Journal articles: 'Advanced Microwave Sounding Unit'

1

Saunders, R. W. "Note on the Advanced Microwave Sounding Unit." Bulletin of the American Meteorological Society 74, no. 11 (November 1993): 2211–12. http://dx.doi.org/10.1175/1520-0477-74.11.2211.

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Weng, Fuzhong, Limin Zhao, Ralph R. Ferraro, Gene Poe, Xiaofan Li, and Norman C. Grody. "Advanced microwave sounding unit cloud and precipitation algorithms." Radio Science 38, no. 4 (June 5, 2003): n/a. http://dx.doi.org/10.1029/2002rs002679.

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3

Vangasse, P., J. Charlton, and M. Jarrett. "Characterisation of the Advanced Microwave Sounding Unit, AMSU-B." Advances in Space Research 17, no. 1 (January 1996): 75–78. http://dx.doi.org/10.1016/0273-1177(95)00451-j.

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4

Mears, Carl A., and Frank J. Wentz. "Construction of the Remote Sensing Systems V3.2 Atmospheric Temperature Records from the MSU and AMSU Microwave Sounders." Journal of Atmospheric and Oceanic Technology 26, no. 6 (June 1, 2009): 1040–56. http://dx.doi.org/10.1175/2008jtecha1176.1.

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Abstract Measurements made by microwave sounding instruments provide a multidecadal record of atmospheric temperature change. Measurements began in late 1978 with the launch of the first Microwave Sounding Unit (MSU) and continue to the present. In 1998, the first of the follow-on series of instruments—the Advanced Microwave Sounding Units (AMSUs)—was launched. To continue the atmospheric temperature record past 2004, when measurements from the last MSU instrument degraded in quality, AMSU and MSU measurements must be intercalibrated and combined to extend the atmospheric temperature data records. Calibration methods are described for three MSU–AMSU channels that measure the temperature of thick layers of the atmosphere centered in the middle troposphere, near the tropopause, and in the lower stratosphere. Some features of the resulting datasets are briefly summarized.

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Bell, William, Sabatino Di Michele, Peter Bauer, Tony McNally, Stephen J. English, Nigel Atkinson, Fiona Hilton, and Janet Charlton. "The Radiometric Sensitivity Requirements for Satellite Microwave Temperature Sounding Instruments for Numerical Weather Prediction." Journal of Atmospheric and Oceanic Technology 27, no. 3 (March 1, 2010): 443–56. http://dx.doi.org/10.1175/2009jtecha1293.1.

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Abstract The sensitivity of NWP forecast accuracy with respect to the radiometric performance of microwave sounders is assessed through a series of observing system experiments at the Met Office and ECMWF. The observing system experiments compare the impact of normal data from a single Advanced Microwave Sounding Unit (AMSU) with that from an AMSU where synthetic noise has been added. The results show a measurable reduction in forecast improvement in the Southern Hemisphere, with improvements reduced by 11% for relatively small increases in radiometric noise [noise-equivalent brightness temperature (NEΔT) increased from 0.1 to 0.2 K for remapped data]. The impact of microwave sounding data is shown to be significantly less than was the case prior to the use of advanced infrared sounder data [Atmospheric Infrared Sounder (AIRS) and Infrared Atmospheric Sounding Interferometer (IASI)], with microwave sounding data now reducing Southern Hemisphere forecast errors by approximately 10% compared to 40% in the pre-AIRS/IASI period.

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Li, Ching‐Chung, Mou‐Hsiang Chang, and Yung‐Chang Chen. "Oceanic typhoon rainfall estimation using Advanced Microwave Sounding Unit‐A data." International Journal of Remote Sensing 27, no. 7 (April 2006): 1477–90. http://dx.doi.org/10.1080/01431160500296875.

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Zhu, Tong, Da-Lin Zhang, and Fuzhong Weng. "Impact of the Advanced Microwave Sounding Unit Measurements on Hurricane Prediction." Monthly Weather Review 130, no. 10 (October 2002): 2416–32. http://dx.doi.org/10.1175/1520-0493(2002)130<2416:iotams>2.0.co;2.

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Zhao, Limin, and Fuzhong Weng. "Retrieval of Ice Cloud Parameters Using the Advanced Microwave Sounding Unit." Journal of Applied Meteorology 41, no. 4 (April 2002): 384–95. http://dx.doi.org/10.1175/1520-0450(2002)041<0384:roicpu>2.0.co;2.

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9

Mo, T. "Postlaunch Calibration of the NOAA-18 Advanced Microwave Sounding Unit-A." IEEE Transactions on Geoscience and Remote Sensing 45, no. 7 (July 2007): 1928–37. http://dx.doi.org/10.1109/tgrs.2007.897451.

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Mo, Tsan. "Postlaunch Calibration of the METOP-A Advanced Microwave Sounding Unit-A." IEEE Transactions on Geoscience and Remote Sensing 46, no. 11 (November 2008): 3581–600. http://dx.doi.org/10.1109/tgrs.2008.2001922.

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Ferraro, R. R., Fuzhong Weng, N. C. Grody, Limin Zhao, Huan Meng, Cezar Kongoli, P. Pellegrino, Shuang Qiu, and C. Dean. "NOAA operational hydrological products derived from the advanced microwave sounding unit." IEEE Transactions on Geoscience and Remote Sensing 43, no. 5 (May 2005): 1036–49. http://dx.doi.org/10.1109/tgrs.2004.843249.

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12

Mo, T. "Prelaunch calibration of the advanced microwave sounding unit-A for NOAA-K." IEEE Transactions on Microwave Theory and Techniques 44, no. 8 (1996): 1460–69. http://dx.doi.org/10.1109/22.536029.

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13

Deng, Guo, Dalin Zhang, Tong Zhu, and Angsheng Wang. "Use of the advanced microwave sounding unit data to improve typhoon prediction." Progress in Natural Science 19, no. 3 (March 2009): 369–76. http://dx.doi.org/10.1016/j.pnsc.2008.08.001.

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Kidder, Stanley Q., Mitchell D. Goldberg, Raymond M. Zehr, Mark DeMaria, James F. W. Purdom, Christopher S. Velden, Norman C. Grody, and Sheldon J. Kusselson. "Satellite Analysis of Tropical Cyclones Using the Advanced Microwave Sounding Unit (AMSU)." Bulletin of the American Meteorological Society 81, no. 6 (June 2000): 1241–59. http://dx.doi.org/10.1175/1520-0477(2000)081<1241:saotcu>2.3.co;2.

