ALBERT

Description: Winds at the Salt Lake City International Airport (SLC) during the April–October period from 1948 to 2003 have been observed to shift to the north (up-valley direction) between late morning and afternoon on over 70% of the days without precipitation. Lake-breeze fronts that develop as a result of the differential heating between the air over the nearby Great Salt Lake and that over the lake’s surroundings are observed at SLC only a few times each month. Fewer lake-breeze fronts are observed during late July–early September than before or after that period. Interannual fluctuations in the areal extent of the shallow Great Salt Lake contribute to year-to-year variations in the number of lake-breeze frontal passages at SLC. Data collected during the Vertical Transport and Mixing Experiment (VTMX) of October 2000 are used to examine the structure and evolution of a lake-breeze front that moved through the Salt Lake Valley on 17 October. The onset of upslope and up-valley winds occurred within the valley prior to the passage of the lake-breeze front. The lake-breeze front moved at roughly 3 m s−1 up the valley and was characterized near the surface by an abrupt increase in wind speed and dewpoint temperature over a distance of 3–4 km. Rapid vertical mixing of aerosols at the top of the 600–800-m-deep boundary layer was evident as the front passed.

Description: Observations of the turbulent exchange between a river surface and the atmosphere in a mountainous area in southern Brazil are presented and discussed. A micrometeorological tower was installed directly above the surface of a 60-m-wide river. This paper describes the observed turbulent fluxes over 12 days of observations at this site. Eddy correlation sensible and latent heat fluxes are directed toward the river during daytime and from the river at night, and they are controlled by differences between water and air temperatures. The magnitude of the vertical fluxes between the river and the atmosphere increases during daytime with increasing temperature gradient up to a threshold, beyond which the increasing stability starts to dampen the fluxes. Water and air temperatures show very little variations across the width of the river, indicating that the measurements taken at one margin may be representative of the mean river exchange. Local scalar budgets show that daytime warming and moistening rates above the river are controlled by local transport from the riverbanks. The main vertical fluxes have a very small magnitude: 0.8 W m−2 for sensible heat and 1.1 W m−2 for latent heat. Events of very large sensible heat fluxes from the river to the atmosphere and very large latent heat fluxes from the atmosphere to the river happened on 3 days, following nights with a very deep fog layer in the valley. These events represented the passage of a warm and dry air mass down the river. A process to explain the occurrence of these large fluxes is suggested that is associated with differential fog dissipation over the valley.

Description: Continuous time series of soil water content over a period of more than 9 months for a midlatitude sandy loam soil covered by grass are calculated with the Campbell and the van Genuchten soil hydraulic functions and the Clapp–Hornberger, Cosby et al., and Rawls–Brakensiek parameter sets. The results are compared with soil water content observed at several soil depths, and the water balance components are evaluated. The Campbell soil hydraulic functions are often used by meteorologists, whereas the van Genuchten functions are widespread among hydrologists. The simulations are performed with the “VEG3D” soil–vegetation model in stand-alone mode forced by on-site meteorological observations. The soil water content and meteorological observations were obtained within the Regional Climate Project (REKLIP) at a site in the Rhine valley in southern Germany with 10-min temporal resolution. Apart from the different soil hydraulic functions and parameter sets, the effects of different lower boundary conditions and initializations on the simulations are compared in terms of statistical quantities like mean error, bias, correlation coefficient, and least squares fit. Large differences between the various combinations are found. For the situation considered in this paper, the van Genuchten–Clapp–Hornberger, the Campbell–Cosby et al., and the van Genuchten–Rawls–Brakensiek combinations give the best overall agreement with the observations.

Description: A vertical distribution formulation of liquid water content (LWC) for steady radiation fog was obtained and examined through the singular perturbation method. The asymptotic LWC distribution is a consequential balance among cooling, droplet gravitational settling, and turbulence in the liquid water budget of radiation fog. The cooling produces liquid water, which is depleted by turbulence near the surface. The influence of turbulence on the liquid water budget decreases with height and is more significant for shallow fogs than for deep fogs. The depth of the region of surface-induced turbulence can be characterized with a fog boundary layer (FBL). The behavior of the FBL bears some resemblance to the surface mixing layer in radiation fog. The characteristic depth of the FBL is thinner for weaker turbulence and stronger cooling, whereas if turbulence intensity increases or cooling rate decreases then the FBL will develop from the ground. The asymptotic formulation also reveals a critical turbulent exchange coefficient for radiation fog that defines the upper bound of turbulence intensity that a steady fog can withstand. The deeper a fog is, the stronger a turbulence intensity it can endure. The persistence condition for a steady fog can be parameterized by either the critical turbulent exchange coefficient or the characteristic depth of the FBL. If the turbulence intensity inside a fog is smaller than the turbulence threshold, the fog persists, whereas if the turbulence intensity exceeds the turbulence threshold or the characteristic depth of the FBL dominates the entire fog bank then the balance will be destroyed, leading to dissipation of the existing fog. The asymptotic formulation has a first-order approximation with respect to turbulence intensity. Verifications with numerical solutions and an observed fog event showed that it is more accurate for weak turbulence than for strong turbulence and that the computed LWC generally agrees with the observed LWC in magnitude.

Description: The eruption of the Mount Asama volcano on 16 September 2004 produced an ash cloud and led to ashfall in the Tokyo metropolitan area that lies on the Kanto Plain. Satellite images showed the ash cloud drifting toward the south in the morning but to the southeast in the afternoon. An aerosol lidar and a ceilometer, installed in the metropolitan area, continuously observed the southeastward-transported ash particles passing at altitudes of 2.6–4.5 km above mean sea level (MSL) in the nighttime. Results of meteorological analyses and numerical experiments showed that the south-to-southeasterly sea breezes and valley winds prevailed at altitudes below 1.5 km MSL over the Kanto Plain in the afternoon and the compensatory return flow (CRF) was formed aloft at altitudes of 1.5–4.5 km MSL as strong northwesterly winds, which were encouraged by a synoptic wind. The numerical experiments also showed that the direction of the ash transport turned from the south to the southeast following the formation of the northwesterly CRF. This demonstrates that the daytime ash transport was influenced by the CRF. The nocturnal ash transport, however, depended on the intensified synoptic wind. Thus, in addition to synoptic winds, the large-scale local wind circulation prevailing over the Kanto Plain can determine the direction of ash transport originating from the Mount Asama volcano and increase the possibility of ashfall in the Tokyo metropolitan area.

Description: Urbanization, the expansion of built-up areas, is an important yet less-studied aspect of land use/land cover change in climate science. To date, most global climate models used to evaluate effects of land use/land cover change on climate do not include an urban parameterization. Here, the authors describe the formulation and evaluation of a parameterization of urban areas that is incorporated into the Community Land Model, the land surface component of the Community Climate System Model. The model is designed to be simple enough to be compatible with structural and computational constraints of a land surface model coupled to a global climate model yet complex enough to explore physically based processes known to be important in determining urban climatology. The city representation is based upon the “urban canyon” concept, which consists of roofs, sunlit and shaded walls, and canyon floor. The canyon floor is divided into pervious (e.g., residential lawns, parks) and impervious (e.g., roads, parking lots, sidewalks) fractions. Trapping of longwave radiation by canyon surfaces and solar radiation absorption and reflection is determined by accounting for multiple reflections. Separate energy balances and surface temperatures are determined for each canyon facet. A one-dimensional heat conduction equation is solved numerically for a 10-layer column to determine conduction fluxes into and out of canyon surfaces. Model performance is evaluated against measured fluxes and temperatures from two urban sites. Results indicate the model does a reasonable job of simulating the energy balance of cities.

Description: The estimation of atmospheric motion vectors from infrared and water vapor channels on the geostationary operational Indian National Satellite System Kalpana-1 has been attempted here. An empirical height assignment technique based on a genetic algorithm is used to determine the height of cloud and water vapor tracers. The cloud-motion-vector (CMV) winds at high and midlevels and water vapor winds (WVW) derived from Kalpana-1 show a very close resemblance to the corresponding Meteosat-7 winds derived at the European Organisation for the Exploitation of Meteorological Satellites when both are compared separately with radiosonde data. The 3-month mean vector difference (MVD) of high- and midlevel CMV and WVW winds derived from Kalpana-1 is very close to that of Meteosat-7 winds, when both are compared with radiosonde. When comparing with radiosonde, the low-level CMVs from Kalpana-1 have a higher MVD value than that of Meteosat-7. This may be due to the difference in spatial resolutions of Kalpana-1 and Meteosat-7.

Description: The assimilation of cloud- and precipitation-affected observations into weather forecasting systems requires very fast calculations of radiative transfer in the presence of multiple scattering. At the European Centre for Medium-Range Weather Forecasts (ECMWF), performance limitations mean that only a single cloudy calculation (including any precipitation) can be made, and the simulated radiance is a weighted combination of cloudy- and clear-sky radiances. Originally, the weight given to the cloudy part was the maximum cloud fraction in the atmospheric profile. However, this weighting was excessive, and because of nonlinear radiative transfer (the “beamfilling effect”) there were biases in areas of cloud and precipitation. A new approach instead uses the profile average cloud fraction, and decreases RMS errors by 40% in areas of rain or heavy clouds when “truth” comes from multiple independent column simulations. There is improvement all the way from low (e.g., 19 GHz) to high (e.g., 183 GHz) microwave frequencies. There is also improvement when truth comes from microwave imager observations. One minor problem is that biases increase slightly in mid- and upper-tropospheric sounding channels in light-cloud situations, which shows that future improvements will require the cloud fraction to vary according to the optical properties at different frequencies.

Description: Consistency of upper-tropospheric water vapor measurements from a variety of state-of-the-art instruments was assessed using collocated Geostationary Operational Environmental Satellite-8 (GOES-8) 6.7-μm brightness temperatures as a common benchmark during the Atmospheric Radiation Measurement Program (ARM) First International Satellite Cloud Climatology Project (ISCCP) Regional Experiment (FIRE) Water Vapor Experiment (AFWEX). To avoid uncertainties associated with the inversion of satellite-measured radiances into water vapor quantity, profiles of temperature and humidity observed from in situ, ground-based, and airborne instruments are inserted into a radiative transfer model to simulate the brightness temperature that the GOES-8 would have observed under those conditions (i.e., profile-to-radiance approach). Comparisons showed that Vaisala RS80-H radiosondes and Meteolabor Snow White chilled-mirror dewpoint hygrometers are systemically drier in the upper troposphere by ∼30%–40% relative to the GOES-8 measured upper-tropospheric humidity (UTH). By contrast, two ground-based Raman lidars (Cloud and Radiation Test Bed Raman lidar and scanning Raman lidar) and one airborne differential absorption lidar agree to within 10% of the GOES-8 measured UTH. These results indicate that upper-tropospheric water vapor can be monitored by these lidars and well-calibrated, stable geostationary satellites with an uncertainty of less than 10%, and that correction procedures are required to rectify the inherent deficiencies of humidity measurements in the upper troposphere from these radiosondes.

Description: The passage of three Australian Category 5 cyclones within 350 km of Darwin (Northern Territory), Australia, during the last decade indicates that that city should have a high wind hazard. In this paper, the wind hazard for Darwin was compared with that for Port Hedland (Western Australia) and Townsville (Queensland) using data from a coupled ocean–atmosphere simulation model and from historical and satellite-era records of tropical cyclones. According to the authoritative statement on wind hazard in Australia, Darwin’s wind hazard is the same as Townsville’s but both locations’ hazards are much less than that of Port Hedland. However, three different estimates in this study indicate that Darwin’s wind hazard at the long return periods relevant to engineering requirements is higher than for both Port Hedland and Townsville. The discrepancy with previous studies may result from the inadequate cyclone records in the low-latitude north of Australia, from accumulated errors from estimates of wind speeds from wind fields and wind–pressure relationships, and from inappropriate extrapolations of short-period records based on assumed probability distributions. It is concluded that the current wind-hazard zoning of northern Australia seriously underestimates the hazard near Darwin and that coupled ocean–atmosphere simulation models could contribute to its revision.

Description: The value of El Niño–Southern Oscillation (ENSO) forecast information to southern high plains winter wheat and cattle-grazing production systems was estimated here by simulation. Although previous work has calculated average forecast value, the approach here was to estimate probabilities of the value of single forecasts from value distributions associated with categorical ENSO forecast conditions. A simple ENSO-phase forecast system’s value was compared with that of an ideal forecast method that exactly predicted the tercile category of regional November–March precipitation. Simulations were conducted for four price scenarios with wheat prices that randomly varied about a historical ($3.22 per bushel) and elevated ($7.00 per bushel) mean and with returns on live weight gain that are consistent with the grain producer leasing pasturage or owning cattle. In the simulations at $3.22 per bushel, the best practices for specific forecast conditions varied with cattle-ownership conditions. However, the ENSO-phase system’s value distributions were comparable to that of the perfect forecast system; thus more-accurate regional precipitation forecasts may not lead to more forecast value at the farm level. In the simulations at $7.00 per bushel, even perfect categorical forecasts produced only minor profit effects, a result that is attributed here to an increased profit margin rather than to increased wheat value. Under both wheat-price conditions, however, the best no-forecast baseline practices are also shown to have value relative to an arbitrarily chosen management practice. Thus, following practices optimized to climatic conditions and current price and cost conditions might increase profits when no forecast information is available.

Description: In the event of the release of a dangerous atmospheric contaminant, an atmospheric transport and dispersion (ATD) model is often used to provide forecasts of the resulting contaminant dispersion affecting the population. These forecasts should also be accompanied by accurate estimates of the forecast uncertainty to allow for more informed decisions about the potential hazardous area. This study examines the calculation of uncertainty in the meteorological data as derived from an ensemble, and its effects when used as additional input to drive an ATD model. The first part of the study examines the capability of a linear function to relate ensemble spread to error variance of the ensemble mean given ensemble spread from 24 days of forecasts from the National Centers for Environmental Prediction (NCEP) Short-Range Ensemble Forecast (SREF). This linear function can then be used to calibrate the ensemble spread to produce a more accurate estimate of the meteorological uncertainty. Results for the linear relationship of wind variance are very good, with values of the coefficient of determination R2 generally exceeding 0.94 for forecast lengths of 12 h and greater. The calibration is shown to be more sensitive to forecast hour than vertical level within the lower troposphere. The second part presents a 24-h case study to assess the impact of meteorological uncertainty calculations on Second-Order Closure Integrated Puff (SCIPUFF) ATD model predictions. Both uncalibrated ensemble wind variances and wind variances calibrated based on the results of the first part show improvement in mean concentration forecasts relative to a control experiment using the default hazard mode uncertainty when compared with a baseline SCIPUFF integration based on a high-resolution dynamic analysis of the meteorological conditions. The SCIPUFF experiments that use a wind variance calibration show both qualitative and quantitative improvement in most of the mean concentrations and patterns over the control experiment and the SCIPUFF experiment using uncalibrated wind variances. The SCIPUFF experiments using meteorological ensemble uncertainty information also produce mean concentrations and patterns that compare favorably to those of an explicit SCIPUFF ensemble based on each SREF member. Use of the uncalibrated variance information within a single ATD prediction produces mean ATD predictions most similar to those of the explicit ATD ensemble, and use of calibrated ensemble variance is shown to have some advantages over the explicit ATD ensemble.

