Probability Density Function Of Temperature Research Articles

Sensible heating as a potential mechanism for enhanced cloud formation over temperate forest

It has been recently shown for two forests in France (Les Landes and Sologne) that summer cloud cover over the forest is increased relative to its surroundings. This study aims to contribute to the elucidation of the physical mechanisms responsible for this increased cloud cover, focusing on surface flux partitioning. This was done by performing a case study for a heatwave day on which enhanced cloud cover over the forest of Les Landes was observed. Two numerical experiments (large‐eddy simulations) with a homogeneous forest cover were performed, one in which the sensible heat flux was increased by approximately 5% of the total available energy and another one in which the same amount of energy was added to the latent heat flux. The addition of energy to the sensible heat flux led to a stronger increase in cloud cover than the same addition to the latent heat flux. The mean relative humidity at the boundary layer top showed only small differences, indicating it was not a sufficient indicator for cloud formation in this case. Important information, which immediately underlines the need for large‐eddy simulations, is contained in modifications of the shape of the probability density functions of temperature and humidity. With enhanced sensible heating, the higher peak values of relative humidity contribute to an increased cloud cover. A crucial reason for the differences in cloud cover between the experiments is conjectured to be a decrease in the required amount of energy for air parcels to reach the lifting condensation level, indirectly caused by the boundary layer and near‐surface warming associated with the stronger sensible heat flux. As forests in the region do have a higher sensible heat flux than their surroundings, we highlight one potential mechanism for enhanced cloud cover.

Five kHz thermometry in turbulent spray flames using chirped-probe-pulse femtosecond CARS, part II: Structure of reaction zones

Temperature was measured in turbulent spray flames of ethanol and acetone stabilized on the piloted Sydney Needle Spray Burner (SYNSBURNTM) using single-laser-shot, chirped-probe-pulse femtosecond coherent anti-Stokes Raman spectroscopy (CPP-fs-CARS) with a repetition rate of 5 kHz. The burner features air-blast atomization of liquid injected from a needle that can be translated by a length Lr within a co-flowing air stream so that piloted spray flames ranging from dilute to dense can be studied. Part I of these investigations has reported on the CPP-fs-CARS technique and extensive details of data processing methodology. Part II is concerned with the structure of the reaction zones at different spray loadings and for different departures from blow-off. While not performed simultaneously, measurements of the size distribution of liquid fragments are also reported and discussed in conjunction with the measured temperature. Measured probability density functions of temperature show that for flames with the same liquid loading but different recess lengths, Lr, the near-field spray structure that forms upstream of x/D = 10 affects flame structure and stability further downstream. As the spray exiting the burner becomes denser, with a higher proportion of ligaments and ‘irregular’ shaped objects, the entrainment of hot pilot gases into the spray envelope is affected, hence changing the rates of vaporization and subsequent combustion. The reported results will also form a useful platform for validating sub-models of atomization and combustion in turbulent, dilute to dense spray flames.

High-Order Statistics of Temperature Fluctuations in an Unstable Atmospheric Surface Layer over Grassland

Skewness (S) and kurtosis (K) of temperature in the surface layer over a grassland are investigated under unstable thermal stratifications.We find that both skewness and kurtosis generally obey Monin–Obukhov similarity theory and tend to be constant values (1.5 and 5.3, respectively) when the stability parameter z/L < −2. Quantitative formulas of the similarity functions are proposed. The temperature probability density function (PDF) is close to Gaussian in near neutral stratification and non-Gaussian in unstable stratification. The influence of coherent motions on the PDF behavior is analyzed using the quadrant analysis technique. It shows that PDF behaviors are controlled by ejections and sweeps. The results also indicate that the PDF type of the ejections always follows a Gaussian distribution, while the PDF of the sweeps changes with stability.

