Using continuous ground-based radar and lidar measurements for evaluating the representation of clouds in four operational models

The ability of four operational weather forecast models [ECMWF, Action de Recherche Petite Echelle Grande Echelle model (ARPEGE), Regional Atmospheric Climate Model (RACMO), and Met Office] to generate a cloud at the right location and time (the cloud frequency of occurrence) is assessed in the present paper using a two-year time series of observations collected by profiling ground-based active remote sensors (cloud radar and lidar) located at three different sites in western Europe (Cabauw. Netherlands; Chilbolton, United Kingdom; and Palaiseau, France). Particular attention is given to potential biases that may arise from instrumentation differences (especially sensitivity) from one site to another and intermittent sampling. In a second step the statistical properties of the cloud variables involved in most advanced cloud schemes of numerical weather forecast models (ice water content and cloud fraction) are characterized and compared with their counterparts in the models. The two years of observations are first considered as a whole in order to evaluate the accuracy of the statistical representation of the cloud variables in each model. It is shown that all models tend to produce too many high-level clouds, with too-high cloud fraction and ice water content. The midlevel and low-level cloud occurrence is also generally overestimated, with too-low cloud fraction but a correct ice water content. The dataset is then divided into seasons to evaluate the potential of the models to generate different cloud situations in response to different large-scale forcings. Strong variations in cloud occurrence are found in the observations from one season to the same season the following year as well as in the seasonal cycle. Overall, the model biases observed using the whole dataset are still found at seasonal scale, but the models generally manage to well reproduce the observed seasonal variations in cloud occurrence. Overall, models do not generate the same cloud fraction distributions and these distributions do not agree with the observations. Another general conclusion is that the use of continuous ground-based radar and lidar observations is definitely a powerful tool for evaluating model cloud schemes and for a responsive assessment of the benefit achieved by changing or tuning a model cloud

The statistical properties of tropical ice clouds generated by the West-African and Australian monsoons from ground-based radar-lidar observations

In the present paper we characterize the statistical properties of non-precipitating tropical ice clouds (deep ice anvils resulting from deep convection and cirrus clouds) over Niamey, Niger, West Africa, and Darwin, northern Australia, using ground-based radar–lidar observations from the Atmospheric Radiation Measurement (ARM) programme. The ice cloud properties analysed in this paper are the frequency of ice cloud occurrence, cloud fraction, the morphological properties (cloud-top height, base height, and thickness), the microphysical and radiative properties (ice water content, visible extinction, effective radius, terminal fall speed, and concentration), and the internal cloud dynamics (in-cloud vertical air velocity). The main highlight of the paper is that it characterizes for the first time the probability density functions of the tropical ice cloud properties, their vertical variability and their diurnal variability at the same time. This is particularly important over West Africa, since the ARM deployment in Niamey provides the first vertically resolved observations of non-precipitating ice clouds in this crucial area in terms of redistribution of water and energy in the troposphere. The comparison between the two sites also provides an additional observational basis for the evaluation of the parametrization of clouds in large-scale models, which should be able to reproduce both the statistical properties at each site and the differences between the two sites. The frequency of ice cloud occurrence is found to be much larger over Darwin when compared to Niamey, and with a much larger diurnal variability, which is well correlated with the diurnal cycle of deep convective activity. The diurnal cycle of the ice cloud occurrence over Niamey is also much less correlated with that of deep convective activity than over Darwin, probably owing to the fact that Niamey is further away from the deep convective sources of the region. The frequency distributions of cloud fraction are strongly bimodal and broadly similar over the two sites, with a predominance of clouds characterized either by a very small cloud fraction (less than 0.3) or a very large cloud fraction (larger than 0.9). The ice clouds over Darwin are also much thicker (by 1 km or more statistically) and are characterized by a much larger diurnal variability than ice clouds over Niamey. Ice clouds over Niamey are also characterized by smaller particle sizes and fall speeds but in much larger concentrations, thereby carrying more ice water and producing more visible extinction than the ice clouds over Darwin. It is also found that there is a much larger occurrence of downward in-cloud air motions less than 1 m s−1 over Darwin, which together with the larger fall speeds retrieved over Darwin indicates that the life cycle of ice clouds is probably shorter over Darwin than over Niamey.

