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The fire danger rating system implemented in New Zealand is the Canadian Fire Weather Index (FWI) System developed 40 years ago for Canadian temperate forests. Issues have been raised in relation to this system when applied in other regions with different climate and vegetation environments. For the first time, two methods were proposed for improving the Drought Code (DC) component of the FWI System for New Zealand. The first method (PotE) employs a potential evaporation (PE) scheme that considers wind speed, surface air stability, and water vapor mixing ratio gradient. The second method (soilM) uses soil moisture. For the latter, when soil moisture is derived from observations, the calculated DC represents the actual drought status of the soil. DC and FWI have been calculated with the original and the two new DC methods at 28 climate stations in New Zealand for a pair of 2-yr periods. The Joint U.K. Land Environment Simulator (JULES) was run to provide the PE and soil moisture for the two methods. The original DC method underestimated the drought status in New Zealand, especially in summer, leading to underestimation of FWI. The PotE method significantly overestimated the drought status in summer. The errors in the calculated drought status and FWI were largely reduced by using the soilM method with simulated soil moisture from JULES. In this paper, the reasons for this reduction in error are investigated by testing the sensitivity of DC to surface evaporation and to soil parameters. Potential benefit is found from using the proposed soilM method for monitoring drought status and for FWI calculations. [ABSTRACT FROM AUTHOR]

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

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

In this paper the construction of real-time integrated water vapor (IWV) maps from a surface network of global positioning system (GPS) receivers is presented. The IWV maps are constructed using a two-dimensional variational technique with a persistence background that is 15 min old. The background error covariances are determined using a novel two-step method, which is based on the Hollingsworth–Lonnberg method. The quality of these maps is assessed by comparison with radiosonde observations and IWV maps from a numerical weather prediction (NWP) model. The analyzed GPS IWV maps have no bias against radiosonde observations and a small bias against NWP analysis and forecasts up to 9 h. The standard deviation with radiosonde observations is around 2 kg m-2, and the standard deviation with NWP increases with increasing forecast length (from 2 kg m-2 for the NWP analysis to 4 kg m-2 for a forecast length of 48 h). To illustrate the additional value of these real-time products for nowcasting, three thunderstorm cases are discussed. The constructed GPS IWV maps are combined with data from the weather radar, a lightning detection network, and surface wind observations. All cases show that the location of developing thunderstorms can be identified 2 h prior to initiation in the convergence of moist air. [ABSTRACT FROM AUTHOR]

Water vapor plays a key role in the global hydrologic cycle and in climatic change. However, the distribution and variability of water vapor in the troposphere are not understood well—in particular, in China with the complex Tibetan Plateau and the influence of the Asian and Pacific monsoons. In this paper, continuous global positioning system (GPS) observations for 2004–07 in China are used to produce precipitable water vapor (PWV) measurements; these measurements constitute the first investigation of PWV distribution and variability over China. It has been found that the stronger water vapor values are in southeastern China and the lower water vapor values are in northwestern China. These distributions are mainly affected by the latitude, topographical features, the season, and the monsoon. Water vapor variations over China are mainly dominated by seasonal variations. The strong seasonal cycles are in summer with maximum water vapor and in winter with minimum water vapor. The PWV in southeastern China has an annual amplitude of about 15 mm, much larger than in northwestern China at about 4 mm, and meanwhile the time of peak water vapor content is one month earlier than in other regions, probably because of the known rainy season (mei-yu). In addition, significant diurnal variations of water vapor are found over all GPS stations, with a mean amplitude of about 0.7 mm, and the peak value occurs around noon or midnight, depending on geographic location and topographical features. The semidiurnal cycle is weaker, with a mean amplitude of about 0.3 mm, and the first peak PWV value appears around noon. [ABSTRACT FROM AUTHOR]

Atmospheric Infrared Sounder (AIRS; NASA Aqua platform) observations over land are interpreted in terms of monthly mean surface emissivity spectra at a resolution of 0.05 μm and skin temperature. For each AIRS observation, an estimation of the atmospheric temperature and water vapor profiles is first obtained through a proximity recognition within the thermodynamic initial guess retrieval (TIGR) climatological library of about 2300 representative clear-sky atmospheric situations. With this a priori information, all terms of the radiative transfer equation are calculated by using the Automatized Atmospheric Absorption Atlas (4A) line-by-line radiative transfer model. Then, surface temperature is evaluated by using a single AIRS channel (centered at 12.183 μm) chosen for its almost constant emissivity with respect to soil type. Emissivity is then calculated for a set of 40 atmospheric windows (transmittance greater than 0.5) distributed over the AIRS spectrum. The overall infrared emissivity spectrum at 0.05-μm resolution is finally derived from a combination of high-spectral-resolution laboratory measurements of various materials carefully selected within the Moderate-Resolution Imaging Spectroradiometer/University of California, Santa Barbara (MODIS/UCSB) and Advanced Spaceborne Thermal Emission and Reflection Radiometer/Jet Propulsion Laboratory (ASTER/JPL) emissivity libraries. It is shown from simulations that the accuracy of the method developed in this paper, the multispectral method (MSM), varies from about 3% around 4 μm to considerably less than 1% in the 10–12-μm spectral window. Three years of AIRS observations (from April 2003 to March 2006) between 30°S and 30°N have been processed and interpreted in terms of monthly mean surface skin temperature and emissivity spectra from 3.7 to 14.0 μm at a spatial resolution of 1° × 1°. AIRS retrievals are compared with the MODIS (also flying aboard the NASA/Aqua platform) monthly mean L3 products and with the University of Wisconsin Cooperative Institute for Meteorological Satellite Studies baseline-fit method (UW/CIMSS BF) global infrared land surface emissivity database. [ABSTRACT FROM AUTHOR]

