Structures and Mechanisms of Heatwaves Related to Quasi-Biweekly Variability over Southern China

Bin Zheng aGuangzhou Institute of Tropical and Marine Meteorology (ITMM), China Meteorological Administration, and Guangdong Provincial Key Laboratory of Regional Numerical Weather Prediction, Guangzhou, China

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Dejun Gu aGuangzhou Institute of Tropical and Marine Meteorology (ITMM), China Meteorological Administration, and Guangdong Provincial Key Laboratory of Regional Numerical Weather Prediction, Guangzhou, China

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Ailan Lin aGuangzhou Institute of Tropical and Marine Meteorology (ITMM), China Meteorological Administration, and Guangdong Provincial Key Laboratory of Regional Numerical Weather Prediction, Guangzhou, China

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Dongdong Peng aGuangzhou Institute of Tropical and Marine Meteorology (ITMM), China Meteorological Administration, and Guangdong Provincial Key Laboratory of Regional Numerical Weather Prediction, Guangzhou, China

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Chunhui Li aGuangzhou Institute of Tropical and Marine Meteorology (ITMM), China Meteorological Administration, and Guangdong Provincial Key Laboratory of Regional Numerical Weather Prediction, Guangzhou, China

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Yanyan Huang aGuangzhou Institute of Tropical and Marine Meteorology (ITMM), China Meteorological Administration, and Guangdong Provincial Key Laboratory of Regional Numerical Weather Prediction, Guangzhou, China

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Abstract

In the present study, the structures and mechanisms of the heatwaves (HWs) associated with the quasi-biweekly (QBW; 10–20-day period) variability (QBW-HW) over southern China (SC; 106°–120°E, 21°–30°N) are investigated by using observation data from surface stations in China and the related gridded dataset (CN05.1), and the National Centers for Environmental Prediction–National Center for Atmospheric Research (NCEP–NCAR) reanalysis. We found that the strongest anticyclonic anomaly and subsidence appear over SC during the developing phase of QBW-HW, and then induced excess solar radiation at surface and significant diabatic heating lead to a positive surface air temperature change, thus favoring occurrence of QBW-HW over SC. In addition, we found a wet near-surface atmosphere in the QBW-HW events over SC, and further confirmed that near-surface moisture should play an important role in the occurrence of QBW-HW, via absorptions of longwave and shortwave radiation. This result is quite different from previous studies since they did not pay attention to the near-surface moisture. On the other hand, warmer SAT favors more water vapor evaporated from the moist soil when considering the Clausius–Clapeyron relationship. Then, the positive feedback processes promote the occurrence of QBW-HW over SC. In contrast, during the developing and warm phases of QBW-HW over SC, except for the near-surface level, the troposphere is in a dry condition, even at 850 and 700 hPa. In the QBW-HW events over SC, the factor responsible for the wet near-surface atmosphere is the enhanced surface evaporation, which is attributed to strengthened surface wind speed and background moist soil.

Significance Statement

Under the background of global warming, heatwaves over Southern China are experiencing an increasing trend. In this study, we want to understand the structures and mechanisms of the heatwaves related to 10–20-day (quasi-biweekly) variability. We that found some structures of heatwaves (e.g., anticyclonic anomalies along with subsidence) are consistent with previous studies. In addition, we also show that the moist soil and increased induced near-surface moisture play a key role in the occurrence of heatwaves over Southern China, via enhanced absorptions of longwave and shortwave radiation. This study is helpful for understanding the processes and prediction of heatwaves over Southern China. Future work should examine the findings by some numerical experiments with a climate model.

© 2022 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: Bin Zheng, zhb@ustc.edu

Abstract

In the present study, the structures and mechanisms of the heatwaves (HWs) associated with the quasi-biweekly (QBW; 10–20-day period) variability (QBW-HW) over southern China (SC; 106°–120°E, 21°–30°N) are investigated by using observation data from surface stations in China and the related gridded dataset (CN05.1), and the National Centers for Environmental Prediction–National Center for Atmospheric Research (NCEP–NCAR) reanalysis. We found that the strongest anticyclonic anomaly and subsidence appear over SC during the developing phase of QBW-HW, and then induced excess solar radiation at surface and significant diabatic heating lead to a positive surface air temperature change, thus favoring occurrence of QBW-HW over SC. In addition, we found a wet near-surface atmosphere in the QBW-HW events over SC, and further confirmed that near-surface moisture should play an important role in the occurrence of QBW-HW, via absorptions of longwave and shortwave radiation. This result is quite different from previous studies since they did not pay attention to the near-surface moisture. On the other hand, warmer SAT favors more water vapor evaporated from the moist soil when considering the Clausius–Clapeyron relationship. Then, the positive feedback processes promote the occurrence of QBW-HW over SC. In contrast, during the developing and warm phases of QBW-HW over SC, except for the near-surface level, the troposphere is in a dry condition, even at 850 and 700 hPa. In the QBW-HW events over SC, the factor responsible for the wet near-surface atmosphere is the enhanced surface evaporation, which is attributed to strengthened surface wind speed and background moist soil.

