Retrieval of tropospheric water vapour from airborne far-infrared measurements: a case study

We describe studies undertaken in support of the Far-infrared Outgoing Radiation Understanding and Monitoring (FORUM) mission, ESA’s ninth Earth Explorer, designed to investigate whether airborne observations of far-infrared radiances can provide beneficial information on mid and upper tropospheric water vapour concentrations.Initially we perform a joint temperature and water vapour retrieval and show that the water vapour retrieval exploiting far-infrared measurements from the Tropospheric Airborne Fourier Transform Spectrometer (TAFTS) shows improvement over the a-priori Unified Model global forecast when compared to in situ dropsonde measurements. For this case the improvement is particularly noticeable in the mid-upper troposphere. Equivalent retrievals using mid-infrared radiances measured by the Airborne Research Interferometer Evaluation System (ARIES) show much reduced performance, with the degrees of freedom for signal (DFS), reduced by a factor of almost 2. Further sensitivity studies show that this advantage is decreased, but still present when the spectral resolution of the TAFTS measurements is reduced to match that of ARIES.The beneficial role of the far infrared for this case is further confirmed by performing water vapour only retrievals using ARIES and TAFTS individually, and then in combination. We find that the combined retrieval has a DFS value of 6.7 for water vapour, marginally larger than that obtained for the TAFTS retrieval and almost twice as large as that obtained for ARIES.These results provide observational support of theoretical studies highlighting the potential improvement that far-infrared observations could bring for the retrieval of tropospheric water vapour

The surface energy balance over drying semi-arid terrain in West Africa

One of the fundamental aspects of current research in earth system science is the proper understanding of land-atmosphere interactions. The role of the land surface is crucial in the climate system, since a large fraction of incoming solar radiation passes through the atmosphere and is converted at the surface into turbulent fluxes. For numerous regions, including the semi-arid regions, only little knowledge is available about the diurnal and seasonal cycle of land surface interactions.The semi-arid areas pose a big challenge due to the large contrasts of dry and wet situations within a seasonal cycle.This is especially valid for the semi-arid region inWest Africa, since it is one of the most climatically sensitive and ecologically unstable regions in the world. The variability of weather and climate in the region is strongly influenced by complicated interactions and feedbacks between the land and the atmosphere. To analyze and to predict these interactions and feedbacks it is inevitable to measure and model the involved components. Since standard methods for this purpose are not always applicable to the heterogeneous surface inWest Africa, new measurement and modeling techniques have to be applied.The overall objective of this thesis is to analyze and to model the land surface interactions intheVolta basin,West Africa, by using meteorological data obtained in the framework of the GLOWA-Volta project. A focus is put on diurnal and seasonal time scales. For measuring turbulent fluxes the key instrument is the large aperture scintillometer.This robust method yields area-averaged fluxes over complexterrain, which arerequired when analyzing meteorological data from heterogeneous surfaces. It is foundthat it is a suitable technique for the kind of environment also in comparison to different measuring techniques.Based on the analysis of the measurements, two different land surface schemes are evaluated. Both schemes are not able to reproduce the measured seasonal cycle in surface fluxes. Several changes are proposed to obtain enhanced model performance.Based on the earlier findings a model is constructed, combining the best parts of each of the two land surface schemes. It is shown that the performance of the new formulation is more realistic. Using a factorial design as the sensitivity analysis method it is assessed, which parameters are the mostimportant.Furthermore it is found that those important parameters and their interactions change significantly during one season.As a final step the gained knowledge is utilized to construct a simple satellite based algorithm to obtain surface water flux as the important flux on a regional basis. For evaluating this first order approach the large aperture scintillometer is utilized to evaluate fluxes on satellite pixel scale

Scalar similarity functions: the influence of surface heterogeneity and entrainment