Uncertainty Analysis of the Conditional Exceedance Probability Calculation for a Probabilistically Significant SBO Sequence

The Risk Informed Safety Margin Characterization methodology combines traditional probabilistic safety assessment (PSA) and the best-estimate plus uncertainty approach. Consequently, both stochastic uncertainty and epistemic uncertainty can be taken into overall consideration to evaluate the risk-informed safety margin. Generally, in calculation of the event sequence success criteria in traditional PSA, the result can only be either success (zero) or failure (unity), which is because uncertainties are not properly taken into consideration. In this paper, the conditional exceedance probability (CEP) of a probabilistically significant station blackout sequence of a typical three-loop pressurized water reactor was calculated with the consideration of both stochastic and epistemic uncertainties by using RELAP5. To get the probability density function of the peak cladding temperature (PCT) of a particular sequence and corresponding CEP, random sampling analysis of major plant status parameters and stochastic parameters was performed. It is assumed that the core is damaged when the PCT reaches 1477.6 K. Through the calculation of CEP of this specific sequence, it can be found that core damage will take place in a certain possibility between zero and unity when taking plant status uncertainties and stochastic uncertainties into consideration. Therefore, the core damage frequency (CDF) of any probabilistically significant sequence can be recalculated to get a more precise CEP. With the application of the computational risk assessment method, not only can the conditional CDF be reasonably reduced, but also the revised model can be made sensitive to a system design change of limited scope. Compared to the traditional PSA evaluation without uncertainty analysis, the CDF of the loss–of–heat sink dominant group can be reduced by a factor of 8.75 ( / ).

A climatology of polar stratospheric cloud composition between 2002 and 2012 based on MIPAS/Envisat observations

Abstract. The Michelson Interferometer for Passive Atmospheric Sounding (MIPAS) instrument aboard the European Space Agency (ESA) Envisat satellite operated from July 2002 to April 2012. The infrared limb emission measurements provide a unique dataset of day and night observations of polar stratospheric clouds (PSCs) up to both poles. A recent classification method for PSC types in infrared (IR) limb spectra using spectral measurements in different atmospheric window regions has been applied to the complete mission period of MIPAS. The method uses a simple probabilistic classifier based on Bayes' theorem with a strong independence assumption on a combination of a well-established two-colour ratio method and multiple 2-D probability density functions of brightness temperature differences. The Bayesian classifier distinguishes between solid particles of ice, nitric acid trihydrate (NAT), and liquid droplets of supercooled ternary solution (STS), as well as mixed types. A climatology of MIPAS PSC occurrence and specific PSC classes has been compiled. Comparisons with results from the classification scheme of the spaceborne lidar Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) on the Cloud-Aerosol-Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) satellite show excellent correspondence in the spatial and temporal evolution for the area of PSC coverage (APSC) even for each PSC class. Probability density functions of the PSC temperature, retrieved for each class with respect to equilibrium temperature of ice and based on coincident temperatures from meteorological reanalyses, are in accordance with the microphysical knowledge of the formation processes with respect to temperature for all three PSC types. This paper represents unprecedented pole-covering day- and nighttime climatology of the PSC distributions and their composition of different particle types. The dataset allows analyses on the temporal and spatial development of the PSC formation process over multiple winters. At first view, a more general comparison of APSC and AICE retrieved from the observations and from the existence temperature for NAT and ice particles based on the European Centre for Medium-Range Weather Forecasts (ECMWF) reanalysis temperature data shows the high potential of the climatology for the validation and improvement of PSC schemes in chemical transport and chemistry–climate models.

Research on heat transfer characteristics of kerosene at supercritical pressure in circular tubes

Understanding the heat transfer characteristics of supercritical kerosene is significant for the corresponding engineering design, and the special properties of supercritical fluids make the heat transfer more complicated. In this article, the heat transfer characteristics of kerosene under the condition of supercritical pressure, high heat flux and high velocity were investigated and analyzed. The experimental results show that with the increase of flow velocity and inlet temperature at supercritical pressure, the heat transfer coefficient of kerosene increases and the pressure has little effect on the heat transfer coefficient. Experiment shows that when the inlet temperature is high, coking phenomenon may occur to affect heat transfer. Considering the particularity of the properties of supercritical kerosene and its violent changes of physical parameters in the flow space, dynamic viscosity and thermal conductivity were introduced to modify the traditional kerosene heat transfer correlation. Simultaneously taking the changes of the physical properties of kerosene in time dimension into consideration, the temperature probability density function (PDF) was introduced to obtain the time average physical property from the perspective of probability and statistics. The results show that when the inner wall temperature exceeds 400 °C, the kerosene heat transfer correlation with radial correction factors can reduce the predicted average error to 13%. With the proper selections of the standard deviation, the PDF model can reduce prediction error of 6% to 11% at high wall temperature. The results of this article provide reliable support for the reasonable design of the relevant equipment.

