Diurnal Air Temperature Range Research Articles

Identifying the multiple drivers of cactus diversification

Our understanding of the complexity of forces at play in the rise of major angiosperm lineages remains incomplete. The diversity and heterogeneous distribution of most angiosperm lineages is so extraordinary that it confounds our ability to identify simple drivers of diversification. Using machine learning in combination with phylogenetic modelling, we show that five separate abiotic and biotic variables significantly contribute to the diversification of Cactaceae. We reconstruct a comprehensive phylogeny, build a dataset of 39 abiotic and biotic variables, and predict the variables of central importance, while accounting for potential interactions between those variables. We use state-dependent diversification models to confirm that five abiotic and biotic variables shape diversification in the cactus family. Of highest importance are diurnal air temperature range, soil sand content and plant size, with lesser importance identified in isothermality and geographic range size. Interestingly, each of the estimated optimal conditions for abiotic variables were intermediate, indicating that cactus diversification is promoted by moderate, not extreme, climates. Our results reveal the potential primary drivers of cactus diversification, and the need to account for the complexity underlying the evolution of angiosperm lineages.

Redistribution of Qiongzhuea tumidinoda in Southwest China under Climate Change: A Study from 1987 to 2012

Qiongzhuea tumidinoda stands out as an endemic bamboo species of significant conservation importance in Southwest China, particularly in the upper reaches of the Yangtze River. It holds a pivotal role in poverty alleviation through the commercialization of its wood and bamboo shoots. However, the suitable area of this species is undergoing rapid changes due to climate change, resulting in species redistribution and potential losses for bamboo farmers. We utilized 209 presence records and 25 environmental variables from 1987 to 2012 to predict the potentially suitable habitats for Q. tumidinoda using MaxEnt (version 3.4.1), ArcGIS (version 10.8.2), and R (4.3.3). We rigorously screened the recorded data for reliability and accuracy through expert consultations and observer interviews. We performed pre-processing to select the variables with high contributions for modeling, and 11 variables were selected for the final modeling. Our findings reveal that the top three most influential variables associated with Q. tumidinoda’s distribution were the mean monthly potential evapotranspiration (Pet), annual range of air temperatures (Bio7), and mean diurnal air temperature range (Bio2), and the rates of contributions from 1987 to 2012 were 4.8333, 3.5833, and 1.7000. There was a southeastward shift and an elevation increase in the potentially suitable habitats for Q. tumidinoda. The area of potentially suitable habitats in the study region exhibited fluctuating growth, expanding from 3063.42 km2 to 7054.38 km2. The mean monthly potential evapotranspiration (Pet) emerged as a critical determinant shaping the distribution of potentially suitable habitats for Q. tumidinoda. Our study sheds light on the response of Q. tumidinoda to climate change, offering valuable insights for the development and management of plantation industries associated with this species. In the future, to enhance prediction accuracy, researchers could equally consider both organic and inorganic environmental variables. For better preservation of environment and development, Q. tumidinoda could be introduced into nature restoration projects in areas with a suitable habitat or as a commodity that participates in forest carbon sink trading.

Role of climate change on Oriental spruce (Picea orientalis L.): Modeling and mapping

Global climate change is a process with dramatic consequences for ecosystems, and changes that may occur in the potential distribution of plant communities especially draw attention. This study aimed to reveal the potential distribution modeling and mapping of the Oriental spruce (Picea orientalis L.), distributed in a limited area, using current and future (year 2100) climate scenarios in Turkey. The maximum entropy method for potential distribution and Chelsa V2.1 technical specification IPSL-CM6A-LR scenarios (SSP126-SSP370-SSP585) were preferred to reveal the effect of climate change. Results for the current were in the “excellent” category with training and test data AUC 0.981 and 0.977, respectively. The variables contributing to the model were the precipitation amount of the driest month, mean diurnal air temperature range, annual precipitation amount, and mean annual air temperature. Variables contributing to the current model were analysed using the SSP126, SSP370, and SSP585 scenarios of the year 2100. It was assessed that the potential distribution for 2100 decreases according to SSP126, was fragmented according to SSP370, and decreased according to the SSP585 scenario. As a result, the authors determined that the high potential distribution is reduced 61% when the current mapping of Oriental spruce is compared with the SSP585 mapping.

