Abstract
Episodes of heat stress constrain crop production and will be aggravated in the near future according to short and medium-term climate scenarios. Global increase in cloudiness has also been observed, decreasing the incident solar radiation. This work was aimed to quantify the probability of occurrence of heat stress and cloudiness, alone or combined, during the typical post-flowering period of wheat and canola in the Southern Cone of South America. Extended climate series (last 3-5 decades with daily register) of 33 conventional weather stations from Argentina, Brazil, Chile and Uruguay (23ºS to 40ºS) were analysed considering the period from September to December. Two different daily events of heat stress were determined: i) maximum daily temperature above 30ºC (T>30ºC), and ii) 5ºC above the historical average maximum temperature of that day (T+5ºC). A cloudiness event was defined in our work as incident solar radiation 50% lower than the historical average radiation of that day (R50%). The T>30ºC event increased its probability of occurrence throughout the post-flowering phase, from September to December. By contrast, the risk of T+5ºC event decreased slightly, just like for R50%, and the higher the latitude, the lower the probability of R50%. The T>30ºC plus R50% combined stresses reached greater cumulated probabilities during post-flowering, compared to T+5ºC plus R50%, being 42% vs. 15% in northernmost locations, 26% vs. 19% in central (between 31ºS to 35ºS), and 28% vs. 1% in southernmost locations, respectively. A curvilinear relationship emerged between the monthly probability of combined stresses and the number of days with stress per month. In summary, T>30ºC was the most frequent thermal stress during post-flowering in wheat and canola. Both combined stresses had a noticeable risk of occurrence, but T>30ºC plus R50% was the highest. Evidence of the recent past and current occurrence of heat stress individually, and its combination with cloudiness events during post-flowering of temperate crops, serves as a baseline for future climate scenarios in main cropped areas in the Southern Cone of South America.
Utilising Open Geospatial Data to Refine Weather Variables for Building Energy Performance Evaluation—Incident Solar Radiation and Wind-Driven Infiltration Modelling
