Comparison of different methods for estimating soil surface evaporation in a bare field

In this paper, three methods for estimating soil evaporation in a bare field were evaluated: evaporation ratio method (k ratio), complementary relationship and bulk equation. Micro-lysimeters were used to measure the actual evaporation for validation of the three methods. For the k ratio method, pan evaporation was used as the reference evaporation instead of the value obtained from the Penman–Monteith equation. This result is important for areas where meteorological data are unavailable. The results showed that, for daytime evaporation, the k ratio and bulk equation produced a good fit with the observation data, while the complementary relationship generated a larger deviation from the measured data. We recommend that the k ratio method and bulk equation could be used to calculate daytime soil evaporation with high accuracy when soil water content and pan evaporation data or meteorological data are available, while the complementary relationship could be used for a rough estimation when pan evaporation is available. All the methods could be applied to calculate cumulative evaporation.     

Semi-idealized modeling of lightning initiation related to vertical air motion and cloud microphysics

A three-dimensional charge–discharge numerical model is used, in a semi-idealized mode, to simulate a thunder-storm cell. Characteristics of the graupel microphysics and vertical air motion associated with the lightning initiation are revealed, which could be useful in retrieving charge strength during lightning when no charge–discharge model is available. The results show that the vertical air motion at the lightning initiation sites (W_ini) has a cubic polynomial correlation with the maximum updraft of the storm cell (W_cell-max), with the adjusted regression coefficient R² of approximately 0.97. Meanwhile, the graupel mixing ratio at the lightning initiation sites (q_g-ini) has a linear correlation with the maximum graupel mixing ratio of the storm cell (q_g-cell-max) and the initiation height (z_ini), with the coefficients being 0.86 and 0.85, respectively. These linear correlations are more significant during the middle and late stages of lightning activity. A zero-charge zone, namely, the area with very low net charge density between the main positive and negative charge layers, appears above the area of q_g-cell-max and below the upper edge of the graupel region, and is found to be an important area for lightning initiation. Inside the zero-charge zone, large electric intensity forms, and the ratio of q_ice (ice crystal mixing ratio) to q_g (graupel mixing ratio) illustrates an exponential relationship to q_g-ini. These relationships provide valuable clues to more accurately locating the high-risk area of lightning initiation in thunderstorms when only dual-polarization radar data or outputs from numerical models without charging/discharging schemes are available. The results can also help understand the environmental conditions at lightning initiation sites.     

An Analytical Model for the Distribution of CO2 Sources and Sinks, Fluxes, and Mean Concentration Within the Roughness Sub-Layer

A one-dimensional analytical model that predicts foliage CO₂ uptake rates, turbulent fluxes, and mean concentration throughout the roughness sub-layer (RSL), a layer that extends from the ground surface up to 5h, where h is canopy height, is proposed. The model combines the mean continuity equation for CO₂ with first-order closure principles for turbulent fluxes and simplified physiological and radiative transfer schemes for foliage uptake. This combination results in a second-order ordinary differential equation in which soil respiration (R) and CO₂ concentration well above the RSL are imposed as lower and upper boundary conditions, respectively. An inverse version of the model was tested against datasets from two contrasting ecosystems: a tropical forest (h = 40m) and a managed irrigated rice canopy (h = 0.7m), with good agreement noted between modelled and measured mean CO₂ concentration profiles within the entire RSL. Sensitivity analysis on the model parameters revealed a plausible scaling regime between them and a dimensionless parameter defined by the ratio between external (R) and internal (stomatal conductance) characteristics controlling the CO₂ exchange process. The model can be used to infer the thickness of the RSL for CO₂ exchange, the inequality in zero-plane displacement between CO₂ and momentum, and its consequences on modelled CO₂ fluxes. A simplified version of the solution is well suited for being incorporated into large-scale climate models. Furthermore, the model framework here can be used to a priori estimate relative contributions from the soil surface and the atmosphere to canopy-air CO₂ concentration, thereby making it synergetic to stable isotopes studies.     

