# Geophysical Research Letters®

## RESEARCH LETTER

10.1029/2024GL108350

**Key Points:**

* Both surface-based temperature inversion (SBTI) and elevated temperature inversion (ETI) show concurrence with humidity inversion (HI)

* Theories of water vapor condensation and turbulent diffusion blockage may not be sufficient for the concurrence of SBTI and HI

* ETI blocks the upward turbulent diffusion of water vapor, contributing to the formation of HI

**Supporting Information:**

Supporting Information may be found in the online version of this article.

**Correspondence to:**

Y. Li and C. Zhang,
ghlyy@mail.iap.ac.cn;
zhangnanshui@126.com

**Citation:**

Zhou, X., Zhang, C., Li, Y., Sun, J., Chen, Z., & Li, L. (2024). Concurrence of temperature and humidity inversions in winter in Qingdao, China. *Geophysical Research Letters*, *51*, e2024GL108350.
https://doi.org/10.1029/2024GL108350

Received 18 JAN 2024
Accepted 21 MAR 2024

© 2024. The Authors.
This is an open access article under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non-commercial and no modifications or adaptations are made.

<figure><img src="image_1.png" /></figure>

## Concurrence of Temperature and Humidity Inversions in Winter in Qingdao, China

Xingxu Zhou¹ ID, Chao Zhang¹ ID, Yunying Li¹ ID, Jing Sun¹,², Zitong Chen¹ ID, and Laurent Li³ ID

¹College of Meteorology and Oceanography, National University of Defense Technology, Changsha, China, ²Hubei Key Laboratory for Heavy Rain Monitoring and Warning Research, Institute of Heavy Rain, CMA, Wuhan, China, ³Laboratoire de Météorologie Dynamique, CNRS, Sorbonne Université, Paris, France

**Abstract** Concurrence of temperature inversion (TI) and humidity inversion (HI) is a particular configuration of the atmospheric boundary layer with important implications for early warning of fog formation. With a microwave radiometer device deployed in a 2-month winter campaign at a coastal island in Qingdao, China, we here examine the relationship between TI and HI, and investigate the underneath mechanisms. Cases of temperature inversion are further divided into surface-based temperature inversion (SBTI) and elevated temperature inversion (ETI), which show different relationship with HI. SBTI typically occurs at night with its strength significantly and positively correlated with HI. ETI also shows a high degree of temporal overlap with HI, but its strength has no obvious relationship with HI. The main explanation for this phenomenon is that ETI may block the vertical diffusion of water vapor, resulting in the formation of HI.

**Plain Language Summary** Temperature inversion (TI) and humidity inversion (HI) often occur simultaneously. Knowledge of their concurrence is, however, still quite limited, due to the lack of continuous observations. Using a 2-month winter observation data set, obtained with a microwave radiometer device deployed in Qingdao, China, a coastal city of the Yellow Sea, we carefully examined the correlation between TI and HI. TI is furthermore regrouped into surface-based temperature inversion (SBTI) and elevated temperature inversion (ETI). Although SBTI and ETI both occur frequently, accompanied with HI, the underneath physical mechanism seems different. For SBTI, the bottom of HI absorbs the radiation emitted from the ground, increases the temperature difference between the land and atmosphere, and finally enhances SBTI. However, ETI plays the role of blocking the water vapor turbulent diffusion and contributes to the development of HI.

## 1. Introduction

Temperature inversion (TI) occurs when air temperature increases with height in the near-surface atmosphere. Similarly, humidity inversion (HI) happens when water vapor increases with height. TI and HI are two important near-surface atmospheric conditions in forecasting local weather, especially in winter. Previous studies have shown that TI could suppress turbulence and convection activities in the planetary boundary layer, which further affects aerosols dispersion and wind vertical structure (Bai et al., 2019, 2022; Das et al., 2021; Esteban & Chen, 2008; Guo et al., 2020; Johnson et al., 1996; Li & Gu, 2006; Palarz et al., 2019). For HI, it could exert significant impact on atmospheric long-wave radiation, and on the formation of cloud, fog and haze (Brunke et al., 2015; Naakka et al., 2018; Nidzgorska-Lencewicz & Czarnecka, 2015). When TI and HI occur simultaneously, the local weather usually becomes stable and remains stable for a few days.

