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  • Vasilenko, E. L., and M. A. Lokoshchenko, 2009: Centennial changes of humidity parameters in Moscow (in Russian). Proc. 13th Int. Conf. of Young Scientists, Zvenigorod, Russia, Obukhov Institute of Atmospheric Physics, 22–23.

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  • View in gallery

    Satellite image of Moscow region. The image is based on the data of the ScanEx Research and Development Center (http://www.kosmosnimki.ru). The white line indicates the contours of Moscow in 1992–2011. Green patches are forests.

  • View in gallery

    Horizontal field of the surface air temperature in Moscow and its long-term changes: (a) 1887–89, (b) 1915–16, (c) 1954–55, (d) 1991–97, and (e) 2010–14. The grayish doubled line indicates the contours of Moscow in 1890 for (a), in 1916 for (b), in 1960 for (c) and in 1992–2011 for (d) and (e); stars are ground meteorological stations; thick black lines are mean annual isotherms. Arrows indicate the location of some stations outside the margins of the figure and their directions.

  • View in gallery

    Dynamics of the UHII in Moscow: (a) average data for five periods of several years, (b) mean annual data for each year since 1951, and (c) moving-averaged values for each five years since 1953. Values from 1951 to 2014 are calculated by the data of 5 urban and 13 rural stations that exist now.

  • View in gallery

    Long-term dynamics of mean annual humidity parameters in Moscow in 1870–2015.

  • View in gallery

    Horizontal field of the relative humidity in Moscow and its long-term changes: (a) 1891–97, (b) 1915–16, (c) 1954–55, (d) 1991–97, and (e) 2010–14. Doubled thin black lines indicate the contours of Moscow city in 1890 for (a), in 1916 for (b), in 1960 for (c), and from 1992 to 2011 for (d) and (e); stars are ground meteorological stations; thick blue lines indicate mean annual isovapors. The black star is the station closest to the city center, gray stars are other urban stations, and open stars are rural stations. Stations are labeled as B for Biryulyovo, T for Tushino, N for Nemchinovka, P for Pogodinka, C for CPKR, G for GAMS, and Ph for Phili. Arrows indicate the location of some stations outside the margins of the figure and their directions.

  • View in gallery

    Dynamics of the UDII in the city of Moscow.

  • View in gallery

    Dynamics of factors that influence the intensity of UHI: (top) dynamics of urban population and its density in Moscow, (middle) dynamics of urban population density in the center of Moscow, and (bottom) dynamics of annual electric power consumption in Moscow and the Moscow region.

  • View in gallery

    The central part of Moscow. Thin black lines indicate the boundaries of old urban districts before 1992 and of new administrative districts since 1992 (except one more special enclave district—Zelenograd—that is distant from the others). The shaded gray areas were used in calculations and show the (left) central districts before 1992 and (right) central administrative district since 1992.

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Urban Heat Island and Urban Dry Island in Moscow and Their Centennial Changes

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  • 1 Faculty of Geography, Department of Meteorology and Climatology, Lomonosov Moscow State University, and Obukhov Institute of Atmospheric Physics, Moscow, Russia
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Abstract

The long-term dynamics of both urban heat island (UHI) and urban dry island (UDI) intensities over the city of Moscow, Russia, has been analyzed for the period from the end of the nineteenth century until recent years using data of the ground meteorological network. Besides traditional maximum heat/dry island intensity, an additional parameter—station-averaged intensity as a mean difference between the data of all urban and rural stations—has been used. The traditional maximum (mean annual) UHI intensity in Moscow was nearly 1.0°C at the end of the nineteenth century, 1.2°C one century ago, 1.5°–1.6°C both in the middle and at the end of the twentieth century, and 2.0°C in recent years. The station-averaged UHI intensity was equal to 0.7°–0.8°C in the second half of the twentieth century and increased up to 1.0°C in recent years. It is probable that stabilization of both parameters from the 1950s to the 1990s was connected with the extensive city growth at that time (mass resettlement of inhabitants from the overpopulated city center to the new urban periphery since the 1960s). The new increase of UHI intensities is the result of the new intensive city growth. The relative humidity in Moscow significantly decreased during the last 146 years (mostly because of warming), unlike water vapor pressure. The UDI is closely connected with the UHI; the absolute value (modulus) of its intensity is increasing in time from −4% at the end of the nineteenth century to −9% now. During the last two decades, the UDI as well as the UHI became much stronger than before.

Publisher's Note: This article was revised on 24 January 2018 to add the additional affiliation of the author, which was missing when originally published.

© 2017 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding author: Mikhail A. Lokoshchenko, loko@geogr.msu.su

Abstract

The long-term dynamics of both urban heat island (UHI) and urban dry island (UDI) intensities over the city of Moscow, Russia, has been analyzed for the period from the end of the nineteenth century until recent years using data of the ground meteorological network. Besides traditional maximum heat/dry island intensity, an additional parameter—station-averaged intensity as a mean difference between the data of all urban and rural stations—has been used. The traditional maximum (mean annual) UHI intensity in Moscow was nearly 1.0°C at the end of the nineteenth century, 1.2°C one century ago, 1.5°–1.6°C both in the middle and at the end of the twentieth century, and 2.0°C in recent years. The station-averaged UHI intensity was equal to 0.7°–0.8°C in the second half of the twentieth century and increased up to 1.0°C in recent years. It is probable that stabilization of both parameters from the 1950s to the 1990s was connected with the extensive city growth at that time (mass resettlement of inhabitants from the overpopulated city center to the new urban periphery since the 1960s). The new increase of UHI intensities is the result of the new intensive city growth. The relative humidity in Moscow significantly decreased during the last 146 years (mostly because of warming), unlike water vapor pressure. The UDI is closely connected with the UHI; the absolute value (modulus) of its intensity is increasing in time from −4% at the end of the nineteenth century to −9% now. During the last two decades, the UDI as well as the UHI became much stronger than before.

Publisher's Note: This article was revised on 24 January 2018 to add the additional affiliation of the author, which was missing when originally published.

© 2017 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding author: Mikhail A. Lokoshchenko, loko@geogr.msu.su

1. Introduction

The urban heat island (UHI) is a well-known phenomenon that was first discovered in London, United Kingdom, by L. Howard (Howard 1818). Since the beginning of the nineteenth century, it has been analyzed almost everywhere in the world (Böer 1964; Kratzer 1956; Landsberg 1981; Oke 1978; etc.). As is known, almost every city and even every village creates its own canopy UHI (i.e., warmer air temperatures on average than the surrounding rural area, at least in the evening, at night, and in the early morning). The only exceptions are specific geographical conditions: for example, some cities are cooler than their outskirts in dry tropical deserts because of the urban “oasis effect”: Beersheba, Israel, all the year round before 1985 (O. Potchter 2011, personal communication); Cairo, Egypt, in late autumn (Robaa 2003); Arbīl, Iraq, in Kurdistan during the dry season (Rasul et al. 2015); irrigated urban areas of Phoenix, Arizona, during the daytime (Baker et al. 2002); and so on. Some general conclusions about the UHI in different cities are made in Lokoshchenko (2014).

