Assessment of Satellite-Based Rainfall Products Using a X-Band Rain Radar Network in the Complex Terrain of the Ecuadorian Andes

Ground based rainfall information is hardly available in most high mountain areas of the world due to the remoteness and complex topography. Thus, proper understanding of spatio-temporal rainfall dynamics still remains a challenge in those areas. Satellite-based rainfall products may help if their rainfall assessment are of high quality. In this paper, microwave-based integrated multi-satellite retrieval for the Global Precipitation Measurement (GPM) (IMERG) (MW-based IMERG) was assessed along with the random-forest-based rainfall (RF-based rainfall) and infrared-only IMERG (IR-only IMERG) products against the quality-controlled rain radar network and meteorological stations of high temporal resolution over the Pacific coast and the Andes of Ecuador. The rain area delineation and rain estimation of each product were evaluated at a spatial resolution of 11 km2 and at the time of MW overpass from IMERG. The regionally calibrated RF-based rainfall at 2 km2 and 30 min was also investigated. The validation results indicate different essential aspects: (i) the best performance is provided by MW-based IMERG in the region at the time of MW overpass; (ii) RF-based rainfall shows better accuracy rather than the IR-only IMERG rainfall product. This confirms that applying multispectral IR data in retrieval can improve the estimation of rainfall compared with single-spectrum IR retrieval algorithms. (iii) All of the products are prone to low-intensity false alarms. (iv) The downscaling of higher-resolution products leads to lower product performance, despite regional calibration. The results show that more caution is needed when developing new algorithms for satellite-based, high-spatiotemporal-resolution rainfall products. The radar data validation shows better performance than meteorological stations because gauge data cannot correctly represent spatial rainfall in complex topography under convective rainfall environments.

Elastic Reverse-Time Migration with Complex Topography

Migration is an important step in seismic data processing for oil and gas exploration. The accuracy of migration directly affects the accuracy of subsequent oil and gas reservoir characterization. Reverse-time migration is one of the most accurate migration methods at present. Multi-wave and multicomponent seismic data contain more P- and S-wave information. Making full use of multi-wave and multicomponent seismic data can offer more information about underground structure and lithology, as well as improve the accuracy of seismic exploration. Elastic reverse-time migration (ERTM) has no dip restriction and can be applied to image multi-wave and multicomponent seismic data in complex structural areas and some special lithology structures. However, the surface topography of complex regions has an influence on wavefield and seriously degrades the quality of ERTM’s migration results. We developed a new ERTM method to migrate multi-wave and multicomponent seismic data in the region with complex surface topography. We first fill the layers between the highest and lowest undulating surface with near-surface elastic parameters in a complex topography model to obtain a new model with a horizontal surface. This allows the finite difference (FD) method based on the regular rectangular grid to be used to numerically solve elastic wave equations in the model with complex topography. The decoupled wave equations are used to generate source P- and S-waves and receiver P- and S-waves to reduce crosstalk artefacts in ERTM. A topography-related filter is further used to remove the influence of surface topography on migration results. The scalar imaging condition is also applied to generate PP and PS migration images. Some numerical examples with different complex topographies demonstrate that our proposed ERTM method can remove the influence of complex topography on ERTM’s images and effectively generate high-quality ERTM images.

Evaluation and Improvement of FY-4A AGRI Quantitative Precipitation Estimation for Summer Precipitation over Complex Topography of Western China

Satellite quantitative precipitation estimation (QPE) can make up for the insufficiency of ground observations for monitoring precipitation. Using an Advanced Geosynchronous Radiation Imager (AGRI) on the FengYun-4A (FY-4A) satellite and rain gauges (RGs) for observations in the summer of 2020. The existing QPE of the FY-4A was evaluated and found to present poor accuracy over the complex topography of Western China. Therefore, to improve the existing QPE, first, cloud classification thresholds for the FY-4A were established with the dynamic clustering method to identify convective clouds. These thresholds consist of the brightness temperatures (TBs) of FY-4A water vapor and infrared channels, and their TB difference. Then, quantitative cloud growth rate correction factors were introduced to improve the QPE of the convective-stratiform technique. This was achieved using TB hourly variation rates of long-wave infrared channel 12, which is able to characterize the evolution of clouds. Finally, the dynamic time integration method was designed to solve the inconsistent time matching between the FY-4A and RGs. Consequently, the QPE accuracy of the FY-4A was improved. Compared with the existing QPE of the FY-4A, the correlation coefficient between the improved QPE of the FY-4A and the RG hourly precipitation increased from 0.208 to 0.492, with the mean relative error and root mean squared error decreasing from −47.4% and 13.78 mm to 8.3% and 10.04 mm, respectively. However, the correlation coefficient is not sufficiently high; thus, the algorithm needs to be further studied and improved.

Thermally and Dynamically Driven Atmospheric Circulations over Heterogeneous Atmospheric Boundary Layer: Support for Safety Protocols and Environment Management at Nuclear Central Areas

Ilha Grande Bay is located in Angra dos Reis, Rio de Janeiro State, Brazil. The area is characterized by different land cover, complex topography and proximity to the Atlantic Ocean. These aspects make it susceptible to thermally and dynamically induced atmospheric circulations such as those associated with valley/mountain and land/sea breeze systems, among others. The Almirante Álvaro Alberto Nuclear Complex (CNAAA) is located in this region, with a total of two nuclear power plants (NPPs) in operation in the Brazilian territory, Angra I and Angra II. Therefore, knowledge of local atmospheric circulation has become a matter of national and international security. Considering the importance of the meteorological security tool as a support for licensing, installation, routine operation and nuclear accident mitigation, the main aim of this study is the development of combined strategies of environmental statistical modeling in the analysis of thermally and dynamically driven atmospheric circulations over mountainous and coastal environments. We identified and hierarchized the influence of the thermally and mechanically driven forcing on the wind regime and stability conditions in the coastal atmospheric boundary layer over the complex topography region. A meteorological network of ground-based instruments was used along with physiographic information for the observational characterization of the atmospheric patterns in the spatial and time–frequency domain. The predominant wind directions and intensity are attributed to the combined action of multiscale weather systems, notably, the valley/mountain and continent/ocean breeze circulations, the forced channeling due to valley axis orientation, the influence of the synoptic scale systems and atmospheric thermal tide. The observational investigation of the combined influence of terrain effects and meteorological systems aimed to understand the local atmospheric circulation serves as support for safety protocols of the NPPs, contemplating operation and environmental management. The importance of the study for the adequacy and skill evaluation of computational modeling systems for atmospheric dispersion of pollutants such as radionuclide and conventional contaminants can be also highlighted, in order that such systems are used as tools for environmental planning and managing nuclear operations, particularly those located in regions over mountainous and coastal environments with a heterogeneous atmospheric boundary layer.

The biogeography of the Mediterranean Taurus Mountains: Illustrating how complex topography and climatic conditions have shaped their biodiversity

Climate is well known as the main driver of species distributions. In this study, I focused on Geyik Mountains and surrounding areas to illustrate how complex topography and climatic conditions have shaped the distribution patterns of species/communities and therefore the biodiversity of the Mediterranean Taurus Mountains, one of the most biologically diverse areas in the Mediterranean Basin biodiversity hotspot. Accordingly, I used an ecological niche modelling approach, which has been widely used in recent biogeographic studies. I chose Taurus ground squirrels (Spermophilus taurensis) and coniferous forests as the representatives of high- and low-altitude species/communities, respectively. The results simply illustrate how complex topography and temperature and precipitation gradients have had a substantial role in shaping the distribution patterns of species/communities and therefore the biodiversity of the Mediterranean Taurus Mountains.