The ECMWF re‐analysis for the AMMA observational campaign

Abstract

During the 2006 African Monsoon Multidisciplinary Analysis (AMMA) field experiment, an unprecedented number of soundings were performed in West Africa. However, due to technical problems many of these soundings did not reach the Global Telecommunication System and therefore they could not be included in the operational numerical weather prediction (NWP) analyses. This issue, together with the realization that there was a significant bias in the radiosonde humidity, led to the conclusion that a re-analysis effort was necessary. This re-analysis was performed at the European Centre for Medium-Range Weather Forecasts (ECMWF) spanning the wet monsoon season of 2006 from May-September. The key features of the ECMWF AMMA re-analysis are presented, including the use of a newer model version with improved physics, all the AMMA radiosonde data available from the AMMA database and a new radiosonde humidity bias-correction scheme. Dataimpact experiments show that there is a benefit from these observations, but also highlight large model physics biases over the Sahel that cause a short-lived impact of the observations on the model forecast. The AMMA re-analysis is compared with independent observations to investigate the biases in the different parts of the physics. In the framework of the AMMA project, a hybrid dataset was developed to provide a best estimate of the different terms of the water cycle. This hybrid dataset is used to evaluate the improvement achieved from the use of extra AMMA observations and of a radiosonde humidity bias-correction scheme in the water cycle of the West African monsoon. Finally, future model developments that offer promising improvements in the water cycle are discussed.

Characterizing energy budget variability at a Sahelian site: a test of NWP model behaviour

“…This effect is exacerbated by the use of an aerosol loading climatology which typically underestimates the real amount of aerosol present in the atmosphere over Niamey and is the major source of the model overestimation of surface DSR in the dry season. This agrees with an assessment of an earlier cycle of the IFS, 32r3, used for a reanalysis by Agustí-Panareda et al (2010), though here we directly link the lack of cloud and aerosol loading to an overestimation of DSR. Marsham et al (2015), in their study of controls of surface and TOA radiation budgets in a similar site in Algeria (Bordj Badji Mokhtar at 21.4 • N, 0.9 • E), also find that net shortwave radiation at the surface is controlled by a balance of clouds, AOD and TCWV, consistent with our results here.…”

“…Agustí-Panareda et al (2010), in their wider comparison of west African data to ECMWF's operational forecast, briefly look at how well surface broadband fluxes are modelled in Niamey. They note that there are periods in the dry season where the observed DSR decreases which are not present in the model and attribute this primarily to the use of a constant climatology for aerosol loading and missing cloudy conditions.…”

Impact of soil moisture and convectively generated waves on the initiation of a West African mesoscale convective system

“…Representation of the soil moisture-precipitation feedback in models is uncertain because soil moisture is not well represented (Agustí-Panareda et al, 2010a, 2010b and there are large biases in the water budget (Meyandier, 2010). Soil moisture is also not the only precipitation trigger mechanism.…”

Unified treatment of dry convective and stratocumulus‐topped boundary layers in the ECMWF model

“…The AMMA-Niamey model-radiosonde comparison is done by employing short-term forecasts (12 h from 0000 UTC) from the ECMWF AMMA reanalysis (Agustí-Panareda et al, 2010) for each day in May 2006. A BL height (BLH) algorithm based on a Richardson number criterion with a parcel excess of 0.5 K (in the sense of Eq.…”