Number Of Sunshine Hours Research Articles

Effects of Temperature, Precipitation, and Sunshine on Cold-Tolerant Wheat Yield Under Warming Trends: A 20-Year Study in Hokkaido, Japan

To clarify the adaptation strategies of cold-tolerant wheat against global warming, this study examined the effects of daily temperature, precipitation, and sunshine duration on wheat yield in Hokkaido, Japan, over 13 years (2011–2023). Yield components were also analyzed over 20 years (2004–2023). The number of snow-cover days decreased by about 24 days over the 20-year period. As a result, the growth of overwintered wheat accelerated, with the heading and maturity of plants advancing by about 8 and 5 days, respectively, and the grain-filling period extending from about 44 to about 48 days. Multiple regression analysis was conducted using wheat yield as the objective variable and weather conditions as explanatory variables. Three weather conditions were selected: precipitation for 8 days from 27 March, sunshine hours for 8 days from 21 March, and sunshine hours for 12 days from 13 June, which yielded a coefficient of determination of 0.953. Despite the highest mean summer temperatures on record being registered in 2023, high yields were ensured by the number of sunshine hours, which were approximately 1.5 times the normally recorded hours. This highlights the importance of this parameter in mitigating the impact of high summer temperatures.

Inter- and intra-annual carbon isotope fluctuations in Pinus sylvestris L. tree rings whole wood and cellulose in north-eastern Lithuania

In temperate regions trees typically exhibit growth sensitivity to climatic conditions during the growth season. Annual tree ring growth increments correlate with a variety of environmental factors. As an index of water use efficiency, δ13C is a preferred proxy to allow accurate interpretation of environmental factors critical for the tree growth, including changes in climate patterns, variation in the ambient temperature and precipitation. We assumed that isotopic differences within individual tree rings are likely to produce seasonal isotope fluctuations in the chronology that might be interpreted as response to environmental impacts. To verify the assumption, we measured δ13C in annual tree rings of Pinus Sylvestris L. split into 13 intra-annual segments each and checked δ13C correlations with temperature, precipitation, the number of sunshine hours and relative air humidity. For the investigation, we chose a site in north-eastern Lithuania, Zarasai, located in boreal latitude and remote from industrial pollution sources. The methodology of the research was based on high coherence of δ13C chronologies measured in the whole wood and α-cellulose extracted by means of two different methods. The experiment produced strong δ13C correlations with hydrometeorological parameters, especially in the earlywood formed in June

Performance Evaluation of Artificial Neural Networks for Estimating Refer-ence Evapotranspiration in Shahat, Libya using limited climatic data

This study was conducted with the aim of evaluating the performance of artificial neural networks (ANNs) to estimate the reference evapotranspiration using limited climate data in Shahat region in Libya, compared to using the FAO Penman-Monteith equation (FPM), which requires temperature, wind speed, relative humidity and number of sunshine hours, which are rarely available in most meteorological stations in developing countries. In this study, we used the average temperature (Tmean) and the average relative humidity (RHmean) obtained from Shahat meteorological station for the period from 1963 to 1999, and the extraterrestrial radiation (Ra), which can be calculated given the location and time of the day. These data are divided into two groups, from 1963 to 1988 and from 1989 to 1999 for the training and validation phases of the neural networks, respectively. This study concluded that using (Tmean), (RHmean) and (Ra) gave the best agreement with the results calculated with the FAO Penman-Monteith equation, where the values of R2 and RMSE are equal to 0.98 and 0.26, respectively.

Climate Change, Biased Technological Advances and Agricultural TFP: Empirical Evidence from China

The impact of climate change on agricultural quality development under the constraint of China’s “Double Carbon” target has been widely discussed by policy practitioners and academic theorists. This paper attempts to deconstruct the logic of how climate change affects agricultural total factor productivity (TFP) in three dimensions—the structure of agricultural input factors, the change in the cropping system, and the stability of crop supply. This paper also reveals the mechanism through which biased technological progress increases agricultural TFP by weakening the magnitude of climate change and empirically tests it by using China’s provincial-level data from 2000 to 2021. This study showed that average annual temperature and annual precipitation had significant negative effects on agricultural TFP, that the number of sunshine hours had a significant positive effect on agricultural TFP, and that obvious regional differences existed in the effect of climate change on agricultural TFP. Further mechanism tests revealed that biased technological progress positively moderated the effect of climate change on agricultural TFP. Based on these findings, the appropriate countermeasures for improving climate early warning mechanisms, promoting the progress of appropriate technology, and fostering new agricultural management bodies.

