Heat waves and drought are often considered the most damaging climatic stressors for wheat. In this study, we characterize and attribute the effects of these climate extremes on wheat yield anomalies (at global and national scales) from 1980 to 2010. Using a combination of up-to-date heat wave and drought indexes (the latter capturing both excessively dry and wet conditions), we have developed a composite indicator that is able to capture the spatio-temporal characteristics of the underlying physical processes in the different agro-climatic regions of the world. At the global level, our diagnostic explains a significant portion (more than 40%) of the inter-annual production variability. By quantifying the contribution of national yield anomalies to global fluctuations, we have found that just two concurrent yield anomalies affecting the larger producers of the world could be responsible for more than half of the global annual fluctuations. The relative importance of heat stress and drought in determining the yield anomalies depends on the region. Moreover, in contrast to common perception, water excess affects wheat production more than drought in several countries. We have also performed the same analysis at the subnational level for France, which is the largest wheat producer of the European Union, and home to a range of climatic zones. Large subnational variability of inter-annual wheat yield is mostly captured by the heat and water stress indicators, consistently with the country-level result.

We present the main results from the second model intercomparison within the GEWEX (Global Energy and Water cycle EXperiment) Atmospheric Boundary Layer Study (GABLS). The target is to examine the diurnal cycle over land in today's numerical weather prediction and climate models for operational and research purposes. The set-up of the case is based on observations taken during the Cooperative Atmosphere-Surface Exchange Study-1999 (CASES-99), which was held in Kansas, USA in the early autumn with a strong diurnal cycle with no clouds present. The models are forced with a constant geostrophic wind, prescribed surface temperature and large-scale divergence. Results from 30 different model simulations and one large-eddy simulation (LES) are analyzed and compared with observations. Even though the surface temperature is prescribed, the models give variable near-surface air temperatures. This, in turn, gives rise to differences in low-level stability affecting the turbulence and the turbulent heat fluxes. The increase in modelled upward sensible heat flux during the morning transition is typically too weak and the growth of the convective boundary layer before noon is too slow. This is related to weak modelled nearsurface winds during the morning hours. The agreement between the models, the LES and observations is the best during the late afternoon. From this intercomparison study, we find that modelling the diurnal cycle is still a big challenge. For the convective part of the diurnal cycle, some of the first-order schemes perform somewhat better while the turbulent kinetic

Drought in spring and early summer has been shown to precede anomalous hot summer temperature. In particular, drought in the Mediterranean region has been recently shown to precede and to contribute to the development of extreme heat in continental Europe. In this paper, this mechanism is investigated by performing integrations of a regional mesoscale model at the scale of the European continent in order to reproduce hot summer inception, starting with different initial values of soil moisture south of 46°N. The mesoscale model is driven by the large-scale atmospheric conditions corresponding to the 10 hottest summers on record from the European Climate Assessment dataset. A northward progression of heat and drought from late spring to summer is observed from the Mediterranean regions, which leads to a further increase of temperature during summer in temperate continental Europe. Dry air formed over dry soils in the Mediterranean region induces less convection and diminished cloudiness, which gets transported northward by occasional southerly wind, increasing northward temperature and vegetation evaporative demand. Later in the season, drier soils have been established in western and central Europe where they further amplify the warming through two main feedback mechanisms: 1) higher sensible heat emissions and 2) favored upper-air anticyclonic circulation. Drier soils in southern Europe accelerate the northward propagation of heat and drying, increasing the probability of strong heat wave episodes in the middle or the end of the summer.

Abstract. The Land Surface, Snow and Soil Moisture Model Intercomparison Project (LS3MIP) is designed to provide a comprehensive assessment of land surface, snow and soil moisture feedbacks on climate variability and climate change, and to diagnose systematic biases in the land modules of current Earth system models (ESMs). The solid and liquid water stored at the land surface has a large influence on the regional climate, its variability and predictability, including effects on the energy, water and carbon cycles. Notably, snow and soil moisture affect surface radiation and flux partitioning properties, moisture storage and land surface memory. They both strongly affect atmospheric conditions, in particular surface air temperature and precipitation, but also large-scale circulation patterns. However, models show divergent responses and representations of these feedbacks as well as systematic biases in the underlying processes. LS3MIP will provide the means to quantify the associated uncertainties and better constrain climate change projections, which is of particular interest for highly vulnerable regions (densely populated areas, agricultural regions, the Arctic, semi-arid and other sensitive terrestrial ecosystems). The experiments are subdivided in two components, the first addressing systematic land biases in offline mode (“LMIP”, building upon the 3rd phase of Global Soil Wetness Project; GSWP3) and the second addressing land feedbacks attributed to soil moisture and snow in an integrated framework (“LFMIP”, building upon the GLACE-CMIP blueprint).

