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Snowfall is one of the primary drivers of the global cryosphere and is declining in many regions of the world with widespread hydrological and ecological consequences. Previous studies have shown that the probability of snowfall occurrence is well described by wet-bulb temperatures below 1°C (1.1°C) over land (ocean). Using this relationship, wet-bulb temperatures from three reanalysis products as well as multisatellite and reanalysis precipitation data are analyzed from 1979 to 2017 to study changes in potential snowfall areas, snowfall-to-rainfall transition latitude, snowfall amount, and snowfall-to-precipitation ratio (SPR). Results are presented at hemispheric scales, as well as for three Köppen–Geiger climate classes and four major mountainous regions including the Alps, the western United States, High Mountain Asia (HMA), and the Andes. In all reanalysis products, while changes in the wet-bulb temperature over the Southern Hemisphere are mostly insignificant, significant positive trends are observed over the Northern Hemisphere (NH). Significant reductions are observed in annual-mean potential snowfall areas over NH land (ocean) by 0.52 (0.34) million km2 decade−1 due to an increase of 0.34°C (0.35°C) decade−1 in wet-bulb temperature. The fastest retreat in NH transition latitudes is observed over Europe and central Asia at 0.7° and 0.45° decade−1. Among mountainous regions, the largest decline in potential snowfall areas is observed over the Alps at 3.64% decade−1 followed by the western United States at 2.81% and HMA at 1.85% decade−1. This maximum decrease over the Alps is associated with significant reductions in annual snowfall of 20 mm decade−1 and SPR of 2% decade−1. [ABSTRACT FROM AUTHOR]

Retrievals of falling snow from space-based observations represent key inputs for understanding and linking Earth's atmospheric, hydrological, and energy cycles. This work quantifies and investigates causes of differences among the first stable falling snow retrieval products from the Global Precipitation Measurement (GPM) Core Observatory satellite and CloudSat's Cloud Profiling Radar (CPR) falling snow product. An important part of this analysis details the challenges associated with comparing the various GPM and CloudSat snow estimates arising from different snow–rain classification methods, orbits, resolutions, sampling, instrument specifications, and algorithm assumptions. After equalizing snow–rain classification methodologies and limiting latitudinal extent, CPR observes nearly 10 (3) times the occurrence (accumulation) of falling snow as GPM's Dual-Frequency Precipitation Radar (DPR). The occurrence disparity is substantially reduced if CloudSat pixels are averaged to simulate DPR radar pixels and CPR observations are truncated below the 8-dBZ reflectivity threshold. However, even though the truncated CPR- and DPR-based data have similar falling snow occurrences, average snowfall rate from the truncated CPR record remains significantly higher (43%) than the DPR, indicating that retrieval assumptions (microphysics and snow scattering properties) are quite different. Diagnostic reflectivity (Z)–snow rate (S) relationships were therefore developed at Ku and W band using the same snow scattering properties and particle size distributions in a final effort to minimize algorithm differences. CPR–DPR snowfall amount differences were reduced to ~16% after adopting this diagnostic Z–S approach. [ABSTRACT FROM AUTHOR]

This paper describes an observational study for the geometrical properties of hydrometeors during a refreezing process initiated by a winter storm in the northern Kanto Plain, Japan, on 29 January 2016, in which a subfreezing layer developed below a melting layer. The observations by using dual-polarization radar showed consistency between high values of differential reflectivity ZDR signals in midair and ice-pellet reports at the surface. The high ZDR was indicative of the sideways-oriented particles with a small axis ratio. The low ZDR signals in midair corresponded with the reports of rain or rain/ice-pellet mixtures. Observations by using a two-dimensional video disdrometer (2DVD) near the ground showed different microphysics corresponding to high ZDR and low ZDR periods. The high ZDR periods of 2DVD observations indicated that the hydrometeors exhibited dual modes of fall velocities, namely, fast-falling and slow-falling modes. The fast-falling particles were found to be deformed ice pellets with long sideways orientations that contributed to the high ZDR. The slow-falling particles were also deformed ice pellets but with a variety of orientations. This feature was rather close to that of general dry conditions of ice particles in the atmosphere. Meanwhile, the low ZDR periods of 2DVD observations indicated that the hydrometeors exhibited a single mode of fall velocity close to the terminal velocity of raindrops, but with a more spherical shape compared to raindrops. Hence, it is suggested that the high ZDR signal occurs during freezing between the initial stage of spherical ice forming and completely freezing stage of ice pellets with a variety of orientations. [ABSTRACT FROM AUTHOR]

Analytical solutions are derived for the steady-state size distributions of precipitating rain and snow particles assuming growth via collection of suspended cloud particles. Application of the Liouville equation to the transfer of precipitating mass through size bins in a "cascade" yields a characteristic gamma distribution with a Marshall–Palmer exponential tail with respect to particle diameter. For rain, the principle parameters controlling size distribution shape are cloud droplet liquid water path and cloud updraft speed. Stronger updrafts lead to greater concentrations of large precipitating drops and a peak in the size distribution. The solutions provide a means for relating size distributions measured in the air or on the ground to cloud bulk microphysical and dynamic properties. [ABSTRACT FROM AUTHOR]

Bulk microphysics parameterizations that are used to represent clouds and precipitation usually allow only solid and liquid hydrometeors. Predicting the bulk liquid fraction on ice allows an explicit representation of mixed-phase particles and various precipitation types, such as wet snow and ice pellets. In this paper, an approach for the representation of the bulk liquid fraction into the predicted particle properties (P3) microphysics scheme is proposed and described. Solid-phase microphysical processes, such as melting and sublimation, have been modified to account for the liquid component. New processes, such as refreezing and condensation of the liquid portion of mixed-phase particles, have been added to the parameterization. Idealized simulations using a one-dimensional framework illustrate the overall behavior of the modified scheme. The proposed approach compares well to a Lagrangian benchmark model. Temperatures required for populations of ice crystals to melt completely also agree well with previous studies. The new processes of refreezing and condensation impact both the surface precipitation type and feedback between the temperature and the phase changes. Overall, prediction of the bulk liquid fraction allows an explicit description of new precipitation types, such as wet snow and ice pellets, and improves the representation of hydrometeor properties when the temperature is near 0°C. [ABSTRACT FROM AUTHOR]

