Average Diurnal Temperature Range Research Articles

Modelling alteration of leaf coloration peak date in Cotinus coggygria in a high-elevation karst region

• The leaf coloration peak date is correlated with temperature and precipitation. • Generalized additive method can predict the leaf coloration peak date well. • Spring phenology may play an important role in predicting autumn phenology. • The leaf coloration peak date can be delayed due to future warming. The importance of deciduous plants’ autumn phenological phase is reflected not only in the material cycle but also in the fall foliage ecotourism industry. However, the lack of observation data has made it difficult to model the phase of deciduous plants in the high-elevation karst region. Based on the data between 2001 and 2020, methods including multiple linear regression, multivariate binomial regression, robust regression, ridge regression, elastic net, and generalized additive were utilized to find out the correlation of the temperature and the precipitation with Cotinus coggygria ’s leaf coloration peak date variation in the related regions of China. The mean absolute error, root mean squared error, coefficient of determination, and ratio of performance to interquartile distance were applied to evaluate the prediction accuracy. Generalized additive model's better performance suggested its capacity as a useful tool in prediction. The results showed that the increase of prophase temperature and the decrease of prophase precipitation could delay the leaf coloration peak date, while the date could be earlier on the contrary. Besides, the number of days with the daily maximum temperature continuously being above 20°C before November 10th exerted the highest contribution in the prediction of the date. Moreover, we showed that a higher average diurnal temperature range in mid-May could defer the date as an objective contributor in prediction. This indirectly reveals the importance of spring phenological phase in predicting the autumn phenological phase. Finally, the model forecasted a trend of the leaf coloration peak date delay from 2021 to 2100 under different emissions scenarios, showing the effects of warming on the plant's growth season and even the development of ecotourism.

Evaluation and Projection of Diurnal Temperature Range in Maize Cultivation Areas in China Based on CMIP6 Models

The diurnal temperature range (DTR) is an important meteorological component affecting maize yield. The accuracy of climate models simulating DTR directly affects the projection of maize production. We evaluate the ability of 26 Coupled Model Intercomparison Project phase 6 (CMIP6) models to simulate DTR during 1961–2014 in maize cultivation areas with the observation (CN05.1), and project DTR under different shared socioeconomic pathway (SSP) scenarios. The root mean square error (RMSE), standard deviation (SD), Kling-Gupta efficiency (KGE) and comprehensive rating index (CRI) are used in the evaluation of the optimal model. The results show that CMIP6 models can generally reproduce the spatial distribution. The reproducibility of the annual average DTR in the maize cultivation areas is better than that in China but lower for the maize-growing season. The optimal model (EC-Earth3-Veg-LR) is used in the projection. Under the two SSPs, the DTR decreases compared with the historical period, especially in Northwest and North China. The DTR under SSP245 remains unchanged (annual) or increases slightly (growing season) during 2015–2050, while a significant decreasing trend is observed under SSP585. This highlights the importance of evaluating DTR in maize cultivation areas, which is helpful to further improve the accuracy of maize yield prediction.

Identification of bio-climatic determinants and potential risk areas for Kyasanur forest disease in Southern India using MaxEnt modelling approach

