scholarly journals Connecting the Time Series of Microwave Sounding Observations from AMSU to ATMS for Long-Term Monitoring of Climate

2014 ◽  
Vol 31 (10) ◽  
pp. 2206-2222 ◽  
Author(s):  
Xiaolei Zou ◽  
Fuzhong Weng ◽  
H. Yang
Keyword(s):  
Time Series ◽  
Atmospheric Temperature ◽  
Advanced Technology ◽  
Central Frequency ◽  
Brightness Temperatures ◽  
Microwave Sounding Unit ◽  
Microwave Sounding ◽  
Cross Calibration ◽  
Term Monitoring

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.

scholarly journals Inter-Calibration of AMSU-A Window Channels

2020 ◽  
Vol 12 (18) ◽  
pp. 2988
Author(s):  
Wenze Yang ◽  
Huan Meng ◽  
Ralph R. Ferraro ◽  
Yong Chen
Keyword(s):  
Atmospheric Temperature ◽  
Global Information ◽  
Temperature Profiles ◽  
Climate Data ◽  
Error Sources ◽  
Bias Drift ◽  
Brightness Temperatures ◽  
Microwave Sounding Unit ◽  
Vapor Cloud ◽  
Microwave Sounding

More than one decade of observations from the Advanced Microwave Sounding Unit-A (AMSU-A) onboard the polar-orbiting satellites NOAA-15 to NOAA-19 and European Meteorological Operational satellite program-A (MetOp-A) provided global information on atmospheric temperature profiles, water vapor, cloud, precipitation, etc. These observations were primarily intended for weather related prediction and applications, however, in order to meet the requirements for climate application, further reprocessing must be conducted to first eliminate any potential satellites biases. After the geolocation and cross-scan bias corrections were applied to the dataset, follow-on research focused on the comparison amongst AMSU-A window channels (e.g., 23.8, 31.4, 50.3 and 89.0 GHz) from the six different satellites to remove any inter-satellite inconsistency. Inter-satellite differences can arise from many error sources, such as bias drift, sun-heating-induced instrument variability in brightness temperatures, radiance dependent biases due to inaccurate calibration nonlinearity, etc. The Integrated microwave inter-calibration approach (IMICA) approach was adopted in this study for inter-satellite calibration of AMSU-A window channels after the appropriate standard deviation (STD) thresholds were identified to restrict Simultaneous Nadir Overpass (SNO) data for window channels. This was a critical step towards the development of a set of fundamental and thematic climate data records (CDRs) for hydrological and climatological applications. NOAA-15 served as the main reference satellite for this study. For ensuing studies that expand to beyond 2015, however, it is recommended that a different satellite be adopted as the reference due to concerns over potential degradation of NOAA-15 AMSU-A.

scholarly journals A Study of the NOAA Near-Nadir AMSU-A Brightness Temperatures over Antarctica

2010 ◽  
Vol 27 (6) ◽  
pp. 995-1004 ◽  
Author(s):  
Tsan Mo
Keyword(s):  
Time Series ◽  
Test Site ◽  
Good Test ◽  
Brightness Temperatures ◽  
Microwave Sounding Unit ◽  
Microwave Sounding ◽  
Diurnal Effect ◽  
Natural Test ◽  
Microwave Radiometers ◽  
The Antarctic

Abstract Daily mean brightness temperatures over Antarctica derived from measurements by three Advanced Microwave Sounding Unit-A (AMSU-A) radiometers on board NOAA-18, NOAA-19, and MetOp-A satellites are studied. To demonstrate the characteristics of the data over this test site, time series of daily averages of the brightness temperatures are constructed. These time series provide a useful pattern of annual variation of the AMSU-A measurements for intercalibration of microwave radiometers on board multiple satellites. To investigate the diurnal effect on the measurements, the time series of daily averaged brightness temperatures are constructed separately for the ascending and descending passes. Results show that there are little diurnal differences in measurements during the Antarctic winter months from each satellite. Therefore these measurements provide a practical approach to obtain relative channel biases of intersatellite data. The monthly averages of the measurements over July 2009 are employed to obtain the relative channel biases because it is the coldest month in Antarctica. The resultant channel biases for the three satellites are within the range of ±0.1 K for channels 1–5 and ±0.3 K for channels 6–15. This is strong evidence that Antarctica is a potentially good test site for intercalibration of microwave radiometers on board multiple satellites. The small relative biases at channels 1–5 indicate that Antarctica is a very stable test site that is particularly useful for intercalibration of measurements from the window channels. The establishment of a natural test site for calibration references is important for calibration and validation of spaceborne microwave instruments.

