Transcript SIMULATION OF THE PRESENT

Simulation of Present-Day Climate in the Caribbean using PRECIS RCM
M
Mr. Arnoldo Bezanilla Marlot
SIMULATION OF THE PRESENT-DAY
CLIMATE IN THE CARIBBEAN USING
PRECIS RCM.
Abel Centella
Arnoldo Bezanilla
Israel Borrajero
Daniel Martinez
Institute of Meteorology, Cuba
Climate Change Impacts on the Caribbean, UWI Mona, Jamaica, June 15,17-2007
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SIMULATION OF THE PRESENT-DAY
CLIMATE IN THE CARIBBEAN USING
PRECIS RCM.
Abel Centella
Arnoldo Bezanilla
Israel Borrajero
Daniel Martinez
Institute of Meteorology, Cuba
Climate Change Impacts on the Caribbean, UWI Mona, Jamaica, June 15,17-2007
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OUTLINE OF PRESENTATION



What is PRECIS?
Simulating Present-Day Climate in the Caribbean
using PRECIS.
How well does PRECIS represent the Caribbean
Climate?

PRECIS and Tropical Cyclones. Preliminary results

PRECIS-CARIBE Online Access to PRECIS Output

What have we done, future plans.

Summary
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Regional Climate Modeling (I)
The main goal of regional climate models (RCMs) is to
reproduce the main climatic features in complex terrain,
where mesoscale forcing becomes important (Giorgi and
Mearns, 1991) and coarse-resolution global climate
models (GCMs) are not sufficient for assessing local
climate change (Aldrian et al. 2004).
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Regional Climate Modeling (II)
An example of a region where present-generation GCMs are
especially lacking in their ability to represent complex terrain and
land-sea contrasts is the Caribbean zone. In this region, tropical
and extra-tropical systems interact (Alfonso and Naranjo, 1996)
and frequently produce complex meteorological conditions. The
sea-breeze circulation in islands and peninsulas favors the
development of convective systems (Riehl, 1979).
In such a
complex meteorological situation, a high-resolution model is
necessary for meaningful regional climate prediction
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PRECIS (Providing REgional Climates for Impact Studies)
 A Regional Modelling System derived
from Hadley Centre GCM
 Providing REgional Climates for
Impact Studies
 PC-based regional climate model
 It can be set up and run over any area
 PRECIS is freely available
 It has two resolutions ~25 km and
~50 km
 PRECIS is a tool for dynamical
downscaling
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Simulating Present-Day Climate in the
Caribbean using PRECIS
1.Quasi-observed climate PRECIS forced by
ECWRF Reanalysis ERA15 (RCM ERA)
2.PRECIS driven by HadAM3 control run (RCM
CTRL)
3.Climate Research Unit database was used as
observed climate (CRU OBS)
RCM ERA and RCM CTRL are identical apart from their
driving data.
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How well does PRECIS represent the
Caribbean Climate?
RCM ERA and RCM CTRL were compared with CRU
OBS
RCM ERA and RCM CTRL biases were also compared
Temperature and Precipitation for land areas only
PRECIS land sea mask
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TEMPERATURE
RCM CTRL- CRU OBS
TEMPERATURE
RCM CTRL vs CRU OBS Statistics 1961-1990
DJF
MAM
JJA
Mean Obs
17.7
22.32
25.42
Mean RCM
17.66
22.72
25.97
RCM-Obs
-0.1
0.37
0.54
Spatial STD Obs
6.7
4.07
3.03
Spatial STD RCM
7.09
4.04
4.37
RMS_error_RCM
1.88
2.02
2.22
S.Correlat
0.96
0.86
0.79
SON
22.15
22.3
0.12
3.81
3.26
1.85
0.85
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PRECIPITATION
RCM CTRL- CRU OBS
PRECIPITATION
RCM CTRL vs CRU OBS Statistics 1961-1990
DJF
MAM
JJA
Mean Obs
1.67
2.54
5.59
Mean RCM
2.15
3.07
4.63
RCM-Obs
0.48
0.53
-0.96
Spatial STD Obs
2.35
2.28
4.36
Spatial STD RCM
2.06
2.91
3.64
RMS_error_RCM
1.4
1.68
2.53
S.Correlat
0.65
0.73
0.64
SON
4.29
3.57
-0.73
3.66
3.4
2.1
0.65
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RCM CTRL- CRU OBS
Temperature and Precipitation seasonal cycle for Cuba
7
30
29
RCM Ctrl
CRU Obs
6
28
5
mm/day
27
ºC
26
25
4
3
24
2
23
RCM Ctrl
CRU Obs
22
1
21
Jan
Feb
Mar
Apr
May
Jun
Jul
Months
Aug
Sep
Oct
Nov
Dec
0
Jan
Feb
Mar
Apr
May
Jun
Jul
Aug
Sep
Oct
Nov
Dec
Months
Warm and dry biases are evident in RCM CTRL simulation
Greater biases occur over Cuba and other islands
The dry biases are more intense in summer