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15

Bessho, Kotaro, Mark DeMaria, and John A. Knaff. "Tropical Cyclone Wind Retrievals from the Advanced Microwave Sounding Unit: Application to Surface Wind Analysis." Journal of Applied Meteorology and Climatology 45, no. 3 (March 1, 2006): 399–415. http://dx.doi.org/10.1175/jam2352.1.

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Abstract Horizontal winds at 850 hPa from tropical cyclones retrieved using the nonlinear balance equation, where the mass field was determined from Advanced Microwave Sounding Unit (AMSU) temperature soundings, are compared with the surface wind fields derived from NASA's Quick Scatterometer (QuikSCAT) and Hurricane Research Division H*Wind analyses. It was found that the AMSU-derived wind speeds at 850 hPa have linear relations with the surface wind speeds from QuikSCAT or H*Wind. There are also characteristic biases of wind direction between AMSU and QuikSCAT or H*Wind. Using this information to adjust the speed and correct for the directional bias, a new algorithm was developed for estimation of the tropical cyclone surface wind field from the AMSU-derived 850-hPa winds. The algorithm was evaluated in two independent cases from Hurricanes Floyd (1999) and Michelle (2001), which were observed simultaneously by AMSU, QuikSCAT, and H*Wind. In this evaluation the AMSU adjustment algorithm for wind speed worked well. Results also showed that the bias correction algorithm for wind direction has room for improvement.

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Yang, Hu, and Martin Burgdorf. "A Study of Lunar Microwave Radiation Based on Satellite Observations." Remote Sensing 12, no. 7 (April 2, 2020): 1129. http://dx.doi.org/10.3390/rs12071129.

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In recent years, the study of microwave radiation from the Moon’s surface has been of interest to the astronomy and remote sensing communities. Due to the stable geophysical properties of the Moon’s surface, microwave lunar radiation is highly predictable and can be accurately modeled, given sufficient observations from reliable instruments. Specifically, for microwave remote sensing study, if International System of Unit (SI) traceable observations of the Moon are available, the Moon can thus be used as an SI traceable calibration reference for microwave instruments to evaluate their calibration accuracies and assess their long-term calibration stabilities. Major challenges of using the Moon as a radiometric source standard for microwave sensors include the uncertainties in antenna pattern measurements, the reliability of measurements of brightness temperature (Tb) in the microwave spectrum of the lunar surface, and knowledge of the lunar phase lag because of penetration depths at different detection frequencies. Most microwave-sounding instruments can collect lunar radiation data from space-view observations during so-called lunar intrusion events that usually occur several days each month. Addressed in this work based on Moon observations from the Advanced Technology Microwave Sounder and the Advanced Microwave Sounding Unit/Microwave Humidity Sounder are two major issues in lunar calibration: the lunar surface microwave Tb spectrum and phase lag. The scientific objective of this study is to present our most recent progress on the study of lunar microwave radiation based on satellite observations. Reported here are the lunar microwave Tb spectrum and phase lag from 23 to 183 GHz based on observations of microwave-sounding instruments onboard different satellite platforms. For current Moon microwave radiation research, this study can help toward better understanding lunar microwave radiation features over a wide spectrum range, laying a solid foundation for future lunar microwave calibration efforts.

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17

Zou, Xiaolei, Fuzhong Weng, and H. Yang. "Connecting the Time Series of Microwave Sounding Observations from AMSU to ATMS for Long-Term Monitoring of Climate." Journal of Atmospheric and Oceanic Technology 31, no. 10 (October 1, 2014): 2206–22. http://dx.doi.org/10.1175/jtech-d-13-00232.1.

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Abstract The measurements from the Microwave Sounding Unit (MSU) and the Advanced Microwave Sounding Unit-A (AMSU-A) on board NOAA polar-orbiting satellites have been extensively utilized for detecting atmospheric temperature trend during the last several decades. After the launch of the Suomi National Polar-orbiting Partnership (Suomi-NPP) satellite on 28 October 2011, MSU and AMSU-A time series will be overlapping with the Advanced Technology Microwave Sounder (ATMS) measurements. While ATMS inherited the central frequency and bandpass from most of AMSU-A sounding channels, its spatial resolution and noise features are, however, distinctly different from those of AMSU. In this study, the Backus–Gilbert method is used to optimally resample the ATMS data to AMSU-A fields of view (FOVs). The differences between the original and resampled ATMS data are demonstrated. By using the simultaneous nadir overpass (SNO) method, ATMS-resampled observations are collocated in space and time with AMSU-A data. The intersensor biases are then derived for each pair of ATMS–AMSU-A channels. It is shown that the brightness temperatures from ATMS now fall well within the AMSU data family after resampling and SNO cross calibration. Thus, the MSU–AMSU time series can be extended into future decades for more climate applications.

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18

Moore, Richard W., and Thomas H. Vonder Haar. "Diagnosis of a Polar Low Warm Core Utilizing the Advanced Microwave Sounding Unit." Weather and Forecasting 18, no. 5 (October 2003): 700–711. http://dx.doi.org/10.1175/1520-0434(2003)018<0700:doaplw>2.0.co;2.

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19

Bennartz, Ralf, Anke Thoss, Adam Dybbroe, and Daniel B. Michelson. "Precipitation analysis using the Advanced Microwave Sounding Unit in support of nowcasting applications." Meteorological Applications 9, no. 2 (June 2002): 177–89. http://dx.doi.org/10.1017/s1350482702002037.

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20

Claud, C., B. M. Funatsu, G. Noer, and J. P. Chaboureau. "Observation of polar lows by the Advanced Microwave Sounding Unit: potential and limitations." Tellus A: Dynamic Meteorology and Oceanography 61, no. 2 (January 2009): 264–77. http://dx.doi.org/10.1111/j.1600-0870.2008.00384.x.

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21

Demuth, Julie L., Mark DeMaria, and John A. Knaff. "Improvement of Advanced Microwave Sounding Unit Tropical Cyclone Intensity and Size Estimation Algorithms." Journal of Applied Meteorology and Climatology 45, no. 11 (November 1, 2006): 1573–81. http://dx.doi.org/10.1175/jam2429.1.

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Abstract Previous work, in which Advanced Microwave Sounding Unit (AMSU) data from the Atlantic Ocean and east Pacific Ocean basins during 1999–2001 were used to provide objective estimates of 1-min maximum sustained surface winds, minimum sea level pressure, and the radii of 34-, 50-, and 64-kt (1 kt ≡ 0.5144 m s−1) winds in the northeast, southeast, southwest, and northwest quadrants of tropical cyclones, is updated to reflect larger datasets, improved statistical analysis techniques, and improved estimation through dependent variable transforms. A multiple regression approach, which utilizes best-subset predictor selection and cross validation, is employed to develop the estimation models, where the dependent data (i.e., maximum sustained winds, minimum pressure, wind radii) are from the extended best track and the independent data consist of AMSU-derived parameters that give information about retrieved pressure, winds, temperature, moisture, and satellite resolution. The developmental regression models result in mean absolute errors (MAE) of 10.8 kt and 7.8 hPa for estimating maximum winds and minimum pressure, respectively. The MAE for the 34-, 50-, and 64-kt azimuthally averaged wind radii are 16.9, 13.3, and 6.8 n mi (1 n mi ≡ 1852 m), respectively.

