Modeling uncertainty of statistical downscaling methods in quantifying the climate change impacts on late spring frost risk over Iran
Late spring frosts (LSFs) play a key role in the evaluation of climate suitability for agricultural and horticultural crop production and are considered to be one of the main components of food security. It is expected that future climate change will affect the occurrence of LSFs and its damages. In order to quantify these changes, this study aims to investigate the performance of two downscaling methods (SDSM and ANN), using two GCMs (general circulation model) data of HadCM3 (A2 and B2 scenarios) and CGCM3 (A1B and A2 scenarios). To this end, daily minimum temperature data (Tmin i ) of 50 meteorological stations located across the entire country were gathered and quality controlled for the period 1961 through 2010. The trend analyses of annual minimum temperature series showed a significant increasing trend of 0.3 °C per decade (α = 0.01). Both downscaling models were calibrated for the 40 years of 1961–2000 and the evaluation is conducted for the 10 years of 2001–2010. The Wilcoxon rank-sum and the Levene and bootstrapping tests were used for comparing and finding confidence intervals of averages and variances of downscaled daily minimum temperatures at each month. Results showed that, firstly, downscaling models’ performance in simulating averages is much better than variances. Secondly, SDSM simulates warmer summers and colder winters comparing ANN. Thirdly, the best and the worst results were achieved by ANN_CGCM3_A2 and ANN_HadCM3_B2, respectively. Finally, very low, moderate, high, and very high-risk zones for critical temperature of 0 °C and their areas at the historical period (1961–2010) and three future periods (2011–2040, 2041–2070, 2071–2100) were quantified and compared. Based on the results, SDSM simulated changes in the high and low frost risk zones more than the ANN model. However, since both Very High and No Frost risk zones will drastically change, SDSM results do not always indicate an increasing risk of frost damage. Moreover, the average of the area covered by “low-risk” zone will increase from 1.00% in the current period to 4.43% at the end of the century, and area of “very high-risk” zone will decrease from 8.2 to 4.7% at the same condition.
KeywordClimate change Uncertainty Frost risk SDSM ANN Iran
This work has been supported by Iran National Science Foundation and executed at University of Tehran-College of Agricultural and Natural Resources (UTCAN).
- Conover WJ (1980) Practical Nonparametric statistics, 2nd edn. Wiley, New YorkGoogle Scholar
- Crimp S, Gobbet D, Thomas D, Bakar S, Nidumolu U, Hayman P, Hopwood G (2012) Understanding frost risk in a variable and changing climate. CSIRO, CanberraGoogle Scholar
- Farajzadeh M, Rahimi M, Kamali GA, Mavrommatis T (2010) Modelling apple tree bud burst time and frost risk in Iran. Meteorol Appl 17(1):45–52Google Scholar
- Giorgi F, Hewitson B, Christensen J, Fu C, Jones R, Hulme M, Mearns L, Von Storch H, Whetton P (2001) Regional climate information—evaluation and projections. In: ed Houghton JT et al Climate change 2001: the scientific basis. Cambridge Univesity Press, New York, pp 583–638Google Scholar
- Khalili A (2009) Agro meteorological zoning of Iran for insurance against drought, frost and heavy rainfall damages, vol 2, 7. Agricultural Insurance Fund, Tehran (in Persian) Google Scholar
- Khalili A (2014) Quantitative evaluation of spring frost risk to agricultural and horticultural crops in iran and modeling. J Agric Meteorol 2(1):17–31Google Scholar
- Khalili A, Darvish Sefat A, Baradaran-e-rade R, Bazrafshan JA (2004) Method for climatic classification on selianinov system in GIS media (a case study for north west of Iran). Biaban (Desert) 9(2):227–237 (in Persian)Google Scholar
- Lehmann EL (1975) Nonparametrics: statistical methods based on ranks. Holden and Day, San FranciscoGoogle Scholar
- Levene H (1960) Robust tests for equality of variances. Contrib Probab Stat 1:278–292Google Scholar
- Rahimi J, Khalili A, Bazrafshan J (2017a) Evaluation of different missing data reconstruction methods for daily minimum temperature in elevated stations of Iran: comparison with new proposed approach. Iran J Soil Water Res 48(2):231:239 (in Persian)Google Scholar
- Ustrnul Z, Wypych A, Winkler JA, Czekierda D (2014) Late spring freezes in Poland in relation to atmospheric circulation. Quaest Geogr 33(3):165–172Google Scholar
- Winkler JA, Andresen J, Bisanz J, Guentchev GS, Nugent J, Piromsopa K, Rothwell N, Zavalloni C, Clark J, Min HK, Pollyea A, Prawiranta H (2013) Michigan’s tart cherry industry: vulnerability to climate variability and change. In: Pryor SC (ed) climate change in the midwest: impacts, risks, vulnerability and adaptation. Indiana University Press, Bloomington, pp 104–116Google Scholar