SlideShare a Scribd company logo
1 of 23
Download to read offline
Extreme Weather Events in Nepal:
Trends and Projections
Nicky Shree Shrestha
The Small Earth Nepal, Kathmandu University
Piyush Dahal
The Small Earth Nepal
The Changing Climate
The Changing Climate
Devastating Natural Disasters
CLIMATOLOGICAL NON-CLIMATOLOGICAL
Distribution of Natural Disasters of Nepal
AVALANCHE COLD WAVE DROUGHT
FAMINE FLOOD FOREST FIRE
FROST HAIL STORM HEAT WAVE
LANDSLIDE RAINS SNOW STORM
STORM STRONG WIND THUNDERSTORM
Distribution of Major Climatological Disasters of Nepal
Looking at the past climate extremes
Looking at the past climate extremes
Looking at the past climate extremes
Looking at the past climate extremes
• Catchment area-32104
km2
• 12 districts (entire) and
7 (partial)
• Altitude-88 to 8148
masl
• Mean annual
temperature-3.1 to
30.9OC.
• 16% area is covered by
snow and ice and water
bodies.
• Around 40% of the is
covered by agricultural
land.
A Case Study of the Gandaki River Basin, Nepal
• DHM, Government of
Nepal.
• Temperature -5 stations
• Precipitation-20
stations
• Data sets from year
1981 to 2012 (above 30
years).
Data Sources
Station
No.
Altitude
(m) SU25 TXx TXn TNn TNx TX10P TX90P TN10P TN90P
601 2744 -0.225 -0.027 0 0.137 0.06 0.106 -0.003 -0.338 0.251
604 2566 0.003 -0.009 0.005 -0.034 -0.007 -0.175 0.321 0.046 -0.142
906 868 0.662 0.016 0.072 0.005 -0.057 -0.406 0.389 -0.031 -0.006
1007 474 0.324 0.020 0.041 0.102 0.03 -0.222 0.169 -0.565 0.393
1038 1085 0.416 -0.034 -0.051 0.012 0.044 -0.153 0.016 -0.381 0.155
Average 0.236 -0.007 0.013 0.044 0.014 -0.170 0.178 -0.254 0.130
No. of Stations with
positive trend 4 2 4 4 3 1 4 1 3
No. of Stations with
negative trend 1 3 1 1 2 4 1 4 2
Station
No.
Altitude
(m) WSDI CSDI DTR
TMAX
Mean
TMIN
Mean TR15 TR20
601 2744 0.184 -0.246 -0.054 -0.004 0.051 0.246 0
604 2566 0.525 -0.524 0.044 0.031 -0.018 -0.065 0
906 868 0.33 0.438 0.051 0.057 0.007 0.496 -0.077
1007 474 0.326 -0.97 -0.037 0.019 0.054 1.899 0
1038 1085 -0.2 -0.463 -0.017 0.015 0.033 0.449 0.994
Average 0.233 -0.353 -0.0026 0.0236 0.0254 0.605 0.1834
No. of Stations with
positive trend 4 1 2 4 4 4 4
No. of Stations with
negative trend 1 4 3 1 1 1 1
Temperature Indices
0
500
1000
1500
2000
2500
3000
-0.8 -0.6 -0.4 -0.2 0 0.2 0.4 0.6
Elevation(m)
Percentage of days/year
Cool Nights
Warm Nights
0
500
1000
1500
2000
2500
3000
-0.6 -0.4 -0.2 0 0.2 0.4 0.6
Elevation(m)
Percentage of days/year
Cool Days
Warm Days
Trend in cool and warm nights
with elevation
Trend in cool and warm days with
elevation
Temperature Indices
0
500
1000
1500
2000
2500
3000
-1.5 -1 -0.5 0 0.5 1
Elevation(m)
Annual count (days)/year
CSDI
WSDI
0
500
1000
1500
2000
2500
3000
-0.4 -0.2 0 0.2 0.4 0.6 0.8
Elevation(m)
Annual count (days)/year
SU25
Trend in CSDI and WSDI with elevation
Trend in summer days (SU25) with
elevation
Temperature Indices
Station
No. CDD CWD PRCPTOT R10 mm R20 mm R50 mm R95p R99p RX1day RX5day SDII
613 0.931 -0.116 0.504 0.06 -0.031 -0.069 -4.02 1.281 0.503 -0.44 -0.027
614 0.368 0.104 -5.013 -0.056 -0.168 -0.059 -3.595 0.397 0.041 0.041 -0.064
701 1.154 0.033 -15.815 -0.529 -0.329 -0.103 -1.662 3.311 0.808 -0.4 -0.101
704 1.718 -0.13 -0.211 -0.173 -0.014 0.049 4.525 1.467 -0.221 2.554 0.242
