scholarly journals Large-Scale Environmental Conditions Related to Midsummer Extreme Rainfall Events around Japan in the TRMM Region

2018 ◽  
Vol 31 (17) ◽  
pp. 6933-6945 ◽  
Author(s):  
Atsushi Hamada ◽  
Yukari N. Takayabu

The precipitation characteristics of extreme events in August determined from 13 years of satellite data around Japan in the TRMM observation region and their relationship with large-scale environmental conditions are examined. Two types of extreme events, extreme rainfall and extreme convective events, are defined in each analysis grid box using maximum near-surface rainfall and maximum 40-dB Z echo-top height in each event, respectively. There are clear differences in precipitation characteristics between the two types of extreme events. Extreme rainfall events are more organized precipitation systems than the extreme convective events, with relatively lower echo-top heights and very low lightning activity. There are also clear differences in the related environmental conditions, where the environments related to the extreme rainfall events are somewhat convectively stable and very humid in almost the entire troposphere. These facts are consistent with our previous studies and reinforce the importance of warm-rain processes in extremely intense precipitation productions. The environments related to the extreme rainfall events exhibit a zonally extended moist anomaly in the free troposphere from southern China to the east of Japan, indicating that the excessive moisture transported from the west by a large-scale flow may partially play a role in producing environmental conditions favorable for extreme rainfall. On the other hand, the environments related to extreme convective events are not associated with free-tropospheric moisture inflow. The relationships with the tropical cyclones and upper-tropospheric dynamical fields are also examined, and are found to be clearly different between the extreme rainfall events and extreme convective events.

2015 ◽  
Vol 28 (19) ◽  
pp. 7894-7913 ◽  
Author(s):  
Á. G. Muñoz ◽  
L. Goddard ◽  
A. W. Robertson ◽  
Y. Kushnir ◽  
W. Baethgen

Abstract The physical mechanisms and predictability associated with extreme daily rainfall in southeastern South America (SESA) are investigated for the December–February season in a two-part study. Through a k-mean analysis, this first paper identifies a robust set of daily circulation regimes that are used to link the frequency of rainfall extreme events with large-scale potential predictors at subseasonal-to-seasonal scales. This represents a basic set of daily circulation regimes related to the continental and oceanic phases of the South Atlantic convergence zone (SACZ) and wave train patterns superimposed on the Southern Hemisphere polar jet. Some of these recurrent synoptic circulation types are conducive to extreme rainfall events in the region through synoptic control of different mesoscale physical features and, at the same time, are influenced by climate phenomena that could be used as sources of potential predictability. Extremely high rainfall (as measured by the 95th and 99th percentiles) is associated with two of these weather types (WTs), which are characterized by moisture advection intrusions from lower latitudes and the Pacific Ocean; another three WTs, characterized by above-normal moisture advection toward lower latitudes or the Andes, are associated with dry days (days with no rain). The analysis permits the identification of several subseasonal-to-seasonal scale potential predictors that modulate the occurrence of circulation regimes conducive to extreme rainfall events in SESA. It is conjectured that a cross–time scale interaction between the different climate drivers improves the predictive skill of extreme precipitation in the region.


2014 ◽  
Vol 44 (7-8) ◽  
pp. 1823-1840 ◽  
Author(s):  
Ghyslaine Boschat ◽  
Alexandre Pezza ◽  
Ian Simmonds ◽  
Sarah Perkins ◽  
Tim Cowan ◽  
...  

Author(s):  
Carlo Montes ◽  
Nachiketa Acharya ◽  
Quamrul Hassan

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.


2021 ◽  
Author(s):  
Moses.A Ojara ◽  
Yunsheng Lou ◽  
Hasssen Babaousmail ◽  
Peter Wasswa

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.


Author(s):  
Douglas Schaefer

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).


2014 ◽  
Vol 27 (21) ◽  
pp. 8151-8169 ◽  
Author(s):  
Atsushi Hamada ◽  
Yuki Murayama ◽  
Yukari N. Takayabu

Abstract Characteristics and global distribution of regional extreme rainfall are presented using 12 yr of the Tropical Rainfall Measuring Mission (TRMM) Precipitation Radar (PR) measurements. By considering each rainfall event as a set of contiguous PR rainy pixels, characteristic values for each event are obtained. Regional extreme rainfall events are defined as those in which maximum near-surface rainfall rates are higher than the corresponding 99.9th percentile on a 2.5° × 2.5° horizontal-resolution grid. The geographical distribution of extreme rainfall rates shows clear regional differences. The size and volumetric rainfall of extreme events also show clear regional differences. Extreme rainfall rates show good correlations with the corresponding rain-top heights and event sizes over oceans but marginal or no correlation over land. The time of maximum occurrence of extreme rainfall events tends to be during 0000–1200 LT over oceans, whereas it has a distinct afternoon peak over land. There are also clear seasonal differences in which the occurrence over land is largely coincident with insolation. Regional extreme rainfall is classified by extreme rainfall rate (intensity) and the corresponding event size (extensity). Regions of “intense and extensive” extreme rainfall are found mainly over oceans near coastal areas and are likely associated with tropical cyclones and convective systems associated with the establishment of monsoons. Regions of “intense but less extensive” extreme rainfall are distributed widely over land and maritime continents, probably related to afternoon showers and mesoscale convective systems. Regions of “extensive but less intense” extreme rainfall are found almost exclusively over oceans, likely associated with well-organized mesoscale convective systems and extratropical cyclones.


