Analysis of photosynthetically active radiation and applied parameterization model for estimating of PAR in the North China Plain

As photosynthetically active radiation (PAR) variability and PAR estimating methods play an important role in climate change and ecological process research, PAR variation trends and broadband global solar radiation (R _s ) ratios (PAR/R _s ) in the North China Plain (NCP) are examined using in situ PAR and R _s observed data for 2005 to 2011. The annual average PAR value found in the NCP is 22.9 mol m^?2 d^?1. The highest and lowest values were recorded at Changwu and Luancheng sites, respectively. The highest PAR/R _s value was found in Jiaozhouwan due to large water vapor volumes present in this area. PAR/R _s levels have increased in the NCP due to a decrease in fine aerosols and increase in water vapor concentration. From these analysis results, a parameterization model that can be applied to all sky conditions was checked. Empirical estimation model comparisons for obtaining PAR values indicate that model was least accurate when R _s was used independently. When the model included R _s, the clearness index (K _s) and the solar zenith angle, the model estimated PAR values with acceptable accuracy. A parameterization model was constructed by considering K _s and attenuation factors of PAR under clear weather conditions (ρ _clear). The improved parameterization model more accurately predicts values for local sites and for various observation sites.     

Comprehensive modeling of monthly mean soil temperature using multivariate adaptive regression splines and support vector machine

Soil temperature (T _s) and its thermal regime are the most important factors in plant growth, biological activities, and water movement in soil. Due to scarcity of the T _s data, estimation of soil temperature is an important issue in different fields of sciences. The main objective of the present study is to investigate the accuracy of multivariate adaptive regression splines (MARS) and support vector machine (SVM) methods for estimating the T _s. For this aim, the monthly mean data of the T _s (at depths of 5, 10, 50, and 100 cm) and meteorological parameters of 30 synoptic stations in Iran were utilized. To develop the MARS and SVM models, various combinations of minimum, maximum, and mean air temperatures (T _min, T _max, T); actual and maximum possible sunshine duration; sunshine duration ratio (n, N, n/N); actual, net, and extraterrestrial solar radiation data (R _s, R _n, R _a); precipitation (P); relative humidity (RH); wind speed at 2 m height (u ₂); and water vapor pressure (V_p) were used as input variables. Three error statistics including root-mean-square-error (RMSE), mean absolute error (MAE), and determination coefficient (R ²) were used to check the performance of MARS and SVM models. The results indicated that the MARS was superior to the SVM at different depths. In the test and validation phases, the most accurate estimations for the MARS were obtained at the depth of 10 cm for T _max, T _min, T inputs (RMSE = 0.71 °C, MAE = 0.54 °C, and R ² = 0.995) and for RH, V _p, P, and u ₂ inputs (RMSE = 0.80 °C, MAE = 0.61 °C, and R ² = 0.996), respectively.     

High-stability algorithm for the three-pattern decomposition of global atmospheric circulation

The study investigates the reliable computation time (RCT, termed as T _c) by applying a double-precision computation of a variable parameters logistic map (VPLM). Firstly, by using the proposed method, we obtain the reliable solutions for the logistic map. Secondly, we construct 10,000 samples of reliable experiments from a time-dependent non-stationary parameters VPLM and then calculate the mean T _c. The results indicate that, for each different initial value, the T _cs of the VPLM are generally different. However, the mean T _c trends to a constant value when the sample number is large enough. The maximum, minimum, and probable distribution functions of T _c are also obtained, which can help us to identify the robustness of applying a nonlinear time series theory to forecasting by using the VPLM output. In addition, the T _c of the fixed parameter experiments of the logistic map is obtained, and the results suggest that this T _c matches the theoretical formula-predicted value.     