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22

Demuth, Julie L., Mark DeMaria, John A. Knaff, and Thomas H. Vonder Haar. "Evaluation of Advanced Microwave Sounding Unit Tropical-Cyclone Intensity and Size Estimation Algorithms." Journal of Applied Meteorology 43, no. 2 (February 2004): 282–96. http://dx.doi.org/10.1175/1520-0450(2004)043<0282:eoamsu>2.0.co;2.

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23

Iacovazzi, Robbie, Lin Lin, Ninghai Sun, and Quanhua Liu. "NOAA Operational Microwave Sounding Radiometer Data Quality Monitoring and Anomaly Assessment Using COSMIC GNSS Radio-Occultation Soundings." Remote Sensing 12, no. 5 (March 4, 2020): 828. http://dx.doi.org/10.3390/rs12050828.

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National Oceanic and Atmospheric Administration (NOAA) operational Advanced Technology Microwave Sounder (ATMS) and Advanced Microwave Sounding Unit-A (AMSU-A) data used in numerical weather prediction and climate analysis are essential to protect life and property and maintain safe and efficient commerce. Routine data quality monitoring and anomaly assessment is important to sustain data effectiveness. One valuable parameter used to monitor microwave sounder data quality is the antenna temperature (Ta) difference (O-B) computed between direct instrument Ta measurements and forward radiative transfer model (RTM) brightness temperature (Tb) simulations. This requires microwave radiometer data to be collocated with atmospheric temperature and moisture sounding profiles, so that representative boundary conditions are used to produce the RTM-simulated Tb values. In this study, Constellation Observing System for Meteorology, Ionosphere, and Climate/Formosa Satellite Mission 3 (COSMIC) Global Navigation Satellite System (GNSS) Radio Occultation (RO) soundings over the ocean and equatorward of 60° latitude are used as input to the Community RTM (CRTM) to generate simulated NOAA-18, NOAA-19, Metop-A, and Metop-B AMSU-A and S-NPP and NOAA-20 ATMS Tb values. These simulated Tb values, together with observed Ta values that are nearly simultaneous in space and time, are used to compute Ta O-B statistics on monthly time scales for each instrument. In addition, the CRTM-simulated Tb values based on the COSMIC GNSS RO soundings can be used as a transfer standard to inter-compare Ta values from different microwave radiometer makes and models that have the same bands. For example, monthly Ta O-B statistics for NOAA-18 AMSU-A Channels 4–12 and NOAA-20 ATMS Channels 5–13 can be differenced to estimate the “double-difference” Ta biases between these two instruments for the corresponding frequency bands. This study reveals that the GNSS RO soundings are critical to monitoring and trending individual instrument O-B Ta biases and inter-instrument “double-difference” Ta biases and also to estimate impacts of some sensor anomalies on instrument Ta values.

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24

Klaes, K. Dieter, Marc Cohen, Yves Buhler, Peter Schlüssel, Rosemary Munro, Juha-Pekka Luntama, Axel von Engeln, et al. "An Introduction to the EUMETSAT Polar system." Bulletin of the American Meteorological Society 88, no. 7 (July 1, 2007): 1085–96. http://dx.doi.org/10.1175/bams-88-7-1085.

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The European Organisation for the Exploitation of Meteorological Satellites (EUMETSAT) Polar System is the European contribution to the European–U.S. operational polar meteorological satellite system (Initial Joint Polar System). It serves the midmorning (a.m.) orbit 0930 Local Solar Time (LST) descending node. The EUMETSAT satellites of this new polar system are the Meteorological Operational Satellite (Metop) satellites, jointly developed with ESA. Three Metop satellites are foreseen for at least 14 years of operation from 2006 onward and will support operational meteorology and climate monitoring. The Metop Programme includes the development of some instruments, such as the Global Ozone Monitoring Experiment, Advanced Scatterometer, and the Global Navigation Satellite System (GNSS) Receiver for Atmospheric Sounding, which are advanced instruments of recent successful research missions. Core components of the Metop payload, common with the payload on the U.S. satellites, are the Advanced Very High Resolution Radiometer and the Advanced Television Infrared Observation Satellite (TIROS) Operational Vertical Sounder (ATOVS) package, composed of the High Resolution Infrared Radiation Sounder (HIRS), Advanced Microwave Sounding Unit A (AMSU-A), and Microwave Humidity Sounder (MHS). They provide continuity to the NOAA-K, -L, -M satellite series (in orbit known as NOAA-15, -16 and -17). MHS is a EUMETSAT development and replaces the AMSU-B instrument in the ATOVS suite. The Infrared Atmospheric Sounding Interferometer (IASI) instrument, developed by the Centre National d'Etudes Spatiales, provides hyperspectral resolution infrared sounding capabilities and represents new technology in operational satellite remote sensing.

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25

Qin, Z., X. Zou, and F. Weng. "Arctic and Antarctic four-month oscillations detected from Advanced Microwave Sounding Unit-A measurements." Antarctic Science 24, no. 5 (May 17, 2012): 507–13. http://dx.doi.org/10.1017/s0954102012000417.

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AbstractSatellite microwave measurements can penetrate through clouds and therefore provide unique information of surface and near-surface temperatures and surface emissivity. In this study, the brightness temperatures from NOAA-15 Advanced Microwave Sounding Unit-A (AMSU-A) are used to analyse the surface temperature variation in the Arctic and Antarctic regions during the past 13 years from 1998–2010. The data from four AMSU-A channels sensitive to surface are analysed with wavelet and Fourier spectrum techniques. A very pronounced maximum is noticed in the period range centred around four months. Application of a statistical significance test confirms that it is a dominant mode of variability over polar regions besides the annual and semi-annual oscillations in the data. No evidence of this feature could be found in middle and low latitudes. The four-month oscillation is 90° out of phase at the Arctic and Antarctic, with the Arctic four-month oscillation reaching its maximum in the beginning of March, July and November and the Antarctic four-month oscillation in the middle of April, August and December. The intensity of the four-month oscillation varies interannually. The years with pronounced four-month oscillation were 2002–03, 2005–06 and 2008–09. The strongest year for the Arctic and Antarctic four-month oscillations occurred in 2005–06 and 2008–09, respectively. The sign of four-month oscillation is also found in the surface skin temperatures and two-metre air temperatures from ERA-Interim reanalysis, with strongest signal in 2005–06 when this oscillation is strongest in the data. It is hypothesized that the Arctic and Antarctic four-month oscillations are a combined result of unique features of solar radiative forcing and snow/sea ice formation and metamorphosis.

