Abstract. Vertical profiles of the aerosol physical and optical properties, with a focus on seasonal means and on transport events, were investigated in Tsukuba, Japan, by a synergis- tic remote sensing method that uses lidar and sky radiometer data. The retrieved aerosol vertical profiles of the springtime mean and five transport events were input to our developed one-dimensional atmospheric model, and the impacts of the aerosol vertical profiles on the evolution of the atmospheric boundary layer (ABL) were studied by numerical sensitivity experiments. The characteristics of the aerosol vertical pro- files in Tsukuba are as follows: (1) the retrieval results in the spring showed that aerosol optical thickness at 532 nm in the free atmosphere (FA) was 0.13, greater than 0.08 in the ABL owing to the frequent occurrence of transported aerosols in the FA. In other seasons, optical thickness in the FA was al- most the same as that in the ABL. (2) The aerosol optical and physical properties in the ABL showed a dependency on the extinction coefficient. With an increase in the extinc- tion coefficient from 0.00 to 0.24 km −1 , the Ångström expo- nent increased from 0.0 to 2.0, the single-scattering albedo increased from 0.87 to 0.99, and the asymmetry factor de- creased from 0.75 to 0.50. (3) The large variability in the physical and optical properties of aerosols in the FA were attributed to transport events, during which the transported aerosols consisted of varying amounts of dust and smoke particles depending on where they originated (China, Mon- golia, or Russia). The results of the numerical sensitivity ex- periments using the aerosol vertical profiles of the spring- time mean and five transport events in the FA are as follows: (1) numerical sensitivity experiments based on simulations conducted with and without aerosols showed that aerosols
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Tirpitz, J.-L., Frieß, U., Hendrick, F., Alberti, C., Allaart, M., Apit- uley, A., Bais, A., Beirle, S., Benavent, N., Berkhout, S., Bösch, T., Bognar, K., Bruchkouski, I., Chan, K. L., Chengxin, Z., den Hoed, M., Donner, S., Drosoglou, T., Friedrich, M. M., Frumau, A., Gast, L., Gomez, L., Gielen, C., Hao, N., Hensen, A., Hen- zing, B., Hoque, S., Irie, H., Jin, J., Koenig, T. K., Kreher, K., Kuhn, J., Kumar, V., Lampel, J., Li, A., Liu, C., Ma, J., Mer- laud, A., Mishra, A., Nieto, D., Peters, E., Pinardi, G., Piters, A., Pöhler, D., Postylyakov, O., Richter, A., van Roozendael, M., Schmitt, S., Sinha, V., Spinei, E., Stein, D., Swart, D., Tack, F., Vlemmix, T., van der Hoff, R., Vonk, J., Wagner, T., Wang, S., Wang, Y., Wang, Z., Wenig, M., Wiegner, M., Wittrock, F., Xie, P., Xing, C., Xu, J., and Zhao, X.: DOAS Vertical Profile Retrieval Algorithms: Studies on Field Data from the CINDI-2 Campaign, Atmos. Meas. Tech., in preparation, 2019.
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Figures 4 to 5 shows the vertical profiles of the normalised streamwise velocity on the floodplains and inside the main channel of non-vegetated and vegetated for both DR cases. Inbank flows inside the main channel represents by water level (WL) below zero and overbank flows by water level above zero. In general, the vertical profiles of non-vegetated cases generated the same patterns for both relative depths even though some discrepancy was recorded at some points in the measurement sections. These similarities were also recorded by vegetated cases of both relative depths on the floodplains and inside the main channel. The most significant discrepancy of the streamwise velocity was recorded at Point E of measurement Section 8 inside the main channel where the cross-over of overbank flows take place.
