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Abstract
This paper presents the results of a field program using a ground-based Raman lidar system to observe changes in moisture profiles as a cold and a warm front passed over the NASA/Goddard Space Flight Center in Greenbelt, Maryland. The lidar operating only during darkness is capable of providing continuous high vertical resolution profiles of water vapor mixing ratio and aerosol scattering ratio from near the surface to about 7 km altitude. The lidar data acquired on three consecutive nights from shortly after sunset to shortly before sunrise, along with upper air data from specially launched rawinsondes, have provided a unique visualization of the detailed structure of the two fronts.
Abstract
This paper presents the results of a field program using a ground-based Raman lidar system to observe changes in moisture profiles as a cold and a warm front passed over the NASA/Goddard Space Flight Center in Greenbelt, Maryland. The lidar operating only during darkness is capable of providing continuous high vertical resolution profiles of water vapor mixing ratio and aerosol scattering ratio from near the surface to about 7 km altitude. The lidar data acquired on three consecutive nights from shortly after sunset to shortly before sunrise, along with upper air data from specially launched rawinsondes, have provided a unique visualization of the detailed structure of the two fronts.
Abstract
A two-stage retrieval technique is presented for deriving water vapor profiles from data provided by a Raman lidar, a microwave radiometer, a radio acoustic sounding system, and surface in situ instruments. In the first stage, a Kalman filtering algorithm is applied to derive water vapor profiles using surface in situ and current and past Raman measurements. In the second stage, a statistical inversion technique is applied to combine the Kalman retrieval with radiometric and climatological data. This retrieval method is tested using data collected during the First ISCCP (International Satellite Cloud Climatology Project) Regional Experiment II experiment. The method is demonstrated to provide accurate profiles at altitudes above which the Raman lidar technique is limited.
Abstract
A two-stage retrieval technique is presented for deriving water vapor profiles from data provided by a Raman lidar, a microwave radiometer, a radio acoustic sounding system, and surface in situ instruments. In the first stage, a Kalman filtering algorithm is applied to derive water vapor profiles using surface in situ and current and past Raman measurements. In the second stage, a statistical inversion technique is applied to combine the Kalman retrieval with radiometric and climatological data. This retrieval method is tested using data collected during the First ISCCP (International Satellite Cloud Climatology Project) Regional Experiment II experiment. The method is demonstrated to provide accurate profiles at altitudes above which the Raman lidar technique is limited.
The Atmospheric Radiation Measurement program's Southern Great Plains Cloud and Radiation Testbed site central facility near Lamont, Oklahoma, offers unique operational water vapor profiling capabilities, including active and passive remote sensors as well as traditional in situ radiosonde measurements. Remote sensing technologies include an automated Raman lidar and an automated Atmospheric Emitted Radiance Interferometer (AERI), which are able to retrieve water vapor profiles operationally through the lower troposphere throughout the diurnal cycle. Comparisons of these two water vapor remote sensing methods to each other and to radiosondes over an 8-month period are presented and discussed, highlighting the accuracy and limitations of each method. Additionally, the AERI is able to retrieve profiles of temperature while the Raman lidar is able to retrieve aerosol extinction profiles operationally. These data, coupled with hourly wind profiles from a 915-MHz wind profiler, provide complete specification of the state of the atmosphere in noncloudy skies. Several case studies illustrate the utility of these high temporal resolution measurements in the characterization of mesoscale features within a 3-day time period in which passage of a dryline, warm air advection, and cold front occurred.
The Atmospheric Radiation Measurement program's Southern Great Plains Cloud and Radiation Testbed site central facility near Lamont, Oklahoma, offers unique operational water vapor profiling capabilities, including active and passive remote sensors as well as traditional in situ radiosonde measurements. Remote sensing technologies include an automated Raman lidar and an automated Atmospheric Emitted Radiance Interferometer (AERI), which are able to retrieve water vapor profiles operationally through the lower troposphere throughout the diurnal cycle. Comparisons of these two water vapor remote sensing methods to each other and to radiosondes over an 8-month period are presented and discussed, highlighting the accuracy and limitations of each method. Additionally, the AERI is able to retrieve profiles of temperature while the Raman lidar is able to retrieve aerosol extinction profiles operationally. These data, coupled with hourly wind profiles from a 915-MHz wind profiler, provide complete specification of the state of the atmosphere in noncloudy skies. Several case studies illustrate the utility of these high temporal resolution measurements in the characterization of mesoscale features within a 3-day time period in which passage of a dryline, warm air advection, and cold front occurred.
