skip to main content
US FlagAn official website of the United States government
dot gov icon
Official websites use .gov
A .gov website belongs to an official government organization in the United States.
https lock icon
Secure .gov websites use HTTPS
A lock ( lock ) or https:// means you've safely connected to the .gov website. Share sensitive information only on official, secure websites.

Explore Research Products in the PAR
It may take a few hours for recently added research products to appear in PAR search results.


  • NSF Public Access
  • Search Results
  • The effect of forced change and unforced variability in heat waves, temperature extremes, and associated population risk in a CO<sub>2</sub>-warmed world
Title: The effect of forced change and unforced variability in heat waves, temperature extremes, and associated population risk in a CO<sub>2</sub>-warmed world
Abstract. This study investigates the impact of global warming on heat and humidityextremes by analyzing 6 h output from 28 members of the Max PlanckInstitute Grand Ensemble driven by forcing from a 1 % yr−1 CO2 increase. We find that unforced variability drives large changes in regional exposure to extremes in different ensemble members, and these variations are mostly associated with El Niño–Southern Oscillation (ENSO) variability. However, while the unforced variability in the climate can alter the occurrence of extremes regionally, variability within the ensemble decreases significantly as one looks at larger regions or at a global population perspective. This means that, for metrics of extreme heat and humidity analyzed here, forced variability in the climate is more important than the unforced variability at global scales. Lastly, we found that most heat wave metrics will increase significantly between 1.5 and 2.0 ∘C, and that low gross domestic product (GDP) regions show significantly higher risks of facing extreme heat events compared to high GDP regions. Considering the limited economic adaptability of the population to heat extremes, this reinforces the idea that the most severe impacts of climate change may fall mostly on those least capable of adapting.  more » « less
Award ID(s):
1841308
PAR ID:
10333303
Author(s) / Creator(s):
; ;
Date Published:
Journal Name:
Atmospheric Chemistry and Physics
Volume:
21
Issue:
15
ISSN:
1680-7324
Page Range / eLocation ID:
11889 to 11904
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
More Like this
  1. ; ; ; ; ; ; ; ; ; ; et al (, Earth System Science Data)
    null (Ed.)
    Abstract. Methane (CH4) emissions from natural landscapes constituteroughly half of global CH4 contributions to the atmosphere, yet largeuncertainties remain in the absolute magnitude and the seasonality ofemission quantities and drivers. Eddy covariance (EC) measurements ofCH4 flux are ideal for constraining ecosystem-scale CH4emissions due to quasi-continuous and high-temporal-resolution CH4flux measurements, coincident carbon dioxide, water, and energy fluxmeasurements, lack of ecosystem disturbance, and increased availability ofdatasets over the last decade. Here, we (1) describe the newly publisheddataset, FLUXNET-CH4 Version 1.0, the first open-source global dataset ofCH4 EC measurements (available athttps://fluxnet.org/data/fluxnet-ch4-community-product/, last access: 7 April 2021). FLUXNET-CH4includes half-hourly and daily gap-filled and non-gap-filled aggregatedCH4 fluxes and meteorological data from 79 sites globally: 42freshwater wetlands, 6 brackish and saline wetlands, 7 formerly drainedecosystems, 7 rice paddy sites, 2 lakes, and 15 uplands. Then, we (2) evaluate FLUXNET-CH4 representativeness for freshwater wetland coverageglobally because the majority of sites in FLUXNET-CH4 Version 1.0 arefreshwater wetlands which are a substantial source of total atmosphericCH4 emissions; and (3) we provide the first global estimates of theseasonal variability and seasonality predictors of freshwater wetlandCH4 fluxes. Our representativeness analysis suggests that thefreshwater wetland sites in the dataset cover global wetland bioclimaticattributes (encompassing energy, moisture, and vegetation-relatedparameters) in arctic, boreal, and temperate regions but only sparselycover humid tropical regions. Seasonality metrics of wetland CH4emissions vary considerably across latitudinal bands. In freshwater wetlands(except those between 20∘ S to 20∘ N) the spring onsetof elevated CH4 emissions starts 3 d earlier, and the CH4emission season lasts 4 d longer, for each degree Celsius increase in meanannual air temperature. On average, the spring onset of increasing CH4emissions lags behind soil warming by 1 month, with very few sites experiencingincreased CH4 emissions prior to the onset of soil warming. Incontrast, roughly half of these sites experience the spring onset of risingCH4 emissions prior to the spring increase in gross primaryproductivity (GPP). The timing of peak summer CH4 emissions does notcorrelate with the timing for either peak summer temperature or peak GPP.Our results provide seasonality parameters for CH4 modeling andhighlight seasonality metrics that cannot be predicted by temperature or GPP(i.e., seasonality of CH4 peak). FLUXNET-CH4 is a powerful new resourcefor diagnosing and understanding the role of terrestrial ecosystems andclimate drivers in the global CH4 cycle, and future additions of sitesin tropical ecosystems and site years of data collection will provide addedvalue to this database. All seasonality parameters are available athttps://doi.org/10.5281/zenodo.4672601 (Delwiche et al., 2021).Additionally, raw FLUXNET-CH4 data used to extract seasonality parameterscan be downloaded from https://fluxnet.org/data/fluxnet-ch4-community-product/ (last access: 7 April 2021), and a completelist of the 79 individual site data DOIs is provided in Table 2 of this paper. 
