Hourly estimation of soil heat flux density at the soil surface with three models and two field methods

Heat flux density at the soil surface (G ₀) was evaluated hourly on a vegetal cover 0.08 m high, with a leaf area index of 1.07 m² m^?2, during daylight hours, using Choudhury et al. (Agric For Meteorol 39:283–297, 1987) ( $ G_0^{\text{rn}} $ ), Santanello and Friedl (J Appl Meteorol 42:851–862, 2003) ( $ G_0^{\text{s}} $ ), and force-restore ( $ G_0^{\text{fr}} $ ) models and the plate calorimetry methodology ( $ G_0^{\text{pco}} $ ), where the gradient calorimetry methodology (G _0R ) served as a reference for determining G ₀. It was found that the peak of G _0R was at 1 p.m., with values that ranged between 60 and 100 W m^?2 and that the G ₀/Rn relation varied during the day with values close to zero in the early hours of the morning and close to 0.25 in the last hours of daylight. The $ G_0^{\text{s}} $ model presented the best performance, followed by the $ G_0^{\text{rn}} $ and $ G_0^{\text{fr}} $ models. The plate calorimetry methodology showed a similar behavior to that of the gradient calorimetry referential methodology.     

Aerodynamic Roughness Length of Fresh Snow

This study presents the results from a series of wind-tunnel experiments designed to investigate the aerodynamic roughness length z ₀ of fresh snow under no-drift conditions. A two-component hot-film anemometer was employed to obtain vertical profiles of velocity statistics in a zero pressure gradient turbulent boundary layer for flow over naturally deposited snow surfaces. The roughness of these snow surfaces was measured by means of digital photography to capture characteristic length scales that can be related to z ₀. Our results show that, under aerodynamically rough conditions, the mean value of the roughness length for fresh snow is \({\langle{z}_{0}\rangle= 0.24}\) mm with a standard deviation σ(z ₀) = 0.05 mm. In this study, we show that variations in z ₀ are associated with variations in the roughness geometry. The roughness measurements suggest that the estimated values of z ₀ are consistent with the presence of irregular roughness structures that develop during snowfalls that mimic ballistic deposition processes.     

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.     

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.     

New alternatives for reference evapotranspiration estimation in West Africa using limited weather data and ancillary data supply strategies.

Accurate estimation of reference evapotranspiration (ET ₀ ) is essential for the computation of crop water requirements, irrigation scheduling, and water resources management. In this context, having a battery of alternative local calibrated ET ₀ estimation methods is of great interest for any irrigation advisory service. The development of irrigation advisory services will be a major breakthrough for West African agriculture. In the case of many West African countries, the high number of meteorological inputs required by the Penman-Monteith equation has been indicated as constraining. The present paper investigates for the first time in Ghana, the estimation ability of artificial intelligence-based models (Artificial Neural Networks (ANNs) and Gene Expression Programing (GEPs)), and ancillary/external approaches for modeling reference evapotranspiration (ET ₀ ) using limited weather data. According to the results of this study, GEPs have emerged as a very interesting alternative for ET ₀ estimation at all the locations of Ghana which have been evaluated in this study under different scenarios of meteorological data availability. The adoption of ancillary/external approaches has been also successful, moreover in the southern locations. The interesting results obtained in this study using GEPs and some ancillary approaches could be a reference for future studies about ET ₀ estimation in West Africa.     

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.     

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.     

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.     

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.     

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.     

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.     

Characteristics of Turbulent Transfer during Episodes of Heavy Haze Pollution in Beijing in Winter 2016/17

We analyzed the structure and evolution of turbulent transfer and the wind profile in the atmospheric boundary layer in relation to aerosol concentrations during an episode of heavy haze pollution from 6 December 2016 to 9 January 2017. The turbulence data were recorded at Peking University’s atmospheric science and environment observation station. The results showed a negative correlation between the wind speed and the PM_2.5 concentration. The turbulence kinetic energy was large and showed obvious diurnal variations during unpolluted (clean) weather, but was small during episodes of heavy haze pollution. Under both clean and heavy haze conditions, the relation between the non-dimensional wind components and the stability parameter z/L followed a 1/3 power law, but the normalized standard deviations of the wind speed were smaller during heavy pollution events than during clean periods under near-neutral conditions. Under unstable conditions, the normalized standard deviation of the potential temperature σ _θ /|θ_*| was related to z/L, roughly following a –1/3 power law, and the ratio during pollution days was greater than that during clean days. The three-dimensional turbulence energy spectra satisfied a –2/3 power exponent rate in the high-frequency band. In the low-frequency band, the wind velocity spectrum curve was related to the stability parameters under clear conditions, but was not related to atmospheric stratification under polluted conditions. In the dissipation stage of the heavy pollution episode, the horizontal wind speed first started to increase at high altitudes and then gradually decreased at lower altitudes. The strong upward motion during this stage was an important dynamic factor in the dissipation of the heavy haze.     

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.     

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.”     

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.     

