The Physics of Heat Waves: What Causes Extremely High Summertime Temperatures?

We analyze observations and develop a hierarchy of models to understand heat waves – long-lived, high temperature anomalies – and extremely high daily temperatures during summertime in the continental extratropics. Throughout the extratropics, the number of extremely hot days found in the three hottest months is much greater than expected from a random, single-process model. Furthermore, in many locations the temperature skewness switches from negative on daily timescales to positive on monthly timescales (or shifts from positive on daily timescales to higher positive values on monthly timescales) in ways that cannot be explained by averaging alone. These observations motivate a hierarchy of models of the surface energy and moisture budgets that we use to illuminate the physics responsible for daily and monthly averaged temperature variability. Shortwave radiation fluctuations drive much of the variance and the negative skewness found in daily temperature observations. On longer timescales, precipitation-induced soil moisture anomalies are important for temperature variability and account for the shift toward positive skewness in monthly averaged temperature. Our results demonstrate that long-lived heat waves are due to (i) the residence time of soil moisture anomalies and (ii) a nonlinear feedback between temperature and evapotranspiration via the impact of temperature on vapor pressure deficit. For most climates, these two processes give rise to infrequent, long-lived heat waves in response to randomly distributed precipitation forcing. Combined with our results concerning high-frequency variability, extremely hot days are seen to be state-independent filigree driven by shortwave variability acting on top of longer-lived, moisture driven heat waves.

Diurnal Extrema Timing—A New Climatological Parameter?

We address the following question: Are turning points of daily air temperature function a piece of relevant climatological information worth recording and analyzing? Diurnal Extrema Timing (DET) are daily occurrence times of air temperature minimum and maximum. Although unrecognized and unrecorded as a meteorological variable, the exact timing of daily temperature extrema plays a crucial role in the characterization of air temperature variability. In this study, we introduce the DET concept and assess the plausibility of this potential parameter in detecting temperature extrema timing changes. Conceptualization of the DET parameter has, for a primary goal, the supplementation of vital spatial information to the daily measurements of air temperature extrema. The elementary analysis of annual trends of daily DET examines the significance of this parameter in describing changes in the time domain of air temperature variability. The introduction of the new Climate Parameter Sensitivity Index (CPSI) for evaluating the susceptibility of climate parameters to climate change directs attention to the importance of the systematic acquisition of the timing of daily extrema in climate observations. The results of this study reveal the timing of daily air temperature maximum as the most vulnerable to climate change among temperature and timing extrema indices.

Air temperature variability in high-elevation glacierized regions: observations from six catchments on the Tibetan Plateau

Near-surface air temperature variability and the reliability of temperature extrapolation within glacierized regions are important issues for hydrological and glaciological studies that remain elusive because of the scarcity of high-elevation observations. Based on air temperature data in 2019 collected from 12 automatic weather stations, 43 temperature loggers and 6 national meteorological stations in six different catchments, this study presents air temperature variability in different glacierized/nonglacierized regions and assesses the robustness of different temperature extrapolations to reduce errors in melt estimation. The results show high spatial variability in temperature lapse rates (LRs) in different climatic contexts, with the steepest LRs located on the cold-dry northwestern Tibetan Plateau and the lowest LRs located on the warm-humid monsoonal-influenced southeastern Tibetan Plateau. Near-surface air temperatures in high-elevation glacierized regions of the western and central Tibetan Plateau are less influenced by katabatic winds and thus can be linearly extrapolated from off-glacier records. In contrast, the local katabatic winds prevailing on the temperate glaciers of the southeastern Tibetan Plateau exert pronounced cooling effects on the ambient air temperature, and thus, on-glacier air temperatures are significantly lower than that in elevation-equivalent nonglacierized regions. Consequently, linear temperature extrapolation from low-elevation nonglacierized stations may lead to as much as 40% overestimation of positive degree days, particularly with respect to large glaciers with a long flowline distances and significant cooling effects. These findings provide noteworthy evidence that the different LRs and relevant cooling effects on high-elevation glaciers under distinct climatic regimes should be carefully accounted for when estimating glacier melting on the Tibetan Plateau.

