## 1 Introduction
There has been an increase in the number of studies using remote sensing data [39; 40; 41] to characterize environmental variables in large areas, sometimes with a very low density of in situ data. Validation of this information is required to increase the security of the information generated and to have confidence in the public policies and mitigating actions to be taken based on these data. This information is important for studies on forestbiomass [42; 43] and other applications [44; 45; 46], and although it has good accuracy and validation in some regions, it still requires validation in many remote areas, such as the MODIS products for the Amazon. The Moderate Resolution Imaging Spectroradiometer (MODIS) remote sensing data suggest that photosynthesis in native forests increases as the dry season progresses over a large area of central Amazonia. The MODIS Leaf Area Index (LAI) product shows a pattern of increase during the dry season, peaking at the beginning and in the middle of the dry season [47]. Similarly, the MODIS Enhanced Vegetation Index (EVI) shows that the equatorial forests of Amazonia continue to \"green up\" throughout the dry season as the availability of sunlight increases [48]. [PERSON] et al. [20] showed that the seasonality of GPP measurements and flux tower data have different associations and correlations throughout the year depending on the type of forest, with data being better correlated in certain months of the year and in certain locations, which would make it easier to extrapolate the analysis to a large area with satellite data. Considering the above, it is important to conduct more studies aimed at characterizing the CO\({}_{2}\) exchange environment in areas of the Amazon rainforest with the atmosphere and its relationship with vegetation indices estimated by satellite. Despite many studies on the subject in recent years [16; 49; 50], the Caxiuana region still lacks research into these estimates for longer periods of its data series and with analyses integrated with satellite data, which are important due to the diverse mosaic of natural environments within the Amazon biome. There are particularities in the exchange of water and CO\({}_{2}\) with the atmosphere in the Amazon basin, and there may be areas that are sinks, neutral, or even sources of CO\({}_{2}\) for the atmosphere, especially in the context of climate change and the influence of severe droughts caused by low-frequency phenomena such as ENOS (El Nino Southern Oscillation). It is known that GPP data from eddy covariance towers are not representative of the global distribution of ecosystem types [51; 52], increasing the need for remote sensing approaches to estimate GPP that can provide information on ecosystem dynamics in response to climate variability at both the regional and global scales [52]. As not all environments within the same biome show the same correlations between surface data and satellite data, it is important that more studies perform this survey to validate this information and help improve or adjust estimates where it is not yet efficient. This creates the necessity to understand these cycles, their controls and their influences, which is the purpose of this study, which aims to: (1) characterize diurnal and daily variations in energy and CO\({}_{2}\) fluxes in the Caxiuana forest (Rn, H, LE, NEE); (2) quantify the CO\({}_{2}\) flux (g C m\({}^{-2}\) d\({}^{-1}\)) using metrics including gross primary production (GPP), ecosystem respiration (Reco) and NEE measurements; and (3) analyze the patterns and correlations of the site's gross primary productivity with vegetation indices (NDVI, EVI and LAI from MODIS satellite) and other satellite estimates.