A Dynamic Urban Canopy Parameterization for Mesoscale Models Based on Computational Fluid Dynamics Reynolds-Averaged Navier–Stokes Microscale Simulations

Urban canopy parameterizations (UCPs) are necessary in mesoscale modelling to take into account the effects of buildings on wind and turbulent structures. This study is focused on the dynamical part of UCPs. The main objective is twofold: first, computing important UCP input parameters (turbulent length scales and the sectional drag coefficient) by means of Reynolds-averaged Navier–Stokes (RANS) simulations of turbulent flow; and second, comparing UCP variables with spatially-averaged properties obtained from RANS simulations for the same configurations. The results show the importance of using a suitable parameterization of the drag force for different packing densities. An urban canopy parameterization that is a compromise between simplicity and accuracy is proposed. This scheme accounts for the variation of drag coefficients with packing densities, and has a parameterization of turbulent length scales. The technique adopted ensures that, at least for the simple configurations studied, the urban canopy parameterization gives values of spatially-averaged variables similar to those computed from a more complex simulation, such as RANS that resolves explicitly the flow around buildings.     

Some Splitting Methods for Equations of Geophysical Fluid Dynamics

In this paper, equations of atmospheric and oceanic dynamics are reduced to a kind of evolutionary equation in operator form, based on which a conclusion that the separability of motion stages is relative is made and an issue that the tractional splitting methods established on the physical separability of the fast stage and the slow stage neglect the interaction between the two stages to some extent is shown. Also, three splitting patterns are summed up from the splitting methods in common use so that a comparison between them is carried out. The comparison shows that only the improved splitting pattern (ISP) can be in second order and keep the interaction well. Finally, the applications of some splitting methods on numerical simulations of typhoon tracks made clear that ISP owns the best effect and can save more than 80% CPU time.     

A Finite-Mode Model of Ideal Fluid Dynamics on the 2-Sphere

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ALow-order Model of Two-dimensional Fluid Dynamics on the Surface of a Sphere

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Climate change and migration: Is agriculture the main channel?

Migration and climate change are two of the most important challenges the world currently faces. They are connected as climate change may stimulate or hinder migration. One of the sectors strongly affected by climate change is agriculture, which is the source of income for most of the world's poor. Climate change may affect agricultural productivity and hence migration because of its impact on average temperatures and rainfall and because it increases the frequency and intensity of weather shocks. In this paper we use data on 108 countries from 1960 to 2010 to analyze the relationship between weather variations, changes in agricultural productivity and international migration. We find that negative shocks to agricultural productivity caused by climate fluctuations significantly increase emigration from developing countries, an especially strong impact in poor countries but less so in middle income countries. These results are robust to the definitions of the poor country sample, and to several checks and alternative explanations suggested by the literature. Importantly, our results point to a causal interpretation of the agricultural channel to explain the climate change-migration nexus.     

Is Canadian cloudiness increasing?

Abstract

Cloud amount records for the Canadian mid‐latitudes have been analysed in the context of a “warming world” analogue model that compares records of two 20‐year periods. The cloud amounts increase over practically all these regions while temperatures rise. This historical data set has also been extended temporally to permit analysis of high‐latitude cloudiness trends. These are of particular interest in the “fingerprinting” of CO₂‐induced climatic change. Station records from the Canadian Arctic show distinctive increases in total cloud amount in the last forty years especially in the summer season. This result, unlike the historical analogue analysis, seems to be decoupled from temperature changes.     

Falling Lake Victoria water levels: Is climate a contributing factor?

Recently, and perhaps most threatening, Lake Victoria water level has been receding at an alarming rate. A recent study suggested the possibility of the expanded hydroelectric power station in Uganda. However, since the lake receives 80% of its refill through direct rainfall and only 20% from the basin discharge, climatic contributions cannot be ignored, since the 80% water is directly dependant on it. It is therefore necessary to investigate climatic contribution to the declining Lake Victoria water level observed over a long period, i.e., 30 years. This contribution uses 30 years period anomalies for rainfall, river discharge and lake level changes of stations within Lake Victoria basin to analyse linear and cyclic trends of climate indicators in relation to Lake levels. Linear trend analysis using the Student’s t test indicate a decreasing pattern in rainfall anomalies, with the slope being statistically similar to those of water levels at both Kisumu, Maziba and Jinja stations for the same period of time (1976–1999), thus showing a strong correlation. On the other hand, cyclic trend analysis using Discrete Fourier Transform (DFT) shows cyclic period of water level to coincide with those of droughts and rainfall. The strong relationship between climatic indicators of drought and rainfall on one-hand and lake levels on the other hand signifies the need to incorporate climate information in predicting, monitoring and managing lake level changes.     