Association with Temperature Variability and Physical Activity, Sedentary Behavior, and Sleep in a Free-Living Population

The present study examines the temperature variability in physical activity (PA), sedentary behavior (SB), and sleep in a free-living population. A representative sample of 1235 adults (ages 21–70) from Iowa, U.S.A., wore a SenseWear Mini Armband (SWA) for a randomly assigned day. Koppen’s weather climate classification was used to precisely classify the temperature: cold (−13 to 32 °F), cool (32 to 50 °F), mild (50 to 64 °F), warm (64 to 73 °F), and hot (73 to 95 °F). The main effect of three-way ANOVA (age × gender × temperature) had differences for SB and sleep, with older adults having higher levels than younger adults (p < 0.05). However, moderate to vigorous PA (MVPA) did not vary systematically by age or gender, and contrary to expectations, the main effect of the weather was not significant for MVPA (p > 0.05). Participants spent more time participating in PA at cold than at hot temperatures. The results clarify the impact of temperature on shaping PA and SB patterns in adults. The variable impacts and differential patterns by age suggest that weather should be considered when interpreting differences in PA patterns in research or surveillance applications.

Trends in surface temperature variability over Mumbai and Ratnagiri cities of coastal Maharashtra, India

Increasing urbanization and expansion of cities has led to intensification of the urban heat island (UHI). High consumption of fossil fuels and trapping of radiated heat leads to increase in surface temperature in and around city. Present research paper focuses on temperature variability over Mumbai and Ratnagiri cities, which are located in the same coastal climatic region and almost at same altitude. Trends in maximum and minimum temperature were investigated at annual and seasonal scale. The occurrences of temperature extremes were also analysed. In general, increasing trends were observed over both the stations, with high rate of increase in maximum temperature than the minimum temperatures statistically significant at 95% confidence level. Mumbai experienced significant warming with higher rates than Ratnagiri. Warm extremes have also increased significantly over Mumbai. Ratnagiri showed decrease in hot days during monsoon and hot nights during remaining seasons significant in summer.

Observed Quantile Features of Summertime Temperature Trends over China: Non-Negligible Role of Temperature Variability

Changes in temperature variability can have more serious social and ecological impacts than changes in the mean state of temperature, especially when they are concurrent with global warming. The present study examines the summertime temperatures’ trends over China from the quantile perspective. Through fully investigating the quantile trends (QTs) of the maximum (Tmax) and minimum temperature (Tmin) using the homogenized observation data and quantile regression analysis, we identify evident region-specific quantile features of summertime temperature trends. In most of northern China, the QTs in Tmax and Tmin for all percentiles generally show strong uniform warmings, which are dominated by a warm shift in mean state temperatures. In contrast, the QTs of Tmax in the Yangtze River Basin show distinguishable inter-quantile features, i.e., an increasing tendency of QTs from cooling trends in the lower percentile to warming trends in the higher percentile. Further investigations show that such robust growing QTs of Tmax across quantiles are dominated by the temperature variance. Our results highlight that more attention should be paid to the region-specific dominance of temperature variability in trends and the related causes.

Adiabatic and diabatic signatures of ocean temperature variability

Anthropogenically induced radiative imbalances in the climate system lead to a slow accumulation of heat in the ocean. This warming is often obscured by natural modes of climate variability such as the El Niño-Southern Oscillation (ENSO), which drive substantial ocean temperature changes as a function of depth and latitude. The use of watermass coordinates has been proposed to help isolate forced signals and filter out fast adiabatic processes associated with modes of variability. However, how much natural modes of variability project into these different coordinate systems has not been quantified. Here we apply a rigorous framework to quantify ocean temperature variability using both a quasi-Lagrangian, watermass-based temperature coordinate and Eulerian depth and latitude coordinates in a free-running climate model under pre-industrial conditions. The temperature-based coordinate removes the adiabatic component of ENSO-dominated interannual variability by definition, but a substantial diabatic signal remains. At slower (decadal to centennial) frequencies, variability in the temperature- and depth-based coordinates is comparable. Spectral analysis of temperature tendencies reveals the dominance of advective processes in latitude and depth coordinates while the variability in temperature coordinates is related closely to the surface forcing. Diabatic mixing processes play an important role at slower frequencies where quasi steady-state balances emerge between forcing and mixing in temperature, advection and mixing in depth, and forcing and advection in latitude. While watermass-based analyses highlight diabatic effects by removing adiabatic variability, our work shows that natural variability has a strong diabatic component and cannot be ignored in the analysis of long term trends.