An overview of global climate change , difference between climate change and climate variability . Analysis of climate wheteher it is change or variability at kharagpur considering over 36 year of temperature.

1. Climate change impacts : An overview
&
Analysis of Climate change
Presented by
Chandra Vanshi Thakur
17WM60R07
School of Water Resources
Indian Institute of Technology Kharagpur

2. Contents
• Introduction
• Historical perspectives
• Methodology
• Climate change analysis

3. Introduction
• Few years ago, climate change was just an opinion
with no significant proofs.
• Some harbingers to climate change were :
– Spreading of diseases like malaria, dengue,
cholera etc.
– Changes in flora and fauna population
– Heavy downpours, flooding, droughts and forest
fires in some places across the globe.

4. Evidences of climate change
Global temperature
rise
Glacier melting Ocean warming
Ocean acidification Severe droughts Severe floods

5. Historical Perspectives
• AAAS panel on Climate Change in 1990
200% increase in
CO2 concentration
20% change
in rainfall
50 % change
in soil
moisture

6. Climate is affected by many factors
ABIOTIC FACTORS:
• Ocean Currents
• Solar Radiation
• Evaporation
• Volcanic Activity
BIOTIC FACTORS:
• Transpiration
• Respiration
• Photosynthesis
• Decomposition

7. •A warming of 0.65 to 1.06°c in land and ocean surface
temperature for the period 1880 to 2012.
Keynotes from the Fifth assessment
report of IPCC, 2014
•Between 1971 to 2010 about 90% of energy has been stored
in oceans.
•From 1971 to 2009, global rate of glacier melting ranged
from 91 to 361 Gt/yr and from 1993 to 2009 it ranged from
140 to 410 Gt/yr.
•The radiative forcing due to human activities for the year
2011 ranged from 1.13 to 3.33 W m−2 which is 43% higher
than in 2005.

8. The concentration of the greenhouse gases in the
atmosphere after industrialization has increased by
150% (methane), 40% (carbon dioxide), 20% (nitrous
oxide) due to human activities. In 2011, concentration
of these gases was as CO2 (391 ppm), CH4 (1803 ppb)
and N2O (324 ppb).

9. Unavoidable Facts
•WMO in Paris Climate Agreement on 30th Oct 2017,
stated that, “CO2 in atmosphere up 145% over pre-
industrialization (403.3 ppm in 2016), methane up by
257% since 1750 and N2O up by 122%”.
•The amount of CO2 in the atmosphere has become so high
that even planting trees can NOT save us because there is
not that space available on earth to plant the number of
trees it would take to prevent the climate from warming at
current rate.
- source: European Commission Climate Action

10. Climate change and climate variability
Climate change is a change in the statistical distribution
of weather patterns when that change lasts for an extended period of
time (i.e., decades to millions of years). Climate change may refer to a
change in average weather conditions, or in the time variation of
weather within the context of longer-term average conditions
Climate variability can be regarded as the variability (the extremes
and differences of monthly, seasonal and annual values from the
climatically expected value) inherent in the stationary process
approximating the climate on a scale of a few decades.

11. Risks to Ecosystems & People in India
• SouSSouc
Sea level rise -
Relocation of
population /Climate
induced refugees
Himalayan
Glacier melt –
Flows in Indus
and Ganga at
Risk
• Increased Incidence of Natural Calamities
• Increase in stress to human & other Life forms
• Increased Probability of Trans-boundary issues
Variability in
monsoons –
affecting crop
production
Erosion of coastal areas
due to Sea Level rise and
Extreme Weather
Source: Mohan & Sinha 2010

12. Methodology
Parametric Method
Non-Parametric Method

13. Contd…
Parametric tests
 Linear regression
 Cumulative deviation
 Chi-Square test
 Student’s t test
 Autocorrelation test
 ANOVA test
Nonparametric tests
 Mann-Kendall test
 Spearman’s Rho test
 Kolmogorov-Smirnov test
 Mann–Whitney U test
 Turning points test

14. Linear regression
• Regression analysis is a statistical technique that
attempts to explore and model the relationship between
two or more variables using straight line.
• Y = m X + c
slope “m”, gives the rate of change in a particular parameter that best fits
the moving average trend curve

15. Mann-Kendall (MK) test
• The most frequently used non-parametric test for identifying
trends in hydrologic variables is the Mann-Kendall (MK)
test.
• Mann-Kendall statistic (S) for a series Y1, Y2,…. Yn is given by

16. Variance of the Mann-Kendall
statistic

17. Analysis of climate change in Kharagpur
using temperature data
• Above two test were followed to check the trend in
temperature data in degree c over the period 1969
to 2005

18. Estimation of trend(change in long term
average) using linear regression test
y = 0.0094x + 7.9913
R² = 0.1163
25.6
25.8
26
26.2
26.4
26.6
26.8
27
27.2
1965 1970 1975 1980 1985 1990 1995 2000 2005 2010
Avg.Temp
Avg.Temp
Linear (Avg.Temp)

19. Thank You…