Summer Tmax Research Articles

Spatiotemporal variation of marsh vegetation productivity and climatic effects in Inner Mongolia, China

Net primary productivity (NPP) is a vital ecological index that reflects the ecological function and carbon sequestration of marsh ecosystem. Inner Mongolia has a large area of marshes, which play a crucial role in the East Asian carbon cycle. Under the influence of climate change, the NPP of Inner Mongolian marsh has changed significantly in the past few decades, but the spatiotemporal variation in marsh vegetation NPP and how climate change affects marsh NPP remain unclear. This study explores, for the first time, the spatiotemporal variation of marsh NPP and its response to climatic change in Inner Mongolia based on the MODIS-NPP and climate datasets. We find that the long-term average annual NPP of marsh is 339.85 g⋅C/m2 and the marsh NPP shows a significantly increasing trend (4.44 g⋅C/m2/a; p < 0.01) over Inner Mongolia during 2000–2020. Spatially, the most prominent increase trend of NPP is mainly distributed in the northeast of the region (Greater Khingan Mountains). The partial correlation results show that increasing autumn and summer precipitation can increase the NPP of marsh vegetation over Inner Mongolia. Regarding the temperature effects, we observe a strong asymmetric effect of maximum (Tmax) and minimum (Tmin) temperature on annual NPP. A high spring Tmax can markedly increase marsh NPP in Inner Mongolia, whereas a high Tmin can significantly reduce it. In contrast to spring temperature effects on NPP, a high summer Tmax can decrease NPP, whereas a high Tmin can increase it. Our results suggest different effects of seasonal climate conditions on marsh vegetation productivity and highlight the influences of day-time and night-time temperatures. This should be considered in simulating and predicting marsh carbon sequestration in global arid and semi-arid regions.

Tree-ring-based seasonal temperature reconstructions and ecological implications of recent warming on oak forest health in the Zagros Mountains, Iran

Abrupt changes in temperature have especially strong impacts on fragile ecosystems located in semi-arid regions. In this study, we analyzed tree-ring widths (TRW) of Mediterranean cypress (Cupressus sempervirens var. horizontalis) in the Zagros Mountains, Iran. Furthermore, we separately measured earlywood width (EWW) and latewood width (LWW) of Persian oak (Quercus brantii Lindl.) to examine if intra-annual resolution of tree-ring parameters of Q. brantii tree rings can be used as high-resolution paleoclimate proxies. Climate-growth relationships revealed that mean monthly maximum temperatures (Tmax) are a dominant factor determining radial tree growth and negatively affect both oak and cypress in the Zagros Mountains. Accordingly, we reconstructed two different seasonal windows of past Tmax variability, namely, January–March and June–August over the periods 1860–2015 and 1560–2015, respectively. Regime shift detection identified twelve warm and nine cold significant regime shifts in our summer Tmax reconstructions. The longest hot summer period occurred in the twentieth century, and two warm regime shifts occurred in 1999 and 2008. The highest values of the warm summer regime shift index occurred in 2008, which coincided with fungal pathogen attacks and insect outbreak of the oak leaf roller moth (Tortrix viridana L.) in the Zagros oak woodlands. Interestingly, we found common warm and cold periods in historic climate variability between the summer and winter Tmax reconstructions. Warm and cold regime shifts occurred simultaneously from 1955 to 2015, and significant regional warm summer and winter regime shifts have occurred between 2008 and 2015. The winter and summer Tmax reconstructions show high spatial correlations with large areas in West Asia, North Africa, and the eastern Mediterranean region. Our results strengthen initial studies on past climate variability in Iran and contribute to an enhanced understanding of past temperature variability in West Asia.

