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ABSTRACT Aerosol trends and rates of change were analysed between 2003 and 2013, over both land and ocean, using MODerate resolution Imaging Spectroradiometer (MODIS) monthly aerosol optical thickness ( AOT) products ( MYD08). Unlike previous research, the ensemble empirical mode decomposition ( EEMD) was implemented in this study. Results show that sustained positive or negative trends are globally observed in most areas during the study period. However, increasing rates were decelerated and even became downward trends over western North America, central South America, East China Sea and southeastern China. Comparing EEMD results with linear regression, it is evident that the increasing and decreasing rates from the EEMD method are much stronger. Zonally averaged trends clearly indicate an opposite trend between the southern and northern hemispheres. In addition, this study demonstrates that linear regression may not fit trends statistically in some areas, such as central South America and part of the Indian Ocean. Around 32.74% (12 816) of pixels exhibit low correlation ( r2 = 0.5) between linear and nonlinear trends from EEMD. Approximately 12.46% (4877), 6.56% (2567) and 1.85% (724) of pixels experience significant variations against the F-test, autoregressive process of the first-order for EEMD and linear regression, respectively. The rates of change observed in this study can be used in analysing the long-term effects of aerosols on climate change and earth's radiative budget. [ABSTRACT FROM AUTHOR]

ABSTRACT Water vapour, an important greenhouse gas in the atmosphere, is crucial for hydrological, atmospheric, and meteorological processes. This study first compared five precipitable water vapour ( PWV) products from multi-sensors including radiosonde, AERosol RObotic NETwork ( AERONET) sunphotometer, Global Positioning System ( GPS) and MODerate resolution Imaging Spectroradiometer ( MODIS), and then characterized the spatial and temporal trends of PWV in mainland China. Intercomparison results indicate good agreements among PWV products with correlation coefficients ranging from 0.775 to 0.937. As for spatial analysis, 13 years of MODIS MOD05 products were investigated and the spatial distribution of PWV is closely correlated with the topography, e.g. latitude and altitude, in mainland China. A monotonically increasing annual trend was detected in some radiosonde sites in China between 1976 and 1999, but a decreasing trend was observed between 2000 and 2012. Analysis of the differences in PWV between weekdays and weekends indicated a marked weekend effect, suggesting the influence of anthropogenic activities. Diurnal variations in PWV were also studied from 1999 to 2009 using GPS data. A pronounced diurnal cycle of PWV was observed in most of the sites during summer and spring seasons. [ABSTRACT FROM AUTHOR]

Water vapour is one of green house gases (GHG) and a key parameter affecting weather forecasting. Situated on the edge of the South China Sea and in the path of the wet Asian monsoon, Hong Kong experiences more rainstorms than most other cities. An accurate observation of water vapour has a special significance in severe weather prediction for Hong Kong, one of the cities with the highest density of population in the world. In this paper, water vapour observations over the last 6 years from an AErosol RObotic NETwork (AERONET) sunphotometer, 9 years from the MODerate resolution Imaging Spectroradiometer (MODIS) TERRA satellite images and 38 years from radiosonde were analysed and cross-validated. The operational MODIS water vapour products, namely MOD05 and MOD07, with a spatial resolution of 1 and 5 km, respectively, were compared with both radiosonde and AERONET data. The correlation coefficients between MODIS water vapour products and radiosonde data are r = 0.878 and 0.876 for MOD05 and MOD07 products, and the correlations of those with AERONET data are r = 0.822, r = 0.976, respectively. The results also indicate that radiosonde and AERONET water vapour observations have a good agreement, with a correlation of r = 0.988 and a small mean absolute difference (MAD), and root mean square error (RMS) of 0.197 and 0.289 cm, respectively. Although the satellite data (with a frequency of once per day) represent water vapour coverage of all the territories of Hong Kong, they do not meet short-term weather prediction demand due to their low temporal resolution. Radiosonde observations with a frequency of twice per day are also temporally inadequate. This study demonstrates that the AERONET sunphotometer can provide accurate and high temporal resolution water vapour data which can be used for short-term weather prediction and long-term climate change research. Copyright © 2011 Royal Meteorological Society [ABSTRACT FROM AUTHOR]

