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Eulerian and Lagrangian persistence of precipitation patterns derived from continental-scale radar composite images are used as a measure of predictability and for nowcasting [the McGill algorithm for precipitation nowcasting by Lagrangian extrapolation (MAPLE)]. A previous paper introduced the method and focused on the lifetime of patterns of rainfall rates and the scale dependence of predictability. This paper shows how the method of persistence of radar precipitation patterns can be extended to produce probabilistic forecasts. For many applications, probabilistic information is at least as important as the expected point value. Four techniques are presented and compared. One is entirely new and makes use of the intrinsic relationship between scale and predictability. The results with this technique suggest potential use for downscaling of numerical model output. For the 143 h of precipitation analyzed so far, roughly a factor of 2 was obtained between lead times of Eulerian and Lagrangian techniques. Three of the four techniques involve a scale parameter. The slope of the relationship between optimum scale and lead time is about 1 and 2 km min[sup -1] for Lagrangian and Eulerian techniques, respectively. The skill scores obtained for the four techniques can be used as a measure of predictability in terms of probabilistic rainfall rates. The progress of other probabilistic forecasting methods, such as expert systems or numerical models, can be evaluated against the standard set by simple persistence. [ABSTRACT FROM AUTHOR]

This paper analyzes the long-term (1901–2002) temporal trends in the agroclimate of Alberta, Canada, and explores the spatial variations of the agroclimatic resources and the potential crop-growing area in Alberta. Nine agroclimatic parameters are investigated: May–August precipitation (PCPN), the start of growing season (SGS), the end of the growing season (EGS), the length of the growing season (LGS), the date of the last spring frost (LSF), the date of the first fall frost (FFF), the length of the frost-free period (FFP), growing degree-days (GDDs), and corn heat units (CHUs). The temporal trends in the agroclimatic parameters are analyzed by using linear regression. The significance tests of the trends are made by using Kendall’s tau method. The results support the following conclusions. 1) The Alberta PCPN has increased 14% from 1901 to 2002, and the increment is the largest in the north and the northwest of Alberta, then diminishes (or even becomes negative over two small areas) in central and southern Alberta, and finally becomes large again in the southeast corner of the province. 2) No significant long-term trends are found for the SGS, EGS, and LGS. 3) An earlier LSF, a later FFF, and a longer FFP are obvious all over the province. 4) The area with sufficient CHU for corn production, calculated according to the 1973–2002 normal, has extended to the north by about 200–300 km, when compared with the 1913–32 normal, and by about 50–100 km, when compared with the 1943–72 normal; this expansion implies that the potential exists to grow crops and raise livestock in more regions of Alberta than was possible in the past. The annual total precipitation follows a similar increasing trend to that of the May–August precipitation, and the percentile analysis of precipitation attributes the increase to low-intensity events. The changes of the agroclimatic parameters imply that Alberta agriculture has benefited from the last century’s climate change. [ABSTRACT FROM AUTHOR]

Filtering of nonpredictable scales of precipitation can be used to improve forecast precision (rms). Previous papers have studied the scale dependence of predictability of patterns of instantaneous rainfall rate and of probabilistic forecasts. In this paper, motivated by the often localized, intermittent nature of rainfall, the wavelet transform is used to develop measures of predictability at each scale. These measures are then used to design optimal forecast filters. This method is applied to radar composites of rainfall reflectivity over much of the continental United States and is developed to be appropriate for operational forecasts of rainfall rates and raining areas. For the four precipitation events studied, the average correlation at 4-h lead time was increased from 0.50 for the original nowcasts to 0.62 with forecast filtering. This forecast filtering is incorporated into the McGill Algorithm for Precipitation Nowcasting by Lagrangian Extrapolation (MAPLE), which now includes variational echo tracking, a semi-Lagrangian advection scheme, scale-based filtering, and appropriate rescaling of the filtered nowcast fields. [ABSTRACT FROM AUTHOR]

Horizontal wind vector fields can be measured in real time by a bistatic Doppler radar network and can be applied directly for hazard warnings and weather surveillance. Most applications, however, especially for meteorological research and operational meteorology, require quality-controlled wind fields. Therefore, a quality-control scheme is developed that includes algorithms to determine the data quality. The algorithms are applied through a decision criterion, and the quality of wind measurement is weighted with values ranging from 1 to 0. The results of each weighting algorithm are merged to an average quality index field, which represents the confidence of each horizontal wind measurement. This averaged field is available together with the measured horizontal wind vector field for further applications. This idea is applicable for all kinds of spatial wind field measurements and is applied in the paper for horizontal wind fields measured for monostatic dual- and bistatic dual- and/or multiple-Doppler radar measurements. Wind synthesis and quality control of three-dimensional wind fields are presented for two frontal passages with stratiform precipitation and for a convective situation. [ABSTRACT FROM AUTHOR]

Determination of the scale of the interaction between precipitation and topography is important for the accurate interpolation of rainfall in mountainous areas and also provides insight into the physical processes involved. In this paper, trivariate thin-plate smoothing splines are used to investigate the scale of interaction between monthly precipitation and topography by interpolating monthly rainfall over three subregions of the Australian continent, incorporating different climatic conditions and rainfall types. The interpolations are based upon elevations derived from digital elevation models (DEMs) of various resolutions. All of the DEMs are local averages of version 2.0 of the 9-s-resolution DEM of Australia. The results suggest that the optimal scale of the interaction between precipitation and topography, as it pertains to the elevation-dependent interpolation of monthly precipitation in Australia, is between 5 and 10 km. This is in agreement with results of similar studies that addressed daily precipitation over Switzerland. [ABSTRACT FROM AUTHOR]

This study investigates the accuracy of various precipitation products for the Sahel. A first set of products is made of three ground-based precipitation estimates elaborated regionally from the gauge data collected by Centre Regional Agrometeorologie–Hydrologie–Meteorologie (AGRHYMET). The second set is made of four global products elaborated by various international data centers. The comparison between these two sets covers the period of 1986–2000. The evaluation of the entire operational network of the Sahelian countries indicates that on average the monthly estimation error for the July–September period is around 12% at a spatial scale of 2.5° × 2.5°. The estimation error increases from south to north and remains below 10% for the area south of 15°N and west of 11°E (representing 42% of the region studied). In the southern Sahel (south of 15°N), the rain gauge density needs to be at least 10 gauges per 2.5° × 2.5° grid cell for a monthly error of less than 10%. In the northern Sahel, this density increases to more than 20 gauges because of the large intermittency of rainfall. In contrast, for other continental regions outside Africa, some authors have found that only five gauges per 2.5° × 2.5° grid cell are needed to give a monthly error of less than 10%. The global products considered in this comparison are the Climate Prediction Center (CPC) merged analysis of precipitation (CMAP), Global Precipitation Climatology Project (GPCP), Global Precipitation Climatology Center (GPCC), and Geostationary Operational Environmental Satellite (GOES) precipitation index (GPI). Several methods (scatterplots, distribution comparisons, root-mean-square error, bias, Nash index, significance test for the mean, variance, and distribution function, and the standard deviation approach for the kriging interval) are first used for the intercomparison. All of these methods lead to the same conclusion that CMAP is slightly the better product overall, followed by GPCC, GPCP, and GPI, with large errors for GPI. However, based on the root-mean-square error, it is found that the regional rainfall product obtained from the synoptic network is better than the four global products. Based on the error function developed in a companion paper, an approach is proposed to take into account the uncertainty resulting from the fact that the reference values are not the real ground truth. This method was applied to the most densely sampled region in the Sahel and led to a significant decrease of the raw evaluation errors. The reevaluated error is independent of the gauge references. [ABSTRACT FROM AUTHOR]

