In this dissertation, three main aims were addressed to examine the changes of heavy rainfall events in the past and in middle-future as well as to validate the reliability of satellite rainfall estimation. These include: (1) Using observation data and re-analysis data to investigate the long-term changes of autumn rainfall over south central Vietnam and impact of SST linkage with changes in the atmospheric dynamics, and thermodynamic fields; (2) Using Vietnam gridded precipitation dataset to evaluate comprehensively three satellite precipitation datasets over central Vietnam along with potential factors, and from that we suggested how to improve and use these products effectively; (3) Using the dynamical downscaling method in combination with the QM BC technique to simulate extreme rainfall events in the reference series (1986–2005) before applying it on extreme precipitation projection for the middle future (2046–2065).
In order to address the above objectives, this dissertation commenced by first reporting the increase of SOND Precipitation indices (PIs) over south central Vietnam for the period 1961–2012 in Chapter 2. The primary findings denote that the obvious decrease/increase in the North/South of 17°N in the coastal areas of Vietnam were clearly recognized. Additionally, both TC rainfalls and non-TC rainfalls increased significantly, contributing to the increase in rainfall amount over the SR. A point worth noting here is that the increasing trend of SOND rainfall had a linkage with the changes in the SST over the SVES. The warming of the SVES supported the increase in the evaporation over the SVES.
Then the supply of moisture along with the strengthening of the northeasterly winds contributed to the moisture convergence that led to the increase of deep convection over the SR. These findings suggested that the La Niña-like pattern might play an important role to drive the local SVES SST variations, thereby affect the inter-annual variation of SOND
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rainfall over central Vietnam. This study suggests that a proper representation of the SST as the lower boundary condition to the inter-annual variation of autumn boreal rainfall over Vietnam could be clarified by using numerical simulation studies.
In chapter 2, the increase of precipitation and extreme precipitation indices over south central Vietnam was reported based on observations at rain gauge stations. However, due to the topography of the central Vietnam are very complicated, the network is not dense enough for hydrological applications, a high temporal and spatial resolutions dataset which cover wide areas are very necessary. In order to provide useful information for hydrological applications such as water management or flood warning in central Vietnam, Chapter 3 represented a comprehensive assessment of three SPDs (CMORPH, GSMaP, and TRMM) during rainfall seasons in 2001–2010 over central Vietnam. In general, the SPDs showed slightly poorer performance in high elevation areas compared to that in the plains. TRMM showed a better performance than GSMaP and CMORPH over the VCH, specifically at regional and monthly scales. The GSMaP presented a fairly good performance in the VCH, but was less efficient in the VCC. On the contrary, CMORPH performed better in the VCC than in the VCH. In terms of detecting heavy rainfall on the WHR days, three SPDs performed relatively better in TI cases than in NM cases. Due to the advantages of gauge calibration and multi-satellite passive microwave data incorporation, the TRMM had best performance in capturing heavy rainfall thresholds, thus, showed a high potential for use in hydrological applications. Another noteworthy point is that, the SPDs underestimated rainfall with relation to monsoonal wind speed and elevation were shown in this chapter.
Therefore, SPDs can be further improved via reasonable algorithm correction for elevation and zonal wind speed.
Another important question that this dissertation aims to answer is how will the extreme precipitation events change in the future? In order to address this major question,
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this study first investigated the capability of representing extreme precipitation events by regional climate models downscaling. The results in Chapter 4 showed that the QM BC technique was applied successfully to the precipitation products over Vietnam from the RCM experiments conducted under the CORDEX–SEA project. The presented results in Chapter 4 also indicated significant improvements in the QM products in representing the six PIs for both major rainfall seasons in all seven sub-regions of Vietnam. It was also noted that the ensemble average of the experiments performed better than any individual member in capturing the spatial distribution of the PIs. Specifically, the results showed that the projected changes in the PIs over Vietnam in the mid-future period 2046–2065 were rather similar for both RCP4.5 and RCP8.5. In the north, drier conditions were anticipated, hence extreme rainfall amounts were projected to decrease in MJJA. Central Vietnam was also projected to experience a drier wet season in SOND. In the southern region, there is a high potential for the wetter condition to persist under RCP4.5, but a drier condition may be likely under RCP8.5. It is also worth mentioning that, the application of the QM BC generates more realistic representation of precipitation and its extremes in the reference period. In addition, the QM BC minimally modifies the future change signal from the original projections. Thus, these QM BC projections could be used towards a better understanding of climate change, and strengthen their applicability in further climate impact and adaptation studies.
