SlideShare a Scribd company logo
1 of 25
Climate Data in India:
           Open and Closed
                                     - Pavan Srinath




Environmental Governance Group, Public Affairs Centre
          pavan.srinath@pacindia.org | @zeusisdead
Introduction




Public Affairs Centre is a non-profit organisation in Bangalore promoting good governance since 1994
through research, advocacy and action.

In 2010, we formed a new group called the Environmental Governance Group, focusing on trying to develop
governance solutions to environmental issues in India, including climate change adaptation.
In the struggle for assessing climate change impacts, exploring robust adaptation options, and trying to
work with both community knowledge & climate science, we thought that it was worthwhile to take a step
back, and try to learn more about our local climate first.

This started an initiative called Know Your Climate.

                              www.pacindia.org | www.knowyourclimate.org
Climate Data in India

• Indian Meteorological Department, the Hegemon
      – Lots of data vs. No data available in the public domain.
      The conundrum is that India has one of the oldest meteorological institutions in the world,
      with a rich instrumental record, but very little data is available for the public to use!
• IMD Stations & Everybody else’s Rain Gauges
      While IMD maintains weather stations across India, state economics departments, disaster
      management cells and others maintain a far larger number of rain gauges across the country.
      Some states like Rajasthan have put rain gauge data in the public domain (HT: India Water
      Portal), but others are yet to follow.
• Station data vs. Gridded products vs. Satellite products
      Station data can be really expensive! So, data from individual stations are usually processed
      to develop gridded data sets, both in India and elsewhere. The IMD has developed a few that
      are inexpensive, but with restrictions on use. There’s currently one daily gridded dataset from
      Japan that’s available for public use! (see next page)
      Now satellites like NASA’s TRMM can directly measure a host of weather & climate
      parameters including surface temperature, rainfall, sea winds and more!
• The Intrepid farmer!
      In the heavily contested area of good quality & open climate data, where you can’t always
      trust the numbers, sometimes it’s the intrepid farmer with a private rain gauge who comes to
      your rescue!
Gridded data from Japan!
The only long-term (1951-2007) daily rainfall data set that’s currently open for non-commercial use:




                                                                                        http://www.chikyu.ac.jp/
                                                                                        Krishnamurthi et al (2009)
                                          APHRODITE Rainfall data set, Research Institute for Humanity and Nature, Japan
Mr. Vimal Kumar, a coffee planter from Wayanad who started collecting
rainfall data daily from April 1983, and hasn’t stopped since!
Gridded data from Japan!




                                         Can’t we go local?
                                Pan-Indian climate & monsoon analyses cannot
                                take into account India’s immense geographic and
                                climatic diversity. It’s imperative that we go ‘local’
                                with our understanding. Let’s ask the question
                                “What do we know about Bangalore’s climate?”
                                rather than “What do we know about India’s
                                climate?”

                                With gridded data sets, we can begin doing that
                                in an inexpensive manner.

                                                             http://www.chikyu.ac.jp/
                                                             Krishnamurthi et al (2009)
               APHRODITE Rainfall data set, Research Institute for Humanity and Nature, Japan
Going Local with Climate Data
Zooming in on Bangalore




                                                           The next few slides will look
                                                           at the little grid cell that
                                                           focuses on Bangalore. The
                                                           two pink dots represent the
                                                           city & HAL airport IMD
                                                           stations, the likely source for
                                                           generating the gridded data.

                   APHRODITE Rainfall data set, Research Institute for Humanity and Nature, Japan
The Joy of Daily Rainfall Data
The Joy of Daily Rainfall Data
                      Monthly Rainfall Profile of Bangalore (1951-2007)
                      This is the most common picture that you
                      see, when somebody talks about the ‘rainfall
                180   profile’ of a place.

                160   What you can tell from this is that Bangalore has                           153.8
                      two seasons of rainfall, one summer and one                                          149.2
                      monsoon.
                140

                120
                                                                                         101.9
Rainfall (mm)




                100
                                                              89.1
                                                                                 82.0
                 80
                                                                          62.1
                 60                                                                                                  50.1

                 40                                 36.7


                 20                                                                                                            15.2
                                           9.7
                        1.6      4.4
                  0


                                                               Source: APHRODITE Rainfall data set, Research Institute for Humanity and Nature, Japan
The Joy of Daily Rainfall Data
                             Monthly Rainfall Profile of Bangalore (1951-2007)
                             If the last graph is converted into mm/day, you
                             end up with this graph, showing the monthly
                             averages of how much rain fell on a ‘per day’
                             basis.
                    10

                                                                                                                       Monthly Average
                    8
Rainfall (mm/day)




                    6



                    4



                    2



                    0
                         1


                                                                      Source: APHRODITE Rainfall data set, Research Institute for Humanity and Nature, Japan
The Joy of Daily Rainfall Data
                             Daily Rainfall Profile of Bangalore (1951-2007)
                             The daily averages show a completely different picture!