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26

Kleespies, Thomas J. "Relative Information Content of the Advanced Technology Microwave Sounder and the Combination of the Advanced Microwave Sounding Unit and the Microwave Humidity Sounder." IEEE Transactions on Geoscience and Remote Sensing 45, no. 7 (July 2007): 2224–27. http://dx.doi.org/10.1109/tgrs.2007.898088.

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27

Mears, Carl A., and Frank J. Wentz. "Construction of the RSS V3.2 Lower-Tropospheric Temperature Dataset from the MSU and AMSU Microwave Sounders." Journal of Atmospheric and Oceanic Technology 26, no. 8 (August 1, 2009): 1493–509. http://dx.doi.org/10.1175/2009jtecha1237.1.

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Abstract Measurements made by microwave sounding instruments provide a multidecadal record of atmospheric temperature in several thick atmospheric layers. Satellite measurements began in late 1978 with the launch of the first Microwave Sounding Unit (MSU) and have continued to the present via the use of measurements from the follow-on series of instruments, the Advanced Microwave Sounding Unit (AMSU). The weighting function for MSU channel 2 is centered in the middle troposphere but contains significant weight in the lower stratosphere. To obtain an estimate of tropospheric temperature change that is free from stratospheric effects, a weighted average of MSU channel 2 measurements made at different local zenith angles is used to extrapolate the measurements toward the surface, which results in a measurement of changes in the lower troposphere. In this paper, a description is provided of methods that were used to extend the MSU method to the newer AMSU channel 5 measurements and to intercalibrate the results from the different types of satellites. Then, satellite measurements are compared to results from homogenized radiosonde datasets. The results are found to be in excellent agreement with the radiosonde results in the northern extratropics, where the majority of the radiosonde stations are located.

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Feltz, M., R. Knuteson, S. Ackerman, and H. Revercomb. "Application of GPS radio occultation to the assessment of temperature profile retrievals from microwave and infrared sounders." Atmospheric Measurement Techniques 7, no. 11 (November 12, 2014): 3751–62. http://dx.doi.org/10.5194/amt-7-3751-2014.

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Abstract. Comparisons of satellite temperature profile products from GPS radio occultation (RO) and hyperspectral infrared (IR)/microwave (MW) sounders are made using a previously developed matchup technique. The profile matchup technique matches GPS RO and IR/MW sounder profiles temporally, within 1 h, and spatially, taking into account the unique RO profile geometry and theoretical spatial resolution by calculating a ray-path averaged sounder profile. The comparisons use the GPS RO dry temperature product. Sounder minus GPS RO differences are computed and used to calculate bias and rms profile statistics, which are created for global and 30° latitude zones for selected time periods. These statistics are created from various combinations of temperature profile data from the Constellation Observing System for Meteorology, Ionosphere & Climate (COSMIC) network, Global Navigation Satellite System Receiver for Atmospheric Sounding (GRAS) instrument, and the Atmospheric Infrared Sounder (AIRS)/Advanced Microwave Sounding Unit (AMSU), Infrared Atmospheric Sounding Interferometer (IASI)/AMSU, and Crosstrack Infrared Sounder (CrIS)/Advanced Technology Microwave Sounder (ATMS) sounding systems. By overlaying combinations of these matchup statistics for similar time and space domains, comparisons of different sounders' products, sounder product versions, and GPS RO products can be made. The COSMIC GPS RO network has the spatial coverage, time continuity, and stability to provide a common reference for comparison of the sounder profile products. The results of this study demonstrate that GPS RO has potential to act as a common temperature reference and can help facilitate inter-comparison of sounding retrieval methods and also highlight differences among sensor product versions.

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Feltz, M., R. Knuteson, S. Ackerman, and H. Revercomb. "Application of GPS radio occultation to the assessment of temperature profile retrievals from microwave and infrared sounders." Atmospheric Measurement Techniques Discussions 7, no. 5 (May 22, 2014): 5075–94. http://dx.doi.org/10.5194/amtd-7-5075-2014.

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Abstract. Comparisons of satellite temperature profile products from GPS radio occultation (RO) and hyperspectral infrared (IR)/microwave (MW) sounders are made using a previously developed matchup technique. The profile matchup technique matches GPS RO and IR/MW sounder profiles temporally, within 1 h, and spatially, taking into account the unique RO profile geometry and theoretical spatial resolution by calculating a ray-path averaged sounder profile. The comparisons use the GPS RO dry temperature product. Sounder minus GPS RO differences are computed and used to calculate bias and RMS profile statistics, which are created for global and 30° latitude zones for selected time periods. These statistics are created from various combinations of temperature profile data from the Constellation Observing System for Meteorology, Ionosphere & Climate (COSMIC) network, Global Navigation Satellite System Receiver for Atmospheric Sounding (GRAS) instrument, and the Atmospheric Infrared Sounder (AIRS)/Advanced Microwave Sounding Unit (AMSU), Infrared Atmospheric Sounding Interferometer (IASI)/AMSU, and Crosstrack Infrared Sounder (CrIS)/Advanced Technology Microwave Sounder (ATMS) sounding systems. By overlaying combinations of these matchup statistics for similar time and space domains, comparisons of different sounders' products, sounder product versions, and GPS RO products can be made. The COSMIC GPS RO network has the spatial coverage, time continuity, and stability to provide a common reference for comparison of the sounder profile products. The results of this study demonstrate that GPS RO has potential to act as a common temperature reference and can help facilitate inter-comparison of sounding retrieval methods and also highlight differences among sensor product versions.

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McLandress, C., T. G. Shepherd, A. I. Jonsson, T. von Clarmann, and B. Funke. "A method for merging nadir-sounding climate records, with an application to the global-mean stratospheric temperature data sets from SSU and AMSU." Atmospheric Chemistry and Physics Discussions 15, no. 7 (April 2, 2015): 10085–122. http://dx.doi.org/10.5194/acpd-15-10085-2015.

