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Changes in the characteristics of precipitation and temperature in india

Changes in the characteristics of precipitation and temperature in india. S. K. Dash Acknowledgements to Co-authors in papers:

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Changes in the characteristics of precipitation and temperature in india

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  1. Changes in the characteristics of precipitation and temperature in india S. K. Dash Acknowledgements to Co-authors in papers: J. C. R. Hunt, F. Giorgi, M. Kulkarni, A.P.Dimri, U. C. Mohanty, S. R. Kalsi, K. Prasad, R. K. Jenamani, M. S. Shekhar, S. K. Panda, AshuMamgain and Archana Centre for Atmospheric Sciences Indian Institute of Technology Delhi HauzKhas, New Delhi – 110 016

  2. Outline of the talk Spatial & Temporal Changes in Temperature and Precipitation Agriculture & Health Applications Model Simulations Future Challenges

  3. Spatial & Temporal Changes in Temperature and Rainfall

  4. Homogeneous rainfall zones of India. The numbers inside the zones indicate mean monsoon rainfall (mm), standard deviation (mm) and coefficient of variation (%) from top to bottom respectively Dash et al., 2002, Mausam, 53(2), 133-144

  5. Western Himalaya + 0.9 0C +0.5 0C Northwest + 0.6 0C - 0.2 0C North Central + 0.8 0C + 0.2 0C Northeast + 1.0 0C +0.2 0C Interior Peninsula + 0.5 0C + 0.5 0C West Coast + 1.2 0C 0 + 0.4 0C East Coast + 0.6 0C + 0.2 0C Changes in the maximum and minimum temperatures in different temperature zones during the last century. The upper numbers indicate maximum and lower ones represent minimum temperatures. Also + sign is for an increase and – is for decrease. The map of seven zones has been obtained from http://www.tropmet.res.in

  6. Surface air temperature (0C) changes during different seasons averaged over the whole of India (+ sign indicates an increase and – represents decrease)

  7. Extreme temperature indices used IETCCDI Klein Tank et al. (2009) http://www.clivar.org/organization/etccdi/etccdi.php Dash et al., 2011, J Appl Met & Climatol (In Press)

  8. Summary of trends in annual and seasonal means of maximum and minimum temperatures with trends in different categories of warm days and nights in summer Dash et al., 2011, J Appl Met & Climatol (In Press)

  9. Summary of trends in annual and seasonal mean of maximum and minimum temperatures with trends in different categories of cold days and nights in winter Dash et al., 2011, J Appl Met & Climatol (In Press)

  10. (b) Summer • nights (a) Summer days Density (d) Winter nights (c) Winter days Density Temperature (oC) Temperature (oC) Decadal variations in the temperature probability density functions (PDFs) for entire India in the years from 1969 to 2005 during (a) summer days, (b) summer nights, (c) winter days and (d) winter nights. The smoothed curves represent the fit of the GEV distribution. Dash et al., 2011, J Appl Met & Climatol (In Press)

  11. Some inferences on surface temperature Indication of warming: Differences in the trends in the minimum and maximum temperatures in the North and south. Different impacts of Ocean and Himalayas to be examined. Asymmetry in the increasing temperature trends between different seasons. In last 2-3 decades the increase in maximum and minimum temperatures during October to February is about 0.30C more than during rest of the months. Significant decrease in the frequency of occurrence of cold nights in the winter months and increasing trend in the number of warm days in summer.

  12. Time series of rainfall in India during monsoon months of June, July, August and September. Dash et al., 2007, Climatic Change, DOI 10.1007

  13. Classification of rain events based on intensities Gamma Cumulative Distribution Function was fitted to the daily rainfall values to categorise the rain events in different groups. The classification is made as follows Heavy : Inverse of gamma CDF for probability ≥ 0.99 Moderate : Inverse of gamma CDF for probabilities lie between ≥ 0.4 & <0.99 Low : Inverse of gamma CDF for probability < 0.4

  14. Characteristics of rain events based on duration of spells Long Spell: Consecutive rainfall for ≥ 4 days Short Spell: Consecutive rainfall for less than 4 days Dry Spell: <2.5mm/day Prolonged Dry Spell : consecutively dry for ≥ 4 days

  15. Monsoon Winter Pre-Monsoon The number of long spell rainfall events shows decreasing trend in monsoon season in last 54 years. This suggests that planetary scale motions, may be southwest monsoon over the country is weakening. Annual Post-Monsoon Number of long spell rain events. Continuous rainfall for ≥4 days over all India in different seasons. The red line is linear trend line. Dash et al. 2009 J. Geophys. Res. Vol. 114