                             And our seasons don’t respect monthly boundaries. 
                    10
                                                                                                                        Monthly Average
                                                                                                                        Daily Rainfall
                    8
Rainfall (mm/day)




                    6



                    4



                    2



                    0
                         1


                                                                     Source: APHRODITE Rainfall data set, Research Institute for Humanity and Nature, Japan
The Joy of Daily Rainfall Data
                               Daily Rainfall Profile of Bangalore (1951-2007)

                    10.0

                                                                                                     Daily Rainfall
                     8.0
                                                                                                When Bangalore
                                                                                                rainfall really
Rainfall (mm/day)




                                                                                                picks up!
                     6.0
                                                                  Onset of the
                                              Summer rain          monsoon

                     4.0



                     2.0



                                               A recurring dry period in June!
                     0.0
                           1


                                                Source: APHRODITE Rainfall data set, Research Institute for Humanity and Nature, Japan
The Joy of Daily Rainfall Data
                                  Daily Rainfall Probability, Bangalore
                       100%

                                                                                        Chance of Rainfall on
                                                                                        any given day
                       80%
% Chance of Rainfall




                       60%
                                  On any given day, assuming no other
                                  knowledge, there’s never any certain rain in
                                  Bangalore. Unlike some places on the coast and
                       40%        elsewhere.



                       20%




                        0%
                              1


                                                                                   Chance of rain >= 2.5mm
The Joy of Daily Rainfall Data
                                        Daily Rainfall Probability, Bangalore
                           100%
                                        But the certainty of some                                 7 day
                                        rain within a week is far
                                        higher.                                                   1 day
                           80%
% Probabiliy of Rainfall




                           60%




                           40%




                           20%




                            0%
                                  Jan
                                                                    Axis Title
                                                                                 Chance of rain >= 2.5mm
The Joy of Daily Rainfall Data
                               Daily Rainfall Profile of Bangalore (1951-2007)

                    10.0

                                                                      Daily Rainfall
                     8.0
Rainfall (mm/day)




                     6.0



                     4.0



                     2.0



                     0.0
                           1
The Joy of Daily Rainfall Data
                         How much rain do we get, when it does rain?
                    20


                                                                                                   Amount of Rainfall
                                                                                                   per rainy day

                    15
Rainfall (mm/day)




                    10




                     5




                     0
                         1


                             Days such as those in Feb/Mar seem to correspond well to the adage:   When it rains, it pours!
The Joy of Daily Rainfall Data
                          What’s the most it can rain in a day?
                    120
                              Maximum recorded
                              rainfall on any date
                    100



                     80
Rainfall (mm/day)




                     60



                     40



                     20



                     0
                          1


                                  We can get heavy rainfall in Bangalore almost any time between April and December. And Bangalore
                                              gets ~1-2 heavy rainfall days almost every year. So why do they still catch us by surprise?
The Depressing part about Rainfall
Rainfall in Aug-Sept 2011, Bangalore
                            This is actual rainfall by day in 2011. On August
                                     16 night, it rained very heavily, with the
                           Bangalore city weather station (near Maharani’s
                                     college) recording over 100mm of rain.




                                        http://www.imdaws.com/ViewAwsData.aspx
The Depressing part about Rainfall
   What happens to Bangalore when it rains…
 Boy drowns in a                                                                                               (Taken from news clippings)
      drain      Storm Drains
                 overflowing
                                                                                                          Flooding of houses Trees uprooted
Gali Anjaneya
                          Severe Flooding                                                                     in Hebbal
  temple &
surroundings
  damaged




                                                                                                                             2 die in mud cave-
                                                                                                                                        in
                     ----------------------------------------------------Traffic Disruptions-------------------------------------------------




                                                                                                    http://www.imdaws.com/ViewAwsData.aspx
The Depressing part about Rainfall
     What happens to Bangalore when it rains…
                                                                                                                (Taken from news clippings)
Boy drowns in a   Storm Drains
     drain        overflowing
                                                                                                           Flooding of houses Trees uprooted
  Gali Anjaneya
                           Severe Flooding                                                                     in Hebbal
    temple &
  surroundings
    damaged                                                     What has JnNURM done for us?

                       Water gushes
                      under the metro
                                                                      Storm Water Drain irregularities
                                                                              discovered.