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Abstract. A method is proposed for merging different nadir-sounding climate data records using measurements from high resolution limb sounders to provide a transfer function between the different nadir measurements. The nadir-sounding records need not be overlapping so long as the limb-sounding record bridges between them. The method is applied to global mean stratospheric temperatures from the NOAA Climate Data Records based on the Stratospheric Sounding Unit (SSU) and the Advanced Microwave Sounding Unit-A (AMSU), extending the SSU record forward in time to yield a continuous data set from 1979 to present. SSU and AMSU are bridged using temperature measurements from the Michelson Interferometer for Passive Atmospheric Sounding (MIPAS), which is of high enough vertical resolution to accurately represent the weighting functions of both SSU and AMSU. For this application, a purely statistical approach is not viable since the different nadir channels are not sufficiently linearly independent, statistically speaking. The extended SSU global-mean data set is in good agreement with temperatures from the Microwave Limb Sounder (MLS) on the Aura satellite, with both exhibiting a cooling trend of ~ 0.6 ± 0.3 K decade−1 in the upper stratosphere from 2004–2012. The extended SSU data set also compares well with chemistry-climate model simulations over its entire record, including the contrast between the weak cooling seen over 1995–2004 compared with the large cooling seen in the period 1986–1995 of strong ozone depletion.

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Burgdorf, Martin, Imke Hans, Marc Prange, Theresa Lang, and Stefan A. Buehler. "Inter-channel uniformity of a microwave sounder in space." Atmospheric Measurement Techniques 11, no. 7 (July 11, 2018): 4005–14. http://dx.doi.org/10.5194/amt-11-4005-2018.

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Abstract. We analyzed intrusions of the Moon in the deep space view of the Advanced Microwave Sounding Unit-B on the NOAA-16 satellite and found no significant discrepancies in the signals from the different sounding channels between 2001 and 2008. However, earlier investigations had detected biases of up to 10 K, by using simultaneous nadir overpasses of NOAA-16 with other satellites. These discrepancies in the observations of Earth scenes cannot be due to non-linearity of the receiver or contamination of the deep space view without affecting the signal from the Moon as well. As neither major anomalies of the on-board calibration target nor the local oscillator were present, we consider radio frequency interference in combination with a strongly decreasing gain the most obvious reason for the degrading photometric stability. By means of the chosen example we demonstrate the usefulness of the Moon for investigations of the performance of microwave sounders in flight.

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McLandress, C., T. G. Shepherd, A. I. Jonsson, T. von Clarmann, and B. Funke. "A method for merging nadir-sounding climate records, with an application to the global-mean stratospheric temperature data sets from SSU and AMSU." Atmospheric Chemistry and Physics 15, no. 16 (August 20, 2015): 9271–84. http://dx.doi.org/10.5194/acp-15-9271-2015.

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Abstract. A method is proposed for merging different nadir-sounding climate data records using measurements from high-resolution limb sounders to provide a transfer function between the different nadir measurements. The two nadir-sounding records need not be overlapping so long as the limb-sounding record bridges between them. The method is applied to global-mean stratospheric temperatures from the NOAA Climate Data Records based on the Stratospheric Sounding Unit (SSU) and the Advanced Microwave Sounding Unit-A (AMSU), extending the SSU record forward in time to yield a continuous data set from 1979 to present, and providing a simple framework for extending the SSU record into the future using AMSU. SSU and AMSU are bridged using temperature measurements from the Michelson Interferometer for Passive Atmospheric Sounding (MIPAS), which is of high enough vertical resolution to accurately represent the weighting functions of both SSU and AMSU. For this application, a purely statistical approach is not viable since the different nadir channels are not sufficiently linearly independent, statistically speaking. The near-global-mean linear temperature trends for extended SSU for 1980–2012 are −0.63 ± 0.13, −0.71 ± 0.15 and −0.80 ± 0.17 K decade−1 (95 % confidence) for channels 1, 2 and 3, respectively. The extended SSU temperature changes are in good agreement with those from the Microwave Limb Sounder (MLS) on the Aura satellite, with both exhibiting a cooling trend of ~ 0.6 ± 0.3 K decade−1 in the upper stratosphere from 2004 to 2012. The extended SSU record is found to be in agreement with high-top coupled atmosphere–ocean models over the 1980–2012 period, including the continued cooling over the first decade of the 21st century.

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Mears, Carl A., and Frank J. Wentz. "Sensitivity of Satellite-Derived Tropospheric Temperature Trends to the Diurnal Cycle Adjustment." Journal of Climate 29, no. 10 (May 3, 2016): 3629–46. http://dx.doi.org/10.1175/jcli-d-15-0744.1.

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Abstract Temperature sounding microwave radiometers flown on polar-orbiting weather satellites provide a long-term, global-scale record of upper-atmosphere temperatures, beginning in late 1978 and continuing to the present. The focus of this paper is the midtropospheric measurements made by the Microwave Sounding Unit (MSU) channel 2 and the Advanced Microwave Sounding Unit (AMSU) channel 5. Previous versions of the Remote Sensing Systems (RSS) dataset have used a diurnal climatology derived from general circulation model output to remove the effects of drifting local measurement time. This paper presents evidence that this previous method is not sufficiently accurate and presents several alternative methods to optimize these adjustments using information from the satellite measurements themselves. These are used to construct a number of candidate climate data records using measurements from 15 MSU and AMSU satellites. The new methods result in improved agreement between measurements made by different satellites at the same time. A method is chosen based on an optimized second harmonic adjustment to produce a new version of the RSS dataset, version 4.0. The new dataset shows substantially increased global-scale warming relative to the previous version of the dataset, particularly after 1998. The new dataset shows more warming than most other midtropospheric data records constructed from the same set of satellites. It is also shown that the new dataset is consistent with long-term changes in total column water vapor over the tropical oceans, lending support to its long-term accuracy.

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Po-Chedley, Stephen, and Qiang Fu. "A Bias in the Midtropospheric Channel Warm Target Factor on the NOAA-9 Microwave Sounding Unit." Journal of Atmospheric and Oceanic Technology 29, no. 5 (May 1, 2012): 646–52. http://dx.doi.org/10.1175/jtech-d-11-00147.1.

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Abstract The University of Alabama at Huntsville (UAH), Remote Sensing Systems (RSS), and the National Oceanic and Atmospheric Administration (NOAA) have constructed long-term temperature records for deep atmospheric layers using satellite Microwave Sounding Unit (MSU) and Advanced Microwave Sounding Unit (AMSU) observations. However, these groups disagree on the magnitude of global temperature trends since 1979, including the trend for the midtropospheric layer (TMT). This study evaluates the selection of the MSU TMT warm target factor for the NOAA-9 satellite using five homogenized radiosonde products as references. The analysis reveals that the UAH TMT product has a positive bias of 0.051 ± 0.031 in the warm target factor that artificially reduces the global TMT trend by 0.042 K decade−1 for 1979–2009. Accounting for this bias increases the global UAH TMT trend from 0.038 to 0.080 K decade−1, effectively eliminating the trend difference between UAH and RSS and decreasing the trend difference between UAH and NOAA by 47%. This warm target factor bias directly affects the UAH lower tropospheric (TLT) product and tropospheric temperature trends derived from a combination of TMT and lower stratospheric (TLS) channels.