Thus far, several studies have suggested that TI and HI are related to each other (Devasthale et al., 2011; Naakka et al., 2018; Nygård et al., 2013, 2014; Palarz & Celiński-Mysław, 2020). For example, Wypych and Bochenek (2018) showed that approximately 70% of HI and TI events in Europe occurred simultaneously. Furthermore, Nygård et al. (2014) found that the strength, base height and depth of HI and TI events in radiosonde profiles were highly correlated. These results imply that HI and TI could, to some extent, interact with each other. But the precise mechanism of interaction is still unclear (Derbyshire, 2019; Naakka et al., 2018; Weston et al., 2021).

TI events can be generally categorized into surface-based temperature inversion (SBTI) and elevated temperature inversion (ETI) depending on their base height. Shukla et al. (2022) found that most fog events (71%) occurred during ETI, while it was uncommon during SBTI. Given that the fog is a special HI, we may argue that the mechanism, governing the concurrence of different types of TI with HI, is different.
<figure><img src="image_2.png" /><figcaption>**Figure 1.** (a) Geographic situation of the microwave radiometer deployed in Qingdao, China. (b) Average absolute error of temperature at different altitudes between the microwave radiometer and the radiosonde launched nearby.</figcaption></figure>

In the past, the formation of TI and HI has been largely studied, but generally as separate events. Their relationship is, however, not well understood. Two mechanisms have been proposed to explain any impact of TI on HI, either through the blocking effect of water vapor vertical transport, or through moisture condensation. Conditions of turbulent mixing, affectable by TI, could also contribute to the development of HI (Naakka et al., 2018; Nygård et al., 2013). According to Devasthale et al. (2011), TI creates a barrier that blocks the moisture transport near the surface. This barrier affects the formation of HI by reducing the water vapor supply. The second mechanism involves the formation of HI due to water vapor condensation. Naakka et al. (2018) suggested that the concurrence of HI and TI under saturated conditions could be due to water vapor condensation. A deficit radiation budget at the surface is one of the main factors leading to TI, which can, in its turn, lead to water condensation and then formation of HI (Naakka et al., 2018; Palarz et al., 2018; Stryhal et al., 2017).

However, the lack of good-quality and high-resolution observations is a major obstacle for the verification and quantification of these processes. For example, Naakka et al. (2018) attempted to use reanalyzed data and radio soundings to investigate the issue. But it was hard for such data to capture the temporal sequence of TI and HI occurrence. In recent years, the availability of new detection technology provides us opportunities to investigate the concurrence of TI and HI. They can be detected by microwave radiometers that are capable of working continuously with minute-scale temporal resolution. Besides, the microwave instrument is also less affected by poor weather conditions (Osibanjo et al., 2022; Wang et al., 2023; Ware et al., 2013). In this paper, a microwave radiometer data set from Qingdao, China, is used to examine the features and concurrence of TI and HI. We also analyze possible mechanisms that controls the interaction of TI and HI.

## 2. Data and Methods

### 2.1. Microwave Radiometer Observation

Temperature and humidity were retrieved from a microwave radiometer deployed in Qingdao, Shandong Province (120.4°E, 36.1°N, north of the Yellow Sea, Figure 1a) from 30 December 2021 to 1 March 2022. The campaign corresponds to two typical winter months in the region. The instrument, in its commercial version QFW-6000, uses microwaves in the K-band (22–32 GHz) and V-band (51–59 GHz) to operate.

Compared with radiosonde data that were already widely used in studies of TI and HI (Chang et al., 2021; Devasthale et al., 2011; Kahl, 1990), microwave radiometer measures have higher temporal and spatial resolutions. Temperature and humidity are retrieved at an interval of 2 min, with the vertical resolution of 50 m below 1,000 m, 100 m between 1,000 and 2,000 m, and 250 m above 2,000 m. During the observation campaign, though vertical profiles effectively reached the height of 10,000 m, this study only uses data in the lower troposphere below 2,000 m where there is an effective higher spatial resolution. A total of 103 radiosonde data from the nearby Qingdao weather station are used to validate the microwave radiometer as the reliability of radiosonde is well known (Guo et al., 2016, 2019). The average absolute error at different altitudes is shown in Figure 1b. The mean
absolute error of temperature from microwave and radiosonde is 0.50°C, the standard deviation is 2.97°C, and the correlation of the two data sets is 0.92 in the lower troposphere below 2,000 m.

Although there is some discrepancy between the two profiles, the difference is small and tolerable. The deviation can be attributed to the spatial localization between the two measurement sites, with the radiosonde site located approximately 7 km southwest of the microwave radiometer site. The temperature and humidity profiles obtained by the radiosonde may not completely reflect the atmospheric conditions prevailing over the microwave radiometer site.