                                                                                              BBMP starts fixing
                                                              More metro woes                        potholes                 2 die in mud cave-
                      ----------------------------------------------------Traffic Disruptions-------------------------------------------------
                                                                                                                                         in
Revisiting traditional knowledge systems
         The Malayalam calendar & Rainfall in Wayanad
If we can map rainfall patterns onto the traditional
                                                               Karkkidakam
calendar, it would go a long way in mainstreaming
traditional knowledge! This is just an example from what we
did in
Wayanad, Kerala.

                                                                        Chinga masam
                                       Edavam paadhi
                                                                                             Tulavarsham
                                 Puthu mazha
                                   Vishu                                     Onam
              Kumbha mazha
                                                                                                               Harvest




        Jan      Feb      Mar      Apr      May       Jun       Jul     Aug        Sep       Oct      Nov        Dec
                                                 Kumar and Srinath, Climate Trends in Wayanad: Voices from the Community (2011)
A year’s rainfall is like a signature – each one unique.
                                     Monthly Rainfall series in Wayanad, 2000-2011

                  1000

                                                                                                          Muttil

                   800
  Rainfall (mm)




                   600



                   400



                   200



                     0
                     2000   2001   2002   2003   2004   2005   2006   2007     2008     2009    2010     2011      2012
                                                               Year
Just to throw a note of caution: the presentation discusses rainfall patterns and daily averages, but it’s good to remember
that they’re just that: Averages. Each year’s climate & rainfall pattern is still quite unique, as seen in the graph above.
Acknowledgements
All that you have seen is a part of the fledgling Know your climate initiative, where we
want people to understand their local climate using data that we help visualize. It’s not
yet operational, and we are looking for volunteers to help us out with web-designing
and visualization! Please spread the word! 




People who’ve helped make this possible are Adarsh DK and Yashas MS (Btech 2nd
year, NIT Surathkal), who spent summer ’11 working with us; Danesh Kumar, RASTA, for
the work in Wayanad; my colleagues at Public Affairs Centre: Jangal Jayaram, Prarthana
Rao, Kuldip Gyaneswar and Director R. Suresh.
References

APHRODITE Daily Rainfall Data set at the Research Institute for Humanity and
Nature, Japan: http://www.chikyu.ac.jp/

“Climate Trends in Wayanad: Voices from the Community”, Conference paper
(2011): http://goo.gl/QIA7k

IMD Automater Weather Station website:
http://www.imdaws.com/ViewAwsData.aspx




                Do keep an eye on blog.knowyourclimate.org! 
Thank you!
www.pacindia.org                                       @zeusisdead
greengovernance.wordpress.com            pavan.srinath@pacindia.org

More Related Content

Viewers also liked

Saudi arabia presentation
Saudi arabia presentationSaudi arabia presentation
Saudi arabia presentation
bpdow12
 
India - climate change adaptaton into DRR programmes - ActionAid
India - climate change adaptaton  into DRR programmes - ActionAidIndia - climate change adaptaton  into DRR programmes - ActionAid
India - climate change adaptaton into DRR programmes - ActionAid
Strengthening Climate Resilience
 
Saudi Aramco Carbon Management - May 2013
Saudi Aramco Carbon Management - May 2013Saudi Aramco Carbon Management - May 2013
Saudi Aramco Carbon Management - May 2013
Global CCS Institute
 

Viewers also liked (16)

20090701 Climate Data Staging
20090701 Climate Data Staging20090701 Climate Data Staging
20090701 Climate Data Staging
 
Climate data in R with the raster package
Climate data in R with the raster packageClimate data in R with the raster package
Climate data in R with the raster package
 
Edwards climate data detectives - yale 2-2015
Edwards   climate data detectives - yale 2-2015Edwards   climate data detectives - yale 2-2015
Edwards climate data detectives - yale 2-2015
 
ESRI User Conference 2014 - A Location Aware Mobile Tool for Direct and Indir...
ESRI User Conference 2014 - A Location Aware Mobile Tool for Direct and Indir...ESRI User Conference 2014 - A Location Aware Mobile Tool for Direct and Indir...
ESRI User Conference 2014 - A Location Aware Mobile Tool for Direct and Indir...
 
Contextualizing the Visualization of Climate Data
Contextualizing the Visualization of Climate DataContextualizing the Visualization of Climate Data
Contextualizing the Visualization of Climate Data
 
Saudi arabia climate policy report
Saudi arabia climate policy reportSaudi arabia climate policy report
Saudi arabia climate policy report
 
Geography Water
Geography WaterGeography Water
Geography Water
 
Collaborate 2012: Environmental Accounting and Reporting
Collaborate 2012: Environmental Accounting and ReportingCollaborate 2012: Environmental Accounting and Reporting
Collaborate 2012: Environmental Accounting and Reporting
 
Saudi arabia presentation
Saudi arabia presentationSaudi arabia presentation
Saudi arabia presentation
 