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Claud, C., B. Alhammoud, B. M. Funatsu, and J. P. Chaboureau. "Mediterranean hurricanes: large-scale environment and convective and precipitating areas from satellite microwave observations." Natural Hazards and Earth System Sciences 10, no. 10 (October 29, 2010): 2199–213. http://dx.doi.org/10.5194/nhess-10-2199-2010.

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Abstract. Subsynoptic scale vortices that have been likened to tropical cyclones or polar lows (medicanes) are occasionally observed over the Mediterranean Sea. Generated over the sea, they are usually associated with strong winds and heavy precipitation and thus can be highly destructive in islands and costal areas. Only an accurate forecasting of such systems could mitigate these effects. However, at the moment, the predictability of these systems remains limited. Due to the scarcity of conventional observations, use is made of NOAA/MetOp satellite observations, for which advantage can be taken of the time coverage differences between the platforms that carry it, to give a very complete temporal description of the disturbances. A combination of AMSU-B (Advanced Microwave Sounding Unit-B)/MHS (Microwave Humidity Sounder) observations permit to investigate precipitation associated with these systems while coincident AMSU-A (Advanced Microwave Sounding Unit-A) observations give insights into the larger synoptic-scale environment in which they occur. Three different cases (in terms of intensity, location, trajectory, duration, and periods of the year – May, September and December, respectively) were investigated. Throughout these time periods, AMSU-A observations show that the persisting deep outflow of cold air over the sea together with an upper-level trough upstream constituted a favourable environment for the development of medicanes. AMSU-B/MHS based diagnostics show that convection and precipitation areas are large in the early stage of the low, but significantly reduced afterwards. Convection is maximum just after the upper-level trough, located upstream of cold mid-tropospheric air, reached its maximum intensity and acquired a cyclonic orientation.

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Brueske, Kurt F., and Christopher S. Velden. "Satellite-Based Tropical Cyclone Intensity Estimation Using the NOAA-KLM Series Advanced Microwave Sounding Unit (AMSU)." Monthly Weather Review 131, no. 4 (April 2003): 687–97. http://dx.doi.org/10.1175/1520-0493(2003)131<0687:sbtcie>2.0.co;2.

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Mejia, Yajaira. "Robust neural network system design for detecting and estimating snowfall from the Advanced Microwave Sounding Unit." Journal of Applied Remote Sensing 2, no. 1 (June 1, 2008): 023524. http://dx.doi.org/10.1117/1.2953971.

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Chou, Chien-Ben, Ching-Yuang Huang, Huei-Ping Huang, Kung-Hwa Wang, and Tien-Chiang Yeh. "The Analysis of Typhoon Structures Using Advanced Microwave Sounding Unit Data and Its Application to Prediction." Journal of Applied Meteorology and Climatology 47, no. 5 (May 1, 2008): 1476–92. http://dx.doi.org/10.1175/2007jamc1577.1.

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Abstract In this study, the Advanced Microwave Sounding Unit (AMSU) data are used to retrieve the temperature and velocity fields of typhoons and assimilate them with the three-dimensional variational data assimilation (3DVAR) routines for uses in numerical model predictions for typhoons. The authors’ procedure of an end-to-end typhoon prediction using an AMSU-based initial condition is similar to the framework developed by Zhu et al. in 2002 but differs from it by considering a downward integration approach in part of the retrieval process and with the starting point of the integration chosen as a constant 50-hPa field without any structure. The typhoon circulation from this retrieval is thus determined objectively from the AMSU observation alone, without a preimposed typhoon vortex structure, allowing an asymmetric structure even at the inner core of a typhoon. The results show that this procedure is capable of retrieving a reasonable typhoon circulation from the AMSU data. The impact of the AMSU data on the assimilated initial condition for prediction is shown to be especially notable in its modification of the upper-level circulation of the typhoons. With the downward integration, the error accumulates downward such that the current approach provides a relatively more accurate estimate of the upper-level circulation, important for the steering of a typhoon. Consistent with this, it is demonstrated that the inclusion of the AMSU data helps to improve the forecast of typhoon tracks for selected cases of typhoons. This approach is less satisfying in producing an accurate retrieval and prediction of the intensity of typhoons. The reasons for this shortcoming and possible future remedies are discussed.

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Ferraro, Ralph, James Beauchamp, Daniel Cecil, and Gerald Heymsfield. "A prototype hail detection algorithm and hail climatology developed with the advanced microwave sounding unit (AMSU)." Atmospheric Research 163 (September 2015): 24–35. http://dx.doi.org/10.1016/j.atmosres.2014.08.010.

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Triana-Gómez, Arantxa M., Georg Heygster, Christian Melsheimer, Gunnar Spreen, Monia Negusini, and Boyan H. Petkov. "Improved water vapour retrieval from AMSU-B and MHS in the Arctic." Atmospheric Measurement Techniques 13, no. 7 (July 9, 2020): 3697–715. http://dx.doi.org/10.5194/amt-13-3697-2020.

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Abstract. Monitoring of water vapour in the Arctic on long timescales is essential for predicting Arctic weather and understanding climate trends, as well as addressing its influence on the positive feedback loop contributing to Arctic amplification. However, this is challenged by the sparseness of in situ measurements and the problems that standard remote sensing retrieval methods for water vapour have in Arctic conditions. Here, we present advances in a retrieval algorithm for vertically integrated water vapour (total water vapour, TWV) in polar regions from data of satellite-based microwave humidity sounders: (1) in addition to AMSU-B (Advanced Microwave Sounding Unit-B), we can now also use data from the successor instrument MHS (Microwave Humidity Sounder), and (2) artefacts caused by high cloud ice content in convective clouds are filtered out. Comparison to in situ measurements using GPS and radiosondes during 2008 and 2009, as well as to radiosondes during the N-ICE2015 campaign and to ERA5 reanalysis, show the overall good performance of the updated algorithm.

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John, V. O., and S. A. Buehler. "Comparison of microwave satellite humidity data and radiosonde profiles: A survey of European stations." Atmospheric Chemistry and Physics 5, no. 7 (July 25, 2005): 1843–53. http://dx.doi.org/10.5194/acp-5-1843-2005.

