%0 Journal Article
%4 sid.inpe.br/mtc-m21d/2022/04.01.16.02
%2 sid.inpe.br/mtc-m21d/2022/04.01.16.02.18
%@doi 10.1007/s11069-021-05147-0
%@issn 0921-030X
%T Aridity indices to assess desertification susceptibility: a methodological approach using gridded climate data and cartographic modeling
%D 2022
%8 Jan.
%9 journal article
%A Santos, Janaina Cassiano dos,
%A Lyra, Gustavo Bastos,
%A Abreu, Marcel Carvalho,
%A Oliveira Júnior, José Francisco,
%A Bohn, Loonardo,
%A Cunha Zeri, Gisleine da Silva,
%A Zeri, Marcelo,
%@affiliation Universidade Federal Fluminense (UFF)
%@affiliation Universidade Federal Rural do Rio de Janeiro (URRFJ)
%@affiliation Universidade Federal Rural do Rio de Janeiro (URRFJ)
%@affiliation Universidade Federal de Alagoas (UFAL)
%@affiliation Universidade Federal do Rio Grande do Sul (UFRGS)
%@affiliation Instituto Nacional de Pesquisas Espaciais (INPE)
%@affiliation Centro Nacional de Monitoramento e Alertas de Desastres Naturais (CEMADEN)
%@electronicmailaddress gblyra@ufrrj.br
%@electronicmailaddress
%@electronicmailaddress
%@electronicmailaddress
%@electronicmailaddress
%@electronicmailaddress giscunhazeri@gmail.com
%B Natural Hazards
%V 111
%P 2531-2558
%K Land degradation, Spatial modeling, Geoprocessing, Climate.
%X Desertification is a land degradation phenomenon with dire and irreversible consequences, affecting different regions of the world. Assessment of spatial climate susceptibility to desertification requires long-term averages of precipitation (P) and potential evapotranspiration (PET). An alternative to desertification susceptibility analysis is the use of spatially gridded climate data. The aim of this study was to assess an approach based on gridded climate data and cartographic modeling to characterize climate susceptibility to desertification over Southeast Brazil. Two indices were used to identify climate desertification susceptibility: the aridity index I-a (P/PET) and D (PET/P). Precipitation gridded data from the Global Precipitation Climatology Centre (GPCC), and air temperature from the Global Historical Climatology Network (GHCN) were used. The PET was estimated by the Thornthwaite's method using air temperature data. The assessment of these gridded climate series, PET and indices was performed using independent observed climate series (1961-2010) from the National Institute of Meteorology (INMET) of Brazil-(68 weather stations). Determination coefficient (r(2)) and the Willmott's coefficient (d) between gridded and observed data revealed satisfactory precision and agreement for grids of precipitation (r(2) > 0.93, d > 0.90), air temperature (r(2) > 0.94, d > 0.53) and PET (r(2) > 0.93, d > 0.63). Overall, the aridity indices based on climate gridded presented good performance when used to identify areas susceptible to desertification. Susceptible areas to desertification were identified by the index I-a over the Northern regions of Minas Gerais and Rio de Janeiro states. No susceptible areas to desertification were identified using the index D. However, both indices indicated large areas of sub-humid climate, which can be strongly affected by desertification in the future.
%@language en
%3 Santos_2022_aridity.pdf