Study of crop coefficient and the ratio of soil evaporation to evapotranspiration in an irrigated maize field in an arid area of Yellow River Basin in China

A field experiment was conducted in a maize field in 2006 in an arid area of the Yellow River Basin in China. The daytime evapotranspiration (ET_c) and soil evaporation beneath the maize canopy (E _g) were measured by Bowen ratio energy balance method and micro-lysimeters, respectively. The results showed that the total ET_c during maize growth season was 696 mm, and the maximum values occurred at about 90–140 days after sowing. The crop coefficient (K _c), which was calculated from the ratio of ET_c to reference evapotranspiration (ET₀), was quite different from the values reported by other researchers in similar climate areas, with average values of 0.34, 0.47, 1.0 and 0.9 for initial, development, mid-season and late-season stages, respectively. High correlations between leaf area index (LAI) and average K _c for every 4 days were obtained. The total E _g was 201.4 mm with average values ranged from 0.92 to 2.05 for four growth stages of maize; and accounted for around 28.9 % of ET_c. The ratio E _g/ET_c showed high negative relationship with LAI. These results were very important in precise management of irrigation for maize in Yellow River Basin areas.     

Experimental Investigation on Shear-Stress Partitioning for Flexible Plants with Approximately Zero Basal-to-Frontal Area Ratio in a Wind Tunnel

Shear-stress partitioning is investigated for one type of flexible plant for very small values of the basal-to-frontal area ratio σ (0.001–0.007). The plant model is made of plastic with irregular structures, which are different from previously investigated rigid regular or flexible roughness elements with larger σ values. The distribution of the surface shear stress and the total shear stress at four plant densities with five plant heights are measured in a wind tunnel using Irwin-type sensors and a load cell, respectively. The wind-tunnel experiments prove that, for these flexible plants, the plant height and lateral cover usually decrease with increasing friction velocity, especially for taller plants, while the plant coverage generally increases. However, these characteristics may be inconsistent with flexible roughness elements with very large σ values (and usually very low aspect ratios) because these elements are less flexible. The present flexible plants generally result in lower shear-stress ratios compared with other roughness elements, which is also proven by the higher values of β (the ratio of the drag coefficient of an isolated roughness element to that of the bare surface) and a constant m (accounting for the difference between the average and peak surface shear stresses) from the present experiments (β?=?184–210 and m?=?0.68–0.79). The peak mean stress ratio of the present flexible plants is not a constant (1.07–1.54) because it is affected by the lateral cover, which is different from previous studies that consider the ratio to be constant without regard for the lateral cover.     

Retrieving air humidity,global solar radiation,and reference evapotranspiration from daily temperatures: development and validation of new methods for Mexico. Part III: reference evapotranspiration

We evaluated two methods to estimate evapotranspiration (ETo) from minimal weather records (daily maximum and minimum temperatures) in Mexico: a modified reduced set FAO-Penman-Monteith method (Allen et al. 1998, Rome, Italy) and the Hargreaves and Samani (Appl Eng Agric 1(2): 96–99, 1985) method. In the reduced set method, the FAO-Penman-Monteith equation was applied with vapor pressure and radiation estimated from temperature data using two new models (see first and second articles in this series): mean temperature as the average of maximum and minimum temperature corrected for a constant bias and constant wind speed. The Hargreaves-Samani method combines two empirical relationships: one between diurnal temperature range ΔT and shortwave radiation Rs, and another one between average temperature and the ratio ETo/Rs: both relationships were evaluated and calibrated for Mexico. After performing a sensitivity analysis to evaluate the impact of different approximations on the estimation of Rs and ETo, several model combinations were tested to predict ETo from daily maximum and minimum temperature alone. The quality of fit of these models was evaluated on 786 weather stations covering most of the territory of Mexico. The best method was found to be a combination of the FAO-Penman-Monteith reduced set equation with the new radiation estimation and vapor pressure model. As an alternative, a recalibration of the Hargreaves-Samani equation is proposed.     