Precipitation over the Arctic Ocean has a significant impact on the basin-scale freshwater and energy budgets but is one of the most poorly constrained variables in atmospheric reanalyses. Precipitation controls the snow cover on sea ice, which impedes the exchange of energy between the ocean and atmosphere, inhibiting sea ice growth. Thus, accurate precipitation amounts are needed to inform sea ice modeling, especially for the production of thickness estimates from satellite altimetry freeboard data. However, obtaining a quantitative estimate of the precipitation distribution in the Arctic is notoriously difficult because of a number of factors, including a lack of reliable, long-term in situ observations; difficulties in remote sensing over sea ice; and model biases in temperature and moisture fields and associated uncertainty of modeled cloud microphysical processes in the polar regions. Here, we compare precipitation estimates over the Arctic Ocean from eight widely used atmospheric reanalyses over the period 2000–16 (nominally the "new Arctic"). We find that the magnitude, frequency, and phase of precipitation vary drastically, although interannual variability is similar. Reanalysis-derived precipitation does not increase with time as expected; however, an increasing trend of higher fractions of liquid precipitation (rainfall) is found. When compared with drifting ice mass balance buoys, three reanalyses (ERA-Interim, MERRA, and NCEP R2) produce realistic magnitudes and temporal agreement with observed precipitation events, while two products [MERRA, version 2 (MERRA-2), and CFSR] show large, implausible magnitudes in precipitation events. All the reanalyses tend to produce overly frequent Arctic precipitation. Future work needs to be undertaken to determine the specific factors in reanalyses that contribute to these discrepancies in the new Arctic. [ABSTRACT FROM AUTHOR]

A real-time, hourly updated, online graphical data product that displays the depth and strength of easterly gap flow in the Columbia River Gorge using a 915-MHz Doppler wind profiler is presented. During precipitation events, this data product also displays observed precipitation accumulation and diagnosed precipitation type using measurements provided by a collocated heated tipping-bucket rain gauge, an optical disdrometer, and temperature and relative humidity sensors. Automated algorithms that determine the existence and depth of the gap flow, as well as precipitation type, are described. The Columbia River Gorge is the only major gap in the Cascade Mountains of Oregon and Washington. Consequently, both easterly and westerly directed gap-flow events are common in this region. Especially during late autumn and winter, easterly gap flow can cause hazardous and damaging weather (e.g., snow, freezing rain, and strong winds) in the Portland, Oregon–Vancouver, Washington metropolitan area. The product described here was developed to help forecasters at the Portland National Weather Service Forecast Office monitor cool-season easterly gap-flow events in order to provide situational awareness and guide warnings to the public about potential weather-related hazards. [ABSTRACT FROM AUTHOR]

The medium-range ensemble (ENS) from the European Centre for Medium-Range Weather Forecasts (ECMWF) Integrated Forecasting System (IFS) is used to create two new products intended to face the challenges of winter precipitation-type forecasting. The products themselves are a map product that represents which precipitation type is most likely whenever the probability of precipitation is.50% (also including information on lower probability outcomes) and a meteogram product, showing the temporal evolution of the instantaneous precipitation-type probabilities for a specific location, classified into three categories of precipitation rate. A minimum precipitation rate is also used to distinguish dry from precipitating conditions, setting this value according to type, in order to try to enforce a zero frequency bias for all precipitation types. The new products differ from other ECMWF products in three important respects: first, the input variable is discretized, rather than continuous; second, the postprocessing increases the output information content; and, third, the map-based product condenses information into a more accessible format. The verification of both products was developed using four months' worth of 3-hourly observations of present weather from manual surface synoptic observation (SYNOPs) in Europe during the 2016/17 winter period. This verification shows that the IFS is highly skillful when forecasting rain and snow, but only moderately skillful for freezing rain and rain and snow mixed, while the ability to predict the occurrence of ice pellets is negligible. Typical outputs are also illustrated via a freezing-rain case study, showing interesting changes with lead time. [ABSTRACT FROM AUTHOR]

In the Pyrenees, freezing precipitation at high elevations is quite frequent in winter, leading to the formation of an ice layer on the surface of the snowpack. It may cause many accidents amongst mountaineers and skiers, with sometimes more fatalities per winter than avalanches. Such events are not predicted by current operational systems for snow and avalanche hazard forecasting. A crowd-sourced database of surface ice layer occurrences was first built up, using reports from Internet mountaineering and ski-touring communities, to mitigate the lack of observations from conventional observation networks. Simple diagnostics of freezing precipitation were then developed, based on the cloud water content and 2-m temperature forecast by the Numerical Weather Prediction model AROME, operating at 2.5-km resolution. An evaluation over five winters gave a probability of detection reaching 81% and a false alarm ratio of 23% compared to occurrences reported in the observation database. A new modelling of ice formation on the surface of the snowpack due to impinging supercooled water was added to the detailed snowpack model Crocus. It was combined with the atmospheric diagnostic of freezing precipitation. Resulting snowpack simulations over five winters captured the formation of the main observed ice layers. The performance of the diagnostic associated with the ice formation modelling was assessed for the event of 5–6 January 2012, with altitudinal and spatial distributions of the ice layer matching the observations. These simple methods enable to forecast the occurrence of surface ice layer formations and to simulate their evolution within the snowpack, even if an accurate estimation of the amount of freezing precipitation remains the main challenge. [ABSTRACT FROM AUTHOR]

Accurate prediction of mixed-phase precipitation remains challenging for numerical weather prediction models even at high resolution and with a sophisticated explicit microphysics scheme and diagnostic algorithm to designate the surface precipitation type. Since mixed-phase winter weather precipitation can damage infrastructure and produce significant disruptions to air and road travel, incorrect surface precipitation phase forecasts can have major consequences for local and statewide decision-makers as well as the general public. Building upon earlier work, this study examines the High-Resolution Rapid Refresh (HRRR) model’s ability to forecast the surface precipitation phase, with a particular focus on model-predicted vertical temperature profiles associated with mixed-phase precipitation, using upper-air sounding observations as well as the Automated Surface Observing Systems (ASOS) and Meteorological Phenomena Identification Near the Ground (mPING) observations. The analyses concentrate on regions of mixed-phase precipitation from two winter season events. The results show that when both the observational and model data indicated mixed-phase precipitation at the surface, the model represents the observed temperature profile well. Overall, cases where the model predicted rain but the observations indicated mixed-phase precipitation generally show a model surface temperature bias of <2°C and a vertical temperature profile similar to the sounding observations. However, the surface temperature bias was ~4°C in weather systems involving cold-air damming in the eastern United States, resulting in an incorrect surface precipitation phase or the duration (areal coverage) of freezing rain being much shorter (smaller) than the observation. Cases with predicted snow in regions of observed mixed-phase precipitation present subtle difference in the elevated layer with temperatures near 0°C and the near-surface layer. [ABSTRACT FROM AUTHOR]

