Impacts of AMSU-A inter-sensor calibration and diurnal correction on satellite-derived linear and nonlinear decadal climate trends of atmospheric temperature

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.

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Observing the climate impact of large wildfires on stratospheric temperature

Scientific Reports ◽

10.1038/s41598-021-02335-7 ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

Matthias Stocker ◽

Florian Ladstädter ◽

Andrea K. Steiner

Keyword(s):

Lower Stratosphere ◽

Volcanic Eruptions ◽

Satellite Observation ◽

Atmospheric Temperature ◽

Climate Impact ◽

Atmospheric Composition ◽

Temperature Structure ◽

Climate Trends ◽

Short Term ◽

Climate Signal

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.

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Spectrally Dependent CLARREO Infrared Spectrometer Calibration Requirement for Climate Change Detection

Journal of Climate ◽

10.1175/jcli-d-16-0704.1 ◽

2017 ◽

Vol 30 (11) ◽

pp. 3979-3998 ◽

Cited By ~ 10

Author(s):

Xu Liu ◽

Wan Wu ◽

Bruce A. Wielicki ◽

Qiguang Yang ◽

Susan H. Kizer ◽

...

Keyword(s):

Climate Change ◽

Water Vapor ◽

Climate Model ◽

Model Simulation ◽

Atmospheric Temperature ◽

Reanalysis Data ◽

Natural Variability ◽

Radiometric Calibration ◽

Climate Trends ◽

Moisture Profiles

Abstract Detecting climate trends of atmospheric temperature, moisture, cloud, and surface temperature requires accurately calibrated satellite instruments such as the Climate Absolute Radiance and Refractivity Observatory (CLARREO). Previous studies have evaluated the CLARREO measurement requirements for achieving climate change accuracy goals in orbit. The present study further quantifies the spectrally dependent IR instrument calibration requirement for detecting trends of atmospheric temperature and moisture profiles. The temperature, water vapor, and surface skin temperature variability and the associated correlation time are derived using the Modern-Era Retrospective Analysis for Research and Applications (MERRA) and European Centre for Medium-Range Weather Forecasts (ECMWF) reanalysis data. The results are further validated using climate model simulation results. With the derived natural variability as the reference, the calibration requirement is established by carrying out a simulation study for CLARREO observations of various atmospheric states under all-sky conditions. A 0.04-K (k = 2; 95% confidence) radiometric calibration requirement baseline is derived using a spectral fingerprinting method. It is also demonstrated that the requirement is spectrally dependent and that some spectral regions can be relaxed as a result of the hyperspectral nature of the CLARREO instrument. Relaxing the requirement to 0.06 K (k = 2) is discussed further based on the uncertainties associated with the temperature and water vapor natural variability and relatively small delay in the time to detect for trends relative to the baseline case. The methodology used in this study can be extended to other parameters (such as clouds and CO2) and other instrument configurations.

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Stability of the MSU-Derived Atmospheric Temperature Trend

Journal of Atmospheric and Oceanic Technology ◽

10.1175/2009jtecha1333.1 ◽

2010 ◽

Vol 27 (11) ◽

pp. 1960-1971 ◽

Cited By ~ 25

Author(s):

Cheng-Zhi Zou ◽

Wenhui Wang

Keyword(s):