2016 ◽  
Vol 29 (16) ◽  
pp. 5915-5934 ◽  
Author(s):  
Á. G. Muñoz ◽  
L. Goddard ◽  
S. J. Mason ◽  
A. W. Robertson

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.


2010 ◽  
Vol 11 (4) ◽  
pp. 950-965 ◽  
Author(s):  
Guobin Fu ◽  
Neil R. Viney ◽  
Stephen P. Charles ◽  
Jianrong Liu

Abstract The temporal variability of the frequency of short-duration extreme precipitation events in Australia for the period 1910–2006 is examined using the high-quality rainfall dataset identified by the Bureau of Meteorology, Australia, for 189 stations. Extreme events are defined by duration and recurrence interval: 1, 5, 10, and 30 days, and 1, 5, and 20 yr, respectively. The results indicate that temporal variations of the extreme precipitation index (EPI) for various durations and recurrence intervals in the last 100 yr, except for the low frequencies before 1918, have experienced three U-shaped cycles: 1918–53, 1953–74, and 1974–2006. Seasonal results indicate that about two-thirds of 1-day, 1-yr recurrence interval extreme events occur from December to March. Time series of anomalies of the regional EPIs for four regions indicate that northeast Australia and southeast Australia have almost the same temporal variation as the national anomalies, South Australia experienced a negative anomaly of extreme rainfall events in the mid-1950s, and southwest Western Australia (SWWA) experienced relatively small temporal variation. The relationships between extreme rainfall events and the Southern Oscillation index (SOI) and the interdecadal Pacific oscillation (IPO) indicate that extreme rainfall events in Australia have a strong relationship with both, especially during La Niña years and after 1942.


2009 ◽  
Vol 22 (7) ◽  
pp. 1589-1609 ◽  
Author(s):  
Alice M. Grimm ◽  
Renata G. Tedeschi

Abstract The influence of the opposite phases of ENSO on the frequency of extreme rainfall events over South America is analyzed for each month of the ENSO cycle on the basis of a large set of daily station rainfall data and compared with the influence of ENSO on the monthly total rainfall. The analysis is carried out with station data and their gridded version and the results are consistent. Extreme events are defined as 3-day mean precipitation above the 90th percentile. The mean frequencies of extreme events are determined for each month and for each category of year (El Niño, La Niña, and neutral), and the differences between El Niño and neutral years and La Niña and neutral years are computed. Changes in the mean intensity of extreme events are also investigated. Significant ENSO signals in the frequency of extreme events are found over extensive regions of South America during different periods of the ENSO cycle. Although ENSO-related changes in intensity show less significance and spatial coherence, there are some robust changes in several regions, especially in southeastern South America. The ENSO-related changes in the frequency of extreme rainfall events are generally coherent with changes in total monthly rainfall quantities. However, significant changes in extremes are much more extensive than the corresponding changes in monthly rainfall because the highest sensitivity to ENSO seems to be in the extreme range of daily precipitation. This is important, since the most dramatic consequences of climate variability result from changes in extreme events. The pattern of frequency changes produced by El Niño and La Niña episodes with respect to neutral years is roughly symmetric, but there are several examples of nonlinearity in the ENSO regional teleconnections.


MAUSAM ◽  
2021 ◽  
Vol 71 (3) ◽  
pp. 405-422
Author(s):  
JAYAWARDENA I M SHIROMANI PRIYANTHIKA ◽  
WHEELER MATTHEW C ◽  
SUMATHIPALA W L ◽  
BASNAYAKE B R S B

The influence of the Madden Julian Oscillation (MJO) on rainfall in Sri Lanka (SL) is examined based on 30 years of daily station data from 1981-2010. Composites are constructed for each of the eight phases of the MJO defined with the Real-time Multivariate MJO (RMM) index, using daily rainfall data from 44 stations over SL for four climatic seasons and comparing to similar results from a satellite-based rainfall product. Composites of lower tropospheric wind and convective anomaly are also investigated in order to examine how the local rainfall anomalies are associated with large-scale circulations. The greatest impact of the MJO on rainfall over SL occurs in the Second Inter-Monsoon (SIM) and Southwest Monsoon (SWM) seasons. Enhanced rainfall generally occurs over SL during RMM phases 2 and 3 when the MJO convective envelop is located in the Indian Ocean and conversely suppressed rainfall in phases 6 and 7. This rainfall impact is due to the direct influence of the MJO’s tropical convective anomalies and associated low-level circulations in the vicinity of SL. In contrast, the MJO influence during the Northeast Monsoon (NEM) season is slightly less than during the SWM and SIM seasons as a result of the southward shift of the MJO convective envelop during boreal winter. Occurrence of extreme rainfall events is most frequent during phase 2 in First Inter-Monsoon (FIM) phases 2 and 3 in SWM, phases 1, 2 and 3 in SIM and phases 2 and 3 in NEM seasons. The analysis of this study provides a useful reference of when and where the MJO has significant impacts on rainfall as well as extreme rainfall events during four climatic seasons in SL. This information can be used along with accurately predicted MJO phase by dynamical or statistical models, to improve extended range forecasting in SL.


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