Agricultural breadbaskets shift poleward given adaptive farmer behavior under climate change.

Modern food production is spatially concentrated in global "breadbaskets." A major unresolved question is whether these peak production regions will shift poleward as the climate warms, allowing some recovery of potential climate-related losses. While agricultural impacts studies to date have focused on currently cultivated land, the Global Gridded Crop Model Intercomparison Project (GGCMI) Phase 2 experiment allows us to assess changes in both yields and the location of peak productivity regions under warming. We examine crop responses under projected end of century warming using seven process-based models simulating five major crops (maize, rice, soybeans, and spring and winter wheat) with a variety of adaptation strategies. We find that in no-adaptation cases, when planting date and cultivar choices are held fixed, regions of peak production remain stationary and yield losses can be severe, since growing seasons contract strongly with warming. When adaptations in management practices are allowed (cultivars that retain growing season length under warming and modified planting dates), peak productivity zones shift poleward and yield losses are largely recovered. While most growing-zone shifts are ultimately limited by geography, breadbaskets studied here move poleward over 600 km on average by end of the century under RCP 8.5. These results suggest that agricultural impacts assessments can be strongly biased if restricted in spatial area or in the scope of adaptive behavior considered. Accurate evaluation of food security under climate change requires global modeling and careful treatment of adaptation strategies.

Large potential for crop production adaptation depends on available future varieties.

Climate change affects global agricultural production and threatens food security. Faster phenological development of crops due to climate warming is one of the main drivers for potential future yield reductions. To counter the effect of faster maturity, adapted varieties would require more heat units to regain the previous growing period length. In this study, we investigate the effects of variety adaptation on global caloric production under four different future climate change scenarios for maize, rice, soybean, and wheat. Thereby, we empirically identify areas that could require new varieties and areas where variety adaptation could be achieved by shifting existing varieties into new regions. The study uses an ensemble of seven global gridded crop models and five CMIP6 climate models. We found that 39% (SSP5-8.5) of global cropland could require new crop varieties to avoid yield loss from climate change by the end of the century. At low levels of warming (SSP1-2.6), 85% of currently cultivated land can draw from existing varieties to shift within an agro-ecological zone for adaptation. The assumptions on available varieties for adaptation have major impacts on the effectiveness of variety adaptation, which could more than half in SSP5-8.5. The results highlight that region-specific breeding efforts are required to allow for a successful adaptation to climate change.

Climate impacts on global agriculture emerge earlier in new generation of climate and crop models.

Potential climate-related impacts on future crop yield are a major societal concern. Previous projections of the Agricultural Model Intercomparison and Improvement Project's Global Gridded Crop Model Intercomparison based on the Coupled Model Intercomparison Project Phase 5 identified substantial climate impacts on all major crops, but associated uncertainties were substantial. Here we report new twenty-first-century projections using ensembles of latest-generation crop and climate models. Results suggest markedly more pessimistic yield responses for maize, soybean and rice compared to the original ensemble. Mean end-of-century maize productivity is shifted from +5% to -6% (SSP126) and from +1% to -24% (SSP585)-explained by warmer climate projections and improved crop model sensitivities. In contrast, wheat shows stronger gains (+9% shifted to +18%, SSP585), linked to higher CO2 concentrations and expanded high-latitude gains. The 'emergence' of climate impacts consistently occurs earlier in the new projections-before 2040 for several main producing regions. While future yield estimates remain uncertain, these results suggest that major breadbasket regions will face distinct anthropogenic climatic risks sooner than previously anticipated.

The Chicago Water Isotope Spectrometer (ChiWIS-lab): A tunable diode laser spectrometer for chamber-based measurements of water vapor isotopic evolution during cirrus formation.

