Low Vertical Resolution Research Articles

Evaluation of Thin Bed Using Resistivity Borehole and NMR Imaging Techniques

In the study of sedimentary units to evaluate thin beds, there lie a lot of uncertainties, primarily, sand, shale or their combination in terms of their petrophysical properties and lateral extant. Good thin beds are capable of yielding a reasonable amount of hydrocarbon if discovered and evaluated. Regrettably, most thin beds are usually bypassed if direct log interpretation techniques are applied in their evaluation due to their low vertical resolutions and ability to only characterize an average of multiple beds which often result to a significant under estimation of oil and gas in the sedimentary unit. To better characterize thin beds and maximize reservoir potential, the resistivity borehole imaging and NMR techniques were adopted in this research study. In addition, the Thomas Stieber equations using laminated sand-shale sequence were employed in calculating parameters such as sand porosity, hydrocarbon saturation and shale volume. Results show that at depths of about 4350m and 4500m (Fig. 2), thin beds were identified, whereas, the conventional logs identified the points as spikes of sand. The NMR imaging technique further confirms the presence of hydrocarbon in the thin beds. It is therefore suggested that the resistivity borehole imaging and NMR techniques should be employed in characterizing thin beds since their use in this study yielded results that are reliable and dependable. Keywords: Thin bed, Borehole image, Sand laminae, Conventional logs, lateral resistivity, Vertical resistivity.

Have mid-latitude ocean rain-lenses been seen by the SMOS satellite?

In winter in mid-latitudes the ocean mixed layer is typically a few hundred metres deep because of intense surface cooling and wind mixing. However, it is shown here that the SMOS (Soil Moisture and Ocean Salinity) satellite has detected 3–4 instances per day (averaged over the globe) of anomalous bands of surface fresh water under atmospheric fronts. One typical case shows a fresh surface anomaly of 4psu located southwest of Australia under an atmospheric front with rainfall of 5.6mm/day. In this case the size of the salinity anomaly and the ECMWF rainfall rate along the front imply that the rainwater is staying within the upper 15cm of the ocean, despite mixing from the frontal winds. If these lenses are confirmed, they are significant because a surface that is 4psu fresher, can be 1K cooler and still be stable, and this could reduce sea to air heat fluxes by 35W/m2. If an air–sea coupled model has a low vertical ocean resolution, and is unable to model these shallow lenses, this may result in incorrectly high sea to air heat fluxes, and the model troposphere would warm unrealistically by 1.3K over a 5day forecast. For a global climate model the error would be 4.4K of tropospheric heating per decade.

Can one detect small-scale turbulence from standard meteorological radiosondes?

Abstract. It has been recently proposed by Clayson and Kantha (2008) to evaluate the climatology of atmospheric turbulence through the detection of overturns in the free atmosphere by applying a Thorpe analysis on relatively low vertical resolution (LR) profiles collected from standard radiosoundings. Since then, several studies based on this idea have been published. However, the impact of instrumental noise on the detection of turbulent layers was completely ignored in these works. The present study aims to evaluate the feasibility of overturns detection from radiosoundings. For this purpose, we analyzed data of two field campaigns during which high-resolution (HR) soundings (10–20 cm) were performed simultaneously with standard LR soundings. We used the raw data of standard meteorological radiosondes, the vertical resolution ranging from 5 to 9 m. A Thorpe analysis was applied to both LR and HR potential temperature profiles. A denoising procedure was first applied in order to reduce the probability of occurrence of artificial overturns, i.e. potential temperature inversions due to instrumental noise only. We then compared the empirical probability density functions (pdf) of the sizes of the selected overturns from LR and HR profiles. From HR profiles measured in the troposphere, the sizes of the detected overturns range from 4 to ~1000 m. The shape of the size pdf of overturns is found to sharply decrease with increasing scales. From LR profiles, the smallest size of detected overturns is ~32 m, a similar decrease in the shape of the pdf of sizes being observed. These results suggest that overturns, resulting either from small-scale turbulence or from instabilities, can indeed be detected from meteorological radiosonde measurements in the troposphere and in the stratosphere as well. However they are rather rare as they belong to the tail of the size distribution of overturns: they only represent the 7 % largest events in the troposphere, and 4 % in the stratosphere.