Global hourly, 5 km, all-sky land surface temperature data from 2011 to 2021 based on integrating geostationary and polar-orbiting satellite data

Abstract. Land surface temperature (LST) plays a dominant role in the surface energy budget (SEB) and hydrological cycling. Thermal infrared (TIR) remote sensing is the primary method of estimating LST globally. However, cloud cover leaves numerous data gaps in satellite LST products, which seriously restricts their applications. Efforts have been made to produce gap-free LST products from polar-orbiting satellites (e.g., Terra and Aqua); however, satellite data from limited overpasses are not suitable for characterizing the diurnal temperature cycle (DTC), which is directly related to heat waves, plant water stress, and soil moisture. Considering the high temporal variability in LST and the importance of the DTC, we refined the SEB-based cloudy-sky LST recovery method by improving its feasibility and efficiency and produced a global hourly, 5 km, all-sky land surface temperature (GHA-LST) dataset from 2011 to 2021. The GHA-LST product was generated using TIR LST products from geostationary and polar-orbiting satellite data from the Copernicus Global Land Service (CGLS) and the Moderate Resolution Imaging Spectroradiometer (MODIS). Based on ground measurements at the 201 global sites from the Surface Radiation Budget (SURFRAD), Baseline Surface Radiation Network (BSRN), Fluxnet, AmeriFlux, Heihe River basin (HRB), and Tibetan Plateau (TP) networks, the overall root-mean-square error (RMSE) of the hourly GHA-LST product was 3.31 K, with a bias of −0.57 K and R2 of 0.95. Thus, this product was more accurate than the clear-sky CGLS and MODIS MYD21C1 LST samples. The RMSE value of the daily mean LST was 1.76 K. Validation results at individual sites indicate that the GHA-LST dataset has relatively larger RMSEs for high-elevation regions, which can be attributed to high surface heterogeneity and input data uncertainty. Temporal and spatial analyses suggested that GHA-LST has satisfactory spatiotemporal continuity and reasonable variation and matches the reference data well at hourly and daily scales. Furthermore, the regional comparison of GHA-LST with other gap-free hourly datasets (ERA5 and Global Land Data Assimilation System, GLDAS) demonstrated that GHA-LST can provide more spatial texture information. The monthly anomaly analysis suggests that GHA-LST couples well with global surface air temperature datasets and other LST datasets at daily mean and minimum temperature scales, whereas the maximum temperature and diurnal temperature range of LST and air temperature (AT) have different anomalous magnitudes. The GHA-LST dataset is the first global gap-free LST dataset at an hourly, 5 km scale with high accuracy, and it can be used to estimate global evapotranspiration, monitor extreme weather, and advance meteorological forecasting models. GHA-LST is freely available at https://doi.org/10.5281/zenodo.7487284 (Jia et al., 2022b) and http://glass.umd.edu/allsky_LST/GHA-LST (last access: 10 February 2023; Jia et al., 2022c).

Long-term trends in daily extreme air temperature indices in Ireland from 1885 to 2018

