Numerical Modeling of Ice Fog in Interior Alaska Using the Weather Research and Forecasting Model

An ice microphysics parameterization scheme has been modified to better describe and understand ice fog formation. The modeling effort is based on observations in the Sub-Arctic Region of Interior Alaska, where ice fog occurs frequently during the cold season due to abundant water vapor sources and strong inversions existing near the surface at extremely low air temperatures. The microphysical characteristics of ice fog are different from those of other ice clouds, implying that the microphysical processes of ice should be changed in order to generate ice fog particles. Ice fog microphysical characteristics were derived with the NCAR Video Ice Particle Sampler during strong ice fog cases in the vicinity of Fairbanks, Alaska, in January and February 2012. To improve the prediction of ice fog in the Weather Research and Forecasting model, observational data were used to change particle size distribution properties and gravitational settling rates, as well as to implement a homogeneous freezing process. The newly implemented homogeneous freezing process compliments the existing heterogeneous freezing scheme and generates a higher number concentration of ice crystals than the original Thompson scheme. The size distribution of ice crystals is changed into a Gamma distribution with the shape factor of 2.0, using the observed size distribution. Furthermore, gravitational settling rates are reduced for the ice crystals since the crystals in ice fog do not precipitate in a similar manner when compared to the ice crystals of cirrus clouds. The slow terminal velocity plays a role in increasing the time scale for the ice crystals to settle to the surface. Sensitivity tests contribute to understanding the effects of water vapor emissions as an anthropogenic source on the formation of ice fog.     

Radiation Fog Prediction Using a Simple Numerical Model

—A simple one-dimensional numerical-analytical model was developed by Meyer and Rao (1995) to predict the onset of radiation fog. The model computes radiative cooling and turbulent diffusion of heat and vapor through the lower boundary layer and produces heat and vapor fluxes at the soil–atmosphere interface. The model is designed for Air Force forecasters who have access to a personal computer, an early evening surface observation of the dry bulb and dewpoint temperature, wind speed, the lapse rate in the upper boundary layer, and the previous 24-h precipitation amount. These initial data are used to predict the diurnal variation of the dry bulb and dewpoint temperatures at 10 m above the surface. In accordance with conventional synoptic observing practices, fog is defined as a restriction of the surface visibility generally to less than 1000 m. Fog is assumed to occur in the model predictions when the dewpoint depression falls to less than 1°C. Observations, from several Air Force bases for selected days when fog was observed to occur, were used to test the model. The present model with default parameters appears to predict the onset of fog slightly ahead of its occurrence. Better verification results are expected when site-relevant parameters are used in model predictions.     

Enhancements to,and forthcoming developments in the Interactive Multisensor Snow and Ice Mapping System (IMS)

The National Oceanic and Atmospheric Administration's National Environmental Satellite Data and Information Service (NOAA/NESDIS) Interactive Multisensor Snow and Ice Mapping System (IMS) has undergone substantial changes since its inception in 1997. These changes include the data sources used to generate the product, methodology of product creation, and even changes in the output. Among the most notable of the past upgrades to the IMS are a 4‐km resolution grid output, ingest of an automated snow detection algorithm, expansion to a global extent, and a static Digital Elevation Model for mapping based on elevation. Further developments to this dynamic system will continue as NOAA strives to improve snow parameterization for weather forecast modeling. Several future short‐term enhancements will be evaluated for possible transition to operations before the Northern Hemisphere winter of 2006–2007. Current and historical data will be adopted to a geographic information systems (GIS) format before 2007, as well. Longer‐term enhancements are also planned to account for new snow data sources, mapping methodologies and user requirements. These modifications are being made with care to preserve the integrity of the long‐standing satellite‐derived snow record that is vital to global change detection. Published in 2007 by John Wiley & Sons, Ltd.     

