**4. Summary and conclusions**

Statistical analysis of precipitation isotopes was carried out on a large number of samples with a variety of spatial scales. Precipitation samples almost always showed a positively skewed pattern with high values of skewness and kurtosis, typically 2 to 3 and 11 to 13, respectively. On the other hand, the oxygen isotopic values of precipitation mostly showed small negative skewness (typically −0.5 to −1.0). The kurtosis value varied from 0 to 4. The secondary parameter d-excess is characterized by low negative skewness (−1 to 0), and its kurtosis ranges from 0.5 to 5. A comparison of these statistical parameters among precipitation and its isotopic values reveals that precipitation pattern is always skewed and contains a significant amount of extreme values. But the isotopic distribution patterns are near-symmetrical, and they are not very sensitive to extreme rainfall events. This may mean that the isotopic values are less constrained by environmental forcing in comparison to the precipitation. Hence the mean values of precipitation isotopes may be estimated/predicted with better precision than the precipitation. This may have application in paleoclimatic reconstruction.

It was observed that the kurtosis value of d-excess is very sensitive to outliers that may have occurred due to analytical error, but similar behavior was not found in the case of δ 18O or δD. Hence, the distribution parameters may offer a means to better quality control of the precipitation isotope data.

One of the potential applications of this technique is to study the interannual variability of monsoon rainfall. If a significant change is found especially in K value of d-excess distribution pattern in the year to year rainfall, then that change could imply different dynamical control and hence the monsoon circulation.

## **Acknowledgements**

IITM is fully supported by the Earth System Science Organization of the Ministry of Earth Science, The Govt. of India. We thank the Director, IITM and R. Krishnan, Executive Director, Centre for Climate Change Research, IITM, for their support and encouragement.

**105**

India

**Author details**

Rajendra K. Trivedi6

Amey Datye1

Pune, India

Supriyo Chakraborty1,2\*, Siddharth Birmal2

, Aravind G.H.4

3 Department of Geology, Anna University, Chennai, India

\*Address all correspondence to: supriyo@tropmet.res.in

4 Geology Department, Central University of Kerala, Periye, India

1 Indian Institute of Tropical Meteorology, Ministry of Earth Science, Pune, India

2 Department of Atmospheric and Space Science, Savitribai Phule Pune University,

6 Department of Applied Geology, Dr. Harisingh Gour Vishwavidyalaya, Sagar,

© 2020 The Author(s). Licensee IntechOpen. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/ by/3.0), which permits unrestricted use, distribution, and reproduction in any medium,

, Fousiya A.A.3

5 Pondicherry University, Port Blair, India

provided the original work is properly cited.

*Statistical Analysis of the Precipitation Isotope Data with Reference to the Indian Subcontinent*

, Pramit Kumar Deb Burman1,2,

, Neha Trivedi6

and

, PM. Mohan5

*DOI: http://dx.doi.org/10.5772/intechopen.93831*

### **Conflict of interest**

The authors declare no conflict of interest.

*Statistical Analysis of the Precipitation Isotope Data with Reference to the Indian Subcontinent DOI: http://dx.doi.org/10.5772/intechopen.93831*