CFD simulations of Industrial Steam Cracking Reactors: Turbulence–Chemistry Interaction and Dynamic Zoning

Modeling finite-rate chemistry in turbulent reacting flows is challenging because of the large span in length and time scales. Reynolds-averaged Navier–Stokes equations-based simulations do not resolve turbulent fluctuations and hence neglect their effect on the reaction rates. Turbulence–chemistry interaction was accounted for in RANS simulations via quadrature-based integration of the reaction rates, calculated using a temperature probability density function with a presumed Gaussian shape and transported mean and variance. The effect on light olefin yield was 0.1–0.2 wt % absolute. A dynamic zoning method was implemented to reduce the computational cost by performing chemical rate calculations only once for thermodynamically similar cells. Speedups of 50–190 were observed while the relative error on conversion remained below 0.05%. The advantages of the presented methodology were illustrated for a large-scale butane-cracking U-coil reactor.

Scalings of heat transport and energy spectra of turbulent Rayleigh-Bénard convection in a large-aspect-ratio box

Direct Numerical Simulations of turbulent convection in a large aspect-ratio box are carried out in the range of Rayleigh number 7 × 104 ≤ Ra ≤ 2 × 106 at Prandtl number Pr=0.71. A strong correlation between the vertical velocity and temperature is observed in the turbulent regime at almost all the length scales. Frequency spectra of all the velocities and temperature show a −5/3 law for a wide band of frequencies. The variances of horizontal velocities at different points in the flow yield a single power-law. Probability density functions of velocities and temperature are close to Gaussian only at higher Rayleigh numbers. The mean and variance of temperature clearly show boundary layers, surface layers and a near-homogeneous bulk region. The boundary layer thickness decreases and bulk-homogeneity is enhanced on increasing the Rayleigh numbers. The wave number spectra of the turbulent kinetic energy exhibit Kolmogorov like (E(k)∼k−5/3) and Bolginao-Obukhov like (E(k)∼k−11/5) behaviour respectively in the central and near-wall regions of the container. An approximate balance between the production due to buoyancy and the dissipation is found in the turbulent kinetic energy budget. Taylor’s approximate equation of the production due to turbulent stretching and the dissipation of turbulent enstrophy is modified by the inclusion of buoyancy production in the enstrophy budget. The present results support the previously proposed 2/7 power-law dependence of the average Nusselt number on the Rayleigh number by yielding an exponent of 0.272, but do not necessarily support the proposed classification of “soft” and “hard” turbulence on the basis of this exponent.

Laser-diagnostic mapping of temperature and soot statistics in a 2-m diameter turbulent pool fire

We present spatial profiles of temperature and soot-volume-fraction statistics from a sooting, 2-m base diameter turbulent pool fire, burning a 10%-toluene/90%-methanol fuel mixture. Dual-pump coherent anti-Stokes Raman scattering and laser-induced incandescence are utilized for simultaneous point measurements of temperature and soot. The research fuel-blend used here results in a lower soot loading than real transportation fuels, but allows us to apply high-fidelity laser diagnostics for spatially resolved measurements in a fully turbulent, buoyant fire of meter-scale base size. Profiles of mean and rms fluctuations are radially resolved across the fire plume, both within the hydrocarbon-rich vapor-dome region near fuel pool, and higher within the actively burning region of the fire. The spatial evolution of the soot and temperature probability density functions is discussed. Soot fluctuations display significant intermittency across the full extent of the fire plume for the research fuel blend used. Simultaneous, spatially overlapped temperature/soot measurements permit us to obtain estimates of joint statistics that are presented as spatially resolved conditional averages across the fire plume, and in terms of a joint pdf obtained by including measurements from multiple spatial locations. Within the actively burning region of the fire, soot is observed to occupy a limited temperature range between ∼1000 and 2000 K, with peak soot concentration occurring at 1600–1700 K across the full radial extent of the fire plume, despite marked changes in the local temperature pdf across the same spatial extent. A wider range of soot temperatures is observed in the fuel vapor-dome region low in the pool fire, with detectable cold soot persisting into conditionally averaged statistics. The results yield insight into soot temperature across a wide spatial extent of a fully turbulent pool fire of meaningful size, which are valuable for development of soot radiative-emission models and for validation of fire fluid-dynamics codes.