Although, this dissertation has shown the relationship between the increase in SVES SST and the increase in SOND rainfall over the southern central Vietnam, it should be noted that their rainfall are dominated by many factors and consequently exact quantification of how many percent of rainfall had increased due to the increased SVES SST still remains a challenge. In future studies, the sensitive test of VES SST to SOND rainfall over central Vietnam will be conducted by using SST as the lower boundary condition in numerical simulation such as study of Dado and Takahashi (2017).
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Besides, due to a limited number of selected SPDs being validated, other different SPDs should be considered in future studies. This study has revealed the relationships among elevation, zonal wind speed and SPDs biases. Therefore, the bias correction method with related-algorithm correction that can improve the performance of SPDs (e.g., Yin et al., 2008; Shige et al., 2013; Castro et al., 2014). Furthermore, the SPDs can be also further improved by being merged/blended with VnGP as reference by using an accordant correction method (e.g., QM BC) to generate a comprehensive rainfall dataset (e.g., Yang et al., 2016).
In the future, a new bias-corrected version of SPD will be generated by reasonable correction method with VnGP for Vietnam.
Finally, It is very important to note that climate change scenarios always have uncertainties, accurate projection of rainfall in the future is a big challenge for not only Vietnam but also for other countries around the world. It is also crucial to note that this study has used RCMs downscaling from five GCMs of CMIP5 under the framework of the CORDEX–SEA due to the computational limitations, from which we highly suggest that more RCMs as well as GCMs should be considered in order to approach less uncertainty projections. Since this study has neither shown the association change in the large scale circulation (e.g., Monsoon system, TCs) nor precipitation change in far future, projections of them will be investigated comprehensively in future studies. Last but not least, the Sixth Assessment Report of IPCC will be reported in 2021, the climate change scenarios for Vietnam will be continuously updated and reviewed.
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Bibliography
Banacos PC, Schultz DM. 2005. The use of moisture flux convergence in forecasting convective initiation: Historical and operational perspectives. Wea. Forecasting 20:
351–366.
Castro LM, Gironás J, Fernández B. 2014. Spatial estimation of daily precipitation in regions with complex relief and scarce data using terrain orientation. J. Hydrol. 517: 481–492.
Chen J, Brissette FP, Chaumont D, Braun M. 2013. Finding appropriate bias correction methods in downscaling precipitation for hydrologic impact studies over North America, Water Resour. Res. 49: 4187–4205.
Chen TC, Tsay JD, Yen MC, Matsumoto J. 2012a. Interannual variation of the late fall rainfall in central Vietnam. J. Climate 25: 392–413.
Chen TC, Yen MC, Tsay JD, Alpert J, Nguyen TTT. 2012b. Forecast advisory for the late fall heavy rainfall/flood event in Central Vietnam developed from diagnostic analysis. Wea. Forecasting 27: 1155–1177.
Chen TC, Matsumoto J, Alpert J. 2015a. Development and formation mechanism of the Southeast Asian winter heavy rainfall events around the South China Sea. Part I:
Formation and propagation of cold surge vortex. J. Climate 28: 1417–1443.
Chen TC, Matsumoto J, Alpert J. 2015b. Development and formation mechanism of the Southeast Asian winter heavy rainfall events around the South China Sea. Part II:
Multiple interactions. J. Climate 28: 1444–1464.
46
Christensen JH, Boberg F, Christensen OB, Lucas‐Picher P. 2008. On the need for bias correction of regional climate change projections of temperature and precipitation. Geophys. Res. Lett. 35: L20709. doi:10.1029/2008GL035694.