It is usual to study only daily and/or seasonal variability of the UHI, but another interesting and important direction is the analysis of UHI long-term centennial changes. This analysis for Moscow, Russia, was first made (Lokoshchenko 2013) for the period from 1915 to 1955; it was then expanded for the period from 1887 to 1997 (Lokoshchenko 2014), and stabilization of the UHI intensity in the second half of the twentieth century was discovered. It was supposed (Lokoshchenko 2014) that the deceleration of the UHI intensity growth is connected with the extensive development of the city, but adding new data for recent years surprisingly shows a new sharp growth of the UHI intensity during the last two decades (Lokoshchenko 2015). Thus, the main purpose of this paper is to study long-term changes of Moscow UHI from the 1880s until nowadays and to explain its dynamics using all of the available data on urban population and its density and energy consumption.

In addition, another climatic phenomenon—the urban dry island (UDI)—and its centennial dynamics for the same period have also been studied for the first time. It is probable that the UDI was first described in Berlin and Munich, Germany (Kratzer 1956), but usually this phenomenon is known only by data averaged over more or less shorter periods. As one knows, relative humidity F depends on two parameters: water vapor pressure e and air temperature T because F = e/E × 100%, where saturation vapor pressure E is a function of T. Thus, the UDI is closely connected with the UHI and is the direct result of higher T in the city. In addition, the urban dry island is also the result of less evaporation in a city because of small green areas, anthropogenic precipitation drainage, and so on. As is known, the relative humidity in cities is usually lower than in the rural zone (e.g., Kratzer 1956; Landsberg 1981). For example, the mean monthly difference of F inside and outside the city of Belgrade, Serbia, ranges from −11% to +5% (Unkašević et al. 2001). The difference of F in Chicago, Illinois, and in its outskirts is usually from −3% to −11% depending on the season and the time of day (Ackerman 1987). According to Landsberg and Maisel (1972), the average daily difference of F inside and outside the city of Columbia, Maryland, is −4%, and one-half of this value is the result of UHI, whereas the other half is the result of lower urban evapotranspiration.

2. Urban island parameters

As a rule, the simplest parameter—the so-called UHI intensity ΔT—is used to describe this phenomenon. It is usually calculated as the difference between air temperature T (or any other meteorological element for any other type of urban island; see below) from the data of one ground weather station in the city center and one or several stations in the rural zone. If there is a station just in the center of a city, its data on air temperature TC are usually the highest among other urban stations (of course assuming that a city has a symmetrical form). In such a case, this parameter ΔT indicates maximal intensity in space. Note that a “center” in urban climatology means a district with the highest buildings density, and therefore a station with the highest TC data may be located anywhere depending on city configuration. Other urban stations in the urban periphery around the center (either real geometrical or conventional) as a rule represent intermediate TU values, whereas rural stations outside a city indicate the lowest TR values (in the absence of additional geographical factors such as coastline, nonflat relief, etc.). Therefore, traditional UHI maximum intensity is equal to
e1
where j is any rural station and m is the number of them around a city.
In addition to this parameter, another useful one is the so-called areal or station-averaged UHI intensity UHIIA (Lokoshchenko 2014), which is averaged not only in time but in space as well; it is equal to
e2
where i is any station in the urban periphery and n is the total number of them.

The geographical basis of reliability of the UHIIA as a new parameter is the well-known fact that a heat island often represents a “plateau” form in the field of T with a sharp increase of air temperatures close to city margins (Landsberg 1981). It is evident that if the density of urban development is nearly the same everywhere inside a city then TC ~ TU and parameters UHIIMAX and UHIIA are close to each other. On the other hand, the more inhomogeneous an urban area inside a city is, the bigger the difference between TC and TU is. Of course, the UHIIA value may be analyzed only if the ground meteorological network is dense, that is, if several weather stations operate inside a city simultaneously. Note that the traditional parameter UHIIMAX strongly depends on the environs and data quality of only one central urban station. The values of UHIIMAX may be biased in time if the close vicinity of a central station has significantly changed or if a central station was displaced. For this reason, UHIIA seems to be a more statistically trustworthy parameter than UHIIMAX. A similar approach (calculation of UHIIA) was used for gridded data for mean annual values of T on the basis of 1 km × 1 km grid cells by Gallo and Xian (2014) and for minimum T on the basis of 1 km × 1 km grid cells by Debbage and Shepherd (2015). Below, we shall use both parameters in their comparison with each other.

The main parameters of the UDI as well as the UHI are its maximum and average intensities:
e3
e4
similar to Eqs. (1) and (2) but where relative humidity is used. It is evident that the UDI intensity, unlike the UHI intensity, has a negative sign, as discussed below in section 5.

3. Method

Note that, since at least the end of the nineteenth century, the air temperature T was measured in the Russian Empire and then in the Soviet Union and Russian Federation at the 2-m level above the surface using classical August psychrometers (which include dry and wet mercury thermometers) in special meteorological boxes—in the “Russian box” (Wild box) from 1874 until 1910–14 and later in the “English box” (Stevenson box). The accuracy of T measurements is in the limits of ±0.2°C for positive values and ±0.3°C for T < 0°C (Reifer et al. 1971). The frequency of measurements was three times per day at 0700, 1300, and 2100 LT (the so-called classical Mannheim hours that were used since the eighteenth century) before 1936; four times per day at 0100, 0700, 1300, and 1900 LT from 1936 to 1965; and eight times per day (every 3 h) from 1966 to the present. All thermometers at any station are tested regularly in accord with the standards of the Russian Hydrometeorological Service; their instrumental correction is usually tested by measurements of the 0°C value (low reference point) in melting snow and other values (±5°, ±10°C, etc.) in some liquids (e.g., in spirits) with the use of a reference platinum thermometer.

The atmospheric humidity, according to classical order, is measured using either an August psychrometer (i.e., simultaneous readings of both dry and wet thermometers in a Stevenson box; Kedrolivansky 1937) when T ≥ −10°C or a hair hygrometer in the same box if T < −10°C (Bespalov 1969). Thus, constant instrumentation provides a homogeneous long-term time series. Mean annual temperature and mean relative humidity F are calculated as an average of 12 monthly averaged values of T and F, respectively.

4. The urban “heat island” in Moscow

The main part of Moscow (except six protuberances) has a symmetrical ellipsoidal form. It is located on flat terrain that is almost homogeneous with no vast areas of open water. As seen from a satellite image (Fig. 1), the Moscow River, which flows across the city from northwest to southeast, is narrow (its width inside the city is only 120–200 m). Therefore, it does not influence the T spatial field except for microscale thermal effects along its banks. Note also that the Moscow region is a significantly forested zone; forests cover about 40% of the region.

Fig. 1.
Fig. 1.

