Soil surface roughness (SSR) is an important indicator that characterizes the microtopography feature of farmland after tillage. It has a high practical value for sowing and seedling raising, farmland management, and drainage irrigation in agricultural production. The traditional method often is prone to damage the surface microstructure and results in low efficiency and accuracy. In this study, a new method was proposed to address the limitations of traditional measurement methods of SSR. The proposed measurement and evaluation method of farmland microtopography feature information based on 3D lidar and inertial measurement unit (IMU) could be used to quickly obtain the global point cloud map containing the height data of the test field. Taking three different tillage methods of farmland as the research object, the surface root mean square height (RMSH), correlation length (CL), and their ratio were selected as roughness parameters to explore the anisotropy of microtopography features in different directions. The measurement method was then used to study the effects of sampling processing methods (number, interval, and length) on the measurement accuracy in both OX and OY directions. The results indicate that under the same accuracy requirements, for the 2 x 2 m area, the farmland with different microtopography features needs to be processed with different sample numbers, sample intervals, and sample lengths. The optimal combination of sample parameters for Test field I is sample number of 50, sample interval of 120 mm, and sample interval of 1600 mm, and that in Test field II is sample number of 50, sample interval of 160 mm, and sample interval of 1800 mm. For Test field III, the optimal combination is sample number of 100, sample interval of 40 mm, and sample length of 1200 mm. The experimental results compared with the traditional method illustrate the high accuracy and good feasibility of the proposed method for measuring and evaluating the microtopography feature information of the farmland. The results of the study help to understand the microtopography features and its parameterization of the farmland after tillage, which could further reveal the role and significance of SSR parameters in objectively evaluating farmland tillage quality and optimizing farmland management.

The radiative forcing of soot is dependent on the morphology, mixing state and structure. Cloud processing has been predicted to affect their mixing properties but little is known about the resulting light absorption properties. We collected ambient particles in the pre-cloud period, the cloud residues and interstitials in the in-cloud period at Mt. Tianjing (southern China). The morphology parameters of soot aggregates with varying mixing materials [sulfate (S) and organics (OM)] and mixing structures were investigated by a transmission electron microscope, and their absorption cross were calculated based on discrete dipole approximation. We found that the number contribution of soot-S decreased from 45% in the pre-cloud period to 32% in the in-cloud period, and that of soot-OM increased from 44% to 60%. Moreover, the number proportion of soot-OM with fully embedded structure increased remarkably in the in-cloud period (29%), compared with that in the pre-cloud period (3%). In addition, the soot-S aggregates became denser after in-cloud aqueous process. However, for soot-OM aggregates, the morphology remained relatively constant. The distinctly different change of soot-S and soot-OM in morphology highlights the chemically resolved reconstruction of soot morphology. Theoretical calculation further shows that the changes of soot particles in the mixing state and morphological characteristics by the cloud process resulted in the light absorption enhancement increase from 1.57 to 2.01. This study highlights that the evolution of microphysical properties upon cloud processing should also be considered in climate models to more accurately evaluate the impacts of soot particles.

Freshly emitted soot particles are fractal-like aggregates, but atmospheric processes often transform their morphology. Morphology of soot particles plays an important role in determining their optical properties, life cycle and hence their effect on Earth's radiative balance. However, little is known about the morphology of soot particles that participated in cold cloud processes. Here we report results from laboratory experiments that simulate cold cloud processing of diesel soot particles by allowing them to form supercooled droplets and ice crystals at -20 and -40 degrees C, respectively. Electron microscopy revealed that soot residuals from ice crystals were more compact (roundness similar to 0.55) than those from supercooled droplets (roundness similar to 0.45), while nascent soot particles were the least compact (roundness similar to 0.41). Optical simulations using the discrete dipole approximation showed that the more compact structure enhances soot single scattering albedo by a factor up to 1.4, thereby reducing the top-of-the-atmosphere direct radiative forcing by similar to 63%. These results underscore that climate models should consider the morphological evolution of soot particles due to cold cloud processing to improve the estimate of direct radiative forcing of soot.