Abstract
Lidar observations of clear-air convection during the 1983 Boundary Layer Experiment (BLX83) reveal the presence of elongated, parallel regions of updrafts marked by enhanced aerosol backscattering. These linear (banded) aerosol structures were observed over a two-hour period during a cloud-free morning. During this period, the depth of the convective boundary layer (CBL) increased from 100 to 1300 m. Wind speeds averaged over the depth of the CBL varied between 0 and 2 m s−1, while the wind direction varied over a range of 160 deg. The CBL instability parameter, −Zi /L, increased from approximately 25 (weakly unstable) to 250 (strongly unstable). The spacings of the elongated, parallel plumes scaled with the CBL height. These findings suggest that secondary circulations in the form of horizontal roll vortices were present under conditions not normally associated with roll vortices. The lines of aerosol structures aligned much more closely (within 15 deg) with the direction of the vertical shear of the horizontal wind through the depth of the CBL than with either the surface wind, mean CBL wind, or the wind at an altitude of 1.1Zi .
Abstract
Lidar observations of clear-air convection during the 1983 Boundary Layer Experiment (BLX83) reveal the presence of elongated, parallel regions of updrafts marked by enhanced aerosol backscattering. These linear (banded) aerosol structures were observed over a two-hour period during a cloud-free morning. During this period, the depth of the convective boundary layer (CBL) increased from 100 to 1300 m. Wind speeds averaged over the depth of the CBL varied between 0 and 2 m s−1, while the wind direction varied over a range of 160 deg. The CBL instability parameter, −Zi /L, increased from approximately 25 (weakly unstable) to 250 (strongly unstable). The spacings of the elongated, parallel plumes scaled with the CBL height. These findings suggest that secondary circulations in the form of horizontal roll vortices were present under conditions not normally associated with roll vortices. The lines of aerosol structures aligned much more closely (within 15 deg) with the direction of the vertical shear of the horizontal wind through the depth of the CBL than with either the surface wind, mean CBL wind, or the wind at an altitude of 1.1Zi .
Abstract
High temporal and vertical resolution water vapor measurements by Raman and differential absorption lidar systems have been used to characterize the turbulent fluctuations in the water vapor mixing ratio field in convective mixed layers. Since daytime Raman lidar measurements are inherently noisy (due to solar background and weak signal strengths), the analysis approach needs to quantify and remove the contribution of the instrument noise in order to derive the desired atmospheric water vapor mixing ratio variance and skewness profiles. This is done using the approach outlined by Lenschow et al.; however, an intercomparison with in situ observations was not performed.
Water vapor measurements were made by a diode laser hygrometer flown on a Twin Otter aircraft during the Routine Atmospheric Radiation Measurement (ARM) Program Aerial Facility Clouds with Low Optical Water Depths Optical Radiative Observations (RACORO) field campaign over the ARM Southern Great Plains (SGP) site in 2009. Two days with Twin Otter flights were identified where the convective mixed layer was quasi stationary, and hence the 10-s, 75-m data from the SGP Raman lidar could be analyzed to provide profiles of water vapor mixing ratio variance and skewness. Airborne water vapor observations measured during level flight legs were compared to the Raman lidar data, demonstrating good agreement in both variance and skewness. The results also illustrate the challenges of comparing a point sensor making measurements over time to a moving platform making similar measurements horizontally.
