Daily Temperature Range Research Articles

Comparison of extreme temperature response to 0.5 °C additional warming between dry and humid regions over East–central Asia

The additional 0.5 °C warming from 1.5 to 2°C global target has a significant impact on the occurrence of extreme temperature events. While the arid and semi‐arid areas (ASA) and humid areas (HA) present different response characteristics to the additional global mean 0.5 °C warming due to their differences in thermal properties. In this study, both the stabilized and transient 1.5 °C (2 °C) global warming scenarios projected by the Community Earth System Model (CESM) are used to compare the extreme temperature responses between the ASA and HA to the 2 and 1.5 °C global warming targets over East–central Asia. The results indicate that cold fixed‐threshold indices (frost days [FD] and icing days [ID]) will decrease more rapidly in ASA, by approximately 10 days (1.5 °C) and 15 days (2 °C) compared to the historical period, respectively. Warm fixed‐threshold indices (summer days [SU] and tropical nights [TR]) will become more common in HA, especially southeast of China. Under 1.5 °C target, the increase of intensity indices is equal to the average temperature warming response (1.5 °C), while the additional 0.5 °C warming makes the response of intensity indices much greater than 0.5 °C. Under 0.5 °C warmer world, the daily temperature range (DTR) will experience a 0.5 °C increase in most HA and a 0.2–0.5 °C decrease in ASA during winter. As a whole, the additional 0.5 °C warming has an amplified effect and the 1.5 °C global warming target could reduce the extreme temperature events significantly over East–central Asia.

Using big data to predict the likelihood of low falling numbers in wheat

AbstractBackground and objectivesPreharvest sprouting in wheat reduces quality and impacts farmer profitability. The international recognized falling number test can be used to measure that damage. Trying to understand the complex interactions that cause a reduction in wheat quality, equating to low falling number levels, is challenging. An alternative research approach to replicated experiments was to use a multiseason dataset of load‐by‐load delivery information to investigate whether correlations between falling number levels and 40 climate measurements could be identified.FindingsThis study used over 250,000 falling number data points from individual truckloads tested during seven harvests in Western Australia. The analyses identified relative humidity measured at the maximum temperature and daily temperature range as having consistent correlations with falling number levels over multiple seasons. Other climate measurements were also observed to have significant correlations with falling number, but these were less consistent within and between seasons.ConclusionsThe linkage of humidity and temperature range levels in the period before harvest commences to the occurrence of low falling number levels helps to further understand the complex interactions that change starch quality.Significance and noveltyThe findings demonstrate that value can be obtained from the use of a large, nonexperimentally designed dataset.

Evaluating the impact of rainfall and temperature on wheat dough strength in Western Australia

AbstractBackground and objectivesWestern Australian wheat farmers rely on the international market to sell their wheat. One advantage they have in the market place is Australia's reputation for good and reliable wheat quality. However, consecutive years of weaker‐than‐expected dough strength placed specific consistency concerns on Western Australian hard‐grained wheat exports. To investigate why weak dough strength occurred, a multi‐season set of data was compiled. It was made up of quality results from historical crop reports and breeder trials. Recycling of data was an efficient initial step to examine the problem, but to overcome limitations, modeled climate measurements and phenotype information needed to be combined with the quality data to allow mixed model statistics to be used for analysis of the unbalanced data.FindingsThe key findings were three climate measurements linked to weak dough properties as measured by extensograph maximum resistance. A negative relationship between dough strength and rainfall in the period 60 days after flowering, tested as the percentage of total growing season rainfall, was found. Two temperature‐related measurements were identified as having a positive relationship with dough strength. These were the number of consecutive days that had a maximum temperature of ≥28°C and mean daily temperature range occurring during the 60‐day period after flowering.ConclusionsThe combined impact of moisture and temperature levels during the post‐flowering period on wheat dough strength builds on the previous understanding of high temperatures changing dough strength.Significance and noveltyThe recycling of data was a useful first step in understanding a complex issue, and the results provide a reference guide for further research into understanding the interaction between a changing growing environment and important wheat quality parameters.