Long-term instrumental series are crucial to analyse extreme air temperature indices and to examine modern climate warming within a historical context. This research provides the first assessment in Ireland of the frequency, duration, intensity and geographical distribution of the daily extreme air temperature indices recommended by the ETCCDI (Expert Team on Climate Change Detection and Indices) and based on long-term rescued, quality-controlled and homogenised data. Prior analysis of air temperature indices in Ireland had focused on the period since the second half of the 20th century, where digital data were readily available. Earlier estimations of long-term air temperature trends in Ireland focused on non-homogenised data from a small network of stations. For this research, 11 long-term (1885–2018) maximum and minimum air temperature series were analysed to assess seasonal and annual trends and construct extreme air temperature indices in Ireland. The non-parametric Mann-Kendall test was employed to test the statistical significance of the maximum and minimum air temperatures and indices trends (p < 0.05). Significant increasing trends were assessed in the seasonal and annual maximum and minimum air temperature series in Ireland, with greater increases in the spring and autumn seasons. Significant increasing trends were determined in the warm days (+6.8 days), warm nights (+7.5 nights), warm spell duration index (+3.9 days), growing season length (+22 days), coldest night (+2.7 °C) and coldest day (+1.5 °C) in the period 1885–2018 in Ireland. In the same period, significant decreasing trends were identified in the cold days (−9.3 days), cold nights (−7 nights), frost days (−13.7 days), cold spell duration index (−6.9 days) and diurnal air temperature range (−0.1 °C) in Ireland. The results follow global patterns presented in the Six Assessment Report of the Intergovernmental Panel on Climate Change. The findings of this research will be crucial to assist stakeholders and policymakers in defining climate action, adaptation and mitigation plans in response to shifting trends in air temperature extremes.

Analysis of Diurnal Air Temperature Range Variation over Bangladesh

Analysis of Diurnal Air Temperature Range Variation over Bangladesh

Low levels of genetic differentiation with isolation by geography and environment in populations of Drosophila melanogaster from across China.

The fruit fly, Drosophila melanogaster, is a model species in evolutionary studies. However, population processes of this species in East Asia are poorly studied. Here we examined the population genetic structure of D. melanogaster across China. There were 14 mitochondrial haplotypes with 10 unique ones out of 23 known from around the globe. Pairwise FST values estimated from 15 novel microsatellites ranged from 0 to 0.11, with geographically isolated populations showing the highest level of genetic uniqueness. STRUCTURE analysis identified high levels of admixture at both the individual and population levels. Mantel tests indicated a strong association between genetic distance and geographical distance as well as environmental distance. Full redundancy analysis (RDA) showed that independent effects of environmental conditions and geography accounted for 62.10% and 31.58% of the total explained genetic variance, respectively. When geographic variables were constrained in a partial RDA analysis, the environmental variables bio2 (mean diurnal air temperature range), bio13 (precipitation of the wettest month), and bio15 (precipitation seasonality) were correlated with genetic distance. Our study suggests that demographic history, geographical isolation, and environmental factors have together shaped the population genetic structure of D. melanogaster after its introduction into China.

Predicting the Suitable Geographical Distribution of Sinadoxa Corydalifolia under Different Climate Change Scenarios in the Three-River Region Using the MaxEnt Model.

Sinadoxa corydalifolia is a perennial grass with considerable academic value as a rare species owing to habitat destruction and a narrow distribution. However, its distribution remains unclear. In this study, we predicted the distribution of Sinadoxa corydalifolia in the three-river region (the source of the Yangtze River, Yellow River, and Lancang River) under the context of climate change using the maximum entropy (MaxEnt) model. Under the current climate scenario, the suitable distribution mainly occurred in Yushu County and Nangqian County. The suitable distribution area of Sinadoxa corydalifolia covered 3107 km2, accounting for 0.57% of the three-river region. The mean diurnal air temperature range (Bio2), temperature seasonality (Bio4), and mean air temperature of the driest quarter (Bio9) contributed the most to the distribution model for Sinadoxa corydalifolia, with a cumulative contribution of 81.4%. The highest suitability occurred when air temperature seasonality (Bio4) ranged from 6500 to 6900. The highest suitable mean air temperature of the driest quarter ranged from −5 to 0 °C. The highest suitable mean diurnal temperature (Bio2) ranged from 8.9 to 9.7 °C. In future (2041–2060) scenarios, the suitable distribution areas of Sinadoxa corydalifolia from high to low are as follows: representative concentration pathway (RCP)26 (6171 km2) > RCP45 (6017 km2) > RCP80 (4238 km2) > RCP60 (2505 km2). In future (2061–2080) scenarios, the suitable distribution areas of Sinadoxa corydalifolia from high to low are as follows: RCP26 (18,299 km2) > RCP60 (11,977 km2) > RCP45 (10,354 km2) > RCP80 (7539 km2). In general, the suitable distribution will increase in the future. The distribution area of Sinadoxa corydalifolia will generally be larger under low CO2 concentrations than under high CO2 concentrations. This study will facilitate the development of appropriate conservation measures for Sinadoxa corydalifolia in the three-river region.

