Review of Downscaling Methods in Climate Change and Their Role in Hydrological Studies
Recent perceived climate variability raises concerns
with unprecedented hydrological phenomena and extremes.
Distribution and circulation of the waters of the Earth become
increasingly difficult to determine because of additional uncertainty
related to anthropogenic emissions. The world wide observed
changes in the large-scale hydrological cycle have been related to an
increase in the observed temperature over several decades. Although
the effect of change in climate on hydrology provides a general
picture of possible hydrological global change, new tools and
frameworks for modelling hydrological series with nonstationary
characteristics at finer scales, are required for assessing climate
change impacts. Of the downscaling techniques, dynamic
downscaling is usually based on the use of Regional Climate Models
(RCMs), which generate finer resolution output based on atmospheric
physics over a region using General Circulation Model (GCM) fields
as boundary conditions. However, RCMs are not expected to capture
the observed spatial precipitation extremes at a fine cell scale or at a
basin scale. Statistical downscaling derives a statistical or empirical
relationship between the variables simulated by the GCMs, called
predictors, and station-scale hydrologic variables, called predictands.
The main focus of the paper is on the need for using statistical
downscaling techniques for projection of local hydrometeorological
variables under climate change scenarios. The projections can be then
served as a means of input source to various hydrologic models to
obtain streamflow, evapotranspiration, soil moisture and other
hydrological variables of interest.
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edition. London, Routledge, 2000.
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Phil. Trans. R. Lond. A., 2002, 360, 1409-1431.
[7] Huntington, T. G., Evidence for intensification of the global water cycle:
Review and synthesis. J. Hydrol., 2006, 319, 83-95.
[8] Zhang, X., Zwiers, F. W., Hegerl, G. C., Lambert, F. H., Gillett, N. P.,
Solomon, S., Stott, P. A. and Nozawa, T., Detection of human influence
on twentieth-century precipitation trends. Nature, 2007, 448, 461-465.
[9] Milly, P. C. D., Dunne, K. A. and Vecchia, A. V., Global pattern of
trends in streamflow and water availability in a changing climate.
Nature, 2005, 438, 347-350.
[10] Wilby, R. L., Beven, K. J. and Reynard, N. S., Climate change and
fluvial flood risk in the UK: more of the same? Hydrol. Process., 2008,
22, 2511-2523.
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the Sierra Nevada, California under two emissions scenarios. Clim.
Change, 2007, 82, 309-325.
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impacts on financial risk in hydropower projects. IEEE Trans. on Power
Sys., 2003, 18, 1324-1330.
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The effects of climate change on the hydrology and water resources of
the Colorado river basin. Clim. Change, 2004, 62, 337-363.
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Trans. of the Royal Soc., 2006, 364, 2135-2145.
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lakes basin Ecosystem Studies. Limnol. Oceanogr., 1996, 41, 903-911.
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continental runoff fluctuations since the beginning of this century. J.
Hydrol., 1987, 94, 289-311.
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conterminous United States, 1939- 1988. Bull. Am. Meteorol. Soc., 1993,
74, 1873-1891.
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and Peterson, B. J., Assessment of contemporary Arctic river runoff
based on observational discharge records. J. Geophys. Res., 2001, 106,
3321-3334.
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Precipitation, and Temperature at the End of the Twentieth Century. J.
Clim., 2003, 16, 3905-3916.
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Water Resour., 2005, 28, 1310-1315.
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and streamflow. Water Resour. Res., 2012, 48, W10520,
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H. S., South Asian summer monsoon precipitation variability: Coupled
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and Xavier, P. K., Increasing trend of extreme rain events over India in a
warming environment. Science, 2006, 314, 1442–1445.
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trends of extreme rainfall events over India using 104 years of gridded
daily rainfall data. Geophys. Res. Lett., 2008, 35, L18707,
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Drought and Wet Events over India in a Future Climate Using a Nested
Bias-Correction Approach. J. Hydrol. Engg., 2013, 18, 760-772.
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Change Impact Assessment of water resources of India. Curr. Sci., 2011,
101, 356-371.
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[1] Bates, B. C., Kundzewicz, Z. W., Wu, S. and Palutikof, J. P., Climate
Change and Water. Technical Paper of the Intergovernmental Panel on
Climate Change, 2008, IPCC Secretariat, Geneva, pp 210.
[2] Jolley, T. J. and Wheater, H. S., A large-scale grid-based hydrological
model of the Severn and Thames catchments. Water Environ. J., 1996,
10, 253-262.
[3] Solomon, S., Qin, D., Manning, M., Chen, Z., Marquis, M., Averyt, K.
B., Tignor, M. and Miller, H. L., IPCC, 2007: Climate Change 2007:
The Physical Science Basis. Contribution of Working Group I to the
Fourth Assessment Report of the Intergovernmental Panel on Climate
Change, 2007.
[4] Carter, T. R., Parry, M. L., Harasawa, H. and Nishioka, S., IPCC
technical guidelines for assessing climate change impacts and adaptions.
