Estimation of the advection effects induced by surface heterogeneities in the surface energy budget

Peer ReviewedPostprint (published version

The vertical cloud structure of the West African monsoon: a 4 year climatology using CloudSat and CALIPSO

The West African summer monsoon (WAM) is an important driver of the global climate and locally provides most of the annual rainfall. A solid climatological knowledge of the complex vertical cloud structure is invaluable to forecasters and modelers to improve the understanding of the WAM. In this paper, 4 years of data from the CloudSat profiling radar and CALIPSO are used to create a composite zonal mean vertical cloud and precipitation structure for the WAM. For the first time, the near-coincident vertical radar and lidar profiles allow for the identification of individual cloud types from optically thin cirrus and shallow cumulus to congestus and deep convection. A clear diurnal signal in zonal mean cloud structure is observed for the WAM, with deep convective activity enhanced at night producing extensive anvil and cirrus, while daytime observations show more shallow cloud and congestus. A layer of altocumulus is frequently observed over the Sahara at night and day, extending southward to the coastline, and the majority of this cloud is shown to contain supercooled liquid in the top. The occurrence of deep convective systems and congestus in relation to the position of the African easterly jet is studied, but only the daytime cumulonimbus distribution indicates some influence of the jet position

The possible role of local air pollution in climate change in West Africa

The climate of West Africa is characterized by a sensitive monsoon system that is associated with marked natural precipitation variability. This region has been and is projected to be subject to substantial global and regional-scale changes including greenhouse-gas-induced warming and sea-level rise, land-use and land-cover change, and substantial biomass burning. We argue that more attention should be paid to rapidly increasing air pollution over the explosively growing cities of West Africa, as experiences from other regions suggest that this can alter regional climate through the influences of aerosols on clouds and radiation, and will also affect human health and food security. We need better observations and models to quantify the magnitude and characteristics of these impacts

Estimation of the advection effects induced by surface heterogeneities in the surface energy budge

The effect of terrain heterogeneities in one-point measurements is a continuous subject of discussion. Here we focus on the order of magnitude of the advection term in the equation of the evolution of temperature as generated by documented terrain heterogeneities and we estimate its importance as a term in the surface energy budget (SEB), for which the turbulent fluxes are computed using the eddy-correlation method. The heterogeneities are estimated from satellite and model fields for scales near 1 km or broader, while the smaller scales are estimated through direct mea- surements with remotely piloted aircraft and thermal cameras and also by high-resolution modelling. The variability of the surface temperature fields is not found to decrease clearly with increasing resolution, and consequently the ad- vection term becomes more important as the scales become finer. The advection term provides non-significant values to the SEB at scales larger than a few kilometres. In contrast, surface heterogeneities at the metre scale yield large values of the advection, which are probably only significant in the first centimetres above the ground. The motions that seem to contribute significantly to the advection term in the SEB equation in our case are roughly those around the hectometre scales

Using a data-driven statistical model to better evaluate surface turbulent heat fluxes in weather and climate numerical models: a demonstration study

This study proposes using a data-driven statistical model to freeze errors due to differences in environmental forcing when evaluating surface turbulent heat fluxes from weather and climate numerical models with observations. It takes advantage of continuous acquisition over approximately 10 years of near-surface sensible and latent heat fluxes (H and LE respectively) together with ancillary parameters at the Météopole flux station, a supersite of the Aerosol, Clouds and Trace Gases Research Infrastructure in France (ACTRIS-FR), located in Toulouse. The statistical model consists of several multi-layer perceptrons (MLPs) with the same architecture. A total of 13 variables characterizing environmental forcing in the surface layer on an hourly timescale are used as input parameters to estimate the observed H and LE simultaneously. The MLPs are trained using 5-year observational data under a 5-fold cross-validation. The remaining data are used to test the estimates under unknown conditions. The performance of the statistical model ranges within the state-of-the-art surface parameterization schemes on hourly and seasonal timescales. It also has a good generalization ability, but it hardly estimates negative H and large LE. A case study is conducted with data from a regional climate simulation. The statistical model is used to evaluate the simulated fluxes in the simulated environment to better examine the flaws of their numerical formulation throughout the simulation. Comparison of simulated fluxes with observed and MLP-based fluxes shows different results. According to MLP-based fluxes in the simulated environment, the land surface scheme of this climate model tends to underestimate large sensible heat flux. Thus, it incorrectly partitions between surface heating and evaporation during the late summer. Our innovative method provides insight into different techniques for evaluating simulated near-surface turbulent heat fluxes when a long period of comprehensive observations is available. It can usefully support ongoing efforts to improve surface parameterization schemes.</p

The observed diurnal cycle of low-level stratus clouds over southern West Africa: a case study

