Scientific/Technical/Management Section
(A) Objectives and Expected Significance of the Proposed Research
A.1 Motivation and Objectives
Vulnerability of West African societies to climate variability is likely to escalate in the
coming decades as demands on resources increase in association with one of the World’s
most rapidly growing populations. There is an urgent need to improve predictions of
West African monsoon rainfall variability, and to increase our confidence in the predicted
impact of anthropogenic climate change in this region. We are currently hindered in
meeting this need due to a combination of poor dynamical models, gaps in our
knowledge and inadequate exploitation of available observations. This proposal is
concerned with improving our knowledge and understanding of processes that influence
rainfall variability at intraseasonal timescales, especially as this relates to extreme wet
and dry periods.
In this proposal intraseasonal variability refers to timescales shorter than the season but
longer than the timescales associated with individual weather systems such as synoptic
African easterly waves (e.g. Reed et al, 1977, Berry and Thorncroft, 2005, Kiladis et al,
2006), synoptic convectively coupled Kelvin waves (e.g. Mounier et al, 2007, Mekonnen
et al, 2008) and the ubiquitous Mesoscale Convective Systems (MCSs, e.g. Laing and
Fritsch, 1993, Hodges and Thorncroft, 1997). There are two distinct periods that typify
the observed intraseasonal variability: 10-25 days, the cause of which remains uncertain
(e.g. Mounier et al, 2008) and 25-60 days which, although climatologically weaker, may
be related to the relatively better understood MJO (e.g. Mathews, 2004 and Janicot et al,
2008 and refs. therein, Maloney and Shaman, 2008).
While a considerable amount of research has been carried out on, the relatively long,
seasonal-to-decadal timescales (e.g. Lamb 1978ab, Nicholson 1978, Ward, 1998,
Giannini et al, 2003) our knowledge and understanding of the intraseasonal variability
and that associated with extremes is very limited. Such extremes are important in their
own right, substantially impacting water and food resources as well as infrastructure. A
recent extreme wet period in the West African region occurred during the summer of
2007 and lead to severe flooding and the displacement of more than 500,000 people (this
extreme event also affected other parts of tropical Africa). Long dry spells at certain
sensitive times in the growing season, especially around the monsoon onset, can also
severely impact food security. We continue to lack information about the nature, the
causes and predictability of such variability and related extremes in the West African
region.
While there is considerable motivation to study intraseasonal variability in its own right,
it is important to remember that the sum of these intraseasonal events comprises the
seasonal mean. Indeed, the limited work that has taken place on intraseasonal timescales
over West Africa (e.g. Mounier et al. 2008; Janicot et al, 2008) has highlighted structures
that resemble the patterns of variability identified at interannual and decadal timescales
(e.g. Chen et al. 2001, Chelliah and Bell, 2004, Aiyyer and Thorncroft, 2008). It is clear
that systematic errors in dynamical models used for climate prediction are often
manifested on short timescales (from hours-to-days) which further motivates the study of
intraseasonal variability of rainfall in this region from observational as well as modeling
perspectives.
Motivated by these issues the key objectives of this proposal are:
(i) To document the nature of the intraseasonal variability in rainfall over West
Africa emphasizing extreme wet and dry periods.
(ii) To explore the dynamical control of the documented intraseasonal
variability in rainfall including the large-scale impacts on water vapor transport
and the role of land surface conditions.
(iii) To evaluate the extent to which dynamical models used for climate prediction
can predict intraseasonal variability in rainfall over West Africa, including
extreme wet and dry periods; and to highlight where potential problems lie.
A.2 Expected Significance
The following bullets highlight the expected significance of this work:

The documentation of the rainfall variability at intraseasonal timescales,
especially as this relates to extreme wet and dry periods, fills an important gap in
our knowledge of the West African monsoon (WAM). This information is
important for scientists concerned with improving dynamical models used for
prediction of rainfall and it is important for scientists and users concerned with
applications (e.g. flooding, crop failures).

The assessment of predictability and causes of extreme wet and dry periods within
the rainy season is an important contribution to our understanding of how the
WAM works and also to those actively involved in forecasting in the region.
Results will be communicated to the Africa Desk at NCEP and to West African
Forecasters through the joint AMMA-THORPEX working group (chaired by the
PI).

