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

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.

2009 ◽  
Vol 26 (8) ◽  
pp. 1493-1509 ◽  
Author(s):  
Carl A. Mears ◽  
Frank J. Wentz

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.


2021 ◽  
Vol 13 (16) ◽  
pp. 3148
Author(s):  
Xinlu Xia ◽  
Xiaolei Zou

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.


2012 ◽  
Vol 24 (5) ◽  
pp. 507-513
Author(s):  
Z. Qin ◽  
X. Zou ◽  
F. Weng

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.


2009 ◽  
Vol 26 (6) ◽  
pp. 1040-1056 ◽  
Author(s):  
Carl A. Mears ◽  
Frank J. Wentz

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.


2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Matthias Stocker ◽  
Florian Ladstädter ◽  
Andrea K. Steiner

AbstractWildfires are expected to become more frequent and intense in the future. They not only pose a serious threat to humans and ecosystems, but also affect Earth’s atmosphere. Wildfire plumes can reach into the stratosphere, but little is known about their climate impact. Here, we reveal observational evidence that major wildfires can have a severe impact on the atmospheric temperature structure and short-term climate in the stratosphere. Using advanced satellite observation, we find substantial warming of up to 10 K of the lower stratosphere within the wildfire plumes during their early development. The short-term climate signal in the lower stratosphere lasts several months and amounts to 1 K for the Northern American wildfires in 2017, and up to striking 3.5 K for the Australian wildfires in 2020. This is stronger than any signal from recent volcanic eruptions. Such extreme events affect atmospheric composition and climate trends, underpinning their importance for future climate.


2014 ◽  
Vol 31 (10) ◽  
pp. 2206-2222 ◽  
Author(s):  
Xiaolei Zou ◽  
Fuzhong Weng ◽  
H. Yang

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.


2010 ◽  
Vol 10 (6) ◽  
pp. 2947-2963 ◽  
Author(s):  
I. S. Stachlewska ◽  
R. Neuber ◽  
A. Lampert ◽  
C. Ritter ◽  
G. Wehrle

Abstract. The Airborne Mobile Aerosol Lidar (AMALi) is an instrument developed at the Alfred Wegener Institute for Polar and Marine Research for reliable operation under the challenging weather conditions at the Earth's polar regions. Since 2003 the AMALi has been successfully deployed for measurements in ground-based installation and zenith- or nadir-pointing airborne configurations during several scientific campaigns in the Arctic. The lidar provides backscatter profiles at two wavelengths (355/532 nm or 1064/532 nm) together with the linear depolarization at 532 nm, from which aerosol and cloud properties can be derived. This paper presents the characteristics and capabilities of the AMALi system and gives examples of its usage for airborne and ground-based operations in the Arctic. As this backscatter lidar normally does not operate in aerosol-free layers special evaluation schemes are discussed, the nadir-pointing iterative inversion for the case of an unknown boundary condition and the two-stream approach for the extinction profile calculation if a second lidar system probes the same air mass. Also an intercomparison of the AMALi system with an established ground-based Koldewey Aerosol Raman Lidar (KARL) is given.


2020 ◽  
Vol 12 (18) ◽  
pp. 2988
Author(s):  
Wenze Yang ◽  
Huan Meng ◽  
Ralph R. Ferraro ◽  
Yong Chen

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.


2006 ◽  
Vol 19 (10) ◽  
pp. 2094-2104 ◽  
Author(s):  
William J. Randel ◽  
Fei Wu

Abstract Temperature trends derived from historical radiosonde data often show substantial differences compared to satellite measurements. These differences are especially large for stratospheric levels, and for data in the Tropics, where results are based on relatively few stations. Detailed comparisons of one radiosonde dataset with collocated satellite measurements from the Microwave Sounding Unit reveal time series differences that occur as step functions or jumps at many stations. These jumps occur at different times for different stations, suggesting that the differences are primarily related to problems in the radiosonde data, rather than in the satellite record. As a result of these jumps, the radiosondes exhibit systematic cooling biases relative to the satellites. A large number of the radiosonde stations in the Tropics are influenced by these biases, suggesting that cooling in the tropical lower stratosphere is substantially overestimated in these radiosonde data. Comparison of trends from stations with larger and smaller biases suggests the cooling bias extends into the tropical upper troposphere. Significant biases are observed in both daytime and nighttime radiosonde measurements.


2009 ◽  
Vol 9 (5) ◽  
pp. 18745-18792 ◽  
Author(s):  
I. S. Stachlewska ◽  
R. Neuber ◽  
A. Lampert ◽  
C. Ritter ◽  
G. Wehrle

Abstract. The Airborne Mobile Aerosol Lidar (AMALi) is an instrument developed at the Alfred Wegener Institute for Polar and Marine Research for a trouble-free operation under the challenging weather conditions at the Earth's polar regions. Since 2003 the AMALi has been successfully deployed for measurements in the ground-based installation and the zenith- or nadir-aiming airborne configurations during several scientific campaigns in the Arctic. The lidar provides profiles of the total backscatter at two wavelengths, from which aerosol and cloud properties are derived. It measures also the linear depolarization of the backscattered return, allowing for the discrimination of thermodynamic cloud phase and the identification of the presence of non-spherical aerosol particles. This paper presents the capability characteristics and performance of the past and present state of the AMALi system, as well as discusses the ground-based and airborne evaluation schemes applied to invert the data.


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