scholarly journals Long-term monitoring programme of the hydrological variability in the Mediterranean Sea: a first overview of the HYDROCHANGES network

Ocean Science ◽  
2013 ◽  
Vol 9 (2) ◽  
pp. 301-324 ◽  
Author(s):  
K. Schroeder ◽  
C. Millot ◽  
L. Bengara ◽  
S. Ben Ismail ◽  
M. Bensi ◽  
...  
Keyword(s):  
Time Series ◽  
Mediterranean Sea ◽  
Sampling Interval ◽  
Global Changes ◽  
Hydrological Variability ◽  
Long Term Monitoring ◽  
The Mediterranean ◽  
Set Up ◽  
Term Monitoring

Abstract. The long-term monitoring of basic hydrological parameters (temperature and salinity), collected as time series with adequate temporal resolution (i.e. with a sampling interval allowing the resolution of all important timescales) in key places of the Mediterranean Sea (straits and channels, zones of dense water formation, deep parts of the basins), constitute a priority in the context of global changes. This led CIESM (The Mediterranean Science Commission) to support, since 2002, the HYDROCHANGES programme (http//www.ciesm.org/marine/programs/hydrochanges.htm), a network of autonomous conductivity, temperature, and depth (CTD) sensors, deployed on mainly short and easily manageable subsurface moorings, within the core of a certain water mass. The HYDROCHANGES strategy is twofold and develops on different scales. To get information about long-term changes of hydrological characteristics, long time series are needed. But before these series are long enough they allow the detection of links between them at shorter timescales that may provide extremely valuable information about the functioning of the Mediterranean Sea. The aim of this paper is to present the history of the programme and the current set-up of the network (monitored sites, involved groups) as well as to provide for the first time an overview of all the time series collected under the HYDROCHANGES umbrella, discussing the results obtained thanks to the programme.

scholarly journals Construction of the RSS V3.2 Lower-Tropospheric Temperature Dataset from the MSU and AMSU Microwave Sounders

2009 ◽  
Vol 26 (8) ◽  
pp. 1493-1509 ◽  
Author(s):  
Carl A. Mears ◽  
Frank J. Wentz
Keyword(s):  
Lower Stratosphere ◽  
Weighting Function ◽  
Lower Troposphere ◽  
Weighted Average ◽  
Atmospheric Temperature ◽  
Tropospheric Temperature ◽  
Satellite Measurements ◽  
Microwave Sounding Unit ◽  
Different Types ◽  
Microwave Sounding

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.

scholarly journals OLCI A/B Tandem Phase Analysis, Part 3: Post-Tandem Monitoring of Cross-Calibration from Statistics of Deep Convective Clouds Observations

2020 ◽  
Vol 12 (18) ◽  
pp. 3105
Author(s):  
Nicolas Lamquin ◽  
Ludovic Bourg ◽  
Sébastien Clerc ◽  
Craig Donlon
Keyword(s):  
Phase Analysis ◽  
Absolute Calibration ◽  
Inflexion Point ◽  
Convective Clouds ◽  
Deep Convective Clouds ◽  
Long Term Monitoring ◽  
The Cross ◽  
Cross Calibration ◽  
Term Monitoring

