Evaluation of the WAMME model surface fluxes using results from the AMMA land-surface model intercomparison project

The West African monsoon (WAM) circulation and intensity have been shown to be influenced by the land surface in numerous numerical studies using regional scale and global scale atmospheric climate models (RCMs and GCMs, respectively) over the last several decades. The atmosphere–land surface interactions are modulated by the magnitude of the north–south gradient of the low level moist static energy, which is highly correlated with the steep latitudinal gradients of the vegetation characteristics and coverage, land use, and soil properties over this zone. The African Multidisciplinary Monsoon Analysis (AMMA) has organised comprehensive activities in data collection and modelling to further investigate the significance land–atmosphere feedbacks. Surface energy fluxes simulated by an ensemble of land surface models from AMMA Land-surface Model Intercomparison Project (ALMIP) have been used as a proxy for the best estimate of the “real world” values in order to evaluate GCM and RCM simulations under the auspices of the West African Monsoon Modelling Experiment (WAMME) project, since such large-scale observations do not exist. The ALMIP models have been forced in off-line mode using forcing based on a mixture of satellite, observational, and numerical weather prediction data. The ALMIP models were found to agree well over the region where land–atmosphere coupling is deemed to be most important (notably the Sahel), with a high signal to noise ratio (generally from 0.7 to 0.9) in the ensemble and a inter-model coefficient of variation between 5 and 15%. Most of the WAMME models simulated spatially averaged net radiation values over West Africa which were consistent with the ALMIP estimates, however, the partitioning of this energy between sensible and latent heat fluxes was significantly different: WAMME models tended to simulate larger (by nearly a factor of two) monthly latent heat fluxes than ALMIP. This results due to a positive precipitation bias in the WAMME models and a northward displacement of the monsoon in most of the GCMs and RCMs. Another key feature not found in the WAMME models is peak seasonal latent heat fluxes during the monsoon retreat (approximately a month after the peak precipitation rates) from soil water stores. This is likely related to the WAMME northward bias of the latent heat flux gradient during the WAM onset.     

Chemistry of fluids from a natural analogue for a geological CO2 storage site (Montmiral, France): Lessons for CO2–water–rock interaction assessment and monitoring

Chemical and isotope studies of natural CO₂ accumulations aid in assessing the chemical effects of CO₂ on rock and thus provide a potential for understanding the long-term geochemical processes involved in CO₂ geological storage. Several natural CO₂ accumulations were discovered during gas and oil exploration in France’s carbogaseous peri-Alpine province (south-eastern France) in the 1960s. One of these, the Montmiral accumulation at a depth of more than 2400 m, is currently being exploited. The chemical composition of the water collected at the wellhead has changed in time and the final salinity exceeds 75 g/L. These changes in time can be explained by assuming that the fraction of the reservoir brine in the recovered brine–CO₂–H₂O mixture varies, resulting in variable proportions of H₂O and brine in the sampled water. The proportions can be estimated in selected samples due to the availability of gas and water flowrate data. These data enabled the reconstruction of the chemical and isotope composition of the brine. The proportions of H₂O and brine can also be estimated from isotope (δ²H, δ¹⁸O) composition of collected water and δ¹⁸O of the sulfates or CO₂. The reconstituted brine has a salinity of more than 85 g/L and, according to its Br⁻ content and isotope (δ²H, δ¹⁸O, δ³⁴S) composition, originates from an evaporated Triassic seawater that underwent dilution by meteoric water. The reconstitution of the brine’s chemical composition enabled an evaluation of the CO₂–water–rock interactions based on: (1) mineral saturation indices; and (2) comparison with initial evaporated Triassic seawater. Dissolution of K- and SO₄-containing minerals such as K-feldspar and anhydrite, and precipitation of Ca and Mg containing minerals that are able to trap CO₂ (carbonates) are highlighted. The changes in concentration of these elements in the brine, which are attributed to CO₂ interactions, illustrate the relevance of monitoring the water quality at future industrial CO₂ storage sites.     