Drivers of the Severity of the Extreme Hot Summer of 2015 in Western China

Western China experienced an extreme hot summer in 2015, breaking a number of temperature records. The summer mean surface air temperature (SAT) anomaly was twice the interannual variability. The hottest daytime temperature (T_Xx) and warmest night-time temperature (T_Nx) were the highest in China since 1964. This extreme hot summer occurred in the context of steadily increasing temperatures in recent decades. We carried out a set of experiments to evaluate the extent to which the changes in sea surface temperature (SST)/sea ice extent (SIE) and anthropogenic forcing drove the severity of the extreme summer of 2015 in western China. Our results indicate that about 65%–72% of the observed changes in the seasonal mean SAT and the daily maximum (T_max) and daily minimum (T_min) temperatures over western China resulted from changes in boundary forcings, including the SST/SIE and anthropogenic forcing. For the relative role of individual forcing, the direct impact of changes in anthropogenic forcing explain about 42% of the SAT warming and 60% (40%) of the increase in T_Nx and Tmin (T_Xx and T_max) in the model response. The changes in SST/SIE contributed to the remaining surface warming and the increase in hot extremes, which are mainly the result of changes in the SST over the Pacific Ocean, where a super El Niño event occurred. Our study indicates a prominent role for the direct impact of anthropogenic forcing in the severity of the extreme hot summer in western China in 2015, although the changes in SST/SIE, as well as the internal variability of the atmosphere, also made a contribution.     

Relationship Between Fine-Particle Pollution and the Urban Heat Island in Beijing,China: Observational Evidence

Urbanization has led to a significant urban heat island (UHI) effect in Beijing in recent years. At the same time, air pollution caused by a large number of fine particles significantly influences the atmospheric environment, urban climate, and human health. The distribution of fine particulate matter (PM_2.5) concentration and its relationship with the UHI effect in the Beijing area are analyzed based on station-observed hourly data from 2012 to 2016. We conclude that, (1) in the last five years, the surface concentrations of PM_2.5 averaged for urban and rural sites in and around Beijing are 63.2 and 40.7 µg m^?3, respectively, with significant differences between urban and rural sites (ΔPM_2.5) at the seasonal, monthly and daily scales observed; (2) there is a large correlation between ΔPM_2.5 and the UHI intensity defined as the differences in the mean (ΔT_ave), minimum (ΔT_min), and maximum (ΔT_max) temperatures between urban and rural sites. The correlation between ΔPM_2.5 and ΔT_min (ΔT_max) is the highest (lowest); (3) a Granger causality analysis further shows that ΔPM_2.5 and ΔT_min are most correlated for a lag of 1–2 days, while the correlation between ΔPM_2.5 and ΔT_ave is lower; there is no causal relationship between ΔPM_2.5 and ΔT_max; (4) a case analysis shows that downwards shortwave radiation at the surface decreases with an increase in PM_2.5 concentration, leading to a weaker UHI intensity during the daytime. During the night, the outgoing longwave radiation from the surface decreases due to the presence of daytime pollutants, the net effect of which is a slower cooling rate during the night in cities than in the suburbs, leading to a larger ΔT_min.     

A compact form for the analytic description of temperature dependence of saturation vapor pressure over plane surfaces of water and ice

A possibility is studied of extending the range of action of the simple three-parameter formula (ITS-90 scale) proposed in the previous work of the author [2] for the dependence of saturation vapor pressure E on temperature T within the range of 250 to 490 K. The results demonstrated that the dependence ln[E(T)/E(T _bas)] = (T - T _bas)[A - B(T - T _bas) + C(T - T _bas)²]/T with four sets of coefficients A, B, and C obtained using one base temperature Tbas equal to the temperature of triple point of water T _t = 273.16 K and two additional base values T _bas2 = 473.16 K and T _bas3 = 623.16 K makes it possible to approximate rather accurately the initial experimental and computed data in the temperature range from the point of homogeneous freezing of 235 K to the critical temperature of 647 K for liquid water and from 193 K to T _t for ice. A procedure used for obtaining the inverse function T(E) by solving the third-degree algebraic equation is validated. A hypothesis is proposed for the physical substantiation of additional base points in the form of “a noticeable appearance of dimers at the point T _bas2 and their 100% concentration at the temperature T _bas3.”     

Atmospheric circulation epochs and climate changes

The atmospheric circulation studies allow climate changes to be diagnosed and forecasted. Variations in occurrence frequencies of the atmospheric circulation forms W, E, and C (by the Vangengeim classification) and Z, M ₁, and M ₂ (by the Girs classification), which characterize climatic conditions in most of the Northern Hemisphere, are analyzed over a period of more than 100 years. It is shown that the occurrence frequency of the forms W, C, and M ₁ continually decreased, while that of the forms E and Z increased, which indicates a significant change in atmospheric circulation in the Northern Hemisphere during the last century. The occurrence frequency of the forms C and Z demonstrates specific features at inter-decade time scales. Correlations are found between accumulated sums of anomalies of occurrence frequencies of the atmospheric circulation forms C, (W + E), Z, and (M ₁ + M ₂) and inter-decade variations of the Earth’s rotation. The causes of these relationships are discussed along with possibilities of their use for diagnosis of climatic variations in the Northern Hemisphere.     