Satellite image of Moscow region. The image is based on the data of the ScanEx Research and Development Center (http://www.kosmosnimki.ru). The white line indicates the contours of Moscow in 1992–2011. Green patches are forests.

Citation: Journal of Applied Meteorology and Climatology 56, 10; 10.1175/JAMC-D-16-0383.1

The urban heat island intensity in Moscow was studied for five separate periods (Fig. 2). Figure 2a shows the following (Lokoshchenko 2014): at the end of the nineteenth century, on an average of 3 yr, the difference between T at Landmark Institute (an almost central station located 3.3 km from the Kremlin center) and Mikhelson Observatory (in the close city outskirts) was equal to 0.9°C, whereas the difference between Landmark Institute and Nikolskoye-Gorushki station in the far rural zone was greater: 1.2°C (Shechtman 1953). Of course, only one rural station is insufficient for the analysis; moreover, this difference may be a bit overestimated because of geographic zonality (this station was located to the north of the city). Nevertheless, we can suppose that the heat island intensity UHIIMAX was equal to about 1.0°C at that time. It is evident that this parameter of the UHI intensity is only available from the data of one urban station.

Fig. 2.
Fig. 2.

Horizontal field of the surface air temperature in Moscow and its long-term changes: (a) 1887–89, (b) 1915–16, (c) 1954–55, (d) 1991–97, and (e) 2010–14. The grayish doubled line indicates the contours of Moscow in 1890 for (a), in 1916 for (b), in 1960 for (c) and in 1992–2011 for (d) and (e); stars are ground meteorological stations; thick black lines are mean annual isotherms. Arrows indicate the location of some stations outside the margins of the figure and their directions.

Citation: Journal of Applied Meteorology and Climatology 56, 10; 10.1175/JAMC-D-16-0383.1

Almost 30 years later, six meteorological stations—two urban ones and four close rural ones—operated in this area (Fig. 2b). As is seen, the +4°C isotherm is a semicircle and goes around the southern margin of the city during the First World War. In total, 15 meteorological stations including two urban ones operated in the Moscow region at that time (six of them are shown in Fig. 2b). The mean T in the rural zone outside the city during these two years was in the range from +2.6° to +3.6°C for 13 rural stations at a distance up to ~100 km from the city (some stations are outside the margins of Fig. 2b). On average, it is equal to +3.2°C both for all of these 13 stations and for four rural stations in the close vicinity of the city (up to 35 km) as Fig. 2b shows. Hence, the UHIIMAX value in 1915–16 was equal to 1.2°C according to Eq. (1). The methodical questions about the real rural air temperature and some details of this analysis are discussed in Lokoshchenko (2014). In this paper, the UHIIMAX for this period was initially supposed to be a bit higher: from 1.2° to 1.4°C, taking into account the value of T = +3.0°C at two stations as probably a real rural background.

Forty years later (Fig. 2c), the density of the ground meteorological network was the highest: at least 34 stations were operating in the Moscow region, including 13 stations inside the present-day margins of the city. Note that in the mid-1950s the margins of Moscow were unclear: they were fixed five years later, in August 1960 (an ellipsoid in Fig. 2c). Nevertheless, probably 10 of these 13 stations were really inside the city in 1954–55, and the other three represented close suburbs at that time. Initially (Lokoshchenko 2014), the measurements of only 8 urban stations and 24 rural ones were analyzed by Shechtman (1971). Later the author found the archival data of two more special urban stations [Main Aviation Meteorological Station (GAMS) and Phili] that operated in the city at that time but were not included in Shechtman (1971); now they have been included in the analysis. The heat island is marked here by two quasi-circle isotherms: +4° and +5°C. The closest station to the city center, Balchug, which is situated only 0.6 km to the south of the Kremlin (1.1 km from the Kremlin center), showed the highest air temperature at that time: +5.35°C. All other urban stations showed a gradual decrease of T from the center to city margins. The mean T inside the city was +4.61°C on the basis of the data from 10 real urban stations and +4.50°C by the data from all 13 stations that were located inside up-to-date margins of the city; previous mean values from 8 old urban stations and 11 new (since 1960) urban stations in Lokoshchenko (2014) were the same, to an accuracy of 0.1°C. In the rural zone of the Moscow region, the mean T at that time was equal to +3.79°C averaged over the data from 24 stations (and +3.74°C; i.e., only a little lower by the data of 21 stations outside modern city margins). Thus, in 1954–55, the traditional UHIIMAX intensity value in Moscow (i.e., the difference between Balchug station and all 24 rural stations) was about +1.56°C, whereas the UHIIA value (the difference between 10 urban and 24 rural stations) was equal to +0.82°C. With the account of new city margins (13 urban and 21 rural stations), both UHIIMAX and UHIIA are the same, to an accuracy of 0.1°C: +1.6° and +0.8°C. It should be taken into account that the ground meteorological network in the Moscow region was later reduced, and only 5 urban stations, including Balchug, and 13 rural stations remained in 1991–97 and 2010–14. Thus, for a more correct comparison of different periods, we must use a lower number of stations. The mean T in the urban area in 1954–55 by the data of only the five stations that exist now is nearly the same (+4.48°C), however, and outside the city by the data of 13 stations it is exactly the same (+3.79°C). Hence, recalculated for n = 4 in Eq. (2) and m = 13 in Eqs. (1) and (2), the UHIIMAX value is the same as before (+1.56°C) and the UHIIA value is only a little lower (+0.69°C).

The heat island mapping from 1991 to 1997 (Fig. 2d) demonstrates two semicircle isotherms: +6°C in the city center and +5°C around the western city margins. The maximum T in the city center (Balchug station) was equal to +6.48°C; the mean T inside the city by the data of five urban stations was +5.69°C, whereas outside the city it was +4.86°C averaged over the data of 13 stations. Note that in Lokoshchenko (2014) only 10 of 13 rural stations were used for the analysis of the 1991–97 period; the data rows of three more rural stations (Kashira, Klin, and New-Jerusalem) have breaks: either one or two of seven mean annual T values are absent for that time. Now the author has received restored values of T for all three of these stations for the lost years by comparing them with the closest neighboring stations and using simple correction as the average difference ∆T between two stations for other years for which mean annual values were available at both places. Note that ∆T is comparatively stable in time; its standard deviation σ from one year to another for closest stations at distances of 40–50 km on flat terrain (e.g., between Kashira and Kolomna) is only 0.09°C. Therefore, the probable error of the restored value of T on the average of seven years is only about ±0.01°C if one year is missing. So, as a result, these three stations were included in the analysis.

Thus, the UHIIMAX intensity value was 1.62°C—that is, only about one-half of a tenth of a degree higher than 40 years ago. The UHIIA value also increased only a little since the 1950s: 0.83°C. In fact, it seems to be a surprising result given the continued fast city growth in the second half of the twentieth century. That is why the UHI intensities for these two periods have been precisely analyzed with such a high accuracy of 0.01° Celsius.

