Observed trends and variability of heatwave across vietnam

VIETNAM NATIONAL UNIVERSITY, HANOI VIETNAM JAPAN UNIVERSITY VU THUAN YEN OBSERVED TRENDS AND VARIABILITY OF HEATWAVE ACROSS VIETNAM MASTER'S THESIS VIETNAM NATIONAL UNIVERSITY, HANOI VIETNAM JAPAN UNIVERSITY VU THUAN YEN OBSERVED TRENDS AND VARIABILITY OF HEATWAVE ACROSS VIETNAM MAJOR: CLIMATE CHANGE AND DEVELOPMENT CODE: 8900201.02QTD RESEARCH SUPERVISOR: Prof Dr Phan Van Tan Prof Dr Kusaka Hiroyuki Hanoi, 2020 PLEDGE I assure that this thesis is the results of my own research and has not been published The use of other research’s result and other documents must comply with regulations The citations and references to documents, books, research papers, and websites must be in the lists of references of the thesis AUTHOR OF THE THESIS VU THUAN YEN i TABLE OF CONTENT PLEDGE .i TABLE OF CONTENT ii LIST OF TABLES iii LIST OF FIGURES iv ACKNOWLEDGEMENT v CHAPTER 1: INTRODUCTION 1.1 Literature review 1.1.1 Heatwave in global scales 1.1.2 Heatwave in Vietnam 1.1.3 Research Gap 1.2 Necessity of research 1.3 Research question 11 1.4 Research hypothesis 12 1.5 Research objective 12 1.6 Scope of research 12 1.7 Research structure 13 CHAPTER 2: DATA AND METHODOLOGY 14 2.1 Data 14 2.2 Method 16 CHAPTER 3: RESULTS AND DISCUSSION 26 3.1 Daily threshold for defining heatwave 26 3.2 Spatial and temporal variations of heatwave across Vietnam 27 3.3 Trend of changes of heatwave characteristics 40 3.4 Limitations of thesis and further research orientation 42 3.5 Recommendations for using the research results 42 CHAPTER 4: CONCLUSION 44 REFERENCES 46 APPENDIX 46 ii LIST OF TABLES Table 2.1 Names, ID, and Regions belonged to 109 meteorological Stations 16 Table 2.2 Different definitions of Heatwave 17 Table 3.1 Average values of Heatwave characteristics of each region 29 iii LIST OF FIGURES Figure 2.1 Climatic sub-regions of Vietnam 15 Figure 2.2 Heatwave characteristics demonstration 22 Figure 3.1 Heatwave threshold: 90th percentile daily maximum temperature ……27 Figure 3.2 Average value of heatwave characteristic of 109 stations 28 Figure 3.3 Heatwave characteristics with 90th percentile threshold and ONI-based ENSO phases in the same period 31 Figure 3.4 Heatwave characteristics with fixed threshold 35° C 33 Figure 3.5 Inter- annual variation of Number of Heatwave (spell) across Vietnam (1980 - 2018) 35 Figure 3.6 Inter- annual variation of Mean duration of Heatwave (days) across Vietnam (1980 - 2018) 37 Figure 3.7 Inter- annual variation of Number of Heatwave days (day) across Vietnam (1980 - 2018) 38 Figure 3.8 Inter- annual variation of Number of hot days (day) across Vietnam (1980 - 2018) 39 Figure 3.9 Trend of changes of heatwave characteristics …………………………41 iv ACKNOWLEDGEMENT After months of work on my research, I would first like to give the sincerest thanks to my supervisors, Prof Phan Van Tan and Prof Kusaka Hiroyuki Their guidance and support have made this research possible Prof Phan Van Tan has supported me all the time while Prof Kusaka Hiroyuki has allowed me to learn about the heatwave at Tsukuba University, during the research internship in Japan I would like to thank Regional Climate Modeling and Climate Change (REMOCLIC) advanced Research Group, Climate Change - Induced Water Disaster, and Participatory Information System for Vulnerability Reduction in North Central Vietnam (CPIS) for providing the database of Vietnam meteorological station data Besides that, the Vietnam General Statistic Office also is a help for me in collecting data Finally, I would like to say thank to my family, friends and all of whom supported me and encourage me to finish the writing when I felt so struggling with the research, especially the VJU, JICA, University of Tsukuba, University of Ibaraki, Hanoi University of Science v CHAPTER 1: INTRODUCTION 1.1 Literature review Heatwave has occurred worldwide, remarkably are record in 2003 of England and Western Europe killed about 2193; 70000 individuals, respectively (Coumou and Rahmstorf, 2012) Moreover, the 2010 Russia heatwave which lasted for over a month is responsible for around 54000 dead people (McMichael and Lindgren, 2011) Due to the significant impact of heatwave, numerous studies of heatwave were conducted regarding characteristics of heatwave, its trend, and impact, as well as the correlation with other factors related to climate change Heatwave studies are notable from 2010 to present in both international scales and local scales 1.1.1 Heatwave in global scales Regarding international works, the scope of studies spread across the globe, continents, and countries Heatwave was defined very differently