Browse
Submit Data
Databases
API
Help

Dataset Information

16 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Natural variability contributes to model-satellite differences in tropical tropospheric warming.

ABSTRACT: A long-standing discrepancy exists between general circulation models (GCMs) and satellite observations: The multimodel mean temperature of the midtroposphere (TMT) in the tropics warms at approximately twice the rate of observations. Using a large ensemble of simulations from a single climate model, we find that tropical TMT trends (1979-2018) vary widely and that a subset of realizations are within the range of satellite observations. Realizations with relatively small tropical TMT trends are accompanied by subdued sea-surface warming in the tropical central and eastern Pacific. Observed changes in sea-surface temperature have a similar pattern, implying that the observed tropical TMT trend has been reduced by multidecadal variability. We also assess the latest generation of GCMs from the Coupled Model Intercomparison Project Phase 6 (CMIP6). CMIP6 simulations with muted warming over the central and eastern Pacific also show reduced tropical tropospheric warming. We find that 13% of the model realizations have tropical TMT trends within the observed trend range. These simulations are from models with both small and large climate sensitivity values, illustrating that the magnitude of tropical tropospheric warming is not solely a function of climate sensitivity. For global averages, one-quarter of model simulations exhibit TMT trends in accord with observations. Our results indicate that even on 40-y timescales, natural climate variability is important to consider when comparing observed and simulated tropospheric warming and is sufficiently large to explain TMT trend differences between models and satellite data.

SUBMITTER: Po-Chedley S

PROVIDER: S-EPMC8020635 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Json Xml

Similar Datasets

Internal variability and forcing influence model-satellite differences in the rate of tropical tropospheric warming.

Project description:Climate-model simulations exhibit approximately two times more tropical tropospheric warming than satellite observations since 1979. The causes of this difference are not fully understood and are poorly quantified. Here, we apply machine learning to relate the patterns of surface-temperature change to the forced and unforced components of tropical tropospheric warming. This approach allows us to disentangle the forced and unforced change in the model-simulated temperature of the midtroposphere (TMT). In applying the climate-model-trained machine-learning framework to observations, we estimate that external forcing has produced a tropical TMT trend of 0.25 ± 0.08 K⋅decade-1 between 1979 and 2014, but internal variability has offset this warming by 0.07 ± 0.07 K⋅decade-1. Using the Community Earth System Model version 2 (CESM2) large ensemble, we also find that a discontinuity in the variability of prescribed biomass-burning aerosol emissions artificially enhances simulated tropical TMT change by 0.04 K⋅decade-1. The magnitude of this aerosol-forcing bias will vary across climate models, but since the latest generation of climate models all use the same emissions dataset, the bias may systematically enhance climate-model trends over the satellite era. Our results indicate that internal variability and forcing uncertainties largely explain differences in satellite-versus-model warming and are important considerations when evaluating climate models.

| S-EPMC9704694 | biostudies-literature

Tropical mid-tropospheric CO2 variability driven by the Madden-Julian oscillation.

Project description:Carbon dioxide (CO(2)) is the most important anthropogenic greenhouse gas in the present-day climate. Most of the community focuses on its long-term (decadal to centennial) behaviors that are relevant to climate change, but there are relatively few discussions of its higher-frequency forms of variability, and none regarding its subseasonal distribution. In this work, we report a large-scale intraseasonal variation in the Atmospheric Infrared Sounder CO(2) data in the global tropical region associated with the Madden-Julian oscillation (MJO). The peak-to-peak amplitude of the composite MJO modulation is ∼1 ppmv, with a standard error of the composite mean < 0.1 ppmv. The correlation structure between CO(2) and rainfall and vertical velocity indicate positive (negative) anomalies in CO(2) arise due to upward (downward) large-scale vertical motions in the lower troposphere associated with the MJO. These findings can help elucidate how faster processes can organize, transport, and mix CO(2) and provide a robustness test for coupled carbon-climate models.

| S-EPMC2984179 | biostudies-literature

Tropospheric Warming Over The Past Two Decades.

