scholarly journals Landslides Triggered by the May 2017 Extreme Rainfall Event in the East Coast Northeast of Brazil

Atmosphere ◽  
2021 ◽  
Vol 12 (10) ◽  
pp. 1261
Author(s):  
Nikolai S. Espinoza ◽  
Carlos A. C. dos Santos ◽  
Madson T. Silva ◽  
Helber B. Gomes ◽  
Rosaria R. Ferreira ◽  
...  
Keyword(s):  
East Coast ◽  
Climate Model ◽  
Regional Climate ◽  
Daily Rainfall ◽  
Extreme Rainfall ◽  
Rainfall Event ◽  
Landslide Risk ◽  
Physical Parameters ◽  
Extreme Rainfall Event ◽  
Risk Areas

Given the increasing occurrence of landslides on the East Coast Northeast of Brazil (ECNEB), it is essential to understand its conditions and triggering factors because meteorological anomalies triggered by a landslide will threaten life and property in the region. In this sense, this research aimed to diagnose the meteorological conditions that triggered landslides in the ECNEB in May 2017, evaluate the terrain’s intrinsic conditions using elevation, slope, and susceptibility parameters and determine critical precipitation thresholds for the city with the highest number of landslide risk areas in the region. A dynamic downscaling experiment was carried out using the Regional Climate Model (RegCM) to verify the ability of this model to represent rainfall over the ECNEB. The results from the intrinsic factors showed that the ECNEB is highly susceptible to landslides with various high-risk sectors for landslides to the population. The extreme rainfall event was associated with the convergence of humidity at low levels over the ocean, which contributed to landslides in the ECNEB, mainly in the State of Pernambuco, where 67 landslides were registered. The RegCM numerical simulation underestimated the high daily rainfall signal seen on the Tropical Rainfall Measuring Mission satellite. It is suggested that sensitivity tests can be performed using other physical parameters to find the best model configuration for the ECNEB. This work recommends that exploring the relationship between precipitation and landslides will provide objective criteria for assessing risk areas by contributing to the predictability of disasters in this region.

Simulation of an extreme rainfall event over Mumbai using a regional climate model: a case study

2021 ◽  
Vol 134 (1) ◽  
Author(s):  
Manas Pant ◽  
Soumik Ghosh ◽  
Shruti Verma ◽  
Palash Sinha ◽  
R. K. Mall ◽  
...  
Keyword(s):  
Regional Climate Model ◽  
Climate Model ◽  
Regional Climate ◽  
Extreme Rainfall ◽  
Rainfall Event ◽  
Extreme Rainfall Event

scholarly journals Extreme rainfall impacts on soil CO2 efflux in an urban forest ecosystem in Beijing, China

2016 ◽  
Vol 96 (4) ◽  
pp. 504-514 ◽  
Author(s):  
Wenjing Chen ◽  
Xin Jia ◽  
Chunyi Li ◽  
Haiqun Yu ◽  
Jing Xie ◽  
...  
Keyword(s):  
Soil Respiration ◽  
Forest Ecosystem ◽  
Urban Forest ◽  
Extreme Rainfall ◽  
Rainfall Event ◽  
Extreme Rainfall Event ◽  
Co2 Efflux ◽  
Abrupt Decrease ◽  
Environmental Controls ◽  
Beijing China

Extreme rainfall events are infrequent disturbances that affect urban environments and soil respiration (Rs). Using data measured in an urban forest ecosystem in Beijing, China, we examined the link between gross primary production (GPP) and soil respiration on a diurnal scale during an extreme rainfall event (i.e., the “21 July 2012 event”), and we examined diel and seasonal environmental controls on Rs. Over the seasonal cycle, Rs increased exponentially with soil temperature (Ts). In addition, Rs was hyperbolically related to soil volumetric water content (VWC), increasing with VWC below a threshold of 0.17 m3 m−3, and then decreasing with further increases in VWC. Following the extreme rainfall event (177 mm), Rs showed an abrupt decrease and then maintained a low value of ∼0.3 μmol m−2 s−1 for about 8 h as soil VWC reached the field capacity (0.34 m3 m−3). Rs became decoupled from Ts and increased very slowly, while GPP showed a greater increase. A bivariate Q10-hyperbolical model, which incorporates both Ts and VWC effects, better fits Rs than the Q10 model in summer but not for whole year.

Future Extreme Climates Projection over Huang-Huai-Hai Region of China

2014 ◽  
Vol 955-959 ◽  
pp. 3887-3892 ◽  
Author(s):  
Huang He Gu ◽  
Zhong Bo Yu ◽  
Ji Gan Wang
Keyword(s):  
Climate Changes ◽  
Climate Model ◽  
Regional Climate ◽  
Surface Air Temperature ◽  
Daily Rainfall ◽  
Heavy Rain ◽  
Near Surface ◽  
Temperature And Precipitation ◽  
Huai River ◽  
The Future

This study projects the future extreme climate changes over Huang-Huai-Hai (3H) region in China using a regional climate model (RegCM4). The RegCM4 performs well in “current” climate (1970-1999) simulations by compared with the available surface station data, focusing on near-surface air temperature and precipitation. Future climate changes are evaluated based on experiments driven by European-Hamburg general climate model (ECHAM5) in A1B future scenario (2070-2099). The results show that the annual temperature increase about 3.4 °C-4.2 °C and the annual precipitation increase about 5-15% in most of 3H region at the end of 21st century. The model predicts a generally less frost days, longer growing season, more hot days, no obvious change in heat wave duration index, larger maximum five-day rainfall, more heavy rain days, and larger daily rainfall intensity. The results indicate a higher risk of floods in the future warmer climate. In addition, the consecutive dry days in Huai River Basin will increase, indicating more serve drought and floods conditions in this region.

scholarly journals Characteristics of convective snow bands along the Swedish east coast

2017 ◽  
Vol 8 (1) ◽  
pp. 163-175 ◽  
Author(s):  
Julia Jeworrek ◽  
Lichuan Wu ◽  
Christian Dieterich ◽  
Anna Rutgersson
Keyword(s):  
Regional Climate Model ◽  
East Coast ◽  
Climate Model ◽  
Regional Climate ◽  
Open Water ◽  
Atmospheric Model ◽  
Ocean Model ◽  
Sea Surface ◽  
Precipitation Rate ◽  
Shallow Convection

Abstract. Convective snow bands develop in response to a cold air outbreak from the continent or the frozen sea over the open water surface of lakes or seas. The comparatively warm water body triggers shallow convection due to increased heat and moisture fluxes. Strong winds can align with this convection into wind-parallel cloud bands, which appear stationary as the wind direction remains consistent for the time period of the snow band event, delivering enduring snow precipitation at the approaching coast. The statistical analysis of a dataset from an 11-year high-resolution atmospheric regional climate model (RCA4) indicated 4 to 7 days a year of moderate to highly favourable conditions for the development of convective snow bands in the Baltic Sea region. The heaviest and most frequent lake effect snow was affecting the regions of Gävle and Västervik (along the Swedish east coast) as well as Gdansk (along the Polish coast). However, the hourly precipitation rate is often higher in Gävle than in the Västervik region. Two case studies comparing five different RCA4 model setups have shown that the Rossby Centre atmospheric regional climate model RCA4 provides a superior representation of the sea surface with more accurate sea surface temperature (SST) values when coupled to the ice–ocean model NEMO as opposed to the forcing by the ERA-40 reanalysis data. The refinement of the resolution of the atmospheric model component leads, especially in the horizontal direction, to significant improvement in the representation of the mesoscale circulation process as well as the local precipitation rate and area by the model.

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