PrecipitationAveraged between ~10ºW - 20ºE

JAS“Wet”

OND“Dry”

Modeling the West African MonsoonRachel McCrary*, Keri Younger°, Eric Maloney* and David Randall*

*Center for Multi-Scale Modeling of Atmospheric Processes, Department of Atmospheric Science, Colorado State UniversityºEmbry-Riddle Aeronautical University, Applied Meterology, Daytona Beach FL

Figure 3. Seasonal climatology of precipitation vs. latitude averaged over all longitudes between 10ºW and 20ºE for GPCP (top), CAM3.5 (middle) and SPCAM3.5 (bottom).

Figure 4. Average July-August-September (JAS) precipitation in mm/day for GPCP, CAM3.5 and SPCAM (Left column). Average October-November-December rain for GPCP, CAM3.5 and SPCAM (Right column).

The West African Monsoon is the term that describes the seasonal rains that occur in West Africa from May to October. Food and water security in the region are directly related to the West African monsoon. Since West Africa is home to one of the World’s most rapidly growing populations, societies in this region are becoming increasingly vulnerable to variability in monsoon precipita-tion. Also, as our climate changes due to increasing greenhouse gas concentrations, it is probable that we can expect changes in the African monsoon circulation which will further influence water resources in the region. Unfortunately, global circulation models (GCMs) which are used to make climate predictions are currently unable to simulate fundamental characteristics in monsoon pre-cipitation over West Africa. This greatly undermines their ability to represent potential changes in the monsoon in a warmer cli-mate. The WAM is a complicated system which involves many interactions between the atmosphere, ocean and land surface. The WAM is also influenced by processes that occur over a range of temporal and spatial scales (Hall and Peyrille, 2006). With this research we are using two unique modeling methods - one with a global model and one with a regional mesoscale model - to try to better understand the complex multiscale interactions which are important for simulating the WAM. The two modeling methods used in this research are: 1. A global simulation using the Multiscale Modeling Framework (MMF) or the Su perparameterized Community Atmosphere Model (SPCAM) 2. A series of regional simulations using the Weather Research and Forecasting (WRF).

0 5 10 15 20 25

USGS - 10 arc minute (1/6º) CAM topography 1.9ºx2.5º

Elevation (m)

GPCP: Seasonal precipitation over this region follows the annual march of the sun, reaching its northernmost extent of ~17ºN in August. The wet season extends from May-October, with the wettest three months being July-August-September.

In both the CAM and SPCAM, precipitation also propagates north-south following the sun. In CAM, precipitation reaches its northern most extent of ~20ºN in August. In SPCAM, precipitation does not penetrate as far northward as observed, and only extends to about 15ºN.

In both models, the wettest seasons occur during the “transition” months of October-NovemberDecember (OND) and March-May-June. This excess of precipitation appears to be due to too much rain occurring near the coastal regions of the Gulf of Guinea.

Spatially, we see that three precipitation maxima occur over the region during JAS. These are along western coast of West Africa, near the Gulf of Guinea, and over the Ethiopian Highlands. Both models have trouble capturing the maxima in precipitation over the Ethiopian Highlands, probably do to poor topographical representation in the model. CAM does not capture the maxima over the gulf of Guinea, however SPCAM does.

The African Easterly Jet (AEJ) devel-ops over this region during the mon-soon season as a dynamical response to the North-South temperature and moisture gradients that occur over West African from the Gulf of Guinea to the Saharan desert.

ERA-I: Jet maximum occurs at ~15ºN and 600 hPa with peak zonal winds reaching ~12-14m/s on average. At 600 hPa easterly winds occur from the equator up to 20ºN and extend from 30ºW - 40ºE .

CAM: AEJ is weaker, less defined, and smaller in its spatial extent. Peak winds only reach 8m/s. The jet is dis-placed westward compared to what is observed, with the jet maximum oc-curring over the Atlantic ocean.

SPCAM: AEJ is similar to that found in CAM, however peak winds do get up to 10m/s and easterly winds do pen-etrate as far east as Saudi Arabia.

In ERA-I, CAM, and SPCAM the low-level westerly monsoon winds are ap-parent in figure _. These winds bring essential moisture onto the continent during the wet season.

Multiscale Modeling Framework: Remove convective pa-rameterizations from a traditional GCM and replace them by embedding a cloud resolving model (CRM) in each grid box (Figure 1.). This allows for the explicit simulation of small-scale cloud and boundary-layer processes (Randall et al. 2003).

Performed two 10-year atmospheric model intercomparison project (AMIP, Fiorino, 2000) style runs forced with ob-served sea surface temperatures from the years 1997-2006:

1. Community Atmosphere Model version 3.5 (CAM). Horizontal resolution of 1.9º x 2.5º 30 levels and a timestep of 30min.

2. Superparameterized CAM version 3.5 (SPCAM, Khair-outdinov et al. 2005). CAM3.5 serves as the “host” GCM, and the CRM used is the system for atmospheric modeling (SAM, Khairoutdinov and Randall 2003) version 6.5.7. The embedded CRM has 32 grid columns with 4-km resolution and 30 levels. The “curtains” of CRMs within each grid cell are periodic and positioned in the north-south direction.

Figure 1. Schematic representing the SP-CAM. From Dave Randall CMMAP presentation.

Figure 2. Topography of Africa from USGS (left) and CAM (right).

