ALBERT

Description: A season-long set of 5-day simulations between 1200 UTC 1 June and 1200 UTC 30 September 2000 are evaluated using the observations taken during the Central California Ozone Study (CCOS) 2000 experiment. The simulations are carried out using the fifth-generation Pennsylvania State University–NCAR Mesoscale Model (MM5), which is widely used for air-quality simulations and control planning. The evaluation results strongly indicate that the model-simulated low-level winds in California’s Central Valley are biased in speed and direction: the simulated winds tend to have a stronger northwesterly component than observed. This bias is related to the difference in the observed and simulated large-scale, upper-level flows. The model simulations also show a bias in the height of the daytime atmospheric boundary layer (ABL), particularly in the northern and southern Central Valley. There is evidence to suggest that this bias in the daytime ABL height is not only associated with the large-scale, upper-level bias but also linked to apparent differences in the surface forcing.

Description: African dust outbreaks are the result of complex interactions between the land, atmosphere, and oceans, and only recently has a large body of work begun to emerge that aims to understand the controls on—and impacts of—African dust. At the same time, long-term records of dust outbreaks are either inferred from visibility data from weather stations or confined to a few in situ observational sites. Satellites provide the best opportunity for studying the large-scale characteristics of dust storms, but reliable records of dust are generally on the scale of a decade or less. Here the authors develop a simple model for using modern and historical data from meteorological satellites, in conjunction with a proxy record for atmospheric dust, to extend satellite-retrieved dust optical depth over the northern tropical Atlantic Ocean from 1955 to 2008. The resultant 54-yr record of dust has a spatial resolution of 1° and a monthly temporal resolution. From analysis of the historical dust data, monthly tropical northern Atlantic dust cover is bimodal, has a strong annual cycle, peaked in the early 1980s, and shows minimums in dustiness during the beginning and end of the record. These dust optical depth estimates are used to calculate radiative forcing and heating rates from the surface through the top of the atmosphere over the last half century. Radiative transfer simulations show a large net negative dust forcing from the surface through the top of the atmosphere, also with a distinct annual cycle, and mean tropical Atlantic monthly values of the surface forcing range from −3 to −9 W m−2. Since the surface forcing is roughly a factor of 3 larger in magnitude than the top-of-the-atmosphere forcing, there is also a positive heating rate of the midtroposphere by dust.

Description: This work describes the seasonal and diurnal variations of downward longwave atmospheric irradiance (LW) at the surface in São Paulo, Brazil, using 5-min-averaged values of LW, air temperature, relative humidity, and solar radiation observed continuously and simultaneously from 1997 to 2006 on a micrometeorological platform, located at the top of a 4-story building. An objective procedure, including 2-step filtering and dome emission effect correction, was used to evaluate the quality of the 9-yr-long LW dataset. The comparison between LW values observed and yielded by the Surface Radiation Budget project shows spatial and temporal agreement, indicating that monthly and annual average values of LW observed in one point of São Paulo can be used as representative of the entire metropolitan region of São Paulo. The maximum monthly averaged value of the LW is observed during summer (389 ± 14 W m−2; January), and the minimum is observed during winter (332 ± 12 W m−2; July). The effective emissivity follows the LW and shows a maximum in summer (0.907 ± 0.032; January) and a minimum in winter (0.818 ± 0.029; June). The mean cloud effect, identified objectively by comparing the monthly averaged values of the LW during clear-sky days and all-sky conditions, intensified the monthly average LW by about 32.0 ± 3.5 W m−2 and the atmospheric effective emissivity by about 0.088 ± 0.024. In August, the driest month of the year in São Paulo, the diurnal evolution of the LW shows a minimum (325 ± 11 W m−2) at 0900 LT and a maximum (345 ± 12 W m−2) at 1800 LT, which lags behind (by 4 h) the maximum diurnal variation of the screen temperature. The diurnal evolution of effective emissivity shows a minimum (0.781 ± 0.027) during daytime and a maximum (0.842 ± 0.030) during nighttime. The diurnal evolution of all-sky condition and clear-sky day differences in the effective emissivity remain relatively constant (7% ± 1%), indicating that clouds do not change the emissivity diurnal pattern. The relationship between effective emissivity and screen air temperature and between effective emissivity and water vapor is complex. During the night, when the planetary boundary layer is shallower, the effective emissivity can be estimated by screen parameters. During the day, the relationship between effective emissivity and screen parameters varies from place to place and depends on the planetary boundary layer process. Because the empirical expressions do not contain enough information about the diurnal variation of the vertical stratification of air temperature and moisture in São Paulo, they are likely to fail in reproducing the diurnal variation of the surface emissivity. The most accurate way to estimate the LW for clear-sky conditions in São Paulo is to use an expression derived from a purely empirical approach.

Description: In this paper, wintertime precipitation from a variety of observational datasets, regional climate models (RCMs), and general circulation models (GCMs) is averaged over the state of California and compared. Several averaging methodologies are considered and all are found to give similar values when the model grid spacing is less than 3°. This suggests that California is a reasonable size for regional intercomparisons using modern GCMs. Results show that reanalysis-forced RCMs tend to significantly overpredict California precipitation. This appears to be due mainly to the overprediction of extreme events; RCM precipitation frequency is generally underpredicted. Overprediction is also reflected in wintertime precipitation variability, which tends to be too high for RCMs on both daily and interannual scales. Wintertime precipitation in most (but not all) GCMs is underestimated. This is in contrast to previous studies based on global blended gauge–satellite observations, which are shown here to underestimate precipitation relative to higher-resolution gauge-only datasets. Several GCMs provide reasonable daily precipitation distributions, a trait that does not seem to be tied to model resolution. The GCM daily and interannual variabilities are generally underpredicted.

Description: The number of atmospheric sounding techniques and the amount of missions within each of them continue to grow at the present time. The probability of having two or more profiles in a given region and time interval therefore is increasing. In the case of three close observations it would be a priori possible to infer the three Cartesian wavelengths of a mountain wave. However, the relative orientation of the three sounding paths cannot be arbitrary and must fulfill some conditions to avoid errors growing out of given bounds.

Description: One of the grand challenges of the Global Precipitation Measurement (GPM) mission is to improve cold-season precipitation measurements in mid- and high latitudes through the use of high-frequency passive microwave radiometry. For this purpose, the Weather Research and Forecasting model (WRF) with the Goddard microphysics scheme is coupled with a Satellite Data Simulation Unit (WRF–SDSU) to facilitate snowfall retrieval algorithms over land by providing a virtual cloud library and corresponding microwave brightness temperature measurements consistent with the GPM Microwave Imager (GMI). When this study was initiated, there were no prior published results using WRF at cloud-resolving resolution (1 km or finer) for high-latitude snow events. This study tested the Goddard cloud microphysics scheme in WRF for two different snowstorm events (a lake-effect event and a synoptic event between 20 and 22 January 2007) that took place over the Canadian CloudSat/Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) Validation Project (C3VP) site in Ontario, Canada. The 24-h-accumulated snowfall predicted by WRF with the Goddard microphysics was comparable to that observed by the ground-based radar for both events. The model correctly predicted the onset and termination of both snow events at the Centre for Atmospheric Research Experiments site. The WRF simulations captured the basic cloud patterns as seen by the ground-based radar and satellite [i.e., CloudSat and Advanced Microwave Sounding Unit B (AMSU-B)] observations, including the snowband featured in the lake event. The results reveal that WRF was able to capture the cloud macrostructure reasonably well. Sensitivity tests utilizing both the “2ICE” (ice and snow) and “3ICE” (ice, snow, and graupel) options in the Goddard microphysical scheme were also conducted. The domain- and time-averaged cloud species profiles from the WRF simulations with both microphysical options show identical results (due to weak vertical velocities and therefore the absence of large precipitating liquid or high-density ice particles like graupel). Both microphysics options produced an appreciable amount of liquid water, and the model cloud liquid water profiles compared well to the in situ C3VP aircraft measurements when only grid points in the vicinity of the flight paths were considered. However, statistical comparisons between observed and simulated radar echoes show that the model tended to have a high bias of several reflectivity decibels (dBZ), which shows that additional research is needed to improve the current cloud microphysics scheme for the extremely cold environment in high latitudes, despite the fact that the simulated ice/liquid water contents may have been reasonable for both events. Future aircraft observations are also needed to verify the existence of graupel in high-latitude continental snow events.

Description: On 2 April 2007, nine cases of moderate-or-greater-level clear-air turbulence (CAT) were observed from pilot reports over South Korea during the 6.5 h from 0200 to 0830 UTC. Those CAT events occurred in three different regions of South Korea: the west coast, Jeju Island, and the eastern mountain areas. The characteristics and possible mechanisms of the CAT events in the different regions are investigated using the Weather Research and Forecasting model. The simulation consists of six nested domains focused on the Korean Peninsula, with the finest horizontal grid spacing of 0.37 km. The simulated wind and temperature fields in a 30-km coarse domain are in good agreement with those of the Regional Data Assimilation and Prediction System (RDAPS) analysis data of the Korean Meteorological Administration and observed soundings of operational radiosondes over South Korea. In synoptic features, an upper-level front associated with strong meridional temperature gradients is intensified, and the jet stream passing through the central part of the Korean Peninsula exceeds 70 m s−1. Location and timing of the observed CAT events are reproduced in the finest domains of the simulated results in three different regions. Generation mechanisms of the CAT events revealed in the model results are somewhat different in the three regions. In the west coast area, the tropopause is deeply folded down to about z = 4 km because of the strengthening of an upper-level front, and the maximized vertical wind shear below the jet core produces localized turbulence. In the Jeju Island area, localized mixing and turbulence are generated on the anticyclonic shear side of the enhanced jet, where inertial instability and ageostrophic flow are intensified in the lee side of the convective system. In the eastern mountain area, large-amplitude gravity waves induced by complex terrain propagate vertically and subsequently break down over the lee side of topography, causing localized turbulence. For most of the CAT processes considered, except for the mountain-wave breaking, standard NWP resolutions of tens of kilometers are adequate to capture the CAT events.

Description: The authors combine urban and soil–vegetation surface parameterization schemes with one-dimensional (1D) boundary layer mixing and radiation parameterizations to estimate the maximum impact of increased surface albedo on urban air temperatures. The combined model is evaluated with measurements from an urban neighborhood in Basel, Switzerland, and the importance of surface–atmosphere model coupling is demonstrated. Impacts of extensive albedo increases in two Chicago, Illinois, neighborhoods are modeled. Clear-sky summertime reductions of diurnal maximum air temperature for the residential neighborhood (λp = 0.33) are −1.1°, −1.5°, and −3.6°C for uniform roof albedo increases of 0.19, 0.26, and 0.59, respectively; reductions are about 40% larger for the downtown core (λp = 0.53). Realistic impacts will be smaller because the 1D modeling approach ignores advection; a lake-breeze scenario is modeled and temperature reductions decline by 80%. Assuming no advection, the analysis is extended to seasonal and annual time scales in the residential neighborhood. Yearly average temperature decreases for a 0.59 roof albedo increase are about −1°C, with summer (winter) reductions about 60% larger (smaller). Annual cooling degree-day decreases are approximately offset by heating degree-day increases and the frequency of very hot days is reduced. Despite the variability of modeling approaches and scenarios in the literature, a consistent range of air temperature sensitivity to albedo is emerging; a 0.10 average increase in neighborhood albedo (a 0.40 roof albedo increase for λp = 0.25) generates a diurnal maximum air temperature reduction of approximately 0.5°C for “ideal” conditions, that is, a typical clear-sky midlatitude summer day.

Description: The number of surface observations from nonstandardized networks across the United States has appreciably increased the last several years. Automated Weather Services, Inc. (AWS), maintains one example of this type of network offering nonstandardized observations for ∼8000 sites. The present study assesses the utility of such a network to improve short-term (i.e., lead times

Description: This paper presents the sensitivity to various atmospheric parameters of two height assignment methods that aim to retrieve the cloud-top height of semitransparent clouds. The use of simulated Meteosat-8 radiances has the advantage that the pressure retrieved by a given method can be compared to the initial pressure set to the cloud in the model, which is exactly known. The methods retrieve the pressure of a perfectly opaque cloud to within a few hectopascals. However, considering more realistic ice clouds, methods are sensitive to all of the tested atmospheric parameters and, especially, to the cloud microphysics, which can bias the results of the CO2-slicing method by several tens of hectopascals. The cloud-top pressure retrieval is especially difficult for thinner clouds with optical thicknesses smaller than 2, for which the errors can reach several tens of hectopascals. The methods have also been tested after introducing realistic perturbations in the temperature and humidity profiles and on the clear-sky surface radiances. The corresponding averages of errors on the retrieved pressures are also very large, especially for thin clouds. In multilayer cloud situations the height assignment methods do not work properly, placing the cloud-top height somewhere between the two cloud layers for most cirrus cloud layers with optical thicknesses between 0.1 and 10.

Description: A novel and unique algorithm for the retrieval of multilayer cloud-top pressure is presented, relying on synergetic observations of the Medium Resolution Imaging Spectrometer (MERIS) and Advanced Along Track Scanning Radiometer (AATSR) on board the Environmental Satellite (Envisat). The retrieval is based on the exploitation of the differing signals observed in the thermal infrared spectral region (AATSR) and the oxygen A band at 0.76 μm (MERIS). Past studies have shown that the cloud-top pressure retrieved from MERIS measurements is highly accurate in the case of low single-layered clouds. In contrast, in the presence of multilayered clouds like cirrus overlying water clouds, the derived cloud height is biased. In this framework, an optimal estimation algorithm for the correction of the measured O2 A transmission for the influence of the upper cloud layer was developed. The algorithm is best applicable in cases of optically thin cirrus (1 ≤ τ ≤ 5) above optically thick water clouds (τ 〉 5), as found frequently in the vicinity of convective or frontal cloud systems. The split-window brightness temperature difference technique is used for the identification of suitable cases. The sensitivities of the AATSR and MERIS measurements to multilayered clouds are presented and discussed, revealing that in the case of dual-layered clouds, the AATSR-derived cloud height is close to the upper cloud layer, even if it is optically thin. In contrast, the cloud height retrieved from MERIS measurements represents the optical center of the cloud system, which is close to the lower layer in cases where the upper layer is optically thin. Two case studies of convective, multilayered cloud systems above the northern Atlantic Ocean are shown, demonstrating the plausibility of the approach. The presented work is relevant especially in view of the upcoming Global Monitoring for Environment and Security Sentinel-3 satellite to be launched in 2012 that will carry the respective MERIS and AATSR follow-up instruments Ocean and Land Colour Instrument (OLCI) and Sea and Land Surface Temperature Radiometer (SLSTR).

