scholarly journals Modulation of Caribbean Precipitation by the Madden–Julian Oscillation

2011 ◽  
Vol 24 (3) ◽  
pp. 813-824 ◽  
Author(s):  
Elinor R. Martin ◽  
Courtney Schumacher
Keyword(s):  
Extreme Events ◽  
Intraseasonal Variability ◽  
Extreme Rainfall ◽  
Strong Relationship ◽  
Madden Julian Oscillation ◽  
Extreme Rainfall Events ◽  
Trade Winds ◽  
Low Level ◽  
Precipitation Anomalies ◽  
The Caribbean

Abstract Based on 12 years of daily satellite precipitation data and reanalysis winds, intraseasonal (30–90 days) variability in Caribbean precipitation is linked to phases of the Madden–Julian oscillation (MJO). Intraseasonal variability is largest during September–November (SON), but some modulation of precipitation by the MJO appears throughout all seasons. Precipitation anomalies up to 50% above (below) the annual mean are observed in phases 1 and 2 (5 and 6) of the MJO. The changes in Caribbean precipitation associated with the MJO are shown to be related to changes in the low-level (925 hPa) winds. When precipitation anomalies are above (below) average in phases 1 and 2 (5 and 6), wind anomalies act to decrease (increase) the strength of the prevailing easterly trade winds. The changes in the low-level winds are most apparent in the region of the Caribbean low-level jet (CLLJ), and divergence anomalies associated with the entrance and exit regions of the CLLJ precede the precipitation anomalies. The CLLJ itself is also shown to be subject to intraseasonal variability, and its magnitude varies with the phase of the MJO. Again, intraseasonal variability in the CLLJ associated with the MJO is observed in all seasons and shows a significant coherence with intraseasonal variability in the precipitation. Extreme rainfall events over islands in the Caribbean show a strong relationship with the MJO phase, with extreme events being most common in phases 1 and 2 of an MJO event. This relationship between the MJO and extreme events has important implications for the predictability of precipitation extremes in the Caribbean.

scholarly journals Data analysis reveals that extreme events have increased the flood inundations in the Taquari River´s Valley, southern Brazil

2021 ◽  
Vol 1 (1) ◽  
pp. 16-25
Author(s):  
Francisco Manoel Wohnrath Tognoli ◽  
Sabrina Deconti Bruski ◽  
Thiago Peixoto de Araujo
Keyword(s):  
Extreme Events ◽  
Extreme Rainfall ◽  
Maximum Level ◽  
Data Series ◽  
Rainfall Time Series ◽  
Southern Brazil ◽  
Human Occupation ◽  
Extreme Rainfall Events ◽  
Starting Point ◽  
The City

Flood inundations represent more than 62% of the deaths caused by natural disasters in Brazil. The dataset comprises the records of the Encantado´s pluviometric station, a municipality located beside the margin of the Taquari River in southern Brazil, which comprises the rainfall time series (n = 36,466) over 78 years, from April 1943 to December 2020. Complementary datasets also include the annual volume of precipitation per year and the level reached by the Taquari River during 44 flood inundations since 1941. The number of events is subsampled because only 32 years have the complete record of the river level. Three of the five major flood inundations at Encantado occurred after 2001, and the more severe flood recorded the maximum level of the Taquari River (20,27 meters) on July 8th, 2020. Thirty-four percent of all flood inundations in the city were recorded between 2011 and 2020. The months of July to October record 70% of all the events, but there is no record of floods in February and December throughout the data series. The human occupation of the floodplain has been fast in the last decades, and most of the urban area has a potential risk of being affected by flood inundations. Moreover, extreme rainfall events and flood events have been more frequent in the last 30 years. This database can contribute as a starting point for developing predictive models and verifying a possible correlation of floods with extreme events and global climatic changes.

Reconstruction of a realistic rainfall field for extreme events happened in mountain area

2021 ◽  
Author(s):  
Andrea Abbate ◽  
Laura Longoni ◽  
Monica Papini
Keyword(s):  
Extreme Events ◽  
Temporal Distribution ◽  
Extreme Rainfall ◽  
Shallow Landslides ◽  
Mountain Areas ◽  
Mountain Area ◽  
Extreme Rainfall Events ◽  
Lombardy Region ◽  
Rain Gauges ◽  
Rainfall Model