Daytime and nighttime temperatures exert different effects on vegetation net primary productivity of marshes in the western Songnen Plain

The western Songnen Plain has a large area of marshes that are able to modulate the regional carbon cycle. Net primary productivity (NPP) is an important ecological indicator of carbon storage within the marsh ecosystems. Although climate change could have significantly changed marsh vegetation NPP during the past decades, the spatiotemporal variation in marsh vegetation NPP and how climate change affects marsh vegetation NPP remain unclear in the western Songnen Plain. In this paper, we assessed the spatiotemporal variation in the NPP of marshes at the western Songnen Plain and evaluated its response to climate change from 2000 to 2020. The NPP of marshes over the western Songnen Plain increased significantly at a rate of 5.69 g C/m2/a during 2000 to 2020, with an average value of about 273.62 g C/m2/a. The largest increase of the NPP of marshes was mainly distributed in the northwest part of the Songnen Plain. Correlation analysis results showed that the increased precipitation in summer and autumn could enhance the NPP of marsh vegetation. By contrast, the increase of mean temperature in summer reduced the NPP of marshes. In addition, we first found the asymmetric impacts of summer minimum temperature (Tmin) and maximum temperature (Tmax) on marsh vegetation NPP. Notably, the increase in summer Tmax could significantly reduce NPP, while the increase in Tmin could increase NPP. Under the background of global asymmetric warming of daytime and nighttime temperatures, more attention should be paid to the different effects of Tmax and Tmin on marsh NPP in the western Sonegnen Plain. The findings of this study can provide theoretical guidance for ecological protection and the adaptive management of marsh vegetation at the western Songnen Plain.

Assessment of Central Asian heat extremes by statistical downscaling: Validation and future projection for 2015‒2100

Increasing heatwaves and extreme temperatures have recently been observed across Central Asia (CA). Accurately assessing and projecting the changing climate extremes at the local (station) scale required for climate risk management are therefore highly important. However, global and regional climate models often fail to represent the statistical distributions of observed daily extreme variables and hence extremes in complex terrain. In this work, we developed a statistical downscaling (SD) model to project summer daily maximum temperature (Tmax) and heatwave indices for 65 meteorological stations in CA toward 2100. The SD model involves first-order autoregression and multiple linear regression using large-scale Tmax and circulation indices (CIs) as predictors, and the model is cross-validated against historical observations. The local Tmax and heatwave indices are then projected for 2015–2100 driven by the output of a global climate model (CNRM-CM6-1) under four Shared Socioeconomic Pathways (SSP126, SSP245, SSP370, and SSP585). The application of the SD model significantly improves forecasting of the probability distribution (10th/90th percentiles) of Tmax at stations, particularly across mountainous regions. The model also captures interannual variability and the long-term trend in Tmax, consistent with synoptic-scale inputs. SD projections demonstrate strong warming trends of summer Tmax in CA toward 2100 with rates between 0.35–0.64 °C per decade based on the SSP245 and SSP370 scenarios. Consequently, heatwave occurrence is projected to rise by 1.0–5.0 and 2.0–7.0 d per decade under the SSP245 and SSP370 scenarios, respectively, by 2100. Duration, intensity, and amplitude of heatwaves rise at greater rates under higher-emission scenarios, particularly in southeastern CA. The proposed SD model serves as a useful tool for assessing local climate extremes, which are needed for regional risk management and policymaking for adaption to climate change.

Hot Days and Heat Waves in Poland in the Period 1951–2019 and the Circulation Factors Favoring the Most Extreme of Them

The aim of the study is to analyze the occurrence of hot days and heat waves in Poland, their intra-annual distribution, and their long-term variability, and to present the circulation factors favoring the appearance of extensive waves in the country. Hot days were days with Tmax not lower than the threshold value defined by the 95th percentile of summer Tmax in the period 1961–1990. Atmospheric circulation was described using sea level pressure, geopotential of 700 and 500 hPa level, and horizontal and vertical wind on these levels. A statistically significant increase in the number of hot days in the entire study period and a significant acceleration in growth after 1980 were shown. In the entire analyzed period, only 11 waves were found covering at least 25% of the country area and lasting no less than a week. Among them, only one occurred before 1990, and more than half were observed in the last decade. Four circulation patterns favoring the extensive heat waves were distinguished differing the location of main baric center location. Spatial and temporal distribution of vertical velocity anomalies allows distinguishing clear phases of strengthening, stabilization, and weakening of anticyclone accompanying the occurrence of a heat wave.