Description: This paper evaluates rainfall detection capabilities of seven satellite rainfall estimates over the desert locust recession regions of the world. The region of interest covers the arid and semiarid region from northwestern Africa to northwestern India. The evaluated satellite rainfall products are the African rainfall climatology (ARC), rainfall estimation algorithm (RFE), Tropical Rainfall Measuring Mission 3B42 and its real-time version (3B42RT), NOAA/Climate Prediction Center morphing technique (CMORPH), and two versions of the Global Satellite Mapping of Precipitation moving vector with Kalman filter (GSMaP-MVK and GSMaP-MVK+). The reference data were obtained from the Desert Locust Information Service of the United Nations Food and Agriculture Organization (FAO). The FAO data are qualitative information collated by desert locust survey teams from different countries during field campaigns. Such data can only be used to assess the rainfall detection capabilities of the satellite products. The validation region is divided into four subregions and validations statistics are computed for each region. The probability of detection varies from 70% for the relatively wet part of the validation region to less than 20% for the driest part. The main weakness of the satellite products is overestimation of rainfall occurrences. The false-alarm ratio was as high as 84% for the driest part and as high as 57% for the wetter region. The satellite products still exhibit positive detection skill for all of the subregions. A comparison of the different products shows that no single product stands out as having the best or the worst overall performance.

Description: Tropical cyclones pose a significant threat to life and property along coastal regions of the United States. As these systems move inland and dissipate, they can also pose a threat to life and property, through heavy rains, high winds, and other severe weather such as tornadoes. While many studies have focused on the impacts from tropical cyclones on coastal counties of the United States, this study goes beyond the coast and examines the impacts caused by tropical cyclones on inland locations. Using geographical information system software, historical track data are used in conjunction with the radial maximum extent of the maximum sustained winds at 34-, 50-, and 64-kt (1 kt ≈ 0.5 m s−1) thresholds for all intensities of tropical cyclones and overlaid on a 30-km equal-area grid that covers the eastern half of the United States. The result is a series of maps with frequency distributions and an estimation of return intervals for inland tropical storm– and hurricane-force winds. Knowing where the climatologically favored areas are for tropical cyclones, combined with a climatological expectation of the inland penetration frequency of these storms, can be of tremendous value to forecasters, emergency managers, and the public.

Description: Despite tremendous efforts to improve weather and climate predictions and to inform farmers about the use of such weather products, farmers’ attitudes toward forecast use remain poor and farmer use of forecasts has not increased. This paper describes features of a new conceptual model for facilitating farmers’ use of weather products and offers preliminary evidence for its effectiveness based on a test-of-concept prototype. The prototype system provides farmers with contextualized information, the opportunity to use that information in relevant farming contexts, and collaborative interaction with other users. In addition, scaffolding and feedback are incorporated in the model to enhance learning and motivation. Surveys before and after use of the prototype system, and focus-group discussion after system use, were conducted to obtain evaluations from 15 farmers in southeastern Nebraska. Farmers’ evaluations of the system were moderately positive and indicated greater intentions to use the products in the future than they had in the past. However, farmers only slightly increased their positive expectancies of various general categories of weather and climate products, supporting the difficulties associated with changing overall attitudes when attempting to transfer scientific improvements into practical uses. It is suggested that multiple exposures to such a system and more individualized and personally relevant use opportunities may further enhance the power of the proposed model.

Description: This study focuses on the evaluation of 3-hourly, 0.25° × 0.25°, satellite-based precipitation products: the Tropical Rainfall Measuring Mission (TRMM) Multisatellite Precipitation Analysis (TMPA) 3B42RT, the NOAA/Climate Prediction Center morphing technique (CMORPH), and Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks (PERSIANN). CMORPH is primarily microwave based, 3B42RT is primarily microwave based when microwave data are available and infrared based when microwave data are not available, and PERSIANN is primarily infrared based. The results show that 1) 3B42RT and CMORPH give similar rainfall fields (in terms of bias, spatial structure, elevation-dependent trend, and distribution function), which are different from PERSIANN rainfall fields; 2) PERSIANN does not show the elevation-dependent trend observed in rain gauge values, 3B42RT, and CMORPH; and 3) PERSIANN considerably underestimates rainfall in high-elevation areas.

Description: Measuring snowfall in the polar regions is an issue met with many complications. Across the Antarctic, ground-based precipitation measurements are only available from a sparse network of manned stations or field studies. Measurements from satellites promise to fill in gaps in time and space but are still in the early stages of development and require surface measurements for proper validation. Currently, measurements of accumulation from automated reporting stations are the only available means of tracking snow depth change over a broad area of the continent. The challenge remains in determining the cause of depth change by partitioning the impacts of blowing snow and precipitation. While a methodology for separating these two factors has yet to be developed, by comparing accumulation measurements with meteorological measurements, an assessment of whether these terms were a factor in snow depth change during an event can be made. This paper describes a field study undertaken between January 2005 and October 2006 designed to identify the influences of precipitation and horizontal snow transport on surface accumulation. Seven acoustic depth gauges were deployed at automatic weather stations (AWS) across the Ross Ice Shelf and Ross Sea regions of Antarctica to measure net accumulation changes. From these measurements, episodic events were identified and were compared with data from the AWS to determine the primary cause of depth change—precipitation or horizontal snow transport. Information regarding the local impacts of these two terms, as well as climatological information regarding snow depth change across this region, is also provided.

Description: Identifying and quantifying the intensity of light precipitation at global scales is still a difficult problem for most of the remote sensing algorithms in use today. The variety of techniques and algorithms employed for such a task yields a rather wide spectrum of possible values for a given precipitation event, further hampering the understanding of cloud processes within the climate. The ability of CloudSat’s millimeter-wavelength Cloud Profiling Radar (CPR) to profile not only cloud particles but also light precipitation brings some hope to the above problems. Introduced as version zero, the present work uses basic concepts of detection and retrieval of light precipitation using spaceborne radars. Based on physical principles of remote sensing, the radar model relies on the description of clouds and rain particles in terms of a drop size distribution function. Use of a numerical model temperature and humidity profile ensures the coexistence of mixed phases otherwise undetected by the CPR. It also provides grounds for evaluating atmospheric attenuation, important at this frequency. Related to the total attenuation, the surface response is used as an additional constraint in the retrieval algorithm. Practical application of the profiling algorithm includes a 1-yr preliminary analysis of global rainfall incidence and intensity. These results underscore once more the role of CloudSat rainfall products for improving and enhancing current estimates of global light rainfall, mostly at higher latitudes, with the goal of understanding its role in the global energy and water cycle.

Description: The NOAA Hurricane Research Division (HRD) P-3 aircraft provided airborne radar observations during the period of rapid intensification of Hurricane Guillermo on 2 August 1997. The inner core structure and evolution of Hurricane Guillermo (1997) over a 120 km by 120 km square area, centered on the storm, was observed by the P-3 aircraft during 10 flight legs at half-hour intervals during a 6-h period from 1800 UTC 2 August to 0000 UTC 3 August 1997. A high-resolution short-term model forecast initialized at 1800 UTC 2 August 1997 was made using the fifth-generation Pennsylvania State University–NCAR nonhydrostatic, two-way interactive, movable, triply nested grid Mesoscale Model (MM5). The weak vortex at the initial time in the NCEP analysis was replaced by a tropical storm–like vortex generated by a 4D variational data assimilation (4D-Var) vortex initialization experiment. The modeled Guillermo followed the observed track with less than a 12-km track error at any time during the 6-h forecast period. The modeled eye is smaller than the observed eye and the modeled vortex is more upright than shown by the radar analysis. The minimum pressure, maximum wind (intensity), and radial profile of tangential winds are close to the radar analysis after 2–3 h of model spinup. A spectral decomposition further reveals that (i) large differences between the model simulation and radar analysis of the asymmetric features are mostly caused by azimuthal phase errors; (ii) the wavenumber 1 component dominates the asymmetric features and remains stationary within the inner core region, as is also observed by airborne Doppler radar; and (iii) although being significantly different from radar analysis, the azimuthal phase of the wavenumber 1 component of modeled reflectivity does not vary greatly with time as the radar data suggest.

Description: The Atmospheric Infrared Sounder (AIRS) and the Infrared Atmospheric Sounding Interferometer (IASI), together with the future Cross-track Infrared Sounder, will provide long-term hyperspectral measurements of the earth and its atmosphere at ∼10 km spatial resolution. Quantifying the radiometric difference between AIRS and IASI is crucial for creating fundamental climate data records and establishing the space-based infrared calibration standard. Since AIRS and IASI have different local equator crossing times, a direct comparison of these two instruments over the tropical regions is not feasible. Using the Geostationary Operational Environmental Satellite (GOES) imagers as transfer radiometers, this study compares AIRS and IASI over warm scenes in the tropical regions for a time period of 16 months. The double differences between AIRS and IASI radiance biases relative to the GOES-11 and -12 imagers are used to quantify the radiance differences between AIRS and IASI within the GOES imager spectral channels. The results indicate that, at the 95% confidence level, the mean values of the IASI − AIRS brightness temperature differences for warm scenes are very small, that is, −0.0641 ± 0.0074 K, −0.0432 ± 0.0114 K, and −0.0095 ± 0.0151 K for the GOES-11 6.7-, 10.7-, and 12.0-μm channels, respectively, and −0.0490 ± 0.0100 K, −0.0419 ± 0.0224 K, and −0.0884 ± 0.0160 K for the GOES-12 6.5-, 10.7-, and 13.3-μm channels, respectively. The brightness temperature biases between AIRS and IASI within the GOES imager spectral range are less than 0.1 K although the AIRS measurements are slightly warmer than those of IASI.

Description: This paper introduces a remote sensing–based approach to rapidly derive urban morphological characteristics using radar satellite data. The approach is based on the expectation that the magnitude of the synthetic aperture radar (SAR) backscatter can be related to urban canopy parameters (UCPs) describing the height, density, and roughness of buildings, trees, and other objects in cities. This hypothesis was tested with full-feature terrain elevation and SAR datasets for the Houston, Texas, metropolitan area. The backscatter magnitude was found to vary as expected across the city with higher backscatter values in the downtown tall building district relative to adjacent residential and commercial areas. To demonstrate the concept of using radar backscatter to estimate UCPs, relationships were derived between SAR backscatter and mean height, plan area fraction, and frontal area index of roughness elements (e.g., buildings and trees). In addition, SAR backscatter relationships were derived with roughness lengths computed using morphometric approaches. In all cases, the derived relationships were found to provide estimates of UCPs acceptable for use in meteorological models. Further testing using data from the Salt Lake City, Utah, metropolitan area validated the relationships and identified key areas for improvement for future research, including SAR instrument view angle differences and buildings split between SAR pixels.

Description: Infrared (IR) data from the Meteosat Second Generation (MSG) satellite are used to understand cloud-top signatures for growing cumulus clouds prior to known convective initiation (CI) events, or the first occurrence of a ≥35-dBZ echo from a new convective cloud. In the process, this study proposes how MSG IR fields may be used to infer three physical attributes of growing cumuli, cloud depth, cloud-top glaciation, and updraft strength, with limited information redundancy. These three aspects are observed as unique signatures within MSG IR data, for which this study seeks to relate to previous research, as well as develop a new understanding on which subset of IR information best identifies these attributes. Data from 123 subjectively identified CI events observed during the 2007 Convection and Orograpically Induced Precipitation Study (COPS) field experiment conducted over southern Germany and northeastern France are processed, per convective cell, to meet this study’s objectives. A total of 67 IR “interest fields” are initially assessed for growing cumulus clouds, with correlation and principal component analyses used to highlight the top 21 fields that are considered the best candidates for describing the three attributes. Using between 6 and 8 fields per category, a method is then proposed on how growing convective clouds may be quantified per 3-km2 pixel (or per cumulus cloud object) toward inferring each attribute. No independent CI-nowcasting analysis is performed, which instead is the subject of ongoing research.

Description: The three-body scattering signature is an appendage seen on weather radar displays of reflectivity behind strong storm cells. It is caused by multiple scattering between hydrometeors and the ground. The radar equation for this phenomenon is reexamined and corrected to include the coherent wave component producing 3 dB more power than previously reported. Furthermore, the possibility to gauge hail size causing this phenomenon is explored. A model of forward scattering by spherical hail and accepted values of ground backscattering cross sections are used in an attempt to reconcile the reflectivity in this signature with observations. This work demonstrates that the signature can be caused by small- (

Description: The effects of artificial turf (AT) on the urban canopy layer energy balance, air and surface temperatures, and building cooling loads are compared to those of other common ground surface materials (asphalt, concrete, and grass) through heat transfer modeling of radiation, convection, and conduction. The authors apply the Temperatures of Urban Facets in 3D (TUF3D) model—modified to account for latent heat fluxes—to a clear summer day at a latitude of 33° over a typical coastal suburban area in Southern California. The low albedo of artificial turf relative to the other materials under investigation results in a reduction in shortwave radiation incident on nearby building walls and an approximately equal increase in longwave radiation. Consequently, building walls remain at a relatively cool temperature that is similar to those that are adjacent to irrigated grass surfaces. Using a simple offline convection model, replacing grass ground cover with artificial turf was found to add 2.3 kW h m−2 day−1 of heat to the atmosphere, which could result in urban air temperature increases of up to 4°C. Local effects of AT on building design cooling loads were estimated. The increased canopy air temperatures with AT increase heat conduction through the building envelope and ventilation in comparison with a building near irrigated grass. However, in this temperate climate these loads are small relative to the reduction in radiative cooling load through windows. Consequently, overall building design cooling loads near AT decrease by 15%–20%. In addition, the irrigation water conservation with AT causes an embodied energy savings of 10 W h m−2 day−1. Locally, this study points to a win–win situation for AT use for urban landscaping as it results in water and energy conservation.