Disaster risk reduction legislations: Is there a move from events to processes?

Disaster research and scholarship is now advocating a shift from focusing on the hazard event to processes that generate vulnerability and loss of resilience to disasters. Disaster legislations are among prominent instruments that can highlight the tensions as well as challenges that are being encountered towards this change in focus. Using textual analysis, this paper presents a study that investigated whether five post-2002 disaster legislations have shifted emphasis from the hazard to the vulnerability and resilience paradigms. The five examples illustrate that while there is a slight change, at least in rhetoric, from response to a prevention focus, disaster legislations largely promote a centralised institutional framework, with inadequate resource commitments and limited participation from vulnerable communities. Consequently, while generalisations simply cannot be made without a wider analysis of many more examples from different countries, the five disaster legislations appear to re-emphasise the response focus with less attention on the processes that reduce vulnerability and enhance resilience. The conclusion is that while the rhetoric has changed, the disaster legislations have not significantly moved from the hazard to vulnerability and resilience focus suggesting that reduction of losses and damages to disasters remains a big challenge     

Is accurate forecasting of economic systems possible?

Structural constancy, both across time and across variable conditions, is a necessary precondition for accurate forecasting. Physical systems exhibit structural constancy, but economic and social systems generally do not. In this paper we examine the effects of policy, technology, and price volatility in commodity markets on the relationship between soybean oil and petroleum prices. An early Energy Information Administration (EIA) forecast of soy-based biodiesel price projected a simple relationship between soybean oil demand and price into the future??a relationship that has little explanatory power over the recent price volatility in oilseed markets. We propose that structural inconstancy and new trading behavior better explain price movements in soybean oil, and we further argue that forecasters must invent new ways of addressing the fundamental epistemological challenge of structural inconstancy in economic and social systems.     

Historical Evolution of Global and Regional Surface Air Temperature Simulated by FGOALS-s2 and FGOALS-g2: How Reliable Are the Model Results?

In order to assess the performance of two versions of the IAP/LASG Flexible Global Ocean-Atmosphere-Land System (FGOALS) model, simulated changes in surface air temperature (SAT), from natural and anthropogenic forcings, were compared to observations for the period 18502005 at global, hemispheric, continental and regional scales. The global and hemispheric averages of SAT and their land and ocean components during 18502005 were well reproduced by FGOALS-g2, as evidenced by significant correlation coefficients and small RMSEs. The significant positive correlations were firstly determined by the warming trends, and secondly by interdecadal fluctuations. The abilities of the models to reproduce interdecadal SAT variations were demonstrated by both wavelet analysis and significant positive correlations for detrended data. The observed land--sea thermal contrast change was poorly simulated. The major weakness of FGOALS-s2 was an exaggerated warming response to anthropogenic forcing, with the simulation showing results that were far removed from observations prior to the 1950s. The observations featured warming trends (19062005) of 0.71, 0.68 and 0.79 (100 yr)-1 for global, Northern and Southern Hemispheric averages, which were overestimated by FGOALS-s2 [1.42, 1.52 and 1.13oC (100 yr)-1] but underestimated by FGOALS-g2 [0.69, 0.68 and 0.73oC (100 yr)-1]. The polar amplification of the warming trend was exaggerated in FGOALS-s2 but weakly reproduced in FGOALS-g2. The stronger response of FGOALS-s2 to anthropogenic forcing was caused by strong sea-ice albedo feedback and water vapor feedback. Examination of model results in 15 selected subcontinental-scale regions showed reasonable performance for FGOALS-g2 over most regions. However, the observed warming trends were overestimated by FGOALS-s2 in most regions. Over East Asia, the meridional gradient of the warming trend simulated by FGOALS-s2 (FGOALS-g2) was stronger (weaker) than observed.     

Is climate change a driver of armed conflict?

The world is generally becoming less violent, but the debate on climate change raises the specter of a new source of instability and conflict. In this field, the policy debate is running well ahead of its academic foundation—and sometimes even contrary to the best evidence. Although comparative research on security implications of climate change is rapidly expanding, major gaps in knowledge still exist. Taken together, extant studies provide mostly inconclusive insights, with contradictory or weak demonstrated effects of climate variability and change on armed conflict. This article reviews the empirical literature on short-term climate/environmental change and intrastate conflict, with special attention to possible insecurity consequences of precipitation and temperature anomalies and weather-related natural disasters. Based on this assessment, it outlines priorities for future research in this area.     

Is the onset of the English summer advancing?

