scholarly journals Interannual Variability of Air Temperature over Myanmar: The Influence of ENSO and IOD

Climate ◽  
2021 ◽  
Vol 9 (2) ◽  
pp. 35
Author(s):  
Zin Mie Mie Sein ◽  
Irfan Ullah ◽  
Sidra Syed ◽  
Xiefei Zhi ◽  
Kamran Azam ◽  
...  
Keyword(s):  
Air Temperature ◽  
El Niño ◽  
Water Resource Management ◽  
El Nino ◽  
Southern Oscillation ◽  
Rapid Change ◽  
Winter Season ◽  
Positive Trend ◽  
Study Region ◽  
Target Region

Myanmar is located in a tropical region where temperature rises very fast and hence is highly vulnerable to climate change. The high variability of the air temperature poses potential risks to the local community. Thus, the current study uses 42 synoptic meteorological stations to assess the spatiotemporal changes in air temperature over Myanmar during 1971–2013. The nonparametric sequential Mann-Kendall (SqMK), linear regression, empirical orthogonal function (EOF), Principal Component Analysis (PCA), and composite analysis were used to assess the long-term trends in maximum (Tmax) and minimum (Tmin) temperature series and their possible mechanism over the study region. The results indicate that the trend of Tmax has significantly increased at the rates of 90% in summer season, while the Tmin revealed a substantial positive trend in winter season time series with the magnitude of 30%, respectively. Moreover, during a rapid change of climate (1995–2013) we observed an air temperature increase of 0.7 °C. The spatial distributions of EOF revealed relatively warmer temperatures over the whole region except the south in the summer; however, a similar pattern can be seen for the rainy season and winter, implying warming in the central part and cooling in the northern and southern parts. Furthermore, the Indian Ocean Dipole (IOD) influence on air temperature over Myanmar is more prevalent than that of the El Niño Southern Oscillation (ENSO). The result implies that the positive phase of the IOD and negative phase of the Southern Oscillation Index (SOI; El Niño) events led to the higher temperature, resulting in intense climatic extremes (i.e., droughts and heatwaves) over the target region. Therefore, this study’s findings can help policymakers and decision-makers improve economic growth, agricultural production, ecology, water resource management, and preserving the natural habitat in the target region.

scholarly journals Identifying El Niño–Southern Oscillation influences on rainfall with classification models: implications for water resource management of Sri Lanka

2019 ◽  
Vol 23 (4) ◽  
pp. 1905-1929 ◽  
Author(s):  
Thushara De Silva M. ◽  
George M. Hornberger
Keyword(s):  
Resource Management ◽  
Sri Lanka ◽  
Water Resource ◽  
El Niño ◽  
Water Resource Management ◽  
El Nino ◽  
Southern Oscillation ◽  
El Niño Southern Oscillation ◽  
El Nino Southern Oscillation ◽  
Kelani River

Abstract. Seasonal to annual forecasts of precipitation patterns are very important for water infrastructure management. In particular, such forecasts can be used to inform decisions about the operation of multipurpose reservoir systems in the face of changing climate conditions. Success in making useful forecasts is often achieved by considering climate teleconnections such as the El Niño–Southern Oscillation (ENSO) and Indian Ocean Dipole (IOD) as related to sea surface temperature variations. We present a statistical analysis to explore the utility of using rainfall relationships in Sri Lanka with ENSO and IOD to predict rainfall to the Mahaweli and Kelani River basins of the country. Forecasting of rainfall as the classes flood, drought, and normal is helpful for water resource management decision-making. Results of these models give better accuracy than a prediction of absolute values. Quadratic discrimination analysis (QDA) and classification tree models are used to identify the patterns of rainfall classes with respect to ENSO and IOD indices. Ensemble modeling tool Random Forest is also used to predict the rainfall classes as drought and not drought with higher skill. These models can be used to forecast the areal rainfall using predicted climate indices. Results from these models are not very accurate; however, the patterns recognized provide useful input to water resource managers as they plan for adaptation of agriculture and energy sectors in response to climate variability.

