Correction to: Evaluation of a multi-model approach to estimate leaf wetness duration: an essential input for disease alert systems

Theoretical and Applied Climatology -     

Methodology for benefit–cost analysis of seismic codes

A number of high-profile seismic events have occurred in recent years, with a wide variation in the resulting economic damage and loss of life. This variation has been attributed in part to the stringency of seismic building codes implemented in different regions. Using the HAZUS Earthquake Model, a benefit?Ccost analysis was performed on varying levels of standard buildings codes for Haiti and Puerto Rico. The methodology computes expected loss assuming a Poisson event process with lognormally distributed event magnitude and idealized damage?Cmagnitude response functions. The event frequency and magnitude distributions are estimated from the historical record, while the damage functions are fit using HAZUS simulation results for events with systematically varying magnitudes and different seismic code levels. To validate the approach, a single-event analysis was conducted using alternative building codes and mean magnitude earthquakes. A probabilistic analysis was then used to evaluate the long-term expected value for alternative levels of building codes. To account for the relationship between lives saved and economic loss, the implicit cost of saving a life is computed for each code option. It was found that in the two areas studied, the expected loss of life was reduced the most by use of high seismic building code levels, but lower levels of seismic building code were more cost-effective when considering only building damages and the costs for code implementation. The methodology presented is meant to provide a basic framework for the future development of an economic-behavioral model for code adoption.     

Geomorphology of the Alluvial Sediments and Bedrock in an Intermontane Basin: Application of Variogram Modeling to Electrical Resistivity Soundings

The study describes a methodology used to integrate legacy resistivity data with limited geological data in order to build three-dimensional models of the near subsurface. Variogram analysis and inversion techniques more typically found in the petroleum industry are applied to a set of 1D resistivity data taken from electrical surveys conducted in the 1980s. Through careful integration with limited geological data collected from boreholes and outcrops, the resultant model can be visualized in three dimensions to depict alluvium layers as lithological and structural units within the bedrock. By tuning the variogram parameters to account for directionality, it is possible to visualize the individual lithofacies and geomorphological features in the subsurface. In this study, an electrical resistivity data set collected as part of a groundwater study in an area of the Peshawar basin in Pakistan has been re-examined. Additional lithological logs from boreholes throughout the area have been combined with local outcrop information to calibrate the data. Tectonic activity during the Himalayan orogeny has caused uplift in the area and generated significant faulting in the bedrock resulting in the formation of depressions which are identified by low resistivity values representing clays. Paleo-streams have reworked these clays which have been eroded and replaced by gravel–sand facies along paleo-channels. It is concluded that the sediments have been deposited as prograding fan-shaped bodies and lacustrine deposits with interlayered gravel–sand and clay–silt facies. The Naranji area aquifer system has thus been formed as a result of local tectonic activity with fluvial erosion and deposition and is characterized by coarse sediments with high electrical resistivities.     

Effectiveness of subsurface pressure monitoring for brine leakage detection in an uncertain CO2 sequestration system

This work evaluates the detection sensitivity of deep subsurface pressure monitoring within an uncertain carbon dioxide sequestration system by linking the output of an analytical reduced-order model and first-order uncertainty analysis. A baseline (non-leaky) modeling run was compared against 10 different leakage scenarios, where the cap rock permeability was increased by factors of 2–100 (cap rock permeability from 10^?3 to 10^?1 millidarcy). The uncertainty variance outputs were used to develop percentile estimates and detection sensitivity for pressure throughout the deep subsurface as a function of space (lateral distance from the injection wells and vertical orientation within the reservoir) and time (years since injection), or P(x, z, t). Conditional probabilities were computed for combinations of x, z, and t, which were then used to generate power curves for detecting leakage scenarios. The results suggest that measurements of the absolute change in pressure within the target injection aquifer would not be able to distinguish small leakage rates (i.e., less than 50 × baseline) from baseline conditions, and that only large leakage rates (i.e., >100 × baseline) would be discriminated with sufficient statistical power (>99 %). Combining measurements, for example by taking the ratio of formation pressure in Aquifer 2/Aquifer 1, provides better statistical power for distinguishing smaller leakage rates at earlier times in the injection program. Detection sensitivity for pressure is a function of space and time. Therefore, design of an adequate monitoring network for subsurface pressure should account for this space–time variability to ensure that the monitoring system performs to the necessary design criteria, e.g., specific false-negative and false-positive rates.     