A quantitative and qualitative investigation of ball and foam covers coated with cement slurry and their composition on reducing evaporation and choosing the best coating by the AHP method

Abstract The present study sought to use a 20 mm thick foam coated with cement slurry and blue ball in 50 and 80% surface covers, and their composite in 80% surface coverage in the Colorado pan. Then, the pans' daily evaporation was calculated and compared with the amount of control evaporation. The results indicated that the combined method (plastic ball and foam) with 80% reduced the evaporation by about 68%, plastic ball with 80% cover about 58%, foam with 80% coating about 53%, plastic ball with 50% coating about 34%, and finally 50% foam by about 28%. Concerning the statistical analysis of this research, a significant correlation was observed between the control pan and average temperature, although there was no fixed and uniform relationship between the control pan and maximum wind speed, air pressure, average relative humidity, and the number of sunshine hours. In this research, foam 50%, composite 80%, foam 80%, ball 80%, and ball 50% had better performance in terms of the best water quality based on the water electrical conductivity (EC), respectively. Finally, the composite cover 80% was selected as the best coverage using the analytic hierarchy process (AHP) and considering different criteria.

Reference evapotranspiration estimation using machine learning approaches for arid and semi-arid regions of India

Accurate estimation of reference evapotranspiration (ET0) is vital for hydrological studies and irrigation scheduling. This study aimed to estimate ET0 using 4 machine learning algorithms: random forest, support vector machine, light gradient boosting decision trees and extreme gradient decision trees. Daily data for 2001 to 2020 at 11 (arid and semi-arid) stations were used for modelling. Eighteen scenarios with different input combinations were evaluated using the data of maximum and minimum air temperature, mean relative humidity and wind speed, number of sunshine hours, solar radiation, and extra-terrestrial radiation data at these stations. The ET0 estimated using the FAO 56 Penman-Monteith equation was chosen as the target value for model fitting. The best input combination was found in the models that used all inputs, while the least accurate were the models that used temperature data only. The results showed that the support vector machine models outperformed the other models at most stations. The application of various input combinations indicated that the use of fewer inputs also gave reasonable accuracy in the modelling. In addition, wind speed and solar radiation were found to be important parameters for precise estimation.

Solar luminosity at Rabia district Analytical Climatological Study

The a study of the number of hours of real and theoretical sunshine duration is one of modern climate studies in the world, as it is supported and confirmed by geographers considering the practical applied approach has its justification in the contemporary climate, and relied on the application of mathematical and statistical equations so it is climatic within the field Applied climate. The sunshine is critical in the proper planning and optimal use of solar energy resources in various fields in order to develop appropriate plans for different activities based on their results. The reasons for the study in the enrichment of climate studies such as these quantitative studies that are associated with many other studies, whether in the natural or human field. The choice of the subject of research (Sunshine duration in the Rabia station/ an analytical climatic study) gave a spatial dimension to the diastolic surface this reflects on the impact of climate elements, and this reflects negatively or positively on the number of sunshine hours, as well as the rare studies that dealt with sunshine duration in geographical studies, especially in Iraq. The elements of solar radiation, outside the Earth's atmosphere absorbed solar radiation (Ra) and total solar radiation (Rs) share the highest values in June and lowest in December, and real and theoretical sunshine duration at the highest values in June and lowest in January. Mathematical relationships have been found to calculate total solar radiation (Rs) from sunshine (real, theoretical, sunshine ratio). The relationship of multiple association of total solar radiation (Rs) with solar sunshine (real, theoretical, sunshine ratio) was positive as it reached (0.998). The adoption of the values of solar radiation outside the atmosphere (Ra) when calculating solar radiation for any time, because it relied on constants such as the latitude and length of the day (theoretical). The rest of the elements of solar radiation values change as climate elements and other variables. And the adoption of theoretical sunshine values (N) because they are fixed for all years because they depend on constants.

Evaluation of the Agromet Indices Impact on Cowpea Crop at Khurdha District of Odisha, India

At the ICAR-IIWM research farm in Odisha, a study was carried out during the rabi season to assess the effects of agromet indices on the cowpea variety Kashi uttam during the two growth seasons of 2018–19 and 2019–20. Different growing seasons and a delay in sowing had a significant impact on the length of phenological stages and accumulation of agro-climatic indices (Growing Degree Days, Photothermal Units, and Heliothermal Units). The findings showed that distinct growth phases at the second growing season were responsible for the greater GDD and PTU. However, the decrease in HTU during the second growing season showed that the crop required fewer heat units as a result of the second growth season's considerably lower number of sunshine hours. Among the seasons and sowing dates, the meteorological indices accretion was perceived in 2nd growing season as compared to 1st growing season crop. Second season crop had sown earlier and get highest heat use efficiency.