Significance Statement

Under the background of global warming, heatwaves over Southern China are experiencing an increasing trend. In this study, we want to understand the structures and mechanisms of the heatwaves related to 10–20-day (quasi-biweekly) variability. We that found some structures of heatwaves (e.g., anticyclonic anomalies along with subsidence) are consistent with previous studies. In addition, we also show that the moist soil and increased induced near-surface moisture play a key role in the occurrence of heatwaves over Southern China, via enhanced absorptions of longwave and shortwave radiation. This study is helpful for understanding the processes and prediction of heatwaves over Southern China. Future work should examine the findings by some numerical experiments with a climate model.

© 2022 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: Bin Zheng, zhb@ustc.edu

1. Introduction

Heatwaves (HWs), with a long duration and high intensity, are a major meteorological disaster on a global scale, which has a severe impact on human health and ecosystems. In China, southern China (SC) is one of the regions where HW events occur frequently, with an increasing trend under the background of global warming (Wei and Chen 2009). In very recent years, especially severe HW events have occurred in SC almost every year. In 2017, for example, a destructive HW hit central and southern China, with record-breaking maximum air temperatures appearing at many observational stations (Chen et al. 2019). Another exceptionally strong HW event occurred in SC during May 2018, when the maximum air temperature in many regions exceeded the records (Deng et al. 2020).

HW events are largely attributed to atmospheric anticyclonic anomalies, which induce excess solar radiation and adiabatic heating along with subsidence, favoring higher air temperature and occurrence of HWs. But the physical processes associated with the anomalous anticyclones are complex and differ from case to case.

Sea surface temperature (SST) anomalies play a role in the atmospheric anticyclonic forcing related to HW events over SC (e.g., Hu et al. 2012; Deng et al. 2019). For instance, the tropical Indian Ocean warm SST anomaly triggers the Kelvin wave to propagate to the western Pacific, and induced Ekman divergence leads to an anticyclonic circulation in the western North Pacific (Xie et al. 2009). During warm events in the eastern Pacific (El Niño events), the anticyclonic anomaly, resulting from a Rossby wave response, appears near the Philippine Sea (Zhang et al. 1996; Wang et al. 2000), the persistence of which is primarily attributed to a local air–sea interaction (Wang et al. 2000).

Besides the SST forcing, intraseasonal oscillation (ISO) should be a key factor in affecting the low-level anticyclonic anomalies associated with HW events. The Madden–Julian oscillation (MJO), a typical ISO, is characterized by a 30–60-day period with a zonal wavenumber 1 propagating eastward along the equator (Madden and Julian 1971). In response to the MJO-induced convective heating, a Rossby wave train extends from the tropics toward higher latitudes, resulting in the anomalous circulation over the off-equatorial areas (i.e., SC) (Matsueda and Takaya 2015). Different from the MJO impacts, boreal summer ISO (BSISO) directly impacts the higher-latitude circulation anomalies via a northward propagation of anomalous convection and circulations (Chen and Lu 2015; Hsu et al. 2017). In addition, the southeastward propagating wave train, originating from high latitudes, can also impact the high pressure anomaly over SC, favoring the occurrence of HWs (e.g., Deng et al. 2019).

In addition to the anomalous anticyclone, soil moisture may be an important key in modulating the surface air temperature. In this mechanism, lack of soil moisture strongly reduces evaporative cooling and thereby amplifies the surface temperature anomalies, and then enhanced sensible heating leads to higher air temperature and favors the occurrence of HWs (e.g., Fischer et al. 2007; Hirschi et al. 2011; Zhang et al. 2015; Deng et al. 2019). Moreover, reduced evaporation makes the air drier and further increases the surface net solar radiation, favoring the occurrence of HWs (e.g., Chen et al. 2016; Luo and Lau 2017; Deng et al. 2020).

In this study, we focus on the HW processes over SC associated with quasi-biweekly (QBW) variability and try to understand the related mechanisms. Since the SST forcing modulates HWs mainly on interannual or longer time scales, it is ignored in this study. On the other hand, the effects of land surface fluxes, especially surface latent heat flux, are reexamined in present work. The remainder of the manuscript is organized as follows: The data and methods used in this study are introduced in section 2. The method to select the HW events over SC associated with the QBW variability is documented in section 3. Details of mechanisms including HW structures are presented in section 4. Finally, a summary and discussion are provided in section 5.

