ALBERT

Beschreibung: A method is presented to analyze the cloud life cycle of frontal systems passing over European supersites. It combines information on the vertical profiles of cloud properties derived from ground-based observations with cloud products obtained from satellite-based observations, including their spatial variability. The Euler and Lagrange perspectives are adopted to consider the history of a cloud system that passes the supersites. The forward model known as RTTOV (Radiative Transfer for the Television and Infrared Observation Satellite Operational Vertical Sounder) and the ground-based “CloudNET” products are used to simulate synthetic satellite observations at the supersites, which are subsequently compared with the actual observations of the Meteosat Spinning Enhanced Visible and Infrared Imager (SEVIRI) instrument. Different metrics are considered to quantify and interpret the consistency of the synthetic and the observed satellite data: brightness temperatures at the thermal IR channels, the split-window channels, and trispectral combinations, as well as the outgoing longwave radiation. In this way, the uncertainties of the individual datasets are investigated. This knowledge provides the motivation to combine the disjunct cloud products from satellite with those from ground instruments to characterize the development of the passing cloud frontal systems. In addition, back trajectories started at different stages of the cloud system were used to analyze its history prior to the supersite overpass. The trajectories are used to study, for example, the life time of the cloud frontal system, changes of the cloud phase, and the evolution of cloud physics such as optical thickness, effective particle size, and water path. As a test bed, a case study with a cold front passing Lindenberg, Germany, is presented.

Beschreibung: Spatial and temporal variation in the urban heat island (UHI) effect from March 2012 through October 2013 was characterized using continuous temperature measurements from an array of up to 151 fixed sensors in and around Madison, Wisconsin, an urban area of population 407 000 surrounded by lakes and a rural landscape of agriculture, forests, wetlands, and grasslands. Spatially, the density of the built environment was the primary driver of temperature patterns, with local modifying effects of lake proximity and topographic relief. Temporally, wind speed, cloud cover, relative humidity, soil moisture, and snow all influenced UHI intensity, although the magnitude and significance of their effects varied by season and time of day. Seasonally, UHI intensities tended to be higher during the warmer summer months and lower during the colder months. Seasonal trends in monthly average wind speed and cloud cover tracked annual trends in UHI intensity, with clearer, calmer conditions that are conducive to the stronger UHIs being more common during the summer. However, clear, calm summer nights still had higher UHI intensities than clear, calm winter nights, indicating that some background factor, such as vegetation, shifted baseline UHI intensities throughout the year. The authors propose that regional vegetation and snow-cover conditions set seasonal baselines for UHI intensity and that factors like wind and clouds modified daily UHI intensity around that baseline.

Beschreibung: Central New York State, located at the intersection of the northeastern United States and the Great Lakes basin, is impacted by snowfall produced by lake-effect and non-lake-effect snowstorms. The purpose of this study is to determine the spatiotemporal patterns of snowfall in central New York and their possible underlying causes. Ninety-three Cooperative Observer Program stations are used in this study. Spatiotemporal patterns are analyzed using simple linear regressions, Pearson correlations, principal component analysis to identify regional clustering, and spatial snowfall distribution maps in the ArcGIS software. There are three key findings. First, when the long-term snowfall trend (1931/32–2011/12) is divided into two halves, a strong increase is present during the first half (1931/32–1971/72), followed by a lesser decrease in the second half (1971/72–2011/12). This result suggests that snowfall trends behave nonlinearly over the period of record. Second, central New York spatial snowfall patterns are similar to those for the whole Great Lakes basin. For example, for five distinct regions identified within central New York, regions closer to and leeward of Lake Ontario experience higher snowfall trends than regions farther away and not leeward of the lake. Third, as compared with precipitation totals (0.02), average air temperatures had the largest significant (ρ 〈 0.05) correlation (−0.56) with seasonal snowfall totals in central New York. Findings from this study are valuable because they provide a basis for understanding snowfall patterns in a region that is affected by both non-lake-effect and lake-effect snowstorms.

Beschreibung: An operational method is presented that corrects the bias of radar-based quantitative precipitation estimations (QPE) in radar networks that is due to the vertical profile of reflectivity (VPR) factor. It is used in both rain and snowfall. Measured average VPRs are obtained from the volume scans of each radar at ranges of 2–40 km. At each radar, two time ensembles of the bias estimates are made use of: the first ensemble contains 0–24 members at each range gate, calculated by beam convolution from the measured VPRs at 15-min intervals during the most recent 6 h. The second ensemble similarly contains 24 members calculated from parameterized climatological VPRs. In each scan the precipitation type classification and the climatological VPR are matched with the freezing level obtained from a numerical weather prediction model. The members of the two ensembles are weighted for both time lapse and quality and are then combined. At each composite grid point, the value of the networked VPR correction is then determined as a distance-weighted mean of the time ensembles of biases from all radars located closer than 300 km. In the absence of calibration errors, the resulting estimate of the reflectivity factor at ground level Ze is a seamless continuous field. As verified by radar–radar and radar–gauge comparisons in the Finnish network of eight C-band Doppler radars, the method efficiently reduces the range-dependent bias in QPE. For example, at radar ranges of 141–219 km, the average bias in the ground level Ze was −8.7 and 1.2 dB before and after the VPR correction, respectively.

Beschreibung: Profiling airborne radar data and accompanying large-eddy-simulation (LES) modeling are used to examine the impact of ground-based glaciogenic seeding on cloud and precipitation in a shallow stratiform orographic winter storm. This storm occurred on 18 February 2009 over a mountain in Wyoming. The numerical simulations use the Weather Research and Forecasting (WRF) Model in LES mode with horizontal grid spacings of 300 and 100 m in a domain covering the entire mountain range, and a glaciogenic seeding parameterization coupled with the Thompson microphysics scheme. A series of non-LES simulations at 900-m resolution, each with different initial/boundary conditions, is validated against sounding, cloud, and precipitation data. The LES runs then are driven by the most representative 900-m non-LES simulation. The 100-m LES results compare reasonably well to the vertical-plane radar data. The modeled vertical-motion field reveals a turbulent boundary layer and gravity waves above this layer, as observed. The storm structure also validates well, but the model storm thins and weakens more rapidly than is observed. Radar reflectivity frequency-by-altitude diagrams suggest a positive seeding effect, but time- and space-matched model reflectivity diagrams only confirm this in a relative sense, in comparison with the trend in the control region upwind of seeding generators, and not in an absolute sense. A model sensitivity run shows that in this case natural storm weakening dwarfs the seeding effect, which does enhance snow mass and snowfall. Since the kinematic and microphysical structure of the storm is simulated well, future Part II of this study will examine how glaciogenic seeding impacts clouds and precipitation processes within the LES.

Beschreibung: Backscatter differential phase δ within the melting layer has been identified as a reliably measurable but still underutilized polarimetric variable. Polarimetric radar observations at X band in Germany and S band in the United States are presented that show maximal observed δ of 8.5° at X band but up to 70° at S band. Dual-frequency observations at X and C band in Germany and dual-frequency observations at C and S band in the United States are compared to explore the regional frequency dependencies of the δ signature. Theoretical simulations based on usual assumptions about the microphysical composition of the melting layer cannot reproduce the observed large values of δ at the lower-frequency bands and also underestimate the enhancements in differential reflectivity ZDR and reductions in the cross-correlation coefficient ρhυ. Simulations using a two-layer T-matrix code and a simple model for the representation of accretion can, however, explain the pronounced δ signatures at S and C bands in conjunction with small δ at X band. The authors conclude that the δ signature bears information about microphysical accretion and aggregation processes in the melting layer and the degree of riming of the snowflakes aloft.

Beschreibung: The stability of the Moderate Resolution Imaging Spectroradiometer (MODIS) ice-surface temperature (IST) product from Terra was investigated for use as a climate-quality data record. The availability of climate-quality air temperature data TA from a NOAA observatory at Greenland’s Summit Station has enabled this high-temporal-resolution study of MODIS ISTs. During a 〉5-yr period (July 2008–August 2013), more than 2500 IST values were compared with ±3-min-average TA values from NOAA’s primary 2-m temperature sensor. This enabled an expected small offset between air and ice-sheet surface temperatures (TA 〉 IST) to be investigated over multiple annual cycles. The principal findings of this study show 1) that IST values are slightly colder than the TA values near freezing but that this offset increases as temperature decreases and 2) that there is a pattern in IST–TA differences as the solar zenith angle (SoZA) varies annually. This latter result largely explains the progressive offset from the in situ data at colder temperatures but also indicates that the MODIS cloud mask is less accurate approaching and during the polar night. The consistency of the results over each year in this study indicates that MODIS provides a platform for remotely deriving surface temperature data, with the resulting IST data being most compatible with in situ TA data when the sky is clear and the SoZA is less than ~85°. The ongoing development of the IST dataset should benefit from improved cloud filtering as well as algorithm modifications to account for the progressive offset from TA at colder temperatures.

Beschreibung: The adequacy of meteorological drought intensity threshold levels based on deviations of monthly precipitation totals from normal climatological conditions is reconsidered. The motivation for this study is the observation that reference classification systems are fixed for all climatological regions, and threshold levels have been proposed without regard for the statistical distribution of accumulated precipitation in space and time. This misrepresentation of precipitation variability may lead to erroneous estimates of meteorological drought onset in specific areas where natural breaks in the cumulative distribution of monthly precipitation do not fit the generalized classification systems. In this study, a new optimized classification system based on the nonparametric “Fisher–Jenks” algorithm is proposed for the estimation of meteorological drought intensity threshold levels from monthly precipitation totals. The optimized classification system is compared using the tabular accuracy index (TAI) to three fixed classification systems that are proposed in the literature and widely applied in the operational setting. An assessment of drought intensity classifications with optimized and fixed threshold levels shows that 1) six optimized categories most accurately divide precipitation totals into the most appropriate drought intensities, 2) optimized thresholds always give considerably improved drought intensity category allocations over fixed thresholds with the same number of categories, and 3) fixed thresholds underestimate the drought onset. An analysis of monthly and long-term drought frequency for Latin America has been conducted for assessing the spatial link between meteorological drought intensity categories computed with the Fisher–Jenks algorithm and different climate classifications. The results show a systematic match between climate variability in the region and spatial patterns of meteorological drought intensity.

Beschreibung: This study investigated the moderation of the urban heat island via changes in the urban form in the Tokyo metropolitan area (TMA). Two urban scenarios with the same population as that of the current urban form were used for sensitivity experiments: the dispersed-city and compact-city scenarios. Numerical experiments using the two urban scenarios as well as an experiment using the current urban form were conducted using a regional climate model coupled with a single-layer urban canopy model. The averaged nighttime surface air temperature in TMA increased by ~0.34°C in the dispersed-city scenario and decreased by ~0.1°C in the compact-city scenario. Therefore, the compact-city scenario had significant potential for moderating the mean areal heat-island effect in the entire TMA. Alternatively, in the central part of the TMA, these two urban-form scenarios produced opposite effects on the surface air temperature; that is, severe thermal conditions worsened further in the compact-city scenario because of the denser population. This result suggests that the compact-city form is not always appropriate for moderation of the urban-heat-island effect. This scenario would need to combine with other mitigation strategies, such as the additional greening of urban areas, especially in the central area. This study suggests that it is important to design a plan to adapt to higher urban temperatures, which are likely to ensue from future global warming and the urban heat island, from several perspectives; that is, designs should take into account not only climatological aspects but also impacts on urban inhabitants.

Beschreibung: The Lake Champlain basin is a critical ecological and socioeconomic resource of the northeastern United States and southern Quebec, Canada. While general circulation models (GCMs) provide an overview of climate change in the region, they lack the spatial and temporal resolution necessary to fully anticipate the effects of rising global temperatures associated with increasing greenhouse gas concentrations. Observed trends in precipitation and temperature were assessed across the Lake Champlain basin to bridge the gap between global climate change and local impacts. Future shifts in precipitation and temperature were evaluated as well as derived indices, including maple syrup production, days above 32.2°C (90°F), and snowfall, relevant to managing the natural and human environments in the region. Four statistically downscaled, bias-corrected GCM simulations were evaluated from the Coupled Model Intercomparison Project phase 5 (CMIP5) forced by two representative concentration pathways (RCPs) to sample the uncertainty in future climate simulations. Precipitation is projected to increase by between 9.1 and 12.8 mm yr−1 decade−1 during the twenty-first century while daily temperatures are projected to increase between 0.43° and 0.49°C decade−1. Annual snowfall at six major ski resorts in the region is projected to decrease between 46.9% and 52.4% by the late twenty-first century. In the month of July, the number of days above 32.2°C in Burlington, Vermont, is projected to increase by over 10 days during the twenty-first century.

Beschreibung: Smoke plume rise is an important factor for smoke transport and air quality impact modeling. This study provides a practical tool for estimating plume rise of prescribed fires. A regression model was developed on the basis of observed smoke plume rise for 20 prescribed fires in the southeastern United States. The independent variables include surface wind, air temperature, fuel moisture, and atmospheric planetary boundary layer (PBL) height. The first three variables were obtained from the Remote Automatic Weather Stations, most of which are installed in locations where they can monitor local fire danger and are easily accessed by fire managers. The PBL height was simulated with the Weather Research and Forecasting Model. The confidence and validation analyses indicate that the regression model is significant at the 95% confidence level and able to predict hourly values and the average smoke plume rise during a burn, respectively. The prediction of the average smoke plume rise shows larger skills. The model also shows improved skills over two extensively used empirical models for the prescribed burn cases examined in this study, suggesting that it may have the potential to improve smoke plume rise and air quality modeling for prescribed burns. The regression model, however, tends to underestimate large plume rise values and overestimate small ones. A suite of alternative regression models was also provided, one of which can be used when no PBL information is available.

Beschreibung: The accuracy of winds derived from Next Generation Weather Radar (NEXRAD) level-II data is assessed by comparison with independent observations from 915-MHz radar wind profilers. The evaluation is carried out at two locations with very different terrain characteristics. One site is located in an area of complex terrain within the State Line Wind Energy Center in northeastern Oregon. The other site is located in an area of flat terrain on the east-central Florida coast. The National Severe Storm Laboratory’s two-dimensional variational data assimilation (2DVar) algorithm is used to retrieve wind fields from the KPDT (Pendleton, Oregon) and KMLB (Melbourne, Florida) NEXRAD radars. Wind speed correlations at most observation height levels fell in the range from 0.7 to 0.8, indicating that the retrieved winds followed temporal fluctuations in the profiler-observed winds reasonably well. The retrieved winds, however, consistently exhibited slow biases in the range of 1–2 m s−1. Wind speed difference distributions were broad, with standard deviations in the range from 3 to 4 m s−1. Results from the Florida site showed little change in the wind speed correlations and difference standard deviations with altitude between about 300 and 1400 m AGL. Over this same height range, results from the Oregon site showed a monotonic increase in the wind speed correlation and a monotonic decrease in the wind speed difference standard deviation with increasing altitude. The poorest overall agreement occurred at the lowest observable level (~300 m AGL) at the Oregon site, where the effects of the complex terrain were greatest.

