Going seamless towards

1
Going seamless - towards

• Suggested seamless ranges open to discussion
• Medium range, monthly, seasonal WCRP-WWRP
  interface
• Seasonal, interannual, decadal - ENSEMBLES
• Seasonal, interannual, decadal, centennial
• Suggested seamless approaches
• Application models across modelling streams
  ENSEMBLES
• Grand ensemble approach THORPEX medium range
• Ensemble dressing

Morse IS-EPS WCRP Seasonal Prediction Barcelona
2007
2
RT6 Assessments and Impacts of Climate Change
24 partners plus affiliated partners

• WP6.1 Global changes in biophysical and
  biogeochemical processes integrated analysis of
  impacts and feedbacks
• - ACC GCM - Colin Prentice - UNIBRIS, UREADMM,
  PIK, ULUND, METO-HC, CNRS-IPSL
• WP6.2 Linking impact models to probabilistic
  scenarios of climate change
• RCM Tim Carter SYKE, DIAS, DISAT, FMI, FUB,
  NOA, PAS, SMHI, UEA, ULUND, UNIK, UREADMM
• WP6.3 - Impact modelling at seasonal to decadal
  timescales
• - s2d Andy Morse - UNILIV, UREADMM, ARPA-SIM,
  JRC-IPSC, METEOSWISS, LSE, IRI, EDF, DWD

ENSEMBLES GA 2006 Lund RT6 Plenary
3
RT6 Assessments and Impacts of Climate Change

• The three WPs method and model refinement and
  application and impact model runs with existing
  climate model data e.g. DEMETER, AR4 etc. And
  publishing papers.
• Partners working within or towards a
  probabilistic framework.
• Range of application models some themes through
  all WPs e.g. crops and gt 1 WP e.g. fire, wind
  damage
• Tasks on going and ready to move to ENSEMBLES
  data streams Stream 1 - s2d and ACC and, RCM
  as available

ENSEMBLES GA 2006 Lund RT6 Plenary
4
Role of users malaria plumes
Botswana malaria forecast for February 1989, LMM
driven by DEMETER multi-model (ERA-driven model
shown in red) All plots unpublished Anne Jones,
University of Liverpool

• November 1997 start
• Improvement in skill due to temperature
  correction
• If temperatures too low, delay in model is
  increased

Morse IS-EPS WCRP Seasonal Prediction Barcelona
2007
5
Tier-3 ROC Areasfor November malaria forecast
ROC Area (lt0.5 no skill), Upper Tercile event,
forecast 6 month totals for Botswana grid
average, () 95 confidence intervals calculated
from 1000 bootstrap samples Validated against
Thomson et al (2005) Malaria Index
6
Tier-1 ROC Areas for November rainfall forecast
Effect of rainfall bias correction

• Bias correction of rainfall causes decrease in
  skill

ROC Area (lt0.5 no skill),forecast 6 month
totals for Botswana grid average, () 95
confidence intervals calculated from 1000
bootstrap samples Validated against ERA-40
rainfall totals
7
Effect of temperature bias correction
Uncorrected Temperature
Corrected Temperature
DEMETER temperature forecasts for Botswana,
November 1997

• Temperature variability not a strong driver of
  malaria variability in this region
• However malaria model requires realistic
  temperatures
• DEMETER temperatures need to be bias corrected to
  achieve this, because models is sensitive to
  biases in uncorrected data of 2 degrees

8
Tier-3 ROC Areas-alternative model outputs

• Skill improved by using model mosquito numbers
• Bias correction decreases skill due to strong
  rainfall driver
• Cannot use in other areas where temperature a
  stronger driver

ROC Area (lt0.5 no skill), Upper Tercile event,
November forecast 6 month totals for Botswana
grid average, () 95 confidence intervals
calculated from 1000 bootstrap samples Validated
against Thomson et al (2005) Malaria Index
9
Conclusions Botswana LMM dynamic

• DEMETER-driven forecasts were skilful, better
  than climatology and persistence forecasts
• Bias correction of temperature is important even
  if variability in temperature not important -
  temperatures must be "realistic" for the
  application model
• Bias correction of rainfall is unsatisfactory -
  use of daily rainfall output is problematic and
  need to consider other methods using monthly
  anomalies instead (e.g. weather generator)
• Lag in model mean malaria cases may occur outside
  forecast window - can be solved for Botswana
  using mosquito model but not applicable to other
  areas

10
Role of users - Statistical Model Malaria PDFs
The probability distribution functions of
predicted standardized log malaria annual
incidence for the years 1992 (anomalously low
incidence, left) and 1993 (anomalously high
incidence, right) computed with the DEMETER
multi-model ensemble forecast system are depicted
in red. Observations Botswana Ministry of health
in blue
from M.C. Thomson, F.J. Doblas-Reyes, S.J. Mason,
R. Hagedorn, S.J. Connor, T. Phindela, A.P.
Morse, and T.N. Palmer (2006). Malaria early
warnings based on seasonal climate forecasts from
multi-model ensembles, Nature, 439, 576-579.
Morse IS-EPS WCRP Seasonal Prediction Barcelona
2007
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Role of users - Tanzania statistical malaria model
Jones et al. 2007 Fig 5d (submitted)
Statistical model C3 driven by Feb-Jul DEMETER
pptn and Aug-Jan. Tmx ob. Giving box-whisker
malaria prediction Apr-Sep obs. driven control,
obs. malaria - all standardised anomalies.
Morse IS-EPS WCRP Seasonal Prediction Barcelona
2007
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RT6 WP6.3 Impact modelling at seasonal to decadal
timescales
Regional crop yield forecasting
To develop tier-3 validation systems. Dynamic
crop model run with 72 downscaled Demeter
hindcast members. Comparison with local field
data showed interesting skill in forecasting
yield two months before harvest.
Vittorio Marletto ENSEMBLES GA 2006 Lund RT6
Plenary
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RT6 WP5.5
Impacts of mean temperature rise and extreme
temperature events on crop yield
The relative importance of mean and extremes of
temperature was examined on crop yield (Task
5.5.x). Response varied geographically, and
depended upon the parameterised response of the
crop. Yields were particularly threatened when
the reproductive temperature threshold was
exceeded, but not the development rate threshold.
Boxplots of the percentage change in yield,
between the baseline and projection climates for
groundnut. S and T refer to sensitive and
tolerant genotypes Topt is 28 or 36 oC OF
without high temperature stress ON with high
temperature stress.
Andrew Challinor, Tom Osborne, Tim
Wheeler ENSEMBLES GA 2006 Lund RT6 Plenary
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RT6 WP6.3 Impact modelling at seasonal to decadal
timescales
PreWiStor Wind storm risk and prediction
Contribution to D2B.12
ERA40 wind storm Calibrated wind storm
Calibration of ERA40 and S2d data to be
compatible with Swiss Re wind storms Preliminary
methods over calibrate the wind gust Unreliable
calibrations are masked in white
Paul Della-Marta et al. ENSEMBLES GA Lund RT6
Plenary
15
Going seamless - towards