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Abstract. A method to compare upper tropospheric humidity (UTH) from satellite and radiosonde data has been applied to the European radiosonde stations. The method uses microwave data as a benchmark for monitoring the performance of the stations. The present study utilizes three years (2001-2003) of data from channel 18 (183.31±1.00 GHz) of the Advanced Microwave Sounding Unit-B (AMSU-B) aboard the satellites NOAA-15 and NOAA-16. The comparison is done in the radiance space, the radiosonde data were transformed to the channel radiances using a radiative transfer model. The comparison results confirm that there is a dry bias in the UTH measured by the radiosondes. This bias is highly variable among the stations and the years. This variability is attributed mainly to the differences in the radiosonde humidity measurements. The analysis also shows a difference between daytime and nighttime soundings which is attributed to radiation error in the radiosonde data. The dry bias due to this error alone correspond to approximately 11% relative error in the UTH measurements.

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Maddy, Eric S., Thomas S. King, Haibing Sun, Walter W. Wolf, Christopher D. Barnet, Andrew Heidinger, Zhaohui Cheng, et al. "Using MetOp-A AVHRR Clear-Sky Measurements to Cloud-Clear MetOp-A IASI Column Radiances." Journal of Atmospheric and Oceanic Technology 28, no. 9 (September 1, 2011): 1104–16. http://dx.doi.org/10.1175/jtech-d-10-05045.1.

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Abstract High spatial resolution measurements from the Advanced Very High Resolution Radiometer (AVHRR) on the Meteorological Operation (MetOp)-A satellite that are collocated to the footprints from the Infrared Atmospheric Sounding Interferometer (IASI) on the satellite are exploited to improve and quality control cloud-cleared radiances obtained from the IASI. For a partial set of mostly ocean MetOp-A orbits collected on 3 October 2010 for latitudes between 70°S and 75°N, these cloud-cleared radiances and clear-sky subpixel AVHRR measurements within the IASI footprint agree to better than 0.25-K root-mean-squared difference for AVHRR window channels with almost zero bias. For the same dataset, surface skin temperatures retrieved using the combined AVHRR, IASI, and Advanced Microwave Sounding Unit (AMSU) cloud-clearing algorithm match well with ECMWF model surface skin temperatures over ocean, yielding total uncertainties ≤1.2 K for scenes with up to 97% cloudiness.

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Buehler, Stefan A., Jana Mendrok, Patrick Eriksson, Agnès Perrin, Richard Larsson, and Oliver Lemke. "ARTS, the Atmospheric Radiative Transfer Simulator – version 2.2, the planetary toolbox edition." Geoscientific Model Development 11, no. 4 (April 18, 2018): 1537–56. http://dx.doi.org/10.5194/gmd-11-1537-2018.

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Abstract. This article describes the latest stable release (version 2.2) of the Atmospheric Radiative Transfer Simulator (ARTS), a public domain software for radiative transfer simulations in the thermal spectral range (microwave to infrared). The main feature of this release is a planetary toolbox that allows simulations for the planets Venus, Mars, and Jupiter, in addition to Earth. This required considerable model adaptations, most notably in the area of gaseous absorption calculations. Other new features are also described, notably radio link budgets (including the effect of Faraday rotation that changes the polarization state) and the treatment of Zeeman splitting for oxygen spectral lines. The latter is relevant, for example, for the various operational microwave satellite temperature sensors of the Advanced Microwave Sounding Unit (AMSU) family.

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Lu, Qifeng, and William Bell. "Characterizing Channel Center Frequencies in AMSU-A and MSU Microwave Sounding Instruments." Journal of Atmospheric and Oceanic Technology 31, no. 8 (August 1, 2014): 1713–32. http://dx.doi.org/10.1175/jtech-d-13-00136.1.

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Abstract Passive microwave observations from the Microwave Sounding Unit (MSU) and the Advanced Microwave Sounding Unit-A (AMSU-A) have been exploited widely for numerical weather prediction (NWP), atmospheric reanalyses, and climate monitoring studies. The treatment of biases in these observations, with respect to models as well as between satellites, has been the focus of much effort in recent years. This study presents evidence that shifts, drifts, and uncertainties in pass band center frequencies are a significant contribution to these biases. Center frequencies for AMSU-A channels 6–14 and MSU channel 3 have been analyzed using NWP fields and radiative transfer models, for a series of operational satellites covering the period 1979–2012. AMSU-A channels 6 (54.40 GHz), 7 (54.94 GHz), and 8 (55.50 GHz) on several satellites exhibit significant shifts and drifts relative to nominal pass band center frequencies. No significant shifts were found for AMSU-A channels 9–14, most probably as a consequence of the active frequency locking of these channels. For MSU channel 3 (54.96 GHz) most satellites exhibit large shifts, the largest for the earliest satellites. For example, for the first MSU on the Television and Infrared Observation Satellite-N (TIROS-N), the analyzed shift is 68 MHz over the lifetime of the satellite. Taking these shifts into account in the radiative transfer modeling significantly improves the fit between model and observations, eliminates the strong seasonal cycle in the model–observation misfit, and significantly improves the bias between NWP models and observations. The study suggests that, for several channels studied, the dominant component of the model–observation bias results from these spectral errors, rather than radiometric bias due to calibration errors.

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Su, Fengge, Huilin Gao, George J. Huffman, and Dennis P. Lettenmaier. "Potential Utility of the Real-Time TMPA-RT Precipitation Estimates in Streamflow Prediction." Journal of Hydrometeorology 12, no. 3 (June 1, 2011): 444–55. http://dx.doi.org/10.1175/2010jhm1353.1.

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Abstract The potential utility of the real-time Tropical Rainfall Measuring Mission (TRMM) Multisatellite Precipitation Analysis real-time product 3B42RT (TMPA-RT) data for streamflow prediction, both through direct comparisons of TMPA-RT estimates with a gridded gauge product and through evaluation of streamflow simulations over four tributaries of La Plata basin (LPB) in South America using the two precipitation products, is investigated. Assessments indicate that the relative accuracy and the hydrologic performance of TMPA-RT-based streamflow simulations generally improved after February 2005. The improvements in TMPA-RT since 2005 are closely related to upgrades in the TMPA-RT algorithm in early February 2005, which include use of additional microwave sensors [Advanced Microwave Scanning Radiometer for Earth Observing System (AMSR-E) and Advanced Microwave Sounding Unit-B (AMSU-B)] and implementation of different calibration schemes. This study suggests considerable potential for hydrologic prediction using purely satellite-derived precipitation estimates (no adjustments by in situ gauges) in parts of the globe where in situ observations are sparse.