BackgroundKyasanur forest disease (KFD), known as monkey fever, was for the first time reported in 1957 from the Shivamogga district of Karnataka. But since 2011, it has been spreading to the neighbouring state of Kerala, Goa, Maharashtra, and Tamil Nadu. The disease is transmitted to humans, monkeys and by the infected bite of ticks Haemaphysalis spinigera. It is known that deforestation and ecological changes are the main reasons for KFD emergence, but the bio-climatic understanding and emerging pathways remain unknown.MethodsThe present study aims to understand the bio-climatic determinants of distribution of tick vector of KFD in southern India using the Maximum Entropy (MaxEnt) model. The analysis was done using 34 locations of Haemaphysalis spinigera occurrence and nineteen bio-climatic variables from WorldClim. Climatic variables contribution was assessed using the Jackknife test and mean AUC 0.859, indicating the model performs with very high accuracy.ResultsMost influential variables affecting the spatial distribution of Haemaphysalis spinigera were the average temperature of the warmest quarter (bio10, contributed 32.5%), average diurnal temperature range (bio2, contributed 21%), precipitation of wettest period (bio13, contributed 17.6%), and annual precipitation (bio12, contributed 11.1%). The highest probability of Haemaphysalis spinigera presence was found when the mean warmest quarter temperature ranged between 25.4 and 30 °C. The risk of availability of the tick increased noticeably when the mean diurnal temperature ranged between 8 and 10 °C. The tick also preferred habitat having an annual mean temperature (bio1) between 23 and 26.2 °C, mean temperature of the driest quarter (bio9) between 20 and 28 °C, and mean temperature of the wettest quarter (bio8) between 22.5 and 25 °C.ConclusionsThe results have established the relationship between bioclimatic variables and KFD tick distribution and mapped the potential areas for KFD in adjacent areas wherein surveillance for the disease is warranted for early preparedness before the occurrence of outbreaks etc. The modelling approach helps link bio-climatic variables with the present and predicted distribution of Haemaphysalis spinigera tick.

A Factor Separation Study of the Effect of Synoptic‐Scale Wind, Atmospheric Moisture and of Their Synergy on the Diurnal Temperature Range During the Israeli Summer

AbstractThe trend of the decrease in the global average diurnal temperature range (DTR) is one of the clearest signals in twentieth century climate data. Regionally, DTR trends exhibit large variations. A factor separation analysis was conducted to investigate the impact of atmospheric moisture, synoptic‐scale winds, and their synergy on the DTR during the Israeli summer. The Weather Research and Forecasting (WRF) Single Column Model was run for summer representative days, at four locations in Israel. In almost all cases, the contribution of the factors and of their synergy to the DTR was dominated by their contribution to the diurnal minimum temperature, Tmin. The largest contribution resulted from atmospheric moisture, reducing the DTR. The contribution of synoptic‐scale winds showed more variability, with significant differences in both magnitude and sign on different days. The sign of the effect on Tmin depended on the relative direction and magnitude of the nocturnal synoptic‐scale wind with respect to the local wind, which in turn determined the effect on the low‐level jet (LLJ) and vertical mixing. The contribution from synergy between the two factors depended on the effect of moisture on the LLJ and on the effect of the synoptic‐scale winds on moisture advection in or out of the atmospheric column. All cases were classified into groups depending on the sign of contributions of the single factors and of their synergy when analyzing the DTR observed trends. These results highlight the importance of the synoptic wind, of its synergy with atmospheric moisture and of the feedback mechanisms.

Dual Effects of Synoptic Weather Patterns and Urbanization on Summer Diurnal Temperature Range in an Urban Agglomeration of East China

Previous studies on the impact of urbanization on the diurnal temperature range (DTR) have mainly concentrated on the intra-seasonal and interannual–decadal scales, while relatively fewer studies have considered synoptic scales. In particular, the modulation of DTR by different synoptic weather patterns (SWPs) is not yet fully understood. Taking the urban agglomeration of the Yangtze River Delta region (YRDUA) in eastern China as an example, and by using random forest machine learning and objective weather classification methods, this paper analyzes the characteristics of DTR and its urban–rural differences (DTRU–R) in summer from 2013 to 2016, based on surface meteorological observations, satellite remote sensing, and reanalysis data. Ultimately, the influences of urbanization-related factors and different large-scale SWPs on DTR and DTRU–R are explored. Results show that YRDUA is controlled by four SWPs in the 850-hPa geopotential height field in summer, and the DTRs in three sub-regions are significantly different under the four SWPs, indicating that they play a role in regulating the DTR in YRDUA. In terms of the average DTR for each SWP, the southern sub-region of the YRDUA is the highest, followed by the northern sub-region, and the middle sub-region is the lowest, which is most significantly affected by high-level urbanization and high anthropogenic heat emission. The DTRU–R is negative and differs under the four different SWPs with variation in sunshine and rainfall. The difference in anthropogenic heat flux between urban and rural areas is one of the potentially important urbanization-related drivers for DTRU–R. Our findings help towards furthering our understanding of the response of DTR in urban agglomerations to different SWPs via the modulation of local meteorological conditions.