Rayleigh-Wave Dispersive Energy Imaging Using a High-Resolution Linear Radon Transform

Multichannel Analysis of Surface Waves (MASW) analysis is an efficient tool to obtain the vertical shear-wave profile. One of the key steps in the MASW method is to generate an image of dispersive energy in the frequency-velocity domain, so dispersion curves can be determined by picking peaks of dispersion energy. In this paper, we propose to image Rayleigh-wave dispersive energy by high-resolution linear Radon transform (LRT). The shot gather is first transformed along the time direction to the frequency domain and then the Rayleigh-wave dispersive energy can be imaged by high-resolution LRT using a weighted preconditioned conjugate gradient algorithm. Synthetic data with a set of linear events are presented to show the process of generating dispersive energy. Results of synthetic and real-world examples demonstrate that, compared with the slant stacking algorithm, high-resolution LRT can improve the resolution of images of dispersion energy by more than 50%.     

High-Resolution Characterization of a Chlorinated Solvent Impacted Aquifer Using a Passive Profiler

A direct-drive high-resolution passive profiler (HRPP) was developed to quantify and delineate concentrations of chlorinated volatile organic compounds (CVOCs), geochemical indicators and CVOC-degrading microorganisms/genes, as well as to perform compound-specific stable isotope analysis (CSIA) of CVOCs and estimate interstitial velocity at <30-cm resolution. The profilers can be coupled together to provide a continuous sample interval and advanced to depths up to approximately 9 m below-ground surface (bgs) within saturated media where direct-push techniques are feasible. The HRPP was field tested in a previous dense nonaqueous phase liquid (DNAPL) source zone at the former Naval Air Station in Alameda, CA. HRPP data sets were compared to the following traditional groundwater data sets: CVOC and anion concentrations in standard and multilevel monitoring well water samples, CVOC concentrations in soil core samples, qualitative contaminant profiles delineated with a membrane interface probe (MIP), microbial community and CSIA profiles from Bio-Traps® deployed in wells, groundwater velocity from passive flux meters (PFMs), lithologic profiles correlated with MIP electrical conductivity (EC), and velocity estimates based on permeability profiles measured with a Geoprobe hydraulic profiling tool (HPT). In some cases, the HRPP data were equivalent to traditional techniques and, in other cases, the HRPP data were more representative of local variability rather than bulk aquifer conditions. Overall the results support the use of the HRPP to provide high-resolution data on concentrations, velocity, and microbial activity in temporary direct-push deployments without well installation, providing a new tool to better assess source zones and contaminated groundwater plumes, even in low permeability media, and to increase the fidelity of site transport models.     

Estimation of Interstitial Velocity Using a Direct Drive High-Resolution Passive Profiler

The fate and transport of groundwater contaminants depends partially on groundwater velocity, which can vary appreciably in highly stratified aquifers. A high-resolution passive profiler (HRPP) was developed to evaluate groundwater velocity, contaminant concentrations, and microbial community structure at ∼20 cm vertical depth resolution in shallow heterogeneous aquifers. The objective of this study was to use mass transfer of bromide (Br⁻), a conservative tracer released from cells in the HRPP, to estimate interstitial velocity. Laboratory experiments were conducted to empirically relate velocity and the mass transfer coefficient of Br⁻ based on the relative loss of Br⁻ from HRPP cells. Laboratory-scale HRPPs were deployed in flow boxes containing saturated soils with differing porosities, and the mass transfer coefficient of Br⁻ was measured at multiple interstitial velocities (0 to 100 cm/day). A two-dimensional (2D) quasi-steady-state model was used to relate velocity to mass transfer of Br⁻ for a range of soil porosities (0.2–0.5). The laboratory data indicate that the mass transfer coefficient of Br⁻, which was directly—but non-linearly—related to velocity, can be determined with a single 3-week deployment of the HRPP. The mass transfer coefficient was relatively unaffected by sampler orientation, length of deployment time, or porosity. The model closely simulated the experimental results. The data suggest that the HRPP will be applicable for estimating groundwater velocity ranging from 1 to 100 cm/day in the field at a minimum depth resolution of 10 cm, depending on sampler design.     