On the basis of temporally sampled data obtained from satellites, spatial statistics of rainfall can be estimated. In this paper, the authors compare the estimated spatial statistics with their “true” or ensemble values calculated using 5 yr of 15-min radar-based rainfall data at a spatial domain of 512 km × 512 km in the central United States. The authors conducted a Monte Carlo sampling experiment to simulate different sampling scenarios for variable sampling intervals and rainfall averaging periods. The spatial statistics used are the moments of spatial distribution of rainfall, the spatial scaling exponents, and the spatial cross correlations between the sample and ensemble rainfall fields. The results demonstrated that the expected value of the relative error in the mean rain-rate estimate is zero for rainfall averaged over 5 days or longer, better temporal sampling produces average fields that are “less noisy” spatially, an increase in the sampling interval causes the sampled rainfall to be increasingly less correlated with the true rainfall map, and the spatial scaling exponent estimators could give a bias of 40% or less. The results of this study provide a basis for understanding the impact of temporal statistics on inferred spatial statistics. [ABSTRACT FROM AUTHOR]

The Tropical Rainfall Measuring Mission (TRMM) Kwajalein Experiment (KWAJEX) was designed to obtain an empirical physical characterization of precipitating convective clouds over the tropical ocean. Coordinated datasets were collected by three aircraft, one ship, five upper-air sounding sites, and a variety of continuously recording remote and in situ surface-based sensors, including scanning Doppler radars, profilers, disdrometers, and rain gauges. This paper describes the physical characterization of the Kwajalein cloud population that has emerged from analyses of datasets that were obtained during KWAJEX and combined with long-term TRMM ground validation site observations encompassing three rainy seasons. The spatial and temporal dimensions of the precipitation entities exhibit a lognormal probability distribution, as has been observed over other parts of the tropical ocean. The diurnal cycle of the convection is also generally similar to that seen over other tropical oceans. The largest precipitating cloud elements—those with rain areas exceeding 14 000 km2—have the most pronounced diurnal cycle, with a maximum frequency of occurrence before dawn; the smallest rain areas are most frequent in the afternoon. The large systems exhibited stratiform rain areas juxtaposed with convective regions. Frequency distributions of dual-Doppler radar data showed narrow versus broad spectra of divergence in the stratiform and convective regions, respectively, as expected because strong up- and downdrafts are absent in the stratiform regions. The dual-Doppler profiles consistently showed low-level convergence and upper-level divergence in convective regions and midlevel convergence sandwiched between lower- and upper-level divergence in stratiform regions. However, the magnitudes of divergence are sensitive to assumptions made in classifying the radar echoes as convective or stratiform. This sensitivity implies that heating profiles derived from satellite radar data will be sensitive to the details of the scheme used to separate convective and stratiform rain areas. Comparison of airborne passive microwave data with ground-based radar data indicates that the pattern of scattering of 85-GHz radiance by ice particles in the upper portions of KWAJEX precipitating clouds is poorly correlated with the precipitation pattern at lower levels while the emission channels (10 and 19 GHz) have brightness temperature patterns that closely correspond to the lower-level precipitation structure. In situ ice particle imagery obtained by aircraft at upper levels (∼11 km) shows that the concentrations of ice particles of all densities are greater in the upper portions of active convective rain regions and lower in the upper portions of stratiform regions, probably because the active updrafts convey the particles to upper levels, whereas in the stratiform regions sedimentation removes the larger ice particles over time. Low-level aircraft flying in the rain layer show similar total drop concentrations in and out of convective cells, but they also show a sudden jump in the concentration of larger raindrops at the boundaries of the cells, indicating a discontinuity in growth processes such as coalescence at the cell boundary. [ABSTRACT FROM AUTHOR]

Stratocumulus is one of the most common cloud types globally, with a profound effect on the earth’s radiation budget, and the drizzle process is fundamental in understanding the evolution of these boundary layer clouds. In this paper a combination of 94-GHz Doppler radar and backscatter lidar is used to investigate the microphysical properties of drizzle falling below the base of stratocumulus clouds. The ratio of the radar to lidar backscatter power is proportional to the fourth power of mean size, and so potentially it can provide an accurate size estimate. Information about the shape of the drop size distribution is then inferred from the Doppler spectral width. The algorithm estimates vertical profiles of drizzle parameters such as liquid water content, liquid water flux, and vertical air velocity, assuming that the drizzle size spectrum may be represented by a gamma distribution. The depletion time scale of cloud liquid water through the drizzle process can be estimated when the liquid water path of the cloud is available from microwave radiometers, and observations suggest that this time scale varies from a few days in light drizzle to a few hours in strong drizzle events. Radar and lidar observations from Chilbolton (in southern England) and aircraft size spectra taken during the Atlantic Stratocumulus Transition Experiment have both been used to derive the following power-law relationship between liquid water flux (LWF) (g m-2 s-1) and radar reflectivity (Z) (mm6 m-3): LWF = 0.0093Z0.69. This relation is valid for frequencies up to 94 GHz and therefore would allow a forthcoming spaceborne radar to measure liquid water flux around the globe to within a factor of 2 for values of Z above -20 dBZ. [ABSTRACT FROM AUTHOR]

This paper reports the results from a regional validation study of monthly precipitation products generated from sensor measurements aboard the Tropical Rainfall Measuring Mission (TRMM) satellite. The study analyzed 4 yr of precipitation estimates (1998–2001) produced from data collected by the TRMM Microwave Imager (TMI) and the precipitation radar (PR) and compared them with corresponding estimates computed using 5-min rain accumulations from 66 rain gauges in the Oklahoma Mesonet. The applied methodology estimated bulk climate-scale sampling and retrieval errors and biases for the TMI and PR at two areal resolutions: 1° × 1° and 2° × 5°. The approach taken in this study generated two gauge-inferred gridded estimates of monthly precipitation over the study period: 1) G[sub 0] , which was computed by performing a complete integration of the monthly gauge time series, and 2) G[sub S] , which consisted of gauge-inferred rain rates subsampled to TRMM overpasses at a gridded resolution of 1° × 1°, with monthly precipitation estimates derived from the bulk statistics collected during each month of the study. The variable G[sub S] depends on the areal swath of each sensor and so yields two sensor-dependent estimates of gauge-inferred precipitation (G[sub TMI] , G[sub PR] ). The advantage of this approach is that it allows for the separation of retrieval and sampling errors, because the subsampled gauge estimates include the temporal sampling errors associated with the satellite sampling. The overall random sampling and retrieval errors for the PR exceeded the TMI errors for the study period, but the PR showed a greater reduction in the errors when the scale was increased to 2° × 5°. Annual coefficients of variation were also generally lower for the PR than the TMI at this scale. This result was consistent with PR retrieval biases, which were positive over all 4 yr, exceeding the TMI biases in every year of the study. [ABSTRACT FROM AUTHOR]