Temperature and precipitation are the most important factors responsible for agricultural productivity variations. In 2018 spring/summer growing season, Europe experienced concurrent anomalies of both. Drought conditions in central and northern Europe caused yield reductions up to 50% for the main crops, yet wet conditions in southern Europe saw yield gains up to 34%, both with respect to the previous 5‐year mean. Based on the analysis of documentary and natural proxy‐based seasonal paleoclimate reconstructions for the past half millennium, we show that the 2018 combination of climatic anomalies in Europe was unique. The water seesaw, a marked dipole of negative water anomalies in central Europe and positive ones in southern Europe, distinguished 2018 from the five previous similar droughts since 1976. Model simulations reproduce the 2018 European water seesaw in only 4 years out of 875 years in historical runs and projections. Future projections under the RCP8.5 scenario show that 2018‐like temperature and rainfall conditions, favorable to crop growth, will occur less frequent in southern Europe. In contrast, in central Europe high‐end emission scenario climate projections show that droughts as intense as 2018 could become a common occurrence as early as 2043. While integrated European and global agricultural markets limited agro‐economic shocks caused by 2018's extremes, there is an urgent need for adaptation strategies for European agriculture to consider futures without the benefits of any water seesaw.

[1] Precipitation extremes are expected to increase in a warming climate; thus, it is essential to characterize their potential future changes. Here we evaluate eight highresolution global climate model simulations in the twentieth century and provide new evidence on projected global precipitation extremes for the 21st century. A significant intensification of daily extremes for all seasons is projected for the middle and high latitudes of both hemispheres at the end of the present century. For the subtropics and tropics, the lack of reliable and consistent estimations found for both the historical and future simulations might be connected with model deficiencies in the representation of organized convective systems. Low intermodel variability and good agreement with high-resolution regional observations are found for the twentieth century winter over the Northern Hemisphere middle and high latitudes. Citation: Toreti, A.,

In this work, the authors investigate possible changes in the distribution of heavy precipitation events under a warmer climate, using the results of a set of 20 climate models taking part in phase 5 of Coupled Model Intercomparison Project (CMIP5). Future changes are evaluated as the difference between the last four decades of the twenty-first century and the twentieth century, assuming the representative concentration pathway 8.5 (RCP8.5) scenario. As a measure of the width of the right tail of the precipitation distribution, the authors use the difference between the 99th and the 90th percentiles. Despite a slight tendency to underestimate the observed heavy precipitation, the considered CMIP5 models well represent the observed patterns in terms of the ensemble average, during both boreal summer and winter seasons for the 1997–2005 period. Future changes in average precipitation are consistent with previous findings based on models from phase 3 of CMIP (CMIP3). CMIP5 models show a projected increase for the end of the twenty-first century of the width of the right tail of the precipitation distribution, particularly pronounced over India, Southeast Asia, Indonesia, and central Africa during boreal summer, as well as over South America and southern Africa during boreal winter.

Agricultural production systems are sensitive to weather and climate anomalies and extremes as well as to other environmental and socio-economic adverse events. An adequate evaluation of the resilience of such systems helps to assess food security and the capacity of society to cope with the effects of global warming and the associated increase of climate extremes. Here, we propose and apply a simple indicator of resilience of annual crop production that can be estimated from crop production time series. First, we address the problem of quantifying resilience in a simplified theoretical framework, focusing on annual crops. This results in the proposal of an indicator, measured by the reciprocal of the squared coefficient of variance, which is proportional to the return period of the largest shocks that the crop production system can absorb, and which is consistent with the original ecological definition of resilience. Subsequently, we show the sensitivity of the crop resilience indicator to the level of management of the crop production system, to the frequency of extreme events as well as to simplified socio-economic impacts of the production losses. Finally, we demonstrate the practical applicability of the indicator using historical production data at national and sub-national levels for France. The results show that the value of the resilience indicator steeply increases with crop diversity until six crops are considered, and then levels off. The effect of diversity on production resilience is highest when crops are more diverse (i.e. as reflected in less well correlated production time series). In the case of France, the indicator reaches about 60% of the value that would be expected if all crop production time-series were uncorrelated.