  16. Winter Pre-Monsoon Annual Monsoon Post-Monsoon Number of short spell rain events (Continuous rainfall for < 4 days) over all India in different seasons. The red line is linear trend line. Short spell rainfall events over India show increasing trend. This is an indication of increasing or intensifying of meso-scale conventions and synoptic scale motions. Dash et al. 2009 J. Geophys. Res. Vol. 114

  17. Summary of trends in heavy and moderate rain events in different Indian regions for the summer monsoon season. Asterisks denote significant trend at 5% level. Dash et al. 2009 J. Geophys. Res. Vol.114

  18. Summary of trends in long, short, dry and prolonged dry spells of rainfall in different Indian regions for the monsoon season. Asterisks denote significant trend at 5% level. Dash et al. 2009 J. Geophys. Res. Vol.114

  19. Some inferences on rain events • Heavy rain events increase and moderate & low events decrease • Short & dry spells increase and long spells decrease • Trends not statistically significant in all zones • Weakening of monsoon circulation?

  20. Difference between the 850hPa mean monsoonal wind speeds in the two decades (1991-2000) and (1951-1960). The shaded region shows the significant change calculated using t test at 5% level. Dash et al. 2009 J. Geophys. Res. Vol.114

  21. (a) (b) Eleven-year running means of annual frequency of disturbances with the minimum intensity of (a) monsoon depressions and (b) low pressure areas over the Indian region (1889-2003) Dash et al., 2004, Current Science,86(10), 1404-1411.

  22. (a) Latitudinal variation of zonal wind component in July over Indian region between 550E-950E a)850 hPa b)200 hPa (b) Dash et al., 2004, Current Science,86(10), 1404-1411.

  23. (a) 11-year running means of anomalies of horizontal wind shear at 850hPa in August between latitudes 00 and 250 N averaged over longitudes 550E to 950E. (a) (b) 11-year running means of vertical wind shear anomalies in August between 850&200 hPa levels averaged over the Indian region 00 to 250 N and 550E to 950E. (b) Dash et al., 2004, Current Science,86(10), 1404-1411.

  24. Further Classification of Rain Events • HL: High intensity Long spell • ML: Moderate intensity Long spell • LL: Low intensity Long spell • HS: High intensity Short spell • MS: Moderate intensity Short spell • LS: Low intensity Short spell

  25. Trends in heavy-intensity long spell (HL), heavy-intensity short spell (HS), moderate-intensity long spell (ML), moderate-intensity short spell (MS), low-intensity long spell (LL), and low-intensity short spell (LS) in different regions Dash et al., 2011, Theor Appl Climato,

  26. Climate models with affiliated country, their surface resolution, incorporated convection schemes and key references CCSM3 (Community Climate System Model, version 3, USA, NCAR) ECHAM5 (European Centre for Medium Range Weather Forecasts and Max Planck Institute for Meteorology in Hamburg version 5, Germany) GFDL-CM2.1 (Geophysical Fluid Dynamics Laboratory Coupled Model, version 2.1, US Department of commerce, NOAA) AS- Arakawa-Schubert, MF-Mass Flux, RAS- Relaxed Arakawa-Schubert

  27. (b) CCSM3 (c) ECHAM5 (d) GFDL 2.1 Future projected changes in mean JJA wind (m/s) at 850hPa in JJA during 2011-2040 w. r. t. 1961-1990 under A2 scenario

  28. Vertical shear (U200-U850) of zonal wind (m/s) in the box 5o-15oN, 40o-70oE

  29. (c) ECHAM5 (b) CCSM3 (d) GFDL 2.1 Future projected changes in mean JJA rainfall (mm/day) during 2011-2040 w. r. t. 1961-1990 under A2 scenario

  30. Schematic diagram showing the snow line and height • of tropopause in • Normal atmosphere and • Warmer atmosphere. Dash and Hunt, 2007, Current Science, Vol 93

  31. Seasonal mean anomalies (DJF) associated with maximum, minimum and daily mean temperatures (with trend line) at Gulmarg

  32. Seasonal mean anomalies (DJF) associated with precipitation along with excess and deficit values based on ± 0.10 standard deviation at Gulmarg