Description: This paper introduces a new method to improve land surface model skill by merging different available precipitation datasets, given that an accurate land surface parameter ground truth is available. Precipitation datasets are merged with the objective of improving terrestrial water and energy cycle simulation skill, unlike most common methods in which the merging skills are evaluated by comparing the results with gauge data or selected reference data. The optimal merging method developed in this study minimizes the simulated land surface parameter (soil moisture, temperature, etc.) errors using the Noah land surface model with the Nelder–Mead (downhill simplex) method. In addition to improving the simulation skills, this method also impedes the adverse impacts of single-source precipitation data errors. Analysis has indicated that the results from the optimally merged precipitation product have fewer errors in other land surface states and fluxes such as evapotranspiration (ET), discharge R, and skin temperature T than do simulation results obtained by forcing the model using the precipitation products individually. It is also found that, using this method, the true knowledge of soil moisture information minimized land surface modeling errors better than the knowledge of other land surface parameters (ET, R, and T). Results have also shown that, although it does not have the true precipitation information, the method has associated heavier weights with the precipitation product that has intensity, amount, and frequency that are similar to those of the true precipitation.

Description: A combination of rainfall estimates from the 13.8-GHz Tropical Rainfall Measuring Mission (TRMM) precipitation radar (PR) and the 94-GHz CloudSat Cloud Profiling Radar (CPR) is used to assess the distribution of rainfall intensity over tropical and subtropical oceans. These two spaceborne radars provide highly complementary information: the PR provides the best information on the total rain volume because of its ability to estimate the intensity of all but the lightest rain rates while the CPR’s higher sensitivity provides superior rainfall detection as well as estimates of drizzle and light rain. Over the TRMM region between 35°S and 35°N, rainfall frequency from the CPR is around 9%, approximately 2.5 times that detected by the PR, and the CPR estimates indicate a contribution by light rain that is undetected by the PR of around 10% of the total. Stratifying the results by total precipitable water (TPW) as a proxy for rainfall regime indicates dramatic differences over stratus-dominated subsidence regions, with nearly 20% of the total rain occurring as light rain. Over moist tropical regions, the CPR substantially underestimates rain from intense convective storms because of large attenuation and multiple-scattering effects while the PR misses very little of the total rain volume because of a lower relative contribution from light rain. Over low-TPW regions, however, inconsistencies between estimates from the PR and the CPR point to uncertainties in the algorithm assumptions that remain to be understood and addressed.

Description: Elevated layers of high ozone concentration were observed over the Seoul metropolitan region (SMR) in Korea by ozonesonde measurements during 6–9 June 2003. An analysis of the synoptic-scale meteorological features and backward trajectories revealed that the layers were associated with the long-range transport of ozone from eastern China. Further examination of the long-range transport process responsible for the development of these layers was performed using the Community Multiscale Air Quality (CMAQ) model. CMAQ demonstrated that the upward mixing of ozone by convective activity in eastern China and subsequent horizontal transport aloft in the periphery of a slow-moving high pressure system led to the development of thick ozone layers over the SMR. Through comparative simulation studies, it was found that the surface ozone levels in the SMR can be significantly enhanced by the vertical down-mixing of ozone from the layer aloft with the growing mixed layer. On average, about 25% of the surface peak concentration in a given area during a high-ozone episode was due to the influence of the ozone layer aloft developed by the long-range transport process.

Description: This study analyzes the daily-mean surface wind variability over an area characterized by complex topography through comparing observations and a 2-km-spatial-resolution simulation performed with the Weather Research and Forecasting (WRF) model for the period 1992–2005. The evaluation focuses on the performance of the simulation to reproduce the wind variability within subregions identified from observations over the 1999–2002 period in a previous study. By comparing with wind observations, the model results show the ability of the WRF dynamical downscaling over a region of complex terrain. The higher spatiotemporal resolution of the WRF simulation is used to evaluate the extent to which the length of the observational period and the limited spatial coverage of observations condition one’s understanding of the wind variability over the area. The subregions identified with the simulation during the 1992–2005 period are similar to those identified with observations (1999–2002). In addition, the reduced number of stations reasonably represents the spatial wind variability over the area. However, the analysis of the full spatial dimension simulated by the model suggests that observational coverage could be improved in some subregions. The approach adopted here can have a direct application to the design of observational networks.

Description: Deep convective storms with overshooting tops (OTs) are capable of producing hazardous weather conditions such as aviation turbulence, frequent lightning, heavy rainfall, large hail, damaging wind, and tornadoes. This paper presents a new objective infrared-only satellite OT detection method called infrared window (IRW)-texture. This method uses a combination of 1) infrared window channel brightness temperature (BT) gradients, 2) an NWP tropopause temperature forecast, and 3) OT size and BT criteria defined through analysis of 450 thunderstorm events within 1-km Moderate Resolution Imaging Spectroradiometer (MODIS) and Advanced Very High Resolution Radiometer (AVHRR) imagery. Qualitative validation of the IRW-texture and the well-documented water vapor (WV) minus IRW BT difference (BTD) technique is performed using visible channel imagery, CloudSat Cloud Profiling Radar, and/or Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) cloud-top height for selected cases. Quantitative validation of these two techniques is obtained though comparison with OT detections from synthetic satellite imagery derived from a cloud-resolving NWP simulation. The results show that the IRW-texture method false-alarm rate ranges from 4.2% to 38.8%, depending upon the magnitude of the overshooting and algorithm quality control settings. The results also show that this method offers a significant improvement over the WV-IRW BTD technique. A 5-yr Geosynchronous Operational Environmental Satellite (GOES)-12 OT climatology shows that OTs occur frequently over the Gulf Stream and Great Plains during the nighttime hours, which underscores the importance of using a day/night infrared-only detection algorithm. GOES-12 OT detections are compared with objective Eddy Dissipation Rate Turbulence and National Lightning Detection Network observations to show the strong relationship among OTs, aviation turbulence, and cloud-to-ground lightning activity.

Description: Ground-validation (GV) radar-rain products are often utilized for validation of the Tropical Rainfall Measuring Mission (TRMM) space-based rain estimates, and, hence, quantitative evaluation of the GV radar-rain product error characteristics is vital. This study uses quality-controlled gauge data to compare with TRMM GV radar rain rates in an effort to provide such error characteristics. The results show that significant differences of concurrent radar–gauge rain rates exist at various time scales ranging from 5 min to 1 day, despite lower overall long-term bias. However, the differences between the radar area-averaged rain rates and gauge point rain rates cannot be explained as due to radar error only. The error variance separation method is adapted to partition the variance of radar–gauge differences into the gauge area–point error variance and radar-rain estimation error variance. The results provide relatively reliable quantitative uncertainty evaluation of TRMM GV radar-rain estimates at various time scales and are helpful to understand better the differences between measured radar and gauge rain rates. It is envisaged that this study will contribute to better utilization of GV radar-rain products to validate versatile space-based rain estimates from TRMM, as well as the proposed Global Precipitation Measurement satellite and other satellites.

Description: This work is motivated by the observation that large-amplitude wind fluctuations on temporal scales of 1–10 h present challenges for the power management of large offshore wind farms. Wind fluctuations on these scales are analyzed at a meteorological measurement mast in the Danish North Sea using a 4-yr time series of 10-min wind speed observations. An adaptive spectral analysis method called the Hilbert–Huang transform is chosen for the analysis, because the nonstationarity of time series of wind speed observations means that they are not well described by a global spectral analysis method such as the Fourier transform. The Hilbert–Huang transform is a local method based on a nonparametric and empirical decomposition of the data followed by calculation of instantaneous amplitudes and frequencies using the Hilbert transform. The Hilbert–Huang transformed 4-yr time series is averaged and summarized to show climatological patterns in the relationship between wind variability and time of day. First, by integrating the Hilbert spectrum along the frequency axis, a scalar time series representing the total variability within a given frequency range is calculated. Second, by calculating average spectra conditional to time of day, the time axis of the Hilbert spectrum is “remapped” to show climatological patterns. Third, the daily patterns in wind variability and wind speed are compared for the four seasons of the year. It is found that the most intense wind variability occurs in autumn even though the strongest observed wind speeds occur in winter.

Description: In many applications, a realistic description of air temperature inversions is essential for accurate snow and glacier ice melt, and glacier mass-balance simulations. A physically based snow evolution modeling system (SnowModel) was used to simulate 8 yr (1998/99–2005/06) of snow accumulation and snow and glacier ice ablation from numerous small coastal marginal glaciers on the SW part of Ammassalik Island in SE Greenland. These glaciers are regularly influenced by inversions and sea breezes associated with the adjacent relatively low temperature and frequently ice-choked fjords and ocean. To account for the influence of these inversions on the spatiotemporal variation of air temperature and snow and glacier melt rates, temperature inversion routines were added to MircoMet, the meteorological distribution submodel used in SnowModel. The inversions were observed and modeled to occur during 84% of the simulation period. Modeled inversions were defined not to occur during days with strong winds and high precipitation rates because of the potential of inversion breakup. Field observations showed inversions to extend from sea level to approximately 300 m MSL, and this inversion level was prescribed in the model simulations. Simulations with and without the inversion routines were compared. The inversion model produced air temperature distributions with warmer lower-elevation areas and cooler higher-elevation areas than without inversion routines because of the use of cold sea-breeze-based temperature data from underneath the inversion. This yielded an up to 2 weeks earlier snowmelt in the lower areas and up to 1–3 weeks later snowmelt in the higher-elevation areas of the simulation domain. Averaged mean annual modeled surface mass balance for all glaciers (mainly located above the inversion layer) was −720 ± 620 mm w.eq. yr−1 (w.eq. is water equivalent) for inversion simulations, and −880 ± 620 mm w.eq. yr−1 without the inversion routines, a difference of 160 mm w.eq. yr−1. The annual glacier loss for the two simulations was 50.7 × 106 and 64.4 × 106 m3 yr−1 for all glaciers—a difference of ∼21%. The average equilibrium line altitude (ELA) for all glaciers in the simulation domain was located at 875 and 900 m MSL for simulations with or without inversion routines, respectively.

Description: Two approaches to producing a hail climatology for Finland are compared. The first approach is based on 70 yr of hail reports from different sources (newspapers, storm spotters, and other volunteers). The second is derived primarily from radar data. It is shown that a selection of newspaper articles of hail damage covering a period of 70 yr provides a good overview of the typical monthly and diurnal distribution of hail occurrence over the country. Radar data covering five summers (2001–05) provide another data source, but with different potential sources of errors. The two distinct methods compared in this paper give roughly the same results in describing the hail climatology of Finland, which gives additional confidence in each of the methods. On the basis of both methods, most hailstones are observed in the afternoon, 1400–1600 local time. The hail “season” extends from May to early September with maximum occurrences in June, July, and August. This means that hail is most frequently observed when the convective energy available for storm growth is at its diurnal or seasonal peak. The length of the hail season is the same according to both radar and newspaper data. The main difference emerges in relation to July and August events: 37% of news about hail events is published in newspapers in late July but only 8% in early August, whereas for radar data the numbers are more evenly distributed, 33% and 18%, respectively. This can be partially explained by sociological factors—July is the main holiday month in Finland, when outdoor activities in more remote areas are more popular.

Description: A new general polarimetric radar simulator for nonhydrostatic numerical weather prediction (NWP) models has been developed based on rigorous scattering calculations using the T-matrix method for reflectivity, differential reflectivity, specific differential phase, and copolar cross-correlation coefficient. A continuous melting process accounts for the entire spectrum of varying density and dielectric constants. This simulator is able to simulate polarimetric radar measurements at weather radar frequency bands and can take as input the prognostic variables of high-resolution NWP model simulations using one-, two-, and three-moment microphysics schemes. The simulator was applied at 10.7-cm wavelength to a model-simulated supercell storm using a double-moment (two moment) bulk microphysics scheme to examine its ability to simulate polarimetric signatures reported in observational studies. The simulated fields exhibited realistic polarimetric signatures that include ZDR and KDP columns, ZDR arc, midlevel ZDR and ρhυ rings, hail signature, and KDP foot in terms of their general location, shape, and strength. The authors compared the simulation with one employing a single-moment (SM) microphysics scheme and found that certain signatures, such as ZDR arc, midlevel ZDR, and ρhυ rings, cannot be reproduced with the latter. It is believed to be primarily caused by the limitation of the SM scheme in simulating the shift of the particle size distribution toward larger/smaller diameters, independent of mixing ratio. These results suggest that two- or higher-moment microphysics schemes should be used to adequately describe certain important microphysical processes. They also demonstrate the utility of a well-designed radar simulator for validating numerical models. In addition, the simulator can also serve as a training tool for forecasters to recognize polarimetric signatures that can be reproduced by advanced NWP models.

Description: This study integrates a Box–Cox power transformation procedure into a common trend two-phase regression-model-based test (the extended version of the penalized maximal F test, or “PMFred,” algorithm) for detecting changepoints to make the test applicable to non-Gaussian data series, such as nonzero daily precipitation amounts or wind speeds. The detection-power aspects of the transformed method (transPMFred) are assessed by a simulation study that shows that this new algorithm is much better than the corresponding untransformed method for non-Gaussian data; the transformation procedure can increase the hit rate by up to ∼70%. Examples of application of this new transPMFred algorithm to detect shifts in real daily precipitation series are provided using nonzero daily precipitation series recorded at a few stations across Canada that represent very different precipitation regimes. The detected changepoints are in good agreement with documented times of changes for all of the example series. This study clarifies that it is essential for homogenization of daily precipitation data series to test the nonzero precipitation amount series and the frequency series of precipitation occurrence (or nonoccurrence), separately. The new transPMFred can be used to test the series of nonzero daily precipitation (which are non Gaussian and positive), and the existing PMFred algorithm can be used to test the frequency series. A software package for using the transPMFred algorithm to detect shifts in nonzero daily precipitation amounts has been developed and made freely available online, along with a quantile-matching (QM) algorithm for adjusting shifts in nonzero daily precipitation series, which is applicable to all positive data. In addition, a similar QM algorithm has also been developed for adjusting Gaussian data such as temperatures. It is noticed that frequency discontinuities are often inevitable because of changes in the measuring precision of precipitation, and that they could complicate the detection of shifts in nonzero daily precipitation data series and void any attempt to homogenize the series. In this case, one must account for all frequency discontinuities before attempting to adjust the measured amounts. This study also proposes approaches to account for detected frequency discontinuities, for example, to fill in the missed measurements of small precipitation or the missed reports of trace precipitation. It stresses the importance of testing the homogeneity of the frequency series of reported zero precipitation and of various small precipitation events, along with testing the series of daily precipitation amounts that are larger than a small threshold value, varying the threshold over a set of small values that reflect changes in measuring precision over time.