The Rapid Refresh (RAP) and High-Resolution Rapid Refresh (HRRR), both operational at NOAA's National Centers for Environmental Prediction (NCEP) use the Thompson et al. mixed-phase bulk cloud microphysics scheme. This scheme permits predicted surface precipitation to simultaneously consist of rain, snow, and graupel at the same location under certain conditions. Here, the explicit precipitation-type diagnostic method is described as used in conjunction with the Thompson et al. scheme in the RAP and HRRR models. The postprocessing logic combines the explicitly predicted multispecies hydrometeor data and other information from the model forecasts to produce fields of surface precipitation type that distinguish between rain and freezing rain, and to also portray areas of mixed precipitation. This explicit precipitation-type diagnostic method is used with the NOAA operational RAP and HRRR models. Verification from two winter seasons from 2013 to 2015 is provided against METAR surface observations. An example of this product from a January 2015 south-central United States winter storm is also shown. [ABSTRACT FROM AUTHOR]

Five implicit precipitation-type algorithms are assessed using observed and model-forecast sounding data in order to measure their accuracy and to gauge the effects of model uncertainty on algorithm performance. When applied to observed soundings, all algorithms provide very reliable guidance on snow and rain (SN and RA). However, their skills for ice pellets and freezing rain (IP and FZRA) are comparatively low. Most misclassifications of IP are for FZRA and vice versa. Deeper investigation reveals that no method used in any of the algorithms to differentiate between IP and FZRA allows for clear discrimination between the two forms. The effects of model uncertainty are also considered. For SN and RA, these effects are minimal and each algorithm performs reliably. Conversely, IP and FZRA are strongly impacted. When the range of uncertainty is fully accounted for, their resulting wet-bulb temperature profiles are nearly indistinguishable, leading to very poor skill for all algorithms. Although currently available data do not allow for a thorough investigation, comparison of the statistics from only those soundings that are associated with long-duration, horizontally uniform regions of FZRA shows there are significant differences between these profiles and those that are from more transient, highly variable environments. Hence, a five-category (SN, RA, IP, FZRA, and IP-FZRA mix) approach is advocated to differentiate between sustained regions of horizontally uniform FZRA (or IP) from more mixed environments. [ABSTRACT FROM AUTHOR]

The purpose of this study is to demonstrate the use of polarimetric observations in a radar-based winter hydrometeor classification algorithm. This is accomplished by deriving bulk electromagnetic scattering properties of stratiform, cold-season rain, freezing rain, sleet, dry aggregated snowflakes, dendritic snow crystals, and platelike snow crystals at X-, C-, and S-band wavelengths based on microphysical theory and previous observational studies. These results are then used to define the expected value ranges, or membership beta functions, of a simple fuzzy-logic hydrometeor classification algorithm. To test the algorithm's validity and robustness, polarimetric radar data and algorithm output from four unique winter storms are investigated alongside surface observations and thermodynamic soundings. This analysis supports that the algorithm is able to realistically discern regions dominated by wet snow, aggregates, plates, dendrites, and other small ice crystals based solely on polarimetric data, with guidance from a melting-level detection algorithm but without external temperature information. Temperature is still used to distinguish rain from freezing rain or sleet below the radar-detected melting level. After appropriate data quality control, little modification of the algorithm was required to produce physically reasonable results on four different radar platforms at X, C, and S bands. However, classification seemed more robust at shorter wavelengths because the specific differential phase is heavily weighted in ice crystal classification decisions. It is suggested that parts, or all, of this algorithm could be applicable in both operational and research settings. [ABSTRACT FROM AUTHOR]

On the basis of simulations and observations made with polarimetric radars operating at X, C, and S bands, the backscatter differential phase δ has been explored; δ has been identified as an important polarimetric variable that should not be ignored in precipitation estimations that are based on specific differential phase KDP, especially at shorter radar wavelengths. Moreover, δ bears important information about the dominant size of raindrops and wet snowflakes in the melting layer. New methods for estimating δ in rain and in the melting layer are suggested. The method for estimating δ in rain is based on a modified version of the 'ZPHI' algorithm and provides reasonably robust estimates of δ and KDP in pure rain except in regions where the total measured differential phase ΦDP behaves erratically, such as areas affected by nonuniform beam filling or low signal-to-noise ratio. The method for estimating δ in the melting layer results in reliable estimates of δ in stratiform precipitation and requires azimuthal averaging of radial profiles of ΦDP at high antenna elevations. Comparisons with large disdrometer datasets collected in Oklahoma and Germany confirm a strong interdependence between δ and differential reflectivity ZDR. Because δ is immune to attenuation, partial beam blockage, and radar miscalibration, the strong correlation between ZDR and δ is of interest for quantitative precipitation estimation: δ and ZDR are differently affected by the particle size distribution (PSD) and thus may complement each other for PSD moment estimation. Furthermore, the magnitude of δ can be utilized as an important calibration parameter for improving microphysical models of the melting layer. [ABSTRACT FROM AUTHOR]

The hourly updating High-Resolution Rapid Refresh (HRRR) model is evaluated with regard to its ability to predict the areal extent of cold-season precipitation and accurately depict the timing and location of regions of snow, rain, and mixed-phase precipitation on the ground. Validation of the HRRR forecasts is performed using observations collected by the Automated Surface Observing System (ASOS) stations across the eastern two-thirds of the United States during the 2010-11 cold season. The results show that the HRRR is able to reliably forecast precipitation extent during the cold season. In particular, the location and areal extent of both snow and rain are very well predicted. Depiction of rain-to-snow transitions and freezing rain is reasonably good; however, the associated evaluation scores are significantly lower than for either snow or rain. The analyses suggest the skill in accurately depicting precipitation extent and phase (i.e., rain, snow, and mixed phase) depends on the size and organization of a weather system. Typically, larger synoptically forced weather systems are better predicted than smaller weather systems, including the associated rain-to-snow transition or freezing-rain areas. Offsets in space or time (i.e., causing misses and false alarms) have a larger effect on the model performance for smaller weather systems. [ABSTRACT FROM AUTHOR]