In recent years (averaged from 2010 to 2014), as one can see in Fig. 2e, T in Moscow became still higher: +7.8°C at Balchug station and from 6.3° to 6.7°C at the other four urban stations. Thus, one more semicircle isotherm of +7°C appeared in the center of Moscow. On the basis of the same data sampling (5 urban and 13 rural meteorological stations), the values of UHIIMAX and UHIIA averaged over five recent years are 2.0° and 1.0°C, respectively. So, both parameters demonstrate a new growth after the previous period of their quasi stabilization. The consequent increase of the air temperature in Moscow from one period to another during 128 years is evident in Fig. 2: T became higher by 0.5°C from 1887–89 to 1915–16, by 1°C from 1915–16 to 1954–55, by 1°C from 1954–55 to 1991–97, and by an additional 1°C from 1991–97 to 2010–14. This increase is the result of both global climate warming and rapid city growth. So, during 128 years, T grew by 4°C in the city center and by nearly 3°C in the rural zone of the Moscow region.

The results of the analysis are presented in Fig. 3a. It demonstrates long-term dynamics of the UHI intensity in Moscow during 128 years, both traditional [Eq. (1)] and station averaged [Eq. (2)]. The general growth is evident, but, as is seen, during the second half of the twentieth century both parameters of the UHI intensity changed only a little, whereas earlier and later the intensity growth was fast. In the previous work (Lokoshchenko 2014), the values of UHIIMAX and UHIIA in 1954–55 and 1991–97 were received as equal. In this work, the author used the same number of stations during both periods for a more correct comparison and, in addition, three more rural stations were considered for the later period—nevertheless, the overall conclusion about quasi stabilization of the UHI has been confirmed. Figure 3b presents mean annual values of both intensity parameters from one year to another for a more detailed analysis of the dynamics (full data from all stations unfortunately are not available from 1966 until 1990). It is evident that one year may be an insufficient period for statistically reliable UHI intensity analysis because the general tendency is masked by local sharp maxima and minima due to specific weather phenomena in some years (mostly because of different durability of anticyclonic conditions that strongly influence intensity values). The standard deviations of mean annual UHIIMAX and UHIIA values are ~0.2°–0.3° and 0.1°C, respectively. Thus, the same dynamics has been analyzed again with the use of a moving average for a more clear indication of the general tendency. Both UHIIMAX and UHIIA mean annual values have been averaged for each 5 years with a 1-yr step in time for the 1953–2012 period (Fig. 3c). Indeed, as is seen, the estimations of both parameters were nearly the same in the 1950s and 1990s, and a new fast growth of the UHI intensity has started in the mid-2000s (since 2003–05).

Fig. 3.
Fig. 3.

Dynamics of the UHII in Moscow: (a) average data for five periods of several years, (b) mean annual data for each year since 1951, and (c) moving-averaged values for each five years since 1953. Values from 1951 to 2014 are calculated by the data of 5 urban and 13 rural stations that exist now.

Citation: Journal of Applied Meteorology and Climatology 56, 10; 10.1175/JAMC-D-16-0383.1

5. The urban “dry island” in Moscow

Let us discuss another interesting phenomenon, the urban dry island. Figure 4 shows long-term variability of both e and F mean annual values for Moscow since 1870 when regular accurate measurements of both parameters started. This time series is combined with the data of three stations: Landmark Institute from 1870 to 1878 (which was the oldest meteorological station in Moscow before its closing in 1932), Mikhelson Observatory from 1879 to 1953 (which is the oldest Moscow station now), and Moscow University Observatory from 1954 to present. Note that monthly averaged values of both parameters were compared for the periods of simultaneous measurements at two stations (in 1879 for Landmark Institute and Mikhelson Observatory and from 1954 to 1970 for Mikhelson Observatory and University Observatory). It was found that the relations between the data in different urban locations are very close, especially for e values: linear correlation coefficient R is equal to 0.974 for relative humidity and even to 0.999 for water vapor pressure in both places (Vasilenko and Lokoshchenko 2009). Therefore, this common row of data may be accepted as homogeneous. For the first time, this long-term dynamics was published by Vasilenko and Lokoshchenko (2009) and Lokoshchenko and Vasilenko (2010); in this paper, it is expanded to recent years. As is seen, water vapor pressure does not demonstrate systematic changes during the last 146 years. The linear regression coefficient K is equal to only 0.0015 hPa yr−1; thus it is seen that during the last 146 years the average water content in the ground air layer above Moscow increased on average by only a little—0.2 hPa. Such a small difference is evidently negligible and statistically nonsignificant. Of course, the change of e is not linear: for example, since the end of the 1970s, its growth became faster but during the recent years it decelerated again. Note that the dynamics of e inside and outside the city is very similar: for the period from 1966 to 1997 when the growth of e accelerated, the K value was equal to 0.007 hPa yr−1 by the data of Moscow University and was a bit larger, 0.012 hPa yr−1, in the Moscow region by the average data of four rural stations (Mozhaisk, Pavlovsky Posad, Serpukhov, and Dmitrov).

Fig. 4.
Fig. 4.

Long-term dynamics of mean annual humidity parameters in Moscow in 1870–2015.

Citation: Journal of Applied Meteorology and Climatology 56, 10; 10.1175/JAMC-D-16-0383.1

Unlike this parameter, relative humidity F demonstrates a quick and systematic (steady in time) fall with the average rate of K = −0.06% yr−1 during the last 146 years; in other words, it decreased from 81% in the 1870s to nearly 72% in recent years. Inside the city, it is the result of general T increase due to both global warming and the intensification of the Moscow UHI. Outside the city, the long-term fall of F is the result of global warming only. So, it is not a surprise that in the Moscow region its rate of decrease is half as fast as inside the city. For the period from 1951 to 2015 (for which data on F in the Moscow region are available), the linear regression coefficient K of F mean annual values is −0.06% yr−1 at Moscow University and only −0.03% yr−1 in the Moscow region by the average data of the same four rural stations mentioned above.

The dynamics of the main humidity parameters allows one to understand long-term changes of the F spatial field in a big city. Let us discuss the dynamics of the urban dry island in Moscow as was done above for UHI. Note that human-body sensations and human health depend on relative humidity more than on absolute humidity level—thus, dryness is a more important parameter than any other humidity parameter such as water vapor pressure, specific humidity, and so on. The hygiene standard for a human body is the F in the range from 30% to 60% (Isaev 2001).

One of the methodical problems of this study is the change in measurement frequency. As was already mentioned above, the meteorological measurements in the Russian Empire and in the Soviet Union were carried out three times per day before 1936, four times per day from 1936 to 1965, and eight times per day since 1966. The relative humidity data are available in Shechtman (1959, 1972) as average values at each time of observation. To receive a homogeneous row of data, a special correction was made using hygrograph records (daily hygrograms) at the Moscow University meteorological observatory that indicate the values of F during every hour. A perfect (the most accurate) mean daily value of F24 as an average of 24 hourly values during a day was compared with an average both of three values F3 and of four values F4 according to the time of observations in the past for each day during three years (1981–83). As a result, the correction coefficient between a perfect mean daily value and mean value of three times (0700, 1300, and 2100 LT) is equal to 1.0049 (standard deviation σ = 0.0384; sample size n = 1095). The similar correction between F24 and F4 is equal to 0.9997 (σ = 0.0386; n = 1095). On the basis of these corrections, all mean values of F before 1966 were recalculated by the author to receive a homogeneous data row.