2. Data and methods

a. Data

In this study, the data used include daily maximum temperature from over 2400 surface stations in China and a related gridded dataset (CN05.1) based on interpolation with 0.25° resolution (Wu and Gao 2013), and daily three-dimensional winds, water vapor, geopotential height, and air temperature from the National Centers for Environmental Prediction–National Center for Atmospheric Research (NCEP–NCAR) reanalysis (Kalnay et al. 1996) with 2.5° × 2.5° grids. The other datasets include the daily surface fluxes (surface solar radiation, longwave radiation, and latent and sensible heat fluxes), soil moisture, surface air temperature (SAT), maximum SAT (SATmax), surface wind, surface pressure, and surface specific humidity from NCEP–NCAR reanalysis with a T62 Gaussian grid. ERA-Interim specific humidity with 1.5° × 1.5° grids (Dee et al. 2011) and monthly mean soil moisture data (version 2) from the Climate Prediction Center (CPC) with 0.5° × 0.5° grids (Fan and van den Dool 2004) are used for comparison in this study. All data have the period of 1 January 1961–31 December 2017, except for the ERA-Interim reanalysis from 1 January 1979–31 December 2017. Note that the surface fluxes are positive upward.

b. Methods

For convenience, all data are interpolated into 1.5° × 1.5° spatial resolution. To obtain the quasi-biweekly component (10–20 days), a 11-day running mean minus a 21-day running mean is applied in this study. Power spectrum analysis of the derived SATmax QBW component for each summer shows that an 8–20-day period is significant in almost every year and other periods are not evident (figure not shown). Therefore, the method for filtering the QBW component is suitable although an 8-day period seems to be evident too. The climatological mean is from 1981 to 2010 and anomalies are obtained by removing the climatological mean. Furthermore, composite analysis is introduced to understand the mechanisms of the HW events related to 10–20-day quasi-biweekly variability over SC.

Following Lin et al. (2021), HW events in this study are defined as when the SATmax meets the given conditions for 3 consecutive days or more. The given conditions include the ratio of the number of stations with SATmax larger than 35°C to the total number of stations in the region greater than or equal to 20%, and regional average SATmax exceeding the 80th percentile. The former condition determines that the SATmax of the HW center must be greater than 35°C. According to Lin et al. (2021), the SC region is 105°–120°E, 21°–26°N where 193 regional HW events are obtained from May to September. Note that the HW region over SC defined by Lin et al. (2021) largely refers to administrative divisions. Based on the HW events, however, the SATmax composite shows a wider range of high temperatures (Fig. 1). Therefore, the SC region is identified by 106°–120°E, 21°–30°N in this study (as shown by box in Fig. 1).

Fig. 1.
Fig. 1.

Composites of SATmax (K) based on HW occurrence over SC from Lin et al. (2021). The box represents the region of SC (106°–120°E, 21°–30°N) defined in this paper.

Citation: Journal of Climate 35, 24; 10.1175/JCLI-D-22-0282.1

3. Selections of HW related to QBW variability (QBW-HW)

Similar to the results in Hsu et al. (2017), the power spectrum of the SC SATmax shows a statistically significant QBW component (Fig. 2), which is critical for the occurrence of HWs in SC (Chen et al. 2016). Note that the QBW is a quasi-period on the 10–20-day time scale and the power spectrum in the entire time series from 1961 to 2017 shows a very detailed periodic variability (Fig. 2), while wavelet analysis of the SATmax subseasonal component for each year shows that a 10–20-day period is indeed one of the most frequent periods (figure not shown). Therefore, we focus on the HW events associated with QBW variability in this study. We define HW events related to 10–20-day intraseasonal variability by using the criterion that the regional mean 10–20-day filtering SATmax is greater than 0.5 times the standard deviation (std) and lasts for 4 days or more; note that the HW from Lin et al. (2021) is at least 3 days in this period. Thus, we obtain 108 HW events over SC. In this study, our analysis of the HW events is based on the 108 selected cases (referred to simply as QBW-HW events or just GBW-HW hereafter). It is worth noting that the definitions of HW events are same between Lin et al. (2021) and this study, but we focus on the QBW-HW events selected from all the HW events via the criterion mentioned above.

Fig. 2.
Fig. 2.

Power spectrum of SATmax anomalies over SC. The dashed curve represents the 95% significant level.

Citation: Journal of Climate 35, 24; 10.1175/JCLI-D-22-0282.1

The QBW-HW events were composited relative to the peak SATmax, as shown in Fig. 3. We can see from Fig. 3 that the amplitude of the negative phases shows an obvious asymmetry. Considering the asymmetry, we divide the QBW process into five phases with 0.75 standard deviations (std) in the positive phase (blue dashed line in Fig. 3) and −0.5 std in the negative one (red dashed line in Fig. 3) as the threshold; that is, the cool phase and developing phase appear before the peak SATmax with values less than −0.5 std and between −0.5 and 0.75 std respectively; the QBW-HW has a warm phase when 10–20-day filtering SATmax is greater than 0.75 std; and the decaying phase and ending phase appear in the period after the peak SATmax when the SATmax is between −0.5 and 0.75 std and less than −0.5 std, respectively.

