Abstract

In recognizing the importance of Stratospheric Sounding Unit (SSU) onboard historical NOAA polar-orbiting satellites in assessment of long-term stratospheric temperature changes and limitations in previous available SSU datasets, this study constructs a fully documented, publicly accessible, and well-merged SSU time series for climate change investigations. Focusing on methodologies, this study describes the details of data processing and bias corrections in the SSU observations for generating consistent stratospheric temperature data records, including 1) removal of the instrument gas leak effect in its CO₂ cell; 2) correction of the atmospheric CO₂ increase effect; 3) adjustment for different observation viewing angles; 4) removal of diurnal sampling biases due to satellite orbital drift; and 5) statistical merging of SSU observations from different satellites. After reprocessing, the stratospheric temperature records are composed of nadirlike, gridded brightness temperatures that correspond to identical weighting functions and a fixed local observation time. The 27-yr reprocessed SSU data record comprises global monthly and pentad layer temperatures, with grid resolution of 2.5° latitude by 2.5° longitude, of the midstratosphere (TMS), upper stratosphere (TUS), and top stratosphere (TTS), which correspond to the three SSU channel observations. For 1979–2006, the global mean trends for TMS, TUS, and TTS, are respectively −1.236 ± 0.131, −0.926 ± 0.139, and −1.006 ± 0.194 K decade⁻¹. Spatial trend pattern analyses indicated that this cooling occurred globally with larger cooling over the tropical stratosphere.

Abstract

Poleward meridional moisture transport across the Southern Ocean during 1988 is investigated by applying conservation of mass to the wind derivation approach of Slonaker and Van Woert. The moisture field is from the Television and Infrared Observational Satellite (TIROS) Operational Vertical Sounder (TOVS) Pathfinder A dataset. The wind field is first derived from a combination of the TOVS temperature profiles and a satellite-based surface wind field using the thermal wind relationship. Then a Lagrange multiplier is introduced in a variational procedure to constrain the wind to conserve mass.

The introduction of the conservation of mass reduces the estimates of the moisture flux and net precipitation dramatically in comparison with the nonmass-conserved method in Slonaker and Van Woert. For instance, the estimates of the zonally averaged, vertically integrated moisture flux across 50°S are reduced by 56% and the net precipitation between the 50°S and 60°S latitude belt are reduced by 63%. The reason for the difference is that the nonmass-conserved approach leads to unrealistically strong annual-mean winds in the lower troposphere, which results in an exaggerated mean moisture transport. In contrast, the mass-conserved annual-mean wind compares favorably with the radiosonde observations at Macquarie Island and European Centre for Medium-Range Weather Forecasts and National Centers for Environmental Prediction–National Center for Atmospheric Research reanalyses, and it yields a mean moisture flux consistent with historical estimates.

In contrast, the satellite-derived eddy moisture flux is underestimated by about 45% when compared with the radiosonde and analysis studies. This underestimation is probably due to the lower spatial and temporal resolutions of the satellite observations and lack of certain types of ageostrophic winds in the wind derivation.

Abstract

Accurate three-dimensional wind fields are essential for diagnosing a variety of important climate processes in the Arctic, such as the advection and deposition of heat and moisture, changes in circulation features, and transport of trace constituents. In light of recent studies revealing significant biases in upper-level winds over the Arctic Ocean from reanalyses, new daily wind fields are generated from 22.5 yr of satellite-retrieved thermal-wind profiles, corrected with a recently developed mass-conservation scheme. Compared to wind measurements from rawinsondes during the Surface Heat Budget of the Arctic (SHEBA) experiment, biases in satellite-retrieved winds are near zero in the meridional direction, versus biases of over 50% for reanalyses. Errors in the zonal component are smaller than those observed in reanalysis winds in the upper troposphere, while in the lower troposphere the effects of Greenland introduce uncertainty in the mass-conservation calculation. Further reduction in error may be achieved by incorporating winds retrieved from feature-tracking techniques using satellite imagers. Overall, satellite-retrieved winds are superior to reanalysis products over the data-sparse Arctic Ocean and provide increased accuracy for analyses requiring wind information.

Trends and anomalies for the 22.5-yr record are calculated for both meridional and zonal winds at eight levels between the surface and 300 hPa. Annual mean trends are similar at varying levels, reflecting the relatively barotropic nature of the Arctic troposphere. Zonal winds are more westerly over Eurasia and the western Arctic Ocean, while westerlies have weakened over northern Canada. Combined with the corresponding pattern in meridional winds, these results suggest that the polar vortex has, on average, shifted toward northern Canada. Seasonal trends show that some changes persist throughout the year while others vary in magnitude and sign. Most striking are spring patterns, which differ markedly from the other seasons. Changes in meridional winds are consistent with observed trends in melt-onset date and sea ice concentration in the marginal seas. Anomalies in zonal wind profiles exhibit decadal-scale cyclicity in the eastern Arctic Ocean, while overall shifts in anomaly signs are evident and vary by region. The winter North Atlantic Oscillation (NAO) index correlates moderately with meridional wind anomalies in the Atlantic sector of the Arctic Ocean: positively (0.48) in the Barents Sea and negatively (−0.59) in the Lincoln Sea. These observed trends and anomalies are expected to translate to changes in advected heat and moisture into the Arctic basin, which are likely linked to trends in sea ice extent, melt onset, cloud properties, and surface temperature.

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.