Five Decadal Trends in Averages and Extremes of Rainfall and Temperature in Sri Lanka

In this study, we used a comprehensive set of statistical metrics to investigate the historical trends in averages and extremes of rainfall and temperature in Sri Lanka. The data consist of 55 years (1961–2015) of daily rainfall, maximum temperature (Tmax), and minimum temperature (Tmin) records from 20 stations scattered throughout Sri Lanka. The linear trends were analyzed using the nonparametric Mann–Kendall test and Sen–Theil regression. The prewhitening method was first used to remove autocorrelation from the time series, and the modified seasonal Mann–Kendall test was then applied for the seasonal data. The results show that, during May, 15% of the stations showed a significant decrease in wet days, which may be due to the delayed southwest monsoon (SWM) to Sri Lanka. A remarkable increase in the annual average temperature of Tmin and Tmax was observed as 70% and 55% of the stations, respectively. For the entire period, 80% of the stations demonstrated statistically significant increases of Tmin during June and July. The daily temperature range (DTR) exhibited a widespread increase at the stations located within the southwestern coast region of Sri Lanka. Although changes in global climate, teleconnections, and local deforestation in recent decades at least partially influence the trends observed in Sri Lanka, a formal trend attribution study should be conducted.

Associations between Ambient Temperature and Acute Myocardial Infarction.

BackgroundThe associations between incidence of acute myocardial infarction (AMI) and the ambient temperature were mixed in prior studies.MethodsData of 2033 consecutive admissions of AMI in a central tertiary hospital in North China from 1st Jan 2003 to 31st Dec 2011 were collected. The weather data in this period were from the local meteorological department. Based on the ambient temperature information, we defined several ambient temperature indices, including daily average temperature, extremely low temperature, and daily temperature range, then characterized the independent associations between them and the incidence of AMI.ResultsThe daily average temperature one day before was independently associated with AMI incidence rate: a rise of 5°C of the daily average temperature led to a 5% decrease in AMI admissions. Daily average temperature and temperature range two days before were independently associated with AMI incidence rate: a rise of 5°C of the daily average temperature led to a fall of 6% in AMI admissions, and a rise of 2°C of the daily temperature range led to a rise of 4% in AMI admission.ConclusionLow ambient temperature has substantial association with AMI, and can play an important role in warning and forecasting the incidence.

Forecasting wildfire disease on tobacco: toward developing a high-accuracy prediction model for disease index using local climate factors and support vector regression

Tobacco wildfire disease is common globally, and climate change may increase the risk of outbreaks. Therefore, there is an urgent need to establish an effective climate model to forecast the occurrence of wildfire disease. To design such a model, we collected data for 40 wildfire disease indices via tobacco field surveys and data for 15 climate factors of Guiyang County in China from 2012 to 2016. First, we built multiple linear regression (MLR), stepwise linear regression (SLR) and support vector regression (SVR) models using three climate features (precipitation, mean daily temperature and sunshine duration), and we could not find an effective model. Second, we built three corresponding models using expanded 15 climate features and an in-house WDEM method (the worst descriptor elimination multi-roundly), and the independent test results showed that the best SVR model had not only a higher predictive accuracy ( $$ {Q}_{ext}^2 $$ = 0.94) but also a better stability. Finally, we further evaluated the biological significance of their retained climate features and the single-factor effects of the best model according to the interpretability analysis, and our results indicated that (1) the three climate factors (minimum value of wind velocity, daily range of temperature and daily pressure) strongly affected the occurrence of wildfire disease; (2) the ranges of relative humidity and sunshine hours were negatively correlated with the occurrence of wildfire disease, while daily mean vapour pressure was positively correlated with the occurrence of the disease. Our work enables a useful theoretical prediction for wildfire disease, especially in terms of climate-related predictions.

