An official website of the United States government
Abstract Paleoclimate reconstructions are increasingly central to climate assessments, placing recent and future variability in a broader historical context. Paleoclimate reconstructions are increasingly central to climate assessments, placing recent and future variability in a broader historical context. Several estimation methods produce plumes of climate trajectories that practitioners often want to compare to other reconstruction ensembles, or to deterministic trajectories produced by other means, such as global climate models. Of particular interest are “offline” data assimilation (DA) methods, which have recently been adapted to paleoclimatology. Offline DA lacks an explicit model connecting time instants, so its ensemble members are not true system trajectories. This obscures quantitative comparisons, particularly when considering the ensemble mean in isolation. We propose several resampling methods to introduce a priori constraints on temporal behavior, as well as a general notion, called plume distance, to carry out quantitative comparisons between collections of climate trajectories (“plumes”). The plume distance provides a norm in the same physical units as the variable of interest (e.g. °C for temperature), and lends itself to assessments of statistical significance. We apply these tools to four paleoclimate comparisons: (1) global mean surface temperature (GMST) in the online and offline versions of the Last Millennium Reanalysis (v2.1); (2) GMST from these two ensembles to simulations of the Paleoclimate Model Intercomparison Project past1000 ensemble; (3) LMRv2.1 to the PAGES 2k (2019) ensemble of GMST and (4) northern hemisphere mean surface temperature from LMR v2.1 to the Büntgen et al. (2021) ensemble. Results generally show more compatibility between these ensembles than is visually apparent. The proposed methodology is implemented in an open-source Python package, and we discuss possible applications of the plume distance framework beyond paleoclimatology.
more »
« less
Local Regions Associated With Interdecadal Global Temperature Variability in the Last Millennium Reanalysis and CMIP5 Models
Abstract Despite the importance of interdecadal climate variability, we have a limited understanding of which geographic regions are associated with global temperature variability at these timescales. The instrumental record tends to be too short to develop sample statistics to study interdecadal climate variability, and Coupled Model Intercomparison Project, Phase 5 (CMIP5) climate models tend to disagree about which locations most strongly influence global mean interdecadal temperature variability. Here we use a new paleoclimate data assimilation product, the Last Millennium Reanalysis (LMR), to examine where local variability is associated with global mean temperature variability at interdecadal timescales. The LMR framework uses an ensemble Kalman filter data assimilation approach to combine the latest paleoclimate data and state‐of‐the‐art model data to generate annually resolved field reconstructions of surface temperature, which allow us to explore the timing and dynamics of preinstrumental climate variability in new ways. The LMR consistently shows that the middle‐ to high‐latitude north Pacific and the high‐latitude North Atlantic tend to lead global temperature variability on interdecadal timescales. These findings have important implications for understanding the dynamics of low‐frequency climate variability in the preindustrial era.
more »
« less
- Award ID(s):
- 1702423
- PAR ID:
- 10445730
- Publisher / Repository:
- DOI PREFIX: 10.1029
- Date Published:
- Journal Name:
- Journal of Geophysical Research: Atmospheres
- Volume:
- 124
- Issue:
- 17-18
- ISSN:
- 2169-897X
- Page Range / eLocation ID:
- p. 9905-9917
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
More Like this
-
-
Abstract We use online data assimilation to combine information from a linear inverse model of coupled atmosphere‐ocean dynamics with proxy records to create a new annual‐resolution reconstruction of atmosphere and ocean fields over the last millennium. Instrumental validation of reconstructed sea‐surface temperature and 0–700 m ocean heat content shows broad regions of positive spatial correlations, and high correlations (∼0.6–0.9) for global averages and indices of large‐scale modes of atmospheric variability. Compared to previous reconstructions, the online reconstructions show global and hemispheric averages with little‐to‐no millennial‐scale trend and global‐mean temperatures ∼0.25–0.5 K cooler during early periods (1000–1400 C.E.). The spatial anomaly differences of average temperature between an early (1000–1250 C.E.) and later (1400–1700 C.E.) period show warm anomalies over high‐latitude Europe and cool tropical conditions in partial agreement with previous assessments. The addition of online data assimilation, which provides dynamical memory to climate proxy information, is shown to be crucial for adequately characterizing decadal‐to‐centennial‐scale variability of 0–700 m ocean heat content. Furthermore, the climate forecasts provide model‐based physical constraints for atmosphere–ocean interaction, which become increasingly important during early periods when less proxy information is available for assimilation.more » « less