Let us discuss the intensity of the UDI and its centennial dynamics in time. As was the case for the UHI, the analysis is possible only from the moment when two stations, urban and rural, began to operate simultaneously. In the Moscow region, only in 1879 did the second station (Mikhelson Observatory, formerly known as Petrovsko-Razumovskoye and TSKhA) appear; before that, only one station (Landmark Institute) operated in the city. Landmark Institute was located close to the Moscow Kremlin center (see above), and therefore it may be accepted as a central station. The station data on relative humidity F are unfortunately available only since 1891 (Shechtman 1959) and for fewer stations than for T. Unlike air temperature, relative humidity at most stations in the Russian Empire was a seasonal parameter and was as a rule measured only during a warm season—hence, mean annual values are available for only a few of the stations (Moscow Province Council 1915). Figure 5a shows that on average for the 1891–97 period we can compare the data of only two stations: Landmark Institute in the central part of the city and Mikhelson Observatory, which at that time represented close suburbs. None of the remote rural stations in the Moscow region measured F continuously in the 1890s. Averaged over seven years, F was equal to 75.0% at Landmark Institute and 78.9% at Mikhelson Observatory so that UDIIMAX = −3.9% according to Eq. (3). Of course, this value is only approximate because for more correct estimation of this parameter we need data from several rural stations.

Fig. 5.
Fig. 5.

Horizontal field of the relative humidity in Moscow and its long-term changes: (a) 1891–97, (b) 1915–16, (c) 1954–55, (d) 1991–97, and (e) 2010–14. Doubled thin black lines indicate the contours of Moscow city in 1890 for (a), in 1916 for (b), in 1960 for (c), and from 1992 to 2011 for (d) and (e); stars are ground meteorological stations; thick blue lines indicate mean annual isovapors. The black star is the station closest to the city center, gray stars are other urban stations, and open stars are rural stations. Stations are labeled as B for Biryulyovo, T for Tushino, N for Nemchinovka, P for Pogodinka, C for CPKR, G for GAMS, and Ph for Phili. Arrows indicate the location of some stations outside the margins of the figure and their directions.

Citation: Journal of Applied Meteorology and Climatology 56, 10; 10.1175/JAMC-D-16-0383.1

One-quarter of a century later, during the First World War, the data of five stations in the Moscow region (four of which are presented in Fig. 5b; one more was too distant from the city) are available. The lowest value of F in average of two years (76.9%) was received just in the city center (at Landmark Institute), whereas the second urban station Mikhelson Observatory (which appeared inside the city already at that time) registered a little higher value: 78.4%. At three rural stations, respective mean F values were 82.1%, 82.0%, and 78.7% (on average: 80.9%). So UDIIMAX remained nearly the same as before: −4.0%. Even for such a short period (two years), this estimation seems to be very reliable because in 1915 and in 1916 UDIIMAX was equal to −4.2% and −3.8%, respectively; that is, its change from one year to another is small. As one can see in Fig. 5b, the urban dry island is evidently a real geographical phenomenon because F grows both to the south and to the north of the city.

For the period of 1954–55, the data on F are available for 32 of 34 weather stations in the Moscow region [Shechtman (1972) and additional archival data] except for two rural stations where data are available only on T (Shechtman 1971). As Fig. 5c shows, the new central Balchug station at that time registered the lowest F value averaged over two years: 71.9%. At the same time, other urban stations demonstrated intermediate values from 74% to 76%, whereas at rural stations this parameter was from 77% to 80%. Two of three urban stations closest to Balchug station demonstrate a little higher value (74%), and only at GAMS station, in the close vicinity of the center, F = 76% (it is seen as a bending curve around it in Fig. 5c). So, a comparatively high value could be the result either of microclimatic specifics of the GAMS location or of wrong instrumental correction to thermometers: either dry thermometer readings were a bit underestimated (it may be as well the cause of similar bending of the +5°C isotherm in Fig. 2c), or wet thermometer readings were a bit overestimated, or both. Averaged over two years in the mid-twentieth century, the relative humidity inside the city (averaged by the data of 10 urban stations including Balchug marked by gray and black stars in Fig. 5c) was equal to 74.7%, whereas in the Moscow region outside the city (averaged by the data of 22 rural stations that existed at that time), it was equal to 77.7%. Therefore, UDIIMAX = 71.9% − 77.7% = −5.8%; UDIIA = 74.7% − 77.7% = −3.0% for n = 9 and m = 22 in Eqs. (3) and (4). For a more correct comparison with the next two periods, however, we should account for the reduction of the ground network. Therefore, all values were recalculated only for the data of stations that exist now: mean relative humidity was 74.8% in the city by the data of 5 urban stations and 77.9% outside the city by the data of 13 rural stations. Hence, average estimations are close to each other despite different sampling. As a result, both parameters of the UDI intensity are nearly the same as well: UDIIMAX = −6.0%; UDIIA = −3.1% (for n = 4 and m = 13).

Forty years later, averaged from 1991 to 1997 (Fig. 5d), the F value at the central urban Balchug station was equal to 73.0%, the average over all 5 urban stations was 76.0%, and the average of all 13 rural stations was 78.1%. Thus, UDIIMAX = −5.1% and UDIIA = −2.1%. In reality, UDI is contoured by the 75% isoline and includes only three stations. Besides Balchug, the isoline includes two more stations: University and Nemchinovka (a close rural station that is located only 1 km to the west of the city margin; usually, it demonstrates intermediate position between urban and rural stations), where the F value was only a little higher than at Balchug station: 74%. In the north of the city and in the rural zone, average F values were from 76% to 80%. So, the UDI became weaker than it was in the mid-1950s because the average F in the urban area increased significantly (by 1.2% for the same 5 stations), whereas outside the city, it remained nearly the same (it increased only a bit by the data of the same 13 stations: by 0.2%). As one can see in the 1990s, all urban stations except for University station demonstrate higher relative humidity than was observed 40 years ago.

Averaged over the five years from 2010 to 2014, the F value at Balchug station is the lowest among other stations: 68.0%; the mean F values in urban and rural areas by the data of the same 5 and 13 stations are 73.2% and 76.6%, respectively. Hence, UDIIMAX = −8.6% and UDIIA = −3.4%; so, UDI recently became much stronger than before. As a result, for the first time, it is marked by two isovapors (lines of the same relative humidity): 70% and 75%. The absence of observations to the south and to the east of the city unfortunately makes it not possible to close the isovapors.