Beschreibung: Weather Research and Forecasting Model forecasts over the Great Salt Lake Desert erroneously underpredict nocturnal cooling over the sparsely vegetated silt loam soil area of Dugway Proving Ground in northern Utah, with a mean positive bias error in temperature at 2 m AGL of 3.4°C in the early morning [1200 UTC (0500 LST)]. Positive early-morning bias errors also exist in nearby sandy loam soil areas. These biases are related to the improper initialization of soil moisture and parameterization of soil thermal conductivity in silt loam and sandy loam soils. Forecasts of 2-m temperature can be improved by initializing with observed soil moisture and by replacing Johansen's 1975 parameterization of soil thermal conductivity in the Noah land surface model with that proposed by McCumber and Pielke in 1981 for silt loam and sandy loam soils. Case studies illustrate that this change can dramatically reduce nighttime warm biases in 2-m temperature over silt loam and sandy loam soils, with the greatest improvement during periods of low soil moisture. Predicted ground heat flux, soil thermal conductivity, near-surface radiative fluxes, and low-level thermal profiles also more closely match observations. Similar results are anticipated in other dryland regions with analogous soil types, sparse vegetation, and low soil moisture.

Beschreibung: The depth of boundary layer water vapor plays a critical role in convective cloud formation in the warm season, but numerical models often struggle with accurate predictions of above-surface moisture. Satellite retrievals of water vapor have been developed, but they are limited by the use of a model’s first guess, instrument spectral resolution, horizontal footprint size, and vertical resolution. In 2016, Geostationary Operational Environmental Satellite-R (GOES-R), the first in a series of new-generation geostationary satellites, will be launched. Its Advanced Baseline Imager will provide unprecedented spectral, spatial, and temporal resolution. Among the bands are two centered at 10.35 and 12.3 μm. The brightness temperature difference between these bands is referred to as the split-window difference, and has been shown to provide information about atmospheric column water vapor. In this paper, the split-window difference is reexamined from the perspective of GOES-R and radiative transfer model simulations are used to better understand the factors controlling its value. It is shown that the simple split-window difference can provide useful information for forecasters about deepening low-level water vapor in a cloud-free environment.

Beschreibung: Meteorological and air-quality model simulations are analyzed alongside observations to investigate the role of the Chesapeake Bay breeze on surface air quality, pollutant transport, and boundary layer venting. A case study was conducted to understand why a particular day was the only one during an 11-day ship-based field campaign on which surface ozone was not elevated in concentration over the Chesapeake Bay relative to the closest upwind site and why high ozone concentrations were observed aloft by in situ aircraft observations. Results show that southerly winds during the overnight and early-morning hours prevented the advection of air pollutants from the Washington, D.C., and Baltimore, Maryland, metropolitan areas over the surface waters of the bay. A strong and prolonged bay breeze developed during the late morning and early afternoon along the western coastline of the bay. The strength and duration of the bay breeze allowed pollutants to converge, resulting in high concentrations locally near the bay-breeze front within the Baltimore metropolitan area, where they were then lofted to the top of the planetary boundary layer (PBL). Near the top of the PBL, these pollutants were horizontally advected to a region with lower PBL heights, resulting in pollution transport out of the boundary layer and into the free troposphere. This elevated layer of air pollution aloft was transported downwind into New England by early the following morning where it likely mixed down to the surface, affecting air quality as the boundary layer grew.

Beschreibung: Environmental conditions for the roughly three million people living in the Taipei basin of Taiwan are greatly affected by the land–sea breeze and afternoon thunderstorm activities. A new perspective on the land–sea breeze life cycle and how it is affected by afternoon thunderstorm activity in the Taipei basin during the dry season is provided. During the summer monsoon break–revival phase, about 75% of rainfall in the Taipei basin is produced by afternoon thunderstorms triggered by sea-breeze interactions with the mountains to the south of this basin. Because the basic characteristics of the land–sea breeze and the changes it undergoes through the influence of afternoon thunderstorms have not been comprehensively analyzed/documented, a mini–field experiment was conducted during the summers of 2004 and 2005 to explore these aspects of the land–sea breeze in this basin. Thunderstorm rainfall is found to change not only the basin’s land–sea-breeze life cycle, but also its ventilation mechanism. On the nonthunderstorm day, the sea breeze supplies the open-sea fresh air for about 8 h during the daytime, but the land breeze persists on the thunderstorm day from afternoon to the next morning, acting to sweep polluted urban air out of the basin.

Beschreibung: Polarimetric radar observations of deep convective storms frequently reveal columnar enhancements of differential reflectivity ZDR. Such “ZDR columns” can extend upward more than 3 km above the environmental 0°C level, indicative of supercooled liquid drops being lofted by the updraft. Previous observational and modeling studies of ZDR columns are reviewed. To address remaining questions, the Hebrew University Cloud Model, an advanced spectral bin microphysical model, is coupled with a polarimetric radar operator to simulate the formation and life cycle of ZDR columns in a deep convective continental storm. In doing so, the mechanisms by which ZDR columns are produced are clarified, including the formation of large raindrops in the updraft by recirculation of smaller raindrops formed aloft back into the updraft at low levels. The internal hydrometeor structure of ZDR columns is quantified, revealing the transition from supercooled liquid drops to freezing drops to hail with height in the ZDR column. The life cycle of ZDR columns from early formation, through growth to maturity, to demise is described, showing how hail falling out through the weakening or ascending updraft bubble dominates the reflectivity factor ZH, causing the death of the ZDR column and leaving behind its “ghost” of supercooled drops. In addition, the practical applications of ZDR columns and their evolution are explored. The height of the ZDR column is correlated with updraft strength, and the evolution of ZDR column height is correlated with increases in ZH and hail mass content at the ground after a lag of 10–15 min.

Beschreibung: An overview of the Wyoming Weather Modification Pilot Project (WWMPP) is presented. This project, funded by the State of Wyoming, is designed to evaluate the effectiveness of cloud seeding with silver iodide in the Medicine Bow and Sierra Madre Ranges of south-central Wyoming. The statistical evaluation is based on a randomized crossover design for the two barriers. The description of the experimental design includes the rationale behind the design choice, the criteria for case selection, facilities for operations and evaluation, and the statistical analysis approach. Initial estimates of the number of cases needed for statistical significance used historical Snow Telemetry (SNOTEL) data (1987–2006), prior to the beginning of the randomized seeding experiment. Refined estimates were calculated using high-resolution precipitation data collected during the initial seasons of the project (2007–10). Comparing the sample size estimates from these two data sources, the initial estimates are reduced to 236 (110) for detecting a 10% (15%) change. The sample size estimates are highly dependent on the assumed effect of seeding, on the correlations between the two target barriers and between the target and control sites, and on the variance of the response variable, namely precipitation. In addition to the statistical experiment, a wide range of physical studies and ancillary analyses are being planned and conducted.

Beschreibung: In South Korea, heating degree-days (HDD) and cooling degree-days (CDD) have been widely used as climatic indicators for the assessment of the impact of climate change, but arbitrary or customary base temperatures have been used for calculation of HDD and CDD. The purpose of this study is to determine real base temperatures to accurately calculate HDD and CDD for South Korea, using monthly electric energy consumption and mean temperature data from 2001 to 2010. The results reveal that the regional electricity demand generally depends on air temperature in a V-shaped curve in urban settings but in an L-shaped curve in rural settings, indicating that the sensitivity of the electricity demand to the temperature change is affected by the size of cities. The South Korean regional base temperatures, defined by a piecewise linear regression method, range from 14.7° to 19.4°C. These results suggest that the assessment of climate change impacts on the energy sector in South Korea should be carried out on a regional scale.

Beschreibung: This paper introduces a method for identifying icing events using a physical icing model, driven by atmospheric data from the Weather Research and Forecasting (WRF) model, and applies it to a wind park in Sweden. Observed wind park icing events were identified by deviation from an idealized power curve and observed temperature. The events were modeled using a physical icing model with equations for both accretion and ablation mechanisms (iceBlade). The accretion model is based on the Makkonen model but was modified to make it applicable to the blades of a wind turbine rather than a static structure, and the ablation model is newly developed. The results from iceBlade are shown to outperform a 1-day persistence model and standard cylinder model in determining the times when any turbine in the wind park is being impacted by icing. The icing model was evaluated using inputs from simulations using nine different WRF physics parameterization combinations. The combination of the Thompson microphysics parameterization and version 2 of the Mellor–Yamada–Nakanishi–Niino PBL scheme was shown to perform best at this location. The distribution of cloud mass into the appropriate hydrometeor classes was found to be very important for forecasting the correct icing period. One concern with the iceBlade approach was the relatively high false alarm rates at the end of icing events due to the ice not being removed rapidly enough.

Beschreibung: Atmospheric motion vectors (AMVs) are derived from satellite-observed motions of clouds and water vapor features. They provide crucial information in regions void of conventional observations and contribute to forecaster diagnostics of meteorological conditions, as well as numerical weather prediction. AMVs derived from geostationary (GEO) satellite observations over the middle latitudes and tropics have been utilized operationally since the 1980s; AMVs over the polar regions derived from low-earth (polar)-orbiting (LEO) satellites have been utilized since the early 2000s. There still exists a gap in AMV coverage between these two sources in the latitude band poleward of 60° and equatorward of 70° (both hemispheres). To address this AMV gap, the use of a novel approach to create image sequences that consist of composites derived from a combination of LEO and GEO observations that extend into the deep middle latitudes is explored. Experiments are performed to determine whether the satellite composite images can be employed to generate AMVs over the gap regions. The derived AMVs are validated over both the Southern Ocean/Antarctic and the Arctic gap regions over a multiyear period using rawinsonde wind observations. In addition, a two-season numerical model impact study using the Global Forecast System indicates that the assimilation of these AMVs can improve upon the control (operational) forecasts, particularly during lower-skill (dropout) events.

Beschreibung: The urban heat island (UHI) effect is one of the most significant phenomena caused by urbanization. This study investigated the UHI effect in the Suzhou–Wuxi area, China, on 19–20 August 2010. Using a combination of meteorological station observations and Moderate Resolution Imaging Spectroradiometer (MODIS) surface skin temperature observations, this study demonstrated that an upwind UHI had an exacerbating influence on the downwind UHI during the study period. Numerical simulations using the Weather Research and Forecasting model also proved the importance of an upwind UHI influence on the leeward UHI in this area. For the near-surface UHI, the windward UHI effect is stronger at night than during the daytime because the background atmospheric stratification is more stable and the local lake breeze is weaker at night. However, in the daytime, a greater stability formed over the downwind city because of the warmer air heated by the windward urban area in the upper part of the planetary boundary layer and the cooler air transported from Tai Lake and the rural area in the lower part of the boundary layer. In comparison with the heating effect of a single city, the upwind UHI led to a decrease in the vertical wind speed of approximately 30% (from 0.15 to 0.10 m s−1) in the upper boundary layer over the downwind city and also reduced the near-surface turbulent movement by 25% (from 0.73 to 0.55 m2 s−2). These results improve the understanding of the overall influence of urban clusters on local synoptic/climate processes.

Beschreibung: This study uses GIS-based modeling of incoming solar radiation to quantify fine-resolved spatiotemporal responses of year-round monthly average temperature within a field study area located on the eastern coast of Sweden. A network of temperature sensors measures surface and near-surface air temperatures during a year from June 2011 to June 2012. Strong relationships between solar radiation and temperature exhibited during the growing season (supporting previous work) break down in snow cover and snowmelt periods. Surface temperature measurements are here used to estimate snow cover duration, relating the timing of snowmelt to low performance of an existing linear model developed for the investigated site. This study demonstrates that linearity between insolation and temperature 1) may only be valid for solar radiation levels above a certain threshold and 2) is affected by the consumption of incoming radiation during snowmelt.

Beschreibung: Limitations in skill of wind speed forecasts lead to conservative bids of wind-plant production in the day-ahead energy market and usually to an underutilization of wind resources. Improvements are needed in understanding wind characteristics in the turbine-rotor layer (40–120 m) for developing refined forecast models. The seasonal and diurnal behavior of wind speed, wind direction, and temperature were analyzed from data taken on five tall meteorological towers across Iowa. Several significant high-shear events, which would have the potential to cause problems by inducing substantial stress on the infrastructure of the wind turbine, were observed, with vertical shear up to 15 m s−1 accompanied by 30° of directional shear between 50 and 200 m. These events exhibited supergeostrophic wind speeds by 50% through the night followed by a collapse of shear through midday, indicating the influence of an inertial oscillation.

Beschreibung: Average heat and momentum fluxes observed by a network of surface stations during the Hudson Valley Ambient Meteorology Study (HVAMS) were found as functions of a spatially representative bulk Richardson number Ribr. Preferential sites were identified for the occurrence of strong turbulence under mesoscale stability conditions common to all stations. Locally sensed turbulence intermittency depends on the mesoscale flow stability. Nearly continuous turbulence with few long-lived intermittent events occurs when Ribr 〈 Ricr, the critical gradient Richardson number. Less-continuous mixing associated with a larger number of events occurs when Ricr 〈 Ribr 〈 5, with the weakest turbulence and fewer events observed for Ribr ≫ Ricr. It was found that the need to allow for extra mixing above the conventional critical bulk Richardson number in numerical weather prediction models is primarily a consequence of spatial averaging in a heterogeneous landscape and is secondarily the result of turbulence above Ricr at locations with “nonideal fetch.”