Future changes due to model biases in probabilities of extreme temperatures over East Asia using CMIP5 data

ABSTRACTThis study examines the performances of 31 global climate models in the Coupled Model Inter‐comparison Project 5 (CMIP5) in terms of probability density functions (PDFs) for maximum (Tmax) and minimum (Tmin) air temperatures over East Asia in the present and CMIP5‐model projected future changes. In general, most of models well reproduce warm‐season peak for both Tmax and Tmin but exhibit large inter‐model spread for simulating cold‐season peak, especially for Tmin. Minimum values of Tmin and Tmax are more strongly dependent upon model selection than maximum values of them. For the last 25 years of the 21st century, under the Representative Concentration Pathways 4.5 scenario, models project shifts toward warmer values in the PDFs of Tmax and Tmin and broadening in the shape of PDFs. Models with warm biases in PDFs tend to show larger shifts in temperature changes, but seasonal mean temperature biases do not affect to future changes. It is notable that the broadening of PDFs in the future influences temperature extreme events. Using the changes in probabilities of heat waves as one of extreme temperature events by comparing multi‐model ensemble (MME) and models with good performance of PDFs, this study shows that MME tends to overestimate its duration. Our findings suggest that future changes in temperature extremes projected by models are strongly come from the biases detected in those models when simulating present extreme temperature PDFs. Therefore, correcting the intrinsic biases of models rather than seasonal mean correction is necessary to reduce the uncertainties in predicting future changes in temperature extremes.

On determining the point of no return in climate change

Abstract. Earth's global mean surface temperature has increased by about 1.0 °C over the period 1880–2015. One of the main causes is thought to be the increase in atmospheric greenhouse gases. If greenhouse gas emissions are not substantially decreased, several studies indicate that there will be a dangerous anthropogenic interference with climate by the end of this century. However, there is no good quantitative measure to determine when it is too late to start reducing greenhouse gas emissions in order to avoid such dangerous interference. In this study, we develop a method for determining a so-called point of no return for several greenhouse gas emission scenarios. The method is based on a combination of aspects of stochastic viability theory and linear response theory; the latter is used to estimate the probability density function of the global mean surface temperature. The innovative element in this approach is the applicability to high-dimensional climate models as demonstrated by the results obtained with the PlaSim model.

Design of an intelligent stochastic model predictive controller for a continuous stirred tank reactor through a Fokker-Planck observer

Over the years, different methods have been presented to control continuous stirred tank reactors (CSTRs) in which stochastic behavior of process has rarely been considered. This article uses the stochastic model of CSTR to compute the temperature of coolant as process input in order to control the joint probability density function (PDF) of process concentration and temperature. The computation is carried out based on receding horizon-model predictive control (RH-MPC). Since observer has important role in the determination of process input, we use a nonlinear stochastic Fokker-Planck observer to calculate process PDF. The CSTR model is nonlinear and complex, so the particle swarm optimization (PSO) algorithm is used for simplification of computations and for determination of the optimal value of process input. For this purpose, an MPC problem is described for which the cost function is defined based on the difference between the process PDF and a desired PDF. In this definition, temperature limitation of the coolant and the corresponding Fokker-Planck equation are both assumed as the problem constraints. When this MPC problem is solved by the use of PSO, the process input is calculated for each time window. The existence and uniqueness of our optimal solution is also studied. In the article, the Fokker-Planck equation for CSTR model will be solved by the use of path integral method. In this way, the joint PDF of process concentration and temperature is obtained for any instance of time. The simulation results are also obtained to evaluate the proposed method.