On the relationship between the Bowen ratio and the near-surface air temperature

The sensitivity of land surface energy partitioning to near-surface air temperature (T _a) is a critical issue to understand the interaction between land surface and climatic system. Thus, studies with in situ observed data compiled from various climates and ecosystems are required. The relations derived from such empirical analyses are useful for developing accurate estimation methods of energy partitioning. In this study, the effect of T _a on land surface energy partitioning is evaluated by using flux measurement data compiled from a global network of eddy covariance tower sites (FLUXNET). According to the analysis of 25 FLUXNET sites (60 site-years) data, the Bowen ratio is found to have a linear relation with the bulk surface resistance normalized by aerodynamic and climatological resistance parameters in general, of which the slope and intercept are dependent on T _a. Energy partitioning in warmer atmosphere is less sensitive to changes in land surface conditions. In addition, a negative relation is found between Bowen ratio and T _a, and this relation is stronger above less vegetated surface and under low vapor pressure deficit and low received radiative energy condition. The empirical results obtained in this study are expected to be useful in gaining better understanding of alternating surface energy partitioning under increasing T _a.     

Pan coefficient (K p) estimation under uncertainty on fetch

The FAO Penman–Monteith (F-PM) method is a frequently applied approach for calculating the daily reference evapotranspiration (ET₀). This method requires long records of meteorological data, which makes it quite hard to employ in locations with no or limited available data. Evaporation pans are widely used to estimate the reference ET₀, but this method requires reliable estimates of the pan coefficient (K _p). The objectives of this study were to determine the proper values of monthly and annual K _p, as well as the best method among those available for the estimation of K _p values in the study area. Measured weather data from 1992 to 2006 were obtained from 18 stations in the North and Northwest of Iran. Daily ET₀ calculated using methods by Bernardo et al. and Pereira et al. were compared with those calculated by the F-PM method. The employed methods at all stations, except those located in the north of the study area with high relative humidity, overestimated the ET₀ compared to the F-PM method. The constant parameters of these methods were optimized by a trial and error scheme to minimize the root mean square error. The results indicated that modified K _p coefficients from Bernardo et al.’s method ranged between 0.41 and 0.87 and the optimal coefficient of Pereira et al.’s method ranged between 0.49 and 0.95. Modified monthly K _p from Bernardo et al.’s method ranged between 0.3 and 1.07 and those from Pereira et al.’s method ranged between 0.4 and 1.18. Modified K _p of the methods by Bernardo et al. and Pereira et al. showed the higher estimation accuracy of daily ET₀ values. In general, the performance of the modified K _p of Bernardo et al.’s method was higher than Pereira et al.’s method for all stations. Thus, in the study region and under the same climatic conditions [in areas with only pan evaporation (E _p) records], the use of climatic monthly modified K _p to calculate ET₀ based on class A E _p is recommended.     

Aircraft measurements of oxides of nitrogen along the eastern rim of the Asian continent: Winter observations

Aircraft observations of oxides of nitrogen (NO _y ), measured with a ferrous sulfate converter, over the sea surrounding the Japanese islands (30–43° N, 131–141° E) were carried out in the winter of 1983 and 1984 at altitudes mostly between 3 and 8 km. NO _y defined here is the sum of NO, NO₂, and other unstable oxides of nitrogen that are converted to NO by ferrous sulfate. The main observations were:

1. Over the Pacific Ocean between the latitudes of 30–35° N, the observed NO _y mixing ratio between 3 and 8 km was a fairly constant 200 pptv. The NO mixing ratio increased with altitude from 15 pptv at 3 km to 35 pptv at 7 km.
2. Over the Sea of Japan, tropospheric NO _y mesured between 1 and 6 km started increasing with latitude North of 35° N and reached about 1000 pptv at 40° N.
3. NO _y was measured in an air mass transported from the stratosphere near a tropopause fold region. When the ozone mixing ratio was between 80 and 140 ppbv, the NO _y mixing ratio was about 200 pptv.