Long-term variation of rainfall erosivity in Calabria (Southern Italy)

The changes in rainfall erosivity have been investigated using the rainfall erosivity factor (R) proposed for USLE by Wischmeier and Smith (R _W-S ) and some simplified indexes (the Fournier index modified by Arnoldus, F, a regional index spatial independent, R _Fr , and a regional index spatial dependent, R _Fs ) estimated by indirect approaches. The analysis has been carried out over 48 rainfall stations located in Calabria (Southern Italy) using data collected in the period 1936–2012 and divided in three sub-periods. The series of the erosivity indexes and of some precipitation variables have been analyzed for evidence of trends using standard methods. The simplified indexes suggested a general underestimation of the rainfall erosivity with respect to R _W-S . The mean underestimation ranged between 23 and 54 % for R _Fr and from 10 to 15 % for R _Fs . Both the sign and the magnitude of the trends were different for the different stations depending on the variable and sub-period considered. In general, the erosivity increased during the period 1936–1955 (1^st sub-period) and during the more recent sub-period (1992–2012, 3^rd sub-period), whereas it decreased during 1958–1977 (2^nd sub-period). The evidence of trends was generally higher for R _W-S than for R _Fr and R _Fs . Focusing on the most recent sub-period (3^rd sub-period), all the variables analyzed showed mainly increasing trends but with different magnitude. More particularly, R _W-S showed a mean increment of 29 %; F, R _Fr and R _Fs increased by 11, 15 and 18 %, respectively; the maximum intensity of 0.5-h precipitation increased by 5 %; and the annual precipitation increased by 22 %. Consequently, it remains difficult to define which precipitation variable plays the dominant role in the temporal variation of rainfall erosivity in the region. However, the overall results suggest that the indexes estimated by indirect procedures (F, R _Fr , and R _Fs ) should be used with caution for climate change analysis, despite they are used for practical purposes considering they are based on easily available information.     

Formulation of stability-dependent empirical relations for turbulent intensities from surface layer turbulence measurements for dispersion parameterization in a lagrangian particle dispersion model

Season- and stability-dependent turbulence intensity (σ _u /u _*, σ _v /u _*, σ _w /u _*) relationships are derived from experimental turbulence measurements following surface layer scaling and local stability at the tropical coastal site Kalpakkam, India for atmospheric dispersion parameterization. Turbulence wind components (u′, v′, w′) measured with fast response UltraSonic Anemometers during an intense observation campaign for wind field modeling called Round Robin Exercise are used to formulate the flux–profile relationships using surface layer similarity theory and Fast Fourier Transform technique. The new relationships (modified Hanna scheme) are incorporated in a Lagrangian Particle Dispersion model FLEXPART-WRF and tested by conducting simulations for a field tracer dispersion experiment at Kalpakkam. Plume dispersion analysis of a ground level hypothetical release indicated that the new turbulent intensity formulations provide slightly higher diffusivity across the plume relative to the original Hanna scheme. The new formulations for σ _u , σ _v , σ _w are found to give better agreement with observed turbulent intensities during both stable and unstable conditions under various seasonal meteorological conditions. The simulated concentrations using the two methods are compared with those obtained from a classical Gaussian model and the observed SF₆ concentration. It has been found that the new relationships provide comparatively higher diffusion across the plume relative to the model default Hanna scheme and provide downwind concentration results in better agreement with observations.     