Elevational patterns of temperature and humidity in the middle Tianshan Mountain area in Central Asia

The vertical distribution of vegetation types along an elevational gradient in mountain areas largely depends on the elevational changes in air temperature and humidity. In this study, we presented the seasonal and diurnal variations in the elevational gradients of air temperature and humidity on the southern and northern slopes in the middle Tianshan Mountain Range using data collected throughout the year via HOBO data loggers. The measurements were conducted at 12 different elevations from 1548 to 3277 m from September 2004 to August 2005. The results showed that the annual mean air temperature decreased along the elevational gradients with temperature lapse rates of (0.71±0.20)°C/100 m and (0.59±0.05)°C/100 m on the northern and southern slopes, respectively. The annual mean absolute humidity significantly decreased with increasing elevation on the northern slope but showed no significant trend on the southern slope. The annual mean relative humidity did not show a significant trend on the northern slope but increased with increasing elevation on the southern slope. The mean air temperature lapse rate exhibited significant seasonal variation, which is steeper in summer and shallower in winter, and this value varied between 0.37°C/100 m and 0.75°C/100 m on the southern slope and between 0.30°C/100 m and 1.02°C/100 m on the northern slope. The mean absolute and relative humidity also exhibited significant seasonal variations on both slopes, with the maximum occurring in summer and the minimum occurring in winter or spring. The monthly diurnal range of air temperature on both slopes was higher in spring than in winter. The annual range of air temperature on the southern slope was higher than that on the northern slope. Our results suggest that significant spatiotemporal variations in humidity and temperature lapse rate are useful when analyzing the relationships between species range sizes and climate in mountain areas.

Estimation of sensible heat flux at a tropical location: a performance evaluation of half-order time derivative method

Measurement of surface energy balance (SEB) components such as sensible heat flux is a very fundamental input in weather forecast, hydrological, and air quality models among many other applications. The instrumentation for measuring SEB components is however resource-intensive and highly susceptible to damage under field-experiment conditions. A simple, less equipment-intensive, cost-effective, and relatively accurate method is thus required to overcome these setbacks. The present study, therefore evaluates the performance of a rather simple half-order time derivative (HTD) method in estimating sensible heat flux at a tropical location in West Africa (Ile-Ife, Nigeria 7°33′N, 4°33′E). HTD estimates of sensible heat flux were made from near surface atmospheric parameters measured during Phase I of the Nigerian Micrometeorological Experiment. At the same site, direct turbulence flux measurements from an eddy covariance system comprising a 3-D ultrasonic anemometer (USA-1) and a krypton hygrometer (KH20) were used as standard benchmark values for the HTD performance evaluation. Within a diurnal air temperature range of 18–34 °C, estimated daytime sensible heat flux reached a peak of 318.7 W m−2 and a lowest nighttime value of − 15.8 W m−2, indicating surface cooling. Statistical tests performed; mean bias error (MBE <2 W m−2), root mean square error (RMSE <7.3 W m−2), mean absolute error (MAE< 2 W m−2), and percent mean relative error (PMRE <1%) indicated a good accuracy of the HTD method with an overall significant correlation (R2 = 0.89) with benchmark values. The HTD method is found most suitable for daytime convective conditions than stable nighttime periods at the tropical location.

