An official website of the United States government
Observational data have long suggested that in the tropics, when the troposphere locally warms, the lower stratosphere locally cools. Here, the observed anti-correlation between tropospheric and lower stratospheric temperature is confirmed—the lower stratosphere cools by approximately 2 degrees per degree of warming in the mid-troposphere. This anti-correlation is explained through a recently proposed theory holding that there is a quasi-balanced response of the stratosphere to tropospheric heating [J. Lin, K. Emanuel, Tropospheric thermal forcing of the stratosphere through quasi-balanced dynamics.J. Atmos. Sci.(2024).]. The local-scale anti-correlation between tropospheric and lower stratospheric temperature also holds when considering climate change—where the troposphere has been anomalously warming relative to the zonal mean, the lower stratosphere has been anomalously cooling, and vice versa. This suggests that zonally asymmetries in tropospheric temperature trends will be reflected in that of the lower stratospheric temperature trends. The zonally asymmetric trends are also found to be comparable in magnitude to the mean temperature trends in the lower stratosphere, highlighting the importance of the pattern of warming. The results and proposed theory suggest that in addition to forcing via wave-dissipation, the lower stratosphere can also be subject to direct forcing by the troposphere, through quasi-steady, quasi-balanced dynamics.
more »
« less
Exceptional stratospheric contribution to human fingerprints on atmospheric temperature
In 1967, scientists used a simple climate model to predict that human-caused increases in atmospheric CO 2 should warm Earth’s troposphere and cool the stratosphere. This important signature of anthropogenic climate change has been documented in weather balloon and satellite temperature measurements extending from near-surface to the lower stratosphere. Stratospheric cooling has also been confirmed in the mid to upper stratosphere, a layer extending from roughly 25 to 50 km above the Earth’s surface (S 25 − 50 ). To date, however, S 25 − 50 temperatures have not been used in pattern-based attribution studies of anthropogenic climate change. Here, we perform such a “fingerprint” study with satellite-derived patterns of temperature change that extend from the lower troposphere to the upper stratosphere. Including S 25 − 50 information increases signal-to-noise ratios by a factor of five, markedly enhancing fingerprint detectability. Key features of this global-scale human fingerprint include stratospheric cooling and tropospheric warming at all latitudes, with stratospheric cooling amplifying with height. In contrast, the dominant modes of internal variability in S 25 − 50 have smaller-scale temperature changes and lack uniform sign. These pronounced spatial differences between S 25 − 50 signal and noise patterns are accompanied by large cooling of S 25 − 50 (1 to 2 ° C over 1986 to 2022) and low S 25 − 50 noise levels. Our results explain why extending “vertical fingerprinting” to the mid to upper stratosphere yields incontrovertible evidence of human effects on the thermal structure of Earth’s atmosphere.
more »
« less
- PAR ID:
- 10462025
- Date Published:
- Journal Name:
- Proceedings of the National Academy of Sciences
- Volume:
- 120
- Issue:
- 20
- ISSN:
- 0027-8424
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
More Like this
-
-
null (Ed.)We compare atmospheric temperature changes in satellite data and in older and newer multi-model and single-model ensembles performed under phases 5 and 6 of the Coupled Model Intercomparison Project (CMIP5 and CMIP6). In the lower stratosphere, multi-decadal 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 differences in the forcings and climate sensitivity of the CMIP5 and CMIP6 ensembles, their ensemble-average global warming over the satellite era is remarkably similar. We also examine four well-understood properties of tropical behavior governed by basic physical processes. The first three properties are ratios between trends in water vapor (WV) and trends in sea surface temperature (SST), the temperature of the lower troposphere (TLT), and the temperature of the mid- to upper troposphere (TMT). The fourth property is the ratio between TMT and SST trends. All four trend ratios are tightly constrained in CMIP simulations. Observed ratios diverge markedly when calculated with SST, TLT, and TMT trends produced by different groups. Observed data sets with larger warming of the tropical ocean surface and tropical troposphere yield atmospheric moistening that is closer to model results. For the TMT/SST ratio, model-data consistency depends on the selected combination of observed data sets used to estimate TMT and SST trends. If model expectations of these four covariance relationships are realistic, one interpretation of our findings is that they reflect a systematic low bias in satellite tropospheric temperature trends. Alternately, the observed atmospheric moistening signal may be overestimated. Given the large structural uncertainties in observed tropical TMT and SST trends, and because satellite WV data are available from one group only, it is difficult to determine which interpretation is more credible. Nevertheless, our analysis illustrates the diagnostic power of simultaneously considering multiple complementary variables and points towards possible problems with certain observed data sets.more » « less
