This study assesses the climate impact on the productivity of five sugarcane varieties (R579, SP711406, M2593/92, M1400/86, and SP701006) in the industrial plantations of Ferké 1 sugar complex. It is a contributi...This study assesses the climate impact on the productivity of five sugarcane varieties (R579, SP711406, M2593/92, M1400/86, and SP701006) in the industrial plantations of Ferké 1 sugar complex. It is a contribution to research efforts aimed at increasing the productivity of sugarcane varieties in the sugar fields. Also to support agricultural development and guarantee the income of planters. The sugarcane production data are from 2013 to 2017. Climatological data are measured and calculated continuously daily at the production site. In addition, the CMIP-5 (Coupled Model Intercomparison Project) climate database at 1<sup></sup><sup>º </sup>× 1<sup>º</sup> horizontal resolution was used for the predictability of crop yields of the 5 sugarcane varieties in the near future (2021-2050) and far future (2056-2075) to improve the quality of climate services to producers. The statistical methodological approach by multiple linear regression associated with the significativity test shows important and significant coefficients of determination (R<sup>2</sup> > 0.90) between the yields of sugarcane varieties with certain climatic parameters such as minimum and maximum temperatures, insolation, global solar radiation, and potential evapotranspiration. The impact of rainfall has not been directly evaluated because the linear models do not explicitly show sensitivities to this parameter and the total water requirements for the plot are completely assured by irrigation. The future climate projections analyzed only from extreme thermal parameters (Tmax and Tmin) highlight their strong sensitivities with yields from an idealized model. In this model, we have assumed that the water supply needed by sugarcane is always met by irrigation on different plots. Moreover, linear models do not evolve fast enough in time and changes due to external environmental constraints are not too important at the plot scale. The projected thermic parameters can thus constitute a limiting factor for the producibility of sugarcane varieties either by excess or by default. In addition, the linear models used allowed us to observe the behavior of yields with respect to observed past climatic conditions. However, for future yields, there is no way to know if these regressions have the ability to predict them since they are based on projected weather conditions (i.e. CMIP5 data) marked by uncertainties. Additionally, none of the regression equations have been tested against independent observations.展开更多
This study aims to understand the current climatic trends and explain the possible losses of agricultural yields. To achieve this objective, this work characterized the evolution of extreme temperature indices in the ...This study aims to understand the current climatic trends and explain the possible losses of agricultural yields. To achieve this objective, this work characterized the evolution of extreme temperature indices in the sugar complexes of Ferké 1 and Ferké 2, two stations located in the northern part of C?te d'Ivoire. The onset and cessation dates of the rainy season and the length of the rainy season were investigated. The agricultural and climatic data were obtained from each sugar complex. The period of study ranges from 2002 to 2019 in Ferké 1 and Ferké 2. The results show significant upward trends in extreme temperature indices. The analysis of sugarcane yield associated with the different climatic parameters shows no significant results in general. However, on the Ferkessédougou sugar complexes, the results highlight that maximum and minimum temperatures could be the variables that influence most yield production. The maximum temperature with coefficients of 1.60 and 0.77 at Ferké 1 and Ferké 2 respectively seems to contribute to an increase in yield while the minimum temperature with coefficients of -0.98 and -0.22 at Ferké 1 and Ferké 2 respectively could lead to a loss in yield. The results obtained with the Single Linear Regression (SLR) and the Multiple Linear Regression (MLR) models also highlight the strong influence of minimum and maximum temperatures.展开更多
The squall line of 21-22 August 1992, documented during the HAPEX-Sahel campaign, is simulated using the regional atmospheric model (MAR). The simulated results are compared to observational data. The aim of this work...The squall line of 21-22 August 1992, documented during the HAPEX-Sahel campaign, is simulated using the regional atmospheric model (MAR). The simulated results are compared to observational data. The aim of this work is both to test the capacity of this model to reproduce tropical disturbances in West Africa and to use this model as a meteorological one. It allows simulating high moisture content in the lower layers. The MAR simulates well updrafts whereas downward currents are neglected. This result may be due to convective scheme used to parameterize the convection in the model. The forecast of stability indexes used to define violent storms shows that the model is able to reproduce the squall line. Despite some differences with the observational data, the model shows its ability to reproduce major characteristics of the mesoscale convective disturbances.展开更多
