Interpretation of Recent Temperature Trends in California

Regional-scale climate change and associated societal impacts result from large-scale (e.g. well-mixed greenhouse gases) and more local (e.g. land-use change) 'forcing' (perturbing) agents. It is essential to understand these forcings and climate responses to them, in order to predict future climate and societal impacts. California is a fine example of the complex effects of multiple climate forcings. The State's natural climate is diverse, highly variable, and strongly influenced by ENSO. Humans are perturbing this complex system through urbanization, irrigation, and emission of multiple types of aerosols and greenhouse gases. Despite better-than-average observational coverage, we are only beginning to understand the manifestations of these forcings in California's temperature record

Weather-based forecasts of California crop yields

Crop yield forecasts provide useful information to a range of users. Yields for several crops in California are currently forecast based on field surveys and farmer interviews, while for many crops official forecasts do not exist. As broad-scale crop yields are largely dependent on weather, measurements from existing meteorological stations have the potential to provide a reliable, timely, and cost-effective means to anticipate crop yields. We developed weather-based models of state-wide yields for 12 major California crops (wine grapes, lettuce, almonds, strawberries, table grapes, hay, oranges, cotton, tomatoes, walnuts, avocados, and pistachios), and tested their accuracy using cross-validation over the 1980-2003 period. Many crops were forecast with high accuracy, as judged by the percent of yield variation explained by the forecast, the number of yields with correctly predicted direction of yield change, or the number of yields with correctly predicted extreme yields. The most successfully modeled crop was almonds, with 81% of yield variance captured by the forecast. Predictions for most crops relied on weather measurements well before harvest time, allowing for lead times that were longer than existing procedures in many cases

Assessing the benefits of crop albedo bio-geoengineering

It has been proposed that growing crop varieties with higher canopy albedo would lower summer-time temperatures over North America and Eurasia and provide a partial mitigation of global warming ('bio-geoengineering') (Ridgwell et al 2009 Curr. Biol. 19 1–5). Here, we use a coupled ocean–atmosphere–vegetation model (HadCM3) with prescribed agricultural regions, to investigate to what extent the regional effectiveness of crop albedo bio-geoengineering might be influenced by a progressively warming climate as well as assessing the impacts on regional hydrological cycling and primary productivity. Consistent with previous analysis, we find that the averted warming due to increasing crop canopy albedo by 0.04 is regionally and seasonally specific, with the largest cooling of ~1 °C for Europe in summer whereas in the low latitude monsoonal SE Asian regions of high density cropland, the greatest cooling is experienced in winter. In this study we identify potentially important positive impacts of increasing crop canopy albedo on soil moisture and primary productivity in European cropland regions, due to seasonal increases in precipitation. We also find that the background climate state has an important influence on the predicted regional effectiveness of bio-geoengineering on societally-relevant timescales (ca 100 years). The degree of natural climate variability and its dependence on greenhouse forcing that are evident in our simulations highlights the difficulties faced in the detection and verification of climate mitigation in geoengineering schemes. However, despite the small global impact, regionally focused schemes such as crop albedo bio-geoengineering have detection advantages

Seasonal cycles enhance disparities between low- and high-income countries in exposure to monthly temperature emergence with future warming

A common proxy for the adaptive capacity of a community to the impacts of future climate change is the range of climate variability which they have experienced in the recent past. This study presents an interpretation of such a framework for monthly temperatures. Our results demonstrate that emergence into genuinely 'unfamiliar' climates will occur across nearly all months of the year for low-income nations by the second half of the 21st century under an RCP8.5 warming scenario. However, high income countries commonly experience a large seasonal cycle, owing to their position in the middle latitudes: as a consequence, temperature emergence for transitional months translates only to more-frequent occurrences of heat historically associated with the summertime. Projections beyond 2050 also show low-income countries will experience 2–10 months per year warmer than the hottest month experienced in recent memory, while high-income countries will witness between 1–4 months per year hotter than any month previously experienced. While both results represent significant departures that may bring substantive societal impacts if greenhouse gas emissions continue unabated, they also demonstrate that spatial patterns of emergence will compound existing differences between high and low income populations, in terms of their capacity to adapt to unprecedented future temperatures

Identification of external influences on temperatures in California

We use eight different observational datasets to estimate California-average temperature trends over 1950-1999. Observed results are compared to trends from a suite of control simulations of natural internal climate variability. Observed increases in annual-mean surface temperature are distinguishable from climate noise in some but not all observational datasets. The most robust results are large positive trends in mean and maximum daily temperatures in late winter/early spring, as well as increases in minimum daily temperatures from January to September. These trends are inconsistent with model-based estimates of natural internal climate variability, and thus require one or more external forcing agents to be explained. Our results suggest that the warming of Californian winters over the second half of the twentieth century is associated with human-induced changes in large-scale atmospheric circulation. We also hypothesize that the lack of a detectable increase in summertime maximum temperature arises from a cooling associated with large-scale irrigation. This cooling may have, until now, counteracted the warming induced by increasing greenhouse gases and urbanization effects