Typical diurnal wind patterns and their relationship to transport of atmospheric aerosol in the Columbia River gorge of Oregon and Washington are addressed in this paper. The measurement program included measurements of light scattering by particles (bsp) with nephelometers, and wind speed and direction, temperature, and relative humidity at seven locations in the gorge. Winds are shown to respond to along-gorge pressure gradients, and five common patterns were identified: strong, moderate, and light westerly (west to east), light easterly, and winter easterly. The strong westerly and winter easterly patterns were the most common summer and winter patterns, respectively, and represented strong gap flow. The light westerly and light easterly patterns occurred most frequently in spring and autumn transition periods. Winter easterly had the highest light scattering and indicated sources east of the gorge mainly responsible for haze. During summer, as westerly winds increased diurnally, a pulse of hazy air from the Portland, Oregon, metropolitan area is transported eastward into the gorge, arriving later with distance into the gorge. During light easterly flow impacts to haze from the city of The Dalles, Oregon, are noted as the wind shifts direction diurnally. [ABSTRACT FROM AUTHOR]

Système d’analyse fournissant des renseignements atmosphériques à la neige (SAFRAN) is a mesoscale atmospheric analysis system for surface variables. It produces an analysis at the hourly time step using ground data observations. One of SAFRAN’s main features is that it is based on climatically homogeneous zones and is able to take vertical variations into account. Originally intended for mountainous areas, it was later extended to cover France. This paper focuses on the validation of the extended version. The principle of the analysis is described and its quality was tested for five parameters (air temperature, humidity, wind speed, rainfall, and incoming radiation), using Météo-France’s observation network and data of some well-instrumented stations. Moreover, SAFRAN’s rainfall was compared with another analysis, known as analyse utilisant le relief pour l’hydrométéorologie (Aurelhy). Last, two different versions of SAFRAN were compared for mountain conditions. Temperature and relative humidity were well reproduced, presenting no bias. Wind speed was also well reproduced; however, its bias was -0.3 m s–1. The interpolation from the 6-h time step of the analysis to the 1-h time step was one of the sources of error. The precipitation analysis was robust and not biased; its root-mean-square error was 2.4 mm day-1. This error was mainly due to the spatial heterogeneity of the precipitation within the geographical zones of analysis (1000 km2). The analysis of incoming solar radiation presented some biases, especially in coastal areas. The results of the comparison with some well-instrumented sites were encouraging. SAFRAN is being run operationally at Météo-France on a real-time basis for various applications. [ABSTRACT FROM AUTHOR]

Correlation analysis between precipitable water vapor (PWV) and precipitation over China was conducted by combining high-quality PWV data based on 1999–2015 ground-based global positioning system (GPS) observations with the measurements at matched meteorological stations in the same period. The mean correlation coefficient at all the stations is approximately 0.73, indicating that there is a significant positive correlation between PWV content and precipitation measurements, and the comparison of correlation among different climate types suggests that the distribution characteristics of the correlation coefficients are distinctively related to different climate types. There is also some positive correlation between PWV and precipitation long-term trends, with the correlation coefficients of monthly anomalies ranging generally from 0.2 to 0.6. Furthermore, the intensity of both PWV and precipitation extremes shows a long-term upward trend overall, with the most-intense events showing more significant increases. The extreme precipitation–temperature scaling rate of changes can reach above Clausius–Clapeyron (CC) scaling, whereas that of the extreme PWV-temperature is sub-CC overall, with regional differences in the specific scaling values. The correlation analysis in this work is of great significance for long-term climate analysis and extreme weather understanding, which provides a valuable reference for better utilizing the advantages of PWV data to carry out the studies above. Significance Statement: Atmospheric water vapor is crucial to the climate system, especially in the context of global warming, and accurate knowledge of the correlation between precipitable water vapor (PWV) and precipitation is of great significance for long-term climate analysis and extreme precipitation weather forecasting. We take full advantage of the long-term homogeneity of ground-based GPS to conduct long-term correlation analysis between GPS-derived PWV and precipitation over China. Results show a significant positive correlation between them, and the degree of correlation is related to different climate types. The correlation of monthly anomalies is also positive, and, over the long-term, both water vapor and precipitation extremes have been increasing in intensity, with more significant increases occurring in the most-intense events. Extreme precipitation might increase beyond thermodynamic expectations, whereas PWV increases below expectations. [ABSTRACT FROM AUTHOR]