Wildfire and spruce beetle outbreak have mixed effects on below‐canopy temperatures in a Rocky Mountain subalpine forest

AbstractAimFine‐scale topography and canopy cover can play an important role in mediating effects of regional‐scale climate change on the below‐canopy environment in mountain forests. The aim of this study was to determine how below‐canopy temperatures in a high‐elevation Rocky Mountain forest have been affected by canopy change resulting from severe wildfire and spruce beetle outbreak within the last 10–15 years.LocationEastern San Juan Mountains, Colorado, USA.TaxonPicea engelmannii, Abies lasiocarpa, Dendroctonus rufipennis.MethodsWe used a network of sensors to record temperatures for a full year in burned and beetle‐impacted areas. Using a Bayesian model that accounted for spatial structure in temperatures, we derived covariate parameters to determine the relative influence of topographic variables (elevation, aspect, slope, topographic position and solar radiation), live tree basal area and burned/unburned status on average daily maximum and minimum temperatures (Tmax, Tmin) in summer and winter.ResultsModel parameters indicated that burned areas were warmer than unburned forest, with three of four average temperature variables (summer Tmax, winter Tmax, and winter Tmin) having >95% likelihood of a positive temperature difference in burned versus unburned locations. Mean temperature changes for these variables ranged from 0.41 to 0.74°C. Conversely, canopy loss in unburned, beetle‐killed forests did not meaningfully affect Tmax but resulted in slight cooling of Tmin. Modelled temperature changes resulting from 100% overstorey mortality were −1.29°C for summer Tmin (95% credible interval: −0.027 to −2.56°C) and −1.31°C for winter Tmin (95% credible interval: 0.17 to −2.79°C).Main ConclusionsOur results indicate that severe wildfire may exacerbate effects of climate change and increase the probability of ecosystem transitions. However, the effects of bark beetle outbreaks are more complex. Cooling of overnight minimum temperatures may counteract warming trends, but an increase in diurnal temperature ranges may have uncertain ecological consequences.

Impacts of Irrigation on Summertime Temperatures in the Pacific Northwest

AbstractIrrigation has the potential to modify local weather and regional climate through a repartitioning of water among the surface, soil, and atmosphere with the potential to drastically change the terrestrial energy budget in agricultural areas. This study uses local observations, satellite remote sensing, and numerical modeling to 1) explore whether irrigation has historically impacted summer maximum temperatures in the Columbia Plateau, 2) characterize the current extent of irrigation impacts to soil moisture (SM) and land surface temperature (LST), and 3) better understand the downstream extent of irrigation’s influence on near-surface temperature, humidity, and boundary layer development. Analysis of historical daily maximum temperature (TMAX) observations showed that the three Global Historical Climate Network (GHCN) sites downwind of Columbia Basin Project (CBP) irrigation experienced statistically significant cooling of the mean summer TMAX by 0.8°–1.6°C in the post-CBP (1968–98) as compared to pre-CBP expansion (1908–38) period, opposite the background climate signal. Remote sensing observations of soil moisture and land surface temperatures in more recent years show wetter soil (~18%–25%) and cooler land surface temperatures over the irrigated areas. Simulations using NASA’s Land Information System (LIS) coupled to the Weather Research and Forecasting (WRF) Model support the historical analysis, confirming that under the most common summer wind flow regime, irrigation cooling can extend as far downwind as the locations of these stations. Taken together, these results suggest that irrigation expansion may have contributed to a reduction in summertime temperatures and heat extremes within and downwind of the CBP area. This supports a regional impact of irrigation across the study area.

Projected extreme temperature and precipitation of the Laurentian Great Lakes Basin

