Over the past 50 years, the climate has changed rapidly with global warming and land surface drying, which has been accompanied by increased forest loss and damage resulting from pests and diseases. Climate data (e.g., air temperature, relative humidity, and sunshine data) from 1961 to 2010 showed that the climate in the Jiangxi Province was warming significantly, with the annual mean temperature increasing by 0.16℃ per 10 years, and the winter mean temperature rising by 0.27℃ per 10 years. The Jiangxi Province climate was also drying throughout this period (annual mean relative humidity decreased -0.45% per 10 years). In addition, forest pests and disease occurrence from 1992 to 2010 showed that in Jiangxi, the area affected by of forest diseases and pests increased significantly, with 58,125 hm² per 10 years. Pearson correlation and principal component analyses showed that 16 (for forest diseases) or 17 (for forest pests) climate elements were significantly related to the forest loss. From these individual elements, the most positively correlated was a 9-year sliding average of summer mean temperature, and the most negatively correlated component was a 9-year sliding average of hydrothermal coefficient (annual mean temperature/annual mean relative humidity). Amongst the four or five principal components, the variables temperature and temperature-humidity contributed most to explaining forest area loss (41.43% and 42.0%, respectively). In stepwise regression analyses, three optimal regression models (Total:Y=3.582×106 -7.750×10⁵X, forest pest:Y=-6.375×10⁵X+2.95×10⁶, forest diseases:Y=-1.375×10⁵X+6.321×10⁵) were analyzed to describe the forest loss (Y) by the 9-year sliding average of temperature humidity coefficient (X). The three models showed a linear fit of 77.9%, 79.1%, and 56.7% and a prediction accuracy of 66.2%, 68.6%, and 47.9%, respectively. A declining trend in the sliding average of temperature humidity coefficient was observed over the past 50 years, for which the anomaly transferred from positive to negative in 1993. This indicates that climate warming and droughts could have aggravated the forest loss and damage over the past 50 years, especially after 1990s. A wavelet analysis showed a 29-year periodicity in the temperature humidity coefficient. If this anomaly started in 1993, the forest loss trend could potentially be relieved by the end of 2022. In Jiangxi, the temperature humidity coefficient significantly increases from the south to the north, suggesting that forest diseases and pest disasters should be more extreme in Gan Nan than in other areas. In addition, since the change rate of climate warming or drought was higher in Gan Dong and Gan Bei, a high variability of forest diseases and pest disasters can be expected there in the future. Overall, our results suggest that climate warming and environmental drought aggravates forest diseases and pest disasters in Jiangxi. They furthermore emphasize that Gan Nan could be a key area in preventing and controlling the effects of forest diseases and pest disasters, whereas the monitoring efforts in Gan Dong and Gan Bei should be increased.