Data from: Modeling seasonal surface temperature variations in secondary tropical dry forests

Secondary tropical dry forests (TDFs) provide important ecosystem services
such as carbon sequestration, biodiversity conservation, and nutrient
cycle regulation. However, their biogeophysical processes at the
canopy-atmosphere interface remain unknown, limiting our understanding of
how this endangered ecosystem influences, and responds to the ongoing
global warming. To facilitate future development of conservation policies,
this study characterized the seasonal land surface temperature (LST)
behavior of three successional stages (early, intermediate, and late) of a
TDF, at the Santa Rosa National Park (SRNP), Costa Rica. A total of 38
Landsat-8 Thermal Infrared Sensor (TIRS) data and the Surface Reflectance
(SR) product were utilized to model LST time series from July 2013 to July
2016 using a radiative transfer equation (RTE) algorithm. We further
related the LST time series to seven vegetation indices which reflect
different properties of TDFs, and soil moisture data obtained from a
Wireless Sensor Network (WSN). Results showed that the LST in the dry
season was 15–20 K higher than in the wet season at SRNP. We found that
the early successional stages were about 6–8 K warmer than the
intermediate successional stages and were 9–10 K warmer than the late
successional stages in the middle of the dry season; meanwhile, a minimum
LST difference (0–1 K) was observed at the end of the wet season. Leaf
phenology and canopy architecture explained most LST variations in both
dry and wet seasons. However, our analysis revealed that it is
precipitation that ultimately determines the LST variations through both
biogeochemical (leaf phenology) and biogeophysical processes
(evapotranspiration) of the plants. Results of this study could help
physiological modeling studies in secondary TDFs.