Evaluation of a satellite-derived model parameterized by three soil moisture constraints to estimate terrestrial latent heat flux in the Heihe River basin of Northwest China

Satellite-derived terrestrial latent heat flux (LE) models are useful tools to understand regional surface energy and water cycle processes for terrestrial ecosystems in the Heihe River basin (HRB) of Northwest China. This study developed a satellite-derived hybrid LE model parameterized by three soil moisture (SM) constraints: SM, relative humidity (RH), and diurnal air temperature range (DT); and assessed model performance and sensitivity. We used MODerate Resolution Imaging Spectroradiometer (MODIS) and eddy covariance (EC) data from 12 EC flux tower sites across the HRB. The hybrid model was trained using observed LE over 2012/2013–2014, and validated using observed LE for 2015 and leave-one-out cross-validation. The results show that the three SM constraints schemes exhibited some modeling differences at the flux tower site scale. LE estimation using SM achieved the highest correlation (R2 = 0.87, p < 0.01) and lowest root mean square error (RMSE = 20.1 W/m2) compared to schemes using RH or DT schemes. We then produced regional daily LE maps at 1 km × 1 km across the HRB for 2013–2015. Regional analysis shows that our LE estimates from all three constraint models exhibited large spatial variability and strong seasonal and annual variations, attributed to differences in parameterizing the model water constraints. This study provides data and model based evidence to improve satellite-derived hybrid LE models with regard to water constraints.

AN ANALYSIS OF DIURNAL AIR TEMPERATURE RANGE CHANGE AND ITS COMPONENTS IN SHAHEED BENAZIR ABAD SINDH

A study has been carried out to analyse the temporal and seasonal patterns in the trends of diurnal air temperature range (DTR) and its components in Shaheed Benazir Abad for the time period 1996–2014.The magnitude, the slope and the significance of trends were investigated by using the linear regression method, the trend magnitude, the Mann-Kendall test and the Sen’s estimator of slope. The Mann-Kendall test and Sen's estimator of slope were calculated by using Addinsoft's XLSTAT 2015 software. The hypothesis of Mann-Kendall test was investigated at 95% confidence level for all variables. The result shows that minimum temperature of Shaheed Benazir Abad has increased at the rate of 0.063°C per year during study period while the maximum temperature for all months exhibits no change. This increase of minimum temperature contributed to the decreasing trend of diurnal temperature range. The DTR decreased at the rate of 0.057°C /year in Shaheed Benazir Abad. The investigation of seasonal DTR trends revealed that Summer and Spring seasons also witnessed a decreasing trends at the rate of 0.26 °C/year and 0.047°C/year respectively. Winter and aseasons, on the other hand, have experienced the increasing trends of DTR at the rate of 0.136 °C/year and 0.115 °C/year respectively. It is found by MK test that Tmax (winter), Tmax (Spring) and Tmin (Spring) exhibited the significant positive trends at the rate of 0.21°C/year, 0.368 °C/year and 0.421°C/year respectively. The increasing trends of Tmax of winter and spring indicate that winter and spring are warmer now.

A note on air temperature and precipitation variability and extremes over Asmara: 1914–2015

AbstractMeteorological series (daily precipitation, minimum and maximum air temperature) for Asmara (Eritrea) for the last 100 years (1914–2015) are analysed. The data were quality‐controlled and homogenized using publicly available data from surrounding countries as well as newly recovered data from 12 stations in Eritrea. Overall, the Asmara data showed a consistent pattern and there were no outliers outside of four standard deviations from the corresponding reference. Climate indices were calculated using the program RClimDex. Overall, 8 indices for description of the air temperature data and 10 for precipitation data were calculated. The analyses of averages and indices reveal large climatic variations in the central highlands of Eritrea. The results indicate significant changes in air temperature since 1943, with daily minimum and maximum air temperature increasing at a similar rate of 0.22 and 0.19°C/decade, respectively. The diurnal air temperature range shows a non‐significant decreasing trend over the study period. No significant variation was found in the annual total and the seasonal precipitation over the last century. Significant trends were detected for some daily precipitation indices, although the lack of reference series prevents an evaluation of their reliability.

