1,282 research outputs found

    Retrieval of moisture from GPS slant-path water vapor observations using 3DVAR and its impact on the prediction of convection initiation and precipitation.

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    The anisotropic explicit filter is computationally expensive in both CPU time and memory usage. Therefore the implicit recursive filter which is computationally much more efficient is implemented in our 3DVAR system, even though its implementation is significantly more complicated. A similar set of water vapor analysis experiments using the recursive filters is performed. The analyses thus obtained are generally comparable to or better than those obtained using the corresponding explicit filters. In addition, the sensitivity of the analyses to the spatial de-correlation scales of the background error is systematically examined.A set of high-resolution numerical experiments is conducted using the Advanced Regional Prediction System (ARPS) for a case that occurred on 12 June, 2002 and involved multiple initiations of convection. The results are verified against the radar composite reflectivity in detail. It is shown that the model performs reasonably well on predicting the initiation timing and location and the subsequent storm evolution for up to 7 hours. Using the most realistic simulation of this case as the 'truth', simulated SWV data and surface moisture observations are generated to perform a set of Observing System Simulation Experiments (OSSEs) using our 3DVAR system with recursive filters. The preliminary results illustrate that convection initiation (CI) without strong low-level mesoscale forcing is highly sensitive to the moisture initial condition and the use of SWV and surface data improves the moisture analysis and thus the prediction of CI and precipitation. The enhanced moisture analysis obtained from the use of anisotropic background error further improves the precipitation forecast though it does not lead to positive impact on the prediction of exact timing and location of the CI due to its high sensitivity to very small-scale moisture structures.The 3DVAR system developed in this study is based on a terrain-following coordinate. A non-negative water vapor weak constraint is included in the cost function. The background term and its associated background error covariance are considered in the system and the latter is modeled using explicit or implicit recursive spatial filters. Most importantly, a direct way to estimate a flow-dependent background error covariance based on the idea of Riishojgaard is proposed for the moisture analysis. The explicit spatial filter first is implemented with both isotropic and anisotropic options. It is demonstrated that this system is robust on deriving mesoscale moisture structures from the GPS SWV and surface observations and the analysis is improved when the anisotropic background error covariance is used. Sensitivity experiments show that surface moisture data are important for the analysis near ground and a vertical filter is essential to obtain an accurate analysis near the surface. The positive impact of flow-dependent background error is enhanced when the density of GPS receiver network is lower.The accurate prediction of convection initiation and the subsequent precipitation in a cloud-resolving numerical model is highly dependent on the precise estimate of the three-dimensional moisture in the initial condition because water vapor is directly involved in the formation of clouds and precipitation. However, the water vapor is currently poorly characterized due to its high variability in space and time. A three-dimensional variational analysis system (3DVAR) is developed in this dissertation to retrieve the moisture field from simulated ground-based GPS slant-path integrated water vapor (SWV) data that are potentially available at high temporal and spatial resolutions

