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Morse_applications

VIEWS: 15 PAGES: 50

									                             8.0 Applications
8.1 Status report on use of and need for research data in
                  seasonal applications
8.1.1. Experience and progress from recent and ongoing
projects (ENSEMBLES, UniCantabria Downscaling Portal, AMMA, QWECI)
                         Andy Morse
                       School of Environmental Sciences,
                      University of Liverpool, Liverpool, U.K.
                               A.P.Morse@liv.ac.uk
    CLIVAR WGSIP13 Buenos Aires, Argentina, 29-31 July 2010

  Cyril Caminade, Dave MacLeod and Anne Jones, School of Environmental Sciences,
 University of Liverpool, Liverpool, U.K.; Matthew Baylis, School of Veterinary Science,
           University of Liverpool; Helene Guis, CIRAD, Montpellier, France.
                   Background, Methods and Results, Discussion




             Introduction and Themes
• Update and connects through research projects

• Recent user experiences – NGOs and Government Research

• Plots of distributed seamless activity (works in progress)

• The climate services agenda
                           Background, Methods and Results, Discussion




            Recent User Experiences
• NGOs (major UK based international development and aid charities)
        Humanitarian Futures Programme, Kings College London
        http://www.humanitarianfutures.org/main/

• UK government bodies and commercial bodies in EQUIP and ENHanCE projects



• African government programmes and decision makers through African partners
          in QWeCI and HealthyFutures

• How do we widen participation?

• How do we leave climate information is a useable way through targeted
narratives?

• How does this experience link with current Climate Services Agenda initiatives?
Introduction, Methods and Results, Discussion




 Seasonal Scales
     Introduction, Methods and Results, Discussion


Seasonal Ensemble Prediction
                        Introduction, Methods and Results, Discussion


  Potential Seasonal Skill in Epidemic Zones for Malaria




Based on the Liverpool Malaria Model simulations driven by seasonal ensemble
                multi-model outputs (Rainfall and Temperature)

            ENSEMBLES Seasonal EPS May 4-6 (ASO) upper tercile
                   epidemic transmission zone ROCSS
                                   Introduction, Methods and Results, Discussion


  Seasonal prediction of malaria epidemic risk in West Africa
      Potential skill using ENSEMBLES re-forecasts to drive a malaria model

       Forecast           Months
                                         Below LT            Above Median           Above UT


       Rainfall            JJA         0.073 (0.050)          0.068 (0.041)        0.083 (0.050)


Degree days above 18 ºC    ASO         0.342 (0.027)          0.200 (0.021)        0.143(0.031)

  Malaria Incidence -
  ENSEMBLES multi-         ASO          0.148 (0.046)          0.261 (0.057)       0.235(0.056)
        model
Skill of multi-model forecasts derived from ENSEMBLES May start date, averaged over
15 high-variability incidence grid points in WA. (15N: 17.5W to 7.5W, 12.5N: 2.5W to
12.5E, and 5N: 10E to12.5E). Standard error in brackets. Measured relative to skill of
NCEP reanalysis-driven simulations.
                                           Introduction, Methods and Results, Discussion


Seasonal prediction of malaria epidemic risk in West Africa
      Potential skill using ENSEMBLES re-forecasts to drive a malaria model
                 1
                      1. ECMWF           4. INGV
                      2. UK Met Of f ice 5. Met France
                      3. Max Planck 6. Multi-model
         ROCSS




                 0




                 -1
                      0         1          2             3       4         5          6    7
                                                         Model
Skill of above the median forecasts for LMM-simulated incidence over May forecast
months 4-6, 13 high-variability grid points in WA. (15N: 17.5W to 7.5W, 12.5N: 2.5W to
12.5E, and 5N: 10E to12.5E). Measured relative to skill of NCEP reanalysis-driven
simulations . Scatter points show grid point values, solid black circles show areal mean.
      Introduction, Methods and Results, Discussion




   Dabbling with Decadal


are working on in



and
       Temperature [K]




Distribution of ensemble members from
first 5 years of ENSEMBLES decadal           Correlation coefficient
forecasts, observations: NCEP reanalysis   (ensemble mean vs obs) =
                                                      0.233
Predicting the AMO?




        Using the first 5 years of decadal hindcast experiments
               (except for the final 2005-2015 forecast)
                 after van Oldenborgh et al 2010 GRL
                Climate Diagnostics
Working with users on recent climate variability and trends,
towards producing climate products, filling decadal gap with RCM runs

Start with recent past climate
using high resolution Eobs for Europe, ENSEMBLES RCM runs for Europe

Need capture real variability – do these runs SRES GCM-RCM runs
have even average variability?

Should we even ask that question of GCM-RCM runs?

How do we use RCM to fill decadal gap?