Description: High-resolution wind fields retrieved from satellite synthetic aperture radar (SAR) imagery are combined for mapping of wind resources offshore where site measurements are costly and sparse. A new sampling strategy for the SAR scenes is introduced, based on a method for statistical–dynamical downscaling of large-scale wind conditions using a set of wind classes that describe representative wind situations. One or more SAR scenes are then selected to represent each wind class and the classes are weighted according to their frequency of occurrence. The wind class methodology was originally developed for mesoscale modeling of wind resources. Its performance in connection with sampling of SAR scenes is tested against two sets of random SAR samples and meteorological observations at three sites in the North Sea during 2005–08. Predictions of the mean wind speed and the Weibull scale parameter are within 5% from the mast observations whereas the deviation on power density and the Weibull shape parameter is up to 7%. These results are promising and may be improved further through a better population of the wind classes. Advantages of the wind class sampling method over random sampling include, in principle, selection of the most representative SAR scenes such that wind resources can be predicted from a lower number of SAR samples. Furthermore, the wind class weightings can be adjusted to represent any time period.

Description: Within cumulus cloud fields that develop in conditionally unstable air masses, only a fraction of the cumuli may eventually develop into deep convection. Identifying which of these convective clouds is most likely to generate lightning often starts with little more than a qualitative visual satellite analysis. The goal of this study is to identify the observed satellite infrared (IR) signatures associated with growing cumulus clouds prior to the first lightning strike, or lightning initiation (LI). This study quantifies the behavior of 10 Geostationary Operational Environmental Satellite-12 (GOES-12) IR fields of interest in the 1 h in advance of LI. A total of 172 lightning-producing storms, which occurred during the 2009 convective season, are manually tracked and studied over four regions: northern Alabama, central Oklahoma, the Kennedy Space Center, and Washington, D.C. Four-dimensional and cloud-to-ground lightning array data provide a total cloud lightning picture (in-cloud, cloud-to-cloud, cloud-to-air, and cloud-to-ground) and thus precise LI points for each storm in both time and space. Statistical significance tests are conducted on observed trends for each of the 10 LI fields to determine the unique information each field provides in terms of behavior prior to LI. Eight out of 10 LI fields exhibited useful information at least 15 min in advance of LI, with 35 min being the average. Statistical tests on these eight fields are compared for separate large geographical areas. Median IR temperatures and 3.9-μm reflectance values are then determined for all 172 events as an outcome, which may be valuable when implementing a LI prediction algorithm into real-time satellite-based systems.

Description: This study is a companion research effort to “Part I,” which emphasized use of infrared data for understanding various aspects of growing convective clouds in the Meteosat Second Generation (MSG) satellite’s Spinning Enhanced Visible and Infrared Imager (SEVIRI) imagery. Reflectance and derived brightness variability (BV) fields from MSG SEVIRI are used here to understand relationships between cloud-top signatures and physical processes for growing cumulus clouds prior to known convective initiation (CI) events, or the first occurrence of a ≥35-dBZ echo from a new convective cloud. This study uses daytime SEVIRI visible (VIS) and near-infrared (NIR) reflectances from 0.6 to 3.9 μm (3-km sampling distance), as well as high-resolution visible (1-km sampling distance) fields. Data from 123 CI events observed during the 2007 Convection and Orographically Induced Precipitation Study (COPS) field experiment conducted over southern Germany and northeastern France are processed, per convective cell, so to meet this study’s objectives. These data are those used in Part I. A total of 27 VIS–NIR and BV “interest fields” are initially assessed for growing cumulus clouds, with correlation and principal component analyses used to highlight the fields that contain the most unique information for describing principally cloud-top glaciation, as well as the presence of vigorous updrafts. Time changes in 1.6- and 3.9-μm reflectances, as well as BV in advance of CI, are shown to contain the most unique information related to the formation and increase in size of ice hydrometeors. Several methods are proposed on how results from this analysis may be used to monitor growing convective clouds per MSG pixel or per cumulus cloud “object” over 1-h time frames.

Description: In this study four mesoscale forecasting systems were used to investigate the four-dimensional structure of atmospheric refractivity and ducting layers that occur within evolving synoptic conditions over the eastern seaboard of the United States. The aim of this study was to identify the most important components of forecasting systems that contribute to refractive structures simulated in a littoral environment. Over a 7-day period in April–May of 2000 near Wallops Island, Virginia, meteorological parameters at the ocean surface and within the marine atmospheric boundary layer (MABL) were measured to characterize the spatiotemporal variability contributing to ducting. By using traditional statistical metrics to gauge performance, the models were found to generally overpredict MABL moisture, resulting in fewer and weaker ducts than were diagnosed from vertical profile observations. Mesoscale features in ducting were linked to highly resolved sea surface temperature forcing and associated changes in surface stability and to local variations in internal boundary layers that developed during periods of offshore flow. Sensitivity tests that permit greater mesoscale detail to develop on the model grids revealed that initialization of the simulations and the resolution of sea surface temperature analyses were critical factors for accurate predictions of coastal refractivity.

Description: Inhomogeneity in gridded meteorological data may arise from the inclusion of inhomogeneous station data or from aspects of the gridding procedure itself. However, the homogeneity of gridded datasets is rarely questioned, even though an analysis of trends or variability that uses inhomogeneous data could be misleading or even erroneous. Three gridded precipitation datasets that have been used in studies of the Upper Colorado River basin were tested for homogeneity in this study: that of Maurer et al., that of Beyene and Lettenmaier, and the Parameter–Elevation Regressions on Independent Slopes Model (PRISM) dataset of Daly et al. Four absolute homogeneity tests were applied to annual precipitation amounts on a grid cell and on a hydrologic subregion spatial scale for the periods 1950–99 and 1916–2006. The analysis detects breakpoints in 1977 and 1978 at many locations in all three datasets that may be due to an anomalously rapid shift in the Pacific decadal oscillation. One dataset showed breakpoints in the 1940s that might be due to the widespread change in the number of available observing stations used as input for that dataset. The results also indicated that the time series from the three datasets are sufficiently homogeneous for variability analysis during the 1950–99 period when aggregated on a subregional scale.

Description: Data Collection 5 processing for the Moderate Resolution Imaging Spectroradiometer (MODIS) on board the NASA Earth Observing System (EOS) Terra and Aqua spacecraft includes an algorithm for detecting multilayered clouds in daytime. The main objective of this algorithm is to detect multilayered cloud scenes, specifically optically thin ice cloud overlying a lower-level water cloud, that present difficulties for retrieving cloud effective radius using single-layer plane-parallel cloud models. The algorithm uses the MODIS 0.94-μm water vapor band along with CO2 bands to obtain two above-cloud precipitable water retrievals, the difference of which, in conjunction with additional tests, provides a map of where multilayered clouds might potentially exist. The presence of a multilayered cloud results in a large difference in retrievals of above-cloud properties between the CO2 and the 0.94-μm methods. In this paper the MODIS multilayered cloud algorithm is described, results of using the algorithm over example scenes are shown, and global statistics for multilayered clouds as observed by MODIS are discussed. A theoretical study of the algorithm behavior for simulated multilayered clouds is also given. Results are compared to two other comparable passive imager methods. A set of standard cloudy atmospheric profiles developed during the course of this investigation is also presented. The results lead to the conclusion that the MODIS multilayer cloud detection algorithm has some skill in identifying multilayered clouds with different thermodynamic phases.

Description: Many large grass fires occurred in north Texas and southern Oklahoma on 9 April 2009, destroying hundreds of homes and businesses and burning thousands of acres of grasslands, producing large smoke and debris plumes that were visible from various remote sensing platforms. At the same time, strong westerly winds were transporting large amounts of dust into the region, mixing with the smoke and debris already being generated. This research uses surface- and satellite-based remote sensing observations of this event to assess the locations of fires and the spatial distribution of smoke and dust aerosols. The authors present a unique perspective by analyzing radar observations of fire debris in conjunction with the satellite analysis of submicrometer smoke aerosol particles. Satellite data clearly show the location of the individual fires and the downwind smoke plumes as well as the large dust storm present over the region. In particular, Moderate Resolution Imaging Spectroradiometer (MODIS) aerosol optical thickness at 0.55 μm within the dust plume was around 0.5, and it increased to greater than 1.0 when combined with smoke. Using the difference in 11- versus 12-μm brightness temperature data combined with surface observations, the large extent of the dust plume was evident through much of north-central Texas, where visibilities were low and the 11–12-μm brightness temperature difference was negative. Conversely, smoke plumes were characterized by higher reflectance at 0.6 μm (visible wavelength). Cross sections of radar data through the several smoke and debris plumes indicated the burnt debris reached up to 5 km into the atmosphere. Plume height output from modified severe storm algorithms produced similar values. Since smoke aerosols are smaller and lighter when compared with the debris, they were likely being transported even higher into the atmosphere. These results show that the combination of satellite and radar data offers a unique perspective on observing the characteristics and evolution of smoke and debris plume emanating from grass fire events.

Description: In reference to previously observed concentrations of methane released from a source enclosed by a windbreak, this paper examines a refined “inverse dispersion” approach for estimating the rate of emission Q from a small ground-level source, when the surface-layer winds near that source are highly disturbed. The inverse dispersion method under investigation is based on simulation of turbulent trajectories between sources and detectors, using a Lagrangian stochastic (LS) model. At issue is whether it is advantageous to recognize the flow as being disturbed and use a computed approximation to that disturbed flow to drive a fully three-dimensional LS model (3D-LS), or whether it suffices to ignore flow disturbance and adopt an LS model attuned to the horizontally homogeneous upwind flow (MO-LS, as Monin–Obukhov similarity theory describes the vertical inhomogeneity). It is demonstrated that both approaches estimate the source strength to within a factor of 2 of the true value, irrespectively of the location of the concentration measurement, and moreover that both approaches estimate the source strength correctly (to within the experimental uncertainty), when based on concentrations measured far away from the immediate influence of obstacles in the flow. However, if the concentration detector is positioned close to the flow-disturbing obstacles, then inverse dispersion based on 3D-LS provides a better estimate of source strength than does MO-LS.

Description: The impact of 1973–2005 land use–land cover (LULC) changes on near-surface air temperatures during four recent summer extreme heat events (EHEs) are investigated for the arid Phoenix, Arizona, metropolitan area using the Weather Research and Forecasting Model (WRF) in conjunction with the Noah Urban Canopy Model. WRF simulations were carried out for each EHE using LULC for the years 1973, 1985, 1998, and 2005. Comparison of measured near-surface air temperatures and wind speeds for 18 surface stations in the region show a good agreement between observed and simulated data for all simulation periods. The results indicate consistent significant contributions of urban development and accompanying LULC changes to extreme temperatures for the four EHEs. Simulations suggest new urban developments caused an intensification and expansion of the area experiencing extreme temperatures but mainly influenced nighttime temperatures with an increase of up to 10 K. Nighttime temperatures in the existing urban core showed changes of up to ∼2 K with the ongoing LULC changes. Daytime temperatures were not significantly affected where urban development replaced desert land (increase by ∼1 K); however, maximum temperatures increased by ∼2–4 K when irrigated agricultural land was converted to suburban development. According to the model simulations, urban landscaping irrigation contributed to cooling by 0.5–1 K in maximum daytime as well as minimum nighttime 2-m air temperatures in most parts of the urban region. Furthermore, urban development led to a reduction of the already relatively weak nighttime winds and therefore a reduction in advection of cooler air into the city.

Description: In this work, the authors present observations of enhanced temporal coherency beyond that expected using the observations of the standard deviation of the Doppler velocities and the assumption of a family of exponentially decaying autocorrelation functions. The purpose of this paper is to interpret these observations by developing the complex amplitude autocorrelation function when both incoherent and coherent backscatter are present. Using this expression, it is then shown that when coherent scatter is present, the temporal coherency increases as observed. Data are analyzed in snow and in rain. The results agree with the theoretical expectations, and the authors interpret this agreement as an indication that coherent scatter is the likely explanation for the observed enhanced temporal coherency. This finding does not affect decorrelation times measured using time series. However, when the time series is not available (as in theoretical studies), the times to decorrelation are often computed based upon the assumptions that the autocorrelation function is a member of the family of exponentially decaying autocorrelation functions and that the signal decorrelation is due solely to the Doppler velocity fluctuations associated with incoherent scatter. Such an approach, at times, may significantly underestimate the true required times to decorrelation thus leading to overestimates of statistical reliability of parameters.

Description: This study estimates whether surface observations of temperature, moisture, and wind at some stations in the continental United States are less critical than others for specifying weather conditions in the vicinity of those stations. Two-dimensional variational analyses of temperature, relative humidity, and wind were created for selected midday hours during summer 2008. This set of 8925 control analyses was derived from 5-km-resolution background fields and Remote Automated Weather Station (RAWS) and National Weather Service (NWS) observations within roughly 4° × 4° latitude–longitude domains. Over 570 000 cross-validation experiments were completed to assess the impact of removing each RAWS and NWS station. The presence of observational assets within relatively close proximity to one another is relatively common. The sensitivity to removing temperature, relative humidity, or wind observations varies regionally and depends on the complexity of the surrounding terrain and the representativeness of the observations. Cost savings for the national RAWS program by removing a few stations may be possible. However, nearly all regions of the country remain undersampled, especially mountainous regions of the western United States frequently affected by wildfires.

Description: Area-averaged estimates of Cn2 from high-resolution numerical weather prediction (NWP) model output are produced from local estimates of the spatial structure functions of refractive index with corrections for the inherent smoothing and filtering effects of the underlying NWP model. The key assumptions are the existence of a universal statistical description of small-scale turbulence and a locally universal spatial filter for the NWP model variables. Under these assumptions, spatial structure functions of the NWP model variables can be related to the structure functions of the atmospheric variables and extended to the smaller underresolved scales. The shape of the universal spatial filter is determined by comparisons of model structure functions with the climatological spatial structure function determined from an archive of aircraft data collected in the upper troposphere and lower stratosphere. This method of computing Cn2 has an important advantage over more traditional methods that are based on vertical differences because the structure function–based estimates avoid reference to the turbulence outer length scale. To evaluate the technique, NWP model–derived structure-function estimates of Cn2 are compared with nighttime profiles of Cn2 derived from temperature structure-function sensors attached to a rawinsonde (thermosonde) near Holloman Air Force Base in the United States.

