scholarly journals Combining FY-3D MWTS-2 with AMSU-A Data for Inter-Decadal Diurnal Correction and Climate Trends of Atmospheric Temperature

2021 ◽  
Vol 13 (16) ◽  
pp. 3148
Author(s):  
Xinlu Xia ◽  
Xiaolei Zou
Keyword(s):  
Warming Trend ◽  
Atmospheric Temperature ◽  
Double Difference ◽  
Target Area ◽  
Climate Trends ◽  
Microwave Sounding Unit ◽  
Microwave Sounding ◽  
Cooling Trend ◽  
The Impact ◽  
Diurnal Correction

Microwave temperature sounding observations from polar-orbiting meteorological satellites have been widely used for research on climate trends of atmospheric temperature at different heights around the world. Taking the Amazon rainforest as the target area, this study combined the Microwave Temperature Sounder-2 (MWTS-2) data onboard the Chinese FengYun-3D (FY-3D) satellite with the Advanced Microwave Sounding unit-A (AMSU-A) data onboard the National Oceanic and Atmospheric Administration (NOAA) and the European Meteorological Operational (MetOp) polar-orbiting meteorological satellites (i.e., NOAA-15, −18, −19, MetOp-A, -B). The double difference method was used to estimate and thus eliminate the inter-sensor bias, and a decadal diurnal correction was used to reduce the impact of different local equator crossing times on climate trends. The “no-rain” conditions were determined for AMSU-A data by channels 1 and 15, and for MWTS-2 data by channels 1 and 7. Finally, the decadal linear trends of atmospheric temperature from 1998 to 2020 were obtained after applying the inter-sensor bias calibration and inter-decadal diurnal correction to AMSU-A and MWTS-2 data from NOAA-15, −18, −19; MetOp-A, -B; and FY-3D. A warming trend was found in the AMSU-A window and tropospheric channels (1–9 and 15) and a cooling trend in stratospheric channels (10–14). The warming (cooling) trends of channels 7–9 (10) were relatively small. The warming (cooling) trends of AMSU-A channels 1–6 (14–15) were significantly reduced after the inter-decadal diurnal correction.

Error Structure and Atmospheric Temperature Trends in Observations from the Microwave Sounding Unit

2009 ◽  
Vol 22 (7) ◽  
pp. 1661-1681 ◽  
Author(s):  
Cheng-Zhi Zou ◽  
Mei Gao ◽  
Mitchell D. Goldberg
Keyword(s):  
Lower Stratosphere ◽  
Weather Conditions ◽  
Atmospheric Temperature ◽  
The Arctic ◽  
Polar Regions ◽  
Climate Trends ◽  
Orbital Geometry ◽  
Microwave Sounding Unit ◽  
Order Of Magnitude ◽  
Microwave Sounding

Abstract The Microwave Sounding Unit (MSU) onboard the National Oceanic and Atmospheric Administration polar-orbiting satellites measures the atmospheric temperature from the surface to the lower stratosphere under all weather conditions, excluding precipitation. Although designed primarily for monitoring weather processes, the MSU observations have been extensively used for detecting climate trends, and calibration errors are a major source of uncertainty. To reduce this uncertainty, an intercalibration method based on the simultaneous nadir overpass (SNO) matchups for the MSU instruments on satellites NOAA-10, -11, -12, and -14 was developed. Due to orbital geometry, the SNO matchups are confined to the polar regions, where the brightness temperature range is slightly smaller than the global range. Nevertheless, the resulting calibration coefficients are applied globally to the entire life cycle of an MSU satellite. Such intercalibration reduces intersatellite biases by an order of magnitude compared to prelaunch calibration and, thus, results in well-merged time series for the MSU channels 2, 3, and 4, which respectively represent the deep layer temperature of the midtroposphere (T2), tropopause (T3), and lower stratosphere (T4). Focusing on the global atmosphere over ocean surfaces, trends for the SNO-calibrated T2, T3, and T4 are, respectively, 0.21 ± 0.07, 0.08 ± 0.08, and −0.38 ± 0.27 K decade−1 from 1987 to 2006. These trends are independent of the number of limb-corrected footprints used in the dataset, and trend differences are marginal for varying bias correction techniques for merging the overlapping satellites on top of the SNO calibration. The spatial pattern of the trends reveals the tropical midtroposphere to have warmed at a rate of 0.28 ± 0.19 K decade−1, while the Arctic atmosphere warmed 2 to 3 times faster than the global average. The troposphere and lower stratosphere, however, cooled across the southern Indian and Atlantic Oceans adjacent to the Antarctic continent. To remove the stratospheric cooling effect in T2, channel trends from T2 and T3 (T23) and T2 and T4 (T24) were combined. The trend patterns for T23 and T24 are in close agreement, suggesting internal consistencies for the trend patterns of the three channels.