Some details of the above analysis and methodical questions need a brief comment. Note that data rows of both the Landmark Institute and Mikhelson Observatory are complete and continuous in time. Unlike them, at some other stations there were short breaks in observations. For example, at Biryulyovo (southern rural station in Fig. 5b) and at Ramenskoye forestry (one of two northern rural stations at that time), the data on F during 1915 and 1916 are available for 22 of 24 months, whereas at Sergiyev Posad (another northern station) data were available only for 17 of 24 months. In a similar way, in 1954 and 1955 relative humidity was measured at Central Park of Culture and Recreation (CPKR) urban station during 21 of 24 months and at Kashira rural station during 20 of 24 months. During the period from 1991 to 1997, there were several breaks as well: the data on F at Balchug and Tushino urban stations were respectively received for 83 and 82 of 84 months. Of 84 months, data were received for 83 months at Klin and Kolomna rural stations, 82 months for Kashira and New-Jerusalem, 80 months at Serpukhov, and only 70 months at Klin. In all of these cases, missing values for some months were restored as the most probable values using special correction in comparison with the nearest station. The mean coefficient K between the values of two stations for the same month (when a break at one of them occurred) during several years before and after a break was used (it is important to note that K may be a function of the annual cycle and therefore for the correction we need to use a comparison for the same month). Note that the spatial field of relative humidity is relatively smoothed in conditions of flat relief and in the absence of large areas of open water. The linear correlation coefficient R between mean monthly values of F at several neighboring stations, both in the city and in the rural zone (at distances from 50 to 90 km from each other), for the period of 1990–2000 ranges from 0.92 to 0.96. As is known, the R values of the spatial field of air temperature in the Moscow region at distances up to 100 km are very similar—higher than 0.8 in the warm season and higher than 0.9 in winter (Rubinstein 1979). As a result of the smoothed F field, relations between mean values of F at neighboring weather stations (up to 100 km from each other) are close (as a rule, K is limited to being from 0.95 to 1.05) and steady in time (standard deviation σK of K values in different years is on average only 0.04). This means that a possible error of the monthly averaged restored value of F taking into account the σK value and a typical range of this parameter (usually from 70% to 80%; extreme monthly averaged values can range from 55% to 95% depending on a season) is about 2%–3%. Hence, for example, if at any station, 2 of 84 monthly averaged values are unknown, the most probable error of the total F value averaged over seven years there is only 0.05%–0.07% (i.e., very small). Note as well that Tushino urban station (star in the northwestern part of the city in Figs. 5c–e) was replaced and has operated 6.5 km to the north from its previous location since 1986.

Another specific correction was made for the data of Pogodinka urban station for the period of 1954–55 where, since June of 1955, the measurements of F began to be made only three times per day instead of four times like before—without a nocturnal reading at 0100 LT. For this station, a comparison with nearest neighbor University Observatory station (3.0 km away from Pogodinka station) was carried out for this nocturnal time only. The coefficient between nocturnal values of F at these two stations in 1954 (when measurements were simultaneous at both places) was used for each month since June–December of 1955 to restore missing values at Pogodinka; then mean monthly values F4 were calculated by three real values and one restored value, and last a correction 0.9997 was used to get accurate daily averaged estimation. Here, the correction was based on simultaneous data during only one year because University Observatory station was founded in 1954 and soon after 1955 Pogodinka station was closed. Thus, the rows of F data are continuous at both stations in 1891–97, at 2 of 5 stations in 1915–16, at 29 of 32 stations in 1954–55, at 10 of 18 stations in 1991–97, and at all 18 stations in 2010–14.

Long-term changes of the UDI intensity are presented in Fig. 6 as was done above in Fig. 3 for the UHI intensity. Similar to Fig. 3, both UDIIMAX and UDIIA values for the period 1954–55 are shown here for a reduced number of stations (5 urban and 13 rural) that operate now for a more correct comparison with the two later periods. As is seen, the UDI intensity dynamics is complicated and nonmonotonic. Periods of clear UDI intensification in the beginning of the twentieth century and during the last two decades are separated by the UDII fall—both maximum and average—in the second half of the past century. This result seems unexpected. The question is what happened and why did UDI become weaker in the 1990s than it was before? This fall corresponds to quasi stabilization of the UHI intensity that took place at that time as was shown above. So, why did the UDI intensity not stabilize as well?

Fig. 6.
Fig. 6.

Dynamics of the UDII in the city of Moscow.

Citation: Journal of Applied Meteorology and Climatology 56, 10; 10.1175/JAMC-D-16-0383.1

Its fall was evidently not the result of some local changes in the close vicinity of the central station Balchug because the UDIIA value, as is seen, also decreased. True, one of five urban stations was displaced as already mentioned, but four other stations remained where they were in the 1950s. According to additional calculations accounting for only four urban stations without Tushino, UDIIA = −3.5% in 1954–55 and UDIIA = −3.0% in 1991–97. Thus, it is seen that weakening of the UDI was a real effect and was not the result of the displacement of one station. The method of humidity measurements and even the type of sensors remained everywhere the same because the Soviet meteorological service was classical and conservative. Note as well that this fall was not the result of some changes in the air moisture content because the e data of University Observatory station remained nearly the same: it was on average 7.6 and 7.7 hPa, respectively, for the periods 1954–55 and 1991–97. In addition, the reduction of UDI intensities was not the consequence of a too-short period of only two years of averaging in 1954–55. An additional calculation was made for 7 years from 1954 to 1960, and the mean F value at Balchug station was received as 71.9%; the mean F at urban (5 stations) and rural (13 stations) areas was 74.8% and 78.2% respectively; thus, UDIIMAX = −6.3%; UDIIA = −3.4%, and therefore averaged over 7 years in the 1950s the UDI was even deeper and, hence, its fall during the next 37 years was even sharper.

The most probable cause of the UDI weakening is the intensive greening of the city. However, park and forest zones inside Moscow did not increase inside new city margins: the total area of all green zones was 68.7 km2 in 1958, 167.8 km2 after city extension in 1961 (Central State Archive of Moscow 1964), nearly 66 km2 in 1978 (Great Soviet Encyclopedia 1980), and 65.6 km2 in 1995 (Great Russian Encyclopedia 1998). Thus, the reason for the UDI weakening in Moscow from the 1950s to 1990s remains an open question.

Nevertheless, despite a temporary decrease, in general during the whole period of the F measurements, the UDI in Moscow became stronger: from −4% at the end of the nineteenth century to −9% in recent years. It is evident that this effect is an indirect consequence of the UHI intensification because both phenomena are closely connected (the warmer the urban air is, the drier it is). It is interesting to note that, according to Kratzer (1956), the average intensity of the UDI in German and Austrian cities (apparently the UDIIMAX value) was from −4% to −6% in the beginning of the twentieth century. In Parma, Italy, this parameter in the 1970s was equal on average to −5% (Landsberg 1981). In the afternoon in anticyclonic conditions, however, the difference of F between the urban center and the park zone may be much bigger—up to 30% as was observed in Munich (Kratzer 1956).

