Trend patterns of the NDVI in the study region.

<p>The base map is only for illustrative purposes.</p

Trend Patterns of Vegetative Coverage and Their Underlying Causes in the Deserts of Northwest China over 1982 – 2008

<div><p>We identified the spatiotemporal patterns of the Normalized Difference Vegetation Index (NDVI) for the years 1982–2008 in the desert areas of Northwest China and quantified the impacts of climate and non-climate factors on NDVI changes. The results indicate that although the mean NDVI has improved in 24.7% of the study region; 16.3% among the region has been stagnating in recent years and only 8.4% had a significantly increasing trend. Additionally, 45.3% of the region has maintained a stable trend over the study period and 30.0% has declined. A multiple regression model suggests that a wetter climate (quantified by the Palmer Drought Severity Index, PDSI) is associated with higher NDVI in most areas (18.1% of significance) but these historical changes in PDSI only caused an average improvement of approximately 0.4% over the study region. Contrasting the regression results under different trend patterns, no significant differences in PDSI impacts were detected among the four trend patterns. Therefore, we conclude that climate is not the primary driver for vegetative coverage in Northwest China. Future studies will be required to identify the impacts of specific non-climatic factors on vegetative coverage based on high-resolution data, which will be beneficial in creating an effective strategy to combat the recent desertification trend in China.</p></div

DataSheet1_Method to Evaluate the Impact of Integration of PMSG on Stability of Synchronous Generator Shaft Under Weak Grid Connection.docx

With the continuous growth in the amount of wind power accessed by the AC grid, the impact of the grid connection of wind-power generators with the power system has gradually increased. In this study, the subsynchronous oscillation of a synchronous generator (SG) shaft caused by the integration of direct-drive permanent-magnet synchronous generators (PMSGs) was investigated. The mechanism governing the effect of the connection strength between the PMSG and AC power system on the stability of the generator shaft system was analyzed based on the complex torque coefficient method. When the connection strength between the PMSG and AC power system weakens, the same voltage variation that occurs at the point of common coupling of the PMSG stimulates more intense power fluctuations in the PMSG, and the electrical damping injected by the PMSG into the SG increases considerably. This may cause the oscillation mode dominated by the generator shaft system to move to the right half of the complex plane, thereby reducing the stability of the generator shaft system. In addition, the evaluation process of the influence of the PMSG on the SG shaft system was summarized, and the proposed method can determine the stability of the AC power system after the integration of the PMSG. Finally, the effectiveness of the proposed method was validated via study cases, and conclusions were drawn. This method is expected to serve as a useful tool for the risk assessment of subsynchronous oscillations in wind farms.</p

Impacts on NDVI by historical trends in PDSI and Year grouped by trend patterns.

<p>Impacts on NDVI by historical trends in PDSI and Year grouped by trend patterns.</p

Study region.

<p>Four provinces were included: Xinjiang (XJ), Qinghai (QH), Gansu (GS) and Ningxia (NX). We concentrated on areas with long-term average NDVI values between 0.05 and 0.15. The base map is only for illustrative purposes.</p

Response of the NDVI to PDSI and Year.

<p>All grids are plotted in (a) and (b), and only significant grids are plotted in (c) and (d). The base map is only for illustrative purposes.</p

Histogram of NDVI responses to the PDSI and Year.

<p>All grids were plotted in (a) and (b), and only significant grids were plotted in (c) and (d).</p

Summary of the NDVI response to the PDSI and Year and the changes in the NDVI due to the historical trends of the PDSI and Year from 1982–2008.

<p>^aNeg_Sig/Pos_Sig: proportion of series showing significantly negative and positive regression coefficients (P<0.05).</p><p>Summary of the NDVI response to the PDSI and Year and the changes in the NDVI due to the historical trends of the PDSI and Year from 1982–2008.</p

The linear time trends of Prcp, PE and PDSI over study period.

<p>The linear time trends of Prcp, PE and PDSI over study period.</p

Histogram of estimated impacts on NDVI by historical trends in PDSI and Year.

<p>All grids were plotted in (a) and (b), and only significant grids were plotted in (c) and (d).</p