Impacts of extreme weather on wheat and maize in France: evaluating regional crop simulations against observed data

Extreme weather conditions can strongly affect agricultural production, with negative impacts that can at times be detected at regional scales. In France, crop yields were greatly influenced by drought and heat stress in 2003 and by extremely wet conditions in 2007. Reported regional maize and wheat yields where historically low in 2003; in 2007 wheat yields were lower and maize yields higher than long-term averages. An analysis with a spatial version (10?×?10?km) of the EPIC crop model was tested with regards to regional crop yield anomalies of wheat and maize resulting from extreme weather events in France in 2003 and 2007, by comparing simulated results against reported regional crops statistics, as well as using remotely sensed soil moisture data. Causal relations between soil moisture and crop yields were specifically analyzed. Remotely sensed (AMSR-E) JJA soil moisture correlated significantly with reported regional crop yield for 2002–2007. The spatial correlation between JJA soil moisture and wheat yield anomalies was positive in dry 2003 and negative in wet 2007. Biweekly soil moisture data correlated positively with wheat yield anomalies from the first half of June until the second half of July in 2003. In 2007, the relation was negative the first half of June until the second half of August. EPIC reproduced observed soil dynamics well, and it reproduced the negative wheat and maize yield anomalies of the 2003 heat wave and drought, as well as the positive maize yield anomalies in wet 2007. However, it did not reproduce the negative wheat yield anomalies due to excessive rains and wetness in 2007. Results indicated that EPIC, in line with other crop models widely used at regional level in climate change studies, is capable of capturing the negative impacts of droughts on crop yields, while it fails to reproduce negative impacts of heavy rain and excessively wet conditions on wheat yield, due to poor representations of critical factors affecting plant growth and management. Given that extreme weather events are expected to increase in frequency and perhaps severity in coming decades, improved model representation of crop damage due to extreme events is warranted in order to better quantify future climate change impacts and inform appropriate adaptation responses.     

Assessment of global warming on the island of Tenerife, Canary Islands (Spain). Trends in minimum, maximum and mean temperatures since 1944

Temperature variation is studied at different altitudes and orientation on the island of Tenerife, according to the trends in the mean, maximum and minimum at 21 meteorological stations. Reference series are obtained by sectors, along with a representative overall series for Tenerife, in which temperature shows a statistically significant growth trend of 0.09?±?0.04°C/decade since 1944. Night-time temperatures have risen most (0.17°C?±?0.04°C/decade), while by day they have been more stable. Consequently, the diurnal temperature range between day and night has narrowed. By regions, warming has been much more intense in the high mountains than the other sectors below the inversion layer between 600 and 1,400?m altitude, and progressively milder towards the coast. The temperature rise on the windward (north-northeast) slopes is greater than on the leeward side and could be related to the increase in cloudiness on the northern side. The general warming of the island is less than in continental areas at between 24 and 44oN, being closer to the sea surface temperature in the same area. This is probably explained largely by the insular conditions. In fact warming is more evident in the high mountains (0.14?±?0.07°C/decade), where the tempering effect of the ocean and the impact of changes in the stratocumulus is weaker, being similar to the mean continental values in the northern hemisphere.     

The bimodal downslope windstorms at Kvísker

Downslope windstorms at Kvísker in Southeast Iceland are explored using a mesoscale model, observations and numerical analysis of the atmosphere. Two different types of gravity-wave induced windstorms are identified. At the surface, their main difference is in the horizontal extent of the lee-side accelerated flow. Type S (Short) is a westerly windstorm, which is confined to the lee-slopes of Mount ?r?faj?kull, while a Type E (Extended) windstorm occurs in the northerly flow and is not confined to the lee-slopes but continues some distance downstream of the mountain. The Type S windstorm may be characterized as a more pure gravity-wave generated windstorm than the Type E windstorm which bears a greater resemblance to local flow acceleration described by hydraulic theory. The low-level flow in the Type E windstorm is of arctic origin and close to neutral with an inversion well above the mountain top level. At middle tropospheric levels there is a reverse vertical windshear. The Type S windstorm occurs in airmasses of southerly origin. It also has a well-mixed, but a shallower boundary-layer than the Type E windstorms. Aloft, the winds increase with height and there is an amplified gravity wave. Climate projections indicate a possible decrease in windstorm frequency up to the year 2050.     

CO2 dilution in the lower atmosphere from temperature and wind speed profiles

Temperature and wind speed profiles obtained from 3?years of radio acoustic sounding system sodar measurements at a rural site in the northern Spanish plateau were fitted to polynomial functions. Depending on the extrema of these fits, several groups of profiles were considered. Daily evolution of temperature profiles corresponded to the lower boundary layer evolution. However, wind speed profiles revealed a frequent low-level jet during the whole day. CO₂ surface concentrations were analysed, and surface CO₂ dilution was also considered by selection of thin canopies with variable depth, resulting in dilution rates of 7 and 18?ppm when the layer increased 100?m for the 95th percentile and temperature and wind speed profiles, respectively.     

