Feng Jinming

Inter-comparison of 10-year precipitation simulated by several RCMs for Asia

In phase II of the Regional Climate Model Inter-comparison Project (RMIP) for Asia, the regional climate has been simulated for July 1988 through December 1998 by five regional climate models and one global variable resolution model. Comparison of the 10-year simulated precipitation with the observations was carried out. The results show that most models have the capacity to reproduce the basic spatial pattern of precipitation for Asia, and the main rainbelt can be reproduced by most models, but there are distinctions in the location and the intensity. Most models overestimate the precipitation over most continental regions. Interannual variability of the precipitation can also be basically simulated, while differences exist between various models and the observations. The biases in the stream field are important reasons behind the simulation errors of the Regional Climate Models (RCMs). The cumulus scheme and land surface process have large influences on the precipitation simulation. Generally, the Grell cumulus scheme produces more precipitation than the Kuo scheme.

Simulation of Extreme Climate Events over China with Different Regional Climate Models

Abstract During phase II of the Regional Climate Model Inter-comparison Project (RMIP) for Asia, the Asian climate was estimated from July 1988 to December 1998 using six climate models. In this paper, the abilities of six climate models to simulate several important extreme climate events in China during the last years of the last century were analyzed. The modeled results for the intensity of the precipitation anomaly over the Yangtze-Huaihe Valley during the summers of 1991 and 1998 were weaker than the observed values. The positive precipitation anomaly responsible for a catastrophic flood in 1991 was well reproduced in almost all simulation results, but the intensity and range of the precipitation anomaly in 1998 were weaker in the modeled results. The spatial distribution of extreme climate events in 1997, when severe drought affected North China and flood impacted South China, was reproduced by most of the regional models because the anomaly of the large-scale background field was well-simulated, despite poor simulation of high temperature areas in the north during the summer by all models.

Modeling Gross Primary Production by Integrating Satellite Data and Coordinated Flux Measurements in Arid and Semi-Arid China

Abstract Assessing large-scale patterns of gross primary production (GPP) in arid and semi-arid (ASA) areas is important for both scientific and practical purposes. Remote sensing-based models, which integrate satellite data with input from ground-based meteorological measurements and vegetation characteristics, improve spatially extended estimates of vegetation productivity with high accuracy. In this study, the authors simulated GPP in ASA areas by integrating moderate resolution imaging spectral radiometer (MODIS) data with eddy covariance and meteorological measurements at the flux tower sites using the Vegetation Photosynthesis Model (VPM), which is a remote sensing-based model for analyzing the spatial pattern of GPP in different land cover types. The field data were collected by coordinating observations at nine stations in 2008. The results indicate that in the region during the growing season GPP was highest in cropland sites, second highest in woodland sites, and lowest in grassland sites. VPM captured the temporal and spatial characteristics of GPP for different land covers in ASA areas. Further, Enhanced Vegetation Index (EVI) had a strong liner relationship with GPP in densely vegetated areas, while the Normalized Difference Vegetation Index (NDVI) had a strong liner relationship with GPP over less dense vegetation. This study demonstrates the potential of satellite-driven models for scaling-up GPP, which is a key component for studying the carbon cycle at regional and global scales.

Increased Browning of Woody Vegetation Due to Continuous Seasonal Droughts in Yunnan Province, China

Abstract In this paper, based on the analysis of satellite measurements, the authors conclude that the continuous seasonal droughts intensify the browning of woody vegetation and that evergreen needleleaf forest (ENF) shows a larger browning percentage than other woody vegetation types over Yunnan Province. Based on the Tropical Rain-fall Measuring Mission (TRMM) precipitation standardized anomaly, in the dry season, which is from October to March, the 2010 drought affected an area of Yunnan Province 1.77 times larger than the 2012 drought, but in the post-drought months (April to June), the browning area of all woody vegetation in 2012 was 1.11 times larger than that in 2010 on the basis of the enhanced vegetation index (EVI) standardized anomaly. The reduction of vegetation greenness over large areas of Yunnan Province represents a photosynthetic capacity loss which will have an impact on carbon fluxes to the atmosphere.

The Common Principal Component Analyses of Multi-RCMs

Abstract Based on a 10-year simulation of six Regional Climate Models (RCMs) in phase II of the Regional Climate Model Inter-Comparison Project (RMIP) for Asia, the multivariate statistical method of common principal components (CPCs) is used to analyze and compare the spatiotemporal characteristics of temperature and precipitation simulated by multi-RCMs over China, including the mean climate states and their seasonal transition, the spatial distribution of interannual variability, and the interannual variation. CPC is an effective statistical tool for analyzing the results of different models. Compared with traditional statistical methods, CPC analyses provide a more complete statistical picture for observation and simulation results. The results of CPC analyses show that the climatological means and the characteristics of seasonal transition over China can be accurately simulated by RCMs. However, large biases exist in the interannual variation in certain years or for individual models.