Ice and Snow Cover of Continental Water Bodies from Simultaneous Radar Altimetry and Radiometry Observations

We show how the studies of ice and snow cover of continental water bodies can benefit from the synergy of more than 15 years-long simultaneous active (radar altimeter) and passive (radiometer) observations from radar altimetric satellites (TOPEX/Poseidon, Jason-1, ENVISAT and Geosat Follow-On) and how this approach can be complemented by SSM/I passive microwave data to improve spatial and temporal coverage. Five largest Eurasian continental water bodies—Caspian and Aral seas, Baikal, Ladoga and Onega lakes are selected as examples. First we provide an overview of ice regime and history of ice studies for these seas and lakes. Then a summary of the existing state of the art of ice discrimination methodology from altimetric observations and SSM/I is given. The drawbacks and benefits of each type of sensor and particularities of radiometric properties for each of the chosen water bodies are discussed. Influence of sensor footprint size, ice roughness and snow cover on satellite measurements is also addressed. A step-by-step ice discrimination approach based on a combined use of the data from the four altimetric missions and SSM/I is presented, as well as validation of this approach using in situ and independent satellite data in the visible range. The potential for measurement of snow depth on ice from passive microwave observations using both altimeters and SSM/I is addressed and a qualitative comparison of in situ snow depth observations and satellite-derived estimates is made.     

A One-dimensional Ensemble Forecast and Assimilation System for Fog Prediction

A probabilistic fog forecast system was designed based on two high resolution numerical 1-D models called COBEL and PAFOG. The 1-D models are coupled to several 3-D numerical weather prediction models and thus are able to consider the effects of advection. To deal with the large uncertainty inherent to fog forecasts, a whole ensemble of 1-D runs is computed using the two different numerical models and a set of different initial conditions in combination with distinct boundary conditions. Initial conditions are obtained from variational data assimilation, which optimally combines observations with a first guess taken from operational 3-D models. The design of the ensemble scheme computes members that should fairly well represent the uncertainty of the current meteorological regime. Verification for an entire fog season reveals the importance of advection in complex terrain. The skill of 1-D fog forecasts is significantly improved if advection is considered. Thus the probabilistic forecast system has the potential to support the forecaster and therefore to provide more accurate fog forecasts.     

Global Snow Mass Measurements and the Effect of Stratigraphic Detail on Inversion of Microwave Brightness Temperatures

Snow provides large seasonal storage of freshwater, and information about the distribution of snow mass as snow water equivalent (SWE) is important for hydrological planning and detecting climate change impacts. Large regional disagreements remain between estimates from reanalyses, remote sensing and modelling. Assimilating passive microwave information improves SWE estimates in many regions, but the assimilation must account for how microwave scattering depends on snow stratigraphy. Physical snow models can estimate snow stratigraphy, but users must consider the computational expense of model complexity versus acceptable errors. Using data from the National Aeronautics and Space Administration Cold Land Processes Experiment and the Helsinki University of Technology microwave emission model of layered snowpacks, it is shown that simulations of the brightness temperature difference between 19 and 37 GHz vertically polarised microwaves are consistent with advanced microwave scanning radiometer-earth observing system and special sensor microwave imager retrievals once known stratigraphic information is used. Simulated brightness temperature differences for an individual snow profile depend on the provided stratigraphic detail. Relative to a profile defined at the 10-cm resolution of density and temperature measurements, the error introduced by simplification to a single layer of average properties increases approximately linearly with snow mass. If this brightness temperature error is converted into SWE using a traditional retrieval method, then it is equivalent to ±13 mm SWE (7 % of total) at a depth of 100 cm. This error is reduced to ±5.6 mm SWE (3 % of total) for a two-layer model.     