Description: In this study, Moderate Resolution Imaging Spectroradiometer (MODIS) infrared-based cloud thermodynamic phase retrievals are evaluated using Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) retrievals for the 6 months from January to June of 2008. The CALIOP 5-km cloud-layer product provides information on cloud opacity, cloud-top height, midlayer cloud temperature, and cloud thermodynamic phase. Comparisons are made between MODIS IR phase and CALIOP observations for single-layer clouds (54% of the cloudy CALIOP scenes) and for the top layer of the CALIOP scenes. Both CALIOP and MODIS retrieve larger fractions of water clouds in the single-layer cases than in the top-layer cases, demonstrating that focusing on only single-layer clouds may introduce a water-cloud bias. Of the single-layer clouds, 60% are transparent and 40% are opaque (defined by the lack of a CALIOP ground return). MODIS tends to classify single-layer clouds with midlayer temperatures below −40°C as ice; around −30°C nearly equally as ice, mixed, and unknown; between −28° and −15°C as mixed; and above 0°C as water. Ninety-five percent of the single-layer CALIOP clouds not detected by MODIS are transparent. Approximately ⅓ of transparent single-layer clouds with temperatures below −30°C are not detected by MODIS and close to another ⅓ are classified as ice, with the rest assigned as water, mixed, or unknown. CALIOP classes nearly all of these transparent cold clouds as ice.

Description: Sea surface temperature (SST) and air temperature were measured in situ in Tokyo Bay. These measurements were made with high spatial and temporal resolutions between November 2006 and September 2007. The analysis of these data revealed 1) the seasonal and diurnal variations of SST and air temperature, and 2) the physical process by which Tokyo Bay lowers urban air temperature in summer. The following were the major findings obtained: 1) the diurnal amplitude of SST was as large as 5.5°C; 2) abrupt increases of SST occurred at the head and mouth of the bay that were due to heated water discharge and the Kuroshio, respectively; 3) the values of the satellite-based objectively analyzed SSTs were higher than those of the in situ SSTs, especially in winter; 4) the relationship between SST and air temperature was classified into three seasonal modes—winter, transient, and summer—and each mode was associated with the seasonal stability condition of the near-surface water; 5) the strong southwesterly wind over the bay in summer decreased the SST mainly because of increased turbulent mixing at the water surface, thereby increasing downward sensible heat flux up to −100 W m−2; 6) the lower SSTs in summer lowered the air temperature, but only for the urban atmosphere near the coast, and no effect was detected at 20 km inland; and 7) the horizontal gradient of air temperature over the land intensified with increasing wind speed.

Description: The standard deviation of wind direction is a very important quantity in meteorology because in addition to being used to determine the dry deposition rate and the atmospheric stability class, it is also employed in the determination of the rate of horizontal diffusion, which in turn determines transport and dispersion of air pollutants. However, the computation of this quantity is rendered difficult by the fact that the horizontal wind direction is a circular variable having a discontinuity at 2π radians, beyond which the wind direction starts again from zero, thus preventing angular subtraction from being a straightforward procedure. In view of such a limitation, this work is meant to provide new mathematical expressions that simplify both the computational and analytical work involved in handling the standard deviation of wind direction. This is achieved by deriving a number of Fourier series and Taylor expansions that can represent the minimum angular distance and its powers. Using these expressions, the relation between two algorithms commonly used to determine the standard deviation of wind direction is analyzed. Furthermore, given that these trigonometric expansions effectively reduce the mathematical complexity involved when dealing with circular statistics, their potential application to solve other problems is discussed.

Description: This paper complements an earlier one that demonstrated the bias in the method-of-moments (MM) estimators frequently used to estimate parameters for drop size distribution (DSD) functions being “fitted” to observed raindrop size distributions. Here the authors consider both the bias and the errors in MM estimators applied to samples from known gamma DSDs (of which the exponential DSD treated in the earlier paper is a special case). The samples were generated using a similar Monte Carlo simulation procedure. The skewness in the sampling distributions of the DSD moments that causes this bias is less pronounced for narrower population DSDs, and therefore the bias problems (and also the errors) diminish as the gamma shape parameter increases. However, the bias still increases with the order of the moments used in the MM procedures; thus it is stronger when higher-order moments (such as the radar reflectivity) are used. The simulation results also show that the errors of the estimates of the DSD parameters are usually larger when higher-order moments are employed. As a consequence, only MM estimators using the lowest-order sample moments that are thought to be well determined should be used. The biases and the errors of most of the MM parameter estimates diminish as the sample size increases; with large samples the moment estimators may become sufficiently accurate for some purposes. Nevertheless, even with some fairly large samples, MM estimators involving high-order moments can yield parameter values that are physically implausible or are incompatible with the input observations. Correlations of the sample moments with the size of the largest drop in a sample (Dmax) are weaker than for the case of sampling from an exponential DSD, as are the correlations of the MM-estimated parameters with Dmax first noted in that case. However, correlations between the estimated parameters remain because functions of the same observations are correlated. These correlations generally strengthen as the sample size increases.

Description: The differential phase (ΦDP) measured by polarimetric radars is recognized to be a very good indicator of the path integrated by rain. Moreover, if a linear relationship is assumed between the specific differential phase (KDP) and the specific attenuation (AH) and specific differential attenuation (ADP), then attenuation can easily be corrected. The coefficients of proportionality, γH and γDP, are, however, known to be dependent in rain upon drop temperature, drop shapes, drop size distribution, and the presence of large drops causing Mie scattering. In this paper, the authors extensively apply a physically based method, often referred to as the “Smyth and Illingworth constraint,” which uses the constraint that the value of the differential reflectivity ZDR on the far side of the storm should be low to retrieve the γDP coefficient. More than 30 convective episodes observed by the French operational C-band polarimetric Trappes radar during two summers (2005 and 2006) are used to document the variability of γDP with respect to the intrinsic three-dimensional characteristics of the attenuating cells. The Smyth and Illingworth constraint could be applied to only 20% of all attenuated rays of the 2-yr dataset so it cannot be considered the unique solution for attenuation correction in an operational setting but is useful for characterizing the properties of the strongly attenuating cells. The range of variation of γDP is shown to be extremely large, with minimal, maximal, and mean values being, respectively, equal to 0.01, 0.11, and 0.025 dB °−1. Coefficient γDP appears to be almost linearly correlated with the horizontal reflectivity (ZH), differential reflectivity (ZDR), and specific differential phase (KDP) and correlation coefficient (ρHV) of the attenuating cells. The temperature effect is negligible with respect to that of the microphysical properties of the attenuating cells. Unusually large values of γDP, above 0.06 dB °−1, often referred to as “hot spots,” are reported for 15%—a nonnegligible figure—of the rays presenting a significant total differential phase shift (ΔϕDP 〉 30°). The corresponding strongly attenuating cells are shown to have extremely high ZDR (above 4 dB) and ZH (above 55 dBZ), very low ρHV (below 0.94), and high KDP (above 4° km−1). Analysis of 4 yr of observed raindrop spectra does not reproduce such low values of ρHV, suggesting that (wet) ice is likely to be present in the precipitation medium and responsible for the attenuation and high phase shifts. Furthermore, if melting ice is responsible for the high phase shifts, this suggests that KDP may not be uniquely related to rainfall rate but can result from the presence of wet ice. This hypothesis is supported by the analysis of the vertical profiles of horizontal reflectivity and the values of conventional probability of hail indexes.

Description: On 1 July 1961, the climatological day was redefined to end at 0600 UTC (coordinated universal time) at all synoptic (airport) stations in Canada. Prior to that, the climatological day ended at 1200 UTC for maximum temperature and 0000 UTC for minimum temperature. This study shows that the redefinition of the climatological day in 1961 has created a cold bias in the annual and seasonal means of daily minimum temperatures across the country while the means of daily maximum temperatures were not affected. Hourly temperatures taken at 121 stations for 1953–2007 are used to determine the magnitude of the bias and its spatial variation. It was found that the bias is more pronounced in the eastern regions; its annual mean varies from −0.2° in the west to −0.8°C in the east. Not all days are affected by this change in observing time, and the annual percentage of affected days ranges from 15% for locations in the west to 38% for locations in the east. An approach based on hourly values is proposed for adjusting the affected daily minimum temperatures over 1961–2007. The adjustment on any individual day varies from 0.5° to 12.5°C. The impact of the adjustment is assessed by examining the trends in the annual mean of the daily minimum temperatures for 1950–2007. Overall, with the adjustment, the trends are becoming either more positive or are reversing from negative to positive, and they have changed by as much as 1°C in numerous locations in the eastern regions.

Description: A procedure for the estimation of rainfall rate, capitalizing on a radar-based raindrop size distribution (RSD) parameter retrieval and neural network (NN) inversion techniques, is validated using an extensive and quality-controlled archive. The RSD retrieval algorithm utilizes polarimetric variables measured by the polarimetric prototype of the Weather Surveillance Radar-1988 Doppler (WSR-88D) in Norman, Oklahoma (KOUN), through an ad hoc regularized neural network method. Evaluation of rainfall estimation from the NN-based method is accomplished using a large radar data and surface gauge observation dataset collected in central Oklahoma during the multiyear Joint Polarization Experiment (JPOLE) field campaign. Point estimates of hourly rainfall accumulations and instantaneous rainfall rates from NN-based and parametric polarimetric rainfall relations are compared with dense surface gauge observations. Rainfall accumulations from RSD retrieval-based methods are shown to be sensitive to the choice of a raindrop fall speed model. To minimize the impact of this choice, a new “direct” neural network approach is tested. Proposed NN-based approaches exhibit bias and root-mean-square error characteristics comparable with those obtained from parametric relations, specifically optimized for the JPOLE dataset, indicating an appealing generalization capability with respect to the climatological context. All tested polarimetric relations are shown to be sensitive to hail contamination as inferred from the results of automatic polarimetric echo classification and available storm reports.

Description: This paper assesses the effect of climate change on crop yield from a soil water balance perspective. The uncertainties of regional-scale climate models, local-scale climate variability, emissions scenarios, and crop growth models are combined to explore the possible range of climate change effects on rainfed corn yield in central Illinois in 2055. The results show that a drier and warmer summer during the corn growth season and wetter and warmer precrop and postcrop seasons will likely occur. Greater temperature and precipitation variability may lead to more variable soil moisture and crop yield, and larger soil moisture deficit and crop yield reduction are likely to occur more frequently. The increased water stress is likely to be most pronounced during the flowering and yield formation stages. The expected rainfed corn yield in 2055 is likely to decline by 23%–34%, and the probability that the yield may not reach 50% of the potential yield ranges from 32% to 70% if no adaptation measures are instituted. Among the multiple uncertainty sources, the greenhouse gas emissions projection may have the strongest effect on the risk estimate of crop yield reduction. The effects from the various uncertainties can be offset to some degree when the uncertainties are considered jointly. An ensemble of GCMs with an equal weight may overestimate the risk of soil moisture deficits and crop yield reduction in comparison with an ensemble of GCMs with different weight determined by the root-mean-square error minimization method. The risk estimate presented in this paper implies that climate change adaptation is needed to avoid reduced corn yields and the resulting profit losses in central Illinois.

Description: Tropical thunderstorms produce large amounts of cirrus anvil clouds, which have a large effect on the climate system. Modeling of the cirrus anvil is a very important factor in the driving processes in atmospheric, climate, and radiation budget models. The current research project is focused on determining the relationships between the thunderstorm intensity and cirrus anvil characteristics of storms during the Cirrus Regional Study of Tropical Anvils and Cirrus Layers–Florida Area Cirrus Experiment (CRYSTAL-FACE). During July 2002, 19 different storms were selected for analysis. A vertical profile of reflectivity was extracted for each cell in which the maximum reflectivity, and maximum 10- and 40-dBZ height were identified. A majority of the thunderstorms in this study were single cells or isolated multicell clusters initiated from outflow boundaries or sea-breeze interactions. The results show that a general thunderstorm life cycle characteristic time sequence was determined, finding that the maximum reflectivity occurred on average 10 min after the cell first appeared in the base scan reflectivity image. The anvil origin and maximum height were found to occur approximately 10 and 25 min after maximum reflectivity, respectively. The anvil’s mean particle size was found to increase with time and decrease with altitude. The opposite relationship holds true for the particle concentration. Contour analysis has shown that the particle size increased with increased thunderstorm intensity and time after maximum reflectivity. An increase in convective core intensity corresponds to increased anvil particle concentrations early after maximum reflectivity, as was observed.

Description: This study examines 2–3-day solar irradiance forecasts with respect to their application in solar energy industries, such as yield prediction for the integration of the strongly fluctuating solar energy into the electricity grid. During cloud-free situations, which are predominant in regions and time periods focused on by the solar energy industry, aerosols are the main atmospheric parameter that determines ground-level direct and global irradiances. Therefore, for an episode of 5 months in Europe the accuracy of forecasts of the aerosol optical depth at 550 nm (AOD550) based on particle forecasts of a chemical transport model [the European Air Pollution Dispersion (EURAD) CTM] are analyzed as a first step. It is shown that these aerosol forecasts underestimate ground-based AOD550 measurements by a mean of −0.11 (RMSE = 0.20). Using these aerosol forecasts together with other remote sensing data (ground albedo, ozone) and numerical weather prediction parameters (water vapor, clouds), a prototype for an irradiance forecasting system (Aerosol-based Forecasts of Solar Irradiance for Energy Applications, AFSOL) is set up. Based on the 5-month aerosol dataset, the results are then compared with forecasts of the ECMWF model and the fifth-generation Pennsylvania State University–National Center for Atmospheric Research Mesoscale Model (MM5), with Meteosat-7 satellite data, and with ground measurements. It is demonstrated that for clear-sky situations the AFSOL system significantly improves global irradiance and especially direct irradiance forecasts relative to ECMWF forecasts (bias reduction from −26% to +11%; RMSE reduction from 31% to 19% for direct irradiance). On the other hand, the study shows that for cloudy conditions the AFSOL forecasts can lead to significantly larger forecast errors. This also justifies an increased research effort on cloud parameterization schemes, which is a topic of ongoing research. One practical solution for solar energy power plant operators in the meanwhile is to combine the different irradiance models depending on the forecast cloud cover, which leads to significant reductions in bias for the overall period.

