Use of Normalized Anomaly Fields to Anticipate Extreme Rainfall in the Mountains of Northern California

2008 ◽  
Vol 23 (3) ◽  
pp. 336-356 ◽  
Author(s):  
Norman W. Junker ◽  
Richard H. Grumm ◽  
Robert Hart ◽  
Lance F. Bosart ◽  
Katherine M. Bell ◽  
...  
Keyword(s):  
Geopotential Height ◽  
Heavy Rainfall ◽  
Extreme Rainfall ◽  
The United States ◽  
Height Anomaly ◽  
Geopotential Height Anomaly ◽  
Northern California ◽  
Extreme Rainfall Events ◽  
Rainfall Events ◽  
Heavy Rainfall Events

Abstract Extreme rainfall events contribute a large portion of wintertime precipitation to northern California. The motivations of this paper were to study the observed differences in the patterns between extreme and more commonly occurring lighter rainfall events, and to study whether anomaly fields might be used to discriminate between them. Daily (1200–1200 UTC) precipitation amounts were binned into three progressively heavier categories (12.5–50.0 mm, light; 50–100 mm, moderate; and >100 mm, heavy) in order to help identify the physical processes responsible for extreme precipitation in the Sierra Nevada range between 37.5° and 41.0°N. The composite fields revealed marked differences between the synoptic patterns associated with the three different groups. The heavy composites showed a much stronger, larger-scale, and slower-moving negative geopotential height anomaly off the Pacific coast of Oregon and Washington than was revealed in either of the other two composites. The heavy rainfall events were also typically associated with an atmospheric river with anomalously high precipitable water (PW) and 850-hPa moisture flux (MF) within it. The standardized PW and MF anomalies associated with the heavy grouping were higher and were slower moving than in either of the lighter bins. Three multiday heavy rainfall events were closely examined in order to ascertain whether anomaly patterns could provide forecast utility. Each of the multiday extreme rainfall events investigated was associated with atmospheric rivers that contained highly anomalous 850-hPa MF and PW within it. Each case was also associated with an unusually intense negative geopotential height anomaly that was similarly located off of the west coast of the United States. The similarities in the anomaly pattern among the three multiday extreme events suggest that standardized anomalies might be useful in predicting extreme multiday rainfall events in the northern Sierra range.

scholarly journals Association of geopotential height patterns with heavy rainfall events in Cyprus

2010 ◽  
Vol 23 ◽  
pp. 73-78 ◽  
Author(s):  
F. Tymvios ◽  
K. Savvidou ◽  
S. C. Michaelides
Keyword(s):  
Geopotential Height ◽  
Heavy Rainfall ◽  
Eastern Mediterranean ◽  
Statistical Processing ◽  
Extreme Rainfall ◽  
Classification Performance ◽  
Extreme Rainfall Events ◽  
Rainfall Events ◽  
The Relationship ◽  
Heavy Rainfall Events

Abstract. Dynamically induced rainfall is strongly connected with synoptic atmospheric circulation patterns at the upper levels. This study investigates the relationship between days of high precipitation volume events in the eastern Mediterranean and the associated geopotential height patterns at 500 hPa. To reduce the number of different patterns and to simplify the statistical processing, the input days were classified into clusters of synoptic cases having similar characteristics, by utilizing Kohonen Self Organizing Maps (SOM) architecture. Using this architecture, synoptic patterns were grouped into 9, 18, 27 and 36 clusters which were subsequently used in the analysis. The classification performance was tested by applying the method to extreme rainfall events in the eastern Mediterranean. The relationship of the synoptic upper air patterns (500 hPa height) and surface features (heavy rainfall events) was established, while the 36 member classification proved to be the most efficient.

scholarly journals Assessment of the Weather Research and Forecasting (WRF) model for simulation of extreme rainfall events in the upper Ganga Basin

2018 ◽  
Vol 22 (2) ◽  
pp. 1095-1117 ◽  
Author(s):  
Ila Chawla ◽  
Krishna K. Osuri ◽  
Pradeep P. Mujumdar ◽  
Dev Niyogi
Keyword(s):  
Land Surface ◽  
Heavy Rainfall ◽  
Wrf Model ◽  
Extreme Rainfall ◽  
Weather Research And Forecasting ◽  
Grid Spacing ◽  
Ganga Basin ◽  
Extreme Rainfall Events ◽  
Rainfall Events ◽  
Heavy Rainfall Events