Historical and proxy records document that there is a substantial asynchronous development in temperature, precipitation and glacier variations between European regions during the last few centuries. The causes of these temporal anomalies are yet poorly understood. Hence, highly resolved glacier reconstructions based on historical evidence can give valuable insights into past climate, but they exist only for few glaciers worldwide. Here, we present a new reconstruction of length changes for the Glacier des Bossons (Mont Blanc massif, France), based on unevaluated historical material. More than 250 pictorial documents (drawings, paintings, prints, photographs, maps) as well as written accounts have been critically analysed, leading to a revised picture of the glacier's history, especially from the mid-eighteenth century up to the 1860s. Very important are the drawings by Jean-Antoine Linck, Samuel Birmann and Eugène Viollet-le Duc, which depict meticulously the glacier's extent during the vast advance and subsequent retreat during the nineteenth century. The new glacier reconstruction extends back to AD 1580 and proves maxima of the Glacier des Bossons around 1610/1643, 1685, 1712, 1777, 1818, 1854, 1892, 1921, 1941, and 1983. The Little Ice Age maximum extent was reached in 1818. Until the present, the glacier has lost about 1.5 km in length, and it is now shorter than at any time during the reconstruction period. The Glacier des Bossons reacts faster than the nearby Mer de Glace (glacier reconstruction back to AD 1570 available). The Mont Blanc area is, together with the valley of Grindelwald in the Swiss Alps (two historical glacier reconstructions available back to AD 1535, and 1590, respectively), among the two regions that are probably best-documented in the world regarding historical glacier data. [ABSTRACT FROM AUTHOR]

The article presents an analysis and simulation with statistical downscaling methods of snow trends in Northern Spain. It examines various topics such as the annual snow frequency measure as the annual number of snow days and precipitation occurrence and the simulation of the observed trends utilizing the connection of daily snow occurrence (DSO). Result shows that the downscaling method with typical values of hit and false alarm rates has predicted that the DSO is around 60% and 2%.

Atmospheric flow over Iceland has been simulated for the period January 1961 to July 2006, using the mesoscale MM5 model driven by initial and boundary data from the ECMWF. A systematic comparison of results to observed precipitation has been carried out. Undercatchment of solid precipitation is dealt with by looking only at days when precipitation is presumably liquid or by considering the occurrence and non-occurrence of precipitation. Away from non-resolved orography, the long term means (months, years) of observed and simulated precipitation are often in reasonable agreement. This is partly due to a compensation of the errors on a shorter timescale (days). The probability of false alarms (the model predicts precipitation, but none is observed) is highest in N Iceland, particularly during winter. The probability of missing precipitation events (precipitation observed but none is predicted by the model) is highest in the summer and on the lee side of Iceland in southerly flows. [ABSTRACT FROM AUTHOR]

The phase of precipitation formed within the atmosphere is highly dependent on the vertical temperature profile through which it falls. In particular, several precipitation types can form in an environment with a melting layer aloft and a refreezing layer below. These precipitation types include freezing rain, ice pellets, wet snow, and slush. To examine the formation of such precipitation, a bulk microphysics scheme was used to compare the characteristics of the hydrometeors produced by the model and observed by a research aircraft flight during the 1998 ice storm near Montreal, Canada. The model reproduced several of the observed key precipitation characteristics. Sensitivity tests on the precipitation types formed during the ice storm were also performed. These tests utilized temperature profiles produced by the North American Regional Reanalysis. The results show that small variations (±0.5°C) in the temperature profiles as well as in the precipitation rate can have major impacts on the types of precipitation formed at the surface. These results impose strong requirements on the accuracy needed by prediction models. [ABSTRACT FROM AUTHOR]

Global climate models predict that terrestrial northern high-latitude snow conditions will change substantially over the twenty-first century. Results from a Community Climate System Model simulation of twentieth and twenty-first (SRES A1B scenario) century climate show increased winter snowfall (+10–40%), altered maximum snow depth (−5 ± 6 cm), and a shortened snow-season (−14 ± 7 days in spring, +20 ± 9 days in autumn). By conducting a series of prescribed snow experiments with the Community Land Model, we isolate how trends in snowfall, snow depth, and snow-season length affect soil temperature trends. Increasing snowfall, by countering the snowpack-shallowing influence of warmer winters and shorter snow seasons, is effectively a soil warming agent, accounting for 10–30% of total soil warming at 1 m depth and ~16% of the simulated twenty-first century decline in near-surface permafrost extent. A shortening snow season enhances soil warming due to increased solar absorption whereas a shallowing snowpack mitigates soil warming due to weaker winter insulation from cold atmospheric air. Snowpack deepening has comparatively less impact due to saturation of snow insulative capacity at deeper snow depths. Snow depth and snow-season length trends tend to be positively related, but their effects on soil temperature are opposing. Consequently, on the century timescale the net change in snow state can either amplify or mitigate soil warming. Snow state changes explain less than 25% of total soil temperature change by 2100. However, for the latter half of twentieth century, snow state variations account for as much as 50–100% of total soil temperature variations. [ABSTRACT FROM AUTHOR]

Several types of precipitation, such as freezing rain, ice pellets, and wet snow, are commonly observed during winter storms. The objective of this study is to better understand the formation of these winter precipitation types. To address this issue, detailed melting and refreezing of precipitation was added onto an existing bulk microphysics scheme. These modifications allow the formation of mixed-phase particles and these particles in turn lead to, or affect, the formation of many of the other types of precipitation. The precipitation type characteristics, such as the mass content, liquid fraction, and threshold diameters formed during a storm over St John’s, Newfoundland, Canada, are studied and compared with observations. Many of these features were reproduced by the model. Sensitivity experiments with the model were carried out to examine the dependence of precipitation characteristics in this event on thresholds of particle evolution in the new parameterization. [ABSTRACT FROM AUTHOR]