India - climate change adaptaton into DRR programmes - ActionAid
India - climate change adaptaton  into DRR programmes - ActionAidIndia - climate change adaptaton  into DRR programmes - ActionAid
India - climate change adaptaton into DRR programmes - ActionAid
 
Making Climate Data Sing
Making Climate Data SingMaking Climate Data Sing
Making Climate Data Sing
 
BigDataEurope - Big Data & Climate Change
BigDataEurope - Big Data & Climate ChangeBigDataEurope - Big Data & Climate Change
BigDataEurope - Big Data & Climate Change
 
Saudi Aramco Carbon Management - May 2013
Saudi Aramco Carbon Management - May 2013Saudi Aramco Carbon Management - May 2013
Saudi Aramco Carbon Management - May 2013
 
The Role of DAta for Climate Monitoring and Prediction
The Role of DAta for Climate Monitoring and PredictionThe Role of DAta for Climate Monitoring and Prediction
The Role of DAta for Climate Monitoring and Prediction
 
Non-renewable groundwater management in Saudi Arabia
Non-renewable groundwater management in Saudi ArabiaNon-renewable groundwater management in Saudi Arabia
Non-renewable groundwater management in Saudi Arabia
 
India - Climate change and disaster management - Oxfam
India - Climate change and disaster management - OxfamIndia - Climate change and disaster management - Oxfam
India - Climate change and disaster management - Oxfam
 

Similar to Climate data in india - Open and Closed

GurminderBharani_Masters_Thesis
GurminderBharani_Masters_ThesisGurminderBharani_Masters_Thesis
GurminderBharani_Masters_Thesis
bharanigurminder
 
On the performance analysis of rainfall prediction using mutual information...
  On the performance analysis of rainfall prediction using mutual information...  On the performance analysis of rainfall prediction using mutual information...
On the performance analysis of rainfall prediction using mutual information...
IJECEIAES
 
Trend analysis of temporal variations in evi with respect to rainfall of jaip...
Trend analysis of temporal variations in evi with respect to rainfall of jaip...Trend analysis of temporal variations in evi with respect to rainfall of jaip...
Trend analysis of temporal variations in evi with respect to rainfall of jaip...
eSAT Journals
 
Comparative Study of Machine Learning Algorithms for Rainfall Prediction
Comparative Study of Machine Learning Algorithms for Rainfall PredictionComparative Study of Machine Learning Algorithms for Rainfall Prediction
Comparative Study of Machine Learning Algorithms for Rainfall Prediction
ijtsrd
 
Binary classification of rainfall time-series using machine learning algorithms
Binary classification of rainfall time-series using machine  learning algorithmsBinary classification of rainfall time-series using machine  learning algorithms
Binary classification of rainfall time-series using machine learning algorithms
IJECEIAES
 

Similar to Climate data in india - Open and Closed (20)

GurminderBharani_Masters_Thesis
GurminderBharani_Masters_ThesisGurminderBharani_Masters_Thesis
GurminderBharani_Masters_Thesis
 
On the performance analysis of rainfall prediction using mutual information...
  On the performance analysis of rainfall prediction using mutual information...  On the performance analysis of rainfall prediction using mutual information...
On the performance analysis of rainfall prediction using mutual information...
 
IRJET- Review on Drought Risk Assessment by using Remote Sensing and GIS
IRJET-  	  Review on Drought Risk Assessment by using Remote Sensing and GISIRJET-  	  Review on Drought Risk Assessment by using Remote Sensing and GIS
IRJET- Review on Drought Risk Assessment by using Remote Sensing and GIS
 
DMAP Formulas
DMAP FormulasDMAP Formulas
DMAP Formulas
 
185-687-1-PB
185-687-1-PB185-687-1-PB
185-687-1-PB
 
213180005 Seminar presentation.pptx
213180005 Seminar presentation.pptx213180005 Seminar presentation.pptx
213180005 Seminar presentation.pptx
 
Integrated Water Resources Management Using Rainfall Forecasting With Artific...
Integrated Water Resources Management Using Rainfall Forecasting With Artific...Integrated Water Resources Management Using Rainfall Forecasting With Artific...
Integrated Water Resources Management Using Rainfall Forecasting With Artific...
 
Trend analysis of temporal variations in evi with respect to rainfall of jaip...
Trend analysis of temporal variations in evi with respect to rainfall of jaip...Trend analysis of temporal variations in evi with respect to rainfall of jaip...
Trend analysis of temporal variations in evi with respect to rainfall of jaip...
 
Complexity Neural Networks for Estimating Flood Process in Internet-of-Things...
Complexity Neural Networks for Estimating Flood Process in Internet-of-Things...Complexity Neural Networks for Estimating Flood Process in Internet-of-Things...
Complexity Neural Networks for Estimating Flood Process in Internet-of-Things...
 