A comparison of OEM CO retrievals from the IASI and MOPITT instruments

Abstract. Observations of atmospheric carbon monoxide (CO) can only be made on continental and global scales by remote sensing instruments situated in space. One such instrument is the Infrared Atmospheric Sounding Interferometer (IASI), producing spectrally resolved, top-of-atmosphere radiance measurements from which CO vertical layers and total columns can be retrieved. This paper presents a technique for intercomparisons of satellite data with low vertical resolution. The example in the paper also generates the first intercomparison between an IASI CO data set, in this case that produced by the University of Leicester IASI Retrieval Scheme (ULIRS), and the V3 and V4 operationally retrieved CO products from the Measurements Of Pollution In The Troposphere (MOPITT) instrument. The comparison is performed for a localised region of Africa, primarily for an ocean day-time configuration, in order to develop the technique for instrument intercomparison in a region with well defined a priori. By comparing both the standard data and a special version of MOPITT data retrieved using the ULIRS a priori for CO, it is shown that standard intercomparisons of CO are strongly affected by the differing a priori data of the retrievals, and by the differing sensitivities of the two instruments. In particular, the differing a priori profiles for MOPITT V3 and V4 data result in systematic retrieved profile changes as expected. An application of averaging kernels is used to derive a difference quantity which is much less affected by smoothing error, and hence more sensitive to systematic error. These conclusions are confirmed by simulations with model profiles for the same region. This technique is used to show that for the data that has been processed the systematic bias between MOPITT V4 and ULIRS IASI data, at MOPITT vertical resolution, is less than 7 % for the comparison data set, and on average appears to be less than 4 %. The results of this study indicate that intercomparisons of satellite data sets with low vertical resolution should ideally be performed with: retrievals using a common a priori appropriate to the geographic region studied; the application of averaging kernels to compute difference quantities with reduced a priori influence; and a comparison with simulated differences using model profiles for the target gas in the region.

High-resolution reservoir characterization by seismic inversion with geological constraints

Fluvio-deltaic sedimentary systems are of great interest for explorationists because they can form prolific hydrocarbon plays. However, they are also among the most complex and heterogeneous ones encountered in the subsurface. Reservoirs in clinoform systems are difficult to characterize because they show two main types of complexity: complex sedimentology and poor seismic imaging. The former is due to complex internal architecture with many small sedimentary elements often at a sub-seismic scale. Poor seismic imaging occurs because the internal layers of the clinoform often do not differ much in their acoustic properties, in addition, they have thicknesses that are below the vertical resolution of seismic data, and therefore such features do not show up very well on seismic images. Obviously, the most unfavorable situation occurs when both conditions interact. The static model of a fluvio-deltaic (clinoform) reservoir is extremely important because it plays a critical role in the field development planning. There are many ways to build a static model but the most effective way is by integrating seismic and well data through the construction of an acoustic impedance model by inversion of seismic data within a sequence stratigraphic framework. There are several reasons to integrate well-log data into the inverse process in the reservoir characterization workflow, such as the integration of different sources of information in a common earth model, the estimation of the seismic distortion (also known as the wavelet filter), etc. In addition, the low vertical resolution of seismic data is an important motivation to integrate well-log information into the inverse process and thereby complement the relatively dense horizontal coverage of seismic data with high-resolution borehole data (Van Riel and Mesdag, 1988; Van Riel and Pendrel, 2000; Van Riel, 2000; Bosch et al., 2009). Another potential benefit of seismic inversion is the ability to incorporate structural and stratigraphic information of the reservoir in order to differentiate between similar mathematical solutions on the basis of their geological viability. We present two different inversion approaches for poststack, time migrated seismic data and apply them to a clinoform sequence in the North Sea. Both inversion methods are not fully 2D, but more than a series of independently processed 1D inversions. To stress the enforced continuity along the geological structure, we use the name pseudo 2D inversion. The methods use well data as a priori constraints but differ in the way they incorporate structural information. One method uses a discrete layer model from the well that is then propagated laterally along the clinoform layers, which are modeled as sigmoids. The second method uses a constant sampling rate from the well data and employs horizontal and vertical regularization parameters for lateral propagation. Both methods obtain an acoustic impedance image with a high level of detail. The first method has a low level of parameterization embedded in a geological framework and is computationally fast. The second method has a much higher degree of parameterization but is flexible enough to detect deviations in the geological settings of the reservoir, however there is no explicit geological significance and it is computationally much less efficient. Forward seismic modeling of the two inversion results indicates a good match of both methods with the actual seismic data. The methods are especially considered to be useful when seismic data alone do not reveal the actual detailed reservoir architecture, which can be the case either because of their low vertical resolution or exceedingly thin layering.