This study is a follow-up of a full methodology for the homogenisation and harmonisation of the two Ocean and Land Colour Instrument (OLCI) payloads based on the OLCI-A/OLCI-B tandem phase analysis. This analysis provided cross-calibration factors between the two instruments with a very high precision, providing a ‘truth’ from the direct comparison of simultaneous and collocated acquisitions. The long-term monitoring of such cross-calibration is a prerequisite for an operational application of sensors harmonisation along the mission lifetime, no other tandem phase between OLCI-A and OLCI-B being foreseen due to the cost of such operation. This article presents a novel approach for the monitoring of the OLCI radiometry based on statistics of Deep Convective Clouds (DCC) observations, especially dedicated to accurately monitor the full across-track dependency of the cross-calibration of OLCI-A and OLCI-B. Specifically, the inflexion point of DCC reflectance distributions is used as an indicator of the absolute calibration for each subdivision of the OLCI Field-of-View. This inflexion point is shown to provide better precision than the mode of the distributions which is commonly used in the community. Excess of saturation in OLCI-A high radiances is handled through the analysis of interband relationships between impacted channels and reference channels that are not impacted by saturation. Such analysis also provides efficient insights on the variability of the target’s response as well as on the evolution of the interband calibration of each payload. First, cross-calibration factors obtained over the tandem period allows to develop and validate the approach, notably for the handling of the saturated pixels, based on the comparison with the ‘truth’ obtained from the tandem analysis. Factors obtained out of (and far from) the tandem period then provides evidence that the cross-calibration reported over the tandem period (1–2% bias between the instruments) as well as inter-camera calibration residuals persist with very similar proportions, to the exception of the 400 nm channel and with slightly less precision for the 1020 nm channel. For all OLCI channels, relative differences between the cross-calibration factors obtained from the tandem analysis and the factors obtained over the other period are below 1% from a monthly analysis, even below 0.5% from a multi-monthly analysis). This opens the way not only to an accurate long-term monitoring of the OLCI radiometry but also, and precisely targeted for this study, to the monitoring of the cross-calibration of the two sensors over the mission lifetime. It also provides complementary information to the tandem analysis as the calibration indicators are traced individually for each sensor across-track, confirming and quantifying inter-camera radiometric biases, independently for both sensors. Assumptions used in this study are discussed and validated, also providing a framework for the adaptation of the presented methodology to other optical sensors.

Characterizing the FY-3A Microwave Temperature Sounder Using the ECMWF Model

2011 ◽  
Vol 28 (11) ◽  
pp. 1373-1389 ◽  
Author(s):  
Qifeng Lu ◽  
William Bell ◽  
Peter Bauer ◽  
Niels Bormann ◽  
Carole Peubey
Keyword(s):  
Weather Prediction ◽  
Quadratic Function ◽  
Climate Science ◽  
Brightness Temperatures ◽  
Microwave Sounding Unit ◽  
Satellite Sensors ◽  
Microwave Sounding ◽  
Data Source ◽  
Nwp Model ◽  
Ecmwf Model

Abstract China’s Feng-Yun-3A (FY-3A), launched in May 2008, is the first in a series of seven polar-orbiting meteorological satellites planned for the next decade by China. The FY-3 series is set to become an important data source for numerical weather prediction (NWP), reanalysis, and climate science. FY-3A is equipped with a microwave temperature sounding instrument (MWTS). This study reports an assessment of the MWTS instrument using the ECMWF NWP model, radiative transfer modeling, and comparisons with equivalent observations from the Advanced Microwave Sounding Unit-A (AMSU-A). The study suggests the MWTS instrument is affected by biases related to large shifts, or errors, in the frequency of the channel passbands as well as radiometer nonlinearity. The passband shifts, relative to prelaunch measurements, are 55, 39, and 33 MHz for channels 2–4, respectively. Relative to the design specification the shifts are 60, 80, and 83 MHz, with uncertainties of ±2.5 MHz. The radiometer nonlinearity results in a positive bias in measured brightness temperatures and is manifested as a quadratic function of measured scene temperatures. By correcting for both of these effects the quality of the MWTS data is improved significantly, with the standard deviations of the (observed minus simulated) differences based on short-range forecast fields reduced by 30%–50% relative to simulations using prelaunch measurements of the passband, to values close to those observed for AMSU-A-equivalent channels. The new methodology could be applied to other microwave temperature sounding instruments and illustrates the value of NWP fields for the on-orbit characterization of satellite sensors.

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