Cruz FT, Narisma GT, Dado JB, Singhruck P, Tangang F, Linarka UA, Wati T, Juneng L, Phan-Van T, Ngo-Duc T, Santisirisomboon J, Gunawan D, Aldrian E. 2017. Sensitivity of temperature to physical parameterization schemes of RegCM4 over the CORDEX‐
Southeast Asia region. Int. J. Climatol. 37: 5139–5153.
Dado JM, Takahashi HG. 2017. Potential impact of sea surface temperature on rainfall over the western Philippines. Prog. Earth Planet. Sci. 4: 23. doi:10.1186/s40645-017-0137-6 Davis N, Bowden J, Semazzi F, Xie L. 2009. Customization of RegCM3 regional climate model for eastern Africa and a tropical Indian Ocean domain. J. Climate 22: 3595−3616.
Dee DP, Uppala SM, Simmons AJ, Berrisford P, Poli P, Kobayashi S, Andrae U, Balmaseda MA, Balsamo G, Bauer P, Bechtold P, Beljaars ACM, van de Berg L, Bidlot J, Bormann N, Delsol C, Dragani R, Fuentes M, Geer AJ, Haimberger L, Healy SB, Hersbach H, Hólm EV, Isaksen L, Kållberg P, Köhler M, Matricardi M, McNally AP, Monge-Sanz BM, Morcrette JJ, Park BK, Peubey C, Rosnay P, Tavolato C, Thépaut JN, Vitart F.
2011. The ERA-Interim reanalysis: Configuration and performance of the data assimilation system. Quart. J. Royal Meteor. Soc. 137: 553–597.
Dinku T, Ceccato P, Grover-Kopec E, Lemma M, Connor SJ, Ropelewski, CF. 2008.
Validation of satellite rainfall products over East Africa's complex topography. Int. J.
Remote Sensing 28: 1503–1526.
Dinku T, Ruiz F, Connor SJ, Ceccato P. 2010 Validation and intercomparison of satellite rainfall estimates over Colombia. J. Appl. Meteor. Climatol. 49: 1004–1014.
47
Dosio A, Paruolo P. 2011. Bias correction of the ENSEMBLES high‐resolution climate change projections for use by impact models: evaluation on the present climate. J.
Geophys. Res. 116: D16106. doi:10.1029/2011JD015934.
Emanuel KA, Zivkovic-Rothman M. 1999. Development and evaluation of a convection scheme for use in climate models. J. Atmos. Sci. 56: 1766–1782.
Endo N, Matsumoto J, Lwin T. 2009. Trends in precipitation extremes over Southeast Asia. SOLA 5: 168–171.
Gao YC, Liu M. 2013. Evaluation of high-resolution satellite precipitation products using rain gauge observations over the Tibetan Plateau. Hydrol. Earth Syst. Sci. 17: 837–849.
Giorgi F, Shields C. 1999. Tests of precipitation parameterizations available in latest version of NCAR regional climate model (RegCM) over continental United States. J. Geophys.
Res. 104: 6353–6375.
Giorgi F, Coppola E, Solmon F, Mariotti L, Sylla MB, Bi X, Elguindi N, Diro GT, Nair V, Giuliani G, Turuncoglu UU, Cozzini S, Güttler I, O’Brien TA, Tawfik AB, Shalaby A, Zakey AS, Steiner AL, Stordal F, Sloan LC, Brankovic C. 2012. RegCM4: Model description and preliminary tests over multiple CORDEX domains. Clim. Res. 52: 7–29.
Granato GE. 2006. Kendall–Theil Robust Line (KTRLine, version 1.0). Techniques and Methods of the US Geological Survey, 31 pp. Available online at:
https://pubs.usgs.gov/tm/2006/tm4a7/ (last accessed: 2 June 2018).
Gudmundsson L, Bremnes JB, Haugen JE, Engen-Skaugen T. 2012. Downscaling RCM precipitation to the station scale using statistical transformations – A comparison of methods. Hydrol. Earth System Sci. 16: 3383–3390.
Ho TMH, Phan VT, Le NQ, Nguyen QT. 2011. Detection of extreme climatic events from observed data and projection with RegCM3 over Vietnam. Clim. Res. 49: 87–100.