    more » « less
  2. ; ; ; (, Geophysical Research Letters)
    Abstract Humid heat extremes, characterized by high wet bulb temperature (Tw), pose significant health risks. While strong El Niño events are known to affect the frequency of extreme Tw days, the distinct impacts of Central Pacific (CP) and Eastern Pacific (EP) El Niño events remain understudied. Using a 12‐member CMIP6 ensemble at discrete global warming targets (+1.5, 2, 3, 4°C), this study shows progressively enhanced humid heat extent during EP events primarily in Mainland Southeast Asia, while South Asia experiences regionally opposing effects from EP and CP events. EP and CP events drive distinctly different, regionally varying patterns of dangerous Tw, yet both significantly increase the affected population and area impacted by humid heat extremes at all global warming levels. This amplification surpasses the impact of an additional degree of global warming, highlighting El Niño's compounding effect on heat stress threats across warmer climates. 
    more » « less
  3. ; ; ; ; ; ; ; ; ; (, Biogeosciences)
    Abstract. The Southern Ocean is highly under-sampled for the purpose of assessing total carbon uptake and its variability. Since this region dominates the mean global ocean sink for anthropogenic carbon, understanding temporal change is critical. Underway measurements of pCO2 collected as part of the Drake Passage Time-series (DPT) program that began in 2002 inform our understanding of seasonally changing air–sea gradients in pCO2, and by inference the carbon flux in this region. Here, we utilize available pCO2 observations to evaluate how the seasonal cycle, interannual variability, and long-term trends in surface ocean pCO2 in the Drake Passage region compare to that of the broader subpolar Southern Ocean. Our results indicate that the Drake Passage is representative of the broader region in both seasonality and long-term pCO2 trends, as evident through the agreement of timing and amplitude of seasonal cycles as well as trend magnitudes both seasonally and annually. The high temporal density of sampling by the DPT is critical to constraining estimates of the seasonal cycle of surface pCO2 in this region, as winter data remain sparse in areas outside of the Drake Passage. An increase in winter data would aid in reduction of uncertainty levels. On average over the period 2002–2016, data show that carbon uptake has strengthened with annual surface ocean pCO2 trends in the Drake Passage and the broader subpolar Southern Ocean less than the global atmospheric trend. Analysis of spatial correlation shows Drake Passage pCO2 to be representative of pCO2 and its variability up to several hundred kilometers away from the region. We also compare DPT data from 2016 and 2017 to contemporaneous pCO2 estimates from autonomous biogeochemical floats deployed as part of the Southern Ocean Carbon and Climate Observations and Modeling project (SOCCOM) so as to highlight the opportunity for evaluating data collected on autonomous observational platforms. Though SOCCOM floats sparsely sample the Drake Passage region for 2016–2017 compared to the Drake Passage Time-series, their pCO2 estimates fall within the range of underway observations given the uncertainty on the estimates. Going forward, continuation of the Drake Passage Time-series will reduce uncertainties in Southern Ocean carbon uptake seasonality, variability, and trends, and provide an invaluable independent dataset for post-deployment assessment of sensors on autonomous floats. Together, these datasets will vastly increase our ability to monitor change in the ocean carbon sink. 