The evaluation of dynamical models used for climate prediction to represent and
predict the intraseasonal variability of rainfall including wet and dry extremes is
an important contribution to highlighting the problems that climate models have
in this region.

The work will support recommendations for future monitoring of intraseasonal
variability of rainfall, including extreme wet and dry extremes, needed to support
prediction and to assess the impacts of anthropogenic climate change in the
region.

Although the emphasis is on West Africa, the results will also be significant for
other tropical and possibly midlatitude regions due to forced teleconnection
patterns in association with variability in heating. For example, the intraseasonal
variability in rainfall over West Africa very likely impacts variability in the
tropical Atlantic including tropical cyclones through its impact on the
environment downstream.
(B) Technical Approach and Methodology
Overview
The main focus of this work will be on the intraseasonal variability in rainfall that
characterized the summers of 2005, 2006 and 2007. The motivation for this is three-fold:
(i) focusing on a relatively few years facilitates a process-study approach (ii) the three
years fall within the African Monsoon Multidisciplinary Analysis (AMMA) Enhanced
Observing Period (EOP), and includes the Special Observing Period (SOP) year in 2006
(see below), and (iii) the three years were characterized by marked intraseasonal
variability in rainfall. Figure 1 shows a time-series of the total number of convective
systems seen by the TRMM 85GHz microwave imager (following Mohr and Thorncroft
(2006)) in the West African region in 2005, 2006 and 2007 (henceforward referred to as
the EOP years). Given that most of the observed rainfall is associated with these systems,
this time-series highlights the marked intraseasonal variability in rainfall with an
approximate 2-week period dominating 2006 and 2007 in particular. It should be noted
that the peak in activity at the end of August 2007 was associated with the devastating
floods over much of West Africa at that time. Also, the dry spell in June 2006 was
associated with a delayed monsoon onset. In contrast to 2006 and 2007 that were strongly
influenced by intreaseasonal variability in the 10-20 day range, the 2007 season appears
to have been influenced by a slower intraseasonal variation, in the 25-60 range that may
have some relation to the MJO (Mathews, 2004, Janicot et al, 2008, Shaman and
Maloney, 2008).
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Figure 1: Time-series of the number of
convective systems as seen by TRMM 85GHz
channel (following Mohr and Thorncroft, 2006),
and for the region between XX and XX and XX
and XX.
The general approach proposed here is to explore the nature and causes of the
intraseasonal variability highlighted in Figure 1 through detailed analysis of the events in
these years, taking advantage of the special AMMA observations, satellite products and
arguably superior NWP analyses for this period (See below). While the emphasis is on
just three years any conclusions or hypotheses reached based on these process studies can
be tested on longer datasets and this comprises a goal for this project. For example we
can use other previous years as cross-validation of the findings for the three years
examined here.
Consistent with the AMMA philosophy and the design of the AMMA field program we
will take a multi-scale approach that combines a regional perspective focused on analysis
of the West African region and how this interacts with the rest of the globe, and a local
perspective focused on assessment of how the intraseasonal variability is manifested in
Niamey, Niger, a focal point of AMMA. We aim to take advantage of the in situ
observations provided by AMMA to achieve this (See Fig. 2). The key in situ
observations for this project (e.g. radar/raingauges for rainfall, and radiosoundings/GPS
for water vapor) will also support some evaluation of the satellite products, that will be
vitally important for the sustained observing system in the region.
The proposed work is organized around the three overarching objectives presented in
Section A above: B.1 Documentation of Rainfall Variability, B.2 Role of Dynamical
Control and Water Vapor Transport, and B.3 Evaluation of Climate Models.
B.1 Documentation of Rainfall Variability
(a) Introduction and Key Scientific Questions
Only a handful of recent studies have been concerned with intraseasonal variability of the
WAM (Sultan and Janicot, 2003, Mathews, 2004, Mounier et al, 2008, Janicot et al,
2008, Maloney and Shaman 2008). Sultan and Janicot (2003) were the first to highlight,
in a climatological sense, the presence of significant intraseasonal variability. They
identified variability at two distinctive timescales, 10-25 days and 25-60 days with the
former contributing most to the total variance.
With one of the collaborators on this proposal, Mounier et al (2008) recently explored, in
more detail, the nature of the 10-25 day variability clearly visible in Figure 1(b,c) above
and proposed the existence of a Quasi Biweekly Zonal Dipole (QBZD) structure based on
a regional EOF analysis. The “dipole” aspect of this refers to a nearly standing oscillation
with an out-of-phase relationship that African rainfall has with rainfall in the Western
Atlantic and Americas.
Mathews (2004) suggested that dry spells over West Africa (linked to the 25-60 day
band) could be linked to a combination of equatorial Kelvin and Rossby waves forced in
the Pacific and linked to the MJO. The same collaborator as above also co-authored a
paper with Janicot et al (2008) that was more focused on the 25-60 day variability. They
also highlight the relationship with the MJO and an associated coupled equatorial Rossby
wave. Separate from equatorial wave dynamics these authors also suggested a link
between intraseasonal variability of the Asian monsoon and variability of the WAM
rainfall at this 25-60 day timescale.
Based on the very limited previous work and lack of any firm conclusions or clear
understanding (see B.2 below), it is important to investigate the nature of the
intraseasonal variability of WAM rainfall in more detail (at both 10-25 days and 2560days); including how it is manifested in terms of the variability of the weather systems.
The key scientific questions that will be addressed in this part of the study are:

What is the nature of the intraseasonal variability in rainfall observed over Africa
in 2005-2007? What is the spatial structure of rainfall anomalies associated with
these variations? Does this coherently vary with regions remote from the African
continent? Is there evidence for the regional rainfall anomalies propagating into
the region or do they develop in situ?

How is the intraseasonal variability of rainfall manifested in variations in
synoptic and mesoscale weather systems in the African region?

How is the intraseasonal variability of rainfall manifested in local variations in
rainfall?
(b) Key Datasets
Satellite Products
Key satellite products relevant to this proposal include:


Rainfall (CMORPH, TRMM)
Convective characteristics (OLR, TRMM, CLAUS for previous years (19832004) and for the EOP years if it becomes extended during the project)
AMMA field campaign data
The AMMA field program provided enhancements to the sustained observing system in
West Africa building on the CATCH hydrological experiment. The CATCH
observational “window”, indicated in Fig. 1, includes 3 mesosites that sample contrasting
environments across the marked north-south gradient in surface conditions. Extra in situ
observations were made at the mesosites and along the climate transect within the broad
CATCH window to address science issues at local-to-regional scales. In addition,
AMMA provided enhancements to the regional observing system over West Africa and
in the Gulf of Guinea to support this analysis at regional scales. AMMA is a multi-year
project with 3 nested observation periods, a long-term observing period (LOP), an
enhanced observing period (EOP: 2005-2007) and a special observing period (SOP)
which took place in 2006. More details of the complete observational suite can be
obtained from http://ammma-international.org.
Embedded within the multi-year framework, the SOP in 2006 supported detailed studies
of key processes, impractical to study in a multi-year framework. The datasets at the heart
of this proposal are: the MIT radar in Niamey (supported by NASA Water Cycle
Program), and raingauges at the local-to-mesoscale, and radiosoundings and NWP
analyses at the regional scale. Satellite products will be used to support the analyses
across all scales. They provide us an opportunity to analyse and better understand the
nature and causes of intraseasonal rainfall variability including the roles played by
dynamics, water vapor transport and land surface conditions.
Figure 2 Field implementation of AMMA observations (From Redelsperger et al, 2006)

MIT radar data
The MIT Doppler radar was deployed in 2006 and 2007 on the periphery of the
International Airport in Niamey (see Fig. 2), and operated nearly continuously (24
hours per day) from July 1 to September 30. Full volume scans were taken at 10minute intervals with interspersed RHI scans through episodes of deep
convection.