depending on research objectives, scope, and resources, geographic and climatic features In general, heatwave is defined as a period of at least three consecutive days the selected temperature value exceeds the threshold This threshold could be an absolute threshold (Smith, Zaitchik et al., 2013) or relative threshold (based on percentile determination) After define and detect heatwave events, heatwave characteristics were determined for analyzing trends and correlation with other phenomena that the author concerned Fischer and Schär (2010) analyzed a set of high-resolution regional climate simulations and indicated a geographically consistent pattern among climate models To that, heatwave frequency and duration, the amplitude is produced for healthrelated indicators Heatwave, used in the study, was defined as a spell of at least six days in a row with maximum temperature exceeding the local 90th percentile of the control period (1961-1990) The 90th percentile is calculated for each calendar day, each model, and at each grided point applying a centered 15-day-long time window to take account of the seasonal cycle In order to quantify changes in heatwave characteristics; the authors individuated heatwave day frequency (HWF90), amplitude (HWA90), number (HWN90), and maximum duration (HWD90) They concentrate on changes in warm nights which are kind to firmly amplify health effects by inhibiting the recovery from the daytime heat and through sleep deprivation Combined hot days and tropical nights (CHT), which is the consecutive occurrence of a hot day (Maximum temperature Tmax > 35°C) and tropical nights (minimum temperature Tmin > 20°C), have been detected to explain spatial and temporal variance in excess mortality The simulated CHT values (1961-1990) differ substantially between models CHT is particularly sensitive to biases in model climatology due to their relation to absolute temperature threshold despite the particular interest of the spatial pattern of CHT changes Because of focusing on health impact, this study embeds some heat index which is related to heat stress For example, AT105F (exceedance of apparent temperature threshold) indicates the average number of summer days with maximum humidity-corrected AT exceeding 40.6°C The study of Pezza and Van Rensch (2012) brought a new perspective on large scale dynamics of severe heatwave events generally affecting southern Australia The study explored the large-scale synoptic associations with heatwave A better understanding of this connection is crucial for the improvement of forecast Heatwave In the study, the authors used daily maximum (after AM) and minimum (before AM local time) temperature of stations including Melbourne Airport, Adelaide Airport, and Perth Airport for the period from January 1979 to March 2008 Heatwave was defined as the periods of three consecutive days in which a temperature threshold was more than or equal to the threshold The 90th percentile of monthly climatology was used to avoid a seasonal bias (Simmonds and Richter 2000) In the meantime, the maximum temperature was met or exceed 90th percentile of the maximum temperature for the month in which the heatwave begins for a minimum of consecutive days Perkins, Alexander (2012) addressed the issues of inconsistent of definitions, measurements, and impacts of the heatwave by employing a set of three heatwave definitions including three or more consecutive days above one of the following: the 90th percentile for maximum temperature (CTX90pct), the 90th percentile for minimum temperature (CTN90pct), and positive extreme heat factor (EHF) conditions For more detail, CTX90pct is the threshold which is the calendar day 90th percentile of Tmax, based on a 15-day window Thus, there is a different percentile value for each day of the year CTN90pct is the calendar day 90th percentile of Tmin EHF is based on two excess heat indices (EHIs) The study applied specifically to the Australian continent The data used are daily gridded observations of Tmin and Tmax, along with vapor pressure and precipitation at 0.05 x 0.05-degree resolution Perkin (2012) followed the similar methodology of Pezza and Van Rensch (2012) for an event of at least three days’ length, rather than events of at least six conservative days by Fischer and Schär (2010) They emphasized on annual values of HWF, HWN, HWD, and HWA for 30-year time slices, while Perkin (2012) calculated average heat wave magnitude (HWM) All five characteristics are calculated annually These are: HWM is the average daily magnitude across all heatwave events within a year; HWA indicates the hottest day of the hottest yearly event; HWN