     

Characteristics of the precipitation recycling ratio and its relationship with regional precipitation in China

A dynamic recycling model (DRM) with an analytical moisture trajectory tracking method, together with Japan Meteorological Agency 25-year reanalysis data, is used to study the regional precipitation recycling process across China, by calculating the regional recycling ratio (ρ _r ) at the daily time scale during 1979–2010. The distribution of ρ _r shows that, in western China, especially the Tibetan Plateau and its surrounding areas, precipitation is strongly dependent on the recycling process associated with regional evaporation. In Southeast China, however, the contribution from the recycling processes is much smaller due to the influence of the summer monsoon. A precipitation threshold value of about 4 mm/day is obtained from detailed analysis of both extreme and all-range ρ _r years. According to this threshold, China is classified into three types of sub-regions: low-precipitation sub-regions (mainly in the northwest), high-precipitation sub-regions (mainly in the south), and medium-precipitation sub-regions (mainly in the northeast). It is found that ρ _r correlates positively with precipitation, as well as convective precipitation (P _CP) and large-scale precipitation (P _LP) in the low-precipitation sub-regions. However, negative ρ _r ?～?P _LP correlations are found in the high-precipitation sub-regions and nonsignificant correlations exist in the medium-precipitation sub-regions. As P _CP is mainly locally generated due to mid-latitude mesoscale systems and the cumulus parameterization used in producing the reanalysis, the recycling ratio positively correlates to the ratio P _CP/P _LP in almost all sub-regions, particularly in the Tibetan Plateau and its surrounding areas. The correlation between radiation flux and ρ _r suggests more net radiation supports more evaporation and higher ρ _r , especially in the high-precipitation sub-regions. The influence of clouds on shortwave radiation is crucial, since evaporation is suppressed when the amount of cloudiness increases, especially in the high-precipitation sub-regions. Together with the consideration of soil moisture, it can be inferred that limited soil moisture inhibits evaporation in the low-precipitation sub-regions, while the energy or radiation is the dominant factor controlling evaporation in the high-precipitation sub-regions.     

The use of the land-sea warming contrast under climate change to improve impact metrics

A favoured method of assimilating information from state-of-the-art climate models into integrated assessment models of climate impacts is to use the transient climate response (TCR) of the climate models as an input, sometimes accompanied by a pattern matching approach to provide spatial information. More recent approaches to the problem use TCR with another independent piece of climate model output: the land-sea surface warming ratio (φ). In this paper we show why the use of φ in addition to TCR has such utility. Multiple linear regressions of surface temperature change onto TCR and φ in 22 climate models from the CMIP3 multi-model database show that the inclusion of φ explains a much greater fraction of the inter-model variance than using TCR alone. The improvement is particularly pronounced in North America and Eurasia in the boreal summer season, and in the Amazon all year round. The use of φ as the second metric is beneficial for three reasons: firstly it is uncorrelated with TCR in state-of-the-art climate models and can therefore be considered as an independent metric; secondly, because of its projected time-invariance, the magnitude of φ is better constrained than TCR in the immediate future; thirdly, the use of two variables is much simpler than approaches such as pattern scaling from climate models. Finally we show how using the latest estimates of φ from climate models with a mean value of 1.6—as opposed to previously reported values of 1.4—can significantly increase the mean time-integrated discounted damage projections in a state-of-the-art integrated assessment model by about 15 %. When compared to damages calculated without the inclusion of the land-sea warming ratio, this figure rises to 65 %, equivalent to almost 200 trillion dollars over 200 years.     

Spectral investigation of the diffuse-to-direct solar beam irradiances ratio (UV–VIS) in the urban Athens atmosphere

