Population and GDP Exposure to Extreme Precipitation Events on Loess Plateau under the 1.5 °C Global Warming Level

Abstract

To mitigate the adverse effects of climate warming, the Paris Agreement proposed the goal to reduce global warming up to an increase of 1.5 °C above the preindustrial level. Study of the population and GDP exposure to precipitation extreme events under the 1.5 °C warming target is fundamental for disaster risk mitigation and adaptation on the Loess Plateau. This study projected the population and GDP exposure to extreme precipitation events under the 1.5 °C global warming level on the Loess Plateau using daily precipitation data from CMIP6 outputs and population and GDP data under a Shared Socioeconomic Pathway 1(SSP1) 2.6 scenario. The population and GDP exposure were evaluated by combing the frequency and the areal coverage of the extreme precipitation events. Results show that population and GDP exposure to extreme precipitation events on the Loess Plateau will increase under the 1.5 °C global warming level. The population exposure was projected from 1.32 × 10⁶ to 2.68 × 10⁶ person-year. The population exposure of eastern and southern Loess Plateau is significantly higher than that of the northern region. The annual exposure of GDP ranges from USD 2.9 to 12.3 billion, and the regions with the highest GDP exposure are Zhengzhou, Xi’an, Taiyuan, and Lanzhou. Our results reveal that limiting the increase of global mean temperature to 1.5 °C warming level is of great significance to reduce the social and economic exposure to extreme precipitation events on the Loess Plateau.

1. Introduction

Increase in the greenhouse gas emissions and human activities have led to an irreversible global warming [1,2,3]. The frequency of extreme climate events including extreme precipitation events, droughts, and heat waves has increased, in addition to an increase in the extent and intensity due to global warming. In places located at mid-to-high latitudes, extreme precipitation increases significantly [4]. Since 1950, the number of extreme precipitation events has increased in more regions than decreased, but the trends are strongly regional and subregional [5]. Previous studies have shown that anthropogenic climate forcing has led to an increase in the frequency and intensity of extreme precipitation worldwide, with that in the temperate regions increasing consistently, along with large inter-annual variation in the tropical regions. Observations and simulations show that greenhouse gas emissions have intensified extreme precipitation over two-thirds of the land areas in the Northern Hemisphere [6]. On a regional scale, regions with increased total precipitation are highly likely to witness a greater proportional increase in extreme precipitation events. Additionally, some areas having low average precipitation may witness an increase in extreme precipitation events. Studies conducted in the United States, Canada, Japan, the United Kingdom, Norway, South Africa, Brazil, and Russia have confirmed this conclusion [7,8,9,10,11,12]. The results of different climate models and different scenarios pertaining to projection of extreme precipitation in China indicate that the intensity and frequency of extreme precipitation in China is likely to increase significantly in the near future in most areas in China, especially due to global warming [13]. In order to reduce the adverse effects of global warming, study of the characteristics of extreme weather events and their socio-economic impacts is among the pertinent issues of concern that have gained attention in the field of climate change and disaster prevention.

Extreme precipitation events caused by global warming pose challenges to global security and development. The severity of the impact of extreme precipitation events depends not only on the actual degree of extremity, but also on the degree of exposure and vulnerability. Exposure is an important aspect of disaster risk management and assessment research. Exposure refers to the adverse effects of extreme events on population and gross domestic product. Many studies have investigated the socioeconomic exposure to extreme precipitation events. For instance, Brian Ayugi et al. [14] projected an intensification of precipitation extremes over Burundi, Rwanda, and some parts of Uganda. The Poyang Lake Basin is experiencing extreme precipitation with increasing population and GDP exposure [15]. With an additional 0.5 °C warming, the population and GDP exposure are likely to increase in most parts of the world [16]. Under a 2.0 °C global warming scenario, population exposure to drought was projected at 4.94 ± 0.36 × 10⁹ person-months, GDP exposure would increase significantly to 2.08 ± 0.15 × 10¹⁴ PPP USD-months [17]. At 1.5 °C, 2.0 °C, and 3.0 °C levels of global warming, an increase in the exposure by 4.4%, 8.8%, and 17.6%, respectively, is expected relative to the (1986–2005) period [18].