## 2.2. Analysis Methods

TI and HI are assessed by three parameters as in Zhang et al. (2011) and Gilson et al. (2018). They are the depth, the difference in height between the top and bottom of the inversion layer with unit of m; the strength, the difference in temperature or absolute humidity (vapor density) between the top and bottom of the inversion layer with unit of °C or g·m⁻³; and the intensity, the ratio of strength over depth with unit of °C·m⁻¹ or g·m⁻⁴.

An inversion is detected when the temperature or humidity of the upper layer is higher than that of the lower layer. However, due to instrumental noises and atmospheric perturbations, weak and short-lived inversions can frequently appear. Therefore, only these events of TI and HI that met certain criteria are analyzed following Guo et al. (2020) and Bai et al. (2022). The selection retains inversion events with temperature differences above 0.5°C or humidity differences above 0.2 g·m⁻³ and event duration exceeding 10 min. In total, 19,084 TIs and 18,998 HIs are identified during the 60 days of the campaign. Our observation was in the local winter with favorable conditions for TI and HI occurrence (Naakka et al., 2018; Nodzu et al., 2006; Palarz & Celiński-Mysław, 2020).

TI profiles are regrouped into SBTI and ETI in our study. Cases with base height of 50 m are classified as SBTI, and those above 50 m as ETI. When SBTI and ETI occur simultaneously or when there are multiple layers of inversion in the atmosphere, it is considered to be a mixed temperature inversion (SBTI&ETI). It is to be noted that for both SBTI and ETI, an inversion event is accounted when it continuously lasts more than 10 min, with its base height variation smaller than 50 m. Only low tropospheric inversions with heights below 2,000 m are analyzed, to take advantage of the best performance offered by the microwave radiometer.

# 3. Results

## 3.1. Basic Facts on TI and HI

Figure 2a displays, for each hour of the day, the frequency of occurrence for different TI types. The configuration of mixed inversion (SBTI and ETI) is rare, occurring with a frequency of less than 0.01% and thus is not separately analyzed. In total, 12,076 cases of SBTI and 7,008 cases of ETI are found. They are regrouped into 65 contiguous events of SBTI and 117 contiguous events of ETI, respectively. Events are distanced from each other by an interval of 1 hr, at least. These SBTI and ETI events have significant differences in their properties such as duration, maximum strength, maximum intensity, and depth (Figures S2 and S3 in Supporting Information S1).

Previous studies have shown that TI is concurrent with HI in approximately 50% of the events. However, the frequency of HI varies widely across regions, with Eastern Europe having more than 90% and Western Europe having less than 60% (Wypych & Bochenek, 2018). According to Brunke et al. (2015), HI is much less frequent and intense outside the polar regions. This is confirmed in Figure 2, which shows that TI and HI occurrence frequency is only about 20% in this region. Different from studies based on radiosonde data (Gettelman et al., 2006; Naakka et al., 2018; Nygård et al., 2014), a significant diurnal variation in SBTI and ETI was observed. SBTI was predominant during nighttime while ETI prevailed during daytime.

In addition, HI has a higher occurrence probability and strength during the daytime compared to the nighttime. This result is similar to the diurnal variation in ETI (Figure 2b), which potentially indicates that ETI has a close relationship with HI.

Let us now examine the association (or non-association) of HI with TI. Under conditions of HI occurrence (Figure 2c), TI coexists in about 56% of the time, confirming the findings of Nygård et al. (2013, 2014) in the polar region. Without HI (Figure 2d), all TI types occur less frequently, and ETI is the mostly reduced, to only 1.0%, while SBTI is reduced to 7.5%.
<figure><img src="image_3.png" /><figcaption>**Figure 2.** (a) Diurnal variation (each hour of the day in abscissa) of temperature inversion (TI) occurrence frequency and its repartition into two sub-groups: surface-based temperature inversion (SBTI) and elevated temperature inversion (ETI). (b) Diurnal variation in the occurrence frequency (gray bars, left axe) and strength (red curve with error bars, right axe) of the humidity inversion (HI). (c) Repartition of different categories of temperature inversion under conditions of humidity inversion (HI): SBTI, ETI and no temperature inversion (No-TI). (d) Same as in (c), but for conditions of no humidity inversion (No HI).</figcaption></figure>

Both SBTI and ETI frequently occur in parallel with HI, and they become rare without HI. However, the occurrence of ETI is more synchronized with HI, while a comparable number of SBTI cases are found without HI (Figure 2d). This potentially indicates a particular relationship of SBTI and ETI with HI.

