Cause, conseguenze e strategie di mitigazione Proponiamo il primo di una serie di articoli in cui affronteremo l’attuale problema dei mutamenti climatici. Presentiamo il documento redatto, votato e pubblicato dall’Ipcc - Comitato intergovernativo sui cambiamenti climatici - che illustra la sintesi delle ricerche svolte su questo tema rilevante.

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Climate Change 2007: The Physical Science Basis.

Exploring the relationships between climatic variables and climate-induced yield of spring maize in Northeast China

For Africa’s developing countries the agricultural system is among the most vulnerable due to extensive use of rainfed crop production, presence of droughts and floods that affect crops as well as initial poverty of population that limits the capacity to adapt. In this study were realized the analysis of long-term rainfall data and its impact on main crop products in Rwanda. Some rainfall data was infilled for the period of 1926-2013. It was done using the monitoring data of a neighbor weather station with relatively the same elevation above sea level and with a monitoring record of no less than 40 years. The neighboring station with the best correlation was selected for the infilling. The missing rainfall data was infilled for all the stations with resulting regression coefficients ranging from 0.55 to 0.80. This indicates the acceptability of the performed regression. Also were constructed different-cumulative curves of rainfall and sort out cycles of decline and increment of rainfall. Similar different-cumulative curves were constructed for main crops in Rwanda. Correlation and regression analysis were used to determine the relationship between rainfall, arable land expansion, fertilizer use and crop yield. Particularly for Rwandan conditions, the rainfall variations are determinant for the crop yield increment. The intensification of extreme flood’s and, as rule, flooding of agricultural lands in connection with rainfall augmentation was also allocated.

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Effect of Climate Change on Crop Production in Rwanda

Coincidence of variation in potato yield and climate in northern China.

With the increasing risk of meteorological disasters, it is of great importance to analyze the spatiotemporal changes of precipitation extremes and its possible impact on rice productivity, especially in Jiangsu province, southeast China. In this study, we explored the relationships between rice yield and extreme precipitation indices using Mann-Kendall trend test, Pettitt's test, and K-means clustering methods. This study used 10 extreme precipitation indices of the rice growing season (May to October) based on the daily precipitation records and rice yield data at 52 meteorological stations during 1961-2012 in Jiangsu province. The main findings were as follows: (1) correlation results indicated that precipitation extremes occurred in the months of July, August, and October, which had noticeable adverse effects on rice yield; (2) the maximum 7-day precipitation of July and the number of rainy days of August and October should be considered as three key indicators for the precipitation-induced rice meteorological disasters; and (3) most of the stations showed an increasing trends for the maximum 7-day precipitation of July and the number of rainy days of August, while the number of rainy days of October in all the stations demonstrated a decreasing trend. Moreover, Jiangsu province could be divided into two major sub-regions such as north and south areas with different temporal variations in the three key indicators.

Spatiotemporal analysis the precipitation extremes affecting rice yield in Jiangsu province, southeast China.

A new methodology to extract crop yield response to climate variability and change from long-term crop yield observations is presented in this study. In contrast to the existing first-difference approach (FDA), the proposed methodology considers that the difference in value between crop yields of two consecutive years reflects necessarily the contributions of climate and management conditions, especially at large spatial scales where both conditions may vary significantly from one year to the next. Our approach was applied to remove the effect of non-climatic factors on crop yield and, hence, to isolate the effect of the observed climate change between 1961 and 2006 on three widely crops grown in three Mediterranean countries—namely wheat, corn and potato—using national-level crop yield observations’ time-series. Obtained results show that the proposed methodology provides us with a ground basis to improve substantially our understanding of crop yield response to climate change at a scale that is relevant to large-scale estimations of agricultural production and to food security analyses; and therefore to reduce uncertainties in estimations of potential climate change effects on agricultural production. Furthermore, a comparison of outputs of our methodology and FDA outputs yielded a difference in terms of maize production in Egypt, for example, that exceeds the production of some neighbouring countries.

https://www.mdpi.com/2073-4433/4/4/365/pdf

Mustapha El-Maayar

Papers

A Methodology to Infer Crop Yield Response to Climate Variability and Change Using Long-Term Observations