The variability of tropical ice cloud properties as a function of the large-scale context from ground-based radar-lidar observations over Darwin, Australia

The high complexity of cloud parameterizations now held in models puts more pressure on observational studies to provide useful means to evaluate them. One approach to the problem put forth in the modelling community is to evaluate under what atmospheric conditions the parameterizations fail to simulate the cloud properties and under what conditions they do a good job. It is the ambition of this paper to characterize the variability of the statistical properties of tropical ice clouds in different tropical "regimes" recently identified in the literature to aid the development of better process-oriented parameterizations in models. For this purpose, the statistical properties of non-precipitating tropical ice clouds over Darwin, Australia are characterized using ground-based radar-lidar observations from the Atmospheric Radiation Measurement (ARM) Program. The ice cloud properties analysed are the frequency of ice cloud occurrence, the morphological properties (cloud top height and thickness), and the microphysical and radiative properties (ice water content, visible extinction, effective radius, and total concentration). The variability of these tropical ice cloud properties is then studied as a function of the large-scale cloud regimes derived from the International Satellite Cloud Climatology Project (ISCCP), the amplitude and phase of the Madden-Julian Oscillation (MJO), and the large-scale atmospheric regime as derived from a long-term record of radiosonde observations over Darwin. The vertical variability of ice cloud occurrence and microphysical properties is largest in all regimes (1.5 order of magnitude for ice water content and extinction, a factor 3 in effective radius, and three orders of magnitude in concentration, typically). 98 % of ice clouds in our dataset are characterized by either a small cloud fraction (smaller than 0.3) or a very large cloud fraction (larger than 0.9). In the ice part of the troposphere three distinct layers characterized by different statistically-dominant microphysical processes are identified. The variability of the ice cloud properties as a function of the large-scale atmospheric regime, cloud regime, and MJO phase is large, producing mean differences of up to a factor 8 in the frequency of ice cloud occurrence between large-scale atmospheric regimes and mean differences of a factor 2 typically in all microphysical properties. Finally, the diurnal cycle of the frequency of occurrence of ice clouds is also very different between regimes and MJO phases, with diurnal amplitudes of the vertically-integrated frequency of ice cloud occurrence ranging from as low as 0.2 (weak diurnal amplitude) to values in excess of 2.0 (very large diurnal amplitude). Modellers should now use these results to check if their model cloud parameterizations are capable of translating a given atmospheric forcing into the correct statistical ice cloud properties.

Joint retrievals of cloud and drizzle in marine boundary layer clouds using ground-based radar, lidar and zenith radiances

Active remote sensing of marine boundary-layer clouds is challenging as drizzle drops often dominate the observed radar reflectivity. We present a new method to simultaneously retrieve cloud and drizzle vertical profiles in drizzling boundary-layer clouds using surface-based observations of radar reflectivity, lidar attenuated backscatter, and zenith radiances under conditions when precipitation does not reach the surface. Specifically, the vertical structure of droplet size and water content of both cloud and drizzle is characterised throughout the cloud. An ensemble optimal estimation approach provides full error statistics given the uncertainty in the observations. To evaluate the new method, we first perform retrievals using synthetic measurements from large-eddy simulation snapshots of cumulus under stratocumulus, where cloud water path is retrieved with an error of 31 g m−2 . The method also performs well in non-drizzling clouds where no assumption of the cloud profile is required. We then apply the method to observations of marine stratocumulus obtained during the Atmospheric Radiation Measurement MAGIC deployment in the Northeast Pacific. Here, retrieved cloud water path agrees well with independent three-channel microwave radiometer retrievals, with a root mean square difference of 10–20 g m−2.

Monitoramento da atenuação natural de pluma de contaminação pelo método de radar de penetração no solo (GPR)

O monitoramento da atenuação natural em áreas contaminadas tem se mostrado uma técnica alternativa e de baixo custo para a remediação de áreas contaminadas. A degradação por microorganismos é um dos processos mais importantes na atenuação natural de contaminantes, especialmente compostos de fase líquida não aquosa (NAPL). em muitos casos, a ação efetiva deste processo resulta na geração de ácidos orgânicos, que sob elevadas concentrações ocasionam a dissolução de minerais presentes em subsuperfície onde se encontra a contaminação, com conseqüente liberação de íons. O aumento na quantidade de íons colabora para o aumento da condutividade elétrica do meio. O princípio físico da técnica de Radar de Penetração no Solo (GPR) é a emissão de ondas eletromagnéticas de alta freqüência. A propagação da onda eletromagnética é condicionada à freqüência de sinal emitido e as propriedades elétricas do meio. O aumento da condutividade elétrica do meio resulta na atenuação do sinal e, por conseqüência, na diminuição da profundidade de penetração da onda eletromagnética. Este fator permite o monitoramento de áreas contaminadas sob atenuação natural a partir de análises temporais com o GPR. Este trabalho apresenta um estudo comparativo entre perfis de GPR adquiridos em 1998 e 2003 em uma área contaminada por compostos de fase líquida leve não aquosa (LNAPL), sob atenuação natural. Os resultados indicam um aumento da condutividade elétrica do meio, a partir da atenuação acentuada do sinal GPR observada nas seções de 2003. Este aumento pode estar associado à liberação de íons por dissolução de minerais, pelo ataque de ácidos orgânicos resultantes do processo de biodegradação.