Trend analysis of rainfall time series for Sindh river basin in India

The main goal of this paper is to estimate a set of optimal seasonal, daily, and hourly values of atmospheric turbidity and surface radiative parameters Ångström’s turbidity coefficient (β), Ångström’s wavelength exponent (α), aerosol single scattering albedo (ω_o), forward scatterance (F_c) and average surface albedo (ρ_g), using the Brute Force multidimensional minimization method to minimize the difference between measured and simulated solar irradiance components, expressed as cost functions. In order to simulate the components of short-wave solar irradiance (direct, diffuse and global) for clear sky conditions, incidents on a horizontal surface in the Metropolitan Area of Rio de Janeiro (MARJ), Brazil (22° 51′ 27″ S, 43° 13′ 58″ W), we use two parameterized broadband solar irradiance models, called CPCR2 and Iqbal C, based on synoptic information. The meteorological variables such as precipitable water (u_w) and ozone concentration (u_o) required by the broadband solar models were obtained from moderate-resolution imaging spectroradiometer (MODIS) sensor on Terra and Aqua NASA platforms. For the implementation and validation processes, we use global and diffuse solar irradiance data measured by the radiometric platform of LabMiM, located in the north area of the MARJ. The data were measured between the years 2010 and 2012 at 1-min intervals. The performance of solar irradiance models using optimal parameters was evaluated with several quantitative statistical indicators and a subset of measured solar irradiance data. Some daily results for Ångström’s wavelength exponent α were compared with Ångström’s parameter (440–870 nm) values obtained by aerosol robotic network (AERONET) for 11 days, showing an acceptable level of agreement. Results for Ångström’s turbidity coefficient β, associated with the amount of aerosols in the atmosphere, show a seasonal pattern according with increased precipitation during summer months (December–February) in the MARJ.     

Effect of solubility limitation on hygroscopic growth and cloud drop activation of SOA particles produced from traffic exhausts

Hygroscopicity measurements of secondary organic aerosol (SOA) particles often show inconsistent results between the supersaturated and subsaturated regimes, with higher activity as cloud condensation nucleus (CCN) than indicated by hygroscopic growth. In this study, we have investigated the discrepancy between the two regimes in the Lund University (LU) smog chamber. Various anthropogenic SOA were produced from mixtures of different precursors: anthropogenic light aromatic precursors (toluene and m-xylene), exhaust from a diesel passenger vehicle spiked with the light aromatic precursors, and exhaust from two different gasoline-powered passenger vehicles. Three types of seed particles were used: soot aggregates from a diesel vehicle, soot aggregates from a flame soot generator and ammonium sulphate (AS) particles. The hygroscopicity of seed particles with condensed, photochemically produced, anthropogenic SOA was investigated with respect to critical supersaturation (s_c) and hygroscopic growth factor (gf) at 90% relative humidity. The hygroscopicity parameter κ was calculated for the two regimes: κ_sc and κ_gf, from measurements of s_c and gf, respectively. The two κ showed significant discrepancies, with a κ_gf /κ_sc ratio closest to one for the gasoline experiments with ammonium sulphate seed and lower for the soot seed experiments. Empirical observations of s_c and gf were compared to theoretical predictions, using modified Köhler theory where water solubility limitations were taken into account. The results indicate that the inconsistency between measurements in the subsaturated and supersaturated regimes may be explained by part of the organic material in the particles produced from anthropogenic precursors having a limited solubility in water.     

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.     

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.     

Projected Changes in Extreme High Temperature and Heat Stress in China

High temperature accompanied with high humidity may result in unbearable and oppressive weather. In this study, future changes of extreme high temperature and heat stress in mainland China are examined based on daily maximum temperature (T_x) and daily maximum wet-bulb globe temperature (T_w). T_w has integrated the effects of both temperature and humidity. Future climate projections are derived from the bias-corrected climate data of five general circulation models under the Representative Concentration Pathways (RCPs) 2.6 and 8.5 scenarios. Changes of hot days and heat waves in July and August in the future (particularly for 2020–50 and 2070–99), relative to the baseline period (1981–2010), are estimated and analyzed. The results show that the future T_x and T_w of entire China will increase by 1.5–5°C on average around 2085 under different RCPs. Future increases in T_x and T_w exhibit high spatial heterogeneity, ranging from 1.2 to 6°C across different regions and RCPs. By around 2085, the mean duration of heat waves will increase by 5 days per annum under RCP8.5. According to T_x, heat waves will mostly occur in Northwest and Southeast China, whereas based on T_w estimates, heat waves will mostly occur over Southeast China and the mean heat wave duration will be much longer than those from T_x. The total extreme hot days (T_x or T_w > 35°C) will increase by 10–30 days. Southeast China will experience the severest heat stress in the near future as extreme high temperature and heat waves will occur more often in this region, which is particularly true when heat waves are assessed based on T_w. In comparison to those purely temperature-based indices, the index T_w provides a new perspective for heat stress assessment in China.