How land cover differences affect runoff and sediment and their relationship with precipitation are largely unknown on the Qinghai–Tibet Plateau. This study was designed to examine precipitation-runoff processes using the runoff observation plots on the 30° slope surfaces. Three plots were selected with vegetative cover average of 30, 68, and 93%. Our results show that runoff with 30% land coverage is larger than those with 68 and 93%, under the same precipitation form and amount in an alpine meadow. The mean sediment per precipitation event is two to four times greater in an area with 30% vegetative cover compared with those in 68 and 93% vegetative cover. Both runoff and mean sediment yields increased with vegetative cover from 30 to 68 and 93%. The precipitation form also affects the runoff and sediment yield. Comparing sleet and rainfall, the runoff yield resulted from melted snow is maximal, but the sediment yield is minimal. Based on the runoff yields of precipitation, the runoff coefficients on a sloping surface of 30° with vegetative cover of 30, 68, and 93% are 5.3, 2.5, and 1.9%, respectively. Quadratic parabolic curves better describe the relationships of runoff and sediment with precipitation on the Qinghai–Tibet Plateau. Our results suggest that vegetation is a major control on runoff and sediment production in the permafrost region. [ABSTRACT FROM AUTHOR]

The present study focuses on spatial patterns of diurnal variability in winter precipitation across the Indian subcontinent. Hourly precipitation data during the months of January and February from 1980 to 2002 were procured for 80 stations spread across the subcontinent. The methodology consisted of calculation of the first harmonics by harmonic analysis for three variables that included frequency, total amount, and intensity of precipitation events. There were substantial variations in the strength of the diurnal cycle prevailing over the subcontinent, with most of the peninsular region and eastern part of the northern Gangetic Plain showing relatively stronger diurnal cycles. The variance explained by the first harmonic was significant at the 90% confidence level for larger parts of the peninsular region and northern plains. The weakest patterns were observed in the interior of the continent over central India. The times of maximum for hourly frequency, total amount, and intensity of precipitation were predominantly during the latter half of the 24–hour period, during late evening hours to just before sunrise hours. This was due to the enhanced warm front lifting during the late night to early morning hours as a result of nighttime inversions in the warm sector. Further, along the foothills of the Himalayas, the times of maximum were observed during predawn hours just before sunrise, caused by the downslope movement of katabatic winds and their convergence with the cyclonic storms in the low-lying areas, leading to enhanced precipitation. Along the west coast, the times of maxima were also concentrated in the midnight to early-morning hours due to the convergence of inland moving seas breeze fronts with the northeast trades. [ABSTRACT FROM AUTHOR]

Receiver operating characteristic (ROC) curves have become a common analysis tool for evaluating forecast discrimination: the ability of a forecast system to distinguish between events and nonevents. As is implicit in that statement, application of the ROC curve is limited to forecasts involving only two possible outcomes, such as rain and no rain. However, many forecast scenarios exist for which there are multiple possible outcomes, such as rain, snow, and freezing rain. An extension of the ROC curve to multiclass forecast problems is explored. The full extension involves high-dimensional hypersurfaces that cannot be visualized and that present other problems. Therefore, several different approximations to the full extension are introduced using both artificial and actual forecast datasets. These approximations range from sets of simple two-class ROC curves to sets of three-dimensional ROC surfaces. No single approximation is superior for all forecast problems; thus, the specific aims in evaluating the forecast must be considered. [ABSTRACT FROM AUTHOR]

The National Operational Hydrologic Remote Sensing Center (NOHRSC) Snow Model (NSM) is an energy- and mass-balance model used by the National Oceanic and Atmospheric Administration’s National Weather Service for moderate-resolution spatially distributed snow analysis and data assimilation over the United States. The NSM was evaluated in a one-dimensional mode using meteorological and snowpit observations from five sites in Colorado collected during 2002–03. Four parameters estimated by the NSM [snow water equivalent (SWE), snow depth, average snowpack temperature, and snow surface temperature] were compared with snowpit observations and with estimates from another snow energy and mass-balance model, SNTHERM. Root-mean-squared differences (RMSDs) between snowpit SWE observations (January–June) at all sites and estimates from the NSM were about 11% (RMSD = 0.073 m) of the average maximum observed SWE from all sites of 0.694 m. SNTHERM exhibited only a slightly better agreement (RMSD = 0.066 m). During the winter and early spring period before snowpacks became isothermal at 273.15 K, both NSM and SNTHERM simulated significantly cooler average snowpack temperatures than observed (RMSD = 3 and 2 K, respectively). During this snow accumulation period estimates of SWE by both models were very similar. Differences in modeled SWE were traced to short periods (5–21 days) during isothermal conditions in early spring when the two models diverged. These events caused SWE differences that persisted throughout the ablation period and resulted in a range in melt-out times of 0.2–7.2 days between depth observations and modeled estimates. The divergence in SWE resulted from differences in snowmelt fluxes estimated by the two models, which are suggested to result from 1) liquid water fractions within a snowpack being estimated by the NSM using an internal energy method and by SNTHERM using a semiempirical temperature-based approach, and 2) SNTHERM, but not the NSM, accounting for the small liquid water fraction that coexists in equilibrium with snow when the snowpack surface is dry (<273.15 K). [ABSTRACT FROM AUTHOR]

Abstract: An extraction method for the quantitative analysis of polybrominated diphenyl ethers (PBDEs) in aqueous samples has been evaluated. The analytical methodology includes the sample filtration through glass fiber filter and subsequent extraction of dissolved phase compounds by C18 solid-phase disk extraction. Dependence of extraction efficiency on factors such as pollutant concentrations, sample volume, and stability during storage has been investigated. Mean extraction efficiencies of 97% for total PBDEs (13 tri- to heptabrominated congeners at spiking levels in the range of 15–90pg) with a RSD between 9 and 20% were achieved. Higher recoveries were observed for the more volatile PBDEs (112%) in relation to more brominated congeners (88%). The developed methodology was successfully applied to the analysis of these compounds in atmospheric deposition and snow samples from remote sites in Europe with method detection and quantitation limits in the range of 2.1–10pgL−1 for almost all congeners, which allow the determination of PBDEs in remote areas with levels in the range of low to medium pgL−1 for ΣPBDEs. [Copyright &y& Elsevier]