Simulated vs. empirical weather responsiveness of crop yields: US evidence and implications for the agricultural impacts of climate change

Global gridded crop models (GGCMs) are the workhorse of assessments of the agricultural impacts of climate change. Yet the changes in crop yields projected by different models in response to the same meteorological forcing can differ substantially. Through an inter-method comparison, we provide a first glimpse into the origins and implications of this divergence—both among GGCMs and between GGCMs and historical observations. We examine yields of rainfed maize, wheat, and soybeans simulated by six GGCMs as part of the Inter-Sectoral Impact Model Intercomparison Project-Fast Track (ISIMIP-FT) exercise, comparing 1981-2004 hindcast yields over the coterminous United States (U.S.) against U.S. Dept. of Agriculture (USDA) time series for about 1,000 counties. Leveraging the empirical climate change impacts literature, we estimate reduced-form econometric models of crop yield responses to temperature and precipitation exposures for both GGCMs and observations. We find that up to 60% of the variance in both simulated and observed yields is attributable to weather variation. Majority of the GGCMs have difficulty reproducing the observed distribution of percentage yield anomalies, and exhibit aggregate responses that show yields to be more weather-sensitive than in the observational record over the predominant range of temperature and precipitation conditions. This disparity is largely attributable to heterogeneity in GGCMs’ responses, as opposed to uncertainty in historical weather forcings, and is responsible for widely divergent impacts of climate on future crop yields

The Impact of Parameterized Convection on the Simulation of Crop Processes

Global climate and weather models are a key tool for the prediction of future crop productivity, but they all rely on parameterizations of atmospheric convection, which often produce significant biases in rainfall characteristics over the tropics. The authors evaluate the impact of these biases by driving the General Large Area Model for annual crops (GLAM) with regional-scale atmospheric simulations of one cropping season over West Africa at different resolutions, with and without a parameterization of convection, and compare these with a GLAM run driven by observations. The parameterization of convection produces too light and frequent rainfall throughout the domain, as compared with the short, localized, high-intensity events in the observations and in the convection-permitting runs. Persistent light rain increases surface evaporation, and much heavier rainfall is required to trigger planting. Planting is therefore delayed in the runs with parameterized convection and occurs at a seasonally cooler time, altering the environmental conditions experienced by the crops. Even at high resolutions, runs driven by parameterized convection underpredict the small-scale variability in yields produced by realistic rainfall patterns. Correcting the distribution of rainfall frequencies and intensities before use in crop models will improve the process-based representation of the crop life cycle, increasing confidence in the predictions of crop yield. The rainfall biases described here are a common feature of parameterizations of convection, and therefore the crop-model errors described are likely to occur when using any global weather or climate model, thus remaining hidden when using climate-model intercomparisons to evaluate uncertainty

The MAHB, the Culture Gap, and Some Really Inconvenient Truths

Humanity's failure to take adequate actions to stem a likely environmental collapse calls for extraordinary measures to understand and alter human behavior, argues Paul Ehrlich. His Millennium Assessment of Human Behavior (MAHB) aims to chart the path to a sustainable future

Climate and southern Africa's water-energy-food nexus

In southern Africa, the connections between climate and the water-energy-food nexus are strong. Physical and socioeconomic exposure to climate is high in many areas and in crucial economic sectors. Spatial interdependence is also high, driven for example, by the regional extent of many climate anomalies and river basins and aquifers that span national boundaries. There is now strong evidence of the effects of individual climate anomalies, but associations between national rainfall and Gross Domestic Product and crop production remain relatively weak. The majority of climate models project decreases in annual precipitation for southern Africa, typically by as much as 20% by the 2080s. Impact models suggest these changes would propagate into reduced water availability and crop yields. Recognition of spatial and sectoral interdependencies should inform policies, institutions and investments for enhancing water, energy and food security. Three key political and economic instruments could be strengthened for this purpose; the Southern African Development Community, the Southern African Power Pool, and trade of agricultural products amounting to significant transfers of embedded water

Louis I. Kahn and Richard Kelly: collaborative design in creation of the luminous environment

As one of the most prominent architects of the twentieth century, Louis I. Kahn aspired to use natural light to shape his architecture. The lighting designer Richard Kelly, one of his close collaborators, had significant influence on modern architectural lighting design in the twentieth century. Kahn and Kelly designed the luminous environments in three art-gallery and museum buildings, The Yale University Art Gallery, the Kimbell Art Museum and the Yale Center for British Art. Collaboration between the architect and the lighting designer resulted in well-resolved lighting solutions. This research investigated the collaboration between Louis I. Kahn and Richard Kelly from both theoretical and pragmatic perspectives. In terms of the theoretical perspective, a detailed overview of their collaborative work is provided through literature review. In terms of the pragmatic perspective, the background of their cooperation and the technical details are presented. In addition, daylighting performance analysis of these three buildings through digital modelling was undertaken. This study found that the lighting design solutions produced together by Louis I. Kahn and Richard Kelly, especially the way of using daylight, have had significant impact on architectural space and the luminous environment. More importantly, this kind of collaborative working method could provide a useful reference and guidance for contemporary architecture and lighting design