Probabilistic description of ice-supersaturated layers in low resolution profiles of relative humidity

Abstract. The global observation, assimilation and prediction in numerical models of ice super-saturated (ISS) regions (ISSR) are crucial if the climate impact of aircraft condensation trails (contrails) is to be fully understood, and if, for example, contrail formation is to be avoided through aircraft operational measures. Given their small scales compared to typical atmospheric model grid sizes, statistical representations of the spatial scales of ISSR are required, in both horizontal and vertical dimensions, if global occurrence of ISSR is to be adequately represented in climate models. This paper uses radiosonde launches made by the UK Meteorological Office, from the British Isles, Gibraltar, St. Helena and the Falkland Islands between January 2002 and December 2006, to investigate the probabilistic occurrence of ISSR. Each radiosonde profile is divided into 50- and 100-hPa pressure layers, to emulate the coarse vertical resolution of some atmospheric models. Then the high resolution observations contained within each thick pressure layer are used to calculate an average relative humidity and an ISS fraction for each individual thick pressure layer. These relative humidity pressure layer descriptions are then linked through a probability function to produce an s-shaped curve which empirically describes the ISS fraction in any average relative humidity pressure layer. Using this empirical understanding of the s-shaped relationship a mathematical model was developed to represent the ISS fraction within any arbitrary thick pressure layer. Two models were developed to represent both 50- and 100-hPa pressure layers with each reconstructing their respective s-shapes within 8–10% of the empirical curves. These new models can be used, to represent the small scale structures of ISS events, in modelled data where only low vertical resolution is available. This will be useful in understanding, and improving the global distribution, both observed and forecasted, of ice super-saturation.

Turbulence Patch Identification in Potential Density or Temperature Profiles

Abstract The Thorpe analysis is a recognized method used to identify and characterize turbulent regions within stably stratified fluids. By comparing an observed profile of potential temperature or potential density to a reference profile obtained by sorting the data, overturns resulting in statically unstable regions, mainly because of turbulent patches and Kelvin–Helmholtz billows, can be identified. However, measurement noise may induce artificial inversions of potential temperature or density, which can be very difficult to distinguish from real (physical) overturns. A method for selecting real overturns is proposed. The method is based on the data range statistics; the range is defined as the difference between the maximum and the minimum of the values in a sample. A statistical hypothesis test on the range is derived and evaluated through Monte Carlo simulations. Basically, the test relies on a comparison of the range of a data sample with the range of a normally distributed population of the same size as the data sample. The power of the test, that is, the probability of detecting the existing overturns, is found to be an increasing function of both trend-to-noise ratio (tnr) and overturns size. A threshold for the detectable size of the overturns as a function of tnr is derived. For very low tnr data, the test is shown to be unreliable whatever the size of the overturns. In such a case, a procedure aimed to increase the tnr, mainly based on subsampling, is described. The selection procedure is applied to atmospheric data collected during a balloon flight with low and high vertical resolutions. The fraction of the vertical profile selected as being unstable (turbulent) is 47% (27%) from the high (low) resolution dataset. Furthermore, relatively small tnr measurements are found to give rise to a poor estimation of the vertical extent of the overturns.

A Global Survey of Static Stability in the Stratosphere and Upper Troposphere

Abstract Static stability is a fundamental dynamical quantity that measures the vertical temperature stratification of the atmosphere. However, the magnitude and structure of finescale features in this field are difficult to discern in temperature data with low vertical resolution. In this study, the authors apply more than six years of high vertical resolution global positioning system radio occultation temperature profiles to document the long-term mean structure and variability of the global static stability field in the stratosphere and upper troposphere. The most pronounced feature in the long-term mean static stability field is the well-known transition from low values in the troposphere to high values in the stratosphere. Superposed on this general structure are a series of finer-scale features: a minimum in static stability in the tropical upper troposphere, a broad band of high static stability in the tropical stratosphere, increases in static stability within the core of the stratospheric polar vortices, and a shallow but pronounced maximum in static stability just above the tropopause at all latitudes [i.e., the “tropopause inversion layer” (TIL)]. The results shown here provide the first global survey of static stability using high vertical resolution data and also uncover two novel aspects of the static stability field. In the tropical lower stratosphere, the results reveal a unique vertically and horizontally varying static stability structure, with maxima located at ∼17 and ∼19 km. The upper feature peaks during the NH cold season and has its largest magnitude between 10° and 15° latitude in both hemispheres; the lower feature exhibits a weaker seasonal cycle and is centered at the equator. The results also demonstrate that the strength of the TIL is closely tied to stratospheric dynamic variability. The magnitude of the TIL is enhanced following sudden stratospheric warmings in the polar regions and the easterly phase of the quasi-biennial oscillation in the tropics.