Information content of snow hydrological signatures based on streamflow,precipitation and air temperature

Hydrological signatures that represent snow processes are valuable to gain insights into snow accumulation and snow melt dynamics. We investigated five snow signatures. Considering inter-annual average of each calendar day, two slopes derived from the relation between streamflow and air temperature for different periods and streamflow peak maxima are used as signatures. In addition, two different approaches are used to compute inter-annual average and yearly snow storage estimates. We evaluated the ability of these signatures to characterize average (a) snow melt dynamics and (b) snow storage. They were applied in 10 Critical Zone Observatory catchments of the Southern Sierra mountains (USA) characterized by a Mediterranean climate. The relevance and information content of the signatures are evaluated using snow depth and snow water equivalent measurements as well as inter-catchment differences in elevation. The slopes quantifying the relations between streamflow and air temperature and the date of streamflow peak were found to characterize snow melt dynamics in terms of snow melt rates and snow melt affected areas. Streamflow peak dates were linked to the period of highest snow melt rates. Snow storage could be estimated both on average, considering all years, and for each year. Snow accumulation dynamics could not be characterized due to the lack of streamflow response during the snow accumulation period. The signatures were found potentially valuable to gain insights into catchment scale snow processes. In particular, when comparing catchments or observed and simulated data, they could provide insights into differences in terms of (a) snow melt rate and/or snow melt affected area over the snow melt season and (b) average or yearly snow storage. Requiring only widely available data, these hydrological signatures can be valuable for snow processes characterization, catchment comparison/classification or model development, calibration or evaluation.     

Mineral chemical study of U-bearing minerals from the Dominion Reefs,South Africa

The Neo-Archean Dominion Reefs (~3.06 Ga) are thin meta-conglomerate layers with concentrations of U- and Th-bearing heavy minerals higher than in the overlying Witwatersrand Reefs. Ore samples from Uranium One Africa’s Rietkuil and Dominion exploration areas near Klerksdorp, South Africa, were investigated for their mineral paragenesis, texture and mineral chemical composition. The ore and heavy mineral assemblages consist of uraninite, other uraniferous minerals, Fe sulphides, Ni–Co sulfarsenides, garnet, pyrite, pyrrhotite, monazite, zircon, chromite, magnetite and minor gold. Sub-rounded uraninite grains occur associated with the primary detrital heavy mineral paragenesis. U–Ti, U–Th minerals, pitchblende (colloform uraninite) and coffinite are of secondary, re-mobilised origin as evidenced by crystal shape and texture. Most of the uranium mineralisation is represented by detrital uraninite with up to 70.2 wt.% UO₂ and up to 9.3 wt.% ThO₂. Re-crystallised phases such as secondary pitchblende (without Th), coffinite, U–Ti and U–Th phases are related to hydrothermal overprint during low-grade metamorphism and are of minor abundance.     

Urban hydrologic trend analysis based on rainfall and runoff data analysis and conceptual model calibration

Urban stormwater is a major cause of urban flooding and natural water pollution. It is therefore important to assess any hydrologic trends in urban catchments for stormwater management and planning. This study addresses urban hydrological trend analysis by examining trends in variables that characterize hydrological processes. The original and modified Mann‐Kendall methods are applied to trend detection in two French catchments, that is, Chassieu and La Lechere, based on approximately 1 decade of data from local monitoring programs. In both catchments, no trend is found in the major hydrological process driver (i.e., rainfall variables), whereas increasing trends are detected in runoff flow rates. As a consequence, the runoff coefficients tend to increase during the study period, probably due to growing imperviousness with the local urbanization process. In addition, conceptual urban rainfall‐runoff model parameters, which are identified via model calibration with an event based approach, are examined. Trend detection results indicate that there is no trend in the time of concentration in Chassieu, whereas a decreasing trend is present in La Lechere, which, however, needs to be validated with additional data. Sensitivity analysis indicates that the original Mann‐Kendall method is not sensitive to a few noisy values in the data series.