Introduction

Global Model

JAS OND

African Easterly Jet

Using eddy kinetic energy as a measurement of African Easterly Wave activity, we see that CAM underestimates wave activity while SPCAM overestimate wave activity. We are actively researching these differences and trying to see if the overly energetic convection found in SPCAM may be a cause for increased wave activity over the region.

Using the methods out-lined in Lavaysse et al. 2009, we identify the loca-tion of the Saharan heat low during May. We see that compared to ERA-I, the heat low is less defined in both CAM and SPCAM. We are currently investi-gating the role that the position/intensity of the heat low has for the gen-eration of the nocturnal low-level jet in SPCAM.

Figure 5. Composite JAS zonal wind from 10ºS-40ºN, 1000-300 hPa from ERA-I, CAM, and SPCAM. Wind speed in m/s. 600 hPa line marked in gray.

Figure 6. Composite JAS zonal wind from at 600 hPa. For ERA-I, CAM, and SPCAM. Wind speed in m/s. Dashed lines indi-cate easterly winds, solid lines are westerlies.

AEJ

Figure 7. Composite eddy kinetic energy (u’+v’)/2, for JAS from ERA-I, CAM, SPCAM. We have applied a 5-day running average to u’ and v’ to help isolate AEW activity.

Precipitation

Afric. East. Waves

Nocturnal Low Level Jet Saharan Heat Low

Figure 9. Composite po-sition of the Saharan Heat Low using the detection method outlined in La-vaysse et al. 2009. Con-tours are in percent, indi-cating how frequently the most extreme low pres-sures occur in that region of Africa.

Regional Simulation with WRF

Figure 8. Diurnal cycle of wind speed (m/s) at Niamey, Niger from May 2006. Top left figure from Lothon et al. 2008, wind speed taken from the wind profiler lo-cated at 13º29’N, 2º10’E, 205MSL. Top right figure from ERA-I, grid point closest to the wind profiler station. Middle right figure from CAM and bottom right figure from SPCAM. In the model derived figures, the boundary layer depth is represented by the thick black line.

During the monsoon season, a nocturnal low-level jet develops over West Africa due to the large-pressure gradient that occurs between the Saharan heat low and the Gulf of Guinea. At night, when surface fluxes of moisture and heat are low, the boundary layer is shallow and the free-atmosphere decouples from the boundary layer. This allows wind speeds to pick up near the surface. During the day, when surface fluxes are large, turbulent mixing occurs, causing the boundary layer to deepen and preventing strong winds from developing near the surface.

While the low-level jet is appar-ent in ERA-I and in CAM, SPCAM fails to represent the nocturnal-low level jet during May. We are investigating why SPCAM has this problem, and we believe it may have to do with the intensity of the Saharan heat low and the position of the intertropical discontinuity.

We are currently doing a series of re-gional simulations using WRF. We hope to use these runs to try and un-derstand the influence that of African Easterly Waves have on convection over the region.

We have run WRF using a nested domain configuration with the following domain sizes: 1. Coarse domain ~5ºS - 35ºN, 30ºW-25ºE, with 36km resolution 2. Finer domain ~ 0º - 30ºN, 25ºW- 20ºE, with 12km resolution

We have forced WRF using ERA-I data from summer 2006 and are currently trying to validate our model configura-tion. We next plan to do a series of runs where we filter AEW information out of the ERA-I input data and look to see how this may change the charac-teristics of convection over the region.

Figure 10. Example of model domains used in our WRF simulation. Outer box represents the coarse dimension, inner box labeled d02 represents the finer domain. This work is being done in collaboration with Keri Younger, a CMMAP intern.

ReferencesFiorino, M., 2000: “AMIP II sea surface temperature and sea ice concentrations observations. ”http://www-pcmdi.llnl.gov/projects/amip/AMIP2EXPDSN/BCS_OBS/amip2_bcs.htm Hall, N. M. J and P. Peyrille, 2006: Dynamics of the West African Monsoon. J. Phys. IV France,139, 81-99.Khairoutdinov, M., D. Randall, and C. DeMott, 2005: Simulations of the Atmospheric General Cir culation using a Cloud-Resolving Model as a Superparameterization of Physical Processes. J. Atmos. Sci., 62, 2136-2154Lavaysse, C, C. Flamant, S. Janicot, D.J. Parker, J.P. Lafore, B. Sultan, J. Pelon: 2009. Seasonal evolution of the West African heat low: a climatological perspective. Climate Dynamics. 33, 313-330.Lothon, M, F. Said, F. Lohou, and B. Campistron, 2008: Observation of the Diunral Cycle in the Low Troposphere of West Africa. Monthly Weather Review. 136, 3477-3500.Randall, D., M. Khairoutdinov, A. Arakawa, and W. Grabowski, 2003: Breaking the Cloud Param eterization Deadlock. Bull. Amer. Meteor. Soc., 1547-1564.

AcknowledgementsWe would like to acknowledge high-performance computing support pro-vided by NCAR's Computational and Information Systems Laboratory, spon-sored by the National Science Foundation.

We would like to acknowledge the Center for Multiscale Modeling of Atmo-sphereic processes, and the STC componenet of NSF for funding this re-search.

We would like to acknowledge UCAR/NCAR/MMM for provision of the WRF model, and the National Science Foundation for funding these entities.