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GIGJ: A Crustal Gravity Model of the Guangdong Province for Predicting the Geoneutrino Signal at the JUNO Experiment

2019; Wiley; Volume: 124; Issue: 4 Linguagem: Inglês

10.1029/2018jb016681

2169-9356

Mirko Reguzzoni, Lorenzo Rossi, Marica Baldoncini, Ivan Callegari, Piero Poli, Daniele Sampietro, Virginia Strati, Fabio Mantovani, Giuseppe Andronico, V. Antonelli, M. Bellato, E. Bernieri, A. Brigatti, R. Brugnera, A. Budano, Mario Buscemi, S. Bussino, R. Caruso, D. Chiesa, Daniele Corti, F. Dal Corso, Xuefeng Ding, S. Dusini, Andrea Fabbri, G. Fiorentini, R. Ford, A. Formozov, G. Galet, A. Garfagnini, M. Giammarchi, A. Giaz, M. Grassi, A. Insolia, R. Isocrate, I. Lippi, F. Longhitano, D. Lo Presti, P. Lombardi, Yury Malyshkin, F. Marini, S. M. Mari, C. Martellini, Emanuela Meroni, M. Mezzetto, L. Miramonti, Salvatore Monforte, M. Montuschi, M. Nastasi, F. Ortica, A. Paoloni, S. Parmeggiano, D. Pedretti, N. Pelliccia, R. Pompilio, E. Previtali, G. Ranucci, A. Re, B. Ricci, A. Romani, P. Saggese, G. Salamanna, F. H. Sawy, Giulio Settanta, M. Sisti, C. Sirignano, M. Spinetti, L. Stančo, G. Verde, L. Votano,

Geophysical and Geoelectrical Methods

Abstract Gravimetric methods are expected to play a decisive role in geophysical modeling of the regional crustal structure applied to geoneutrino studies. GIGJ (GOCE Inversion for Geoneutrinos at JUNO) is a 3‐D numerical model constituted by ~46 × 10 3 voxels of 50 × 50 × 0.1 km, built by inverting GOCE (Gravity field and steady‐state Ocean Circulation Explorer) gravimetric data over the 6° × 4° area centered at the JUNO (Jiangmen Underground Neutrino Observatory) experiment, currently under construction in the Guangdong Province (China). The a priori modeling is based on the adoption of deep seismic sounding profiles, receiver functions, teleseismic P wave velocity models, and Moho depth maps, according to their own accuracy and spatial resolution. The inversion method allowed for integrating GOCE data with the a priori information and some regularization conditions through a Bayesian approach and a stochastic optimization. GIGJ fits the highly accurate and homogeneously distributed GOCE gravity data with a ~1 mGal standard deviation of the residuals, compatible with the observation accuracy. GIGJ provides a site‐specific subdivision of the crustal layers masses, of which uncertainties include estimation errors, associated to the gravimetric solution, and systematic uncertainties, related to the adoption of a fixed sedimentary layer. A consequence of this local rearrangement of the crustal layer thicknesses is a ~21% reduction and a ~24% increase of the middle and lower crust geoneutrino signal, respectively. The geophysical uncertainties of geoneutrino signals at JUNO produced by unitary uranium and thorium abundances distributed in the upper, middle, and lower crust are reduced by 77%, 55%, and 78%, respectively. The numerical model is available at this site ( http://www.fe.infn.it/radioactivity/GIGJ ).