Influence of the Boreal Summer Intraseasonal Oscillation on Extreme Temperature Events in the Northern Hemisphere

The impact of the boreal summer intraseasonal oscillation (BSISO) on extreme hot and cool events was investigated, by analyzing the observed and reanalysis data for the period from 1983 to 2012. It is found that the frequency of the extreme events in middle and high latitudes is significantly modulated by the BSISO convection in the tropics, with a 3–9-day lag. During phases 1 and 2 when the BSISO positive rainfall anomaly is primarily located over a northwest–southeast oriented belt extending from India to Maritime Continent and a negative rainfall anomaly appears in western North Pacific, the frequency of extreme hot events is 40% more than the frequency of non-extreme hot events. Most noticeable increase appears in midlatitude North Pacific (north of 40°N) and higher-latitude polar region.Two physical mechanisms are primarily responsible for the change of the extreme frequency. First, an upper-tropospheric Rossby wave train (due to the wave energy propagation) is generated in response to a negative heating anomaly over tropical western North Pacific in phases 1 and 2. This wave train consists of a strong high pressure anomaly center northeast of Japan, a weak low pressure anomaly center over Alaska, and a strong high pressure anomaly center over the western coast of United States. Easterly anomalies to the south of the two strong midlatitude high pressure centers weaken the climatological subtropical jet along 40°N, which is accompanied by anomalous subsidence and warming in North Pacific north of 40°N. Second, an enhanced monsoonal heating over South Asia and East Asia sets up a transverse monsoonal overturning circulation, with large-scale ascending (descending) anomalies over tropical Indian (Pacific) Ocean. Both the processes favor more frequent extreme hot events in higher-latitude Northern Hemisphere. An anomalous atmospheric general circulation model is used to confirm the tropical heating effect.     

Assessment of Gradient-Based Similarity Functions in the Stable Boundary Layer Derived from a Large-Eddy Simulation

Most of our knowledge on forest-edge flows comes from numerical and wind-tunnel experiments where canopies are horizontally homogeneous. To investigate the impact of tree-scale heterogeneities (\({>}1\) m) on the edge-flow dynamics, the flow in an inhomogeneous forest edge on Falster island in Denmark is investigated using large-eddy simulation. The three-dimensional forest structure is prescribed in the model using high resolution helicopter-based lidar scans. After evaluating the simulation against wind measurements upwind and downwind of the forest leading edge, the flow dynamics are compared between the scanned forest and an equivalent homogeneous forest. The simulations reveal that forest inhomogeneities facilitate flow penetration into the canopy from the edge, inducing important dispersive fluxes in the edge region as a consequence of the flow spatial variability. Further downstream from the edge, the forest inhomogeneities accentuate the canopy-top turbulence and the skewness of the wind-velocity components while the momentum flux remains unchanged. This leads to a lower efficiency in the turbulent transport of momentum within the canopy. Dispersive fluxes are only significant in the upper canopy. Above the canopy, the mean flow is less affected by the forest inhomogeneities. The inhomogeneities induce an increase in the mean wind speed that was found to be equivalent to a decrease in the aerodynamic height of the canopy. Overall, these results highlight the importance of forest inhomogeneities when looking at canopy–atmosphere exchanges in forest-edge regions.     

Validation of climate model output using Bayesian statistical methods

The growing interest in and emphasis on high spatial resolution estimates of future climate has demonstrated the need to apply regional climate models (RCMs) to that problem. As a consequence, the need for validation of these models, an assessment of how well an RCM reproduces a known climate, has also grown. Validation is often performed by comparing RCM output to gridded climate datasets and/or station data. The primary disadvantage of using gridded climate datasets is that the spatial resolution is almost always different and generally coarser than climate model output. We have used a Bayesian statistical model derived from observational data to validate RCM output. We used surface air temperature (SAT) data from 109 observational stations in California, all with records of approximately 50 years in length, and created a statistical model based on this data. The statistical model takes into account the elevation of the station, distance from coastline, and the NOAA climate region in which the station resides. Analysis indicates that the statistical model provides reliable estimates of the mean monthly SAT at any given station. In our method, the uncertainty in the estimates produced by the statistical model are directly determined by obtaining probability density functions for predicted SATs. This statistical model is then used to estimate average SATs corresponding to each of the climate model grid cells. These estimates are compared to the output of the RCM to assess how well the RCM matches the observed climate as defined by the statistical model. Overall, the match between the RCM output and the statistical model is good, with some deficiencies likely due in part to the representation of topography in the RCM.     

The Northward Shift of Climatic Belts in China During the Last 50 Years and the Corresponding Seasonal Responses

Along the meridian of 105°E, the Chinese region are divided into two parts, east and west. The results show that in the east part of China the temperate extratropical belt, the warm extratropical belt,and the northern subtropical belt shift northward significantly, whereas the middle subtropical belt and the southern subtropical belt have less or no change. As for the northern subtropical belt, the maximal northward shift can reach 3.7 degrees of latitude. As for the warm extratropical belt, along the meridian of 120°-125°E, the maximal northward shift can reach 3-4 degrees. In the west part of China, each climatic belt changes little. Only in the Xinjiang area are the significant northward shifts. Correspondingly, it is found that in the last 50 years the traditional seasons have changed. For Beijing, Hailar, and Lanzhou, in general, summer becomes longer and winter shorter over the last 50 years. Summer begins early and ends late with respect to early 1950s. Contrary to the summer, winter begins la     

On the Derivation of Input Parameters for Urban Canopy Models from Urban Morphological Datasets

Two techniques are analysed to derive mean street width and mean building width from morphological data of real cities: one based on a two-dimensional simplified morphology, and the other based on a three-dimensional regular simplified morphology. For each simplified morphology (two-dimensional and three-dimensional), the sky-view factors (street-to-sky) are computed and compared with the sky-view factors derived from the real morphology for selected districts of three European and two North American cities. The two-dimensional simplified morphology reproduces the real sky-view factors better than the three-dimensional morphology. Since many urban canopy parameterizations represent the city using simplified morphologies, this can be useful information for the derivation of input parameters for urban canopy parameterizations from real morphological data.     

Is it hot in here or is it just me? Temperature anomalies and political polarization over global warming in the American public

Do temperature anomalies affect political polarization over global warming? Americans’ attitudes about global warming are affected by whether they reside in states experiencing unseasonably warm (or cold) temperatures versus those experiencing milder temperatures. Specifically, in terms of causal attribution, political polarization over global warming is more pronounced in states experiencing temperature anomalies. Using pooled data collected during 2013–2014, this study utilizes logistic regression to explore how temperature anomalies exacerbate the political polarization among Americans over perceptions of whether global warming impacts are immediately evident as well as the attribution of global warming to human activity. Results indicate that very cold or warm temperature anomalies from a 5-year baseline predict perceptions of global warming impacts and exacerbate existing political polarization over the causal attribution of global warming. These effects are particularly noticeable among Democrats. This analysis provides a contribution to understanding how temperature anomalies from the recent past shape the sociophysical context of global warming attitudes.