In order to reduce the negative impact of global warming, the Paris Agreement proposes to limit the global mean temperature warming below 2.0 °C, and makes efforts to limit the increase to 1.5 °C above preindustrial levels [19]. There is an urgent need to study the extreme precipitation events, their impact on the population and the GDP for a 1.5 °C global warming level. Several studies pertaining to the 1.5 °C warming scenario have achieved many results. At the 1.5 °C warming target, population exposure to drought is likely to research 12.89 million in China [20]. Similar findings have been reported by other researchers [21]. Some studies have considered socioeconomic exposure to extreme precipitation events under 1.5 °C and 2.0 °C warming scenarios [22,23,24]. However, the exposure of the population to extreme precipitation and its impact on the GDP in the Loess Plateau in China needs to be studied in detail, as it has received less attention.

Located in the middle reaches of the Yellow River, the Loess Plateau region is sensitive to climate change, and is one of the regions having the most fragile ecological environment and facing the most serious soil erosion in China. Extreme precipitation events have a negative impact on the social economy of the Loess Plateau to a certain extent. To the best of my knowledge, currently, there are few studies on extreme climate events and their socioeconomic impact on the Loess Plateau. Therefore, with respect to global warming, it is highly important to study the socioeconomic impact of extreme precipitation events on the Loess Plateau (i.e., on livelihood, species, ecosystem services, economic, and social).

In this study, population and GDP exposure to extreme precipitation events under the 1.5 °C global warming scenario was quantified. First, R95p was employed as an extreme precipitation index. Second, population and GDP data from shared socioeconomic pathways (SSPs) were used to analyze spatiotemporal variation in the population and GDP exposures as a result of extreme precipitation events in the Loess Plateau. Thus, we aim to address the following questions in this study: (a) what are the spatiotemporal characteristics of extreme precipitation events under the 1.5 °C global warming target on the Loess Plateau? (b) What are the impacts of extreme precipitation events on the population and GDP for the 1.5 °C global warming target on the Loess Plateau?

2. Materials and Methods

2.1. Study Area

The Loess Plateau (100°54′–114°33′ E, 33°43′–41°16′ N) is located in central and western China, covering an area of about 640,000 km² (Figure 1). The Loess Plateau is a semi-arid temperate continental monsoon climate, with a cold, dry, and windy winter and spring, and a hot and rainy summer and autumn. The annual average temperature ranges between 4.3 to 14.3 °C [25], and the mean annual temperature varies greatly from year to year, and the temperature difference between the east and the west is significant. The mean annual precipitation ranges between 200 mm in the northwest to 750 mm in the southeast, being heterogeneous with regard to space, and about 60–70% of the total annual precipitation occurs in the rainy season during June to September [26]. Due to low vegetation coverage and serious water and soil loss, the Loess Plateau is one of the areas that faces extreme water and soil loss and has a very poor ecological environment in China and even in the world.

2.2. Data

According to previous studies [27,28,29], under the SSP1-2.6 scenario, the global mean temperature is projected to increase by 1.5 °C in 2020–2039 relative to the preindustrial level. This study used 12 global climate models from CMIP6 (

Table 1. Information of 12 global climate models in CMIP6.

