In northeastern China, over the last four decades, global warming has resulted in a decrease in precipitation and increase in temperature that have intensified evaporation, resulting in a decline in soil moisture. Dew is a crucial factor in the water and nutrient cycle of urban ecosystems; thus, could exert considerable influence on the water cycle by affecting the vapor condensation. To reveal the effects of global warming on dew variation in urban ecosystems, dew was monitored daily using poplar wooden sticks, asphalt blocks, and soil blocks in the complex urban landscapes of Changchun, northeastern China. A correlation analysis was conducted between meteorological factors and dew intensity in greenbelt areas of the urban ecosystem. The results indicated that dew intensity correlated positively with relative humidity, dew point temperature, air temperature, wind chill temperature, and solar radiation (n=254, P<0.01), whereas it correlated negatively with PM_2.5, PM₁₀, air quality index, nocturnal wind speed, and atmospheric pressure (n=254, P<0.01). During the monitoring period, there were 132-136 dew days per year, which accounted for 62.5% of the frost-free season in Changchun. Substrate plays a notable roll in the formation of dew, and at night, dew intensity showed different patterns among the various landscapes. The landscapes in descending order of average dew intensity were greenbelt (0.0607 mm), bare land (0.0100 mm), and roads (0.0049 mm) (P<0.01). Dew plays an important role in the greenbelt water balance and the dewfall in July, August, and September was equal to 22.52% and 23.61% of the rainfall for the same period in 2014 and 2015, respectively. According to the proportion of each landscape, dewfall was 23-25 mm/ac in Changchun. The results suggested that increased vegetation coverage could enhance the amount of water vapor available to condense on the ground surface. However, water could not condense if the proportion of the urban greenbelt area was reduced to 5%. Based on synchronous meteorological data, a stepwise linear multiple regression model was established to predict the dew amount. The model successfully revealed the relationship between simulated and measured dew intensities. The results suggested that a warmer and drier climate would not lead to a substantial reduction in dew. Combining the model and climate data for the study area from 1965-2015 during the dew condensation period, annual dewfall showed a decreasing trend of -1.07 mm/10 ac (P<0.01). However, under the mutual influence of relative humidity, wind speed, and solar radiation, the impact of climate change on dew condensation was not obvious. The present study developed a method for monitoring and calculating dew on different underlying surfaces of an urban ecosystem, and it improved the system of dew surveillance. The established empirical model could be used to predict dew intensity and help clarify the impact of climate change on the near-surface water cycle.