is the number of heatwave per year; HWD is the length (in days) of the longest event in a year; HWF is the total of participating heatwave days per year that satisfy the definition criteria In the paper of Smith and Zaitchik (2013), they aim to describe and explain the impact of choosing a definition regarding the observed frequency of extreme heat events in different regions of the Continental United States (CONUS) in the previous period of 30 years, to provide a baseline for interpreting studies projected future trends in extreme heat events The approach of study is analyzing geographic patterns and trends for CONUS in 15 heatwave indices (HI) which are published previously The authors stated that there is no universal standard definition of heatwave The patterns, trends, and impacts, therefore confuse amongst various indexes Experts defined threshold values differently which are absolute and relative 16 heat indices used in the study categorized into two main groups based on thresholds used in defining heatwave: relative thresholds and absolute thresholds Warm-season is defined as the period starting from 1st May to 30th September for the years 19792011 Regarding relative thresholds, indices from HI01 to HI06 according to Anderson and Bell (2009), a threshold defined based on the long-term local temperature record must be met for at least two days in a row Some indices used daily Tmean, while some used Tmin Some relative-thresholds-based indices applied three steps process to define heatwave For absolute thresholds, heatwave day is a 3.4 Limitations of thesis and further research orientation One limitation of the method of calculation is El Niño in the year 1982-1983; 1987-1988 does not seem to be demonstrated through the characteristics An extremely strong 1997-1998 El Nino show in the chart is not clear This may mean that the method of calculating HWMag and HWAmp has not worked Another limitation of the thesis is the test of the 31-day-window-method for a narrow period Since this method applied for mid-latitude regions in which the climate quite stable, does not vary like the tropical climate in Vietnam The longdays-window would result in moderating the values of the threshold during the transition of the season in which temperature changes in the wide range In the context of climate change, the increase in heatwave has many negative consequences In order to study these effects in more detail, it is necessary to use indicators that affect health (heat stress) A prolonged heatwave can greatly affect human health, even affecting plants or animals Those are supposed to be suffered from "uncomfortable thermal condition" Based on the results of this study, further study of heat stress and its impact should be considered 3.5 Recommendations for using the research results The impact of the heatwave is heavy on nature and social systems Through this study, the increased trend changes in the heatwave in Vietnam are clearly seen In the context of climate change, the trend is expected to rise even more Therefore, in order to protect our life, minimize damage in community health, agricultural production; it is necessary to have appropriate measures to cope with the above phenomenon The results of this study could be reliable sources for policymakers Policymakers could have better urban planning with more green space base on this scientific evidence due to Urban Heat Island in the urban area Furthermore, from heatwave tracking, the evaluation criteria related to the human thermal threshold could be served as a premise to recommend the early heat warning system assisting appropriate adaptive solutions by changing living habits and major changes in the 42 context of climate change For example, the policy of working time for outdoor workers during the summer months is adjusted to limit the impact of heatwaves on workers' health Other vulnerable people such as the elderly and children are also taken care of carefully before and during the hot summertime 43 CHAPTER 4: CONCLUSION In general, based on the series of heatwave characteristics’ analysis, this thesis concludes the overall increase tendency in number, frequency, and severity of heatwave occurred across Vietnam territory over decades (1980-2018) In terms of heatwave thresholds, the level of the threshold of stations located in high elevator land is mostly lower than the average level amongst the climatic subregions containing these stations due to the humid subtropical climate of the area that these upland stations established In stations with low elevator, especially center is like big cities, the common threshold is above approximately 35°C