Description: This study focuses on documenting the seasonal progression of the Asian monsoon by analyzing clouds and convection in the pre-, peak-, and postmonsoon seasons. This effort was possible as a result of the movement of Meteosat-5 over the Indian continent during the Indian Ocean Experiment (INDOEX) starting in 1998. The Meteosat-5 observations provide a unique opportunity to study in detail the daytime diurnal variability of clouds and components of the radiation budget. Hourly Meteosat-5 observations are utilized to characterize the Indian monsoon daytime cloud variability on seasonal and diurnal time scales. Distinct patterns of variability can be identified during the various stages of the monsoon cycle. The daytime (0800–1500 LST) diurnal cycle of total cloud amounts is generally flat during the premonsoon season, U shaped during peak-monsoon season, and ascending toward an afternoon peak in the postmonsoon season. Low clouds dominate the Tibetan Plateau and northern Arabian Sea while high clouds are more frequent in the southern Bay of Bengal and Arabian Sea. An afternoon peak in high clouds is most prominent in central India and the Bay of Bengal. Afternoon convection peaks earlier over water than land. Preliminary comparison of cloud amounts from Meteosat-5, International Satellite Cloud Climatology Project (ISCCP) D1, and model output from the 40-yr ECMWF Re-Analysis (ERA-40) and the NCEP–NCAR reanalysis indicates a large disparity among cloud amounts from the various sources, primarily during the peak-monsoon period. The availability of the high spatial and temporal resolution of Meteosat-5 data is important for characterizing cloud variability in regions where clouds vary strongly in time and space and for the evaluation of numerical models known to have difficulties in predicting clouds correctly in this monsoon region. This study also has implications for findings on cloud variability from polar-orbiting satellites that might not correctly represent the daily average situation.

Description: The aim of this study was to identify clear air boundaries and to obtain spatial distribution of convective areas associated with the sea breeze over the Iberian Mediterranean zone and the isle of Mallorca, both in Spain. Daytime Advanced Very High Resolution Radiometer (AVHRR) data from National Oceanic and Atmospheric Administration (NOAA) polar-orbiting satellites were collected for May–October 2004. A cloud detection algorithm was used to identify clouds to derive daytime sea-breeze cloud frequency composites over land. The high-resolution composites aided in identifying the location of five preferential sea-breeze convergence zones (SBCZ) in relation to the shape of coastline and orographic effects. Additionally, eight regimes were designated using mean boundary layer wind speed and direction to provide statistics about the effect of prevailing large-scale flows on sea-breeze convection over the five SBCZ. The offshore SW to W and the NW to N regimes were characterized by high cloud frequencies parallel to the coast. Small differences in mean cloud frequency values from morning to afternoon composites were detected with these regimes because sea-breeze fronts tended to form early and persist into the afternoon. Just the opposite occurred under the onshore NE to E and SE to S regimes. It was found that light to moderate (≤5.1 m s−1) winds aloft result in more clouds at the leading edge of sea breezes. In contrast, strong synoptic-scale (〉5.1 m s−1) flows weaken boundary layer convergence. The results from this satellite meteorology study could have practical applications for many people including those that forecast the weather and those that use the forecast for making decisions related to energy use, fishing, recreation, or agriculture activities, as well as for estimating pollution or issuing warnings for heavy rain or flash flooding.

Description: The authors present a combination of different statistical methods for the validation of climate simulation data with respect to observational data of the same spatial and temporal coverage. It is assumed that simulated data and observed data are both given as time series at locations such as grid cells or station locations. The aim of this approach is to quantify the agreement between the two spatial structures of observed and simulated data. These spatial structures consist of the spatial distributions of clusters (obtained from a cluster analysis) that contain climatologically similar locations. If the spatial distribution of clusters were identical for the observed and the simulated data, the simulation would describe the spatial structure of the observations perfectly. Differences from this ideal situation can be objectively quantified using the κ statistic. If the simulation data have shortcomings, the different κ variants can be used to diagnose where these are located. The method is demonstrated using simulation data from the Statistical Regional Model (STAR) for Germany. The combination of cluster analysis and κ statistic proves to be an excellent tool for quantifying the spatial correctness of climate models that can be extended to multimodel comparisons. It can thereby serve as a standard measure for climate model evaluation.

Description: A climatology of nocturnal low-level jets (LLJs) is presented for the topographically flat measurement site at Cabauw, the Netherlands. LLJ characteristics are derived from a 7-yr half-hourly database of wind speed profiles, obtained from the 200-m mast and a wind profiler. Many LLJs at Cabauw originate from an inertial oscillation, which develops after sunset in a layer decoupled from the surface by stable stratification. The data are classified to different types of stable boundary layers by using the geostrophic wind speed and the isothermal net radiative cooling as classification parameters. For each of these classes, LLJ characteristics like frequency of occurrence, height above ground level, and the turning of the wind vector across the boundary layer are determined. It is found that LLJs occur in about 20% of the nights, are typically situated at 140–260 m above ground level, and have a speed of 6–10 m s−1. Development of a substantial LLJ is most likely to occur for moderate geostrophic forcing and a high radiative cooling. A comparison with the 40-yr ECMWF Re-Analysis (ERA-40) is added to illustrate how the results can be used to evaluate the performance of atmospheric models.

Description: Reflected solar radiation measured by the Medium Resolution Imaging Spectrometer (MERIS) on the Environmental Satellite (Envisat) is currently used within the European Space Agency’s ground segment for the retrieval of cloud-top pressure. The algorithm is based on the analysis of the gaseous absorption of solar radiation in the oxygen A band at 761 nm. The strength of absorption is directly related to the average photon pathlength, which is mainly determined by the cloud-top pressure. However, it additionally depends on surface and cloud properties, like cloud thickness and microphysics. The interpretation of the measurements is further complicated by the temperature dependence of the absorption line shapes and the sensitivity to the spectral properties of the spectrometer like spectral position and width. This paper is focused on results of sensitivity studies using the Matrix Operator Model (MOMO) radiative transfer model that examine the most important parameters affecting the measurements of MERIS or similar instruments. The cloud-top pressure retrieval scheme is briefly presented. An analysis of the information content and the degrees of freedom of measurements within the oxygen A band is included in this study.

Description: A novel approach is presented to objectively identify regional patterns of climate variability within the state of California using principal component analysis on monthly precipitation and temperature data from a network of 195 climate stations statewide and an ancillary gridded database. The confluence of large-scale circulation patterns and the complex geography of the state result in 11 regional modes of climate variability within the state. A comparison between the station and gridded analyses reveals that finescale spatial resolution is needed to adequately capture regional modes in complex orographic and coastal settings. Objectively identified regions can be employed not only in tracking regional climate signatures, but also in improving the understanding of mechanisms behind regional climate variability and climate change. The analysis has been incorporated into an operational tool called the California Climate Tracker.

Description: Differences between satellite-derived and ground-based values of cloud liquid water path (LWPsat and LWPgr, respectively) in validation studies are partly associated with the validation itself, in particular with scale differences and parallax. This paper aims at establishing standards for validation procedures to minimize these contributions to the differences. To investigate this, LWP values were collected as computed from ground-based microwave radiometer (MWR) summer measurements made at two Cloudnet sites and from the spaceborne Spinning Enhanced Visible and Infrared Imager (SEVIRI) instrument. The large number of all-sky sample pairs (∼2500 after selection) formed an essential condition for the present study. The best validation method was determined by optimum statistical agreement between LWPsat and LWPgr. The method consists of (i) computation of LWPsat by averaging LWP over the pixels surrounding the ground station by means of a Gaussian weight function with a length scale defining the validation area, (ii) computation of LWPgr by averaging the MWR measurements with a Gaussian weight function, by using a time scale that is considerably longer than the time in which the clouds move across the validation area (by a factor of 3–15), and (iii) correcting for parallax. The authors argue that the best length scale for averaging the satellite data is equal to the image resolution. The improvement resulting from the parallax correction was significant at the 99.5% level, but its effect was not significant for a subset of the data for relatively homogeneous cloud fields. Also, there was no significant improvement when, instead of taking a constant, the time scale for averaging the ground data was adjusted to the instantaneous wind field.

Description: This study uses regression analysis to evaluate the relationships among sea surface temperature anomalies (SSTA) averaged over the Niño-3.4 region (5°N–5°S, 120°–170°W), rainfall, and rice production, area harvested, and yield in Luzon, the large island on which most Philippine rice is grown. Previous research on Philippine rice production and El Niño–Southern Oscillation (ENSO) has found negative associations between El Niño events and rice yields in rainfed systems. This analysis goes further and shows that both irrigated and rainfed ecosystems are impacted. It also compares impacts on area harvested and yield. Variations in average July–September Niño-3.4 SSTAs explain approximately 29% of the interannual variations in the deviations of total January–June (dry season) rice production from a polynomial trend for 1970–2005. In contrast, no impact was found on July–December production in either year t or t + 1. The impact of ENSO on dry-season rice production in Luzon appears to be primarily due to changes in area harvested rather than yield. Production declines for rainfed ecosystems are relatively larger than for irrigated ecosystems: a 1°C increase in average July–September Niño-3.4 SSTA is associated with a 3.7% decrease in irrigated dry-season production but with a 13.7% decline in rainfed dry-season production.

Description: The spatial variability and temporal variability of precipitation are widely recognized. In particular, rainfall rates can fluctuate widely in regions where the raindrops are clustered and where mean conditions are changing (statistical heterogeneity). Indeed, at times, the ambiguity associated with an estimated average rainfall rate may become very large. Therefore, in quantitative measurements of precipitation, it would be useful to identify where this occurs. In this work a technique is proposed and applied to quantify the variability in rainfall rates introduced by statistical heterogeneity and raindrop clustering using deviations from Rayleigh statistics of intensity fluctuations. This technique separates the Rayleigh contributions to the observed relative dispersion from those arising from clustering and statistical heterogeneities. Applications to conventional meteorological radar measurements are illustrated using two scans. Often, but not always, the greatest ambiguities in estimates of the average rainfall rate occur just where the rainfall rates are the largest and presumably where accurate estimates are most important. This ambiguity is not statistical; rather, it indicates the presence of important sub-beam-scale fluctuations. As a consequence, no single average value can be applied uniformly to the entire domain. The examples provided here also demonstrate that the appropriate observations are feasible using current conventional meteorological radars with adequate processing capabilities. However, changes in radar technology that improve and increase pulse-to-pulse statistical independence will permit such observations to be gathered more routinely at finer spatial resolution and with enhanced precision.

Description: The Oklahoma Dispersion Model (ODM) represents a current innovative application of the classic Gaussian plume model in an operational setting. Utilizing a statewide mesoscale automated weather station network (the Oklahoma Mesonet) for current weather conditions and 60-h gridded Nested Grid Model (NGM) model output statistics (MOS) forecasts for future conditions, the ODM is an Internet-based management tool that can be used to qualitatively assess current and future atmospheric dispersion conditions across Oklahoma for near-surface releases of gases and small particulates. The ODM is designed to qualitatively assess concentrations at ground level near the plume centerline at downwind distances of up to 4000 m. The Gaussian plume model is used in conjunction with rural Briggs sigma-y and sigma-z coefficients to estimate horizontal and vertical dispersion. Pasquill stability class is calculated in two ways: for current conditions, Oklahoma Mesonet weather data are used in conjunction with algorithms recommended by the Environmental Protection Agency; for forecast conditions, the Turner method is used. A method is employed that breaks the atmosphere into six dispersion categories, ranging from excellent to very poor. The ODM generates both graphical and text output. Statewide colored maps showing current conditions for dispersion (dilution of plume) and transport (direction of plume movement) are generated every 15 and 5 min, respectively. Similar maps for future conditions are generated every 12 h using gridded 60-h NGM MOS forecasts. In addition to graphical output, tabular output for future conditions at specific MOS locations is available. The ODM has been used as a management tool in the agriculture and natural resources arenas in conjunction with prescribed burning (smoke), pesticide application, and odors associated with animal agriculture.

Description: An updated and expanded version of the Carbon Bond mechanism (CB05) has been incorporated into the Community Multiscale Air Quality (CMAQ) modeling system to more accurately simulate wintertime, pristine, and high-altitude situations. The CB05 mechanism has nearly 2 times the number of reactions relative to the previous version of the Carbon Bond mechanism (CB-IV). While the expansions do provide more detailed treatment of urban areas, most of the new reactions involve biogenics, toxics, and species potentially important to particulate formation and acid deposition. Model simulations were performed using the CB05 and the CB-IV mechanisms for the winter and summer of 2001. For winter with the CB05 mechanism, ozone, aerosol nitrate, and aerosol sulfate concentrations were within 1% of the results obtained with the CB-IV mechanism. Organic carbon concentrations were within 2% of the results obtained with the CB-IV mechanism. However, formaldehyde and hydrogen peroxide concentrations were lower by 25% and 32%, respectively, during winter with the CB05 mechanism. For the summer, ozone concentrations increased by 8% with the CB05 mechanism relative to the CB-IV mechanism. The aerosol sulfate, aerosol nitrate, and organic carbon concentrations with the CB05 mechanism decreased by 8%, 2%, and 10%, respectively. The formaldehyde and hydrogen peroxide concentrations with the CB05 mechanism were lower by 12% and 47%, respectively, during summer. Model performance with the CB05 mechanism improved at high-altitude conditions and in rural areas for ozone. Model performance also improved for organic carbon with the CB05 mechanism.

Description: Two statistical methods for predicting the number of tropical cyclones (TCs) making landfall on sections of the North American coastline are compared. The first method—the “local model”—is derived exclusively from historical landfalls on the particular coastline section. The second method—the “track model”—involves statistical modeling of TC tracks from genesis to lysis, and is based on historical observations of such tracks. Identical scoring schemes are used for each model, derived from the out-of-sample likelihood of a Bayesian analysis of the Poisson landfall number distribution. The track model makes better landfall rate predictions on most coastal regions, when coastline sections at a scale of several hundred kilometers or smaller are considered. The reduction in sampling error due to the use of the much larger dataset more than offsets any bias in the track model. When larger coast sections are considered, there are more historical landfalls, and the local model scores better. This is the first clear justification for the use of track models for the assessment of TC landfall risk on regional and smaller scales.