Model Number	Model Name	Modeling Center and Country	Resolution (Lat × Lon)
1	BCC-CSM2-MR	Beijing Climate Center, China Meteorological Administration (China)	1.125° × 1.125°
2	BCC-ESM1	Beijing Climate Center, China Meteorological Administration (China)	2.8° × 2.8°
3	CNRM-CM6-1	National Centre for Meteorological Research-European Centre for Advanced Research and Training in Scientific Computing (France)	1.4° × 1.4°
4	CNRM-ESM2-1	National Centre for Meteorological Research-European Centre for Advanced Research and Training in Scientific Computing (France)	1.4° × 1.4°
5	EC-Earth3-Veg	EC-EARTH consortium	0.7° × 0.7°
6	GFDL-CM4	NOAA Geophysical Fluid Dynamics Laboratory (USA)	1° × 1.25°
7	GFDL-ESM4	NOAA Geophysical Fluid Dynamics Laboratory (USA)	1° × 1.25°
8	IPSL-CM6A-LR	PierrcSimon Laplace Institute (France)	1.26° × 2.5°
9	MRI-ESM2-0	Meteorological Research Institute (Japan)	1.125° × 1.125°
10	NESM3	Nanjing University of Information Science and Technology (China)	1.875° × 1.875°
11	SAM0-UNICON	Seoul National University (Republic of Korea)	0.94° × 1.25°
12	UKESML-0-LL	Met Office Hadley Centre (UK)	1.25° × 1.875°

). According to the results of ZHU et al. [30], these 12 CMIP6 climate models can better simulate the characteristics of extreme precipitation in China. Since these 12 GCMs have different spatial resolutions, they were first interpolated into 0.5° × 0.5° grids on latitude and longitude by using the bilinear methods for further analysis.

The population and GDP data are collected to study the socioeconomic exposure to extreme precipitation events. Yearly population and GDP data were from the National Institute for Environmental Studies (NIES) in Japan [31]. Population and GDP simulations under the SSP1 scenario were used in this study.

2.3. Methods

2.3.1. Define of Extreme Precipitation

The method of using wet day percentile to determine the extreme precipitation threshold of each grid or station has been adopted in many studies [32,33,34]. The threshold for defining extreme precipitation events is the R95p, which has been recommended by the World Meteorological Organization (WMO), is the 95th percentile of daily precipitation at each grid. In this study, the wet day threshold is defined as the daily precipitation that exceeds 1 mm. The wet day precipitation series (daily precipitation > 1 mm) of each grid on the Loess Plateau was arranged in ascending order: a1, a2, a3, …, am, …, an, and the 95th percentile of wet day precipitation was used as the threshold of extreme precipitation. The probability p was calculated as follows:

$$p=\frac{m-0.31}{n+0.38}$$

(1)

where m is the serial number of am, n is the number of precipitation series. If the number of samples is 40, the 95th percentile of the sequence is the linear interpolation of the 38th value a38 (p = 93.3%) and 39th value a39 (p = 95.8%) after the arrangement in ascending order.

2.3.2. Frequency

The frequency of extreme precipitation events was calculated as follows:

$$\mathrm{f}=\frac{n}{N}\times 100\%$$

(2)

where n is the number of months that extreme precipitation events occurred in each grid, and N is the total number of months.

2.3.3. Areal Coverage

An extreme precipitation event is defined as a region that occurs simultaneously on an adjacent grid and exceeds the extreme precipitation threshold. The total areal coverage of the extreme precipitation event was defined as the affected area of the extreme precipitation event. That is, the adjacent grids that exceeded the daily precipitation threshold of R95p were identified, and the areas of all grids where extreme precipitation events occurred were added up.

2.3.4. Population and GDP Exposure to Extreme Precipitation Events

The frequency of the extreme precipitation events was used to calculate the population and GDP exposure, which was calculated as follows:

$$E_{pop}=\frac{{{\displaystyle \sum }}_{i=1}^m{p}_i}{m},p=s\times k$$

(3)

$$E_{GDP}=\frac{{{\displaystyle \sum }}_{i=1}^m{q}_i}{m},q=s\times n$$

(4)

where m is the number of annual extreme precipitation events, p is the number of people exposed to each extreme precipitation event, q is the GDP exposed to each extreme precipitation event, k is the population in each grid, n is the GDP in each grid, and s is the areal coverage of each extreme precipitation event.

