National Polar-orbiting Operational Environmental Satellite System Research Articles

Precipitation profile retrievals using temperature‐sounding microwave observations

A Bayesian retrieval algorithm was developed to demonstrate the potential of microwave temperature‐sounding channels for precipitation profile retrieval from spaceborne observations. The algorithm uses a database from combined cloud‐radiative transfer model simulations of Hurricane Bonnie which was observed during the field campaign Convection and Moisture Experiment 3 (CAMEX‐3). Sounding channels from two oxygen absorption complexes at 50–57 GHz and 118.75 GHz were combined to make use of their differential response to absorption and scattering by hydrometeors. The retrieval method was applied to airborne observations with the National Polar‐Orbiting Operational Environmental Satellite System (NPOESS) Aircraft Sounder Testbed‐Microwave (NAST‐M) radiometer on board the ER 2 aircraft. The retrieved profiles were used to simulate radar reflectivities to be compared to ER 2 Doppler observations from the same aircraft. The results lead to the following conclusions: (1) The sounding channels provide the unique potential of cloud slicing because the channel‐dependent variation of clear‐air absorption allows the adjustment of maximum sensitivity to different altitudes. (2) The validation with radar data indicates a good performance of the algorithm; however, at least four channels in each absorption complex are required to constrain the retrieval well enough with the observations. (3) The validation also shows that even though a Hurricane Bonnie cloud model simulation was used, the simulated database does not represent the observations very well. (4) The database may bias the retrievals by the underlying assumptions on temperature, humidity, and hydrometeor distributions. Sounding channels are more sensitive to a possible temperature bias in the database. While this bias can be corrected, the retrievals forward the database bias to the retrieved products independent of sensor. For global applications, more flexible retrieval approaches are required that are capable of constraining the algorithm according to the local situation.

Spaceborne soil moisture estimation at high resolution: a microwave-optical/IR synergistic approach

An approach is evaluated for the estimation of soil moisture at high resolution using satellite microwave and optical/infrared (IR) data. This approach can be applied to data acquired by the Visible/Infrared Imager Radiometer Sensor Suite (VIIRS) and a Conical Scanning Microwave Imager/Sounder (CMIS), planned for launch in the 2009–2010 time frame under the National Polar-Orbiting Operational Environmental Satellite System (NPOESS). The approach for soil moisture estimation involves two steps. In the first step, a passive microwave remote sensing technique is employed to estimate soil moisture at low resolution (∼25 km). This involves use of a simplified radiative transfer model to invert dual-polarized microwave brightness temperature. In the second step, the microwave-derived low-resolution soil moisture is linked to the scene optical/IR parameters, such as Normalized Difference Vegetation Index (NDVI), surface albedo, and Land Surface Temperature (LST). The linking is based on the ‘Universal Triangle’ approach of relating land surface parameters to soil moisture. The optical/IR parameters are available at high resolution (∼1 km) but are aggregated to the microwave resolution for the purpose of building the linkage model. The linkage model in conjunction with high-resolution NDVI, surface albedo and LST is then used to disaggregate microwave soil moisture into high-resolution soil moisture. The technique is applied to data from the Special Sensor Microwave Imager (SSM/I) and Advanced Very High Resolution Radiometer (AVHRR) acquired for the Southern Great Plains (SGP-97) experiment conducted in Oklahoma in June–July 1997. An error budget analysis performed on the estimation procedure shows that the rms error in the estimation of soil moisture is of the order of 5%. Predicted soil moisture results at high resolution agree reasonably well with low resolution results in both magnitude and spatio-temporal patterns. The high resolution results are also compared with in situ (0–5 cm deep) point measurements. While the trends are similar, the soil moisture estimates in the two cases are different. Issues involving comparison of satellite derived soil moisture with in situ point measurements are also discussed.

Thermodynamic product retrieval methodology and validation for NAST-I.

The National Polar-Orbiting Operational Environmental Satellite System (NPOESS) Airborne Sounder Testbed (NAST) consists of two passive collocated cross-track scanning instruments, an infrared interferometer (NAST-I) and a microwave radiometer (NAST-M), that fly onboard high-altitude aircraft such as the NASA ER-2 at an altitude near 20 km. NAST-I provides relatively high spectral resolution (0.25-cm(-1)) measurements in the 645-2700-cm(-1) spectral region with moderate spatial resolution (a linear resolution equal to 13% of the aircraft altitude at nadir) cross-track scanning. We report the methodology for retrieval of atmospheric temperature and composition profiles from NAST-I radiance spectra. The profiles were determined by use of a statistical eigenvector regression algorithm and improved, as needed, by use of a nonlinear physical retrieval algorithm. Several field campaigns conducted under varied meteorological conditions have provided the data needed to verify the accuracy of the spectral radiance, the retrieval algorithm, and the scanning capabilities of this instrumentation. Retrieval examples are presented to demonstrate the ability to reveal fine-scale horizontal features with relatively high vertical resolution.