Projections of excess mortality related to diurnal temperature range under climate change scenarios: a multi-country modelling study

SummaryBackgroundVarious retrospective studies have reported on the increase of mortality risk due to higher diurnal temperature range (DTR). This study projects the effect of DTR on future mortality across 445 communities in 20 countries and regions.MethodsDTR-related mortality risk was estimated on the basis of the historical daily time-series of mortality and weather factors from Jan 1, 1985, to Dec 31, 2015, with data for 445 communities across 20 countries and regions, from the Multi-Country Multi-City Collaborative Research Network. We obtained daily projected temperature series associated with four climate change scenarios, using the four representative concentration pathways (RCPs) described by the Intergovernmental Panel on Climate Change, from the lowest to the highest emission scenarios (RCP 2.6, RCP 4.5, RCP 6.0, and RCP 8.5). Excess deaths attributable to the DTR during the current (1985–2015) and future (2020–99) periods were projected using daily DTR series under the four scenarios. Future excess deaths were calculated on the basis of assumptions that warmer long-term average temperatures affect or do not affect the DTR-related mortality risk.FindingsThe time-series analyses results showed that DTR was associated with excess mortality. Under the unmitigated climate change scenario (RCP 8.5), the future average DTR is projected to increase in most countries and regions (by −0·4 to 1·6°C), particularly in the USA, south-central Europe, Mexico, and South Africa. The excess deaths currently attributable to DTR were estimated to be 0·2–7·4%. Furthermore, the DTR-related mortality risk increased as the long-term average temperature increased; in the linear mixed model with the assumption of an interactive effect with long-term average temperature, we estimated 0·05% additional DTR mortality risk per 1°C increase in average temperature. Based on the interaction with long-term average temperature, the DTR-related excess deaths are projected to increase in all countries or regions by 1·4–10·3% in 2090–99.InterpretationThis study suggests that globally, DTR-related excess mortality might increase under climate change, and this increasing pattern is likely to vary between countries and regions. Considering climatic changes, our findings could contribute to public health interventions aimed at reducing the impact of DTR on human health.FundingKorea Ministry of Environment.

Climatic influence on the magnitude of COVID-19 outbreak: a stochastic model-based global analysis

ABSTRACT We investigate the climatic influence on COVID-19 transmission risks in 228 cities globally across three climatic zones. The results, based on the application of a Boosted Regression Tree algorithm method, show that average temperature and average relative humidity explain significant variations in COVID-19 transmission across temperate and subtropical regions, whereas in the tropical region, the average diurnal temperature range and temperature seasonality significantly predict the infection outbreak. The number of positive cases showed a decrease sharply above an average temperature of 10°C in the cities of France, Turkey, the US, the UK, and Germany. Among the tropical countries, COVID-19 in Indian cities is most affected by mean diurnal temperature, and those in Brazil by temperature seasonality. The findings have implications on public health interventions, and contribute to the ongoing scientific and policy discourse on the complex interplay of climatic factors determining the risks of COVID-19 transmission.