Note that the level of absolute humidity mostly reflects total water content in different air masses, and so its variability is large scale and the spatial field of e is comparatively smoothed. According to Oke (1978), the difference between the values of e inside and outside cities is small and changes its sign in the daily cycle. Thus, unlike average dryness, average humidity does not demonstrate time-stable local effects such as an urban island. The urban “humidity island” (i.e., higher values of e inside the city) may exist only late in the evening and at night in anticyclonic conditions because of the absence of dew or at least much weaker dew in the city than in the rural zone (Chandler 1967; Landsberg 1981; Oke 1978; Kuttler et al. 2007). Even if the urban humidity island exists in the afternoon, it is the strongest on average at night—for example, in Chicago (Ackerman 1987).

Using mean annual e values, the average intensity of a hypothetical urban humidity island (UHumI) in Moscow,
eq1
was calculated for different times. For the first period, from 1891 to 1897, the average value of UHumIIA [i.e., the difference between the average values of e at Landmark Institute (the city) and Mikhelson Observatory (close suburbs)] is −0.3 hPa. For the second period (1915–16) when Mikhelson Observatory became an urban periphery, however, the difference between the same two stations (whose data are the only ones available in the whole region) is 0 hPa. Over the 41 years of available simultaneous measurements at these two locations (1891–1931), the average difference is only −0.06, whereas the standard deviation σ of the mean annual values is 0.16. Thus, the sign of this difference is not clear.

For the period of 1991–97, the average e is 8.0 hPa in the city (by the data of 5 urban stations) and 7.9 hPa in the rural zone (by the data of 13 rural stations). The standard deviation σ is 0.5 hPa for the sampling of 35 mean annual values of e at urban stations and σ = 0.4 hPa for the sampling of 89 mean annual values at rural stations (two values are absent). Thus, the difference between the city and rural zone (0.1 hPa) averaged over 7 years is not statistically significant.

6. The analysis of the city development

The dynamics of both urban islands that was discussed above needs explanation. The previous results of the long-term dynamics of the UHI intensity that were analyzed by Lokoshchenko (2013, 2014) and its quasi stabilization from the mid-1950s (Fig. 2c) to the mid-1990s (Fig. 2d) were explained in Lokoshchenko (2014) by the probable extensive growth of the city in the second half of the twentieth century. As a result, the heat island intensity asymptotically approaches its upper limit. A similar effect was noted, for example, for London (Wilby et al. 2011) and Madrid, Spain (D. F. Rasilla Alvarez 2013, personal communication).

Later (Lokoshchenko 2015) a new increase of the UHI intensity during the recent two decades (Fig. 2e) was observed in new additional data. As was shown above, the UDI intensity, as well as the UHI intensity, was in general increasing. Yet from the 1950s until the 1990s, it even decreased. To explain these changes, it is necessary to take into account the factors that create additional heat and additional dryness in the city. Note that the exact real intensity of urban heat sources, the density of the urban development (the average part of buildings and asphalt pavement in an area unit in the city), and some other physical parameters that directly influence the UHI and UDI intensities are unfortunately unavailable. Some indirect economic and social factors—for example, the density of urban population and energy consumption—are closely connected with the direct physical factors, however. Let us discuss their long-term changes in Moscow.

As the top panel of Fig. 7 shows, the population of the city (filled symbols) demonstrates an almost monotonically increasing function since at least 1886 excepting only two falls during the Russian Civil War in 1917–20 and the Second World War (called the Great Patriotic War in the Soviet Union) in 1941–45. The official statistics of Moscow population are available from the Central State Archive of Moscow (1957, 1963, 1964), Great Soviet Encyclopedia (1980), Great Russian Encyclopedia (1998), and others. There is a big gap from 1939 to 1956, however, which was earlier shown by the author (Lokoshchenko 2015). Now, in addition to the official data, the author also used special estimations of Moscow population from 1940 to 1947 made by Gavrilova (2000) and Ulianova (2006). As is seen, the reduction of the urban population in Moscow was sharp but comparatively short: in 1947, according to Gavrilova (2000), it already became only a little smaller than before the war. Later, the increase of population took place at nearly the same rate—therefore, this parameter cannot explain the stabilization of the UHI intensity values from the 1950s to 1990s.

Fig. 7.
Fig. 7.

Dynamics of factors that influence the intensity of UHI: (top) dynamics of urban population and its density in Moscow, (middle) dynamics of urban population density in the center of Moscow, and (bottom) dynamics of annual electric power consumption in Moscow and the Moscow region.

Citation: Journal of Applied Meteorology and Climatology 56, 10; 10.1175/JAMC-D-16-0383.1

Indeed, a more important parameter is not the urban population but its density per area unit. The dynamics of the population density in Moscow from 1905 until recent years (open symbols in the top panel of Fig. 7) takes into account both population number and urban area (all statistics were received for the beginning of each year). Note that accurate estimation of the urban area is not always possible: sometimes city margins are strictly determined (e.g., since August 1960) but earlier urban area could be estimated only approximately. The author used the values of the urban area from 1905 to 2011 from the data of official statistics including Central State Archive of Moscow (1963) and others. As one can see, the population density function, unlike the population function, is stepwise: gradual increases are followed by sharp falls. Two of three main falls were connected with the rapid reduction of population during the Civil and Great Patriotic Wars (because of both military mobilization and civil population evacuating from the city), whereas the third reduction in the beginning of 1961 is explained by the sharp increase of the city area which, in accord with a Soviet government decision, was suddenly expanded in August of 1960 up to new ellipsoid margins (see Fig. 2c). At that moment, the territory of Moscow became 2.5 times as large as before (from 356 km2 before August 1960 to 885 km2 later). As a result, the population density of the city decreased by nearly a factor of 2, but just after 1961 it began to increase again; in the beginning of the 2010s, it was already almost 11 000 people per square kilometer. In 2011, the Russian government greatly expanded again the area of Moscow to the southwest, but the new official city margins are unrealistic, and the newly urban area, so-called New Moscow, is a phantom because it still remains a typical rural zone. Therefore, we shall discuss below the real urban area, which since 1984 has had the shape of a turtle, that is, an ellipsoid with several outer protuberances (Figs. 1 and 2d,e).

