Collocating satellite-based radar and radiometer measurements – methodology and usage examples (original) (raw)
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Formulation and validation of simulated data for the Atmospheric Infrared Sounder (AIRS
IEEE Transactions on Geoscience and Remote Sensing, 2003
Abstruct-Models for synthesizing radiance measurements by the Atmospheric Infrared Sounder (AIRS) are described. Synthetics radiances have been generated for developing and testing data processing algorithms. The radiances are calculated from geophysical states derived from weather forecasts and climatology using the AIRS rapid transmission algorithms. The data contains horizontal variability at the spatial resolution of AIRS from the surface and cloud fields. This is needed to test retrieval algorithms under partially cloudy conditions. The surface variability is added using vegetation and IGBP surface type maps, while cloud variability is added randomly. The radiances are spectrally averaged to create High Resolution Infrared Sounder (HIRS) data and this is compared with actual HIRSZ data on the NOAA 14 satellite. The data are in agreement to 1-4 K, but the simulated data under represent high altitude equatorial cirrus clouds and have too much local variability. They agree in the mean to within 1-4 K and global standard deviation agree to better than 2 K. Simulated data have been a valuable tool for developing retrieval algorithms and studying error characteristics and will continue to do so after launch.
Analysis of Information Content of Infrared Sounding Radiances in Cloudy Conditions
Monthly Weather Review, 2006
Information content analysis of the Geostationary Operational Environmental Satellite (GOES) sounder observations in the infrared was conducted for use in satellite data assimilation. Information content is defined as a first-order response of the top-of-atmosphere brightness temperature to perturbations of simulated temperature and humidity profiles, obtained from a cloud-resolving model, both in the presence and absence of clouds. Sensitivity to the perturbations was numerically evaluated using an observational operator for visible and infrared radiative transfer developed within a research satellite data assimilation system. The vertical distribution of the sensitivities was analyzed as a function of cloud optical thickness covering the range from a cloud-free scene to an optically thick cloud. The clear-sky sensitivities to temperature and humidity perturbations for each channel are representative of the corresponding channel weighting functions for a clear-sky case. For optical...
Advances in Atmospheric Sciences, 2015
The successful launch and commissioning of the first geostationary meteorological satellite of Korea has the potential to enhance earth observation capability over the Asia Pacific region. Although the specifications of the payload, the meteorological imager (MI), have been verified during both ground and in-orbit tests, there is the possibility of variation and/or degradation of data quality due to many different reasons, such as the accumulation of contaminants, the aging of instrument components, and unexpected external disturbance. Thus, for better utilization of MI data, it is imperative to continuously monitor and maintain the data quality. As a part of such activity, this study presents an inter-calibration, based on the Global Space-based Inter-Calibration System (GSICS), between the MI data and the high quality hyperspectral data from the Infrared Atmospheric Sounding Interferometer (IASI) of the Metop-A satellite. Both sets of data, acquired for three years from April 2011 to March 2014, are processed to prepare the matchup dataset, which is spatially collocated, temporally concurrent, angularly coincident, and spectrally comparable. The results show that the MI data are stable within the specifications and show no significant degradation during the study period. However, the water vapor channel shows a rather large bias value of −0.77 K, with a root-mean-square difference (RMSD) of around 1.1 K, which is thought to be due to the shift in the spectral response function. The shortwave channel shows a maximum RMSD of around 1.39 K, mainly due to the coarse digitization at the lower temperature. The inter-comparison results are rechecked through a sensitivity analysis with different sets of threshold values used for the matchup dataset. Based on this, we confirm that the overall quality of the MI data meets the user requirements and maintains the expected performance, although the water vapor channel requires further investigation.