The formation mechanisms and vertical extent of TI vary depending on their type (Ji et al., 2018; Palarz et al., 2018). SBTI is usually caused by a deficit of surface energy budget, while ETI may develop from the sinking of air masses under high-pressure conditions, the advection of warmer air masses, or as residual of SBTI (Palarz et al., 2019). The different development conditions of SBTI and ETI also determine their different relationships with HI.

Moreover, 44.3% of the HI lack a TI associated with them (Figure 2c). The formation of these HIs may be attributed to the advection of moist air masses over dry air, which results in an inversion of the humidity distribution, with the layer of higher humidity moving above the layer of lower humidity (Naakka et al., 2018; Zhang et al., 2022). The high daytime occurrence and strength of HI (Figure 2b) may be due to the strong daytime sea breeze in winter, which produces more humidity advection and thus more HI.
<figure><img src="image_4.png" /><figcaption>**Figure 3.** Scatter plot and the linear regression between SBTI (ordinate: strength and intensity) and HI (abscissa: strength and intensity).</figcaption></figure>

## 3.2. SBTI Reinforced With HI

The correlation between HI and TI parameters varies across regions. Nygård et al. (2013) reported a positive correlation between HI and TI depth, and a negative correlation between HI base height and TI intensity over the Antarctic. However, Nygård et al. (2014) found a different correlation in the Arctic, where HI and TI base height, depth and intensity were positively correlated, and HI base height and TI intensity were negatively correlated.

Let us now examine the statistical relationship between SBTI and HI in Qingdao, with scatter plots shown in Figure 3 and Figure S4 in Supporting Information S1. For both strength and intensity, SBTI and HI are strongly correlated (with 0.52 and 0.68 as their correlation coefficients). This is consistent with what shown in Figure 2 indicating that SBTI and HI often appear simultaneously. The results for the correlation of SBTI with HI generally agree with what reported in Palarz and Celiński-Mysław (2020). In contrast to SBTI, ETI shows poor correlation with HI (Figure S5 in Supporting Information S1), indicating that the two types of TI have different types of relationship with HI.

Box plots indicating the extreme values are plotted to analyze the statistical relationship between HI and TI characteristics (Figure S6 in Supporting Information S1) since the correlation could be distorted in the presence of extreme cases. The results show no significant correlation between the intensity of ETI and HI, while the extreme values of ETI are more pronounced than that of SBTI. This could suggest that the mechanism of ETI with HI is not reflected in the strength or intensity. In contrast, both the strength and intensity of SBTI have a positive correlation with the strength of HI.

Devasthale et al. (2011) and Naakka et al. (2018) proposed two different mechanisms to explain the concurrence of HI and TI. Devasthale et al. (2011) argued that TI acts as a barrier that prevents water vapor transport near the surface, which affects the formation of HI. Naakka et al. (2018), on the other hand, suggested that HI and TI can form simultaneously under saturated conditions due to water vapor condensation.

To further reveal the relationship between TI and HI, we examine the presence of HI at different development stages of TI, both before its onset and after its termination, as shown in Figure S7 in Supporting Information S1. The pre-onset phase is defined as the 3-hr period preceding the onset of TI and the post-termination phase as the 3-hr period following the termination of TI. For the pre-onset of SBTI, HI's occurrence frequency is about 48%. It decreases to 29% when SBTI decays. It is to be noted that HI is absent in many cases, regardless of the stages of SBTI. This indicates that HI may not be the direct cause of SBTI, and that water vapor condensation and turbulent diffusion blockage may not predate SBTI. These results may not support the concurrence mechanisms of water vapor condensation and turbulent diffusion blockage (Devasthale et al., 2011; Naakka et al., 2018).
<figure><img src="image_5.png" /><figcaption>**Figure 4.** Scatter plot and the linear regression between the intensity of TI (abscissa) and the difference of base height between the two inversion layers (TI-minus-HI). Negative values indicate that TI is below HI and positive values indicate the opposite. SBTI in red and ETI in blue. Density functions are plotted on the right side and the top side, respectively.</figcaption></figure>

HI occurred in approximately 32% of the cases for the pre-onset of ETI. The occurrence frequency increases to 62% while ETI decays. Moreover, ETI is highly concurrent with HI (Figure 2). This suggests that the mechanisms proposed by Naakka et al. (2018) and Devasthale et al. (2011), which involved water vapor condensation and transport, were more likely to operate after the ETI onset.

We have investigated the correlation between SBTI and HI, and found that they are positively related. However, past theories of water vapor condensation and turbulent diffusion blockage may not be sufficient for the concurrence of SBTI and HI.