Application of the Dozier retrieval to wildfire characterization: a sensitivity analysis

The demand for improved information on regional and global fire activity in the context of land use/land cover change, ecosystem disturbance, climate modeling, and natural hazards has increased efforts in recent years to improve earth-observing satellite sensors and associated methods for fire information retrieval. While sensor development has made considerable headway for fire monitoring with the recent launch of Terra in late 1999 and upcoming missions such as bispectral infrared detection (BIRD), FOCUS, and the National Polar-Orbiting Operational Environmental Satellite System (NPOESS), the retrieval of fire properties from satellite observations remains problematic. Current methods for determining properties of actively burning fires, for example, continue to be based on a simple two-component model developed by Dozier in 1981 [Remote Sens. Environ. 11 (1981) 221.]. Its limitations in terms of reliable operational fire property retrieval have been known for some time, although not examined in detail to date. With new measurements from recently deployed and evolving satellite systems, which offer key advantages for fire remote sensing, it is appropriate now to more comprehensively examine the heritage methodology for fire property retrieval. The results of a sensitivity analysis indicate that under realistic conditions the random errors in fire temperature and area retrieved using Dozier's method are ±100 K and ±50% at one standard deviation, respectively, for fires occupying a pixel fraction greater than 0.005 (this corresponds to a 5000-m 2 fire within a 1-km pixel). For smaller active fires, larger random and systematic errors are likely to occur.

NPOESS Aircraft Sounder Testbed-Microwave (NAST-M): instrument description and initial flight results

The National Polar-Orbiting Operational Environmental Satellite System (NPOESS) Aircraft Sounder Testbed (NAST) has been developed and deployed on the NASA ER-2 high-altitude aircraft. The testbed consists of two co-located cross-track scanning instruments: a Fourier transform interferometer spectrometer (NAST-I) with spectral coverage of 3.7-15.5 /spl mu/m and a passive microwave spectrometer (NAST-M) with 17 channels near the oxygen absorption lines at 50-57 GHz and 118.75 GHz. The testbed provides the first coregistered imagery from high-resolution microwave and infrared sounders and will provide new data that will help (1) validate meteorological satellite environmental data record feasibility, (2) define future satellite instrument specifications, and (3) demonstrate operational issues in ground validation, data calibration, and retrievals of meteorological parameters. To help validate the performance and potential of NAST-M, imagery was collected from more than 20 overpasses of hurricanes Bonnie and Earl during the Convection and Moisture Experiment (CAMEX-3), Florida, boreal summer 1998. The warm core and convection morphology of Hurricane Bonnie (August, 1998) is clearly revealed both by aircraft-based microwave brightness temperature imagery and temperature retrievals within the eye. Radiance comparisons with the Advanced Microwave Sounding Unit on the NOAA-15 satellite and radiosonde observations yield root mean-squared agreements of approximately 1 K or less.

System Design Considerations for the Retrieval of Sea Surface Temperatures in the NPOESS Era

Abstract The National Polar-Orbiting Operational Environmental Satellite System (NPOESS) requires improved accuracy in the retrieval of sea surface skin temperature (SSTS) from its Visible Infrared Imager Radiometer Suite (VIIRS) sensor over the capability to retrieve bulk sea surface temperature (SSTB) that has been demonstrated with currently operational National Oceanic and Atmospheric Administration (NOAA) satellites carrying the Advanced Very High Resolution Radiometer (AVHRR) sensor. Statistics show an existing capability to retrieve SSTB with a 1σ accuracy of about 0.8 K in the daytime and 0.6 K with nighttime data. During the NPOESS era, a minimum 1σ SSTS measurement uncertainty of 0.5 K is required during daytime and nighttime conditions, while 0.1 K is desired. Simulations have been performed, using PACEOS™ scene generation software and the multichannel sea surface temperature (MCSST) algorithms developed by NOAA, to better understand the implications of this more stringent requirement on algori...