Modelling reference evapotranspiration using gene expression programming and artificial neural network at Pantnagar, India

Evapotranspiration is an essential component of the hydrological cycle that is of particular interest for water resource planning. Its quantification is helpful in irrigation scheduling, water balance studies, water allocation, etc. Modelling of reference evapotranspiration (ET0) using both gene expression programming (GEP) and artificial neural network (ANN) techniques was done using the daily meteorological data of the Pantnagar region, India, from 2010 to 2019. A total of 15 combinations of inputs were used in developing the ET0 models. The model with the least number of inputs consisted of maximum and minimum air temperatures, whereas the model with the highest number of inputs consisted of maximum air temperature, minimum air temperature, mean relative humidity, number of sunshine hours, wind speed at 2 m height and extra-terrestrial radiation as inputs and with ET0 as the output for all the models. All the GEP models were developed for a single functional set and pre-defined genetic operator values, while the best structure in each ANN model was found based on the performance during the testing phase. It was found that ANN models were superior to GEP models for the estimation purpose. It was evident from the reduction in RMSE values ranging from 2 % to 56 % during training and testing phases in all the ANN models compared with GEP models. The ANN models showed an increase of about 0.96 % to 9.72 % of R2 value compared to the respective GEP models. The comparative study of these models with multiple linear regression (MLR) depicted that the ANN and GEP models were superior to MLR models.

Spatio-Temporal Variation and Influencing Factors of Ozone Pollution in Beijing

The temporal and spatial distribution and variation characteristics of ozone (O3) in Beijing, China, are investigated using hourly monitoring data from 2020. Kriging interpolation analysis and correlation analysis are applied to describe the spatial-temporal distribution and to identify associated influencing factors. The average concentration of O3 was found to be 59.58 μg·m−3. The daily maximum sliding 8 h average ozone concentration values exceeded the primary standard (100 μg·m−3) for 129 days and exceeded the secondary standard (160 μg·m−3) for 48 days. Temporally, the general pattern of daily maximum 8 h average O3 concentration was high in spring and summer and low in autumn and winter. Monthly average values showed a maximum in June. The highest daily concentrations appeared between 13:00 and 18:00 local time, and O3 concentrations had a distinct weekly pattern of variability with daily average concentrations at weekends higher than those during working days. Spatially, annual average O3 concentrations were highest in the northeast and lowest in the southeast of the city, and the seasonal variation of O3 was most significant in the southwest of the city. In relation to city districts and counties, the annual average O3 concentrations in the Miyun District were the highest, while those in the Haidian District were the lowest. On the whole, annual average O3 concentrations in Beijing were higher in the suburbs than in central areas. Based on daily average values, there was no significant correlation between O3 concentrations and rainfall (p > 0.05), but there were significant correlations between O3 concentration and sunshine hours, wind speed, maximum temperature and minimum temperature (p < 0.05), with correlation coefficients of 0.158, 0.267, 0.724 and 0.703, respectively. O3 concentrations increased with an increasing number of sunshine hours, first increased and then decreased with increasing wind speed and increased with increasing temperature. O3 concentrations were correlated with SO2 concentrations (0.05 < p > 0.001), CO concentrations (p < 0.001) and NO2 concentrations (p < 0.001), the latter having the highest correlation coefficient of −0.553 and exhibiting opposite trends in daily and monthly variations to O3 variations. Analysis of ozone pollution sources showed that automobile exhaust, coal and oil combustion and volatile organic compounds released by industrial plants were the main sources. Terrain affected the distribution of ozone, as well as human activities and industry.