Abstract The Laurentian Great Lakes Basin has been subject to increasingly extreme weather events in the past seven decades. This study uses a regional climate model spanning the region to project summer maximum temperature (Tmax), winter minimum temperature (Tmin), and seasonal extremes of precipitation for the mid-century (2030–2059) and late-century (2060–2089) relative to the baseline period (1980–2009). The basin's southern portion (US side) summer Tmax increases are projected to be greater than those in the northern portion of the basin (Canadian side), whereas Canadian side winter Tmin increases will be greater than those on the US side. The annual number of extremely hot days (Tmax ≥ 32 °C) in this region during mid-century and late century periods is projected to rise by 6.1–15.3 days and 10.0–32.1 days relative to the baseline period (1980–2009) values (0.1–21.5 days), respectively; whereas the annual number of extremely cold days (Tmin ≤ −18 °C) is projected to be reduced by 3.9–6.2 days (mid-century) and 5.5–9.9 days (late century) compared to the baseline period (2.6–60.5 days). The annual number of extremely cold days is projected to remain unchanged in 23%–61% of the area over the Lakes. The Basin's annual precipitation is projected to rise continuously but the degree of change will vary by season. Winter and spring precipitations are projected to rise greatly, autumn precipitation will rise to a lesser extent, but summer precipitation is projected to decline relative to the baseline period. The annual number of extremely wet days (≥40 mm/day) over the Lakes only is projected to increase by between 0.3 and 0.6 days (mid-century) and 0.5–0.8 days (late century). The annual number of extremely wet days over land areas is projected to increase by 0.2–0.6 days and 0.5–0.8 days, respectively. However, about 20% of the region will also experience a reduced number of extremely wet days, which implies that future precipitation changes in this region may be quite different at smaller scales (e.g. county to county) than over larger scales. We propose that lake and land differences, seasonal variations, and changed and unchanged areas should all be considered in climate studies of regions within which large inland water bodies reside, as these regions will have similarities with the Great Lakes basin.

Strong impacts of daily minimum temperature on the green-up date and summer greenness of the Tibetan Plateau.

Understanding vegetation responses to climate change on the Tibetan Plateau (TP) helps in elucidating the land-atmosphere energy exchange, which affects air mass movement over and around the TP. Although the TP is one of the world's most sensitive regions in terms of climatic warming, little is known about how the vegetation responds. Here, we focus on how spring phenology and summertime greenness respond to the asymmetric warming, that is, stronger warming during nighttime than during daytime. Using both insitu and satellite observations, we found that vegetation green-up date showed a stronger negative partial correlation with daily minimum temperature (Tmin ) than with maximum temperature (Tmax ) before the growing season ('preseason' henceforth). Summer vegetation greenness was strongly positively correlated with summer Tmin , but negatively with Tmax . A 1-K increase in preseason Tmin advanced green-up date by 4days (P<0.05) and in summer enhanced greenness by 3.6% relative to the mean greenness during 2000-2004 (P<0.01). In contrast, increases in preseason Tmax did not advance green-up date (P>0.10) and higher summer Tmax even reduced greenness by 2.6%K(-1) (P<0.05). The stimulating effects of increasing Tmin were likely caused by reduced low temperature constraints, and the apparent negative effects of higher Tmax on greenness were probably due to the accompanying decline in water availability. The dominant enhancing effect of nighttime warming indicates that climatic warming will probably have stronger impact on TP ecosystems than on apparently similar Arctic ecosystems where vegetation is controlled mainly by Tmax . Our results are crucial for future improvements of dynamic vegetation models embedded in the Earth System Models which are being used to describe the behavior of the Asian monsoon. The results are significant because the state of the vegetation on the TP plays an important role in steering the monsoon.

Time Series Construction of Summer Surface Temperatures for Alabama, 1883–2014, and Comparisons with Tropospheric Temperature and Climate Model Simulations

AbstractThree time series of average summer [June–August (JJA)] daily maximum temperature (TMax) are developed for three interior regions of Alabama from stations with varying periods of record and unknown inhomogeneities. The time frame is 1883–2014. Inhomogeneities for each station’s time series are determined from pairwise comparisons with no use of station metadata other than location. The time series for the three adjoining regions are constructed separately and are then combined as a whole assuming trends over 132 yr will have little spatial variation either intraregionally or interregionally for these spatial scales. Varying the parameters of the construction methodology creates 333 time series with a central trend value based on the largest group of stations of −0.07°C decade−1 with a best-guess estimate of measurement uncertainty from −0.12° to −0.02°C decade−1. This best-guess result is insignificantly different (0.01°C decade−1) from a similar regional calculation using NOAA’s divisional dataset based on daily data from the Global Historical Climatology Network (nClimDiv) beginning in 1895. Summer TMax is a better proxy, when compared with daily minimum temperature and thus daily average temperature, for the deeper tropospheric temperature (where the enhanced greenhouse signal is maximized) as a result of afternoon convective mixing. Thus, TMax more closely represents a critical climate parameter: atmospheric heat content. Comparison between JJA TMax and deep tropospheric temperature anomalies indicates modest agreement (r2 = 0.51) for interior Alabama while agreement for the conterminous United States as given by TMax from the nClimDiv dataset is much better (r2 = 0.86). Seventy-seven CMIP5 climate model runs are examined for Alabama and indicate no skill at replicating long-term temperature and precipitation changes since 1895.