Seasonal Characteristics of Black Carbon Aerosols over an Urban City in India: Source Analysis Using Concentration Weighted Trajectories

In this study year-round (2013) measurements of surface black carbon (BC) mass concentration recorded using a seven-channel Aethalometer (AE-31) over a tropical semi-urban site in Nagpur, in central India are presented. The annual mean BC during the studied period was 3.64 ± 1.81 μg m−3, which is comparable to that observed at few Indian and international sites. Seasonal variability in BC concentration with maximum values during the winter (4.86 ± 2.3 μgm-3) and minimum in the monsoon (2.3 ± 0.7 μg m−3) season and moderate (~3.7 μg m−3) during the pre and post monsoon seasons was observed. The diurnal variation of BC concentration shows two peaks, one in the morning (07:00–08:00 h local time (LT)) and other prominent peak in the evening hours (19:00–21:00 h LT), with a minimum peak in the afternoon (~16:00 h LT), which could be associated with diurnal variation in local sources, boundary-layer dynamics and synoptic meteorology. The relationship between measured BC concentration and the meteorological parameters for the study location reveals a positive (negative) correlation with the mean diurnal range of air temperature (relative humidity, wind speed and rainfall). The estimated monthly mean absorption Angstrom exponent values range from 0.87 to 1.13 suggesting the change in the sources from fossil-fuel burning in the monsoon and post-monsoon periods to biomass burning in the winter and pre-monsoon. The concentration weighted trajectories analysis suggests that the potential source regions contributing to the observed BC concentration change seasonally and are positioned in the north, northwest of the observational site and in central India.

New Evidences on Anomalous Phenomenon of Buildings in Regulating Urban Climate From Observations in Beijing, China

AbstractUrban buildings and parks play an important role in regulating urban climate and ecosystem services. Diurnal air temperature range (DTRa) of rocklike buildings is commonsensically regarded as higher due to no latent heat from evapotranspiration and its smaller thermal inertia compared to wet soil. Therefore, the building DTRa is supposed to be higher than that of parks due to its building fabric. However, we found an opposite phenomenon (smaller building DTRa than that of parks), and the underlying mechanisms explaining this phenomenon are unclear. Here we conducted, in Beijing (China), a long‐term observational campaign of standard meteorological variables and radiation/energy fluxes to provide a new valuable evidence (a part of external energy) to explain this phenomenon. The observations indicated external heat energies from horizontal advection and anthropogenic heat sources. We found a significantly lower building DTRa than that of parks (ΔDTRa =2.53±1.93 °C), with a maximum difference of 3.54±1.96 °C in autumn; which was mainly attributed to higher daily minimum air temperature. We also found the large differences in air temperature contribution between the buildings and the parks happened mainly at night. The external heat sources of the building contributed 16.71% to the nighttime air temperature, which was higher than that of the parks (8.39%). The more indoor and outdoor anthropogenic heat sources in the building footprints were the major cause of the slower decrease in Tmin. The comparison between buildings and parks can be extensively applied to analyzing the effects of urbanization on climate.

Mars Science Laboratory Observations of the 2018/Mars Year 34 Global Dust Storm

AbstractMars Science Laboratory Curiosity rover observations of the 2018/Mars year 34 global/planet‐encircling dust storm represent the first in situ measurements of a global dust storm with dedicated meteorological sensors since the Viking Landers. The Mars Science Laboratory team planned and executed a science campaign lasting approximately 100 Martian sols to study the storm involving an enhanced cadence of environmental monitoring using the rover's meteorological sensors, cameras, and spectrometers. Mast Camera 880‐nm optical depth reached 8.5, and Rover Environmental Monitoring Station measurements indicated a 97% reduction in incident total ultraviolet solar radiation at the surface, 30K reduction in diurnal range of air temperature, and an increase in the semidiurnal pressure tide amplitude to 40 Pa. No active dust‐lifting sites were detected within Gale Crater, and global and local atmospheric dynamics were drastically altered during the storm. This work presents an overview of the mission's storm observations and initial results.