725 1.093 -0.047 -5.974 -0.262 -0.113 -0.016 1.121 1.495 0.546 -0.513 0.029
802 0.892 -0.232 -0.177 -0.08 0.087 -0.026 -0.727 -3.61 -0.849 -1.121 0.017
805 1.538 0.114 10.022 -0.086 0.01 0.137 13.435 6.341 1.292 2.189 0.045
807 1.245 -0.071 10.469 0.252 0.181 0.158 9.87 0.504 0.691 2.083 0.215
808 0.628 0.237 -3.71 -0.407 0.017 0.008 0.885 2.623 0.296 0.101 -0.051
810 1.29 0.083 -8.5 -0.1 -0.12 -0.095 -4.873 -2.769 -1.807 -3.241 -0.172
814 0.431 0.802 7.61 -0.038 0.032 0.079 11.601 5.859 -0.469 -1.343 0.112
815 0.941 0.066 -10.275 -0.006 -0.212 -0.14 -1.474 0.558 0.208 1.07 -0.096
824 0.594 -0.284 2.456 -0.079 0.22 0.085 3.365 -1.925 0.106 -0.198 0.074
903 1.373 -0.261 5.449 -0.249 0.025 0.093 10.357 4.743 1.596 2.142 0.069
904 1.749 -0.293 -3.698 -0.296 -0.079 0.063 5.292 1.258 0.292 2.446 0.075
906 0.588 -0.096 5.082 0.015 -0.054 0.076 10.458 4.273 1.203 3.471 0.109
920 1.222 -0.511 -5.821 -0.359 -0.047 0.066 3.191 -0.256 -0.721 -0.211 0.124
1007 2.808 0.351 -14.923 -0.25 -0.275 -0.147 -9.623 -0.855 -0.584 -1.106 -0.151
1038 0.45 -0.037 5.366 0.254 0.137 0.027 0.519 -2.744 -1.1 -0.168 0.017
1054 2.059 -0.821 -13.247 -0.562 -0.009 0.001 2.915 7.208 -0.317 -0.955 -0.014
Average 1.154 -0.056 -2.0203 -0.14755 -0.0371 0.00935 2.578 1.45795 0.0757 0.32005 0.0226
Stations
with
positive
trend 20 8 8 3 8 12 13 14 12 9 12
Stations
with
negative
trend 0 12 12 17 12 8 7 6 8 11 8
Precipitation Indices
0
500
1000
1500
2000
2500
-6 -4 -2 0 2 4 6 8
Elevation(m)
Trend (mm/year)
R99p
R99p
0
500
1000
1500
2000
2500
-0.8 -0.6 -0.4 -0.2 0 0.2 0.4
Elevation(m)
Trend (mm/year)
R10 mm
R10
Trend in R99P (extremely
wet days) with elevation
Trend in R10 (No. of heavy
precipitation days) with elevation
Precipitation Indices
0
500
1000
1500
2000
2500
-20 -15 -10 -5 0 5 10 15
Elevation(m)
Trend (mm/year)
PRCPTOT
PRCPTOT
0
500
1000
1500
2000
2500
0 0.5 1 1.5 2 2.5 3
Elevation(m)
Trend (mm/year)
CDD
CDD
Trend in CDD with elevation
Trend in PRCPTOT (wet day
precipitation) with elevation
Precipitation Indices
Future projection of extremes events
Future (2041-2071) projection of change (%) in Consecutive dry days with baseline 1970-1999
Trend in CDD with elevation
Future projection of extremes events
Future (2041-2071) projection of change (%) in wet days index with baseline 1970-1999
Future projection of extremes events
Future (2041-2071) projection of change (%) in highest one day rainfall with baseline 1970-1999
Trend in CDD with elevation
Future projection of extremes events
Future (2041-2071) projection of change (%) in consecutive wet days with baseline 1970-1999
Conclusion
Warming trend of temperature.
No distinct trends of precipitation but the extreme precipitation events are
increasing.
Consecutive dry days are increasing and are more pronounced in the higher
altitude.
In future, the wet days index is projected to increase in the lowland Terai but
decrease in the higher altitude.
Acknowledgement
This study is a part of research project “Climate Change Adaptation for
Livestock Smallholders in Gandaki River Basin Nepal” and is
supported by USAID Feed the Future Innovation Lab for
Collaborative Research on Adapting Livestock Systems to
Climate Change.
THANK YOU