Modelling Snow Slab Release Using a Temperature-Dependent Viscoelastic Finite Element Model with Weak Layers

A two-dimensional thermo-mechanicalplane-strain finite element model forsnow is presented. Snow is modeled asa two component porous medium consisting ofa solid ice matrix and interstitial pore air.The ice and air phases are not always in thermalequilibrium. Therefore, heat transport is governedby two non-stationary energy conservation equationswhich are coupled by free convection heat exchangesat the interfacial ice-air boundary. The icematrix deforms viscoelastically according to anexperimentally-based temperature dependent constitutivelaw. Creep deformation rates are governed by a powerlaw with a density dependent exponent n.The highly nonlinear character of the mechanical modelis illustrated by simulating snowcovers with layersof variable height and density. Weak layerinterfaces – believed to be the location of initiationof snow slab fracture – are modeled using specialfinite elements which transfer normal stresses buthave little or no shear resistance. Stress andstrain-rate concentrations at the boundaries ofweak zones are calculated and compared withbrittle fracture strain-rates.     

Seasonal Sensitivity on COBEL-ISBA Local Forecast System for Fog and Low Clouds

Skillful low visibility forecasts are essential for air-traffic managers to effectively regulate traffic and to optimize air-traffic control at international airports. For this purpose, the COBEL-ISBA local numerical forecast system has been implemented at Paris CDG international airport. This local approach is robust owing to the assimilation of detailed local observations. However, even with dedicated observations and initialization, uncertainties remain in both initial conditions and mesoscale forcings. The goal of the research presented here is to address the sensitivity of COBEL-ISBA forecast to initial conditions and mesoscale forcings during the winter season 2002–2003. The main sources of uncertainty of COBEL-ISBA input parameters have been estimated and the evaluation of parameter uncertainty on the forecasts has been studied. A budget strategy is applied during the winter season to quantify COBEL-ISBA sensitivity. This study is the first step toward building a local ensemble prediction system based on COBEL-ISBA. The conclusions of this work point out the potential for COBEL-ISBA ensemble forecasting and quantify sources of uncertainty that lead to dispersion.     

Continuous Multi‐probe Measurements in Fastflowing Waters Using a Hydrographic Slot

Taking continuous spatiotemporal in situ measurements with multi‐probes in fast‐flowing waters/rivers can be problematic because the sensors may be damaged by high shear forces and flotsam. To protect the multi‐probe and to enable easy access for the maintenance and calibration of the sensors, a special multi‐probe holder fixed in a hydrographic slot was developed. The validation of the probe system revealed a “memory effect” at short time scales (< 10 s) within sharp gradients caused by the overflow container of the multi‐probe rack keeping the sensors submerged in the sample water. Continuously recorded data (conductivity, temperature, pH, oxygen concentration and saturation, as well as in vivo fluorescence of chlorophyll‐a) from a research cruise on board the RV ALBIS along the river Elbe (river km 309) and entering the river Saale are presented. This river stretch upstream of the city of Magdeburg to the mouth of the Saale tributary was found to have a complex physicochemical character, which is attributable to the long mixing process of water from the river Saale and the river Elbe.     

Quality Assessment of the Cobel-Isba Numerical Forecast System of Fog and Low Clouds

Short-term forecasting of fog is a difficult issue which can have a large societal impact. Fog appears in the surface boundary layer and is driven by the interactions between land surface and the lower layers of the atmosphere. These interactions are still not well parameterized in current operational NWP models, and a new methodology based on local observations, an adaptive assimilation scheme and a local numerical model is tested. The proposed numerical forecast method of foggy conditions has been run during three years at Paris-CdG international airport. This test over a long-time period allows an in-depth evaluation of the forecast quality. This study demonstrates that detailed 1-D models, including detailed physical parameterizations and high vertical resolution, can reasonably represent the major features of the life cycle of fog (onset, development and dissipation) up to +6 h. The error on the forecast onset and burn-off time is typically 1 h. The major weakness of the methodology is related to the evolution of low clouds (stratus lowering). Even if the occurrence of fog is well forecasted, the value of the horizontal visibility is only crudely forecasted. Improvements in the microphysical parameterization and in the translation algorithm converting NWP prognostic variables into a corresponding horizontal visibility seems necessary to accurately forecast the value of the visibility.     