Daily temperature changes and variability in ENSEMBLES regional models predictions: Evaluation and intercomparison for the Ebro Valley (NE Iberia)

We employ a suite of regional climate models (RCMs) to assess future changes in summer (JJA) maximum temperature (Tmax) over the Ebro basin, the largest hydrological division in the Iberian Peninsula. Under the A1B emission scenario, future changes in both mean values and their corresponding time varying percentiles were examined by comparing the control period (1971–2000) with two future time slices: 2021–2050 and 2071–2100. Here, the rationale is to assess how lower/upper tails of temperature distributions will change in the future and whether these changes will be consistent with those of the mean. The model validation results demonstrate significant differences among the models in terms of their capability to representing the statistical characteristics (e.g., mean, skewness and asymmetry) of the observed climate. The results also indicate that the current substantial warming observed in the Ebro basin is expected to continue during the 21st century, with more intense warming occurring at higher altitudes and in areas with greater distance from coastlines. All models suggest that the region will experience significant positive changes in both the cold and warm tails of temperature distributions. However, the results emphasize that future changes in the lower and upper tails of the summer Tmax distribution may not follow the same warming rate as the mean condition. In particular, the projected changes in the warm tail of the summer Tmax are shown to be significantly larger than changes in both mean values and the cold tail, especially at the end of the 21st century. The finding suggests that much of the changes in the summer Tmax percentiles will be driven by a shift in the entire distribution of temperature rather than only changes in the central tendency. Better understanding of the possible implications of future climate systems provides information useful for vulnerability assessments and the development of local adaptation strategies for multi-disciplinary investigations.

Attribution of the United States "warming hole": aerosol indirect effect and precipitable water vapor.

Aerosols can influence the climate indirectly by acting as cloud condensation nuclei and/or ice nuclei, thereby modifying cloud optical properties. In contrast to the widespread global warming, the central and south central United States display a noteworthy overall cooling trend during the 20th century, with an especially striking cooling trend in summertime daily maximum temperature (Tmax) (termed the U.S. “warming hole”). Here we used observations of temperature, shortwave cloud forcing (SWCF), longwave cloud forcing (LWCF), aerosol optical depth and precipitable water vapor as well as global coupled climate models to explore the attribution of the “warming hole”. We find that the observed cooling trend in summer Tmax can be attributed mainly to SWCF due to aerosols with offset from the greenhouse effect of precipitable water vapor. A global coupled climate model reveals that the observed “warming hole” can be produced only when the aerosol fields are simulated with a reasonable degree of accuracy as this is necessary for accurate simulation of SWCF over the region. These results provide compelling evidence of the role of the aerosol indirect effect in cooling regional climate on the Earth. Our results reaffirm that LWCF can warm both winter Tmax and Tmin.

Exploring the behaviour of atmospheric temperatures under dry conditions in Europe: evolution since the mid‐20th century and projections for the end of the 21st century

AbstractIn a changing climate, it is likely that precipitation patterns will experience shifts in amount and seasonality, with a tendency towards increased drought in many parts of Europe. In order to investigate what could be some of the feedbacks of dry conditions on temperature, this paper has investigated close to 30 European locations to assess the influence of observed dry summer days on daily maximum temperature (Tmax) as well as a clustering of rainless days, and finally the temperature impact related to drought conditions as defined by the Standardized Precipitation Index. The results show that for the three main European climatic regions investigated (‘Mediterranean’, ‘Maritime’, ‘Continental’), the influence of rainless days is discernible, with an average difference between mean summer Tmax and Tmax during rainless days only of up to 1.5 °C. A further aim of the study is to determine whether recent shifts in the occurrence of rainless days during the summer have a bearing on temperature trends. Results show that shifts in rainless days explain only a fraction of the observed temperature change at the locations studied, thereby hinting that the enhanced greenhouse effect remains the dominant mechanism for temperature change. Finally, using a regional climate model, very preliminary insight into a ‘greenhouse climate’ highlights the fact that changes in dry conditions seem to confirm the findings for current climate, i.e. they account for only a fraction of the increase in temperatures. Copyright © 2012 Royal Meteorological Society