• Suggested seamless ranges open to discussion
• Medium range, monthly, seasonal WCRP-WWRP
  interface
• Seasonal, interannual, decadal - ENSEMBLES
• Seasonal, interannual, decadal, centennial
• Suggested seamless approaches
• Application models across modelling streams
  ENSEMBLES
• Grand ensemble approach THORPEX medium range
• Ensemble dressing

Morse IS-EPS WCRP Seasonal Prediction Barcelona
2007
16
R index of reproducibility (Stern and Miyakoda,
1995)
where sn is the standard deviation of the
ensemble members about the ensemble mean and ss
is the climatological variability calculated over
all ensemble members and years.
W. Stern and K. Miyakoda, 1995. Feasibility of
Seasonal Forecasts Inferred from Multiple GCM
Simulations. Journal of Climate Vol. 8, No. 5,
pp. 10711085.   Ratio of variances used in
CEDO BRANKOVIC T.N. PALMER, 2000. Seasonal skill
and predictability of ECMWF PROVOST ensembles.
Quarterly Journal of the Royal Meteorological
Society, Volume 126, Number 567, July 2000 Part
B, pp. 2035-2067(33)
17
Pan-African R scores
Temperature (bias corrected)
Rainfall (uncorrected)
DEMETER multimodel ensemble, 1980-2001, Feb
forecast totals/mean 1-6 no masking for zero and
low CoV
18
Time-averaged R for Botswana Malaria incidence
February forecast
Feb 2-4
Feb 2-4
R
DEMETER CV
1982-2001 averages of R, malaria incidence for
DEMETER multimodel using bias-corrected
temperature. Mask ERAlt1 case per 100 people per
month, CVlt0.5
19
Time-averaged R for Botswana Malaria incidence
November forecast
Nov 2-4
Nov 4-6
DEMETER CV
R
1982-2001 averages of R, malaria incidence for
DEMETER multimodel using bias-corrected
temperature. Mask ERAlt1 case per 100 people per
month, CVlt0.5
20
Distributions of Malaria Incidence for each model
and multi-model
Epidemic grid points, Feb 2-4
21
Distributions of Malaria Incidence for each model
and multi-model
Epidemic grid points, Nov 4-6
22
Rainfall
23
Time-averaged R for Botswana Rainfall February
forecast
Feb 2-4
Feb 2-4
R
DEMETER CV
1982-2001 averages of R, malaria incidence for
DEMETER multimodel using bias-corrected
temperature. Mask ERAlt1 case per 100 people per
month, CVlt0.5
24
Time-averaged R for Botswana Rainfall November
forecast
Nov 2-4
Nov 4-6
R
DEMETER CV
1982-2001 averages of R, malaria incidence for
DEMETER multimodel uncorrected normalised
rainfall. Mask from incidence ERAlt1 case per 100
people per month, CVlt0.5
25
Distributions of Rainfall for each model and
multi-model
Epidemic grid points, Feb 2-4
26
Distributions of Rainfall for each model and
multi-model
Epidemic grid points, Nov 4-6
27
Temperature
28
Time-averaged R for Botswana temperature
February forecast
Feb 2-4
Feb 2-4
R
DEMETER CV
1982-2001 averages of R, malaria incidence for
DEMETER multimodel bias-corrected temperature.
Mask from incidence ERAlt1 case per 100 people per
month, CVlt0.5
29
Time-averaged R for Botswana temperature
November forecast
Nov 2-4
Nov 4-6
R
DEMETER CV
1982-2001 averages of R, malaria incidence for
DEMETER multimodel bias-corrected temperature.
Mask from incidence ERAlt1 case per 100 people per
month, CVlt0.5
30
Distributions of temperature for each model and
multi-model
Epidemic grid points, Feb 2-4
31
Distributions of temperature (bias-corrected) for
each model and multi-model
Epidemic grid points, Nov 4-6
32
Morse IS-EPS WCRP Seasonal Prediction Barcelona
2007
33
Morse IS-EPS WCRP Seasonal Prediction Barcelona
2007
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Role of users MARA transmission map
original
ERA
Based on model Craig et al. 1999 www.mara.org.za
run with climatology and observations and ERA-40
Morse IS-EPS WCRP Seasonal Prediction Barcelona
2007
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Botswana malaria
slide from Anne Jones, University of Liverpool
Morse IS-EPS WCRP Seasonal Prediction Barcelona
2007
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Morse IS-EPS WCRP Seasonal Prediction Barcelona
2007