Skip to main content

Urbanisation: The problem of local climate modification

People migrate to cities due to different reasons such as easy access to schools, health facilities, jobs and transportation . More people, therefore, live in urban areas than in rural. According to the  United Nations estimate, in 2014 more than 54% of the world population dwell in cities. It was 30% in 1950. Projections indicate that 66%  of the world's population will live in urban by 2050 . Most of urban people reside in relatively small areas with high number of inhabitants per square meter of land (UN, 2015):
"Close to half of the world's urban dwellers reside in relatively small settlements of less than 500, 000 inhabitants, while only around one in eight live in the 28 mega-cities with more than 10 million inhabitants."

It is ages since people noticed that urban air was different from rural air. However, it was air pollution which is the hallmark of the urban atmosphere. In 1818 Luke Howard (1772-1864) published the first edition of a book dealing with the climate of the city (Landsberg, 1981). Howard clearly recognized a major alteration of meteorological element and called it "city fog". He compared mean temperature taken from measurements in the city and out of the city and found out the urban center was warmer than the surrounding countryside. Another discovery of this temperature anomaly was discovered in Paris metropolis by E. Renou (1815-1902) a few decades later. Micro-meteorological investigations of the urban landscape was stated by Wilhelm Schmidt (Landsberg, 1981).It is not only air pollution and high temperature which are attributed to urban weather and climate, but also atmospheric influence of of the city, causing an increase in rain towards the lee side of the city. This was asserted by August Schmauss (1877-1954) while making assessment for the city of Munich (Landsberg, 1981) . Other studies also suggested there is an increase in urban rainfall as the cities grow.On of the steps needed is to measure meteorological variables (temperature, humidity, wind precipitation) of importance in rural and urban environments and compare the results. Simple mean value difference can give an overview of the difference between rural and urban weather. However, topographical features, proximity to industrial sites, and leeward or windward measurement site may produce difference already even before the cities were built.Comparison of such weather and climate elements can be made with certainty if there are observations from a site prior to urbanization for a considerable period of time. But such observation data available rarely.Three major elements that influence the measured values of a metropolitan variable, M are basic climate of the region C, a difference introduced by location L (e.g. topography, water bodies, etc), and an alteration term U produced by urbanization (Landsberg, 1981). M is statistical ensemble consisting of the three components.  

                           M = C + L + U                                             (1)


 From measurements M is the only known quantity. How can we determine U which is the urban effect? Using sample at time 0 and later time t, and assuming in-variance of C and L, one can determine U:

                         Mt = C + L + U                                      (2)

                              Mo = C + L + 0                                               (3)

Urban influence is assumed to be negligible at t = 0, but one can use the system only in the absence of trends in C, certainly not a good assumption. The other scheme to establish an urban influence is to get urban-rural difference of variables measure at one or more sites in the two environments

                       
                                        U = Mu - Mr                                          (4)


the subscripts u and re stand for urban and rural respectively. This is a quick approach that can give at least an estimate of the urban effect.Another frequently used approach is the comparison of time trends in the two environments. Assuming that C and L are not time dependent one can state that    

         
                                            (5)


where i represents individual values of a time series of n members, such as successive yearly values, t is time, and  is the probability that a given weather type will occur in a given time interval t, perhaps suitably split by seasons.Assumptions can also be made that industrial workweek and traffic create difference between workdays and weekends in human influences on some atmospheric parameters. Such comparison of Monday-Friday values with Saturday-Sunday values may reveal urban effects:                

                                                               (6)

where  is a mean value of the element tested on workdays and  is the value for 
non-workdays. This test also needs comparison of no differences in the values for comparable 
splits of days simultaneously in the same area not affected by urbanization. It helps us to find how
 far the city influence reaches.The desire to study urban climate emanates from: a) scientific
 curiosity as to how climate differs between urban and rural, b) application for urban design 
purposes, including building construction, highway and bridge design, drainage systems, stack 
designs for minimizing effluent nuisances, space heating, and air conditioning and similar 
pursuits, c) to identify the causes of extreme weather events like heat and flooding, and d) to 
monitor air pollution.It is generally agreed that solar energy is lower over the cities. The loss could
 be due to availability of aerosols or pollutants in the urban atmosphere. The other reason why 
solar rays are lower is because of turbidity. Turbulence is higher over cities than the 
surrounding rural areas.  Radiative reduction occur because of molecular scattering (Rayleigh
 scattering). Turbidity is a useful measure of atmospheric suspensions, and is expressed as               