Intraseasonal variability in the far-east pacific: investigation of the role of air�Csea coupling in a regional coupled model

Intraseasonal variability in the eastern Pacific warm pool in summer is studied, using a regional ocean?Catmosphere model, a linear baroclinic model (LBM), and satellite observations. The atmospheric component of the model is forced by lateral boundary conditions from reanalysis data. The aim is to quantify the importance to atmospheric deep convection of local air?Csea coupling. In particular, the effect of sea surface temperature (SST) anomalies on surface heat fluxes is examined. Intraseasonal (20?C90?day) east Pacific warm-pool zonal wind and outgoing longwave radiation (OLR) variability in the regional coupled model are correlated at 0.8 and 0.6 with observations, respectively, significant at the 99% confidence level. The strength of the intraseasonal variability in the coupled model, as measured by the variance of outgoing longwave radiation, is close in magnitude to that observed, but with a maximum located about 10° further west. East Pacific warm pool intraseasonal convection and winds agree in phase with those from observations, suggesting that remote forcing at the boundaries associated with the Madden?CJulian oscillation determines the phase of intraseasonal convection in the east Pacific warm pool. When the ocean model component is replaced by weekly reanalysis SST in an atmosphere-only experiment, there is a slight improvement in the location of the highest OLR variance. Further sensitivity experiments with the regional atmosphere-only model in which intraseasonal SST variability is removed indicate that convective variability has only a weak dependence on the SST variability, but a stronger dependence on the climatological mean SST distribution. A scaling analysis confirms that wind speed anomalies give a much larger contribution to the intraseasonal evaporation signal than SST anomalies, in both model and observations. A LBM is used to show that local feedbacks would serve to amplify intraseasonal convection and the large-scale circulation. Further, Hovm?ller diagrams reveal that whereas a significant dynamic intraseasonal signal enters the model domain from the west, the strong deep convection mostly arises within the domain. Taken together, the regional and linear model results suggest that in this region remote forcing and local convection?Ccirculation feedbacks are both important to the intraseasonal variability, but ocean?Catmosphere coupling has only a small effect. Possible mechanisms of remote forcing are discussed.     

The CARIB97 high-resolution geoid height model for the Caribbean Sea

A 2×2 arc-minute resolution geoid model, CARIB97, has been computed covering the Caribbean Sea. The geoid undulations refer to the GRS-80 ellipsoid, centered at the ITRF94 (1996.0) origin. The geoid level is defined by adopting the gravity potential on the geoid as W ₀=62 636 856.88 m²/s² and a gravity-mass constant of GM=3.986 004 418×10¹⁴ m³/s². The geoid model was computed by applying high-frequency corrections to the Earth Gravity Model 1996 global geopotential model in a remove-compute-restore procedure. The permanent tide system of CARIB97 is non-tidal. Comparison of CARIB97 geoid heights to 31 GPS/tidal (ITRF94/local) benchmarks shows an average offset (h–H–N) of 51 cm, with an Root Mean Square (RMS) of 62 cm about the average. This represents an improvement over the use of a global geoid model for the region. However, because the measured orthometric heights (H) refer to many differing tidal datums, these comparisons are biased by localized permanent ocean dynamic topography (PODT). Therefore, we interpret the 51 cm as partially an estimate of the average PODT in the vicinity of the 31 island benchmarks. On an island-by-island basis, CARIB97 now offers the ability to analyze local datum problems which were previously unrecognized due to a lack of high-resolution geoid information in the area. Received: 2 January 1998 / Accepted: 18 August 1998     

On the control of subantarctic stratification by the ocean circulation

Climate Dynamics - A shallow mixed layer depth bias in Austral winter in the Subantarctic Zone is a common feature of Coupled Model Intercomparison Project (CMIP5) models, including the Community...     

An algorithm for soil moisture estimation using GPS-interferometric reflectometry for bare and vegetated soil

Ground-reflected global positioning system signals measured by a geodetic-quality GPS system can be used to infer temporal changes in near-surface soil moisture for the area surrounding the antenna. This technique, known as GPS-interferometric reflectometry, analyzes changes in the interference pattern of the direct and reflected signals, which are recorded in signal-to-noise ratio (SNR) data, as interferograms. Temporal fluctuations in the phase of the interferogram are indicative of changes in near-surface volumetric soil moisture content. However, SNR phase is also highly sensitive to changes in overlying vegetation, and thus, the effects of seasonal vegetation changes on the ground-reflected signal must be considered. Here a method is described for determining whether SNR data are significantly corrupted by vegetation and for correcting these effects. Absolute soil moisture content must be determined for each site using ancillary data for the residual moisture content. Accounting for vegetation effects significantly improves the agreement between GPS-derived soil moisture and in situ measurements.