Description: This paper investigates the formation mechanisms for a local wind phenomenon known as Washoe Zephyr that occurs frequently in the lee of the Sierra Nevada. Unlike the typical thermally driven slope flows with upslope wind during daytime and downslope at night, the Washoe Zephyr winds blow down the lee slopes of the Sierra Nevada in the afternoon against the local pressure gradient. Long-term hourly surface wind data from several stations on the eastern slope of the Sierra Nevada and rawinsonde sounding data in the region are analyzed and numerical simulations are performed to test the suggested hypotheses on the formation mechanisms for this interesting phenomenon. The results from surface and upper-air climate data analyses and numerical modeling indicate that the Washoe Zephyr is primarily a result of a regional-scale pressure gradient that develops because of asymmetric heating of the atmosphere between the western side of the Sierra Nevada and the elevated, semiarid central Nevada and Great Basin on the eastern side of the Sierra Nevada. The frequent influence of the Pacific high on California in the summer season helps to enhance this pressure gradient and therefore strengthen the flow. Westerly synoptic-scale winds over the Sierra Nevada and the associated downward momentum transfer are not necessary for its development, but strong westerly winds aloft work in concert with the regional-scale pressure gradient to produce the strongest Washoe Zephyr events.

Description: 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.

Description: A method to retrieve total vertical amounts of cloud liquid and ice in stratiform precipitating systems is described. The retrievals use measurements from the vertically pointing Ka- and W-band cloud radars operated by the U.S. Department of Energy Atmospheric Radiation Measurement (ARM) Program and auxiliary measurements from a scanning National Weather Service radar and a ground-based disdrometer. Separation between the cloud liquid and rain is based on estimations of the total attenuation of millimeter-wavelength radar signals in the liquid hydrometeor layer. Disdrometer measurements are used for the retrieval constraints. Because the liquid phase hydrometeor retrievals use only differential measurements, they are immune to the absolute radar calibration uncertainties. Estimates of the ice cloud phase are performed using empirical relations between absolute radar reflectivity and ice water content. Data from the nearby scanning weather-service radar, which operates at a lower frequency, are used to correct cloud radar measurements observed above the freezing level for attenuation caused by the layers of liquid and melting hydrometeors and also by wet radomes of cloud radars. Polarimetric and vertical Doppler measurements from ARM cloud radars provide a distinct separation between regions of liquid and ice phases, and therefore the corresponding retrievals are performed in each region separately. The applicability of the suggested method is illustrated for a stratiform precipitation event observed at the ARM Southern Great Plains facility. Expected uncertainties for retrievals of cloud liquid water path are estimated at about 200–250 g m−2 for typical rainfall rates observed in stratiform systems (∼3–4 mm h−1). These uncertainties increase as rainfall rate increases. The ice water path retrieval uncertainties can be as high as a factor of 2.

Description: Seasonal streamflow forecasts contingent on climate information are essential for short-term planning (e.g., water allocation) and for setting up contingency measures during extreme years. However, the water allocated based on the climate forecasts issued at the beginning of the season needs to be revised using the updated climate forecasts throughout the season. In this study, reservoir inflow forecasts downscaled from monthly updated precipitation forecasts from ECHAM4.5 forced with “persisted” SSTs were used to improve both seasonal and intraseasonal water allocation during the October–February season for the Angat reservoir, a multipurpose system, in the Philippines. Monthly updated reservoir inflow forecasts are ingested into a reservoir simulation model to allocate water for multiple uses by ensuring a high probability of meeting the end-of-season target storage that is required to meet the summer (March–May) demand. The forecast-based allocation is combined with the observed inflows during the season to estimate storages, spill, and generated hydropower from the system. The performance of the reservoir is compared under three scenarios: forecasts issued at the beginning of the season, monthly updated forecasts during the season, and use of climatological values. Retrospective reservoir analysis shows that the operation of a reservoir by using monthly updated inflow forecasts reduces the spill considerably by increasing the allocation for hydropower during above-normal-inflow years. During below-normal-inflow years, monthly updated streamflow forecasts could be effectively used for ensuring enough water for the summer season by meeting the end-of-season target storage. These analyses suggest the importance of performing experimental reservoir analyses to understand the potential challenges and opportunities in improving seasonal and intraseasonal water allocation by using real-time climate forecasts.

Description: A number of Earth remote sensing satellites are currently carrying passive microwave radiometers. A variety of different retrieval algorithms are used to estimate surface rain rates over the ocean from the microwave radiances observed by the radiometers. This study compares several different satellite algorithms with each other and with independent data from rain gauges on ocean buoys. The rain gauge data are from buoys operated by the NOAA Pacific Marine Environmental Laboratory. Potential errors and biases in the gauge data are evaluated. Satellite data are from the Tropical Rainfall Measuring Mission Microwave Imager and from the Special Sensor Microwave Imager instruments on the operational Defense Meteorological Satellite Program F13, F14, and F15 satellites. These data have been processed into rain-rate estimates by the NASA Precipitation Measurement Mission and by Remote Sensing Systems, Inc. Biases between the different datasets are estimated by computing differences between long-term time averages. Most of the satellite datasets agree with each other, and with the gauge data, to within 10% or less. The biases tend to be proportional to the mean rain rate, but the geographical patterns of bias vary depending on the choice of data source and algorithm. Some datasets, however, show biases as large as about 25%, so care should be taken when using these data for climatological studies.

Description: The Bollène-2002 Experiment was aimed at developing the use of a radar volume-scanning strategy for conducting radar rainfall estimations in the mountainous regions of France. A developmental radar processing system, called Traitements Régionalisés et Adaptatifs de Données Radar pour l’Hydrologie (Regionalized and Adaptive Radar Data Processing for Hydrological Applications), has been built and several algorithms were specifically produced as part of this project. These algorithms include 1) a clutter identification technique based on the pulse-to-pulse variability of reflectivity Z for noncoherent radar, 2) a coupled procedure for determining a rain partition between convective and widespread rainfall R and the associated normalized vertical profiles of reflectivity, and 3) a method for calculating reflectivity at ground level from reflectivities measured aloft. Several radar processing strategies, including nonadaptive, time-adaptive, and space–time-adaptive variants, have been implemented to assess the performance of these new algorithms. Reference rainfall data were derived from a careful analysis of rain gauge datasets furnished by the Cévennes–Vivarais Mediterranean Hydrometeorological Observatory. The assessment criteria for five intense and long-lasting Mediterranean rain events have proven that good quantitative precipitation estimates can be obtained from radar data alone within 100-km range by using well-sited, well-maintained radar systems and sophisticated, physically based data-processing systems. The basic requirements entail performing accurate electronic calibration and stability verification, determining the radar detection domain, achieving efficient clutter elimination, and capturing the vertical structure(s) of reflectivity for the target event. Radar performance was shown to depend on type of rainfall, with better results obtained with deep convective rain systems (Nash coefficients of roughly 0.90 for point radar–rain gauge comparisons at the event time step), as opposed to shallow convective and frontal rain systems (Nash coefficients in the 0.6–0.8 range). In comparison with time-adaptive strategies, the space–time-adaptive strategy yields a very significant reduction in the radar–rain gauge bias while the level of scatter remains basically unchanged. Because the Z–R relationships have not been optimized in this study, results are attributed to an improved processing of spatial variations in the vertical profile of reflectivity. The two main recommendations for future work consist of adapting the rain separation method for radar network operations and documenting Z–R relationships conditional on rainfall type.

Description: The characterization of high clouds as performed from selected spaceborne observations is assessed in this article by employing a number of worldwide ground-based lidar multiyear datasets as reference. Among the latter, the ground lidar observations conducted at Lannion, Bretagne (48.7°N, 3.5°W), and Palaiseau, near Paris [the Site Instrumental de Recherche par Télédétection Atmosphérique (SIRTA) observatory: 48.7°N, 2.2°E], both in France, are discussed in detail. High-cloud altitude statistics at these two sites were found to be similar. Optical thicknesses disagree, and possible reasons were analyzed. Despite the variety of instruments, observation strategies, and methods of analysis employed by different lidar groups, high-cloud optical thicknesses from the Geoscience Laser Altimeter System (GLAS) on board the Ice, Cloud and land Elevation Satellite (ICESat) were found to be consistent on the latitude band 40°–60°N. Respective high-cloud altitudes agree within 1 km with respect to those from ground lidars at Lannion and Palaiseau; such a finding remains to be verified under other synoptic regimes. Mean altitudes of high clouds from Lannion and Palaiseau ground lidars were compared with altitudes of thin cirrus from the Television and Infrared Observation Satellite (TIROS) Operational Vertical Sounder (TOVS) Path-B 8-yr climatology for a common range of optical thicknesses (0.1–1.4). Over both sites, the annual altitude distribution of thin high clouds from TOVS Path-B is asymmetric, with a peak around 8–9.5 km, whereas the distribution of high clouds retrieved from ground lidars seems symmetric with a peak around 9.5–11.5 km. Additional efforts in standardizing ground lidar observation and processing methods, and in merging high-cloud statistics from complementary measuring platforms, are recommended.

Description: Electric-field measurements made in and near clouds during two airborne field programs are presented. Aircraft equipped with multiple electric-field mills and cloud physics sensors were flown near active convection and into thunderstorm anvil and debris clouds. The magnitude of the electric field was measured as a function of position with respect to the cloud edge to provide an observational basis for modifications to the lightning launch commit criteria (LLCC) used by the U.S. space program. These LLCC are used to reduce the risk that an ascending launch vehicle will trigger a lightning strike that could cause the loss of the mission or vehicle. Even with fields of tens of kV m−1 inside electrically active convective clouds, the fields external to these clouds decay to less than 3 kV m−1 within 15 km of cloud edge. Fields that exceed 3 kV m−1 were not found external to anvil and debris clouds.

Description: Boundary layer wind data observed by a Doppler lidar and sonic anemometers during the mornings of three intensive observational periods (IOP2, IOP3, and IOP7) of the Joint Urban 2003 (JU2003) field experiment are analyzed to extract the mean and turbulent characteristics of airflow over Oklahoma City, Oklahoma. A strong nocturnal low-level jet (LLJ) dominated the flow in the boundary layer over the measurement domain from midnight to the morning hours. Lidar scans through the LLJ taken after sunrise indicate that the LLJ elevation shows a gradual increase of 25–100 m over the urban area relative to that over the upstream suburban area. The mean wind speed beneath the jet over the urban area is about 10%–15% slower than that over the suburban area. Sonic anemometer observations combined with Doppler lidar observations in the urban and suburban areas are also analyzed to investigate the boundary layer turbulence production in the LLJ-dominated atmospheric boundary layer. The turbulence kinetic energy was higher over the urban domain mainly because of the shear production of building surfaces and building wakes. Direct transport of turbulent momentum flux from the LLJ to the urban street level was very small because of the relatively high elevation of the jet. However, since the LLJ dominated the mean wind in the boundary layer, the turbulence kinetic energy in the urban domain is correlated directly with the LLJ maximum speed and inversely with its height. The results indicate that the jet Richardson number is a reasonably good indicator for turbulent kinetic energy over the urban domain in the LLJ-dominated atmospheric boundary layer.

Description: Two models have been developed to predict airflow and dispersion in urban environments. The first model, the Realistic Urban Spread and Transport of Intrusive Contaminants (RUSTIC) model, is a fast-running urban airflow code that rapidly converges to a numerical solution of a modified set of the compressible Navier–Stokes equations. RUSTIC uses the k–ω turbulence model with a buoyancy production term to handle atmospheric stability effects. The second model, “MESO,” is a Lagrangian particle transport and dispersion code that predicts concentrations of a released chemical or biological agent in urban or rural areas. As a preliminary validation of the models, concentrations simulated by MESO are compared with experimental data from wind-tunnel testing of dispersion around both a multistory rectangular building and a single-story L-shaped building. For the rectangular building, trace gas is forced out at the base of the downwind side, whereas for the L-shaped building, trace gas is forced out of a side door in the inner corner of the “L.” The MESO–RUSTIC combination is set up with the initial conditions of the wind-tunnel experiment, and the steady-state concentrations simulated by the models are compared with the wind-tunnel data. For the multistory building, a dense set of detector locations was available downwind at ground level. For the L-shaped building, concentration data were available at three heights in a lateral plane at a distance of one building height downwind of the lee side. A favorable comparison between model simulations and test data is shown for both buildings.

Description: This paper demonstrates that the split-window approach for estimating cloud properties can improve upon the methods commonly used for generating cloud temperature and emissivity climatologies from satellite imagers. Because the split-window method provides cloud properties that are consistent for day and night, it is ideally suited for the generation of a cloud climatology from the Advanced Very High Resolution Radiometer (AVHRR), which provides sampling roughly four times per day. While the split-window approach is applicable to all clouds, this paper focuses on its application to cirrus (high semitransparent ice clouds), where this approach is most powerful. An optimal estimation framework is used to extract estimates of cloud temperature, cloud emissivity, and cloud microphysics from the AVHRR split-window observations. The performance of the split-window approach is illustrated through the diagnostic quantities generated by the optimal estimation approach. An objective assessment of the performance of the algorithm cloud products from the recently launched space lidar [Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation/Cloud-Aerosol Lidar with Orthogonal Polarization (CALIPSO/CALIOP)] is used to characterize the performance of the AVHRR results and also to provide the constraints needed for the optimal estimation approach.

Description: Temperature and wind data from a rural micronet and nearby site of the Oklahoma Mesonet are analyzed to study the frequency, strength, and formation processes of cold-pool events in a region with gentle terrain. Spatial analyses were performed for a 2-yr-long temperature record from 26 temperature/humidity surface stations, deployed across a 120 m × 320 m micronet located in a region of gently sloped terrain with maximum elevation changes of ∼25 m. Cold pools frequently formed at the base of a gentle slope in a small depression of only ∼6-m depth that is also sheltered by trees. The strength of each cold-pool event was classified according to a cold-pool index based on average nocturnal temperature perturbations within the cold-pool region. Wind data collected with sonic anemometers on a 15-m-tall tower at the micronet for a period of three months (spring 2005) suggest that flow sheltering by vegetation plays an important role in the cold-pool formation. The wind data also show signatures of katabatic flow for about 50% of the strong cold-pool events. However, a heat budget analysis for these nights suggested that the katabatic flows were associated with warm-air advection along the slope and that if katabatic jets had penetrated the cold pool, they would have produced substantial warming in the region of the cold pool. Since such warming was not observed, it is concluded that the katabatic jets did not actually penetrate the cold pool but likely flowed over it. An analysis of Richardson numbers demonstrates that cold-pool formation frequently occurs under strongly stable conditions that tend to suppress vertical turbulent mixing in the surface layer. Observations that significant temperature changes can occur even with elevation changes on the order of 6 m have important implications in agriculture as well as in data assimilation.