Downscaling Multiple Seismic Inversion Constraints to Fine-Scale Flow Models

Summary Well data reveal reservoir layering with high vertical resolution but are areally sparse, whereas seismic data have low vertical resolution but are areally dense. Improved reservoir models can be constructed by integrating these data. The proposed method combines stochastic seismic inversion results, finer-scale well data, and geologic continuity models to build ensembles of flow models. Stochastic seismic inversions operating at the mesoscale generate rock property estimates, such as porosity, that are consistent with regional rock physics and true-amplitude imaged seismic data. These can be used in a cascading workflow to generate ensembles of fine-scale reservoir models wherein each realization from the Bayesian seismic inversion is treated as an exact constraint for a subensemble of fine-scale models. Exact constraints ensure that relevant interproperty and interzone correlations implied by rock physics and seismic data are preserved in the downscaled models. Uncertainty in the rock physics and seismic response is included by using multiple stochastic inversions in a cascading workflow. In contrast, inexact constraints generally do not preserve these correlations. We use two-point covariance at the fine scale to provide prior model thickness and porosity distributions of multiple facies. A Bayesian formulation uses the kriged data as the prior with the coarse constraints as the likelihood, and this posterior is sampled using a Markov Chain Monte Carlo (MCMC) method in a sequential simulation framework. These methods generate rich pinchout behavior and flexible spatial connectivities in the fine-scale model. These flow models are easily represented on a cornerpoint grid. 2D examples illustrate the interactions of prior and constraint data, and 3D examples demonstrate algorithm performance and the effects of stratigraphic variability on flow behavior.

Specification of External Forcing for Regional Model Integrations

Abstract The effect of vertical and time interpolations of external forcings on the accuracy of regional simulations is examined. Two different treatments of the forcings, one with conventional lateral boundary nudging and the other with spectral nudging, are studied. The main result is that the accuracy of the regional simulation increases very slowly as the number of forcing field levels increase when no spectral nudging is used. Thus, for better simulation, it is desirable to have as many forcing levels as possible. By contrast, spectral nudging improves the regional model simulation when reasonably large numbers of forcing field levels, at least up to nine levels, are given. The accuracy worsens drastically when the number of forcing levels is reduced to less than nine. To improve the simulation, in particular when the forcing field is given at a coarse vertical resolution and at lower time frequency, an incremental interpolation method is introduced. The incremental interpolation in the vertical direction significantly improves the regional simulation at all numbers of forcing field levels. The improvement is largest at very low vertical resolution. Incremental interpolation in time also works excellently, allowing the use of daily output for reasonably accurate downscaling. By using a combination of spectral nudging and incremental interpolation, it is possible to make a reasonably accurate downscaling from the forcing given daily at three–five levels in the vertical direction with low overhead. This considerably reduces the amount of data currently believed to be required to downscale global model integrations.

Evaluation of upper tropospheric humidity forecasts from ECMWF using AIRS and CALIPSO data

Abstract. An evaluation of the upper tropospheric humidity from the European Centre of Medium-Range Weather Forecasts (ECMWF) Integrated Forecast System (IFS) is presented. We first make an analysis of the spinup behaviour of ice supersaturation in weather forecasts. It shows that a spinup period of at least 12 h is necessary before using forecast humidity data from the upper troposphere. We compare the forecasted upper tropospheric humidity with coincident relative humidity fields retrieved from the Atmospheric InfraRed Sounder (AIRS) and with cloud vertical profiles from the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO). The analysis is made over one year, from October 2006 to September 2007, and we discuss how relative humidity and cloud features appear both in the IFS and in the observations. The comparison with AIRS is made difficult because of the vertical resolution of the sounder and the impossibility to retrieve humidity for high cloudiness. Clear sky relative humidities show a rather good correlation whereas cloudy situations reflect more the effect of a dry bias for AIRS increasing with the relative humidity. The comparison with CALIPSO shows that the IFS predicts high relative humidity where CALIPSO finds high clouds, which supports the good quality of the ECMWF upper tropospheric cloud forecast. In a last part, we investigate the presence of ice supersaturation within low vertical resolution pressure layers by comparing the IFS outputs for high-resolution and low-resolution humidity profiles and by simulating the interpolation of humidity over radiosonde data. A new correction method is proposed and tested with these data.