Abstract
High temporal and vertical resolution water vapor measurements by Raman and differential absorption lidar systems have been used to characterize the turbulent fluctuations in the water vapor mixing ratio field in convective mixed layers. Since daytime Raman lidar measurements are inherently noisy (due to solar background and weak signal strengths), the analysis approach needs to quantify and remove the contribution of the instrument noise in order to derive the desired atmospheric water vapor mixing ratio variance and skewness profiles. This is done using the approach outlined by Lenschow et al.; however, an intercomparison with in situ observations was not performed.
Water vapor measurements were made by a diode laser hygrometer flown on a Twin Otter aircraft during the Routine Atmospheric Radiation Measurement (ARM) Program Aerial Facility Clouds with Low Optical Water Depths Optical Radiative Observations (RACORO) field campaign over the ARM Southern Great Plains (SGP) site in 2009. Two days with Twin Otter flights were identified where the convective mixed layer was quasi stationary, and hence the 10-s, 75-m data from the SGP Raman lidar could be analyzed to provide profiles of water vapor mixing ratio variance and skewness. Airborne water vapor observations measured during level flight legs were compared to the Raman lidar data, demonstrating good agreement in both variance and skewness. The results also illustrate the challenges of comparing a point sensor making measurements over time to a moving platform making similar measurements horizontally.
Abstract
Simultaneous measurements of atmospheric water vapor were made by the Millimeter-wave Imaging Radiometer (MIR), Raman lidar, and rawinsondes. Two types of rawinsonde sensor packages (AIR and Vaisala) were carried by the same balloon. The measured water vapor profiles from Raman lidar, and the Vaisala and AIR sondes were used in the radiative transfer calculations. The calculated brightness temperatures were compared with those measured from the MIR at all six frequencies (89, 150, 183.3 ± 1, 183.3 ±3, 183.3 ±7, and 220 GHz). The results show that the MIR-measured brightness temperatures agree well (within ±K) with those calculated from the Raman lidar and Vaisala measurements. The brightness temperatures calculated from the AIR sondes differ from the MIR measurements by as much as 10 K, which can be attributed to low sensitivity of the AIR sondes at relative humidity less than 20%. Both calculated and the MIR-measured brightness temperatures were also used to retrieve water vapor profiles. These retrieved profiles were compared with those measured by the Raman lidar and rawinsondes. The results of these comparisons suggest that the MIR can measure the brightness of a target to an accuracy of at most ±K and is capable of retrieving useful water vapor profiles.
Abstract
Simultaneous measurements of atmospheric water vapor were made by the Millimeter-wave Imaging Radiometer (MIR), Raman lidar, and rawinsondes. Two types of rawinsonde sensor packages (AIR and Vaisala) were carried by the same balloon. The measured water vapor profiles from Raman lidar, and the Vaisala and AIR sondes were used in the radiative transfer calculations. The calculated brightness temperatures were compared with those measured from the MIR at all six frequencies (89, 150, 183.3 ± 1, 183.3 ±3, 183.3 ±7, and 220 GHz). The results show that the MIR-measured brightness temperatures agree well (within ±K) with those calculated from the Raman lidar and Vaisala measurements. The brightness temperatures calculated from the AIR sondes differ from the MIR measurements by as much as 10 K, which can be attributed to low sensitivity of the AIR sondes at relative humidity less than 20%. Both calculated and the MIR-measured brightness temperatures were also used to retrieve water vapor profiles. These retrieved profiles were compared with those measured by the Raman lidar and rawinsondes. The results of these comparisons suggest that the MIR can measure the brightness of a target to an accuracy of at most ±K and is capable of retrieving useful water vapor profiles.