In the Alps, the volume visible by a radar is reduced because of ground clutter, elevated horizon, and earth curvature. This often inhibits a direct view on precipitation close to the ground. When using radar measurements from aloft to estimate precipitation rates at ground level, the measurements must be corrected for the vertical change of the radar echo (the profile) caused by the growth and transformation of precipitation. In this paper a robust profile-correction scheme for operational use in complex orography is presented. The aim is to correct for the large errors related to the profile in an Alpine environment: frequent underestimation caused by the vertical decrease of the radar echo, and occasional overestimation in the bright band. The profile is determined from volumetric radar data integrated over a few hours within a 70-km range of the radar (mesobeta scale). The correction scheme is verified by comparing radar estimates to gauge measurements of 247 h of summer and winter precipitation in a highly mountainous area. During the selected period, 10 gauges collected a total of 3966 mm of water. Four concepts to estimate ground-level precipitation are compared: the vertical maximum echo, the lowest visible echo, estimates corrected with the average-event profile, and estimates corrected using the mesobeta profile. Comparisons with the ground truth show that in summer profile correction considerably reduces the bias and scatter. The root-mean-square error diminishes by a factor of 2. Thus, corrected radar images give a much better overall view of the precipitation field than uncorrected ones. In winter, the improvement is found in a very significant reduction of the bias. The algorithm is currently being implemented in the operational radar network of MeteoSwiss. Long-term verification is needed after a few years of operation. [ABSTRACT FROM AUTHOR]

Soil quality models developed for ecodistrict polygons (EDP) and the polygons of the soil landscapes of Canada (SLC) to monitor the concentration of soil organic matter require daily climate data as an important input. The objectives of this paper are (i) to provide a method that interpolates the daily station data onto the 894 SLC polygons and 150 EDP in the province of Alberta, Canada, so that the interpolated data fit not only climate mean but also climate variability, especially for the precipitation field, and hence can be used as realistic climate input to soil quality models and (ii) to understand the variability of the Alberta daily climate, such as precipitation frequency. The procedure interpolates the station data onto a dense network of grid points and then averages the gridpoint values inside polygons. The procedure and results for maximum temperature, minimum temperature, and precipitation are reported in detail. The interpolation uses the observed daily data for the period 1 January 1961-31 December 1997 (13 514 days) within the latitude-longitude box (45°-64°N, 116°-124°W). Because the precipitation field can have a short spatial correlation length scale and large variability, a hybrid of the methods of inverse-distance weight and nearest-station assignment is developed for interpolating the precipitation data. This method can reliably calculate not only the number of precipitation days per month, but also the precipitation amount for a day. The temperature field has a long spatial correlation scale, and its data are interpolated by the inverse-distance-weight method. Cross-validation shows that the interpolated results on polygons are accurate and appropriate for soil quality models. The computing algorithm uses all the daily observed climate data; despite that, some stations have a very short time record or only summer records. [ABSTRACT FROM AUTHOR]

In this paper, the impact of Doppler radar radial velocity on the prediction of a heavy rainfall event is examined. The three-dimensional variational data assimilation (3DVAR) system for use with the fifth-generation Pennsylvania State University–NCAR Mesoscale Model (MM5) is further developed to enable the assimilation of radial velocity observations. Doppler velocities from the Korean Jindo radar are assimilated into MM5 using the 3DVAR system for a heavy rainfall case that occurred on 10 June 2002. The results show that the assimilation of Doppler velocities has a positive impact on the short-range prediction of heavy rainfall. The dynamic balance between atmospheric wind and thermodynamic fields, based on the Richardson equation, is introduced to the 3DVAR system. Vertical velocity (w) increments are included in the 3DVAR system to enable the assimilation of the vertical velocity component of the Doppler radial velocity observation. The forecast of the hydrometeor variables of cloud water (qc) and rainwater (qr) is used in the 3DVAR background fields. The observation operator for Doppler radial velocity is developed and implemented within the 3DVAR system. A series of experiments, assimilating the Korean Jindo radar data for the 10 June 2002 heavy rainfall case, indicates that the scheme for Doppler velocity assimilation is stable and robust in a cycling mode making use of high-frequency radar data. The 3DVAR with assimilation of Doppler radial velocities is shown to improve the prediction of the rainband movement and intensity change. As a result, an improved skill for the short-range heavy rainfall forecast is obtained. The forecasts of other quantities, for example, winds, are also improved. Continuous assimilation with 3-h update cycles is important in producing an improved heavy rainfall forecast. Assimilation of Doppler radar radial velocities using the 3DVAR background fields from a cycling procedure produces skillful rainfall forecasts when verified against observations. [ABSTRACT FROM AUTHOR]

Part II. Presents research that develops schemes for an attenuation correction for dual-beam airborne Doppler radars commonly used in convection experiments. Procedure to retrieve the attenuation-corrected reflectivity in convective cells; Application to the February 9, 1993 dataset; Conclusions.

Presents a paper which in part, is dedicated to establishing relations among rain-integrated parameters representative of west Pacific precipitation. How this is establishing the use of airborne microphysical data collected during the Tropical Ocean and Global Atmosphere Coupled Ocean-Atmosphere Response Experiment of 1993; How these relations are used to check the reliability of a rain-profiling method applied at airborne radar-mapping radar observations.

A validation of passive microwave–adjusted rainfall analyses of tropical cyclones using spaceborne radar data is presented. This effort is part of the one-dimensional plus four-dimensional variational (1D+4D-Var) rain assimilation project that is being carried out at the European Centre for Medium-Range Weather Forecasts (ECMWF). Brightness temperatures or surface rain rates from the Tropical Rainfall Measuring Mission (TRMM) satellite are processed through a 1D-Var retrieval to derive values of total column water vapor that can be ingested into the operational ECMWF 4D-Var. As an indirect validation, the precipitation fields produced at the end of the 1D-Var minimization process are converted into equivalent radar reflectivity at the frequency of the TRMM precipitation radar (13.8 GHz) and are compared with the observations averaged at model resolution. The averaging process is validated using a sophisticated downscaling/upscaling approach that is based on wavelet decomposition. The precipitation radar measurements are ideal for this validation exercise, being approximately collocated with but completely independent of the TRMM Microwave Imager (TMI) radiometer measurements. Qualitative and statistical comparisons between radar observations and retrievals from the TMI-derived surface rain rates and from TMI radiances are made using 17 well-documented tropical cyclone occurrences between January and April of 2003. Several statistical measures, such as bias, root-mean-square error, and Heidke skill score, are introduced to assess the 1D-Var skill as well as the model background skill in producing a realistic rain distribution. Results show a good degree of skill in the retrievals, especially near the surface and for medium–heavy rain. The model background produces precipitation in the domain that is sometimes in excess with respect to the observations, and it often shows an error in the location of precipitation maxima. Differences between the two 1D-Var approaches are not large enough to make final conclusions regarding the advantages of one method over the other. Both methods are capable of redistributing the rain patterns according to the observations. It appears, however, that the brightness temperature approach is in general more effective in increasing precipitation amounts at moderate-to-high rainfall rates. [ABSTRACT FROM AUTHOR]

