Person:

Huybers, Peter

A number of previous observational studies have found that the waters of the deep Pacific Ocean have an age, or elapsed time since contact with the surface, of 700–1000 yr. Numerical models suggest ages twice as old. Here, the authors present an inverse framework to determine the mean age and its upper and lower bounds given Global Ocean Data Analysis Project (GLODAP) radiocarbon observations, and they show that the potential range of ages increases with the number of constituents or sources that are included in the analysis. The inversion requires decomposing the World Ocean into source waters, which is obtained here using the total matrix intercomparison (TMI) method at up to 2° × 2° horizontal resolution with 11 113 surface sources. The authors find that the North Pacific at 2500-m depth can be no younger than 1100 yr old, which is older than some previous observational estimates. Accounting for the broadness of surface regions where waters originate leads to a reservoir-age correction of almost 100 yr smaller than would be estimated with a two or three water-mass decomposition and explains some of the discrepancy with previous observational studies. A best estimate of mean age is also presented using the mixing history along circulation pathways. Subject to the caveats that inference of the mixing history would benefit from further observations and that radiocarbon cannot rule out the presence of extremely old waters from exotic sources, the deep North Pacific waters are 1200–1500 yr old, which is more in line with existing numerical model results.

We investigate the stability of marine ice sheets by coupling a gravitationally self-consistent sea level model valid for a self-gravitating, viscoelastically deforming Earth to a 1-D marine ice sheet-shelf model. The evolution of the coupled model is explored for a suite of simulations in which we vary the bed slope and the forcing that initiates retreat. We find that the sea level fall at the grounding line associated with a retreating ice sheet acts to slow the retreat; in simulations with shallow reversed bed slopes and/or small external forcing, the drop in sea level can be sufficient to halt the retreat. The rate of sea level change at the grounding line has an elastic component due to ongoing changes in ice sheet geometry, and a viscous component due to past ice and ocean load changes. When the ice sheet model is forced from steady state, on short timescales (<∼500 years), viscous effects may be ignored and grounding-line migration at a given time will depend on the local bedrock topography and on contemporaneous sea level changes driven by ongoing ice sheet mass flux. On longer timescales, an accurate assessment of the present stability of a marine ice sheet requires knowledge of its past evolution.

One of the many ways that climate change may affect human health is by altering the nutrient content of food crops. However, previous attempts to study the effects of increased atmospheric CO2 on crop nutrition have been limited by small sample sizes and/or artificial growing conditions. Here we present data from a meta-analysis of the nutritional contents of the edible portions of 41 cultivars of six major crop species grown using free-air CO2 enrichment (FACE) technology to expose crops to ambient and elevated CO2 concentrations in otherwise normal field cultivation conditions. This data, collected across three continents, represents over ten times more data on the nutrient content of crops grown in FACE experiments than was previously available. We expect it to be deeply useful to future studies, such as efforts to understand the impacts of elevated atmospheric CO2 on crop macro- and micronutrient concentrations, or attempts to alleviate harmful effects of these changes for the billions of people who depend on these crops for essential nutrients.

The climatological annual cycle in surface air temperature, defined by its amplitude and phase lag with respect to solar insolation, is one of the most familiar aspects of the climate system. Here, the authors identify three first-order features of the spatial structure of amplitude and phase lag and explain them using simple physical models. Amplitude and phase lag 1) are broadly consistent with a land and ocean end-member mixing model but 2) exhibit overlap between land and ocean and, despite this overlap, 3) show a systematically greater lag over ocean than land for a given amplitude. Based on previous work diagnosing relative ocean or land influence as an important control on the extratropical annual cycle, the authors use a Lagrangian trajectory model to quantify this influence as the weighted amount of time that an ensemble of air parcels has spent over ocean or land. This quantity explains 84% of the space–time variance in the extratropical annual cycle, as well as features 1 and 2. All three features can be explained using a simple energy balance model with land and ocean surfaces and an advecting atmosphere. This model explains 94% of the space–time variance of the annual cycle in an illustrative midlatitude zonal band when incorporating the results of the trajectory model. The aforementioned features of annual variability in surface air temperature thus appear to be explained by the coupling of land and ocean through mean atmospheric circulation.

Significant discrepancies exist between the detrended variability of late-Holocene marine temperatures inferred from Mg/Ca and Uk37 proxies, with the former showing substantially more centennial-scale variation than the latter. Discrepancies exceed that attributable to differences in location and persist across various calibrations, indicating that they are intrinsic to the proxy measurement. We demonstrate that these discrepancies can be reconciled using a statistical model that accounts for the effects of bioturbation, sampling and measurement noise, and aliasing of seasonal variability. The smaller number of individual samples incorporated into Mg/Ca measurements relative to Uk37 measurements leads to greater aliasing and generally accounts for the differences in the magnitude and distribution of variability. An inverse application of the statistical model is also developed and applied in order to estimate the spectrum of marine temperature variability after correcting for proxy distortions. The correction method is tested on surrogate data and shown to reliably estimate the spectrum of temperature variance when using high-resolution records. Applying this inverse method to the actual Mg/Ca and Uk37 data results in estimates of the spectrum of temperature variance that are consistent. This approach provides a basis by which to accurately estimate the distribution of intrinsic marine temperature variability from marine proxy records.