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

To support the planning of future solar energy production in India, forthcoming changes in incoming surface solar radiation and the main physical factors contributing to the change were inferred from simulations performed with 27 global CMIP5 climate models. According to the multimodel-mean response, radiation diminishes by 0.5%–4% by the period 2030–59 (relative to 1971–2000), in tandem with strengthening aerosol and water vapor dimming. The largest reduction is anticipated for northern India. The evolution of incident radiation in the mid- and late twenty-first century depends substantially on the emission scenario. According to the representative concentration pathways RCP2.6 and RCP4.5, solar radiation would gradually recover close to the level that prevailed in the late twentieth century. This results from the peaking of aerosol loading before midcentury while the water vapor content continuously increases somewhat. Conversely, under RCP8.5, incident radiation would still decline, although more slowly than during the early century. This coincides with a substantial increase in atmospheric water vapor content and a modest decrease in aerosol forcing. In cloud forcing, multimodel-mean changes are minor, but divergence among the model simulations is substantial. Moreover, cloud forcing proved to be the factor that correlates most strongly with intermodel differences in the solar radiation response. Multimodel-mean changes in solar radiation are small and would not crucially affect the conditions of solar energy production. Nevertheless, some individual models simulate far more substantial reductions of up to ~10%. [ABSTRACT FROM AUTHOR]

The long-term dynamics of both urban heat island (UHI) and urban dry island (UDI) intensities over the city of Moscow, Russia, has been analyzed for the period from the end of the nineteenth century until recent years using data of the ground meteorological network. Besides traditional maximum heat/dry island intensity, an additional parameter-station-averaged intensity as a mean difference between the data of all urban and rural stations-has been used. The traditional maximum (mean annual) UHI intensity in Moscow was nearly 1.0°C at the end of the nineteenth century, 1.2°C one century ago, 1.5°-1.6°C both in the middle and at the end of the twentieth century, and 2.0°C in recent years. The station-averaged UHI intensity was equal to 0.7°-0.8°C in the second half of the twentieth century and increased up to 1.0°C in recent years. It is probable that stabilization of both parameters from the 1950s to the 1990s was connected with the extensive city growth at that time (mass resettlement of inhabitants from the overpopulated city center to the new urban periphery since the 1960s). The new increase of UHI intensities is the result of the new intensive city growth. The relative humidity in Moscow significantly decreased during the last 146 years (mostly because of warming), unlike water vapor pressure. The UDI is closely connected with the UHI; the absolute value (modulus) of its intensity is increasing in time from −4% at the end of the nineteenth century to −9% now. During the last two decades, the UDI as well as the UHI became much stronger than before. [ABSTRACT FROM AUTHOR]

Convective available potential energy (CAPE) is one of the physical quantities used by operational meteorologists when issuing severe-weather convective watches and warnings. Recent advances in satellite technology could provide timely observations of atmospheric temperature and water vapor profiles over the continental United States, but only limited validation exists in the literature to characterize uncertainties in CAPE derived from the new satellite sensors. In this study, 10 years of Vaisala, Inc., RS92 radiosonde observations from the U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) site were matched to overpasses of the NASA Aqua satellite that were made from January 2005 through December 2014. Vertical profiles of temperature and water vapor from the NASA Atmospheric Infrared Sounder (AIRS) were extracted in a region surrounding the DOE ARM SGP central facility near Lamont, Oklahoma. Surface-based CAPE was computed using software consistent with methods used by the National Weather Service Storm Prediction Center. The one-to-one correspondence of the AIRS-derived CAPE with the ARM-radiosonde-derived CAPE has a correlation coefficient of only 0.34. Substitution of the ARM-radiosonde surface values into the AIRS profiles improves the correlation to 0.95. The use of AIRS profiles above the surface level provides surface-based CAPE values that are very similar to those computed from Vaisala radiosondes. These results suggest that a merging of surface observations with satellite-derived thermodynamic profiles could make better use of the satellite spatial coverage and temporal sampling for estimation of CAPE in near-real time. [ABSTRACT FROM AUTHOR]