48
Hobouchian MP, Salio P, Skabar YG, Vila D, Garreaud R. 2017. Assessment of satellite precipitation estimates over the slopes of the subtropical Andes. Atmos. Res. 190: 43–
54.
Huffman GJ, Bolvin DT. 2013. TRMM and other data precipitation data set documentation. NASA, Greenbelt, USA, 28 pp. Available online at:
ftp://precip.gsfc.nasa.gov/pub/trmmdocs/3B42_3B43_doc.pdf (last accessed: 2 June 2018).
IPCC. 2013. The Physical Science Basis. Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change (eds: Stocker, TF, Qin D, Plattner GK, Tignor M, Allen SK, Boschung J, Nauels A, Xia Y, Bex V, Midgley PM). Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA, 1535 pp.
Jamandre CA, Narisma GT. 2013. Spatio-temporal validation of satellite-based rainfall estimates in the Philippines. Atmos. Res. 122: 599–608.
Joyce RJ, Janowiak JE, Arkin PA, Xie P. 2004. CMORPH: A method that produces global precipitation estimates from passive microwave and infrared data at high spatial and temporal resolution. J. Hydrometeor. 5: 487–503.
Juneng L, Tangang F, Chung JX, Ngai ST, Tay TW, Narisma G, Cruz F, Phan-Van T, Ngo-Duc T, Santisirisomboon J, Singhruck P, Gunawan D, Aldrian E. 2016. Sensitivity of Southeast Asia rainfall simulations to cumulus and air-sea flux parameterizations in RegCM4. Clim. Res. 69: 59–77.
Katzfey J, Nguyen K, McGregor J, Hoffmann P, Ramasamy S, Nguyen VH, Mai VK, Nguyen VT, Truong BK, Vu VT, Nguyen HT, Tran T, Doan HP, Nguyen TB, Phan-Van T, Nguyen-Quang T, Ngo-Duc T, Trinh-Tuan L. 2016. High-resolution simulations for
49
Vietnam-methodology and evaluation of current climate. Asia-Pacific J. Atmos. Sci. 52:
91–106.
Kendall MG. 1975. Rank Correlation Methods, 4th ed. Charles Griffin, London, 210 pp.
Kidd C. 2001. Satellite rainfall climatology: A review. Int. J. Climatol. 21, 1041–1066.
Kobayashi C, Endo H, Ota Y, Kobayashi S, Onoda H, Harada Y, Onogi K, Kamahori H.
2014. Preliminary results of the JRA-55C, an atmospheric reanalysis assimilating conventional observations only. SOLA 10: 78–82.
Kobayashi S, Ota Y, Harada Y, Ebita A, Moriya M, Onoda H, Onogi K, Kamahori H, Kobayashi C, Endo H, Miyaoka K, Takahashi K. 2015. The JRA-55 reanalysis: General specifications and basic characteristics. J. Meteor. Soc. Japan 93: 5–48.
Kubota T, Ushio T, Shige S, Kida S, Kachi M, Okamoto KI. 2009. Verification of high-resolution satellite-based rainfall estimates around Japan using a gauge-calibrated ground-radar dataset. J. Meteor. Soc. Japan 87A: 203–222. doi:10.2151/jmsj.87A.203.
Kuriyama Y, Banno M, Suzuki T. 2012. Linkages among interannual variations of shoreline, wave and climate at Hasaki, Japan. Geophys. Res. Lett. 39: L06604.
doi:10.1029/2011GL050704
Leander R, Buishand TA. 2007. Resampling of regional climate model output for the simulation of extreme river flows. J. Hydrol. 332: 487–496.
Lee HT. 2014. Climate algorithm theoretical basis document (C-ATBD): Outgoing longwave radiation (OLR)—Daily. NOAA’s Climate Data Record (CDR) Program. Technical Report CDRP-ATBD-0526, 46 pp. Available online at:
https://www.esrl.noaa.gov/psd/data/ (last accessed: 31 Jan 2019).
50
Li T, Zhang L, Murakami H. 2015. Strengthening of the Walker circulation under global warming in an aqua-planet general circulation model simulation. Adv. Atmos. Sci. 32:
1473–1480.
