@Article{GuSCGLMWANMMORNS:2004:WeDrSu,
author = "Gu, Jiujing and Smith, Eric A. and Cooper, Harry J. and Grose,
Andrew and Liu, Guosheng and Merritt, James D. and Waterloo,
Maarten J. and Ara{\'u}jo, Alessandro C. de and Nobre, Antonio D.
and Manzi, Antonio Ocimar and Marengo, Jos{\'E} Antonio and
Oliveira, Paulo J. de and von Randow, Celso and Norman, John and
Silva Dias, Pedro Leite",
affiliation = "The Florida State University, Department of Meteorology and NASA
and The Florida State University, Department of Meteorology and
The Florida State University, Department of Meteorology and The
Florida State University, Department of Meteorology and The
Florida State University, Department of Meteorology and {Vrije
Universiteit Amsterdan} and {Instituto Nacional de Pesquisas da
Amaz{\^o}nia (INPA)} and {Instituto Nacional de Pesquisas da
Amaz{\^o}nia (INPA)} and Instituto Nacional de Pesquisas
Espaciais, Centro de Previs{\~a}o do Tempo e Estudos
Clim{\'a}ticos (INPE.CPTEC) and Instituto Nacional de Pesquisas
Espaciais, Centro de Previs{\~a}o do Tempo e Estudos
Clim{\'a}ticos (INPE.CPTEC) and Instituto Nacional de Pesquisas
Espaciais, Centro de Previs{\~a}o do Tempo e Estudos
Clim{\'a}ticos (INPE.CPTEC) and Instituto Nacional de Pesquisas
Espaciais, Centro de Previs{\~a}o do Tempo e Estudos
Clim{\'a}ticos (INPE.CPTEC) and University of Wisconsin,
Department of Soil Science and Universidade de S{\~a}o Paulo,
Departamento de Ci{\^e}ncias Atmosf{\'e}ricas (USP)",
title = "Modeling Carbon Sequestration over the Large-Scale Amazon Basin,
Aided by Satellite Observations. Part I: Wet- and Dry-Season
Surface Radiation Budget Flux and Precipitation Variability Based
on GOES Retrievals",
journal = "Journal of Applied Meteorology",
year = "2004",
volume = "43",
number = "6",
pages = "870--886",
month = "june",
keywords = "METEOROLOGY, Amaz{\^o}nia region, Satellites, Dry season,
METEOROLOGIA, Regi{\~a}o amaz{\^o}nica, Sat{\'e}lites,
Esta{\c{c}}{\~a}o seca.",
abstract = "In this first part of a two-part investigation, large-scale
Geostationary Operational Environmental Satellite (GOES) analyses
over the Amaz{\^o}nia region have been carried out for March and
October of 1999 to provide detailed information on surface
radiation budget (SRB) and precipitation variability. SRB fluxes
and rainfall are the two foremost cloud-modulated control
variables that affect land surface processes, and they require
specification at spacetime resolutions concomitant with the
changing cloud field to represent adequately the complex coupling
of energy, water, and carbon budgets. These processes ultimately
determine the relative variations in carbon sequestration and
carbon dioxide release within a forest ecosystem. SRB and
precipitation retrieval algorithms using GOES imager measurements
are used to retrieve surface downward radiation and surface rain
rates at high spacetime resolutions for large-scale carbon budget
modeling applications in conjunction with the Large-Scale
BiosphereAtmosphere Experiment in Amaz{\^o}nia. To validate the
retrieval algorithms, instantaneous estimates of SRB fluxes and
rain rates over 8 km × 8 km areas were compared with
30-min-averaged surface measurements obtained from tower sites
located near Ji-Paran{\'a} and Manaus in the states of
Rond{\^o}nia and Amazonas, respectively. Because of large aerosol
concentrations originating from biomass burning during the dry
season (i.e., September and October for purposes of this
analysis), an aerosol index from the Total Ozone Mapping
Spectrometer is used in the solar radiation retrieval algorithm.
The validation comparisons indicate that bias errors for incoming
total solar, photosynthetically active radiation (PAR), and
infrared flux retrievals are under 4%, 6%, and 3% of the mean
values, respectively. Precision errors at the analyzed space time
scales are on the order of 20%, 20%, and 5%. The visible and
infrared satellite measurements used for precipitation retrieval
do not directly detect rainfall processes, and yet they are
responsive to the rapidly changing cloud fields, which are
directly associated with precipitation life cycles over the Amazon
basin. In conducting the validation analysis at high spacetime
scales, the comparisons indicate systematic bias uncertainties on
the order of 25%. These uncertainties are comparable to published
values from an independent assessment of bias uncertainties
inherent to the current highest-quality satellite retrievals, that
is, from the Tropical Rainfall Measuring Mission. Because
precipitation is a weak direct control on photosynthesis for the
Amazon ecosystem, that is, photosynthesis is dominated by the
strong diurnal controls of incoming PAR and ambient air-canopy
temperatures, such uncertainties are tolerable. By the same token,
precipitation is a strong control on soil thermal properties and
carbon respiration through soil moisture, but the latter is a
time-integrating variable and thus inhibits introduction of
modeling errors caused by random errors in the precipitation
forcing. The investigation concludes with analysis of the monthly,
daily, and diurnal variations intrinsic to SRB and rainfall
processes over the Amazon basin, including explanations of how
these variations arise during wet- and dry-season periods.",
copyholder = "SID/SCD",
issn = "0894-8763",
language = "en",
targetfile = "Gu_Modeling carbon_part 1.pdf",
urlaccessdate = "20 abr. 2024"
}