-
Abstract Large volcanic eruptions are one of the dominant perturbations to global and regional atmospheric temperatures on timescales of years to decades. Discrepancies remain, however, in the estimated magnitude and persistence of the surface temperature cooling caused by volcanic eruptions, as characterized by paleoclimatic proxies and climate models. We investigate these discrepancies in the context of large tropical eruptions over the Last Millennium using two state‐of‐the‐art data assimilation products, the Paleo Hydrodynamics Data Assimilation product (PHYDA) and the Last Millennium Reanalysis (LMR), and simulations from the National Center for Atmospheric Research Community Earth System Model‐Last Millennium Ensemble (NCAR CESM‐LME). We find that PHYDA and LMR estimate mean global and hemispheric cooling that is similar in magnitude and persistence once effects from eruptions occurring in short succession are removed. The estimates also compare well to Northern‐Hemisphere reconstructions based solely or partially on tree‐ring density, which have been proposed as the most accurate proxy estimates of surface cooling due to volcanism. All proxy‐based estimates also agree well with the magnitude of the mean cooling simulated by the CESM‐LME. Differences remain, however, in the spatial patterns of the temperature responses in the PHYDA, LMR, and the CESM‐LME. The duration of cooling anomalies also persists for several years longer in the PHYDA and LMR relative to the CESM‐LME. Our results demonstrate progress in resolving discrepancies between proxy‐ and model‐based estimates of temperature responses to volcanism, but also indicate these estimates must be further reconciled to better characterize the risks of future volcanic eruptions.more » « less
-
Abstract Attribution and prediction of global and regional warming requires a better understanding of the magnitude and spatial characteristics of internal global mean surface air temperature (GMST) variability. We examine interdecadal GMST variability in Coupled Modeling Intercomparison Projects, Phases 3, 5, and 6 (CMIP3, CMIP5, and CMIP6) preindustrial control (piControl), last millennium, and historical simulations and in observational data. We find that several CMIP6 simulations show more GMST interdecadal variability than the previous generations of model simulations. Nonetheless, we find that 100‐year trends in CMIP6 piControl simulations never exceed the maximum observed warming trend. Furthermore, interdecadal GMST variability in the unforced piControl simulations is associated with regional variability in the high latitudes and the east Pacific, whereas interdecadal GMST variability in instrumental data and in historical simulations with external forcing is more globally coherent and is associated with variability in tropical deep convective regions.more » « less
-
Abstract Large uncertainties exist in climate model projections of the Asian summer monsoon (ASM). The El Niño‐Southern Oscillation (ENSO) is an important modulator of the ASM, but the ENSO‐ASM teleconnection is not stationary. Furthermore, teleconnections between ENSO and the East Asian versus South Asian subcomponents of the ASM exhibit distinct characteristics. Therefore, understanding the variability of the ENSO‐ASM teleconnection is critical for anticipating future variations in ASM intensity. To this end, we here use paleoclimate records to extend temporal coverage beyond the instrumental era by millennia. Recently, data assimilation techniques have been applied for the last millennium, which facilitates physically consistent, globally gridded climate reconstructions informed by paleoclimate observations. We use these novel data assimilation products to investigate variations in the ENSO‐ASM relationship over the last 1,000 years. We find that correlations between ENSO and ASM indices are mostly negative in the last millennium, suggesting that strong ASM years are often associated with La Niña events. During periods of weak correlations between ENSO and the East Asian summer monsoon, we observe an El Niño‐like sea surface temperature (SST) pattern in the Pacific. Additionally, SST patterns associated with periods of weak correlations between ENSO and South Asian summer monsoon rainfall are not consistent among data assimilation products. This underscores the importance of developing more precipitation‐sensitive paleoclimate proxies in the Indian subcontinental realm over the last millennium. Our study serves as a baseline for future appraisals of paleoclimate assimilation products and an example of informing our understanding of decadal‐scale ENSO‐ASM teleconnection variability using paleoclimate data sets.more » « less
