Abstract
This study evaluates the National Aeronautics Space Administration (NASA) Earth Exchange Global Daily Downscaled Projections (NEX-GDDP) dataset that provides statistically downscaled CMIP5 historical and future climate projections (precipitation and temperature), at high spatial (25 km) and temporal (daily) resolutions. The study is performed over Southeast Asia for the historical period 1976–2005 and compared against gridded observations on daily scales. Future climate change is assessed over the future time slices, 2020–2050 and 2070–2099, under two Representative Concentration Pathways (RCP) scenarios 4.5 and 8.5 with respect to 1976–2005. The future climate projections indicate that surface temperatures over Southeast Asia are likely to increase by more than 3.5 °C by the end of the century. As to precipitation, both the mean and extreme rainfall are likely to increase but the biases in the historical simulations could contribute to larger uncertainties in the estimates of rainfall projections. Findings of the study indicate that NEX-GDDP are in good agreement with observations over the historical period only on monthly scales and that they do not capture the observed statistics on daily scales which suggests that these data need a deeper scrutiny on daily scales, especially when used for impacts studies.
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References
Adam JC, Lettenmaier DP (2003) Adjustment of global gridded precipitation for systematic bias. J Geophys Res 108:1–14
Bao Y, Wen X (2017) Projection of China’s near- and long-term climate in a new high-resolution daily downscaled dataset NEX-GDDP. J Meteorol Res. https://doi.org/10.1007/s13351-017-6106-6
Bosshard T, Carambia M, Goergen K, Kotlarski S, Krahe P, Zappa M, Schar C (2013) Quantifying uncertainty sources in an ensemble of hydrological climate-impact projections. Water Resour Res 49:1523–1536. https://doi.org/10.1029/2011WR011533
Chotamonsak C, Salathé EP Jr, Kreasuwan J, Chantara S, Siriwitayakorn K (2011) Projected climate change over Southeast Asia simulated using a WRF regional climate model. Atmos Sci Let 12:213–219
Christensen JH, Carter TR, Rummukainen M, Amanatidis G (2006) Evaluating the performance and utility of regional climate models: the PRUDENCE project. Clim Chang 81(1):1–6
Dufresne et al (2013) Climate change projections using the IPSL-CM5 Earth System Model: from CMIP3 to CMIP5. Clim Dyn 40:2123–2165
Giorgetta et al (2013) Climate and carbon cycle changes from 1850 to 2100 in MPI-ESM simulations for the Coupled Model Intercomparison Project Phase 5. J Adv Model Earth Syst 5:572–597
Giorgi F (1990) Simulations of regional climate using a limited area model nested in a general circulation model. J Clim 3(9):941–963
Harris I, Jones PD, Osborn TJ, Lister DH (2014) Updated high-resolution grids of monthly climatic observations - the CRU TS310 dataset. Int. J Clim 25(3):623–642
Hewitson BC, Crane RG (2006) Consensus between GCM climate change projections with empirical downscaling: precipitation downscaling over South Africa. Int J Climatol 26(10):1315–1337
Hirsch RM, Slack JR, Smith RA (1982) Techniques of trend analysis for monthly water quality data. Water Resour Res 18(1):107–121. https://doi.org/10.1029/WR018i001p00107
Ho TMH, Phan VT, Le NQ, Nguyen QT (2011) Extreme climatic events over Vietnam from observational data and RegCM3 projections. Clim Res 49:87–100
Hur J, Raghavan SV, Nguyen NS, Liong SY (2017) Are satellite products good proxies for gauge precipitation over Singapore? Theor Appl Climatol. https://doi.org/10.1007/s00704-017-2132-7
IPCC (2007) Climate Change 2007: The Physical Science Basis. In: Solomon S, Qin D, Manning M, Chen Z, Marquis M, Averyt KB, Tignor M, Miller HL (eds) Contribution of Working Group I to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge University Press, Cambridge
Jacob D, Petersen J, Eggert B et al (2014) EURO-CORDEX: new high-resolution climate change projections for European impact research. Reg Environ Change 14(2):563–578
Kendall MG (1975) Rank correlation methods, 4th edn. Charles Griffin, London
Mann HB (1945) Non-parametric tests against trend. Econometrica 13:245–259. https://doi.org/10.2307/1907187
Maraun D, Widmann M (2018) Statistical downscaling and bias correction for climate research. Cambridge University Press. https://doi.org/10.1017/9781107588783
Maurer EP, Adam JC, Wood AW (2009) Climate model based consensus on the hydrologic impacts of climate change to the Rio Lempa basin of Central America. Hydrol Earth Syst Sci 13:183–194
SEACAM (2014) A regional climate modelling experiment for Southeast Asia, technical report initiated by the Centre for Climate Research Singapore of the Meteorological Service Singapore (CCRS-MSS) in collaboration with the Met Office Hadley Centre (MOHC), UK
Sheffield J, Goteti G, Wood EF (2006) Development of a 50-year high-resolution global dataset of meteorological forcings for land surface modeling. J Clim 19:3088–3111
Shongwe ME, Lennard C, Liebmann B, Kalognomou E-A, Ntsangwane L, Pinto I (2015) An evaluation of CORDEX regional climate models in simulating precipitation over Southern Africa. Atmos Sci Lett 16(3):199–207
Siew JH, Tangang FT, Juneng L (2014) Evaluation of CMIP5 coupled atmosphere-ocean general circulation models and projections of the Southeast Asian winter monsoon in the 21st century. Int J Clim 34:287–2884
Taylor KE (2001) Summarizing multiple aspects of model performance in a single diagram. J Geophys Res: Atmos 106(D7):7183–7192
Thrasher B, Maurer EP, McKellar C, Duffy PB (2012) Technical note: bias correcting climate model simulated daily temperature extremes with quantile mapping. Hydrol Earth Syst Sci 16(9):3309–3314
Trzaska S, Schnarr E (2014) A review for downscaling methods for climate change projections. USAID report by the Center for International Earth Science Information Network (CIESIN), 45 pp
Voldorie et al (2013) The CNRM-CM5.1 global climate model: description and basic evaluation. Clim Dyn 40:2091–2121
Watanabe et al (2010) Improved climate simulation by MIROC5: mean states, variability, and climate sensitivity. J Clim 23:6312–6335
Yukimoto et al (2012) A new global climate model of the Meteorological Research Institute: MRI-CGCM3–model description and basic performance. J Meteorol Soc Jpn 90A:23–64
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Raghavan, S.V., Hur, J. & Liong, SY. Evaluations of NASA NEX-GDDP data over Southeast Asia: present and future climates. Climatic Change 148, 503–518 (2018). https://doi.org/10.1007/s10584-018-2213-3
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DOI: https://doi.org/10.1007/s10584-018-2213-3