AMMA Raingauges
The extensive AMMA raingauge network is nicely situated under the region of
high resolution radar surveillance and was operated throughout the EOP,
providing daily rainfall values.
(c) Methodology
At the heart of this work will be a space-time analysis of satellite-estimated rainfall from
CMORPH. The high temporal (30 minutes) and spatial (8km at the equator) resolution
lends itself to the analysis of intraseasonal rainfall variability that is required here. The
CMORPH product is available for the three EOP years central to this proposal but we
will also consider summers back to 2003 as well as years subsequent to the EOP. To
corroborate the conclusions from this work we will carry out parallel analyses based on
TRMM estimated rainfall, OLR and CLAUS if available. We will band-pass filter the
data in the 10-25 and 30-60 day ranges in order to emphasize the regional and more
slowly varying intraseasonal signals (thereby removing the synoptic and mesoscale
contribution). We will explore the nature of the signal using a combination of daily maps,
hovmoellers and time-series analysis at a number of key locations that will include
Niamey (a major AMMA mesosite and location of the MIT radar). Although propagation
characteristics may be visible in these diagnostics, we will also carry out space-time
filtering (Wheeler and Kiladis, 1999) of the data to highlight separately the roles of
westward and eastward propagation if present. We will highlight the repeatable aspects of
the variability through this analysis, and will support this through the use of composites
where appropriate.
Assessment of how the intraseasonal variability is manifested at the synoptic easterly
wave scale will be achieved by space-time filtering the CMORPH data in the tropical
depression (TD) band (cf Kiladis et al, 2006). Maps, hovmoellers and time-series of areaaveraged variances of this diagnostic will clearly show any coherent variations in easterly
wave activity. At the mesoscale we will use TRMM observations to highlight the
variability in Mesoscale Convective Systems (MCSs). Following Mohr and Thorncroft
(2006) we will analyse variability in the number of convective systems using the 85GHz
microwave imager. Indeed Figure 1 already provides us with evidence that the number of
convective systems are likely strongly influenced by the intraseasonal variability at both
10-25 days and 30-60 days. Variability of MCS activity and characteristics can be
assessed using the TRMM 2A23 product, that distinguishes convective and stratiform
rain amounts, following Schumacher and Houze (2006).
At the local scale, we will focus on the AMMA observations located in the Niamey
region. In particular we will combine analysis of MIT radar reflectivity and rainfall
estimates (using standard Z-R relationships as well as derived Z-R relationships for this
location) to explore how the intraseasonal variability is manifested at a particular
location. The radar can also be used to derive MCS characteristics (convective and
stratiform contributions) to assess how these are impacted by the intraseasonal
oscillations and also to compare with the TRMM 2A23 view above. Where appropriate
we will also make use of the daily raingauge data in the Niamey region to support this
more local analysis.
B.2 Role of Dynamical Control and Water Vapor Transport
(a) Introduction and Key Scientific Questions
We know very little about the causes of the intraseasonal variability characterizing the
West African monsoon. The key research on this topic has mainly been carried out by
Serge Janicot and co-workers including one of the collaborators on this proposal. Sultan
and Janicot (2003) using composite techniques identified a westward moving cyclonic
vortex emanating out of East Africa and suggested that associated enhanced poleward
moisture transport on the eastern side of the vortex had a role to play in determining
variability at 10-25 day timescales. In contrast, Mounier et al (2008), using compositing
techniques based on a regional EOF analysis suggested that the QBZD structure is
controlled by a combination of equatorial atmospheric dynamics through a “Kelvinwave-like” disturbance propagating eastwards towards Africa and by land surface
processes over Africa that enhance moisture transport towards the continent during the
dry phase. These dynamical explanations of the 10-25 day variability should be evaluated
in more detail but other explanations may also be possible. For example, it may also be
important to consider in more detail the role played by intraseasonal variability in the
Asian monsoon region. It may also be the case that the observed “Kelvin-wave-like”
structure in Mounier et al (2008) is passive rather than active in this; so rather than
“causing” the development of a wet period over Africa it simply represents the response
to the cessation of the wet period over the West Atlantic-Americas.
Mounier et al (2008) hypothesized that the surface conditions also have a role to play at
10-25 day timescales although their analysis was not conclusive. They argue that the
reduced cloud cover over the land in dry periods results in a warming of the surface and a
decrease in surface pressure that encourages an onshore flux of low-level water vapor
that is separate from the contribution of the equatorial Kelvin waves. Irrespective of the
validity of this mechanism it is important to assess the extent to which the surface
conditions impact the nature and predictability of the intraseasonal variability, and
especially the extremes.
At the 25-60 day timescale two different mechanisms have been proposed. Mathews
(2004) highlighted the role of dry eastward propagating equatorial Kelvin waves and dry
westward moving equatorial Rossby waves emanating from an MJO in the West Pacific
warm pool region. On arrival in the West African coast these waves can either affect
rainfall through modification of the regional moisture transport or through their impact on
large-scale vertical motion. In contrast, Janicot et al. (2008), tie the WAM variability at
this timescale to the MJO, and a westward propagating convectively coupled equatorial
Rossby wave from the Indian sector.
There are two basic areas of research that need to be addressed – the fundamental causes
of the intraseasonal variability in rainfall at 10-25 day and 25-60 day timescales and the
mechanisms through which this impacts the main weather makers in the region (namely
the African easterly waves and MCSs).
The key scientific questions that will be addressed in this part of the study are:

