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Downloaded 10/04/21 02:53 AM UTC OCTOBER 2014 Z O U E T a L 2206 JOURNAL OF ATMOSPHERIC AND OCEANIC TECHNOLOGY VOLUME 31 Connecting the Time Series of Microwave Sounding Observations from AMSU to ATMS for Long-Term Monitoring of Climate XIAOLEI ZOU Department of Earth, Ocean and Atmospheric Science, Florida State University, Tallahassee, Florida FUZHONG WENG NOAA/NESDIS/Center for Satellite Applications and Research, College Park, Maryland H. YANG Earth System Science Interdisciplinary Center, University of Maryland, College Park, College Park, Maryland (Manuscript received 18 October 2013, in final form 8 May 2014) 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 over- lapping 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. 1. Introduction were launched successively through 2009. AMSU-A contains 15 channels. Channels 3, 5, 7, and 9 have simi- Since the first launch of Television and Infrared lar frequencies to the four MSU channels. Today, the Observation Satellite (TIROS-N) in 1978, microwave Advanced Technology Microwave Sounder (ATMS) temperature sounding data have been used for both is flying on board the Suomi National Polar-orbiting weather and climate applications. From 1978 to 2004, Partnership (Suomi-NPP) satellite and will be also on the National Oceanic and Atmospheric Administration board future U.S. Joint Polar Satellite System (JPSS) (NOAA) launched eight satellites (NOAA-6–NOAA-12 satellites, which are scheduled for launch in both 2017 and NOAA-14) carrying Microwave Sounding Unit and 2022. ATMS contains 22 channels. Channels 1–3 (MSU) instruments. MSU had four channels for sounding and 5–16 have the same central frequencies as the 15 atmospheric temperatures. Beginning in 1998, the MSU AMSU-A channels. instruments were replaced by the Advanced Microwave Polar-orbiting satellites circle the earth in sun- Sounding Unit-A (AMSU-A) when NOAA-15–NOAA-19 synchronous orbits with different equator crossing times (ECTs). NOAA-6, -8, -10, -12,and-15 are the morning satellites with their ECT occurring at either 0530 or Corresponding author address: Dr. X. Zou, Department of Earth, Ocean and Atmospheric Science, Florida State University, 0730 local time (LT). The satellites with ECT after 0930 LT Mail Code 4520, P.O. Box 3064520, Tallahassee, FL 32306-4520. are referring to midmorning satellites, such as NOAA-17, E-mail: [email protected] Meteorological Operation-A (MetOp-A) and MetOp-B, DOI: 10.1175/JTECH-D-13-00232.1 Ó 2014 American Meteorological Society Unauthenticated | Downloaded 10/04/21 02:53 AM UTC OCTOBER 2014 Z O U E T A L . 2207 whereas those after 1300 LT are afternoon satellites, condition. As such, MSU, AMSU-A, and ATMS will such as TIROS-N, NOAA-7, -9, -11, -14, -16, -18, -19, provide a continuous time series for more than 35 years, and Suomi NPP. On all of these platforms, MSU, containing a wealth of information on global atmospheric AMSU-A and ATMS provide the measurements of the temperature. Although the MSU, AMSU-A, and ATMS global atmospheric temperature from the surface to the instruments are primarily designed for providing atmo- low stratosphere (MSU) and to the upper stratosphere spheric temperatures on a daily basis for predicting at- at about 1 hPa (AMSU-A and ATMS) and can also be mospheric weather systems, they are also applicable of used for climate trend studies. monitoring decadal climate changes of the atmospheric Soon after the launch of Suomi NPP, an intensive temperature because of the same channel frequencies calibration of the ATMS was carried out. The ATMS from different sensors, the sensor stability, and high cal- sensor data records have now reached a validated ma- ibration accuracy. turity level. For the JPSS program, both sensor data To derive atmospheric temperature trends from the record (SDR) and environmental data record (EDR) above-mentioned long-term MSU and AMSU-A data products are evaluated at three maturity levels. The beta series, satellite-to-satellite cross calibration must be car- maturity level is made when the initial calibration is ried out (Grody et al. 2004; Christy et al. 2000; Zou et al. applied and the product is minimally validated, and may 2006). Using a well-calibrated MSU–AMSU-A data se- still contain significant errors (Weng and Zou 2013). At ries, global warming ranging from 0.08 