Estratigrafia da sucessão sedimentar Pós-Barreiras (Zona Bragantina, Pará) com base em radar de penetração no solo

Investigação pioneira aplicando Radar de Penetração no Solo (GPR) na área da Praia do Atalaia, norte do Brasil, nos permitiu caracterizar, pela primeira vez, fácies e estratigrafia dos depósitos conhecidos informalmente como Sedimentos Pós-Barreiras (Plioceno e mais recente). Esta sucessão sedimentar recobre discordantemente o embasamento miocênico, representado pelas formações Pirabas/Barreiras. Três unidades estratigráficas foram reconhecidas. A Unidade 1, inferior, consiste em um intervalo com 6 m de espessura média dominado por reflexões pobremente definidas e de baixa amplitude, e que intergradam com reflexões de média escala dos tipos tangencial, obliquo e hummocky. A Unidade 2, intermediária, possui cerca de 9 m de espessura e inclui, principalmente, reflexões oblíquas de larga escala, cujas configurações variam de paralela, tangencial, sigmoidal a sigmoidal-complexa. A Unidade 3, superior, corresponde a um intervalo entre 3,5 e 9 m de espessura, sendo dominada por reflexões hummocky, seguidas por reflexões de média escala dos tipos oblíquo, paralelo a sub-paralelo, e em corte-e-preenchimento. A análise da configuração das reflexões internas e geometria das reflexões nos leva a propor que a unidade correspondente aos Sedimentos Pós-Barreiras é mais variável faciologicamente que inicialmente imaginado, incluindo depósitos eólicos (dunas costeiras), bem como depósitos de cordão litorâneo, planície de maré, canal e mangue. Além disto, o mapeamento das três unidades descritas acima é importante para desvendar a complexidade de sedimentação versus erosão durante o Neógeno tardio no norte do Brasil.

Upper Pleistocene to Holocene peatland evolution in Southern Brazilian highlands as depicted by radar stratigraphy, sedimentology and palynology

Paleoenvironmental interpretation of proxy data derived from peatlands is largely based upon an evolutionary model for ombrotrophic bogs, in which peat accumulates in still environments. Reports on proxies obtained from minerotrophic fens, where hydrologic inputs are variable, are less common. In this study, a highland peatland in southern Brazil is presented through ground penetrating radar (GPR) and sedimentological, palynological and geochronologic data. The radar stratigraphic interpretation suggests a relatively complex history of erosion and deposition at the site since the beginning of Marine Isotope Stage 3 (MIS 3) interstadial period. In spite of this, radar stratigraphic and palynologic interpretations converge. Electromagnetic reflections tend to group in clusters that show lateral coherence and correlate with different sediment types, while pollen grains abound and are well preserved. As a result, the study of minerotrophic fens provides a source of proxies. suggesting that ombrotrophic bogs are not the only reliable source of data in wetlands for palynological analysis. (C) 2012 University of Washington. Published by Elsevier Inc. All rights reserved.

Radar profiles from South Shetland Islands/Western Antarctic Peninsula

The sedimentary architecture of polar gravel-beach ridges is presented and it is shown that ridge internal geometries reflect past wave-climate conditions. Ground-penetrating radar (GPR) data obtained along the coasts of Potter Peninsula (King George Island) show that beach ridges unconformably overlie the prograding strand plain. Development of individual ridges is seen to result from multiple storms in periods of increased storm-wave impact on the coast. Strand-plain progradation, by contrast, is the result of swash sedimentation at the beach-face under persistent calm conditions. The sedimentary architecture of beach ridges in sheltered parts of the coast is characterized by seaward-dipping prograding beds, being the result of swash deposition under stormy conditions, or aggrading beds formed by wave overtopping. By contrast, ridges exposed to high-energy waves are composed of seaward- as well as landward-dipping strata, bundled by numerous erosional unconformities. These erosional unconformities are the result of sediment starvation or partial reworking of ridge material during exceptional strong storms. The number of individual ridges which are preserved from a given time interval varies along the coast depending on the morphodynamic setting: sheltered coasts are characterized by numerous small ridges, whereas fewer but larger ridges develop on exposed beaches. The frequency of ridge building ranges from decades in the low-energy settings up to 1600 years under high-energy conditions. Beach ridges in the study area cluster at 9.5, 7.5, 5.5, and below 3.5 m above the present-day storm beach. Based on radiocarbon data, this is interpreted to reflect distinct periods of increased storminess and/or shortened annual sea-ice coverage in the area of the South Shetland Islands for the times around 4.3, c. 3.1, 1.9 ka cal BP, and after 0.65 ka cal BP. Ages further indicate that even ridges at higher elevations can be subject to later reactivation and reworking. A careful investigation of the stratigraphic architecture is therefore essential prior to sampling for dating purposes.