Average Protein Content and Its Variability in Winter Wheat: A Forecast Model based on Weather Parameters

Abstract In this article, the effect of different weather parameters on the mean height and the variability of the protein content in winter wheat is investigated. The analysis is based on the proteins of 148 800 wheat deliveries in Mecklenburg-Western Pomerania during 2004–15. From April to July, the forecast model was estimated with the following weather parameters: temperature sum, daily temperature range, precipitation, and sunshine duration. A Just and Pope function was estimated as a random intercept model. In addition to the weather parameters, a dummy variable is integrated into the forecast model to record differences in quality between A and B wheat varieties. The results show that 76.5% of the annual variability of the mean protein content can be explained on the basis of these weather parameters. In contrast, weather variables can only explain a small part of the variance in protein content per se.

Climatological Study for the Cherenkov Telescope Array North Site at the Canary Islands I: Temperature, Precipitation, and Relative Humidity

We obtained climate normals over a period of 10 years (2003–2012) at Izaña (2395 m), Tenerife (Spain) with the aim of characterizing the mesoscale climate conditions governing the two astronomical observatories in the Canary Islands: Teide Observatory, located on the summit of Izaña and Roque de los Muchachos Observatory (ORM), approximately 140 km away, on the island of La Palma. Both sites are at the same height (≈2300 m) and share very similar regional climatological conditions. The study was carried out as part of the site selection campaign for the Cherenkov Telescope Array (CTA) in the northern hemisphere, which was finally installed at the ORM. We used long-term and high-quality climate data series recorded by the Centro de Investigación Atmosférica de Izaña (CIAI) at the Izaña Atmospheric Observatory (IZO; WMO#60010). In this paper, we analyze the temperature (central tendency, maxima, minima, and ranges), precipitation (intensities per hour and daily, monthly, and yearly cumulative), and relative humidity. The precipitation data are divided into liquid, snow, and hail. All the results are presented in triplicate, covering the whole series, nighttime, and daytime. The results show a smooth temperature profile with sporadic but moderate extremes, a low daily (24 h) temperature range (median 7.1 °C), and extremely low nighttime temperature range (median 2.7 °C). Rainfall is very rare and sporadic (287 mm a−1), with low intensities. The relative humidity is also low (median 29% and 25th percentile 15%) and follows the precipitation cycle. These results confirm the stability and optimal conditions required to fully operate CTA and other astronomical facilities. The requirements specified in the CTA project documentation are fulfilled.

Trends in Extreme Climate Events over Three Agroecological Zones of Southern Ethiopia

The study aims to assess trends in extremes of surface temperature and precipitation through the application of the World Meteorological Organization’s (WMO) Expert Team on Climate Change Detection and Indices (ETCCDI) on datasets representing three agroecological zones in Southern Ethiopia. The indices are applied to daily temperature and precipitation data. Nonparametric Sen’s slope estimator and Mann–Kendall’s trend tests are used to detect the magnitude and statistical significance of changes in extreme climate, respectively. All agroecological zones (AEZs) have experienced both positive and negative trends of change in temperature extremes. Over three decades, warmest days, warmest nights, and coldest nights have shown significantly increasing trends except in the midland AEZ where warmest days decreased by 0.017°C/year (p<0.05). Temperature extreme’s magnitude of change is higher in the highland AEZ and lower in the midland AEZ. The trend in the daily temperature range shows statistically significant decrease across AEZs (p<0.05). A decreasing trend in the cold spell duration indicator was observed in all AEZs, and the magnitude of change is 0.667 days/year in lowland (p<0.001), 2.259 days/year in midland, and 1 day/year in highland (p<0.05). On the contrary, the number of very wet days revealed a positive trend both in the midland and highland AEZs (p<0.05). Overall, it is observed that warm extremes are increasing while cold extremes are decreasing, suggesting considerable changes in the AEZs.