Fig. 3.
Fig. 3.

Composite 10–20-day filtering SATmax (K) based on the peak value. The positive (negative) value of the x axis means the day after (before) the peak SATmax (zero day). The blue dashed line denotes 0.75 std and the red one −0.5 std.

Citation: Journal of Climate 35, 24; 10.1175/JCLI-D-22-0282.1

4. Mechanisms for QBW-HW over SC

a. QBW-HW structures

The spatial structures of QBW-HW are examined in different phases. Figures 4 and 5 show the composites of SATmax from CN05.1 and the NCEP–NCAR reanalysis, respectively. One can see from Figs. 4 and 5 that there are similar patterns between two datasets: a negative SATmax anomaly appears over SC during the cool and ending phases (Figs. 4a,e and 5a,e), a developing positive SATmax anomaly and negative one occur in the developing and decaying phases, respectively (Figs. 4b,d and 5b,d), and a maximum SATmax anomaly appears in the warm phase (Figs. 4c and 5c), although the result from the NCEP–NCAR reanalysis is weaker than that from CN05.1.

Fig. 4.
Fig. 4.

Composites of SATmax (K) from CN05.1 based on different phases. Shading represents the 99% confidence level, and orange and green indicate positive and negative anomalies, respectively. The variable is after 10–20-day filtering. The box in (c) represents the region of SC.

Citation: Journal of Climate 35, 24; 10.1175/JCLI-D-22-0282.1

Fig. 5.
Fig. 5.

As in Fig. 4, but for SATmax (K) and surface winds (m s−1) from the NCEP–NCAR reanalysis.

Citation: Journal of Climate 35, 24; 10.1175/JCLI-D-22-0282.1

The most significant anticyclonic anomaly appears over SC during the developing phase (Fig. 6), accompanied by the strongest descending motion (Fig. 7), which would favor a positive SAT tendency over SC due to adiabatic heating. Meanwhile, reduced cloud cover would increase solar radiation at the surface (Fig. 8b), further heating the surface atmosphere. These results are consistent with previous studies (e.g., Meehl and Tebaldi 2004; Chen et al. 2016; Hsu et al. 2017). In addition, a southeast–northwest-tilted wave train exists in nearly all phases, except for the cool phase (Fig. 6). As revealed by previous studies, although the northeastward and southwestward propagating QBW variabilities have different origins and life cycles (e.g., Kikuchi and Wang 2009), both promote the occurrence of HW via strengthening the anomalous anticyclone (e.g., Chen and Lu 2015; Hsu et al. 2017; Deng et al. 2019). The wave train should be a key factor in generating the anticyclonic anomaly over SC. In this study, we place more emphasis on northward and southward propagation due to the focus on the effects from tropics and higher latitudes. Wavelength-period analysis for the vorticity anomalies indicates both southward and northward propagation with a comparable strength of power spectrum (figure not shown) on the quasi-biweekly time scale, implying that the QBW-HW event is affected by the QBWV from both the tropics and higher latitudes.

Fig. 6.
Fig. 6.

As in Fig. 5, but for 850-hPa vorticity (s−1) and winds (m s−1).

Citation: Journal of Climate 35, 24; 10.1175/JCLI-D-22-0282.1

Fig. 7.
Fig. 7.

As in Fig. 5, but for 500-hPa vertical velocity (Pa s−1).

Citation: Journal of Climate 35, 24; 10.1175/JCLI-D-22-0282.1

Fig. 8.
Fig. 8.

As in Fig. 5, but for surface solar radiation (W m−2).

Citation: Journal of Climate 35, 24; 10.1175/JCLI-D-22-0282.1

b. Effects of advection

In this study, the SATmax is used to define HW event over SC (as shown in Figs. 15), but it is a value at a time of day and is not suitable for the diagnostic analysis of air temperature balance. Therefore, we next use SAT instead of SATmax for budget analysis.

Considering the effects of topography, we use the σ(P/Ps) coordinate system in this study. The temperature change in σ coordinates could be written as follows:
Tt=VTσ˙Tσ+RTcpP(Psσ˙+Pt+VP)+Q1cp,
where T is the air temperature, V is the horizontal velocity vector, σ˙=dσ/dt is the vertical velocity in σ coordinates, R is the gas constant, cp is the specific heat at constant pressure, P is the pressure, with subscript s representing surface variable, and Q1 is the atmospheric apparent heat source.
At the surface, σ = 1 and 0. Thus, the SAT change is given by
Tst=VsTs+RTscpPs(Pst+VsPs)+Q1cp.
Here TS means the SAT. We focus on the SAT change in the developing phase when the maximum SAT change appears according to the HW definition. The SAT budget shows that the surface advection of SAT has a modest negative contribution to the SAT tendency (Fig. 9a), while the vertical advection of SAT has no effect due to σ = 0 at surface. The mean state of the SAT shows that the meridional and zonal gradients are negative (figure not shown), and thus the anomalous southwesterly (Fig. 5b) would increase the SAT over SC by the advection of background SAT. However, the anomalous SAT advected by climatological southeasterly in SC leads to a negative change, resulting in an overall insignificantly cold advection as shown in Fig. 9a.
Fig. 9.
Fig. 9.