More Related Content

Similar to Nicky shree shrestha

Response of Low Grown Tea to Irrigation in Sri Lanka
Response of Low Grown Tea to Irrigation in Sri LankaResponse of Low Grown Tea to Irrigation in Sri Lanka
Response of Low Grown Tea to Irrigation in Sri LankaShyamantha BANDARA
 
REPORT SURVEY LEVELLING CIVIL ENGINEERING.pdf
REPORT SURVEY LEVELLING CIVIL ENGINEERING.pdfREPORT SURVEY LEVELLING CIVIL ENGINEERING.pdf
REPORT SURVEY LEVELLING CIVIL ENGINEERING.pdfMuhammadMuazzam16
 
Barind nw bangladesh drought gw and adaptation
Barind nw bangladesh drought gw and adaptationBarind nw bangladesh drought gw and adaptation
Barind nw bangladesh drought gw and adaptationJaminur Rahman
 
Extreme value distribution to predict maximum precipitation
Extreme value distribution to predict maximum precipitationExtreme value distribution to predict maximum precipitation
Extreme value distribution to predict maximum precipitationJonathan D'Cruz
 
THEME – 2 Identifying climate patterns during the crop growing cycle from 30 ...
THEME – 2 Identifying climate patterns during the crop growing cycle from 30 ...THEME – 2 Identifying climate patterns during the crop growing cycle from 30 ...
THEME – 2 Identifying climate patterns during the crop growing cycle from 30 ...ICARDA
 
Peramalan Data Time Series #2
Peramalan Data Time Series #2Peramalan Data Time Series #2
Peramalan Data Time Series #2Adhitya Akbar
 
Market Analysis MGF Futures 16 april 2014
Market Analysis MGF Futures 16 april 2014 Market Analysis MGF Futures 16 april 2014
Market Analysis MGF Futures 16 april 2014 MegagrowthFutures
 
Finite element analysis and experimental investigations
Finite element analysis and experimental investigationsFinite element analysis and experimental investigations
Finite element analysis and experimental investigationsiaemedu
 
Finite element analysis and experimental investigations on small size wind tu...
Finite element analysis and experimental investigations on small size wind tu...Finite element analysis and experimental investigations on small size wind tu...
Finite element analysis and experimental investigations on small size wind tu...iaemedu
 
Smart Utilities 2012 - Peak Demand
Smart Utilities 2012 - Peak DemandSmart Utilities 2012 - Peak Demand
Smart Utilities 2012 - Peak DemandDr Robert Simpson
 
Tablas normal chi cuadrado y t student 1-semana 6
Tablas normal chi cuadrado y t student 1-semana 6Tablas normal chi cuadrado y t student 1-semana 6
Tablas normal chi cuadrado y t student 1-semana 6Karla Diaz
 
ai232_presentation_copy
ai232_presentation_copyai232_presentation_copy
ai232_presentation_copyAlannah Irwin
 
Jeeban panthi
Jeeban panthiJeeban panthi
Jeeban panthiClimDev15
 
Hasil perhitungan Orifice Gas
Hasil perhitungan Orifice GasHasil perhitungan Orifice Gas
Hasil perhitungan Orifice GasGGM Spektafest
 

Similar to Nicky shree shrestha (20)