Projections of Excessive Mortality Related to Diurnal Temperature Range Under Climate Change Scenarios: A Multi-Country Study

Background: Various retrospective studies report that a higher diurnal temperature range (DTR) increases mortality risk. This study projects the impact of DTR on future mortality across 445 communities in 20 countries. Methods: We first estimated the DTR-related mortality risk based on the historical daily time-series of mortality and of weather factors from 1985 to 2015. Next, we projected the excess deaths attributable to the DTR during the current (1985–2015) and future (2020–2099) periods using daily DTR series under four climate-change scenarios. We then calculated the future excess deaths based on two assumptions: warmer temperatures affect or do not affect the DTR-mortality risk. Findings: DTR was associated with excess mortality in our time-series analyses. Under the unmitigated scenario, the future average DTR is projected to increase in most countries (-0·4–1·6 °C), and the increasing pattern was more evident in the United States, south-central Europe, Mexico, and South Africa. The excess deaths currently attributable to DTR were estimated to be 0·2–7·4%. Furthermore, the DTR-related mortality risk increased with an increasing average temperature. Based on the positive interactive effect between DTR and temperature, the DTR-related excess deaths are projected to increase in all countries (1·4–10·3%) in 2090–2099. Interpretation: This study suggests that the DTR-related excess mortality may increase globally under climate change, and this increasing pattern may vary between countries. Our findings can contribute to both international and regional public health interventions to reduce the DTR impacts on health under climate change. Funding Statement: Ho Kim is supported by the Korea Ministry of Environment via the “Climate Change Correspondence Program” (2014001310007). Declaration of Interests: All authors report no financial relationships with commercial interests.

Global diurnal temperature range (DTR) changes since 1901

Previous observational analyses show that the land-surface diurnal temperature range (DTR) has decreased in the past 6 decades worldwide. Based on a newly developed China Meteorological Administration–Land Surface Air Temperature (CMA-LSAT) dataset, we analyzed the DTR changes between 1901 and 2014. Results indicate that the global land surface DTR significantly decreased at a rate of − 0.036 °C decade− 1 over the 1901–2014 period, mainly due to the large decrease in DTR from 1951 to 2014. For the first half of the twentieth century, most grid boxes (spatial resolution 5° × 5°) show a positive DTR trend, with the positive trends of 32.4% grid boxes being statistically significant, leading to a large and significant increase of 0.048 °C decade− 1 in DTR. However, a dramatic reversal in DTR change occurred in early 1950s, with most parts of global lands exhibiting a shift from increasing to decreasing trends. The global land average DTR decrease during 1951–2014 was − 0.054 °C decade− 1, with 45.0% grid boxes showing significant negative trends. The reverse phenomenon is more obvious in the Northern Hemisphere than that in the Southern Hemisphere. For the periods 1979–2014 and 1998–2014, the decreasing trends in DTR mainly occur in the Northern Hemisphere. The DTR in the Southern Hemisphere experienced much larger increases during the two recent periods than during the period 1951–2014. Asia, Eastern North America, and Australia exhibited widespread decreases in DTR, although the trend pattern for global DTR is generally mixed during 1979–2014 and 1998–2014. There is a good negative correlation between DTR and precipitation in the Northern Hemisphere from 1901 to 2014, with a correlation coefficient of − 0.61. The change in precipitation and number of volcanic eruptions, and the “early brightening” of Europe (Stockholm) all benefit the increase of DTR at global and regional scales in the first half of the twentieth century.

β-glucan content spatial distribution characteristics and its influencing factors of cultivated barley in Qinghai-Tibet Plateau, China

β-glucan content spatial distribution characteristics of cultivated barley in Qinghai-Tibet Plateau were investigated based on the data measured from 83 sampling sites. The results showed that β-glucan content exhibited a macrocosm pattern of spatial distribution along the horizontal direction in Qinghai-Tibet Plateau, with staggered patches of different values. Two regions of higher β-glucan content were observed with centers of Guide and Tongde in Qinghai Province and Xiahe and Hezuo in Gansu Province (northeast), and Jiangzi, Bailang, Xietongmen, Shigatse, Lazi, Kangma, Gongga and Qushui in Tibet (southwest). Along the vertical direction, β-glucan content distribution pattern appeared with double peak curves. There were two high value zones between the altitudes from 2700 m to 3000 m and from 3600 m to 3900 m, with average β-glucan content value of (5.7±1.7)% and (4.6±1.1)%, respectively. Influencing factors of β-glucan content with importance value index more than 40.0% were as follows: grain color ＞ ear density ＞ average relative humidity in September ＞ soil available N content ＞ soil available K content ＞ average diurnal temperature range in June ＞ ≥10 ℃ accumulated temperature ＞ average annual temperature ＞ soil available P content ＞ average diurnal temperature range in September.

