A New method for identifying possible causal relationships between CO2, total solar irradiance and global temperature change

The study compares two formulas for calculating the daily evapotranspiration ET₀ for a reference crop. The first formula was proposed by Allen et al. (AL), while the second one was proposed by Katerji and Perrier with the addition of the carbon dioxide (CO₂) effect on evapotranspiration (KP). The study analyses the impact of the calculation by the two formulas on the irrigation requirement (IR). Both formulas are based on the Penman-Monteith equation but adopt different approaches for parameterising the canopy resistance r _c . In the AL formula, r _c is assumed constant and not sensitive to climate change, whereas in the KP formula, r _c is first parameterised as a function of climatic variables, then ET₀ is corrected for the air CO₂ concentration. The two formulas were compared in two periods. The first period involves data from two sites in the Mediterranean region within a measured climate change period (1981–2006) when all the input climatic variables were measured. The second period (2070–2100) involves data from a future climate change period at one site when the input climatic variables were forecasted for two future climate scenarios (A2 and B2). The annual cumulated values of ET₀ calculated by the AL formula are systematically lower than those determined by the KP formula. The differences between the ET₀ estimation with the AL and KP formulas have a strong impact on the determination of the IR for the reference crop. In fact, for the two periods, the annual values of IR when ET₀ is calculated by the AL formula are systematically lower than those calculated by the KP formula. For the actual measured climate change period, this reduction varied from 26 to 28 %, while for the future climate change period, it varied based on the scenario from 16 % (A2) to 20 % (B2).     

Trend of monthly temperature and daily extreme temperature during 1951–2012 in New Zealand

A new method for calculating evaporation is proposed, using the Penman–Monteith (P-M) model with remote sensing. This paper achieved the effective estimation to daily evapotranspiration in the Ziya river catchment by using the P-M model based on MODIS remote sensing leaf area index and respectively estimated plant transpiration and soil evaporation by using coefficient of soil evaporation. This model divided catchment into seven different sub-regions which are prairie, meadow, grass, shrub, broad-leaved forest, cultivated vegetation, and coniferous forest through thoroughly considering the vegetation diversity. Furthermore, optimizing and calibrating parameters based on each sub-region and analyzing spatio-temporal variation rules of the model main parameters which are coefficient of soil evaporation f and maximum stomatal conductance g _sx . The results indicate that f and g _sx calibrated by model are basically consistent with measured data and have obvious spatio-temporal distribution characteristics. The monthly average evapotranspiration value of simulation is 37.96 mm/mon which is close to the measured value with 33.66 mm/mon and the relative error of simulation results in each subregion are within 11 %, which illustrates that simulated values and measured values fit well and the precision of model is high. In addition, plant transpiration and soil evaporation account for about 84.64 and 15.36 % respectively in total evapotranspiration, which means the difference between values of them is large. What is more, this model can effectively estimate the green water resources in basin and provide effective technological support for water resources estimation.     

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.     

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.     

Estimation of ground heat flux from soil temperature over a bare soil

Ground soil heat flux, G ₀, is a difficult-to-measure but important component of the surface energy budget. Over the past years, many methods were proposed to estimate G ₀; however, the application of these methods was seldom validated and assessed under different weather conditions. In this study, three popular models (force-restore, conduction-convection, and harmonic) and one widely used method (plate calorimetric), which had well performance in publications, were investigated using field data to estimate daily G ₀ on clear, cloudy, and rainy days, while the gradient calorimetric method was regarded as the reference for assessing the accuracy. The results showed that harmonic model was well reproducing the G ₀ curve for clear days, but it yielded large errors on cloudy and rainy days. The force-restore model worked well only under rainfall condition, but it was poor to estimate G ₀ under rain-free conditions. On the contrary, the conduction-convection model was acceptable to determine G ₀ under rain-free conditions, but it generated large errors on rainfall days. More importantly, the plate calorimetric method was the best to estimate G ₀ under different weather conditions compared with the three models, but the performance of this method is affected by the placement depth of the heat flux plate. As a result, the heat flux plate was recommended to be buried as close as possible to the surface under clear condition. But under cloudy and rainy conditions, the plate placed at depth of around 0.075 m yielded G ₀ well. Overall, the findings of this paper provide guidelines to acquire more accurate estimation of G ₀ under different weather conditions, which could improve the surface energy balance in field.     

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.     

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.”     

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.     

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.     

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.     

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.     

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.     

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.     

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.     

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.     

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.     

Investigation of Primary Factors Affecting the Variation of Modeled Oak Pollen Concentrations: A Case Study for Southeast Texas in 2010

Oak pollen concentrations over the Houston-Galveston-Brazoria (HGB) area in southeastern Texas were modeled and evaluated against in-situ data. We modified the Community Multi-scale Air Quality (CMAQ) model to include oak pollen emission, dispersion, and deposition. The Oak Pollen Emission Model (OPEM) calculated gridded oak pollen emissions, which are based on a parameterized equation considering a plant-specific factor (C _e ), surface characteristics, and meteorology. The simulation period was chosen to be February 21 to April 30 in the spring of 2010, when the observed monthly mean oak pollen concentrations were the highest in six years (2009-2014). The results indicated C _e and meteorology played an important role in the calculation of oak pollen emissions. While C _e was critical in determining the magnitude of oak pollen emissions, meteorology determined their variability. In particular, the contribution of the meteorology to the variation in oak pollen emissions increased with the oak pollen emission rate. The evaluation results using in-situ surface data revealed that the model underestimated pollen concentrations and was unable to accurately reproduce the peak pollen episodes. The model error was likely due to uncertainty in climatology-based C _e used for the estimation of oak pollen emissions and inaccuracy in the wind fields from the Weather Research and Forecast (WRF) model.     

Spatiotemporal variations of potential evapotranspiration and aridity index in relation to influencing factors over Southwest China during 1960–2013

This study investigated the spatial–temporal patterns and trends of potential evapotranspiration (ET₀) and aridity index (AI) over Southwest China during 1960–2013 based on daily temperature, precipitation, wind speed, sunshine duration, total solar radiation, and relative humidity data from 108 meteorological stations. The Penman–Monteith model, Mann–Kendall (M–K) test, moving t test, and Morlet wavelet method were used. The results indicated that ET₀ and AI across the region displayed decreasing trends, but the former was significant. After 2000, regionally average trends in ET₀ and AI increased rapidly, indicating that droughts increased over Southwest China in recent years. Spatially, the changes of ET₀ and AI were dissimilar and not clustered, either. Temporally, both ET₀ and AI displayed obvious abrupt change points over different timescales and that of AI was during the winter monsoon period. Significant periodic variations with periods of 27, 13, and 5 years were found in ET₀, but only of 13 and 5 years existed in AI. Correlation analysis revealed that the sunshine duration and wind speed were the dominant factors affecting ET₀ and that AI showed strong negative correlation with precipitation. The findings of this study enhance the understanding of the relationship between climate change and drought in Southwest China, while the mechanism controlling the variation in drought requires further study.     

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.     

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.