The Influence of the El Niño–Southern Oscillation on Cloud-to-Ground Lightning Activity along the Gulf Coast. Part I: Lightning Climatology

2008 ◽  
Vol 136 (7) ◽  
pp. 2523-2542 ◽  
Author(s):  
Mark LaJoie ◽  
Arlene Laing
Keyword(s):  
El Niño ◽  
Gulf Coast ◽  
El Nino ◽  
Southern Oscillation ◽  
Winter Season ◽  
Lightning Activity ◽  
El Niño Southern Oscillation ◽  
El Nino Southern Oscillation ◽  
Enso Cycle ◽  
Lightning Flash

Abstract Cloud-to-ground (CG) lightning flashes from the National Lightning Detection Network are analyzed to determine if the El Niño–Southern Oscillation (ENSO) cycle influences lighting activity along the Gulf Coast region. First, an updated climatology of lightning was developed for the region. Flash density maps are constructed from an 8-yr dataset (1995–2002) and compared with past lightning climatologies. Second, lightning variability is compared with the phases of ENSO. Winter lightning distributions are compared with one published study of ENSO and lightning days in the Southeast. Flash density patterns are, overall, consistent with past U.S. lightning climatology. However, the peak flash density for the annual mean was less than observed in previous climatologies, which could be due to the disproportionately large percentage of cool ENSO periods compared to previous lightning climatologies. The highest annual lightning counts were observed in 1997, which consisted of mostly warm ENSO seasons; the 1997–98 El Niño was one of the strongest on record. The lowest lightning counts were observed in 2000, which had mostly cool or neutral phases of ENSO including the lowest Niño-3.4 anomaly of the study period. Analysis of winter season lightning flash densities substantiated the role of the ENSO cycle in winter season lightning fluctuations. Winter lightning activity increased dramatically during the 1997–98 El Niño. The lowest winter flash densities are associated with cool ENSO phases. Although 8 yr is inadequate to establish a long-term pattern, results indicate that ENSO influences lightning and that further study is warranted. As more years of lightning data are acquired, a more complete climatology can be developed.

scholarly journals Wintertime Nonbrightband Rain in California and Oregon during CALJET and PACJET: Geographic, Interannual, and Synoptic Variability

2005 ◽  
Vol 133 (5) ◽  
pp. 1199-1223 ◽  
Author(s):  
Paul J. Neiman ◽  
Gary A. Wick ◽  
F. Martin Ralph ◽  
Brooks E. Martner ◽  
Allen B. White ◽  
...  
Keyword(s):  
El Niño ◽  
El Nino ◽  
Southern Oscillation ◽  
Winter Season ◽  
Radar Data ◽  
Operational Environment ◽  
Low Level ◽  
Synoptic Variability ◽  
Synoptic Conditions ◽  
Cloud Tops

Abstract An objective algorithm presented in White et al. was applied to vertically pointing S-band (S-PROF) radar data recorded at four sites in northern California and western Oregon during four winters to assess the geographic, interannual, and synoptic variability of stratiform nonbrightband (NBB) rain in landfalling winter storms. NBB rain typically fell in a shallow layer residing beneath the melting level (<∼3.5 km MSL), whereas rainfall possessing a brightband (BB) was usually associated with deeper echoes (>∼6 km MSL). The shallow NBB echo tops often resided beneath the coverage of the operational Weather Surveillance Radar-1988 Doppler (WSR-88D) scanning radars yet were still capable of producing flooding rains. NBB rain contributed significantly to the total winter-season rainfall at each of the four geographically distinct sites (i.e., 18%–35% of the winter-season rain totals). In addition, the rainfall observed at the coastal mountain site near Cazadero, California (CZD), during each of four winters was composed of a significant percentage of NBB rain (18%–50%); substantial NBB rainfall occurred regardless of the phase of the El Niño–Southern Oscillation (which ranged from strong El Niño to moderate La Niña conditions). Clearly, NBB rain occurs more widely and commonly in California and Oregon than can be inferred from the single-winter, single-site study of White et al. Composite NCEP–NCAR reanalysis maps and Geostationary Operational Environment Satellite (GOES) cloud-top temperature data were examined to evaluate the synoptic conditions that characterize periods of NBB precipitation observed at CZD and how they differ from periods with bright bands. The composites indicate that both rain types were tied generally to landfalling polar-cold-frontal systems. However, synoptic conditions favoring BB rain exhibited notable distinctions from those characterizing NBB periods. This included key differences in the position of the composite 300-mb jet stream and underlying cold front with respect to CZD, as well as notable differences in the intensity of the 500-mb shortwave trough offshore of CZD. The suite of BB composites exhibited dynamically consistent synoptic-scale characteristics that yielded stronger and deeper ascent over CZD than for the typically shallower NBB rain, consistent with the GOES satellite composites that showed 20-K warmer (2.3-km shallower) cloud tops for NBB rain. Composite soundings for both rain types possessed low-level potential instability, but the NBB sounding was warmer and moister with stronger low-level upslope flow, thus implying that orographically forced rainfall is enhanced during NBB conditions.

scholarly journals The Influence of Large-Scale Climate Variability on Winter Maximum Daily Precipitation over North America

