Long-term Continuous SIF-informed Photosynthesis Proxy reconstructed with calibrated AVHRR surface reflectance (LCSPP-AVHRR), 2001-2023

Usage Notes:This is the updated LCSPP dataset (v3.2), generated using the LCREF-AVHRR record from 1982–2023. Due to Zenodo’s size constraints, LCSPP-AVHRR is divided into two separate repositories. Previously referred to as "LCSIF," the dataset was renamed to emphasize its role as a SIF-informed long-term photosynthesis proxy derived from surface reflectance and to avoid confusion with directly measured SIF signals. Key updates in version 3.2 include: Improved Calibration: Enhanced consistency in calibration methods, addressing technical limitations in version 3.1 including applying more stringent quality filtering and snow masks. Quality Flags: New quality flag layer enables users to identify whether a pixel is derived from observed surface reflectance (QA=0), high-quality gap-filled values (QA=1), lower-quality gap-filled based on the mean seasonal cycle (QA=2), or missing entirely (QA=3). We advice the user to rely only on observed and high-quality gap-filled values for their analyses. Extension to include observations from the year of 2023. Other LCSPP repositories can be accessed via the following links: LCSPP-AVHRR v3.2 (1982-2000): 10.5281/zenodo.7916850 LCSPP-MODIS v3.2(2001-2023): 10.5281/zenodo.11658088 The user can choose between LCSPP-AVHRR and LCSPP-MODIS for the overlapping period from 2001-2023. The two datasets are generally consistent during this overlapping period, although LCSPP-MODIS shows a stronger greening trend between 2001-2023. For studies exploring the long-term vegetation dynamics, the user can either use only LCSPP-AVHRR or use a blend dataset of LCSPP-AVHRR and LCSPP-MODIS as a sensitivity test. In addition, the updated long-term continuous reflectance datasets (LCREF), used for the production of LCSPP, can be accessed using the following links: LCREF-AVHRR v3.2 (1982-2023): 10.5281/zenodo.11905959 LCREF-MODIS v3.2 (2001-2023): 10.5281/zenodo.11657458 A manuscript describing the technical details is available at https://arxiv.org/abs/2311.14987, while detailed the uses and limitations of the dataset. In particular, we note that LCSPP is a reconstruction of SIF-informed photosynthesis proxy and should not be treated as SIF measurements. Although LCSPP has demonstrated skill in tracking the dynamics of GPP and PAR absorbed by canopy chlorophyll (APARchl), it is not suitable for estimating fluorescence quantum yield. All data outputs from this study are available at 0.05° spatial resolution and biweekly temporal resolution in NetCDF format. Each month is divided into two files, with the first file “a” representative of the 1st day to the 15th day of a month, and the second file “b” representative of the 16th day to the last day of a month. Abstract: Satellite-observed solar-induced chlorophyll fluorescence (SIF) is a powerful proxy for the photosynthetic characteristics of terrestrial ecosystems. Direct SIF observations are primarily limited to the recent decade, impeding their application in detecting long-term dynamics of ecosystem function. In this study, we leverage two surface reflectance