Abstract. Reliable estimates of extreme rainfall events are necessary for an accurate prediction of floods. Most of the global rainfall products are available at a coarse resolution, rendering them less desirable for extreme rainfall analysis. Therefore, regional mesoscale models such as the advanced research version of the Weather Research and Forecasting (WRF) model are often used to provide rainfall estimates at fine grid spacing. Modelling heavy rainfall events is an enduring challenge, as such events depend on multi-scale interactions, and the model configurations such as grid spacing, physical parameterization and initialization. With this background, the WRF model is implemented in this study to investigate the impact of different processes on extreme rainfall simulation, by considering a representative event that occurred during 15–18 June 2013 over the Ganga Basin in India, which is located at the foothills of the Himalayas. This event is simulated with ensembles involving four different microphysics (MP), two cumulus (CU) parameterizations, two planetary boundary layers (PBLs) and two land surface physics options, as well as different resolutions (grid spacing) within the WRF model. The simulated rainfall is evaluated against the observations from 18 rain gauges and the Tropical Rainfall Measuring Mission Multi-Satellite Precipitation Analysis (TMPA) 3B42RT version 7 data. From the analysis, it should be noted that the choice of MP scheme influences the spatial pattern of rainfall, while the choice of PBL and CU parameterizations influences the magnitude of rainfall in the model simulations. Further, the WRF run with Goddard MP, Mellor–Yamada–Janjic PBL and Betts–Miller–Janjic CU scheme is found to perform best in simulating this heavy rain event. The selected configuration is evaluated for several heavy to extremely heavy rainfall events that occurred across different months of the monsoon season in the region. The model performance improved through incorporation of detailed land surface processes involving prognostic soil moisture evolution in Noah scheme compared to the simple Slab model. To analyse the effect of model grid spacing, two sets of downscaling ratios – (i) 1 : 3, global to regional (G2R) scale and (ii) 1 : 9, global to convection-permitting scale (G2C) – are employed. Results indicate that a higher downscaling ratio (G2C) causes higher variability and consequently large errors in the simulations. Therefore, G2R is adopted as a suitable choice for simulating heavy rainfall event in the present case study. Further, the WRF-simulated rainfall is found to exhibit less bias when compared with the NCEP FiNaL (FNL) reanalysis data.

scholarly journals Brief communication "Climatic covariates for the frequency analysis of heavy rainfall in the Mediterranean region"

2011 ◽  
Vol 11 (9) ◽  
pp. 2463-2468 ◽  
Author(s):  
Y. Tramblay ◽  
L. Neppel ◽  
J. Carreau
Keyword(s):  
Extreme Events ◽  
Heavy Rainfall ◽  
Climate Models ◽  
Extreme Event ◽  
Generalized Pareto Distribution ◽  
Climatic Conditions ◽  
Extreme Rainfall Events ◽  
Rainfall Events ◽  
The Future ◽  
Heavy Rainfall Events

Abstract. In Mediterranean regions, climate studies indicate for the future a possible increase in the extreme rainfall events occurrence and intensity. To evaluate the future changes in the extreme event distribution, there is a need to provide non-stationary models taking into account the non-stationarity of climate. In this study, several climatic covariates are tested in a non-stationary peaks-over-threshold modeling approach for heavy rainfall events in Southern France. Results indicate that the introduction of climatic covariates could improve the statistical modeling of extreme events. In the case study, the frequency of southern synoptic circulation patterns is found to improve the occurrence process of extreme events modeled via a Poisson distribution, whereas for the magnitude of the events, the air temperature and sea level pressure appear as valid covariates for the Generalized Pareto distribution scale parameter. Covariates describing the humidity fluxes at monthly and seasonal time scales also provide significant model improvements for the occurrence and the magnitude of heavy rainfall events. With such models including climatic covariates, it becomes possible to asses the risk of extreme events given certain climatic conditions at monthly or seasonal timescales. The future changes in the heavy rainfall distribution can also be evaluated using covariates computed by climate models.

scholarly journals On the Use of an Innovative Trend Analysis Methodology for Temporal Trend Identification in Extreme Rainfall Indices Over the Central Highlands, Vietnam