As one can see, the urban density from 1961 to recent years has increased at nearly the same rate, and therefore it does not explain the changes of the UHI and UDI intensities. We should, however, take into account the fact that the intensities of both islands, according to Eqs. (1)(4), depend mostly on the conditions at the city center rather than those of the whole city because four of five urban weather stations in Moscow (including Balchug, Mikhelson, and University Observatories) are located inside the old urban area from before 1960. A separate analysis of the population density dynamics for the city center is a difficult problem, however, because administrative division of the city changed several times. Before 1992, Moscow was divided into urban districts (7 from 1920 to 1922, 6 from 1922 to 1929, 10 from 1929 to 1936, 23 from 1936 to 1941, 25 from 1941 to 1957, 20 from 1957 to August 1960, 30 from August 1960 to 1969, 32 from 1969 to 1977, and 33 from 1983), whereas in 1992 the administrative network changed and 10 municipal districts, including the central district, were created instead of the former 33 urban districts. The official annual statistics on urban population for some urban districts exist since 1977; for the earlier period, only three estimations are available: the results of population censuses in 1959 and in 1970 (when citizens were asked, among other questions, in which urban district they were living) and, in addition, a special municipal estimation that was made in 1963 (Central State Archive of Moscow 1963). As is seen in the middle panel of Fig. 7, Moscow center was extremely overpopulated at the end of the 1950s. At that time, most Moscow families consisted of two or even three generations and, as a rule, occupied one room in multiroom shared apartments. Thus, urban population density averaged over seven districts in the central part of Moscow (see the left panel in Fig. 8) was almost 32 800 per square kilometer in 1959 (black filled diamonds in the middle panel of Fig. 7), that is, just before city area expansion. The serious housing crisis was soon overcome because of mass construction in the new urban area and mass resettlement of Moscow population from the overpopulated center to the new urban periphery. As a result, in 1970, population density in the center reduced to nearly 20 200 per square kilometer on average for three of seven central Moscow regions and then to 15 800 per square kilometer in 1977 and 11 000 per square kilometer in 1992 on average over five of the same seven districts, taking into account changes of their boundaries in time. The boundaries of five central districts whose data are available since 1977 until 1992 and of the new central district since 1992 (Fig. 8b, right panel) do not coincide with each other; that is why urban population density in 1992 (the only year for which both statistics exist) is a bit different: 11 000 people per square kilometer averaged over seven districts and 10 400 per square kilometer in the new central district (gray filled diamonds in the middle panel of Fig. 7). Then urban population density in the city center continued to decrease up to 1997–98, when it reached a minimum (a little less than 10 100 per square kilometer). Thus, the change of urban population density during the last decades had opposite signs in the whole city (gradual growth) and in the center (rapid fall).

Fig. 8.
Fig. 8.

The central part of Moscow. Thin black lines indicate the boundaries of old urban districts before 1992 and of new administrative districts since 1992 (except one more special enclave district—Zelenograd—that is distant from the others). The shaded gray areas were used in calculations and show the (left) central districts before 1992 and (right) central administrative district since 1992.

Citation: Journal of Applied Meteorology and Climatology 56, 10; 10.1175/JAMC-D-16-0383.1

Since 1999, the population density in the city center began to increase, and in 2015 it was already equal to 11 500 persons per square kilometer. Indeed, at the end of the 1990s, the growth of the city became intensive again because of a mass migration of people to Moscow from other Russian regions and from the former republics of the Soviet Union because living standards and the possibility of finding a job in the capital were much higher than in the rest of the country. As a result, massive or so-called point construction of new high buildings between old houses started in Moscow, including in its center. Indeed, the increase of population density in the city center since 1998 was not so high, but we should take into account two more things. First, the official statistics on population in Moscow (including the city center) were probably underestimated during the recent 25 years because a lot of migrants lived (and are living now) there without any registration. Second, a lot of nonresidential buildings, mostly trade centers, were constructed in Moscow center since the mid-1990s—evidently they strengthen the UHI intensity like dwelling houses. Thus, the extensive growth of the city that took place from 1960 until the mid-1990s was followed by new densification of housing during the recent two decades.

That is not the only reason for the new increase of Moscow UHI and UDI intensities, however. One more important parameter is electric power consumption (PC). Integral annual data of PC in the whole Moscow region, including both the city of Moscow and surrounding rural area, from 1990 to 2015 are plotted in the bottom panel of Fig. 7. As is seen, after 1991 a sharp fall of power consumption took place as a result of economic crisis and the dissolution of the Soviet Union followed by industrial collapse and mass closing of plants. Since 1998, this parameter began to grow again (one more minimum in 2009 was the result of another economic crisis). Thus, PC in the whole region increased from 62–63 TW h in the mid-1990s to nearly 100 TW h in 2014–15. It is evident that a significant part of energy is emitted as heat into the atmosphere, which leads to additional city warming—both directly (e.g., operation of domestic heaters) and indirectly (e.g., the reduction of infrared effective radiation by plumes from smoke chimneys). Note that we only have general statistics for the whole region, including both the city and its suburbs (an approximate fraction for power consumption only in the city limits is about 0.50–0.55 of the total value for the region). We should acknowledge that the city area (1081 km2 in the 2000s) is very small relative to Moscow-region area without the city (~47 000 km2). Hence, the increase of PC evidently leads to more intensive warming of the city than its suburbs because the city occupies only 2% of the region area but spends one-half of the total energy. Thus, energy consumption increase since 1998 seems to be an additional cause of the UHI intensification (and, as a result, the UDI intensification, too) in recent times.

7. Conclusions

  1. The urban dry island is a real physical phenomenon that is closely connected with the urban heat island. As a rule, relative humidity in the city center is lower than in the rural zone outside the city.
  2. The urban heat island intensity in Moscow since the 1880s has increased from 1.0° to 2.0°C. During almost the same time, the absolute value of urban dry island intensity increased (in a negative direction) from −4% to −9%.
  3. The space-averaged urban island intensity seems to be a more reliable and trustworthy parameter than simple traditional estimation of the maximum intensity using only one central urban station. In Moscow, this additional parameter for the UHI increased from 0.7° to 1.0°C during the last 60 years; for the UDI, it is now equal to −3%.
  4. The dynamics of Moscow UHI and UDI intensities during the last 128 years demonstrate an increase in the first half of the twentieth century followed by its quasi stabilization for the UHI (and even a temporary reduction for the UDI) in the second half of the twentieth century because of the extensive growth of the city at that time and then new amplification of both islands during the last two decades. The probable reasons of up-to-date UHI and UDI amplifying are the growth of urban population density, especially in the city center, and, in addition, a rapid increase of power consumption since the end of the 1990s.
  5. Relative humidity F in Moscow decreased significantly during the last 146 years—on average from 81% in the 1870s to 72% in recent years. At the same time, water vapor pressure remains almost the same and does not demonstrate any significant changes in time.
  6. The spatial field of relative humidity is comparatively smoothed; the correlation coefficients between monthly averaged F values at different stations at distances up to 100 km range from 0.92 to 0.96.

Acknowledgments

The author is very grateful to N. A. Tereshonok and N. S. Nikolaev from the central administration of the Russian Hydrometeorological Service, T. M. Rosinskaya—the head of Mikhelson Observatory, I. S. Shcherbakova from Moscow Statistical Service (Mosgorstat), and I. V. Gorodkova and her colleagues from System Operator of Russian Integrated/Unified Power System (IPS/UPS) for the data on measurements that they provided. This work was supported by the Russian Scientific Foundation (Project 16-17-10275).

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