Effects of optimized root water uptake parameterization schemes on water and heat flux simulation in a maize agroecosystem

As root water uptake (RWU) is an important link in the water and heat exchange between plants and ambient air, improving its parameterization is key to enhancing the performance of land surface model simulations. Although different types of RWU functions have been adopted in land surface models, there is no evidence as to which scheme most applicable to maize farmland ecosystems. Based on the 2007–09 data collected at the farmland ecosystem field station in Jinzhou, the RWU function in the Common Land Model (CoLM) was optimized with scheme options in light of factors determining whether roots absorb water from a certain soil layer (W_x) and whether the baseline cumulative root efficiency required for maximum plant transpiration (W_c) is reached. The sensibility of the parameters of the optimization scheme was investigated, and then the effects of the optimized RWU function on water and heat flux simulation were evaluated. The results indicate that the model simulation was not sensitive to W_x but was significantly impacted by W_c. With the original model, soil humidity was somewhat underestimated for precipitation-free days; soil temperature was simulated with obvious interannual and seasonal differences and remarkable underestimations for the maize late-growth stage; and sensible and latent heat fluxes were overestimated and underestimated, respectively, for years with relatively less precipitation, and both were simulated with high accuracy for years with relatively more precipitation. The optimized RWU process resulted in a significant improvement of CoLM’s performance in simulating soil humidity, temperature, sensible heat, and latent heat, for dry years. In conclusion, the optimized RWU scheme available for the CoLM model is applicable to the simulation of water and heat flux for maize farmland ecosystems in arid areas.     

Uncertainty of global summer precipitation in the CMIP5 models: a comparison between high-resolution and low-resolution models

Worldwide, the majority of rapidly growing neighborhoods are found in the Global South. They often exhibit different building construction and development patterns than the Global North, and urban climate research in many such neighborhoods has to date been sparse. This study presents local-scale observations of net radiation (Q _* ) and sensible heat flux (Q _H ) from a lightweight low-rise neighborhood in the desert climate of Andacollo, Chile, and compares observations with results from a process-based urban energy-balance model (TUF3D) and a local-scale empirical model (LUMPS) for a 14-day period in autumn 2009. This is a unique neighborhood-climate combination in the urban energy-balance literature, and results show good agreement between observations and models for Q _* and Q _H . The unmeasured latent heat flux (Q _E ) is modeled with an updated version of TUF3D and two versions of LUMPS (a forward and inverse application). Both LUMPS implementations predict slightly higher Q _E than TUF3D, which may indicate a bias in LUMPS parameters towards mid-latitude, non-desert climates. Overall, the energy balance is dominated by sensible and storage heat fluxes with mean daytime Bowen ratios of 2.57 (observed Q _H /LUMPS Q _E )–3.46 (TUF3D). Storage heat flux (ΔQ _S ) is modeled with TUF3D, the empirical objective hysteresis model (OHM), and the inverse LUMPS implementation. Agreement between models is generally good; the OHM-predicted diurnal cycle deviates somewhat relative to the other two models, likely because OHM coefficients are not specified for the roof and wall construction materials found in this neighborhood. New facet-scale and local-scale OHM coefficients are developed based on modeled ΔQ _S and observed Q _* . Coefficients in the empirical models OHM and LUMPS are derived from observations in primarily non-desert climates in European/North American neighborhoods and must be updated as measurements in lightweight low-rise (and other) neighborhoods in various climates become available.     

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.     

Velocity Adjustment and Passive Scalar Diffusion in and Above an Urban Canopy in Response to Various Approach Flows

We used wind-tunnel experiments to investigate velocity-field adjustment and scalar diffusion behaviour in and above urban canopies located downwind of various roughness elements. Staggered arrays of rectangular blocks of various heights H and plan area ratios λ_p were used to model the urban canopies. The velocity field in the roughness sublayer (height \({z \lesssim 2H}\)) reached equilibrium at distances proportional to \({\sqrt{L_{\rm c}H}}\) where L _c is the canopy-drag length scale determined as a function of λ_p and the block side length L. A distance of about \({20\sqrt{L_{\rm c}H}}\) was required for adjustment at z = H/2 (in the canopy), and a distance of about \({10\sqrt{L_{\rm c}H}}\) was required at z = 2H (near the top of the roughness sublayer). Diffusion experiments from a ground emission source revealed that differences in upwind roughness conditions had negligible effects on the plume growth near the source (up to a few multiples of L from the source) if the source was located at a fetch F larger than about \({10\sqrt{L_{\rm c}H}}\) from the upwind edge of the canopy. However, at locations farther downwind (more than several multiples of L from the source), upwind conditions had considerable effects on the plume growth. For a representative urban canopy, it was shown that a much larger fetch than required for velocity-field adjustment in the roughness sublayer was necessary to eliminate the effects of upwind conditions on plume widths at 24L downwind from the source.     