What are the dynamical causes of the pronounced intraseasonal variability in
rainfall in the tropical African region? Is there a role played by remotely forced
equatorial or other dynamical waves? Does it involve interactions with heat
sources over Central America or Asia? Do land-surface conditions have a role?

What is the mechanism through which the intraseasonal variability of rainfall
relates to variability in synoptic and mesoscale weather systems? Is the
variability in regional moisture transport and associated moisture convergence
key and/or does variability in the African easterly jet have a role?
(b) Key Datasets
Satellite Products
Key satellite products relevant to this proposal include:



Rainfall (CMORPH, TRMM rainfall)
Convective characteristics (OLR, TRMM, CLAUS for previous years (19832004) and for the EOP years if it becomes extended during the project)
3D Water Vapor (AIRS/AMSU-A, MLS)
NWP analyses
In the proposed work here we plan to utilize ECMWF and NCEP operational analyses.
Due to the extra AMMA radiosoundings launched and reaching the GTS, (especially in
2006 and 2007), these analyses are likely far superior to those available in previous years.
We will also look at reanalyses for this period as they become available (ECMWF and
NCEP are planning special reanalyses for the 2006 summer season).
AMMA field campaign data

Radiosondes
One of the major achievements of AMMA in the past few years has been the
improvements to the radiosounding network. This has included establishing new
stations, refurbishing existing stations, updating communications and providing
higher frequency launches at stations across the whole of West Africa. During the
SOP in 2006 soundings were launched 4 x daily at the six core stations indicated
in Fig. 2, and 8 x daily for two periods (20-29 June, and 1-15 August). Between
June and September 2006, around 7000 radiosondes were released on the
network, an unprecedented number. Many of these were assimilated into the
operational analyses at ECMWF and NCEP. Based on this we expect the
operational analyses to be superior compared with other recent years during
which the network has been in decline. In 2007 a reduced network compared to
2006 was operational but substantially better than that prior to AMMA including
2005 which was close to pre-AMMA levels with only minor improvements
having been made by then.

GPS Stations
Seven GPS stations were operated and run by AMMA in the region providing in
situ water vapor profiles that will support the local analysis of water vapor
transport and comparison with satellite products (see Figure 2 for locations). This
includes a station at Niamey which will be the focus of the local analysis. The
GPS stations (including the station at Niamey) are available for the EOP and are
still in the field.
Land surface data