Abstract
The Modern-Era Retrospective Analysis for Research and Applications, version 2 (MERRA-2), updates NASA’s previous satellite-era (1980 onward) reanalysis system to include additional observations and improvements to the Goddard Earth Observing System, version 5 (GEOS-5), Earth system model. As a major step toward a full Integrated Earth Systems Analysis (IESA), in addition to meteorological observations, MERRA-2 now includes assimilation of aerosol optical depth (AOD) from various ground- and space-based remote sensing platforms. Here, in the first of a pair of studies, the MERRA-2 aerosol assimilation is documented, including a description of the prognostic model (GEOS-5 coupled to the GOCART aerosol module), aerosol emissions, and the quality control of ingested observations. Initial validation and evaluation of the analyzed AOD fields are provided using independent observations from ground, aircraft, and shipborne instruments. The positive impact of the AOD assimilation on simulated aerosols is demonstrated by comparing MERRA-2 aerosol fields to an identical control simulation that does not include AOD assimilation. After showing the AOD evaluation, this paper takes a first look at aerosol–climate interactions by examining the shortwave, clear-sky aerosol direct radiative effect. The companion paper (Part II) evaluates and validates available MERRA-2 aerosol properties not directly impacted by the AOD assimilation (e.g., aerosol vertical distribution and absorption). Importantly, while highlighting the skill of the MERRA-2 aerosol assimilation products, both studies point out caveats that must be considered when using this new reanalysis product for future studies of aerosols and their interactions with weather and climate.
Abstract
The Modern-Era Retrospective Analysis for Research and Applications, version 2 (MERRA-2), updates NASA’s previous satellite-era (1980 onward) reanalysis system to include additional observations and improvements to the Goddard Earth Observing System, version 5 (GEOS-5), Earth system model. As a major step toward a full Integrated Earth Systems Analysis (IESA), in addition to meteorological observations, MERRA-2 now includes assimilation of aerosol optical depth (AOD) from various ground- and space-based remote sensing platforms. Here, in the first of a pair of studies, the MERRA-2 aerosol assimilation is documented, including a description of the prognostic model (GEOS-5 coupled to the GOCART aerosol module), aerosol emissions, and the quality control of ingested observations. Initial validation and evaluation of the analyzed AOD fields are provided using independent observations from ground, aircraft, and shipborne instruments. The positive impact of the AOD assimilation on simulated aerosols is demonstrated by comparing MERRA-2 aerosol fields to an identical control simulation that does not include AOD assimilation. After showing the AOD evaluation, this paper takes a first look at aerosol–climate interactions by examining the shortwave, clear-sky aerosol direct radiative effect. The companion paper (Part II) evaluates and validates available MERRA-2 aerosol properties not directly impacted by the AOD assimilation (e.g., aerosol vertical distribution and absorption). Importantly, while highlighting the skill of the MERRA-2 aerosol assimilation products, both studies point out caveats that must be considered when using this new reanalysis product for future studies of aerosols and their interactions with weather and climate.
Abstract
The Modern-Era Retrospective Analysis for Research and Applications, version 2 (MERRA-2), is NASA’s latest reanalysis for the satellite era (1980 onward) using the Goddard Earth Observing System, version 5 (GEOS-5), Earth system model. MERRA-2 provides several improvements over its predecessor (MERRA-1), including aerosol assimilation for the entire period. MERRA-2 assimilates bias-corrected aerosol optical depth (AOD) from the Moderate Resolution Imaging Spectroradiometer and the Advanced Very High Resolution Radiometer instruments. Additionally, MERRA-2 assimilates (non bias corrected) AOD from the Multiangle Imaging SpectroRadiometer over bright surfaces and AOD from Aerosol Robotic Network sunphotometer stations. This paper, the second of a pair, summarizes the efforts to assess the quality of the MERRA-2 aerosol products. First, MERRA-2 aerosols are evaluated using independent observations. It is shown that the MERRA-2 absorption aerosol optical depth (AAOD) and ultraviolet aerosol index (AI) compare well with Ozone Monitoring Instrument observations. Next, aerosol vertical structure and surface fine particulate matter (PM2.5) are evaluated using available satellite, aircraft, and ground-based observations. While MERRA-2 generally compares well to these observations, the assimilation cannot correct for all deficiencies in the model (e.g., missing emissions). Such deficiencies can explain many of the biases with observations. Finally, a focus is placed on several major aerosol events to illustrate successes and weaknesses of the AOD assimilation: the Mount Pinatubo eruption, a Saharan dust transport episode, the California Rim Fire, and an extreme pollution event over China. The article concludes with a summary that points to best practices for using the MERRA-2 aerosol reanalysis in future studies.