Response of Date of Sowing and Varieties on Growth and Yield of Niger under Eastern Ghat High Land Zone of Odisha

A field experiment was carried out under All India Coordinated Research Project on Niger at Regional Research and Technology Transfer Station (OUAT), Semiliguda of Koraput district under Eastern Ghat High Land zone of Odisha in acidic soil during three consecutive kharif seasons from 2015 to 2017 to study the response of date of sowing and varieties on growth and yield of niger. The experiment consists of six dates of sowing with 15 days interval viz. 15th July, 30th July, 14th August, 29th August, 13th September and 28th September with two varieties of niger namely Deomali and Utkal Niger-150. The experiment was performed in split plot design with three replications. The pooled data for three years revealed that out of six different dates of sowing, the crop which was sown on 15th July resulted significantly the highest seed yield (563 kg ha-1) with a net monetary return (Rs. 8083 ha-1) and benefit cost ratio (1.6). Niger variety Utkal Niger-150 recorded higher seed yield and economic returns. It was discovered that the environment had a greater impact on variety yield levels than the varieties themselves. Less dry spells, no wet spells, a high number of sunshine hours and a moderate temperature were all essential environmental factors.

Simulation of Self-Consumption Photovoltaic Installations: Profitability Thresholds

PV self-consumption can contribute positively to the spread of PV and, therefore, to the progress of renewable energies as a key element in a decarbonized energy model. However, the policies of each country regarding the promotion of this type of renewable technology is fundamental for their growth. Despite the high number of sunshine hours registered in Spain, self-consumption in this country has not been authorized until recently. In this new context, this work presents a systematic study of the profitability limits of a self-consumption PV installation under different conditions of installed peak power, orientation and inclination of the PV panels and level of obstruction of the installation. It was proved that, for the case of study (Córdoba, Spain), the maximum profitability was achieved for PV panels oriented to the south and with an inclination of 15° whereas the most unfavourable conditions are those of PV panels with an orientation and inclination of 180° and 90°, respectively. Furthermore, when the level of obstruction increases the maximum of the Net Present Value of self-consumptions PV installations decreases and this optimal value is achieved for installations with lower power. Finally, empirical adjustment equations have been developed to estimate the profitability parameters of self-consumptions PV installations as a function of their design variables.

ОБРАЗ МИРА КАК ПСИХОЛОГИЧЕСКАЯ СИСТЕМА И ЕГО ПРИРОДНО-СРЕДОВЫЕ ДЕТЕРМИНАНТЫ

The image of the world is considered as a psychological system that includes spatial-temporal and value-semantic dimensions. The theoretical analysis of the research problem allows us to state as follows. There is a contradiction between the significance of objective natural and geographical factors in the formation of a human's lifestyle, and the lack of knowledge of their influence on the formation of his subjective image of the world. The pur-pose of this article is to study the determination of subjective chronotopic characteristics of the human world image by objective environmental factors. The study involved 450 residents of 10 Russian cities that differ significantly in their natural and geographical features. The following characteristics of the respondents’ place of residence were evaluated: geographical latitude; the degree of discrepancy between the offi-cial time zone and the actual time set by geographical longitude; the average annual tempera-ture; the number of sunshine hours per year. The complex of psychodiagnostic methods included the author’s questionnaire of structure identity; the graphic test "Circles"; the scale of polychronous values; the scale of time value as an economic resource; the semantic differen-tial of time; the author’s methodology of studying value preferences; the test of life-meaning orientations. Natural and geographical features of the life environment determine significant diffe-rences in the spatial-temporal and value-semantic characteristics of the subjective image of the world. Representatives of the northern territories have a significant belonging to the modern generation, the semantic connectedness of the time perspective, and the subjective value of time. They see their present and future as about anxious and tense; they focus on the values of adaptation, as well as internality. Residents of warm regions have a more signi-ficant gender and family identity, semantic connectedness of the time perspective, anxiety of their present, orientation to the values of adaptation. If the officially set time goes ahead over the actual longitudinal time, it is correlated with the disturbing image of the present, the idea of saturation, brightness and iridescence of past and future, focus on the value of sociali-zation. The environmental characteristics of residence have a significant impact on the subjective image of reality. The greatest value among the considered determinants is the geographical latitude of the place of residence. The influence of environmental determinants on the subjec-tive parameters of the image of the world is indirectly related to the intermediate links such as economic and cultural type or psychophysiological characteristics of life activity in the corresponding natural conditions.

Climatic Characteristics of Hubei Tobacco Area and Its Influence on the Quality of Upper Leaves

In order to provide a more suitable environment for tobacco leaf growth, this study collected meteorological information and tobacco leaf quality information from the main tobacco-producing counties in the province and conducted relevant analysis to find out the main meteorological factors affecting the growth, development, yield, and quality of upper tobacco leaves. Clarify the suitable climatic conditions for the growth and development of the upper leaves, and clarify the influence of various meteorological factors on the quality of the upper leaves. The results showed that the nicotine and total nitrogen content of the upper leaves were significantly positively correlated with the average daily temperature during the maturity period, and negatively correlated with the rainfall during the maturity period; the rainfall in July was significantly positively correlated with the upper leaf clutter score, which was sufficient in the mature period. Moisture conditions are conducive to alleviating the upper leaf clutter; the number of sunshine hours in August is the main factor affecting the content of aroma substances in the upper leaves, and it is also significantly positively correlated with the content of aroma substances.