GLDAS – Provides information about the land surface state that will be
considered here (e.g. soil moisture and surface temperature). Based on multiple
offline land surface models (see Rodell et al, 2004) these datasets are available for
the EOP.
(c) Methodology
We will make extensive use of NWP analyses and satellite water vapor products to
explore the role of dynamics and associated moisture transports in the intraseasonal
rainfall variability. At a basic level, this will include an examination of maps (e.g.
unfiltered winds, water vapor, moisture fluxes and their convergence) and hovmoellers
for all the cases in the EOP period along with spectral analysis of rainfall, OLR, and
dynamical time series from AMMA observations and reanalysis. Attempts will be made
to highlight the key repeated features that characterize these events in order to shed light
on their causes, and ultimately their predictability. If appropriate we will use compositing
techniques to emphasize these features, either based on just the EOP events or on longer
available datasets if deemed more appropriate (ie to ensure statistical significance). This
basic analysis will help expose the potential roles played by remotely forced dynamical
waves (Mathews, 2001, Mounier et al, 2008, Janicot et al, 2008), westward moving
cyclonic vortices (Sultan and Janicot, 2003) as well as interactions between heat sources
over Africa, Americas/West Atlantic and Asia.
At a more sophisticated level, we will combine dynamical fields and related moisture
transports from the NWP analyses with space-time filtered CMORPH to assess the
potential role played by remotely forced equatorial waves including eastward moving
Kelvin waves and westward moving Equatorial Rossby and mixed Rossby-Gravity
waves. Their role will be assessed again using a combination of spectral analysis, maps,
hovmoellers and compositing if appropriate.
We will compare the evolution of the documented intraseasonal variability during the
EOP with the surface conditions (e.g. surface pressure, temperature, soil moisture)
alongside the satellite view of rainfall and cloudiness (e.g. CMORPH and OLR). To
facilitate the comparison we will band-pass filter the variables in the 10-25 day band.
Again we see value in considering all the intraseasonal events during the EOP, using a
basic analysis of maps, hovmeollers and time-series for key locations (including
Niamey). If appropriate we will again use composite analysis to highlight the repeatable
features of the intraseasonal oscillations. We will evaluate the extent to which anomalous
surface conditions and fluxes were present before the establishment of a wet or dry period
as suggested by Janicot et al (2008). Such a phase lag with respect to the rainfall anomaly
would suggest an important role for the surface conditions that would likely impact
predictability of the amplitude as well as timing of the intraseasonal event. A comparison
between this analysis and that concerned with the equatorial waves carried out in B.4 will
help us assess the extent to which the land surface conditions are crucial to the
intraseasonal event timing or whether they are more related to the intensity.
We will explore whether the variability in meso and synoptic scale weather system
activity varies in a coherent manner with intraseasonal variability in the large-scale
moisture transports (based on NWP analyses and satellite products) and with
intraseasonal variability in the African Easterly Jet (based on NWP analyses). Motivated
by the work of Hall et al (2006) and Thorncroft et al (2008) we will also assess whether
variability in upstream MCS activity has a role to play in determining the observed
variability in African easterly waves. Such a multi-scale analysis is fundamentally
important for understanding the key scale interactions in the WAM that need to be well
represented by dynamical models.
We will also ensure that the regional approach is interpreted at the local level by
exploring how this variability is manifested in Niamey. In addition to the analysis of
radar and raingauges proposed in B.3 we will compare our analysis of water vapor
transport, based on NWP analyses and satellite, with in situ GPS measurements of water
vapor provided by AMMA.
B.3 Evaluation of Climate Models
(a) Introduction and Key Scientific Questions
Confidence in climate predictions in this region will be increased if the dynamical models
used for climate prediction were able to predict the dominant intraseasonal variability in
rainfall at the heart of this project. Intraseasonal variability represents an ideal timescale
at which to evaluate the fidelity of dynamical models used for climate prediction.
The work carried out in B.1 and B.2 above will highlight the nature and causes of the
variability in the EOP years. The results will also be more generally relevant (which will
be highlighted by the composites). The knowledge gained from these earlier parts of the
project will be used to evaluate the ability of dynamical models to predict both the nature
and frequency of the events (in a seasonal forecast mode) as well as of particular events
identified in the EOP years (in medium range or weather forecast mode).
The key scientific questions that will be addressed in this part of the study are:

To what extent do dynamical models used for climate prediction predict the
intraseasonal variability in weather forecast mode? Can they skillfully predict the
onset, duration and intensity of particular wet or dry periods?

To what extent do dynamical models used for climate prediction represent the
nature of the intraseasonal rainfall variability in climate forecast mode?