All profiles from the reference instruments that provide continuous vertical profiles of methane, satellite-borne and MkIV, were interpolated to the MIPAS grid for intercompar- ison. Rodgers and Connor (1999) suggest application of av- eraging kernels of the poorer resolved profiles to the better resolved profiles during the regridding of atmospheric pro- files. However, for all satellite or MkIV comparison instru- ments, the vertical resolution of typical MIPAS IMK/IAA methane profiles differs from the vertical resolution of ref- erence instrument profiles by less than a factor of 2–2.5 and often is close to 1. Thus the application of averaging kernels appears unnecessary. To be on the safe side, sensitivity stud- ies were performed to assess the impact of the application of the averaging kernels; this was done for all reference in- struments providing continuous profiles of methane, i.e., all satellite instruments and MkIV. When no averaging kernels were available for the coarser resolved reference instrument, the smoothing was done with a Gaussian filter of correspond- ing width. Application of the averaging kernels changed the significant parts of the profiles by less than 2 %. Hence, the differences in vertical resolution were chosen to be neglected and no averaging kernels were applied.
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The turbulence intensity profiles over the solid surface and the liquid surface are shown as a function of height in Fig 7 and 8, respectively. As with the wind speed profiles, the vertical profiles of turbulence intensity are not uniform regardless of the airflow rate and surface type. In fact, the turbulence intensity shows an inverse relationship with wind speed. The highest intensity is located where wind speed is lowest, that is, close to the wall of the wind tunnel. The turbulence intensity profiles are similar in shape to those reported by Loubet et al. (1999a). However, it is observed that the peak turbulence intensity over the solid surface is higher than for the liquid surface for the same fan speed.
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Satellite-borne instruments offer the opportunity to mea- sure stratospheric water vapour with global coverage. One such instrument is the Michelson Interferometer for Passive Atmospheric Sounding (MIPAS) on board the research satel- lite Envisat, operated by the European Space Agency (ESA). MIPAS is a Fourier transform spectrometer operating in a limb-viewing mode, measuring the emission of the Earth’s atmosphere in the infrared (Fischer et al., 2008). Envisat was launched on 1 March 2002 and operates at an altitude of approximately 800 km in a sun-synchronous polar orbit with equatorial local crossing times of 10:00 and 22:00 in descending and ascending node, respectively. The orbital pe- riod is about 100 min. The measurement time of one single limb scan is about 75 s and – in the original nominal mea- surement mode used from July 2002 to 25 March 2004 – consists of 17 tangent altitudes between 6 and 68 km, with 3 km spacing from 6 to 42 km and coarser spacing above. The vertical instantaneous field of view (FOV) is approxi- mately 3 km. The generation of calibrated radiance spectra, so-called level 1b data, is performed by ESA (Nett et al., 1999), as well as the retrieval of vertical profiles of temper- ature and atmospheric constituents including water vapour (Ridolfi et al., 2000; Raspollini et al., 2006). Besides ESA, several institutes operate their own scientific data processors for retrieval of atmospheric state variables (von Clarmann et al., 2003). One of these processors is the scientific MIPAS processor – developed by the “Institut f¨ur Meteorologie und Klimaforschung”, Karlsruhe, Germany (IMK) and the “In-
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MIPAS is an instrument that was carried on the European Envisat satellite; along with ∼ 30 other atmospheric trace gases, MIPAS measured vertical profiles of ozone. MIPAS measured day and night, and pole to pole, providing more than 1300 profiles per day. The failure of a MIPAS mirror slide in 2004 led to the division of the 10 years of MIPAS data into two operational periods: 2002–2004 when the in- strument measured with high spectral resolution (usually re- ferred to as “full-resolution (FR) period”) and 2005–2012 when the instrument measured with lower spectral but better vertical resolution (“reduced resolution (RR) period”). The MIPAS data from these two periods are evaluated separately. In this paper we present the results of an extensive val- idation of vertical ozone profiles retrieved from MIPAS reduced-resolution spectra with the IMK/IAA research pro- cessor. The MIPAS IMK/IAA (Institute for Meteorology and Climate Research/Instituto de Astrofísica de Andalucía) data set has been used as part of the SPARC (Strato- sphere–troposphere Processes And their Role in Climate) Data Initiative (Tegtmeier et al., 2013) and in the HARMOZ (HARMonized data set of Ozone profiles) databank (Sofieva et al., 2013). The ozone data set from the MIPAS IMK/IAA processor was selected to be used in the framework of the Eu- ropean Ozone Climate Change Initiative project, after an ex- tensive round-robin intercomparison of four existing MIPAS processors: the ESA (European Space Agency) operational