Dual-pump vibrational CARS measurements of temperature and species concentrations in turbulent premixed flames with CO2 addition

A dual-pump vibrational coherent anti-Stokes Raman scattering (DPVCARS) system was applied for simultaneous temperature and species concentration measurements in jet flames on a newly developed piloted axisymmetric reactor assisted turbulent (PARAT) premixed flame burner. Turbulent lean premixed methane/air round jet flames with varying CO2 dilution were stabilized using an annular flow of hydrogen at the flame base. Carbon dioxide was injected into the fuel stream to simulate effects of dry exhaust gas recirculation (EGR). The flames were operated at a nearly constant Reynolds number, Lewis number, and adiabatic flame temperature to minimize thermal and transport effects. Velocity boundary conditions at the burner exit were measured using particle image velocimetry. Simultaneous temperature and major species concentrations (O2 and CO2) were measured along the axial direction at the burner centerline and along the radial direction at representative axial locations above the burner. Progress variables calculated based on the temperatures were used to study the mean flame brush thickness and the turbulent burning velocity. Probability density functions (PDFs) of temperature at various locations are presented and discussed. The DPVCARS measurements provide an experimental database including temperature and turbulent burning velocity for combustion model evaluation and validation and demonstrated a strong potential for flame structure investigation with future improvement on spatial resolution and signal to noise ratio. The merits and limitations of vibrational CARS for diagnostics in turbulent premixed combustion are discussed. The results show that flames with CO2 addition depart from the universal mean flame brush structure, while their RMS fluctuation values at an identical mean temperature collapse with the undiluted flame. The CO2 addition increases the combustion intensity with a decrease in turbulent burning velocity when minimizing the thermal and transport effects.

Thermal convection with mixed thermal boundary conditions: effects of insulating lids at the top

The effects of insulating lids on the convection beneath were investigated experimentally using rectangular convection cells in the flux Rayleigh number range $2.3\times 10^{9}\leqslant Ra_{F}\leqslant 1.8\times 10^{11}$ and cylindrical cells in the range $1.4\times 10^{10}\leqslant Ra_{F}\leqslant 1.2\times 10^{12}$ with the Prandtl number $Pr$ fixed at 4.3. It is found that the presence of the insulating lids leads to reduction of the global heat transfer efficiency as expected, which primarily depends on the insulating area but is insensitive to the detailed insulating patterns. At the leading-order level, the magnitude of temperature fluctuations in the bulk fluid is, again, found to be insensitive to the insulating pattern and mainly depends on the insulating area; while the temperature probability density function in the bulk is essentially invariant with respect to both the insulating area and the spatial pattern of the lids. The flow dynamics, on the other hand, is sensitive to both the covering area and the spatial distribution of the lids. At fixed $Ra_{F}$, the flow strength is found to increase with increasing insulating area so as to transfer the same amount of heat through a smaller cooling area. Moreover, for a constant insulating area, a symmetric insulating pattern results in a symmetric flow pattern, i.e. double-roll structure; whereas an asymmetric insulating pattern leads to asymmetric flow, i.e. single-roll structure. It is further found that the symmetry breaking of the insulating pattern leads to a stronger flow that enhances the horizontal velocity more than the vertical velocity.

The non‐local character of turbulence asymmetry in the convective atmospheric boundary layer

The inadequacy of conventional gradient diffusion in closure modelling of turbulent heat fluxes within the convective atmospheric boundary layer is often alleviated by accounting for non‐local transport effects, such as Deardorff's counter‐gradient models, Wyngaard's transport asymmetry closures or mass‐flux parametrization. This concept of large‐eddy flux transport is examined here with the principal aim of unifying these seemingly different models. Using large‐eddy simulation (LES) runs for the atmospheric boundary layer, spanning weakly to strongly convective conditions, a generic diagnostic framework that encodes the role of third‐order moments in non‐local transport is developed and tested. The premise is that these non‐local effects are responsible for the inherent asymmetry in vertical transport and hence the necessary non‐Gaussian nature of the joint probability density function (JPDF) of vertical velocity and potential temperature must account for these effects. Conditional sampling (quadrant analysis) of this JPDF and the imbalance between the flow mechanisms of ejections and sweeps are used to characterize this asymmetry, which is then linked to the third‐order moments using a cumulant‐discard method for the Gram–Charlier expansion of the JPDF. While the concept of ejection‐sweep events used here is not a simple extension of that commonly used in the surface layer, their connection to third‐order moments shows that the concepts of bottom‐up/top‐down diffusion or updraught/downdraught models are accounted for by various quadrants of the JPDF. An analogy between mass‐flux models and the relaxed eddy accumulation method reveals that there is a seemingly implicit assumption of a Gaussian JPDF in the former.