Analysis of temperature variability over north-west part of India for the period 1970–2000

The main aim of this study was to investigate the temporal trends in maximum (T max), minimum (T min) temperature and diurnal temperature range (DTR) at annual and seasonal basis for seven sites in north-west region of India. The analysis was carried out for period of 31 years (1970–2000). The magnitude of trends and their significance were determined using Sen’s slope and Mann–Kendall methods. Additionally, persistence analysis of annual average DTR and mean temperature (T mean) has been carried out using cumulative annual mean (CAM) method. It is clear from the results that during last three decades the majority of sites showed decrease/(increases) in DTR/(T min) trends for seasonal and annual time scale. While, trends in annual and seasonal T max were observed insignificant. CAM analysis demonstrated that T mean has increased consistently since 1987–1988 onwards at majority of the sites. Further, correlation analysis revealed that rainfall along with potential evapotranspiration may be one of the important reasons for observed DTR decrease.

Impact of volcanic stratospheric aerosols on diurnal temperature range in Europe over the past 200 years: Observations versus model simulations

AbstractWe analyze the impact of stratospheric volcanic aerosols on the diurnal temperature range (DTR) over Europe using long‐term subdaily station records. We compare the results with a 28‐member ensemble of European Centre/Hamburg version 5.4 (ECHAM5.4) general circulation model simulations. Eight stratospheric volcanic eruptions during the instrumental period are investigated. Seasonal all‐ and clear‐sky DTR anomalies are compared with contemporary (approximately 20 year) reference periods. Clear sky is used to eliminate cloud effects and better estimate the signal from the direct radiative forcing of the volcanic aerosols. We do not find a consistent effect of stratospheric aerosols on all‐sky DTR. For clear skies, we find average DTR anomalies of −0.08°C (−0.13°C) in the observations (in the model), with the largest effect in the second winter after the eruption. Although the clear‐sky DTR anomalies from different stations, volcanic eruptions, and seasons show heterogeneous signals in terms of order of magnitude and sign, the significantly negative DTR anomalies (e.g., after the Tambora eruption) are qualitatively consistent with other studies. Referencing with clear‐sky DTR anomalies to the radiative forcing from stratospheric volcanic eruptions, we find the resulting sensitivity to be of the same order of magnitude as previously published estimates for tropospheric aerosols during the so‐called “global dimming” period (i.e., 1950s to 1980s). Analyzing cloud cover changes after volcanic eruptions reveals an increase in clear‐sky days in both data sets. Quantifying the impact of stratospheric volcanic eruptions on clear‐sky DTR over Europe provides valuable information for the study of the radiative effect of stratospheric aerosols and for geo‐engineering purposes.

Energy storage and C:N:P variation in a holometabolous insect (Curculio davidi Fairmaire) larva across a climate gradient