Unlike the commonly used relative humidity, vapor pressure deficit (VPD) is an absolute measure of the difference between the water vapor content of the air and its saturation value and an accurate metric of the ability of the atmosphere to extract moisture from the land surface. VPD has been shown to be closely related to variability in burned forest areas in the western United States. Here, the climatology, variability, and trends in VPD across the United States are presented. VPD reaches its climatological maximum in summer in the interior southwest United States because of both high temperatures and low vapor pressure under the influence of the northerly, subsiding eastern flank of the Pacific subtropical anticyclone. Maxima of variance of VPD are identified in the Southwest and southern plains in spring and summer and are to a large extent driven by temperature variance, but vapor pressure variance is also important in the Southwest. La Niña-induced circulation anomalies cause subsiding, northerly flow that drives down actual vapor pressure and increases saturation vapor pressure from fall through spring. High spring and summer VPDs can also be caused by reduced precipitation in preceding months, as measured by Bowen ratio anomalies. Case studies of 2002 (the Rodeo-Chediski and Hayman fires, which occurred in Arizona and Colorado, respectively) and 2007 (the Murphy Complex fire, which occurred in Idaho and Nevada) show very high VPDs caused by antecedent surface drying and subsidence warming and drying of the atmosphere. VPD has increased in the southwest United States since 1961, driven by warming and a drop in actual vapor pressure, but has decreased in the northern plains and Midwest, driven by an increase in actual vapor pressure. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Forecasts of precipitation and water vapor made by the Met Office global numerical weather prediction (NWP) model are evaluated using products from satellite observations by the Special Sensor Microwave Imager/Sounder (SSMIS) and Tropical Rainfall Measuring Mission (TRMM) Multisatellite Precipitation Analysis (TMPA) for June-September 2011, with a focus on tropical areas (30°S-30°N). Consistent with previous studies, the predicted diurnal cycle of precipitation peaks too early (by ~3 h) and the amplitude is too strong over both tropical ocean and land regions. Most of the wet and dry precipitation biases, particularly those over land, can be explained by the diurnal-cycle discrepancies. An overall wet bias over the equatorial Pacific and Indian Oceans and a dry bias over the western Pacific warm pool and India are linked with similar biases in the climate model, which shares common parameterizations with the NWP version. Whereas precipitation biases develop within hours in the NWP model, underestimates in water vapor (which are assimilated by the NWP model) evolve over the first few days of the forecast. The NWP simulations are able to capture observed daily-to-intraseasonal variability in water vapor and precipitation, including fluctuations associated with tropical cyclones. [ABSTRACT FROM AUTHOR]

The Satellite Application Facility on Climate Monitoring (CM-SAF) focuses on retrieving geophysical parameters from satellite data by using inversion schemes that are based on radiative transfer theory. In this study, the focus is on the daily mean vertically integrated water vapor [i.e., total precipitable water vapor (TPW)] and the monthly mean layered vertically integrated water vapor [i.e., low-level precipitable water vapor (LPW), midlevel precipitable water vapor (MPW), and upper-level precipitable water vapor] obtained from CM-SAF Germany for the 2004-08 period and for 20 radiosonde stations distributed over Nigeria. The mean annual cycle shows a structure with two maxima, in May and September, respectively, for all low- and midlevel water vapor in the coastal and Guinea savannah regions, whereas at the midland and Sahelian regions, an almost constant maximum lasting between May and September occurs. The two-maxima structure manifested by TPW, LPW, and MPW at the coastal and Guinea savannah regions and the single maximum exhibited by them at the midland and the Sahelian regions are in synchronism with the movement of the intertropical discontinuity. In addition, comparisons have been made between the precipitable water from CM-SAF (CM-SAF PWV) and precipitable water from radiosonde (RS-PWV). Comparisons of the products at the seasonal scale show that CM-SAF PWV at all levels is larger than that of RS-PWV. In addition, a seasonal intercomparison between them shows that CM-SAF PWV and RS-PWV agree significantly at all of the stations that were investigated. [ABSTRACT FROM AUTHOR]

Radar ducting is caused by sharp vertical changes in temperature and, especially, water vapor at the top of the atmospheric boundary layer, both of which are sensitive to variations in the underlying surface conditions, local mesoscale weather, and synoptic weather patterns. High-resolution numerical weather prediction (NWP) models offer an alternative to observation to determine boundary layer (BL) structure and to assess the spatial variability of radar ducts. The benefit of using NWP models for simulating ducting conditions very much depends on the initial state of sea surface temperature (SST) and the model spinup time, both of which have a great impact on BL structure. This study investigates the effects of variation of NWP-model initial conditions and simulation length on the accuracy of simulating the atmosphere's refractive index over the Wallops Island, Virginia, region, which has pronounced SST variability and complex BL structure. The Met Office Unified Model (MetUM) with horizontal resolution of 4 km (4-km model) was used to simulate the atmospheric environment when observations were made during the Wallops-2000 experiment. Sensitivity tests were conducted in terms of the variability of SST and model spinup time. The evaluation of the model results was focused on low-level moisture, temperature, and surface ducting characteristics including the frequency, strength, and the height of the ducting layer. When provided with more accurate SST and adequate simulation length, the MetUM 4-km model demonstrated an improved ability to predict the observed ducting. [ABSTRACT FROM AUTHOR]

Temporal trends in precipitation associated with 500-hPa low pressure systems are assessed for consistency with overall precipitation trends in the northeastern United States. Increases in precipitation associated with closed upper lows can be attributed to an increase in the number of closed lows and/or an increase in the average precipitation occurring in association with closed lows. A climatological description of 500-hPa closed lows was developed, and precipitation was analyzed using data from the U.S. Cooperative Observer Program. Closed 500-hPa lows were identified within a rectangular geographic region bounded by 35° and 50°N and 65° and 90°W. Precipitation observations within 1.25° of latitude and 1.25° of longitude of the closed-low center were attributed to the closed low. Statistical testing procedures were conducted to evaluate whether a long-term trend existed in the closed-low frequency, the average precipitation occurring near closed lows, or the percentage of >2.54-cm precipitation observations associated with the lows. Regional trends (1948-2007) in the frequency of closed lows were evident, and a statistically significant increase in average precipitation near closed lows was found. Likewise, the percentage of precipitation totals in excess of 2.54 cm (and separately 5.08 cm) showed a statistically significant increase with time. In both cases, recent (2007) values were nearly 50%% higher than the comparable value in 1948. Increases were particularly evident during the winter months. These trends are consistent with increases in tropospheric water vapor due to increased global mean temperature. [ABSTRACT FROM AUTHOR]