bands available both from Advanced Very High-Resolution Radiometer (AVHRR, 1982-2023) and MODerate-resolution Imaging Spectroradiometer (MODIS, 2001-2023). Importantly, we calibrate and orbit-correct the AVHRR bands against their MODIS counterparts during their overlapping period. Using the long-term bias-corrected reflectance data from AVHRR and MODIS, a neural network is trained to produce a Long-term Continuous SIF-informed Photosynthesis Proxy (LCSPP) by emulating Orbiting Carbon Observatory-2 SIF, mapping it globally over the 1982-2023 period. Compared with previous SIF-informed photosynthesis proxies, LCSPP has similar skill but can be advantageously extended to the AVHRR period. Further comparison with three widely used vegetation indices (NDVI, kNDVI, NIRv) shows a higher or comparable correlation of LCSPP with satellite SIF and site-level GPP estimates across vegetation types, ensuring a greater capacity for representing long-term photosynthetic activity.使用说明：本数据集为更新后的LCSPP（Long-term Continuous SIF-informed Photosynthesis Proxy）数据集v3.2，基于1982–2023年的LCREF-AVHRR（Long-term Continuous Reflectance from AVHRR）记录生成。受限于Zenodo（Zenodo）的文件大小限制，LCSPP-AVHRR被拆分为两个独立的存储库。该数据集此前被称为“LCSIF”，此次重命名旨在突出其作为基于地表反射率构建的、受太阳诱导叶绿素荧光（SIF, solar-induced chlorophyll fluorescence）约束的长期光合作用代理数据的定位，并避免与直接测量的SIF信号产生混淆。 v3.2版本的主要更新包括： 1. 校准优化：校准方法的一致性得到提升，解决了v3.1版本中的技术局限，例如采用了更严格的质量过滤与雪覆盖掩码处理。 2. 质量标记：新增质量标记图层，支持用户识别像素的来源类型：观测得到的地表反射率（QA=0）、高质量间隙填充值（QA=1）、基于平均季节循环的低质量间隙填充值（QA=2），以及完全缺失的数据（QA=3）。我们建议用户在分析中仅使用观测数据与高质量间隙填充值。 3. 数据扩展：新增了2023年的观测数据。 其他LCSPP存储库可通过以下链接获取： LCSPP-AVHRR v3.2（1982–2000）：10.5281/zenodo.7916850 LCSPP-MODIS v3.2（2001–2023）：10.5281/zenodo.11658088 用户可在2001–2023年的重叠时段选择使用LCSPP-AVHRR或LCSPP-MODIS。两类数据集在该重叠时段内整体一致性较好，但LCSPP-MODIS在2001–2023年间呈现出更强的绿化趋势。针对长期植被动态研究，用户可仅使用LCSPP-AVHRR数据集，或结合LCSPP-AVHRR与LCSPP-MODIS构建混合数据集以开展敏感性测试。 此外，用于生成LCSPP的更新版长期连续地表反射率数据集（LCREF, Long-term Continuous Reflectance Datasets）可通过以下链接获取： LCREF-AVHRR v3.2（1982–2023）：10.5281/zenodo.11905959 LCREF-MODIS v3.2（2001–2023）：10.5281/zenodo.11657458 一篇阐述该数据集技术细节的手稿可在https://arxiv.org/abs/2311.14987获取，其中也详细说明了数据集的用途与局限性。需特别注意的是，LCSPP是受SIF约束的光合作用代理数据重构结果，不应被视为直接测量的SIF数据。尽管LCSPP已被证明能够有效追踪总初级生产力（GPP, Gross Primary Productivity）与冠层叶绿素吸收的光合有效辐射（APARchl, PAR absorbed by canopy chlorophyll）的动态变化，但该数据集不适用于估算荧光量子产率。 本研究产出的所有数据均为0.05°空间分辨率、双周时间分辨率的NetCDF（Network Common Data Form）格式文件。每月的数据被拆分为两个文件：以“a”命名的文件代表当月1日至15日的数据，以“b”命名的文件代表当月16日至当月最后一日的数据。 摘要：卫星观测的太阳诱导叶绿素荧光（SIF）是表征陆地生态系统光合作用特征的有效代理指标。但直接SIF观测主要局限于近十年，这限制了其在生态系统功能长期动态监测中的应用。本研究利用了高级甚高分辨率辐射计（AVHRR, Advanced Very High-Resolution Radiometer，1982–2023）与中分辨率成像光谱仪（MODIS, MODerate-resolution Imaging Spectroradiometer，2001–2023）均可获取的两个地表反射率波段。尤为关键的是，我们在两类传感器的重叠时段内，以MODIS反射率数据为基准对AVHRR波段开展了校准与轨道校正。基于经过长期偏差校正的AVHRR与MODIS反射率数据，我们训练了一个神经网络，以模拟轨道碳观测站2号（OCO-2, Orbiting Carbon Observatory-2）的SIF数据，从而生成长期受SIF约束的光合作用代理数据集（LCSPP），并在1982–2023年的全球范围内完成制图。与此前基于SIF构建的光合作用代理数据相比，LCSPP具备相当的性能优势，且可扩展至AVHRR的观测时段，这是其突出亮点。进一步与三种常用植被指数：归一化植被指数（NDVI, Normalized Difference Vegetation Index）、核化归一化植被指数（kNDVI, kernel normalized difference vegetation index）、近红外植被指数（NIRv, Near-Infrared Reflectance of Vegetation）的对比结果显示，LCSPP与卫星SIF及站点尺度GPP估算值的相关性更高或相当，且在不同植被类型中均表现稳定，因此具备更强的长期光合作用活动表征能力。