Images of frozen drops with pieces missing were collected on two days of airborne sampling in shallow supercooled stratiform frontal clouds in the coastal waters of Washington State. In those limited regions where ice appeared to be newly formed, ice fragments with rounded portions accounted for about 5% of the total ice particle concentrations. These results are in rough agreement with the body of literature on laboratory experiments concerning the freezing of drops in free fall that have suggested a modest, though not insignificant, role for the fragmentation of freezing drops on total ice particle concentrations when larger supercooled drops are present. [ABSTRACT FROM AUTHOR]

To explore the role of cloud microphysics in a large dataset of precipitating clouds, a 6-month dataset of satellite-derived cloud-top brightness temperatures from the longwave infrared band (channel 4) on the Geostationary Operational Environmental Satellite (GOES) is constructed over precipitation-reporting surface observation stations, producing 144 738 observations of snow, rain, freezing rain, and sleet. The distributions of cloud-top brightness temperatures were constructed for each precipitation type, as well as light, moderate, and heavy snow and rain. The light-snow distribution has a maximum at -16°C, whereas the moderate- and heavy-snow distributions have a bimodal distribution with a primary maximum around -16° to -23°C and a secondary maximum at -35° to -45°C. The light, moderate, and heavy rain, as well as the freezing rain and sleet, distributions are also bimodal with roughly the same temperature maxima, although the colder mode dominates when compared with the snow distributions. The colder of the bimodal peaks trends to lower temperatures with increasing rainfall intensity: -45°C for light rain, -47°C for moderate rain, and -50°C for heavy rain. Like the distributions for snow, the colder peak increases in amplitude relative to the warmer peak at heavier rainfall intensities. The steep slope in the snow distribution for cloud-tops warmer than -15°C is likely due to the combined effects of above-freezing cloud-top temperatures not producing snow, the activation of ice nuclei, the maximum growth rate for ice crystals at temperatures near -15°C, and ice multiplication processes from -3° to -8°C. In contrast, the rain distributions have a gentle slope toward higher cloud-top brightness temperatures (-5° to 0°C), likely due to the warm-rain process. Last, satellite-derived cloud-top brightness temperatures are compared with coincident radiosonde-derived cloud-top temperatures. Although most differences between these two are small, some are as large as ±60°C. The cause of these differences remains unclear, and several hypotheses are offered. [ABSTRACT FROM AUTHOR]

This paper presents a new, purely physical approach to simulate ice-particle scattering at microwave frequencies. Temperature-dependent ice particle size distributions measured by aircraft in midlatitude frontal systems are used to represent the distribution of precipitation-sized frozen hydrometeors above the freezing level through derived radar reflectivity–snow water content (Z–M) relationships. The discrete dipole approximation is employed to calculate optical properties of selected types of idealized nonspherical ice particles (hexagonal columns, four-arm rosettes, and six-arm rosettes). Based on those assumptions, passive microwave optical properties are calculated using radar observations from Gotland Island in the Baltic Sea. These forward-simulated brightness temperatures are compared with observed data from both the Advanced Microwave Scanning Radiometer (AMSR-E) and the Advanced Microwave Sounding Unit-B (AMSU-B). Results show that the new ice scattering/microphysics model is able to generate brightness temperatures that are consistent with AMSR and AMSU-B observations of two light-winter-precipitation cases. The overall differences among the various ice-habit results at 89 GHz are generally not that expansive, whereas the AMSU-B 150-GHz comparisons show increased sensitivity to ice-particle shapes. [ABSTRACT FROM AUTHOR]

Rain-type statistics derived from Tropical Rainfall Measuring Mission (TRMM) precipitation radar (PR) standard product show that some 70% of raining pixels in the central Tibetan Plateau summer are stratiform—a clear contradiction to the common knowledge that rain events during summer in this region are mostly convective, as a result of the strong atmospheric convective instability resulting from surface heating. In examining the vertical distribution of the stratiform rain-rate profiles, it is suspected that the TRMM PR algorithm misidentifies weak convective rain events as stratiform rain events. The possible cause for this misidentification is believed to be that the freezing level is close to the surface over the plateau, so that the ground echo may be mistakenly identified as the melting level in the PR rain classification algorithm. [ABSTRACT FROM AUTHOR]

Conditions for freezing precipitation (FP), including freezing rain (FR) and freezing drizzle (FZ) for 8 airports in Russia and 4 in the Ukraine are studied on the basis of 10 to 20-year series of surface observations, radiosonde and objective analysis data. Statistical characteristics are presented of the FP episode durations and of occurrence frequency dependences on surface air temperature, wind direction and speed and cloud base height. From the radiosonde data, it is found that the "classical mechanism" of FP generation (for which, stratification of "warm nose" type in the cloud layer is necessary) is not frequent: most of FP cases are associated with "all cold" conditions in the lower 3-km layer, that is, with negative temperatures in and below the clouds. [ABSTRACT FROM AUTHOR]

The article presents information on the forests that were damaged in the 1998 ice storms which struck Canada and destroyed most of the regions of southern Ontario in Canada and northern New England. The reason behind the occurrences of these ice storms was due to the large amount of freezing rain which was accumulated in some areas. The destruction raised several issues related to social, economic, and ecological aspects of the forests. However, certain measures were undertaken which concentrated on developing aggressive techniques to reduce future destruction.

Abstract: This work is a continuation of the previous climatological study of freezing precipitation and rime over the USSR territory [] aimed at creating an atlas of the frequency of these phenomena. This study gives considerable information about and a statistical analysis of freezing precipitation and rime events observed over the territory of the former USSR during a decade (1981–1990) and over the European territory of the USSR during two decades (1971–1990). This paper intends to draw the attention of the reader to the atlas and statistics by showing some interesting points. The authors used the data provided by the ground-based weather stations involved in the international exchange of meteorological data. The USSR network''s [Monthly Meteorological Tables, 1971–1990. Part 1, Novosibirsk-Obninsk. (in Russian).] comprising selected daily ground-based meteorological observations from more than 220 stations served as a basis for the analysis. All the types of freezing precipitation (FP) events were given as WMO Codes 56, 57, 66, 67, 24 and freezing fog (FF) deposited rime as WMO Codes 48, 49. The entire territory was divided into six major regions: the Arctic, the European part of the USSR, the Trans-Caucasus, Central Asia, Siberia, and the Far East. The frequency and distribution of events by regions versus temperature, atmospheric pressure, clouds base height, and some other meteorological parameters concerned were obtained. Climatic maps of annual mean, monthly mean, and seasonal mean occurrences of FP and FF were constructed for these regions. The study also analyzes the space–time variability of monthly mean ice-coating duration in hours for the 20-year period of 1971–1990 as observed at over 80 stations in the European part of the USSR (ET), and climatic maps of annual mean and monthly mean ice coating duration for the ET are constructed. The correlation between ice coating duration and height has been evaluated. [Copyright &y& Elsevier]