2021 ◽  
Author(s):  
Dang Nguyen Dong Phuong ◽  
Nguyen Thi Huyen ◽  
Nguyen Duy Liem ◽  
Nguyen Thi Hong ◽  
Dang Kien Cuong ◽  
...  
Keyword(s):  
Trend Analysis ◽  
Heavy Rainfall ◽  
Precipitation Amount ◽  
Extreme Rainfall ◽  
Rainfall Events ◽  
Monotonic Trend ◽  
Innovative Trend Analysis ◽  
Central Highlands ◽  
Warming World ◽  
Heavy Rainfall Events

Abstract Understanding past changes in the characteristics of climate extremes (such as frequency, intensity, and duration) forms an essential part of viable countermeasures to cope with climate-induced risks under a rapidly warming world. Thus, this paper endeavored to explore possible non-monotonic trend components in heavy rainfall events over the Central Highlands of Vietnam by employing the Şen’s innovative trend analysis (ITA) method in conjunction with the well-defined extreme rainfall indices developed by the Joint CCl/CLIVAR/JCOMM Expert Team on Climate Change Detection and Indices (ETCCDI). The outcomes show that the overall trends in most extreme rainfall indices exhibited significant increases at several stations. Moreover, the high-value subgroups of most analyzed indices (such as maximum 5-day precipitation amount (Rx5day), simple daily intensity index (SDII), very wet days (R95p), extremely wet days (R99p), number of extremely heavy precipitation days (R50mm), and consecutive dry days (CDD)) were characterized mainly by significant increasing trends, thereby implying that heavy rainfall events have become more frequent and intense over recent decades. Some stations also exposed significant increasing trend behaviors in a given extreme index within all low-, medium-, and high-value subgroups. In general, it is expected that these findings yield more insightful knowledge on rainfall extremes to local decision-makers and other stakeholders.

scholarly journals ­Trends and Zonal Variability of Extreme Rainfall Events Over East Africa During 1960-2017

2021 ◽  
Author(s):  
Moses.A Ojara ◽  
Yunsheng Lou ◽  
Hasssen Babaousmail ◽  
Peter Wasswa
Keyword(s):  
Extreme Events ◽  
Heavy Rainfall ◽  
Rainwater Harvesting ◽  
Southern Oscillation ◽  
Extreme Rainfall ◽  
Mitigation Measures ◽  
Fluctuation Analysis ◽  
Positive Trend ◽  
Extreme Rainfall Events ◽  
Rainfall Events

Abstract East African countries (Uganda, Kenya, Tanzania, Rwanda, and Burundi) are prone to weather extreme events. In this regard; the past occurrence of extreme rainfall events is analyzed for 25 stations following the Expert Team on Climate Change Detection and Indices (ETCCDI) regression method. Detrended Fluctuation Analysis (DFA) is used to show the future development of extreme events. Pearson’s correlation analysis is performed to show the relationship of extreme events between different rainfall zones and their association with El Niño -Southern Oscillation (ENSO and Indian Ocean dipole (IOD) IOD-DMI indices. Results revealed that the consecutive wet day's index (CWD) was decreasing trend in 72% of the stations analyzed, moreover consecutive dry days (CDD) index also indicated a positive trend in 44% of the stations analyzed. Heavy rainfall days index (R10mm) showed a positive trend at 52% of the stations and was statistically significant at a few stations. In light of the extremely heavy rainfall days (R25mm) index, 56% of the stations revealed a decreasing trend for the index and statistically significant trend at some stations. Further, a low correlation coefficient of extreme rainfall events in the regions; and between rainfall extreme indices with the atmospheric teleconnection indices (Dipole Mode Index-DMI and Nino 3.4) (r = -0.1 to r = 0.35). Most rainfall zones showed a positive correlation between the R95p index and DMI, while 5/8 of the rainfall zones experienced a negative correlation between Nino 3.4 index and the R95p. In light of the highly variable trends of extremes events, we recommend planning adaptation and mitigation measures that consider the occurrence of such high variability. Measures such as rainwater harvesting, stored and used during needs, planned settlement, and improved drainage systems management supported by accurate climate and weather forecasts is highly advised.

scholarly journals Effects of Global Warming on Heavy Rainfall During the Baiu Season Projected by a Cloud-System-Resolving Model