Tracking emerging diseases from space: Geoinformatics for human health
Tracking emerging diseases from space: Geoinformatics for human healthTracking emerging diseases from space: Geoinformatics for human health
Tracking emerging diseases from space: Geoinformatics for human health
 
Agricultural risk micro-insurance product for Mozambique
Agricultural risk micro-insurance product for MozambiqueAgricultural risk micro-insurance product for Mozambique
Agricultural risk micro-insurance product for Mozambique
 
Assessment of two Methods to study Precipitation Prediction
Assessment of two Methods to study Precipitation PredictionAssessment of two Methods to study Precipitation Prediction
Assessment of two Methods to study Precipitation Prediction
 
Anand Utsav_CV
Anand Utsav_CVAnand Utsav_CV
Anand Utsav_CV
 
20320140503021
2032014050302120320140503021
20320140503021
 
Comparative Study of Machine Learning Algorithms for Rainfall Prediction
Comparative Study of Machine Learning Algorithms for Rainfall PredictionComparative Study of Machine Learning Algorithms for Rainfall Prediction
Comparative Study of Machine Learning Algorithms for Rainfall Prediction
 
AUTOMATIC IRRIGATION SYSTEM DESIGN AND IMPLEMENTATION BASED ON IOT FOR AGRICU...
AUTOMATIC IRRIGATION SYSTEM DESIGN AND IMPLEMENTATION BASED ON IOT FOR AGRICU...AUTOMATIC IRRIGATION SYSTEM DESIGN AND IMPLEMENTATION BASED ON IOT FOR AGRICU...
AUTOMATIC IRRIGATION SYSTEM DESIGN AND IMPLEMENTATION BASED ON IOT FOR AGRICU...
 
THREDDS Data Server and Solar Insolation Prediction using Machine Learning Te...
THREDDS Data Server and Solar Insolation Prediction using Machine Learning Te...THREDDS Data Server and Solar Insolation Prediction using Machine Learning Te...
THREDDS Data Server and Solar Insolation Prediction using Machine Learning Te...
 
Merging multiple soil moisture products for improving the accuracy in rainfal...
Merging multiple soil moisture products for improving the accuracy in rainfal...Merging multiple soil moisture products for improving the accuracy in rainfal...
Merging multiple soil moisture products for improving the accuracy in rainfal...
 
flood prediction.pptx
flood prediction.pptxflood prediction.pptx
flood prediction.pptx
 
Binary classification of rainfall time-series using machine learning algorithms
Binary classification of rainfall time-series using machine  learning algorithmsBinary classification of rainfall time-series using machine  learning algorithms
Binary classification of rainfall time-series using machine learning algorithms
 

Recently uploaded

Beyond the EU: DORA and NIS 2 Directive's Global Impact
Beyond the EU: DORA and NIS 2 Directive's Global ImpactBeyond the EU: DORA and NIS 2 Directive's Global Impact
Beyond the EU: DORA and NIS 2 Directive's Global Impact
PECB
 
The basics of sentences session 2pptx copy.pptx
The basics of sentences session 2pptx copy.pptxThe basics of sentences session 2pptx copy.pptx
The basics of sentences session 2pptx copy.pptx
heathfieldcps1
 
Making and Justifying Mathematical Decisions.pdf
Making and Justifying Mathematical Decisions.pdfMaking and Justifying Mathematical Decisions.pdf
Making and Justifying Mathematical Decisions.pdf
Chris Hunter
 
The basics of sentences session 3pptx.pptx
The basics of sentences session 3pptx.pptxThe basics of sentences session 3pptx.pptx
The basics of sentences session 3pptx.pptx
heathfieldcps1
 

Recently uploaded (20)

Unit-IV; Professional Sales Representative (PSR).pptx
Unit-IV; Professional Sales Representative (PSR).pptxUnit-IV; Professional Sales Representative (PSR).pptx
Unit-IV; Professional Sales Representative (PSR).pptx
 
Sociology 101 Demonstration of Learning Exhibit
Sociology 101 Demonstration of Learning ExhibitSociology 101 Demonstration of Learning Exhibit
Sociology 101 Demonstration of Learning Exhibit
 
Advanced Views - Calendar View in Odoo 17
Advanced Views - Calendar View in Odoo 17Advanced Views - Calendar View in Odoo 17
Advanced Views - Calendar View in Odoo 17
 
General Principles of Intellectual Property: Concepts of Intellectual Proper...
General Principles of Intellectual Property: Concepts of Intellectual  Proper...General Principles of Intellectual Property: Concepts of Intellectual  Proper...
General Principles of Intellectual Property: Concepts of Intellectual Proper...
 