    Amelioration of Factors Limiting the Use of Lipid-Based Diesel Products

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    High-purity oleate esters can decrease the melting points and improve the oxidative stability of lubricants. High-oleic soybean oil (HOSO) was esterified to butyl or isopropyl esters. Fractional distillation and low-temperature crystallization were applied to improve the purity of oleate of HOSO esters. Although the purity of butyl esters of HOSO attained 91.8% by fractional distillation, the rate of distillation must be slow which made this approach not very feasible. After subjecting the esters to a two-step crystallization at reduced temperatures, the percentage of oleate in the HOSO esters was increased from 83.2 to 92.5%. The percentage of saturated fatty acids decreased to less than 2.2%, but polyunsaturates percentage remained almost unchanged. Methyl linoleate monolayer has a highest lipid oxidation rate. It can be employed to produce useful oxidation products including expoxides and hydroxides. Methyl linoleate (20% by weight) was coated to silica gel H to form monolayers and heated at 35, 40, 50 and 60yC. Methyl palmitate (5% by weight of methyl linoleate) was added as internal standard. The identification of oxidation products was by comparison to standards. The oxidation rate increased with temperature. The temperature for optimal yields of epoxides (20.26%) and total non-scission products (NSPs, 38.79%) was 50yC. Citric acid and EDTA (0.01% and 0.02% by weight of oil) were added as chelating agents to minimize the effects of iron on oxidation. Citric acid at 0.01% achieved higher PV and also reduced the loss of NSPs to scission products (SPs) after reaching the maximum peroxide value. The addition of 20 ppm vanadium (by weight of silica gel) increased the yield of epoxides (23.85%); however, it also led to lower peroxide values and longer induction period. After long operation of biodiesel engine, hard and dark deposits accumulate on injector tips, which affect engine performance. The type and composition of biodiesel have major effect on the formation of deposits. The major compounds of thermal stable residues of biodiesel from muffle furnace heated at 200yC for 15 min were analysed by GC-MS. Those compounds were mostly fragments of fatty esters, in which the terminal ends are acids, aldehydes. Methyl linolenate formed significantly greater amounts of residue than neat biodiesel, methyl palmitate, methyl stearate, methyl oleate, and methyl linoleate. The GC profile of methyl linolenate residues included more compounds than from other oils

    LpL^p-improving bounds of maximal functions along planar curves

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    In this paper, we study the Lp(R2)L^p(\mathbb{R}^2)-improving bounds, i.e., Lp(R2)β†’Lq(R2)L^p(\mathbb{R}^2)\rightarrow L^q(\mathbb{R}^2) estimates, of the maximal function MΞ³M_{\gamma} along a plane curve (t,Ξ³(t))(t,\gamma(t)), where MΞ³f(x1,x2):=sup⁑u∈[1,2]∣∫01f(x1βˆ’ut,x2βˆ’uΞ³(t)) dt∣,M_{\gamma}f(x_1,x_2):=\sup_{u\in [1,2]}\left|\int_{0}^{1}f(x_1-ut,x_2-u \gamma(t))\,\textrm{d}t\right|, and Ξ³\gamma is a general plane curve satisfying some suitable smoothness and curvature conditions. We obtain MΞ³:Lp(R2)β†’Lq(R2)M_{\gamma} : L^p(\mathbb{R}^2)\rightarrow L^q(\mathbb{R}^2) if (1p,1q)βˆˆΞ”βˆͺ{(0,0)}(\frac{1}{p},\frac{1}{q})\in \Delta\cup \{(0,0)\} and (1p,1q)(\frac{1}{p},\frac{1}{q}) satisfying 1+(1+Ο‰)(1qβˆ’1p)>01+(1 +\omega)(\frac{1}{q}-\frac{1}{p})>0, where Ξ”:={(1p,1q):Β 12p<1q≀1p,1q>3pβˆ’1}\Delta:=\{(\frac{1}{p},\frac{1}{q}):\ \frac{1}{2p}<\frac{1}{q}\leq \frac{1}{p}, \frac{1}{q}>\frac{3}{p}-1 \} and Ο‰:=lim sup⁑tβ†’0+ln⁑∣γ(t)∣ln⁑t\omega:=\limsup_{t\rightarrow 0^{+}}\frac{\ln|\gamma(t)|}{\ln t}. This result is sharp except for some borderline cases. As Hickman stated in [J. Funct. Anal. 270 (2016), pp. 560--608], this is a very different situation

    On Cooperative Coevolution and Global Crossover

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    Cooperative coevolutionary algorithms (CCEAs) divide a given problem in to a number of subproblems and use an evolutionary algorithm to solve each subproblem. This short paper is concerned with the scenario under which only a single, global fitness measure exists. By removing the typically used subproblem partnering mechanism, it is suggested that such CCEAs can be viewed as making use of a generalised version of the global crossover operator introduced in early Evolution Strategies. Using the well-known NK model of fitness landscapes, the effects of varying aspects of global crossover with respect to the ruggedness of the underlying fitness landscape are explored. Results suggest improvements over the most widely used form of CCEAs, something further demonstrated using other well-known test functions
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