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Mears, Carl A., and Frank J. Wentz. "A Satellite-Derived Lower-Tropospheric Atmospheric Temperature Dataset Using an Optimized Adjustment for Diurnal Effects." Journal of Climate 30, no. 19 (August 30, 2017): 7695–718. http://dx.doi.org/10.1175/jcli-d-16-0768.1.

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Abstract Temperature sounding microwave radiometers flown on polar-orbiting weather satellites provide a long-term, global-scale record of upper-atmosphere temperatures, beginning in late 1978 and continuing to the present. The focus of this paper is a lower-tropospheric temperature product constructed using measurements made by the Microwave Sounding Unit channel 2 and the Advanced Microwave Sounding Unit channel 5. The temperature weighting functions for these channels peak in the middle to upper troposphere. By using a weighted average of measurements made at different Earth incidence angles, the effective weighting function can be lowered so that it peaks in the lower troposphere. Previous versions of this dataset used general circulation model output to remove the effects of drifting local measurement time on the measured temperatures. This paper presents a method to optimize these adjustments using information from the satellite measurements themselves. The new method finds a global-mean land diurnal cycle that peaks later in the afternoon, leading to improved agreement between measurements made by co-orbiting satellites. The changes result in global-scale warming [global trend (70°S–80°N, 1979–2016) = 0.174°C decade−1], ~30% larger than our previous version of the dataset [global trend (70°S–80°N, 1979–2016) = 0.134°C decade−1]. This change is primarily due to the changes in the adjustment for drifting local measurement time. The new dataset shows more warming than most similar datasets constructed from satellites or radiosonde data. However, comparisons with total column water vapor over the oceans suggest that the new dataset may not show enough warming in the tropics.

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Zabolotskikh, E. V., and B. Chapron. "MODELING X-BAND MICROWAVE RADIATION OF THE ARCTIC SEAS BASED ON SATELLITE OBSERVATIONS: TAKING INTO ACCOUNT A MEASUREMENT ANGLE." Meteorologiya i Gidrologiya, no. 4 (2021): 69–77. http://dx.doi.org/10.52002/0130-2906-2021-4-69-77.

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The ocean X-band microwave emission model for modeling measurements of satellite radiometers over the cold Arctic seas at an observation angle of 65° is proposed. The model is based on the experimental geophysical model function (GMF) of microwave emission dependence on surface wind speed for an angle of 55°, that was developed from the AMSR2 (Advanced Microwave Scanning Radiometer 2) measurements and the two-scale theory of the ocean microwave radiation. The experimental GMF is derived from the comparison of AMSR2 measurements over the Arctic seas with surface wind speeds retrieved from these data. The model is limited by wind speed of 15 m/s and does not take into account the foam emission. The model allows discriminating between longwave and shortwave wind-induced microwave radiation and using the presented approach to proceed to the observation angle of the MTVZA-GYa (temperature and humidity atmospheric sounding unit) microwave radiometer on board the Meteor-M Russian polar orbiting satellites.

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Peubey, Carole, and William Bell. "The Influence of Frequency Shifts in Microwave Sounder Channels on NWP Analyses and Forecasts." Journal of Atmospheric and Oceanic Technology 31, no. 4 (April 1, 2014): 788–807. http://dx.doi.org/10.1175/jtech-d-13-00016.1.

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Abstract The sensitivity of numerical weather prediction (NWP) analysis and forecast accuracies with respect to frequency shifts in microwave passbands is quantified through a series of observing system experiments using the ECMWF Integrated Forecast System. First, a parameterization is developed to describe the form and magnitude of the brightness temperature errors arising from frequency shifts in Advanced Microwave Sounding Unit-A (AMSU-A) channels 4–10 and Microwave Humidity Sounder (MHS) channels 3–5. Observing system experiments are then run in which realistic synthetic brightness temperature errors are added to AMSU-A observations for various assumptions about the magnitude of a frequency shift, using the parameterization derived previously. A large negative impact on forecast quality is found when a 20-MHz frequency shift is introduced in experiments using a static bias-correction scheme. Although the degradation in forecast scores is reduced by using a variational bias-correction scheme, it remains around 7%–14% (relative) in RMS 6-h forecast errors for temperature and geopotential. Frequency shifts of 5 MHz or greater give rise to a measurable degradation of the forecast even when the variational correction scheme is used. Only low-frequency shifts (of ~1.5 MHz) are found to have a neutral impact on forecasts. Hence, the value of 1.5 MHz can be regarded as an upper limit below which frequency shifts do not degrade forecasts for the key tropospheric and lower-stratospheric temperature sounding channels in a microwave sounding mission. Calculations show that frequency shift is less problematic for 183-GHz humidity sounding channels due to the symmetric positioning of passbands relative to the 183-GHz absorption line. For these channels a passband center frequency stability of 10 MHz is adequate.

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Kleespies, Thomas J., and Philip Watts. "Comparison of simulated radiances, Jacobians and linear error analysis for the Microwave Humidity Sounder and the Advanced Microwave Sounding Unit-B." Quarterly Journal of the Royal Meteorological Society 132, no. 621C (October 2006): 3001–10. http://dx.doi.org/10.1256/qj.05.03.

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Iacovazzi, Robert A., and Changyong Cao. "Reducing Uncertainties of SNO-Estimated Intersatellite AMSU-A Brightness Temperature Biases for Surface-Sensitive Channels." Journal of Atmospheric and Oceanic Technology 25, no. 6 (June 1, 2008): 1048–54. http://dx.doi.org/10.1175/2007jtecha1020.1.

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Abstract In this study, a technique has been developed to improve collocation of two passive-microwave satellite instrument datasets at a simultaneous nadir overpass (SNO). The technique has been designed for the purpose of reducing uncertainties related to SNO-inferred intersatellite brightness temperature (Tb) biases, and it involves replacing the current “nearest-neighbor pixel matching” collocation technique with quality-controlled bilinear interpolation. Since the largest Tb bias estimation uncertainties of the SNO method are associated with highly variable earth scenes and window channels of microwave radiometers that have relatively large (∼50 km) separation between measurements, the authors have used Advanced Microwave Sounding Unit A (AMSU-A) data to develop the technique. It is found that using the new data collocation technique reduces SNO ensemble mean Tb bias confidence intervals in the SNO method, as applied to surface-sensitive channels of AMSU-A, by nearly 70% on average. This improvement in the SNO method enhances its ability to quantify intersatellite Tb biases at microwave radiometer channels that are sensitive to surface radiation, which is necessary to advance the sciences of numerical weather prediction and climate change detection.

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Journal articles on the topic 'Advanced Microwave Sounding Unit'

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