To study turbulent flows in the atmospheric boundary layer dimensional analysis is widely applied. For flows in the lower part of the atmospheric boundary layer the cornerstone of (the analysis of) experiments and modelling is Monin-Obukhov Similarity Theory (MOST). The central assumption is that once all relevant variables are identified, the number of dimensionless groups can be determined. Those dimensionless groups should be related in a universal way, irrespective of the magnitude of the individual (dimensional) variables. For MOST the list of relevant variables is rather limited, which is both its strength and its weakness. The main assumptions needed to limit the number of relevant variables are stationarity and horizontal homogeneity. Furthermore the analysis should be restricted to the lower part of the boundary layer where the only relevant height is the height above the ground, not the distance to the top of the boundary layer. This study presents a detailed analysis of two data sets of surface layer observations over drying terrain (Bowen ratio increasing from 0.5-1 to 4 in a month time). One data set was obtained over savannah vegetation in Ghana (West Africa). The vegetation consisted of a mixture of grass, bushes and trees (approx. 25 trees/ha). Data were gathered directly following the rainy season. In that period the grass died, whereas the trees went on transpiring, yielding an increasingly heterogeneous distribution of sources and sinks for humidity sources, heat and carbondioxide: a first violation of the MOST assumptions. The other data set was collected during CASES-99, over relatively flat and homogeneous terrain in Kansas (US). Both data sets have in common that the surface flux of humidity decreased over time. Provided that the entrainment flux of humidity remains relatively constant, this could lead to an increasing importance of processes outside the surface layer, thus violating the assumptions underlying MOST. For the present study only high-quality data (based wind direction and on the statistical error in the dimensionless groups under consideration) were utilized for the derivation of MOST-relationships for the variances. A general conclusion is that the dimensionless variances of humidity (and carbondioxide in the Ghana data) are higher (statistically significant) than those of temperature. It turns out that for the savannah data the dimensionless variances of humidity and carbondioxide increase over time. From a deeper analysis there are indications that both the surface heterogeneity and the entrainment processes play an important role. The role of the surface heterogeneity can be inferred from the fact that also during night-time the dimensionless variances increase during the dry season. The role of entrainment is indicated by a large increase in the dominant timescale of the humidity fluctuations. The dimensionless variances in the CASES-99 data do not show a trend in time, despite the decrease in the surface humidity flux. One reason for the absence of a clear effect of entrainment may be that the entrainment flux of humidity is more variable over time in mid-latitudes compared to tropical regions

Uncertainty analysis for satellite derived sensible heat fluxes and scintillometer measurements over Savannah environment and comparison to mesoscale meteorological simulation results

Three methods for estimating instantaneous sensible heat flux (H) over Savannah environment in West Africa were compared: first, satellite derived estimations using the Surface Energy Balance Algorithm for Land (SEBAL) method [Bastiaanssen, W.G.M., Menenti, M., Feddes, R.A., Holtslag, A.A.M., 1998a. A remote sensing energy balance algorithm for land, SEBAL: 1. Formulation. J. Hydrol. 212¿213, 198¿212]; secondly, measurements at two test sites in Ghana with a large-aperture scintillometer (LAS); third, high resolution mesoscale meteorological simulations using the MM5 (5th-Generation Penn State/NCAR) mesoscale modelling system. Satellite-derived sensible heat flux was based on seven NOAA-16 AVHRR images that were processed for a 2-week period in December 2001 (dry season) and were compared to LAS-data and MM5 simulation results. A methodology based on Gaussian Error Propagation is presented to derive uncertainties in satellite derived sensible heat flux due to (a) input data, (b) coefficients to determine leaf area index (LAI) and (c) methodological differences in estimating surface temperature T0. Total computed relative uncertainty in H was 15% for the Tamale test site and 20% for the Ejura site. Uncertainties in instantaneous evapotranspiration ¿E, however, are much smaller than uncertainties of H. This results due to the same bias in H and Rn ¿ G. For LAS-data, an uncertainty analysis due to input data was performed which showed relative uncertainty of 8% for the Tamale site and 7% for Ejura. Satellite derived net radiation (Rn) was underestimated in comparison to ground measurements which finally caused an underestimation of H. Satellite estimates of H using spatially interpolated ground based measurements of net radiation showed good agreement to LAS data. MM5-computed latent heat flux showed very low values for the entire region. This caused a serious relative MM5-overestimation of sensible heat flux in comparison to LAS and satellite derived estimates. It could be shown that Gaussian Error Propagation can serve as an essential tool to asses the reliability of satellite derived sensible heat fluxes. The resulting uncertainties give information on sensitivities in estimating H and therefore provide a tool for validation purposes

Sensitivity and uncertainty of analytical footprint models according to a combined natural tracer and ensemble approach

Evaluations of analytical footprint models using data from several stations located in different land use types are still scarce, but valuable for defining the spatial context of the measurements. Therefore, we evaluated two analytical footprint models by applying a ‘forward’ and an ‘inversion’ method. We used eddy covariance measurements from a flat agricultural landscape in western Germany in the summer of 2009, with seven eddy covariance systems over three different land use types with contrasting sensible heat fluxes. We found that the model of Hsieh et al. (2000. Adv. Water Resour. 23, 765–772) and of Kormann and Meixner (2001. Boundary Layer Meteorol. 99, 207–224) are both overestimating the distance of the peak contribution of the footprint. In our evaluation, the former model performs slightly better, independent of whether the crosswind dispersion was used from the latter model, or from the proposed model by Detto et al. (2006. Water Resour. Res. 42, 1–16)