Effects of pressure on cellular flame structure of high hydrogen content lean premixed syngas spherical flames: A DNS study

The structure and propagation of turbulent lean premixed high hydrogen content syngas flames at pressure values of 1 bar, 2 bar and 4 bar are studied using three-dimensional direct numerical simulations. Simulations for each pressure considered were performed for three different initial turbulence levels at the turbulent Reynolds numbers of 50, 100 and 150. The DNS of expanding spherical flames has taken into account detailed chemical kinetics and preferential diffusion effects. The mixture-averaged transport model has been employed. Effects of pressure on flame structures, heat release rate and radical species distributions under low to high initial turbulent conditions are examined. The results show that elevated pressures greatly influence the cellular flame structure of syngas spherical flames under different initial turbulent conditions. At the atmospheric pressure, the flame shows weakly wrinkling structures due to the initial turbulence level imposed in the simulation. At elevated pressures under turbulence conditions, the flame develops cellular burning structures, superimposed by flame wrinkles due to turbulence. It is shown that highly wrinkled cells that develop over the surface of a spherical flame increase its area and thereby the global propagation speed at elevated pressures. Results show noticeable increases in the local heat release rate with increasing pressure. The analysis also reveals the formation of cusped structures with low heat release rate values in areas of negative curvatures at elevated pressures, in agreement with previous studies. The joint probability density functions of OH radical mass fraction and temperature show broadening OH values in the high temperature zone at elevated pressures compared to its distribution at the atmospheric pressure. Comparisons of mean species distributions of OH and HO2 over temperature between laminar and turbulent flames show that pressure elevation has a major influence on the flame structure in the composition space.

Probability-Weighted Ensembles of U.S. County-Level Climate Projections for Climate Risk Analysis

AbstractQuantitative assessment of climate change risk requires a method for constructing probabilistic time series of changes in physical climate parameters. Here, two such methods, surrogate/model mixed ensemble (SMME) and Monte Carlo pattern/residual (MCPR), are developed and then are applied to construct joint probability density functions (PDFs) of temperature and precipitation change over the twenty-first century for every county in the United States. Both methods produce likely (67% probability) temperature and precipitation projections that are consistent with the Intergovernmental Panel on Climate Change’s interpretation of an equal-weighted Coupled Model Intercomparison Project phase 5 (CMIP5) ensemble but also provide full PDFs that include tail estimates. For example, both methods indicate that, under “Representative Concentration Pathway” 8.5, there is a 5% chance that the contiguous United States could warm by at least 8°C between 1981–2010 and 2080–99. Variance decomposition of SMME and MCPR projections indicates that background variability dominates uncertainty in the early twenty-first century whereas forcing-driven changes emerge in the second half of the twenty-first century. By separating CMIP5 projections into unforced and forced components using linear regression, these methods generate estimates of unforced variability from existing CMIP5 projections without requiring the computationally expensive use of multiple realizations of a single GCM.

