Jingyong Zhang

New evidence for effects of land cover in China on summer climate

The effects of land cover in different regions of China on summer climate are studied by lagged correlation analysis using NOAA/AVHRR normalized difference vegetation index (NDVI) data for the period of 1981–1994 and temperature, precipitation data of 160 meteorological stations in China. The results show that the correlation coefficients between NDVI in previous season and summer precipitation are positive in most regions of China, and the lagged correlations show a significant difference between regions. The stronger correlations between NDVI in previous winter and precipitation in summer occur in Central China and the Tibetan Plateau, and the correlations between spring NDVI and summer precipitation in the eastern arid/semiarid region and the Tibetan Plateau are more significant. Vegetation changes have more sensitive feedback effects on climate in the three regions (eastern arid/semi-arid region, Central China and Tibetan Plateau). The lagged correlations between NDVI and precipitation suggest that, on interannual time scales, land cover affects summer precipitation to a certain extent. The correlations between NDVI in previous season and summer temperature show more complex, and the lagged responses of temperature to vegetation are weaker compared with precipitation, and they are possibly related to the global warming which partly cover up the correlations.

The role of May vegetation greenness on the southeastern Tibetan Plateau for East Asian summer monsoon prediction

Received 21 September 2010; revised 11 December 2010; accepted 3 January 2011; published 5 March 2011. [1] It is well known that the slowly varying oceanic processes provide the primary source for East Asian summer monsoon (EASM) predictability. However, the memory inherent in the land surface state is less well understood or applied toward the EASM prediction. Here we investigate the role of antecedent vegetation conditions over East Asia for the EASM variation and prediction using March, April, May, and spring mean satellite‐sensed Normalized Difference Vegetation Index (NDVI) for the period of 1982–2006. Results show that May vegetation greenness on the southeastern Tibetan Plateau (TP) is most closely linked to the EASM, accounting for about half of the total EASM variance. May vegetation greenness on the southeastern TP has significant and positive correlations with summer rainfall over the southeastern TP, East Asian summer subtropical frontal region, and many areas of northern China. We further discuss the possible physical mechanism explaining our findings. It is proposed that increased TP vegetation greenness enhances surface thermal effects, which subsequently warm atmospheric temperature, as well as strengthen ascending motion, convergence at the lower layers and divergence at the higher layers, and summer monsoon circulation. Finally, a linear regression model is developed to predict the EASM strength by combination of El Nino–Southern Oscillation (ENSO) and the vegetation greenness. Hindcast for the period 1982–2006 shows that the use of the southeastern TP vegetation information can highly improve the EASM prediction skill compared to that using ENSO alone.

Asymmetric effects of soil moisture on mean daily maximum and minimum temperatures over eastern China

This study statistically investigates the effects of soil moisture on mean daily maximum (

Skillful prediction of hot temperature extremes over the source region of ancient Silk Road

T_{\rm{max} }

Assessing land‐atmosphere coupling using soil moisture from the Global Land Data Assimilation System and observational precipitation

Tmax) and minimum temperatures (

Contribution of land‐atmosphere coupling to summer climate variability over the contiguous United States

T_{\rm{min} }