Giulia Panegrossi

Research Activity

My research interests include remote sensing of clouds and precipitation; passive microwave precipitation retrieval algorithms; radiative transfer through precipitating clouds; microphysics characterisation of precipitating clouds using models and observations; development of microphysics schemes; cloud electrification; nowcasting techniques; analysis of heavy precipitation events through the use of NWP models (UW-NMS, MM5, WRF-ARW) and comparison with remote, ground-based and in-situ measurements. My current scientific activity is mainly related to the development of passive microwave (PMW) precipitation retrieval algorithms for the cross-track and conically scanning radiometers in the Global Precipitation Measurement (GPM) mission constellation of satellites, PMW snowfall retrieval with focus on high-latitudes, global precipitation climatology, extreme events in the Mediterranean area, water cycle, hydrological applications. This activity is carried out within different international and national projects. 

Main official roles

  • Co-Coordinator of the ISAC Research MacroArea Climate And Meteorology, modelling and Earth Observations (CAMEO) (since October 2018)
  • EUMETSAT H SAF Science Manager (since October 2019)
  • Precipitation Measurement Mission (PMM) Science Team Member (since 2014)

Current Research Projects

  1. EUMETSAT Satellite Application Facility on Support to Operational Hydrology and Water Management (HSAF) (CDOP-3 2017-2022): Science Manager, Co-PI, member of the Project Team. As member of the Precipitation Product development team since 2012, I coordinate and supervise the development and delivery of operational precipitation products exploiting all current and future microwave radiometers on board LEO satellites.
  2. Copernicus C3S_312b_Lot1 (Oct. 2018- Jun. 2021) "Essential Climate Variable (ECV) products derived from observations Lot 1: precipitation, surface radiation budget, water vapour, cloud properties, and Earth radiation budget":  Co-PI, Leads the Precipitation ECV Climate Data Record generation (global daily and monthly mean precipitation estimate) based on passive microwave long-term Level 1 fundamental climate data record. 
  3. ESA RainCast study (ESA ITT AO/1-9324/18/NL/IA) (Jan. 2019-Jun. 2021): “A multi-platform and multi-sensor study to address the requirement from the research and operational communities for global precipitation measurements”, Co-PI and responsible of the CNR-ISAC unit. I lead the activity related to the assessment of snowfall detection and estimate capabilities of spaceborne MW active and passive sensors. 
  4. GAMES (EUMETSAT ITT 19/218140)  Geolocation Assessment/validation Methods for EPS-SG ICI and MWI (GAMES) (2020-2021)
  5. PON OT4CLIMA (Sep. 2018-Jun. 2021) (MIUR PNR 2015-2020, Aerospace) “EO innovative technologies for the study of environmental climate change impact”.  Forecasting, characterisation and monitoring of extreme weather events.
 Activities focuses on: precipitation estimation from multi-platform/sensor EO data through innovative algorithms for forecasting, monitoring and tracking extreme precipitation events, combined use of NWP models and satellite and ground-based observations.
  6. "GAMMA-FLASH": HIGH-ENERGY RADIATION AND PARTICLES IN THUNDERSTORMS, LIGHTNING, AND TERRESTRIAL GAMMA-RAY FLASHES (2019-2021), Progetto Premiale del MIUR progetti e sviluppo ASI. Member of the CNR-ISAC team: relationships between tra TGF and deep convection systems and lightning activity (Resp. S. Dietrich).
  7. H SAF and GPM scientific Collaboration proposal (2014-present) “H-SAF and GPM: precipitation algorithm development and validation activity”, approved by the NASA PMM Research Program and endorsed by EUMETSAT. PI, and responsible for the scientific collaboration between H-SAF and the NASA/JAXA GPM related to precipitation retrieval algorithm development and member of the Land surface Working Group and Passive Microwave retrieval Algorithm working group.