Accurately mapped meteorological data are an essential component for hydrologic and ecological research conducted at broad scales. A simple yet effective method for mapping daily weather conditions across heterogeneous landscapes is described and assessed. Daily weather data recorded at point locations are integrated with long-term-average climate maps to reconstruct spatially explicit estimates of daily precipitation and temperature extrema. The method uses ordinary kriging to interpolate base station data spatially into fields of approximately 2-km grain size. The fields are subsequently adjusted by 30-yr-average climate maps [Parameter-Elevation Regression on Independent Slopes Model (PRISM)], which incorporate adiabatic lapse rates, orographic effects, coastal proximity, and other environmental factors. The accuracy assessment evaluated an interpolation-only approach and the new method by comparing predicted and observed values from an independent validation dataset. The results of the accuracy assessment are compared for a 24-yr period for California. For all three weather variables, mean absolute errors (MAE) of the climate-imprint method were considerably smaller than those of the interpolation-only approach. MAE for predicted daily precipitation was ±2.5 mm, with a bias of +0.01. MAE for predicted daily minimum and maximum temperatures were ±1.7° and ±2.0°C, respectively, with corresponding biases of -0.41° and -0.38°C. MAE differed seasonally for all three weather variables, but the method was stable despite variation in the number of base stations available for each day. [ABSTRACT FROM AUTHOR]

The radar return powers from a three-frequency radar, with center frequency at 22.235 GHz and upper and lower frequencies chosen with equal water vapor absorption coefficients, can be used to estimate water vapor density and parameters of the precipitation. A linear combination of differential measurements between the center and lower frequencies on one hand and the upper and lower frequencies on the other provide an estimate of differential water vapor absorption. The coupling between the precipitation and water vapor estimates is generally weak but increases with bandwidth and the amount of non-Rayleigh scattering of the hydrometeors. The coupling leads to biases in the estimates of water vapor absorption that depend primarily on the phase state and the median mass diameter of the hydrometeors. For a down-looking radar, path-averaged estimates of water vapor absorption are possible under rain-free as well as raining conditions by using the surface returns at the three frequencies. Simulations of the water vapor attenuation retrieval show that the largest source of error typically arises from the variance in the measured radar return powers. Although the error can be mitigated by a combination of a high pulse repetition frequency, pulse compression, and averaging in range and time, the radar receiver must be stable over the averaging period. For fractional bandwidths of 20% or less, the potential exists for simultaneous measurements at the three frequencies with a single antenna and transceiver, thereby significantly reducing the cost and mass of the system. [ABSTRACT FROM AUTHOR]

Daily rainfall totals are a key input for hydrological models that are designed to simulate water and pollutant flow through both soil and waterways. Within New Zealand there are large areas and many river catchments where no long-term rainfall observations exist. A method for estimating daily rainfall over the whole of New Zealand on a 5-km grid is described and tested over a period from January 1985 to April 2002. Improvement over a spatial interpolation method was gained by scaling high-elevation rainfall estimates using simulated mesoscale model rainfall surfaces that are generated for short periods in 1994 and 1996. This method is judged to produce reasonable and useful estimates of daily rainfall. [ABSTRACT FROM AUTHOR]

Source–receptor relationships for mercury (Hg) and other trace elements wet deposited in southeastern Florida were investigated using daily event precipitation samples collected over a 1-yr period in 1995–96. Data collected in Davie, Florida, showed significantly higher (2.2 times) volume-weighted mean (VWM) Hg concentrations during the spring and summer seasons relative to winter. A meteorological tracer analysis, utilizing the ratio of trace elements lanthanum (La) to cerium (Ce), determined that “feed” air to precipitation cells arriving at the site incorporated local urban emissions more frequently during the spring and summer seasons. Using Weather Surveillance Radar-1988 Doppler (WSR-88D) data, analysis of precipitation-cell path histories for events collected at 17 sites in southeastern Florida over 1 month in the summer of 1995 showed significantly higher (2.0 times) VWM Hg concentrations in events with easterly cell paths than in those with westerly paths for storms arriving at Everglades sites. Significantly higher VWM concentrations for known anthropogenic elements vanadium (V) and nickel (Ni) (oil combustion) and lead (Pb) and antimony (Sb) (waste incineration) were also observed in events with easterly paths. In addition, events arriving from the east (offshore) that impacted the coastal sites were significantly lower in Hg (a factor of 2.6) than were events from the east that impacted the urban sites (after events moved inland over emission sources). This study demonstrates that source–receptor relationships can be established by analyzing the meteorological conditions corresponding to each precipitation event, and it supports the previous finding that local anthropogenic sources played the dominant role in the wet deposition of Hg to southern Florida and the Everglades during the study period. [ABSTRACT FROM AUTHOR]

The retrieval errors of cloud and precipitation hydrometeor contents from spaceborne observations are estimated at microwave frequencies in atmospheric windows between 18 and 150 GHz and in oxygen absorption complexes near 50–60 and 118 GHz. The method is based on a variational retrieval framework using a priori information on the cloud, atmosphere, and surface states from ECMWF short-range forecasts under different weather regimes. This approach was chosen because a consistent description of the model state and its uncertainties is provided, which is unavailable for other methods. The results show that the sounding channels provide more stable, more accurate, and less biased retrievals than window channels—in particular, over land surfaces and with regard to snowfall. Average performance estimates showed that if sounding channels are used, 80% of all retrievals are within 100% error limits and 60% of them are within 50% error limits with regard to rainfall. For snowfall, the sounding channels produce 60% of all retrievals with errors below 100% for rates smaller than 1 mm h-1, and 50%–80% of the cases have errors below 50% for more intense snowfall. [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]

Through modification of the planetary boundary layer, urbanization has the potential to have a significant impact on precipitation totals locally. Using daily summer-season precipitation data at 30 stations from 1953 to 2002, this study explores the possibility of urban effects as causes of spatial anomalies in precipitation in a zone within 180 km of Atlanta, Georgia. The time period is divided into consecutive epochs (e.g., 1953–77 and 1978–2002), and interepochal differences in precipitation totals, heavy-precipitation days, cumulative heavy precipitation, and atmospheric conditions are explored. The southern stations experienced significant decreases in precipitation, whereas significant precipitation increases occurred at central/west-central stations. The most striking increases occurred at Norcross, Georgia, which is ∼30 km northeast of downtown Atlanta; Norcross had the third smallest number of heavy-precipitation days during 1953–77, but, during 1978–2002, it had the most heavy-precipitation days. Not only did the amount of urban land cover upwind of Norcross increase substantially from the earlier to the later epochs, but regionwide dewpoint temperatures also increased significantly. Therefore, it is suspected that the increased precipitation at Norcross was caused by urban effects, and these effects may have been enhanced by increased atmospheric humidity. [ABSTRACT FROM AUTHOR]

This study provides an intensive evaluation of the Global Precipitation Climatology Project (GPCP) 1° daily (1DD) rainfall products over the Mississippi River basin, which covers 435 1° latitude × 1° longitude grids for the period of January 1997–December 2000 using radar-based precipitation estimates. The authors’ evaluation criteria include unconditional continuous, conditional (quasi) continuous, and categorical statistics, and their analyses cover annual and seasonal time periods. The authors present spatial maps that reflect the results for the 1° grids and a summary of the results for three selected regions. They also develop a statistical framework that partitions the GPCP–radar difference statistics into GPCP error and radar error statistics. They further partition the GPCP error statistics into sampling error and retrieval error statistics and estimate the sampling error statistics using a data-based resampling experiment. Highlights of the results include the following: 1) the GPCP 1DD product captures the spatial and temporal variability of rainfall to a high degree, with more than 80% of the variance explained, 2) the GPCP 1DD product proficiently detects rainy days at a large range of rainfall thresholds, and 3) in comparison with radar-based estimates the GPCP 1DD product overestimates rainfall. [ABSTRACT FROM AUTHOR]

