Climate Extremes indices Research Papers (original) (raw)

Background and Objectives: Now most reliable tool to produce climate scenarios is use of Atmosphere-Ocean General Circulation Model outputs which stands as AOGCM. One of the using major problems of AOGCM outputs is computational large cell size of their simulation in any region. So first must their outputs has been downscaled and then they used. Present several stochastically methods for downscaling AOGCM outputs to increase their accuracy in simulate. It should be noted that Deference in downscaling methods can cause deference in simulation results. So assess accuracy of downscaling methods is very necessary in any region. Many researchers around the world to check the accuracy of various downscaling methods have focused. Results of Research study around the world indicates that simulation of climate and hydrological parameters depending on output of AOGCM models and also quality and quantity of observation data are very deferent. The aim of this study is assessment of statistical downscaling methods for precipitation and temperature include LARS-WG and SDSM in Birjand synoptic station.
Materials and Methods: Observation data of Birjand synoptic station include precipitation, maximum and minimum temperature and solar watch daily on 1960-2000 were taken of province Meteorological organization. The period 1960-1990 is used for models calibration (train) and 1991-2000 for validation (test) selected. Series of climate extremes indices evaluated for observed data of synoptic station and simulated by downscaling methods on validation period. Statistical tests are used for evaluation and analysis of downscaling methods performance. The sensitivity of the methods to large-scale anomalies (correlation between observed and simulated data) and their ability to replicate the observed data distribution in the validation period are separately tested for each index by Pearson correlation and Wilcoxon signed rank tests, respectively.
Results: By analysis of results defined that between of downscaling methods there isn’t significant superiority in person correlation test. While in correlation test in both model p-value of more 50% of observation and simulation indices is most of 0.05 and they acceptable. Results of performance models in Wilcoxon test showed that performance of weather generator technic is significantly better than linear regression method. Results of this test showed that more of 90% of indices have a suitable fit in LARS-WG. Also fit of temperature indices in SDSM-DC compared with LARS-WG were very weak.
Conclusion: results of this study showed that LARS-WG method compared with SDSM-DC method is more accurate generally. This accuracy in forecast of distribution function was more tangible.

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- HadCM3, Pearson Correlation, Wilcoxon Signed Rank Test, Climate Extremes indices

The northeast region of Côte d’Ivoire, where agriculture is the main economic activity, is potentially vulnerable to extreme climatic conditions. This study aims to make a comprehensive spatio-temporal analysis of trends in extreme indices related to precipitation and temperature for the Zanzan region of Côte d’Ivoire over the period of 1981–2020. The statistical significance of the calculated trends was assessed using the non-parametric Mann–Kendall test, while Sen’s slope estimation was used to define the amount of change. For extreme precipitations, the results showed a decreasing trend in annual total precipitations estimated at 112.37 mm and in daily precipitations intensity indices. Furthermore, the consecutive dry days’ index showed an increasing trend estimated at 18.67 days. Unlike the trends in precipitation extremes, which showed statistically non-significant trends, the trends in temperature extremes were mostly significant over the entire study area. The cold spells indices all show decreasing trends, while the warm spells show increasing trends. Drawing inferences from the results, it becomes clear that the study area may be threatened by food insecurity and water scarcity. The results are aimed to support climate adaptation efforts and policy intervention in the region.