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of the local wind maximum (Fig. 7f, g). The region below this local flow acceleration corresponds to a region of re- duced turbulent mixing as observed in the vertical profiles of heat and momentum flux (Fig. 7f, g). The rapid decrease of all strong local motions below the peak at z = − 0.05 m fur- ther confirms a strong suppression of turbulent mixing, thus strong atmospheric decoupling over the deepest point of the concave. Boundary-layer decoupling is also revealed by the high gradient Richardson numbers for those points within the cavity, clearly exceeding the critical value of 0.25 only for the low-wind-velocity case (Fig. 8a). Furthermore, very low Reynolds numbers calculated for measurement points below z = − 0.05 m that are significantly lower than for the higher- wind-velocity case indicate laminar flow close to the surface (Fig. 8b). These profiles suggest that the higher stability at X2 at the lowest velocity forces the unsteady and coherent flow structures to develop above the cold pool. Moreover, in this latter case such strong reduction of ejections (Q2) and sweeps (Q4) in the decoupled region to the level of the other
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The TIMED satellite was launched on 7 December 2001 and the on-board limb sounder SABER soon started to de- liver vertical profiles of kinetic temperature on a routine ba- sis from approximately 10 km to more than 100 km altitude with a vertical resolution of about 2 km (Mertens et al., 2004; Mlynczak, 1997). The high vertical resolution is suitable for the investigation of gravity wave activity. About 1200 tem- perature profiles are available per day. The latitudinal cover- age on a given day extends from about 52 ◦ latitude in one hemisphere to 83 ◦ in the other (Russell et al., 1999). Due to 180 ◦ yaw manoeuvres of the TIMED satellite this viewing geometry alternates once every 60 days (Russell et al., 1999). An overview of the large number of SABER publications is available at http://saber.gats-inc.com/publications.php.
Abstract. We formulate tracer particle transport and mixing in soils due to disturbance-driven particle motions in terms of the Fokker–Planck equation. The probabilistic basis of the formulation is suitable for rarefied particle conditions, and for parsing the mixing behavior of extensive and intensive properties belonging to the particles rather than to the bulk soil. The significance of the formulation is illustrated with the examples of vertical profiles of expected beryllium-10 ( 10 Be) concentrations and optically stimulated luminescence (OSL) particle ages for the benchmark situation involving a one-dimensional mean upward soil motion with nominally steady surface erosion in the presence of either uniform or depth-dependent particle mixing, and varying mixing intensity. The analysis, together with Eulerian–Lagrangian numerical simulations of tracer particle motions, highlights the significance of calculating ensemble-expected values of extensive and intensive particle properties, including higher moments of particle OSL ages, rather than assuming de facto a continuum-like mixing behavior. The analysis and results offer guidance for field sampling and for describing the mixing behavior of other particle and soil properties. Profiles of expected 10 Be concentrations and OSL ages systematically vary with mixing intensity as measured by a Péclet number involving the speed at which particles enter the soil, the soil thickness, and the particle diffusivity. Profiles associated with uniform mixing versus a linear decrease in mixing with depth are distinct for moderate mixing, but they become similar with either weak mixing or strong mixing; uniform profiles do not necessarily imply uniform mixing.
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Measurements of the local axial bubble velocity distribution and the local gas volume fraction distribution in vertical and inclined, bubbly, air-water flows were made using the dual-sensor probe in a multiphase flow loop with a 2.5 m long, 80 mm internal diameter, inclinable working section. Tap water was pumped into the base of the working section via a turbine meter which enabled the water superficial velocity u ws in the working section to be calculated. Air was pumped into the working section via a series of 1 mm diameter holes equispaced around the circumference of the base of the working section. The mass flow rate of the air was measured before it entered the working section using a thermal mass flow meter. Measurements of the pressure and temperature in the working section enabled the mean air superficial velocity u gs to be calculated. A reference measurement α ref of the mean air volume fraction in the working section at a given flow condition was obtained using a differential pressure measurement, compensated for the effects of frictional pressure loss. This technique is widely described in the literature (Lucas and Jin, 2001) and so no further description will be given here.
