Plant stomata mediate the fluxes of both carbon and water between the land and the atmosphere. The ratio between photosynthesis and stomatal conductance (gs), or intrinsic water-use efficiency (iWUE), can be directly inferred from leaf or tree-ring carbon isotope composition. In many Earth system models, iWUE is inversely proportional and controlled by a parameter (g1M) in the calculation of gs. Here we examine how iWUE perturbations, setting g1M to the 5th (low) and 95th (high) percentile for each plant type based on observations, influence photosynthesis using coupled Earth System model simulations. We find that while lower iWUE leads to reductions in photosynthesis nearly everywhere, higher iWUE had a photosynthetic response that is surprisingly regionally dependent. Higher iWUE increases photosynthesis in the Amazon and central North America, but decreases photosynthesis in boreal Canada under fixed atmospheric conditions. However, the photosynthetic response to higher iWUE in these regions unexpectedly reverses when the atmosphere dynamically responds due to spatially differing sensitivity to increases in temperature and vapor pressure deficit. iWUE also influences the photosynthetic response to atmospheric CO2, with higher and lower iWUE modifying the total global response to elevated 2x preindustrial CO2 by 6.4% and -9.6%, respectively. Our work demonstrates that assumptions about iWUE in Earth system models significantly affect photosynthesis and its response to climate. Further, the response of photosynthesis to iWUE depends on which components of the model are included, therefore studies of iWUE impacts on historical or future photosynthesis can not be generalized across model configurations.

The increasing frequency of very high temperatures driven by global warming has motivated growing interest in how the probability distribution of summertime temperatures will evolve in the future. Climate models predict increasing temperature variance in global warming simulations, but given their biased representations of historical temperature variability, it is important to use simple models to evaluate and understand these predictions. In this study we show that the projections of increasing temperature variance are indeed credible and are driven primarily by the magnitude of local warming. A simple analytic theory based on the surface energy and water budgets reproduces the increased midlatitude summertime temperature variance shown by state of the art climate models using only the local change in summertime mean temperature and relative humidity. The relative contributions of local warming and relative humidity changes to the increases in summertime temperature variance are roughly equal.

General Circulation Models (GCMs) exhibit substantial biases in their simulation of tropical climate. One particularly problematic bias exists in GCMs’ simulation of the tropical rainband known as the Intertropical Convergence Zone (ITCZ). Much of the precipitation on Earth falls within the ITCZ, which plays a key role in setting Earth’s temperature by affecting global energy transports, and partially dictates dynamics of the largest interannual mode of climate variability: the El Nino-Southern Oscillation (ENSO). Most GCMs fail to simulate the mean state of the ITCZ correctly, often exhibiting a “double ITCZ bias”, with rainbands both north and south rather than just north of the equator. These tropical mean state biases limit confidence in climate models’ simulation of projected future and paleoclimate states, and reduce the utility of these models for understanding present climate dynamics. Adjusting GCM parameterizations of cloud processes and atmospheric convection can reduce tropical biases, as can artificially correcting sea surface temperatures (SSTs) through modifications to air-sea fluxes (i.e. “flux adjustment”). Here we argue that a significant portion of these rainfall and circulation biases are rooted in orographic height being biased low due to assumptions made in fitting observed orography onto GCM grids. We demonstrate that making different, and physically defensible, assumptions that raise the orographic height significantly improves model simulation of climatological features such as the ITCZ and North American rainfall as well as the simulation of ENSO. These findings suggest a simple, physically-based, and computationally inexpensive method that can improve climate models and projections of future climate.