This study explores the influence of air gaseous pollutants–aerosols and solar zenith angle (SZA) on the spectral diffuse-to-direct beam E _dλ/E _bλ irradiances ratio. It does so using ground-based spectroradiometric measurements taken over the Athens atmosphere during May 1995. It was found that the spectral E _dλ/E _bλ ratio decreases rapidly with increasing wavelength and regression curves of the form E _dλ/E _bλ = aλ^?b fitted the experimental data. These curves are strongly modified by aerosols–air pollutants, aerosol optical properties, and SZA. The log–log plot of E _dλ/E _bλ versus λ reveals a significant departure from linearity, which is likely to be associated with aerosol physical properties and SZA effects. The effect of atmospheric turbidity, as expressed through the aerosol optical at 500 nm and SZA on the spectral E _dλ/E _bλ ratio, is investigated in detail for two discernible atmospheric conditions observed in the urban Athens atmosphere. The first case includes different atmospheric turbidity levels under the same SZA, while the second corresponds to different SZA values under the same turbidity levels. It was found that the correlation between E _dλ/E _bλ and spectral aerosol optical depth can be a useful tool in determining the aerosol optical properties and aerosol types composition.     

Error sensitivity analysis in 10–30-day extended range forecasting by using a nonlinear cross-prediction error model

Extended range forecasting of 10–30 days, which lies between medium-term and climate prediction in terms of timescale, plays a significant role in decision-making processes for the prevention and mitigation of disastrous meteorological events. The sensitivity of initial error, model parameter error, and random error in a nonlinear crossprediction error (NCPE) model, and their stability in the prediction validity period in 10–30-day extended range forecasting, are analyzed quantitatively. The associated sensitivity of precipitable water, temperature, and geopotential height during cases of heavy rain and hurricane is also discussed. The results are summarized as follows. First, the initial error and random error interact. When the ratio of random error to initial error is small (10^–6–10^–2), minor variation in random error cannot significantly change the dynamic features of a chaotic system, and therefore random error has minimal effect on the prediction. When the ratio is in the range of 10^–1–2 (i.e., random error dominates), attention should be paid to the random error instead of only the initial error. When the ratio is around 10^–2–10^–1, both influences must be considered. Their mutual effects may bring considerable uncertainty to extended range forecasting, and de-noising is therefore necessary. Second, in terms of model parameter error, the embedding dimension m should be determined by the factual nonlinear time series. The dynamic features of a chaotic system cannot be depicted because of the incomplete structure of the attractor when m is small. When m is large, prediction indicators can vanish because of the scarcity of phase points in phase space. A method for overcoming the cut-off effect (m > 4) is proposed. Third, for heavy rains, precipitable water is more sensitive to the prediction validity period than temperature or geopotential height; however, for hurricanes, geopotential height is most sensitive, followed by precipitable water.     

A note on peak-to-mean concentration ratios

The peak-to-mean concentration ratio obtained from observations near a point source of pollution is a particular example of the ratio of any short-period concentration to the long-term mean. The value of this ratio may be obtained from the probability distribution function: $$F(C) = F(0) exp [ - F(0) C/M]$$ whereF(C) is the probability or frequency that the ratio of a short-period average concentration (C) to the long-term mean (M) exceeds the valueC/M, andF(0) is a parameter dependent on the length of the short period and the position of the sampler relative to the centre-line of the plume. From (1) the peak-to-mean concentration ratio is shown to be related to the two averaging times by the expression $$P/M = 1/F(0) [lnF(0) - lnt_M /t_P ]$$ wheret _M andt _P are, respectively, the averaging times of the long-term meanM and the short-term peakP. Using recently published experimental data, Equation (1) and hence also (2) are shown to be valid for averaging timest _P from 5 s to 24 h and oft _M from 6 min to 5 yr providedt _P ?t _M .     

Sensitivity analysis of climatic parameters for sky classification

Climatic variables are frequently used as weighting factors to indicate the degree of clearness for interpreting sky patterns. However, such important parameters are not always widely available and their criteria to define a sky condition are not clear-cut. In addition, certain variables may be more effective than the others in terms of sky identification. This paper studies the capability of various daylight parameters, namely zenith luminance, global, direct-beam and sky-diffuse illuminance, and solar altitude for categorizing the 15 International Commission on Illumination (CIE) standard skies. A new form of artificial neural networks called probabilistic neural network (PNN) which is a powerful technique for pattern recognition was used for the analysis. The findings suggested that the PNN is an appropriate tool when a number of climatic parameters of various criteria for differentiating sky standards are employed, and the ratio of zenith luminance to diffuse illuminance (L _z/D _v) and solar altitude (?? _s) are respectively the most and the least significant input parameters for discriminating between the 15 CIE skies.     