RCMs with s2d initial condition ensembles?
                         Introduction, Method, Climatic Trends, Health Impact examples



        Observed Climatic Trends: 1961-2004




Wetter and warmer winters over Northern Europe, warmer and drier winters over
Southern Europe.
More drought conditions over the Mediterranean basin in summer
      Introduction, Method, Climatic Trends, Health Impact examples


Future Changes: 2030-2050 vs 1960-2000

                                            Warming, faster over northern
                                            Europe in winter and southern
                                            Europe in summer.

                                            The winters get wetter over
                                            northern Europe for both seasons.

                                            Strong drying signal over the
                                            Mediterranean basin in summer.


                                            Shading: changes
                                            Dots: 80% of the climate models
                                            agree on the sign of changes
      Introduction, Method, Climatic Trends, Health Impact examples



Recent climate T2m PDF JJA 1961-2000
                                          EOBS observation in black

                                          ENSEMBLES RCM CTL ensemble
                                          (ERA40 driven) in blue

                                          ENSEMBLES RCM SRESA1B
                                          ensemble (GCM driven)

                                          The envelope d(red thin lines)
                                          depicts the spread (2stddev) of the
                                          CTL (SRESA1B) model ensemble
                                          with respect to the mean
    Introduction, Method, Climatic Trends, Health Impact examples



T2m PDF JJA 2030-2050 vs 1961-2000
                                        ENSEMBLES RCM SRESA1B
                                        ensemble (GCM driven)

                                        1961-2000: Orange

                                        2030-2050: Red

                                        The envelope (thin red lines)
                                        depicts the spread (2stddev) of the
                                        model ensemble with respect to
                                        the mean

                                        -> shift to warmer summers
                                        -> spread increases in the future
Health Impact examples for
         Europe
                        Health Impact examples: Bluetongue over Europe

         Mean Bluetongue Risk (OBS): ASO 1961-
                        2008
                                                       High BT risk over Spain, Portugal,
                                                       south western France, Sardegna
                                                       and Sicilia.

                                                       This misses out observed
                                                       outbreaks in Corsica

                                                       Unrealistic values over mountains
                                                       and Eastern Europe


                                                       Shading: Ro risk (arbitrary scaled
                                                       between 0 and 1)




From Guis et al, 2010
                                  Health Impact examples: Bluetongue over Europe



         Bluetongue Risk changes: 2030-2050 vs 1961-2000




   MULTI-MODEL CHANGES:                 MULTI-MODEL SPREAD:                 MULTI-MODEL SPREAD:
          MEAN                              MAGNITUDE                        SIGN CONSISTENCY


  The BT risk increases over UK, Southern France and North-western Spain (Galicia)

  Changes in Northern Europe are related to the pathogen properties

  Changes in Southern Europe are associated with the spread of the Afro-Tropical vector (Imicola spp)


From Guis et al, 2010
Health Impact examples for
          Africa
   Health Impact examples: Malaria Climatic Risk over Africa


Mean seasonal cycle 1990-2007

                                                    Hovmoeller like diagram
                                                    (zonal average between
                                                    16W and 16E)

                                                    Shading: Rainfall
                                                    Contours: Malaria
                                                    Incidence



                                                    Underestimation of the
                                                    northern extension of
                                                    the malaria incidence
                                                    belt by LMM

                                                    2-3 months LAG
                                                    between rainfall and
                                                    malaria incidence
                   Health Impact examples: Malaria Climatic Risk over Africa


Mean annual malaria incidence 1990-2007
                                                                    Endemic areas >80%

                                                                    “Endemic and seasonal”
                                                                    areas between 20-80%

                                                                    Epidemic Areas (<20%)
                                                                    -> Northen fringe of the
                                                                    Sahel
                                                                    -> Strongly connected to
                                                                    climate variability



                                                                    Underestimation of the
                                                                    Northern extension of
                                                                    the malaria incidence
                                                                    belt by LMM

                                                                    ITCZ extends too far
                                                                    north in the RCM world
Mean annual simulated Malaria Incidence (1990-2007) driven by
“Observed datasets” and the ENSEMBLES RCM ensemble
        Health Impact examples: Malaria Climatic Risk over Africa


Mean Incidence changes SON 2031-50 vs 1990-2010


                                                  Simulated changes in Malaria
                                                  Incidence (SON) based on the
                                                  different RCMs


                                                  -> common feature: decrease
                                                  of the Malaria Incidence at
                                                  the Northern fringe of the
                                                  Sahel

                                                  -> Related to changes in the
                                                  number of rainy days (and
                                                  not the seasonal amounts)
                           Health Impact examples: Rift Valley Fever over West Africa


              RVF climatic risk 1990-2007
                                                   RVF risk