Greenland has experienced large changes since the last glacial with its summit warming by approximately 21°C, average accumulation rates tripling, and annual amplitudes of temperature and accumulation seemingly declining. The altered seasonal cycle of accumulation has been attributed to a combination of the large-scale dynamical response of the North Atlantic storm track to surface boundary conditions and the modulation of moisture availability due to changes in winter sea ice cover. Using atmospheric simulations of preindustrial and glacial climate, the contributions of these two mechanisms are evaluated. Estimates of moisture source footprints make it possible to distinguish between long-range transport related to the storm track and regional transport from the ocean surface near Greenland. It is found that the contribution of both mechanisms varies significantly with the background climate. With greater ice cover and the North Atlantic storm track locked to the topographically enhanced stationary wave during the glacial, seasonal migration of the sea ice edge becomes relatively important in controlling moisture availability. In contrast, the preindustrial simulation has relatively greater transient eddy activity and is less moisture limited by sea ice extent, so accumulation is more strongly related to synoptic variability in the North Atlantic. These results highlight how changes in atmospheric circulation and sea ice together explain the shifts in annual mean and seasonal moisture supply to Greenland. Also discussed are some implications of the inferred narrow source distribution of accumulation during the glacial for the interpretation of stable isotopes derived from the central Greenland ice cores.

Variations in extreme daily temperatures are explored in relation to changes in seasonal mean temperature using 1218 high-quality U.S. temperature stations spanning 1900–2012. Extreme temperatures are amplified (or damped) by as much as ±50% relative to changes in average temperature, depending on region, season, and whether daily minimum or maximum temperature is analyzed. The majority of this regional structure in amplification is shown to follow from regional variations in temperature distributions. More specifically, there exists a close relationship between departures from normality and the degree to which extreme changes are amplified relative to the mean. To distinguish between intraseasonal and interannual contributions to nonnormality and amplification, an additional procedure, referred to as z bootstrapping, is introduced that controls for changes in the mean and variance between years. Application of z bootstrapping indicates that amplification of winter extreme variations is generally consistent with nonnormal intraseasonal variability. Summer variability, in contrast, shows interannual variations in the spread of the temperature distribution related to changes in the mean, especially in the Midwest. Changes in midwestern temperature variability are qualitatively consistent with those expected from decreases in evapotranspiration and are strongly correlated with a measure of drought intensity. The identified patterns of interannual variations in means and extremes may serve as an analog for modes of variability that can be expected at longer time scales.

Extratropical near-surface air temperature variability is explored on three different time scales: the seasonal cycle, observed changes in temperature since 1950, and the equilibrium response to increasing CO2 in an atmospheric general circulation simulation with fixed sea surface temperatures. Exploration is undertaken using an energy balance model (EBM) that parameterizes advective land-ocean heat fluxes. The EBM is tuned only to the climatological seasonal cycle yet captures 47% of the variability in observed multidecadal temperature changes in the extratropics and 78% of the variability in the equilibrated model simulation. The subseasonal time scale of atmosphere-surface heat fluxes explains, at least in the context of this EBM, the ability to infer patterns of multidecadal change using information primarily drawn from the seasonal cycle.

Dietary deficiencies of zinc and iron are a substantial global public health problem. An estimated two billion people suffer these deficiencies1, causing a loss of 63 million life-years annually2, 3. Most of these people depend on C3 grains and legumes as their primary dietary source of zinc and iron. Here we report that C3 grains and legumes have lower concentrations of zinc and iron when grown under field conditions at the elevated atmospheric CO2 concentration predicted for the middle of this century. C3 crops other than legumes also have lower concentrations of protein, whereas C4 crops seem to be less affected. Differences between cultivars of a single crop suggest that breeding for decreased sensitivity to atmospheric CO2 concentration could partly address these new challenges to global health.

The temperature variability simulated by climate models is generally consistent with that observed in instrumental records at the scale of global averages, but further insight can also be obtained from regional analysis of the marine temperature record. A protocol is developed for comparing model simulations to observations that account for observational noise and missing data. General consistency between Coupled Model Intercomparison Project Phase 5 model simulations and regional sea surface temperature variability is demonstrated at interannual timescales. At interdecadal timescales, however, the variability diagnosed from observations is significantly greater. Discrepancies are greatest at low latitudes, with none of the 41 models showing equal or greater interdecadal variability. The pattern of suppressed variability at longer timescales and smaller spatial scales appears consistent with models generally being too diffusive. Suppressed variability of low-latitude marine temperatures points to underestimation of intrinsic variability and may help explain why few models reproduce the observed temperature trends during the last 15 years.