Testing for increasing weather risk

Stochastic Environmental Research and Risk Assessment

Volumn 27, Issue 7, 2013, Pages 1565-1574

  Wang, W ^a   Bobojonov, I ^b   Hardle W K ^a   Odening, M ^a  

^a HUMBOLDT UNIVERSITY   (Germany)

^b LEIBNIZ INSTITUTE OF AGRICULTURAL DEVELOPMENT IN TRANSITION ECONOMIES IAMO   (Germany)

Author keywords

Agricultural risk; Change point test; Quantile regression; Weather extremes

Indexed keywords

CHANGE-POINTS; DIFFERENT CLIMATIC ZONES; GEOGRAPHICAL LOCATIONS; MANN-KENDALL TEST; QUANTILE REGRESSION; TREND DETECTION; TYPE OF RISKS; WEATHER EXTREMES;

AGRICULTURE; CLIMATE CHANGE; WEATHER MODIFICATION;

TESTING;

CLIMATE CHANGE; EXTREME EVENT; GEOGRAPHICAL REGION; REGRESSION ANALYSIS; RISK ASSESSMENT;

EID: 84883802883     PISSN: 14363240     EISSN: 14363259     Source Type: Journal    
DOI: 10.1007/s00477-013-0692-3     Document Type: Article

References (35)