IPCC special report to Working Group II of IPCC,1994, University
College, London. 1994, pp.59.
[5] Acreman, M. C., The hydrology of the UK: A study of change. 1st
edition. London, Routledge, 2000.
[6] Wheater, H. S., Progress in and prospects for fluvial flood modelling.
Phil. Trans. R. Lond. A., 2002, 360, 1409-1431.
[7] Huntington, T. G., Evidence for intensification of the global water cycle:
Review and synthesis. J. Hydrol., 2006, 319, 83-95.
[8] Zhang, X., Zwiers, F. W., Hegerl, G. C., Lambert, F. H., Gillett, N. P.,
Solomon, S., Stott, P. A. and Nozawa, T., Detection of human influence
on twentieth-century precipitation trends. Nature, 2007, 448, 461-465.
[9] Milly, P. C. D., Dunne, K. A. and Vecchia, A. V., Global pattern of
trends in streamflow and water availability in a changing climate.
Nature, 2005, 438, 347-350.
[10] Wilby, R. L., Beven, K. J. and Reynard, N. S., Climate change and
fluvial flood risk in the UK: more of the same? Hydrol. Process., 2008,
22, 2511-2523.
[11] Maurer, E. P., Uncertainty in hydrologic impacts of climate change in
the Sierra Nevada, California under two emissions scenarios. Clim.
Change, 2007, 82, 309-325.
[12] Harrison, G. P., Whittington, W. and Wallace, R. A., Climate change
impacts on financial risk in hydropower projects. IEEE Trans. on Power
Sys., 2003, 18, 1324-1330.
[13] Christensen, N., Wood, A., Voisin, N., Lettenmaier, D. and Palmer, R.,
The effects of climate change on the hydrology and water resources of
the Colorado river basin. Clim. Change, 2004, 62, 337-363.
[14] Wheater, H. S., Flood hazard and Management a UK perspective. Phil.
Trans. of the Royal Soc., 2006, 364, 2135-2145.
[15] Mortsch, L., D. and Quinn, F. H., Climate change scenarios for great
lakes basin Ecosystem Studies. Limnol. Oceanogr., 1996, 41, 903-911.
[16] Probst, J. L. and Tardy, Y., Long range streamflow and world
continental runoff fluctuations since the beginning of this century. J.
Hydrol., 1987, 94, 289-311.
[17] Guetter, A. K. and Georgakakos, K. P., River outflow of the
conterminous United States, 1939- 1988. Bull. Am. Meteorol. Soc., 1993,
74, 1873-1891.
[18] Lammers, R. B., Shiklomanov, A. I., Vorosmarty, C. J., Fekete, B. M.
and Peterson, B. J., Assessment of contemporary Arctic river runoff
based on observational discharge records. J. Geophys. Res., 2001, 106,
3321-3334.
[19] Mauget, S. A., Multidecadal Regime Shifts in US Streamflow,
Precipitation, and Temperature at the End of the Twentieth Century. J.
Clim., 2003, 16, 3905-3916.
[20] Labat, D., Godderis, Y., Probst, J. L. and Guyot, J. L., Evidence for
global runoff increase related to climate warming. Adv. Water Resour.,
2004, 27, 631-642.
[21] Legates, D. R., Lins, H. F. and McCabe, G. J., Comments on Evidence
for global runoff increase related to climate warming by Labat et al. Adv.
Water Resour., 2005, 28, 1310-1315.
[22] Lettenmaier, D. and Gan, T., Hydrologic Sensitivities of the
Sacramento-San Joaquin River Basin, California, to Global Warming.
Water Resour. Res., 1990, 26, 69-86.
[23] McCabe Jr, G. J. and Wolock, D. M., Climate change and the detention
of trends in annual runoff. Clim. Res., 1997, 8, 129-134.
[24] IPCC (Intergovernmental Panel on Climate Change), Climate models
and their evaluation Climate Change: The Physical Science Basis.
Contribution of Working Group I to the Fourth Assessment Report of
the Intergovernmental Panel of Climate Change (ed. Solomon, S., et al.),
Cambridge University Press, 2007.
[25] Mondal, A., and Mujumdar, P. P., On the basin-scale detection and
attribution of human-induced climate change in monsoon precipitation
and streamflow. Water Resour. Res., 2012, 48, W10520,
doi:10.1029/2011WR011468.
[26] Steinschneider, S., Polebitski, A., Brown, C. and Letcher, B. H., Toward
a statistical framework to quantify the uncertainties of hydrologic
response under climate change. Water Resour. Res., 2012, 48, W11525,
doi:10.1029/2011WR011318.
[27] Peterson, T. C. and Vose, R. S., An overview of the Global Historical
Climatology Network temperature database. Bull. Am. Meteorol. Soc.,
1997, 78, 2837-2849.
[28] Mitchell, T. D. and Jones, P. D., An improved method of constructing a
database of monthly climate observations and associated high-resolution
grids. Int. J. Climatol., 2005, 25, 693-712.