Examination of the early radar echo histories of several vigorous, cumulus clouds in northeast Colorado and northwest Kansas, with sensitive, dual-polarization radar, reveals the formation of millimeter-sized water drops at about the same time that the conventional, first precipitation echo (from ice) forms aloft. The early, positive ZDR values appear in the vicinity of the 0°C level (the radar data do not specify height accurately) and soon extend both above and below it. Positive ZDR is found within and to the upwind side of the updraft, separate from the conventional first precipitation echoes, which appear first at higher altitude, generally downwind of the updraft core, and have no significantly positive ZDR. Big, liquid drops were not expected this early in the formation of continental cumulus. The early presence of supercooled water drops larger than cloud droplets may be a significant factor in the glaciation of these clouds. The kind of early radar coverage illustrated here would be a priceless adjunct to aircraft studies of precipitation formation in cumulus. Microphysical data from aircraft must be interpreted with numerical models in order to deduce (or verify) the processes, and such models require the kind of early data illustrated here, both for initialization and verification. [ABSTRACT FROM AUTHOR]

Abstract: The extreme variability of rainfall over huge ranges of space–time scales makes direct rain gauge measurements of areal rainfall impossible; assumptions about the rainfall scaling—whether trivial (homogeneous), or multifractal (heterogeneous)—are required even for interpolation. The alternative is to use rain surrogates such as radar reflectivities or those based on visible-infra red radiances. In this paper, we argue that cloud radiances should be studied to obtain basic information about the range and type of scaling in the atmosphere. Since, rain and clouds are strongly non-linearly coupled—and since the scaling of the fields, the scale invariance of the generators/exponents is a symmetry principle—a break in the scaling in one of the fields would cause a break in the other. Using 909 images from three satellites and six sensors (visible and infra red) collectively spanning the range of scales 5000–1km, we demonstrate that power law scaling is respected to within an error of ±0.3–0.5%; that an upper bound on the deviations from the theoretical universal multifractal scaling is 1–2% per octave in scale. We also show that the outer scale of the cascade is very close to 20,000km, the largest great circle distance on the earth. Allowing for (one-parameter) subpower law (logarithmic) scaling corrections we show that universal multifractal cascades starting at this scale explain the isotropic moments (order ≤1.6) to within an error of ±0.8%. We argue that the scaling of these isotropic statistics shows that the diversity of cloud morphologies reflects differences in anisotropies which are effectively washed out by the isotropic statistical methods used. We compare and contrast existing multifractal models showing which can be used as realistic cloud and rain models. We go on to use continuous in scale, anisotropic, space–time multifractal rain and cloud simulations (including radiative transfer) to show how diverse cloud, rain and radiance morphologies can be compatible with the observed isotropic scaling statistics. Finally, we argue that these will be necessary for solving measurement problems including the use of rain gauge, radar and visible/infra red surrogate fields. [Copyright &y& Elsevier]

This study provides an assessment of changes in the occurrence frequency of four types of adverse-weather (freezing precipitation, blowing snow, fog, and low ceilings) and no-weather (i.e., no precipitation or visibility obscuration) events as observed at 15 Canadian Arctic stations of good hourly weather observations for 1953–2004. The frequency time series were subjected to a homogenization procedure prior to a logistic regression–based trend analysis. The results show that the frequency of freezing precipitation has increased almost everywhere across the Canadian Arctic since 1953. Rising air temperature in the region has probably resulted in more times that the temperature is suitable for freezing precipitation. On the contrary, the frequency of blowing snow occurrence has decreased significantly in the Canadian Arctic. The decline is most significant in spring. Changes in fog and low ceiling (LC) occurrences have similar patterns and are most (least) significant in summer (autumn). Decreases were identified for both types of events in the eastern region in all seasons. In the southwest, however, the fog frequency has increased significantly in all seasons, while the LC frequency has decreased significantly in spring and summer. The regional mean rate of change in the frequency of the four types of adverse weather was estimated to be 7%–13% per decade. The frequency of no-weather events has also decreased significantly at most of the 15 sites. The decrease is most significant and extensive in autumn. Comparison with the adverse-weather trends above indicates that the decline in no-weather occurrence (i.e., increase in weather occurrence) is not the result of an increase in blowing snow or fog occurrence; it is largely the result of the increasing frequency of freezing precipitation and, most likely, other types of precipitation as well. This is consistent with the reported increases in precipitation amount and more frequent cyclone activity in the lower Canadian Arctic. [ABSTRACT FROM AUTHOR]

For many years, spatial and temporal inhomogeneities in precipitation fields have been studied using scanning radars, cloud radars, and disdrometers, for example. Each measurement technique has its own advantages and disadvantages. Conventional profiling radars point vertically and collect data while the atmosphere advects across the field of view. Invoking Taylor’s frozen turbulence hypothesis, it is possible to construct time-history data, which are used to study the structure and dynamics of the atmosphere. In the present work, coherent radar imaging is used to estimate the true three-dimensional structure of the atmosphere within the field of view of the radar. The 915-MHz turbulent eddy profiler radar is well suited for imaging studies and was used in June 2003 to investigate the effects of turbulence on the formation of rain. The Capon adaptive algorithm was implemented for imaging and clutter rejection purposes. In the past several years, work by the authors and others has proven the Capon method to be effective in this regard and to possess minimal computational burden. A simple but robust filtering procedure is presented whereby echoes from precipitation and clear-air turbulence can be separated, facilitating the study of their interaction. By exploiting the three-dimensional views provided by this imaging radar, it is shown that boundary layer turbulence can have either a constructive or destructive effect on the formation of precipitation. Evidence is also provided that shows that this effect can be enhanced by updrafts in the wind field. [ABSTRACT FROM AUTHOR]