Estimation of Actual Evapotranspiration Distribution in the Huaihe River Upstream Basin Based on the Generalized Complementary Principle

The accurate estimation of actual evapotranspiration can help improve the utilization of water resources and ease the ecological stress. Based on the generalized complementary principle proposed by Brutsaert in 2015, we used meteorological and hydrological data to estimate the actual evapotranspiration at a resolution of 1 km × 1 km between the years of 1961 and 2000 and also verified the model’s stability. In this study, we used the water balance equation to calibrate the parameters, coupled with the spatial simulation results of the meteorological elements in the actual evapotranspiration model. The estimation results of actual evapotranspiration show that the generalized complementary principle model had high estimation precision in this basin, with an average absolute error of 16.64 mm and an average relative error of 2.25%. With respect to spatial distribution, the average actual evapotranspiration over the years in the basin tended to have high and low distribution in the northern and southern parts of the basin, respectively. The actual evapotranspiration in the basin showed a decreasing trend over the period, with a rate of 24.1 mm/10 years. Correlation coefficient analysis showed that the percentage decreases in percentage sunshine and the decreases in the daily range of temperature were the main reasons for the decrease in actual evapotranspiration.

The Study of Near-surface wind and pollution characteristics in Yuxi Center District

The pilot balloon observation system with dual theodolite was used to investigate the effect of near-surface wind characteristics on pollutant diffusion in Yuxi NO.1 middle school, and by using the meteorological observation data analysis of the different weather characteristic and the impact on the pollutant concentration distribution. The experimental results showed that the predominant wind direction was not so apparent due to the affection of channels to the wind and the valley of the wind. During the observation, the regional atmospheric stability is more unstable and neutral stability, and longer duration of neutral stability would not be good at contamination diffusion. Winds profile observed four types of irregular, reverse, extreme value, normal. Under neutral stability conditions, the degree of fitting of wind profile exponent P in normal-type wind velocity is good, and its value is 0.608. The mountain-valley wind relates to daily range of temperature and the greater this difference in temperature is, the more frequency of mountain-valley wind blowing. In the morning and evening is the transition of mountain-valley wind, the period of time due to wind direction changes, causing the circulate accumulation of the pollutants in the air over the city.

Microclimate variables of the ambient environment deliver the actual estimates of the extrinsic incubation period of Plasmodium vivax and Plasmodium falciparum: a study from a malaria-endemic urban setting, Chennai in India

BackgroundEnvironmental factors such as temperature, relative humidity and their daily variation influence a range of mosquito life history traits and hence, malaria transmission. The standard way of characterizing environmental factors with meteorological station data need not be the actual microclimates experienced by mosquitoes within local transmission settings.MethodsA year-long study was conducted in Chennai, India to characterize local temperature and relative humidity (RH). Data loggers (Hobos) were placed in a range of probable indoor and outdoor resting sites of Anopheles stephensi. Recordings were taken hourly to estimate mean temperature and RH, together with daily temperature range (DTR) and daily relative humidity range. The temperature data were used to explore the predicted variation in extrinsic incubation period (EIP) of Plasmodium falciparum and Plasmodium vivax between microhabitats and across the year.ResultsMean daily temperatures within the indoor settings were significantly warmer than those recorded outdoors. DTR in indoor environments was observed to be modest and ranged from 2 to 6 °C. Differences in EIP between microhabitats were most notable during the hottest summer months of April–June, with parasite development predicted to be impaired for tiled houses and overhead tanks. Overall, the prevailing warm and stable conditions suggest rapid parasite development rate regardless of where mosquitoes might rest. Taking account of seasonal and local environmental variation, the predicted EIP of P. falciparum varied from a minimum of 9.1 days to a maximum of 15.3 days, while the EIP of P. vivax varied from 8.0 to 24.3 days.ConclusionsThis study provides a detailed picture of the actual microclimates experienced by mosquitoes in an urban slum malaria setting. The data indicate differences between microhabitats that could impact mosquito and parasite life history traits. The predicted effects for EIP are often relatively subtle, but variation between minimum and maximum EIPs can play a role in disease transmission, depending on the time of year and where mosquitoes rest. Appropriate characterization of the local microclimate conditions would be the key to fully understand the effects of environment on local transmission ecology.