A new intersensor calibration scheme is developed for the Defense Meteorological Satellite Program Special Sensor Microwave Imager (SSM/I) to correct its scan-angle-dependent bias, the radar calibration beacon interference on the F-15 satellite, and other intersensor biases. The intersensor bias is characterized by the simultaneous overpass measurements with the F-13 SSM/I as a reference. This sensor data record (SDR) intersensor calibration procedure is routinely running at the National Oceanic and Atmospheric Administration and is now used for reprocessing all SSM/I environmental data records (EDR), including total precipitable water (TPW) and surface precipitation. Results show that this scheme improves the consistency of the monthly SDR''s time series from different SSM/I sensors. Relative to the matched rain products from the Tropical Rainfall Measuring Mission, the bias of SSM/I monthly precipitation is reduced by 12%% after intersensor calibration. TPW biases between sensors are reduced by 75%% over the global ocean and 20%% over the tropical ocean, respectively. The intersensor calibration reduces biases by 20.6%%, 15.7%%, and 6.5%% for oceanic, land, and global precipitation, respectively. The TPW climate trend is 1.59%% decade−−1 (or 0.34 mm decade−−1) for the global ocean and 1.39%% decade−−1 (or 0.63 mm decade−−1) for the tropical ocean, indicating related trends decrease of 38%% and 54%%, respectively, from the uncalibrated SDRs. Results demonstrate the large impacts of this calibration on the TPW climate trend. [ABSTRACT FROM AUTHOR]

Reference evapotranspiration (ET o) and pan evaporation ( Epan) are key parameters in hydrological and meteorological studies. The authors’ objectives were to evaluate the ratio of ET o to Epan ( kp) at daily and monthly scales and to predict average ET o in the following years using calibrated kp and observed Epan at the two time scales. Using 50 yr of data obtained at six typical sites in north China, daily and monthly ET o were calculated using the Food and Agriculture Organization estimation method (FAO-56) Penman–Monteith equation, and kp values were determined at the two time scales. Values of kp varied from 0.457 to 0.589 daily and from 0.392 to 0.528 monthly for the six sites. Both daily and monthly kp could be fitted as multilinear functions of longitude, latitude, elevation, and relative humidity. Relatively accurate predictions of daily mean ET o for the subsequent years following the calibration years at all six sites were obtained when the year number L used for calibrating daily mean kp was sufficient (>38). In cases when large deviations occurred between average kp for the L calibration years and the actual kp of the following ( L + 1)th year, relatively large prediction errors resulted. For the monthly scale, soil heat flux G fluctuated periodically. When variations of G were included, the calculated monthly ET o values were smaller than the monthly ET o cumulated from daily ET o. Thus, monthly kp values were smaller than daily kp values. Predictions of monthly ET o in 2001 for the six sites were relatively accurate with relative errors ranging from −11.9% to 12.1%. In conclusion, this method is simple and accurate with a small demand for weather data. [ABSTRACT FROM AUTHOR]

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

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

The study proposes the simplification of the multilayer urban canopy model. Four types of multilayer urban canopy models—level 4, level 3, level 2, and level 1—are developed to reduce the computational load of the heat budget calculations at the wall surface. The level 4 model, which accounts for the wall directions and the vertical layer, is simplified in three ways: the level 3 model only accounts for the vertical layers, the level 2 model accounts for the wall directions, and the level 1 model accounts for neither the wall directions nor the vertical layer. From the simplification, compared to the level 4 model, the memory is reduced by 57%, 65%, and 72% for the level 3–level 1 models, respectively, when the vertical canopy layer is seven. At the same time, the CPU time is reduced by 67%, 70%, and 78% for the level 3–level 1 models. Then, each canopy model is compared with observations in Tokyo. The results show that the simulations from the four models are close to the observed ones, and the differences among the four models are very small. An additional model intercomparison study based on idealized simulations indicates that the level 3 model can be used instead of the level 4 model in any condition, whereas the level 2 and level 1 models are proposed to be used under conditions with a large sky view factor. [ABSTRACT FROM AUTHOR]

The use of a mesoscale model–based four-dimensional data assimilation (FDDA) system for generating mesoscale climatographies is demonstrated. This dynamical downscaling method utilizes the fifth-generation Pennsylvania State University–National Center for Atmospheric Research Mesoscale Model (MM5), wherein Newtonian relaxation terms in the prognostic equations continually nudge the model solution toward surface and upper-air observations. When applied to a mesoscale climatography, the system is called Climate-FDDA (CFDDA). Here, the CFDDA system is used for downscaling eastern Mediterranean climatographies for January and July. The downscaling method performance is verified by using independent observations of monthly rainfall, Quick Scatterometer (QuikSCAT) ocean-surface winds, gauge rainfall, and hourly winds from near-coastal towers. The focus is on the CFDDA system’s ability to represent the frequency distributions of atmospheric states in addition to time means. The verification of the monthly rainfall climatography shows that CFDDA captures most of the observed spatial and interannual variability, although the model tends to underestimate rainfall amounts over the sea. The frequency distributions of daily rainfall are also accurately diagnosed for various regions of the Levant, except that very light rainfall days and heavy precipitation amounts are overestimated over Lebanon. The verification of the CFDDA against QuikSCAT ocean winds illustrates an excellent general correspondence between observed and modeled winds, although the CFDDA speeds are slightly lower than those observed. Over land, CFDDA- and the ECMWF-derived wind climatographies when compared with mast observations show similar errors related to their inability to properly represent the local orography and coastline. However, the diurnal variability of the winds is better estimated by CFDDA because of its higher horizontal resolution. [ABSTRACT FROM AUTHOR]