Modeling thematic and spatial dynamic behaviors of urban heat islands (UHIs) over time is important for understanding the evolution of this phenomenon to mitigate the warming effect in urban areas. Although previous studies conceptualized that a UHI only has a single life cycle with spatial behaviors, a UHI can be detected to appear and disappear several times periodically in terms of thematic and spatial integrated behaviors. Such multiple behaviors have not yet been illustrated with proof or evidence. This study conceptualizes a UHI as an object which has thematic and spatial behaviors simultaneously and proposes several graphs to depict periodic life‐cycle transitions triggered by behaviors. The conceptualized behaviors have been modeled and implemented in an object‐relational database management system and temperature readings collected from numerous weather stations were interpolated as temperature images per hour. The results of this study indicate that the model could track the spatial and thematic evolution of UHIs continuously and reveal their periodical patterns and abnormal cases. [ABSTRACT FROM AUTHOR]

This study compares the space‐time patterns and characteristics of high‐risk areas of COVID‐19 transmission in Hong Kong between January 23 and April 14 (the first and second waves) and between July 6 and August 29 (the third wave). Using space‐time scan statistics and the contact tracing data of individual confirmed cases, we detect the clusters of residences of, and places visited by, both imported and local cases. We also identify the built‐environment and demographic characteristics of the high‐risk areas during different waves of COVID‐19. We find considerable differences in the space‐time patterns and characteristics of high‐risk residential areas between waves. However, venues and buildings visited by the confirmed cases in different waves have similar characteristics. The results can inform policymakers to target mitigation measures in high‐risk areas and at vulnerable groups, and provide guidance to the public to avoid visiting and conducting activities at high‐risk places. [ABSTRACT FROM AUTHOR]

The surface urban heat island intensity (SUHII) when using nadir‐viewing radiometric and complete surface temperature (Tr and Tc) was evaluated. The urban areas of the Kowloon peninsula and Hong Kong Island were selected and four daytime Landsat TM images and two nighttime ASTER images were collected to retrieve Tr and then model Tc based on a semi‐empirical model. SUHIIs were estimated using both the retrieved Tr and modelled Tc. High spatial resolution (HR) airborne thermal images (0.2 m) observed at 12:10 noon on Oct 24, 2017 were used to retrieve Tc directly. Results based on HR data and satellite data were consistent and indicated that the geometry of the built‐up space had a larger impact on SUHII when using Tc (SUHIIc) than Tr (SUHIIr). During daytime SUHIIc decreased while SUHIIr showed a very slight increase with building density. Both SUHIIc and SUHIIr decreased with higher building height but the rate of decrease of SUHIIc was higher than SUHIIr. Both SUHIIc and SUHIIr decreased with increasing building height variance and increased with increasing sky view factor (SVF). The rate of decrease with building height variance for SUHIIc was larger than SUHIIr. The rate of increase of SUHIIc with SVF was higher than SUHIIr. During nighttime, geometry effects on SUHIIc and SUHIIr were different from daytime. Both SUHIIc and SUHIIr increased with building density, while the rate of increase of SUHIIc with building density, as well as with building height, was much higher than SUHIIr. Both SUHIIc and SUHIIr decreased with SVF, but the rate of decrease of SUHIIc was higher than SUHIIr. Both SUHIIc and SUHIIr initially increased with building height variance and then remained approximately constant. We also evaluated the UHI intensity: SUHIIc was much closer to UHII than SUHIIr. Overall, building geometry had larger impact on SUHIIc than on SUHIIr, that is, SUHIIc is more representative of urban climate than SUHIIr. [ABSTRACT FROM AUTHOR]