The OMI data are provided as column values in Dobson units. As OMI is a nadir sounder and is on the same plat- form as MLS, its measurement at a given location is made at 425 ± 10 s after the MLS measurement. This 7 min delay is small enough that we do not attempt to correct for it. As the MLS horizontal field of view is narrower than an OMI pixel, we only consider those OMI pixels which are less than 18 km from the line joining successive MLS profile positions. For each MLS profile we form an average of those OMI pixels which meet this criterion and which are closer to that MLS profile than to any other. For most MLS profiles this means that the single MLS column is compared to a mean value of between 12 and 26 OMI pixels. We also calculate the stan- dard deviation of this set of pixels. The slight oblateness of the Earth means that the coincident pixels are not all in the same pixel row of the OMI swath; the coincident row varies
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always softer types of surface compared to the vegetated lands. J.L. Sánchez,ainsi que al.(2013) proposed a lot of the meteorological phenomena developing from meso-γ require findings enough close in concert around time and space. Your multichannel micro wave radiometer (MMWR) offers constant temperatures and wetness profiles. Many of us illustrate the solution to account disposition static correction that tremendously enhances vertical temperatures (T) and mineral water vapor denseness (δwv) account accuracy. We compared MMWR temperatures (TRD) and wetness (δwvRD) users during winter within the Sierra associated with Guadarrama (Madrid) from 1150 meters altitude together with thousands of radiosonde temperatures (TRW) and wetness soundings at a launch site from 610 meters altitude and 50 km distance. Even with somewhat significant vertical and horizontal separating involving the 2 main web sites, looking distinctions above the limit part tend to be comparable to observation problem normally allotted to radiosonde soundings when consumed in to math weather models. Wolfgang Krüll,ainsi que al.(2012) proved your scientific study “Intercontinental Woodlands Flame Fighting” (iWBB) has been loaned from the Reverend with regard to Economic Extramarital affairs and Strength of the Talk about associated with North Rhine- Westphalia, Germany. Several grouped corporations, investigation organizations and schools have been group to cultivate an incorporated, nonetheless flip-up system. An internal approach for earlier woodland fire detection and reduction will depend on a respectable collaboration of detection programs according to a wild fire danger, how big the the spot and man occurrence connected to a respectable logistical facilities, education through simulation, and impressive extinguishing technology. Seeing that regarding wildfires significant spots should
Figure 8. Top panels: Permeability and porosity profiles yielded by the joint inversion of two-snapshot induction logging measurements (acquired by the AIT tool) and pressure-transient measurements (acquired by the wireline formation tester probes) [log-test-log strategy]. The first induction log and the formation test were conducted subsequent to a 1.5 day-long mud-filtrate invasion. A second induction log was acquired right after the formation test. Measurements are contaminated with 3% Gaussian, random noise. The Cramer-Rao bounds (with 99.7% probability) for the inversion results are computed post-convergence. The initial-guess model parameter values are also shown. The bottom panel shows the misfit reduction plot for all investigated noise-contamination levels (1%, 3%, and 5%). the log-log strategy in Figure 7, and for the log-test-log strategy in Figure 8.
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zontal displacement at the substrate explains well the buffering mechanism of the bond coat. For the longitudinal stress and the shear stress distribution profiles, the variation of cutting angle under high vertical force displays profound influence on the movement implying that the controlling the factors: cutting angle and vertical force are important process.