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TEMPERATURE
RCM ERA- CRU OBS
TEMPERATURE
RCM ERA15 vs CRU OBS Statistics 1980-1990
DJF
MAM
JJA
Mean Obs
19.9
23.43
25.21
Mean RCM
19.77
24.06
25.43
RCM-Obs
-0.17
0.6
0.19
Spatial STD Obs
5.26
3.82
3.24
Spatial STD RCM
5.68
3.94
3.98
RMS_error_RCM
1.89
2.08
1.97
S.Correlat
0.94
0.85
0.82
SON
23.06
22.67
-0.42
3.78
4.24
1.8
0.86
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PRECIPITATION
RCM ERA- CRU OBS
PRECIPITATION
RCM ERA15 vs CRU OBS Statistics 1980-1990
DJF
MAM
JJA
Mean Obs
1.66
2.77
6.28
Mean RCM
1.64
2.88
4.93
RCM-Obs
-0.01
0.11
-1.35
Spatial STD Obs
2.07
2.49
4.09
Spatial STD RCM
1.7
2.68
2.95
RMS_error_RCM
1.34
1.63
2.92
S.Correlat
0.5
0.72
0.55
SON
4.81
4.14
-0.68
3.73
3.09
2.43
0.58
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RCM ERA- CRU OBS
Temperature and Precipitation seasonal cycle for Cuba
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6.5
6
29
RCM ERA
CRU Obs
5.5
28
5
4.5
mm/day
27
ºC
26
25
24
4
3.5
3
2.5
2
23
1.5
RCM ERA
CRU Obs
22
1
0.5
21
0
Jan
Feb
Mar
Apr
May
Jun
Jul
Aug
Sep
Oct
Nov
Dec
Jan
Feb
Mar
Months
Apr
May
Jun
Jul
Aug
Sep
Oct
Nov
Months
Warm and dry biases also exist in RCM ERA simulation
Greater biases occur over Cuba and other islands
The dry biases are more intense in summer

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Dec
Partial conclusions
 There consistency beetwen CTRL and ERA biases
suggest the RCM model don’t capture very well
some of the mesoscale process.
 The significant summer dry biases observed in
both simulations motivate further analysis of
convective process.
 Comparisons with GCM outputs are also needed to
assess the improvement that PRECIS could
produce.
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The Frequency of tropical cyclones in the
Caribbean and Mexico as show in Regional Climate
Model simulations
Cyclone representation is a
potential tool for:
Investigate and assess the Model
ability to represent this type of
event.
•
Investigate or project future TC
behavior in the area
•
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TCLVs detection methodology
 It is designed to work with daily mean fields
 On a grid of 0.44o (50 km), a point of minimum in surface
pressure is sought so that the averaged pressure over a
circumference of 6o (700 km) centered in the point is at
least 5.5 hPa greater than in the point.
 The difference between the maximum and minimum values
of the wind speed in a neighborhood of 3 grid points radius
(1.3o or 150 km) centered in the point of minimum pressure
must be at least 40 km/h (11 m/s).
 The end of the track of each individual vortex occurs when
in two consecutive days, the points of two consecutive TCLV
position are located at a mutual distance of more than 7o
(800 km).
 The above criteria were adjusted in practice by trial and
error based on a detailed visual analysis of selected
animated image sequences in the output of the model.
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S
W
E
N
19
Historical North Atlantic and East-Central North Pacific Tropical Cyclone Tracks,
1851-2005
National Oceanic and Atmospheric Administration, Tropical Prediction
Center/National Hurricane Center
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Climate Change Impacts on the Caribbean, UWI Mona, Jamaica, June 15,17-2007
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The method allow us to identify possible
change in tropical cyclone activity, but:
 More experiments are needed
 Add new fields to be used in the detection criteria.
 Specify the definition of TCLV based on daily means of
surface parameters using the criteria defined by
Walsh et al. for instant(hourly mean) observations in a
limited run of the model.
 Adjust a theoretical Cyclone Model to obtain hourly
values of main TCLV parameters from the mean daily
fields.
 Validate
the definition using the adjustment to
climatologic
data.
 Analyze the dependence of TCLVs on projected
temperature and wind shear projections.
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PRECIS (Sharing Results)
http://precis.insmet.cu/Precis-Caribe.htm
PRECIS-CARIBE: Online Access to Climate Change Scenarios in the Caribbean.
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PRECIS (Sharing Results)
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PRECIS (Outputs)
Examples for small island countries
Grid results over Haiti
Grid results over Jamaica
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PRECIS (What have we Done)
As part of a very prominent collaborative
initiative between 5C, INSMET and UWI
Jamaica and Barbados
 15 Years Reanalysis (1979-1993)
 2 B1 30 Years Baseline Ensembles
(Control Experiments) 1960-1990 (S)
 3 A2 30 Years de future scenarios 2070-2100
(S).
 B2 30 Years de future scenarios 2070-2100
(S).
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PRECIS (At this moment & upcoming work)
 ECHAM4 50km



Control 1960-1990 31yrs
A2
1990-2100 114 yrs
B2
1990-2100 114 yrs
 ERA40 with sulphur cycle 50km

Observed 1957-2002 45yrs
 SRES Control hourly with sulphur cycle 50km

1960-1969 10 yrs
 HadCM3 perturbed parameter ensemble members
(50km)

1 High & 1 Low 150 Years
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PRECIS
(Possibilities)
 Obtain and Use our own scenarios for climate
change
 To share the obtained results with all the
scientific community, and stakeholders.
 The improvement of the Collaboration in the
Caribbean
 Using the outputs to feed other numeric
models (Hydrological, Crops models, etc )
 The investigation of the extreme events in
the future (strength, duration, frequency,
season shifting, etc )
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PRECIS (Summary)
 Improvements on the Precis-Caribe Web Site,
Languages, outputs added for another scenarios
(HadCM3-B2) and another GCM (ECHAM4 A2 and
B2 scenarios).
 Define whether to make daily data available.
 Add some specific variables, another domain
(high res Scenario for West Indias).
 Work more Deeply in the analysis and validation
of the outputs. ERA40 Data.
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Thanks !!!!
PRECIS Online Access
http://precis.insmet.cu/Precis-Caribe.htm
Email: [email protected]
Contacts PRECIS Group in Cuba
Abel Centella [email protected]
Arnoldo Bezanilla [email protected]
Israel Borrajero [email protected]
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