Time Series ◽

Correction Term ◽

Empirical Relationship ◽

Information Service ◽

Atmospheric Temperature ◽

Tropospheric Temperature ◽

Climate Trends ◽

Drift Correction ◽

Target Effect ◽

Best Fit

Abstract Warm target effect and diurnal drift errors are the main sources of uncertainties in the trend determination from the NOAA Microwave Sounding Unit (MSU) observations. Currently, there are two methods to correct the warm target effect: 1) finding a best root-level (level-1c) calibration nonlinearity using simultaneous nadir overpass (SNO) matchups to minimize this effect for each scene radiance, and 2) finding a best-fit empirical relationship between the correction term of the end-level gridded brightness temperature and warm target temperature and then removing the best fit from the unadjusted time series. The former corrects the warm target effect before the diurnal drift adjustment and provides more accurate, warm target effect–minimized, level-1c scene radiances for reanalysis applications. The latter corrects the warm target effect at the end-level merging step, which depend on the diurnal drift correction that occurred at a previous step. Although minimized, the first method still leaves small residual warm target–related errors due to imperfect calibrations. This study demonstrates that when the diurnal drift effect is negligible, a combination of the two methods completely removes warm target effect and produces an invariant trend that is independent of the level-1c calibration in the SNO framework. The conclusion is directly applicable to the MSU channel-2 oceanic midtropospheric temperature (T2) and global channel-3 upper-tropospheric temperature (T3) and channel-4 lower-stratospheric temperature (T4), which satisfy the condition of negligible diurnal drift effect. On the basis of these results, version 1.2 of the National Environmental Satellite, Data, and Information Service (NESDIS)–Center for Satellite Applications and Research (STAR) multisatellite MSU time series was constructed, including all T2, T3, and T4 products. In addition, a diurnal drift correction based on the Remote Sensing Systems diurnal anomalies was applied to the T2 product, which produces consistent climate trends between land and ocean. The global long-term climate trends for T2 and T4 derived from the STAR V1.2 dataset are, respectively, 0.18 ± 0.05 and −0.39 ± 0.36 K decade−1 during 1979–2006; the T3 trend is 0.11 ± 0.08 K decade−1 for 1981–2006.

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

Journal of Climate ◽

10.1175/2008jcli2233.1 ◽

2009 ◽

Vol 22 (7) ◽

pp. 1661-1681 ◽

Cited By ~ 65

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.

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Absence of internal multidecadal and interdecadal oscillations in climate model simulations

Nature Communications ◽

10.1038/s41467-019-13823-w ◽

2020 ◽

Vol 11 (1) ◽

Cited By ~ 16

Author(s):

Michael E. Mann ◽

Byron A. Steinman ◽

Sonya K. Miller

Keyword(s):

Climate Model ◽

Southern Oscillation ◽

Low Frequency ◽

Climate Trends ◽

Internal Oscillation ◽

Model Simulations ◽

Control Climate ◽

Climate Model Simulations ◽

Decadal Climate ◽

And Control

AbstractFor several decades the existence of interdecadal and multidecadal internal climate oscillations has been asserted by numerous studies based on analyses of historical observations, paleoclimatic data and climate model simulations. Here we use a combination of observational data and state-of-the-art forced and control climate model simulations to demonstrate the absence of consistent evidence for decadal or longer-term internal oscillatory signals that are distinguishable from climatic noise. Only variability in the interannual range associated with the El Niño/Southern Oscillation is found to be distinguishable from the noise background. A distinct (40–50 year timescale) spectral peak that appears in global surface temperature observations appears to reflect the response of the climate system to both anthropogenic and natural forcing rather than any intrinsic internal oscillation. These findings have implications both for the validity of previous studies attributing certain long-term climate trends to internal low-frequency climate cycles and for the prospect of decadal climate predictability.

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System Design and Evaluation of Coupled Ensemble Data Assimilation for Global Oceanic Climate Studies

Monthly Weather Review ◽

10.1175/mwr3466.1 ◽

2007 ◽

Vol 135 (10) ◽

pp. 3541-3564 ◽

Cited By ~ 257

Author(s):

S. Zhang ◽

M. J. Harrison ◽

A. Rosati ◽

A. Wittenberg

Keyword(s):