<p>In the field of hydrogeological risk, rainfalls represent the most important triggering factor for superficial terrain failures such as shallow landslides, soil slips and debris flow. The availability of local rain gauges measurements is fundamental for defining the cause-effect relationship for predicting failure scenarios. Unfortunately, these hydrogeological phenomena are typical triggered over mountains regions where the density of the ground-based meteorological network is poor, and the local effects caused by mountains topography can change dramatically the spatial and temporal distribution of rainfall. Therefore, trying to reconstruct a representative rainfall field across mountain areas is a challenge but is a mandatory task for the interpretation of triggering causes. We present a reanalysis of an ensemble of extreme rainfall events happened across central Alps and Pre-Alps, in the northern part of Lombardy Region, Italy. We have investigated around some critical aspects such as their intensity and persistency also proposing a modelling of their meteorological evolution, using the Linear Upslope-Rainfall Model (LUM). We have considered this model because it is designed for describing the mechanism of orographic precipitation intensification that was identified as the main cause of that extreme events. To test and calibrate the LUM model we have considered local rain gauges data because they represent the effective rainfall poured on the ground. These punctual data are generally considered for landslide assessment, in particular for rainfall induced phenomena such as shallow landslides and debris flows. Considering our test cases, the results obtained have shown that the LUM has been able to reproduce accurately the rainfall field. In this regard, LUM model can help to address further information around those ungauged area where rainfall estimation could be critical for evaluating the hazard. We are conscious that our and other studies around this topic would be propaedeutic in the next future for the adoption of an integrated framework among the real-time meteorological modelling and the hydrogeological induced risk assessment and prevision.</p>

Influence of the Madden-Julian Oscillation on moisture transport by the Caribbean Low Level Jet during the Midsummer Drought in Mexico

2021 ◽  
Vol 248 ◽  
pp. 105243
Author(s):  
Juliet Perdigón-Morales ◽  
Rosario Romero-Centeno ◽  
Paulina Ordoñez ◽  
Raquel Nieto ◽  
Luis Gimeno ◽  
...  
Keyword(s):  
Moisture Transport ◽  
Madden Julian Oscillation ◽  
Low Level ◽  
Low Level Jet ◽  
The Caribbean

A Diagnosis of the 1979–2005 Extreme Rainfall Events in the Southeastern United States with Isentropic Moisture Tracing

2010 ◽  
Vol 138 (4) ◽  
pp. 1172-1185 ◽  
Author(s):  
Steven C. Chan ◽  
Vasubandhu Misra
Keyword(s):  
United States ◽  
Land Surface ◽  
Southeastern United States ◽  
Extreme Rainfall ◽  
Heavy Precipitation ◽  
Extreme Rainfall Events ◽  
Moisture Sources ◽  
Precipitation Total ◽  
Precipitation Anomalies ◽  
Precipitation Events

Abstract A detailed analysis is performed to better understand the interannual and subseasonal variability of moisture sources of major recent dry (1980, 1990, and 2000) and wet (1994, 2003, and 2005) June–August (JJA) seasons in the southeastern United States. Wet (dry) JJAs show an increased (decreased) standard deviation of daily precipitation. Whereas most days during dry JJAs have little or no precipitation, wet JJAs contain more days with significant precipitation and a large increase of heavy (+10 mm) precipitation days. At least two tropical cyclone/depression landfalls occur in the southeastern United States during wet JJAs, whereas none occur during dry JJAs. The trajectory analysis suggests significant local recycling of moisture, implying that land surface feedback has the potential to enhance (suppress) precipitation anomalies during a wet (dry) JJA. Remote moisture sources during heavy precipitation events are very similar between wet and dry JJAs. The distinction between wet and dry JJAs lies in the frequency of heavy precipitation events. During the wet JJAs, heavy precipitation events contribute to more than half of the JJA precipitation total.

scholarly journals Assessing the Performance of Satellite-Based Products for Monitoring Extreme Rainfall Events in Bangladesh

2021 ◽  
Author(s):  
Carlo Montes ◽  
Nachiketa Acharya ◽  
Quamrul Hassan
Keyword(s):  
Extreme Events ◽  
Extreme Rainfall ◽  
Ground Truth ◽  
Extreme Rainfall Events ◽  
Ground Truth Data ◽  
Rainfall Events ◽  
Variable Performance

This work focuses on the analysis of the performance of satellite-based precipitation products for monitoring extreme rainfall events. Five precipitation products are inter-compared and evaluated in capturing indices of extreme rainfall events during 1998-2019 considering four indices of extreme rainfall. Satellite products show a variable performance, which in general indicates that the occurrence and amount of rainfall of extreme events can be both underestimated or overestimated by the datasets in a systematic way throughout the country. Also, products that consider the use of ground truth data have the best performance.

scholarly journals Evaluation of Rainfall-Triggered Debris Flows under the Impact of Extreme Events: A Chenyulan Watershed Case Study, Taiwan

Water ◽  
2021 ◽  
Vol 13 (16) ◽  
pp. 2201
Author(s):  
Jinn-Chyi Chen ◽  
Wen-Shun Huang
Keyword(s):  
Debris Flow ◽  
Extreme Events ◽  
Debris Flows ◽  
Extreme Rainfall ◽  
Extreme Rainfall Event ◽  
Extreme Rainfall Events ◽  
Hourly Rainfall ◽  
Central Taiwan ◽  
The Impact

This study examined the conditions that lead to debris flows, and their association with the rainfall return period (T) and the probability of debris flow occurrence (P) in the Chenyulan watershed, central Taiwan. Several extreme events have occurred in the Chenyulan watershed in the past, including the Chi-Chi earthquake and extreme rainfall events. The T for three rainfall indexes (i.e., the maximum hourly rainfall depth (Im), the maximum 24-h rainfall amount (Rd), and RI (RI = Im× Rd)) were analyzed, and the T associated with the triggering of debris flows is presented. The P–T relationship can be determined using three indexes, Im, Rd, and RI; how it is affected and unaffected by extreme events was developed. Models for evaluating P using the three rainfall indexes were proposed and used to evaluate P between 2009 and 2020 (i.e., after the extreme rainfall event of Typhoon Morakot in 2009). The results of this study showed that the P‒T relationship, using the RI or Rd index, was reasonable for predicting the probability of debris flow occurrence.