What is the nature of the systematic errors in the weather and climate forecasts?
Are they similar? Based on the analysis of the intaseasonal variability in the EOP
what are the likely causes of these errors?
(b) Key Datasets
NWP Reanalyses
During the lifetime of this project we expect to be able to take advantage of the
reanalysis provided by NASA based on the climate model GEOS5 – MERRA
(Modern Era Restrospective Reanalysis for Research and Applications) that will
be available for the years 1979-to-present. This will include a rainfall product as
well as the normal suite of meteorological variables.
Forecasts made by GEOS5
Model forecasts made with GEOS5 will be available at 0.5o and 1.0o horizontal
resolutions, appropriate for the scales of interest in this project. Forecasts at 15days and 1-10 days will be made available by the GEOS5 team for the whole
EOP period. These will include runs forced with observed SSTs as well as fully
coupled atmosphere-ocean runs.
Max: Ideally we would like forecasts out to 15 days andfollow this up with a look
at seasonal forecasts with the same model.
(c) Methodology
We will evaluate the ability of the NASA GEOS-5 climate model to represent
intraseasonal variability of rainfall in “weather mode” by comparing forecasts of the EOP
intraseasonal events with the analysis of these events in B.1 and B.2. This will be
achieved by comparison of maps, and hovmoellers of key variables identified in B.1 and
B.2. Indeed it will be a goal of this work to establish a key set of metrics for future
monitoring and evaluation of NWP models. Such metrics will have a regional (based on
satellite and NWP analyses) as well as local aspect to them (focusing on Niamey and
taking advantage of the sustained observations at this site). Based on the knowledge
gained in B.1 and B.2 we will identify any systematic errors in the representation of the
intraseasonal variability as well as some of the potential problems that these relate to.
Such information will be fed back to the GEOS5 development team through the
collaboration that will be established (see section E below). We will explore the impact
of running the GEOS5 in “AMIP-mode” (with prescribed observed SSTs) as well as the
fully coupled mode that relates more closely to how the model would be run in “climate
mode”. In addition we will explore the sensitivity to the representation of the land
surface (Max – what can be done here?)
In addition we will evaluate the nature of the intraseasonal variability of rainfall in
dynamical model in “climate mode” by exploration of seasonal forecasts made for the
EOP years using the NCEP climate model (Max – can we not say GEOS5 here?). Rather
than focusing on particular dates (although this can be looked at, especially at the
beginning of the forecast), the emphasis here would be on the nature of the intraseasonal
variability compared to that observed in B.1 and B.2. These analyses will be compared
with the analysis for the forecasts in “weather mode” in order to assess the extent to
which systematic errors are similar at the different lead times.
Before the end of this project we expect the next suite of IPCC climate change forecasts
to become available. Should this happen we will endeavour to evaluate the fidelity of
these models to represent the intraseasonal variability of WAM rainfall highlighted in this
project. This will be achieved using a combination of time-filtering and space-time
filtering and using the metrics established above.
(C) Perceived Impact of Proposed Work to the State of Knowledge in the Field
Our current state of knowledge and understanding of intraseasonal variability of rainfall
in the West African region is extremely limited. The role this has on the nature of
extreme wet and dry periods is virtually nil. This project brings together the ideal set of
datasets, diagnostic tools and expertise in order to make substantial leaps in our
knowledge and understanding of this area.
We will:

Highlight in detail the nature of individual intraseasonal events during a 3 year
period that was better observed in the West African region than ever before, both
from a satellite perspective as well as from an in-situ observing perspective. We
will provide some emphasis to the extreme events that has not been done
previously.

Highlight the processes that explain the intraseasonal events in these years and in
general. Given the limited published literature on this we are far from having
consensus on this – we will endeavour to provide the definitive work in this area.
This will include a description of the role played by dynamics and associated
water vapor transport as well as the possible role of the land surface – both
required in order to asses the predictability of the intraseasonal events.