Description: The North Atlantic Oscillation (NAO) is a large-scale climate teleconnection that coincides with worldwide changes in weather. Its impacts have been documented at large scales, particularly in Europe, but not as much at regional scales. Furthermore, despite documented impacts on ecological dynamics in Europe, the NAO’s influence on North American biota has been somewhat overlooked. This paper examines long-term temperature and precipitation trends in the southern Appalachian Mountain region—a region well known for its biotic diversity, particularly in salamander species—and examines the connections between these trends and NAO cycles. To connect the NAO phase shifts with southern Appalachian ecology, trends in stream salamander abundance are also examined as a function of the NAO index. The results reported here indicate no substantial long-term warming or precipitation trends in the southern Appalachians and suggest a strong relationship between cool season (November–April) temperature and precipitation and the NAO. More importantly, trends in stream salamander abundance are best explained by variation in the NAO as salamanders are most plentiful during the warmer, wetter phases.

Description: Temperature data in the mountain forest regions are often extrapolated from temperature data recorded at base stations at lower elevation. Such extrapolation is often based on elevation differences between target regions and base stations at low elevation assuming a constant temperature lapse rate throughout the year. However, this assumption might be problematic where slope circulation is active and decoupled from the regional circulation. To model the seasonal change in the lapse rate, the authors compared daily maximum (Tmax) and minimum temperatures (Tmin) observed at a mountain forest site (Kog–Ma; 1300-m altitude) with those observed at the bottom of the basin (Chiang–Mai; 314-m altitude) in northern Thailand, where slope circulation is active and decoupled from the regional circulation. The difference in Tmax between Kog–Ma and Chiang–Mai (ΔTmax; Kog–Ma minus Chiang–Mai) was relatively unchanged throughout the year. However, the difference in Tmin between Kog–Ma and Chiang–Mai (ΔTmin) changed seasonally. Thus, assuming a constant lapse rate throughout the year could cause large errors in extrapolating Tmin data in mountainous areas in northern Thailand. The difference ΔTmin was related to nighttime net radiation (Rn), suggesting that nocturnal drainage flow affects the determination of ΔTmin. This relationship would be useful in formulating seasonal changes in the lapse rate for Tmin. As Rn data are generally unavailable for meteorological stations, an index that relates to the lapse rate for Tmin and is calculated from Tmax and Tmin data is proposed. This index might be useful for accurately estimating Tmin values in mountainous regions in northern Thailand.

Description: A new method for retrieving air velocity fluctuations in the cloud-capped boundary layer (BL) using radar reflectivity and the Doppler velocity fields is proposed. The method was developed on the basis of data obtained by the Transportable Atmospheric Radar (TARA) located in Cabauw, Netherlands, at 0500–0812 UTC 8 May 2004, and tested using a detailed trajectory ensemble model of the cloud-capped BL. During the observations, the BL depth was 1200 m, and the cloud base (measured by a lidar) was at 500–550 m. No preliminary assumptions concerning the shapes of drop size distributions were made. On the basis of the TARA radar data, vertical profiles of the vertical air velocity standard deviation, of turbulent dissipation rate, etc. were estimated. The correlation functions indicate the existence of large eddies in the BL with a characteristic horizontal scale of about 600 m. Analysis of the slope (the scaling parameter) of the structure functions indicates that turbulence above 400 m can be considered to be isotropic. Below this level, the turbulence becomes anisotropic. The rate of anisotropy increases with the decrease of the height above the surface. The averaged values of the dissipation rate were evaluated as 1–2 cm2 s−3. The importance of using the cloud-capped BL model as a link between different types of observed data (radar, lidar, aircraft, etc.) is discussed. More data should be analyzed to understand the changes in the turbulent structure of the BL during its growth, as well as during cloud and drizzle formation.

Description: Seven different satellite rainfall estimates are evaluated at daily and 10-daily time scales and a spatial resolution of 0.25° latitude/longitude. The reference data come from a relatively dense station network of about 600 rain gauges over Colombia. This region of South America has a very complex terrain with mountain ranges that form the northern tip of the Andes Mountains, valleys between the mountain ranges, and a vast plain that is part of the Amazon. The climate is very diverse with an extremely wet Pacific coast, a dry region in the north, and different rainfall regimes between the two extremes. The evaluated satellite rainfall products are the Tropical Rainfall Measuring Mission 3B42 and 3B42RT products, the NOAA/Climate Prediction Center morphing technique (CMORPH), Precipitation Estimation from Remotely Sensed Information using Artificial Neural Network (PERSIANN), the Naval Research Laboratory’s blended product (NRLB), and two versions of the Global Satellite Mapping of Precipitation moving vector with Kalman filter (GSMaP_MVK and GSMaP_MVK+). The validation and intercomparison of these products is done for the whole as well as different parts of the country. Validation results are reasonably good for daily rainfall over such complex terrain. The best results were obtained for the eastern plain, and the performance of the products was relatively poor over the Pacific coast. In comparing the different satellite products, it was seen that PERSIANN and GSMaP-MVK exhibited poor performance, with significant overestimation by PERSSIAN and serious underestimation by GSMaP-MVK. CMORPH and GSMaP-MVK+ exhibited the best performance among the products evaluated here.

Description: The urban-breeze circulation is a mesoscale response of the atmospheric flow that is related to horizontal variations in temperature associated, for dry conditions, with gradients in sensible heat flux densities. This local circulation is difficult to observe with a simple observational deployment, and the 3D numerical simulations needed to model it are very demanding in computer time. A theoretical approach scaling the daytime urban heat island and urban-breeze characteristics has been developed and provides a simple set of equations that depend on measurable parameters. Three-dimensional high-resolution numerical simulations, performed with the Nonhydrostatic Mesoscale (Meso-NH) atmospheric model, were used to generate a set of urban-breeze circulations forced by an idealized urban environment. The pertinent forcing parameters chosen were the size of the city, the height of the thermal inversion topping the mixed turbulent air layer, and the difference (urban – rural) of surface heat flux. Scaling laws are presented that describe the shape of the urban heat island and the horizontal and vertical wind intensity and profiles.

Description: This study proposes a Bayesian approach to retrieve raindrop size distributions (DSDs) and to estimate rainfall rates from radar reflectivity in horizontal polarization ZH and differential reflectivity ZDR. With this approach, the authors apply a constrained-gamma model with an updated constraining relation to retrieve DSD parameters. Long-term DSD measurements made in central Oklahoma by the two-dimensional video disdrometer (2DVD) are first used to construct a prior probability density function (PDF) of DSD parameters, which are estimated using truncated gamma fits to the second, fourth, and sixth moments of the distributions. The forward models of ZH and ZDR are then developed based on a T-matrix calculation of raindrop backscattering amplitude with the assumption of drop shape. The conditional PDF of ZH and ZDR is assumed to be a bivariate normal function with appropriate standard deviations. The Bayesian algorithm has a good performance according to the evaluation with simulated ZH and ZDR. The algorithm is also tested on S-band radar data for a mesoscale convective system that passed over central Oklahoma on 13 May 2005. Retrievals of rainfall rates and 1-h rain accumulations are compared with in situ measurements from one 2DVD and six Oklahoma Mesonet rain gauges, located at distances of 28–54 km from Norman, Oklahoma. Results show that the rain estimates from the retrieval agree well with the in situ measurements, demonstrating the validity of the Bayesian retrieval algorithm.

Description: Two previously developed Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks (PERSIANN) algorithms that incorporate cloud classification system (PERSIANN-CCS) and multispectral analysis (PERSIANN-MSA) are integrated and employed to analyze the role of cloud albedo from Geostationary Operational Environmental Satellite-12 (GOES-12) visible (0.65 μm) channel in supplementing infrared (10.7 mm) data. The integrated technique derives finescale (0.04° × 0.04° latitude–longitude every 30 min) rain rate for each grid box through four major steps: 1) segmenting clouds into a number of cloud patches using infrared or albedo images; 2) classification of cloud patches into a number of cloud types using radiative, geometrical, and textural features for each individual cloud patch; 3) classification of each cloud type into a number of subclasses and assigning rain rates to each subclass using a multidimensional histogram matching method; and 4) associating satellite gridbox information to the appropriate corresponding cloud type and subclass to estimate rain rate in grid scale. The technique was applied over a study region that includes the U.S. landmass east of 115°W. One reference infrared-only and three different bispectral (visible and infrared) rain estimation scenarios were compared to investigate the technique’s ability to address two major drawbacks of infrared-only methods: 1) underestimating warm rainfall and 2) the inability to screen out no-rain thin cirrus clouds. Radar estimates were used to evaluate the scenarios at a range of temporal (3 and 6 hourly) and spatial (0.04°, 0.08°, 0.12°, and 0.24° latitude–longitude) scales. Overall, the results using daytime data during June–August 2006 indicate that significant gain over infrared-only technique is obtained once albedo is used for cloud segmentation followed by bispectral cloud classification and rainfall estimation. At 3-h, 0.04° resolution, the observed improvement using bispectral information was about 66% for equitable threat score and 26% for the correlation coefficient. At coarser 0.24° resolution, the gains were 34% and 32% for the two performance measures, respectively.

Description: Bark beetles kill millions of acres of trees in the United States annually by using chemical signaling to attack host trees en masse. As an attempt to control infestations, forest managers use synthetic semiochemical sources to attract beetles to traps and/or repel beetles from high-value resources such as trees and stands. The purpose of this study was to develop a simple numerical technique that may be used by forest managers as a guide in the placement of synthetic semiochemicals. The authors used a one-dimensional, one-equation turbulence model (k–lm) to drive a three-dimensional transport and dispersion model. Predictions were compared with observations from a unique tracer gas experiment conducted in a successively thinned loblolly pine canopy. Predictions of wind speed and turbulent kinetic energy compared well with observations. Scalar concentration was predicted well and trends of maximum observed concentration versus leaf area index were captured within 30 m of the release location. A hypothetical application of the numerical technique was conducted for a 12-day period to demonstrate the model’s usefulness to forest managers.

Description: Two years of high-resolution backscatter profiles obtained with a commercial lidar ceilometer in Santiago Basin (33.5°S, 70.6°W) are analyzed. The generally large aerosol load in the Santiago atmospheric boundary layer (ABL) facilitates the use of these backscatter profiles for the retrieval of the daytime mixed layer height (MH), especially around midday. In winter mornings, however, MH retrievals are frequently confused by upper residual aerosol layers, while in summer afternoons very low aerosol concentrations often preclude them. Based on a database formed with successful MH retrievals over Santiago, the hourly, synoptic, and seasonal variability of clear-day MHs are documented. Daytime growth rates of MH show typical values of 50 m h−1 in winter and 100 m h−1 in summer. MHs at 1200 LT (UTC − 4 h) present a fourfold change between the cold months (MH ∼200 m) and the warm months (MH ∼800 m). Interquartile ranges of the monthly distributions of MH are about 200 m, with little change along the seasons. This statistical description of MH data is supplemented with analysis of temperature, solar radiation, and wind data at selected stations located at the basin’s floor, at the basin’s entrance, and at an elevated location representative of a level about 400 m above the basin’s floor. Seasonal MH variability appears highly controlled by the surface energy budget, with about 30% of the top-of-the-atmosphere radiative energy being used in the warming and growth of the daytime MH. Advection of cool air from the marine boundary layer to the west of the basin also appears to be important in the basin’s ABL energy budget in some cases. Stability of the early morning temperature profile in the basin’s air mass is also a factor in the mixed layer growth. Under conditions of large bulk stability of the basin’s air mass, there exist cases of very shallow daytime mixed layers that appear to develop after nights in which the stability is highly enhanced near the surface. Results herein are a first step toward a better understanding of the dynamics of this complex terrain ABL.

Description: Monitoring land surface drought using remote sensing data is a challenge, although a few methods are available. Evapotranspiration (ET) is a valuable indicator linked to land drought status and plays an important role in surface drought detection at continental and global scales. In this study, the evaporative drought index (EDI), based on the estimated actual ET and potential ET (PET), is described to characterize the surface drought conditions. Daily actual ET at 4-km resolution for April–September 2003–05 across the continental United States is estimated using a simple improved ET model with input solar radiation acquired by Moderate-Resolution Imaging Spectroradiometer (MODIS) at a spatial resolution of 4 km and input meteorological parameters from NCEP Reanalysis-2 data at a spatial resolution of 32 km. The PET is also calculated using some of these data. The estimated actual ET has been rigorously validated with ground-measured ET at six Enhanced Facility sites in the Southern Great Plains (SGP) of the Atmosphere Radiation Measurement Program (ARM) and four AmeriFlux sites. The validation results show that the bias varies from −11.35 to 27.62 W m−2 and the correlation coefficient varies from 0.65 to 0.86. The monthly composites of EDI at 4-km resolution during April–September 2003–05 are found to be in good agreement with the Palmer Z index anomalies, but the advantage of EDI is its finer spatial resolution. The EDI described in this paper incorporates information about energy fluxes in response to soil moisture stress without requiring too many meteorological input parameters, and performs well in assessing drought at continental scales.

Description: Surface winds blowing through the Tsushima Strait are statistically investigated using satellite wind measurements and atmospheric reanalysis data. This study first presents structures and seasonal variations of the northeasterly and southwesterly along-strait winds by imposing newly proposed conditions for defining them. Although the speeds of the northeasterly along-strait winds are generally high within the entire strait, the maximum wind speeds are located downwind of the two channels. The southwesterly along-strait winds start to accelerate at the west exit within the strait. Weak-wind regions are formed in the lee of Tsushima Island in both cases. The occurrence frequencies of the northeasterly and southwesterly along-strait winds are high (low) in the warm (cool) season. The northeasterly along-strait winds are more often observed than the southwesterly along-strait winds. The frequency of the northeasterly along-strait wind is extraordinarily high in September, but the averaged wind speed is comparable to those in the other months. Most of the southwesterly along-strait wind cases fall within low-Froude-number regimes, suggesting the significant effects of Tsushima Island on the wind in the strait. Synoptic situations favorable for the along-strait winds are investigated. Correlations between the along-strait wind component and sea level pressure (SLP) indicate that the along-strait winds are induced by SLP perturbations primarily over the Japan Sea and secondarily on the south of the strait. In addition, cluster analysis of the SLP fields shows four representative SLP fields favorable for the along-strait winds and their monthly occurrence frequencies.