High frequency temperature variability reduces the risk of coral bleaching

Coral bleaching is the detrimental expulsion of algal symbionts from their cnidarian hosts, and predominantly occurs when corals are exposed to thermal stress. The incidence and severity of bleaching is often spatially heterogeneous within reef-scales (<1 km), and is therefore not predictable using conventional remote sensing products. Here, we systematically assess the relationship between in situ measurements of 20 environmental variables, along with seven remotely sensed SST thermal stress metrics, and 81 observed bleaching events at coral reef locations spanning five major reef regions globally. We find that high-frequency temperature variability (i.e., daily temperature range) was the most influential factor in predicting bleaching prevalence and had a mitigating effect, such that a 1 °C increase in daily temperature range would reduce the odds of more severe bleaching by a factor of 33. Our findings suggest that reefs with greater high-frequency temperature variability may represent particularly important opportunities to conserve coral ecosystems against the major threat posed by warming ocean temperatures.

Habitat structure modifies microclimate: An approach for mapping fine‐scale thermal refuge

Abstract Contemporary techniques predicting habitat suitability under climate change projections often underestimate availability of thermal refuges. Habitat structure contributes to thermal heterogeneity at a variety of spatial scales, but quantifying microclimates at organism‐relevant resolutions remains a challenge. Landscapes that appear homogeneous at large scales may offer patchily distributed thermal refuges at finer scales. We quantified the relationship between vegetation structure and the thermal environment at a scale relevant to small, terrestrial animals using a new approach for mapping fine‐scale thermal heterogeneity. We expected that vegetation would create attenuated microclimates and that the influence of vegetation structure would vary seasonally. We measured shrub volume, horizontal cover and operative temperature (Te) in a sagebrush‐steppe habitat in Idaho, USA, at 534 microsites across two study sites of c. 1 km2 each. We modelled relationships between habitat structure and both mean daily maximum temperature () and mean diurnal temperature range () for each study site during summer and winter. Aerial imagery from unmanned aerial systems was used to estimate shrub volume and canopy cover at 1‐m resolution, and we applied the best fit model to map thermal heterogeneity across broader extents. Increasing shrub volume and cover was associated with lower and , but strengths of the relationships differed between study sites. There was considerable heterogeneity in availability of thermal refuges across sagebrush‐steppe rangelands that have traditionally been considered relatively homogeneous. This technique can help ecologists and land managers identify critical thermal refuges that large‐scale climate modelling can overlook and thus contribute to an understanding of animal–habitat relationships under changing climates and land uses.

Evaluation of a lower-powered analyzer and sampling system for eddy-covariance measurements of nitrous oxide fluxes

Abstract. Nitrous oxide (N2O) fluxes measured using the eddy-covariance method capture the spatial and temporal heterogeneity of N2O emissions. Most closed-path trace-gas analyzers for eddy-covariance measurements have large-volume, multi-pass absorption cells that necessitate high flow rates for ample frequency response, thus requiring high-power sample pumps. Other sampling system components, including rain caps, filters, dryers, and tubing, can also degrade system frequency response. This field trial tested the performance of a closed-path eddy-covariance system for N2O flux measurements with improvements to use less power while maintaining the frequency response. The new system consists of a thermoelectrically cooled tunable diode laser absorption spectrometer configured to measure both N2O and carbon dioxide (CO2). The system features a relatively small, single-pass sample cell (200 mL) that provides good frequency response with a lower-powered pump ( ∼ 250 W). A new filterless intake removes particulates from the sample air stream with no additional mixing volume that could degrade frequency response. A single-tube dryer removes water vapour from the sample to avoid the need for density or spectroscopic corrections, while maintaining frequency response. This eddy-covariance system was collocated with a previous tunable diode laser absorption spectrometer model to compare N2O and CO2 flux measurements for two full growing seasons (May 2015 to October 2016) in a fertilized cornfield in Southern Ontario, Canada. Both spectrometers were placed outdoors at the base of the sampling tower, demonstrating ruggedness for a range of environmental conditions (minimum to maximum daily temperature range: −26.1 to 31.6 °C). The new system rarely required maintenance. An in situ frequency-response test demonstrated that the cutoff frequency of the new system was better than the old system (3.5 Hz compared to 2.30 Hz) and similar to that of a closed-path CO2 eddy-covariance system (4.05 Hz), using shorter tubing and no dryer, that was also collocated at the site. Values of the N2O fluxes were similar between the two spectrometer systems (slope = 1.01, r2 = 0.96); CO2 fluxes as measured by the short-tubed eddy-covariance system and the two spectrometer systems correlated well (slope = 1.03, r2 = 0.998). The new lower-powered tunable diode laser absorption spectrometer configuration with the filterless intake and single-tube dryer showed promise for deployment in remote areas.