Description: This paper presents the hydrological component of the Submesoscale Soil Model, urbanized version (SM2-U). This model is an extension of the rural Interactions between Soil, Biosphere, and Atmosphere (ISBA) soil model to urban surfaces. It considers in detail both rural and urban surfaces. Its purpose is to compute the sensible heat and humidity fluxes at the canopy–atmosphere interface for the computational domain lower boundary condition of atmospheric mesoscale models in order to simulate the urban boundary layer in any weather conditions. Because it computes separately the surface temperature of each land use cover mode while the original model computes a unique temperature for the soil and vegetation system, the new version is first validated for rural grounds by comparison with experimental data from the Hydrological Atmospheric Pilot Experiment-Modélisation du Bilan Hydrique (HAPEX-MOBILHY) and the European Field Experiment in a Desertification Threatened Area (EFEDA). The SM2-U water budget is then evaluated on the experimental data obtained at a suburban site in the Nantes urban area (Rezé, France), both on an annual scale and for two stormy events. SM2-U evaluates correctly the water flow measured in the drainage network (DN) at the annual scale and for the summer storm. As for the winter storm, when the soil is saturated, the simulation shows that water infiltration from the soil to the DN must be taken care of to evaluate correctly the DN flow. Yet, the addition of this soil water infiltration to the DN does not make any difference in the simulated surface fluxes that are the model outputs for simulating the urban boundary layer. Urban hydrological parameters are shown to largely influence the available water on artificial surfaces for evaporation and to influence less the evapotranspiration from natural surfaces. The influence of the water budget and surface structure on the suburban site local climatology is demonstrated.

Description: Polarimetric radar measurements are used to retrieve drop size distributions (DSD) in subtropical thunderstorms. Retrievals are made with the single-moment exponential drop size model of Marshall and Palmer driven by radar reflectivity measurements and with a two-parameter constrained-gamma drop size model that utilizes reflectivity and differential reflectivity. Results are compared with disdrometer observations. Retrievals with the constrained-gamma DSD model gave better representation of total drop concentration, liquid water content, and drop median volume diameter and better described their natural variability. The Marshall–Palmer DSD model, with a fixed intercept parameter, tended to underestimate the total drop concentration in storm cores and to overestimate significantly the concentration in stratiform regions. Rainwater contents in strong convection were underestimated by a factor of 2–3, and drop median volume diameters in stratiform rain were underestimated by 0.5 mm. To determine possible DSD model impacts on numerical forecasts, evaporation and accretion rates were computed using Kessler-type parameterizations. Rates based on the Marshall–Palmer DSD model were lower by a factor of 2–3 in strong convection and were higher by about a factor of 2 in stratiform rain than those based on the constrained-gamma model. The study demonstrates the potential of polarimetric radar measurements for improving the understanding of precipitation processes and microphysics parameterization in numerical forecast models.

Description: A variety of atmospheric boundary layer parameters are examined as a function of wind direction in both urban and suburban settings in Oklahoma City, Oklahoma, derived from measurements during the Joint Urban 2003 field campaign. Heterogeneous surface characteristics result in significant differences in upwind fetch and, therefore, statistically significant differences in measured values, even for small changes in wind direction. Taller upwind obstructions yield larger measured values of drag coefficient and turbulence intensity than do shorter upwind obstructions regardless of whether the obstruction is a building or a tree. The fraction of turbulent kinetic energy going into streamwise, cross-stream, and vertical variances differs depending on the upwind fetch, and reduced cross-stream values may indicate locations of persistent wind stream convergence. In addition, a quadrant analysis of burst/sweep behavior near the surface is examined as a function of wind direction in urban and suburban environments.

Description: Into the Community Multiscale Air Quality modeling system (CMAQ) that is widely used for simulating the transport and fate of air pollutants, a new module was inserted that accounts for the partitioning of semivolatile organic compounds—in particular, polycyclic organic hydrocarbons (PAHs)—between the gaseous and the particulate phases. This PAH version of CMAQ can at this time be applied to substances that are predominantly associated with particles and can be assumed to be inert, as is the case for benzo(a)pyrene [B(a)P]. The model was set up for Europe on a grid with 54-km cell width with a nest of 18-km gridcell width located around the North Sea to simulate ambient air concentrations and depositions of B(a)P in January, April, July, and October 2000. To evaluate the quality of the simulation results, daily and monthly mean concentrations were compared with measurements from six monitoring stations. The typical ratio of modeled to measured values is circa 4 (median), which—with respect to both measurement and simulation uncertainties and problems involved when comparing measurements with simulations—proved that the PAH version of CMAQ is suitable to simulate the fate and transport of B(a)P over Europe and can serve as a starting point for models for other PAHs that additionally consider degradation.

Description: Because of a lack of regular, direct measurements, little information is available about the frequency and spatial and temporal distribution of icing conditions aloft, including supercooled large drops (SLD). Research aircraft provide in situ observations of these conditions, but the sample set is small and can be biased. Other techniques must be used to create a more unbiased climatology. The presence and absence of icing and SLD aloft can be inferred using surface weather observations in conjunction with vertical profiles of temperature and moisture. In this study, such a climatology was created using 14 yr of coincident, 12-hourly Canadian and continental U.S. surface weather reports and balloonborne soundings. The conditions were found to be most common along the Pacific Coast from Alaska to Oregon, and in a large swath from the Canadian Maritimes to the Midwest. Prime locations migrated seasonally. Most SLD events appeared to occur below 4 km, were less than 1 km deep, and were formed via the collision–coalescence process.

Description: Wind is the world’s fastest growing electric energy source. Because it is intermittent, though, wind is not used to supply baseload electric power today. Interconnecting wind farms through the transmission grid is a simple and effective way of reducing deliverable wind power swings caused by wind intermittency. As more farms are interconnected in an array, wind speed correlation among sites decreases and so does the probability that all sites experience the same wind regime at the same time. The array consequently behaves more and more similarly to a single farm with steady wind speed and thus steady deliverable wind power. In this study, benefits of interconnecting wind farms were evaluated for 19 sites, located in the midwestern United States, with annual average wind speeds at 80 m above ground, the hub height of modern wind turbines, greater than 6.9 m s−1 (class 3 or greater). It was found that an average of 33% and a maximum of 47% of yearly averaged wind power from interconnected farms can be used as reliable, baseload electric power. Equally significant, interconnecting multiple wind farms to a common point and then connecting that point to a far-away city can allow the long-distance portion of transmission capacity to be reduced, for example, by 20% with only a 1.6% loss of energy. Although most parameters, such as intermittency, improved less than linearly as the number of interconnected sites increased, no saturation of the benefits was found. Thus, the benefits of interconnection continue to increase with more and more interconnected sites.

Description: A detailed sensitivity analysis was conducted to help to quantify the impacts of various emission control options in terms of potential visibility improvements at class I national parks and wilderness areas in the southeastern United States. Particulate matter (PM) levels were estimated using the Community Multiscale Air Quality (CMAQ) model, and light extinctions were calculated using the modeled PM concentrations. First, likely changes in visibility at class I areas were estimated for 2018. Then, using emission projections for 2018 as a starting point, the sensitivity of light extinction was evaluated by reducing emissions from various source categories by 30%. Source categories to be analyzed were determined using a tiered approach: any category that showed significant impact in one tier was broken into subcategories for further analysis in the next tier. In the first tier, sulfur dioxide (SO2), nitrogen oxides, ammonia, volatile organic compound, and primary carbon emissions were reduced uniformly over the entire domain. During summer, when most class I areas experience their worst visibility, reduction of SO2 emissions was the most effective control strategy. In the second tier, SO2 sources were separated as ground level and elevated. The elevated sources in 10 southeastern states were differentiated from those in the rest of the domain and broken into three subcategories: coal-fired power plant (CPP), other power plant, and other than power plant [i.e., non–electric generating unit (non EGU)]. The SO2 emissions from the CPP subcategory had the largest impact on visibility at class I areas, followed by the non-EGU subcategory. In the third tier, emissions from these two subcategories were further broken down by state. Most class I areas were affected by the emissions from several states, indicating the regional nature of the haze problem. Here, the visibility responses to all of the aforementioned emission reductions are quantified and deviations from general trends are identified.

Description: Lagrangian parcel models are often used to predict the fate of airborne hazardous material releases. The atmospheric input for these integrations is typically supplied by surrounding surface and upper-air observations. However, situations may arise in which observations are unavailable and numerical model forecasts may be the only source of atmospheric data. In this study, the quality of the atmospheric forecasts for use in dispersion applications is investigated as a function of the horizontal grid spacing of the atmospheric model. The Coupled Ocean–Atmosphere Mesoscale Prediction System (COAMPS) was used to generate atmospheric forecasts for 14 separate Dipole Pride 26 trials. The simulations consisted of four telescoping one-way nested grids with horizontal spacings of 27, 9, 3, and 1 km, respectively. The 27- and 1-km forecasts were then used as input for dispersion forecasts using the Hazard Prediction Assessment Capability (HPAC) modeling system. The resulting atmospheric and dispersion forecasts were then compared with meteorological and gas-dosage observations collected during Dipole Pride 26. Although the 1-km COAMPS forecasts displayed considerably more detail than those on the 27-km grid, the RMS and bias statistics associated with the atmospheric observations were similar. However, statistics from the HPAC forecasts showed the 1-km atmospheric forcing produced more accurate trajectories than the 27-km output when compared with the dosage measurements.

Description: The Aerosol Robotic Network (AERONET) site “El Arenosillo,” equipped with a Cimel sun photometer, has been in operation since 2000. The data collected there are analyzed to establish an aerosol synoptic climatological description that is representative of the region. Different air masses and aerosol types are present over the site depending on the synoptic conditions. The frequent intrusion of dust from the Sahara Desert at El Arenosillo suggested the use of back trajectories to determine the airmass origins of other types of aerosol observed there. The focus of this study is to classify the air masses arriving at El Arenosillo by means of back-trajectory analyses and to characterize the aerosol within each type by means of the aerosol optical depth (AOD) and its spectral signature, given as the Ångström exponent (AE). The goal is to determine how aerosols observed over the station (receptor site) differ depending on source region and transport pathways. Two classification methods are used, one based on sectors and a second based on cluster analysis. The period analyzed is from 2000 to 2004. Both methods show that maritime air masses are predominant, occurring 70% of the time and having relatively low AOD (≈0.1 at 440 nm) and a wide range of AE (from about 0 to 2.0). Air masses with continental characteristics are moderately turbid and have values of AE that average ≈1.4. Air masses arriving from the south and southwest show the distinct features of the desert dust, having moderate to high values of AOD (0.30–0.35 at 440 nm) and low values of AE.

Description: The Tropical Rainfall Measuring Mission (TRMM) satellite has been used to infer distributions of intense thunderstorms. Besides the lightning measurements from TRMM, the radar reflectivities and passive microwave brightness temperatures have been used as proxies for convective vigor. This is based on large graupel or hail lofted by strong updrafts being the cause of high–radar reflectivity values aloft and extremely low brightness temperatures. This paper seeks to empirically confirm that extremely low brightness temperatures are often accompanied by large hail at the surface. The three frequencies examined (85, 37, and 19 GHz) all show an increasing likelihood of hail reports with decreasing brightness temperature. Quantification is limited by the sparsity of hail reports. Hail reports are common when brightness temperatures are below 70 K at 85 GHz, 180 K at 37 GHz, or 230 K at 19 GHz.

Description: This paper presents a review of recent natural surface mercury exchange research in the context of a new modeling framework. The literature indicates that the mercury biogeochemical flux is more dynamic than the current models predict, with interacting multimedia storage and processes. Although several natural mercury emissions models have been created and incorporated into air quality models (AQMs), none are coupled with air quality models on a mass balance basis, and all lack the capacity to explain processes that involve the transport of mercury across atmosphere–surface media concentration gradients. Existing natural mercury emission models treat the surface as both an infinite source and infinite sink for emissions and deposition, respectively, and estimate emissions through the following three pathways: soil, vegetation, and surface waters. The use of these three transport pathways, but with compartmentalized surface storage in a surface–vegetation–atmosphere transport (SVAT) resistance model, is suggested. Surface water fluxes will be modeled using a two-film diffusion model coupled to a surface water photochemical model. This updated framework will allow both the parameterization of the transport of mercury across atmosphere–surface media concentration gradients and the accumulation/depletion of mercury in the surface media. However, several key parameters need further experimental verification before the proposed modeling framework can be implemented in an AQM. These include soil organic mercury interactions, bioavailability, cuticular transport of mercury, atmospheric surface compensation points for different vegetation species, and enhanced soil diffusion resulting from pressure perturbations.

Description: Polarization radar offers the promise of much more accurate rainfall-rate R estimates than are possible from radar reflectivity factor Z alone, not only by better characterization of the drop size distribution, but also by more reliable correction for attenuation and the identification of hail. However, practical attempts to implement retrieval algorithms have been hampered by the difficulty in coping with the inherent noise in the polarization parameters. In this paper, a variational retrieval scheme is described that overcomes these problems by employing a forward model for differential reflectivity Zdr and differential phase shift ϕdp and iteratively refining the coefficient a in the relationship Z = aRb such that the difference between the forward model and the measurements is minimized in a least squares sense. Two methods are used to ensure that a varies smoothly in both range and azimuth. In range, a is represented by a set of cubic-spline basis functions; in azimuth, the retrieval at one ray is used as a constraint on the next. The result of this smoothing is that the retrieval is tolerant of random errors in Zdr of up to 1 dB and in ϕdp of up to 5°. Correction for attenuation is achieved simply and effectively by including its effects in the forward model. If hail is present then the forward model is unable to match the observations of Zdr and ϕdp simultaneously. This enables a first pass of the retrieval to be used to identify the radar pixels that contain hail, followed by a second pass in which the fraction of the Z in those gates that is due to hail is retrieved, this time with the scheme being able to forward-model both Zdr and ϕdp accurately. The scheme is tested on S-band radar data from southern England in cases of rain, spherical hail, oblate hail, and mixtures of rain and hail. It is found to be robust and stable, even in the presence of differential phase shift on backscatter.