Increasing empirical evidence has documented variability in elemental composition within species. However, the extent, causes, and pattern of variability in consumer stoichiometry across a large geographical scale are not well understood. Here, we investigated this issue using a holometabolous insect, weevils (Curculio davidi Fairmaire). Larvae of this species store energy needed for diapause, and variable energy requirements across the geographic range of this species could lead to differences in body elemental composition. Our results showed that variability was high (assessed as the coefficient of variation (CV)) in larval body nitrogen (N) and phosphorus (P) (CV, 10% for N and 13% for P) compared to emerging adults (CV, 5% for N and 8% for P). Temperature-related factors explained more variation than other climatic factors and food for carbon (C), N and P in weevil. In warmer regions, larval C concentration was higher, while N and P were lower. The high C content of weevil larvae relative to both their food source and their adult stage was attributed to energy storage. Across the climatic gradient of its geographic range, larval body C content increased with mean annual temperature and decreased with average diurnal temperature range. This finding implies that temperature-related C storage drives the high variability in elemental composition of larvae across the climate gradient, and also effectively dampens the stoichiometric imbalance between consumers and food resources while serving as an energy reservoir for overwintering and metamorphosis.

Changes in diurnal temperature range in Bangladesh during the time period 1961–2008

Diurnal temperature range (DTR) is a meteorological indicator independent of internal climate variation and therefore, considered as a signature of observed climate change. It has been observed that global averaged DTR has decreased significantly in the last fifty years. However, the change in DTR has regional and seasonal characteristics. A study has been carried out in this paper to analyze the spatial and seasonal patterns in the trends of DTR in Bangladesh. Daily temperature data from 18 stations for the time period 1961–2008 has been used for the study. The result shows that both mean minimum and mean maximum temperatures of Bangladesh have increased significantly at a rate of 0.15°C/decade and 0.11°C/decade, respectively. However, the increase of minimum temperature compared to maximum temperature is not high enough to cause a significant change in average diurnal temperature range in Bangladesh. Seasonal DTR trends show a decrease in winter and pre-monsoon DTR, and an increase in monsoon DTR. Spatial distribution of DTR trends shows an increase of annual DTR in the southeastern coastal stations and decrease in the northern stations of Bangladesh. Significant negative relation between rainfall and DTR is observed in Bangladesh. Regression analysis shows that an annual increase of 1% of rainfall is correlated with a decrease of DTR by 0.1°C.

Examination of diurnal temperature range at coterminous U.S. stations during Sept. 8–17, 2001

The tragic events of Sept. 11, 2001 resulted in suspension of commercial flights over North America. It has been suggested that the diurnal temperature range (DTR) increased due to an absence of airplane contrails. This study examined hourly data observed at 288 stations. The average DTR, temperature, maximum/minimum temperature and relative humidity were found for each day in 2001 and compared to the average value occurring during 1975–2005. For the coterminous U.S., the DTR averaged over the period Sept. 11–14, 2001 was about 1°C larger than that found for the 3 days prior and after the flight ban. However, the day-to-day DTR does not correlate well with the flight ban. Plots of the change in DTR throughout North America during Sept. 8–17 show changes consistent with the natural progression of weather systems.

Weekend effect in diurnal temperature range in China: Opposite signals between winter and summer

Intense human activity can impact weather and climate in many ways. One possible important consequence is the weekly cycle (so‐called weekend effect) in the diurnal temperature range (DTR). The weekend effect is defined as the average DTR for Saturday through Monday minus the average DTR for Wednesday through Friday. In the present study, the weekend effect in the DTR over east China combined with station observations of maximum and minimum temperatures, relative humidity, and total solar irradiance for the period 1955–2000 was analyzed. Results show that the weekend effect in the DTR has the opposite signal between winter (December, January, and February) and summer (June, July, and August). Wintertime DTR tends to have a positive weekend effect (i.e., larger DTR in weekend days compared to weekdays), in association with increased maximum temperature and total irradiance but decreased relative humidity. While summertime DTR displays a much stronger and significantly negative weekend effect (i.e., smaller DTR in weekend days), in association with decreased maximum temperature and total solar irradiance but increased relative humidity and a greater number of rainy days. This study indicates that the DTR difference between weekend and weekdays is predominantly related to weekly changes in the maximum temperature. The weekend effect in the DTR and maximum temperature is also found in the Reanalysis 2 data. The weekend effect in winter is supported by an analogous holiday (Spring Festival) effect. Since the late 1970s, the weekend effect has been enhanced in both winter and summer, concurrent with rapid development and enhanced human activity in China. The direct and indirect effects of human‐related aerosols on radiation, cloud, precipitation, and so on, might play an important role in generating the opposite signal in the weekend effect for different seasons. During a dry winter, the reduction of aerosol concentrations may overwhelmingly impact on the DTR through a direct effect, i.e., by increasing total solar irradiance near the surface and raising the daytime temperature and maximum temperature and lowering relative humidity. By contrast, in summer the indirect effect of aerosols, i.e., reduction in precipitation efficiency caused by more numerous and smaller cloud droplets, would largely be responsible for the increased numbers of rainy days, the reduction of the total solar irradiance, and the lowering of the maximum temperature and DTR.

