Mean Seasonal Cycle of Leaf Area Index

Value of this dataset:<i></i>The High Resolution Model Intercomparison Project (HighResMIP) is one of the major projects for the Coupled Model Intercomparison Project 6 (CMIP6) (Haarsma et al., 2016). It, for the first time, adopts a multi-model approach to systematicly investigate the impacts of model horizonal resolution on historical and future climate variabilities and changing trends. Functioning as one of the required drivers for the HighResMIP, this mean seasonal cycle of leaf area index (LAI) product will be adopted by different modeling groups to quantify the sensitivity of land-atmosphere feedbacks to the high resolution LAI datasets. Moreover, through the comprehensive evaluation of LAI-related simulaitons against multi-source observations, the CMIP6 community will better understand the sources of their model uncertainties. <br>Data Description: This mean seasonal cycle of LAI version 1 (LAI_V1_for_HighResMIP.nc) was reprocessed from the monthly AVHRR GIMMS LAI3g version 2 (1981/08 to 2015/09, Mao et al., 2013; Zhu et al., 2013). It is a gridded mean product (0.25 degree by 0.25 degree) specially designed for the abovementioned HighResMIP of CMIP6. <br>Data Collection Methods: We downloaded the raw monthly LAI3g time series from http://pan.baidu.com/s/1kUXTQp5. We then made necessary processes including the remapping to produce multi-year LAI means. More detailed information can be found in the “Data Processing Steps” below. <br><br>Data Processing Steps: All missing values (e.g., 25000) and unreasonable values higher than 7000 in the raw LAI3g data were first replaced by 0, and a scaling factor of 0.001 was adopted to obtain the actual LAI. The raw 1/12 degree by 1/12 degree LAI3g data were then regridded to 0.25 degree by 0.25 degree using the bilinear interpolation. Since the raw LAI3g data provide bi-weekly LAI, i.e., two LAI values for a certain grid every month, monthly mean LAI for the new product was calculated as the average of the two values for the remapped data. The 34-year or 35-year mean monthly LAI was then calculated for each 12-month based on the data availability. For example, the LAI climatology for January was calculated as the average of 1982 to 2015, but the LAI climatology for August was computed as the average of 1981 to 2015.<br>