Beyond the EU: DORA and NIS 2 Directive's Global Impact
Beyond the EU: DORA and NIS 2 Directive's Global ImpactBeyond the EU: DORA and NIS 2 Directive's Global Impact
Beyond the EU: DORA and NIS 2 Directive's Global Impact
 
Holdier Curriculum Vitae (April 2024).pdf
Holdier Curriculum Vitae (April 2024).pdfHoldier Curriculum Vitae (April 2024).pdf
Holdier Curriculum Vitae (April 2024).pdf
 
Measures of Central Tendency: Mean, Median and Mode
Measures of Central Tendency: Mean, Median and ModeMeasures of Central Tendency: Mean, Median and Mode
Measures of Central Tendency: Mean, Median and Mode
 
The basics of sentences session 2pptx copy.pptx
The basics of sentences session 2pptx copy.pptxThe basics of sentences session 2pptx copy.pptx
The basics of sentences session 2pptx copy.pptx
 
Making and Justifying Mathematical Decisions.pdf
Making and Justifying Mathematical Decisions.pdfMaking and Justifying Mathematical Decisions.pdf
Making and Justifying Mathematical Decisions.pdf
 
PROCESS RECORDING FORMAT.docx
PROCESS      RECORDING        FORMAT.docxPROCESS      RECORDING        FORMAT.docx
PROCESS RECORDING FORMAT.docx
 
Introduction to Nonprofit Accounting: The Basics
Introduction to Nonprofit Accounting: The BasicsIntroduction to Nonprofit Accounting: The Basics
Introduction to Nonprofit Accounting: The Basics
 
Food Chain and Food Web (Ecosystem) EVS, B. Pharmacy 1st Year, Sem-II
Food Chain and Food Web (Ecosystem) EVS, B. Pharmacy 1st Year, Sem-IIFood Chain and Food Web (Ecosystem) EVS, B. Pharmacy 1st Year, Sem-II
Food Chain and Food Web (Ecosystem) EVS, B. Pharmacy 1st Year, Sem-II
 
Measures of Dispersion and Variability: Range, QD, AD and SD
Measures of Dispersion and Variability: Range, QD, AD and SDMeasures of Dispersion and Variability: Range, QD, AD and SD
Measures of Dispersion and Variability: Range, QD, AD and SD
 
Energy Resources. ( B. Pharmacy, 1st Year, Sem-II) Natural Resources
Energy Resources. ( B. Pharmacy, 1st Year, Sem-II) Natural ResourcesEnergy Resources. ( B. Pharmacy, 1st Year, Sem-II) Natural Resources
Energy Resources. ( B. Pharmacy, 1st Year, Sem-II) Natural Resources
 
Web & Social Media Analytics Previous Year Question Paper.pdf
Web & Social Media Analytics Previous Year Question Paper.pdfWeb & Social Media Analytics Previous Year Question Paper.pdf
Web & Social Media Analytics Previous Year Question Paper.pdf
 
The basics of sentences session 3pptx.pptx
The basics of sentences session 3pptx.pptxThe basics of sentences session 3pptx.pptx
The basics of sentences session 3pptx.pptx
 
Asian American Pacific Islander Month DDSD 2024.pptx
Asian American Pacific Islander Month DDSD 2024.pptxAsian American Pacific Islander Month DDSD 2024.pptx
Asian American Pacific Islander Month DDSD 2024.pptx
 
Explore beautiful and ugly buildings. Mathematics helps us create beautiful d...
Explore beautiful and ugly buildings. Mathematics helps us create beautiful d...Explore beautiful and ugly buildings. Mathematics helps us create beautiful d...
Explore beautiful and ugly buildings. Mathematics helps us create beautiful d...
 
On National Teacher Day, meet the 2024-25 Kenan Fellows
On National Teacher Day, meet the 2024-25 Kenan FellowsOn National Teacher Day, meet the 2024-25 Kenan Fellows
On National Teacher Day, meet the 2024-25 Kenan Fellows
 
Unit-V; Pricing (Pharma Marketing Management).pptx
Unit-V; Pricing (Pharma Marketing Management).pptxUnit-V; Pricing (Pharma Marketing Management).pptx
Unit-V; Pricing (Pharma Marketing Management).pptx
 