Beschreibung: Clouds pose many operational hazards to the aviation community in terms of ceilings and visibility, turbulence, and aircraft icing. Realistic descriptions of the three-dimensional (3D) distribution and temporal evolution of clouds in numerical weather prediction models used for flight planning and routing are therefore of central importance. The introduction of satellite-based cloud radar (CloudSat) and Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) sensors to the National Aeronautics and Space Administration A-Train is timely in light of these needs but requires a new paradigm of model-evaluation tools that are capable of exploiting the vertical-profile information. Early results from the National Center for Atmospheric Research Model Evaluation Toolkit (MET), augmented to work with the emergent satellite-based active sensor observations, are presented here. Existing horizontal-plane statistical evaluation techniques have been adapted to operate on observations in the vertical plane and have been extended to 3D object evaluations, leveraging blended datasets from the active and passive A-Train sensors. Case studies of organized synoptic-scale and mesoscale distributed cloud systems are presented to illustrate the multiscale utility of the MET tools. Definition of objects on the basis of radar-reflectivity thresholds was found to be strongly dependent on the model’s ability to resolve details of the cloud’s internal hydrometeor distribution. Contoured-frequency-by-altitude diagrams provide a useful mechanism for evaluating the simulated and observed 3D distributions for regional domains. The expanded MET provides a new dimension to model evaluation and positions the community to better exploit active-sensor satellite observing systems that are slated for launch in the near future.

Beschreibung: The process of moving from an ensemble of global climate model temperature projections to local sea level projections requires several steps. Sea level was estimated in Olympia, Washington (a city that is very concerned with sea level rise because parts of downtown are barely above mean highest high tide), by relating global mean temperature to global sea level; relating global sea level to sea levels at Seattle, Washington; and finally relating Seattle to Olympia. There has long been a realization that accurate assessment of the precision of projections is needed for science-based policy decisions. When a string of statistical and/or deterministic models is connected, the uncertainty of each individual model needs to be accounted for. Here the uncertainty is quantified for each model in the described system and the total uncertainty is assessed in a cascading effect throughout the system. The projected sea level rise over time and its total estimated uncertainty are visualized simultaneously for the years 2000–2100, the increased uncertainty due to each of the component models at a particular projection year is identified, and estimates of the time at which a certain sea level rise will first be reached are made.

Beschreibung: This paper demonstrates that a statistical–dynamical method can be used to accurately estimate the wind climate at a wind farm site. In particular, postprocessing of mesoscale model output allows an efficient calculation of the local wind climate required for wind resource estimation at a wind turbine site. The method is divided into two parts: 1) preprocessing, in which the configurations for the mesoscale model simulations are determined, and 2) postprocessing, in which the data from the mesoscale simulations are prepared for wind energy application. Results from idealized mesoscale modeling experiments for a challenging wind farm site in northern Spain are presented to support the preprocessing method. Comparisons of modeling results with measurements from the same wind farm site are presented to support the postprocessing method. The crucial element in postprocessing is the bridging of mesoscale modeling data to microscale modeling input data, via a so-called generalization method. With this method, very high-resolution wind resource mapping can be achieved.

Beschreibung: This study presents radar-based precipitation estimates collected during the 2-month U.S. Department of Energy Atmospheric Radiation Measurement Program (ARM)–NASA Midlatitude Continental Convective Clouds Experiment (MC3E). Emphasis is on the usefulness of radar observations from the C-band and X-band scanning ARM precipitation radars (CSAPR and XSAPR, respectively) for rainfall estimation products to distances within 100 km of the Lamont, Oklahoma, ARM facility. The study utilizes a dense collection of collocated ARM, NASA Global Precipitation Measurement, and nearby surface Oklahoma Mesonet gauge records to evaluate radar-based hourly rainfall products and campaign-optimized methods over individual gauges and for areal rainfall characterizations. Rainfall products are also evaluated against the performance of a regional NWS Weather Surveillance Radar-1988 Doppler (WSR-88D) S-band dual-polarization radar product. Results indicate that the CSAPR system may achieve similar point– and areal–gauge bias and root-mean-square (RMS) error performance to a WSR-88D reference for the variety of MC3E deep convective events sampled. The best campaign rainfall performance was achieved when using radar relations capitalizing on estimates of the specific attenuation from the CSAPR system. The XSAPRs demonstrate limited capabilities, having modest success in comparison with the WSR-88D reference for hourly rainfall accumulations that are under 10 mm. All rainfall estimation methods exhibit a reduction by a factor of 1.5–2.5 in RMS errors for areal accumulations over a 15-km2 NASA dense gauge network, with the smallest errors typically associated with dual-polarization radar methods.

Beschreibung: Circulations in and around cumulus clouds are inferred by using a passive tracer (radar chaff) and an airborne cloud radar during the Barbados Aerosol Cloud Experiment (BACEX). The radar chaff elements used for this experiment are fibers that are cut to a length of about ½ of the radar wavelength to maximize radar returns by serving as dipole antennas. The fibers are packed in fiber tubes and are mounted in a dispenser beneath the wing of the aircraft. The chaff was released near the tops and edges of a growing small cumulus cloud. The aircraft then made penetrations of the cloud at lower levels to observe the chaff signals above the aircraft with the zenith-pointing cloud radar. This study shows that the environmental air above the cloud top descends along the downshear side of the cloud edge and is subsequently entrained back into the same cloud near the observation level. The in-cloud flow follows an inverted letter P pattern. The merits and limitations of the chaff method for tracking circulations in and around small cumuli are discussed.

Beschreibung: Collocated active and passive remote sensing measurements collected at U.S. Department of Energy Atmospheric Radiation Measurement Program sites enable simultaneous retrieval of cloud and precipitation properties and air motion. Previous studies indicate the parameters of a bimodal cloud particle size distribution can be effectively constrained using a combination of passive microwave radiometer and radar observations; however, aspects of the particle size distribution and particle shape are typically assumed to be known. In addition, many retrievals assume the observation and retrieval error statistics have Gaussian distributions and use least squares minimization techniques to find a solution. In truth, the retrieval error characteristics are largely unknown. Markov chain Monte Carlo (MCMC) methods can be used to produce a robust estimate of the probability distribution of a retrieved quantity that is nonlinearly related to the measurements and that has non-Gaussian error statistics. In this work, an MCMC algorithm is used to explore the error characteristics of cloud property retrievals from surface-based W-band radar and low-frequency microwave radiometer observations for a case of orographic snowfall. In this particular case, it is found that a combination of passive microwave radiometer measurements with radar reflectivity and Doppler velocity is sufficient to constrain the liquid and ice particle size distributions, but only if the width parameter of the assumed gamma particle size distribution and mass–dimensional relationships are specified. If the width parameter and mass–dimensional relationships are allowed to vary realistically, a unique retrieval of the liquid and ice particle size distribution for this orographic snowfall case is rendered far more problematic.

Beschreibung: In this study, power-law relations are developed between the intercept parameter N0 of the exponential particle size distribution and the water content for the rain, hail, graupel, and snow hydrometeor categories within the Milbrandt and Yau microphysics scheme. Simulations of the 3 May 1999 Oklahoma tornadic supercell are performed using the diagnostic relations for rain only and alternately for all four precipitating species, and results are compared with those from the original fixed-N0 single- and double-moment versions of the scheme. Diagnosing N0 for rain is found to improve the results of the simulation in terms of reproducing the key features of the double-moment simulation while still retaining the computational efficiency of a single-moment scheme. Results more consistent with the double-moment scheme are seen in the general storm structure, the cold-pool structure and intensity, and the number concentration fields. Diagnosing the intercept parameters for all four species, including those for the ice species, within the single-moment scheme yields even closer agreement with the double-moment simulation results. The decreased cold-pool intensity is very similar to that produced by the double-moment simulation, as is the areal extent of the simulated storm. The diagnostic relations are also tested on a simulated squall line, with similar promising results. This study suggests that, when compared with traditional fixed intercept parameters used in typical single-moment microphysics schemes, results closer to a double-moment scheme can be obtained through the use of diagnostic relations for the parameters of the particle size distribution, with little extra computational cost.

Beschreibung: Multiwavelength solar irradiance measurements between 400 and 900 nm were made on cloudless days in Tucson, Arizona, over a 30-month period between March 2010 and August 2012. They were analyzed to simultaneously retrieve aerosol optical depth (AOD) and ozone column abundance and to examine their monthly variation. These retrievals were compared with results from a similar study done at the same location between 1975 and 1977. The near tripling of population in Tucson over the past 35 years may have contributed to a 19% increase in the AOD, and the annual-mean ozone column abundance was found to be 11% lower than that inferred during the mid-1970s.

Beschreibung: Global land-cover data are widely used in regional and global models because land cover influences land–atmosphere exchanges of water, energy, momentum, and carbon. Many models use data of maximum green vegetation fraction (MGVF) to describe vegetation abundance. MGVF products have been created in the past using different methods, but their validation with ground sites is difficult. Furthermore, uncertainty is introduced because many products use a single year of satellite data. In this study, a global 1-km MGVF product is developed on the basis of a “climatology” of data of Moderate Resolution Imaging Spectroradiometer (MODIS) normalized difference vegetation index and land-cover type, which removes biases associated with unusual greenness and inaccurate land-cover classification for individual years. MGVF shows maximum annual variability from 2001 to 2012 for intermediate values of average MGVF, and the standard deviation of MGVF normalized by its mean value decreases nearly monotonically as MGVF increases. In addition, there are substantial differences between this climatology and MGVF data from the MODIS Continuous Fields (CF) Collection 3, which is currently used in the Community Land Model. Although the CF data only use 2001 MODIS data, many of these differences cannot be explained by usage of different years of data. In particular, MGVF as based on CF data is usually higher than that based on the MODIS climatology from this paper. It is difficult to judge which product is more realistic because of a lack of ground truth, but this new MGVF product is more consistent than the CF data with the MODIS leaf area index product (which is also used to describe vegetation abundance in models).

Beschreibung: The statistical properties of turbulence at upper levels in the atmosphere [upper troposphere and lower stratosphere (UTLS)] are still not well known, partly because of the lack of adequate routine observations. This is despite the obvious benefit that such observations would have for alerting aircraft of potentially hazardous conditions, either in real time or for route planning. To address this deficiency, a research project sponsored by the Federal Aviation Administration has developed a software package that automatically estimates and reports atmospheric turbulence intensity levels (as EDR ≡ ε1/3, where ε is the energy or eddy dissipation rate). The package has been tested and evaluated on commercial aircraft. The amount of turbulence data gathered from these in situ reports is unprecedented. As of January 2014, there are ~200 aircraft outfitted with this system, contributing to over 137 million archived records of EDR values through 2013, most of which were taken at cruise levels of commercial aircraft, that is, in the UTLS. In this paper, techniques used for estimating EDR are outlined and comparisons with pilot reports from the same or nearby aircraft are presented. These reports allow calibration of EDR in terms of traditionally reported intensity categories (“light,” “moderate,” or “severe”). The results of some statistical analyses of EDR values are also presented. These analyses are restricted to the United States for now, but, as this program is expanded to international carriers, such data will begin to become available over other areas of the globe.

Beschreibung: Climate data are increasingly scrutinized for accuracy because of the need for reliable input for climate-related decision making and assessments of climate change. Over the last 30 years, vast improvements to U.S. instrumentation, data collection, and station siting have created more accurate data. This study explores the spatial accuracy of daily maximum and minimum air temperature data in Nebraska networks, including the U.S. Historical Climatology Network (HCN), the Automated Weather Data Network (AWDN), and the more recent U.S. Climate Reference Network (CRN). The spatial structure of temperature variations at the earth’s surface is compared for timeframes 2005–09 for CRN and AWDN and 1985–2005 for AWDN and HCN. Individual root-mean-square errors between candidate station and surrounding stations were calculated and used to determine the spatial accuracy of the networks. This study demonstrated that in the 5-yr analysis CRN and AWDN were of high spatial accuracy. For the 21-yr analysis the AWDN proved to have higher spatial accuracy (smaller errors) than the HCN for both maximum and minimum air temperature and for all months. In addition, accuracy was generally higher in summer months and the subhumid area had higher accuracy than did the semiarid area. The findings of this study can be used for Nebraska as an estimate of the uncertainty associated with using a weather station’s data at a decision point some distance from the station.

Beschreibung: The main object of this work is to study the lightning climatology in the Po Valley in Italy and how it varies in time (interannual, annual, weekly, and daily time scales) and space (sea coast, plains, and mountain areas) and how that is related to topographic characteristics and anthropogenic emissions. Cloud-to-ground (CG) lightning in the target area is analyzed for 18 yr of data (about 7 million records). It is found that the Julian Prealps of the Friuli Venezia Giulia region are one of the areas of maximum CG lightning activity across all of Europe. During spring lightning activity is more confined toward the mountainous regions, whereas during summer and even more during autumn the lightning activity involves also the coastal region and the Adriatic Sea. This is due to different triggering mechanisms acting in different topographic zones and during different periods of the year and times of the day. In analogy to previous studies of lightning done in the United States, a weekly cycle is also identified in the area of interest, showing that on Friday the probability of thunderstorms reaches its maximum. After conducting a parallel analysis with monitoring stations of atmospheric particulates (diameter ≤ 10 μm: PM10) and sounding-derived potential instability, the results presented herein seem to support the hypothesis that the weekly cycle in the thunderstorm activity may be due to anthropogenic emissions.

Beschreibung: In 2011, exceptionally low atmospheric moisture content combined with moderately high temperatures to produce a record-high vapor pressure deficit (VPD) in the southwestern United States (SW). These conditions combined with record-low cold-season precipitation to cause widespread drought and extreme wildfires. Although interannual VPD variability is generally dominated by temperature, high VPD in 2011 was also driven by a lack of atmospheric moisture. The May–July 2011 dewpoint in the SW was 4.5 standard deviations below the long-term mean. Lack of atmospheric moisture was promoted by already very dry soils and amplified by a strong ocean-to-continent sea level pressure gradient and upper-level convergence that drove dry northerly winds and subsidence upwind of and over the SW. Subsidence drove divergence of rapid and dry surface winds over the SW, suppressing southerly moisture imports and removing moisture from already dry soils. Model projections developed for the fifth phase of the Coupled Model Intercomparison Project (CMIP5) suggest that by the 2050s warming trends will cause mean warm-season VPD to be comparable to the record-high VPD observed in 2011. CMIP5 projections also suggest increased interannual variability of VPD, independent of trends in background mean levels, as a result of increased variability of dewpoint, temperature, vapor pressure, and saturation vapor pressure. Increased variability in VPD translates to increased probability of 2011-type VPD anomalies, which would be superimposed on ever-greater background VPD levels. Although temperature will continue to be the primary driver of interannual VPD variability, 2011 served as an important reminder that atmospheric moisture content can also drive impactful VPD anomalies.