We describe a new tunable diode laser (TDL) absorption instrument, the Chicago Water Isotope Spectrometer, designed for measurements of vapor-phase water isotopologues in conditions characteristic of the upper troposphere [190-235 K temperature and 2-500 parts per million volume (ppmv) water vapor]. The instrument is primarily targeted for measuring the evolving ratio of HDO/H2O during experiments in the "Aerosol Interaction and Dynamics in the Atmosphere" (AIDA) cloud chamber. The spectrometer scans absorption lines of both H2O and HDO near the 2.64 µm wavelength in a single current sweep, increasing the accuracy of isotopic ratio measurements. At AIDA, the instrument is configured with a 256-m path length White cell for in situ measurements, and effective sensitivity can be augmented by enhancing the HDO content of chamber water vapor by an order of magnitude. The instrument has participated to date in the 2012-2013 IsoCloud campaigns studying isotopic partitioning during the formation of cirrus clouds and in the AquaVIT-II instrument intercomparison campaign. Realized precisions for 1-s measurements during these campaigns were 22 ppbv for H2O and 16 ppbv for HDO, equivalent to relative precisions of less than 0.5% for each species at 8 ppmv water vapor. The 1-s precision of the [HDO]/[H2O] ratio measurement ranged from 1.6‰ to 5.6‰ over the range of experimental conditions. H2O measurements showed agreement with calculated saturation vapor pressure to within 1% in conditions of sublimating ice and agreement with other AIDA instruments (the AIDA SP-APicT reference TDL instrument and an MBW 373LX chilled mirror hygrometer) to within 2.5% and 3.8%, respectively, over conditions suitable for all instruments (temperatures from 204 K to 234 K and H2O content equivalent to 15-700 ppmv at 200 hPa).

Improved light collection in OA-ICOS cells using non-axially-symmetric optics.

We show that the introduction of a non-axially-symmetric optical component can significantly improve light collection in instruments that use off-axis integrated cavity output spectroscopy (OA-ICOS). OA-ICOS is a robust technique for field measurements of scarce trace gases, but the inherent skewness of its output makes light collection onto small detectors difficult. Here, we derive the constraining effect of skewness in OA-ICOS cavities with Herriott alignments, and show how this constraint can be overcome by the addition of a non-axially-symmetric optical component. We describe such a component consisting of eight ZnSe wedges designed for the OA-ICOS-based Chicago Water Isotope Spectrometer, and show that this component increases the instrument's signal-to-noise ratio by a factor of three. The ratio of improvement is expected to be even larger in compact OA-ICOS instruments.

Laboratory measurements of HDO/H2O isotopic fractionation during ice deposition in simulated cirrus clouds.

The stable isotopologues of water have been used in atmospheric and climate studies for over 50 years, because their strong temperature-dependent preferential condensation makes them useful diagnostics of the hydrological cycle. However, the degree of preferential condensation between vapor and ice has never been directly measured at temperatures below 233 K (-40 °C), conditions necessary to form cirrus clouds in the Earth's atmosphere, routinely observed in polar regions, and typical for the near-surface atmospheric layers of Mars. Models generally assume an extrapolation from the warmer experiments of Merlivat and Nief [Merlivat L, Nief G (1967) Tellus 19:122-127]. Nonequilibrium kinetic effects that should alter preferential partitioning have also not been well characterized experimentally. We present here direct measurements of HDO/H2O equilibrium fractionation between vapor and ice ([Formula: see text]) at cirrus-relevant temperatures, using in situ spectroscopic measurements of the evolving isotopic composition of water vapor during cirrus formation experiments in a cloud chamber. We rule out the recent proposed upward modification of [Formula: see text], and find values slightly lower than Merlivat and Nief. These experiments also allow us to make a quantitative validation of the kinetic modification expected to occur in supersaturated conditions in the ice-vapor system. In a subset of diffusion-limited experiments, we show that kinetic isotope effects are indeed consistent with published models, including allowing for small surface effects. These results are fundamental for inferring processes on Earth and other planets from water isotopic measurements. They also demonstrate the utility of dynamic in situ experiments for studying fractionation in geochemical systems.