2010 ◽  
Vol 23 (11) ◽  
pp. 2902-2915 ◽  
Author(s):  
Xuebin Zhang ◽  
Jiafeng Wang ◽  
Francis W. Zwiers ◽  
Pavel Ya Groisman
Keyword(s):  
North America ◽  
Climate Variability ◽  
El Niño ◽  
Extreme Precipitation ◽  
Large Scale ◽  
El Nino ◽  
Southern Oscillation ◽  
Statistical Significance ◽  
Winter Season ◽  
The North

Abstract The generalized extreme value (GEV) distribution is fitted to winter season daily maximum precipitation over North America, with indices representing El Niño–Southern Oscillation (ENSO), the Pacific decadal oscillation (PDO), and the North Atlantic Oscillation (NAO) as predictors. It was found that ENSO and PDO have spatially consistent and statistically significant influences on extreme precipitation, while the influence of NAO is regional and is not field significant. The spatial pattern of extreme precipitation response to large-scale climate variability is similar to that of total precipitation but somewhat weaker in terms of statistical significance. An El Niño condition or high phase of PDO corresponds to a substantially increased likelihood of extreme precipitation over a vast region of southern North America but a decreased likelihood of extreme precipitation in the north, especially in the Great Plains and Canadian prairies and the Great Lakes/Ohio River valley.

scholarly journals Climatic Risk Zoning for Potential Occurrence of Cacao Moniliasis Disease in Northeastern Brazil Under The Influence of ENSO Phases

2021 ◽  
Author(s):  
Ícaro Monteiro Galvão ◽  
Gislaine Silva Pereira ◽  
Paulo Sentelhas
Keyword(s):  
Relative Humidity ◽  
Latin American ◽  
Air Temperature ◽  
El Niño ◽  
El Nino ◽  
Southern Oscillation ◽  
The State ◽  
Northeastern Brazil ◽  
Cocoa Production ◽  
Enso Phases

Abstract Air temperature and relative humidity are the main drivers of many fungal diseases, such as moniliasis (Moniliophthora roreri), which affects cocoa production worldwide. This disease occurs in some Latin American countries; however, it has not yet occurred in Brazil. Moniliasis could cause serious damage to the Brazilian cocoa production if present in the country. Therefore, to know the risks of moniliasis to cocoa production in the largest Brazilian producing region, in the state of Bahia, this study investigated the climatic favorability for the occurrence of this disease in this state, by defining and mapping the climatic risks and by assessing the influence of El Niño Southern Oscillation (ENSO) phases on it. Daily air temperature and relative humidity data from 28 weather stations of the national weather network in the state of Bahia, between 1988 and 2018, were employed to determine the risk index for cocoa moniliasis occurrence (RICM), based on the number of days favorable to the disease, which was categorized in five levels of favorability, ranging from “unfavorable” to “very favorable”. Seasonal and annual RICM maps were generated by a multiple linear regression procedure, considering raster layers of latitude, longitude, and altitude. The maps showed a high spatial and temporal RICM variability in the state of Bahia, with the highest risk for moniliasis occurrence in the eastern part of the state, where most producing areas are located. The ENSO phase showed to influence cocoa moniliasis occurrence, with the years with a transition between El Niño and Neutral phases being the most critical for this disease in majority of assessed locations. These results show that cocoa producers in the state of Bahia, Brazil, should be concerned with moniliasis occurrence as a potential disease for their crops, mainly in the traditional producing regions and when ENOS is in a transition from El Niño to Neutral.

scholarly journals Dry-Season Snow Cover Losses in the Andes (18°–40°S) driven by Changes in Large-Scale Climate Modes

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Raul R. Cordero ◽  
Valentina Asencio ◽  
Sarah Feron ◽  
Alessandro Damiani ◽  
Pedro J. Llanillo ◽  
...  
Keyword(s):  
Snow Cover ◽  
El Niño ◽  
Large Scale ◽  
El Nino ◽  
Southern Oscillation ◽  
Average Rate ◽  
Dry Season ◽  
Positive Trend ◽  
Entire Study ◽  
Snow Cover Extent

AbstractThe Andean snowpack is the primary source of water for many communities in South America. We have used Landsat imagery over the period 1986–2018 in order to assess the changes in the snow cover extent across a north-south transect of approximately 2,500 km (18°–40°S). Despite the significant interannual variability, here we show that the dry-season snow cover extent declined across the entire study area at an average rate of about −12% per decade. We also show that this decreasing trend is mainly driven by changes in the El Niño Southern Oscillation (ENSO), especially at latitudes lower than 34°S. At higher latitudes (34°–40°S), where the El Niño signal is weaker, snow cover losses appear to be also influenced by the poleward migration of the westerly winds associated with the positive trend in the Southern Annular Mode (SAM).

scholarly journals Atmospheric torques and Earth's rotation: what drove the millisecond-level length-of-day response to the 2015–2016 El Niño?