Manomaiphiboon K, Octaviani M, Torsri K, Towprayoon S. 2013. Projected changes in means and extremes of temperature and precipitation over Thailand under three future emissions scenarios. Clim. Res. 58: 97–115.
Mantas VM, Liu Z, Caro C, Pereira AJSC. 2015. Validation of TRMM multi-satellite precipitation analysis (TMPA) products in the Peruvian Andes. Atmos. Res. 163: 132–
145.
Maraun D. 2013. Bias correction, quantile mapping, and downscaling: Revisiting the inflation issue. J. Climate 26: 2137–2143.
Matsumoto J. 1997. Seasonal transition of summer rainy season over Indochina and adjacent monsoon region. Adv. Atmos. Sci. 14: 231–245.
Matsumoto J, Wang B, Wu G, Li J, Wu P, Hattori M, Mori S, Yamanaka M, Ogino S, Hamada J-I, Syamsudin F, Koike T, Tamagawa K, Ikoma E, Kinutani H, Kamahori H, Kamiguchi K, Harada Y. 2017. An overview of the Asian Monsoon Years 2007–2012 (AMY) and multi-scale interactions in the extreme rainfall events over the Indonesian maritime continent. In The Global Monsoon System: Research and Forecast, 3rd, eds.
Chang CP, Kuo HC, Lau NC, Johnson RH, Wang B, Wheeler M. 365–385, World Scientific.
MONRE. 2009. Climate Change, Sea Level Rise Scenarios for Vietnam. Ministry of Natural Resources and Environment Report, 33 pp.
MONRE. 2012. Climate Change, Sea Level Rise Scenarios for Vietnam. Ministry of Natural Resources and Environment Report, 96 pp.
51
Nakicenovic N, Alcamo J, Grubler A, Riahi K, Roehrl RA, Rogner HH, Victor N. 2000.
IPCC Special Report on Emissions Scenarios. Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA, 599 pp.
Ngai ST, Tangang F, Juneng L. 2017. Bias correction of global and regional simulated daily precipitation and surface mean temperature over Southeast Asia using quantile mapping method. Global and Planetary Change 149: 79–90.
Ngo-Duc T, Matsumoto J, Kamimera H, Bui HH. 2013. Monthly adjustment of Global Satellite Mapping of Precipitation (GSMaP) data over the VuGia–ThuBon River Basin in Central Vietnam using an artificial neural network. Hydrol. Res. Lett. 7: 85–90.
Ngo-Duc T, Kieu C, Thatcher M, Nguyen-Le D, Phan-Van T. 2014. Climate projections for Vietnam based on regional climate models. Clim. Res. 60: 199–213.
Ngo-Duc T, Tangang F, Santisirisomboon J, Cruz F, Trinh-Tuan L, Nguyen-Xuan T, Phan-Van T, Juneng L, Narisma G, Singhruck P, Gunawan D, Aldrian E. 2017. Performance evaluation of RegCM4 in simulating extreme rainfall and temperature indices over the CORDEX-Southeast Asia region. Int. J. Climatol. 37: 1634–1647.
Ngo-Thanh H, Ngo-Duc T, Nguyen-Hong H, Baker P, Phan-Van T. 2018. A distinction between summer rainy season and summer monsoon season over the Central Highlands of Vietnam. Theor. Appl. Climatol. 132: 1237–1246.
Nguyen DN, Nguyen TH. 2004. Vietnamese Climate and Climatic Resources. Hanoi Agriculture Press, Hanoi, 60 pp. (in Vietnamese).
Nguyen DQ, Renwick J, McGregor J. 2014. Variations of surface temperature and rainfall in Vietnam from 1971 to 2010. Int. J. Climatol. 34: 249–264.
Nguyen-Le D, Matsumoto J, Ngo-Duc T, 2015. Onset of the rainy seasons in the eastern Indochina Peninsula. J. Climate 28: 5645–5666.
52
Nguyen‐Le D, Matsumoto J. 2016. Delayed withdrawal of the autumn rainy season over central Vietnam in recent decades. Int. J. Climatol. 36: 3002–3019.