Spatio-temporal analysis of diurnal air temperature parameterization in Weather Stations over Iran

Diurnal air temperature modeling is a beneficial experimental and mathematical approach which can be used in many fields related to Geosciences. The modeling and spatio-temporal analysis of air Diurnal Temperature Cycle (DTC) was conducted using data obtained from 105 synoptic stations in Iran during the years 2013-2014 for the first time; the key variable for controlling the cosine term in DTC modeling known as β was analyzed and considered both as monthly and annual parameter. The effect of environmental variables of humidity, pressure, diurnal air temperature range, and wind speed were analyzed on β. The results showed that there is no significant difference between considering β as monthly (dynamic) or annual (constant) parameter through the year. The RMSE of approach with dynamic β was 2.1 °C and with constant 2.2 °C at 95% percent of whole data in all stations. The analysis of environmental variables showed that humidity had an indirect effect on β. Low pressure areas showed higher β values but high pressure areas showed higher variability in β and lower mean values. In areas with high air diurnal temperature range, lower β values with less standard deviation were observed. High wind areas showed positive effect on β values.

Maximum and Minimum Soil Surface Temperature Trends Over China, 1965–2014

AbstractMinimum and maximum soil surface temperatures have shown significant warming trends since the midtwentieth century in China, with minimum temperatures rising at a faster pace than maximums, resulting in a decrease in the soil surface diurnal temperature range. Similar to air temperature, these changes demonstrate spatial coherence, with regions at higher latitudes experiencing relatively more change. While increases in air temperatures in China slowed after 1998, paralleling the global “warming hiatus,” soil temperatures at the surface and in shallow layers have continued to rise across China. The increases in soil surface temperatures are fastest at night since 1998, reducing the soil surface diurnal temperature range. Thus, we find that while the decrease in the diurnal air temperature range mainly happened during the earlier “dimming” period ending around 1988, the decrease in the diurnal soil surface temperature range is detectable only during the renewed dimming period after 1998. This has caused soil temperatures at the surface and in shallow layers to diverge from air temperatures since 1998. Although changes in soil temperatures were associated with changes in air temperature, the patterns of change are different. Calculations using only nonurban stations show similar warming rates, indicating that the effects of urbanization are small.

Change of climate conditions in the forest area of South Yakutia

A statistical analysis of meteorological parameters which influence the intensity of exogenous processes in the forest area of South Yakutia has been performed. The indicated increase in mean annual air and soil temperature rates occurred non-uniformly. Annual precipitation increase was due to precipitation rates in cold or transitional seasons; increase in snow cover depth and decrease in diurnal air temperature range was observed in cold season.

Biological and Environmental Controls on Evaporative Fractions at AmeriFlux Sites

AbstractKnowledge of the evaporative fraction (EF: the ratio of latent heat flux to the sum of sensible and latent heat fluxes) and its controls is particularly important for accurate estimates of water flux, heat exchange, and ecosystem response to climatic changes. In this study, the biological and environmental controls on monthly EF were evaluated across 81 AmeriFlux sites, mainly in North America, for 2000–12. The land-cover types of these sites include forest, shrubland, grassland, and cropland, and the local climates vary from humid to arid. The results show that vegetation coverage, indicated by the normalized difference vegetation index (NDVI), has the best agreement with EF (site-averaged partial correlation coefficient ρ = 0.53; significance level p &lt; 0.05) because of vegetation transpiration demand. The minimum air temperature is closely related to EF (site-averaged ρ = 0.51; p &lt; 0.05) because of the inhibition of respiratory enzyme activity. Relative humidity, an indicator of surface aridity, shows a significant positive correlation with EF (site-averaged ρ = 0.46; p &lt; 0.05). The impacts of wind speed and diurnal air temperature range on EF depend on land-cover types and are strong over grasslands and cropland. From these findings, empirical methods were established to predict monthly EF using meteorological data and NDVI. Correlation coefficients between EF estimates and observations range from 0.80 to 0.93, with root-mean-square errors varying from 0.09 to 0.12. This study demonstrates the varying controls on EF across different landscapes and enhances understanding of EF and its dynamics under changing climates.