                                                    (7)   



                           where  solar radiation extra terrestrially (solar constant)  Solar radiation

 at the Earth's surface correction factor of the seasonally changing distance of sun-earth 
optical air mass extinction factor for pure dry air (Rayleigh) water vapour. This is a 
measure of ratio of the prevailing attenuation of solar radiation to that produced by a clean 
atmosphere where only molecular extinction (Rayleigh scatter and absorption) occurs.Net energy 
flux


                                 
                                                 (8)



[At night the term  vanishes], where net energy balance incoming short wave 
radiation at the surface net energy balance albedo of the surface (reflectivity)downward
 long-wave atmospheric radiation upward long-wave radiation emitted by the surface  
heat flux into and out of the ground or other surfaces sensible heat transfer between
 atmosphere and ground heat loss by evaporation or gain by condensation sensible 
heat transfer between atmosphere and ground heat production or heat rejection from
 man made sources including human and animal metabolism. Each of these factors is different
 in urban and rural areas.Their values can be determined from measurements using 
pyranometer and pyrgeometer. One can also determine the upward long-wave flux using

                                                                        (9)

where emissivity Stefan-Boltzmann constant absolute temperature (K) of the surface

References


Comments

Popular posts from this blog

Building Resilience in the Face of Climate Change: The Limitations of Adaptation

Climate change is an undeniable reality, and its impacts are already being felt across the globe. However, many parts of the world, particularly developing regions like sub-Saharan Africa, are ill-prepared to adapt to these changes. This lack of preparedness stems from several interconnected factors: Limited access to climate predictions: Many regions in sub-Saharan Africa lack access to reliable and accurate climate predictions, making it difficult for communities to anticipate and plan for future climate-related events. Inadequate adaptation technologies: Even when climate predictions are available, communities may not have access to the necessary technologies and resources to implement effective adaptation measures. This can be particularly challenging in regions with limited infrastructure and economic resources. Dependency on external aid: Many developing countries rely heavily on international aid to support climate adaptation efforts. However, this can create a dependency on...

Urban surface parameterizations, uncertainties and challenges

My recent review paper "Review of urban surface parameterizations for numerical climate models"( https://www.sciencedirect.com/science/article/pii/S2212095517300858 ) presents the historical development of urban climate models, uncertainties and challenges  in obtaining representative urban weather and climate information. There are wide scale urban weather/climate models and the level of detail and complexity required for a particular study is oftentimes a challenge for the climate modeling communities. Weather/climate models are required for different purposes, such as understanding the teleconnections between different scale weather/climate phenomena, for weather forecasting and climate projections, and for policy purposes. Therefore, improving the performance of climate models is one of the top priorities in the climate modeling communities. On the other hand, obtaining accurate initial and boundary information is challenging. Observations data of high spatial density ...

Notes on spectral nudging urban climate models - Nudging is wrong, do not do it

Debate erupted about spectrally nudging regional climate models during summer 2016 training on regional climate modeling at National Center for Atmospheric Research (NCAR). The debate was whether nudging is valid for regional climate models. Because of the interest of many participants who were PhDs and postdocs from all over the world, special session was assigned for extended discussion. I was new to the nudging concepts at the time, but thought that it is interesting, especially whether nudging is useful for downscaling reanalysis and GCMs incorporating urban canopy models. I dropped my ear and followed the discussion. Based on the ideas raised from the organizers and participants, I also forwarded some questions of relevance for the urban climate modeling. As an extended discussion during the afternoon, many questions were raised: If a regional climate model is spectrally nudged, doesn't it lose its added value as a regional climate model because nudging forces the model t...