Description: A case study illustrating the impact of moisture variability on convection initiation in a synoptically active environment without strong moisture gradients is presented. The preconvective environment on 30 April 2007 nearly satisfied the three conditions for convection initiation: moisture, instability, and a low-level lifting mechanism. However, a sounding analysis showed that a low-level inversion layer and high LFC would prevent convection initiation because the convective updraft velocities required to overcome the convective inhibition (CIN) were much higher than updraft velocities typically observed in convergence zones. Radar refractivity retrievals from the Twin Lakes, Oklahoma (KTLX), Weather Surveillance Radar-1988 Doppler (WSR-88D) showed a moisture pool contributing up to a 2°C increase in dewpoint temperature where the initial storm-scale convergence was observed. The analysis of the storm-relative wind field revealed that the developing storm ingested the higher moisture associated with the moisture pool. Sounding analyses showed that the moisture pool reduced or nearly eliminated CIN, lowered the LFC by about 500 m, and increased CAPE by 2.5 times. Thus, these small-scale moisture changes increased the likelihood of convection initiation within the moisture pool by creating a more favorable thermodynamic environment. The results suggest that refractivity data could improve convection initiation forecasts by assessing moisture variability at finer scales than the current observation network.

Description: The impact of surface flux boundary conditions and geostrophic forcing on multiday evolution of flow in the atmospheric boundary layer (ABL) was assessed using large-eddy simulations (LES). The LES investigations included several combinations of surface boundary conditions (temperature and heat flux) and geostrophic forcing (constant, time varying, time and height varying). The setup was based on ABL characteristics observed during a selected period of the Cooperative Atmosphere–Surface Exchange Study—1999 (CASES-99) campaign. The LES cases driven by a constant geostrophic wind achieved the best agreement with the CASES-99 observations specifically in terms of daytime surface fluxes and daytime and nighttime profiles. However, the nighttime fluxes were significantly overestimated. The LES cases with the surface temperature boundary condition and driven by a time- and height-varying geostrophic forcing showed improved agreement with the observed nighttime fluxes, but there was less agreement with other observations (e.g., daytime profiles). In terms of the surface boundary condition, the LES cases driven by either surface temperature or heat fluxes produced similar trends in terms of the daytime profiles and comparisons with data from soundings. However, in reproducing the fluxes and nighttime profiles, the agreement was better with imposed temperature because of its ability to interact dynamically with the air temperature field. Therefore, it is concluded that surface temperature boundary condition is better suited for simulations of temporally evolving ABL flow as in the diurnal evolution of the ABL.

Description: A climatological analysis was conducted of the environmental and atmospheric conditions that occurred during 125 identified lake-effect (LE) precipitation events in the New York State Finger Lakes region for the 11 winters (October–March) from 1995/96 through 2005/06. The results complement findings from an earlier study reporting on the frequency and temporal characteristics of Finger Lakes LE events that occurred as 1) isolated precipitation bands over and downwind of a lake (NYSFL events), 2) an enhancement of LE precipitation originating from Lake Ontario (LOenh events), 3) an LE precipitation band embedded within widespread synoptic precipitation (SYNOP events), or 4) a transition from one type to another. In comparison with SYNOP and LOenh events, NYSFL events developed with the 1) coldest temperatures, 2) largest lake–air temperature differences, 3) weakest wind speeds, 4) highest sea level pressure, and 5) lowest height of the stable-layer base. Several significant differences in conditions were found when only one or both of Cayuga and Seneca Lakes, the largest Finger Lakes, had LE precipitation as compared with when the smaller Finger Lakes also produced LE precipitation. In addition, transitional events containing an NYSFL time period occurred in association with significantly colder and drier air masses, larger lake–air temperature differences, and a less stable and shallower boundary layer in comparison with those associated with solitary NYSFL events.

Description: A morphometric analysis of a southern European city and the derivation of relevant fluid dynamical parameters for use in urban flow and dispersion models are explained in this paper. Calculated parameters are compared with building statistics that have already been computed for parts of three northern European and two North American cities. The aim of this comparison is to identify similarities and differences between several building configurations and city types, such as building packing density, compact versus sprawling neighborhoods, regular versus irregular street orientation, etc. A novel aspect of this work is the derivation and use of digital elevation models (DEMs) for parts of a southern European city. Another novel aspect is the DEMs’ construction methodology, which is low cost, low tech, and of simple implementation. Several building morphological parameters are calculated from the urban DEMs using image processing techniques. The correctness and robustness of these techniques have been verified through a series of sensitivity tests performed on both idealized building configurations, as well as on real case DEMs, which were derived using the methodology here. In addition, the planar and frontal area indices were calculated as a function of elevation. It is argued that those indices, estimated for neighborhoods of real cities, may be used instead of the detailed building geometry within urban canopy models as those indices together synthesize the geometric features of a city. The direct application of these results will facilitate the development of fast urban flow and dispersion models.

Description: The potential of rainfall-rate assignment using Meteosat Second Generation (MSG) Spinning Enhanced Visible and Infrared Instrument (SEVIRI) data is investigated. For this purpose, a new conceptual model for precipitation processes in connection with midlatitude cyclones is developed, based on the assumption that high rainfall rates are linked to a high optical thickness and a large effective particle radius, whereas low rainfall rates are linked to a low optical thickness and a small effective particle radius. Reflection values in the 0.56–0.71-μm (VIS0.6) and 1.5–1.78-μm (NIR1.6) channels, which provide information about the optical thickness and the effective radius, are considered in lieu of the optical and microphysical cloud properties. An analysis of the relationship between VIS0.6 and NIR1.6 reflection and the ground-based rainfall rate revealed a high correlation between the sensor signal and the rainfall rate. Based on these findings, a method for rainfall-rate assignment as a function of VIS0.6 and NIR1.6 reflection is proposed. The validation of the proposed technique showed encouraging results, especially for temporal resolutions of 6 and 12 h. This is a significant improvement compared to existing IR retrievals, which obtain comparable results for monthly resolution. The existing relationship between the VIS0.6 and NIR1.6 reflection values and the ground-based rainfall rate is corroborated with the new conceptual model. The good validation results indicate the high potential for rainfall retrieval in the midlatitudes with the high spatial and temporal resolution provided by MSG SEVIRI.

Description: An improvement was developed and tested for surface longwave flux algorithms used in the Clouds and the Earth’s Radiant Energy System processing based on lessons learned during the validation of global results of those algorithms. The algorithms involved showed significant overestimation of downward longwave flux for certain regions, especially dry–arid regions during hot times of the day. The primary cause of this overestimation was identified and the algorithms were modified to (i) detect meteorological conditions that would produce an overestimation, and (ii) apply a correction when the overestimation occurred. The application of this correction largely eliminated the positive bias that was observed in earlier validation studies. Comparisons of validation results before and after the application of correction are presented.

Description: Coastally trapped wind reversals (CTWRs) occur periodically in the marine boundary layer off the western coast of the United States and dramatically change the low-level wind regime and coastal weather. Southerly flow becomes established with the passage of a CTWR along with cooler temperatures and a low stratus deck in a narrow band along the coast. CTWRs can propagate northward along the coast for hundreds of kilometers. A strong CTWR commenced in southern California on 22 June 2006 and moved north along the California coastline before stalling at Cape Mendocino on 24 June 2006. A transcritical Froude number differentiates the CTWR layer from the climatologically favored northern wind regime to the north of Cape Mendocino and indicates a barrier to the movement of a density current. A well-defined cloud boundary is present as detected by radar and satellite imagery and sharp gradients exist in the basic-state parameters as measured by instrumented aircraft. As the Pacific high migrates back offshore, the horizontal pressure field near Cape Mendocino becomes increasingly adverse to the continued northward movement of the CTWR layer and typical summertime conditions are reestablished. Observations and modeling results show that the cessation phase of this CTWR was characterized by a surprising lack of topographic blocking due to the mountainous coastal terrain and Cape Mendocino massif. The horizontal pressure field over the ocean to the north of the CTWR was the key impeding force to continued propagation of this event.

Description: Soon, the National Weather Service’s Weather Surveillance Radar-1988 Doppler (WSR-88D) network will be upgraded to allow dual-polarization capabilities. Therefore, it is imperative to understand and identify microphysical processes using the polarimetric variables. Though melting and size sorting of hydrometeors have been investigated, there has been relatively little focus devoted to the impacts of evaporation on the polarimetric characteristics of rainfall. In this study, a simple explicit bin microphysics one-dimensional rainshaft model is constructed to quantify the impacts of evaporation (neglecting the collisional processes) on vertical profiles of polarimetric radar variables in rain. The results of this model are applicable for light to moderate rain (

Description: The individual components of the slope-parallel surface radiation balance were measured in and around Arizona’s Meteor Crater to investigate the effects of topography on the radiation balance. The crater basin has a diameter of 1.2 km and a depth of 170 m. The observations cover the crater floor, the crater rim, four sites on the inner sidewalls on an east–west transect, and two sites outside the crater. Interpretation of the role of topography on radiation differences among the sites on a representative clear day is facilitated by the unique symmetric crater topography. The shortwave radiation balance was affected by the topographic effects of terrain exposure, terrain shading, and terrain reflections, and by surface albedo variations. Terrain exposure caused a site on the steeper upper eastern sidewall of the crater to receive 6% more daily integrated shortwave energy than a site on the lower part of the same slope. Terrain shading had a larger effect on the lower slopes than on the upper slopes. At the lower western slope site the daily total was reduced by 6%. Measurements indicate a diffuse radiation enhancement due to sidewall reflections. The longwave radiation balance was affected by counterradiation from the crater sidewalls and by reduced emissions due to the formation of a nighttime temperature inversion. The total nighttime longwave energy loss at the crater floor was 72% of the loss observed at the crater rim.

Description: The annual rainfall pattern of the intra-Americas sea reveals a bimodal feature with a minimum during the midsummer known as the midsummer dry spell (MSD). A first attempt is made to examine the impact of the MSD on vegetation through a normalized difference vegetation index (NDVI) analysis in Jamaica. Tropical Rainfall Measuring Mission rainfall estimates and NDVI derived from the Terra Moderate Resolution Imaging Spectroradiometer highlight a consistent MSD feature in both rainfall and vegetative vigor. Spatial variation of this MSD NDVI response is evident throughout Jamaica, with the strongest relationship between the rainfall reduction and NDVI decline throughout the southern portions of Jamaica including the area of major domestic food production. In all years except 2005 there is a notable reduction from early-summer NDVI to midsummer NDVI in this agricultural region. However, the lagged vegetative response undergoes clear interannual variation and is affected by other forcings besides rainfall, such as brush fires and extreme wind.

Description: This paper presents a study of spatiotemporal variation of lightning activity over Peninsular India (8°–22°N, 72°–88°E) by using monthly satellite-based lightning flash grid (1° × 1°) data for a period of 10 yr (1998–2007). The data are examined in terms of spatial, annual, and seasonal distribution of the lightning activity. It is found that lightning activity is higher over south Peninsular India and eastern India. On a seasonal time scale, the lightning activity shows two maxima—first in the month of May and then in the month of September. The lightning activity in the monsoon period is noticed to be considerable because of the occurrence of the low-level jet and increase in the monsoon break period. During the postmonsoon, the activity is mainly due to the presence of the convective nature of the disturbed weather during the northeast monsoon season over most parts of the east coast of south Peninsular India. The relationship between lightning activity over Peninsular India and sea surface temperature in the bordering seas (Arabian Sea and Bay of Bengal) is also examined. The results disclose a significant link between them.

Description: Rainfall products from radar, satellite, rain gauges, and combinations have been evaluated for a season of record rainfall in a heavily instrumented study domain in Oklahoma. Algorithm performance is evaluated in terms of spatial scale, temporal scale, and rainfall intensity. Results from this study will help users of rainfall products to understand their errors. Moreover, it is intended that developers of rainfall algorithms will use the results presented herein to optimize the contribution from available sensors to yield the most skillful multisensor rainfall products.

Description: A groundbreaking new-concept multiwavelength dual-polarized Advanced Microwave Radiometer for Rain Identification (ADMIRARI) has been built and continuously operated in two field campaigns: the Convective and Orographically Induced Precipitation Study (COPS) and the European Integrated Project on Aerosol Cloud Climate Air Quality Interactions (EUCAARI). The radiometer has 6 channels working in horizontal and vertical polarization at 10.65, 21.0, and 36.5 GHz, and it is completely steerable both in azimuth and in elevation. The instrument is suited to be operated in rainy conditions and is intended for retrieving simultaneously water vapor, rain, and cloud liquid water paths. To this goal the authors implemented a Bayesian retrieval scheme based on many state realizations simulated by the Goddard Cumulus Ensemble model that build up a prior probability density function of rainfall profiles. Detailed three-dimensional radiative transfer calculations, which account for the presence of nonspherical particles in preferential orientation, simulate the downwelling brightness temperatures and establish the similarity of radiative signatures and thus the probability that a given profile is actually observed. Particular attention is devoted to the sensitivity of the ADMIRARI signal to 3D effects, raindrop size distribution, and axial ratio parameterizations. The polarization and multifrequency signals represent key information to separate the effects introduced by non-Rayleigh scatterers and to separate rainwater (r-LWP) from the cloud water component (c-LWP). Long-term observations demonstrate that observed brightness temperatures and polarization differences can be well interpreted and reproduced by the simulated ones for all three channels simultaneously. Rough estimates of r-LWP derived from collocated observations with a micro rain radar confirm the rain/no rain separation and the variability trend of r-LWP provided by the radiometer-based retrieval algorithm. With this work the authors demonstrate the potential of ADMIRARI to retrieve information about the rain/cloud partitioning for midlatitude precipitation systems; future studies with this instrument will provide crucial information on rain efficiency of clouds for cloud modelers that might lead toward a better characterization of rain processes.

