school of earth and environment - jwcrp

School of Earth and Environment INSTITUTE FOR CLIMATE AND ATMOSPHERIC SCIENCE

Forecasting convection in West Africa

Douglas Parker, Cathryn Birch,

University of Leeds and Met Office

Dartington Hall, 28 January 2013

Contents

1.  Some comments on forecasting issues for West Africa

2.  Dynamics of convective triggering – a case study

3.  Final remarks.

120 km

Drought?

2005 rainfall around Niamey (13.5N, 2E): courtesy Thierry Lebel.

Cambridge

Oxford*

* 1981-2010

Forecasting convection in West Africa

Given the synoptic state, and some existing pattern of convective storms,

... what will the pattern of convective rainfall be in the future?

Tools: •  Current observations

•  Numerical models

•  Statistical relationships / climatology

•  Conceptual models

It has been argued for some time, that the conceptual models for the tropics are still immature, relative to the understanding we have for midlatitudes.

School of Earth and Environment INSTITUTE FOR CLIMATE AND ATMOSPHERIC SCIENCE

African Monsoon Multidisciplinary Analyses Afrikanske Monsun: Multidisiplinære Analyser Afrikaanse Moesson Multidisciplinaire Analyse

Analisi Multidisciplinare per il Monsone Africano Afrikanischer Monsun: Multidisziplinäre Analysen

 Analisis Multidiciplinar de los Monzones Africanos  Analyses Multidisciplinaires de la Mousson Africaine

SOP1&2

SOP3

Around 800 scientists, engineers and operational specialists from 25 countries

7 aircraft AMMA observations, 2004 - 2009

Budget ~ 50 MEu

Over 500 papers and 7 special issues so far.

AMMA and weather forecasting

African Monsoon Multidisciplinary Analysis (AMMA): 2002-2020 programme ; intensive field programme 2005-2007.

Forecast development included in 2006 AMMA Operational Centre (AMMA-AOC) – Jean-Philippe Lafore.

Forecasters’ Handbook being written currently, for completion July 2013, published by Wiley-Blackwell. Editors Parker and Diop-Kane. Conceived in JET2000 – developed in AMMA.

Integration of recent AMMA research with operational forecasting methods We are writing a “Forecasters’ handbook for West Africa.

(JET2000) AOC, 2006 Trieste, 2009 Leeds, 2012 Dakar, 2013

WASF 1800 D+1

New “synthetic analysis” conventions: Lafore et al. West African Synthetic Analysis/Forecast (WASA/F)

WASA 1800 D

WASF 1800 D

MSG OLR 1800 28 July 2006

Some forecaster perspectives

Forecasters don’t trust NWP for convection (but they use it for the large-scale state ...)

•  Is this fair? Some cases may be more predictable (e.g. 27-28 July 2006).

•  Convergence and divergence are used – dangerous.

Lots of (minor?) differences between theory and practice, •  e.g. Academics discuss 925 and 700 hPa ; forecasters like 850 hPa (=

steering level = closed vortices).

•  Some concepts not well-defined for objective analysis (e.g. “monsoon trough”, African Easterly Wave trough, ITD, ...).

Availability of tools (e.g. Software) and training in their use, is variable.

Can NWP be skilful?

MSG cold cloud fraction and meridional winds (contours)

Söhne, Chaboureau and Guichard (2008): Meso-NH skill seems to be higher during periods of active synoptic African Easterly waves.

Meso-NH D+1 forecast

23 Aug 2006 23 Jul

Heidke skill score

MSG obs

Some dynamical perspectives 90% of rainfall at Niamey is from organised, propagating convection

(squall lines); ~ 50% in Benin. Need to separate problem of initiation from maintenance of convection (e.g. role of midlevel dryness).

The diurnal cycle is our friend. •  Separates cause and effect •  Separates isolated and organised convection

Remarkably, there is still no clear consensus on the physics of the relationship between convection and synoptic state in this region.

Synthetic charts need to be: •  Repeatable (i.e. Objective rules) •  Quantifiable, for evaluation (for instance in geographic position of

objects).

Link to synoptic state

Stein et al. 2011; See also Parker et al. 2005

CloudSat mean cloud-type distributions: Deep convection shaded. Contours = adiabats : Solid black dashed = African Easterly Jet

Dry Saharan air layer (SAL)

Monsoon layer

CIN and midlevel dry air suppress initiation but organise mature systems.