Recent and future changes in the combination of annual temperature and precipitation throughout China

ABSTRACTClimate involves different combinations of temperature and precipitation, and each year's combination of factors can be assigned a climatic year type (CYT; e.g. Warm‐Humid). Describing the changes in the CYT provides more information than describing the temperature or precipitation data alone. In this study, we defined nine CYTs using the probability density function of annual temperature and precipitation. Recent and future spatiotemporal changes in CYT were analysed using 507‐station observational data and projected data obtained from the CMIP5 multi‐model ensemble under RCP2.6, RCP4.5, and RCP8.5 scenarios. China was divided into six subregions to analyse the spatiotemporal changes. Obvious differences in spatial patterns among the various CYTs reflect the climate regime throughout China. The warmth‐associated CYTs (Warm‐Humid, Warm‐Dry, and Warm‐Normal) mainly occur in West China (e.g. Southwest China). The cold‐associated CYTs (Cold‐Humid, Cold‐Dry, and Cold‐Normal) dominate at high latitudes and high altitudes (e.g. Northeast China and the Tibetan Plateau). The climate in China changed from cold to warm in the last half‐century, accompanying the transformation of Cold‐Humid, Cold‐Dry, and Cold‐Normal before the early 1990s to Warm‐Humid, Warm‐Dry, and Warm‐Normal from the early 1990s onward. In the 21st century, the projected CYTs are mainly Warm‐Humid, Warm‐Dry, and Warm‐Normal in China. Warm‐Humid dominates in West China, North China, and Northeast China. Warm‐Dry is mainly projected in the Yellow River Valley and South China. High‐frequency Warm‐Normal is projected in the Yellow River Valley. Warm‐Humid is projected to increase whereas Warm‐Dry and Warm‐Normal are projected to decrease from 2015 to 2099. All three CYTs are projected to exhibit larger changes in trends under stronger versus weaker RCPs (RCP8.5 &gt; RCP4.5 &gt; RCP2.6). Compared with temperature or precipitation data alone, CYTs provide more complete information on climate change and more accurately characterize regional differences in climate throughout China.

Estimating ENSO predictability based on multi-model hindcasts

Based on hindcasts of seasonal forecast systems participating in the North American Multi-Model Ensemble, the seasonal dependence of predictability of the El Nino–Southern Oscillation (ENSO) was estimated. The results were consistent with earlier analyses in that the predictability of ENSO was highest in winter and lowest in spring and summer. Further, predictability as measured by the relative amplitude of predictable and unpredictable components was dominated by the ensemble mean instead of the spread (or dispersion) among ensemble members. This result was consistent with previous analysis that most of ENSO predictability resides in the shift of the probability density function (PDF) of ENSO sea surface temperature (SST) anomalies (i.e., changes in the first moment of the PDF that is associated with the ensemble mean of ENSO SST anomalies) rather than due to changes in the spread of the PDF. The analysis establishes our current best estimate of ENSO predictability that can serve as a benchmark for quantifying further improvements resulting from advances in observing, assimilation, and seasonal prediction systems.

An experimental and numerical investigation of the combustion and heat transfer characteristics of hydrogen-fueled catalytic microreactors

The combustion and heat transfer characteristics of a hydrogen-fueled microreactor are investigated experimentally and numerically. The microreactor comprises a 30×30×4mm3 SiC-block equipped with six 1.5mm diameter platinum channels. Combustion of fuel-lean H2/air mixtures at equivalence ratios φ=0.25−0.50 and inlet velocities 15–50m/s is studied at coflow and counterflow configurations. Surface temperatures are measured with an infrared camera, while simulations are carried out with a 3D code that includes conjugate heat transfer, appropriate external heat losses, and detailed hetero-/homogeneous chemistry. Higher mass throughputs reduce the surface temperature spatial non-uniformities, while the onset of gaseous combustion lowers the catalyst surface temperatures and is thus detrimental for power generation applications. Four different channel configurations are tested for optimum temperature uniformity. Counterflow configurations are shown superior to the coflow configuration in attaining better surface temperature uniformities with standard deviations less than 19K and maximum surface temperatures up to 1311K. Comparisons of measurements and predictions are very favorable in terms of temperature probability density function (PDF) shapes and higher distribution moments. Counterflow configurations yield narrower PDFs slightly skewed to the low temperatures, while the coflow configuration yields mostly bimodal shapes. Radiation efficiencies increase with increasing inlet velocity and equivalence ratio. Application of the microreactor to power generation systems, in conjunction with thermoelectric devices, appears quite promising given the attained good spatial uniformity and the high values of surface temperatures.