                          RVF risk




           Ndione et al, 2008

Dry spell followed by a rainfall peak                                     Caminade et al, 2010 (in review)
during the late rainy season (Sep-Oct)             Rift Valley Fever risk (%) based on rainfall from ERAINTERIM reanalysis
                                                   (1990-2007). The number of RVF risk events is defined by a dry spell (10
over Northern Senegal                              consecutive days with total rainfall below 1mm) followed by a convective
                                                   event (high precipitation defined by one or two days following the dry spell
 Rehydrating ponds                                above the 90th percentile) occurring during the late rainy season (SON). The

 mosquitoes hatching + hosts                      total number of RVF risk events is then rescaled to range between 0 and
                                                   100% to define the risk. The dotted, crossed and filled black areas depict
                                                   animal host densities (cattle + buffalo + sheep + goats) above 1, 10 and 100
availability                                       per km2 (FAO, 2005).
 high RVF risk
           Health Impact examples: Rift Valley Fever over West Africa


Synoptic situation: Senegal RVF outbreak 2002


          RVF                      OLR Hovmoeller Diagram
          outbreak                 (averaged between 12°N and 18°N).

                                   OLR Anomaly for 2002 (NCEP).
         10-15 days
         predictability?           Brown: Convective event

                                   Black Box: Senegal location

                                   2 weeks predictability???
                                   -> Value of medium range forecasts
                      Introduction, Methods and Results, Discussion



   Climate Services Agenda - a seamless one?
• Who  is doing what, where and with whom e.g. can we share good
practise and/or join forces?

• Are Met Services interacting as much as possible with other
researchers working on impacts and data use?

• Who is thinking seamlessly across multiple timescales?

• Who is developing this seamlessness with the user community?

• How can WGSIP, CLIVAR, WCRP help connect this Agenda with the
impacts community?
                              Introduction, Methods and Results, Discussion



                       Summary to seamlessness
•    Grand ensemble approach – combined ensembles from different systems –
    bound uncertainty, maximise skill, model climates

•   Impacts model portability – develop models work different climate streams and
    grand ensemble – impact uncertainty, integrated model value

•   Field and Environmental Observations – verification and dynamic insight

•   Model data post processing – downscaling, bias correction, dressing

•    Continuity to society – decision makers, product tailoring, decision support
    systems, understanding critical uncertainty and thresholds, agent based models,
    combination with remote sensing and observations, through to policy and project
    impact on society
           QWeCI

FP7 SEVENTH FRAMEWORK PROGRAMME THEME ENV.2009.1.2.1.2
Methods to quantify the impacts of climate and weather on health in
developing low income countries

Collaborative Project (small- or medium scale focused research project) for
specific cooperation actions (SICA) dedicated to international cooperation
partner countries

Quantifying Weather and Climate Conditions on health in developing
countries (QWeCI)

3.5 MEu EC contribution (~4.7MEu total) 1st Feb 2010 start

13 partners = 7 Africa, 6 EU, Liverpool coordinator, 42 months

UNILIV, CSE, CSIC, ECMWF, IC3, ICTP, ILRI, IPD, KNUST, UCAD,
                         UNIMA, UOC, UP
http://www.equip.leeds.ac.uk/
            Introduction

Improving the use of climate prediction by
quantifying, understanding and managing
uncertainty.

Through working with stakeholders, the EQUIP
team will develop new methodologies and analyses
for using climate information that will be employed
by decision makers in a set of case studies.

We will quantify and understand the uncertainty
surrounding future droughts, heatwaves, crop
production and marine ecosystems.
  EQUIP: End-to-end Quantification of
   Uncertainty for Impacts Prediction




• Edinburgh, Newcastle, Liverpool
• NERC directed research
• EQUIP network (external users and
  academics) is a core part of our research
Introduction, Methods and Results, Discussion


     Extra Slides
                   Background, Methods and Results, Discussion


Integrated Climate Model Impacts Verification Paradigm




                 from Morse et al. (2005)
                  Tellus A 57 (3) 464-475
                         Introduction, Methods and Results, Discussion



  Relative contributions of uncertainties
 Internal
variability



                                                                          Scenario
                                                                         uncertianty




  Model
uncertainty




              Hawkins & Sutton, 2009, BAMS, 90(8):1095-1107
              Introduction, Method, Climatic Trends, Health Impact examples



UK Rainfall and Temperature Trends: EOBS

Rainfall 1961-2004                           Temperature 1961-2004
                   Introduction, Method, Climatic Trends, Health Impact examples



            UK extremes in winter: EOBS
Heavy rainy days: 1961-2004                       Frost days: 1961-2004
      Introduction, Method, Climatic Trends, Health Impact examples



Recent climate T2m PDF DJF 1961-2000

                                           EOBS observation in black

                                           ENSEMBLES RCM CTL ensemble
                                           (ERA40 driven) in blue