Response of Low Grown Tea to Irrigation in Sri Lanka
Response of Low Grown Tea to Irrigation in Sri LankaResponse of Low Grown Tea to Irrigation in Sri Lanka
Response of Low Grown Tea to Irrigation in Sri Lanka
 
Msc Thesis Final1
Msc Thesis Final1Msc Thesis Final1
Msc Thesis Final1
 
REPORT SURVEY LEVELLING CIVIL ENGINEERING.pdf
REPORT SURVEY LEVELLING CIVIL ENGINEERING.pdfREPORT SURVEY LEVELLING CIVIL ENGINEERING.pdf
REPORT SURVEY LEVELLING CIVIL ENGINEERING.pdf
 
Barind nw bangladesh drought gw and adaptation
Barind nw bangladesh drought gw and adaptationBarind nw bangladesh drought gw and adaptation
Barind nw bangladesh drought gw and adaptation
 
Extreme value distribution to predict maximum precipitation
Extreme value distribution to predict maximum precipitationExtreme value distribution to predict maximum precipitation
Extreme value distribution to predict maximum precipitation
 
THEME – 2 Identifying climate patterns during the crop growing cycle from 30 ...
THEME – 2 Identifying climate patterns during the crop growing cycle from 30 ...THEME – 2 Identifying climate patterns during the crop growing cycle from 30 ...
THEME – 2 Identifying climate patterns during the crop growing cycle from 30 ...
 
6 g wadi network for see-zlatanović&dimkić
6 g wadi network for see-zlatanović&dimkić6 g wadi network for see-zlatanović&dimkić
6 g wadi network for see-zlatanović&dimkić
 
Peramalan Data Time Series #2
Peramalan Data Time Series #2Peramalan Data Time Series #2
Peramalan Data Time Series #2
 
Market Analysis MGF Futures 16 april 2014
Market Analysis MGF Futures 16 april 2014 Market Analysis MGF Futures 16 april 2014
Market Analysis MGF Futures 16 april 2014
 
Finite element analysis and experimental investigations
Finite element analysis and experimental investigationsFinite element analysis and experimental investigations
Finite element analysis and experimental investigations
 
Finite element analysis and experimental investigations on small size wind tu...
Finite element analysis and experimental investigations on small size wind tu...Finite element analysis and experimental investigations on small size wind tu...
Finite element analysis and experimental investigations on small size wind tu...
 
Smart Utilities 2012 - Peak Demand
Smart Utilities 2012 - Peak DemandSmart Utilities 2012 - Peak Demand
Smart Utilities 2012 - Peak Demand
 
Jhon
JhonJhon
Jhon
 
Tablas normal chi cuadrado y t student 1-semana 6
Tablas normal chi cuadrado y t student 1-semana 6Tablas normal chi cuadrado y t student 1-semana 6
Tablas normal chi cuadrado y t student 1-semana 6
 
ai232_presentation_copy
ai232_presentation_copyai232_presentation_copy
ai232_presentation_copy
 
Jeeban panthi
Jeeban panthiJeeban panthi
Jeeban panthi
 
Hasil perhitungan Orifice Gas
Hasil perhitungan Orifice GasHasil perhitungan Orifice Gas
Hasil perhitungan Orifice Gas
 
736.500Tunnel As.pdf
736.500Tunnel As.pdf736.500Tunnel As.pdf
736.500Tunnel As.pdf
 
Power to voltage
Power to voltagePower to voltage
Power to voltage
 
Change Point Analysis (CPA)
Change Point Analysis (CPA)Change Point Analysis (CPA)
Change Point Analysis (CPA)
 

More from ClimDev15

Nir y. krakauer
Nir y. krakauerNir y. krakauer
Nir y. krakauerClimDev15
 
Gerald spreitzhofer
Gerald spreitzhoferGerald spreitzhofer
Gerald spreitzhoferClimDev15
 
Dibas shrestha
Dibas shresthaDibas shrestha
Dibas shresthaClimDev15
 
Anita khadka
Anita khadkaAnita khadka
Anita khadkaClimDev15
 
Md. abu hanif
Md. abu hanifMd. abu hanif
Md. abu hanifClimDev15
 
Gokarna jung thapa
Gokarna jung thapaGokarna jung thapa
Gokarna jung thapaClimDev15
 