A seasonal study of the atmospheric dynamics over the Iberian Peninsula based on circulation types

A seasonal analysis of the atmospheric circulation over the Iberian Peninsula (IP) based on circulation types (CTs) obtained from sea level pressure and 500-hPa geopotential height is presented. The study covers the period of 1958–2008, when a high variability and important changes in winter and spring precipitation and temperature have been reported. Frequency, persistence, and the most probable transitions of the circulation types are analyzed. Among the clustering methods available in the literature, two of the most reliable classification methods have been tested, K-means and simulated annealing and diversified randomization. A comparison of both methods over the IP is presented for winter (DJF). The quality of the circulation types obtained through both methods as well as the better stability achieved by K-means suggest this method as more appropriated for our target area. Twelve CTs were obtained for each season and were analyzed. The patterns obtained were regrouped in five general situations: anticyclonic, cyclonic, zonal, summertime, and hybrid-mixed. The analysis of frequencies of these situations offers a similar characterization of the atmospheric circulation that others previously obtained by subjective methods. The analysis of the trends in frequency and persistence for each CT shows few significant trends, mainly in winter and spring with a general decrease of the cyclonic patterns and an increase of the anticyclonic situations. This can be related to the negative precipitation trends reported by other authors. Regarding the persistence, an interesting result is that there is a high interannual variability of the persistence in autumn and spring, when patterns can persist longer than in other seasons. An analysis of the most probable transitions between the CTs has been performed, revealing the existence of cyclic sequences in all seasons. These sequences are related to the high frequency of certain patterns such as the anticyclonic situations in winter. Finally, a clear seasonal dependence of the transitions between cyclonic situations associated with extratropical disturbances was found. This dependence suggests that the transitions of low-pressure systems towards the south of the IP are more likely in spring and autumn than in winter.     

Recent trends in mean maximum and minimum air temperatures over Spain (1961–2006)

This study analyzes the mean maximum and minimum temperature trends on a monthly, seasonal, and annual timescale by applying various statistical tools to data from 476 Spanish weather stations during the period between 1961 and 2006. The magnitude of the trends was derived from the slopes of the regression lines using the least squares method, and the nonparametric Mann–Kendall test was used to determine the statistical significance of the trends. Temperature significantly increased in over 60% of the country in March, June, spring, and summer in the case of maximum temperatures and in March, May, June, August, spring, and summer for minimum temperatures. At the annual resolution, temperatures significantly increased in over 90% of Spain with a rise of around 0.3°C/decade. The maximum temperature increased at a higher rate than the minimum temperature from midsummer to early winter as well as in winter, spring, and summer and also on an annual basis.     

North Atlantic atmospheric circulation and surface wind in the Northeast of the Iberian Peninsula: uncertainty and long term downscaled variability

The variability and predictability of the surface wind field at the regional scale is explored over a complex terrain region in the northeastern Iberian Peninsula by means of a downscaling technique based on Canonical Correlation Analysis. More than a decade of observations (1992–2005) allows for calibrating and validating a statistical method that elicits the main associations between the large scale atmospheric circulation over the North Atlantic and Mediterranean areas and the regional wind field. In an initial step the downscaling model is designed by selecting parameter values from practise. To a large extent, the variability of the wind at monthly timescales is found to be governed by the large scale circulation modulated by the particular orographic features of the area. The sensitivity of the downscaling methodology to the selection of the model parameter values is explored, in a second step, by performing a systematic sampling of the parameters space, avoiding a heuristic selection. This provides a metric for the uncertainty associated with the various possible model configurations. The uncertainties associated with the model configuration are considerably dependent on the spatial variability of the wind. While the sampling of the parameters space in the model set up moderately impact estimations during the calibration period, the regional wind variability is very sensitive to the parameters selection at longer timescales. This fact illustrates that downscaling exercises based on a single configuration of parameters should be interpreted with extreme caution. The downscaling model is used to extend the estimations several centuries to the past using long datasets of sea level pressure, thereby illustrating the large temporal variability of the regional wind field from interannual to multicentennial timescales. The analysis does not evidence long term trends throughout the twentieth century, however anomalous episodes of high/low wind speeds are identified.     

Origin and source regions of PM10 in the Eastern Mediterranean atmosphere

A set of daily PM₁₀ (n = 281) samples collected from April 2001 to April 2002 at a rural site (Erdemli), located on the coast of the Eastern Mediterranean, were analyzed applying Mass Closure (MC), absolute principal factor analysis (APFA) and Positive Matrix Factorization (PMF) to determine source contributions. The results from the three techniques were compared to identify the similarities and differences in the sources and source contributions. Source apportionment analysis indicated that PM₁₀ were mainly originated from natural sources (sea salt + crustal ≈ 60%) whilst secondary aerosols and residual oil burning accounted for approximately 20% and 10% of the total PM₁₀ mass, respectively. Calculations for sulfate showed that on average 8% and 12% of its total concentration were originated from sea salt and biogenic emissions, respectively. However, the contribution by biogenic emissions may reach up to a maximum of ~ 40% in the summer. Potential Source Contribution Function (PSCF) analysis for identification of source regions showed that the Saharan desert was the main source area for crustal components. For secondary aerosol components the analysis revealed one source region, (i.e. the south-Eastern Black Sea), whereas for residual oil, Western Europe and the western Balkans areas were found to be the main source regions.     

Interannual to decadal variations of precipitation and daily maximum and daily minimum temperatures in southern Brazil

The interannual to decadal variability of precipitation and daily maximum and daily minimum temperature (TMAX and TMIN) in southern Brazil for the 1913–2006 period is investigated using indices for these variables. Relations of these indices and the sea surface temperature (SST) variability in the eastern equatorial Pacific (Niño 3.4 index) and southwestern subtropical Atlantic (SSA index) are also investigated. Analyses are based on the Morlet wavelet transform. The interannual precipitation variability during the 1913–2006 period is mostly due to the high variances that occurred in specific sub-periods. The TMAX and TMIN indices also show significant interannual variability. The coherency and phase difference analyses of the precipitation index and the SST indices show higher coherency with the Niño 3.4 than with the SSA index. On the other hand, examining the coherencies and phase difference between the temperature indices and the SST indices, weaker coherencies with the Niño 3.4 index than with the SSA index are noted. These differences are discussed in the context of previous results. The new results here, with possible application for climate monitoring tasks, refer to the spectral differences between TMIN and TMAX.