25 September 2019

Capability of CAM5.1 in Simulating Maximum Air Temperature Anomaly Patterns Over West Africa During Boreal Spring

Evaluation of the performance of the CAM5.1 atmospheric model in reproducing causes in variations in daily maximum temperature over West Africa.


We examine how the CAM5.1 model of the atmosphere, run at 1° horizontal resolution under observed conditions following an international experiment protocol, performs in simulating the causes of variations in maximum daily maximum temperature.  We focus on the March-May (hot) season.  While the model reproduces many of the regional processes well, it does poorly in representing how global phenomena influence regional temperatures via teleconnections.


This research helps characterize the potential usefulness of this climate model as part of ongoing efforts in developing multi-model seasonal forecasting over West Africa. This project is also a direct outreach from LBNL scientists to African scientists from developing nations enabling their access to the results of computational results otherwise unavailable to them.


This study classifies maximum air temperature patterns over West Africa into six groups and evaluates the capability of a global climate model (Community Atmospheric Model version 5.1; CAM) to simulate them. We analyzed 45-year (1961–2005) multi-ensemble (50 members) simulations from CAM and compared the results with those of the Climate Research Unit (CRU) and the twentieth Century Reanalysis data sets. Using a Self Organizing Map algorithm to classify the spatial patterns of maximum air temperature during boreal spring, the study reveals the temperature patterns that CAM can simulate well and those the model struggles to reproduce. The results show that the best agreements between the composites of observations and CAM occur in the first temperature pattern group (which features positive temperatures anomalies over the Sahel) and Node 2 (which features near-normal temperature) pattern of the third group. CAM succeeded in reproducing some of the associated regional atmospheric dynamics and thermodynamic features in winds (horizontal and vertical), temperature fields, the cloud fractions, and the mean sea-level pressure. Although CAM struggles to capture the relationship between air temperature patterns and tele-connection indices during the boreal spring season over West Africa, it agrees with observations that temperature patterns over the sub-region cannot be associated with a single climate index. One ensemble member (SIM48) captures the inter-annual variation of the observed temperature patterns with high sychronization (ɳ > 44%), much better than that of ensembles mean (ɳ < 30%). SIM48 also captures adequately four of the spatial patterns in comparison to three captured by the ensembles mean. This indicates that, for better seasonal forecasts and more reliable future climate projections, the practice whereby an ensemble mean is based on uniformly averaging the members rather than the performance of individual ensemble members needs to be reviewed. The results of the study may be used to improve the performance of CAM over West Africa, thereby strengthening the on-going efforts to include CAM as part of multi-model forecasting system over West Africa.

William D. Collins
Lawrence Berkeley National Laboratory
Lawal, K, B Abiodun, D Stone, E Olaniyan, and M Wehner.  2019.  "Capability of CAM5.1 in Simulating Maximum Air Temperature Anomaly Patterns Over West Africa During Boreal Spring."  Modeling Earth Systems and Environment.  https://doi.org/10.1007/s40808-019-00639-2.