(a) SAT budget and (b) surface radiation and heat fluxes in the developing phase of QBW-HW over SC.

Citation: Journal of Climate 35, 24; 10.1175/JCLI-D-22-0282.1

c. Effects of adiabatic heating

According to Eq. (2), the adiabatic heating has two terms, the effect from local change of the surface pressure and the effect of advection of surface pressure. The latter plays an important role in warming the surface atmosphere over SC (Fig. 9a). As shown in Figs. 6b and 7b, the most significant anticyclonic anomaly along with the strongest descending motion appears over SC during the developing phase, when the anomalous ps increases first and then decreases. Therefore, there is little change in ps throughout the developing phase, which contributes almost nothing to the SAT tendency (Fig. 9a). In contrast, the adiabatic heating induced by ps advection has a modest contribution to the SAT change because the high pressure is located in SC at this time. Since the high pressure is closely linked to the atmospheric anticyclone, it is believed that an anticyclone is the atmospheric general circulation responsible for HWs (e.g., Meehl and Tebaldi 2004; Chen et al. 2016; Hsu et al. 2017; Deng et al. 2019). In SC, the anticyclonic anomaly should be closely connected with the wave train (Fig. 6), which originates from higher latitudes with a southward propagation (e.g., Deng et al. 2019) and/or from the equator with a northward propagation (e.g., Chen and Lu 2015; Hsu et al. 2017). In addition, based on wavelength-period analysis, we obtained a comparable strength of power spectrum of the southward and northward propagating vorticity perturbations on the quasi-biweekly time scale, which are related to the QBW-HW events over SC, implying they have a comparable contribution to the QBW-HW occurrence over SC.

It is worth noting that the term [RTs/(cpPs)][(Ps/t)+VsPs] in Eq. (2) represents the effect from vertical motion, namely ω{(T/p)[RT/(cpp)]} in the level of surface pressure. The result from Eq. (2) in the level of surface pressure also indicates that the total effect from vertical motion plays a weak role in the SAT change, which is the same as shown in Fig. 9a, although the former has a large positive contribution to the change in SAT (figure not shown).

d. Effects of diabatic heating

The anticyclonic anomaly and accompanying descending motion reduce cloud cover, and then increase solar radiation at surface (Figs. 8b and 9b), which would warm the surface atmosphere due to diabatic heating. In this study, the increased upward longwave radiation at surface enhances the diabatic heating over SC, while the decreased upward sensible heat flux weakens the diabatic heating to a certain degree (Fig. 9b).

Different from the previous studies (e.g., Chen et al. 2016; Hsu et al. 2017), we propose another diabatic heat mechanism associated with QBW-HW over SC. During the developing phase, an increased latent heat flux at surface (Fig. 9b) leads to a positive moisture change (Fig. 10). We know that water vapor absorbs longwave and shortwave radiation more effectively than dry air. Thus, more near-surface water vapor would absorb more longwave and shortwave radiations to heat the surface atmosphere, favoring the occurrence of HW. Note that absorption by water vapor is the major source of solar radiative heating in the troposphere (e.g., Lacis and Hansen 1974), which mainly occurs in the near-infrared band.

Fig. 10.
Fig. 10.

Moisture tendency at surface in the developing phase. Shading denotes the composite anomalies exceeding the 99% significance level.

Citation: Journal of Climate 35, 24; 10.1175/JCLI-D-22-0282.1

Previous studies argued that drier air conditions favor the occurrence of HW (e.g., Chen et al. 2016; Luo and Lau 2017; Deng et al. 2020) because the moist air generally corresponds to the development of convection and the increased cloud cover, leading to cold air temperature. Figure 11 shows that the positive moisture anomaly for the QBW-HW over SC peaks in the warm phase and appears in the near-surface atmosphere. The positive anomaly of water vapor extends to the mid- and upper-level troposphere in the decaying and ending phase, implying that the convection develops and leads to an increased cloud cover and decreased downward solar radiation at surface (Figs. 8d,e), and then tends to cool the atmosphere after the warm phase. Note that the developed convection is attributed to both the cyclonic anomaly effects from the tropics and higher latitudes by the propagating QBW wave train and the increased atmospheric instability due to the warming and humidification of the local lower troposphere. In contrast, the negative moisture anomalies mainly appear in the mid- and upper-level troposphere, even in the lower atmosphere (e.g., 850 hPa), during the developing and warm phases. Therefore, the previous studies (e.g., Chen et al. 2016; Luo and Lau 2017; Deng et al. 2020) concluded that drier air conditions favor the occurrence of HWs, since the near-surface moisture anomaly had not been paid attention to. For the QBW-HW over SC, drier air conditions are present in almost the entire troposphere except for near-surface water vapor increases (Fig. 11).