  33. Trends and P values for temperature and precipitation indices __________________________________________________________________________________ A1 A2 A3 34°11′49″N, 34°59′32″N, 35°34′55″N, 77°12′28″E, 3570 m 76°57′14″E, 5215 m 76°47′32″E, 5995 m _________________ ________________ ________________ Temperature Precipitation Indices Trend P(trend) Trend P(trend) Trend P(trend) __________________________________________________________________________________ Warm days 0.0122 0.0384* 0.0182 0.0001* 0.0045 0.0317* Warm nights 0.0084 0.6394 0.0253 0.0006* – 0.01 0.0176* Cold days 0.0065 0.5214 0.0069 0.002* – 0.0045 0.0309* Cold nights 0.0109 0.0017* 0.0084 0.0041* – 0.0028 0.1812 Mean climatological 0.0297 0.1578 – 0.0731 0.0009* – 0.0183 0.2968 Precipitation Heavy precipitation 0.3893 0.2727 – 0.3626 0.0005* – 0.0383 0.3061 Days Maximum number – 0.0102 0.8364 0.7461 0.0006* 0.2641 0.5073 Of consecutive dry days Maximum number 1.2246 0.465 – 5.3202 0.0007* – 0.0351 0.0345* of consecutive wet days __________________________________________________________________________________ Dimri and Dash (2010) Curr. Sc.

  34. Applications in Agriculture & Health

  35. Palampur Pantnagar Jodhpur Jabalpur Anand Bhubanswar Akola Rajendranagar Coimbatore ERFS Project Agricultural Universities

  36. Decadal variations in the numbers of heavy, moderate, and low rain days in agro-met divisions Dash et al., 2011, Theor Appl Climato,

  37. Trends in the contributions of heavy, moderate, and low-intensity rainfall categories to total respective rainfall in All India, homogeneous zones, and agro-met divisions Dash et al., 2011, Theor Appl Climato,

  38. Contributions of different spells of rain to total summer monsoon rainfall Dash et al., 2011, Theor Appl Climato,

  39. Percentage changes in various categories of long and short spells in the decade 1991–2000 compared with the 1951–1960 decade Dash et al., 2011, Theor Appl Climato,

  40. Some rainfall facts for Agriculture • High intensity Short spells increase and Moderate and Low intensity Long spells decrease. • Contribution of Moderate Long spells to total rain decreases and Moderate Short spells increases. • Contribution of Heavy categories to total rain increases and that of Moderate decreases.

  41. 18.00 16.00 14.00 12.00 Series1 10.00 8.00 Series2 6.00 4.00 2.00 0.00 1960-79 1980s 1990s 2000s Decade Number of workable days Fully workable days out of 30 by decade at Delhi in the month of June. (Series 1 is heavy labour; Series 2 is light factory work)

  42. Climate change in cities • Numerouscities in South and Southeast Asia are highly vulnerable to climate change. • In India, the expected increase in extreme rainfall events and changes to seasonal monsoon patterns will increase the risk of major floods and the likelihood of drought, with severe consequences for the health and livelihoods of millions of people.

  43. Climate change in cities objectives (1) to identify generic climate change parameters in four selected cities in India and (2) to scientifically contribute in the local climate adaptation plans. • The four selected cities in India are Howrah, Kochi, Madurai and Visakhapatnam. • For each of the above cities its local indicators for climate change adaptation are being developed.

  44. Model Simulations

  45. Central Lat and Long 20oN, 80oE • 99 x 118 points along x-y direction • Domain covers 51o E to 109o E and 3oS to 43oN with 55 km grid distance Model domain used in RegCM3 simulations

  46. Percentage difference in JJAS precipitation between RegCM3 and Observations RegCM3-IMD RegCM3-CRU RegCM3-APHRODITE RegCM3-CMAP RegCM3-GPCP Dash et al. 2011. Spatial and temporal variations of Indian summer monsoon: An analysis of RegCM3 simulations

  47. July June August September JJAS Correlation Coefficients between RegCM3 and IMD observed ensemble mean monsoon rainfall for the period 1982-2009 spanning 28 years. The contours are obtained with 9 point smoothing to the gridded result.

  48. CC 0.53* RMSE 3.40 JUNE CC 0.67* RMSE 3.90 JULY CC 0.61* RMSE 3.18 CC 0.15 RMSE 5.44 AUGUSTT SEPTEMBER Rainfall (cm) CC 0.50* RMSE 10.02 Inter-annual variations in precipitation simulated by RegCM3 *Significant at 0.05 level JJAS Years

  49. 2003 good monsoon 2002 weak monsoon RegCM3 IMD Monsoon active spells (blue circle) and break spells (red circles) in the contrasting monsoon years are shown over central India (15-25oN, 75-85oE), the monsoon core zone. Standardized Anomaly

  50. (a) North West India (70-80oE and 25-30oN) RegCM3 IMD (b) Central India (75-85oE and 15-25oN) IMD RegCM3 (c) Peninsular India (75-85oE and 09-15oN) IMD RegCM3 Rainfall (mm) Frequency distribution of area weighted average daily rainfall from June to September in domain of (a) North West 70-80oE and 25-30oN, (b) Central India 75-85oE and 15-25oN and (c) Peninsular India 75-85oE and 09-15oN. The smooth curves are obtained using 5-point binomial filter. Frequency

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