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

December–March climatologies of precipitation and vertically integrated water vapor transport were analyzed and compared to find the main paths by which moisture is fed to high-rainfall regions in the Southern Hemisphere in this season. The southern tropics (20°S–0°) exhibit high rainfall and receive ample moisture from the northern trades, except in the eastern Pacific and the Atlantic Oceans. This interhemispheric flow is particularly important for Amazonian rainfall, establishing the North Atlantic as the main source of moisture for the forest during its main rainy season. In the subtropics the rainfall distribution is very heterogeneous. The meridional average of precipitation between 35° and 25°S is well modulated by the meridional water vapor transport through the 25°S latitude circle, being greater where this transport is from the north and smaller where it is from the south. In South America, to the east of the Andes, the moisture that fuels precipitation between 20° and 30°S comes from both the tropical South and North Atlantic Oceans whereas between 30° and 40°S it comes mostly from the North Atlantic after passing over the Amazonian rain forest. The meridional transport (across 25°S) curve exhibits a double peak over South America and the adjacent Atlantic, which is closely reproduced in the mean rainfall curve. This corresponds to two local maxima in the two-dimensional field of meridional transport: the moisture corridor from Amazonia into the continental subtropics and the moisture flow coming from the southern tropical Atlantic into the subtropical portion of the South Atlantic convergence zone. These two narrow pathways of intense moisture flow could be suitably called “aerial rivers.” Their longitudinal positions are well defined. The yearly deviations from climatology for moisture flow and rainfall correlate well (0.75) for the continental peak but not for the oceanic peak (0.23). The structure of two maxima is produced by the effect of transients in the time scale of days. [ABSTRACT FROM AUTHOR]

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

Grassland environments constitute approximately 40% of the earth’s vegetated surface, and they play a key role in a number of processes linking the land surface with the atmosphere. To investigate these linkages, a variety of techniques, including field and modeling studies, are required. Using data collected at the Central Plains Experimental Range (CPER) in northeastern Colorado from 25 March to 10 November 2004, this study compares two common ways of measuring turbulent fluxes of latent heat, sensible heat, and carbon dioxide in the field: the eddy covariance (EC) and Bowen ratio energy balance (BREB) methods. The turbulent fluxes measured by each of these methods were compared in terms of magnitude and seasonal behavior and were combined to calculate eddy diffusivities and examine turbulent transport. Relative to the EC method, the BREB method tended to overestimate the magnitude of the sensible heat, latent heat, and carbon dioxide fluxes. As a result, substantial differences in both the diurnal pattern and long-term magnitudes of the water and carbon budgets were apparent depending on which method was used. These differences arise from (i) the forced closure of the surface energy balance and (ii) the assumption of similarity between the eddy diffusivities required by the BREB method. An empirical method was developed that allows the BREB and EC datasets to be reconciled; this method was tested successfully using data collected at the CPER site during 2005. Ultimately, however, the BREB and EC methods show important differences that must be recognized and taken into account when analyzing issues related to the energy, water, or carbon cycles. [ABSTRACT FROM AUTHOR]

Using the available upper-air data for three stations in Nigeria (Lagos, a coastal station; Minna, an inland station; and Kano, a sub-Sahelian station), an intensive examination has been carried out on the linkage between surface mixing ratio rs and layered integrated water vapor W (g cm-2) over Nigeria. The goal was to identify the seasonal distribution of the parameter and to develop models that can best be used to estimate W from surface mixing ratio. To achieve these objectives, integrated water vapor at the low level (WL), midlevel (Wm), and upper level (Wu) and total column integrated water WT have been calculated using daily values of upper-air data spanning over a decade from the above three radiosonde stations. A relationship of the form W = αrs + β (where α and β are constants) has been established between W and rs using the analysis-of-variance (ANOVA) technique. Tests carried out on the models, using daily soundings made in 1990 for Lagos, 1983 for Minna, and 1991 for Kano, respectively, gave encouraging results as established by the use of Kolmogorov–Smirnov tests. Owing to the difference in the climatological patterns of precipitation among the different regions in Nigeria (i.e., southern, midland, and northern regions) as represented by the three stations, no single relationship was found to be suitable for the entire country of Nigeria. Earlier models, generally of the form W = αqb (where α and b are constants and q is specific humidity), were found to be less adequate over the stations. [ABSTRACT FROM AUTHOR]