Description: The paper describes an original method that is complementary to the radar–lidar algorithm method to characterize ice cloud properties. The method makes use of two measurements from a Doppler cloud radar (35 or 95 GHz), namely, the radar reflectivity and the Doppler velocity, to recover the effective radius of crystals, the terminal fall velocity of hydrometeors, the ice water content, and the visible extinction from which the optical depth can be estimated. This radar method relies on the concept of scaling the ice particle size distribution. An error analysis using an extensive in situ airborne microphysical database shows that the expected errors on ice water content and extinction are around 30%–40% and 60%, respectively, including both a calibration error and a bias on the terminal fall velocity of the particles, which all translate into errors in the retrieval of the density–diameter and area–diameter relationships. Comparisons with the radar–lidar method in areas sampled by the two instruments also demonstrate the accuracy of this new method for retrieval of the cloud properties, with a roughly unbiased estimate of all cloud properties with respect to the radar–lidar method. This method is being systematically applied to the cloud radar measurements collected over the three-instrumented sites of the European Cloudnet project to validate the representation of ice clouds in numerical weather prediction models and to build a cloud climatology.

Description: The sensitivity of a mesoscale model to different microphysical parameterizations is investigated for two events of precipitation in the Mediterranean region, that is, the Mesoscale Alpine Program (MAP) intensive observation periods (IOP) 2b (19–21 September 1999) and 8 (20–22 October 1999). Simulations are performed with the fifth-generation Pennsylvania State University–National Center for Atmospheric Research Mesoscale Model (MM5); the most commonly used bulk microphysical parameterization schemes are evaluated, with a particular focus on their impact on the forecast of rainfall. To evaluate the forecast skill, the verification is carried out quantitatively by using the observations recorded by a high-resolution rain gauge network during the MAP campaign. The results show that, for the surface rainfall forecast, all microphysical schemes produce a similar precipitation field and none of them perform significantly better than the others. The ability of different schemes to reproduce events with different ongoing microphysical processes is briefly discussed by comparing model simulations and knowledge of hydrometeor fields from radar observations. The vertical profiles of hydrometeors from two of the analyzed schemes show gross similarities with available radar observations. Last, the role of one of the parameterizations appearing in a typical bulk microphysical scheme, that is, the one of the snowfall speed, is evaluated in detail. Adjustments in the semiempirical relationships describing the fall speed of snow particles have a large impact, because a reduced snowfall speed enhances precipitation on the lee side of mountain ridges and diminishes it on the windward side. Anyway, this effect does not appear to be able to largely improve or reduce the forecast skill of the MM5 systematically; the impact of changes in the parameterization of the snow deposition velocity very likely depends on the dynamics of the event under investigation.

Description: Several flights were conducted by the University of Wyoming King Air near Cape Mendocino, California, during June 2004 to examine finescale features of the coastal low-level jet (CJ) that frequently forms during summer over the ocean off the West Coast of the United States. The primary goal of these flights was to measure the horizontal pressure gradient force (PGF) and hence to determine the forcing of the CJ directly. By flying a series of redundant legs on an isobaric surface, heights of the pressure surface can be obtained from radar altimeter measurements and refined position estimates from an onboard global positioning system receiver. The slope of the isobaric surface height is proportional to the PGF. Results are shown for the 22 June 2004 case study conducted to the south of Cape Mendocino. The forcing of a CJ under weak synoptic forcing and the role of the elevated terrain near Cape Mendocino are explored. Ten isobaric legs approximately 70 km in length and directed east–west were conducted near the level of the maximum CJ wind speed. The vertical structure of the CJ was obtained from sawtooth legs conducted along an east–west flight leg. Numerical simulations have been performed for this case using the fifth-generation Pennsylvania State University–National Center for Atmospheric Research Mesoscale Model (MM5) for comparison with in situ measurements. Model simulations show pressure perturbations in the vicinity of the cape as the northerly winds associated with the CJ interact with the coastal topography. Close agreement is found between in situ measurements and MM5 analyses of the various state parameters and the PGF along the east–west flight track in the lee of Cape Mendocino. Strong variation in the PGF is observed along the flight path. Large ageostrophic accelerations are present in response to the adjustment of the CJ with Cape Mendocino, reflecting the force imbalance between the observed PGF and Coriolis force.

Description: Freezing precipitation is a persistent winter weather problem that costs the United States millions of dollars annually. Costs and infrastructure disruption may be greatly reduced by ice-storm warnings issued by the National Weather Service (NWS), and by the development of climatologies that allow improved design of infrastructure elements. However, neither the NWS nor developers of climatologies have had direct measurements of ice-storm accumulations as a basis for issuing warnings and developing storm design standards. This paper describes the development of an aviation routine/special weather report (METAR/SPECI) remark that will report quantitative ice thickness at over 650 locations during ice storms using new algorithms developed for the Automated Surface Observing System (ASOS). Characteristics of the ASOS icing sensor, a field program to develop the algorithms, tests of accuracy, application of the algorithms, and sources of error are described, as is the implementation of an ice-thickness METAR/SPECI remark. The algorithms will potentially allow freezing precipitation events to be tracked with regard to ice accumulation in near–real time as they progress across the United States.

Description: The European Organisation for the Exploitation of Meteorological Satellites (EUMETSAT) currently operates three geostationary satellites: Meteosat-5, Meteosat-7, and Meteosat-8. Observations by Meteosat-5 can be combined with observations from either Meteosat-7 or Meteosat-8 to allow geostationary stereo height retrievals within the overlap area over the Indian Ocean and east Africa. This paper aims to demonstrate the capabilities of the geostationary stereophotogrammetric cloud-top height retrieval—in particular, with the new high-resolution visible channel (HRV) of Meteosat-8. Conceived as a proof-of-concept study, the retrieval was limited to four distinct cloud areas in northeast Africa. The effects of the geolocation, spatial resolution, satellite position, and acquisition time on the cloud-top height accuracy were studied. It is demonstrated that the matching accuracy is sensitive to the acquisition-time difference and spatial resolution. As a result, there is only a marginal benefit from the good spatial resolution offered by the Meteosat-8 HRV channel because of the low spatial resolution of Meteosat-5 and the poor time synchronization between the observations of the two satellites. On the contrary, the good time synchronization between Meteosat-5 and Meteosat-7 observations offsets the errors in the height assignment resulting from the relatively coarse spatial resolution, if the geolocation accuracy is locally enhanced with additional landmarks from higher-resolution images. With the geolocation correction and the newly implemented time information in the Meteosat-5 and -7 header information, the stereo cloud-top height assignment for the Meteosat-5/-7 and Meteosat-5/-8 HRV combination resulted in about the same accuracy of approximately ±1 km. For the Meteosat-5/-8 HRV combination, the time differences of up to 7.5 min preclude higher accuracy. To validate the cloud-top heights, observations by the Multiangle Imaging Spectroradiometer (MISR) and Moderate Resolution Imaging Spectroradiometer (MODIS) were used.

Description: A prototype online photolysis module has been developed for the Community Multiscale Air Quality (CMAQ) modeling system. The module calculates actinic fluxes and photolysis rates (j values) at every vertical level in each of seven wavelength intervals from 291 to 850 nm, as well as the total surface irradiance and aerosol optical depth within each interval. The module incorporates updated opacity at each time step, based on changes in local ozone, nitrogen dioxide, and particle concentrations. The module is computationally efficient and requires less than 5% more central processing unit time than using the existing CMAQ “lookup” table method for calculating j values. The main focus of the work presented here is to describe the new online module as well as to highlight the differences between the effective cross sections from the lookup-table method currently being used and the updated effective cross sections from the new online approach. Comparisons of the vertical profiles for the photolysis rates for nitrogen dioxide (NO2) and ozone (O3) from the new online module with those using the effective cross sections from a standard CMAQ simulation show increases in the rates of both NO2 and O3 photolysis.

Description: The authors’ objective was to apply the Simple Urban Energy Balance Model for Mesoscale Simulation (SUMM) to cities. Data were selected from 1-yr flux observations conducted at three sites in two cities: one site in Kugahara, Japan (Ku), and two sites in Basel, Switzerland (U1 and U2). A simple vegetation scheme was implemented in SUMM to apply the model to vegetated cities, and the surface energy balance and radiative temperature TR were evaluated. SUMM generally reproduced seasonal and diurnal trends of surface energy balance and TR at Ku and U2, whereas relatively large errors were obtained for the daytime results of sensible heat flux QH and heat storage ΔQS at U1. Overall, daytime underestimations of QH and overestimations of ΔQS and TR were common. These errors were partly induced by the poor parameterization of the natural logarithm of the ratio of roughness length for momentum to heat (κB−1); that is, the observed κB−1 values at vegetated cities were smaller than the simulated values. The authors proposed a new equation for predicting this coefficient. This equation accounts for the existence of vegetation and improves the common errors described above. With the modified formula for κB−1, simulated net all-wave radiation and TR agreed well with observed values, regardless of site and season. However, at U1, simulated QH and ΔQS were still overestimated and underestimated, respectively, relative to observed values.

Description: The retrieval of ice cloud microphysical and optical properties from satellite-based infrared observation remains a challenging research topic, partly because of the sensitivity of observed infrared radiances to many surface and atmospheric parameters that vary on fine spatial and temporal scales. In this study, the sensitivity of an infrared-based ice cloud retrieval to effective cloud temperature is investigated, with a focus on the effects of cloud-top height and geometric thickness. To illustrate the sensitivity, the authors first simulate brightness temperatures at 8.5 and 11.0 μm using the discrete ordinates radiative transfer (DISORT) model for five cloud-top heights ranging from 8 to 16 km and for varying cloud geometric thicknesses of 1, 2, 3, and 5 km. The simulations are performed across a range of visible optical thicknesses from 0.1 to 10 and ice cloud effective diameters from 30 to 100 μm. Furthermore, the effective particle size and optical thickness of ice clouds are retrieved from the Moderate Resolution Imaging Spectroradiometer (MODIS) measurements on the basis of a lookup-table approach. Specifically, the infrared brightness temperatures are simulated from the collocated Atmospheric Infrared Sounder (AIRS) level-2 product at 28 atmospheric levels and prescribed ice cloud parameters. Variations of the retrieved effective particle size and optical thickness versus cloud-top height and geometric thickness are investigated. Results show that retrievals based on the 8.5- and 11.0-μm bispectral approach are most valid for cloud-top temperatures of less than 224 K with visible optical thickness values between 2 and 5. The present retrievals are also compared with the collection-5 MODIS level-2 ice cloud product.

Description: Drought is a complex phenomenon that is difficult to accurately describe because its definition is both spatially variant and context dependent. Decision makers in local, state, and federal agencies commonly use operational drought definitions that are based on specific drought index thresholds to trigger water conservation measures and determine levels of drought assistance. Unfortunately, many state drought plans utilize operational drought definitions that are derived subjectively and therefore may not be appropriate for triggering drought responses. This paper presents an objective methodology for establishing operational drought definitions. The advantages of this methodology are demonstrated by calculating meteorological drought thresholds for the Palmer drought severity index, the standardized precipitation index, and percent of normal precipitation using both station and climate division data from Texas. Results indicate that using subjectively derived operational drought definitions may lead to over- or underestimating true drought severity. Therefore, it is more appropriate to use an objective location-specific method for defining operational drought thresholds.

Description: Asian soybean rust, caused by Phakopsora pachyrhizi, an airborne fungal pathogen, is an annual threat to U.S. soybean production. The disease is spread during the growing season by fungal spores that are transported from warm southern locations where they overwinter. Current models of long distance spore transport treat spore sources as constant emitters. However, evidence suggests that the spore escape rate depends on 1) the interaction between spores and turbulence within and above an infected canopy and 2) the filtering capacity of the canopy to trap upward-traveling spores. Accordingly, a theoretically motivated yet computationally simple forecast model for escape rate is proposed using a simple turbulence closure method and a parameterization of the canopy porosity. Preliminary escape-rate forecasts were made using the friction velocity, an estimate of initial spore concentrations inside an infected canopy, and the canopy’s leaf area distribution. Sensitivity tests were conducted to determine which biological and meteorological variables and parameters most impact modeled spore escape rates. The spore escape model was integrated with a large-scale spore transport model that was used to forecast spore deposition over U.S. soybean production regions. Preliminary results suggest that varying meteorological conditions significantly impact escape rates and the spread of the disease.

Description: Pollution aerosols acting as cloud condensation nuclei (CCN) have the potential to alter warm rain clouds via the aerosol first and second indirect effects in which they modify the cloud droplet population, cloud lifetime and size, rainfall efficiency, and radiation balance from increased albedo. For constant liquid water content, an increase in CCN concentration (NCCN) tends to produce an increased concentration of droplets with smaller diameters. This reduces the collision and coalescence rate, and thus there is a local reduction in rainfall. While this process applies to warm clouds, it does not identically carry over to mixed-phase clouds in which crystal nucleation, crystal riming, crystal versus droplet fall speed, and collection efficiency play active roles in determining precipitation amount. Sulfate-based aerosols serve as very efficient cloud nuclei but are not effective as ice-forming nuclei. In clouds where precipitation formation is dominated by the ice phase, NCCN influences precipitation growth by altering the efficiency of droplet collection by ice crystals and the fall trajectories of both droplet and crystal hydrometeors. The temporal and spatial variation in both crystal and droplet populations determines the resultant snowfall efficiency and distribution. Results of numerical simulations in this study suggest that CCN can play a significant role in snowfall production by winter, mixed-phase, cloud systems when liquid and ice hydrometeors coexist. In subfreezing conditions, a precipitating ice cloud overlaying a supercooled liquid water cloud allows growth of precipitation particles via the seeder–feeder process, in which nucleated ice crystals fall through the supercooled liquid water cloud and collect droplets. Enhanced NCCN from sulfate pollution by fossil fuel emissions modifies the droplet distribution and reduces crystal riming efficiency. Reduced riming efficiency inhibits the rate of snow growth, producing lightly rimed snow crystals that fall slowly and advect farther downstream prior to surface deposition. Simulations indicate that increasing NCCN along the orographic barrier of the Park Range in north-central Colorado results in a modification of the orographic cloud such that the surface snow water equivalent amounts are reduced on the windward slopes and enhanced on the leeward slopes. The inhibition of snowfall by pollution aerosols (ISPA) effect has significant implications for water resource distribution in mountainous terrain.