Twentieth Century ◽

Data Assimilation ◽

Climate Variability ◽

Climate Model ◽

Heat Content ◽

Coupled Model ◽

Atmospheric Temperature ◽

Meridional Overturning Circulation ◽

Climate Trends ◽

Fully Coupled

Abstract A fully coupled data assimilation (CDA) system, consisting of an ensemble filter applied to the Geophysical Fluid Dynamics Laboratory’s global fully coupled climate model (CM2), has been developed to facilitate the detection and prediction of seasonal-to-multidecadal climate variability and climate trends. The assimilation provides a self-consistent, temporally continuous estimate of the coupled model state and its uncertainty, in the form of discrete ensemble members, which can be used directly to initialize probabilistic climate forecasts. Here, the CDA is evaluated using a series of perfect model experiments, in which a particular twentieth-century simulation—with temporally varying greenhouse gas and natural aerosol radiative forcings—serves as a “truth” from which observations are drawn, according to the actual ocean observing network for the twentieth century. These observations are then assimilated into a coupled model ensemble that is subjected only to preindustrial forcings. By examining how well this analysis ensemble reproduces the “truth,” the skill of the analysis system in recovering anthropogenically forced trends and natural climate variability is assessed, given the historical observing network. The assimilation successfully reconstructs the twentieth-century ocean heat content variability and trends in most locations. The experiments highlight the importance of maintaining key physical relationships among model fields, which are associated with water masses in the ocean and geostrophy in the atmosphere. For example, when only oceanic temperatures are assimilated, the ocean analysis is greatly improved by incorporating the temperature–salinity covariance provided by the analysis ensemble. Interestingly, wind observations are more helpful than atmospheric temperature observations for constructing the structure of the tropical atmosphere; the opposite holds for the extratropical atmosphere. The experiments indicate that the Atlantic meridional overturning circulation is difficult to constrain using the twentieth-century observational network, but there is hope that additional observations—including those from the newly deployed Argo profiles—may lessen this problem in the twenty-first century. The challenges for data assimilation of model systematic biases and evolving observing systems are discussed.

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Predicting ecological changes on benthic estuarine assemblages through decadal climate trends along Brazilian Marine Ecoregions

Estuarine Coastal and Shelf Science ◽

10.1016/j.ecss.2015.05.021 ◽

2015 ◽

Vol 166 ◽

pp. 74-82 ◽

Cited By ~ 38

Author(s):

Angelo F. Bernardino ◽

Sérgio A. Netto ◽

Paulo R. Pagliosa ◽

Francisco Barros ◽

Ronaldo A. Christofoletti ◽

...

Keyword(s):

Climate Trends ◽

Ecological Changes ◽

Decadal Climate

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Observed Temperature Changes in the Troposphere and Stratosphere from 1979 to 2018

Journal of Climate ◽

10.1175/jcli-d-19-0998.1 ◽

2020 ◽

Vol 33 (19) ◽

pp. 8165-8194 ◽

Cited By ~ 1

Author(s):

A. K. Steiner ◽

F. Ladstädter ◽

W. J. Randel ◽

A. C. Maycock ◽

Q. Fu ◽

...

Keyword(s):

Lower Troposphere ◽

Atmospheric Temperature ◽

Lapse Rate ◽

Rate Theory ◽

Climate Trends ◽

Upper Troposphere ◽

Air Atmosphere ◽

Temperature Trends ◽

Current State ◽

Vertical Range

AbstractTemperature observations of the upper-air atmosphere are now available for more than 40 years from both ground- and satellite-based observing systems. Recent years have seen substantial improvements in reducing long-standing discrepancies among datasets through major reprocessing efforts. The advent of radio occultation (RO) observations in 2001 has led to further improvements in vertically resolved temperature measurements, enabling a detailed analysis of upper-troposphere/lower-stratosphere trends. This paper presents the current state of atmospheric temperature trends from the latest available observational records. We analyze observations from merged operational satellite measurements, radiosondes, lidars, and RO, spanning a vertical range from the lower troposphere to the upper stratosphere. The focus is on assessing climate trends and on identifying the degree of consistency among the observational systems. The results show a robust cooling of the stratosphere of about 1–3 K, and a robust warming of the troposphere of about 0.6–0.8 K over the last four decades (1979–2018). Consistent results are found between the satellite-based layer-average temperatures and vertically resolved radiosonde records. The overall latitude–altitude trend patterns are consistent between RO and radiosonde records. Significant warming of the troposphere is evident in the RO measurements available after 2001, with trends of 0.25–0.35 K per decade. Amplified warming in the tropical upper-troposphere compared to surface trends for 2002–18 is found based on RO and radiosonde records, in approximate agreement with moist adiabatic lapse rate theory. The consistency of trend results from the latest upper-air datasets will help to improve understanding of climate changes and their drivers.

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