Trends of seasonal maximum and minimum temperatures and precipitation in Southern Brazil for the 1913–2006 period

Long-term variations of monthly average maximum and minimum temperature (TMAX and TMIN) and precipitation records in southern Brazil are investigated for the 1913–2006 period. These variations are carefully analyzed for seasonal and annual indices, taken as regional averages. For this purpose, the serial correlation and trend of the indices are investigated using the run and Mann–Kendall tests. The significant trends are obtained from linear least-square fits. The annual and seasonal TMIN indices show significant warming trends with magnitudes (1.7°C per 100 years for annual index) comparable to those reported by the Intergovernmental Panel on Climate Change, but lower than those found for the southern Brazil in another previous work. Regarding the two other variables, the indices show significant trends only for summer, being a cooling trend of 0.6°C per 100 years for the TMAX and an increasing trend of 93 mm per 100 years over an average summer precipitation of 367 mm. Concerning the decadal analysis, the 1920s present the lowest annual, autumn, and spring TMIN and the 1990s, the highest ones. The 1970s is the decade with the lowest summer TMAX, and the 1940s the decade with the highest one. The driest decade is the 1940s and the wettest, the 1980s.

Effect of climatic variability on δ13C and tree-ring growth in piñon pine (Pinus edulis)

Understanding the response of long-lived species to natural climatic variability at multiple scales is a prerequisite for forecasting ecosystem responses to global climate change. This study investigated the response of pinon pine (Pinus edulis) to natural climatic variability using information on physiology and growth as recorded in leaves and tree rings. δ13C of annual leaf cohorts (δ13Cleaf) and tree rings (δ13Cring) were measured at an ecotonal/xeric site and a mid-range/mesic site. Ring width indices (RWI) were used to estimate annual growth of individual trees. Relationships between seasonal and annual climate parameters and δ13C and growth were investigated. δ13C–climate relationships were stronger for δ13Cleaf than for δ13Cring especially at the xeric site. The mean monthly maximum summer temperatures over May through September (summer Tmax) had the strongest influence on δ13Cleaf. There was a strong negative relationship between RWI with summer Tmax and a strong positive relationship between RWI with October to October precipitation (water–year PPN) at both sites. This suggests that pinon pine populations could be vulnerable to decreased growth and, perhaps mortality, in response to warmer, drier conditions predicted by models of global climate change.

Prediction of Summer Maximum and Minimum Temperature over the Central and Western United States: The Roles of Soil Moisture and Sea Surface Temperature

Abstract A statistical model based on canonical correlation analysis (CCA) was used to explore climatic associations and predictability of June–August (JJA) maximum and minimum surface air temperatures (Tmax and Tmin) as well as the frequency of Tmax daily extremes (Tmax90) in the central and western United States (west of 90°W). Explanatory variables are monthly and seasonal Pacific Ocean SST (PSST) and the Climate Division Palmer Drought Severity Index (PDSI) during 1950–2001. Although there is a positive correlation between Tmax and Tmin, the two variables exhibit somewhat different patterns and dynamics. Both exhibit their lowest levels of variability in summer, but that of Tmax is greater than Tmin. The predictability of Tmax is mainly associated with local effects related to previous soil moisture conditions at short range (one month to one season), with PSST providing a secondary influence. Predictability of Tmin is more strongly influenced by large-scale (PSST) patterns, with PDSI acting as a short-range predictive influence. For both predictand variables (Tmax and Tmin), the PDSI influence falls off markedly at time leads beyond a few months, but a PSST influence remains for at least two seasons. The maximum predictive skill for JJA Tmin, Tmax, and Tmax90 is from May PSST and PDSI. Importantly, skills evaluated for various seasons and time leads undergo a seasonal cycle that has maximum levels in summer. At the seasonal time frame, summer Tmax prediction skills are greatest in the Midwest, northern and central California, Arizona, and Utah. Similar results were found for Tmax90. In contrast, Tmin skill is spread over most of the western region, except for clusters of low skill in the northern Midwest and southern Montana, Idaho, and northern Arizona.