Calibration functions for estimating soil moisture from GPR dielectric constant measurements

Ground-penetrating radar (GPR) is widely used for assessment of soil moisture variability in field soils. Because GPR does not measure soil water content directly, it is common practice to use calibration functions that describe its relationship with the soil dielectric properties and textural parameters. However, the large variety of models complicates the selection of the appropriate function. In this article an overview is presented of the different functions available, including volumetric models, empirical functions, effective medium theories, and frequency-specific functions. Using detailed information presented in summary tables, the choice for which calibration function to use can be guided by the soil variables available to the user, the frequency of the GPR equipment, and the desired level of detail of the output. This article can thus serve as a guide for GPR practitioners to obtain soil moisture values and to estimate soil dielectric properties.

Hydraulic conductivity fields: Gaussian or not?

Hydraulic conductivity (K) fields are used to parameterize groundwater flow and transport models. Numerical simulations require a detailed representation of the K field, synthesized to interpolate between available data. Several recent studies introduced high-resolution K data (HRK) at the Macro Dispersion Experiment (MADE) site, and used ground-penetrating radar (GPR) to delineate the main structural features of the aquifer. This paper describes a statistical analysis of these data, and the implications for K field modeling in alluvial aquifers. Two striking observations have emerged from this analysis. The first is that a simple fractional difference filter can have a profound effect on data histograms, organizing non-Gaussian ln K data into a coherent distribution. The second is that using GPR facies allows us to reproduce the significantly non-Gaussian shape seen in real HRK data profiles, using a simulated Gaussian ln K field in each facies. This illuminates a current controversy in the literature, between those who favor Gaussian ln K models, and those who observe non-Gaussian ln K fields. Both camps are correct, but at different scales.

Landform characterization using geophysics—Recent advances, applications, and emerging tools

This paper presents an overview of the strengths and limitations of existing and emerging geophysical tools for landform studies. The objectives are to discuss recent technical developments and to provide a review of relevant recent literature, with a focus on propagating field methods with terrestrial applications. For various methods in this category, including ground-penetrating radar (GPR), electrical resistivity (ER), seismics, and electromagnetic (EM) induction, the technical backgrounds are introduced, followed by section on novel developments relevant to landform characterization. For several decades, GPR has been popular for characterization of the shallow subsurface and in particular sedimentary systems. Novel developments in GPR include the use of multi-offset systems to improve signal-to-noise ratios and data collection efficiency, amongst others, and the increased use of 3D data. Multi-electrode ER systems have become popular in recent years as they allow for relatively fast and detailed mapping. Novel developments include time-lapse monitoring of dynamic processes as well as the use of capacitively-coupled systems for fast, non-invasive surveys. EM induction methods are especially popular for fast mapping of spatial variation, but can also be used to obtain information on the vertical variation in subsurface electrical conductivity. In recent years several examples of the use of plane wave EM for characterization of landforms have been published. Seismic methods for landform characterization include seismic reflection and refraction techniques and the use of surface waves. A recent development is the use of passive sensing approaches. The use of multiple geophysical methods, which can benefit from the sensitivity to different subsurface parameters, is becoming more common. Strategies for coupled and joint inversion of complementary datasets will, once more widely available, benefit the geophysical study of landforms.Three cases studies are presented on the use of electrical and GPR methods for characterization of landforms in the range of meters to 100. s of meters in dimension. In a study of polygonal patterned ground in the Saginaw Lowlands, Michigan, USA, electrical resistivity tomography was used to characterize differences in subsurface texture and water content associated with polygon-swale topography. Also, a sand-filled thermokarst feature was identified using electrical resistivity data. The second example is on the use of constant spread traversing (CST) for characterization of large-scale glaciotectonic deformation in the Ludington Ridge, Michigan. Multiple CST surveys parallel to an ~. 60. m high cliff, where broad (~. 100. m) synclines and narrow clay-rich anticlines are visible, illustrated that at least one of the narrow structures extended inland. A third case study discusses internal structures of an eolian dune on a coastal spit in New Zealand. Both 35 and 200. MHz GPR data, which clearly identified a paleosol and internal sedimentary structures of the dune, were used to improve understanding of the development of the dune, which may shed light on paleo-wind directions.