Airborne in situ measurements of updrafts in tropical convective storms were analyzed to determine the similarities and differences between updrafts in a tropical continental and a tropical oceanic region. Two hundred fifteen updraft cores from the Tropical Rainfall Measuring Mission (TRMM) component of the Large Scale Biosphere–Atmosphere (LBA) experiment (tropical continental wet season) and 377 updraft cores from the Kwajalein Experiment (KWAJEX) (tropical oceanic) were analyzed in a similar manner to that of previous studies of tropical updrafts. Average speed, maximum speed, width, and mass flux of the updraft cores from the TRMM-LBA and KWAJEX were generally similar to each other and also were similar to results from previous studies of tropical updrafts. [ABSTRACT FROM AUTHOR]

A single-moment bulk microphysics scheme with multiple ice precipitation categories is described. It has 2 liquid hydrometeor categories (cloud droplets and rain) and 10 ice categories that are characterized by habit, size, and density—two ice crystal habits (column and plate), rimed cloud ice, snow (ice crystal aggregates), three categories of graupel with different densities and intercepts, frozen drops, small hail, and large hail. The concept of riming history is implemented for conversions among the graupel and frozen drops categories. The multiple precipitation ice categories allow a range of particle densities and fall velocities for simulating a variety of convective storms with minimal parameter tuning. The scheme is applied to two cases—an idealized continental multicell storm that demonstrates the ice precipitation process, and a small Florida maritime storm in which the warm rain process is important. [ABSTRACT FROM AUTHOR]

Reanalysis data provide an excellent test bed for impacts prediction systems, because they represent an upper limit on the skill of climate models. Indian groundnut (Arachis hypogaea L.) yields have been simulated using the General Large-Area Model (GLAM) for annual crops and the European Centre for Medium-Range Weather Forecasts (ECMWF) 40-yr reanalysis (ERA-40). The ability of ERA-40 to represent the Indian summer monsoon has been examined. The ability of GLAM, when driven with daily ERA-40 data, to model both observed yields and observed relationships between subseasonal weather and yield has been assessed. Mean yields were simulated well across much of India. Correlations between observed and modeled yields, where these are significant, are comparable to correlations between observed yields and ERA-40 rainfall. Uncertainties due to the input planting window, crop duration, and weather data have been examined. A reduction in the root-mean-square error of simulated yields was achieved by applying bias correction techniques to the precipitation. The stability of the relationship between weather and yield over time has been examined. Weather–yield correlations vary on decadal time scales, and this has direct implications for the accuracy of yield simulations. Analysis of the skewness of both detrended yields and precipitation suggest that nonclimatic factors are partly responsible for this nonstationarity. Evidence from other studies, including data on cereal and pulse yields, indicates that this result is not particular to groundnut yield. The detection and modeling of nonstationary weather–yield relationships emerges from this study as an important part of the process of understanding and predicting the impacts of climate variability and change on crop yields. [ABSTRACT FROM AUTHOR]

It is well known that precipitation rate estimation is poor over land. Using the Tropical Rainfall Measuring Mission (TRMM) precipitation radar (PR) and TRMM Microwave Imager (TMI), the performance of the TMI rain estimation was investigated. Their differences over land were checked by using the orbit-by-orbit data for June 1998, December 1998, January 1999, and February 1999, and the following results were obtained: 1) Rain rate (RR) near the surface for the TMI (TMI-RR) is smaller than that for the PR (PR-RR) in winter; it is also smaller from 0900 to 1800 LT. These dependencies show some variations at various latitudes or local times. 2) When the storm height is low (<5 km), the TMI-RR is smaller than the PR-RR; when it is high (>8 km), the PR-RR is smaller. These dependencies of the RR on the storm height do not depend on local time or latitude. The tendency for a TMI-RR to be smaller when the storm height is low is more noticeable in convective rain than in stratiform rain. 3) Rain with a low storm height predominates in winter or from 0600 to 1500 LT, and convective rain occurs frequently from 1200 to 2100 LT. Result 1 can be explained by results 2 and 3. It can be concluded that the TMI underestimates rain with low storm height over land because of the weakness of the TMI algorithm, especially for convective rain. On the other hand, it is speculated that TMI overestimates rain with high storm height because of the effect of anvil rain with low brightness temperatures at high frequencies without rain near the surface, and because of the effect of evaporation or tilting, which is indicated by a PR profile and does not appear in the TMI profile. Moreover, it was found that the PR rain for the cases with no TMI rain amounted to about 10%–30% of the total but that the TMI rain for the cases with no PR rain accounted for only a few percent of the TMI rain. This result can be explained by the difficulty of detecting shallow rain with the TMI. [ABSTRACT FROM AUTHOR]

A satellite-based rainfall estimation algorithm, Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks (PERSIANN) Cloud Classification System (CCS), is described. This algorithm extracts local and regional cloud features from infrared (10.7 μm) geostationary satellite imagery in estimating finescale (0.04° × 0.04° every 30 min) rainfall distribution. This algorithm processes satellite cloud images into pixel rain rates by 1) separating cloud images into distinctive cloud patches; 2) extracting cloud features, including coldness, geometry, and texture; 3) clustering cloud patches into well-organized subgroups; and 4) calibrating cloud-top temperature and rainfall (Tb–R) relationships for the classified cloud groups using gauge-corrected radar hourly rainfall data. Several cloud-patch categories with unique cloud-patch features and Tb–R curves were identified and explained. Radar and gauge rainfall measurements were both used to evaluate the PERSIANN CCS rainfall estimates at a range of temporal (hourly and daily) and spatial (0.04°, 0.12°, and 0.25°) scales. Hourly evaluation shows that the correlation coefficient (CC) is 0.45 (0.59) at a 0.04° (0.25°) grid scale. The averaged CC of daily rainfall is 0.57 (0.63) for the winter (summer) season. [ABSTRACT FROM AUTHOR]

This study investigates the spatial characteristics of nonzero rain rates to develop a probability density function (PDF) model of precipitation using rainfall data from the Tropical Rainfall Measuring Mission (TRMM) satellite. The minimum χ2 method is used to find a good estimator for the rain-rate distribution between the gamma and lognormal distributions, which are popularly used in the simulation of the rain-rate PDF. Results are sensitive to the choice of dynamic range, but both the gamma and lognormal distributions match well with the PDF of rainfall data. Comparison with sample means shows that the parametric mean from the lognormal distribution overestimates the sample mean, whereas the gamma distribution underestimates it. These differences are caused by the inflated tail in the lognormal distribution and the small shape parameter in the gamma distribution. If shape constraint is given, the difference between the sample mean and the parametric mean from the fitted gamma distribution decreases significantly, although the resulting χ2 values slightly increase. Of interest is that a consistent regional preference between two test functions is found. The gamma fits outperform the lognormal fits in wet regions, whereas the lognormal fits are better than the gamma fits for dry regions. Results can be improved with a specific model assumption depending on mean rain rates, but the results presented in this study can be easily applied to develop the rainfall retrieval algorithm and to find the proper statistics in the rainfall data. [ABSTRACT FROM AUTHOR]