This study presents the first detailed observational analysis of the complete diurnal cycle of stratiform low-level clouds (LLC) and involved atmospheric processes over southern West Africa (SWA). The data used here were collected during the comprehensive DACCIWA (Dynamics-Aerosol-Chemistry-Cloud-Interactions in West Africa) ground-based campaign, which aimed at monitoring LLC characteristics and capturing the wide range of atmospheric conditions related to the West African monsoon flow. In this study, in situ and remote sensing measurements from the supersite near Savè (Benin) collected during a typical day, which is characterized by the onset of a nocturnal low-level jet (NLLJ) and the formation of LLC, are analyzed. The associated dynamic and thermodynamic conditions allow the identification of five different phases related to the LLC diurnal cycle: the stable, jet, stratus I, stratus II, and convective phases. The analysis of relative humidity tendency shows that cooling is a dominant process for LLC formation, which leads to a continuous increase in relative humidity at a maximum rate of 6&thinsp;%&thinsp;h−1, until finally saturation is reached and LLC form with a cloud-base height near the height of NLLJ maximum. Results of heat budget analysis illustrate that horizontal cold-air advection, related to the maritime inflow, which brings the cool maritime air mass and a prominent NLLJ wind profile, has the dominant role in the observed strong cooling of −1.2&thinsp;K&thinsp;h−1 during the jet phase. The contribution from horizontal cold advection is quantified to be up to 68&thinsp;%, while radiative cooling and sensible heat flux divergence both contribute 16&thinsp;% to the observed heat budget below the NLLJ maximum. After the LLC form (stratus phases I and II), turbulent mixing is an important factor leading to the cooling below the cloud base, while strong radiative cooling at the cloud top helps to maintain thick stratus.</p

Studying the Boundary Layer Late Afternoon nd Sunset Turbulence (BLLAST)

At the end of the afternoon, when the surface heat fluxes start to sharply decrease, the CBL turns from a convective well-mixed layer to an intermittently turbulent residual layer overlying a stably-stratified boundary layer. This transition raises several observational and modeling issues. Even the definition of the boundary layer during this period is fuzzy, since there is no consensus on what criteria to use and no simple scaling laws to apply. Yet it plays an important role in such diverse atmospheric phenomena as transport and diffusion of trace constituents or wind energy production. This phase of the diurnal cycle remains largely unexplored, partly due to the difficulty of measuring weak and intermittent turbulence, anisotropy, horizontal heterogeneity, and rapid time changes. The Boundary Layer Late Afternoon and Sunset Turbulence (BLLAST) project is gathering about thirty research scientists from the European Union and the United States to work on this issue. A field campaign (BLLAST-FE) is planned for spring or summer 2011 in Europe. BLLAST will utilize these observations, as well as previous datasets, large-eddy and direct numerical simulations, and mesoscale modeling to better understand the processes, suggest new parameterizations, and evaluate forecast models during this transitional period. We will present the issues raised by the late afternoon transition and our strategy to study it.Peer ReviewedPostprint (published version

Surface representation impacts on turbulent heat fluxes in the Weather Research and Forecasting (WRF) model (v.4.1.3)

The water and energy transfers at the interface between the Earth's surface and the atmosphere should be correctly simulated in numerical weather and climate models. This implies the need for a realistic and accurate representation of land cover (LC), including appropriate parameters for each vegetation type. In some cases, the lack of information and crude representation of the surface lead to errors in the simulation of soil and atmospheric variables. This work investigates the ability of the Weather Research and Forecasting (WRF) model to simulate surface heat fluxes in a heterogeneous area of southern France using several possibilities for the surface representation. In the control experiments, we used the default LC database in WRF, which differed significantly from the actual LC. In addition, sub-grid variability was not taken into account since the model uses, by default, only the surface information from the dominant LC category in each pixel (dominant approach). To improve this surface simplification, we designed three new interconnected numerical experiments with three widely used land surface models (LSMs) in WRF. The first one consisted of using a more realistic and higher-resolution LC dataset over the area of analysis. The second experiment aimed at investigating the effect of using a mosaic approach; 30 m sub-grid surface information was used to calculate the final grid fluxes based on weighted averages from values obtained for each LC category. Finally, in the third experiment, we increased the model stomatal conductance for conifer forests due to the large flux errors associated with this vegetation type in some LSMs. The simulations were evaluated with gridded area-averaged fluxes calculated from five tower measurements obtained during the Boundary-Layer Late Afternoon and Sunset Turbulence (BLLAST) field campaign. The results from the experiments differed depending on the LSM and displayed a high dependency of the simulated fluxes on the specific LC definition within the grid cell, an effect that was enhanced with the dominant approach. The simulation of the fluxes improved using the more realistic LC dataset except for the LSMs that included extreme surface parameters for coniferous forest. The mosaic approach produced fluxes more similar to reality and served to particularly improve the latent heat flux simulation of each grid cell. Therefore, our findings stress the need to include an accurate surface representation in the model, including soil and vegetation sub-grid information with updated surface parameters for some vegetation types, as well as seasonal and man-made changes. This will improve the modelled heat fluxes and ultimately yield more realistic atmospheric processes in the model