Determining cloud thermodynamic phase using infrared satellite observations typically requires a priori assumptions about relationships between cloud phase and cloud temperature. In this study, limitations of an approach using two infrared channels with moderate spectral resolutions are demonstrated, as well as the potential for improvement using channels with higher spectral resolution. The Moderate Resolution Imaging Spectroradiometer (MODIS) instrument uses a bispectral infrared cloud phase determination algorithm. MODIS observations during January 2005 show that approximately 23% of cloudy pixels are classified as mixed or unknown cloud phase; this increases to 78% when only cloud-top temperatures between 250 and 265 K are considered. Radiative transfer simulations show that the bispectral algorithm has limited ability to discriminate between water and ice clouds in this temperature range. There is also the potential for thin ice clouds at colder temperatures to be misclassified as water clouds. In addition, sensitivities to cloud particle size and cloud height can be larger than sensitivities to cloud phase. Simulations suggest that phase sensitivity may be higher with hyperspectral observations such as those from the Atmospheric Infrared Sounder (AIRS). The AIRS brightness temperature differences between channels at 8.1 and 10.4 μm show phase sensitivities of at least 0.5 K, regardless of cloud particle size, cloud-top temperature, or cloud height. They also demonstrate reduced sensitivity to atmospheric temperature and water vapor variability. The reduced sensitivity of AIRS radiances to these physical quantities shows that hyperspectral sounders will serve an important role in refining estimates of cloud phase. [ABSTRACT FROM AUTHOR]

The potential to predict cotton yields up to one month before planting in the southeastern United States is assessed in this research. To do this, regional atmospheric variables that are related to historic summer rainfall and cotton yields were identified. The use of simulations of those variables from a global circulation model (GCM) for estimating cotton yields was evaluated. The authors analyzed detrended cotton yields (1970–2004) from 48 counties in Alabama and Georgia, monthly rainfall from 53 weather stations, monthly reanalysis data of 850- and 200-hPa winds and surface temperatures over the southeast U.S. region, and monthly predictions of the same variables from the ECHAM 4.5 GCM. Using the reanalysis climate data, it was found that meridional wind fields and surface temperatures around the Southeast were significantly correlated with county cotton yields (explaining up to 52% of the interannual variability of observed yields), and with rainfall over most of the region, especially during April and July. The tendency for cotton yields to be lower during years with atmospheric circulation patterns that favor higher humidity and rainfall is consistent with increased incidence of disease in cotton during flowering and harvest periods under wet conditions. Cross-validated yield estimations based on ECHAM retrospective simulations of wind and temperature fields forced by observed SSTs showed significant predictability skill (up to 55% and 60% hit skill scores based on terciles and averages, respectively). It is concluded that there is potential to predict cotton yields in the Southeast by using variables that are forecast by numerical climate models. [ABSTRACT FROM AUTHOR]

An airborne microwave temperature profiler (MTP) was deployed during the Texas 2000 Air Quality Study (TexAQS-2000) to make measurements of boundary layer thermal structure. An objective technique was developed and tested for estimating the mixed layer (ML) height from the MTP vertical temperature profiles. The technique identifies the ML height as a threshold increase of potential temperature from its minimum value within the boundary layer. To calibrate the technique and evaluate the usefulness of this approach, coincident estimates from radiosondes, radar wind profilers, an aerosol backscatter lidar, and in situ aircraft measurements were compared with each other and with the MTP. Relative biases among all instruments were generally less than 50 m, and the agreement between MTP ML height estimates and other estimates was at least as good as the agreement among the other estimates. The ML height estimates from the MTP and other instruments are utilized to determine the spatial and temporal evolution of ML height in the Houston, Texas, area on 1 September 2000. An elevated temperature inversion was present, so ML growth was inhibited until early afternoon. In the afternoon, large spatial variations in ML height developed across the Houston area. The highest ML heights, well over 2 km, were observed to the north of Houston, while downwind of Galveston Bay and within the late afternoon sea breeze ML heights were much lower. The spatial variations that were found away from the immediate influence of coastal circulations were unexpected, and multiple independent ML height estimates were essential for documenting this feature. [ABSTRACT FROM AUTHOR]

Within the framework of a large urban meteorology program recently launched in Canada, the Montreal Urban Snow Experiment (MUSE) campaign has been conducted in order to document the thermoradiative exchanges in a densely built-up area of Montreal in late winter and spring conditions. The targeted period is of particular scientific interest because it covers the transition period from a mainly snow-covered urban environment to a mainly snow-free environment. The campaign is based on four weeks of observations from 17 March to 14 April 2005. It couples automatic and continuous measurements of radiation and turbulent fluxes, radiative surface temperatures, and air temperature and humidity with manual observations performed during intensive observation periods to supplement the surface temperature observations and to characterize the snow properties. The footprints of radiation and turbulent flux measurements are computed using the surface–sensor–sun urban model and the flux-source area model, respectively. The analysis of the radiometer footprint underscores the difficulty of correctly locating this type of instrument in urban environments, so that the sensor sees a representative combination of the urban and nonurban surfaces. Here, the alley contribution to the upward radiation tends to be overestimated to the detriment of the road contribution. The turbulent footprints cover homogeneous zones in terms of surface characteristics, whatever the wind direction. The initial analysis of the energy balance displays the predominance of the residual term (QRes = Q* - QH - QE) in comparison with the turbulent sensible (QH) and latent (QE) heat fluxes, since its daytime contribution exceeds 50% of the net radiation (Q*). The investigation of energy balances observed at the beginning and at the end of the experiment (i.e., with and without snow) also indicates that the snow plays a significant role in the flux partitioning and the daily pattern of fluxes. Without snow, the energy balance is characteristic of energy balances that have been already observed in densely built-up areas, notably because of the hysteresis observed for QRes and QH in relation to Q* and because of the high contribution of QRes, which includes the effect of heat storage inside the urban structures. With snow, the flux partitioning is modified by the snowmelt process leading to contributions of the residual term and latent heat flux, which are larger than in the case without snow to the detriment of the sensible heat flux. [ABSTRACT FROM AUTHOR]