Bhawani s. dongol
Bhawani s. dongolBhawani s. dongol
Bhawani s. dongolClimDev15
 
Sarah mc kune
Sarah mc kuneSarah mc kune
Sarah mc kuneClimDev15
 
Smrittee kala panta
Smrittee kala pantaSmrittee kala panta
Smrittee kala pantaClimDev15
 
Praju gurung
Praju gurungPraju gurung
Praju gurungClimDev15
 
Netra p. osti
Netra p. ostiNetra p. osti
Netra p. ostiClimDev15
 
Md. monowar hossain ronee
Md. monowar hossain roneeMd. monowar hossain ronee
Md. monowar hossain roneeClimDev15
 
Dinesh pandey
Dinesh pandeyDinesh pandey
Dinesh pandeyClimDev15
 
Soni m pradhanang
Soni m pradhanangSoni m pradhanang
Soni m pradhanangClimDev15
 
Prakash tiwari
Prakash tiwariPrakash tiwari
Prakash tiwariClimDev15
 
Narayan prasad gaire
Narayan prasad gaireNarayan prasad gaire
Narayan prasad gaireClimDev15
 
M. levent kurnaz
M. levent kurnazM. levent kurnaz
M. levent kurnazClimDev15
 

More from ClimDev15 (20)

Nir y. krakauer
Nir y. krakauerNir y. krakauer
Nir y. krakauer
 
Gerald spreitzhofer
Gerald spreitzhoferGerald spreitzhofer
Gerald spreitzhofer
 
Dibas shrestha
Dibas shresthaDibas shrestha
Dibas shrestha
 
Anita khadka
Anita khadkaAnita khadka
Anita khadka
 
Rinku verma
Rinku vermaRinku verma
Rinku verma
 
Md. abu hanif
Md. abu hanifMd. abu hanif
Md. abu hanif
 
Gokarna jung thapa
Gokarna jung thapaGokarna jung thapa
Gokarna jung thapa
 
Bhawani s. dongol
Bhawani s. dongolBhawani s. dongol
Bhawani s. dongol
 
Sarah mc kune
Sarah mc kuneSarah mc kune
Sarah mc kune
 
Smrittee kala panta
Smrittee kala pantaSmrittee kala panta
Smrittee kala panta
 
Praju gurung
Praju gurungPraju gurung
Praju gurung
 
Metthew
MetthewMetthew
Metthew
 
Madhav giri
Madhav giriMadhav giri
Madhav giri
 
Netra p. osti
Netra p. ostiNetra p. osti
Netra p. osti
 
Md. monowar hossain ronee
Md. monowar hossain roneeMd. monowar hossain ronee
Md. monowar hossain ronee
 
Dinesh pandey
Dinesh pandeyDinesh pandey
Dinesh pandey
 
Soni m pradhanang
Soni m pradhanangSoni m pradhanang
Soni m pradhanang
 
Prakash tiwari
Prakash tiwariPrakash tiwari
Prakash tiwari
 
Narayan prasad gaire
Narayan prasad gaireNarayan prasad gaire
Narayan prasad gaire
 