Project description:Satellite temperature measurements do not support the recent claim of a "leveling off of warming" over the past two decades. Tropospheric warming trends over recent 20-year periods are always significantly larger (at the 10% level or better) than model estimates of 20-year trends arising from natural internal variability. Over the full 38-year period of the satellite record, the separation between observed warming and internal variability estimates is even clearer. In two out of three recent satellite datasets, the tropospheric warming from 1979 to 2016 is unprecedented relative to internally generated temperature trends on the 38-year timescale.

| S-EPMC5443760 | biostudies-literature

Upper-tropospheric moistening in response to anthropogenic warming.

Project description:Water vapor in the upper troposphere strongly regulates the strength of water-vapor feedback, which is the primary process for amplifying the response of the climate system to external radiative forcings. Monitoring changes in upper-tropospheric water vapor and scrutinizing the causes of such changes are therefore of great importance for establishing the credibility of model projections of past and future climates. Here, we use coupled ocean-atmosphere model simulations under different climate-forcing scenarios to investigate satellite-observed changes in global-mean upper-tropospheric water vapor. Our analysis demonstrates that the upper-tropospheric moistening observed over the period 1979-2005 cannot be explained by natural causes and results principally from an anthropogenic warming of the climate. By attributing the observed increase directly to human activities, this study verifies the presence of the largest known feedback mechanism for amplifying anthropogenic climate change.

| S-EPMC4136590 | biostudies-literature

Uncertainty in near-term global surface warming linked to tropical Pacific climate variability.

Project description:Climate models generally simulate a long-term slowdown of the Pacific Walker Circulation in a warming world. However, despite increasing greenhouse forcing, there was an unprecedented intensification of the Pacific Trade Winds during 1992-2011, that co-occurred with a temporary slowdown in global surface warming. Using ensemble simulations from three different climate models starting from different initial conditions, we find a large spread in projected 20-year globally averaged surface air temperature trends that can be linked to differences in Pacific climate variability. This implies diminished predictive skill for global surface air temperature trends over decadal timescales, to a large extent due to intrinsic Pacific Ocean variability. We show, however, that this uncertainty can be considerably reduced when the initial oceanic state is known and well represented in the model. In this case, the spatial patterns of 20-year surface air temperature trends depend largely on the initial state of the Pacific Ocean.

| S-EPMC6491465 | biostudies-literature

Deglacial Tropical Atlantic subsurface warming links ocean circulation variability to the West African Monsoon.

Project description:Multiple lines of evidence show that cold stadials in the North Atlantic were accompanied by both reductions in Atlantic Meridional Overturning Circulation (AMOC) and collapses of the West African Monsoon (WAM). Although records of terrestrial change identify abrupt WAM variability across the deglaciation, few studies show how ocean temperatures evolved across the deglaciation. To identify the mechanism linking AMOC to the WAM, we generated a new record of subsurface temperature variability over the last 21 kyr based on Mg/Ca ratios in a sub-thermocline dwelling planktonic foraminifera in an Eastern Equatorial Atlantic (EEA) sediment core from the Niger Delta. Our subsurface temperature record shows abrupt subsurface warming during both the Younger Dryas (YD) and Heinrich Event 1. We also conducted a new transient coupled ocean-atmosphere model simulation across the YD that better resolves the western boundary current dynamics and find a strong negative correlation between AMOC strength and EEA subsurface temperatures caused by changes in ocean circulation and rainfall responses that are consistent with the observed WAM change. Our combined proxy and modeling results provide the first evidence that an oceanic teleconnection between AMOC strength and subsurface temperature in the EEA impacted the intensity of the WAM on millennial time scales.

| S-EPMC5684145 | biostudies-literature

Tropical nighttime warming as a dominant driver of variability in the terrestrial carbon sink.