CO emission and export from Asia: an analysis combining complementary satellite measurements (MOPITT, SCIAMACHY and ACE-FTS) with global modeling

Abstract. This study presents the complementary picture of the pollution outflow provided by several satellite observations of carbon monoxide (CO), based on different observation techniques. This is illustrated by an analysis of the Asian outflow during the spring of 2005, through comparisons with simulations by the LMDz-INCA global chemistry transport model. The CO observations from the MOPITT and SCIAMACHY nadir sounders, which provide vertically integrated information with excellent horizontal sampling, and from the ACE-FTS solar occultation instrument, which has limited spatial coverage but allows the retrieval of vertical profiles, are used. Combining observations from MOPITT (mainly sensitive to the free troposphere) and SCIAMACHY (sensitive to the full column) allows a qualitative evaluation of the boundary layer CO. The model tends to underestimate this residual compared to the observations, suggesting underestimated emissions, especially in eastern Asia. However, a better understanding of the consistency and possible biases between the MOPITT and SCIAMACHY CO is necessary for a quantitative evaluation. Underestimated emissions, and possibly too low lofting and underestimated chemical production in the model, lead to an underestimate of the export to the free troposphere, as highlighted by comparisons with MOPITT and ACE-FTS. Both instruments observe large trans-Pacific transport extending from ~20° N to ~60° N, with high upper tropospheric CO observed by ACE-FTS above the eastern Pacific (with values of up to 300 ppbv around 50° N at 500 hPa and up to ~200 ppbv around 30° N at 300 hPa). The low vertical and horizontal resolutions of the global model do not allow the simulation of the strong enhancements in the observed plumes. However, the transport patterns are well captured, and are mainly attributed to export from eastern Asia, with increasing contributions from South Asia and Indonesia towards the tropics. Additional measurements of C2H2, C2H6 and HCN by ACE-FTS provide further information on the plume history. C2H2 and C2H6 enhancements are well correlated with the CO plumes, indicating common sources and rapid trans-Pacific transport. HCN observations show that the biomass burning contributes mainly at latitudes lower than ~40° N. This study provides a first step towards a full combination of complementary observations, but also highlights the need for a better evaluation of consistency between the datasets in order to allow precise quantitative analyses.

A New Two-Moment Bulk Stratiform Cloud Microphysics Scheme in the Community Atmosphere Model, Version 3 (CAM3). Part I: Description and Numerical Tests

Abstract A new two-moment stratiform cloud microphysics scheme in a general circulation model is described. Prognostic variables include cloud droplet and cloud ice mass mixing ratios and number concentrations. The scheme treats several microphysical processes, including hydrometeor collection, condensation/evaporation, freezing, melting, and sedimentation. The activation of droplets on aerosol is physically based and coupled to a subgrid vertical velocity. Unique aspects of the scheme, relative to existing two-moment schemes developed for general circulation models, are the diagnostic treatment of rain and snow number concentration and mixing ratio and the explicit treatment of subgrid cloud water variability for calculation of the microphysical process rates. Numerical aspects of the scheme are described in detail using idealized one-dimensional offline tests of the microphysics. Sensitivity of the scheme to time step, vertical resolution, and numerical method for diagnostic precipitation is investigated over a range of conditions. It is found that, in general, two substeps are required for numerical stability and reasonably small time truncation errors using a time step of 20 min; however, substepping is only required for the precipitation microphysical processes rather than the entire scheme. A new numerical approach for the diagnostic rain and snow produces reasonable results compared to a benchmark simulation, especially at low vertical resolution. Part II of this study details results of the scheme in single-column and global simulations, including comparison with observations.

