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Inspired by concerns of the effects of a warming climate, drought variation and its impacts have gained much attention in China. Arguments about China's drought persist and little work has utilized agricultural drought survey area to evaluate the impact of natural drought on agriculture. Based on a newly revised self‐calibrating Palmer Drought Severity Index (PDSI) model driven with air‐relative‐humidity‐based two‐source (ARTS) E0 (PDSIARTS; Yan et al., 2014), spatial and temporal variations of drought were analyzed for 1982–2011 in China, which indicates that there was nonsignificant change of drought over this interval but with an extreme drought event happened in 2000–2001. However, using air temperature (Ta)‐based Thornthwaite potential evaporation (EP_Th) and Penman‐Monteith potential evaporation (EP_PM) to drive the PDSI model, their corresponding PDSITh and PDSIPM all gave a significant drying trend for 1982–2011. This suggests that PDSI model was sensitive to EP parameterization in China. Annual drought‐covered area from agriculture survey was initially adopted to evaluate impact of PDSI drought on agriculture in China during 1982–2011. The results indicate that PDSIARTS drought area (defined as PDSIARTS < −0.5) correlated well with the agriculture drought‐covered area and PDSIARTS successfully detected the extreme agriculture drought in 2000–2001 during 1982–2011, i.e., climate factors dominated the interannual changes of agriculture drought area, while PDSITh and PDSIPM drought areas had no relationship with the agriculture drought‐covered area and overestimated the uptrend of agriculture drought This study highlights the importance of coupling PDSI with drought survey data in evaluating the impact of natural drought on agriculture.

Vegetation effects are currently disregarded in Palmer Drought Severity Index (PDSI), and the sensitivity of PDSI to the choice of potential evaporation (E P ) parameterization is often a concern. We developed a revised self-calibrating PDSI model that replaces E P with leaf area index-based total evapotranspiration (ARTS E 0 ). It also included a simple snowmelt module. Using a unique satellite leaf area index data set and climate data, we calculated and compared ARTS E 0 , three other types of E P (i.e., Thornthwaite E P_Th , Allen E P_Al , and Penman-Monteith E P_PM ), and corresponding PDSI values (i.e., PDSI_ARTS, PDSI_Th, PDSI_Al, and PDSI_PM) for the period 1982-2011. The results of PDSI_ARTS, PDSI_Al, and PDSI_PM show that global land became wetter mainly due to increased precipitation and El Niño-Southern Oscillation (ENSO) effect for the period, which confirms the ongoing intensification of global hydrologic cycle with global temperature increase. However, only PDSI_Th gave a trend of global drying, which confirms that PDSI_Th overestimates the global drying in response to global warming; i.e., PDSI values are sensitive to the parameterizations for E p . Thus, ARTS E 0 , E P_Al , and E P_PM are preferred to E P_Th in global drought monitoring. In short, global warming affects global drought condition in two opposite ways. One is to contribute to the increases of E P and hence drought; the other is to increase global precipitation that contributes to global wetting. These results suggest that precipitation trend and its interaction with global warming and ENSO should be given much attention to correctly quantify past and future trends of drought.

The forest shelterbelt (afforestation) project in northern China is the most significant ecosystem project initiated in China during the past three decades. It aims to improve and conserve the ecological environment in the project areas. The tree belt stands along the southern edge of the sandy lands, nearly paralleling to the Great Wall. This study used a regional climate model to simulate the potential of improving regional hydroclimate conditions resulting from the afforestation project. Two simulations with preafforestation and postafforestation land cover were performed over East Asia from January 1987 to February 1988. The model resolution is 60 km. The differences between the two simulations suggest that the northern China forest shelterbelt project is likely to improve overall hydroclimate conditions by increasing precipitation, relative humidity, and soil moisture, and by reducing prevailing winds and air temperature. The effects are more significant in spring and summer than fall and winter. Changes in many hydrologic properties (e.g., evapotranspiration, soil moisture, and water yield), however, differ between the dry Northeast China and the moist Northeast China. The hydroclimate effects are also found in the surrounding areas, featured by noticeably moister conditions in the area south of the afforestation project. The results imply that the shelterbelt project would reduce water yield in afforested Northwest and North China during spring, but increase water yield in the afforested Northeast China as well as in the southern surrounding area, offset some greenhouse effects, and reduce the severity of dust storms. Possible improvements of this study by using actual afforestation data, modeling with higher resolution, longer integration and more detailed processes, and analyzing the physical mechanisms are discussed.

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