RCM data as input for hydrological modelling, Correction method of RCM data Uldis Bethers, Juris Sennikovs, Andrejs Timuhins Laboratory for mathematical modelling of environmental and technological processes Faculty of Physics and mathematics, Unive

1
Impact of climate change on Baltic resorts
Uldis Bethers, Juris Sennikovs Laboratory for
mathematical modelling of environmental and
technological processesFaculty of Physics and
mathematicsUniversity of Latvia
2
GLOBAL CLIMATE CHANGE SCENARIOUS
Intergovernmental Panel on Climate Change (IPCC)
by the World Meteorological Organization (WMO)
and the United Nations Environment Programme
(UNEP)
3
Choice of RCM
Global scenario
Global climate model
Regional climate model
PRUDENCE - EU FP5 project to assess and evaluate
European RCMs. PRUDENCE provides access to
modelling results by 22 European RCM for
contemporary climate (reference period,
1961-1990) and climate change scenarios
(2071-2100)
4
Comparison of RCM vs. observations indicates SMHI
model most suitable for our region
5
Data used in this presentation

• National research programme Impact of climate
  change on Latvian water environment (2006-2009).
  WP1 Scenarious and modelling. In 2007
• Evaluation of RCM data
• Method of RCM data correction
• Three long-term climatic data sets for Latvia
• Contemporary climate (1961-1990)
• Climate change scenario B2 (2071-2100)
• Climate change scenario A2 (2071-2100)
• Temperature and precipitation data used for
  analysis in this presentation
• Monthly means and their interannual variability
  considered

6
Monthly average temperatures
Jurmala
7
Increase of average monthly temperatures
Difference A2-REF
8
Monthly average precipitation
Jurmala
9
Change of monthly average precipitation
Difference A2-REF
10
T-P diagram
Jurmala
11
T-P diagram
Palanga
12
Monthly average parameters - summary

• The average temperature in our region will
  increase by 4 (scenario A2) or 2.6 (scenario
  B2)
• The annual precipitation will increase by 8-11
  (scenario A2) or by 4-8 (scenario B2)
• The largest temperature increase is expected in
  Dec-Jan (up to 6), whilst the smallest in June
• Monthly average precipitation will increase in
  winters (Dec-Feb) and in beggining of summers
  (Jun), while decrease in summers (Jul-Sep)

13
Interannual variability of monthly temperature
Jurmala
14
Interannual variability of monthly precipitation
Jurmala
15
Interannual variability of monthly means -
summary

• Maximum values of monthly mean temperatures will
  increase more than average temperature in summer
  months (Jul-Sep)
• Minimum values of monthly mean temperatures will
  increase more than average temperatures in winter
  months (Dec-Jan)
• Interannual variation of monthly temperatures
  will decrease in winters but increase in summers
• Interannual variation of monthly precipitation
  will change insignificantly except for June