Two overflows in the Northern Gulf of California

Two overflows, originating at sills in the northern Gulf of California, are marked by strong average downstream slopes of 17 and 4%. Near‐bottom stratification upstream of both sills is relatively strong, but the near‐bottom water is very well mixed downstream of the sills. The homogenization of a thick bottom layer downstream, albeit close to the sills, is indicative of very strong mixing. Waters in the downstream basins are well ventilated with relatively high oxygen concentrations. These hydrographic patterns were observed during three different seasons. Time series of temperature, salinity, and potential density show that water, flowing over the sills, is essentially subsurface, subtropical water from the Pacific Ocean. The time series also indicate that water is nearly always denser at the sills compared to water in the downstream basins, despite the two‐fold (∼800 m) and more than three‐fold (∼1500 m) increase in depth. The long‐term (more than a year) average current at both sills is bottom intensified with maximum average speeds of 33 and 17 cm/s. There are also strong tidal currents at the sills, although the subinertial currents near the bottom are quite persistent with nearly no flow reversals. Transports, estimated exclusively with the mean flow, are about 0.08 and 0.09 Sv (1 Sv = 1× 106, m3/s), which agree well with previous estimates based on shorter time series and a lower vertical resolution. These results indicate that the deep water at both downstream basins are renewed by these overflows, which enter at sill depths ≤400 m and are capable of reaching the deepest part of both basins. The overflows appear to be responsible for the main mechanisms that transform subsurface, subtropical water into Gulf of California water.

Steering of upper ocean currents and fronts by the topographically constrained abyssal circulation

A two-layer theory is used to investigate (1) the steering of upper ocean current pathways by topographically constrained abyssal currents that do not impinge on the bottom topography and (2) its application to upper ocean – topographic coupling via flow instabilities where topographically constrained eddy-driven deep mean flows in turn steer the mean pathways of upper ocean currents and associated fronts. In earlier studies the two-layer theory was applied to ocean models with low vertical resolution (2–6 layers). Here we investigate its relevance to complex ocean general circulation models (OGCMs) with high vertical resolution that are designed to simulate a wide range of ocean processes. The theory can be easily applied to models ranging from idealized to complex OGCMs, provided it is valid for the application. It can also be used in understanding some persistent features seen in observed ocean frontal pathways (over deep water) derived from satellite imagery and other data. To facilitate its application, a more thorough explanation of the theory is presented that emphasizes its range of validity. Three regions of the world ocean are used to investigate its application to eddy-resolving ocean models with high vertical resolution, including one where an assumption of the two-layer theory is violated. Results from the OGCMs with high vertical resolution are compared to those from models with low vertical resolution and to observations. In the Kuroshio region upper ocean – topographic coupling via flow instabilities and a modest seamount complex are used to explain the observed northward mean meander east of Japan where the Kuroshio separates from the coast. The Japan/East Sea (JES) is used to demonstrate the impact of upper ocean – topographic coupling in a relatively weak flow regime. East of South Island, New Zealand, the Southland Current is an observed western boundary current that flows in a direction counter to the demands of Sverdrup flow and counter to the direction simulated in nonlinear global flat bottom and reduced gravity models. A model with high vertical resolution (and topography extending through any number of layers) and a model with low vertical resolution (and vertically compressed but otherwise realistic topography confined to the lowest layer) both simulate a Southland Current in the observed direction with dynamics depending on the configuration of the regional seafloor. However, the dynamics of these simulations are very different because the Campbell Plateau and Chatham Rise east and southeast of New Zealand are rare features of the world ocean where the topography intrudes into the stratified water column over a relatively broad area but lies deeper than the nominal 200 m depth of the continental shelf break, violating a limitation of the two-layer theory. Observations confirm the results from the high vertical resolution model. Overall, the model simulations show increasingly widespread upper ocean – topographic coupling via flow instabilities as the horizontal resolution of the ocean models is increased, but fine resolution of mesoscale variability and the associated flow instabilities are required to obtain sufficient coupling. As a result, this type of coupling is critical in distinguishing between eddy-resolving and eddy-permitting ocean models in regions where it occurs.