Abstract

Temperature trends in the middle and upper stratosphere are evaluated using measurements from the Stratospheric Sounding Unit (SSU), combined with data from the Aura Microwave Limb Sounder (MLS) and Sounding of the Atmosphere Using Broadband Emission Radiometry (SABER) instruments. Data from MLS and SABER are vertically integrated to approximate the SSU weighting functions and combined with SSU to provide a data record spanning 1979–2015. Vertical integrals are calculated using empirically derived Gaussian weighting functions, which provide improved agreement with high-latitude SSU measurements compared to previously derived weighting functions. These merged SSU data are used to evaluate decadal-scale trends, solar cycle variations, and volcanic effects from the lower to the upper stratosphere. Episodic warming is observed following the volcanic eruptions of El Chichón (1982) and Mt. Pinatubo (1991), focused in the tropics in the lower stratosphere and in high latitudes in the middle and upper stratosphere. Solar cycle variations are centered in the tropics, increasing in amplitude from the lower to the upper stratosphere. Linear trends over 1979–2015 show that cooling increases with altitude from the lower stratosphere (from ~−0.1 to −0.2 K decade⁻¹) to the middle and upper stratosphere (from ~−0.5 to −0.6 K decade⁻¹). Cooling in the middle and upper stratosphere is relatively uniform in latitudes north of about 30°S, but trends decrease to near zero over the Antarctic. Mid- and upper-stratospheric temperatures show larger cooling over the first half of the data record (1979–97) compared to the second half (1998–2015), reflecting differences in upper-stratospheric ozone trends between these periods.

Abstract

Updated and improved satellite retrievals of the temperature of the mid-to-upper troposphere (TMT) are used to address key questions about the size and significance of TMT trends, agreement with model-derived TMT values, and whether models and satellite data show similar vertical profiles of warming. A recent study claimed that TMT trends over 1979 and 2015 are 3 times larger in climate models than in satellite data but did not correct for the contribution TMT trends receive from stratospheric cooling. Here, it is shown that the average ratio of modeled and observed TMT trends is sensitive to both satellite data uncertainties and model–data differences in stratospheric cooling. When the impact of lower-stratospheric cooling on TMT is accounted for, and when the most recent versions of satellite datasets are used, the previously claimed ratio of three between simulated and observed near-global TMT trends is reduced to approximately 1.7. Next, the validity of the statement that satellite data show no significant tropospheric warming over the last 18 years is assessed. This claim is not supported by the current analysis: in five out of six corrected satellite TMT records, significant global-scale tropospheric warming has occurred within the last 18 years. Finally, long-standing concerns are examined regarding discrepancies in modeled and observed vertical profiles of warming in the tropical atmosphere. It is shown that amplification of tropical warming between the lower and mid-to-upper troposphere is now in close agreement in the average of 37 climate models and in one updated satellite record.

Abstract

We compare atmospheric temperature changes in satellite data and in model ensembles performed under phases 5 and 6 of the Coupled Model Intercomparison Project (CMIP5 and CMIP6). In the lower stratosphere, multidecadal stratospheric cooling during the period of strong ozone depletion is smaller in newer CMIP6 simulations than in CMIP5 or satellite data. In the troposphere, however, despite forcing and climate sensitivity differences between the two CMIP ensembles, their ensemble-average global warming over 1979–2019 is very similar. We also examine four properties of tropical behavior governed by basic physical processes. The first three are ratios between trends in water vapor (WV) and trends in sea surface temperature (SST), lower-tropospheric temperature (TLT), and mid- to upper-tropospheric temperature (TMT). The fourth property is the ratio between TMT and SST trends. All four ratios are tightly constrained in CMIP simulations but diverge markedly in observations. Model trend ratios between WV and temperature are closest to observed ratios when the latter are calculated with datasets exhibiting larger tropical warming of the ocean surface and troposphere. For the TMT/SST ratio, model–data consistency depends on the combination of observations used to estimate TMT and SST trends. If model expectations of these four covariance relationships are realistic, our findings reflect either a systematic low bias in satellite tropospheric temperature trends or an overestimate of the observed atmospheric moistening signal. It is currently difficult to determine which interpretation is more credible. Nevertheless, our analysis reveals anomalous covariance behavior in several observational datasets and illustrates the diagnostic power of simultaneously considering multiple complementary variables.

Abstract

Previous work identified an anthropogenic fingerprint pattern in T _AC(x, t), the amplitude of the seasonal cycle of mid- to upper-tropospheric temperature (TMT), but did not explicitly consider whether fingerprint identification in satellite T _AC(x, t) data could have been influenced by real-world multidecadal internal variability (MIV). We address this question here using large ensembles (LEs) performed with five climate models. LEs provide many different sequences of internal variability noise superimposed on an underlying forced signal. Despite differences in historical external forcings, climate sensitivity, and MIV properties of the five models, their T _AC(x, t) fingerprints are similar and statistically identifiable in 239 of the 240 LE realizations of historical climate change. Comparing simulated and observed variability spectra reveals that consistent fingerprint identification is unlikely to be biased by model underestimates of observed MIV. Even in the presence of large (factor of 3–4) intermodel and inter-realization differences in the amplitude of MIV, the anthropogenic fingerprints of seasonal cycle changes are robustly identifiable in models and satellite data. This is primarily due to the fact that the distinctive, global-scale fingerprint patterns are spatially dissimilar to the smaller-scale patterns of internal T _AC(x, t) variability associated with the Atlantic multidecadal oscillation and El Niño–Southern Oscillation. The robustness of the seasonal cycle detection and attribution results shown here, taken together with the evidence from idealized aquaplanet simulations, suggest that basic physical processes are dictating a common pattern of forced T _AC(x, t) changes in observations and in the five LEs. The key processes involved include GHG-induced expansion of the tropics, lapse-rate changes, land surface drying, and sea ice decrease.