3. Results

3.1. Spatial and Temporal Patterns of Extreme Precipitation Events

The frequency and areal coverage of extreme precipitation events were calculated for the 1.5 °C global warming level to evaluate the spatial and temporal variation in the frequency and areal coverage (Figure 2, Figure 3 and Figure 4). The multi-model reveals that the extreme precipitation events are projected to happen 5.8 to 11.2 times. They are likely to be more frequent in 2030 (11.2) and the least frequent in 2024 (5.8). The (2020–2029) decade showed an increasing trend and reached its maximum value in 2030, after 2030, fluctuations could be observed. In general, the frequency of extreme precipitation events is likely to increase significantly at a rate of 0.9 times per decade (significant at the 95% level).

Figure 3 illustrates the changes of the impacted area under the 1.5 global warming level. The annual areal coverage of extreme precipitation events on the Loess Plateau are projected from 14.2 × 10³ km² to 28.1 × 10³ km². The figure shows that in 2030, the largest area would be impacted (i.e., 28.1 × 10³ km²), and the lowest area in 2024 (i.e., 14.2 × 10³ km²).

Spatially, the annual frequency of extreme precipitation events for the 1.5 °C global warming level is shown in Figure 4. In the period of 2020–2039, extreme precipitation events are likely to occur most frequently in the southwestern Loess Plateau, (i.e., the eastern parts of Qinghai and Gansu provinces), and the annual frequency is about 12–15 times. Those areas with a lower frequency were mainly concentrated in northern Loess Plateau, (i.e., Inner Mongolia Autonomous Region), the annual frequency is about 3–6 times.

3.2. Population Exposure to Extreme Precipitation Events

The annual population exposure to extreme precipitation events under the 1.5 °C global warming level was projected from 1.32 × 10⁶ to 2.68 × 10⁶ person-year. Although the frequency of extreme precipitation events in the Loess Plateau was likely to increase under the 1.5 °C global warming level, the population of the Loess Plateau will not increase indefinitely. Figure 5 illustrates the exposure of the population to extreme precipitation events on Loess Plateau that is likely to reach its peak around 2030 and, after that, it is likely to decline gradually.

Figure 6 shows that the spatial distribution of average annual population exposure to extreme precipitation events on the Loess Plateau with reference to the 1.5 °C global warming scenario (Figure 6), the population exposure of eastern and southern regions of the Loess Plateau is significantly higher than that of the northern region, because the northern region of the Loess Plateau is sparsely populated. The cities having high population exposure are Lanzhou, Xining, and Xi’an, respectively, the areas being provincial capitals having a large population. The largest population that is exposed to extreme precipitation is that of Xi’an, which exceeded 10 million in 2020, and hence has the highest exposure as compared to any city on the Loess Plateau. Areas having low population exposure lie in the northern part of the Loess Plateau, in which the population density is low and the frequency of extreme precipitation events is also low.

3.3. GDP Exposure to Extreme Precipitation Events

Like the population, the GDP also shows a similar upward trend (Figure 7) with an increase of about USD 0.8 billion per decade. For the 1.5 °C global warming level, the annual GDP exposure ranges from USD 2.9 to 12.3 billion on the Loess Plateau. From 2020 to 2030, GDP exposure is likely to increase and attain its peak in 2030 (i.e., about USD 12.3 billion). GDP exposure is likely to show a decreasing trend from 2030 to 2039, and may reach the lowest value in 2039 (i.e., about USD 2.9 billion).

According to the spatial distribution of the GDP exposure of extreme precipitation events on the Loess Plateau (Figure 8), it is expected to be much higher in cities having high GDP, which is consistent with the spatial distribution of population exposure in Zhengzhou, Xi’an, Taiyuan, and Lanzhou. The average annual GDP exposure of the above areas exceeds USD 100 billion. The GDP exposure of other regions of the Loess Plateau range from 1 × 10⁷ to 10 × 10⁷ billion USD per year.

4. Discussion

Many studies have explored the impact of extreme climate events on the population and GDP with respect to the global warming scenario. The significant impact of extreme climate events on human life and security under the global warming scenario has become a hot issue in the world, attracting attention of many countries. Since frequent occurrence of extreme climate events pose a great threat to human survival and development as well as social economics, how to deal with, avoid and solve the disaster risk caused by extreme climate events has become an important part of disaster risk management in many countries. In this study, the impact of extreme precipitation events on the population and GDP of the Loess Plateau were analyzed for 1.5 °C of global warming.