Beschreibung: Tracking clouds using scanning cloud radars can help to document the temporal evolution of cloud properties well before large-drop formation (weather radar “first echo”). These measurements also complement cloud and precipitation tracking using geostationary satellites and weather radars. Here, two-dimensional (2D) along-wind range–height indicator observations of a population of shallow cumuli (with and without precipitation) from the 35-GHz scanning Atmospheric Radiation Measurement Program (ARM) cloud radar (SACR) at the U.S. Department of Energy (DOE)–ARM Southern Great Plains (SGP) site are presented. Observations from the ARM SGP network of scanning precipitation radars are used to provide the larger-scale context of the cloud field and to highlight the advantages of the SACR to detect the numerous small nonprecipitating cloud elements. A new cloud identification and tracking algorithm (CITA) is developed to track cloud elements. In CITA, a cloud element is identified as a region having a contiguous set of pixels exceeding a preset reflectivity and size threshold. The high temporal resolution of the SACR 2D observations (30 s) allows for an area superposition criteria algorithm to match cloud elements at consecutive times. Following CITA, the temporal evolution of cloud-element properties (number, size, and maximum reflectivity) is presented. The vast majority of the designated elements during this cumulus event were short-lived nonprecipitating clouds having an apparent life cycle shorter than 15 min. The advantages and disadvantages of cloud tracking using an SACR are discussed.

Beschreibung: Recognizing the importance and challenges inherent to the remote sensing of precipitation in mountainous areas, this study investigates the performance of the commonly used satellite-based high-resolution precipitation products (HRPPs) over several basins in the mountainous western United States. Five HRPPs [Tropical Rainfall Measuring Mission 3B42 and 3B42-RT algorithms, the Climate Prediction Center morphing technique (CMORPH), Precipitation Estimation from Remotely Sensed Imagery Using Artificial Neural Networks (PERSIANN), and the PERSIANN Cloud Classification System (PERSIANN-CCS)] are analyzed in the present work using ground gauge, gauge-adjusted radar, and CloudSat precipitation products. Using ground observation of precipitation and streamflow, the skill of HRPPs and the resulting streamflow simulations from the Variable Infiltration Capacity hydrological model are cross-compared. HRPPs often capture major precipitation events but seldom capture the observed magnitude of precipitation over the studied region and period (2003–09). Bias adjustment is found to be effective in enhancing the HRPPs and resulting streamflow simulations. However, if not bias adjusted using gauges, errors are typically large as in the lower-level precipitation inputs to HRPPs. The results using collocated Advanced Microwave Scanning Radiometer for Earth Observing System (AMSR-E) and CloudSat precipitation data show that missing data, often over frozen land, and limitations in retrieving precipitation from systems that lack frozen hydrometeors contribute to the observed microwave-based precipitation errors transferred to HRPPs. Over frozen land, precipitation retrievals from infrared sensors and microwave sounders show some skill in capturing the observed precipitation climatology maps. However, infrared techniques often show poor detection skill, and microwave sounding in dry atmosphere remains challenging. By recognizing the sources of precipitation error and in light of the operation of the Global Precipitation Measurement mission, further opportunity for enhancing the current status of precipitation retrievals and the hydrology of cold and mountainous regions becomes available.

Beschreibung: Five years of measurements from the Earth Radiation Budget Satellite (ERBS) have been analyzed to define the diurnal cycle of albedo from 55°N to 55°S. The ERBS precesses through all local times every 72 days so as to provide data regarding the diurnal cycles for Earth radiation. Albedo together with insolation at the top of the atmosphere is used to compute the heating of the Earth–atmosphere system; thus its diurnal cycle is important in the energetics of the climate system. A principal component (PC) analysis of the diurnal variation of top-of-atmosphere albedo using these data is presented. The analysis is done separately for ocean and land because of the marked differences of cloud behavior over ocean and over land. For ocean, 90%–92% of the variance in the diurnal cycle is described by a single component; for land, the first PC accounts for 83%–89% of the variance. Some of the variation is due to the increase of albedo with increasing solar zenith angle, which is taken into account in the ERBS data processing by a directional model, and some is due to the diurnal cycle of cloudiness. The second PC describes 2%–4% of the variance for ocean and 5% for land, and it is primarily due to variations of cloudiness throughout the day, which are asymmetric about noon. These terms show the response of the atmosphere to the cycle of solar heating. The third PC for ocean is a two-peaked curve, and the associated map shows high values in cloudy regions.

Beschreibung: One of the challenges that limit the amount of information that can be inferred from radar measurements of ice and mixed-phase precipitating clouds is the variability in ice mass within hydrometeors. The variable amount of ice mass within particles of a given size drives further variability in single-scattering properties that results in uncertainties of forward-modeled remote sensing quantities. Nonspherical ice-phase hydrometeors are often approximated as spheroids to simplify the calculation of single-scattering properties, yet offline calculations remain necessary to quantify these radiative properties as a function of size in discrete increments. In this paper, a simple scaling of the Clausius–Mossotti factor is used that allows for an approximation of the scattering and extinction cross sections for an arbitrary mass–dimensional power-law relationship of a nonspherical particle given a single T-matrix calculation. Using data collected by the University of Wyoming King Air in snow clouds over the Colorado Park Range, the uncertainty in forward-modeled radar reflectivity to assumptions regarding mass–dimensional relationships is examined. This is accomplished by taking advantage of independently measured condensed mass and particle size distributions to estimate the variability of the prefactor in the mass–dimensional power law. Then, calculating the partial derivative of the radar backscatter cross sections using the scaling relationships, an estimate is made of the statistical uncertainty in forward-modeled radar reflectivity. Uncertainties on the order of 4 dB are found in this term for the dataset considered.

Beschreibung: This brief paper addresses the frequency of precipitating open-cell convection over the northeastern Gulf of Alaska during a 5-yr period (2002–06). The research employs 154 previously documented satellite synthetic aperture radar–derived wind speed (SDWS) images that contain open-cell convection signatures. Each SDWS image is paired with a near-in-time, National Weather Service Weather Surveillance Radar-1988 Doppler Level-III 0.5°-elevation-angle short-range base reflectivity image from coastal Alaska for which coverage spatially overlaps open-cell convection signatures. The time difference between any two images of a single pair is typically a few minutes or less. For 65% of the image pairs, at least one SDWS open-cell convection signature in the overlap region is associated with precipitation. That percentage may be conservative given the method used in this research. Thus, the results of this research support a suggestion that has been posed in previous studies that the organization of open-cell convection can be controlled by the interaction of the environmental vertical wind shear and precipitation-driven cold pools.

Beschreibung: Climatic variability over southern Africa is a well-recognized phenomenon, yet knowledge about the temporal variability of extreme seasons is lacking. This study investigates the intraseasonal progression of extreme seasons over Zimbabwe using precipitation and normalized difference vegetation index (NDVI) data covering the 1981–2005 period. Results show that the greatest deficits/surpluses of precipitation occur during the middle of the rainfall season (January and February), and the temporal distribution of precipitation during extreme dry seasons seems to shift earlier than that of extreme wet seasons. Furthermore, anomalous wet (dry) conditions were observed prior to the development of extreme dry (wet) seasons. Impacts of precipitation variations on vegetation lag by approximately 1–2 months. The semiarid southern region experiences more variability of vegetation cover than do the northern and eastern regions. Three distinct temporal patterns of dry years were noted by considering the maximum NDVI level, the mid-postseason NDVI condition, and nested dry spells. The findings of this study emphasize that climate extremes ought not to be simply understood in terms of total seasonal precipitation, because they may have within them some nested distribution patterns that may have a strong influence on primary production.

Beschreibung: The Water Vapor Variability-Satellite/Sondes (WAVES) 2006 field campaign provided a contiguous 5-day period of concentrated high-resolution measurements to examine finescale boundary layer phenomena under the influence of a summertime subtropical high over the mid-Atlantic region that is characterized by complex geography. A holistic analytical approach to low-level wind observations was adopted to identify the low-level flow structures and patterns of evolution on the basis of airmass properties and origination. An analysis of the measurements and the other available observations is consistent with the classic depiction of the daytime boundary layer development but revealed a pronounced diurnal cycle that was categorized into three stages: (i) daytime growth of the convective boundary layer, (ii) flow intensification into a low-level jet regime after dusk, and (iii) interruption by a downslope wind regime after midnight. The use of the field campaign data allows for the differentiation of the latter two flow regimes by their directions with respect to the orientation of the Appalachian Mountains and their airmass origins. Previous studies that have investigated mountain flows and low-level jet circulations have focused on regions with overt geographic prominence, stark gradients, or frequent reoccurrences, whereby such meteorological phenomena exhibit a clear signature and can be easily isolated and diagnosed. The results of this study provide evidence that similar circulation patterns operate in nonclassic locations with milder topography and atmospheric gradients, such as the mid-Atlantic region. The new results have important implications for the understanding of the mountain-forced flows and some air quality problems during the nocturnal period.

Beschreibung: A new rainfall retrieval technique for determining rainfall rates in a continuous manner (day, twilight, and night) resulting in a 24-h estimation applicable to midlatitudes is presented. The approach is based on satellite-derived information on cloud-top height, cloud-top temperature, cloud phase, and cloud water path retrieved from Meteosat Second Generation (MSG) Spinning Enhanced Visible and Infrared Imager (SEVIRI) data and uses the random forests (RF) machine-learning algorithm. The technique is realized in three steps: (i) precipitating cloud areas are identified, (ii) the areas are separated into convective and advective-stratiform precipitating areas, and (iii) rainfall rates are assigned separately to the convective and advective-stratiform precipitating areas. Validation studies were carried out for each individual step as well as for the overall procedure using collocated ground-based radar data. Regarding each individual step, the models for rain area and convective precipitation detection produce good results. Both retrieval steps show a general tendency toward elevated prediction skill during summer months and daytime. The RF models for rainfall-rate assignment exhibit similar performance patterns, yet it is noteworthy how well the model is able to predict rainfall rates during nighttime and twilight. The performance of the overall procedure shows a very promising potential to estimate rainfall rates at high temporal and spatial resolutions in an automated manner. The near-real-time continuous applicability of the technique with acceptable prediction performances at 3–8-hourly intervals is particularly remarkable. This provides a very promising basis for future investigations into precipitation estimation based on machine-learning approaches and MSG SEVIRI data.

Beschreibung: The scale and intensity of extreme wind events have tremendous relevance to determining the impact on infrastructure and natural and managed ecosystems. Analyses presented herein show the following. 1) Wind speeds in excess of the station-specific 95th percentile are coherent over distances of up to 1000 km over the eastern United States, which implies that the drivers of high wind speeds are manifest at the synoptic scale. 2) Although cold fronts associated with extratropical cyclones are a major cause of high–wind speed events, maximum sustained and gust wind speeds are only weakly dependent on the near-surface horizontal temperature gradient across the front. 3) Gust factors (GF) over the eastern United States have a mean value of 1.57 and conform to a lognormal probability distribution, and the relationship between maximum observed GF and sustained wind speed conforms to a power law with coefficients of 5.91 and −0.499. Even though there is coherence in the occurrence of intense wind speeds at the synoptic scale, the intensity and spatial extent of extreme wind events are not fully characterized even by the dense meteorological networks deployed by the National Weather Service. Seismic data from the USArray, a program within the Earthscope initiative, may be suitable for use in mapping high-wind and gust events, however. It is shown that the seismic channels exhibit well-defined spectral signatures under conditions of high wind, with a variance peak at frequencies of ~0.04 s−1 and an amplitude that appears to scale with the magnitude of observed wind gusts.

Beschreibung: A simulation with the Méso-NH model over the island of Mallorca, Spain, has been made in a case of synoptic high pressure (5 June 2010) that allowed the development of sea breezes (SB) in the three main basins of the island. The results compare well to the available observations and are qualitatively very close to a previous idealized study with no synoptic forcing made by Ramis and Romero in 1995. The temporal and spatial structure of the SB in the southeastern basin is analyzed with the use of the momentum, temperature, and turbulence kinetic energy budgets provided by the numerical model. Five stages of evolution from before dawn to after sunset are discussed, identifying the main physical mechanisms at play. The morning land heating warms the land and the air over it until an air temperature gradient is created and a marine flow accelerates inland, dragged by turbulence in the low layers. The upper part of the inland current and the layers just above are dominated by compensatory motions, which oppose the corresponding pressure gradient at these levels. These mechanisms last while the SB is active, with significant effects from the local topography, and they decrease in intensity as sunset approaches. This relatively simple case has been used to check the goodness of two analytical models of the SB that perform relatively well because they use turbulence as a surrogate for the missing advection terms in the layers above 200 m. These models are formulated here in a more consistent manner in the turbulence parameterization than were the original propositions.

Beschreibung: Prediction of direct solar radiation is key in sectors such as solar power and agriculture; for instance, it can enable more efficient production of energy from concentrating solar power plants. An assessment of the quality of the direct solar radiation forecast by two versions of the European Centre for Medium-Range Weather Forecasts (ECMWF) global numerical weather prediction model up to 5 days ahead is carried out here. The performance of the model is measured against observations from four solar monitoring stations over Australia, characterized by diverse geographic and climatic features, for the year 2006. As a reference, the performance of global radiation forecast is carried out as well. In terms of direct solar radiation, while the skill of the two model versions is very similar, and with relative mean absolute errors (rMAEs) ranging from 18% to 45% and correlations between 0.85 and 0.25 at around midday, their performance is substantially enhanced via a simple postprocessing bias-correction procedure. There is a marked dependency on cloudy conditions, with rMAEs 2–4 times as large for very cloudy-to-overcast conditions relative to clear-sky conditions. There is also a distinct dependency on the background climatic clear-sky conditions of the location considered. Tests made on a simulated operational setup targeting three quantiles show that direct radiation forecasts achieve potentially high scores. Overall, these analyses provide an indication of the potential practical use of direct irradiance forecast for applications such as solar power operations.

