青藏高原高寒草地返青期和黄枯期模拟数据集（1960–2020）

本数据集包含两套数据，每套数据都包含了1960-2020年青藏高原高寒草地逐年返青期和黄枯普遍期，这两套数据分别基于植被生长季指数（GSI）模型（Jolly et al., 2005）和改进的高寒草地生长季指数（AGSI）模型（Sun et al., 2025）模拟得到，模型由气候因子驱动，根据地面观测的返青/萌芽期和黄枯普遍期数据进行参数化。数据采用NetCDF格式存储，空间分辨率为0.1°，采用WGS84空间参考系，数据类型为32位浮点型（float32）。该物候数据集是考虑气候因子的影响和限制模拟得到的冠层叶物候，与地面观测的植物群落叶物候有较好的吻合度，能够为深入理解青藏高原气候变化及其对高寒草地的影响提供良好的数据支持。

This dataset contains two sets of data, each including annual green-up date and general senescence date of alpine grasslands on the Qinghai-Tibet Plateau from 1960 to 2020. These two datasets are simulated based on the Vegetation Growing Season Index (GSI) model (Jolly et al., 2005) and the improved Alpine Grassland Growing Season Index (AGSI) model (Sun et al., 2025), respectively. Both models are driven by climatic factors and parameterized using in-situ observed green-up/sprouting date and general senescence date data. The data are stored in NetCDF format, with a spatial resolution of 0.1°, using the WGS84 spatial reference system, and the data type is 32-bit floating-point (float32). This phenological dataset simulates canopy leaf phenology by considering the influences and constraints of climatic factors, and it exhibits good consistency with in-situ observed plant community leaf phenology. It can provide robust data support for in-depth understanding of climate change on the Qinghai-Tibet Plateau and its impacts on alpine grasslands.

搜集汇总

背景与挑战

背景概述

该数据集提供了1960-2020年青藏高原高寒草地的逐年返青期和黄枯普遍期模拟数据，基于植被生长季指数（GSI）模型和改进的高寒草地生长季指数（AGSI）模型生成，空间分辨率为0.1°，以NetCDF格式存储。这些数据通过气候因子驱动，并基于地面观测参数化，旨在支持气候变化对高寒草地影响的研究，具有较高的观测吻合度。