No abstract

A determination of the aerosol particle size distribution function by using the particle spectrum extinction equation is an ill-posed integral equation of the first kind. To overcome this, we must incorporate regularization techniques. Most of the literature focuses on the Phillips-Twomey regularization or its variations. However, there are drawbacks for some applications in which the real aerosol distributions have large oscillations in a Junge-type distribution. The reason for this is that the scale matrix based on the norm of the second differences in the Phillips-Twomey regularization is too ill- conditioned to filter the large perturbations induced by the small algebraic spectrum of the kernel matrix and the additive noise. Therefore we reexamine the aerosol particle size distribution function retrieval problem and solve it in W1,2 space. This setting is based on Sobolev's embedding theorem in which the approximate solution best simulates the true particle size distribution functions. For choosing the regularization parameters, we also develop an a posteriori parameter choice method, which is based on the discrepancy principle. Our numerical results are based on the remote sensing data measured by the CE318 sunphotometer in Jia Xiang County, Shan Dong Province, China, and are performed to show the feasibility of the proposed algorithms.

The recent slowdown in global warming has initiated a reanalysis of temperature data in some mountainous regions for understanding the consequences and impact that a hiatus has on the climate system. Spatiotemporal temperature variability is analyzed over the Tibetan Plateau because of its sensitivity to climate change with a station network updated to 2014, and its linkages to remote sensing-based variability of MODIS daytime and nighttime temperature are investigated. Results indicate the following: 1) Almost all stations have experienced a notable warming in the time interval 1961-2014, with most obvious warming in winter, which depends on the selected time intervals. 2) There is no clear shift from a predominant warming to a near stagnation during the most recent period (2001-present). 3) Uniform altitudinal dependence of temperature change trends could not be confirmed for all regions, time intervals, and seasons, but sometimes an altitude threshold around 3 km is apparent. 4) Most of the meteorological stations are associated with MODIS temperature warming pixels, and thus regional cooling is missing when considering only the locations of meteorological stations. In summarizing, previous studies based on station observations do not provide a complete picture for the temperature change over the Tibetan Plateau. Remote sensing-based analyses have the potential to find early signals of regional climate changes and assess the impact of global climate changes in complex regional, seasonal, and altitudinal environments.