The Supplementary irrigation and drying method affect the yield and essential oil content and composition of lavender (lavandula angustifolia mill.) flowers

This paper presents the results of a study conducted over the period 2016–2017 which was designed to determine to what extent crop irrigation and raw material drying process determine the content and composition of lavender essential oil. In cultivation with irrigation, a higher yield of fresh and yield of air-dried inflorescences was obtained compared to cultivation without irrigation. The use of supplementary irrigation in lavender crops contributed to an increased amount of essential oil (EO) compared to plants without irrigation. The main components of the essential oil were Linalyl acetate, Linalool, and E-Caryophyllene. In EO obtained from plants cultivated with irrigation, the share of oxygenated monoterpenes (OM) was higher and the share of hydrogenated monoterpenes (HM) was lower than in the oil from plants without irrigation. The EO content in lavender flowers dried at a temperature of 30°C was twice higher than in those dried in natural conditions. In 2016 in which the air temperatures were high and a greater number of sunshine hours was recorded in July and August, plants accumulated more EO than in 2017. Study shows that there are prospects for practical application of crop irrigation in lavender cultivation and of raw material preservation method in order to modify EO content and chemical composition.

Weather and its impact on population buildup of pod borers in pigeonpea

The experiment conducted at Regional Agricultural Research Station, Lam, Guntur during 2016-17 on pigeonpea (Cajanus cajan (L.) Millspaugh) yielded a good amount of information on the trend of population build up and seasonal abundance of gram pod borer, Helicoverpa armigera, spotted pod borer, Maruca vitrata and tobacco caterpillar, Spodoptera litura. Peak populations of H. armigera adults were observed during 37 and 45th SMW, whereas peak populations of S. litura adults were observed during 37, 42 and 46th SMW. The peak larval population of H. armigera and M. vitrata were observed during 39th SMW and 48th SMW, respectively which coincides with peak flowering stage. The correlation studies conducted between weather parameters and pest incidence showed that moderately significant correlation was obtained between adults of H. armigera and rainy days and sunshine hours with correlation coefficient (r) being 0.578 and -0.583, respectively. Moderately significant correlation was obtained between adults of S. litura and RH-II and rainy days with correlation coefficient (r) being 0.510 and 0.518, respectively. Further, moderately significant correlation was obtained between larval population of H. armigera and M. vitrata with sunshine hours with correlation coefficient (r) being -0.509 and -0.495, respectively. Thus, concluded that as the number of rainy days increase with decrease in sunshine hours the adult population of H. armigera and S. litura will increase. Similarly, the larval population of H. armigera and M. vitrata will increase as the number of sunshine hours decrease during the crop growing period. Thus, farmers can predict the pest early and optimize the application of insecticides in order to check the pest population from reaching the economic threshold level.

Meteorological conditions and their associations with the productive performance of wheat

This study aimed at assessing the effect of the photothermal quotient, meteorological variables and their effects on the grain production and yield of the wheat cultivars in terms of hectoliter mass in Santa Maria, Rio Grande do Sul state, Brazil. The experiments were carried out in the same experimental area in different years. Four experiments were performed in the experimental field during the agricultural years of 2013 (10 cultivars), 2014 (16 cultivars), 2015 (15 cultivars) and 2016 (15 cultivars) with the principal cultivars in the Rio Grande do Sul state, during each of these years. The meteorological factors (mean air temperature, solar radiation, insolation and accumulated precipitation) showed wide fluctuations over these years. They induced instability in the production. The grain yield and the hectoliter mass were compared in each of the agricultural years (Scott-Knott, α≤0.05) and are related in dispersion plots according to the climatic variables for the set of years and cultivars (regression analysis). The available solar radiation (number of sunshine hours), quality (photothermal quotient) and average air temperature were the determinant factors for wheat productivity. However, the hectoliter mass was influenced more by the effect of genetic variability, lack of precipitation during crop maturation, and photothermal quotient around the time of anthesis. Wheat crop investments can be expanded to maximize wheat grain yield when average cycle temperatures remain near 16.5 oC, high solar radiation and low rainfall. Better quality trains (hectoliter mass) will be obtained when smaller precipitations are observed at harvest and higher photothermal quotient.