Nguyen-Thi HA, Matsumoto J, Ngo-Duc T, Endo N. 2012a. A climatological study of tropical cyclone rainfall in Vietnam. SOLA 8: 41–44.
Nguyen-Thi HA, Matsumoto J, Ngo-Duc T, Endo N. 2012b. Long-term trends in tropical cyclone rainfall in Vietnam. J. Agrofor. Environ. 6: 89–92.
Nguyen-Xuan T, Ngo-Duc T, Kamimera H, Trinh-Tuan L, Matsumoto J, Inoue T, Phan-Van T. 2016. The Vietnam Gridded Precipitation (VnGP) Dataset: Construction and Validation. SOLA 12: 291–296.
Phan VT, Ngo-Duc T, Ho TMH. 2009. Seasonal and interannual variations of surface climate elements over Vietnam. Clim. Res. 40: 49–60.
Piani C, Haerter JO, Coppola E. 2010. Statistical bias correction for daily precipitation in regional climate models over Europe. Theor. Appl. Climatol. 99: 187–192.
Raghavan SV, Vu MT, Liong SY. 2017. Ensemble climate projections of mean and extreme rainfall over Vietnam. Global and Planetary Change 148: 96–104.
Rayner NA, Parker DE, Horton EB, Folland CK, Alexander LV, Rowell DP, Ken EC, Kaplan A. 2003. Global analyses of sea surface temperature, sea ice, and night marine air temperature since the late nineteenth century. J. Geophys. Res. Atmos. 108: D14.
doi:10.1029/2002JD002670.
Reiter P, Gutjahr O, Schefczyk L, Heinemann G, Casper M. 2016. Bias correction of ENSEMBLES precipitation data with focus on the effect of the length of the calibration period. Meteorologische Zeitschrift, 25: 85–96. doi:10.1127/metz/2015/0714.
53
Schneider U, Becker A, Finger P, Meyer-Christoffer A, Ziese M, Rudolf B. 2014. GPCC's new land surface precipitation climatology based on quality-controlled in situ data and its role in quantifying the global water cycle. Theor. Appl. Climatol. 115: 15–40.
Schneider U, Becker A, Finger P, Meyer-Christoffer A, Rudolf B. 2015. GPCC full data reanalysis version 7.0 at 0.5°: Monthly land-surface precipitation from rain-gauges built on GTS-based and historic data. doi:10.5676/DWD_GPCC/FD_M_V7_050. Available online at: https://rda.ucar.edu/datasets/ds496.0/ (last accessed: 31 March 2018).
Sen PK. 1968. Estimates of the regression coefficient based on Kendall's tau. J. Amer. Stat.
Assoc. 63: 1379–1389.
Shen Y, Xiong A, Wang Y, Xie P. 2010. Performance of high resolution satellite precipitation products over China. J. Geophys. Res. Atmos. 115: D02114.
doi:10.1029/2009JD012097.
Shige S, Kida S, Ashiwake H, Kubota T, Aonashi K. 2013. Improvement of TMI rain retrievals in mountainous areas. J. Appl. Meteorol. Climatol. 52: 242–254.
Takahashi HG. 2013. Orographic low-level clouds of Southeast Asia during the cold surges of the winter monsoon. Atmos. Res. 131: 22–33.
Tang L, Tian Y, Yan F, Habib E. 2015. An improved procedure for the validation of satellite-based precipitation estimates. Atmos. Res. 163: 61–73.
Tangang F, Supari S, Chung JX, Cruz F, Salimun E, Ngai ST, Juneng L, Santisirisomboon J, Ngo-Duc T, Phan-Van T, Narisma G, Singhruck P, Gunawan D, Aldrian E, Sopaheluwakan A, Nikulin G,Yang H, Remedio ARC, Sein D, Hein-Griggs D.
2018. Future changes in annual precipitation extremes over Southeast Asia under global warming of 2°C. APN Science Bulletin 8: 3–8. doi:10.30852/sb.2018.436.