The vertical structure of the atmosphere for this case study is summarized in Fig. 2, and was calculated using data from the Jeddah weather station (at 09:00 UTC, 11 May 2004, which was acquired less than a hour after the MODIS satel- lite image in Fig. 1b). Figure 2a shows the vertical profile of the atmospheric stability, N 2 (z), Fig. 2b shows a profile of the horizontal wind velocity U in the direction of wave prop- agation, and Fig. 2c the Scorer parameter l 2 . These results clearly show a layer (close to the ground) between approxi- mately 200 m and 1000–1300 m, where N 2 develops a sharp increase, peaking around 500 m, and l 2 >0, whereas above 1300 m l 2 ≈ 0. Thus the vertical profile of the Scorer param- eter in Fig. 2c is typical for a waveguide capable of sustain- ing horizontal wave propagation. This is a common mech- anism to trap wave energy. Moreover, AGWs frequently occur when strong stratification occurs close to the earth’s surface (Rottman and Grimshaw, 2002; da Silva and Mag- alhaes, 2009). Note that, in Eq. (2) N 2 tends to dominate over the other terms whenever sharp peaks in stability occur within the lower layers of the troposphere (in this case study U also varies linearly when l 2 > 0, implying that U 00 ≈ 0 and thus the second term is negligible compared to the first, see Fig. 2b). Note that here l 2 k 2 in the boundary layer, en- abling the use of weakly nonlinear long wave theory as fol- lows.
Finally, figures 13 and 14 compare the profiles of heat advection and conduction in the vertical direction at positions of ascending and descending currents. Conduction is always positive, and its magnitude is much smaller than that of advection. Nevertheless, it is the most important heat transfer mechanism near the boundaries, where the steepest temperature gradients take place and vertical advection of heat is weak due to the no-penetration condition. This is similar to what happens in the CBL . The maximum values of total heat transfer occur very close to z* = 0.5 at positions of descending currents, whereas it happens nearer the upper plate at positions of ascending currents.
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ventional counterparts employed in HIRLAM, we have com- pared one-month statistical skills of parallel simulations that used both formulations. The difference between the simula- tions was only in the formulation of the vertical eddy viscos- ity and eddy diffusivity for the case of stable stratification; the rest of the model was left intact. Although the model in these simulations was run over the entire computational domain, we have concentrated on its predictions over Scan- dinavia only as this area was strongly affected by the cold weather. Figure 12 summarizes the results of the parallel ex- periment; it shows the percentage of relative improvement (PRI) in +48 h weather forecast for the bias of the sea-level pressure as well as those of the temperature and relative hu- midity at the height of 2 m. The PRI was calculated as (new bias – reference bias)/(reference bias). As one can see, the new stability functions significantly improve the predictive skills of HIRLAM for stably stratified atmospheric boundary layers.
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within 4 %. The more sensitive ceilometer model operating at 1064 nm is unaffected by water vapour attenuation but is more prone to saturation in liquid clouds; such profiles can be recognised and rejected and, despite the more restricted sam- ple of cloud profiles, a robust calibration is readily achieved. In the UK, the running mean 90 d calibration coefficients var- ied by about 4 % over a period of 1 year. The consistency of profiles observed by nine pairs of co-located ceilometers in the UK Met Office network operating at around 910 and 1064 nm provided independent validation of the calibration technique. In all cases, if quantitative and reliable backscatter observations are to be obtained it is essential to keep the win- dow clean. This may be a challenge in dusty locations. EU- METNET is currently networking 700 European ceilometers so they can provide ceilometer profiles in near real time to European weather forecast centres and has adopted the cloud calibration technique described in this paper for ceilometers with a wavelength of around 910 nm.
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Figure 9. Water vapor trend analysis on Boulder sonde data for (a) the 75–85 hPa pressure range from 1981 to 2010 and for downsampled data into the three domains, i.e., (b) tropical domain D1, (c) transitional domain D2, and (d) extratropical domain D3. Black diamonds show water vapor means, white diamonds show outliers. Linear trend as green line, 2 year running mean as orange lines. Counts of HALOE values are gray shaded, their respective 2 year running mean is shown as white line. HALOE water vapor values are increased by the difference of mean HALOE (1993–2005) and mean Boulder sonde data (1981–2010) per altitude bin. Note different color bar ranges between Figures 9a and 9b–9d. (e) Distance to the thermal tropopause for each of the water vapor means, color coded regarding tropopause domains. Vertical black dashed line marks the year 2001. B represents the difference of mean Boulder sonde water vapor between 1996–2000 and 2001–2005, H represents the respective changes based on HALOE data.
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