### 3.3. Occurrence of HI Below ETI

In contrast to SBTI that is strongly related to HI, ETI is not enhanced by HI (Figure S5 in Supporting Information S1). However, it is common to observe the occurrence of ETI and HI (Figures 2c and 2d). This observational evidence also suggests that the concurrence of ETI with HI may have a different mechanism compared to that of SBTI.

To determine the relationship of ETI and HI, the vertical distances of HI relative to SBTI and ETI at each concurrence moment are counted separately. Figure 4 shows that when SBTI and HI occur concurrently, HI is always above SBTI and the distance between the two does not decrease significantly

when SBTI is intensified. While HI could theoretically occur above or below ETI, it is, actually, always below ETI when ETI and HI occur concurrently. Moreover, the distance between HI and ETI decreases significantly as ETI is intensified. This result may indicate that the formation of HI is a result of ETI blocking the turbulent diffusion of water vapor, thus validating the hypothesis of Devasthale et al. (2011).

Furthermore, during the occurrence of HI, the intensity of ETI is weaker, less than $1^{\circ}\text{C}\cdot\text{100m}^{-1}$, while the intensity spectrum of SBTI is much wider and has a maximum intensity of more than $2^{\circ}\text{C}\cdot\text{100m}^{-1}$. This observation supports the notion that HI may intensify SBTI, but not ETI.

### 4. Conclusions

In this study, we investigated the phenomenon of TI and HI concurrence by a high-temporal resolution data set containing temperature and humidity profiles obtained from a microwave radiometer deployed in Qingdao (Yellow Sea coast), China. During the two-month campaign, we obtained 106,424 temperature and humidity profiles and identified 19,084 valid TI records and 18,998 HI records.

Previous studies suggested that the water vapor condensation and the transport-inhibition effect may play a key role in leading to the concurrence of HI and TI (Devasthale et al., 2011; Naakka et al., 2018). Our results partly confirmed this conclusion but raised some important issues. Actually, if we further divided TI into subgroups of SBTI and ETI, different relationships exist with HI. Our study confirmed that ETI could block the water vapor transport near the surface, leading to HI formation, as proposed by Devasthale et al. (2011). However, such a mechanism cannot explain the positive correlation between SBTI and HI. SBTI typically occurs at night. Its intensity was significantly and positively correlated with HI. Nevertheless, a fraction of SBTIs don't coincide with HI. HI decreases significantly after the onset of SBTI. These findings don't support the mechanisms suggested by Naakka et al. (2018) and Devasthale et al. (2011), involving water vapor condensation and transport inhibition.

We recall that ETI has a higher temporal overlap with HI, and HI almost always occurs below the ETI layer. The presence of ETI in the lower troposphere can play the role of a lid trapping moisture and preventing it from further dispersion in the free atmosphere. There are thus favorable conditions for fog and cloud formation below the ETI layer (Klein & Hartmann, 1993; Solomon et al., 2011).

We can also speculate on a possible mechanism leading to the concurrence of SBTI and HI (Figure S9 in Supporting Information S1). It involves the radiative transfer that is altered by water vapor in the presence of HI (eventually attributable to water vapor advection, as shown in Brunke et al., 2015; Devasthale et al., 2011). We
believe that the formation of fog and low clouds can enhance the absorption of longwave radiation from the surface (Stanhill, 2011; Vaquero-Martínez et al., 2020), thereby increasing the temperature gradient. The negative radiative flux from the dry ground and the positive radiative flux from the bottom of HI could enhance or trigger the development of SBTI, as already suggested in a few past studies (Banta et al., 1993; Miller et al., 2003; Naakka et al., 2018; Wood & Bretherton, 2006; Zhou et al., 2023). It may provide insight into the mechanism and forecast of fog in winter in coastal areas, and deepen the understanding of meteorological processes in the boundary layer.

Finally, it is to be noted that results presented here are from a single-site campaign in Qingdao, while the concurrence of temperature inversion and humidity inversion may differ in other regions or under different atmospheric conditions. Temperature inversions are widely observed across Eastern China (Li & Gu, 2006), and Qingdao can serve as a representative station in eastern China. Further studies and more comprehensive observations are needed to investigate the spatial extension of TI and HI concurrence, and to test the role of radiation for the concurrence of SBTI and HI.

## Data Availability Statement

The temperature and humidity inversion data used in this study can be retrieved from https://doi.org/10.5281/zenodo.7817812 (Zhou et al., 2023).

## Acknowledgments

This research was supported by the National Natural Science Foundation of China (Grants U2242201, 42075077, 42305069) and the Hunan Provincial Natural Science Foundation of China (Grants 2021JC0009, 2023JJ30629).

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