanographic Education: Advancing Our Awareness.” Thirty-six oral presentations and 47 poster presentations summarized a variety of educational programs or examined educational issues relevant for both the precollege and university levels.
There were also joint sessions held with the Second Conference on Coastal Atmospheric and Oceanic Prediction and Processes and the Ninth Conference on Interaction of the Sea and Atmosphere, as well as the 10th Symposium on Meteorological Observations and Instruments. Over 200 people representing a wide spectrum of the Society attended one or more of the sessions during this two-day event.
The American Meteorological Society (AMS) held its Seventh Symposium on Education in conjunction with the 78th AMS Annual Meeting. The theme of the symposium was “Atmospheric and Oceanographic Education: Advancing Our Awareness.” Thirty-six oral presentations and 47 poster presentations summarized a variety of educational programs or examined educational issues relevant for both the precollege and university levels.
There were also joint sessions held with the Second Conference on Coastal Atmospheric and Oceanic Prediction and Processes and the Ninth Conference on Interaction of the Sea and Atmosphere, as well as the 10th Symposium on Meteorological Observations and Instruments. Over 200 people representing a wide spectrum of the Society attended one or more of the sessions during this two-day event.
High-resolution surface fluxes over the global ocean are needed to evaluate coupled atmosphere–ocean models and weather forecasting models, provide surface forcing for ocean models, understand the regional and temporal variations of the exchange of heat between the atmosphere and ocean, and provide a large-scale context for field experiments. Under the auspices of the World Climate Research Programme (WCRP) Global Energy and Water Cycle Experiment (GEWEX) Radiation Panel, the SEAFLUX Project has been initiated to investigate producing a high-resolution satellite-based dataset of surface turbulent fluxes over the global oceans to complement the existing products for surface radiation fluxes and precipitation. The SEAFLUX Project includes the following elements: a library of in situ data, with collocated satellite data to be used in the evaluation and improvement of global flux products; organized intercomparison projects, to evaluate and improve bulk flux models and determination from the satellite of the input parameters; and coordinated evaluation of the flux products in the context of applications, such as forcing ocean models and evaluation of coupled atmosphere–ocean models. The objective of this paper is to present an overview of the status of global ocean surface flux products, the methodology being used by SEAFLUX, and the prospects for improvement of satellite-derived flux products.
High-resolution surface fluxes over the global ocean are needed to evaluate coupled atmosphere–ocean models and weather forecasting models, provide surface forcing for ocean models, understand the regional and temporal variations of the exchange of heat between the atmosphere and ocean, and provide a large-scale context for field experiments. Under the auspices of the World Climate Research Programme (WCRP) Global Energy and Water Cycle Experiment (GEWEX) Radiation Panel, the SEAFLUX Project has been initiated to investigate producing a high-resolution satellite-based dataset of surface turbulent fluxes over the global oceans to complement the existing products for surface radiation fluxes and precipitation. The SEAFLUX Project includes the following elements: a library of in situ data, with collocated satellite data to be used in the evaluation and improvement of global flux products; organized intercomparison projects, to evaluate and improve bulk flux models and determination from the satellite of the input parameters; and coordinated evaluation of the flux products in the context of applications, such as forcing ocean models and evaluation of coupled atmosphere–ocean models. The objective of this paper is to present an overview of the status of global ocean surface flux products, the methodology being used by SEAFLUX, and the prospects for improvement of satellite-derived flux products.
The Fourth Assessment Report (AR4) of the Intergovernmental Panel on Climate Change (IPCC) concluded that global warming is “unequivocal” and that most of the observed increase since the mid-twentieth century is very likely due to the increase in anthropogenic greenhouse gas concentrations, with discernible human influences on ocean warming, continental-average temperatures, temperature extremes, wind patterns, and other physical and biological indicators, impacting both socioeconomic and ecological systems. It is now clear that we are committed to some level of global climate change, and it is imperative that this be considered when planning future climate research and observational strategies. The Global Climate Observing System program (GCOS), the World Climate Research Programme (WCRP), and the International Geosphere-Biosphere Programme (IGBP) therefore initiated a process to summarize the lessons learned through AR4 Working Groups I and II and to identify a set of high-priority modeling and observational needs. Two classes of recommendations emerged. First is the need to improve climate models, observational and climate monitoring systems, and our understanding of key processes. Second, the framework for climate research and observations must be extended to document impacts and to guide adaptation and mitigation efforts. Research and observational strategies specifically aimed at improving our ability to predict and understand impacts, adaptive capacity, and societal and ecosystem vulnerabilities will serve both purposes and are the subject of the specific recommendations made in this paper.
The Fourth Assessment Report (AR4) of the Intergovernmental Panel on Climate Change (IPCC) concluded that global warming is “unequivocal” and that most of the observed increase since the mid-twentieth century is very likely due to the increase in anthropogenic greenhouse gas concentrations, with discernible human influences on ocean warming, continental-average temperatures, temperature extremes, wind patterns, and other physical and biological indicators, impacting both socioeconomic and ecological systems. It is now clear that we are committed to some level of global climate change, and it is imperative that this be considered when planning future climate research and observational strategies. The Global Climate Observing System program (GCOS), the World Climate Research Programme (WCRP), and the International Geosphere-Biosphere Programme (IGBP) therefore initiated a process to summarize the lessons learned through AR4 Working Groups I and II and to identify a set of high-priority modeling and observational needs. Two classes of recommendations emerged. First is the need to improve climate models, observational and climate monitoring systems, and our understanding of key processes. Second, the framework for climate research and observations must be extended to document impacts and to guide adaptation and mitigation efforts. Research and observational strategies specifically aimed at improving our ability to predict and understand impacts, adaptive capacity, and societal and ecosystem vulnerabilities will serve both purposes and are the subject of the specific recommendations made in this paper.
