A hierarchical Bayesian spatio-temporal model for extreme precipitation events

2011 ◽  
Vol 22 (2) ◽  
pp. 192-204 ◽  
Author(s):  
Souparno Ghosh ◽  
Bani K. Mallick
Keyword(s):  
Extreme Precipitation ◽  
Hierarchical Bayesian ◽  
Extreme Precipitation Events ◽  
Temporal Model ◽  
Spatio Temporal ◽  
Precipitation Events

scholarly journals Recognizing the Aggregation Characteristics of Extreme Precipitation Events Using Spatio-Temporal Scanning and the Local Spatial Autocorrelation Model

Atmosphere ◽  
2021 ◽  
Vol 12 (2) ◽  
pp. 218
Author(s):  
Changjun Wan ◽  
Changxiu Cheng ◽  
Sijing Ye ◽  
Shi Shen ◽  
Ting Zhang
Keyword(s):  
Spatial Autocorrelation ◽  
Extreme Precipitation ◽  
Eastern China ◽  
Temporal Aggregation ◽  
Global Changes ◽  
Percentile Method ◽  
Extreme Precipitation Events ◽  
Spatio Temporal ◽  
Precipitation Events ◽  
Local Spatial Autocorrelation

Precipitation is an essential climate variable in the hydrologic cycle. Its abnormal change would have a serious impact on the social economy, ecological development and life safety. In recent decades, many studies about extreme precipitation have been performed on spatio-temporal variation patterns under global changes; little research has been conducted on the regionality and persistence, which tend to be more destructive. This study defines extreme precipitation events by percentile method, then applies the spatio-temporal scanning model (STSM) and the local spatial autocorrelation model (LSAM) to explore the spatio-temporal aggregation characteristics of extreme precipitation, taking China in July as a case. The study result showed that the STSM with the LSAM can effectively detect the spatio-temporal accumulation areas. The extreme precipitation events of China in July 2016 have a significant spatio-temporal aggregation characteristic. From the spatial perspective, China’s summer extreme precipitation spatio-temporal clusters are mainly distributed in eastern China and northern China, such as Dongting Lake plain, the Circum-Bohai Sea region, Gansu, and Xinjiang. From the temporal perspective, the spatio-temporal clusters of extreme precipitation are mainly distributed in July, and its occurrence was delayed with an increase in latitude, except for in Xinjiang, where extreme precipitation events often take place earlier and persist longer.

scholarly journals Spatio-Temporal Distribution of Deep Convection Observed along the Trans-Mexican Volcanic Belt

2021 ◽  
Vol 13 (6) ◽  
pp. 1215
Author(s):  
José Francisco León-Cruz ◽  
Cintia Carbajal Henken ◽  
Noel Carbajal ◽  
Jürgen Fischer
Keyword(s):  
Extreme Precipitation ◽  
Deep Convection ◽  
Temporal Distribution ◽  
Volcanic Belt ◽  
Convective Cloud ◽  
Extreme Precipitation Events ◽  
Mexican Volcanic Belt ◽  
Spatio Temporal ◽  
Terrain Features ◽  
Precipitation Events

Complex terrain features—in particular, environmental conditions, high population density and potential socio-economic damage—make the Trans-Mexican Volcanic Belt (TMVB) of particular interest regarding the study of deep convection and related severe weather. In this research, 10 years of Moderate-Resolution Imaging Spectroradiometer (MODIS) cloud observations are combined with Climate Hazards Group Infrared Precipitation with Station (CHIRPS) rainfall data to characterize the spatio-temporal distribution of deep convective clouds (DCCs) and their relationship to extreme precipitation. From monthly distributions, wet and dry phases are identified for cloud fraction, deep convective cloud frequency and convective precipitation. For both DCC and extreme precipitation events, the highest frequencies align just over the higher elevations of the TMVB. A clear relationship between DCCs and terrain features, indicating the important role of orography in the development of convective systems, is noticed. For three sub-regions, the observed distributions of deep convective cloud and extreme precipitation events are assessed in more detail. Each sub-region exhibits different local conditions, including terrain features, and are known to be influenced differently by emerging moisture fluxes from the Gulf of Mexico and the Pacific Ocean. The observed distinct spatio-temporal variabilities provide the first insights into the physical processes that control the convective development in the study area. A signal of the midsummer drought in Mexico (i.e., “canícula”) is recognized using MODIS monthly mean cloud observations.

scholarly journals Semiarid grasslands and extreme precipitation events: Do experimental results scale to the landscape?

Ecology ◽  
2021 ◽  
Author(s):  
Alison K. Post ◽  
Kristin P. Davis ◽  
Jillian LaRoe ◽  
David L. Hoover ◽  
Alan K. Knapp
Keyword(s):  
Extreme Precipitation ◽  
Experimental Results ◽  
Extreme Precipitation Events ◽  
Precipitation Events
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