Beschreibung: The Atmospheric Emitted Radiance Interferometer (AERI) observes spectrally resolved downwelling radiance emitted by the atmosphere in the infrared portion of the electromagnetic spectrum. Profiles of temperature and water vapor, and cloud liquid water path and effective radius for a single liquid cloud layer, are retrieved using an optimal estimation–based physical retrieval algorithm from AERI-observed radiance data. This algorithm provides a full error covariance matrix for the solution, and both the degrees of freedom for signal and the Shannon information content. The algorithm is evaluated with both synthetic and real AERI observations. The AERI is shown to have approximately 85% and 70% of its information in the lowest 2 km of the atmosphere for temperature and water vapor profiles, respectively. In clear-sky situations, the mean bias errors with respect to the radiosonde profiles are less than 0.2 K and 0.3 g kg−1 for heights below 2 km for temperature and water vapor mixing ratio, respectively; the maximum root-mean-square errors are less than 1 K and 0.8 g kg−1. The errors in the retrieved profiles in cloudy situations are larger, due in part to the scattering contribution to the downwelling radiance that was not accounted for in the forward model. Scattering is largest in one of the spectral regions used in the retrieval, however, and removing this spectral region results in a slight reduction of the information content but a considerable improvement in the accuracy of the retrieved thermodynamic profiles.

Beschreibung: This research compares reanalysis-derived proxy soundings from the North American Regional Reanalysis (NARR) with collocated observed radiosonde data across the central and eastern United States during the period 2000–11: 23 important parameters used for forecasting severe convection are examined. Kinematic variables such as 0–6-km bulk wind shear are best represented by this reanalysis, whereas thermodynamic variables such as convective available potential energy exhibit regional biases and are generally overestimated by the reanalysis. For thermodynamic parameters, parcel-ascent choice is an important consideration because of large differences in reanalysis low-level moisture fields versus observed ones. Results herein provide researchers with potential strengths and limitations of using NARR data for the purposes of depicting climatological information for hazardous convective weather and initializing model simulations. Similar studies should be considered for other reanalysis datasets.

Beschreibung: Commonly used statistical tests of hypothesis, also termed inferential tests, that are available to meteorologists and climatologists all require independent data in the time series to which they are applied. However, most of the time series that are usually handled are actually serially dependent. A common approach to handle such a serial dependence is to replace in those statistical tests the actual number of data by an estimated effective number of independent data that is computed from a classical and widely used formula that relies on the autocorrelation function. Despite being perfectly demonstrable under some hypotheses, this formula provides unreliable results on practical cases, for two different reasons. First, the formula has to be applied using the estimated autocorrelation function, which bears a large uncertainty because of the usual shortness of the available time series. After the impact of this uncertainty is illustrated, some recommendations of preliminary treatment of the time series prior to any application of this formula are made. Second, the derivation of this formula is done under the hypothesis of identically distributed data, which is often not valid in real climate or meteorological problems. It is shown how this issue is due to real physical processes that induce temporal coherence, and an illustration is given of how not respecting the hypotheses affects the results provided by the formula.

Beschreibung: This study presents the development of a method to statistically downscale daily wind speed variations in an extended Great Lakes region. A probabilistic approach is used, predicting a daily-varying probability density function (PDF) of local-scale daily wind speed conditioned on large-scale daily wind speed predictors. Advantages of a probabilistic method are that it provides realistic information on the variance and extremes in addition to information on the mean, it allows the autocorrelation of downscaled realizations to be tuned to match the autocorrelation of local-scale observations, and it allows flexibility in the use of the final downscaled product. Much attention is given to fitting the proper functional form of the PDF by investigating the observed local-scale wind speed distribution (predictand) as a function of the decile of the large-scale wind (predictor). It is found that the local-scale standard deviation and the local-scale shape parameter (from a gamma distribution) are nonconstant functions of the large-scale predictor. As such, a vector generalized linear model is developed to relate the large-scale and local-scale wind speeds. Maximum likelihood and cross validation are used to fit local-scale gamma distribution shape and scale parameters to the large-scale wind speed. The result is a daily-varying probability distribution of local-scale wind speed, conditioned on the large-scale wind speed.

Beschreibung: In sub-Saharan Africa, with its high rainfall variability and limited irrigation options, the crop planting date is a crucial tactical decision for farmers and therefore a major concern in agricultural decision making. To support decision making in rainfed agriculture, a new approach has been developed to optimize crop planting date. The General Large-Area Model for Annual Crops (GLAM) has been used for the first time to simulate maize yields in West Africa. It is used in combination with fuzzy logic rules to give more flexibility in crop planting date computation when compared with binary logic methods. A genetic algorithm is applied to calibrate the crop model and to optimize the planting dates at the end. The process for optimizing planting dates results in an ensemble of optimized planting rules. This principle of ensemble members leads to a time window of optimized planting dates for a single year and thereby potentially increases the willingness of farmers to adopt this approach. The optimized planting date (OPD) approach is compared with two well-established methods in sub-Saharan Africa. The results suggest earlier planting dates across Burkina Faso, ranging from 10 to 20 days for the northern and central part and less than 10 days for the southern part. With respect to the potential yields, the OPD approach indicates that an average increase in maize potential yield of around 20% could be obtained in water-limited regions in Burkina Faso. The implementation of the presented approach in agricultural decision support is expected to have the potential to improve agricultural risk management in these regions dominated by rainfed agriculture and characterized by high rainfall variability.

Beschreibung: Extreme heat events (EHEs) are linked to mortality rates, making them an important research subject in both the climate and public health fields. This study evaluated linear trends in EHEs using the U.S. Historical Climatology Network (USHCN), version 2.0, dataset and quantified the longer-term EHE trends across the continental United States (CONUS). The USHCN-daily, version 1, dataset was integrated with the homogenized USHCN-monthly, version 2.0, dataset to create daily data for trend analysis. Time series and estimated trends in multiple characteristics of EHEs (number, total days, mean duration, etc.) were calculated as were the continental means and spatial maps. The differences between EHEs based on daily maximum temperatures, minimum temperatures, and both minimum and maximum temperatures were explored. To focus on warming and cooling periods, the trends were also estimated separately over the first half and second half of the study period (1930–2010). The results indicated that the trends for different EHE characteristics were coherent (e.g., temporally correlated, similar spatial pattern of trends). Maps indicated negative trends in the interior of the CONUS and positive trends in coastal and southern areas. Continental-scale increases between 1970 and 2010 were mostly offset by the decreases between 1930 and 1970. Several daily maximum (minimum) EHEs near the 1930s (2000s) led to 1930–2010 trends of daily maximum (minimum) EHEs decreasing (increasing). Last, the results suggest that linear trends depend on which daily temperature extreme is required to exceed the threshold.

Beschreibung: Gauge-calibrated radar estimates of daily precipitation are compared with daily observed values of precipitation from National Weather Service (NWS) Cooperative Observer Network (COOP) stations to evaluate the multisensor precipitation estimate (MPE) product that is gridded by the National Centers for Environmental Prediction (NCEP) for the eastern United States (defined as locations east of the Mississippi River). This study focuses on a broad evaluation of MPE across the study domain by season and intensity. In addition, the aspect of precipitation type is considered through case studies of winter and summer precipitation events across the domain. Results of this study indicate a north–south gradient in the error of MPE and a seasonal pattern with the highest error in summer and autumn and the lowest error in winter. Two case studies of precipitation are also considered in this study. These case studies include instances of intense precipitation and frozen precipitation. These results suggest that MPE is less able to estimate convective-scale precipitation as compared with precipitation variations at larger spatial scales. In addition, the results suggest that MPE is subject to errors related both to the measurement gauges and to the radar estimates used. Two case studies are also included to discuss the differences with regard to precipitation type. The results from these case studies suggest that MPE may have higher error associated with estimating the liquid equivalent of frozen precipitation when compared with NWS COOP network data. The results also suggest the need for more analysis of MPE error for frozen precipitation in diverse topographic regimes.

Beschreibung: Observations of cloud properties and thermodynamics from two Arctic locations, Barrow, Alaska, and Surface Heat Budget of the Arctic (SHEBA), are examined. A comparison of in-cloud thermodynamic mixing characteristics for low-level, single-layer clouds from nearly a decade of data at Barrow and one full annual cycle over the sea ice at SHEBA is performed. These cloud types occur relatively frequently, evident in 27%–30% of all cloudy cases. To understand the role of liquid water path (LWP), or lack thereof, on static in-cloud mixing, cloud layers are separated into optically thin and optically thick LWP subclasses. Clouds with larger LWPs tend to have a deeper in-cloud mixed layer relative to optically thinner clouds. However, both cloud LWP subclasses are frequently characterized by an in-cloud stable layer above the mixed layer top. The depth of the stable layer generally correlates with an increased temperature gradient across the layer. This layer often contains a specific humidity inversion, but it is more frequently present when cloud LWP is optically thinner (LWP 〈 50 g m−2). It is suggested that horizontal thermodynamic advection plays a key role modifying the vertical extent of in-cloud mixing and likewise the depth of in-cloud stable layers. Furthermore, longwave atmospheric opacity above the cloud top is generally enhanced during cases with optically thinner clouds. Thermodynamic advection, cloud condensate distribution within the stable layer, and enhanced atmospheric radiation above the cloud are found to introduce a thermodynamic–radiative feedback that potentially modifies the extent of LWP and subsequent in-cloud mixing.

Beschreibung: Active remote sensing instruments such as lidar and radar allow one to accurately detect the presence of clouds and give information on their vertical structure and phase. To better address cloud radiative impact over the Arctic area, a combined analysis based on lidar and radar ground-based and A-Train satellite measurements was carried out to evaluate the efficiency of cloud detection, as well as cloud type and vertical distribution, over the Eureka station (80°N, 86°W) between June 2006 and May 2010. Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) and CloudSat data were first compared with independent ground-based cloud measurements. Seasonal and monthly trends from independent observations were found to be similar among all datasets except when compared with the weather station observations because of the large reported fraction of ice crystals suspended in the lower troposphere in winter. Further investigations focused on satellite observations that are collocated in space and time with ground-based data. Cloud fraction occurrences from ground-based instruments correlated well with both CALIPSO operational products and combined CALIPSO–CloudSat retrievals, with a hit rate of 85%. The hit rate was only 77% for CloudSat products. The misdetections were mainly attributed to 1) undetected low-level clouds as a result of sensitivity loss and 2) missed clouds because of the distance between the satellite track and the station. The spaceborne lidar–radar synergy was found to be essential to have a complete picture of the cloud vertical profile down to 2 km. Errors are quantified and discussed.

Beschreibung: A framework based on measured raindrop size distribution (DSD) data has been developed to assess uncertainties in DSD models employed in Ku- and Ka-band dual-wavelength radar retrievals. In this study, the rain rates and attenuation coefficients from DSD parameters derived by dual-wavelength algorithms are compared with those directly obtained from measured DSD spectra. The impact of the DSD gamma parameterizations on rain estimation from the Global Precipitation Measurement mission (GPM) Dual-Frequency Precipitation Radar (DPR) is examined for the cases of a fixed shape factor μ as well as for a constrained μ—that is, a μ–Λ relation (a relationship between the shape parameter and slope parameter Λ of the gamma DSD)—by using 11 Particle Size and Velocity (Parsivel) disdrometer measurements with a total number of about 50 000 one-minute spectra that were collected during the Iowa Flood Studies (IFloodS) experiment. It is found that the DPR-like dual-wavelength techniques provide fairly accurate estimates of rain rate and attenuation if a fixed-μ gamma DSD model is used, with the value of μ ranging from 3 to 6. Comparison of the results reveals that the retrieval errors from the μ–Λ relations are generally small, with biases of less than ±10%, and are comparable to the results from a fixed-μ gamma model with μ equal to 3 and 6. The DSD evaluation procedure is also applied to retrievals in which a lognormal DSD model is used.

Beschreibung: Meteorological application of Global Navigation Satellite System (GNSS) data over Brazil has increased significantly in recent years, motivated by the significant amount of investment from research agencies. Several projects have, among their principal objectives, the monitoring of humidity over Brazilian territory. These research projects require integrated water vapor (IWV) values with maximum quality, and, accordingly, appropriate data from the installed meteorological stations, together with the GNSS antennas, have been used. The model that is applied to estimate the water-vapor-weighted mean tropospheric temperature (Tm) is a source of uncertainty in the estimate of IWV values using the ground-based GNSS receivers in Brazil. Two global models and one algorithm for Tm, developed through the use of radiosondes, numerical weather prediction products, and 40-yr ECMWF Re-Analysis (ERA-40), as well as two regional models, were evaluated using a dataset of ~78 000 radiosonde profiles collected at 22 stations in Brazil during a 12-yr period (1999–2010). The regional models (denoted the Brazilian and regional models) were developed with the use of multivariate statistical analysis using ~90 000 radiosonde profiles launched at 12 stations over a 32-yr period (1961–93). The main conclusion is that the Brazilian model and two global models exhibit similar performance if the complete dataset and the entire period are taken into consideration. However, for seasonal and local variations of the Tm values, the Brazilian model was better than the other two models for most stations. The Tm values from ERA-40 present no bias, but their scatter is larger than that in the other models.

Beschreibung: As computing capabilities expand, operational and research environments are moving toward the use of finescale atmospheric numerical models. These models are attractive for users who seek an accurate description of small-scale turbulent motions. One such numerical tool is the Weather Research and Forecasting (WRF) model, which has been extensively used in synoptic-scale and mesoscale studies. As finer-resolution simulations become more desirable, it remains a question whether the model features originally designed for the simulation of larger-scale atmospheric flows will translate to adequate reproductions of small-scale motions. In this study, turbulent flow in the dry atmospheric convective boundary layer (CBL) is simulated using a conventional large-eddy-simulation (LES) code and the WRF model applied in an LES mode. The two simulation configurations use almost identical numerical grids and are initialized with the same idealized vertical profiles of wind velocity, temperature, and moisture. The respective CBL forcings are set equal and held constant. The effects of the CBL wind shear and of the varying grid spacings are investigated. Horizontal slices of velocity fields are analyzed to enable a comparison of CBL flow patterns obtained with each simulation method. Two-dimensional velocity spectra are used to characterize the planar turbulence structure. One-dimensional velocity spectra are also calculated. Results show that the WRF model tends to attribute slightly more energy to larger-scale flow structures as compared with the CBL structures reproduced by the conventional LES. Consequently, the WRF model reproduces relatively less spatial variability of the velocity fields. Spectra from the WRF model also feature narrower inertial spectral subranges and indicate enhanced damping of turbulence on small scales.