Link to synoptic state

Convective initiation is not closely tied to the African Easterly Waves, in comparison with midlatitude cyclones for example.

Initiation is strongly controlled by •  Time of day

•  Surface forcing •  Mesoscale triggers (e.g. convergence

lines, gravity waves).

Can we improve on this if we define the synoptic environment better.?

Squall line initiations; Fink and Reiner 2003

10° X X

1700 UTC, 27 July 2006

AMMA AOC.

B223 case study: 31 July 2006 “The Mummy”

Parent storm Band of cloud Daughter storm

•  Gravity wave emitted from the parent storm may have played a part in the development of the daughter storm

•  Could have been a ‘bore’ which travelled along CBL-SAL interface

•  Could have been a ‘wave-front’, covering the depth of the troposphere

Daughter storm

Gravity wave

Taylor et al. 2010. QJRMS

Mapes (1993)

Gravity wave-fronts

Marsham and Parker (2006)

n=2 n=3

•  The waves extends over the entire troposphere

•  n=1 mode travels the quickest •  n=2 and 3 are slower •  Important over the tropics – lots

of deep convection and influence of the Coriolis force is lower

•  A surprisingly small number of model studies of observed cases (non-idealised), none over west Africa

θ (K)

n=1 n=2

MCS

Bores and solitary waves

Elevated inversion layer

Stable nocturnal BL

Density current

Observed in US storms and over Australia

ρ1

ρ2

ρ0

Gravity currents and waves in the lab.

Aaron O’Leary •  Wave displaces air upwards – could trigger new deep convection •  Waves could continue propagating long after density current has been eroded by the

surface fluxes

Exploring the dynamics with the Met Office Unified Model (MetUM)

• Met Office Unified Model global-12km-4km •  4km explicit convection •  12Z, 30th July 2006 with ECMWF analysis produced best results

See Birch et al. (2012), QJRMetS

15-‐18Z 30th July 2006

18-‐21Z 30th July 2006

21-‐00Z 30th July 2006

Storm initiation and development

TRMM MetUM - control


00-‐03Z 31st July 2006

03-‐06Z 31st July 2006

06-‐09Z 31st July 2006



09-‐12Z 31st July 2006

12-‐15Z 31st July 2006

15-‐18Z 31st July 2006



18-‐21Z 31st July 2006

21-‐00Z 31st July 2006

00-‐03Z 1st Aug 2006



Rainfall rates


Organisation by a synoptic-scale trough (not shown).

Soil moisture and initiation

Soil moisture

Cold cloud

Observations Model

5°W 5°E

•  New convective cells initiate on dry soil but close to strong soil moisture gradients

Soil moisture and initiation

Observations Model


Gravity waves

11Z 31st

Upward and downward displacement of air by wave, n=2

Gravity waves


Gravity waves

11Z 31st


Gravity waves

•  W1 travels towards the northwest at ~15.7 m s-1

•  W2 travels towards the northwest at ~ 20.2 m s-1

•  W1 sets up environment for W2 •  Second example of initiation by waves

Wave speed calculation

•  The waves appear to be wave-fronts rather than bores •  Assuming that the tropopause acts as a rigid lid, the vertical

wavelength (λz) of the wave can be estimated using the equation:

where: n is the wave mode = 2 c is the phase speed = 17.5 m s-1

N is the Brünt-Väisälä frequency = 0.01 s-1

Gives a vertical wavelength of λz ≈ 11 km, which is approximately equal to the depth of the troposphere in this case.


Triggering of the B223 storm

•  Larger-scale synoptic state determined the existence of the storm.

•  Soil moisture pattern determined the location of the storm.

•  Gravity wave determined the timing of initiation of the storm.

•  The operational model was capable of capturing all this ... with considerable trial and error.


“Conclusions”

•  Forecasting convection in this region is a balance between the synoptic control and the mesoscale triggering. Synoptic control seems to provide predictability.

•  Can we do more to understand the synoptic control, through better conceptual models?

•  The forecaster needs to deal separately with questions of initiation and organisation/maintenance.

•  Models can capture these processes a posteriori, but for forecasting we have some way to go.

•  We are preparing a “Forecasters’ Handbook” for this region: Chapter 3 (Lafore et al.) will be “Convective systems”.

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