Fig. 11.
Fig. 11.

Moisture (g kg−1) evolution in different phases of QBW-HW over SC. Shading denotes the composite anomalies exceeding the 99% significance level.

Citation: Journal of Climate 35, 24; 10.1175/JCLI-D-22-0282.1

To examine whether the relationship between SC QBW-HW and the near-surface moisture is robust, we conduct a composite analysis with respect to greater and less near-surface water vapor in the QBW-HW period with regional mean moisture as a threshold. That is, during the warm phase of QBW-HW, the surface moisture anomaly averaged over SC with more or less moisture indicates, in this study, that the surface moisture anomaly is larger or less than the mean result, respectively. Note that “less” near-surface water vapor here is relative to the mean moisture when the QBW-HW event occurs, while the actual moisture anomaly is still positive. Thus, we obtained 45 QBW-HW cases with more near-surface water vapor and 63 QBW-HW cases with less near-surface water vapor. The latter includes 10 QBW-HW events with negative moisture anomalies. Figure 12 shows that more near-surface water vapor would lead to a stronger heatwave. Furthermore, the SAT budget shows that more near-surface water vapor does enhance the SAT change mainly via diabatic heating (Fig. 13).

Fig. 12.
Fig. 12.

Composites of the warm phase of QBW-HW over SC for (a) more and (b) less moisture (g kg−1) at the surface, and (c),(d) the corresponding SAT (K) for (a) and (b), respectively. Shading denotes the composite anomalies exceeding the 99% significance level.

Citation: Journal of Climate 35, 24; 10.1175/JCLI-D-22-0282.1

Fig. 13.
Fig. 13.

SAT budget (K day−1) for (a) more and (b) less surface moisture in the developing phase of QBW-HW over SC.

Citation: Journal of Climate 35, 24; 10.1175/JCLI-D-22-0282.1

In the QBW-HW over SC, we consider a simple case with a same atmospheric condition in addition to near-surface water vapor, such that the difference in absorption of radiation by the atmosphere is attributed to the different near-surface water vapor. In this study, it is estimated as follows:
ΔASW=Δ(TSWSSW),
ΔALW=Δ(SLWTLW),
where Δ denotes the difference for more or less near-surface moisture, A is the absorption of radiation by the atmosphere, with subscripts SW and LW representing shortwave and longwave radiation respectively, SSW represents the surface net shortwave radiation, TSW represents the top-of-atmosphere net shortwave radiation, SLW is the surface net longwave radiation, and TLW is the top-of-atmosphere longwave radiation.

Figure 14 further confirms the roles of near-surface moisture in SAT anomalies via absorption of shortwave and longwave radiation. Moreover, shortwave radiation heating is more significant, almost 3 times that of longwave. It is worth noting that while it absorbs solar and longwave radiation, water vapor also emits longwave radiation (i.e., thermal radiation), which is closely related to the temperature, offsetting part of its absorption.

Fig. 14.
Fig. 14.

Difference in absorption of (a) shortwave and (b) longwave radiation for more and less near-surface moisture in the warm phase of QBW-HW over SC according to Eqs. (2) and (3) respectively. Shading denotes the fluxes exceeding the 90% significance level.

Citation: Journal of Climate 35, 24; 10.1175/JCLI-D-22-0282.1

For Eqs. (3) and (4) and Fig. 14, we consider a simple case with the same atmospheric condition in addition to near-surface water vapor. This assumption is reasonable to a certain extent since the water vapor centers mainly occur in the lower atmosphere (Fig. 11). However, the results under the simple case assumption do not fully represent the absorption of near-surface moisture. Therefore, we next calculate the absorption of longwave and shortwave radiation by water vapor by using empirical formulas (Sasamori 1968; Lacis and Hansen 1974). Although the empirical formulas used in this study are really very old, the shortwave radiation scheme by Lacis and Hansen (1974) and the longwave radiation scheme by Sasamori (1968) are applied in the intermediate complexity model Planet Simulator (Fraedrich et al. 2005; Fraedrich 2012), which has been widely used in climate research in very recent years (e.g., Bordi et al. 2012; Ragone et al. 2015; Herein et al. 2017; Tran et al. 2019; Ghil and Lucarini 2020).