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 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.

Removing Diurnal Cycle Contamination in Satellite-Derived Tropospheric Temperatures: Understanding Tropical Tropospheric Trend Discrepancies

2015 ◽  
Vol 28 (6) ◽  
pp. 2274-2290 ◽  
Author(s):  
Stephen Po-Chedley ◽  
Tyler J. Thorsen ◽  
Qiang Fu
Keyword(s):  
Diurnal Cycle ◽  
General Circulation ◽  
Circulation Model ◽  
Tropospheric Temperature ◽  
University Of Alabama ◽  
Temperature Trends ◽  
Microwave Sounding Unit ◽  
Microwave Sounding ◽  
The University ◽  
Diurnal Correction

Abstract Independent research teams have constructed long-term tropical time series of the temperature of the middle troposphere (TMT) using satellite Microwave Sounding Unit (MSU) and Advanced MSU (AMSU) measurements. Despite careful efforts to homogenize the MSU/AMSU measurements, tropical TMT trends beginning in 1979 disagree by more than a factor of 3. Previous studies suggest that the discrepancy in tropical TMT trends is caused by differences in both the NOAA-9 warm target factor and diurnal drift corrections. This work introduces a new observationally based method for removing biases related to satellite diurnal drift. Over land, the derived diurnal correction is similar to a general circulation model (GCM) diurnal cycle. Over ocean, the diurnal corrections have a negligible effect on TMT trends, indicating that oceanic biases are small. It is demonstrated that this method is effective at removing biases between coorbiting satellites and biases between nodes of individual satellites. Using a homogenized TMT dataset, the ratio of tropical tropospheric temperature trends relative to surface temperature trends is in accord with the ratio from GCMs. It is shown that bias corrections for diurnal drift based on a GCM produce tropical trends very similar to those from the observationally based correction, with a trend difference smaller than 0.02 K decade−1. Differences between various TMT datasets are explored further. Large differences in tropical TMT trends between this work and that of the University of Alabama in Huntsville (UAH) are attributed to differences in the treatment of the NOAA-9 target factor and the diurnal cycle correction.

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 The Analysis of Typhoon Structures Using Advanced Microwave Sounding Unit Data and Its Application to Prediction

2008 ◽  
Vol 47 (5) ◽  
pp. 1476-1492 ◽  
Author(s):  
Chien-Ben Chou ◽  
Ching-Yuang Huang ◽  
Huei-Ping Huang ◽  
Kung-Hwa Wang ◽  
Tien-Chiang Yeh
Keyword(s):  
Inner Core ◽  
Current Approach ◽  
Asymmetric Structure ◽  
Initial Condition ◽  
Starting Point ◽  
Microwave Sounding Unit ◽  
Microwave Sounding ◽  
Advanced Microwave Sounding Unit ◽  
Upper Level ◽  
The Impact

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.

scholarly journals The Radiometric Sensitivity Requirements for Satellite Microwave Temperature Sounding Instruments for Numerical Weather Prediction

2010 ◽  
Vol 27 (3) ◽  
pp. 443-456 ◽  
Author(s):  
William Bell ◽  
Sabatino Di Michele ◽  
Peter Bauer ◽  
Tony McNally ◽  
Stephen J. English ◽  
...  
Keyword(s):  
Southern Hemisphere ◽  
Weather Prediction ◽  
Forecast Accuracy ◽  
Forecast Errors ◽  
Atmospheric Infrared Sounder ◽  
Microwave Sounding Unit ◽  
Atmospheric Sounding ◽  
Microwave Sounding ◽  
Satellite Microwave ◽  
The Impact

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.

Construction of the Remote Sensing Systems V3.2 Atmospheric Temperature Records from the MSU and AMSU Microwave Sounders

2009 ◽  
Vol 26 (6) ◽  
pp. 1040-1056 ◽  
Author(s):  
Carl A. Mears ◽  
Frank J. Wentz
Keyword(s):  
Lower Stratosphere ◽  
Atmospheric Temperature ◽  
Temperature Record ◽  
Sensing Systems ◽  
Calibration Methods ◽  
Microwave Sounding Unit ◽  
Microwave Sounding ◽  
Remote Sensing Systems ◽  
Temperature Records ◽  
Thick Layers

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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