Global positioning system (GPS) data from a dense network have been used for the analysis of the diurnal cycle of water vapor over Marseille, France, during the second intensive observation period (IOP2; 21–26 June 2001) of the Expérience sur Sites pour Contraindre les Modèles de Pollution Atmosphérique et de Transport d’Emission (ESCOMPTE) field experiment. Both tomographic analyses and integrated water vapor (IWV) contents from GPS have been used, in addition to wind profiler data and surface observations. Tomographic analysis of data from the dense GPS network and radiosondes provided the continuous temporal evolution of the vertical distribution of water vapor over the city of Marseille. The city is located on the shore of the Mediterranean Sea in southeastern France and is often under the influence of sea-breeze effects. Two different layers of breeze circulation are identified: a shallow sea breeze, blowing perpendicular to the local coastline, and a deep sea breeze, induced by the regional temperature gradient between sea and land. The origin of water vapor is shown to be mainly due to the advection of marine moist air by these sea-breeze circulations. However, the diurnal cycle of water vapor over Marseille is strongly influenced by the synoptic situation, which changes during the IOP2 (between a northerly mistral in the early stage of the IOP and an easterly wind at the end). It is shown that vertical profiles from tomographic analyses (combined with wind profiler data) allow for a proper interpretation of the diurnal cycle observed in IWV. Two-dimensional maps of IWV are also shown to complement the description of the horizontal advection of moisture by the different circulation regimes. [ABSTRACT FROM AUTHOR]

In the frame of this work, the storm that occurred on 5 December 2002 in Antalya, located on the southwestern Mediterranean Sea coast of Turkey, is analyzed. More than 230 mm of 24-h-accumulated rainfall have been reported during the event that produced floods in the area. The analysis is based on the results of model simulations with the fifth-generation Pennsylvania State University–NCAR Mesoscale Model (MM5). Observational data provided by the Tropical Rainfall Measuring Mission (TRMM) sensors (including the Lightning Imaging Sensor and TRMM Microwave Imager), Special Sensor Microwave Imager (SSM/I), Meteosat-7, and Met Office Arrival Time Difference (ATD) lightning network are used for both the comparison with the model results and also for the characterization of the storm. The synergetic use of all of this information was crucial for the description of the event. The maximum of precipitation was associated with the warm and moist air masses driven by a low-level jet over the area and impinging over the orographic barriers. The improvement of representation of the humidity field in the model initial conditions, through a simple technique of humidity adjustment based on satellite rainfall estimates, resulted in an improvement of the prediction of the timing and quantity of the precipitation maxima during the event. [ABSTRACT FROM AUTHOR]

The evaluation of water vapor (WV) images taken by satellite-borne radiometers has become an essential source of data in modern meteorology. The analysis of structure displacements within sections of WV images is an effective way to get horizontal components of wind vectors. In contrast to intermediate-level and high-level clouds, the height assignment of displacement vectors connected with cloud-free WV structures needs additional information from atmospheric profiles. Nevertheless, interpreting these motion vectors as independent wind vectors and not simply matching them to any model wind field is tried. This contribution reports on the evaluation of structure displacements and how it can be done efficiently in the case of smooth and shallow scenes by the use of appropriate filters. Then, a series of height-assignment methods is tested for altitude-sensitive parameters such as wind shear and brightness contrast of pixels within segments used for structure tracking. The results are verified by comparison with reference wind data from the analysis of a weather prediction model as well as from radiosonde ascents. From a statistical point of view and for cases of strong wind shear it is clearly revealed that methods that use the effective brightness temperature, in particular from the coldest pixels, lead to better height assignment than do others that are based on the contribution function explicitly. From a series of individual cases it is found that the relative minimum of the difference between reference wind and clear-air structure displacement is not related uniquely to either the coldest (or warmest) pixel of the segment or the effective brightness temperature of pixels leading the tracking procedure. A cloud-free WV structure consequently contains information from an atmospheric layer whose displacement vector is a weighted sum over the motions within its specific thickness. Then the individual situation will determine whether a structure displacement reflects the motion at a well-defined height or whether it should be taken as a collective motion within an atmospheric layer that is an essential part of the upper troposphere. [ABSTRACT FROM AUTHOR]