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

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.

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

Journal of Disaster Research ◽

10.20965/jdr.2008.p0015 ◽

2008 ◽

Vol 3 (1) ◽

pp. 15-24 ◽

Cited By ~ 12

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.

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

Hydrology and Earth System Sciences ◽

10.5194/hess-22-1095-2018 ◽

2018 ◽

Vol 22 (2) ◽

pp. 1095-1117 ◽

Cited By ~ 38

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.

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

Journal of Geographical Research ◽

10.30564/jgr.v4i3.3204 ◽

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.

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Association of geopotential height patterns with heavy rainfall events in Cyprus

Advances in Geosciences ◽

10.5194/adgeo-23-73-2010 ◽

2010 ◽

Vol 23 ◽

pp. 73-78 ◽

Cited By ~ 17

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.

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

MAUSAM ◽

10.54302/mausam.v64i2.684 ◽

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.

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Assessment of spatial uncertainty of heavy local rainfall using a dense gauge network

10.5194/hess-2018-517 ◽

2018 ◽

Cited By ~ 1

Author(s):

Sungmin O ◽

Ulrich Foelsche

Keyword(s):

Heavy Rainfall ◽

Extreme Rainfall ◽

Rain Gauge ◽

Spatial Uncertainty ◽

Wet Season ◽

Rainfall Events ◽

Rain Gauges ◽

Areal Rainfall ◽

The Impact ◽

Heavy Rainfall Events

Abstract. Hydrology and remote-sensing communities have made use of dense rain-gauge networks for studying rainfall uncertainty and variability. However, in most regions, these dense networks are only available at sub-pixel scales and over short periods of time. Just a few studies have applied a similar approach, employing dense gauge networks, to local-scale areas, which limits the verification of their results in other regions. Using 10-year rainfall measurements from a network of 150 rain gauges, we assess spatial uncertainty in observed heavy rainfall events. The network is located in southeastern Austria over an area of 20 km × 15 km with no significant orography. First, the spatial variability of rainfall in the region was characterised using a correlogram at daily and sub-daily scales. Differences in the spatial structure of rainfall events between wet and dry seasons are apparent and we selected heavy rainfall events, the upper 10 % of wettest days during the wet season, for further analyses because of their high potential for causing hazard risk. Secondly, we investigated uncertainty in estimating mean areal rainfall arising from a limited gauge density. The number of gauges required to obtain areal rainfall with > 20 % accuracy tends to increase roughly following a power law as time scale decreases. Lastly, the impact of spatial aggregation on extreme rainfall was examined using gridded rainfall data with horizontal grid spacings from 0.1° to 0.01°. The spatial scale dependence was clearly observed at high intensity thresholds and high temporal resolutions. Quantitative uncertainty information from this study can guide both data users and producers to estimate uncertainty in their own observational datasets, consequently leading to the rational use of the data in relevant applications. Our findings are generalisable to other plain regions in mid-latitudes, however the degree of uncertainty could be affected by regional variations, like rainfall type or topography.

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Verification of heavy rainfall in NWP models : A case study

MAUSAM ◽

10.54302/mausam.v68i4.772 ◽

2021 ◽

Vol 68 (4) ◽

pp. 699-712

Author(s):

KULDEEP SHARMA ◽

RAGHAVENDRA ASHRIT ◽

R. BHATLA ◽

R. RAKHI ◽

G. R. IYENGAR ◽

...