Vertical coherence and phase delay between wind components in strong winds below 20 m

Vertical coherence and phase delay between wind components in strong winds in the lowest 20 m over uniform terrain in New Zealand have been analysed. The vertical decay constants and slopes for the horizontal wind components could be described as linear functions of the ratio of vertical spacing to mean height (δz/z), with relatively little scatter. The decay constants for the lateral were smaller than for the longitudinal components, the slopes larger for the lateral components, as found previously. The coherence of vertical velocity is best described by exponential decay functions multiplied by a parameter which decreases linearly from 1 (for δz/z=0) to 0.5 (for δz/z=1). The decay constants increased linearly with δz/z, as in the case of the horizontal components. There were no significant phase differences for the vertical components. Lateral and vertical decay constants for the longitudinal wind component could be fitted to identical functions of δy/z and δz/z, respectively.     

On clustering of non-stationary meteorological time series

A method for clustering of multidimensional non-stationary meteorological time series is presented. The approach is based on optimization of the regularized averaged clustering functional describing the quality of data representation in terms of several regression models and a metastable hidden process switching between them. Proposed numerical clustering algorithm is based on application of the finite element method (FEM) to the problem of non-stationary time series analysis. The main advantage of the presented algorithm compared to Hidden Markov Models (HMMs) and to finite mixture models is that no a priori assumptions about the probability model for the hidden and observed processes (e.g., Markovianity or stationarity) are necessary for the proposed method. Another attractive numerical feature of the discussed algorithm is the possibility to choose the optimal number of metastable clusters and a natural opportunity to control the fuzziness of the resulting decomposition a posteriory, based on the statistical distinguishability of the resulting persistent cluster states. The resulting FEM-K-trends algorithm is compared with some standard fuzzy clustering methods on toy model examples and on analysis of multidimensional historical temperature data locally in Europe and on the global temperature data set.     

X波段双线偏振气象雷达反射率的衰减订正

X波段天气雷达的强衰减是影响其探测精度与应用推广的主要问题.本文旨在寻求适用于降水过程中对X波段双偏振雷达进行衰减订正的一种方法.在订正前先对雷达数据进行了质量控制和预处理;在分析了国内外已有订正方法的基础上,选择并改进了自适应约束算法作为雷达反射率进行衰减订正的方法;最后进行方法的效果验证.既对衰减订正前后反射率与同...     

An explanation for the difference between twentieth and twenty-first century land–sea warming ratio in climate models

A land–sea surface warming ratio (or φ) that exceeds unity is a robust feature of both observed and modelled climate change. Interestingly, though climate models have differing values for φ, it remains almost time-invariant for a wide range of twenty-first century climate transient warming scenarios, while varying in simulations of the twentieth century. Here, we present an explanation for time-invariant land–sea warming ratio that applies if three conditions on radiative forcing are met: first, spatial variations in the climate forcing must be sufficiently small that the lower free troposphere warms evenly over land and ocean; second, the temperature response must not be large enough to change the global circulation to zeroth order; third, the temperature response must not be large enough to modify the boundary layer amplification mechanisms that contribute to making φ exceed unity. Projected temperature changes over this century are too small to breach the latter two conditions. Hence, the mechanism appears to show why both twenty-first century and time-invariant CO₂ forcing lead to similar values of φ in climate models despite the presence of transient ocean heat uptake, whereas twentieth century forcing—which has a significant spatially confined anthropogenic tropospheric aerosol component that breaches the first condition—leads to modelled values of φ that vary widely amongst models and in time. Our results suggest an explanation for the behaviour of φ when climate is forced by other regionally confined forcing scenarios such as geo-engineered changes to oceanic clouds. Our results show how land–sea contrasts in surface and boundary layer characteristics act in tandem to produce the land–sea surface warming contrast.