2008 ◽  
Vol 3 (1) ◽  
pp. 15-24 ◽  
Author(s):  
Masaomi Nakamura ◽  
◽  
Sachie Kaneda ◽  
Yasutaka Wakazuki ◽  
Chiashi Muroi ◽  
...  
Keyword(s):  
Global Warming ◽  
Heavy Rainfall ◽  
Climate Models ◽  
Climate Model ◽  
Regional Climate ◽  
Extreme Rainfall ◽  
Horizontal Resolution ◽  
Rainfall Events ◽  
Future Global Warming ◽  
Heavy Rainfall Events

Under the Kyosei-4 Project, unprecedented high resolution global and regional climate models were developed on the Earth Simulator to investigate the effect of global warming on tropical cyclones, baiu frontal rainfall systems, and heavy rainfall events that could not be resolved using conventional climate models.For the regional climate model, a nonhydrostatic model (NHM) with a horizontal resolution of 5 km was developed to be used in the simulation of heavy rainfall during the baiu season in Japan. Simulations in June and July were executed for 10 years in present and future global warming climates. It was found that, due to global warming, mean rainfall is projected to increase except in eastern and northern Japan, the frequency of heavy rainfall events would increase and its increment rate become higher for heavier rainfall, and return values for extreme rainfall would grow.Experiments using an NHM with a horizontal resolution of 1 km were conducted to study the effects of resolution. Compared to 5 km resolution, it expresses the organization of rainfall systems causing heavy rainfall and the appearance-frequency distribution of rainfall for variable intensities more realistically.

scholarly journals A Climatology of Heavy Rain and Major Flood Events in Victoria 1876-2019 and the Effect of the 1976 Climate Shift

2021 ◽  
Vol 4 (3) ◽  
Author(s):  
Jeff Callaghan
Keyword(s):  
Heavy Rainfall ◽  
Southern Oscillation ◽  
Extreme Rainfall ◽  
Heavy Rain ◽  
Rainfall Events ◽  
Climate Shift ◽  
Weather Patterns ◽  
Synoptic Weather ◽  
Extensive Search ◽  
Heavy Rainfall Events

An extensive search has been carried out to find all major flood and very heavy rainfall events in Victoria since 1876 when Southern Oscillation (SOI) data became available. The synoptic weather patterns were analysed and of the 319 events studied,121 events were found to be East Coast Lows (ECLs) and 82 were other types of low-pressure systems. Tropical influences also played a large role with 105 events being associated with tropical air advecting down to Victoria into weather systems. Examples are presented of all the major synoptic patterns identified. The SOI was found to be an important climate driver with positive SOIs being associated with many events over the 144 years studied. The 1976 Climate Shift and its influence on significant Victorian rainfall events is studied and negative SOI monthly values were shown to dominate following the Shift.However,one of the most active periods in 144 years of Victorian heavy rain occurred after the shift with a sustained period of positive SOI events from 2007 to 2014. Therefore, it is critical for forecasting future Victorian heavy rainfall is to understand if sequences of these positive SOI events continue like those preceding the Shift. Possible relationships between the Shift and Global Temperature rises are also explored. Upper wind data available from some of the heaviest rainfall events showed the presence of anticyclonic turning of the winds between 850hPa and 500hPa levels which has been found to be linked with extreme rainfall around the Globe. 

scholarly journals Synoptic study of extremely heavy rainfall events over lower Yamuna catchment : Some cases

MAUSAM ◽  
2021 ◽  
Vol 64 (2) ◽  
pp. 265-280
Author(s):  
MEHFOOZ ALI MEHFOOZALI ◽  
U.P. SINGH ◽  
D. JOARDAR ◽  
NIZAMUDDIN NIZAMUDDIN
Keyword(s):  
Bay Of Bengal ◽  
Heavy Rainfall ◽  
Extreme Rainfall ◽  
Low Pressure ◽  
Crop Damage ◽  
Local Conditions ◽  
Rainfall Events ◽  
Synoptic Conditions ◽  
Heavy Rainfall Events ◽  
Low Pressure Systems

