@Article{GonçalvesSNBMCHT:2006:EvMoRe,
author = "De Gon{\c{c}}alves, L. G. and Shuttleworth, W. James and Nijssen,
Bart and Burke, Eleanor J. and Marengo, Jose Antonio and Chan,
Chou Sin and Houser, Paul and Toll, David L.",
affiliation = "{Nasa Goddard Space Flight Center} and Department of Hydrology and
Water Resources, University of Arizona and Department of Hydrology
and Water Resources, University of Arizona and Hadley Centre for
Climate Prediction and Research, Met Office, Exeter, UK and
{Instituto Nacional de Pesquisas Espaciais (INPE)} and {Instituto
Nacional de Pesquisas Espaciais (INPE)} and Center for Research on
Environment and Water, George Mason University and Hydrological
Sciences Branch, Code 614.3, NASA Goddard Space Flight Center",
title = "Evaluation of model-derived and remotely sensed precipitation
products for continental South America",
journal = "Revista Brasileira de Geof{\'{\i}}sica",
year = "2006",
volume = "111",
number = "D16113",
pages = "doi:10.1029/2005JD006276",
month = "Ago",
note = "doi:10.1029/2005JD006276",
keywords = "precipitation, South America, remotely sensed evaluation.",
abstract = "This paper investigates the reliability of some of the more
important remotely sensed daily precipitation products available
for South America as a precursor to the possible implementation of
a South America Land Data Assimilation System. Precipitation data
fields calculated as 6 hour predictions by the CPTEC Eta model and
three different satellite-derived estimates of precipitation
(Precipitation Estimation from Remotely Sensed Information using
Artificial Neural Networks (PERSIANN), National Environmental
Satellite, Data and Information Service (NESDIS), and Tropical
Rainfall Measuring Mission (TRMM)) are compared with the available
observations of daily total rainfall across South America. To make
this comparison, the threat score, fractional-covered area, and
relative volumetric bias of the model-calculated and remotely
sensed estimates are computed for the year 2000. The results show
that the Eta model-calculated data and the NESDIS product capture
the area without precipitation within the domain reasonably well,
while the TRMM and PERSIANN products tend to underestimate the
area without precipitation and to heavily overestimate the area
with a small amount of precipitation. In terms of precipitation
amount the NESDIS product significantly overestimates and the TRMM
product significantly underestimates precipitation, while the Eta
model-calculated data and PERSIANN product broadly match the
domain average observations. However, both tend to bias the zonal
location of precipitation more heavily toward the equator than the
observations. In general, the Eta model-calculated data outperform
the several remotely sensed data products currently available and
evaluated in the present study.",
copyholder = "SID/SCD",
issn = "0102-261X",
language = "en",
targetfile = "Goncalves_Evaluation.pdf",
urlaccessdate = "15 jun. 2024"
}