Inland flooding caused by heavy rainfall from landfalling tropical cyclones is a significant threat to life and property. The tropical rainfall potential (TRaP) technique, which couples satellite estimates of rain rate in tropical cyclones with track forecasts to produce a forecast of 24-h rainfall from a storm, was developed to better estimate the magnitude of this threat. This paper outlines the history of the TRaP technique, details its current algorithms, and offers examples of its use in forecasting. Part II of this paper covers verification of the technique. [ABSTRACT FROM AUTHOR]

The “current icing potential” (CIP) algorithm combines satellite, radar, surface, lightning, and pilot-report observations with model output to create a detailed three-dimensional hourly diagnosis of the potential for the existence of icing and supercooled large droplets. It uses a physically based situational approach that is derived from basic and applied cloud physics, combined with forecaster and onboard flight experience from field programs. Both fuzzy logic and decision-tree logic are applied in this context. CIP determines the locations of clouds and precipitation and then estimates the potential for the presence of supercooled liquid water and supercooled large droplets within a given airspace. First developed in the winter of 1997/98, CIP became an operational National Weather Service and Federal Aviation Administration product in 2002, providing real-time diagnoses that allow users to make route-specific decisions to avoid potentially hazardous icing. The CIP algorithm, its individual components, and the logic behind them are described. [ABSTRACT FROM AUTHOR]

The authors investigate the meteorology associated with two elongated swaths of crop damage produced by severe hailstorms that crossed North Dakota and South Dakota on 4 July and 20 July 2003. These hailswaths, which were observed in a Moderate Resolution Imaging Spectroradiometer (MODIS) Normalized Difference Vegetation Index (NDVI) image time series, each persisted for more than a month and were associated with local temperature increases, presumably owing to the enhanced Bowen ratio over dry, crop-free ground. This paper documents the creation and evolution of the convective storms that produced the hailswaths, and then presents evidence that devegetated hailswaths may impact future convective weather. Idealized numerical simulations including hailswath-like surface anomalies, as well as analogies to the extant literature, suggest that hailswaths may play a part in initiating new convective clouds, especially when the low-level winds are parallel to their long axes. Analyses of conventional operational observations also show that the 4 July hailswath may have played a part in the initiation and intensification of a convective storm on 17 July and in the temporarily deviant motion of a convective storm that crossed it on 20 July. Because devegetated hailswaths are common to the central and northern plains during the summer months, and because they have heretofore received little study, a deeper understanding of hailswaths’ impacts upon moist convection may lead to improved short-term weather prediction. [ABSTRACT FROM AUTHOR]

In western North America, snow provides crucial storage of winter precipitation, effectively transferring water from the relatively wet winter season to the typically dry summers. Manual and telemetered measurements of spring snow-pack, corroborated by a physically based hydrologic model, are examined here for climate-driven fluctuations and trends during the period of 1916–2002. Much of the mountain West has experienced declines in spring snowpack, especially since midcentury, despite increases in winter precipitation in many places. Analysis and modeling show that climatic trends are the dominant factor, not changes in land use, forest canopy, or other factors. The largest decreases have occurred where winter temperatures are mild, especially in the Cascade Mountains and northern California. In most mountain ranges, relative declines grow from minimal at ridgetop to substantial at snow line. Taken together, these results emphasize that the West's snow resources are already declining as earth's climate warms. *Joint Institute for the Study of the Atmosphere and the Ocean Contribution Number 1073 [ABSTRACT FROM AUTHOR]

A simple empirical procedure for determining freezing levels with polarimetric radar measurements is described. The algorithm takes advantage of the strong melting-layer signatures and the redundancy provided by the suite of polarimetric radar measurements—in particular, radar reflectivity, linear depolarization ratio, and cross-correlation coefficient. Freezing-level designations can be made with all volumetric scanning strategies. Application to uniform (stratiform) precipitation within 60 km of the radar and with brightband reflectivity maxima of greater than 25 dBZ suggests an accuracy of 100–200 m. [ABSTRACT FROM AUTHOR]

Intermittent atmospheric blocking-high activity in the South Tasman Sea is shown to play a key role in delivering substantial snowfall as far south as at least 75°S on the central East Antarctic Ice Sheet plateau. Typically, cyclones fail to penetrate this far (> 1000 km ) inland, and accumulation was thought to be dominated by clear-sky precipitation. In East Antarctica, the meridional cloud bands delivering tile moisture originate from as far north as 35°–40°S, find appear to preferentially pass over the East Antarctic coast in a corridor from ∼120&ddeg; to 160°E. Comparison of surface observations, model and satellite data suggests that a few such episodes contribute a significant proportion of tile (low) mean annual accumulation of the central East Antarctic Ice Sheet (e.g., an estimated 44% at Dome C over days in December 2001–January 2002) Blocking-high-related incursions also cruise abrupt increases in the surface wind speed (snow redistribution) and air temperature: this has implications lot the interpretation of ice core data. Blocking-high-related precipitation episodes can generally be detected over the ice sheet interior, via abrupt changes (of∼0.02–0.04) in polarization in 37- and 85-Gllz SSM/I data, due to the relative stability of the surface and its “background” microwave signature and the relative hick of cloud cover overall. This is not the case in high-accumulation near-coastal regions such as Law Dome, where additional information is required. Ambiguities remain due to blowing snow and hoarfrost formation. Further research is necessary to examine the frequency of occurrence and variability of midlatitude blocking-high systems, their effect on precipitation in the Antarctic Ice Sheet interior, and the potential effect of global change [ABSTRACT FROM AUTHOR]

Develops the general applicability of an isomonogram to diagnose the position of the geographic boundary between freezing precipitation and ice pellets. Tests of the isomonogram using a 25-year database; Soundings that did not conform to the profile.

Reports on simultaneous in situ photographs and shadowgraphs of precipitation particles and the linear depolarization ratio (LDR) of the three-centimeter polarimetric radar echo from one Convection & Precipitation/Electrification project (CaPE) convective storm; Observations aboard storm-penetrating aircraft; Freezing of raindrops; Effects of cloud liquid water; Effects of cloud ice.

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Copyright of Atmosphere - Ocean (Canadian Meteorological & Oceanographic Society) is the property of Canadian Meteorological & Oceanographic Society and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)