vR;f/kd o"kkZ gksus ds dkj.k HkwL[kyu gksrk gS vDlekr ck<+ vk tkrh gS vkSj Qly dks {kfr igq¡prh gSA lekt] vFkZO;oLFkk vkSj i;kZoj.k ij bldk cgqr nq"izHkko iM+rk gSA i;kZoj.kh; vkSj flukWfIVd fLFkfr;ksa ds mRiUu gksus ls  vR;f/kd vFkok cgqr Hkkjh o"kkZ gksus ds dkj.k Hkkjr esa nf{k.k if’peh ekulwu _rq ds nkSjku vf/kdk¡’kr% ck<+ vkrh gSA bl 'kks/k i= esa izeq[k flukWfIVd dkj.kksa dk irk yxkus dk iz;kl fd;k x;k gS tks y?kq vof/k iwokZuqeku ds {ks= esa fodflr iwokZuqeku rduhd vkSj vk/kqfud izs{k.kkRed izkS|ksfxdh ij vk/kkfjr o"kZ 1998&2010 dh vof/k dh bl o"kkZ  vkSj ok;qeaMyh; iz.kkfy;ksa ds e/; laca/kksa ds fo’ys"k.k ds ek/;e ls ;equk ds fupys tyxzg.k {ks= ¼,y-okbZ-lh-½ esa vR;f/kd Hkkjh o"kkZ dh ?kVukvksa ds fy, mRrjnk;h gSA bl v/;;u ls ;g irk pyk gS fd  bl {ks= esa caxky dh [kkM+h esa fuEu nkc iz.kkfy;ksa dk cuuk izeq[k dkjd gS fuLlansg ;fn LFkkuh; fLFkfr;k¡ izHkkoh gks tSlsa fd xehZ dk c<+uk rks ogk¡ ij Hkkjh o"kkZ gksrh gSA lkekU;r% caxky dh [kkM+h esa fuEu vcnkc iz.kkfy;k¡ ¼pØokr] vonkc] fuEu vonkc {ks= vkfn tSls ¼,y-ih-,l-½ fodflr gqbZ tks if’pe ls mRrjh  if’peh fn’kk dh vksj c<+h rFkk ;equk ds fupys tyxzg.k ¼,y-okbZ-lh-½ {ks= esa igq¡phA ,slh ?kVukvksa ds fy, mRrjnk;h mifjru  ok;q pØokrh ifjlapj.k ¼lkblj½ ds izHkko ls ogha ij ,y- ih- ,l- Hkh cu ldrk gSA ,slh iz.kkyh ls bDds&nwDds LFkkuksa ij vR;f/kd Hkkjh o"kkZ dh ?kVuk,¡ ¼lkekU;r% iz.kkyh ds nf{k.k if’pe {ks= esa½ vkSj dqN LFkkuksa ij Hkkjh ls cgqr Hkkjh o"kkZ gqbZ ftlds dkj.k ck<+ vkbZA ;fn ;equk ds fupys tyxzg.k ¼,y-okbZ-lh-½ {ks= esa ,y-ih-,l- fuf"Ø; ;k /khek iM+ tkrk gS rks bl izdkj dh o"kkZ dh ?kVukvksa dh laHkkouk c<+ ldrh gSA ,y-ih-,l- ds vkxs c<+us dk lgh iwokZuqeku nsus ds fy, vkj-,l-,e-lh- ¼Hkkjr ekSle foKku foHkkx½ ubZ fnYYkh ds iwoZuqeku :i js[kk ds ,u-MCY;w-ih- mRikn@72] 48 vkSj 24 ?kaVksa ds iou pkVZ lgh lk/ku ik, x, gSaA vR;f/kd o"kkZ dh ?kVukvksa ds iwokZuqeku esa bl izdkj dh lwpuk nsus ls iwokZuqekudrkvksa dks fuf’pr :i ls lgh iwokZuqeku feysxk rkfd ftyk izkf/kdkjh le; jgrs vkink dh rS;kjh ds fy, vko’;d ewyHkwr lqfo/kk,¡ miyC/k djk ldsaA  Extreme rainfall results in landslides, flash flood and crop damage that have major impact on society, the economy and the environment. During southwest monsoon season, flood mostly occurs in India due to extremely or very heavy rain that originates from environmental and   synoptic conditions. An attempt has been made to identify the main synoptic reasons, which are responsible for extremely heavy rainfall events over Lower Yamuna catchment (LYC) through the analysis of the relationship between this rainfall and atmospheric systems for the period 1998-2010 based on modern observational technology and developed forecasting technique in the field of short range prediction. The finding of this study show that the major factor have is the arrival of Bay of Bengal low pressure systems in this region, of course if the ascent local conditions such as heat occur, causing the heaviest rains there. The low pressure systems (LPS like, Cyclone, depression, low pressure area etc.) developed generally over Bay of Bengal moved in west to north-westwards direction and reached over the LYC region. Also LPS may be formed in situ under the influence of upper air cyclonic circulation (cycir) responsible for such events. Such system yield extremely heavy rainfall events (generally in the south-west sector of the system) at isolated places and heavy to very heavy rainfall at a few places and there by caused flood situation. The possibility of occurrence of such type of rainfall would be higher if the LPS is either stagnate or slow over LYC region. The NWP products of RSMC (IMD) New Delhi forecast contours / wind charts for 72, 48 & 24 hrs were found good tool for accurate forecast position of the movement of the LPS. Such information certainly facilitate to forecaster in prediction of extreme rainfall events more accurately so that district authorities may set up necessary infrastructures for disaster preparedness in time.