Project description:The terrestrial biosphere is currently a strong carbon (C) sink but may switch to a source in the 21st century as climate-driven losses exceed CO2-driven C gains, thereby accelerating global warming. Although it has long been recognized that tropical climate plays a critical role in regulating interannual climate variability, the causal link between changes in temperature and precipitation and terrestrial processes remains uncertain. Here, we combine atmospheric mass balance, remote sensing-modeled datasets of vegetation C uptake, and climate datasets to characterize the temporal variability of the terrestrial C sink and determine the dominant climate drivers of this variability. We show that the interannual variability of global land C sink has grown by 50-100% over the past 50 y. We further find that interannual land C sink variability is most strongly linked to tropical nighttime warming, likely through respiration. This apparent sensitivity of respiration to nighttime temperatures, which are projected to increase faster than global average temperatures, suggests that C stored in tropical forests may be vulnerable to future warming.

| S-EPMC4697419 | biostudies-literature

Anthropogenic Fingerprint Detectable in Upper Tropospheric Ozone Trends Retrieved from Satellite.

Project description:Tropospheric ozone (O3) is a strong greenhouse gas, particularly in the upper troposphere (UT). Limited observations point to a continuous increase in UT O3 in recent decades, but the attribution of UT O3 changes is complicated by large internal climate variability. We show that the anthropogenic signal ("fingerprint") in the patterns of UT O3 increases is distinguishable from the background noise of internal variability. The time-invariant fingerprint of human-caused UT O3 changes is derived from a 16-member initial-condition ensemble performed with a chemistry-climate model (CESM2-WACCM6). The fingerprint is largest between 30°S and 40°N, especially near 30°N. In contrast, the noise pattern in UT O3 is mainly associated with the El Niño-Southern Oscillation (ENSO). The UT O3 fingerprint pattern can be discerned with high confidence within only 13 years of the 2005 start of the OMI/MLS satellite record. Unlike the UT O3 fingerprint, the lower tropospheric (LT) O3 fingerprint varies significantly over time and space in response to large-scale changes in anthropogenic precursor emissions, with the highest signal-to-noise ratios near 40°N in Asia and Europe. Our analysis reveals a significant human effect on Earth's atmospheric chemistry in the UT and indicates promise for identifying fingerprints of specific sources of ozone precursors.

| S-EPMC11325641 | biostudies-literature

Wetter summers can intensify departures from natural variability in a warming climate.

Project description:Climate change can drive local climates outside the range of their historical year-to-year variability, straining the adaptive capacity of ecological and human communities. We demonstrate that dependencies between climate variables can produce larger and earlier departures from natural variability than is detectable in individual variables. Using the example of summer temperature (Tx) and precipitation (Pr), we show that this departure intensification effect occurs when the bivariate climate change trajectory is misaligned with the dominant mode of joint historical variability. Departure intensification is evident in all six CMIP5 models that we examined: 23% (9-34%) of the global land area of each model exhibits a pronounced increase in 2σ anomalies in the Tx-Pr regime relative to Tx or Pr alone. Observational data suggest that summer Tx-Pr correlations in distinct regions on all continents are sufficient to produce departure intensification. Precipitation can be an important driver of multivariate climate change signals relative to natural variability, despite typically having a much weaker univariate signal than temperature.

| S-EPMC5823852 | biostudies-literature

Seasonal energy exchange in sea ice retreat regions contributes to differences in projected Arctic warming.

Project description:Rapid and, in many cases, unprecedented Arctic climate changes are having far-reaching impacts on natural and human systems. Despite state-of-the-art climate models capturing the rapid nature of Arctic climate change, termed Arctic amplification, they significantly disagree on its magnitude. Using a regional, process-oriented surface energy budget analysis, we argue that differences in seasonal energy exchanges in sea ice retreat regions via increased absorption and storage of sunlight in summer and increased upward surface turbulent fluxes in fall/winter contribute to the inter-model spread. Models able to more widely disperse energy drawn from the surface in sea ice retreat regions warm more, suggesting that differences in the local Arctic atmospheric circulation response contribute to the inter-model spread. We find that the principle mechanisms driving the inter-model spread in Arctic amplification operate locally on regional scales, requiring an improved understanding of atmosphere-ocean-sea ice interactions in sea ice retreat regions to reduce the spread.

| S-EPMC6258731 | biostudies-literature

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

Tweets

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data