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.

Watershed Hydrological and Chemical Responses to Precipitation Variability in the Luquillo Mountains of Puerto Rico

2003 ◽  
Author(s):  
Douglas Schaefer
Keyword(s):  
Puerto Rico ◽  
Extreme Events ◽  
Extreme Rainfall ◽  
Precipitation Variability ◽  
Extreme Rainfall Events ◽  
Rainfall Events ◽  
Tropical Regions ◽  
The North ◽  
Temperature And Precipitation ◽  
The North Atlantic

Variations in temperature and precipitation are both components of climate variability. Based on coral growth rates measured near Puerto Rico, the Caribbean was 2–3ºC cooler during the “Little Ice Age” during the seventeenth century (Winter et al. 2000). At the millennial scale, temperature variations in tropical regions have been inferred to have substantial biological effects (such as speciation and extinction), but not at the multidecadal timescales considered here. My focus is on precipitation variability in particular, because climate models examining effects of increased greenhouse gases suggest greater changes in precipitation than in temperature patterns in tropical regions. Some correspondence between both the El Niño–Southern Oscillation (ENSO) and the Northern Atlantic Oscillation (NAO) and average temperatures and total annual precipitation have been reported for the LTER site at Luquillo (Greenland 1999; Greenland and Kittel 2002), but those studies did not refer to extreme events. Based on climate records for Puerto Rico since 1914, Malmgren et al. (1997) found small increases in air temperature during El Niño years and somewhat greater total rainfall during the positive phase of the NAO. Similar to ENSO, the NAO index is characterized by differences in sea-level atmospheric pressure, in this case based on measurements in Iceland and Portugal (Walker and Bliss 1932). Its effects on climate have largely been described in terms of temperature and precipitation anomalies in countries bordering the North Atlantic (e.g., Hurrell 1995). Puerto Rico is in the North Atlantic hurricane zone, and hurricanes clearly play a major role in precipitation variability. The association between extreme rainfall events and hurricanes is discussed in detail in this chapter. I examine the degree to which extreme rainfall events are associated with hurricanes and other tropical storms. I discuss whether the occurrence of these extreme events has changed through time in Puerto Rico or can be linked to the recurrent patterns of the ENSO or the NAO. I examine the 25-year daily precipitation record for the Luquillo LTER site, the 90-year monthly record from the nearest site to Luquillo with such a long record, Fajardo, and those of the two other Puerto Rico stations with the longest daily precipitation records, Manati and Mayaguez (figure 8.1).

Cross–Time Scale Interactions and Rainfall Extreme Events in Southeastern South America for the Austral Summer. Part II: Predictive Skill

2016 ◽  
Vol 29 (16) ◽  
pp. 5915-5934 ◽  
Author(s):  
Á. G. Muñoz ◽  
L. Goddard ◽  
S. J. Mason ◽  
A. W. Robertson
Keyword(s):  
South America ◽  
Surface Temperature ◽  
Extreme Events ◽  
Time Scale ◽  
Extreme Rainfall ◽  
Sea Surface ◽  
Weather Types ◽  
Extreme Rainfall Events ◽  
Rainfall Events ◽  
Predictive Skill

Abstract Potential and real predictive skill of the frequency of extreme rainfall in southeastern South America for the December–February season are evaluated in this paper, finding evidence indicating that mechanisms of climate variability at one time scale contribute to the predictability at another scale; that is, taking into account the interference of different potential sources of predictability at different time scales increases the predictive skill. Part I of this study suggested that a set of daily atmospheric circulation regimes, or weather types, was sensitive to these cross–time scale interferences, conducive to the occurrence of extreme rainfall events in the region, and could be used as a potential predictor. At seasonal scale, a combination of those weather types indeed tends to outperform all the other candidate predictors explored (i.e., sea surface temperature patterns, phases of the Madden–Julian oscillation, and combinations of both). Spatially averaged Kendall’s τ improvements of 43% for the potential predictability and 23% for real-time predictions are attained with respect to standard models considering sea surface temperature fields alone. A new subseasonal-to-seasonal predictive methodology for extreme rainfall events is proposed based on probability forecasts of seasonal sequences of these weather types. The cross-validated real-time skill of the new probabilistic approach, as measured by the hit score and the Heidke skill score, is on the order of twice that associated with climatological values. The approach is designed to offer useful subseasonal-to-seasonal climate information to decision-makers interested not only in how many extreme events will happen in the season but also in how, when, and where those events will probably occur.

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