The water and heat balances of an arable field and a forest in the boreal zone in Scandinavia were explored using 3 yr of observations and simulations with two different soil–vegetation–atmosphere transfer (SVAT) models over a 30-yr period. Results from a detailed mechanistic model [coupled heat and mass transfer model (COUP)] were compared with those obtained with a large-scale type of SVAT model used in the weather prediction model at the European Centre for Medium-Range Weather Forecasts [ECMWF tiled land surface scheme (TESSEL)]. The COUP model simulations agreed well with the observations from a seasonal perspective. The TESSEL model differed significantly from the measurements when standard operational parameter values were used. The introduction of a seasonal variation in leaf-area index values, tuned canopy resistance for forest, and a reduced roughness length over snow-covered open land reduced the discrepancies. Net radiation was 40% higher in the forest when compared with the arable land, based on 30-yr simulations with both models. Furthermore, the forest was a net source of sensible heat flux, whereas the arable land was a net sink. Because of different treatment of winter interception evaporation, forest latent heat flux based on the COUP model considerably exceeded that from the TESSEL model, and suggested that the total annual evaporation was higher from the forest than from arable land. The representation of interception evaporation in winter, as well as seasonal dynamics in vegetation properties are, thus, of considerable importance for adequate simulation of forest and arable land energy fluxes within the boreal zone. [ABSTRACT FROM AUTHOR]

Stable boundary layer height h is determined from eddy correlation measurements of the vertical profiles of the buoyancy flux and turbulence energy from a tower over grassland in autumn, a tower over rangeland with variable snow cover during winter, and aircraft data in the stable marine boundary layer generated by warm air advection over a cool ocean surface in summer. A well-defined h within the tower layer at the grass site (lowest 50 m) and the snow site (lowest 30 m) was definable only about 20% of the time. In the remaining stable periods, the buoyancy flux and turbulence energy either (a) remained constant with height, indicating a deep boundary layer, (b) increased with height, or (c) varied erratically with height. Approximately one-half of the tower profiles did not fit the traditional concepts of a boundary layer. The well-defined cases of h are compared with various formulations for the equilibrium depth of the stably stratified boundary layer based on the Richardson number or surface fluxes. The diagnostic models for h have limited success in explaining both the variance and mean magnitude of h at all three sites. The surface bulk Richardson number and gradient Richardson number approaches perform best for the combined data. For the surface bulk Richardson number method, the required critical value varies systematically between sites. The surface bulk Richardson number approach is modified to include a critical value that depends on the surface Rossby number, which incorporates the influence of surface roughness and wind speed on boundary layer depth. [ABSTRACT FROM AUTHOR]

Snow water equivalent and snow extent are key parameters for the earth's energy and water budget. In this study, the current operational snow-depth analysis (2D spatial Cressman interpolation) at the European Centre for Medium-Range Weather Forecasts (ECMWF), which relies on real-time observations of snow depth, the short-range forecast, and snow-depth climatic data, is presented. The operational product is compared with satellite-derived snow cover. It is found that the total area of grid boxes affected by snow is approximately 10% larger in the analysis than in the National Oceanic and Atmospheric Administration National Environmental Satellite, Data, and Information Service (NOAA/NESDIS) snow-extent product. The differences are persistent in time and space and cover the entire Northern Hemisphere. They comprise areas with intermittent and/or patchy snow cover, for example, the Tibetan Plateau, the edges of snow fields, and areas with a low density of observations, which are difficult to capture in the current operational analysis. A modified snow analysis is presented, in which the operational NESDIS snow product is incorporated. The current analysis and the revised analysis are compared with high-resolution snow-cover datasets derived from the Moderate-Resolution Imaging Spectroradiometer (MODIS) and independent ground-based snow-depth observations from the Meteorological Service of Canada. Using the NOAA/NESDIS snow-extent dataset in the operational analysis leads to a more realistic description of the actual snow extent. [ABSTRACT FROM AUTHOR]

An algorithm, the spectral latent heating (SLH) algorithm, has been developed to estimate latent heating profiles for the Tropical Rainfall Measuring Mission precipitation radar with a cloud-resolving model (CRM). Heating-profile lookup tables for the three rain types—convective, shallow stratiform, and anvil rain (deep stratiform with a melting level)—were produced with numerical simulations of tropical cloud systems in the Tropical Ocean and Global Atmosphere Coupled Ocean–Atmosphere Response Experiment. For convective and shallow stratiform regions, the lookup table refers to the precipitation-top height (PTH). For the anvil region, on the other hand, the lookup table refers to the precipitation rate at the melting level instead of PTH. A consistency check of the SLH algorithm was also done with the CRM-simulated outputs. The first advantage of this algorithm is that differences of heating profiles between the shallow convective stage and the deep convective stage can be retrieved. This is a result of the utilization of observed information, not only on precipitation type and intensity, but also on the precipitation depth. The second advantage is that heating profiles in the decaying stage with no surface rain can also be retrieved. This comes from utilization of the precipitation rate at the melting level for anvil regions. [ABSTRACT FROM AUTHOR]

A case study is presented on the impact of two isolated, strong thundershowers during a prevailing dry, sunny season on the spectral optical depths and inferred columnar size characteristics of atmospheric aerosols at a tropical station. Results show a remarkable decrease in the aerosol optical depth and change in the spectral slope after the rain. The scavenging was found to be dependent on the particle size distribution; the larger, supermicron particles were found to be removed faster during the first shower itself, even though it was of only moderate intensity, resulting in about a 64% decrease in the columnar mass loading. In the second shower, which was stronger and more widespread than the former, more of the submicron particles in the optically active submicron size range were removed, but the reduction in mass loading was very small. The effective radius decreased continuously and so too did the columnar mass loading (total aerosol volume). The data are used to estimate the apparent columnar scavenging efficiency. The inferred apparent scavenging efficiencies were ∼57% and 68% for the aerosol columnar number density in the optically active submicron size range for the two events, whereas for the coarse aerosols (r > 0.5 μm), it was ∼75% for the first event but insignificant for the subsequent event, in line with the pattern of mass loading. The prevailing synoptic conditions (continental air mass and dry weather) helped the atmosphere to “recharge” within about 1 week after the events (which removed more than 70% of the aerosol burden), unlike the case with extensive synoptic phenomena, like monsoons, for which the aerosol optical depths remain depleted over the entire season. This recharging is also dependent on the size distribution of aerosols; the fine and accumulation particles are replenished faster than the coarse particles. [ABSTRACT FROM AUTHOR]

have responded with critical comments as to whether urbanization-enhanced precipitation is maximized in the south-southeast of Atlanta, Georgia, as was recently documented byThe reply herein offers both general and specific responses to the issues raised by [ABSTRACT FROM AUTHOR]

Presents a response by authors to a letter to the editor on their article "Modeling of Convective-Stratiform Precipitation Processes: Sensitivity to Partitioning Methods," that was published in the "Journal of Applied Meteorology."