Evaluating the sensitivity of agricultural model performance to different climate inputs.

Projections of future food production necessarily rely on models, which must themselves be validated through historical assessments comparing modeled to observed yields. Reliable historical validation requires both accurate agricultural models and accurate climate inputs. Problems with either may compromise the validation exercise. Previous studies have compared the effects of different climate inputs on agricultural projections, but either incompletely or without a ground truth of observed yields that would allow distinguishing errors due to climate inputs from those intrinsic to the crop model. This study is a systematic evaluation of the reliability of a widely-used crop model for simulating U.S. maize yields when driven by multiple observational data products. The parallelized Decision Support System for Agrotechnology Transfer (pDSSAT) is driven with climate inputs from multiple sources - reanalysis, reanalysis bias-corrected with observed climate, and a control dataset - and compared to observed historical yields. The simulations show that model output is more accurate when driven by any observation-based precipitation product than when driven by un-bias-corrected reanalysis. The simulations also suggest, in contrast to previous studies, that biased precipitation distribution is significant for yields only in arid regions. However, some issues persist for all choices of climate inputs: crop yields appear oversensitive to precipitation fluctuations but undersensitive to floods and heat waves. These results suggest that the most important issue for agricultural projections may be not climate inputs but structural limitations in the crop models themselves.

Evaluating the utility of dynamical downscaling in agricultural impacts projections.

Interest in estimating the potential socioeconomic costs of climate change has led to the increasing use of dynamical downscaling--nested modeling in which regional climate models (RCMs) are driven with general circulation model (GCM) output--to produce fine-spatial-scale climate projections for impacts assessments. We evaluate here whether this computationally intensive approach significantly alters projections of agricultural yield, one of the greatest concerns under climate change. Our results suggest that it does not. We simulate US maize yields under current and future CO2 concentrations with the widely used Decision Support System for Agrotechnology Transfer crop model, driven by a variety of climate inputs including two GCMs, each in turn downscaled by two RCMs. We find that no climate model output can reproduce yields driven by observed climate unless a bias correction is first applied. Once a bias correction is applied, GCM- and RCM-driven US maize yields are essentially indistinguishable in all scenarios (<10% discrepancy, equivalent to error from observations). Although RCMs correct some GCM biases related to fine-scale geographic features, errors in yield are dominated by broad-scale (100s of kilometers) GCM systematic errors that RCMs cannot compensate for. These results support previous suggestions that the benefits for impacts assessments of dynamically downscaling raw GCM output may not be sufficient to justify its computational demands. Progress on fidelity of yield projections may benefit more from continuing efforts to understand and minimize systematic error in underlying climate projections.

Precise multipass Herriott cell design: derivation of controlling design equations.

Multipass Herriott cells are often designed using the thin lens approximation, which results in approximate dimensions or imperfect patterns due to both spherical aberration and the finite width of the optic. We derive the design equations for exact solutions to the Herriott cell problem. We also show that Herriott cells using spherical mirrors cannot be designed such that multiple concentric beam patterns all meet their reentrant condition. We derive a solution for elliptical mirrors that allows this condition to be met simultaneously for many beams.

Ultrasensitive near-infrared integrated cavity output spectroscopy technique for detection of CO at 1.57 microm: new sensitivity limits for absorption measurements in passive optical cavities.

A robust absorption spectrometer using the off-axis integrated cavity output spectroscopy (ICOS) technique in a passive cavity is presented. The observed sensitivity, conceptually the detection threshold for the absorption cross section (cm2) multiplied by the concentration (cm(-3)) and normalized by the averaging time, is measured to be 1.9 x 10(-12) (1/cm square root of Hz). This high sensitivity arises from using the optical cavity to amplify the observed path length in the spectrometer while avoiding cavity resonances by careful design of the spot pattern within the cavity. The instrument is ideally suited for routine monitoring of trace gases in the near-infrared region. A spectrum showing ambient carbon monoxide at 1.57 microm is presented.