since the Urban Heat Island (UHI) effect and Foehn wind effect In terms of heatwave characteristics, El Nino years have the number of heatwaves (HWN), the total number of heatwave days of events (HWF), number of hot days (Hdays) have the highest average value The reason is that the rise of sea temperature of El-Nino years leading to the higher received temperature Otherwise, two characteristics include heatwave magnitude (HWMag) and mean heatwave severity (HWS) of La-Nina years is higher than both El Nino and Neutral years In terms of trend, firstly, most characteristics of stations have increased over time, especially in the climatic sub-region R3 (Red River Delta) One possible reason for this increasing trend is rapid urbanization The other reason is related to the synoptic mechanism In R3, subtropical high pressure much encroaches and there is a combination of shifting to the east or expanding to the east of South Asia's low pressure that is when the two systems combine and create the heat Secondly, HWN, HWDx, Hdays, HWF, HWSx characteristics of the whole region tend to increase enormously in terms of the number of days, events, and Celsius degree due to global warming Otherwise, HWDmean, HWAmp, HWMag, HWS characteristics increase insignificantly and unclearly In the big picture, in 39 years (1980-2018), heatwave characteristics increase strongly in R3 and R4 Especially, the severity of heatwave increases most dramatically in R4 in mid-June (peak summer month which is the hottest month of 44 the year); then gradually decreases to the R3, R5, R6, R1, R2, R7 at the beginning of April and the end of September This result is consistent with the general trend of extreme weather in global studies Based on the results of this study, further study of heat stress and its impacts should be studied and implemented 45 REFERENCES Anderson, B G., & Bell, M L (2009) Weather-related mortality: how heat, cold, and heat waves affect mortality in the United States Epidemiology 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change: A science update from climate communication Climate Outreach Welbergen, J A., Klose, S M., Markus, N., & Eby, P (2008) Climate change and the effects of temperature extremes on Australian flying-foxes Proceedings of the Royal Society B: Biological Sciences, 275(1633), 419-425 Zacharias, S., Koppe, C., & Mücke, H G (2015) Climate change effects on heat waves and future heat wave-associated IHD mortality in Germany Climate, 3(1), 100-117 Zhao, Y., Ducharne, A., Sultan, B., Braconnot, P., & Vautard, R (2015) Estimating heat stress from climate-based indicators: present-day biases and future spreads in the CMIP5 global climate model ensemble Environmental Research Letters, 10(8), 084013 Zschenderlein, P., Fink, A H., Pfahl, S., & Wernli, H (2019) Processes determining heat waves across different European climates Quarterly Journal of the Royal Meteorological Society, 145(724), 2973-2989 48 APPENDIX Annex 1.a The trend of changes in the Number of heatwaves (events /decade) Dots with outer circle are satisfied 5% significant levels 49 Annex 2.d The trend of changes in the number of hot days (days /decade) Dots with outer circle are satisfied 5% significant levels 50 Annex 3.e- Trend of changes in Number of heatwave days (days /decade) Dots with outer circle are satisfied 5% significant levels 51 Annex 4.i- Trend of changes in Maximum heatwave severity (°C/decade) Dots with outer circle are satisfied 5% significant levels 52 Annex Inter-annual variation of Heatwave Amplitude (°C) across Vietnam 53 Annex Inter-annual variation of Heatwave Magnitude (°C) across Vietnam 54 Annex Inter-annual variation of Mean Heatwave Severity (°C) across Vietnam 55 Annex Heatwave threshold q90(°C): 90th percentile of daily maximum temperature (Tx) at stations of climatic sub-regions for summertime, the stations on the left-side vertical axis are listed according to their position on a North to South axis (North at the top), the climatic sub-regions that stations belong to are on the right-sides vertical axis 56 ... tittle ? ?Observed change and variability of heatwave across Vietnam. ” 1.5 Research objective This research aims to: + select the suitable heatwave index and identify heatwave conditions across Vietnam. .. Highland (R7) Delta 2.2 Method In order to evaluate observed trends and variability of a heatwave across Vietnam, the research applied methods of Zschenderlein (2019) in heatwave definition and. .. number of heatwaves and droughts in Vietnam The study of Binh and Dan (2015) presented verification and projection of the number of hot days for Vietnam by clWRF model The hot day's threshold of