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The sensitivity analysis of genetic coefficients used in the productivity simulation of sugarcane by Canegro/DSSAT model (CD) was performed in order to identify which parameters have most relevance in the model calibration. The CD uses 20 parameters that aim to capture the differences between the varieties of sugarcane. The sensitivity analysis has been developed varying one parameter at a time within a certain range and keeping the others constant. Were simulated the stalk dry weight, leaf area index of green leaves and sucrose dry weight at the end of each crop cycle in a period of twenty years, between 1995 and 2014, considering three planting dates, August 01, September 01 and 01 October. The simulations were made to the city of Pelotas -RS and the results were evaluated by the standard deviation (D). The results show that genetic coefficients with great sensitivity in the simulation of the stalk dry weight were PARCEmax (D ≈ 6 t.ha -1 ) and STKPFmax (D ≈ 5 t.ha -1 ). In the sucrose dry weight simulation, the genetic coefficients with higher sensitivity were PARCEmax (D ≈ 3,5 t.ha -1 ) and STKPFmax (D ≈ 3 t.ha -1 ). In the simulation of the maximum leaf area index, the more sensitive genetic coefficients were LFMAX (D ≈ 2 cm 2 .cm -2 ), TT_POPGROWTH (D ≈ 1,4 cm 2 .cm -2 ) and Mxlfarea (D ≈ 1 cm 2 .cm -2 ). The results also show that differences in the planting date have influence in the sensitivity of genetic coefficients. Keywords: Sensitivity analysis; genetic coefficents; canegro; sugarcane Resumo A análise de sensibilidade dos coeficientes genéticos utilizados na simulação de produtividade da cana de açúcar pelo modelo Canegro/DSSAT (CD) foi realizada com o objetivo de identificar quais parâmetros tem maior relevância na calibração do modelo. O CD faz uso de 20 parâmetros que têm como objetivo capturar as diferenças entre as cultivares de cana-de-açúcar. A análise de sensibilidade foi desenvolvida variando um parâmetro por vez dentro de um determinado intervalo e mantendo os demais constantes. Foram simulados o peso seco do colmo, índice de área foliar de folhas verdes e peso seco de sacarose ao final de cada ciclo de cultivo em um período de vinte anos, entre 1995 e 2014, considerando três datas de plantio, 01 de agosto, 01 de setembro e 01 de outubro. As simulações foram feitas para o município de Pelotas -RS e os resultados foram avaliados pelo desvio padrão (D

Bioenergy from sugarcane production is considered a key mitigation strategy for global warming. Improving its representation in land surface models is important to further understand the interactions between climate and bioenergy production, supporting accurate climate projections and decision‐making. This study aimed to calibrate and evaluate the Joint UK Land Environment Simulator (JULES) for climate impact assessments in sugarcane. A dataset composed of soil moisture, water and carbon fluxes and biomass measurements from field experiments across Brazil was used to calibrate and evaluate JULES‐crop and JULES‐BE parametrizations. The ability to predict the spatiotemporal variability of sugarcane yields and the impact of climate change was also tested at five Brazilian microregions. Parameters related to sugarcane allometry, crop growth and development were derived and tested for JULES‐crop and JULES‐BE, together with the response to atmospheric carbon dioxide, temperature and low‐water availability (CTW‐response). Both parametrizations showed comparable performance to other sugarcane dynamic models, with a root mean squared error of 6.75 and 6.05 t ha−1 for stalk dry matter for JULES‐crop and JULES‐BE, respectively. The parametrizations were also able to replicate the average yield patterns observed in the five microregions over 30 years when the yield gap factors were taken into account, with the correlation (r) between simulated and observed interannual variability of yields ranging from 0.33 to 0.56. An overall small positive trend was found in future yield projections of sugarcane using the new calibrations, with exception of the Jataí mesoregion which showed a clear negative trend for the SSP5 scenario from the years 2070 to 2100. Our simulations showed that an abrupt negative impact on sugarcane yields is expected if daytime temperatures above 35°C become more frequent. The newly calibrated version of JULES can be applied regionally and globally to help understand the interactions between climate and bioenergy production.