Climate data in india - Open and Closed

  • 1. Climate Data in India: Open and Closed - Pavan Srinath Environmental Governance Group, Public Affairs Centre pavan.srinath@pacindia.org | @zeusisdead
  • 2. Introduction Public Affairs Centre is a non-profit organisation in Bangalore promoting good governance since 1994 through research, advocacy and action. In 2010, we formed a new group called the Environmental Governance Group, focusing on trying to develop governance solutions to environmental issues in India, including climate change adaptation. In the struggle for assessing climate change impacts, exploring robust adaptation options, and trying to work with both community knowledge & climate science, we thought that it was worthwhile to take a step back, and try to learn more about our local climate first. This started an initiative called Know Your Climate. www.pacindia.org | www.knowyourclimate.org
  • 3. Climate Data in India • Indian Meteorological Department, the Hegemon – Lots of data vs. No data available in the public domain. The conundrum is that India has one of the oldest meteorological institutions in the world, with a rich instrumental record, but very little data is available for the public to use! • IMD Stations & Everybody else’s Rain Gauges While IMD maintains weather stations across India, state economics departments, disaster management cells and others maintain a far larger number of rain gauges across the country. Some states like Rajasthan have put rain gauge data in the public domain (HT: India Water Portal), but others are yet to follow. • Station data vs. Gridded products vs. Satellite products Station data can be really expensive! So, data from individual stations are usually processed to develop gridded data sets, both in India and elsewhere. The IMD has developed a few that are inexpensive, but with restrictions on use. There’s currently one daily gridded dataset from Japan that’s available for public use! (see next page) Now satellites like NASA’s TRMM can directly measure a host of weather & climate parameters including surface temperature, rainfall, sea winds and more! • The Intrepid farmer! In the heavily contested area of good quality & open climate data, where you can’t always trust the numbers, sometimes it’s the intrepid farmer with a private rain gauge who comes to your rescue!
  • 4. Gridded data from Japan! The only long-term (1951-2007) daily rainfall data set that’s currently open for non-commercial use: http://www.chikyu.ac.jp/ Krishnamurthi et al (2009) APHRODITE Rainfall data set, Research Institute for Humanity and Nature, Japan
  • 5. Mr. Vimal Kumar, a coffee planter from Wayanad who started collecting rainfall data daily from April 1983, and hasn’t stopped since!
  • 6. Gridded data from Japan! Can’t we go local? Pan-Indian climate & monsoon analyses cannot take into account India’s immense geographic and climatic diversity. It’s imperative that we go ‘local’ with our understanding. Let’s ask the question “What do we know about Bangalore’s climate?” rather than “What do we know about India’s climate?” With gridded data sets, we can begin doing that in an inexpensive manner. http://www.chikyu.ac.jp/ Krishnamurthi et al (2009) APHRODITE Rainfall data set, Research Institute for Humanity and Nature, Japan
  • 7. Going Local with Climate Data Zooming in on Bangalore The next few slides will look at the little grid cell that focuses on Bangalore. The two pink dots represent the city & HAL airport IMD stations, the likely source for generating the gridded data. APHRODITE Rainfall data set, Research Institute for Humanity and Nature, Japan
  • 8. The Joy of Daily Rainfall Data
  • 9. The Joy of Daily Rainfall Data Monthly Rainfall Profile of Bangalore (1951-2007) This is the most common picture that you see, when somebody talks about the ‘rainfall 180 profile’ of a place. 160 What you can tell from this is that Bangalore has 153.8 two seasons of rainfall, one summer and one 149.2 monsoon. 140 120 101.9 Rainfall (mm) 100 89.1 82.0 80 62.1 60 50.1 40 36.7 20 15.2 9.7 1.6 4.4 0 Source: APHRODITE Rainfall data set, Research Institute for Humanity and Nature, Japan
  • 10. The Joy of Daily Rainfall Data Monthly Rainfall Profile of Bangalore (1951-2007) If the last graph is converted into mm/day, you end up with this graph, showing the monthly averages of how much rain fell on a ‘per day’ basis. 10 Monthly Average 8 Rainfall (mm/day) 6 4 2 0 1 Source: APHRODITE Rainfall data set, Research Institute for Humanity and Nature, Japan
  • 11. The Joy of Daily Rainfall Data Daily Rainfall Profile of Bangalore (1951-2007) The daily averages show a completely different picture! And our seasons don’t respect monthly boundaries.  10 Monthly Average Daily Rainfall 8 Rainfall (mm/day) 6 4 2 0 1 Source: APHRODITE Rainfall data set, Research Institute for Humanity and Nature, Japan