An Experimental High-Resolution Forecast System During the Vancouver 2010 Winter Olympic and Paralympic Games

Environment Canada ran an experimental numerical weather prediction (NWP) system during the Vancouver 2010 Winter Olympic and Paralympic Games, consisting of nested high-resolution (down to 1-km horizontal grid-spacing) configurations of the GEM–LAM model, with improved geophysical fields, cloud microphysics and radiative transfer schemes, and several new diagnostic products such as density of falling snow, visibility, and peak wind gust strength. The performance of this experimental NWP system has been evaluated in these winter conditions over complex terrain using the enhanced mesoscale observing network in place during the Olympics. As compared to the forecasts from the operational regional 15-km GEM model, objective verification generally indicated significant added value of the higher-resolution models for near-surface meteorological variables (wind speed, air temperature, and dewpoint temperature) with the 1-km model providing the best forecast accuracy. Appreciable errors were noted in all models for the forecasts of wind direction and humidity near the surface. Subjective assessment of several cases also indicated that the experimental Olympic system was skillful at forecasting meteorological phenomena at high-resolution, both spatially and temporally, and provided enhanced guidance to the Olympic forecasters in terms of better timing of precipitation phase change, squall line passage, wind flow channeling, and visibility reduction due to fog and snow.     

Using Natural Stable Hydrogen and Oxygen Isotopes for Studying the Conditions of Ground Ice Formation

The isotopic composition of ground ice in lacustrine deposits of different age in the Taimyr Peninsula is discussed. It is shown that the combined use of two isotopic indicators (²H and ¹⁸O) provides additional information (unavailable when any of the isotopes is used alone) about the conditions of formation of segregated ground ice.     

A Review of some Recent Radiation Fog Prediction Studies and the Results of Integrating a Simple Numerical Model to Predict Radiation Fog over Brunei

— Several radiation fog studies with emphasis on numerical simulation and prediction are reviewed. One of the earliest attempts started with a given surface diurnal variation of temperature and water vapor, and concluded by forecasting the onset of saturation at various levels; thus fog, by examining the spread of temperature and moisture in the vertical. The one-dimensional (1-D) models are still popular. Some of the recent numerical simulations use more than 100 levels in the vertical and treat various kinds of vegetation, aerosols, and soils with moisture contents. Some also employ a mesoscale model in conjunction with a 1-D model to consider the advective effects. In the following a simple 1-D numerical model was used to predict the onset of fog at Brunei, based on a desktop computer and routine surface observations of dry bulb temperature (T), dewpoint temperature (T _d ), and wind speed at 1800 Local Time (LT). Optimism exists in improved predictions of fog and stratus as 1-D models incorporate many physical processes, and mesoscale models continue to improve in predicting advection and cloud cover.     

氡,汞测量用于断裂活动性和分段的研究

作者首先给出海原活动断裂带从边沟至硝口的３条较长次级剪切断层，干盐池拉分盆地和边沟推挤构造区内的断层，以及尾端挤压构造区内的六盘山东麓逆断层的气氡，气汞浓度测量结果，然后分析了断层气浓度与断层活动性之间的关系，研究结果表明，测试条件大体一致的基础上，气氡，气汞浓度与断层活动性之间有着明显的对应关系，从而证明了断层气测量方法对于活断层分段和活动性研究是一种有效的手段。     

Analysis of Fog Probability from a Combination of Satellite and Ground Observation Data

The Cloud Type product, developed by the Satellite Application Facility to support to nowcasting and very short-range forecasting (SAFNWC) of EUMETSAT and based on Météosat-8/SEVIRI, identifies cloud categories, and especially low and very low clouds which are first estimates of areas where fog is likely to occur. This cloud type is combined with precipitation information from radar data and with hourly diagnostic analyses of 2-metre relative humidity and 10-metre wind to elaborate an hourly analysis of fog probability. This analysis provides four levels of fog probability with a 3-kilometre horizontal resolution: No risk, low-level risk, medium-level risk and high-level risk. An evaluation of such fog probability analyses versus a one-year set of French hourly SYNOP reports shows encouraging results (potential of detection = 0.73 for low and medium and high-level risks), even if false alarm ratios remain high. Most of the non-detections occur at twilight and are due to satellite non-detections. Eventually, we show case studies that clearly illustrate the high potential of the method.