Following Lacis and Hansen (1974), the water vapor absorptivity of solar radiation is estimated as follows:
aSW=2.9y(1+141.5y)0.635+5.925y,
where y is the effective water vapor amount (with units of centimeters),
y=Mg0Pq(PsP0)(T0Ts)1/2dP;
M is the magnification factor (M = 1.155 in this study), g is the acceleration of gravity, q is the specific humidity, with subscript s representing variables at the surface, and P0 and T0 denote standard pressure and temperature (P0 = 1013 hPa and T0 = 273 K), respectively. Thus, we have the heating rate HSW due to absorption of solar radiation by moisture:
HSWS0sin(θ)gcpaSWP,
where S0 is the solar constant 1367 W m−2, and θ is the solar zenith angle (in this study, θ is 60° averaged over SC from May to September). From Eq. (7), the heating rate due to solar absorption by moisture is calculated (as shown in Fig. 15a), and we found that the heating rate has a similar pattern to the anomalous moisture (Fig. 11). This implies that more moisture would lead to a warm air temperature under the same background of solar radiation.
Fig. 15.
Fig. 15.

Heating rates (K day−1) evolution in different phases of QBW-HW over SC from Eqs. (7) and (10) based on the moisture anomalies as shown in Fig. 11a.

Citation: Journal of Climate 35, 24; 10.1175/JCLI-D-22-0282.1

Following Sasamori (1968), the water vapor transmissivity of longwave radiation is estimated as follows:
τLW=1.330.832(u+0.0286)0.26,
where u is the effective path length of water vapor (with units of meters):
u=1gPPsq(PsP0)dP.
The heating rate HSW due to absorption of longwave radiation by moisture is then
HLWgcp(ULs)τLWP,
where ULs is the upward longwave radiation at the surface.

Figure 15b shows the heating rate due to absorption of longwave radiation calculated from Eq. (10). It is the same as the heating rate due to solar absorption, but with a smaller magnitude, and has a similar pattern to the anomalous moisture (Fig. 11). This confirms that more near-surface water vapor would lead to warmer SAT.

According to Eqs. (7) and (10), the heating rate difference between shortwave and longwave absorption is attributed to the radiation source intensity and vertical gradient of absorptivity or transmissivity. In this study, the solar radiation source intensity over SC is S0 sin (60°) with a value of 1183.86 W m−2, while climatological upward longwave radiation at surface over SC is about 443.7 W m−2. In addition, although the vertical gradient of solar absorptivity is smaller than that of longwave transmissivity when the specific humidity is greater than 6 g kg−1, the former is larger than the latter when the specific humidity is less than 4 g kg−1 (figure not shown). On the QBW time scale, the anomalous moisture has a value less than 1 g kg−1 over SC, so that there is a smaller vertical gradient of longwave transmissivity relative to that of solar absorptivity. Therefore, as a result, the amplitude of shortwave absorption (Fig. 15a) is much larger than that of longwave absorption (Fig. 15b)

e. Near-surface moisture budget

The moisture change in σ coordinates could be written as follows:
qt=Vqσ˙qσQ2L,
where Q2 is the apparent moisture sink, and L is the latent heat constant. In Eq. (4), (Q2/L) at the surface is mainly determined by surface evaporation during summer season, when HW events often occur. In the near-surface layer,
qst=VsqsQ2L.

As shown in Fig. 16, a positive moisture change at the surface appears over SC in the developing phase of QBW-HW. The horizontal advection term −V ⋅ ∇q plays a small role in the moisture tendency. The main positive contribution to the moisture tendency comes from the term (Q2/L) (mainly determined by surface evaporation), as shown in Fig. 16.

Fig. 16.
Fig. 16.

Surface moisture budget in the developing phase of QBW-HW over SC.

Citation: Journal of Climate 35, 24; 10.1175/JCLI-D-22-0282.1

Why does a large surface evaporation appear in SC during the QBW-HW developing phase? First, the anomalous southwesterlies at the low-level troposphere enhance the mean wind in the rainy season, leading to a larger surface evaporation. In addition, the surface energy budget indicates that more downward solar radiation would induce the positive soil temperature anomaly during the QBW-HW events (Fig. 9b), along with the background moist soil (as shown in Fig. 17, SC soil has richer water content), which favors more surface evaporation. Note that the ground heat flux is ignored in this study, since it is generally small.

Fig. 17.
Fig. 17.

Summer mean (May–September) soil moisture averaged between 106° and 120°E from (a) NCEP–NCAR reanalysis (m3 m−3) and (b) CPC soil moisture data V2 (mm).

Citation: Journal of Climate 35, 24; 10.1175/JCLI-D-22-0282.1

5. Summary and discussion

HWs are one of the most influential meteorological disasters in SC, and are closely related to BSISO (e.g., Hsu et al. 2017). In this study, we focus on the SC HW processes related to 10–20-day (QBW) variability (QBW-HW) and try to understand the mechanisms. By composite analysis, we found that the strongest anticyclonic anomaly and subsidence appear over SC during the developing phase of QBW-HW (Figs. 6 and 7), and then induced excess solar radiation (Fig. 8b) at surface and significant diabatic heating (Fig. 9a) lead to a positive SAT change in the phase (Fig. 10), thus favoring occurrence of QBW-HW over SC. These results are consistent with previous studies (e.g., Meehl and Tebaldi 2004; Xie et al. 2009; Hsu et al. 2017; Deng et al. 2020).