Impacts of the decreased freeze-up period on primary production in Qinghai Lake

Although previous research has focused on the inundation changes in Qinghai Lake, the largest lake in China, few studies have investigated the variations in primary production and correlated these changes with environmental transitions. In this study, this knowledge gap was filled using multiple ocean color satellite missions between 2003 and 2017. The results indicated a substantial increase in phytoplankton growth over recent years, during which the normalized fluorescence line height (nFLH) and algal bloom index (ABI) increased by approximately 45% and 61%, respectively, from the first (2003–2012) to the second period (2013–2017). Such a remarkable increase is likely associated with a rapid decrease in the duration of the freeze-up period, for which the 2014–2017 mean was >2 standard deviations below that of the previous years. High temperatures and a large number of sunshine hours could possibly explain the elevated nFLH and ABI in 2013. A multiple general linear model revealed that the freeze-up period, number of sunshine hours, and temperature explained 76.1%, 5.6%, and 10.2%, respectively, of the long-term changes in primary production in Qinghai Lake during the observed period. This study not only provides the first comprehensive analysis of the biogeochemical properties of Qinghai Lake but also demonstrates the capability of multiple remote sensing products in addressing environmental problems. Further, the method here is easily extendable to similar water bodies worldwide to study their potential responses to climate variability.

Reallocating regional water apparent productivity in the long term: methodological contributions and application for Spain

The main objective of this paper is to quantify and explain the main trends and determinants of long-term agricultural water apparent productivity (WAP). The WAP shows the economic value of products per cubic meter of water used and is calculated as the ratio between the value of agricultural production and its water use (the water footprint). In order to understand economic and agricultural structural changes, we use index decomposition analysis, novel in the study of WAP. This approach is consistently multidimensional (results for different crops and provinces are analyzed) and multilevel (different levels of crops and regional disaggregation are combined), and hence applications are possible for different regions and settings. In the case of Spanish agriculture (analyzed here), the study is of particular importance, given the profound political, economic, and agricultural transformations experienced in the twentieth century. Furthermore, given Spain’s particular environmental conditions—such as the high number of sunshine hours and the unequal distribution of rainfall—the spatial and temporal differences are notable in terms of crop production composition, economic value, and water footprint. The results show a 27% increase in agricultural WAP from 1955 to 2005–2010, totally explained by an improvement in water efficiency (intensity effect reflecting the use of water relative to the production attained) that happened in most areas of the country. The relative variations in the regional composition of the water footprint (share effect), and especially the crop production patterns (composition effect), contributed to a slowdown in total WAP at the country level. However, the share and composition effects encouraged the WAP’s growth in South and Southeast Spain, areas that produced high value-added crops with large water needs.

Environmental and individual predictors of 25-hydroxyvitamin D concentrations in Denmark measured from neonatal dried blood spots: the D-tect study.

Environmental factors such as sunshine hours, temperature and UV radiation (UVR) are known to influence seasonal fluctuations in vitamin D concentrations. However, currently there is poor understanding regarding the environmental factors or individual characteristics that best predict neonatal 25-hydroxyvitamin D (25(OH)D) concentrations. The aims of this study were to (1) identify environmental and individual determinants of 25(OH)D concentrations in newborns and (2) investigate whether environmental factors and individual characteristics could be used as proxy measures for neonatal 25(OH)D concentrations. 25-Hydroxyvitamin D3 (25(OH)D3) was measured from neonatal dried blood spots (DBS) of 1182 individuals born between 1993 and 2002. Monthly aggregated data on daily number of sunshine hours, temperature and UVR, available from 1993, were retrieved from the Danish Meteorological Institute. The individual predictors were obtained from the Danish National Birth register, and Statistics Denmark. The optimal model to predict 25(OH)D3 concentrations from neonatal DBS was the one including the following variables: UVR, temperature, maternal education, maternal smoking during pregnancy, gestational age at birth and parity. This model explained 30 % of the variation of 25(OH)D3 in the neonatal DBS. Ambient UVR in the month before the birth month was the best single-item predictor of neonatal 25(OH)D3, accounting for 24 % of its variance. Although this prediction model cannot substitute for actual blood measurements, it might prove useful in cohort studies ranking individuals in groups according to 25(OH)D3 status.