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PRISMA is a hyperspectral satellite mission launched by the Italian Space Agency (ASI) in April 2019. The mission is designed to collect data at global scale for a variety of applications, including those related to the cryosphere. This study presents an evaluation of PRISMA Level 1 (L1) and Level 2 (L2D) products for different snow conditions. To the aim, PRISMA data were collected at three sites: two in the Western European Alps (Torgnon and Plateau Rosa) and one in East Antarctica (Nansen Ice Shelf). PRISMA data were acquired contemporary to both field measurements and Sentinel‐2 data. Simulated Top of the Atmosphere (TOA) radiance data were then compared to L1 PRISMA and Sentinel‐2 TOA radiance. Bottom Of Atmosphere (BOA) reflectance from PRISMA L2D and Sentinel‐2 L2A data were then evaluated by direct comparison with field data. Both TOA radiance and BOA reflectance PRISMA products were generally in good agreement with field data, showing a Mean Absolute Difference (MAD) lower than 5%. L1 PRISMA TOA radiance products resulted in higher MAD for the site of Torgnon, which features the highest topographic complexity within the investigated areas. In Plateau Rosa we obtained the best comparison between PRISMA L2D reflectance data and in situ measurements, with MAD values lower than 5% for the 400–900 nm range. The Nansen Ice Shelf instead resulted in MAD values <10% between PRISMA L2D and field data, while Sentinel‐2 BOA reflectance showed higher values than other data sources. Plain Language Summary: Satellite imaging spectroscopy data provide valuable information on Earth surface processes. In this study we evaluated data acquired from the PRISMA satellite mission in the Alps and Antarctica. Those studies are important to validate satellite observations with contemporary field measurements since they open the possibility of quantitatively use PRISMA data for cryosphere monitoring. Key Points: We present an evaluation of PRISMA Level 1 and Level 2 products for different snow conditionsContemporary to PRISMA acquisition, field spectroscopy data were collected on snow in the Alps and in AntarcticaBoth radiance and reflectance PRISMA products were generally in good agreement with field data [ABSTRACT FROM AUTHOR]

Space‐borne retrievals of solar‐induced chlorophyll fluorescence (SIF) over land surfaces have recently become a resource for studying and quantifying the broad scale dynamics of gross carbon uptake (gross primary productivity—GPP) across ecosystems. To prepare for the assimilation of SIF data in terrestrial biosphere models, we examine how differences between SIF products (due to differences in acquisition characteristics and processing chain) may affect the optimization of model parameters and the resultant GPP estimate. We compare recent daily mean SIF products (one from the Orbiting Carbon Observatory‐2 [OCO‐2] and two from the Global Ozone Monitoring Experiment–2 [GOME‐2], GlobFluo [GF] and NASA‐v28 [N28], missions), averaged at 0.5° × 0.5° spatial resolution and 16‐day temporal resolution, at the biome level. Phase differences between these products are relatively small. A first‐order correction of the difference in spectral sampling between the two instruments shows that OCO‐2 and N28 are consistent in terms of magnitude and amplitude, while GF is twice as large as the others. Using a bias‐blind toy data assimilation framework, we analyze how biases between SIF products, and between model and products, can be partially alleviated by optimizing the slope and intercept parameters of a linear GPP‐SIF operator. As observation biases can transfer to biases in other optimized process‐based parameters and to modeled carbon fluxes— thereby resulting in unidentified inaccurate parameter values—we argue that potential SIF biases should be treated cautiously in real‐world experiments in order to achieve realistic and reliable future simulations. Key Points: The differences between three space‐borne SIF products (one from OCO‐2 and two from GOME‐2) are quantified at the biome levelWhile two SIF products show consistent magnitude and seasonal amplitude, the third product is twice as large for most biomesUsing a toy assimilation framework we discuss the impact of these differences on the optimization of process‐based parameters related to GPP [ABSTRACT FROM AUTHOR]

Variations in photosynthesis still cause substantial uncertainties in predicting photosynthetic CO2 uptake rates and monitoring plant stress. Changes in actual photosynthesis that are not related to greenness of vegetation are difficult to measure by reflectance based optical remote sensing techniques. Several activities are underway to evaluate the sun-induced fluorescence signal on the ground and on a coarse spatial scale using space-borne imaging spectrometers. Intermediate-scale observations using airborne-based imaging spectroscopy, which are critical to bridge the existing gap between small-scale field studies and global observations, are still insufficient. Here we present the first validated maps of sun-induced fluorescence in that critical, intermediate spatial resolution, employing the novel airborne imaging spectrometer HyPlant. HyPlant has an unprecedented spectral resolution, which allows for the first time quantifying sun-induced fluorescence fluxes in physical units according to the Fraunhofer Line Depth Principle that exploits solar and atmospheric absorption bands. Maps of sun-induced fluorescence show a large spatial variability between different vegetation types, which complement classical remote sensing approaches. Different crop types largely differ in emitting fluorescence that additionally changes within the seasonal cycle and thus may be related to the seasonal activation and deactivation of the photosynthetic machinery. We argue that sun-induced fluorescence emission is related to two processes: (i) the total absorbed radiation by photosynthetically active chlorophyll; and (ii) the functional status of actual photosynthesis and vegetation stress. [ABSTRACT FROM AUTHOR]