Influence of water vapor and aerosol on the integral transparency of the atmosphere

The temporal variability of the total atmospheric water content W and the connection of the coefficient of integral transparency P ₂, reduced to the air mass m = 2, with W and aerosol optical depth τ _a ,λ₀ at a wavelength of 550 nm were analyzed and studied from the observational data of the Meteorological Observatory of Moscow State University for 50 years (1955–2004). The regression equations between mean daily and monthly τ _a ,λ₀ and τ₂ = ?ln P ₂ were derived in different months and seasons and can be used for retrieving τ _a ,λ₀ from the coefficient of the integral transparency for the temperate latitudes. The P ₂ intervals are given for which these equations can be used.     

Multivariate drought frequency estimation using copula method in Southwest China

This study reveals the impacts of climatic variable trends on drought severity in Xinjiang, China. Four drought indices, including the self-calibrating Palmer drought severity index (sc-PDSI), Erinç’s index (I _m), Sahin’s index (I _sh), and UNEP aridity index (AI), were used to compare drought severity. The ensemble empirical mode decomposition and the modified Mann-Kendall trend test were applied to analyze the nonlinear components and trends of the climatic variable and drought indices. Four and six climatic scenarios were generated in sc-PDSI, I _m, I _sh, and AI with different combinations of the observed and detrended climatic variables, respectively. In Xinjiang, generally increasing trends in minimal, average, and maximal air temperature (T _min, T _ave, T _max) and precipitation (P) were found, whereas a decreasing trend in wind speed at 2 m height (U ₂) was observed. There were significantly increasing trends in all of the four studied drought indices. Drought relief was more obvious in northern Xinjiang than in southern Xinjiang. The strong influences of increased P on drought relief and the weak influences of increased T _min, T _ave, and T _max on drought aggravation were shown by comparing four drought indices under different climate scenarios. Decreased U ₂ had a weak influence on drought, as shown by the AI in different climate scenarios. The weak influences of T and U ₂ were considered to be masked by the strong influences of P on droughts. Droughts were expected to be more severe if P did not increase, but were likely milder without an increase in air temperature and with a decrease in U ₂.     

A new approach to identify the sensitivity and importance of physical parameters combination within numerical models using the Lund–Potsdam–Jena (LPJ) model as an example

Daily global solar irradiation (R _s) is one of the main inputs in environmental modeling. Because of the lack of its measuring facilities, high-quality and long-term data are limited. In this research, R _s values were estimated based on measured sunshine duration and cloud cover of our synoptic meteorological stations in central and southern Iran during 2008, 2009, and 2011. Clear sky solar irradiation was estimated from linear regression using extraterrestrial solar irradiation as the independent variable with normalized root mean square error (NRMSE) of 4.69 %. Daily R _s was calibrated using measured sunshine duration and cloud cover data under different sky conditions during 2008 and 2009. The 2011 data were used for model validation. According to the results, in the presence of clouds, the R _s model using sunshine duration data was more accurate when compared with the model using cloud cover data (NRMSE = 11. 69 %). In both models, with increasing sky cloudiness, the accuracy decreased. In the study region, more than 92 % of sunshine durations were clear or partly cloudy, which received close to 95 % of total solar irradiation. Hence, it was possible to estimate solar irradiation with a good accuracy in most days with the measurements of sunshine duration.     

Modeling monthly meteorological and agronomic frost days,based on minimum air temperature,in Center-Southern Brazil

Although Brazil is predominantly a tropical country, frosts are observed with relative high frequency in the Center-Southern states of the country, affecting mainly agriculture, forestry, and human activities. Therefore, information about the frost climatology is of high importance for planning of these activities. Based on that, the aims of the present study were to develop monthly meteorological (F _MET) and agronomic (F _AGR) frost day models, based on minimum shelter air temperature (T _MN), in order to characterize the temporal and spatial frost days variability in Center-Southern Brazil. Daily minimum air temperature data from 244 weather stations distributed across the study area were used, being 195 for developing the models and 49 for validating them. Multivariate regression models were obtained to estimate the monthly T _MN, once the frost day models were based on this variable. All T _MN regression models were statistically significant (p < 0.001), presenting adjusted R ² between 0.69 and 0.90. Center-Southern Brazil is mainly hit by frosts from mid-fall (April) to mid-spring (October). The period from November to March is considered as frost-free, being very rare a frost day within that period. Monthly F _MET and F _AGR presented significant sigmoidal relationships with T _MN (p < 0.0001), with adjusted R ² above of 0.82. The residuals of the frost day models were random, which means that the sigmoidal models performed quite well for interpreting the frost day variability throughout the study area. The highlands of Santa Catarina, Rio Grande do Sul, São Paulo, and Minas Gerais had in average more than 25 and 13 frosts per year, respectively, for F _MET and F _AGR. The F _MET and F _AGR maps developed in this study for Center-Southern Brazil is a useful tool for farmers, foresters, and researchers, since they contribute to reduce frost spatial and temporal uncertainty, helping in planning project for strategic purposes. Furthermore, the monthly F _MET and F _AGR maps for this Brazilian region are the first zoning of these variables for the country.     