[29] Kripalani, R. H., Oh J. H., Kulkarni, A., Sabade, S. S., and Chaudhari,
H. S., South Asian summer monsoon precipitation variability: Coupled
climate model simulations and projections under IPCC AR4. Theor.
Appl. Climatol., 2007, 90, 133–159.
[30] Goswami, B. N., Venugopal, V., Sengupta, D., Madhusoodanan, M. S.
and Xavier, P. K., Increasing trend of extreme rain events over India in a
warming environment. Science, 2006, 314, 1442–1445.
[31] Rajeevan, M., Bhate, J. and Jaiswal A. K., Analysis of variability and
trends of extreme rainfall events over India using 104 years of gridded
daily rainfall data. Geophys. Res. Lett., 2008, 35, L18707,
doi:10.1029/2008GL035143.
[32] Ojha, R., Kumar, D. N., Sharma, A., and Mehrotra, R., Assessing Severe
Drought and Wet Events over India in a Future Climate Using a Nested
Bias-Correction Approach. J. Hydrol. Engg., 2013, 18, 760-772.
[33] Gosain, A. K., Sandhya, R., Srinivasan, R. and Gopal R., N., Climate
Change Impact Assessment of water resources of India. Curr. Sci., 2011,
101, 356-371.
[34] Hughes, J., Guttorpi, P. and Charles, S., A non-homogeneous hidden
Markov model for precipitation occurrence. Appl. Stat., 1999, 48, 15-30.
[35] Prudhomme, C., Reynard, N. and Crooks, S., Downscaling of global
climate models for flood frequency analysis: where are we now? Hydrol.
Process., 2002, 16, 1137-1150.
[36] Brands, S., Herrera, S., Fernández, J. and Gutiérrez, J. M., How well do
CMIP5 Earth System Models simulate present climate conditions in
Europe and Africa? Clim. Dynam., 2013, 41, 803-817.
[37] Taylor, K. E., Stouffer, R. J. and Meehl, G. A., An overview of CMIP5
and the experiment design. Bull. Am. Meteorol. Soc., 2012, 93, 485–498.
[38] Ghosh, S., and Mujumdar, P. P., Climate change impact assessment:
Uncertainty modeling with imprecise probability. J. Geophys. Res.,
2009, 114, D18113, doi:10.1029/2008JD011648.
[39] Moss, R. H., Edmonds, J. A., Hibbard, K. A., Manning, M. R., Rose, S.
K., van Vuuren, D. P., Carter, T. R., Emori, S., Kainuma, M., Kram, T.,
Meehl, G. A., Mitchell, J. F. B., Nakicenovic, N., Riahi, K., Smith, S. J.,
Stouffer, R. J., Thomson, A. M., Weyant, J. P. and Wilbanks, T. J., The
next generation of scenarios for climate change research and assessment.
Nature, 2010, 463, 747–756.
[40] Jones, R. G., Murphy, J. M., Noguer, M. and Keen, A. B., Simulation of
climate change over Europe using a nested regional-climate model. II:
Comparison of driving and regional model responses to a doubling of
carbon dioxide. Q. J. R. Meteorol. Soc., 1997, 123, 265-292.
[41] Hewitson, B.C. and Crane R.G., Climate downscaling: techniques and
application. Clim. Res., 1996, 7, 85-95.
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@article{"International Journal of Earth, Energy and Environmental Sciences:68117", author = "Nishi Bhuvandas and P. V. Timbadiya and P. L. Patel and P. D. Porey", title = "Review of Downscaling Methods in Climate Change and Their Role in Hydrological Studies", abstract = "Recent perceived climate variability raises concerns
with unprecedented hydrological phenomena and extremes.
Distribution and circulation of the waters of the Earth become
increasingly difficult to determine because of additional uncertainty
related to anthropogenic emissions. The world wide observed
changes in the large-scale hydrological cycle have been related to an
increase in the observed temperature over several decades. Although
the effect of change in climate on hydrology provides a general
picture of possible hydrological global change, new tools and
frameworks for modelling hydrological series with nonstationary
characteristics at finer scales, are required for assessing climate
change impacts. Of the downscaling techniques, dynamic
downscaling is usually based on the use of Regional Climate Models
(RCMs), which generate finer resolution output based on atmospheric
physics over a region using General Circulation Model (GCM) fields
as boundary conditions. However, RCMs are not expected to capture
the observed spatial precipitation extremes at a fine cell scale or at a
basin scale. Statistical downscaling derives a statistical or empirical
relationship between the variables simulated by the GCMs, called
predictors, and station-scale hydrologic variables, called predictands.
The main focus of the paper is on the need for using statistical
downscaling techniques for projection of local hydrometeorological
variables under climate change scenarios. The projections can be then
served as a means of input source to various hydrologic models to
obtain streamflow, evapotranspiration, soil moisture and other
hydrological variables of interest.
", keywords = "Climate Change, Downscaling, GCM, RCM.", volume = "8", number = "10", pages = "726-6", }