A combined stochastic analysis of mean daily temperature and diurnal temperature range

In this paper, a stochastic model, previously proposed for the maximum daily temperature, has been improved for the combined analysis of mean daily temperature and diurnal temperature range. In particular, the procedure applied to each variable sequentially performs the deseasonalization, by means of truncated Fourier series expansions, and the normalization of the temperature data, with the use of proper transformation functions. Then, a joint stochastic analysis of both the climatic variables has been performed by means of a FARIMA model, taking into account the stochastic dependency between the variables, namely introducing a cross-correlation between the standardized noises. The model has been applied to five daily temperature series of southern Italy. After the application of a Monte Carlo simulation procedure, the return periods of the joint behavior of the mean daily temperature and the diurnal temperature range have been evaluated. Moreover, the annual maxima of the temperature excursions in consecutive days have been analyzed for the synthetic series. The results obtained showed different behaviors probably linked to the distance from the sea and to the latitude of the station.

Diurnal water temperature dynamics in lowland rivers: A case study from Central Poland

AbstractThe paper examines spatial and seasonal variations in diurnal water temperature dynamics in lowland rivers. Temperature data was obtained from digital temperature loggers located in nine sites across the Mazovian Lowland during the hydrological year 2016. On the basis of measurement data, mean, maximum, and minimum daily ranges were calculated in the monthly timescale, as well as the timing of extreme temperatures during the day. The results indicate that water temperature dynamics of lowland rivers have a clear seasonal pattern, with the highest variations of temperature in May and June and the lowest in January. Statistically significant differences were found in the daily temperature range between groups of the investigated sites; a higher diurnal temperature range was observed in sites draining a smaller catchment area, while larger rivers were generally more thermally stable in the daily timescale. There was also found an effect of anthropopressure on diurnal temperature dynamics in urbanized catchments, mainly due to impoundments and sewage inflows. Maximum water temperature in the studied sites usually occurred in the morning, from 06:00 to 10:00 CEST, while minimum temperature occurred in the late afternoon, from 14:00 to 18:00 CEST. Spatially, the timing of the maximum and minimum water temperatures during the day was similar in all of the investigated sites, with no statistically significant differences. However, cluster analysis indicated that in the summer half of the year the timing of the extreme temperatures was more varied between investigated sites. The results provide new insight into short-term river thermal behaviour and they are valuable in the context of game fisheries due to the significance of daily temperature variations in fish activity and feeding.

Is extreme climate or moderate climate more conducive to longevity in China?