54
Tapiador FJ, Turk FJ, Petersen W, Hou AY, García-Ortega E, Machado LA, Angelis CF, Salio P, Kidd C, Huffman GJ and De Castro M. 2012. Global precipitation measurement: Methods, datasets and applications. Atmos. Res. 104: 70–97.
Taylor KE. 2001. Summarizing multiple aspects of model performance in a single diagram. J. Geophys. Res. 106: 7183–7192.
Themeßl MJ, Gobiet A, Heinrich G. 2012. Empirical-statistical downscaling and error correction of regional climate models and its impact on the climate change signal. Climatic Change 112: 449–468.
Thiemig V, Rojas R, Zambrano-Bigiarini M, Levizzani V, De Roo A. 2012. Validation of satellite-based precipitation products over sparsely gauged African river basins. J.
Hydrometeor. 13: 1760–1783.
Toté C, Patricio D, Boogaard H, van der Wijngaart R, Tarnavsky E, Funk C. 2015.
Evaluation of satellite rainfall estimates for drought and flood monitoring in Mozambique. Remote Sensing 7: 1758–1776.
Trenberth KE, Dai A, Rasmussen RM, Parsons DB. 2003. The changing character of precipitation. Bull. Amer. Meteor. Soc. 84: 1205–1217.
Trinh-Tuan L, Konduru TR, Inoue T, Ngo-Duc T, Matsumoto J. 2019a. Autumn rainfall increasing trend in South Central Vietnam and its association with changes in Vietnam East Sea surface temperature. Geogr. Rep. Tokyo Metro. Univ. 54: 11–22.
Trinh-Tuan L, Matsumoto J, Ngo-Duc T, Nodzu IM, Inoue T, Nguyen P. 2019b. Evaluation of satellite precipitation products over Central Vietnam. Prog. Earth and Planet. Sci.
(under revision).
Trinh-Tuan L, Matsumoto J, Tangang FT, Juneng L, Cruz F, Narisma G, Santisirisomboon J, Phan-Van T, Gunawan D, Aldrian E, Ngo-Duc, T. 2019c. Application of quantile
55
mapping bias correction for mid-future precipitation projections over Vietnam. SOLA 15: 1–6.
Turkington T, Timbal B, Rahmat R. 2018. The impact of global warming on sea surface temperature based El Niño–Southern Oscillation monitoring indices. Int. J.
Climatol. 39: 1092–1103.
Ushio T, Sasashige K, Kubota T, Shige S, Okamoto KI, Aonashi K, Inoue T, Takahashi N, Iguchi T, Kachi M, Oki R. 2009. A Kalman filter approach to the Global Satellite Mapping of Precipitation (GSMaP) from combined passive microwave and infrared radiometric data. J. Meteor. Soc. Japan 87A: 137–151. doi:10.2151/jmsj.87A.137.
Van der Linden P, Mitchell JFB. 2009. ENSEMBLES: Climate change and its impacts:
Summary of research and results from the ENSEMBLES project. Met Office Hadley Centre Tech. Rep., 160 pp. (http://ensemblesrt3.dmi.dk).
Van Khiem M, Redmond G, McSweeney C, Thuc T. 2014. Evaluation of dynamically downscaled ensemble climate simulations for Vietnam. Int. J. Climatol. 34: 2450–2463.
Venema VK, Mestre O, Aguilar E, Auer I, Guijarro JA, Domonkos P, Vertacnik G, Szentimrey T, Stepanek P, Zahradnicek P, Viarre J, Muller-Westermeier G, Lakatos M, Williams CN, Menne MJ, Lindau R, Rasol D, Rustemeier E, Kolokythas K, Marinova T, Andresen L, Acquaotta F, Fratianni S, Cheval S, Klancar M, Brunetti M, Gruber C, Duran MP, Likso T, Esteban P, Brandsma T. 2013. Benchmarking homogenization algorithms for monthly data. AIP Conference Proceedings 1552: 1060–1065.
Vernimmen RRE, Hooijer A, Aldrian E, van Dijk AIJM. 2012. Evaluation and bias correction of satellite rainfall data for drought monitoring in Indonesia. Hydrol. Earth Syst. Sci. 16: 133–146.