Empirical orthogonal function (EOF) and correlation analyses were employed to investigate the winter and spring snow depth in Eurasia and its relationship with Eastern China precipitation based on the observed and reanalyzed data from 1980 to 2016. The results show that the winter and spring snow cover in Eurasia not only highlights a decreasing trend due to global warming (the first EOF mode, its variance accounted for 24.4%...

Accurate representation of soil and snow state variables in the land surface model is crucial for good simulation results. In order to investigate the potential impacts of the overestimated snow cover over the Tibetan Plateau (TP) on precipitation over China, we designed comparative experiments over TP with and without updated soil texture data, soil hydrological parameters, and the fresh snow density scheme to address this is...

Subseasonal to seasonal (S2S) prediction of droughts and floods is one of the major challenges of weather and climate prediction. Recent studies suggest that the springtime land surface temperature/subsurface temperature (LST/SUBT) over the Tibetan Plateau (TP) can be a new source of S2S predictability. The project “Impact of Initialized Land Surface Temperature and Snowpack on Subseasonal to Seasonal Prediction (LS4P)” was in...

The prediction skill for precipitation anomalies in late spring and summer months—a significant component of extreme climate events—has remained stubbornly low for years. This paper presents a new idea that utilizes information on boreal spring land surface temperature/subsurface temperature (LST/SUBT) anomalies over the Tibetan Plateau (TP) to improve prediction of subsequent summer droughts/floods over several regions over t...

This study focuses on improving prediction of the two types of ENSO by combining multi-model ensemble (MME) with a statistical error correction method that is based on a stepwise pattern projection and applied to all models before doing the MME. We evaluate such a combinational approach using five dynamical model datasets from the North American Multi-model Ensemble (NMME) project for the period of 1982–2010. The prediction sk...

The global mean surface air temperature (GMST) shows multidecadal variability over the period of 1910–2013, with an increasing trend. This study quantifies the contribution of hemispheric surface air temperature (SAT) variations and individual ocean sea surface temperature (SST) changes to the GMST multidecadal variability for 1910–2013. At the hemispheric scale, both the Goddard Institute for Space Studies (GISS) observations...