    more » « less
  4. ; ; ; ; ; ; ; ; ; ; et al (, Earth System Science Data)
    Abstract. Ship-based time series, some now approaching over 3 decades long, are critical climate records that have dramatically improved our ability to characterize natural and anthropogenic drivers of ocean carbon dioxide (CO2) uptake and biogeochemical processes. Advancements in autonomous marine carbon sensors and technologies over the last 2 decades have led to the expansion of observations at fixed time series sites, thereby improving the capability of characterizing sub-seasonal variability in the ocean. Here, we present a data product of 40 individual autonomous moored surface ocean pCO2 (partial pressure of CO2) time series established between 2004 and 2013, 17 also include autonomous pH measurements. These time series characterize a wide range of surface ocean carbonate conditions in different oceanic (17 sites), coastal (13 sites), and coral reef (10 sites) regimes. A time of trend emergence (ToE) methodology applied to the time series that exhibit well-constrained daily to interannual variability and an estimate of decadal variability indicates that the length of sustained observations necessary to detect statistically significant anthropogenic trends varies by marine environment. The ToE estimates for seawater pCO2 and pH range from 8 to 15 years at the open ocean sites, 16 to 41 years at the coastal sites, and 9 to 22 years at the coral reef sites. Only two open ocean pCO2 time series, Woods Hole Oceanographic Institution Hawaii Ocean Time-series Station (WHOTS) in the subtropical North Pacific and Stratus in the South Pacific gyre, have been deployed longer than the estimated trend detection time and, for these, deseasoned monthly means show estimated anthropogenic trends of 1.9±0.3 and 1.6±0.3 µatm yr−1, respectively. In the future, it is possible that updates to this product will allow for the estimation of anthropogenic trends at more sites; however, the product currently provides a valuable tool in an accessible format for evaluating climatology and natural variability of surface ocean carbonate chemistry in a variety of regions. Data are available at https://doi.org/10.7289/V5DB8043 and https://www.nodc.noaa.gov/ocads/oceans/Moorings/ndp097.html (Sutton et al., 2018). 
    more » « less
  5. ; ; (, Journal of Climate)
    Abstract Constraining unforced and forced climate variability impacts interpretations of past climate variations and predictions of future warming. However, comparing general circulation models (GCMs) and last millennium Holocene hydroclimate proxies reveals significant mismatches between simulated and reconstructed low-frequency variability at multidecadal and longer time scales. This mismatch suggests that existing simulations underestimate either external or internal drivers of climate variability. In addition, large differences arise across GCMs in both the magnitude and spatial pattern of low-frequency climate variability. Dynamical understanding of forced and unforced variability is expected to contribute to improved interpretations of paleoclimate variability. To that end, we develop a framework for fingerprinting spatiotemporal patterns of temperature variability in forced and unforced simulations. This framework relies on two frequency-dependent metrics: 1) degrees of freedom (≡N) and 2) spatial coherence. First, we useNand spatial coherence to characterize variability across a suite of both preindustrial control (unforced) and last-millennium (forced) GCM simulations. Overall, we find that, at low frequencies and when forcings are added, regional independence in the climate system decreases, reflected in fewerNand higher coherence between local and global mean surface temperature. We then present a simple three-box moist-static-energy-balance model for temperature variability, which is able to emulate key frequency-dependent behavior in the GCMs. This suggests that temperature variability in the GCM ensemble can be understood through Earth’s energy budget and downgradient energy transport, and allows us to identify sources of polar-amplified variability. Finally, we discuss insights the three-box model can provide into model-to-model GCM differences. Significance StatementForced and unforced temperature variability are poorly constrained and understood, particularly that at time scales longer than a decade. Here, we identify key differences in the time scale–dependent behavior of forced and unforced temperature variability using a combination of numerical climate models and principles of downgradient energy transport. This work, and the spatiotemporal characterizations of forced and unforced temperature variability that we generate, will aid in interpretations of proxy-based paleoclimate reconstructions and improve mechanistic understanding of variability. 
    more » « less
  • Citation Formats
  • MLA
  • APA
  • Chicago
  • BibTeX
  • Save / Share this Record
  • Send to Email