  • 12. The Joy of Daily Rainfall Data Daily Rainfall Profile of Bangalore (1951-2007) 10.0 Daily Rainfall 8.0 When Bangalore rainfall really Rainfall (mm/day) picks up! 6.0 Onset of the Summer rain monsoon 4.0 2.0 A recurring dry period in June! 0.0 1 Source: APHRODITE Rainfall data set, Research Institute for Humanity and Nature, Japan
  • 13. The Joy of Daily Rainfall Data Daily Rainfall Probability, Bangalore 100% Chance of Rainfall on any given day 80% % Chance of Rainfall 60% On any given day, assuming no other knowledge, there’s never any certain rain in Bangalore. Unlike some places on the coast and 40% elsewhere. 20% 0% 1 Chance of rain >= 2.5mm
  • 14. The Joy of Daily Rainfall Data Daily Rainfall Probability, Bangalore 100% But the certainty of some 7 day rain within a week is far higher. 1 day 80% % Probabiliy of Rainfall 60% 40% 20% 0% Jan Axis Title Chance of rain >= 2.5mm
  • 15. The Joy of Daily Rainfall Data Daily Rainfall Profile of Bangalore (1951-2007) 10.0 Daily Rainfall 8.0 Rainfall (mm/day) 6.0 4.0 2.0 0.0 1
  • 16. The Joy of Daily Rainfall Data How much rain do we get, when it does rain? 20 Amount of Rainfall per rainy day 15 Rainfall (mm/day) 10 5 0 1 Days such as those in Feb/Mar seem to correspond well to the adage: When it rains, it pours!
  • 17. The Joy of Daily Rainfall Data What’s the most it can rain in a day? 120 Maximum recorded rainfall on any date 100 80 Rainfall (mm/day) 60 40 20 0 1 We can get heavy rainfall in Bangalore almost any time between April and December. And Bangalore gets ~1-2 heavy rainfall days almost every year. So why do they still catch us by surprise?
  • 18. The Depressing part about Rainfall Rainfall in Aug-Sept 2011, Bangalore This is actual rainfall by day in 2011. On August 16 night, it rained very heavily, with the Bangalore city weather station (near Maharani’s college) recording over 100mm of rain. http://www.imdaws.com/ViewAwsData.aspx
  • 19. The Depressing part about Rainfall What happens to Bangalore when it rains… Boy drowns in a (Taken from news clippings) drain Storm Drains overflowing Flooding of houses Trees uprooted Gali Anjaneya Severe Flooding in Hebbal temple & surroundings damaged 2 die in mud cave- in ----------------------------------------------------Traffic Disruptions------------------------------------------------- http://www.imdaws.com/ViewAwsData.aspx
  • 20. The Depressing part about Rainfall What happens to Bangalore when it rains… (Taken from news clippings) Boy drowns in a Storm Drains drain overflowing Flooding of houses Trees uprooted Gali Anjaneya Severe Flooding in Hebbal temple & surroundings damaged What has JnNURM done for us? Water gushes under the metro Storm Water Drain irregularities discovered. BBMP starts fixing More metro woes potholes 2 die in mud cave- ----------------------------------------------------Traffic Disruptions------------------------------------------------- in
  • 21. Revisiting traditional knowledge systems The Malayalam calendar & Rainfall in Wayanad If we can map rainfall patterns onto the traditional Karkkidakam calendar, it would go a long way in mainstreaming traditional knowledge! This is just an example from what we did in Wayanad, Kerala. Chinga masam Edavam paadhi Tulavarsham Puthu mazha Vishu Onam Kumbha mazha Harvest Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Kumar and Srinath, Climate Trends in Wayanad: Voices from the Community (2011)
  • 22. A year’s rainfall is like a signature – each one unique. Monthly Rainfall series in Wayanad, 2000-2011 1000 Muttil 800 Rainfall (mm) 600 400 200 0 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 Year Just to throw a note of caution: the presentation discusses rainfall patterns and daily averages, but it’s good to remember that they’re just that: Averages. Each year’s climate & rainfall pattern is still quite unique, as seen in the graph above.
  • 23. Acknowledgements All that you have seen is a part of the fledgling Know your climate initiative, where we want people to understand their local climate using data that we help visualize. It’s not yet operational, and we are looking for volunteers to help us out with web-designing and visualization! Please spread the word!  People who’ve helped make this possible are Adarsh DK and Yashas MS (Btech 2nd year, NIT Surathkal), who spent summer ’11 working with us; Danesh Kumar, RASTA, for the work in Wayanad; my colleagues at Public Affairs Centre: Jangal Jayaram, Prarthana Rao, Kuldip Gyaneswar and Director R. Suresh.
  • 24. References APHRODITE Daily Rainfall Data set at the Research Institute for Humanity and Nature, Japan: http://www.chikyu.ac.jp/ “Climate Trends in Wayanad: Voices from the Community”, Conference paper (2011): http://goo.gl/QIA7k IMD Automater Weather Station website: http://www.imdaws.com/ViewAwsData.aspx Do keep an eye on blog.knowyourclimate.org! 
  • 25. Thank you! www.pacindia.org @zeusisdead greengovernance.wordpress.com pavan.srinath@pacindia.org