Description: Lightning data from the Pacific Lightning Detection Network (PacNet) and Lightning Imaging Sensor (LIS) on the Tropical Rainfall Measuring Mission (TRMM) satellite were compared with TRMM precipitation radar products and latent heating and hydrometeor data. Three years of data over the central North Pacific Ocean were analyzed. The data were divided into winter (October–April) and summer (June–September) seasons. During the winter, the thunderstorms were typically embedded in cold fronts associated with eastward-propagating extratropical cyclones. Summer thunderstorms were triggered by cold upper-level lows associated with the tropical upper-tropospheric trough (TUTT). Concurrent lightning and satellite data associated with the storms were averaged over 0.5° × 0.5° grid cells and a detection efficiency correction model was applied to quantify the lightning rates. The results of the data analysis show a consistent logarithmic increase in convective rainfall rate with increasing lightning rates. Moreover, other storm characteristics such as radar reflectivity, storm height, ice water path, and latent heat show a similar logarithmic increase. Specifically, the reflectivity in the mixed-phase region increased significantly with lightning rate and the lapse rate of Z decreased; both of these features are well-known indicators of the robustness of the cloud electrification process. In addition, the height of the echo tops showed a strong logarithmic correlation with lightning rate. These results have application over data-sparse ocean regions by allowing lightning-rate data to be used as a proxy for related storm properties, which can be assimilated into NWP models.

Description: Coupled and noncoupled models in a grid of 60 × 60 km2 in the eastern Asian domain have been employed to examine the effect of the direct radiative forcing of the Asian dust aerosol on meteorological fields for an intense Asian dust event observed in eastern Asia on 18–23 March 2002. The coupled model consists of the modified fifth-generation Pennsylvania State University–National Center for Atmospheric Research (NCAR) Mesoscale Model (MM5) with direct radiative forcing of the Asian dust aerosol through the NCAR Column Radiation Model and the Asian Dust Aerosol Model. The noncoupled model is MM5 without the direct radiative forcing of the Asian dust aerosol. The results indicate that the radiative cooling of the dust aerosol over the high-dust-concentration (HDC) region induces sinking motion and positive pressure perturbation near the surface, whereas the radiative warming of the aerosol near the top of the HDC layer induces rising motion and negative pressure perturbation, thereby enhancing the stable stratification in the dust layer. The induced positive pressure perturbation near the surface causes a dipole shape of the pressure perturbation field by forming a negative pressure perturbation toward the low pressure center downstream near the surface. This negative pressure perturbation is so deep and wide that the perturbation of the meteorological fields extends in the wide and deep regions away from the HDC region. The associated secondary circulation of this pressure perturbation reduces the low-level wind speed in the upstream HDC region but strengthens the downstream wind speed, resulting in reduction of dust emission in the upstream source region and downstream enhancement. Some of the dust aerosols lifted to the higher level by the synoptic rising motion are transported to the downstream direction more quickly with the upper-level strong wind, resulting in a bent-over shape of dust cloud in the downstream region with a maximum concentration near the surface and a secondary maximum in the upper level. The radiative flux convergence between these maximum dust layers produces a warm layer, thereby further enhancing the stable stratification.

Description: Urban climate experimental results from the Comprehensive Outdoor Scale Model (COSMO) were used to estimate roughness lengths for momentum and heat. Two different physical scale models were used to investigate the scale dependence of the roughness lengths; the large scale model included an aligned array of 1.5-m concrete cubes, and the small scale model had a geometrically similar array of 0.15-m concrete cubes. Only turbulent data from the unstable boundary layers were considered. The roughness length for momentum relative to the obstacle height was dependent on wind direction, but the scale dependence was not evident. Estimated values agreed well with a conventional morphometric relationship. The logarithm of the roughness length for heat relative to the obstacle height depended on the scale but was insensitive to wind direction. COSMO data were used successfully to regress a theoretical relationship between κB−1, the logarithmic ratio of roughness length for momentum to heat, and Re*, the roughness Reynolds number. Values of κB−1 associated with Re* for three different urban sites from previous field experiments were intercompared. A surprising finding was that, even though surface geometry differed from site to site, the regressed function agreed with data from the three urban sites as well as with the COSMO data. Field data showed that κB−1 values decreased as the areal fraction of vegetation increased. The observed dependency of the bulk transfer coefficient on atmospheric stability in the COSMO data could be reproduced using the regressed function of Re* and κB−1, together with a Monin–Obukhov similarity framework.

Description: In this investigation, how annual water use in the city of Phoenix, Arizona, was influenced by climatic variables between 1980 and 2004 is examined. Simple correlation coefficients between water use and annual mean temperature, total annual precipitation, and annual mean Palmer hydrological drought index values are +0.55, −0.69, −0.52, respectively, over the study period (annual water use increases with higher temperature, lower precipitation, and drought). Multivariate analyses using monthly climatic data indicate that annual water use is controlled most by the overall state of drought, autumn temperatures, and summer-monsoon precipitation. Model coefficients indicate that temperature, precipitation, and/or drought conditions certainly impact water use, although the magnitude of the annual water-use response to changes in climate was relatively low for an urban environment in which a sizable majority of residential water use is for outdoor purposes. People’s perception of the landscape’s water needs and their willingness and ability to respond to their perceptions by changing landscaping practices are probably more important than the landscape’s need for water in assessing residential water demand and the variation therein.

Description: Multiply nested urbanized mesoscale model [Coupled Ocean–Atmosphere Mesoscale Prediction System (COAMPS)] simulations of the New York–New Jersey metropolitan region are conducted for 4–11 July 2004. The simulations differ only in their specification of sea surface temperatures (SSTs) on nest 4 (1.33-km resolution) and nest 5 (0.44-km resolution). The “control SST” simulation (CONTROL-SST) uses an analyzed SST product, whereas the “New York Harbor Observing and Prediction System (NYHOPS) SST” simulation (NYHOPS-SST) uses hourly SSTs from the NYHOPS model hindcast. Upwelling-favorable (southerly) winds preceding the simulation time period and continuing for much of the first 5 days of the simulation generate cold water adjacent to the New Jersey coast and a cold eddy immediately outside of the harbor in the New York Bight. Both features are prominent in NYHOPS-SST but are not pronounced in CONTROL-SST. The upwelled water has a discernible influence on the overlying atmosphere by cooling near-surface air temperatures by approximately 1°–2°C, slowing the near-surface winds by 15%–20%, and reducing the nocturnal urban heat island effect by up to 1.3°C. At two coastal land-based sites and one overwater station, the wind speed mean bias is systematically reduced in NYHOPS-SST. During a wind shift to northwesterly on day 6 (9 July 2004) the comparatively cooler NYHOPS-SSTs impact the atmosphere over an even broader offshore area than was affected in the mean during the previous 5 days. Hence, air temperature evolution measured at the overwater site is better reproduced in NYHOPS-SST. Interaction of the offshore flow with the cool SSTs in NYHOPS-SST induces internal boundary layer (IBL) formation, sustained and deepened by turbulent kinetic energy advected from adjacent land areas; IBL formation did not occur in CONTROL-SST.

Description: The observed scatter of observations about air quality model predictions stems from a combination of naturally occurring stochastic variations that are impossible for any model to simulate explicitly and variations arising from limitations in knowledge and from imperfect input data. In this paper, historical tracer experiments of atmospheric dispersion were analyzed to develop algorithms to characterize the observed stochastic variability in the ground-level crosswind concentration profile. The algorithms were incorporated into a Lagrangian puff model (“INPUFF”) so that the consequences of variability in the dispersion could be simulated using Monte Carlo methods. The variability in the plume trajectory was investigated in a preliminary sense by tracking the divergence in trajectories from releases adjacent to the actual release location. The variability in the near-centerline concentration values not described by the Gaussian crosswind profile was determined to be on the order of a factor of 2. The variability in the trajectory was determined as likely to be larger than the plume width, even with local wind observations for use in characterizing the transport. Two examples are provided to illustrate how estimates of variability 1) can provide useful information to inform decisions for emergency response and 2) can provide a basis for sound statistical designs for model performance assessments.

Description: This study presents a first attempt to address the propagation of radar rainfall nowcasting errors to flood forecasts in the context of distributed hydrological simulations over a range of catchment sizes or scales. Rainfall forecasts with high spatiotemporal resolution generated from observed radar fields are used as forcing to a fully distributed hydrologic model to issue flood forecasts in a set of nested subbasins. Radar nowcasting introduces errors into the rainfall field evolution that result from spatial and temporal changes of storm features that are not captured in the forecast algorithm. The accuracy of radar rainfall and flood forecasts relative to observed radar precipitation fields and calibrated flood simulations is assessed. The study quantifies how increases in nowcasting errors with lead time result in higher flood forecast errors at the basin outlet. For small, interior basins, rainfall forecast errors can be simultaneously amplified or dampened in different flood forecast locations depending on the forecast lead time and storm characteristics. Interior differences in error propagation are shown to be effectively averaged out for larger catchment scales.

Description: A nonhomogeneous hidden Markov model (NHMM) is used to make stochastic simulations of March–August daily rainfall at 10 stations over the southeastern United States, 1923–98. Station-averaged observed daily rainfall amount is prescribed as an input to the NHMM, which is then used to disaggregate the rainfall in space. These rainfall simulations are then used as inputs to a Crop Estimation through Resource and Environment Synthesis (CERES) crop model for maize. Regionally averaged yields derived from the NHMM rainfall simulations are found to correlate very highly (r = 0.93) with those generated by the crop model using observed rainfall; stationwise correlations range between 0.44 and 0.74. Rainfall and crop simulations are then constructed under increasing degrees of temporal smoothing applied to the regional rainfall input to the NHMM, designed to exclude the submonthly weather details that would be unpredictable in seasonal climate forecasts. Regional yields are found to be remarkably insensitive to this temporal smoothing; even with 90-day low-pass-filtered inputs to the NHMM, resulting yields are still correlated at 0.85 with the baseline simulation, whereas stationwise correlations range between 0.18 and 0.68. From these findings, it is expected that regional maize yields over the southeastern United States will be largely insensitive to year-to-year details of subseasonal rainfall variability; they should be downscalable, in principle, using an NHMM from climate forecasts archived at daily resolution, with the important caveat that the latter need to be skillful enough at the 90-day time scale. As a by-product of the analysis, subseasonal-to-interdecadal summer rainfall variability over the southeastern United States is interpretable in terms of six discrete weather states indicative of a monsoonlike climate regime. Low-simulated-yield years are found to be associated with delayed summer rainfall onset.

Description: In this paper, a penalized maximal t test (PMT) is proposed for detecting undocumented mean shifts in climate data series. PMT takes the relative position of each candidate changepoint into account, to diminish the effect of unequal sample sizes on the power of detection. Monte Carlo simulation studies are conducted to evaluate the performance of PMT, in comparison with the most popularly used method, the standard normal homogeneity test (SNHT). An application of the two methods to atmospheric pressure series recorded at a Canadian site is also presented. It is shown that the false-alarm rate of PMT is very close to the specified level of significance and is evenly distributed across all candidate changepoints, whereas that of SNHT can be up to 10 times the specified level for points near the ends of series and much lower for the middle points. In comparison with SNHT, therefore, PMT has higher power for detecting all changepoints that are not too close to the ends of series and lower power for detecting changepoints that are near the ends of series. On average, however, PMT has significantly higher power of detection. The smaller the shift magnitude Δ is relative to the noise standard deviation σ, the greater is the improvement of PMT over SNHT. The improvement in hit rate can be as much as 14%–25% for detecting small shifts (Δ 〈 σ) regardless of time series length and up to 5% for detecting medium shifts (Δ = σ–1.5σ) in time series of length N 〈 100. For all detectable shift sizes, the largest improvement is always obtained when N 〈 100, which is of great practical importance, because most annual climate data series are of length N 〈 100.

Description: This study investigates the potential utility of the application of a photochemical modeling system in providing simultaneous forecasts of ozone (O3) and fine particulate matter (PM2.5) over New York State. To this end, daily simulations from the Community Multiscale Air Quality (CMAQ) model for three extended time periods during 2004 and 2005 have been performed, and predictions were compared with observations of ozone and total and speciated PM2.5. Model performance for 8-h daily maximum O3 was found to be similar to other forecasting systems and to be better than that for the 24-h-averaged total PM2.5. Both pollutants exhibited no seasonal differences in model performance. CMAQ simulations successfully captured the urban–rural and seasonal differences evident in observed total and speciated PM2.5 concentrations. However, total PM2.5 mass was strongly overestimated in the New York City metropolitan area, and further analysis of speciated observations and model predictions showed that most of this overprediction stems from organic aerosols and crustal material. An analysis of hourly speciated data measured in Bronx County, New York, suggests that a combination of uncertainties in vertical mixing, magnitude, and temporal allocation of emissions and deposition processes are all possible contributors to this overprediction in the complex urban area. Categorical evaluation of CMAQ simulations in terms of exceeding two different threshold levels of the air quality index (AQI) again indicates better performance for ozone than PM2.5 and better performance for lower exceedance thresholds. In most regions of New York State, the routine air quality forecasts based on observed concentrations and expert judgment show slightly better agreement with the observed distributions of AQI categories than do CMAQ simulations. However, CMAQ shows skill similar to these routine forecasts in terms of capturing the AQI tendency, that is, in predicting changes in air quality conditions. Overall, the results presented in this study reveal that additional research and development is needed to improve CMAQ simulations of PM2.5 concentrations over New York State, especially for the New York City metropolitan area. On the other hand, because CMAQ simulations capture urban–rural concentration gradients and day-to-day fluctuations in observed air quality despite systematic overpredictions in some areas, it would be useful to develop tools that combine CMAQ’s predictive capability in terms of spatial concentration gradients and AQI tendencies with real-time observations of ambient pollutant levels to generate forecasts with higher temporal and spatial resolutions (e.g., county level) than those of techniques based exclusively on monitoring data.

Description: A new combined local and nonlocal closure atmospheric boundary layer model called the Asymmetric Convective Model, version 2, (ACM2) was described and tested in one-dimensional form and was compared with large-eddy simulations and field data in Part I. Herein, the incorporation of the ACM2 into the fifth-generation Pennsylvania State University–NCAR Mesoscale Model (MM5) is described. Model simulations using the MM5 with the ACM2 are made for the summer of 2004 and evaluated through comparison with surface meteorological measurements, rawinsonde profile measurements, and observed planetary boundary layer (PBL) heights derived from radar wind profilers. Overall model performance is as good as or better than similar MM5 evaluation studies. The MM5 simulations with the ACM2 compare particularly well to PBL heights derived from radar wind profilers during the afternoon hours. The ACM2 is designed to simulate the vertical mixing of any modeled quantity realistically for both meteorological models and air quality models. The next step, to be described in a subsequent article, is to incorporate the ACM2 into the Community Multiscale Air Quality (CMAQ) model for testing and evaluation.