2017 ◽  
Vol 8 (4) ◽  
pp. 1009-1017 ◽  
Author(s):  
Sébastien B. Lambert ◽  
Steven L. Marcus ◽  
Olivier de Viron
Keyword(s):  
El Niño ◽  
El Nino ◽  
Southern Oscillation ◽  
Winter Season ◽  
Eastern Pacific ◽  
Earth’S Rotation ◽  
Length Of Day ◽  
Central Pacific ◽  
Earth's Rotation ◽  
Enso Events

Abstract. El Niño–Southern Oscillation (ENSO) events are classically associated with a significant increase in the length of day (LOD), with positive mountain torques arising from an east–west pressure dipole in the Pacific driving a rise of atmospheric angular momentum (AAM) and consequent slowing of the Earth's rotation. The large 1982–1983 event produced a lengthening of the day of about 0.9 ms, while a major ENSO event during the 2015–2016 winter season produced an LOD excursion reaching 0.81 ms in January 2016. By evaluating the anomaly in mountain and friction torques, we found that (i) as a mixed eastern–central Pacific event, the 2015–2016 mountain torque was smaller than for the 1982–1983 and 1997–1998 events, which were pure eastern Pacific events, and (ii) the smaller mountain torque was compensated for by positive friction torques arising from an enhanced Hadley-type circulation in the eastern Pacific, leading to similar AAM–LOD signatures for all three extreme ENSO events. The 2015–2016 event thus contradicts the existing paradigm that mountain torques cause the Earth rotation response for extreme El Niño events.

scholarly journals Prediction and Validation of Rainfall Classes for Vaigai River Catchment using El Nino

2019 ◽  
Vol 8 (2) ◽  
pp. 1412-1427
Keyword(s):  
Statistical Analysis ◽  
El Niño ◽  
Tamil Nadu ◽  
Water Resource Management ◽  
El Nino ◽  
Southern Oscillation ◽  
Rain Gauge ◽  
Enso Cycle ◽  
Neural Network Models ◽  
River Catchment

Extraordinary weather patterns are being observed globally during the past 30 years due to climate change resulting in variations in temperature and rainfall. Studies on long-term trend pattern of temperature and rainfall since 1980 distinctly shows a rise in mean temperature and declining rainfall trend. Due to change of climate at global level change, forecasting of rainfall with the conventional statistical analysis could not predict satisfactory results. Among the available processes, the El Niño Southern Oscillation (ENSO) cycle is considered efficient. Statistical analysis was carried out in this study so as to investigate the implication of rainfall data in seven rain gauge stations located in Vaigai River Catchment through the period from 1959 to 2016. ENSO Cycle was used also to predict rainfall for Vaigai River catchment of the Tamil Nadu State, India. Quadratic discrimination analysis (QDA) and Neural Network models are used to identify the class of rainfall classes with reference to ENSO cycle. The patterns recognized on the study area offer constructive information to administrators of water resource management, to implement the same for agriculture, water supply and power generation.

scholarly journals South Carolina's Climate Report Card: The Influence of the El Niño Southern Oscillation Cold Warm Event Cycles on South Carolina's Seasonal Precipitation

2015 ◽  
pp. 3-10 ◽  
Author(s):  
Hope Mizzell ◽  
Jennifer Simmons
Keyword(s):  
El Niño ◽  
Water Resource Management ◽  
El Nino ◽  
Southern Oscillation ◽  
The United States ◽  
El Niño Southern Oscillation ◽  
El Nino Southern Oscillation ◽  
Seasonal Precipitation ◽  
Seasonal Temperature ◽  
Warm Event

This study was driven by the need to better understand variations in South Carolina’s seasonal precipitation. Numerous weather-sensitive sectors such as agriculture and water resource management are impacted by the seasonal variability and distribution of precipitation. Studies have shown that El Niño-Southern Oscillation (ENSO) has varying effects on seasonal temperature and precipitation across the United States. The purpose of this study was to determine the relative influence of ENSO cold and warm event cycles on interannual variations of South Carolina’s seasonal precipitation (1950- 2015). The relationship between seasonal precipitation departures from normal and the average Multivariate ENSO Index was analyzed. Seasonal precipitation totals for each of South Carolina’s seven climate divisions and for three key city locations (Greenville-Spartanburg Airport, Columbia Airport, and Charleston Downtown) were examined. Results from the study indicate that the magnitude, seasonal variation, and consistency of the precipitation response to ENSO vary spatially and from episode to episode. Winter precipitation tends to be enhanced during the warm phase (El Niño) and reduced during the cold phase (La Niña). There is a less consistent signal during fall and no evident connection between ENSO and spring and summer precipitation.

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