We will establish metrics to describe the intraseasonal variability succinctly and
appropriately, to support evaluation of climate models and long-term monitoring.
(D) Relevance of Proposed Work to NASA Programs
The proposal is concerned with intraseasonal variability of rainfall over West Africa
with an emphasis on the extreme wet and dry periods that they are sometimes associated
with. Special emphasis given to improving our understanding of the casues of this
variability including the role played by large-scale dynamics and associated water vapor
transport as well as the role of surface conditions. It also includes evaluation of climate
models to predict these events and thus directly addresses the solicitation.
In addition:
 It contributes to all five scientific priorities outlined in the NEWS implementation
plan.
 It fills a key gap in the current NEWS team by addressing variability in a
monsoon system (that also impacts the US through its influence on tropical
cyclones).
 Collaborations are expected with many of the current members of the NEWS
team (especially Adler, Koster, Liu, Peters-Lidard, Waliser, Wentz). It is directly
relevant to the integration project on “Daily Time Scale” and some interactions
with the “Golden Years” integration project may also be useful.
 Analysis of in situ data will highlight deficiencies (if present) in NASA satellite
products for the West African region.
 Evaluation of the NASA GEOS5 model and relevant feedback is an essential
activity towards improving this NASA climate model.
 The work will be a major contribution to the International AMMA program that
involves substantial interactions between Africans, Europeans and US scientists.
The linkages that AMMA provides with African scientists, forecasters and users
of climate information will ensure that this NASA supported research will have a
high impact in Africa.
(E) Plan of work, milestones, accomplishments, management structure,
collaborations
Chris Thorncroft will manage the project. He will oversee the work taking place in
Albany with the postdoc and will make the appropriate linkages to the collaborators, two
of which he is collaborating with already. A brief description of all participants and their
role is given here.
Gareth Berry (Post Doc): Gareth is currently completing his PhD with the PI. He is
currently working on scale interaction issues between African easterly waves and
convection using satellite products (including CMORPH and TRMM), NWP analyses,
and running WRF. He is an excellent student with two papers in print already and several
others in progress – one of which is concerned with evaluating NWP models to represent
African easterly waves and associated rainfall in 2007. He is ideal for this project.
George Kiladis (NOAA-ERL) (Collaborator): George is currently collaborating with the
PI on the nature and the observed nature of African easterly waves and has also been a
co-author on the few papers that have been written on intraseasonal variability of West
African rainfall coming out of Serge Janicot’s group in Paris. George will participate in
this project in all aspects, providing expertise in the use of space-time filtering as well as
in the area of intraseasonal variability in general.
Karen Mohr (University at Albany) (Collaborator): Karen has been collaborating with
the PI for a number of years on the nature and variability of convective systems in the
West African region. Karen will contribute to the project through provision of
observations of the convective systems based on the TRMM 85GHz microwave sensor.
She will also interact on other aspects of the project including providing advice and
expertise on the use and interpretation of satellite products as well as in the area of land
surface interactions (one of her areas of expertise).
Earle Williams (MIT) (Collaborator): Earle and the PI collaborated together to achieve
the deployment of the MIT radar in Niamey in 2006 and 2007 (with substantial
contributions made by the NASA Water Cycle program). Earle is currently collaborating
with the PI on an NSF grant that deals with details analyses of the nature of the MCSs.
Earle will provide the radar data and rainfall estimates for 2006 and 2007, and will also
interact on other aspects of the project including advice on interpretation of the radar data
and other in situ observations in the Niamey region.
Max Suarez (NASA Goddard): Max is the lead scientist for modeling in the GEOS-5
management team…..
In addition we expect a number of more informal collaborations with AMMA colleagues
including those involved in the International Working Groups on Wesat African
Monsoon and Global Climate, Water Cycle, Land Surface, and the joint AMMATHORPEX WG on High impact Weather (chaired by the PI). This will be achieved
through e-mail and attendance of AMMA meetings.
Research Topic
Milestones
Year 1:
Start B.1
M1: 3 Months (Retrieve and store all needed
Satellite Products, NWP Analyses, and In Situ data)
M2: 6 Months (Rainfall Analysis Completed)
Start B.2
Year 2:
Continue B.2
M3: 12 Months (Write First Paper)
M4: 24 Months (Dynamical Control work
Completed)
M5: 24 Months (Write up Paper(s) on B.2)
Year 3:
Start B.3
M6: 25 Months (Establish Metrics for Model
Evaluation)
M7: 30 Months (Complete Evaluation of GEOS5
Model in “Weather Mode”)
M8: 36 Months (Complete Evaluation of Forecasts
made in “Climate Mode”)
M9: 36 Months (Write up Paper(s) on B.3