1. Aguilar E, Auer I, Brunet M, Peterson TC, Wieringa J (2003) Guidelines on climate metadata and homogenization, WCDMP 53, WMO-TD 1186, World Meteorol Org Geneva, pp 55.
2. Alexander LV, Zhang X, Peterson TC, Caesar J, Gleason B, Klein Tank A, Haylock M, Collins D, Trewin B, Rahimzadeh F, Tagipour A, Ambenje P, Kumar KR, Revadekar J, Griffiths G, Vincent L, Stephenson DB, Burn J, Aguliar E, Brunet M, Taylor M, New M, Zhai P, Rusticucci M, Vazquez-Aguirre JL (2006) Global observed changes in daily climate extremes of temperature and precipitation. J Geophys Res 111: 1-22.
3. Anderson RL (1941) Distribution of the serial correlation coefficients. Ann Math Stat 8(1): 1-13.
4. Andriyashin A, Benko M, Härdle W, Timofeev R, Ziegenhagen U (2006) Color harmonization in car manufacturing processes. Appl Stoch Models Bus Ind 22: 519-532.
5. Bayazit M, Önöz B (2007) To prewhiten or not to prewhiten in trend analysis? Hydrol Sci J 52(4): 611-624.
6. Beniston M, Stephenson DB (2004) Extreme climatic events and their evolution under changing climatic conditions. Glob Planet Change 44: 1-9.
7. Bertranda P (2000) A local method for estimating change points: the "Hat-function". Statistics 34(3): 215-235.
8. Dawdy DR, Matalas NC (1964) Statistical and probability analysis of hydrologic data, part III: analysis of variance, covariance and time series. In: Chow VT (ed) Handbook of applied hydrology, a compendium of water-resources technology. McGraw-Hill Book Company, New York, pp 868-890.
9. Environmental Protection Administration (EPA) (2009) Extreme events and disasters are biggest threat to Taiwan. Typhoon Morakot. Executive Yuan, ROC Taiwan. http://www. epa. gov. tw.
10. Fischer T, Gemmer M, Liu L, Su B (2012) Change-points in climate extremes in the Zhujiang River Basin, South China, 1961-2007. Clim Change 110: 783-799.
11. Frich P, Alexander L, Della-Marta P, Gleason B, Haylock M, Klein Tank A, Peterson T (2002) Observed coherent changes in climatic extremes during the second half of the twentieth century. Clim Res 19: 193-212.
12. Härdle WK (1990) Applied nonparametric regression. Cambridge University Press, Cambridge.
13. Härdle WK, Song S (2010) Confidence bands in quantile regression. Econom Theory 26: 1180-1200.
14. Härdle WK, Cabrera BL, Okhrin O, Wang W (2011) Localising temperature Risk. SFB 649 Discussion Paper 2011-001. Humboldt Universität zu, Berlin.
15. Härdle WK, Spokoiny V, Wang W (2011) Locale quantile regression. SFB 649 Discussion Paper 2011-005. Humboldt Universität zu, Berlin.
16. Hegerl GC, Zwiers F, Kharin S, Stott P (2007) Detectability of anthropogenic changes in temperature and precipitation extremes. J Clim 17: 3683-3700.
17. Hu Y, Maskey S, Uhlenbrook S (2012) Trends in temperature and rainfall extremes in the Yellow River source region, China. Clim Change 110: 403-429.
18. Iowa Climate Change Impacts Committee (ICCIC) (2011) Climate change impacts on Iowa 2010. Report to the Governor and the Iowa General Assembly. www. energy. iowa. gov.
19. Klein Tank AMG, Zwiers FW, Zhang X (2009) Guidelines on analysis of extremes in a changing climate in support of informed decisions for adaptation. Climate Data and Monitoring WCDMP 72. World Meteorological Organization.
20. Koenker R, Bassett G (1978) Regression quantiles. Econometrica 46(1): 33-50.
21. Kürbis K, Mudelsee M, Tetzlaff G, Brázdil R (2009) Trends in extremes of temperature, dew point, and precipitation from long instrumental series from central Europe. Theory Appl Climatol 98: 187-195.
22. Liu X, Xu Z, Yu R (2011) Trend of climate variability in China during the past decades. Clim Change 109: 503-516.
23. Mercurio D, Spokoiny V (2004) Statistical inference for time-inhomogeneous volatility models. Ann Stat 32: 577-602.
24. Nadolnyak D, Vedenov D, Novak J (2008) Information value of climate-based yield forecasts in selecting optimal crop insurance coverage. Am J Agric Econ 90(5): 1248-1255.
25. Noguchi K, Gel YR, Duguay CR (2011) Bootstrap-based tests for trends in hydrological time series, with application to ice phenology data. J Hydrol 410(3-4): 150-161.
26. Siliverstovs B, Rainald Ö, Kemfert C, Jaeger C, Armin H, Kremers H (2010) Climate change and modelling of extreme temperatures in Switzerland. Stoch Environ Res Risk Assess 24: 311-326.
27. Spokoiny V (2009) Multiscale local change point detection with applications to value at risk. Ann Stat 37(3): 1405-1436.
28. Tebaldi C, Hayhoe K, Arblaster JM, Meehl GA (2006) Going to the extremes: an intercomparison of model-simulated historical and future changes in extreme events. Clim Change 79(3-4): 185-211.
29. Trenberth KE (2011) Changes in precipitation with climate change. Clim Res 47: 123-138.
30. Vasiliades L, Loukas A, Patsonas G (2009) Evaluation of a statistical downscaling procedure for the estimation of climate change impacts on droughts. Nat Hazards Earth Syst Sci 9: 879-894.
31. Wilson LT, Yang Y, Lu P, Wang J, Nielsen-Gammon JW, Smith N, Fernandez CJ (2007) Integrated Agricultural Information and Management System (iAIMS): World Climatic Data. http://beaumont. tamu. edu/ClimaticData/.
32. World Bank (2005) Managing agricultural production risk: innovations in developing countries, www. worldbank. org/rural.
33. Xu W, Filler G, Odening M, Okhrin O (2010) On the systemic nature of weather risk. Agric Finance Rev 70(2): 267-284.
34. Yue S, Pilon P, Caradias G (2002) Power of the Mann-Kendall and Spearman's rho tests for detecting monotonic trends in hydrological series. J Hydrol 259: 254-271.
35. Zhang Q, Xu CY, Zhang Z, Chen Y (2009) Changes of temperature extremes for 1960-2004 in Far-West China. Stoch Environ Res Risk Assess 23(6): 721-735.