文摘This study assesses the climate impact on the productivity of five sugarcane varieties (R579, SP711406, M2593/92, M1400/86, and SP701006) in the industrial plantations of Ferké 1 sugar complex. It is a contribution to research efforts aimed at increasing the productivity of sugarcane varieties in the sugar fields. Also to support agricultural development and guarantee the income of planters. The sugarcane production data are from 2013 to 2017. Climatological data are measured and calculated continuously daily at the production site. In addition, the CMIP-5 (Coupled Model Intercomparison Project) climate database at 1<sup></sup><sup>º </sup>× 1<sup>º</sup> horizontal resolution was used for the predictability of crop yields of the 5 sugarcane varieties in the near future (2021-2050) and far future (2056-2075) to improve the quality of climate services to producers. The statistical methodological approach by multiple linear regression associated with the significativity test shows important and significant coefficients of determination (R<sup>2</sup> > 0.90) between the yields of sugarcane varieties with certain climatic parameters such as minimum and maximum temperatures, insolation, global solar radiation, and potential evapotranspiration. The impact of rainfall has not been directly evaluated because the linear models do not explicitly show sensitivities to this parameter and the total water requirements for the plot are completely assured by irrigation. The future climate projections analyzed only from extreme thermal parameters (Tmax and Tmin) highlight their strong sensitivities with yields from an idealized model. In this model, we have assumed that the water supply needed by sugarcane is always met by irrigation on different plots. Moreover, linear models do not evolve fast enough in time and changes due to external environmental constraints are not too important at the plot scale. The projected thermic parameters can thus constitute a limiting factor for the producibility of sugarcane varieties either by excess or by default. In addition, the linear models used allowed us to observe the behavior of yields with respect to observed past climatic conditions. However, for future yields, there is no way to know if these regressions have the ability to predict them since they are based on projected weather conditions (i.e. CMIP5 data) marked by uncertainties. Additionally, none of the regression equations have been tested against independent observations.
文摘This study aims to understand the current climatic trends and explain the possible losses of agricultural yields. To achieve this objective, this work characterized the evolution of extreme temperature indices in the sugar complexes of Ferké 1 and Ferké 2, two stations located in the northern part of C?te d'Ivoire. The onset and cessation dates of the rainy season and the length of the rainy season were investigated. The agricultural and climatic data were obtained from each sugar complex. The period of study ranges from 2002 to 2019 in Ferké 1 and Ferké 2. The results show significant upward trends in extreme temperature indices. The analysis of sugarcane yield associated with the different climatic parameters shows no significant results in general. However, on the Ferkessédougou sugar complexes, the results highlight that maximum and minimum temperatures could be the variables that influence most yield production. The maximum temperature with coefficients of 1.60 and 0.77 at Ferké 1 and Ferké 2 respectively seems to contribute to an increase in yield while the minimum temperature with coefficients of -0.98 and -0.22 at Ferké 1 and Ferké 2 respectively could lead to a loss in yield. The results obtained with the Single Linear Regression (SLR) and the Multiple Linear Regression (MLR) models also highlight the strong influence of minimum and maximum temperatures.
文摘The squall line of 21-22 August 1992, documented during the HAPEX-Sahel campaign, is simulated using the regional atmospheric model (MAR). The simulated results are compared to observational data. The aim of this work is both to test the capacity of this model to reproduce tropical disturbances in West Africa and to use this model as a meteorological one. It allows simulating high moisture content in the lower layers. The MAR simulates well updrafts whereas downward currents are neglected. This result may be due to convective scheme used to parameterize the convection in the model. The forecast of stability indexes used to define violent storms shows that the model is able to reproduce the squall line. Despite some differences with the observational data, the model shows its ability to reproduce major characteristics of the mesoscale convective disturbances.