Beschreibung: Across the globe, wind speed trends have shown a slight decline for in situ meteorological datasets. Yet few studies have assessed long-term wind speed trends for alpine regions or how such trends could influence snow transport and distribution. Alpine-region meteorological stations are sparsely distributed, and their records are short. To increase spatial and temporal coverage, use of modeled data is appealing, but the level of agreement between modeled and in situ data is unknown for alpine regions. Data agreement, temporal trends, and the potential effects on snow distribution were evaluated using two in situ sites in an alpine region [Niwot Ridge in Colorado and the Glacier Lakes Ecological Experiments Station (GLEES) in Wyoming] and the corresponding grid cells of the North American Regional Reanalysis (NARR). Temperature, precipitation, and wind speed variables were used to assess blowing-snow trends at annual, seasonal, and daily scales. The correlation between NARR and in situ datasets showed that temperature data were correlated but that wind speed and precipitation were not. NARR wind speed data were systematically lower when compared with in situ data, yet the frequency of wind events was captured. Overall, there were not many significant differences between NARR and in situ wind speed trends at annual, seasonal, and daily scales, aside from GLEES daily values. This finding held true even when trends presented opposite signatures and slopes, which was likely a result of low trend slopes. The lack of agreement between datasets prohibited the use of NARR to broaden analyses for blowing-snow dynamics in alpine regions.

Beschreibung: This observational study examines zonal gradients in the lower atmosphere and upper ocean across the windward Antilles during midsummer 2012. While earlier work reported on meridional confluence, here the focus is on the zonal enrichment of trade winds by upstream shallow seas and islands. Intercomparisons along 18.2°N are made between modern reanalysis and satellite estimates, and coastal station, moored buoy, aircraft, and radiosonde observations for one case and as a June–July 2012 average. Mean gradients per 100 km east of Puerto Rico were 0.2 g kg−1 for 925-hPa specific humidity, 0.16°C for SST, 0.01 m for sea level, and 2.0 × 10−3 g kg−1 for cloud water. Zonal changes in the lower atmosphere occur in three stages: 1) Atlantic, where westward ocean currents, strong trade winds, and subsidence prevail; 2) Antilles, where ocean currents diminish and sea temperatures increase; and 3) island, where trade winds abate [−1 m s−1 (100 km)−1] and diurnal evapotranspiration greater than 10 mm day−1 offsets large-scale subsidence producing a localized convection.

Beschreibung: Rainfall in the Sahel region of Africa is prone to large interannual variability, and it has exhibited a recent multidecadal drying trend. The well-documented social impacts of this variability have motivated numerous efforts at seasonal precipitation prediction, many of which employ statistical techniques that forecast Sahelian precipitation as a function of large-scale indices of surface air temperature (SAT) anomalies, sea surface temperature (SST), surface pressure, and other variables. These statistical models have demonstrated some skill, but nearly all have adopted conventional statistical modeling techniques—most commonly generalized linear models—to associate predictor fields with precipitation anomalies. Here, the results of an artificial neural network (ANN) machine-learning algorithm applied to predict summertime (July–September) Sahel rainfall anomalies using indices of springtime (April–June) SST and SAT anomalies for the period 1900–2011 are presented. Principal component analysis was used to remove multicollinearity between predictor variables. Predictive accuracy was assessed using repeated k-fold random holdout and leave-one-out cross-validation methods. It was found that the ANN achieved predictive accuracy superior to that of eight alternative statistical methods tested in this study, and it was also superior to that of previously published predictive models of summertime Sahel precipitation. Analysis of partial dependence plots indicates that ANN skill is derived primarily from the ability to capture nonlinear influences that multiple major modes of large-scale variability have on Sahelian precipitation. These results point to the value of ANN techniques for seasonal precipitation prediction in the Sahel.

Beschreibung: Global land cover data are widely used in weather, climate, and hydrometeorological models. The Collection 5.1 Moderate Resolution Imaging Spectroradiometer (MODIS) Land Cover Type (MCD12Q1) product is found to have a substantial amount of interannual variability, with 40% of land pixels showing land cover change one or more times during 2001–10. This affects the global distribution of vegetation if any one year or many years of data are used, for example, to parameterize land processes in regional and global models. In this paper, a value-added global 0.5-km land cover climatology (a single representative map for 2001–10) is developed by weighting each land cover type by its corresponding confidence score for each year and using the highest-weighted land cover type in each pixel in the 2001–10 MODIS data. The climatology is validated by comparing it with the System for Terrestrial Ecosystem Parameterization database as well as additional pixels that are identified from the Google Earth proprietary software database. When compared with the data of any individual year, this climatology does not substantially alter the overall global frequencies of most land cover classes but does affect the global distribution of many land cover classes. In addition, it is validated as well as or better than the MODIS data for individual years. Also, it is based on higher-quality data and is validated better than the Global Land Cover Characteristics database, which is based on 1 year of Advanced Very High Resolution Radiometer data and represents a widely used first-generation global product.

Beschreibung: Atmospheric motion vectors (AMVs) provide valuable wind information for the initial conditions of numerical weather prediction models, but height-assignment issues and horizontal error correlations require a rigid thinning of the available AMVs in current data assimilation systems. The aim of this study is to investigate the feasibility of correcting the pressure heights of operational AMVs from the geostationary satellites Meteosat-9 and Meteosat-10 with cloud-top heights derived from lidar observations by the polar-orbiting Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) satellite. The study shows that the wind error of AMVs above 700 hPa is reduced by 12%–17% when AMV winds are assigned to 120-hPa-deep layers below the lidar cloud tops. This result demonstrates the potential of lidar cloud observations for the improvement of the AMV height assignment. In addition, the lidar correction reduces the “slow” bias of current upper-level AMVs and is expected to reduce the horizontal correlation of AMV errors.

Beschreibung: Data collected by the National Center for Atmospheric Research S-band polarimetric radar (S-Pol) during the Terrain-Influenced Monsoon Rainfall Experiment (TiMREX) in Taiwan are analyzed and used to infer storm microphysics in the ice phase of convective storms. Both simultaneous horizontal (H) and vertical (V) (SHV) transmit polarization data and fast-alternating H and V (FHV) transmit polarization data are used in the analysis. The SHV Zdr (differential reflectivity) data show radial stripes of biased data in the ice phase that are likely caused by aligned and canted ice crystals. Similar radial streaks in the linear depolarization ratio (LDR) are presented that are also biased by the same mechanism. Dual-Doppler synthesis and sounding data characterize the storm environment and support the inferences concerning the ice particle types. Small convective cells were observed to have both large positive and large negative Kdp (specific differential phase) values. Negative Kdp regions suggest that ice crystals are vertically aligned by electric fields. Since high |Kdp| values of 0.8° km−1 in both negative and positive Kdp regions in the ice phase are accompanied by Zdr values close to 0 dB, it is inferred that there are two types of ice crystals present: 1) smaller aligned ice crystals that cause the Kdp signatures and 2) larger aggregates or graupel that cause the Zdr signatures. The inferences are supported with simulated ice particle scattering calculations. A radar scattering model is used to explain the anomalous radial streaks in SHV and LDR.

Beschreibung: The capability of the Canadian land surface external modeling system known as the Global Environmental Multiscale Surface (GEM-SURF) system with respect to surface wind predictions is evaluated. Based on the Interactions between Soil, Biosphere, and Atmosphere (ISBA) land surface scheme, and an exponential power law adjusted to the local stability conditions for the prediction of surface winds, the system allows decoupling of surface processes from those of the free atmosphere and enables high resolutions at the surface as dictated by the small-scale heterogeneities of the surface boundary. The simulations are driven by downscaled forecasts from the Regional Deterministic Prediction System, the 15-km Canadian regional operational modeling system. High-resolution, satellite-derived datasets of orography, vegetation, and soil cover are used to depict the surface boundary. The integration domains cover Canada’s eastern provinces at resolutions ranging from that of the driving model to resolutions similar to those of the geophysical datasets. The GEM-SURF predictions outperform those of the driving operational model. Reduction of the standard error and improvement of the model skill is seen as resolution increases, for all wind speeds. Further, the bias error is reduced in association with a rise in the corresponding value of the roughness length. For all examined resolutions GEM-SURF’s predictions are shown to be superior to those obtained through a simple statistical downscaling. In the prospect of the future development of a multicomponent system that provides wind forecasts at levels of wind energy generation, GEM-SURF’s potential for improved scores at the surface and its limited requirements in computer resources make it a suitable surface component of such a system.

Beschreibung: A statistical downscaling model was developed with reanalysis data and applied to forecast northern China summer rainfall (NCSR) using the outputs of the real-time seasonal Climate Forecast System, version 2 (CFSv2). Large-scale climate signals in sea level pressure, 850-hPa meridional wind, and 500-hPa geopotential height as well as several well-known climate indices were considered as potential predictors. Through correlation analysis and stepwise screening, two “optimal” predictors (i.e., sea level pressure over the southwestern Indian Ocean and 850-hPa meridional wind over eastern China) were selected to fit the regression equation. Model reliability was validated with independent data during a test period (1991–2012), in which the simulated NCSR well represented the observed variability with a correlation coefficient of 0.59 and a root-mean-square error of 18.6%. The statistical downscaling model was applied to forecast NCSR for a 22-yr period (1991–2012) using forecast predictors from the CFSv2 with lead times from 1 to 6 months. The results showed much better forecast skills than that directly from the CFSv2 for all lead months, except the 3-month-lead example. The biggest improvement occurred in the 1-month-lead forecast, in which the hit rate increased to 77.3% from 45.5% in the CFSv2 forecast. In the forecast of rainfall at 15 stations, the statistical downscaling model also showed superior capability when compared with the CFSv2, with forecast skill being improved at 73% of stations. In particular, 13 of 15 stations obtained a hit rate exceeding 55%.

Beschreibung: A global stochastic tropical cyclone model was developed as a means for preparing a large number of artificial tropical cyclone (TC) samples with different values for parameters such as track, minimum sea level pressure, and translation speed. In this paper, the model and the results of its verification are presented in detail. The proposed stochastic model is sensitive to approximations of the joint probability distribution functions (PDFs) of TC parameters and temporal correlations. A newly introduced accurate method for approximating joint PDFs by using principal component analysis and cluster analysis resulted in improved reproducibility of TC parameters. The simulation results were compared with historical observational data from the northwestern Pacific, southwestern Pacific, and North Atlantic Oceans. The grid-averaged mean values and distribution patterns of PDFs of TC parameters were in agreement with observational data.

Beschreibung: To accommodate accurate analyses and forecasts of a heavy rainfall event over the Korean Peninsula, the authors assimilated the GPS radio occultation (RO) data by using the Weather Research and Forecasting Model (WRF) and its three-dimensional variational data assimilation system (3DVAR). The employed datasets are from the Constellation Observing System for Meteorology, Ionosphere, and Climate (COSMIC) and Challenging Minisatellite Payload (CHAMP) missions. The selected case was from late October 2006, which intensively hit the northeastern part of the Korean Peninsula with record-breaking rainfall. In this study, the local refractivity observation operator was used in assimilating GPS RO soundings. The results are more pronounced for the cycling assimilation of GPS RO data than for the one-time data assimilation. From all of the parameters investigated (temperature, geopotential height, specific humidity, and winds), the GPS RO soundings highly modified the moisture distribution in the lower troposphere and also changed the wind field via the model dynamics. For the heavy rainfall forecast, the quantitative accuracy of the precipitation forecast with the GPS RO data assimilation was in good agreement with observations in terms of the maximum rainfall amount and threat scores. The improved forecast in the experiment came from the exact positioning of the low pressure system and its consequent convergence near the rainfall area. When RO data and GPS precipitable water data were assimilated simultaneously, the moisture distribution changed horizontally and vertically such that it increased the amount of rainfall, and an accurate description of the convective system development was feasible.

Beschreibung: A comprehensive change-point analysis of annual radiosonde temperature measurements collected at the surface, troposphere, tropopause, and lower-stratosphere levels at both the South and North Polar zones has been done. The data from each zone are modeled as a multivariate Gaussian series with a possible change point in both the mean vector as well as the covariance matrix. Prior to carrying out an analysis of the data, a methodology for computing the large sample distribution of the maximum likelihood estimator of the change point is first developed. The Bayesian approach for change-point estimation under conjugate priors is also developed. A simulation study is carried out to compare the maximum likelihood estimator and various Bayesian estimates. Then, a comprehensive change-point analysis under a multivariate framework is carried out on the temperature data for the period 1958–2008. Change detection is based on the likelihood ratio procedure, and change-point estimation is based on the maximum likelihood principle and other Bayesian procedures. The analysis showed strong evidence of change in the correlation between tropopause and lower-stratosphere layers at the South Polar zone subsequent to 1981. The analysis also showed evidence of a cooling effect at the tropopause and lower-stratosphere layers, as well as a warming effect at the surface and troposphere layers at both the South and North Polar zones.

Beschreibung: The northeastern Pacific Ocean is a preferential location for the formation of closed low pressure systems. These slow-moving, quasi-barotropic systems influence vertical stability and sustain a moist environment, giving them the potential to produce or affect sustained precipitation episodes along the west coast of the United States. They can remain motionless or change direction and speed more than once and thus often pose difficult forecast challenges. This study creates an objective climatological description of 500-hPa closed lows to assess their impacts on precipitation in the western United States and to explore interannual variability and preferred tracks. Geopotential height at 500 hPa from the NCEP–NCAR global reanalysis dataset was used at 6-h and 2.5° × 2.5° resolution for the period 1948–2011. Closed lows displayed seasonality and preferential durations. Time series for seasonal and annual event counts were found to exhibit strong interannual variability. Composites of the tracks of landfalling closed lows revealed preferential tracks as the features move inland over the western United States. Correlations of seasonal event totals for closed lows with ENSO indices, the Pacific decadal oscillation (PDO), and the Pacific–North American (PNA) pattern suggested an above-average number of events during the warm phase of ENSO and positive PDO and PNA phases. Precipitation at 30 U.S. Cooperative Observer stations was attributed to closed-low events, suggesting 20%–60% of annual precipitation along the West Coast may be associated with closed lows.

