The circulation of the atmosphere is affected by the horizontal, vertical, and temporal distribution of atmospheric constituents such as water vapor, aerosols, clouds, precipitation, and latent heat released by cloud formation. Improving our ability to predict weather and climate depends upon accurate representation of these constituents in the vertical dimension. However, the depth and turbulence of the atmosphere make observing gases and microscopic particles in the vertical dimension, i.e., profiling, particularly challenging. Scientists conceive, design, develop, and implement ultraviolet, infrared, optical, radar, laser, and lidar technology for profiling the atmosphere. These instruments are deployed both in field experiments and in regular operations for weather forecasting. They use the observations from these instruments to construct profiles of winds, water vapor, aerosols, and precipitation for applications that include satellite sensor calibration and Earth system model development and validation.
Physical Retrievals of Rainrate and Structure
Estimates of surface rain fluxes and precipitation vertical structure from satellite sensors can be used to characterize storm structure and intensity, and to indirectly infer distributions of vertical air motion and latent heat of condensation in precipitation systems. Therefore, in aggregate, these data are also important for global hydrological and energy cycle studies. The most accurate satellite estimates of precipitation rates and vertical structure are currently derived from a combination of spaceborne weather radar and passive microwave radiometer observations. The spaceborne radar data reveal the structure of precipitation at relative high spatial resolution, while the microwave radiometer observations provide a measure of the vertical column-integrated water content of the atmosphere due to water vapor, clouds, and precipitation. Since these atmospheric constituents attenuate the spaceborne radar pulses that are reflected by precipitation, the passive microwave measurements can be used to help "attenuation-correct" the radar observations. The greater relative accuracy of combined radar-radiometer estimates of precipitation makes them useful not only for direct science applications, but also for calibrating other satellite sensors that have lower accuracy but provide greater sampling in space and time; see Global Precipitation Estimates tab.
Shown in the figure at right is a schematic of the Global Precipitation Measurement (GPM) mission Core satellite, including the scanning of its Dual-frequency Precipitation Radar (DPR) and GPM Microwave Imager (GMI). The GPM Core mission is slated for launch in 2014. The DPR and GMI represent the next-generation of sensors that are currently flown on the Tropical Rainfall Measuring Mission (TRMM) satellite (1997 - present). The DPR's two channels generally yield more accurate precipitation particle size distribution and rain rate estimates. The GMI has additional higher-frequency microwave channels useful for light rain and snow detection.
Laboratory researchers are developing computer algorithms for diagnosing precipitation rates, vertical structure, and latent heating from a combination of the DPR and GMI data; see Grecu et al. (2004, 2009, 2011). In the pre-launch phase of GPM, these algorithms are applied to either TRMM data or synthesized GPM observations. Below are the surface rainfall rate fields in Hurricane Floyd (1999) and a Pacific wintertime cold-frontal band derived from TRMM data and a prototype algorithm being designed for GPM. The performance of this algorithm is similar to previously-developed TRMM algorithms, but it has the advantage that it can incorporate the additional channel data from GPM to improve precipitation estimates.
- Grecu, M . S. Olson, and E. N. Anagnostou, 2004: Retrieval of precipitation profiles from multiresolution, multifrequency, active and passive microwave observations. J. Appl. Meteor., 43, 562-575.
- Grecu M., W. S. Olson, C.-L. Shie, T. S. L'Ecuyer, and W.-K. Tao, 2009: Combining satellite microwave radiometer and radar observations to estimate atmospheric latent heating profiles. Journal of Climate, 22, 6356-6376.
- Grecu, M., L. Tian, W. S. Olson, and S. Tanelli, 2011: A robust dual-frequency radar profiling algorithm. J. Appl. Meteor. and Climatol., 50, 1543-1557.
Goddard Lidar Observatory for Wind (GLOW)
GLOW stands for Goddard Lidar Observatory for Wind. It is a mobile Doppler lidar system based on double edge direct detection technology. It consists of a molecular system at 355nm and a aerosol system at 1064nm. GLOW merges atmospheric science with innovative new remote sensing methodologies. New lidar technologies are perfected during ground use in preparation for eventual use in air and space based wind measurement systems.