Intercomparison of Odin–SMR ozone profiles with ground-based millimetre-wave observations in the Arctic, the mid-latitudes, and the tropics

The sub-millimetre radiometer (SMR) on board the Odin satellite measures signatures of ozone in two bands centred at 501.8 and 544.6 GHz. From the measurements, ozone volume mixing ratio profiles in the stratosphere and lower mesosphere are retrieved using the Optimal Estimation Method. In this paper, the ozone profiles measured by Odin–SMR (level-2 data ver. 2.1 and 2.0, respectively) are compared to measurements taken by ground-based millimetre wave radiometers in the Arctic; at Kiruna, Sweden; in the mid-latitudes on the Zugspitze, Germany; and in the tropics at Mérida, Venezuela. The Kiruna Microwave Radiometer (KIMRA) covers the frequency range 195–224 GHz, and the Millimeter Wave Radiometer MIRA 2, which was operated on the Zugspitze and at Mérida, measures in the frequency band 268–281 GHz. From the measurements, ozone profiles in the vertical range between approximately 15–65 km were retrieved using the Optimal Estimation Method. Since the ground-based measurements have a lower vertical resolution than those of Odin the latter were degraded using the averaging kernels of the ground-based retrievals. The comparison of the resulting profiles to the ground-based data enables the identification of biases in the Odin measurements and their possible latitudinal variation. In general, a good agreement between satellite and ground-based measurements for the 501.8 GHz band was found in the stratosphere except for a negative bias in the Odin data of about 10–15% in the tropical measurements. The Odin measurements taken at 544.9 GHz yielded systematically 20–30% lower ozone mixing ratios in the middle stratosphere than the ground-based measurements at all sites. PACS No.: 92.60.hd

Direct Prediction of Reservoir Performance With Bayesian Updating

Abstract Conventional geostatistics aims at creating models of heterogeneity and uncertainty in static rock properties such as facies, porosity and permeability. This is appropriate for providing input to flow simulations. There are times, however, when no flow simulation is going to be performed and we would like to directly predict reservoir flow characteristics. Different techniques are required when the aim is to directly create maps of the (uncertainty in) production potential. This paper summarizes a technique for this purpose. The petroleum industry is reliant on many types of geological and geophysical information to predict reservoir performance. This data covers different areas, provides data on different scales and is variably correlated to the production characteristics we are trying to predict. Statistical techniques can be used to summarize the relationships between the variables, however, they do not account for spatial correlation. Geostatistical techniques incorporate spatial structure but these techniques are cumbersome in the presence of many secondary variables. We propose that all secondary data be merged statistically by a multivariate Gaussian approach into a single variable that contains all of the secondary variable information. This would provide a likelihood distribution. The spatial distribution of each variable by itself is mapped independently of the secondary variable information, which provides a prior distribution. The likelihoods and priors are merged to provide an updated posterior distribution. We describe the methodology and show an example application. Introduction Our goal is to directly predict reservoir performance potential summarized by production variables. The production variables we are predicting are measures of hydrocarbon flow rate and projected cumulative production. We assume that the wells are far enoughapart to avoid any significant interactions. Reservoir characterization aims to use all data to improve the understanding of reservoir performance potential at locations where we have no wells(1). In general, we can group the available data into the following categories:Geological variables that take two forms:maps of interpreted variables based on expert judgment and regional depositional setting; anddirect well measurements of variables such as porosity, pay thickness and so on.Alternatively, these variables can be grouped in structural variables dealing with container size and shape, and geological variables dealing with internal reservoir quality.Geophysical variables that have high areal resolution, low vertical resolution and variable correlation to actual rock properties and production variables. These variables can be direct attributes such as amplitudes, or processed variables such as interpreted fracture densities or P/S impedances.Production variables that we are trying to predict, such as initial production rate and projected cumulative production. These variables would typically be interpreted from the production at existing wells; that is, some kind of decline analysis. The production variables have some spatial correlation that we can exploit, however, we must also exploit the information contained in the geological and geophysical variables that are related to the production variables we are trying to predict. These secondary data sources are also redundant with each other and we need to establish the true information content in all data sources.

Sensitivity analysis of data-related factors controlling AVA simultaneous inversion of partially stacked seismic amplitude data: Application to deepwater hydrocarbon reservoirs in the central Gulf of Mexico