Description: The National Oceanic and Atmospheric Administration National Climatic Data Center has served as the archive of the Defense Meteorological Satellite Program Special Sensor Microwave Imager (SSM/I) data from the F-8, F-10, F-11, F-13, F-14, and F-15 platforms covering the period from July 1987 to the present. Passive microwave satellite measurements from SSM/I have been used to generate climate products in support of national and international programs. The SSM/I temperature data record (TDR) and sensor data record (SDR) datasets have been reprocessed and stored as network Common Data Form (netCDF) 3-hourly files. In addition to reformatting the data, a normalized anomaly (z score) for each footprint temperature value was calculated by subtracting each radiance value with the corresponding monthly 1° grid climatological mean and dividing it by the associated climatological standard deviation. Threshold checks were also used to detect radiance, temporal, and geolocation values that were outside the expected ranges. The application of z scores and threshold parameters in the form of embedded quality flags has improved the fidelity of the SSM/I TDR/SDR period of record for climatological applications. This effort has helped to preserve and increase the data maturity level of the longest satellite passive microwave period of record while completing a key first step before developing a homogenized and intercalibrated SSM/I climate data record in the near future.

Description: It is well acknowledged that there are large uncertainties associated with the operational quantitative precipitation estimates produced by the U.S. national network of the Weather Surveillance Radar-1988 Doppler (WSR-88D). These errors result from the measurement principles, parameter estimation, and the not fully understood physical processes. Even though comprehensive quantitative evaluation of the total radar-rainfall uncertainties has been the object of earlier studies, an open question remains concerning how the error model results are affected by parameter values and correction setups in the radar-rainfall algorithms. This study focuses on the effects of different exponents in the reflectivity–rainfall (Z–R) relation [Marshall–Palmer, default Next Generation Weather Radar (NEXRAD), and tropical] and the impact of an anomalous propagation removal algorithm. To address this issue, the authors apply an empirically based model in which the relation between true rainfall and radar rainfall could be described as the product of a systematic distortion function and a random component. Additionally, they extend the error model to describe the radar-rainfall uncertainties in an additive form. This approach is fully empirically based, and rain gauge measurements are considered as an approximation of the true rainfall. The proposed results are based on a large sample (6 yr) of data from the Oklahoma City radar (KTLX) and processed through the Hydro-NEXRAD software system. The radar data are complemented with the corresponding rain gauge observations from the Oklahoma Mesonet and the Agricultural Research Service Micronet.

Description: The problem of providing dispersion models with meteorological information from general atmospheric models used, for example, for weather forecasting is considered. As part of a generalized meteorological-to-dispersion model interface, a noniterative scheme diagnosing the surface layer characteristics from wind, temperature, and humidity profiles was developed. The scheme verification included long-term comparison with data of meteorological masts at Cabauw, the Netherlands, and Hyytiälä, Finland. The algorithm compatibility and consistency with the High-Resolution Limited-Area Model (HIRLAM) was also checked, as this model is routinely used as a meteorological driver for the Air Quality and Emergency Modeling System (SILAM). The comparison with Cabauw mast data showed a good quantitative agreement between observed and diagnosed heat and momentum fluxes: the temporal correlation coefficient was ∼0.8, bias was less than 10% of the absolute flux levels, regression slope deviated from unity for less than 20% with the intercept being less than 10% of the absolute flux values, and so on. In the case of complex surface features (Hyytiälä mast in forest) the scheme proved to be robust with large deviations appearing only if the input profile data were taken outside the constant-flux layer. Comparison with the HIRLAM model showed qualitatively good agreement but also highlighted several differences between the goals, standards, and methodologies of meteorological and dispersion models. The scheme was implemented in SILAM, which served as the development platform.

Description: A study of air quality was performed using a compact, aircraft aerosol lidar designed in the Science Directorate at NASA Langley Research Center and Moderate Resolution Imaging Spectroradiometer (MODIS) aerosol optical depth (AOD) retrievals. Five flights of lidar measurements conducted in the Hampton–Norfolk–Virginia Beach, Virginia, region showed complex regional aerosol distributions. Comparisons with MODIS AOD at 10 km × 10 km and 5 km × 5 km resolutions show good agreement, with correlation R2 values of 0.82 and 0.88, respectively. Linear regressions of particulate matter with a diameter of less than 2.5 μm (PM2.5) and AOD within the ranges of 5–40 μg m−3 and 0.05–0.7, respectively, result in R2 values of ∼0.64 and ∼0.82 for MODIS and the Compact Aerosol Lidar, respectively. The linear regressions reflect approximately 51 μg m−3 to 1 AOD. These relationships are in agreement with previous findings for air pollution aerosols in the eastern United States and in northern Italy. However, large vertical variation is seen case by case, with planetary boundary layer heights ranging between 0.7 and 2 km and uncertainties ranging between 0.1 and 0.4 km. The results of the case studies suggest that AOD can be used as an indicator of surface measurements of PM2.5 but with larger uncertainties associated with small aerosol loading (AOD 〈 0.3).

Description: Daily observations of cloud condensation nuclei (CCN) were made for three summer months in 2005 at a site in rural western North Dakota. The goal was to define the natural background CCN population characteristics and to lay the groundwork for investigating the potential impact of intentionally modifying clouds in this region using hygroscopic cloud-seeding techniques. Concentrations of CCN active at ∼0.5% supersaturation, averaged over several midday hours on each day, ranged from less than 200 to more than 1700 cm−3. This is similar to variability in CCN concentrations that have been observed in past studies in other rural areas of the central and northern high plains of the United States. At this site, only 2 out of 17 days with active convection at that site were characterized by concentrations of less than 300 cm−3 active at 0.5% supersaturation, indicating that the region is characterized by typically continental CCN populations on most convective days. Operational seeding might be more effectively conducted if CCN population characteristics could be forecast based on source regions for air forecast to arrive in a particular region on a particular day. However, back-trajectory calculations were found to have limited use for predicting CCN concentrations based on prior history of the air arriving at this observation site during this period.

Description: A surface-precipitation-rate retrieval algorithm for 13-channel Advanced Microwave Sounding Unit (AMSU) millimeter-wave spectral observations from 23 to 191 GHz is described. It was trained using cloud-resolving fifth-generation Pennsylvania State University–National Center for Atmospheric Research Mesoscale Model (MM5) simulations over 106 global storms. The resulting retrievals from the U.S. NOAA-15 and NOAA-16 operational weather satellites are compared with average annual accumulations (mm yr−1) for 2006–07 observed by 787 rain gauges globally distributed across 11 surface classifications defined using Advanced Very High Resolution Radiometer infrared spectral images and two classifications defined geographically. Most surface classifications had bias ratios for AMSU/gauges that ranged from 0.88 to 1.59, although higher systematic AMSU overestimates by factors of 2.4, 3.1, and 9 were found for grassland, shrubs over bare ground, and pure bare ground, respectively. The retrievals were then empirically corrected using these observed biases for each surface type. Global images of corrected average annual accumulations of rain, snow, and convective and stratiform precipitation are presented for the period 2002–07. Most results are consistent with Global Precipitation Climatology Project estimates. Evidence based on MM5 simulations suggests that near-surface evaporation of precipitation may have necessitated most of the corrections for undervegetated surfaces. A new correction for radio-frequency interference affecting AMSU is also presented for the same two NOAA satellites and improves retrieval accuracies.

Description: The Montreal Urban Snow Experiment was dedicated to furthering the understanding of micrometeorological processes involved in the late winter–early spring transition period in a Canadian city. A surface energy budget (SEB) measurement site was installed in a dense residential area of Montreal for several weeks in 2005 and 2006. This paper focuses on the last 6 days of the 2006 experiment (23–28 March 2006), after snowmelt and before vegetation became active, with the objectives of providing a better understanding of physical processes involved during this transition period and examining their impact on the SEB. The Town Energy Balance urban canopy model and the Interactions between Soil, Biosphere, and Atmosphere force–restore land surface model are used in stand-alone mode and are forced with meteorological data measured at the top of a 20-m AGL instrumented tower. Preliminary results reveal deficiencies in the models’ ability to simulate the surface energy budget partitioning, and in particular show overestimation of the sensible heat flux. Sensitivity studies indicate that a large portion of these problems is related to the latent heat transfer involved in natural soil freeze/thaw processes, which has a significant effect on the surface energy budget in this urban area. It is also found that the SEB in this particular situation is very sensitive to the thermal roughness length used for local energy exchange over the roof and road surfaces.

Description: The Clouds and the Earth’s Radiant Energy System (CERES) project uses two shortwave (SW) and two longwave (LW) algorithms to derive surface radiative fluxes on an instantaneous footprint basis from a combination of top-of-atmosphere fluxes, ancillary meteorological data, and retrieved cloud properties. Since the CERES project examines the radiative forcings and feedbacks for Earth’s entire climate system, validation of these models for a wide variety of surface conditions is paramount. The present validation effort focuses upon the ability of these surface-only flux algorithms to produce accurate CERES Edition 2B single scanner footprint data from the Terra and Aqua spacecraft measurements. To facilitate the validation process, high-quality radiometric surface observations have been acquired that were coincident with the CERES-derived surface fluxes. For both SW models, systematic errors range from −20 to −12 W m−2 (from −2.8% to −1.6%) for global clear-sky cases, while for the all-sky SW model, the systematic errors range from 14 to 21 W m−2 (3.2%–4.8%) for global cloudy-sky cases. Larger systematic errors were seen for the individual surface types, and significant random errors where observed, especially for cloudy-sky cases. While the SW models nearly achieved the 20 W m−2 accuracy requirements established for climate research, further improvements are warranted. For the clear-sky LW model, systematic errors were observed to fall within ±5.4 W m−2 (±1.9%) except for the polar case in which systematic errors on the order from −15 to −11 W m−2 (from −13% to −7.2%) occurred. For the all-sky LW model, systematic errors were less than ±9.2 W m−2 (±7.6%) for both the clear-sky and cloudy-sky cases. The random errors were less than 17 W m−2 (6.2%) for clear-sky cases and 28 W m−2 (13%) for cloudy-sky cases, except for the desert cases in which very high surface skin temperatures caused an overestimation in the model-calculated surface fluxes. Overall, however, the LW models met the accuracy requirements for climate research.

Description: A satellite microwave emission brightness temperature histograms (METH) technique has been applied to Special Sensor Microwave Imager (SSM/I) data taken on board the Defense Meteorological Satellite Program (DMSP) satellites and preprocessed by Remote Sensing Systems (RSS) Co. to produce 21 yr (July 1987–present) of oceanic rainfall products. These rain products are used as input to the Global Precipitation Climatology Project (GPCP) rain maps. Analysis of the METH product using SSM/I version-4 (V4) data shows jumps in vertically polarized 19-GHz brightness temperatures that are attributed to changes in DMSP satellites. A version-6 (V6) SSM/I that corrects for intersatellite differences was released by RSS in 2006. The jumps in the time series are reduced, with most of the changes occurring in the early part of the DMSP F13 data. The bias between RSS V6 and V4 of brightness temperature at 19 and 22 GHz is less than 0.5 K. METH rain rates were reprocessed using V6 data and were analyzed. The 20-yr global mean difference between the METH V4 and V6 is less than 0.3%, with differences as large as 3% in individual years. Trend analyses show increases in the oceanic rain belts, such as the intertropical convergence zone and the South Pacific convergence zone, and in the Bay of Bengal. These rain-rate trends, from both linear trend analysis and empirical mode decomposition analysis, are comparable to the version-2 GPCP analyses but are smaller than those found in the unified microwave ocean retrieval algorithm.

Description: A climatological description (“climatology”) of storm surges and actual flooding (storm tide) events from 1959 to 2007 is presented for the New York City (NYC) harbor. The prevailing meteorological conditions associated with these surges are also highlighted. Two surge thresholds of 0.6–1.0 m and 〉1.0 m were used at the Battery, New York (south side of Manhattan in NYC), to identify minor and moderate events, respectively. The minor-surge threshold combined with a tide at or above mean high water (MHW) favors a coastal flood advisory for NYC, and the moderate surge above MHW leads to a coastal flood warning. The number of minor surges has decreased gradually during the last several decades at NYC while the number of minor (storm tide) flooding events has increased slightly given the gradual rise in sea level. There were no moderate flooding events at the Battery from 1997 to 2007, which is the quietest period during the last 50 yr. However, if sea level rises 12–50 cm during the next century, the number of moderate flooding events is likely to increase exponentially. Using cyclone tracking and compositing of the NCEP global reanalysis (before 1979) and regional reanalysis (after 1978) data, the mean synoptic evolution was obtained for the NYC surge events. There are a variety of storm tracks associated with minor surges, whereas moderate surges favor a cyclone tracking northward along the East Coast. The average surface winds at NYC veer from northwesterly at 48 h before the time of maximum surge to a persistent period of east-northeasterlies beginning about 24 h before the surge. There is a relatively large variance in wind directions and speeds around the time of maximum surge, thus suggesting the importance of other factors (fetch, storm duration and track, etc.).

Description: This study analyzes the occurrence of the visibility (Vis) versus precipitation rates (PR) for rain and versus relative humidity (RH) from surface observations that were collected during the Fog Remote Sensing and Modeling (FRAM) field project, which was conducted near Toronto, Ontario, Canada, during the winter of 2005/06 and in Lunenburg, Nova Scotia, during the summers of 2006 and 2007. The main observations used in the analysis were PR and Vis for rain episodes from the Vaisala, Inc., FD12P present-weather sensor and RH and temperature from the Campbell Scientific Instruments, Inc., HMP45 sensor. The PR is compared with those from a total precipitation sensor to check the accuracy of the FD12P measurements. Vis parameterizations related to precipitation type have been previously studied by many other researchers and showed large variability in Vis (up to 1 order of magnitude) for a fixed PR. The results from the work presented here suggest that 1) significant differences exist among the various parameterizations of Vis (deterministic approach) and 2) statistical relationships obtained using fits applied to percentiles (probabilistic approach) can be a feasible alternative for model applications. Comparisons of previous parameterizations with the new Vis relationships suggest that simulated Vis values based on probabilistic approaches could be used in extreme-weather applications.