Beschreibung: Improvements on a statistical tropical cyclone (TC) track model in the western North Pacific Ocean are described. The goal of the model is to study the effect of El Niño–Southern Oscillation (ENSO) on East Asian TC landfall. The model is based on the International Best-Track Archive for Climate Stewardship (IBTrACS) database of TC observations for 1945–2007 and employs local regression of TC formation rates and track increments on the Niño-3.4 index and seasonally varying climate parameters. The main improvements are the inclusion of ENSO dependence in the track propagation and accounting for seasonality in both genesis and tracks. A comparison of simulations of the 1945–2007 period with observations concludes that the model updates improve the skill of this model in simulating TCs. Changes in TC genesis and tracks are analyzed separately and cumulatively in simulations of stationary extreme ENSO states. ENSO effects on regional (100-km scale) landfall are attributed to changes in genesis and tracks. The effect of ENSO on genesis is predominantly a shift in genesis location from the southeast in El Niño years to the northwest in La Niña years, resulting in higher landfall rates for the East Asian coast during La Niña. The effect of ENSO on track propagation varies seasonally and spatially. In the peak activity season (July–October), there are significant changes in mean tracks with ENSO. Landfall-rate changes from genesis– and track–ENSO effects in the Philippines cancel out, while coastal segments of Vietnam, China, the Korean Peninsula, and Japan show enhanced La Niña–year increases.

Beschreibung: Statistical properties of tornado debris signatures (TDSs) are investigated using S- and C-band polarimetric radar data with comparisons to damage surveys and satellite imagery. Close proximity of the radars to the 10 May 2010 Moore–Oklahoma City, Oklahoma, tornado that was rated as a 4 on the enhanced Fujita scale (EF4) provides a large number of resolution volumes, and good temporal and spatial matching for dual-wavelength comparisons. These comparisons reveal that S-band TDSs exhibit a higher radar reflectivity factor (ZHH) and copolar cross-correlation coefficient (ρhv) than do C-band TDSs. Higher S-band ρhv may result from a smaller ratio of non-Rayleigh scatterers to total scatterers due to the smaller electrical sizes of debris and, consequently, reduced resonance effects. A negative ZDR signature is observed at 350 m AGL at both the S and C bands as the tornado passes over a vegetated area near a large body of water. Another interesting signature is a positive (negative) shift in propagation differential phase (ΦDP) at S band (C band), which could result from increased phase folding at C band. With increasing height above 350 m AGL, the S- and C-band ZHH decreases and ρhv increases, indicating a decrease in debris size. To investigate relationships between polarimetric variables and tornado wind fields, range profiles of radial and tangential wind speeds are obtained using two radars. Velocity profiles reveal radial divergence within vortex core flow through 700 m AGL collocated with the TDS. Formation of a weak-echo hole and higher ρhv in the vortex center aloft suggests debris centrifuging, outward motion of scatterers due to radial divergence (i.e., two-cell vortex flow), or both.

Beschreibung: A numerical modeling study has been conducted to explore the ability of the Weather Research and Forecasting (WRF) model-based large-eddy simulation (LES) with 100-m grid spacing to reproduce silver iodide (AgI) particle dispersion by comparing the model results with measurements made on 16 February 2011 over the Medicine Bow Mountains in Wyoming. Xue et al.'s recently developed AgI cloud-seeding parameterization was applied in this study to simulate AgI release from ground-based generators. Qualitative and quantitative comparisons between the LES results and observed AgI concentrations were conducted. Analyses of turbulent kinetic energy (TKE) features within the planetary boundary layer (PBL) and comparisons between the 100-m LES and simulations with 500-m grid spacing were performed as well. The results showed the following: 1) Despite the moist bias close to the ground and above 4 km AGL, the LES with 100-m grid spacing captured the essential environmental conditions except for a slightly more stable PBL relative to the observed soundings. 2) Wind shear is the dominant TKE production mechanism in wintertime PBL over complex terrain and generates a PBL of about 1000-m depth. The terrain-induced turbulent eddies are primarily responsible for the vertical dispersion of AgI particles. 3) The LES-simulated AgI plumes were shallow and narrow, in agreement with observations. The LES overestimated AgI concentrations close to the ground, which is consistent with the higher static stability in the model than is observed. 4) Non-LES simulations using PBL schemes had difficulty in capturing the shear-dominant turbulent PBL structure over complex terrain in wintertime. Therefore, LES of wintertime orographic clouds with grid spacing close to 500 m or finer are recommended.

Beschreibung: Part I of this paper presents the results from a series of plume-tracing flights over the Medicine Bow and Sierra Madre Ranges in south-central Wyoming. These flights, conducted during February and early March of 2011, were part of the Wyoming Weather Modification Pilot Project. Effective targeting of ground-based silver iodide plumes to supercooled clouds has long been a problem for winter orographic cloud-seeding projects. Surface-based ice nucleus (IN) measurements made at a fixed location near the Medicine Bow Range target area had confirmed the effective transport of IN plumes in many cases, but not all. Airborne plume tracing, undertaken to further illuminate the processes involved, provided additional insight into the plume behavior while providing physical measurements that were later compared with large-eddy-simulation modeling (Part II). It was found that the plumes were most often encountered along the flight paths set out in the experimental designs and, in the absence of convection, appear to be mostly confined to the lowest 600 m above the highest terrain. All passes above 600 m above ground level revealed IN concentrations greater than background levels, however. An estimate of IN flux measured over the Medicine Bow Range was approximately 85% of that produced by the five ground-based IN generators active at the time.

Beschreibung: The impact of 8-day-averaged data from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor—namely, the 1-km leaf area index, absorbed photosynthetic radiation, and land-use data—is investigated for use in the Weather Research and Forecasting (WRF) model for regional weather prediction. These high-resolution, near-real-time MODIS data are hypothesized to enhance the representation of land–atmosphere interactions and to potentially improve the WRF model forecast skill for temperature, surface moisture, surface fluxes, and soil temperature. To test this hypothesis, the impact of using MODIS-based land surface data on surface energy and water budgets was assessed within the “Noah” land surface model with two different canopy-resistance schemes. An ensemble of six model experiments was conducted using the WRF model for a typical summertime episode over the U.S. southern Great Plains that occurred during the International H2O Project (IHOP_2002) field experiment. The six model experiments were statistically analyzed and showed some degree of improvement in surface latent heat flux and sensible heat flux, as well as surface temperature and moisture, after land use, leaf area index, and green vegetation fraction data were replaced by remotely sensed data. There was also an improvement in the WRF-simulated temperature and boundary layer moisture with MODIS data in comparison with the default U.S. Geological Survey land-use and leaf area index inputs. Overall, analysis suggests that recalibration and improvements to both the input data and the land model help to improve estimation of surface and soil parameters and boundary layer moisture and led to improvement in simulating convection in WRF runs. Incorporating updated land conditions provided the most notable improvements, and the mesoscale model performance could be further enhanced when improved land surface schemes become available.

Beschreibung: The liquid water content and drop diameters in supercooled clouds have been measured since the 1940s at the summit of Mount Washington in New Hampshire using a rotating multicylinder. Many of the cloud microphysics models in the Weather Research and Forecasting Model (WRF) assume a gamma distribution for cloud drops. In this paper, years of multicylinder data are reanalyzed to determine the best-fitting gamma or monodisperse distribution to compare with parameters in the WRF cloud models. The single-moment cloud schemes specify a predetermined and constant drop number density in clouds, which leads to a fixed relationship between the median volume drop diameter and the liquid water content. The Mount Washington drop number densities are generally larger and best-fit distributions are generally narrower than is typically assumed in WRF.

Beschreibung: The U.S. tornado record is subject to inhomogeneities that are due to inconsistent practices in counting tornadoes, assessing their damage, and measuring pathlength and path width. Efforts to improve the modern tornado record (1950–2012) have focused on the following: 1) the rationale for removing the years 1950–52, 2) identification of inconsistencies in F0, F1, and F2 counts based on implementation of the Fujita scale (F scale) and Doppler radar, 3) overestimation of backward-extrapolated F-scale intensity, and 4) a change in path-width reporting from mean width (1953–94) to maximum width (1995–2012). Unique adjustments to these inconsistencies are made by analyzing trends in tornado counts, comparing with previous studies, and making an upward adjustment of tornadoes classified by mean width to coincide with those classified by maximum width. Such refinements offer a more homogeneous tornado record and provide the opportunity to better evaluate climatological trends in significant (F/EF2–F/EF5) tornado activity. The median EF-scale (enhanced Fujita scale) wind speeds Vmed have been adopted for all significant tornadoes from 1953 to 2012, including an adjustment for overestimated intensities from 1953 to 1973. These values are used to calculate annual mean kinetic energy, which shows no apparent trend. The annual mean maximum path width from 1953 to 2012 (adjusted upward from 1953 to 1994 to obtain a common lower threshold), however, displays an increasing trend. Also, the EF-scale median wind speeds are highly correlated with . The quantity (Vmed × PWmax)2 is proposed as a tornado destruction index, and, when calculated as an annual cumulative value, the three largest years are 2007, 2008, and 2011.

Beschreibung: Deep convective systems observed by the High Altitude Imaging Wind and Rain Airborne Profiler (HIWRAP) radar during the 2011 Midlatitude Continental Convective Clouds Experiment (MC3E) field campaign in Oklahoma provide the first evidence of multiple-scattering effects simultaneously at Ku and Ka band. One feature is novel and noteworthy: often, in correspondence to shafts with strong convection and when moving from the top of the cloud downward, the dual wavelength ratio (DWR) first increases as usual in Ku–Ka-band observations, but then it reaches a maximum and after that point it steadily decreases all the way to the surface, forming what will be hereinafter referred to as a knee. This DWR knee cannot be reproduced by single-scattering theory under almost any plausible cloud microphysical profile. On the other hand, it is explained straightforwardly with the help of multiple-scattering theory when simulations involving hail-bearing convective cores with large horizontal extents are performed. The DWR reduction in the lower troposphere (i.e., DWR increasing with altitude) is interpreted as the result of multiple-scattering pulse stretching caused by the highly diffusive hail layer positioned high up in the atmosphere, with Ka multiple scattering typically exceeding that occurring in the Ku channel. Since the effects of multiple scattering increase with increasing footprint size, if multiple-scattering effects are present in the aircraft measurements, they are likely to be more pronounced in the spaceborne dual-frequency Ku–Ka radar observations, envisaged for the NASA–Japan Aerospace Exploration Agency (JAXA) Global Precipitation Measurement (GPM) Mission, launched in February 2014. This notional study supports the idea that DWR knees will be observed by the GPM radar when overflying high-density ice shafts embedded in large convective systems and suggests that their explanation must not be sought in differential attenuation or differential Mie effects but via multiple-scattering effects.

Beschreibung: To date, one of the most widely used parametric forms for modeling raindrop size distribution (DSD) is the three-parameter gamma. The aim of this paper is to analyze the error of assuming such parametric form to model the natural DSDs. To achieve this goal, a methodology is set up to compare the rain rate obtained from a disdrometer-measured drop size distribution with the rain rate of a gamma drop size distribution that produces the same triplets of dual-polarization radar measurements, namely reflectivity factor, differential reflectivity, and specific differential phase shift. In such a way, any differences between the values of the two rain rates will provide information about how well the gamma distribution fits the measured precipitation. The difference between rain rates is analyzed in terms of normalized standard error and normalized bias using different radar frequencies, drop shape–size relations, and disdrometer integration time. The study is performed using four datasets of DSDs collected by two-dimensional video disdrometers deployed in Huntsville (Alabama) and in three different prelaunch campaigns of the NASA–Japan Aerospace Exploration Agency (JAXA) Global Precipitation Measurement (GPM) ground validation program including the Hydrological Cycle in Mediterranean Experiment (HyMeX) special observation period (SOP) 1 field campaign in Rome. The results show that differences in rain rates of the disdrometer DSD and the gamma DSD determining the same dual-polarization radar measurements exist and exceed those related to the methodology itself and to the disdrometer sampling error, supporting the finding that there is an error associated with the gamma DSD assumption.

Beschreibung: The daily cycle of precipitation (DCP) in the austral autumn on the northern coast of Brazil (NCB) is examined in detail. The Tropical Rainfall Measuring Mission 3B42 dataset was used to obtain the DCP, and the intradaily variability was measured using the coefficient of variation (CV). The DCP data of the NCB were grouped into five regimes. A new regime was found, called the shore regime. It has a minimum CV, and its cycle shows both continental (late afternoon peak) and oceanic features (morning peak). The landside coastal regime was divided into two areas: a continental coast regime, with very high CV, and an inland coast regime, with clear inland phase propagation. The continental regime was divided into two categories: an inland regime with low and high variability. The Forecast and Tracking of the Evolution of Cloud Clusters (ForTraCC) data were used to relate convective systems (CS) and their processes to the DCP. The following processes are studied for the CS: initiation/dissipation, merge/split, area increase/reduction, and advection. Initiation is more concentrated in time, while dissipation is more distributed. Physical mechanisms that generate initiation can promote area expansion and hence CS merge. By considering a simple parameterization, the time scale of the CS area reduction under environmental conditions that are unfavorable to initiation ranges from 6 to 12 h. Therefore, there is upscaling of the CS in the afternoon and slow decay during the night and morning, which leads to a more uniform cycle inland.

Beschreibung: Based on the observational datasets of rime and glaze from 743 stations in China and the atmospheric circulation data from the NCEP–NCAR reanalysis during 1954–2009, large-scale atmospheric and oceanic conditions for extensive and persistent rime and glaze events were examined with a composite analysis. Results show that rime events mostly occur in northern China while glaze events are mainly observed in southern China. The icing events are accompanied by low temperature and high humidity but not necessarily by above-normal precipitation. The Asian low, blocking highs, strong moisture transport, and an inversion layer related to major abnormal circulation systems contribute to the occurrence and persistence of icing events in China. The Ural blocking high plays a major role in the glaze events, and the Okhotsk blocking high is closely related to the rime events. For glaze events, extratropical circulation anomalies and the southward outbreak of cold air play a dominant role. In contrast, the strong northward transport of warm and moist airflows plays a leading role and the blocking high and the southward outbreak of extratropical cold air take a supporting role for rime events. There is nearly an equal chance for occurrences of rime events under La Niña and El Niño backgrounds. However, glaze events more likely occur under the background of La Niña. Additionally, the sea surface temperatures from the tropical Indian Ocean to the tropical northwestern Pacific Ocean also contribute to the occurrence and maintenance of icing events in China.