                                           ENSEMBLES RCM SRESA1B
                                           ensemble (GCM driven)

                                           The envelope d(red thin lines)
                                           depicts the spread (2stddev) of the
                                           CTL (SRESA1B) model ensemble
                                           with respect to the mean

                                           Problems with 2 models (freezing
                                           days too frequent)
      Introduction, Method, Climatic Trends, Health Impact examples



T2m PDF DJF 2030-2050 vs 1961-2000

                                           ENSEMBLES RCM SRESA1B
                                           ensemble (GCM driven)

                                           1961-2000: Orange

                                           2030-2050: Red

                                           The envelope (thin red lines)
                                           depicts the spread (2stddev) of the
                                           model ensemble with respect to
                                           the mean

                                           -> shift to warmer winters
                                           -> spread increases in the future
        Introduction, Method, Climatic Trends, Health Impact examples



Observed Climatic Trends: extremes 1961-2004

                                                   Largest Increase of winter
                                                   rainfall extremes over the
                                                   western coasts of the UK
                                                   and Norway.

                                                   Decrease in the number of
                                                   frost days in winter over
                                                   Europe

                                                   Significant increase of
                                                   warm days and warm
                                                   nights over the
                                                   Mediterranean basin in
                                                   summer  Health Impacts
      Introduction, Method, Climatic Trends, Health Impact examples



Observed Climatic Trends extremes

                                            Wetter and warmer winters over
                                            Northern Europe, warmer and
                                            drier winters over Southern Europe

                                            More drought conditions over the
                                            Mediterranean basin in summer
                                  Health Impact examples: Bluetongue over Europe



            Bluetongue Risk ASO, Northern Europe
                                                            Simulated Relative Ro BT changes (with
                                                            respect to 1961-2000) over Northern
                                                            Europe.

                                                            Black: BT risk based on EOBS
                                                            Blue: BT risk based on CTL exp
                                                            Red: BT risk based on SRESA1B exp

                                                            The relative envelope depicts the spread
                                                            within the RCMs ensemble (1 Stddev)




  2006: BT outbreak in France Benelux and Germany captured by EOBS and the CTL exp

  Increasing trend for the future over Northern Europe



From Guis et al, 2010
                        Health Impact examples: Liver Fluke over the UK



         Liver Fluke: Fo=f(T,Rdays)
                                                      106
                                                              Fo: The total predicted
                                                              number of adult progeny
                                                              arising from pasture
                                                              contamination by a single
                                                      103     fluke present in a non-
                                                              immune sheep for one year.
                                                      102
                                                              X axis: Temperature (°C)
                                                              Y axis: Fraction of rainy days
                                                              (1 means it rains every day, 0
                                                              no rain, based on the 1mm
                                                              threshold).




Work with J. Van Dijk
       Health Impact examples: Malaria Climatic Risk over Europe


Mean Malaria “climatic” Risk: JAS 1990-2008

                                             Based on LMM simulations driven
                                             by observed Rainfall and
                                             Temperature from different
                                             observed datasets.


                                             Northern Italy, some parts of
                                             Galicia in Spain and the “Landes”
                                             region in France are climatically
                                             “at risk”

                                             The incidence values are relatively
                                             low in magnitude (20-50%)
                                             compared to what can be expected
                                             in Africa.
         Health Impact examples: Malaria Climatic Risk over Africa


Shift of the epidemic belt 2031-50 vs 1990-2010

                                                  Gray: Location of the
                                                  epidemic belt 1990-2010

                                                  Black dots: Future location of
                                                  the epidemic belt 2030-2050

                                                  The epidemic belt location is
                                                  defined by the coefficient of
                                                  variation, namely:

                                                  Mean Incidence > 1%
                                                  1stddev > 50% of the average



                                                  Southward shift of the
                                                  epidemic belt over WA

                                                  -> to more populated areas...
          Health Impact examples: Rift Valley Fever over West Africa


RVF climatic risk based on RCMs: 1990-2007
                                        RVF Risk based on the control RCMs
                                        ensemble (runs driven by ERAINTERIM
                                        at the boundaries). The analysis is
                                        carried out for the period 1990-2007.
                                        Problems as most of the models
                                        overestimate the northward extension of
                                        the ITCZ.
                                        KNMI and DMI pattern relatively realistic
                                        with respect to the reanalysis / GPCP
                                        driven runs.

                                            RVF risk estimated from ERAINT
Health Impact examples: Rift Valley Fever over Africa



                RVF distribution map according to the
                Central for Disease Control and
                prevention. Blue areas show where RVF
                is endemic




                                     RVF risk as estimated from
                                     a) ERAINTERIM and b) GPCP
                                     for the whole African
                                     continent.
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                       Title
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