Description: Linear parametric models are commonly assumed and used for unknown data-generating mechanisms. This study demonstrates the value of inferring statistics of meteorological and climatological time series by using a computer-intensive subsampling method that allows one to avoid time series analysis anchored in parametric models with imposed perceived physical assumptions. A first-order autoregressive model, typically adopted as the default model for correlated time series in climate studies, has been selected and altered with a nonlinear component to provide insight into possible errors in estimation due to nonlinearities in the real data-generating mechanism. The nonlinearity undetected by basic diagnostic procedures is shown to invalidate statistical inference based on the linear model, whereas the inference derived through subsampling remains valid. It is argued that subsampling and other resampling methods are preferable in complex dependent-data situations that are typical for atmospheric and climatic series when the real data-generating mechanism is unknown.

Description: The impacts of urban-enhanced aerosol concentrations on convective storm development and precipitation over and downwind of St. Louis, Missouri, are investigated. This is achieved through the use of a cloud-resolving mesoscale model, in which sophisticated land use processes and aerosol microphysics are both incorporated. The results indicate that urban-forced convergence downwind of the city, rather than the presence of greater aerosol concentrations, determines whether storms actually develop in the downwind region. Once convection is initiated, urban-enhanced aerosols can exert a significant effect on the dynamics, microphysics, and precipitation produced by these storms. The model results indicate, however, that the response to urban-enhanced aerosol depends on the background concentrations of aerosols; a weaker response occurs with increasing background aerosol concentrations. The effects of aerosols influence the rate and amount of liquid water and ice produced within these storms, the accumulated surface precipitation, the strength and timing of the updrafts and downdrafts, the longevity of the updrafts, and the strength and influence of the cold pool. Complex, nonlinear relationships and feedbacks between the microphysics and storm dynamics exist, making it difficult to make definitive statements about the effects of urban-enhanced aerosols on downwind precipitation and convection. Because the impacts of urban aerosol on downwind storms decrease with increasing background aerosol concentrations, generalization of these results depends on the unique character of background aerosol for each urban area. For urban centers in coastal areas where background aerosol concentrations may be very low, it is speculated that urban aerosol can have very large influences on convective storm dynamics, microphysics, and precipitation.

Description: The spectral latent heating (SLH) algorithm was developed for the Tropical Rainfall Measuring Mission (TRMM) precipitation radar (PR) in Part I of this study. The method uses PR information [precipitation-top height (PTH), precipitation rates at the surface and melting level, and rain type] to select heating profiles from lookup tables. Heating-profile lookup tables for the three rain types—convective, shallow stratiform, and anvil rain (deep stratiform with a melting level)—were derived from numerical simulations of tropical cloud systems from the Tropical Ocean and Global Atmosphere Coupled Ocean–Atmosphere Response Experiment (TOGA COARE) utilizing a cloud-resolving model (CRM). To assess its global application to TRMM PR data, the universality of the lookup tables from the TOGA COARE simulations is examined in this paper. Heating profiles are reconstructed from CRM-simulated parameters (i.e., PTH, precipitation rates at the surface and melting level, and rain type) and are compared with the true CRM-simulated heating profiles, which are computed directly by the model thermodynamic equation. CRM-simulated data from the Global Atmospheric Research Program Atlantic Tropical Experiment (GATE), South China Sea Monsoon Experiment (SCSMEX), and Kwajalein Experiment (KWAJEX) are used as a consistency check. The consistency check reveals discrepancies between the SLH-reconstructed and Goddard Cumulus Ensemble (GCE)-simulated heating above the melting level in the convective region and at the melting level in the stratiform region that are attributable to the TOGA COARE table. Discrepancies in the convective region are due to differences in the vertical distribution of deep convective heating due to the relative importance of liquid and ice water processes, which varies from case to case. Discrepancies in the stratiform region are due to differences in the level separating upper-level heating and lower-level cooling. Based on these results, improvements were made to the SLH algorithm. Convective heating retrieval is now separated into upper-level heating due to ice processes and lower-level heating due to liquid water processes. In the stratiform region, the heating profile is shifted up or down by matching the melting level in the TOGA COARE lookup table with the observed one. Consistency checks indicate the revised SLH algorithm performs much better for both the convective and stratiform components than does the original one. The revised SLH algorithm was applied to PR data, and the results were compared with heating profiles derived diagnostically from SCSMEX sounding data. Key features of the vertical profiles agree well—in particular, the level of maximum heating. The revised SLH algorithm was also applied to PR data for February 1998 and February 1999. The results are compared with heating profiles derived by the convective–stratiform heating (CSH) algorithm. Because observed information on precipitation depth is used in addition to precipitation type and intensity, differences between shallow and deep convection are more distinct in the SLH algorithm in comparison with the CSH algorithm.

Description: Advances in numerical weather prediction have occurred on numerous fronts, from sophisticated physics packages in the latest mesoscale models to multimodel ensembles of medium-range predictions. Thus, the skill of numerical weather forecasts continues to increase. Statistical techniques have further increased the utility of these predictions. The availability of large atmospheric datasets and faster computers has made pattern recognition of major weather events a feasible means of statistically enhancing the value of numerical forecasts. This paper examines the utility of pattern recognition in assisting the prediction of severe and major weather in the Middle Atlantic region. An important innovation in this work is that the analog technique is applied to NWP forecast maps as a pattern-recognition tool rather than to analysis maps as a forecast tool. A technique is described that employs a new clustering algorithm to objectively identify the anomaly patterns or “fingerprints” associated with past events. The potential refinement and applicability of this method as an operational forecasting tool employed by comparing numerical weather prediction forecasts with fingerprints already identified for major weather events are also discussed.

Description: The ability to forecast the number and location of large wildfire events (with specified confidence bounds) is important to fire managers attempting to allocate and distribute suppression efforts during severe fire seasons. This paper describes the development of a statistical model for assessing the forecasting skills of fire-danger predictors and producing 1-month-ahead wildfire-danger probabilities in the western United States. The method is based on logistic regression techniques with spline functions to accommodate nonlinear relationships between fire-danger predictors and probability of large fire events. Estimates were based on 25 yr of historic fire occurrence data (1980–2004). The model using the predictors monthly average temperature, and lagged Palmer drought severity index demonstrated significant improvement in forecasting skill over historic frequencies (persistence forecasts) of large fire events. The statistical models were particularly amenable to model evaluation and production of probability-based fire-danger maps with prespecified precisions. For example, during the 25 yr of the study for the month of July, an area greater than 400 ha burned in 3% of locations where the model forecast was low; 11% of locations where the forecast was moderate; and 76% of locations where the forecast was extreme. The statistical techniques may be used to assess the skill of forecast fire-danger indices developed at other temporal or spatial scales.

Description: 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.

Description: Numerous studies have indicated the potential for giant and ultragiant aerosol particles to expedite the warm-rain process as a result of their extreme sizes. The central question regarding their importance is, Are they present in large enough numbers to influence the microphysics of the clouds significantly? Thus, quantification of these particles and their variability is paramount. New observations collected during the second Alliance Icing Research Study (AIRS II) are presented as evidence of the presence and variability of giant and ultragiant aerosol particles over a continental region—in this case, within the eastern Great Lakes region and parts of the midwestern United States and Canada during one month in winter 2003. Sources and factors contributing to the amount of these particles observed in the lower atmosphere were difficult to identify separately; future studies incorporating high-resolution weather modeling are likely needed.

Description: In terms of the effects of future climate change upon society, some of the most important parameters to estimate are associated with changing risks of extreme rainfall events, both floods and droughts. However, such aspects of the climate system are hard to estimate well using general circulation models (GCMs)—in particular, for a small mountainous landmass such as New Zealand. This paper describes a downscaling technique using broad-scale changes simulated by GCMs to select past analogs of future climate. The analog samples are assumed to represent an unbiased sample of future rainfall and are used to develop detailed descriptions of rainfall statistics using hidden semi-Markov models of rainfall breakpoint information. Such models are used to simulate long synthetic rainfall time series for comparison with the historical record. Results for three New Zealand sites show overall increases in rainfall with climate change, brought about largely by an increased frequency of rainfall events rather than an increase in rainfall intensity. There was little evidence for significant increases in high-intensity short-duration rainfalls at any site. Such results suggest that, although regional increases of rainfall are consistent with expected future climate changes, it may be that circulation changes, rather than temperature (and vapor pressure) changes, will be the more important determinant of future rainfall distributions, at least for the coming few decades.

Description: Winter-storm hydrometeor distributions along the Front Range in eastern Colorado are studied with a ground-based two-dimensional video disdrometer. The instrument provides shape, size, and terminal velocity information for particles that are larger than about 0.4 mm. The dataset is used to determine the form of particle size distributions (PSDs) and to search for useful interrelationships among the governing parameters of assumed distribution forms and environmental factors. Snowfalls are dominated by almost spherical aggregates having near-exponential or superexponential size distributions. Raindrop size distributions are more peaked than those for snow. A relation between bulk snow density and particle median volume diameter is derived. The data suggest that some adjustment may be needed in relationships found previously between temperature and the concentration and slope parameters of assumed exponential PSDs. A potentially useful relationship is found between the slope and shape terms of the gamma PSD model.

Description: This study reports on the development of bulk single-scattering models for ice clouds that are appropriate for use in hyperspectral radiative transfer cloud modeling over the spectral range from 100 to 3250 cm−1. The models are developed in a manner similar to that recently reported for the Moderate-Resolution Imaging Spectroradiometer (MODIS); therefore these models result in a consistent set of scattering properties from visible to far-infrared wavelengths. The models incorporate a new database of individual ice-particle scattering properties that includes droxtals, 3D bullet rosettes, hexagonal solid and hollow columns, aggregates, and plates. The database provides single-scattering properties for each habit in 45 size bins ranging from 2 to 9500 μm, and for 49 wavenumbers between 100 and 3250 cm−1, which is further interpolated to 3151 discrete wavenumbers on the basis of a third-order spline interpolation method. Bulk models are developed by integrating various properties over both particle habit and size distributions. Individual bulk models are developed for 18 effective diameters Deff, ranging from Deff = 10 μm to Deff = 180 μm. A total of 1117 particle size distributions are used in the analyses and are taken from analysis of the First International Satellite Cloud Climatology Project Regional Experiment (FIRE)-I, FIRE-II, Atmospheric Radiation Measurement Program intensive operation period (ARM-IOP), Tropical Rainfall Measuring Mission Kwajalein Experiment (TRMM-KWAJEX), and Cirrus Regional Study of Tropical Anvils and Cirrus Layers Florida-Area Cirrus Experiment (CRYSTAL-FACE) data. The models include microphysical and scattering properties such as median mass diameter, effective diameter, single-scattering albedo, asymmetry factor, and scattering phase function. The spectral models are appropriate for applications involving the interpretation of the radiometric measurements of ice clouds acquired by infrared spectrometers such as the Atmospheric Infrared Sounder (AIRS) on the NASA Aqua satellite and the Cross-Track Infrared Sounder (CrIS) on the upcoming National Polar-Orbiting Environmental Satellite System (NPOESS) platforms.

Description: This paper presents the revision and evaluation of the interface between the convective parameterization by Emanuel and Živković-Rothman and the Lagrangian particle dispersion model “FLEXPART” based on meteorological data from the European Centre for Medium-Range Weather Forecasts (ECMWF). The convection scheme relies on the ECMWF grid-scale temperature and humidity and provides a matrix necessary for the vertical convective particle displacement. The benefits of the revised interface relative to its previous version are presented. It is shown that, apart from minor fluctuations caused by the stochastic convective redistribution of the particles, the well-mixed criterion is fulfilled in simulations that include convection. Although for technical reasons the calculation of the displacement matrix differs somewhat between the forward and the backward simulations in time, the mean relative difference between the convective mass fluxes in forward and backward simulations is below 3% and can therefore be tolerated. A comparison of the convective mass fluxes and precipitation rates with those archived in the 40-yr ECMWF Reanalysis (ERA-40) data reveals that the convection scheme in FLEXPART produces upward mass fluxes and precipitation rates that are generally smaller by about 25% than those from ERA-40. This result is interpreted as positive, because precipitation is known to be overestimated by the ECMWF model. Tracer transport simulations with and without convection are compared with surface and aircraft measurements from two tracer experiments and to 222Rn measurements from two aircraft campaigns. At the surface no substantial differences between the model runs with and without convection are found, but at higher altitudes the model runs with convection produced better agreement with the measurements in most of the cases and indifferent results in the others. However, for the tracer experiments only few measurements at higher altitudes are available, and for the aircraft campaigns the 222Rn emissions are highly uncertain. Other datasets better suitable for the validation of convective transport in models are not available. Thus, there is a clear need for reliable datasets suitable to validate vertical transport in models.

Description: A dataset gathered over 369 days in various midlatitude sites with a 12-frequency microwave radiometric profiler is used to analyze the statistical distribution of tropospheric water vapor content (WVC) in clear and cloudy conditions. The WVC distribution inside intervals of temperature is analyzed. WVC is found to be well fitted by a Weibull distribution. The two Weibull parameters, the scale (λ) and shape (k), are temperature (T) dependent; k is almost constant, around 2.6, for clear conditions. For cloudy conditions, at T 〈 −10°C, k is close to 2.6. For T 〉 −10°C, k displays a maximum in such a way that skewness, which is positive in most conditions, reverses to negative in a temperature region approximately centered around 0°C (i.e., at a level where the occurrence of cumulus clouds is high). Analytical λ(T) and k(T) relations are proposed. The WVC spatial distribution can thus be described as a function of T. The mean WVC vertical profiles for clear and cloudy conditions are well described by a function of temperature of the same form as the Clausius–Clapeyron equation. The WVCcloudy/WVCclear ratio is shown to be a linear function of temperature. The vertically integrated WV (IWV) is found to follow a Weibull distribution. The IWV Weibull distribution parameters retrieved from the microwave radiometric profiler agree very well with the ones calculated from the 15-yr ECMWF reanalysis (ERA-15) meteorological database. The radiometric retrievals compare fairly well to the corresponding values calculated from an operational radiosonde sounding dataset.