Recent publications

2021

  1. Panegrossi, G., D. Casella, P. Sanò, A. Camplani, A. Battaglia, Recent Advances and Challenges in Snowfall detection and Estimation, In: Precipitation Science, Ed. Silas Michaelides, Elsevier, in press
  2. Turk, J. F., S. E Ringerud, A. Camplani, D. Casella, R. J Chase, A. Ebtehaj, J. Gong, M. Kulie, G. Liu, L. Milani, G. Panegrossi, R. Padulles, J.-F. Rysman, P. Sanò, S. Vahedizade, N. Wood, Applications of a CloudSat-TRMM and CloudSat-GPM Satellite Coincidence Dataset, Rem. Sensing, under review
  3. Camplani, A., D. Casella, P. Sanò, G. Panegrossi, The Passive microwave Empirical frozen Surface Classification Algorithm (PESCA): application to GMI and ATMS, J. of Hydrometeorol., https://doi.org/10.1175/JHM-D-20-0260.1, 2021
  4. Bagaglini L., P. Sanò, D. Casella, E. Cattani, G. Panegrossi, The Passive microwave Neural network Precipitation Retrieval algorithm for Climate applications (PNPR-CLIM): design and application, Remote Sens.13(9), 1701; https://doi.org/10.3390/rs130917012021
  5. Hourngir, D., G. Panegrossi, D. Casella, P. Sanò, L.P. D’Adderio, C. Liu, A 4-year climatological analysis based on GPM observations of deep convective events in the Mediterranean region, Remote Sens. 13(9), 1685; https://doi.org/10.3390/rs130916852021
  6. Turk J., Ringerud, S., You Y., Camplani A., Casella D., Panegrossi G., Sanò P., Ebtehaj A., Guilloteau C., Utsumi N., Prigent C., Peters-Lidard C., Adapting Passive Microwave-Based Precipitation Algorithms to Variable Microwave Land Surface Emissivity to Improve Precipitation Estimation from the GPM Constellation, J. of Hydrometeorol., https://doi.org/10.1175/JHM-D-20-0296.1, 2021
  7. Mroz K., M. Montopoli, G. Panegrossi, L. Baldini, P. Kirtsetter, Quality assessment of spaceborne active and passive microwave snowfall products over the continental United States, J. of Hydrometeorology, https://doi.org/10.1175/JHM-D-20-0222.1, 2021
  8. Torcasio, Rosa Claudia, Stefano Federico *, Albert Comellas Prat, Giulia Panegrossi, Leo Pio D'Adderio, Stefano Dietrich, Impact of lightning data assimilation on the short-term precipitation forecast over Central Mediterranean Sea, Remote Sens. 13(4), 682; https://doi.org/10.3390/rs130406822021

2020

  1. Battaglia A., G. Panegrossi, What Can We Learn from the CloudSat Radiometric Mode Observations of Snowfall over the Ice-Free Ocean?, Remote Sens.,12, 3285; doi:10.3390/rs12203285, 2020.
  2. Milani L.,M. S. Kulie, D. Casella P. Kirstetter, G. Panegrossi, V. Petkovic, S. E. Ringerud1, J-F Rysman, P. Sanò, N.-Y .Wang, Y. You, G. Skofronick-Jackson, Extreme Lake-Effect Snow from a GPM Microwave Imager Perspective: Observational Analysis and Precipitation Retrieval Evaluation, J. of Atmos. and Ocean. Tech., https://doi.org/10.1175/JTECH-D-20-0064.1, 2020.
  3. Chen F., W. T. Crow, L. Ciabatta, P. Filippucci, G. Panegrossi, A. C. Marra, S. Puca, and C. Massari, Enhanced large-scale validation of satellite-based land rainfall products, F. J. of Hydrometeor., https://doi.org/10.1175/JHM-D-20-0056.1, 2020
  4. Massari, C., Camici, S., Ciabatta, L., Penna, D., Marra, A. C., & Panegrossi, G. (2020). Floods in the Mediterranean area: The role of soil moisture and precipitation. In Water Resources in the Mediterranean Region (pp. 191-218). Elsevier
  5. Panegrossi, G. et al., Heavy precipitation systems in the Mediterranean area: The role of GPM. In: Satellite Precipitation Measurement. V. Levizzani, C. Kidd, D. B. Kirschbaum, C. D. Kummerow, K. Nakamura, F. J. Turk, Eds. Advances in Global Change Research69, Springer Nature, Cham, 819-841, doi:10.1007/978-3-030-35798-6_1, 2020