Extending the record of photosynthetic activity in the eastern United States into the presatellite period using surface diurnal temperature range

In this study, we demonstrate that mid‐latitude surface measurements of diurnal temperature range (DTR) can be used to reconstruct decadal variability of regional‐scale terrestrial photosynthetic activity 1) during and prior to the period with satellite retrievals of land greenness and 2) without the need for moisture data. While the two relative maxima present in the seasonal evolution of DTR can determine the beginning and the end of the growing season, the summertime average DTR can be used as a proxy of summertime terrestrial photosynthesis. In a case study in the eastern United States (1966–1997), the DTR reconstructions indicate significant natural decadal variability in photosynthetic activity, but no secular, long‐term trend. The summertime photosynthesis was found to be controlled primarily by moisture availability. Also, contrary to existing model parameterizations, the timing of spring onset was found to depend on both temperature and moisture.

Observations of a "weekend effect" in diurnal temperature range.

Using surface measurements of maximum and minimum temperatures from the Global Daily Climatological Network data set, we find evidence of a weekly cycle in diurnal temperature range (DTR) for many stations in the United States, Mexico, Japan, and China. The "weekend effect," which we define as the average DTR for Saturday through Monday minus the average DTR for Wednesday through Friday, can be as large as 0.5 K, similar to the magnitude of observed long-term trends in DTR. This weekend effect has a distinct large-scale pattern that has changed only slightly over time, but its sign is not the same in all locations. The station procedures and the statistical robustness of both the individual station data and the patterns of DTR differences are thoroughly examined. We conclude that the weekend effect is a real short time scale and large spatial scale geophysical phenomenon, which is necessarily human in origin. We thus provide strong evidence of an anthropogenic link to DTR, an important climate indicator. Several possible anthropogenic mechanisms are discussed; we speculate that aerosol-cloud interactions are the most likely cause of this weekend effect, but we do not rule out others.

Contrails reduce daily temperature range.

The potential of condensation trails (contrails) from jet aircraft to affect regional-scale surface temperatures has been debated for years, but was difficult to verify until an opportunity arose as a result of the three-day grounding of all commercial aircraft in the United States in the aftermath of the terrorist attacks on 11 September 2001. Here we show that there was an anomalous increase in the average diurnal temperature range (that is, the difference between the daytime maximum and night-time minimum temperatures) for the period 11-14 September 2001. Because persisting contrails can reduce the transfer of both incoming solar and outgoing infrared radiation and so reduce the daily temperature range, we attribute at least a portion of this anomaly to the absence of contrails over this period.

Littoral water temperature response to experimental shoreline logging around small boreal forest lakes

Shoreline logging did not significantly increase average littoral water temperatures in two small boreal forest lakes in northwestern Ontario, Canada. However, over the early summer monitoring period clearcut shorelines were associated with increases of 1–2°C in maximum littoral water temperature, and increases of 0.3–0.6°C in average diurnal temperature range, compared with undisturbed shorelines or shorelines with 30-m shoreline buffer strips. Comparison of simultaneous water temperatures at littoral locations with and without shoreline forest showed that increased temperatures were caused by daytime heating.