M. levent kurnaz
M. levent kurnazM. levent kurnaz
M. levent kurnaz
 

Nicky shree shrestha

  • 1. Extreme Weather Events in Nepal: Trends and Projections Nicky Shree Shrestha The Small Earth Nepal, Kathmandu University Piyush Dahal The Small Earth Nepal
  • 4. Devastating Natural Disasters CLIMATOLOGICAL NON-CLIMATOLOGICAL Distribution of Natural Disasters of Nepal AVALANCHE COLD WAVE DROUGHT FAMINE FLOOD FOREST FIRE FROST HAIL STORM HEAT WAVE LANDSLIDE RAINS SNOW STORM STORM STRONG WIND THUNDERSTORM Distribution of Major Climatological Disasters of Nepal
  • 5. Looking at the past climate extremes
  • 6. Looking at the past climate extremes
  • 7. Looking at the past climate extremes
  • 8. Looking at the past climate extremes
  • 9. • Catchment area-32104 km2 • 12 districts (entire) and 7 (partial) • Altitude-88 to 8148 masl • Mean annual temperature-3.1 to 30.9OC. • 16% area is covered by snow and ice and water bodies. • Around 40% of the is covered by agricultural land. A Case Study of the Gandaki River Basin, Nepal
  • 10. • DHM, Government of Nepal. • Temperature -5 stations • Precipitation-20 stations • Data sets from year 1981 to 2012 (above 30 years). Data Sources
  • 11. Station No. Altitude (m) SU25 TXx TXn TNn TNx TX10P TX90P TN10P TN90P 601 2744 -0.225 -0.027 0 0.137 0.06 0.106 -0.003 -0.338 0.251 604 2566 0.003 -0.009 0.005 -0.034 -0.007 -0.175 0.321 0.046 -0.142 906 868 0.662 0.016 0.072 0.005 -0.057 -0.406 0.389 -0.031 -0.006 1007 474 0.324 0.020 0.041 0.102 0.03 -0.222 0.169 -0.565 0.393 1038 1085 0.416 -0.034 -0.051 0.012 0.044 -0.153 0.016 -0.381 0.155 Average 0.236 -0.007 0.013 0.044 0.014 -0.170 0.178 -0.254 0.130 No. of Stations with positive trend 4 2 4 4 3 1 4 1 3 No. of Stations with negative trend 1 3 1 1 2 4 1 4 2 Station No. Altitude (m) WSDI CSDI DTR TMAX Mean TMIN Mean TR15 TR20 601 2744 0.184 -0.246 -0.054 -0.004 0.051 0.246 0 604 2566 0.525 -0.524 0.044 0.031 -0.018 -0.065 0 906 868 0.33 0.438 0.051 0.057 0.007 0.496 -0.077 1007 474 0.326 -0.97 -0.037 0.019 0.054 1.899 0 1038 1085 -0.2 -0.463 -0.017 0.015 0.033 0.449 0.994 Average 0.233 -0.353 -0.0026 0.0236 0.0254 0.605 0.1834 No. of Stations with positive trend 4 1 2 4 4 4 4 No. of Stations with negative trend 1 4 3 1 1 1 1 Temperature Indices
  • 12. 0 500 1000 1500 2000 2500 3000 -0.8 -0.6 -0.4 -0.2 0 0.2 0.4 0.6 Elevation(m) Percentage of days/year Cool Nights Warm Nights 0 500 1000 1500 2000 2500 3000 -0.6 -0.4 -0.2 0 0.2 0.4 0.6 Elevation(m) Percentage of days/year Cool Days Warm Days Trend in cool and warm nights with elevation Trend in cool and warm days with elevation Temperature Indices
  • 13. 0 500 1000 1500 2000 2500 3000 -1.5 -1 -0.5 0 0.5 1 Elevation(m) Annual count (days)/year CSDI WSDI 0 500 1000 1500 2000 2500 3000 -0.4 -0.2 0 0.2 0.4 0.6 0.8 Elevation(m) Annual count (days)/year SU25 Trend in CSDI and WSDI with elevation Trend in summer days (SU25) with elevation Temperature Indices