Recent Development of the Hong Kong Landslip Warning System

2021 ◽  
Author(s):  
Raymond Cheung ◽  
Edward Chu ◽  
Rachel Law ◽  
Philip Chung
Keyword(s):  
Hong Kong ◽  
Heavy Rainfall ◽  
Warning System ◽  
Extreme Rainfall ◽  
Safety System ◽  
Landslide Risk ◽  
Extreme Rainfall Events ◽  
Rainfall Events ◽  
The Public ◽  
Landslide Hazards

&lt;p&gt;Hong Kong is situated at the south-eastern tip of China.&amp;#160; It has a sub-tropical climate, with a rainy season from April to October each year. &amp;#160;Rainfall intensities can be high, with 50 mm to 100 mm per hour and 250 mm to 350 mm in 24 hours being not uncommon.&amp;#160; Because of its mountainous terrain, Hong Kong is susceptible to landsliding during the periods of heavy rainfall.&amp;#160; As part of the Slope Safety System, the Geotechnical Engineering Office (GEO) of the Hong Kong Special Administrative Region Government has been operating a territory-wide Landslip Warning System for over 40 years.&amp;#160; The primary objective of the Landslip Warning is to forewarn the public of possible landslide risk during periods of heavy rainfall.&amp;#160; This paper summarises the major components of the current GEO Landslip Warning System as a landslide risk management tool.&amp;#160; Hong Kong has an extensive network of automatic raingauges and comprehensive records of landslides.&amp;#160; With this, rainfall-landslide correlation models have been established and updated regularly through statistical means to facilitate the prediction of the severity of landslide based on real-time rainfall recorded in the raingauge network and the rainfall forecast by the Hong Kong Observatory (HKO).&amp;#160; The System has been continuously enhanced and upgraded along with the development of novel technology and analytical techniques.&amp;#160; Currently, Internet of Things (IoT) technology are used in the automatic raingauge network jointly operated by the GEO and the HKO to ensure reliable data transmission.&amp;#160; The collected rainfall data are stored and processed using cloud computing service that predicts the severity of landslide at every five-minute intervals.&amp;#160; The prediction allows the GEO and the HKO to determine the necessity of issuing a Landslip Warning.&amp;#160; Apart from technology, the effectiveness of the Landslip Warning also depends on the actions taken by the public when it is in force.&amp;#160; The GEO has ongoing public education campaigns to raise the public awareness and preparedness to reduce vulnerability to landslide hazards.&amp;#160; &amp;#160;In recent years, occurrence of severe landslides and casualties in landslide have been significantly reduced, which is attributed largely to the successful implementation of the Slope Safety System and partly to the absence of extreme rainfall events.&amp;#160; As a result, there is a genuine concern that the public is becoming complacent to the potential landslide hazards.&amp;#160; The GEO has enhanced the efforts in maintaining public participation in combating landslide hazards and improved the public perception of the landslide risk of a rainstorm by using a quantitative Landslide Potential Index.&amp;#160; &amp;#160;Besides providing public warning, the GEO also endeavours to enhance the emergency response to landslide incidents through innovative solutions.&amp;#160; Selected debris barriers are installed with IoT sensors for providing immediate alert of the occurrence of sizable landslides and quadrupled robots are being studied and tested for inspecting landslide sites.&amp;#160; It is anticipated that innovation and technology have great potential in improving the GEO&amp;#8217;s capability in emergency management, in particular in the case of extreme rainfall events that are expected be more frequent and intense in future.&lt;/p&gt;

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