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Abstract 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

We experimentally quantified the impact of cloud fraction and cloud type on the heating rate (HR) of black and brown carbon (HRBC and HRBrC). In particular, we examined in more detail the cloud effect on the HR detected in a previous study (Ferrero et al., 2018). High-time-resolution measurements of the aerosol absorption coefficient at multiple wavelengths were coupled with spectral measurements of the direct, diffuse and surface reflected irradiance and with lidar–ceilometer data during a field campaign in Milan, Po Valley (Italy). The experimental set-up allowed for a direct determination of the total HR (and its speciation: HRBC and HRBrC) in all-sky conditions (from clear-sky conditions to cloudy). The highest total HR values were found in the middle of winter (1.43 ± 0.05 K d−1), and the lowest were in spring (0.54 ± 0.02 K d−1). Overall, the HRBrC accounted for 13.7 ± 0.2 % of the total HR, with the BrC being characterized by an absorption Ångström exponent (AAE) of 3.49 ± 0.01. To investigate the role of clouds, sky conditions were classified in terms of cloudiness (fraction of the sky covered by clouds: oktas) and cloud type (stratus, St; cumulus, Cu; stratocumulus, Sc; altostratus, As; altocumulus, Ac; cirrus, Ci; and cirrocumulus–cirrostratus, Cc–Cs). During the campaign, clear-sky conditions were present 23 % of the time, with the remaining time (77 %) being characterized by cloudy conditions. The average cloudiness was 3.58 ± 0.04 oktas (highest in February at 4.56 ± 0.07 oktas and lowest in November at 2.91 ± 0.06 oktas). St clouds were mostly responsible for overcast conditions (7–8 oktas, frequency of 87 % and 96 %); Sc clouds dominated the intermediate cloudiness conditions (5–6 oktas, frequency of 47 % and 66 %); and the transition from Cc–Cs to Sc determined moderate cloudiness (3–4 oktas); finally, low cloudiness (1–2 oktas) was mostly dominated by Ci and Cu (frequency of 59 % and 40 %, respectively). HR measurements showed a constant decrease with increasing cloudiness of the atmosphere, enabling us to quantify for the first time the bias (in %) of the aerosol HR introduced by the simplified assumption of clear-sky conditions in radiative-transfer model calculations. Our results showed that the HR of light-absorbing aerosol was ∼ 20 %–30 % lower in low cloudiness (1–2 oktas) and up to 80 % lower in completely overcast conditions (i.e. 7–8 oktas) compared to clear-sky ones. This means that, in the simplified assumption of clear-sky conditions, the HR of light-absorbing aerosol can be largely overestimated (by 50 % in low cloudiness, 1–2 oktas, and up to 500 % in completely overcast conditions, 7–8 oktas). The impact of different cloud types on the HR was also investigated. Cirrus clouds were found to have a modest impact, decreasing the HRBC and HRBrC by −5 % at most. Cumulus clouds decreased the HRBC and HRBrC by −31 ± 12 % and −26 ± 7 %, respectively; cirrocumulus–cirrostratus clouds decreased the HRBC and HRBrC by −60 ± 8 % and −54 ± 4 %, which was comparable to the impact of altocumulus (−60 ± 6 % and −46 ± 4 %). A higher impact on the HRBC and HRBrC suppression was found for stratocumulus (−63 ± 6 % and −58 ± 4 %, respectively) and altostratus (−78 ± 5 % and −73 ± 4 %, respectively). The highest impact was associated with stratus, suppressing the HRBC and HRBrC by −85 ± 5 % and −83 ± 3 %, respectively. The presence of clouds caused a decrease of both the HRBC and HRBrC (normalized to the absorption coefficient of the respective species) of −11.8 ± 1.2 % and −12.6 ± 1.4 % per okta. This study highlights the need to take into account the role of both cloudiness and different cloud types when estimating the HR caused by both BC and BrC and in turn decrease the uncertainties associated with the quantification of their impact on the climate.

This study investigates the performances in a terrestrial ecosystem of gross primary production (GPP) estimation of a suite of spectral vegetation indexes (VIs) that can be computed from currently orbiting platforms. Vegetation indexes were computed from near-surface field spectroscopy measurements collected using an automatic system designed for high temporal frequency acquisition of spectral measurements in the visible near-infrared region. Spectral observations were collected for two consecutive years in Italy in a subalpine grassland equipped with an eddy covariance (EC) flux tower that provides continuous measurements of net ecosystem carbon dioxide (CO2) exchange (NEE) and the derived GPP. Different VIs were calculated based on ESA-MERIS and NASA-MODIS spectral bands and correlated with biophysical (Leaf area index, LAI; fraction of photosynthetically active radiation intercepted by green vegetation, fIPARg), biochemical (chlorophyll concentration) and ecophysiological (green light-use efficiency, LUEg) canopy variables. In this study, the normalized difference vegetation index (NDVI) was the index best correlated with LAI and fIPARg (r = 0.90 and 0.95, respectively), the MERIS terrestrial chlorophyll index (MTCI) with leaf chlorophyll content (r = 0.91) and the photochemical reflectance index (PRI551), computed as (R531-R551)/(R531+R551) with LUEg (r = 0.64). Subsequently, these VIs were used to estimate GPP using different modelling solutions based on Monteith's light-use efficiency model describing the GPP as driven by the photosynthetically active radiation absorbed by green vegetation (APARg) and by the efficiency (ε) with which plants use the absorbed radiation to fix carbon via photosynthesis. Results show that GPP can be successfully modelled with a combination of VIs and meteorological data or VIs only. Vegetation indexes designed to be more sensitive to chlorophyll content explained most of the variability in GPP in the ecosystem investigated, characterised by a strong seasonal dynamic of GPP. Accuracy in GPP estimation slightly improves when taking into account high frequency modulations of GPP driven by incident PAR or modelling LUEg with the PRI in model formulation. Similar results were obtained for both measured daily VIs and VIs obtained as 16-day composite time series and then downscaled from the compositing period to daily scale (resampled data). However, the use of resampled data rather than measured daily input data decreases the accuracy of the total GPP estimation on an annual basis.

Different Bacillus species with PGPR (plant growth-promoting rhizobacterium) activity produce potent biofungicides and stimulate plant defense responses against phytopathogenic fungi. However, very little is known about how these PGPRs recognize phytopathogens and exhibit the antifungal response. Here, we report the antagonistic interaction between B. subtilis and the phytopathogenic fungus Fusarium verticillioides. We demonstrate that this bacterial-fungal interaction triggers the induction of the SigB transcription factor, the master regulator of B. subtilis stress adaptation. Dual-growth experiments performed with live or dead mycelia or culture supernatants of F. verticillioides showed that SigB was activated and required for the biocontrol of fungal growth. Mutations in the different regulatory pathways of SigB activation in the isogenic background revealed that only the energy-related RsbP-dependent arm of SigB activation was responsible for the specific fungal detection and triggering the antagonistic response. The activation of SigB increased the expression of the operon responsible for the production of the antimicrobial cyclic lipopeptide surfactin (the srfA operon). SigB-deficient B. subtilis cultures produced decreased amounts of surfactin, and B. subtilis cultures defective in surfactin production (ΔsrfA) were unable to control the growth of F. verticillioides. In vivo experiments of seed germination efficiency and early plant-growth inhibition in the presence of F. verticillioides confirmed the physiological importance of SigB activity for plant bioprotection. [ABSTRACT FROM AUTHOR]