Neural network microwave precipitation retrievals and modeling results
Microwave Remote Sensing of the Atmosphere and Environment VI, 2008
We describe a simulation methodology used to develop and validate precipitation retrieval algorithms for current and future passive microwave sounders with emphasis on the NPOESS (National Polar-orbiting Operational Environmental Satellite System) sensors. Precipitation algorithms are currently being developed for ATMS, MIS, and NAST-M. ATMS, like AMSU, will have channels near the oxygen bands throughout 50-60 GHz, the water vapor resonance band at 183.31 GHz, as well as several window channels. ATMS will offer improvements in radiometric and spatial resolution over the AMSU-A/B and MHS sensors currently flying on NASA (Aqua), NOAA (POES) and EUMETSAT (MetOp) satellites. The similarity of ATMS to AMSU-A/B will allow the AMSU-A/B precipitation algorithm developed by Chen and Staelin to be adapted for ATMS, and the improvements of ATMS over AMSU-A/B suggest that a superior precipitation retrieval algorithm can be developed for ATMS. Like the Chen and Staelin algorithm for AMSU-A/B, the algorithm for ATMS to be presented will also be based a statisticsbased approach involving extensive signal processing and neural network estimation in contrast to traditional physics-based approaches. One potential advantage of a neural-network-based algorithm is computational speed. The main difference in applying the Chen-Staelin method to ATMS will consist of using the output of the most up-to-date simulation methodology instead of the ground-based weather radar and earlier versions of the simulation methodology.
Testing IWC Retrieval Methods Using Radar and Ancillary Measurements with In Situ Data
Journal of Applied Meteorology and Climatology, 2008
Vertical profiles of ice water content (IWC) can now be derived globally from spaceborne cloud satellite radar (CloudSat) data. Integrating these data with Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) data may further increase accuracy. Evaluations of the accuracy of IWC retrieved from radar alone and together with other measurements are now essential. A forward model employing aircraft Lagrangian spiral descents through mid- and low-latitude ice clouds is used to estimate profiles of what a lidar and conventional and Doppler radar would sense. Radar reflectivity Ze and Doppler fall speed at multiple wavelengths and extinction in visible wavelengths were derived from particle size distributions and shape data, constrained by IWC that were measured directly in most instances. These data were provided to eight teams that together cover 10 retrieval methods. Almost 3400 vertically distributed points from 19 clouds were used. Approximate cloud optical dept...
A multichannel radiometric profiler of temperature, humidity, and cloud liquid
Radio Science, 2003
1] A microwave radiometer is described that provides continuous thermodynamic (temperature, water vapor, and moisture) soundings during clear and cloudy conditions. The radiometric profiler observes radiation intensity at 12 microwave frequencies, along with zenith infrared and surface meteorological measurements. Historical radiosonde and neural network or regression methods are used for profile retrieval. We compare radiometric, radiosonde, and forecast soundings and evaluate the accuracy of radiometric temperature and water vapor soundings on the basis of statistical comparison with radiosonde soundings. We find that radiometric soundings are equivalent in accuracy to radiosonde soundings when used in numerical weather forecasting. A case study is described that demonstrates improved fog forecasting on the basis of variational assimilation of radiometric soundings. The accuracy of radiometric cloud liquid soundings is evaluated by comparison with cloud liquid sensors carried by radiosondes. Accurate high-resolution three-dimensional water vapor and wind analysis is described on the basis of assimilation of simulated thermodynamic and wind soundings along with GPS slant delays. Examples of mobile thermodynamic and wind profilers are shown. Thermodynamic profiling, particularly when combined with wind profiling and slant GPS, provides continuous atmospheric soundings for improved weather and dispersion forecasting.
Validation of the IASI temperature and water vapor profile retrievals by correlative radiosondes
SPIE Proceedings, 2008
The METOP-A satellite Infrared Atmospheric Sounding Interferometer (IASI) Level 2 products comprise retrievals of vertical profiles of temperature and water vapor. The L2 data were validated through assessment of their error covariances and biases using radiosonde data for the reference. The radiosonde data set includes dedicated launches as well as the ones performed at regular synoptic times at Lindenberg station (Germany). For optimal error estimate the linear statistical Validation Assessment Model (VAM) was used. The model establishes relation between the compared satellite and reference measurements based on their relations to the true atmospheric state. The VAM utilizes IASI averaging kernels and statistical characteristics of the ensembles of the reference data to allow for finite vertical resolution of the retrievals and spatial and temporal non-coincidence. For temperature retrievals expected and assessed errors are in good agreement; error variances/rms of a single FOV retrieval are 1K between 800-300 mb with an increase to ~1K in tropopause and ~2K at the surface, possibly due to wrong surface parameters and undetected clouds/haze. Bias against radiosondes oscillates within 0 5K. between 950-100 mb. As for water vapor, its highly variable complex spatial structure does not allow assessment of retrieval errors with the same degree of accuracy as for temperature. Error variances/rms of a single FOV relative humidity retrieval are between 10-13% RH in the 800-300 mb range.