Beschreibung: Two mixed-phase precipitation events were observed on 21 September and 20 October 2010 over the southern part of Finland during the Light Precipitation Validation Experiment (LPVEx). These events have been simulated using the Weather Research and Forecasting Model coupled with spectral bin microphysics (WRF–SBM). The detailed ice-melting scheme with prognosis of the liquid water fraction during melting enables explicit simulation of microphysical properties in the melting layer. First, the simulations have been compared with C-band 3D radar measurements for the purpose of evaluating the overall profiles of cloud and precipitation. The simulation has some artificial convective patterns and errors in the forecast displacement of the precipitation system. The overall overestimation of reflectivity is consistent with a bias toward the range characterized by large-diameter droplets in the surface drop size distribution. Second, the structure of the melting bands has been evaluated against vertically pointing K-band radar measurements. A peak in reflectivity and a gradual change in Doppler velocity are observed and similarly simulated in the common temperature range from approximately 0° to 3°C. The effectiveness of the time-dependent melting scheme has been justified by intercomparison with a corresponding simulation using an instantaneous melting scheme. A weakness of the new melting scheme is that melting particles having high liquid water fractions on the order of 80%–90% cannot be simulated. This situation may cause underestimation of radar reflectivity in the melting layer because of the assumptions of melting-particle structure used to calculate the scattering properties.

Beschreibung: Tropical Applications of Meteorology Using Satellite Data and Ground-Based Observations (TAMSAT) rainfall monitoring products have been extended to provide spatially contiguous rainfall estimates across Africa. This has been achieved through a new, climatology-based calibration, which varies in both space and time. As a result, cumulative estimates of rainfall are now issued at the end of each 10-day period (dekad) at 4-km spatial resolution with pan-African coverage. The utility of the products for decision making is improved by the routine provision of validation reports, for which the 10-day (dekadal) TAMSAT rainfall estimates are compared with independent gauge observations. This paper describes the methodology by which the TAMSAT method has been applied to generate the pan-African rainfall monitoring products. It is demonstrated through comparison with gauge measurements that the method provides skillful estimates, although with a systematic dry bias. This study illustrates TAMSAT’s value as a complementary method of estimating rainfall through examples of successful operational application.

Beschreibung: In this study, the summertime outdoor heat stress hazard and heat disorder risks (HDR) were simulated numerically using a mesoscale meteorological model combined with an urban canopy model and a building energy model. Model grid maps including the 23 wards of Tokyo (23 Tokyo), Japan, were produced with a 1-km horizontal resolution for the period of July–September 2010. Model simulations of the daily maximum wet-bulb globe temperature (WBGTmax), which was adopted as a heat stress index, indicated the spatial heterogeneity of the heat stress hazard within 23 Tokyo. The heat stress hazard was greater in the inland western region, particularly for sunny conditions in July and August (based on the monthly mean; the maximum difference exceeded 2°C for both sunny and shaded conditions). This likely occurred as a result of greater spatial heterogeneity in the globe temperature than in the air temperature among model grid cells, with differences in the radiation environment induced by differences in urban geometric parameters. Gridded mapping of HDR simulations proceeded in two steps, using the incidence rate and the absolute number of heat disorder patients (HDP). These simulations were achieved by combining the exponential relationships between the actual WBGTmax and the number of HDP with the daytime grid population. Eventually, the resulting HDR maps incorporated the effects of the spatial heterogeneities of both the outdoor heat stress hazard and the daytime grid population.

Beschreibung: The radiative properties of clouds are related to cloud microphysical and optical properties, including water path, optical depth, particle size, and thermodynamic phase. Ground-based observations from remote sensors provide high-quality, long-term, continuous measurements that can be used to obtain these properties. In the Arctic, a more comprehensive understanding of cloud microphysics is important because of the sensitivity of the Arctic climate to changes in radiation. Eureka, Nunavut (80°N, 86°25′W, 10 m), Canada, is a research station located on Ellesmere Island. A large suite of ground-based remote sensors at Eureka provides the opportunity to make measurements of cloud microphysics using multiple instruments and methodologies. In this paper, cloud microphysical properties are presented using a retrieval method that utilizes infrared radiances obtained from an infrared spectrometer at Eureka between March 2006 and April 2009. These retrievals provide a characterization of the microphysics of ice and liquid in clouds with visible optical depths between 0.25 and 6, which are a class of clouds whose radiative properties depend greatly on their microphysical properties. The results are compared with other studies that use different methodologies at Eureka, providing context for multimethod perspectives. The authors’ findings are supportive of previous studies, including seasonal cycles in phase and liquid particle size, weak temperature–phase dependencies, and frequent occurrences of supercooled water. Differences in microphysics are found between mixed-phase and single-phase clouds for both ice and liquid. The Eureka results are compared with those obtained using a similar retrieval technique during the Surface Heat Budget of the Arctic Ocean (SHEBA) experiment.

Beschreibung: Diagnosing foehn winds from weather station data downwind of topographic obstacles requires distinguishing them from other downslope winds, particularly nocturnal ones driven by radiative cooling. An automatic classification scheme to obtain reproducible results that include information about the (un)certainty of the diagnosis is presented. A statistical mixture model separates foehn and no-foehn winds in a measured time series of wind. In addition to wind speed and direction, it accommodates other physically meaningful classifiers such as the (potential) temperature difference to an upwind station (e.g., near the crest) or relative humidity. The algorithm was tested for Wipp Valley in the central Alps against human expert classification and a previous objective method (Drechsel and Mayr 2008), which the new method outperforms. Climatologically, using only wind information gives nearly identical foehn frequencies as when using additional covariables. A data record length of at least one year is required for satisfactory results. The suitability of mixture models for objective classification of foehn at other locations will have to be tested in further studies.

Beschreibung: The Pearl River Delta region has experienced rapid urbanization and economic development during the past 20 years. To investigate the impacts of urbanization on regional climate, the Advanced Research core of the Weather Research and Forecasting (ARW-WRF) model is used to conduct a pair of 1-yr simulations with two different representations of urbanization. Results show that the reduction in vegetated and irrigated cropland due to urban expansion significantly modifies the near-surface temperature, humidity, wind speed, and regional precipitation, which are obtained based on the significance t test of the differences between two simulations with different urbanization representations at the 95% level. Urbanization causes the mean 2-m temperature over urbanized areas to increase in all seasons (from spring to winter: 1.7° ± 0.7°C, 1.4° ± 0.3°C, 1.3° ± 0.3°, and 0.9° ± 0.4°C, respectively) and the urban diurnal temperature range decreases in three seasons and increases in one (from spring to winter: −0.5° ± 0.3°C, +0.6° ± 0.3°C, −0.4° ± 0.2°C, and −0.8° ± 0.2°C, respectively). Urbanization reduces near-surface water vapor (1.5 g kg−1 in summer and 0.4 g kg−1 in winter), 10-m wind speed (37% independent of season), and annual total precipitation days (approximately 6–14 days). However, the total rainfall amount increases by approximately 30%, since the decrease in the number of days with light rain (8–12) is overcome by the increase in the number of days of heavy or extreme rain (3–6), suggesting that urbanization induces more heavy rain events over the urban areas. Overall, the effect of urbanization on regional climate in the Pearl River Delta is found to be significant and must be considered in any broader regional climate assessment.

Beschreibung: The relationship between atmospheric boundary layer (ABL) depth uncertainty and uncertainty in atmospheric transport and dispersion (ATD) simulations is investigated by examining profiles of predicted concentrations of a contaminant. Because ensembles are an important method for quantifying uncertainty in ATD simulations, this work focuses on the utilization and analysis of ensemble members’ ABL structures for ATD simulations. A 12-member physics ensemble of meteorological model simulations drives a 12-member explicit ensemble of ATD simulations. The relationship between ABL depth and plume depth is investigated using ensemble members, which vary both the relevant model physics and the numerical methods used to diagnose ABL depth. New analysis methods are used to analyze ensemble output within an ABL-depth relative framework. Uncertainty due to ABL depth calculation methodology is investigated via a four-member mini-ensemble. When subjected to a continuous tracer release, concentration variability among the ensemble members is largest near the ABL top during the daytime, apparently because of uncertainty in ABL depth. This persists to the second day of the simulation for the 4-member diagnosis mini-ensemble, which varies only the ABL depth, but for the 12-member physics ensemble the concentration variability is large throughout the daytime ABL. This suggests that the increased within-ABL concentration variability on the second day is due to larger differences among the ensemble members’ predicted meteorological conditions rather than being solely due to differences in the ABL depth diagnosis methods. This work demonstrates new analysis methods for the relationship between ABL depth and plume depth within an ensemble framework and provides motivation for directly including ABL depth uncertainty from a meteorological model into an ATD model.

Beschreibung: Pseudovertical temperature “soundings” from lines of inexpensive temperature sensors on the sidewalls of Utah’s Salt Lake valley are compared with contemporaneous radiosonde soundings from the north, open end of the valley. Morning [0415 mountain standard time (MST)] soundings are colder, and afternoon (1615 MST) soundings are warmer than radiosonde soundings because of warm and cold boundary layers that form over the slopes. Cross-valley temperature differences occur between east- and west-facing sidewalls because of differing insolation. Differences in vertically averaged pseudovertical and radiosonde temperatures are generally within 1°C, with a standard deviation of 2°–3°C. The pseudovertical soundings are especially good proxies for radiosondes in winter. The sounding comparisons identified along-valley differences in temperature, inversion depth, and lapse rate that have led to hypotheses concerning their causes, to be evaluated with future research. The low cost and much better time resolution of the pseudovertical soundings suggest that such lines will be a useful supplement to valley radiosondes and will have significant operational advantages if available in real time. Lines of surface-based sensors will prove useful in identifying intravalley meteorological differences and may be used to estimate free-air temperature structure in other valleys where radiosondes are unavailable.

Beschreibung: Background error modeling plays a key role in a variational data assimilation system. The National Meteorological Center (NMC) method has been widely used in variational data assimilation systems to generate a forecast error ensemble from which the climatological background error covariance can be modeled. In this paper, the characteristics of the background error modeling via the NMC method are investigated for the variational data assimilation system of the Weather Research and Forecasting (WRF-Var) Model. The background error statistics are extracted from short-term 3-km-resolution forecasts in June, July, and August 2012 over a limited-area domain. It is found 1) that background error variances vary from month to month and also have a feature of diurnal variations in the low-level atmosphere and 2) that u- and υ-wind variances are underestimated and their autocorrelation length scales are overestimated when the default control variable option in WRF-Var is used. A new approach of control variable transform (CVT) is proposed to model the background error statistics based on the NMC method. The new approach is capable of extracting inhomogeneous and anisotropic climatological information from the forecast error ensemble obtained via the NMC method. Single observation assimilation experiments show that the proposed method not only has the merit of incorporating geographically dependent covariance information, but also is able to produce a multivariate analysis. The results from the data assimilaton and forecast study of a real convective case show that the use of the new CVT improves synoptic weather system and precipitation forecasts for up to 12 h.

Beschreibung: The standardized precipitation index (SPI) is computed and analyzed using 55 years of precipitation data recorded in 24 observation stations in Cameroon along with University of East Anglia Climate Research Unit (CRU) spatialized data. Four statistical distribution functions (gamma, exponential, Weibull, and lognormal) are first fitted to data accumulated for various time scales, and the appropriate functions are selected on the basis of the Anderson–Darling goodness-of-fit statistic. For short time scales (up to 6 months) and for stations above 10°N, the gamma distribution is the most frequent choice; below this belt, the Weibull distribution predominates. For longer than 6-month time scales, there are no consistent patterns of fitted distributions. After calculating the SPI in the usual way, operational drought thresholds that are based on an objective method are determined at each station. These thresholds are useful in drought-response decision making. From SPI time series, episodes of severe and extreme droughts are identified at many stations during the study period. Moderate/severe drought occurrences are intra-annual in short time scales and interannual for long time scales (greater than 9 months), usually spanning many years. The SPI calculated from CRU gridded precipitation shows similar results, with some discrepancies at longer scales. Thus, the spatialized dataset can be used to extend such studies to a larger region—especially data-scarce areas.

Beschreibung: The liquid water fraction of individual snowflakes f is an important parameter when calculating the radar reflectivity of a melting layer. A ground-based observation of f at Nagaoka, Japan, was conducted by using dye-treated filter papers that were kept at a temperature of 0°C. From the results of these measurements, which consisted of 6179 particles taken with 44 sheets of filter paper, two empirical relationships are proposed. The first is a relationship between the ratio of liquid water flux to total precipitation intensity (FL; taking values from 0 to 1) and meteorological surface data. The second is a relationship to estimate f using the melted diameter of a snowflake, median mass diameter, and FL. It was determined that the root-mean-square errors for estimating FL and f by using these relationships were 0.160 and 0.144, respectively. It was also found that the ratio of raindrop flux to the total precipitation intensity FR was always below 0.1 when FL was less than 0.6 but increased rapidly when FL exceeded 0.8.

Beschreibung: In this study, methods of convective/stratiform precipitation classification and surface rain-rate estimation based on the Atmospheric Radiation Measurement Program (ARM) cloud radar measurements were developed and evaluated. Simultaneous and collocated observations of the Ka-band ARM zenith radar (KAZR), two scanning precipitation radars [NCAR S-band/Ka-band Dual Polarization, Dual Wavelength Doppler Radar (S-PolKa) and Texas A&M University Shared Mobile Atmospheric Research and Teaching Radar (SMART-R)], and surface precipitation during the Dynamics of the Madden–Julian Oscillation/ARM MJO Investigation Experiment (DYNAMO/AMIE) field campaign were used. The motivation of this study is to apply the unique long-term ARM cloud radar observations without accompanying precipitation radars to the study of cloud life cycle and precipitation features under different weather and climate regimes. The resulting convective/stratiform classification from KAZR was evaluated against precipitation radars. Precipitation occurrence and classified convective/stratiform rain fractions from KAZR compared favorably to the collocated SMART-R and S-PolKa observations. Both KAZR and S-PolKa radars observed about 5% precipitation occurrence. The convective (stratiform) precipitation fraction is about 18% (82%). Collocated disdrometer observations of two days showed an increased number concentration of small and large raindrops in convective rain relative to dominant small raindrops in stratiform rain. The composite distributions of KAZR reflectivity and Doppler velocity also showed distinct structures for convective and stratiform rain. These evidences indicate that the method produces physically consistent results for the two types of rain. A new KAZR-based, two-parameter [the gradient of accumulative radar reflectivity Ze (GAZ) below 1 km and near-surface Ze] rain-rate estimation procedure was developed for both convective and stratiform rain. This estimate was compared with the exponential Z–R (reflectivity–rain rate) relation. The relative difference between the estimated and surface-measured rainfall rates showed that the two-parameter relation can improve rainfall estimation relative to the Z–R relation.