RC2: For L73-75, there are a few FPAR products existing (doi: 10.1109/TGRS.2018.2818929). For example:

1. GEOV2-FPAR product

Verger, A., Baret , F., Weiss, M., 2020. Algorithm Theoretical Basis Document - GEOV2/AVHRR: Leaf Area Index (LAI), Fraction of Absorbed Photosynthetically Active Radiation (FAPAR) and Fraction of green Vegetation Cover (FCOVER) from LTDR AVHRR (Issue I2.50), Report for THEIA-SP-44-0207-CREAF, https://www.theia-land.fr/wp-content/uploads/2022/03/THEIA-SP-44-0207-CREAF_I2.50.pdf, p. 51.

1. FPAR3g from Boston University (http://www.mdpi.com/2072-4292/5/2/927)
2. JRC-TIP FAPAR (https://doi.org/10.3390/rs11243055)

Authors: the reviewer is correct that several valuable FPAR timeseries have been published in recent years. Nonetheless, the mentioned sources did not respond to the operational needs of near-real-time (NRT) monitoring systems.

The QA4ECV black-sky FAPAR long-term record (referred to in RC1) aims to provide a long timeseries of intercalibrated NOAA-AVHHR FPAR data between 1982 and 2006 for retrospective studies. The product did not aim to serve operational systems with continuous NRT data flow. Additionally, the ground resolution of the product (0.05° x 0.05°, roughly 5km at the equator) is considered sub-optimal for crop monitoring.

Regarding the other three suggestions provided:

1. GEOV2-FPAR products are operationally delivered within the Copernicus Land Monitoring Service (CLMS). It consists of two timeseries. One has a spatial resolution of 1 km (based on SPOT/VEGETATION and Proba-V) and covers the time period 1998-2020. The second has a 300 m spatial resolution (based on Proba-V and Sentinel 3), it starts in 2014 and is updated in NRT. However, the latter offers only 12 years of data, which is too short to be used for robust statistical analysis (e.g. anomalies, crop yield forecast). No continuous long term (i.e. since 2000) and NRT product is currently available from CLMS. A possible combination of the three sources (SPOT/VEGETATION, Proba-V and Sentinel-3) would be difficult as requires the harmonization of FPAR data produced by different algorithms and different spatial resolutions.
2. GIMMS FPAR3g offers a timeseries from 1981 to 2011 while the update product (GIMMS FPAR4g, Zhao et al., 2024) released in 2024, covers from 1982 to 2022. The products offer low temporal (15-days) and spatial (1/12 degree, roughly 8km) resolution and no NRT production is available. These elements frame both products as unsuitable for operational agricultural monitoring purposes.
3. JRC-TIP FAPAR: the reference proposed for this product is the same as QA4ECV black-sky FAPAR long-term records. We acknowledge that TIP (Two-stream Inversion Package) FPAR is a well-known and used FPAR retrieval algorithm, but no operational timeseries has been released so far.

Given these considerations, we have changed the introduction citing the products from GIMMS FPAR4g, CLMS and the timeseries cited by RC3 (HiQ-LAI). After line 84 we inserted the following paragraph:

“Several products exist that offer high-quality timeseries of biophysical variables, such as HiQ-LAI (Yan et al., 2025) or GIMMS FPAR4g (Zhao et al., 2024), but they usually lack some of the mandatory features needed by operational agricultural monitoring systems (i.e., long-term record and NRT availability). Typically, there is no guaranteed NRT data delivery into the future, nor are datasets filtered to reduce atmospheric influences. An exception is the Copernicus Land Monitoring Service that provides continuous, NRT, and filtered timeseries of biophysical variables from Proba-V and Sentinel-3 satellites (https://land.copernicus.eu/en/products/vegetation/fraction-of-absorbed-photosynthetically-active-radiation-v1-0-300m). Nevertheless, the timeseries length offered is too short (around 12 years) for robust statistical analysis needed for anomaly computation or crop yield forecasting. In this study we fill this gap by proposing a new dataset meeting the requirements of continuous, NRT, and filtered biophysical timeseries for more than 20 years.”