Abstract
The Modern-Era Retrospective Analysis for Research and Applications, version 2 (MERRA-2), is NASA’s latest reanalysis for the satellite era (1980 onward) using the Goddard Earth Observing System, version 5 (GEOS-5), Earth system model. MERRA-2 provides several improvements over its predecessor (MERRA-1), including aerosol assimilation for the entire period. MERRA-2 assimilates bias-corrected aerosol optical depth (AOD) from the Moderate Resolution Imaging Spectroradiometer and the Advanced Very High Resolution Radiometer instruments. Additionally, MERRA-2 assimilates (non bias corrected) AOD from the Multiangle Imaging SpectroRadiometer over bright surfaces and AOD from Aerosol Robotic Network sunphotometer stations. This paper, the second of a pair, summarizes the efforts to assess the quality of the MERRA-2 aerosol products. First, MERRA-2 aerosols are evaluated using independent observations. It is shown that the MERRA-2 absorption aerosol optical depth (AAOD) and ultraviolet aerosol index (AI) compare well with Ozone Monitoring Instrument observations. Next, aerosol vertical structure and surface fine particulate matter (PM2.5) are evaluated using available satellite, aircraft, and ground-based observations. While MERRA-2 generally compares well to these observations, the assimilation cannot correct for all deficiencies in the model (e.g., missing emissions). Such deficiencies can explain many of the biases with observations. Finally, a focus is placed on several major aerosol events to illustrate successes and weaknesses of the AOD assimilation: the Mount Pinatubo eruption, a Saharan dust transport episode, the California Rim Fire, and an extreme pollution event over China. The article concludes with a summary that points to best practices for using the MERRA-2 aerosol reanalysis in future studies.
Abstract
Automated routines have been developed to derive water vapor mixing ratio, relative humidity, aerosol extinction and backscatter coefficient, and linear depolarization profiles, as well as total precipitable water vapor and aerosol optical thickness, from the operational Raman lidar at the Atmospheric Radiation Measurement (ARM) program's site in north-central Oklahoma. These routines have been devised to maintain the calibration of these data products, which have proven sensitive to the automatic alignment adjustments that are made periodically by the instrument. Since this Raman lidar does not scan, aerosol extinction cannot be directly computed below approximately 800 m due to the incomplete overlap of the outgoing laser beam with the detector's field of view. Therefore, the extinction-to-backscatter ratio at 1 km is used with the aerosol backscatter coefficient profile to compute aerosol extinction from 60 m to the level of complete overlap. Comparisons of aerosol optical depth derived using these algorithms with a collocated CIMEL sun photometer for clear-sky days over an approximate 2-yr period show a slope of 0.90 with a correlation coefficient of 0.884. Furthermore, comparing the aerosol extinction profile retrieved from this system with that from the National Aeronautics and Space Administration (NASA) Goddard Space Flight Center's scanning Raman lidar agrees within 10% for the single available case.
Abstract
Automated routines have been developed to derive water vapor mixing ratio, relative humidity, aerosol extinction and backscatter coefficient, and linear depolarization profiles, as well as total precipitable water vapor and aerosol optical thickness, from the operational Raman lidar at the Atmospheric Radiation Measurement (ARM) program's site in north-central Oklahoma. These routines have been devised to maintain the calibration of these data products, which have proven sensitive to the automatic alignment adjustments that are made periodically by the instrument. Since this Raman lidar does not scan, aerosol extinction cannot be directly computed below approximately 800 m due to the incomplete overlap of the outgoing laser beam with the detector's field of view. Therefore, the extinction-to-backscatter ratio at 1 km is used with the aerosol backscatter coefficient profile to compute aerosol extinction from 60 m to the level of complete overlap. Comparisons of aerosol optical depth derived using these algorithms with a collocated CIMEL sun photometer for clear-sky days over an approximate 2-yr period show a slope of 0.90 with a correlation coefficient of 0.884. Furthermore, comparing the aerosol extinction profile retrieved from this system with that from the National Aeronautics and Space Administration (NASA) Goddard Space Flight Center's scanning Raman lidar agrees within 10% for the single available case.