We consider the inversion of synthetic and recorded seismic amplitude variation with angle AVA data to appraise the influence of several data-related factors that control the vertical resolution and accuracy of the estimated spatial distributions of elastic properties. We use measurements acquired in deepwater hydrocarbon reservoirs in the central Gulf of Mexico to generate synthetic seismic amplitude data and evaluate inversion results with both synthetic and recorded seismic amplitudes. Detailed sensitivity analysis of synthetic amplitude data indicates that, even in the most ideal scenario (perfectly migrated data, isotropic media, noise-free seismic amplitude data, sufficient far-angle coverage, and accurate estimates of angle-dependent wavelets and low-frequency components), input elastic models are not reconstructedaccurately by the inversion of synthetic seismic amplitudes. We attribute this result to the relatively low vertical resolution of the seismic amplitude data. P-wave impedance is the most accurate of the inverted properties, followed by S-impedance and bulk density. Additionally, sufficient far-angle coverage is crucial for the accurate estimation of 1D distributions of S-impedance and bulk density. We show that time alignment of partial-angle stacks for correcting residual NMO effects improves the vertical resolution of the estimated spatial distributions of elastic parameters and consistently decreases the data misfit. Finally, we found that the accuracy of the inverted distributions of elastic parameters is improved substantially by (1) increasing the preserved AVA information via multiple single-angle stacks, (2) correcting the P-wave velocity field used for calculating angles in partial-angle stacking, and (3) excluding far-angle data with low signal-to-noise ratios.

Sensitivity of Simulated Climate to Horizontal and Vertical Resolution in the ECHAM5 Atmosphere Model

Abstract The most recent version of the Max Planck Institute for Meteorology atmospheric general circulation model, ECHAM5, is used to study the impact of changes in horizontal and vertical resolution on seasonal mean climate. In a series of Atmospheric Model Intercomparison Project (AMIP)-style experiments with resolutions ranging between T21L19 and T159L31, the systematic errors and convergence properties are assessed for two vertical resolutions. At low vertical resolution (L19) there is no evidence for convergence to a more realistic climate state for horizontal resolutions higher than T42. At higher vertical resolution (L31), on the other hand, the root-mean-square errors decrease monotonically with increasing horizontal resolution. Furthermore, except for T42, the L31 versions are superior to their L19 counterparts, and the improvements become more evident at increasingly higher horizontal resolutions. This applies, in particular, to the zonal mean climate state and to the stationary wave patterns in boreal winter. As in previous studies, increasing horizontal resolution leads to a warming of the troposphere, most prominently at midlatitudes, and to a poleward shift and intensification of the midlatitude westerlies. Increasing the vertical resolution has the opposite effect, almost independent of horizontal resolution. Whereas the atmosphere is colder at low and middle latitudes, it is warmer at high latitudes and close to the surface. In addition, increased vertical resolution results in a pronounced warming in the polar upper troposphere and lower stratosphere, where the cold bias is reduced by up to 50% compared to L19 simulations. Consistent with these temperature changes is a decrease and equatorward shift of the midlatitude westerlies. The substantial benefits in refining both horizontal and vertical resolution give some support to scaling arguments deduced from quasigeostrophic theory implying that horizontal and vertical resolution ought to be chosen consistently.

Meteorological implementation issues in chemistry and transport models

Abstract. Offline chemistry and transport models (CTMs) are versatile tools for studying composition and climate issues requiring multi-decadal simulations. They are computationally fast compared to coupled chemistry climate models, making them well-suited for integrating sensitivity experiments necessary for understanding model performance and interpreting results. The archived meteorological fields used by CTMs can be implemented with lower horizontal or vertical resolution than the original meteorological fields in order to shorten integration time, but the effects of these shortcuts on transport processes must be understood if the CTM is to have credibility. In this paper we present a series of sensitivity experiments on a CTM using the Lin and Rood advection scheme, each differing from another by a single feature of the wind field implementation. Transport effects arising from changes in resolution and model lid height are evaluated using process-oriented diagnostics that intercompare CH4, O3, and age tracer carried in the simulations. Some of the diagnostics used are derived from observations and are shown as a reality check for the model. Processes evaluated include tropical ascent, tropical-midlatitude exchange, poleward circulation in the upper stratosphere, and the development of the Antarctic vortex. We find that faithful representation of stratospheric transport in this CTM is possible with a full mesosphere, ~1 km resolution in the lower stratosphere, and relatively low vertical resolution (>4 km spacing) in the middle stratosphere and above, but lowering the lid from the upper to lower mesosphere leads to less realistic constituent distributions in the upper stratosphere. Ultimately, this affects the polar lower stratosphere, but the effects are greater for the Antarctic than the Arctic. The fidelity of lower stratospheric transport requires realistic tropical and high latitude mixing barriers which are produced at 2°×2.5°, but not lower resolution. At 2°×2.5° resolution, the CTM produces a vortex capable of isolating perturbed chemistry (e.g. high Cly and low NOy) required for simulating polar ozone loss.