  • 14. Station No. CDD CWD PRCPTOT R10 mm R20 mm R50 mm R95p R99p RX1day RX5day SDII 613 0.931 -0.116 0.504 0.06 -0.031 -0.069 -4.02 1.281 0.503 -0.44 -0.027 614 0.368 0.104 -5.013 -0.056 -0.168 -0.059 -3.595 0.397 0.041 0.041 -0.064 701 1.154 0.033 -15.815 -0.529 -0.329 -0.103 -1.662 3.311 0.808 -0.4 -0.101 704 1.718 -0.13 -0.211 -0.173 -0.014 0.049 4.525 1.467 -0.221 2.554 0.242 725 1.093 -0.047 -5.974 -0.262 -0.113 -0.016 1.121 1.495 0.546 -0.513 0.029 802 0.892 -0.232 -0.177 -0.08 0.087 -0.026 -0.727 -3.61 -0.849 -1.121 0.017 805 1.538 0.114 10.022 -0.086 0.01 0.137 13.435 6.341 1.292 2.189 0.045 807 1.245 -0.071 10.469 0.252 0.181 0.158 9.87 0.504 0.691 2.083 0.215 808 0.628 0.237 -3.71 -0.407 0.017 0.008 0.885 2.623 0.296 0.101 -0.051 810 1.29 0.083 -8.5 -0.1 -0.12 -0.095 -4.873 -2.769 -1.807 -3.241 -0.172 814 0.431 0.802 7.61 -0.038 0.032 0.079 11.601 5.859 -0.469 -1.343 0.112 815 0.941 0.066 -10.275 -0.006 -0.212 -0.14 -1.474 0.558 0.208 1.07 -0.096 824 0.594 -0.284 2.456 -0.079 0.22 0.085 3.365 -1.925 0.106 -0.198 0.074 903 1.373 -0.261 5.449 -0.249 0.025 0.093 10.357 4.743 1.596 2.142 0.069 904 1.749 -0.293 -3.698 -0.296 -0.079 0.063 5.292 1.258 0.292 2.446 0.075 906 0.588 -0.096 5.082 0.015 -0.054 0.076 10.458 4.273 1.203 3.471 0.109 920 1.222 -0.511 -5.821 -0.359 -0.047 0.066 3.191 -0.256 -0.721 -0.211 0.124 1007 2.808 0.351 -14.923 -0.25 -0.275 -0.147 -9.623 -0.855 -0.584 -1.106 -0.151 1038 0.45 -0.037 5.366 0.254 0.137 0.027 0.519 -2.744 -1.1 -0.168 0.017 1054 2.059 -0.821 -13.247 -0.562 -0.009 0.001 2.915 7.208 -0.317 -0.955 -0.014 Average 1.154 -0.056 -2.0203 -0.14755 -0.0371 0.00935 2.578 1.45795 0.0757 0.32005 0.0226 Stations with positive trend 20 8 8 3 8 12 13 14 12 9 12 Stations with negative trend 0 12 12 17 12 8 7 6 8 11 8 Precipitation Indices
  • 15. 0 500 1000 1500 2000 2500 -6 -4 -2 0 2 4 6 8 Elevation(m) Trend (mm/year) R99p R99p 0 500 1000 1500 2000 2500 -0.8 -0.6 -0.4 -0.2 0 0.2 0.4 Elevation(m) Trend (mm/year) R10 mm R10 Trend in R99P (extremely wet days) with elevation Trend in R10 (No. of heavy precipitation days) with elevation Precipitation Indices
  • 16. 0 500 1000 1500 2000 2500 -20 -15 -10 -5 0 5 10 15 Elevation(m) Trend (mm/year) PRCPTOT PRCPTOT 0 500 1000 1500 2000 2500 0 0.5 1 1.5 2 2.5 3 Elevation(m) Trend (mm/year) CDD CDD Trend in CDD with elevation Trend in PRCPTOT (wet day precipitation) with elevation Precipitation Indices
  • 17. Future projection of extremes events Future (2041-2071) projection of change (%) in Consecutive dry days with baseline 1970-1999
  • 18. Trend in CDD with elevation Future projection of extremes events Future (2041-2071) projection of change (%) in wet days index with baseline 1970-1999
  • 19. Future projection of extremes events Future (2041-2071) projection of change (%) in highest one day rainfall with baseline 1970-1999
  • 20. Trend in CDD with elevation Future projection of extremes events Future (2041-2071) projection of change (%) in consecutive wet days with baseline 1970-1999
  • 21. Conclusion Warming trend of temperature. No distinct trends of precipitation but the extreme precipitation events are increasing. Consecutive dry days are increasing and are more pronounced in the higher altitude. In future, the wet days index is projected to increase in the lowland Terai but decrease in the higher altitude.
  • 22. Acknowledgement This study is a part of research project “Climate Change Adaptation for Livestock Smallholders in Gandaki River Basin Nepal” and is supported by USAID Feed the Future Innovation Lab for Collaborative Research on Adapting Livestock Systems to Climate Change.