Yulei Chi

• Doctor of Education
• PhD Student at Beijing Normal University

The impact of aerosols on clouds, which remains one of the largest aspects of uncertainty in current weather forecasting and climate change research, can be influenced by various factors, such as the underlying surface type, cloud type, cloud phase, and aerosol type. To explore the impact of different underlying surfaces on the effect of aerosols o...

Plain Language Summary The Arctic Dipole Anomaly is one of the principal atmospheric circulation patterns in the Arctic region, significantly influencing the spatial distribution of sea ice through induced changes in polar wind directions. These wind changes also affect the fraction of Arctic clouds and, by modifying cloud‐surface radiative forcing...

As a core element of weather and climate change research, convective clouds have complex physical structures and dynamic processes, and knowledge of their evolution is limited by remote sensing data along with detection and tracking algorithms. In this study, we construct convective cloud detection and tracking algorithms for the Himawari-8 AHI dat...

Using the CloudSat and CALIPSO active remote sensing dataset from 2006 to 2017, this study investigates the spatial and temporal distribution along with vertical distribution of cloud macrophysical characteristics in six study areas over China mainland and east coast (15°–55°N, 70°–140°E). The results show that the cloud top height and cloud base h...

Clouds play a significant role in the climate system, which affects the radiation balance and modulates the global hydrological cycle. However, the existing cloud property products have poor spatiotemporal continuity with only daytime cloud property retrieval results, which makes it challenging for us to carry out researches related to clouds at ni...

Aerosol first indirect effect (FIE), which causes variations of cloud droplet effective radius (re) and then cloud radiative effect (CRE), is one of the critical factors leading to uncertainties in climate model simulations. Different from most previous studies over continental regions, using 10-year observation data from CERES, this study investig...

Particulate matter 2.5 (PM2.5) pollution has long been a global environmental problem and still poses a great threat to public health. This study investigates global spatiotemporal variations in PM2.5 using the newly developed satellite-derived PM2.5 dataset from 1998 to 2018. An integrated exposure-response (IER) model was employed to examine the...

Most current scientific research on NO2 remote sensing focuses on tropospheric NO2 column concentrations rather than ground-level NO2 concentrations; however, ground-level NO2 concentrations are more related to anthropogenic emissions and human health. This study proposes a machine learning estimation method for retrieving the ground-level NO2 conc...

Although the ground-level NO2 measurement from air quality monitoring sites is relatively accurate, it is a challenge to obtain continuous spatial coverage due to the discrete distribution of sites. Thus, the tropospheric column NO2 amount from satellites with wide spatial and temporal coverage and higher resolution has been increasingly used to es...

Universal Dynamic Threshold Cloud Detection Algorithm (UDTCDA) is a recently proposed cloud detection algorithm for remote sensing image with the support of a prior land surface reflectance database. In the visible and near infrared bands, the overall accuracy of cloud detection is still low due to the similar spectral characteristics of some brigh...

Herein, we propose an improved dynamic threshold cloud detection algorithm (I-DTCDA) for visible infrared imaging radiometers (VIIRS) based on the multi-channel, wide coverage, and short revisit period features of a VIIRS.In addition, the algorithm is also based on the characteristics of the cloud distributions and variations in the visible and the...

In terms of traditional threshold methods, uniform thresholds are used for cloud detection for remote sensing images; however, due to complex surface structures and cloud status, such an approach is usually difficult to effectively implement for the high-precision cloud detection of images. To solve this problem, a new cloud detection algorithm is...