-
Previous work identified an anthropogenic fingerprint pattern in 𝑇AC (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 𝑇AC(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 𝑇AC (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) inter-model 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 𝑇AC(𝑥,𝑡) variability associated with the Atlantic Multidecadal Oscillation and the El Niño~Southern Oscillation. The robustness of the seasonal cycle D&A results shown here, taken together with the evidence fromidealized aquaplanet simulations, suggest that basic physical processes are dictating a common pattern of forced𝑇AC(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.more » « less
-
Abstract Interannual variability of tropospheric moisture and temperature are key aspects of Earth’s climate. In this study, monthly mean specific humidity ( q ) and temperature ( T ) variability is analyzed using 12 years of COSMIC-1 (C1) radio occultation retrievals between 60°N and 60°S, with a focus on the tropics. C1 retrievals are relatively independent of the a priori values for q and T within the lower/middle troposphere and upper troposphere/lower stratosphere, respectively. Tropical interannual variability is dominated by El Niño–Southern Oscillation (ENSO). Systematic increases and decreases in zonal mean q and T are observed during the 2009/10 and 2015/16 El Niño events and 2007/08 and 2010/11 La Niña events, respectively. ENSO patterns in q and T are isolated using linear regression, and anomaly magnitudes increase with altitude, reaching a maximum in the upper troposphere. Upper-tropospheric q anomalies expand from the tropics into the midlatitude lower stratosphere, and the T vertical structure is consistent with a moist adiabatic response. C1 results are compared with NCAR’s Whole Atmosphere Community Climate Model (WACCM), forced by observed sea surface temperatures, to evaluate model behavior in an idealized setting. WACCM ENSO variations in q and T generally show consistent behavior with C1 with somewhat smaller magnitudes. Case studies are conducted for major ENSO events during the study period. The spatial variability of q is closely aligned with outgoing longwave radiation (OLR) anomalies. For example, midtropospheric q increases over 100% and OLR decreases over 50 W m −2 over the central Pacific during the 2015/16 El Niño, and substantial regional q and T anomalies are observed throughout the tropics and midlatitudes for each event.more » « less
-
Abstract We investigate changes in the vertical structure of the ocean temperature annual cycle amplitude (TEMPAC) down to a depth of 300 m, providing important insights into the relative contributions of anthropogenic and natural influences. Using observations and phase 6 of the Coupled Model Intercomparison Project (CMIP6) simulations, we perform a detection and attribution analysis by applying a standard pattern-based “fingerprint” method to zonal-mean TEMPACanomalies for three major ocean basins. In all model historical simulations and observational datasets, TEMPACincreases significantly in the surface layer, except in the Southern Ocean, and weakens within the subsurface ocean. There is a decrease in TEMPACbelow the annual-mean mixed layer depth, mainly due to a deep-reaching winter warming signal. The temporal evolution of signal-to-noise (S/N) ratios in observations indicates an identifiable anthropogenic fingerprint in both surface and interior ocean annual temperature cycles. These findings are consistent across three different observational datasets, with variations in fingerprint detection time likely related to differences in dataset coverage, interpolation method, and accuracy. Analysis of CMIP6 single-forcing simulations reveals the dominant influence of greenhouse gases and anthropogenic aerosols on TEMPACchanges. Our identification of an anthropogenic TEMPACfingerprint is robust to the selection of different analysis periods. S/N ratios derived with model data only are consistently larger than ratios calculated with observational signals, primarily due to model versus observed TEMPACdifferences in the Atlantic. Human influence on the seasonality of surface and subsurface ocean temperature may have profound consequences for fisheries, marine ecosystems, and ocean chemistry. Significance StatementThe seasonal cycle is a fundamental aspect of our climate, and gaining insight into how anthropogenic forcing has impacted seasonality is of scientific, economic, and societal importance. Using observations and CMIP6 model simulations, this research applies a pattern-based detection and attribution method to ocean temperature annual cycle amplitude (TEMPAC) down to 300 m across three major ocean basins. Key findings reveal significant increases in surface layer TEMPACexcept in the Southern Ocean and a weakening of TEMPACwithin the subsurface ocean. Importantly, the analysis confirms human influence on TEMPAC. These findings underscore the profound influence of human-caused climate change on the world’s oceans and have important implications for marine ecosystems, fisheries, and ocean chemistry.more » « less
- Free Publicly Accessible Full Text
-
Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.1073/pnas.2300758120