British summers are known to have become warmer and drier in recent decades, but has there also been a change in the timing of this season’s beginning, as has occurred for spring? This paper addresses this question by examining records of the first blooming date of early summer flowering plants (phenology) and the timing of first occurrences of warm ‘summer’ temperatures, both events that we associate with the onset of summer. This has revealed that the onset of summer in England has been advancing since the mid 1950s. The occurrence of ‘summer’ temperatures has advanced more than early summer flowering, by eleven and three days respectively in the 1990s compared to the period 1954–1963. This may have encouraged drought or heat wave conditions by prolonging the period of warm temperatures and lower rainfall in which these events occur.     

The climate change research that makes the front page: Is it fit to engage societal action?

By growing awareness for and interest in climate change, media coverage enlarges the window of opportunity by which research can engage individuals and collectives in climate actions. However, we question whether the climate change research that gets mediatized is fit for this challenge. From a survey of the 51,230 scientific articles published in 2020 on climate change, we show that the news media preferentially publicizes research outputs found in multidisciplinary journals and journals perceived as top-tier. An in-depth analysis of the content of the top-100 mediatized papers, in comparison to a random subset, reveals that news media showcases a narrow and limited facet of climate change knowledge (i.e., natural science and health). News media selectivity reduces climate change research to the role of a sentinel and whistleblower for the large-scale, observed, or end-of-century consequences of climate change for natural Earth system components. The social, economic, technological, and energy aspects of climate change are curtailed through mediatization, as well as local and short-term scales of processes and solutions. Reviewing the social psychological mechanisms that underlie behavioral change, we challenge the current criteria used to judge newsworthiness and argue that the consequent mediatization of climate change research fails to breed real society engagement in actions. A transformative agenda for the mediatization of climate change research implies aligning newsworthiness with news effectiveness, i.e., addressing the extent to which communication is effective in presenting research that is likely to produce behavioral change.     

Parameter identification for Kalman filtering of noisy and censored data: Is this a data quality control method?

Summary The quality control of rain amount data is usually based on a posteriori defined sets of empirical thresholds, e.g. when crosscheking neighbouring observations. While these procedures are well suited for very long time series, it is difficult to adopt the rules for time series of special observation periods with higher resolution in time. We propose a linear Kalman filter and present several methods, how to fit it onto the stochastic structure of the time series in the presence of many zeroes. These zeroes may indicate light rain or no rain and, therefore, are considered censored. They do not fit into the stochastic structure of the non-zero values and have to be treated separately. Fitting one out of four model parameters of the Kalman filter also determinates two other dependent ones. Only one model parameter has to be known from independent sources. The fitting algorithms are tested with artificial rain rate time series with known stochastic structure and several zero rain data points. Furthermore, applied to time series of observed hourly rain amounts for 4 consecutive winter months, the Kalman filter shows its sensitivity for faulty data points. The detection of conspicuous data by the method of Kalman filtering is discussed.With 3 FiguresProf. Dr. H.-D. Schilling died November 22, 1997.     

Is there any long-term memory effect in the tropical cyclones?

The investigation of the intrinsic properties of the annual tropical cyclone count over Atlantic, during 1870–2006, is herewith attempted. The motivation behind this exploration is to contribute to the current understanding about the dynamics of these disastrous events, as tropical cyclones create destructive impacts for people living around tropical areas. The analytical tool used is the detrended fluctuation analysis, and the exponent obtained reveals that the time series of the annual tropical cyclone count over Atlantic obeys the classical random walk (white noise). In other words, the number of tropical cyclones seems to exhibit neither persistent nor antipersistent behavior. The reliability of the lack of scaling dependence in the time series of the annual tropical cyclone count is confirmed, by applying error bounds statistics and studying the decay of the autocorrelation function (i.e., not rejected exponential decay) and the variability of local slopes (i.e., lack of constancy in a sufficient range). In addition, the fact that the series used is fractional Gaussian noise depicts that the results obtained are reliable, despite the fact that the available data set is still limited. The indication of a nearly white noise signal in the tropical cyclone count fluctuations does not suggest that the climate change phenomenon does not exist.     

Is climate change affecting wolf populations in the high arctic?

Gobal climate change may affect wolves in Canadas High Arctic (80° N) acting through three trophic levels (vegetation, herbivores, and wolves). A wolf pack dependent on muskoxen and arctic hares in the Eureka area of Ellesmere Island denned and produced pups most years from at least 1986 through 1997. However, when summer snow covered vegetation in 1997 and 2000 for the first time since records were kept, halving the herbivore nutrition-replenishment period, muskox and hare numbers dropped drastically, and the area stopped supporting denning wolves through 2003. The unusual weather triggering these events was consistent with global-climate-change phenomena.