Spatial-Temporal Variability of Land Surface Dry Anomalies in Climatic Aspect: Biogeophysical Insight by Meteosat Observations and SVAT Modeling

Abstract

The spatial-temporal variability of drought occurrence over Bulgaria is characterized based on long-term records (2007–2018) of Meteosat information and the SVAT model-derived soil moisture availability index (referred to root zone depth, SMAI). Land surface temperature according to the satellite-derived Land Surface Analysis Satellite Application Facility Land Surface Temperature (LSASAF LST) product and SMAI were used to designate land surface state dry anomalies. The utility of LST for drought assessment is tested by statistical comparative analyses, applying two approaches, site-scale quantitative comparison, and evaluation of spatial-temporal consistency between SMAI and LST variability. Pearson correlation and regression modeling techniques were applied. The main results indicate for a synchronized behavior between SMAI and LST during dry spells, as follows: opposite mean seasonal course (March–October); high to strong negative monthly correlation for different microclimate regimes. Negative linear regressions between the anomalies of SMAI and LST (monthly mean), with a strong correlation in their spatial-temporal variability. Qualitative evaluation of spatial-temporal variability dynamics is analyzed using color maps. Drought-prone areas were identified on the bases of LST maps (monthly mean), and it is illustrated they are more vulnerable to vegetation burning as detected by the Meteosat FRP-PIXEL product. The current study provides an advanced framework for using LST retrievals based on IR satellite observations from the geostationary MSG satellite as an alternative tool to SMAI, whose calculation requires the input of many parameters that are not always available.

Urban Canyon in the CBD of Rio de Janeiro (Brazil): Thermal Profile of Avenida Rio Branco during Summer

“…Overall, the results suggest that the average LST of the study area was relatively high (Figure 3). Airport (Galeão) [29], was performed in order to qualify the configuration of the thermal field and enable its understanding under the conditions of distinct atmospheric processes. The charts were the basis for visual interpretation and recognition of the atmospheric systems and air masses prevailing on the days of the field experiments, as well as for the comprehension of the impact of synoptic conditions on the variability of the atmospheric parameters registered by the weather station.…”

“…Finally, the analysis of synoptic charts (00Z and 12Z) [27], comprised of the available images from channel 13 of the GOES 16 satellite (00 GMT and 12 GMT) [28] and the radiosonde plots (00 UTC and 12 UTC) captured by the station at Tom Jobim International Airport (Galeão) [29], was performed in order to qualify the configuration of the thermal field and enable its understanding under the conditions of distinct atmospheric processes.…”

“…The images from GOES-16 Infrared channel 1 (IR-1, with 10.35 µ) and channel 13 allowed us to identify the temperature of the cloud tops and thus infer their level of vertical development, which contributed to the knowledge of weather conditions that favor the different magnitudes and intensities of heat islands. On the other hand, the radiosonde plots from Galeão International Airport allowed us to evaluate the vertical variation of temperature in the troposphere, offering parameters for classification of the atmospheric situation (stability, instability and post-instability), like CAPE index [28], criteria for a categorization analysis of field experiments [29].…”

“…An atmosphere considered stable [29,32] is resistant to vertical drafts (updrafts and downdrafts) and tends to return to its initial position. In this case, if the air is forced to rise, it will tend to spread horizontally; if there are cloud formations (altostratus, nimbostratus, or stratus), this process will cause them to spread in the same way and in relatively thin layers.…”

Global Climate Pattern Impacts on Long-Term Olive Yields in Northwestern Africa: Case from Souss-Massa Region

“…In their work Xue et al [51][52][53] suggest a new mechanism that may contribute to extreme events where land surface temperature variability in high elevation influences hydro-climate conditions in downstream areas. The analysis of soil moisture of the top vegetation/soil layer and its anomalies are to take into consideration as parameters of the underlying process, the obtained results from [54,55] indicate a negative linear relationship between soil moisture availability index and land surface temperature during periods of dry land surface anomalies. During events of heatwaves, the surface temperature and soil moisture are strongly influencing the atmosphere temperature and the yields consequently [56].…”