Our result indicates that the frequency of the extreme precipitation events on the Loess Plateau will increase significantly 0.9 times per decade (significant at the 95% level), and it has greater spatial heterogeneity. A combination of topography, climate, and other factors may contribute to the spatial heterogeneity of extreme precipitation events on the Loess Plateau. The diversity of topography and climate types may be the main reason for the spatial heterogeneity of extreme precipitation events on the Loess Plateau. Topographically, the Loess Plateau Region ranges from northwest to southeast, comprising hills, plateaus, plains, deserts, mountains and other geomorphic types. The complex terrain has a significant impact on the climate of the whole region. The Loess Plateau region mainly has a continental monsoon climate, but some regions in the northwest have temperate continental and alpine climate. In summer and autumn, it is affected by the Indian Ocean low and the Western Pacific subtropical high, hence, it is hot and rainy.

In recent years, studies on exposure to natural disasters have achieved many results [35,36,37,38]. Based on the intensity-area-duration (IAD) method, many scholars have applied IAD method to analyze extreme precipitation events and their spatial distribution pattern at a regional scale. For example, based on historical flood disaster data and social economic data in Jiangsu Province from 1984 to 2011, Wang et al. [38] analyzed the characteristics of exposure and vulnerability to flood disaster by calculating the exposure of the population, GDP, and farmland. Inspired by this, we will use IAD method to analyze the relative intensity, affected area, and duration of extreme precipitation events on the Loess Plateau in our next research work. In addition, in order to verify the robustness of the projection results, it is necessary to adopt higher resolution regional climate models for analysis in our future research.

The projected population and the GDP impacted by extreme precipitation events in this study may not be an actual overview, as it does not take into account the effect of national polices and human activities on extreme precipitation. Additionally, in future studies, we intend to analyze the population and GDP that is likely to be impacted by extreme precipitation events on the Loess Plateau under 1.5 °C, 2 °C, and 3 °C global warming scenarios, and consider the impact of national polices, education level, age structure, and other factors.

5. Conclusions

This study analyzes the population and GDP of the Loess plateau affected by extreme precipitation events, based on 12 CMIP6 models and the projected population and GDP for the 1.5 °C global warming level. In addition, we also analyzed the temporal and spatial distribution characteristics of extreme precipitation events, including their frequency of occurrence and the affected area. The major findings of this study are as follows:

(1) The frequency and areal coverage of extreme precipitation events were likely to occur more frequently on the Loess Plateau under the 1.5 °C global warming level, especially in the southwestern region of the Loess Plateau (i.e., Xining, Lanzhou, and Xi’an), that have the highest frequency and areal coverage of extreme precipitation events. The annual frequency of extreme precipitation events on the Loess Plateau ranged from 5.8 to 11.2 times and is likely to increase significantly 0.9 times per decade.

(2) The exposure of the population to the extreme precipitation events annually at the 1.5 °C global warming level ranges from 1.32 × 10⁶ to 2.68 × 10⁶ persons per year. The highest population of the Loess Plateau that is exposed to extreme precipitation events is located in the southern and eastern Loess Plateau, such as Xining, Lanzhou, and Xi’an, which are the cities having large population.

(3) The impact of extreme precipitation on the GDP is projected to increase for the 1.5 global warming level. The annual GDP exposure on the Loess Plateau ranges from USD 2.9 to 12.3 billion, with an increase of about USD 0.8 billion per decade. The cities that experience high GDP exposure on the Loess Plateau are Zhengzhou, Xi’an, Taiyuan, and Lanzhou.

Overall, the frequency of extreme precipitation events and the area impacted, in addition to the exposure of the population and GDP on the Loess Plateau, is likely to increase at the 1.5 °C global warming level. It is necessary to control global warming up to the 1.5 °C level, for mitigating the adverse effects of climate change on the Loess Plateau, especially the socio-economic impact of the extreme precipitation events.