Climate is closely related to human longevity. In China, there are many climate types. According to national population censuses from 1982 to 2000, most provinces with a high ratio of centenarians are located in western and northwestern China far from the sea; these areas are characterized by a dry, cold climate, very high altitude, very high daily temperature range, strong winds, and partial hypoxia. Meanwhile, provinces with a high ratio of nonagenarians from 1982 to 2000 are located in southern China near the sea. Previous studies have attributed the high ratio of centenarians in western and northwestern China to the extreme local climate. However, centenarians in these areas decreased greatly in 2010, whereas residents in southern China frequently reached 90 to 100years old in 2010. This study aims to explain this strange phenomenon and find whether extreme climate in Tibetan plateau and northwestern China or moderate climate in southern China is more conducive to longevity. The study found that mortality rate in Tibetan plateau is much higher than southern China, then a population evolution experiment was proposed to compare longevity indicators between low mortality rate and high mortality rate and shows that longevity indicators will decrease in the near future and increase above their original levels after several decades when the mortality rate is decreased. Results of this study show individuals in northwestern China do not live as long as those in eastern and southern China. A moderate climate is more conducive to longevity than extreme climate in China. The longevity of a region should be judged by long-term longevity indicators.

Coherent variability between seasonal temperatures and rainfalls in the Iberian Peninsula, 1951–2016

In this work trends of seasonal mean of daily minimum (TN), maximum (TX), mean (TM) temperatures, daily range of temperature (DTR), and total seasonal rainfall (R) in 35 Iberian stations since mid-twentieth century are studied. The interest is focused on the relationships between temperature variables and rainfall, taking into account the correlation coefficients between R and the temperature variables. The negative link between rainfall and temperatures is detected in the four seasons of the year, except in western stations in winter for TN and TM, and in autumn for TN (for this variable a certain annual cycle is detected, with predominance of positive correlation in winter, negative in spring and summer, and the autumn as transition season). The role of cloud cover is confirmed in those stations with total cloud cover data. Using an average peninsular series, the relationship between nighttime temperature and rainfall related to long wave radiation is confirmed for the four seasons of the year, although in spring and summer has minor importance than in the cold half year. The relationships between R, TN, and TX are in general terms stable after a moving correlation analysis, although the negative correlation between TX and R seems be weakened in spring and autumn and reinforced in summer. The role of convective precipitation in autumn is discussed. The analysis of combined extreme indices in four representative stations shows an increase of warm and dry days, and a decrease of cold and wet days.

Multi-temporal scale analysis of impacts of extreme high temperature on net carbon uptake in subtropical coniferous plantation.

Extreme high temperature is one of important extreme weathers that impact forest ecosystem carbon cycle. In this study, applying CO2 flux and routine meteorological data measured during 2003-2012, we examined the impacts of extreme high temperature and extreme high temperature event on net carbon uptake of subtropical coniferous plantation in Qianyanzhou. Combining with wavelet analysis, we analyzed environmental controls on net carbon uptake at different temporal scales, when the extreme high temperature and extreme high temperature event happened. The results showed that mean daily cumulative NEE decreased by 51% in the days with daily maximum air temperature range between 35 ℃ and 40 ℃, compared with that in the days with the range between 30 ℃ and 34 ℃. The effects of the extreme high temperature and extreme high temperature event on monthly NEE and annual NEE related to the strength and duration of extreme high tempe-rature event. In 2003, when strong extreme high temperature event happened, the sum of monthly cumulative NEE in July and August was only -11.64 g C·m-2·(2 month)-1. The value decreased by 90%, compared with multi-year average value. At the same time, the relative variation of annual NEE reached -6.7%. In July and August, when the extreme high temperature and extreme high temperature event occurred, air temperature (Ta) and vapor press deficit (VPD) were the dominant controller for the daily variation of NEE. The coherency between NEE Ta and NEE VPD was 0.97 and 0.95, respectively. At 8-, 16-, and 32-day periods, Ta, VPD, soil water content at 5 cm depth (SWC), and precipitation (P) controlled NEE. The coherency between NEE SWC and NEE P was higher than 0.8 at monthly scale. The results indicated that atmospheric water deficit impacted NEE at short temporal scale, when the extreme high temperature and extreme high temperature event occurred, both of atmospheric water deficit and soil drought stress impacted NEE at long temporal scales in this ecosystem.