Predictability of the moisture regime during the pre onset period of sahelian rains
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Predictability of the Moisture Regime During the Pre-onset Period of Sahelian Rains. Robert J. Mera Marine, Earth and Atmospheric Sciences North Carolina State University Seminar, April 3rd 2009. Motivation. Why is the moisture regime important?. Prediction of Monsoon rainfall.

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Predictability of the moisture regime during the pre onset period of sahelian rains

Predictability of the Moisture Regime During the Pre-onset Period of Sahelian Rains

Robert J. Mera

Marine, Earth and Atmospheric Sciences

North Carolina State University

Seminar, April 3rd 2009


Motivation
Motivation Period of Sahelian Rains

  • Why is the moisture regime important?

Prediction of Monsoon rainfall

African Easterly Waves

Agriculture

Public health: Meningitis Outbreaks


Outline
Outline Period of Sahelian Rains

  • The Application

    • Background

    • Health-climate link

  • Our Study

    • Importance of Downscaling

    • Predictability of Pre-onset Conditions

    • Ensemble Prediction and Evaluation of Model Skill


The application
The Application Period of Sahelian Rains

  • Meningitis is a serious infectious disease affecting 21 countries

  • 300 million people at risk across the Sahel

  • 700,000 cases in the past 10 years

  • 10-50 % fatality rate

  • 256,000 people lost to the disease in 1996

SAHEL


Meningitis climate link
Meningitis-Climate link Period of Sahelian Rains

  • Outbreaks coincide with dry, dusty conditions over the Sahel due to the Harmattan winds flowing south from the Sahara (Jan-May)

  • Largest correlation occurs between low humidity and disease outbreaks (Molesworth et al., 2006)

  • Disease occurrence drops dramatically with the onset of humidity

SH

SHL

Harmattan

ITCZ

Moisture

ITCZ

January

July


Meningitis climate link1
Meningitis-Climate link Period of Sahelian Rains

  • The most actionable case involves the link between humidity onset and cessation of disease

1998

2004

Pink: # of cases

Orange: Relative Humidity (%)


Current efforts
Current Efforts Period of Sahelian Rains

  • University Corporation for Atmospheric Research (UCAR) and the Google Foundation are funding efforts to explore climate-meningitis dynamics

  • Global scale models will be employed for operational purposes


Our study importance of downscaling
Our study: Importance of Downscaling Period of Sahelian Rains

65

60

55

50

45

40

35

Ghana

Ghana

30

25

20

WRF at 30km resolution

NCEP/NCAR Reanalysis at 2.5°

Relative Humidity (%)


The scientific question predictability of moisture
The Scientific Question: Predictability of Moisture Period of Sahelian Rains

  • What are the dynamics governing the northward progression of the moisture regime?

  • How well does the model represent the physical processes?

  • What is the skill of the model in predicting the dynamics and statistics of the physical processes?


In the literature
In the literature Period of Sahelian Rains

  • The West Africa summer monsoon is characterized by two steps: preonset and onset(Sultan and Janicot, 2003)

  • The preonset stage corresponds to the arrival of the Inter Tropical Front (ITF) at 15°N

ITF

Rain (mm/day)

From Sultan and Janicot (2003)


Schematic cross section of the west african monsoon
Schematic Cross Section of the West African Monsoon Period of Sahelian Rains

200 hPa

Deep moist convection

AEJ

600 hPa

Deep dry

convection

1000 hPa

10 N

20 N

Equator

ITCZ

Sahel

Sahara

Slide from John Marsham, U. of Leeds


Our study
Our Study Period of Sahelian Rains

  • The northward progression of moisture is related to the preonset stage of the monsoon and the position of the ITF

  • Two important factors at work:

    • Interannual variability is dictated by fluxes in sea surface temperatures (SST), interaction with mid-latitude systems (teleconnections)

    • Intraseasonal variability is related to east-west transient disturbances, African Easterly Jet


Data and methods
Data and Methods Period of Sahelian Rains

  • NCEP/NCAR, ECMWF Reanalysis, In-situ observations & satellite data: Statistics of Relative Humidity, etc

  • We use the Advanced Research WRF (WRF-ARW) Model for downscaling of reanalysis and operational forecasts, sensitivity analyses

*NCEP: National Centers for Environmental Prediction

*NCAR: National Center for Atmospheric Research

*WRF: Weather Research and Forecasting Model

*ECMWF: European Centre for Medium-Range Weather Forecasts


Preliminary analysis and results
Preliminary analysis and results Period of Sahelian Rains


Historical data reanalysis
Historical Data: Reanalysis Period of Sahelian Rains

JUN 24

  • Mean 2000–2008 relative humidity time series (%) computed on the grid points located between 10°W and 10°E longitude, 14.5°N and 15.5°N latitude

JUN 14

APR 15

Two distinct slopes


Model simulations
Model simulations Period of Sahelian Rains

April 1, 2006 relative humidity (%) at the surface, 925mb winds and u component at 0 to delineate ITF

700 mb

AEJ

Cross section along the prime meridian from 0° to 20 °N: Relative humidity (shaded) and u component at 0

20N

EQ


Ensemble prediction
Ensemble Prediction Period of Sahelian Rains

  • We will use the ensemble prediction approach to generate probabilistic forecasts that will also allow us to analyze model skill


An ensemble forecast run was tested against interpolated observations

Interpolated Observations

Ensemble Simulation


An ensemble forecast run was tested against interpolated observations

-10 -8 -6 -4 -2 2 4 6 8 10

Relative Humidity Anomaly (%)

The error (anomaly) is much smaller than the signal


Analyzing model skill
Analyzing Model Skill observations

Observations

EPS Forecast


The relative operating characteristic roc
The Relative Operating Characteristic (ROC) observations

  • The ROC method is widely used for estimating the skill of ensemble prediction systems (EPS)(Marzban, 2004)

  • A perfect forecast system would have a ROC area (ROCA) of 1


An extended roc procedure
An Extended ROC Procedure observations

  • ROC plots model skill only for an optimum user

  • We developed an extended (EROC) procedure that caters to a particular user’s needs:

Shift in baselines

According to user

Semazzi & Mera, 2006


Model skill for end user
Model Skill for End-user observations

  • Additional analysis through EROC can help with current health efforts and the incurred costs:

    • Transportation of Supplies

    • Inoculation

    • Personnel


Looking forward
Looking Forward observations

  • Understanding the moisture regime statistics: variance of 40% RH date and changes in slope of humidity trends

  • Sensitivity studies using SSTs, land cover, meridional transient distrubances, teleconnections with mid-latitude systems

  • Application of EROC for surface conditions pertinent to health efforts


Acknowledgements
Acknowledgements observations

  • Dr Semazzi

  • CML crew

  • Google/UCAR group

  • NOAA ISET

  • Dr Arlene Laing, Dr Tom Hopson


Questions

Questions? observations


Auxiliary slides
Auxiliary slides observations


Historical data reanalysis1
Historical Data: Reanalysis observations

  • Mean 2000–2008 relative humidity time series (%) computed on the grid points located between 10°W and 10°E longitude, 14.5°N and 15.5°N latitude




Criteria for issuing a forecast

Decision to issue a forecast of an event (E) to occur is probabilistically based on the criteria:

Criteria for Issuing a forecast

Where:

(N): size of the ensemble

(n): number of the runs in the ensemble for which (E) actually occurs

(p): probability given by the ratio (n/N)

This is the threshold fraction above which the event (E) is predicted to occur based on the model forecast


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