The distributions of ice particles, precipitation embryos, and supercooled water are examined within updrafts in convective clouds in the Amazon and at Kwajalein, Marshall Islands, based on in situ measurements during two Tropical Rainfall Measuring Mission field campaigns. Composite vertical profiles of liquid water, small particle concentration, and updraft/downdraft magnitudes exhibit similar peak values for the two tropical regions. Updrafts were found to be favored locations for precipitation embryos in the form of liquid or frozen drizzle-sized droplets. Most updrafts glaciated rapidly, removing most of the liquid water between -5° and -17°C. However, occasional encounters with liquid water occurred in much colder updraft regions. The updraft magnitudes where liquid water was observed at cold (e.g., -16° to -19°C) temperatures do not appear to be stronger than updrafts without liquid water at similar temperatures, however. The concentrations of small spherical frozen particles in glaciated regions without liquid water are approximately one-half of the concentrations in regions containing liquid cloud droplets, suggesting that a substantial portion of the cloud droplets may be freezing at relatively warm temperatures. Further evidence for a possible new type of aggregate ice particle, a chain aggregate found at cloud midlevels, is given. [ABSTRACT FROM AUTHOR]

In this study, a technique for estimating vertical profiles of precipitation from multifrequency, multiresolution active and passive microwave observations is investigated. The technique is applicable to the Tropical Rainfall Measuring Mission (TRMM) observations, and it is based on models that simulate high-resolution brightness temperatures as functions of observed reflectivity profiles and a parameter related to the raindrop size distribution. The modeled high-resolution brightness temperatures are used to determine normalized brightness temperature polarizations at the microwave radiometer resolution. An optimal estimation procedure is employed to minimize the differences between the simulated and observed normalized polarizations by adjusting the drop size distribution parameter. The impact of other unknowns that are not independent variables in the optimal estimation, but affect the retrievals, is minimized through statistical parameterizations derived from cloud model simulations. The retrieval technique is investigated using TRMM observations collected during the Kwajalein Experiment (KWAJEX). These observations cover an area extending from 5° to 12°N latitude and from 166° to 172°E longitude from July to September 1999 and are coincident with various ground-based observations, facilitating a detailed analysis of the retrieved precipitation. Using the method developed in this study, precipitation estimates consistent with both the passive and active TRMM observations are obtained. Various parameters characterizing these estimates, that is, the rain rate, precipitation water content, drop size distribution intercept, and the mass- weighted mean drop diameter, are in good qualitative agreement with independent experimental and theoretical estimates. Combined rain estimates are, in general, higher than the official TRMM precipitation radar (PR)-only estimates for the area and the period considered in the study. Ground-based precipitation estimates, derived from an analysis of rain gauge and ground radar data, are in better agreement with the combined estimates than with the TRMM PR-only estimates, which suggests that information useful for improving the radar-only estimates is contained in the brightness temperature data. [ABSTRACT FROM AUTHOR]

Geostationary Meteorological Satellite Visible/Infrared Spin-Scan Radiometer (GMS VISSR) images have been used to estimate diurnal variations of land surface temperature distributions over the Tibetan Plateau. The infrared split-window algorithm developed for NOAA Advanced Very High Resolution Radiometer (AVHRR) has been adapted for this purpose. Radiative transfer simulations are carried out to obtain the atmospheric transmittances and the difference temperatures that are involved in the internal coefficients of the split-window algorithm. Precipitable water distribution that is required by this algorithm is estimated from 6.7-μm brightness temperature utilizing spectral characteristics of the GMS water vapor channel. Cloud removal plays an important role in the surface temperature retrieval process. To identify convective cloud activity, many researchers use satellite infrared measurements with a fixed threshold technique. In this study, it is necessary to remove not only convective clouds but also warm clouds. For this purpose, a variable threshold technique is proposed. The threshold varies both seasonally and diurnally, and its value is determined on the basis of surface observations. With a variable threshold, it becomes possible to remove relatively warmer clouds in summer and detect colder ground surfaces at nighttime in the winter. The results of comparing estimated surface temperature from GMS data using this algorithm with in situ surface measurements show correlations around 0.8. [ABSTRACT FROM AUTHOR]

Polarimetric radar measurements are used to retrieve properties of raindrop distributions. The procedure assumes that drops are represented by a gamma distribution and retrieves the governing parameters from an empirical relation between the distribution shape and slope parameters and measurements of radar reflectivity and differential reflectivity. Retrieved physical characteristics of the drop size distribution (DSD) were generally well matched with disdrometer observations. The method is applied to select storms to demonstrate utility. Broad DSDs were determined for the core (high reflectivity) regions of thunderstorms. Largest drop median volume diameters were at the leading edge of the storm core and were displaced slightly downwind from updrafts. Rainy downdrafts exhibited what are believed to be equilibrium DSDs in which breakup and accretion are roughly in balance. DSDs for stratiform precipitation were dominated by relatively large drops. Median volume diameters at the ground were closely related to the intensity of an overlying bright band. The radar measurements suggest that, although DSDs in stratiform rain were also broad and nearly constant in the rain layer, they were not at equilibrium but were merely steady. DSD invariance is attributed to small total drop numbers, which result in few collisions. [ABSTRACT FROM AUTHOR]

Raindrop size distribution (DSD) retrieval from remote radar measurements or from in situ disdrometer measurements is an important area of research. If the shape (μ) and slope (Λ) of a three-parameter gamma distribution n(D) = N[sub 0] D[sup μ] exp(-ΛD) are related to one another, as recent disdrometer measurements suggest, the gamma DSD model is simplified to a two-parameter DSD, that is, a constrained gamma DSD. An empirical relation between the μ and Λ was derived using moments estimated from video-disdrometer measurements. Here, the effects of DSD truncation on a μ and Λ relation were analyzed. It was shown that characteristic size and variance of size of a constrained gamma DSD depend only on the shape parameter μ. Assuming that a constrained gamma DSD is valid, S-band polarimetric radar–based estimators for rain rate, median volume diameter, specific propagation phase, attenuation, and differential attenuation were derived. The radar-based estimators were used to obtain the spatial distribution of DSD parameters corresponding to a range–height indicator of radar measurements. Self-consistency among polarization radar measurements is used to indirectly verify constrained gamma DSD-based polarization radar estimators. [ABSTRACT FROM AUTHOR]

The effective scene temperature, or “brightness temperature,” measured in channel 3 (3.5–3.9 μm) of the Advanced Very High Resolution Radiometer (AVHRR) is shown to be sensitive, in principle, to the effective particle size of snow grains on the Antarctic plateau, over the range of snow grain sizes reported in field studies. In conjunction with a discrete ordinate method radiative transfer model that couples the polar atmosphere with a scattering and absorbing snowpack, the thermal infrared channels of the AVHRR instrument can, therefore, be used to estimate effective grain size at the snow surface over Antarctica. This is subject to uncertainties related to the modeled top-of-atmosphere bidirectional reflectance distribution function resulting from the possible presence of sastrugi and to lack of complete knowledge of snow crystal shapes and habits as they influence the scattering phase function. However, when applied to NOAA-11 and NOAA-12 AVHRR data from 1992, the snow grain effective radii of order 50 μm are retrieved, consistent with field observations, with no apparent discontinuity between two spacecraft having different viewing geometries. Retrieved snow grain effective radii are 10–20-μm larger when the snow grains are modeled as hexagonal solid columns rather than as spheres with a Henyey–Greenstein phase function. Despite the above-mentioned uncertainties, the retrievals are consistent enough that one should be able to monitor climatically significant changes in surface snow grain size due to major precipitation events. It is also shown that a realistic representation of the surface snow grain size is critical when retrieving the optical depth and effective particle radius of clouds for the optically thin clouds most frequently encountered over the Antarctic plateau. [ABSTRACT FROM AUTHOR]