2019

  1. Rysman J.-F., G. Panegrossi, P. Sanò, A. C. Marra, S. Dietrich, L. Milani, M. S. Kulie, D. Casella, A. Camplani, C. Claud, L. Edel, Retrieving surface snowfall with GPM Microwave Imager: A new module for SLALOM algorithm, Geophys. Res. Let., doi :10.1029/2019GL084576, 2019 
  2. Marra, A. C., S. Federico, M. Montopoli, E. Avolio, L. Baldini, D. Casella, L. P. D’Adderio, S. Dietrich, P. Sanò, R. C. Torcasio, and G. Panegrossi, The Precipitation Structure of the Mediterranean Tropical-Like Cyclone Numa: Analysis of GPM Observations and NumericalWeather Prediction Model Simulations, Remote Sens. 2019, 11, 1690; doi:10.3390/rs11141690, 2019.
  3. D’Adderio L.P., F.
Porcù, G. Panegrossi, A.C. Marra, P. Sanò, S.
Dietrich, Comparison of the GPM DPR Single- and Double-Frequency Products Over the Mediterranean Area, IEEE Trans. Geosci. Remote Sens, doi: 10.1109/TGRS.2019.2928871, 2019

2018

  1. Rysman, J.-F., G. Panegrossi, A. C. Marra, S. Dietrich, L. Milani, M. Kulie, SLALOM: An all-surface snow water path retrieval algorithm for the GPM Microwave Imgaer, Remote Sens. 10(8), 1278; https://doi.org/10.3390/rs10081278, 2018.
  2. Sanò P., G. Panegrossi, D. Casella, A. C. Marra, L. P. D’Adderio, J.-F. Rysman, S. Dietrich, The Passive Microwave Neural Network Precipitation Retrieval (PNPR) algorithm for the Conical Scanning GMI Radiometer, Remote Sens. 10, 1122; doi:10.3390/rs10071122, 2018 
  3. Milani, L., M. Kulie, D. Casella, S. Dietrich, T. L'Ecuyer, G. Panegrossi, F. Porcu', P. Sano', N. Wood, CloudSat Snowfall Estimates over Antarctica and the Southern Ocean: An Assessment of Independent Retrieval Methodologies and Multi-Year Snowfall Analysis, Atmos. Res., 213, 121-135, DOI: 10.1016/j.atmosres.2018.05.015, 2018
  4. Capozzi V., M. Montopoli, V. Mazzarella, A. C. Marra, N. Roberto, G. Panegrossi, S. Dietrich and G. Budillon, Multi-Variable Classification Approach for the Detection of Lightning Activity Using a Low-Cost and Portable X Band Radar, Remote Sens.10(11), 1797; https://doi.org/10.3390/rs10111797, 2018
  5. Amaral, L. Martins Costa, S. Barbieri, D. Vila, S. Puca, G. Vulpiani, G. Panegrossi, T. Biscaro, P. Sanò, M. Petracca, A. C. Marra, M. Gosset, S. Dietrich, Assessment of Ground-Reference Data and Validation of the H-SAF Precipitation Products in Brazil, Remote Sens.10(11), 1743; doi:10.3390/rs10111743, 2018.
  6. Derin, Y.,  E. Anagnostou, M. Anagnostou, J. Kalogiros, D. Casella, A. C. Marra, G. Panegrossi P. Sanò, , Passive Microwave Rainfall Error Analysis Using High- Resolution X-Band Dual-Polarization Radar Observations in Complex Terrain, IEEE Transactions on Geoscience and Remote Sensing pp(99):1-22, DOI 10.1109/TGRS.2017.2763622, 2018
  7. Abdel Wahab, M.M., Essa, Y.H., Khalil, A.A., Elfadli, K., Panegrossi, G., Water loss in Egypt based on the lake nasser evaporation and agricultural evapotranspiration, EnvironmentAsia, 11 (2), pp. 192-204, doi: 10.14456/ea.2018.33, 2018.