to 0.22 K per de- this level, the product is not appropriate for quantitative cade is detected in the lower troposphere represented by scientific publication, studies, or applications. The pro- MSU channel 2 (53.74 GHz) (Christy et al. 1998, 2000, visional maturity level is achieved when the instruments 2003; Mears et al. 2003; Mears and Wentz 2009; Vinnikov are calibrated and the products are validated but in- and Grody 2003;andZou et al. 2009). In this study, the cremental improvements are ongoing. The user com- ATMS data are first resampled into AMSU-like data and munity is encouraged to participate in the quality an intersensor calibration is then carried out for merging assurance and product validation processes. The vali- ATMS data into the AMSU-A data family. dated maturity level is reached when the on-orbit sensor The Backus–Gilbert (B-G) inversion method (Kirsch performance is characterized and calibration parameters et al. 1988; Caccin et al. 1992) is employed for the ATMS are adjusted accordingly. The data are ready for use by resampling purpose, which will be referred to as ATMS the operational center and scientific publications. Over- resample data. The B-G method solves an inverse prob- all, ATMS in-orbit performance is well characterized and lem that involves the integral equations. It can be viewed its noise equivalent differential temperature (NEDT) as an optimal linear interpolation filter in which the spatial meets the specification (Weng et al. 2013). The other resolution of the AMSU-A radiometer (i.e., the 3.38 ATMS features, such as channel specifications, bias beamwidth) and the antenna gain function of the ATMS characteristics, and impact of observation resolution on radiometer are preserved, the sensor noise can be con- capturing tropical storm structures, were described in trolled, and the data-processing artifacts are minimized. Weng et al. (2012, 2013). The scan biases related to Stogryn (1978) used the B-G method for estimating ATMS sidelobes and possible antenna emission were brightness temperatures from antenna temperatures mea- quantified by Weng et al. (2013) using the ATMS pitch- sured by a conical-scanning satellite-borne radiometer over maneuver data. A postlaunch calibration of ATMS system. Since the work by Stogryn (1978), the B-G algo- middle- and upper- tropospheric and stratospheric rithm was successfully applied to the Special Sensor Mi- channels (i.e., channels 5–15) was carried out by Zou et al. crowave Imager (SSM/I) satellite data (Poe 1990) to realize (2014) using the global positioning system (GPS) radio a spatial resolution enhancement of brightness tempera- occultation (RO) data. Preliminary assessments of the ture measurements from SSM/I (Poe 1990; Robinson et al. impact of ATMS data assimilation on hurricane track and 1992; Farrar and Smith 1992; Sethmann et al. 1994; Long intensity forecasts were reported in Zou et al. (2013). and Daum 1998). The lifetime of a given MSU or AMSU-A is limited While they all fly in sun-synchronous orbits, Suomi from a few years to more than 10 years. Fortunately, each NPP, NOAA-18, MetOp-A, and NOAA-15 satellites of these satellites overlaps other satellites. For example, have different ECTs. To collocate the data from any two during the period of 1998–2006, the last MSU on board different satellites during their overlapping period, Cao NOAA-14 operated as a backup, while the AMSU-A on et al. (2004) proposed a simultaneous nadir overpass the NOAA-15, -16,and-17 satellites became primary (SNO) method for intersatellite cross calibration. Yan ones. The Suomi NPP ATMS has been operational since and Weng (2008) used the SNO method for intersensor 2011, while AMSU-A on NOAA-15, -18,and-19 and calibration between the Special Sensor Microwave MetOp-A and MetOp-B are still operating in a healthy Imager/Sounder (SSM/IS) and SSM/I. In this study, the Unauthenticated | Downloaded 10/04/21 02:53 AM UTC 2208 JOURNAL OF ATMOSPHERIC AND OCEANIC TECHNOLOGY VOLUME 31 FIG. 1. ATMS FOVs (circles) used for remapping into an AMSU-like FOV (light gray) for ATMS channels (a) 3–16 and (b) 1 and 2 FOVs. Magnitudes of B-G coefficients are indicated with colors. Integration time and satellite movement were taken into consideration. SNO method is used for the intersensor calibration NOAA-18, MetOp-A,andNOAA-15.
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