Polarimetric rainfall retrieval from a C-Band weather radar in a tropical environment (The Philippines)

We evaluated the potential of polarimetric rainfall retrieval methods for the Tagaytay C-Band weather radar in the Philippines. For this purpose, we combined a method for fuzzy echo classification, an approach to extract and reconstruct the differential propagation phase, Φ _DP , and a polarimetric self-consistency approach to calibrate horizontal and differential reflectivity. The reconstructed Φ _DP was used to estimate path-integrated attenuation and to retrieve the specific differential phase, K _DP . All related algorithms were transparently implemented in the Open Source radar processing software wradlib. Rainfall was then estimated from different variables: from re-calibrated reflectivity, from re-calibrated reflectivity that has been corrected for path-integrated attenuation, from the specific differential phase, and from a combination of reflectivity and specific differential phase. As an additional benchmark, rainfall was estimated by interpolating the rainfall observed by rain gauges. We evaluated the rainfall products for daily and hourly accumulations. For this purpose, we used observations of 16 rain gauges from a five-month period in the 2012 wet season. It turned out that the retrieval of rainfall from K _DP substantially improved the rainfall estimation at both daily and hourly time scales. The measurement of reflectivity apparently was impaired by severe miscalibration while K _DP was immune to such effects. Daily accumulations of rainfall retrieved from K _DP showed a very low estimation bias and small random errors. Random scatter was, though, strongly present in hourly accumulations.     

Wind-Speed Undulations Over Swell: Field Experiment and Interpretation

Results of field measurements of the swell-induced undulation of the wind speed taken from a Black Sea platform are presented. The wind speed and its fluctuations were measured at several heights between 1.3 and 21 m above the mean sea level under various wind and swell conditions. Parameters of the swell-induced undulations were derived from cross spectra of the wind-speed fluctuations and the sea-surface displacement. As found, the phase and the amplitude of the wind speed undulation in the layer from k _p z = 0.1 to k _p z = 3 (k _p is the swell wavenumber) are in good agreement with the theory of inviscid shear flow over a wavy surface. The main feature of the vertical profile of the swell-induced undulation is the exponential attenuation of its amplitude with height typical for the potential flow over the fast running waves. At the lowest levels the potential undulations are significantly distorted by the wind-speed variations caused by the vertical displacements of the shear airflow relative to a fixed sensor. No direct impact of swell on the mean properties of the turbulent boundary layer at k _p z > 0.1 is revealed. In particular, the mean wind-speed profile and spectra of the horizontal velocity in the inertial subrange obey Monin-Obukhov similarity theory.     

Improving Representation of Tropical Cloud Overlap in GCMs Based on Cloud-Resolving Model Data

The decorrelation length (L_cf) has been widely used to describe the behavior of vertical overlap of clouds in general circulation models (GCMs); however, it has been a challenge to associate L_cf with the large-scale meteorological conditions during cloud evolution. This study explored the relationship between L_cf and the strength of atmospheric convection in the tropics based on output from a global cloud-resolving model. L_cf tends to increase with vertical velocity in the mid-troposphere (w₅₀₀) at locations of ascent, but shows little or no dependency on w₅₀₀ at locations of descent. A representation of L_cf as a function of vertical velocity is obtained, with a linear regression in ascending regions and a constant value in descending regions. This simple and dynamic-related representation of L_cf leads to a significant improvement in simulation of both cloud cover and radiation fields compared with traditional overlap treatments. This work presents a physically justifiable approach to depicting cloud overlap in the tropics in GCMs.