2017

  1. Panegrossi G., J-F. Rysman, D. Casella, A. C. Marra, P. Sanò, and M. S. Kulie, CloudSat-based assessment of GPM Microwave Imager snowfall observation capabilities, Rem. Sensing, 9(12), 1263; doi:10.3390/rs9121263, 2017.
  2. Federico, S., M. Petracca, G. Panegrossi, C. Transerici, and S. Dietrich, Impact of lightning data assimilation on the precipitation forecast at different forecast ranges, Adv. in Sci. and Res., 14, 187-194, https://doi.org/10.5194/asr-14-187-2017, 2017.
  3. Casella, D., Panegrossi G., Dietrich S., Marra A.C., Sanò P., M. S. Kulie, B. T. Johnson,  Evaluation of the GPM-DPR snowfall detection capability: comparison with CloudSat, Atmos. Res., 197, 64-75, doi :10.1016/j.atmosres.2017.06.018, 2017
  4. Marra A. C., F. Porcu', L. Baldini, M. Petracca, D. Casella, S. Dietrich, A. Mugnai, P. Sanò, G. Vulpiani, G. Panegrossi, Observational analysis of an exceptionally intense hailstorm over the Mediterranean area: Role of the GPM Core Observatory, Atmos. Res., 182, 72-90, doi: 10.1016/j.atmosres.2017.03.019, 2017
  5. Casella D., L. M. Amaral, S. Dietrich, A. C. Marra, P. Sanò, and G. Panegrossi, The Cloud Dynamics and Radiation Database algorithm for AMSR2: exploitation of the GPM observational dataset for operational applications, IEEE J. of Sel. Topics in Appl. Earth Obs. and Rem. Sens. (J-STARS), 10(8), DOI : 10.1109/JSTARS.2017.2713485, 2017
  6. Federico, S., Petracca, M., Panegrossi, G., and Dietrich, S.: Improvement of RAMS precipitation forecast at the short-range through lightning data assimilation, Nat. Hazards Earth Syst. Sci., 17, 61-76, doi:10.5194/nhess-17-61-2017, 2017.
  7. Ciabatta L., Marra A. C., Panegrossi G., Casella D., Sanò P., Dietrich S., Massari C., Brocca L., Daily precipitation estimation through different microwave sensors: Verification study over Italy, J. of Hydrology, 545, 436-450, doi: 10.1016/j.jhydrol.2016.12.057, 2017.

2016

  1. Sanò, P., Panegrossi, G., Casella, D., Marra, A. C., Di Paola, F., and Dietrich, S.: The new Passive microwave Neural network Precipitation Retrieval (PNPR) algorithm for the cross-track scanning ATMS radiometer: description and verification study over Europe and Africa using GPM and TRMM spaceborne radars, Atmos. Meas. Tech., 9, 5441-5460, doi:10.5194/amt-9-5441-2016, 2016.
  2. Panegrossi G., D. Casella, S. Dietrich, A. C. Marra, M. Petracca, P. Sanò, A. Mugnai, L. Baldini, N. Roberto, E. Adirosi, R. Cremonini, R. Bechini, G. Vulpiani, and F. Porcù: Use of the GPM constellation for monitoring heavy precipitation events over the Mediterranean region, IEEE J. of Sel. Topics in Appl. Earth Obs. and Rem. Sens. (J-STARS), Volume 9, Issue 6, Pages: 2733 - 2753, doi: 10.1109/JSTARS.2016.2520660, 2016.