Tropospheric Wind Lidar Technology Experiment (TWiLiTE)
The TWiLiTE (Tropospheric Wind Lidar Technology Experiment) airborne Doppler lidar was developed as an ESTO funded IIP instrument over the three year time period beginning in August 2005. The TWiLiTE instrument is designed for autonomous operation on NASAs high altitude research aircraft, such as the ER-2, WB-57 or Global Hawk. Flight testing and validation of TWiLiTE is a critical step forward for direct detection Doppler lidar on the path to a space based global 3DWinds Mission.
The Cloud Physics Lidar (CPL)
The Cloud Physics Lidar, or CPL, is a airborne backscatter lidar designed to operate simultaneously at three wavelengths: 1064, 532, and 355 nm. The CPL flies on high-altitude research aircraft, such as the ER-2 or WB-57. The purpose of the CPL is to provide multiwavelength measurements of cirrus, subvisual cirrus, and aerosols with high temporal and spatial resolution. The CPL utilizes state-of-art technology with a high repetition rate, low pulse energy laser and photon-counting detection. Vertical resolution of the CPL measurements is fixed at 30 m; horizontal resolution can vary but is typically about 200 m. From a fundamental measurement of 180-degree volume backscatter coefficients, various data products are derived, including time-height cross-section images; cloud and aerosol layer boundaries; optical depth for clouds, aerosol, and planetary boundary layer; and extinction profiles.
Micro-Pulse Lidar Network (MPLNET)
The Micro-Pulse Lidar Network (MPLNET) is comprised of ground-based lidar systems, co-located with sun/sky photometer sites in the NASA Aerosol Robotic Network (AERONET). The MPLNET project utilizes the micro-pulse lidar (MPL) system, which is a compact and eye-safe lidar capable of determining the range of aerosols and clouds continuously in an autonomous fashion. The unique capability of this lidar to operate unattended in remote areas makes it an ideal instrument to use for a network. The primary purpose of MPLNET is to acquire long-term observations of aerosol and cloud vertical structure at key sites around the world. These types of observations are required for several NASA satellite validation programs, and are also a high priority of the Intergovernmental Panel on Climate Change (IPCC) and related programs. The combined lidar and sunphotometer measurements are able to produce quantitative aerosol and cloud products, such as optical depth, sky radiance, vertical structure, and extinction profiles. MPLNET results have contributed to studies of dust, biomass, marine, and continental aerosol properties, the effects of soot on cloud formation, aerosol transport processes, and polar clouds and snow. MPLNET data has also been used to validate results from NASA satellite sensors such as MISR and TOMS, and to help construct algorithms used to interpret space-based lidar data. MPLNET sites are used for validation of NASA's GLAS and CALIPSO satellite lidar sensors.
