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 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 Evaluation of convection-permitting extreme precipitation simulations for the south of France

2020 ◽  
Author(s):  
Linh N. Luu ◽  
Robert Vautard ◽  
Pascal Yiou ◽  
Jean-Michel Soubeyroux
Keyword(s):  
Extreme Precipitation ◽  
Deep Convection ◽  
Coastal Region ◽  
Heavy Precipitation ◽  
Mediterranean Area ◽  
Climate Simulation ◽  
The South ◽  
Extreme Precipitation Events ◽  
Hourly Rainfall ◽  
Precipitation Events

Abstract. In the autumn, the French Mediterranean area is frequently exposed to heavy precipitation events whose daily accumulation can exceed 300 mm. One of the key processes contributing to these precipitation amounts is the deep convection, which can be resolved explicitly by state-or-the-art convection-permitting model to reproduce heavy rainfall events that are comparable to observations. However, this approach has never been used in climate simulation for the Mediterranean coastal region. In this research, we investigate the added values of using three ensembles of climate simulations at convection-permitting resolution (approx. 3 km) in replicating extreme precipitation events in both daily and shorter time scale over the South of France. These three convection-permitting simulations are performed with the Weather Research and Forecasting Model (WRF). They are forced by three EURO-CORDEX simulations, which are also downscaled with WRF at the resolution of 0.11° (approx. 12 km). We found that a convection-permitting approach provides a more realistic representation of extreme daily and 3-hourly rainfall simulations in comparison with EURO-CORDEX simulations. Their similarity with observations allows a use for climate change studies and its impacts.

scholarly journals Distribución y variabilidad de la precipitación en la Región Pampeana, Argentina

2016 ◽  
Vol 42 (1) ◽  
pp. 261 ◽  
Author(s):  
V. S. Aliaga ◽  
F. Ferrelli ◽  
E. D. Alberdi-Algarañaz ◽  
V. Y. Bohn ◽  
M. C. Piccolo
Keyword(s):  
Extreme Precipitation ◽  
Standardized Precipitation Index ◽  
Temporal Distribution ◽  
Continuous Wavelet ◽  
Precipitation Data ◽  
Extreme Precipitation Events ◽  
The Standardized Precipitation Index ◽  
Rainfall Regimes ◽  
Precipitation Events ◽  
Pampas Region

Pampas region is the main agricultural area of Argentina. Its economy mainly depends on rainfall regimes. The aim of this study was to sub-regionalize the Pampas, considering the spatial and temporal distribution of rainfalls. Cluster analysis was applied to study precipitation data from 33 meteorological stations from National Weather Service (SMN, Argentina) during the period 1960-2010. As a result, 6 sub-regions were obtained. Extreme precipitation events were studied with the Standardized Precipitation Index (SPI) and Continuous Wavelet Transform (CWT). Rainfalls respond to annual and seasonal timescales. Four of the sub-regions presented rainfalls homogeneity, permitting to redefine the limits of the Pampas region proposed by Labraga et al. (2011). Thus, a new pluviometric regionalization was achieved considering the typical precipitation patterns of Pampas region.

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