PROBABILITY OF EXTREME RAINFALL EVENTS BASED ON DIFFERENT GREENHOUSE GASES EMISSION RATES: A FLEXIBLE NON-LINEAR MODELLING. Dataset and scripts

Published: 6 October 2020| Version 1 | DOI: 10.17632/d3y48gmwzv.1
Contributors:
Ana Carolina Freitas Xavier,
,

Description

This database and scripts were used to process climatological data from the NEX-GDDP models for São Paulo for the execution of the doctorate in Tropical and Subtropical Agriculture by Ana Carolina Freitas Xavier. __________________________________________________ Folders: NEX-GDDP-SP-HIST: models extracted from a list of better weather stations in São Paulo state (list-lat-long-better.csv) from 1950 to 2005 (historical period). Temporal resolution: daily. NEX-GDDP-SP-RCP45: models extracted from a list of better weather stations in São Paulo state (list-lat-long-better.csv) from 2006 to 2100 (RCP 4.5 W m-2).Temporal resolution: daily. NEX-GDDP-SP-RCP85: models extracted from a list of better weather stations in São Paulo state (list-lat-long-better.csv) from 2006 to 2100 (RCP 8.5 W m-2). Temporal resolution: daily. NEX-GDDP source: https://www.nccs.nasa.gov/services/data-collections/land-based-products/nex-gddp Maps: Maps provided by GEV-CDN (block of maxima time series, cumulative probabilities, and values of GEV parameters). Scripts: scripts were used to process the netcdf files and the GEV-CDN (setup defined and evaluated by Xavier, A. C. F., Blain, G. C., Morais, M. V. B. D., & Sobierajski, G. D. R. (2019). Selecting “the best” nonstationary Generalized Extreme Value (GEV) distribution: on the influence of different numbers of GEV-models. Bragantia, 78(4), 606-621.)

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Change in Climate Extremes

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