Description: Typhoon passages across Taiwan can generate sudden surface warming in downslope regions. Special characteristics and mechanisms for 54 such warming events that were identified during the 1961–2007 period are examined. Preferred warming regions were identified in northwest Taiwan, where warming is generated by downslope flow from east or northeast winds in westward-moving typhoons, and in southeast Taiwan, where it is generated by downslope flow from west or northwest winds in northwestward-moving typhoons. In addition to the orographic effect, warmings occurred exclusively within nonprecipitation zones of typhoons. Most northwest (southeast) warmings occur during the day (night) with an average lifetime of 4 (5) h, which roughly corresponds to the average time a nonprecipitation zone remains over a station. During the period examined, three typhoons generated warming events in both northwest and southeast Taiwan, and only Typhoon Haitang (2005) generated warmings with comparable magnitudes (∼12-K increase) in both regions. For Typhoon Haitang as an example, diagnostic analyses with two different approaches reveal that the majority of the warming is contributed by downslope adiabatic warming, but the warming associated with the passage of a nonprecipitation zone is not negligible. Similar results were found when these two diagnostic approaches were applied to the other warming events. The diurnal mode of the atmospheric divergent circulation over East Asia–western North Pacific undergoes a clockwise rotation. The vorticity tendency generated by this diurnal divergent circulation through vortex stretching may modulate the arrival time of typhoons to cause daily (nighttime) warming in the northwest (southeast).

Description: The depth h of the stable boundary layer (SBL) has long been an elusive measurement. In this diagnostic study the use of high-quality, high-resolution (Δz = 10 m) vertical profile data of the mean wind U(z) and streamwise variance σu2(z) is investigated to see whether mean-profile features alone can be equated with h. Three mean-profile diagnostics are identified: hJ, the height of maximum low-level-jet (LLJ) wind speed U in the SBL; h1, the height of the first zero crossing or minimum absolute value of the magnitude of the shear ∂U/∂z profile above the surface; and h2, the minimum in the curvature ∂2U/∂z2 profile. Boundary layer BL here is defined as the surface-based layer of significant turbulence, so the top of the BL was determined as the first significant minimum in the σu2(z) profile, designated as hσ. The height hσ was taken as a reference against which the three mean-profile diagnostics were tested. Mean-wind profiles smooth enough to calculate second derivatives were obtained by averaging high-resolution Doppler lidar profile data, taken during two nighttime field programs in the Great Plains, over 10-min intervals. Nights are chosen for study when the maximum wind speed in the lowest 200 m exceeded 5 m s−1 (i.e., weak-wind, very stable BLs were excluded). To evaluate the three diagnostics, data from the 14-night sample were divided into three profile shapes: Type I, a traditional LLJ structure with a distinct maximum or “nose,” Type II, a “flat” structure with constant wind speed over a significant depth, and Type III, having a layered structure to the shear and turbulence in the lower levels. For Type I profiles, the height of the jet nose hJ, which coincided with h1 and h2 in this case, agreed with the reference SBL depth to within 5%. The study had two major results: 1) among the mean-profile diagnostics for h, the curvature depth h2 gave the best results; for the entire sample, h2 agreed with hσ to within 12%; 2) considering the profile shapes, the layered Type III profiles gave the most problems. When these profiles could be identified and eliminated from the sample, regression and error statistics improved significantly: mean relative errors of 8% for hJ and h1, and errors of

Description: Retrieval schemes often use two important components: 1) a radiative transfer model (RTM) inside the retrieval procedure or to construct the learning dataset for the training of the statistical retrieval algorithms and 2) a numerical weather prediction (NWP) model to provide a first guess or, again, to construct a learning dataset. This is particularly true in operational centers. As a consequence, any physical retrieval or similar method is limited by inaccuracies in the RTM and NWP models on which it is based. In this paper, a method for partially compensating for these errors as part of the sensor calibration is presented and evaluated. In general, RTM/NWP errors are minimized as best as possible prior to the training of the retrieval method, and then tolerated. The proposed method reduces these unknown and generally nonlinear residual errors by training a separate preprocessing neural network (NN) to produce calibrated radiances from real satellite data that approximate those radiances produced by the “flawed” NWP and RTM models. The final “compensated/flawed” retrieval assures better internal consistency of the retrieval procedure and then produces more accurate results. To the authors’ knowledge, this type of NN model has not been used yet for this purpose. The calibration approach is illustrated here on one particular application: the retrieval of atmospheric water vapor from the Advanced Microwave Scanning Radiometer for Earth Observing System (AMSR-E) and the Humidity Sounder for Brazil (HSB) measurements for nonprecipitating scenes, over land and ocean. Before being inverted, the real observations are “projected” into the space of the RTM simulation space from which the retrieval is designed. Validation of results is performed with radiosonde measurements and NWP analysis departures. This study shows that the NN calibration of the AMSR-E/HSB observations improves water vapor inversion, over ocean and land, for both clear and cloudy situations. The NN calibration is efficient and very general, being applicable to a large variety of problems. The nonlinearity of the NN allows for the calibration procedure to be state dependent and adaptable to specific cases (e.g., the same correction will not be applied to medium-range measurement and to extreme conditions). Its multivariate nature allows for a full exploitation of the complex correlation structure among the instrument channels, making the calibration of each single channel more robust. The procedure would make it possible to project the satellite observations in a reference observational space defined by radiosonde measurements, RTM simulations, or other instrument observational space.

Description: New evidence from collocated measurements, with support from theory and numerical simulations, that multidirectional measurements in the oxygen A band from the third Polarization and Directionality of the Earth’s Reflectances (POLDER-3) instrument on the Polarization and Anisotropy of Reflectances for Atmospheric Sciences coupled with Observations from a Lidar (PARASOL) satellite platform within the “A-Train” can help to characterize the vertical structure of clouds is presented. In the case of monolayered clouds, the standard POLDER cloud oxygen pressure product PO2 is shown to be sensitive to the cloud geometrical thickness H in two complementary ways: 1) PO2 is, on average, close to the pressure at the geometrical middle of the cloud layer (MCP) and methods are proposed for reducing the pressure difference PO2 − MCP and 2) the angular standard deviation of PO2 and the cloud geometrical thickness H are tightly correlated for liquid clouds. Accounting for cloud phase, there is thus the potential to obtain a statistically reasonable estimate of H. Such derivation from passive measurements, as compared with or supplementing other observations, is expected to be of interest in a broad range of applications for which it is important to define better the macrophysical cloud parameters in a practical way.

Description: Wildfires are often governed by rapid changes in seasonal rainfall. Therefore, measuring seasonal rainfall on a temporally finescale should facilitate the prediction of wildfire regimes. To explore this hypothesis, daily rainfall data over a 58-yr period (1950–2007) in south-central Florida were transformed into cumulative rainfall anomalies (CRAs). This transformation allowed precise estimation of onset dates and durations of the dry and wet seasons, as well as a number of other variables characterizing seasonal rainfall. These variables were compared with parameters that describe ENSO and a wildfire regime in the region (at the Avon Park Air Force Range). Onset dates and durations were found to be highly variable among years, with standard deviations ranging from 27 to 41 days. Rainfall during the two seasons was distinctive, with the dry season having half as much as the wet season despite being nearly 2 times as long. The precise quantification of seasonal rainfall led to strong statistical models describing linkages between climate and wildfires: a multiple-regression technique relating the area burned with the seasonal rainfall characteristics had an of 0.61, and a similar analysis examining the number of wildfires had an of 0.56. Moreover, the CRA approach was effective in outlining how seasonal rainfall was associated with ENSO, particularly during the strongest and most unusual events (e.g., El Niño of 1997/98). Overall, the results presented here show that using CRAs helped to define the linkages among seasonality, ENSO, and wildfires in south-central Florida, and they suggest that this approach can be used in other fire-prone ecosystems.

Description: An experimental study of small-scale variability of raindrop size distributions (DSDs) has been carried out at Wallops Island, Virginia. Three Joss–Waldvogel disdrometers were operated at a distance of 0.65, 1.05, and 1.70 km in a nearly straight line. The main purpose of the study was to examine the variability of DSDs and its integral parameters of liquid water content, rainfall, and reflectivity within a 2-km array: a typical size of Cartesian radar pixel. The composite DSD of rain events showed very good agreement among the disdrometers except where there were noticeable differences in midsize and large drops in a few events. For consideration of partial beam filling where the radar pixel was not completely covered by rain, a single disdrometer reported just over 10% more rainy minutes than the rainy minutes when all three disdrometers reported rainfall. Similarly two out of three disdrometers reported 5% more rainy minutes than when all three were reporting rainfall. These percentages were based on a 1-min average, and were less for longer averaging periods. Considering only the minutes when all three disdrometers were reporting rainfall, just over one quarter of the observations showed an increase in the difference in rainfall with distance. This finding was based on a 15-min average and was even less for shorter averaging periods. The probability and cumulative distributions of a gamma-fitted DSD and integral rain parameters between the three disdrometers had a very good agreement and no major variability. This was mainly due to the high percentage of light stratiform rain and to the number of storms that traveled along the track of the disdrometers. At a fixed time step, however, both DSDs and integral rain parameters showed substantial variability. The standard deviation (SD) of rain rate was near 3 mm h−1, while the SD of reflectivity exceeded 3 dBZ at the longest separation distance. These standard deviations were at 6-min average and were higher at shorter averaging periods. The correlations decreased with increasing separation distance. For rain rate, the correlations were higher than previous gauge-based studies. This was attributed to the differences in data processing and the difference in rainfall characteristics in different climate regions. It was also considered that the gauge sampling errors could be a factor. In this regard, gauge measurements were simulated employing existing disdrometer dataset. While a difference was noticed in cumulative distribution of rain occurrence between the simulated gauge and disdrometer observations, the correlations in simulated gauge measurements did not differ from the disdrometer measurements.

Description: The focus of this study is the evaluation of the research-version Tropical Rainfall Measuring Mission (TRMM) Multisatellite Precipitation Analysis (TMPA) rainfall product at its finest spatial and temporal resolutions (3-hourly and 0.25° × 0.25°) over the Rome, Italy, metropolitan area during the period from October 2008 to January 2009. Accurate ground reference rainfall estimates for two satellite pixels are obtained from a dense rain gauge network (22 rain gauges in one pixel and 16 in the other one). The evaluation is based on examination of time series, scatterplots, and survival functions, as well as measures of agreement and disagreement. The results of this study point to the importance of using the TRMM satellite for rainfall estimation. Suggestions in terms of minimum number of rain gauges required to estimate ground reference rainfall are also provided.

Description: There is currently significant uncertainty about the extent to which cirrus clouds are composed of “small” ice crystals smaller than about 20-μm effective radius. This is due in part to concerns that in situ measurements from aircraft are plagued by ice particle shattering on instrument inlets, artificially negatively biasing effective radii. Here, space-based measurements are applied to the problem. It is found that a space-based infrared split-window technique is less sensitive but more accurate than a visible-near-infrared technique for confident assessment of whether thin cirrus clouds have small effective radii, independent of a normal range of retrieval assumptions. Because of the sensitivities of the infrared split-window technique, however, this method can only accurately determine the presence of small particles for ice clouds with optical depths between roughly 0.5 and 3.0. Applied to Moderate Resolution Imaging Spectroradiometer (MODIS) data, it is found that a very conservative minimum of 15%–20% of such thin cirrus globally are composed of small ice crystals, but that the actual value could be as high as 40%, and even higher for cold clouds or those in the tropics. Retrievals are found to be in good agreement with airborne probe measurements from the Cirrus Regional Study of Tropical Anvils and Cirrus Layers–Florida-Area Cirrus Experiment (CRYSTAL-FACE) field campaign, implying that, for the cases examined, the impact of inlet shattering on measurements must have been limited.

Description: Most climatological datasets are beset with urban temperature influences that distort long-term trends. Using an hourly dataset of 41 urban and rural stations from the United States, discriminant functions were developed using diurnal temperature range indices based on temperature, dewpoint, and dewpoint depression that capture the differences between the two environments. Based on data for 1997–2006, diurnal temperature range and nighttime dewpoint depression range indices provide the best classification variables to statistically discriminate between urban and rural climates. Of the 41 stations, 93% were correctly classified by this technique in a cross-validation analysis. An additional discriminant analysis specific to coastal stations was needed because coastal climates were noted to be aberrant. Here, all stations tested were correctly classified by the procedure. Temporal trends in discriminant scores indicate periods of time during which urbanization was occurring or increasing. Instrumental and location changes were noted to affect both temperature and dewpoint series and therefore the classification. However, such discontinuities can potentially be adjusted and the homogenized data used with the classification technique. The use of this data-driven approach complements existing methods used to classify the urban character of stations, because it is objective, is applicable in the presatellite era, and can infer changes at higher temporal resolution.

Description: This paper describes a simple technique for creating regional, high-resolution, daytime and nighttime composites of sea surface temperature (SST) for use in operational numerical weather prediction (NWP). The composites are based on observations from NASA’s Moderate Resolution Imaging Spectroradiometer (MODIS) aboard Aqua and Terra. The data used typically are available nearly in real time, are applicable anywhere on the globe, and are capable of roughly representing the diurnal cycle in SST. The composites’ resolution is much higher than that of many other standard SST products used for operational NWP, including the low- and high-resolution Real-Time Global (RTG) analyses. The difference in resolution is key because several studies have shown that highly resolved SSTs are important for driving the air–sea interactions that shape patterns of static stability, vertical and horizontal wind shear, and divergence in the planetary boundary layer. The MODIS-based composites are compared to in situ observations from buoys and other platforms operated by the National Data Buoy Center (NDBC) off the coasts of New England, the mid-Atlantic, and Florida. Mean differences, mean absolute differences, and root-mean-square differences between the composites and the NDBC observations are all within tenths of a degree of those calculated between RTG analyses and the NDBC observations. This is true whether or not one accounts for the mean offset between the skin temperatures of the MODIS dataset and the bulk temperatures of the NDBC observations and RTG analyses. Near the coast, the MODIS-based composites tend to agree more with NDBC observations than do the RTG analyses. The opposite is true away from the coast. All of these differences in point-wise comparisons among the SST datasets are small compared to the ±1.0°C accuracy of the NDBC SST sensors. Because skin-temperature variations from land to water so strongly affect the development and life cycle of the sea breeze, this phenomenon was chosen for demonstrating the use of the MODIS-based composite in an NWP model. A simulated sea breeze in the vicinity of New York City and Long Island shows a small, net, but far from universal improvement when MODIS-based composites are used in place of RTG analyses. The timing of the sea breeze’s arrival is more accurate at some stations, and the near-surface temperature, wind, and humidity within the breeze are more realistic.