Keyword(s):

Heavy Rainfall ◽

Extreme Rainfall ◽

Heavy Rain ◽

Low Pressure ◽

Modeling Framework ◽

Deterministic Models ◽

Rainfall Events ◽

The Impact ◽

Heavy Rainfall Events ◽

Low Pressure Systems

Forecasting of heavy rainfall events is still a challenge even for the most advanced state-of-art high resolution NWP modelling systems. Very often the models fail to accurately predict the track and movement of the low pressure systems leading to large spatial errors in the predicted rain. Quantification of errors in forecast rainfall location and amounts is important for forecasters (to choose a forecast and interpret) and modelers for monitoring the impact of changes and improvements in model physics and dynamics configurations. This study aims to quantify and summarize errors in rainfall forecast for heavy rains associated with a Bay of Bengal (BOB) low pressure systems. The verification analysis is based on three heavy rain events during June to September (JJAS) 2015. The performance of the three deterministic models, NCMRWF’s Global Forecast Systems (NGFS), NCMRWF’s Unified Model (NCUM) and Australian Community Climate and Earth-System Simulator – Global (ACCESS-G) in predicting these heavy rainfall events has been analysed. In addition to standard verification metrics like RMSE, ETS, POD and HK Score, this paper also uses new family of scores like EDS (Extreme Dependency Score), EDI (Extremal Dependence Index) and Symmetric EDI with special emphasis on verification of extreme rainfall to bring out the relative performance of the models for these three rainfall events. The results indicate that Unified modeling framework in NCUM and ACCESS-G by and large performs better than NGFS in rainfall forecasts over India specially at higher lead times. Relatively improved skill in NCUM forecasts can be attributed to (i) improved resolution (~17 km) and (ii) END Game dynamics of NCUM.

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

Weather and Forecasting ◽

10.1175/2007waf2007013.1 ◽

2008 ◽

Vol 23 (3) ◽

pp. 336-356 ◽

Cited By ~ 45

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.

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Sensitivity of Simulations of Zambian Heavy Rainfall Events to the Atmospheric Boundary Layer Schemes

Climate ◽

10.3390/cli9020038 ◽

2021 ◽

Vol 9 (2) ◽

pp. 38

Author(s):

Mary-Jane M. Bopape ◽

David Waitolo ◽

Robert S. Plant ◽

Elelwani Phaduli ◽

Edson Nkonde ◽

...

Keyword(s):

Boundary Layer ◽

Heavy Rainfall ◽

Large Scale ◽

Weather Forecasting ◽

Weather Prediction ◽

Wrf Model ◽

Extreme Rainfall ◽

Maximum Temperature ◽

Rainfall Events ◽

Heavy Rainfall Events

Weather forecasting relies on the use of numerical weather prediction (NWP) models, whose resolution is informed by the available computational resources. The models resolve large scale processes, while subgrid processes are parametrized. One of the processes that is parametrized is turbulence which is represented in planetary boundary layer (PBL) schemes. In this study, we evaluate the sensitivity of heavy rainfall events over Zambia to four different PBL schemes in the Weather Research and Forecasting (WRF) model using a parent domain with a 9 km grid length and a 3 km grid spacing child domain. The four PBL schemes are the Yonsei University (YSU), nonlocal first-order medium-range forecasting (MRF), University of Washington (UW) and Mellor–Yamada–Nakanishi–Niino (MYNN) schemes. Simulations were done for three case studies of extreme rainfall on 17 December 2016, 21 January 2017 and 17 April 2019. The use of YSU produced the highest rainfall peaks across all three cases; however, it produced performance statistics similar to UW that are higher than those of the two other schemes. These statistics are not maintained when adjusted for random hits, indicating that the extra events are mainly random rather than being skillfully placed. UW simulated the lowest PBL height, while MRF produced the highest PBL height, but this was not matched by the temperature simulation. The YSU and MYNN PBL heights were intermediate at the time of the peak; however, MYNN is associated with a slower decay and higher PBL heights at night. WRF underestimated the maximum temperature during all cases and for all PBL schemes, with a larger bias in the MYNN scheme. We support further use of the YSU scheme, which is the scheme selected for the tropical suite in WRF. The different simulations were in some respects more similar to one another than to the available observations. Satellite rainfall estimates and the ERA5 reanalysis showed different rainfall distributions, which indicates a need for more ground observations to assist with studies like this one.

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