Scanning Raman Lidar (SRL)
Because of its importance in radiative transfer, convection, general circulation, and the hydrological cycle, atmospheric water vapor plays a crucial role in understanding atmospheric processes. For example, since water is the most active infrared molecule in the atmosphere, water vapor response is a major factor in any global warming triggered by increasing carbon dioxide. In addition, atmospheric aerosols also have a significant impact on the earth's climate by scattering and absorbing solar radiation and by altering the physical and radiative properties of clouds. Clouds also play an active role in the atmospheric radiation balance. A Scanning Raman Lidar (SRL) was developed and is used to provide frequent and accurate measurements of water vapor, aerosols and clouds to study these atmospheric processes. For this system, laser scattering by molecules (water vapor and nitrogen) and particles (suspended aerosols and cloud droplets or ice crystals) is detected as a function of altitude. Water vapor mixing ratio, which is the ratio of the mass of water vapor to the mass of dry air, is computed from the ratio of the Raman scattering from water vapor and nitrogen. When combined with measurements of temperature, the lidar water vapor data gives profiles of relative humidity. The lidar water vapor data acquired during field experiments have been used to validate radiative transfer models and study atmospheric features such as fronts, gravity waves, drylines and bores. The water vapor measurements also assess the quality of ground, balloon, and space-based sensors. These water vapor data have been used to determine how advanced statistical techniques (spectral, multifractal, and wavelet analysis) can be used to help understand the nature and causes of atmospheric structure and variability. In addition to measuring water vapor, the Scanning Raman Lidar simultaneously measures both aerosol backscattering, extinction and depolarization. Research is underway to use measurements from the system to quantify cirrus cloud ice water content and warm cloud liquid water content. In the International H2O experiment (IHOP) held in the Oklahoma-Kansas region in 2002, the SRL provided simultaneous measurements of water vapor, aerosol backscatter/extinction/depolarization, cirrus cloud optical depth/ice water content/particle diameter and, as a new research experiment rotational, Raman temperature profiles. Figure 13 shows an example of simultaneous water vapor mixing ratio, relative humidity, cirrus cloud scattering, depolarization, ice water content and particle diameter in an evolving cirrus cloud field. Not shown but also quantified for this case are cirrus cloud optical depth and extinction to backscatter ratio. This case is being used to as a case study for state of the art cirrus cloud modeling activity also occurring in Mesoscale Atmospheric Processes. Itemized captions: a) relative humidity with respect to ice calculated from SRL water vapor and radiosonde temperatures at two hour intervals during the development of the cloud system shown in the other images. Potential temperature profiles from radiosonde measurements are shown indicating a well-mixed region in the upper part of the cirrus cloud that decreases in depth over the measurement period.Significant upper tropospheric humidification is observed due to cirrus precipitation. Ice super saturation is also observed inside the cloud. b) time series of aerosol scattering ratio image of a cloud system involving two layers. The upper layer is a cirrus cloud due to outflow from a thunderstorm system to the north. The lower layer, which shows interesting oscillations, is studied further in the main text. c) Upper: volume depolarization ratio calculated for the cloud event of June 19-20. d) Lower: particle depolarization ratio for the same period. The particle depolarization ratio provides a much stronger indication of cirrus precipitation at 27 and 29 UT. e) ice water content retrievals for the cirrus system shown that uses Raman scattering from ice along with the cloud scattering ratioWangZ2004. f) generalized particle diameter retrievals using the newly developed retrieval WangZ2004 that uses Raman scattering from ice along with the cloud scattering ratio.
Raman Airborne Spectroscopic Lidar (RASL)
Raman lidar systems have proven to be very powerful research tools for study of atmospheric radiation and dynamics by offering accurate measurements of water vapor mixing ratio, aerosol backscatter/extinction and cloud properties. However, most of these measurements have been limited to ground-based platforms (Scanning Raman Lidar) and/or nighttime measurement periods. The Raman Airborne Spectroscopic Lidar (RASL), developed under the first NASA Instrument Incubator Program, offers measurements of water vapor, aerosols and clouds under both day and night conditions. It is the only airborne lidar system that combines the ability to measure water vapor mixing ratio and aerosol extinction either daytime or nighttime. The first time that RASL was turned on, it was run for 24 continuous hours and demonstrated measurement capability that met or exceeded numerical simulation predictions. Simultaneous measurements of water vapor mixing ratio, aerosol and cirrus cloud depolarization and cirrus cloud optical depth and extinction to backscatter ratio from that measurement period in September, 2002 are shown in figure xx. RASL is now being configured for first flight. Itemized captions: a) water vapor mixing ratio during a daytime segment of the measurement period. Convective plumes in the water vapor field are observed at ~1400 UT. b) boundary layer aerosol depolarization during the nighttime showing significant stratification. c) Cirrus cloud scattering ratio measured during the daytime d) Cirrus cloud depolarization measured at night. Cirrus precipitation is seen between 1400 and 1500 UT. A segment of the cloud that is believed to be supercooled water can be seen after 1530 UT. e) Cirrus optical depth and extinction to backscatter ratio (EB) quantified during the daytime f) Cirrus optical depth and extinction to backscatter ratio quantified during the nighttime