Normalization of drop size distributions (DSDs) is reexamined here. First, an extension of the scaling normalization that uses one moment of the DSD as a scaling parameter to a more general scaling normalization that uses two moments as scaling parameters of the normalization is presented. In addition, the proposed formulation includes all two-parameter normalizations recently introduced in the literature. Thus, a unified vision of the question of DSD normalization and a good model representation of DSDs are given. Data analysis of some convective and stratiform DSDs shows that, from the point of view of the compact representation of DSDs, the double-moment normalization is preferred. However, in terms of physical interpretation, the scaling exponent of the single-moment normalization clearly indicates two different rain regimes, whereas in the double-moment normalization the two populations are not readily separated. It is also shown that DSD analytical models (exponential, gamma, and generalized gamma DSD) have the same scaling properties, indicating that the scaling formalism of DSDs is a very general way of describing DSDs. [ABSTRACT FROM AUTHOR]

A two-dimensional measure of effectiveness for comparing hazardous material transport and dispersion model predictions and field observations has been developed. This measure is used for comparing predictions and observations paired in space and time, and the components of this measure—overprediction, or false-positive fraction, and underprediction, or false-negative fraction—can illuminate strengths and weaknesses of a model in ways that many one-dimensional measures cannot. Comparisons of predictions of short-range field observations are used to illustrate features of this measure of effectiveness, including its computation based on dosages or based on a dosage threshold of interest. With this user-oriented measure of effectiveness, statistically significant resolution of transport and dispersion model performance differences as a function of downwind range and meteorological stability category grouping, as well as between different models, is described. Evaluation of probabilistic prediction outputs is also demonstrated with this measure of effectiveness. The user-oriented measure of effectiveness can be evaluated for different assumed hazardous materials and human effects of interest and, as such, can relate the quality of a prediction for agents of greatly varying toxicity. A quantitative method that can aid in the communication of a user's risk tolerance is identified and allows one to divide the two-dimensional measure of effectiveness space into regions of relative acceptability for the particular user and application. [ABSTRACT FROM AUTHOR]

Precipitation measurement using passive or active microwaves from space- or ground-based radar involves hypotheses about the raindrop size distribution (DSD). A universal knowledge of DSD characteristics is needed. A 4-yr dataset collected with a disdrometer at Dakar, Senegal, on the Atlantic coast of West Africa is used to analyze the DSD at the end of the continental trajectory of Sahelian squall lines. The DSDs are stratified in eight rain-rate classes and are fitted to analytical distributions. The shape of the averaged DSDs is found to be very similar from one year to the next. From rain rates R higher than about 20 mm h[sup -1] , the slope of the DSDs tends toward a constant value. The coefficients of the Z–R relation, between the radar reflectivity factor Z and R, are different for convective and stratiform parts of the squall lines. However, because the Z–R relations for convective rain intersect the relation for stratiform rain for high rates, it is suggested that using a single Z–R relation enables correct representation of the whole Z and R range of variation in West Africa. The coefficients of this single Z–R are close to that of the stratiform relation and to that observed in other West African areas. The conditional probability density function of rain rate, P(R), is of lognormal shape and also is very stable year after year. The coefficient of variation of R is found to be constant and close to 2.24, the value observed at many other sites. From P(R), the linear coefficient S(τ) of the relation that links the area-averaged rain rate to the fractional area where the rain rate is higher than the threshold τ is computed and is found to be very stable for the values of τ close to m[sub R] , the mean climatic value of R (around 5–6 mm h[sup -1] ). Because most of the sub-Saharan West African sites have a similar m[sub R] , comparison shows that S(τ) is homogeneous over this area. This result suggests that S(τ) can be used with confidence for average rainfall estimation over a climatically homogeneous region. [ABSTRACT FROM AUTHOR]

A physical model of snow transport and deposition is used in combination with historical climatological data to derive a climatological measure of extreme snowdrift loads on building roofs. The snowdrift metric used relies on hourly wind speed, temperature, and weather occurrence data and daily observations of snow water equivalent, snowfall, and snow depth. The model is applicable to both roof steps and gable roofs. On average, the maximum drift surcharge corresponds to 10%–20% of the snow on the upwind roof snow source area. There is some degree of spatial variation in this maximum drift surcharge. Values range from about 3% at stations that receive minimal snow to a maximum of 24% in the northern plains and eastern Great Lakes regions of the United States. The amount of drifting is strongly influenced by wind direction. For instance, under easterly winds, the drift-load ratio averages only 3% over all stations. These findings are in general agreement with current building-code provisions for roof steps but indicate that existing provisions for gable roof drifts may be too conservative. [ABSTRACT FROM AUTHOR]

Although airborne Doppler radar is increasingly relied upon to provide detailed descriptions of mesoscale precipitation systems in remote and complex meteorological settings, the utility of these observations has often been limited by the considerable difficulty in their manual processing to remove ground clutter and other sources of contamination, which is a prerequisite to synthesis of reliable airflow and reflectivity fields. This difficulty is further magnified over mountainous terrain, where these sources of contamination take on increased spatial extent and geometric complexity. Removal of such contamination has traditionally required tedious and time-consuming manual editing. As such, routine retrieval of near-surface airflow and precipitation characteristics over steep orography and within hydrologically critical zones, such as deep valleys cutting through mountainous regions (along which population and transportation corridors are frequently concentrated), has been impractical. A new approach is described that largely automates this data-editing procedure for airborne radar platforms, achieving reliable elimination of corrupted data with minimal loss of meteorological signal. Subjective decisions are minimized through a judicious combination of data renavigation, pattern recognition, and reliance upon high-resolution digital terrain information. This technique is applied to data obtained over the Alps by the NCAR Electra and NOAA P-3 aircraft during the recent Mesoscale Alpine Programme field campaign. Three-dimensional airflow and reflectivity fields are shown to illustrate the power and fidelity of this new approach by capitalizing on data collected near, and even beneath, the aircraft track to provide a unique and highly illuminating description of airflow deep within Alpine river valleys and their tributaries during two contrasting orographic precipitation events. The validity of these results is explored through quantitative comparison of this output with independent kinematic measures obtained from ground-based Doppler radar. The utility of airborne radar to provide comprehensive and near-simultaneous views reaching into multiple valleys hidden from the view of ground-based radars is highlighted for a notable case of “down valley” flow, more comprehensively illustrating the nature and extent of low-level upstream blocking during a widespread orographic precipitation event. [ABSTRACT FROM AUTHOR]

Information about the microstructure and precipitation potential of cloud revealed by the brightness temperature difference between a thermal IR channel (11 μm) and a mid-IR channel (3.7 μm) at nighttime is implemented into a precipitation delineation algorithm. The algorithm is simple to implement and uses data available from almost all of the operational and research satellites. The delineation algorithm performs well also in cases of warm clouds over land for which passive microwave algorithms fail. [ABSTRACT FROM AUTHOR]

Nighttime microphysical retrievals can be obtained to a much lesser accuracy than those of the daytime, because of lack of the solar radiation. However, a proper treatment of the brightness temperature difference (BTD) between a thermal IR channel (11 μm) and a mid-IR channel (3.7 μm) reveals information about the microstructure and precipitation potential of clouds at nighttime. The two factors that contribute to large BTD are the particle size at cloud top and the optical depth of the cloud layer. These two factors have contradictory effects on precipitation. The respective contributions were simulated and compared with observations of the Tropical Rainfall Measuring Mission. Based on that, a method was developed to use the distribution of BTD with cloud-top temperature for retrieving cloud microstructure and precipitation properties. [ABSTRACT FROM AUTHOR]