In addition, we found that near-surface moisture should play an important role in the occurrence of QBW-HW over SC, via absorption of longwave and shortwave radiation. This result is quite different from previous studies (e.g., Chen et al. 2016; Luo and Lau 2017; Deng et al. 2020), which argued that drier air would favor the occurrence of HW. In their studies, the negative moisture anomalies do appear in the lower atmosphere [e.g., 850 hPa for Deng et al. (2020); 700 hPa for Chen et al. (2016)]; however, they ignore the near-surface moisture. As shown in Fig. 11, the results from NCEP–NCAR and ERA-Interim reanalysis data both show a drier atmosphere in the developing and warm phases that is consistent with previous studies, while the near-surface moisture has a positive anomaly that absorbs longwave and shortwave radiation more effectively (Figs. 14 and 15) to increase the SAT. In the developing and warm phases, the drier conditions in the mid- to upper troposphere result from the strong descending motion (Fig. 7) that prevents the abundant water vapor in the lower troposphere from being transported upward, while the more near-surface moisture is due to enhanced surface evaporation (or upward latent heat flux; Fig. 9b) over SC that is attributed to the increased wind speed and surface warming under the background of moist soil. In contrast, wet soil is heated less by the same incoming solar radiation than dry soil, due to both the large heat capacity of water and the evaporation. Therefore, although the upward sensible heat flux anomaly is induced by the anomaly of wind speed, reduced ground-air temperature difference causes a downward sensible heat flux anomaly. The heating rate due to sensible heat flux anomaly is estimated by assuming that the sensible heat flux decreases linearly with height, reaching zero at 850 hPa. Thus, the sensible heat flux anomaly, with a heating rate of −0.021 K day−1, does have a negative contribution to the SAT change because of the evaporative cooling process, which does not favor the occurrence of QBW-HW in SC (Fig. 9). The radiation absorption due to the near-surface moisture, especially the absorption of solar radiation, plays a key role in the occurrence of QBW-HW over SC (Figs. 9a and 15).

In addition to the effect of anomalous water vapor on the air temperature change, we can see from Figs. 4, 5, 11, and 14 that the moisture and air temperature anomalies are almost in phase, implying a contribution of air temperature anomaly to the change in moisture. In fact, more evaporation appears over SC in the developing phase of QBW-HW because of warm surface temperature induced by enhanced solar radiation (Figs. 8b, 9b, and 16), and then more water vapor in the near-surface layer (Fig. 11) leads to an increase of SAT (Fig. 15) in the developing and warm phases. Simultaneously, warmer SAT favors more water vapor evaporated from the moist soil when considering the Clausius–Clapeyron relationship. Then, the positive feedback processes promote the occurrence of QBW-HW over SC (Fig. 18). In contrast, the increased water vapor and air temperature can destabilize the atmosphere and induce ascending motion (Figs. 7d,e), which results in more cloud to decrease solar radiation at surface (Figs. 8d,e). In addition, the cyclonic anomaly related to tropical and higher-latitude QBW propagating into the SC region would lead to developed convection. Therefore, the positive feedback will be interrupted from the decaying phase.

Fig. 18.
Fig. 18.

Schematic diagram for mechanisms of QBW-HW occurrence over SC. A strong anticyclonic anomaly ① over SC results in a descending flow and more solar radiation ②, which warms the moist soil ③ to increase the evaporation ④. Thus, more moisture ⑤ at the near surface absorbs more solar and longwave radiation ⑥ to heat the SAT ⑦. On the other hand, warmer SAT ⑦ accommodates more water vapor evaporated from the wet soil according to the Clausius–Clapeyron relationship. This is a positive feedback process favoring the occurrence of QBW-HW.

Citation: Journal of Climate 35, 24; 10.1175/JCLI-D-22-0282.1

Although the focus of this study is on the QBW-HW, HW events are the result of the combined influence of multiple time-scale processes. The calculation result shows that around 40% of the SAT change (without any filtering) during a HW event is contributed by the 10–20-day component (figure not shown). Moreover, the heating rates due to the 10–20-day processes of advection and sensible heat flux contribute approximately 10% negatively to the total nonfiltering SAT change, respectively, while those induced by the adiabatic and radiative processes are positive contributions. It is worth noting that the contributions of 10–20-day radiative heating can reach more than 50% of the total nonfiltering SAT change. This implies that the 10–20-day processes, especially the effect of radiative heating, are greatly important for HW events over SC.

Over SC, wet near-surface air, due to enhanced surface evaporation, is a key factor in the occurrence of QBW-HW. In the QBW-HW events over SC, the enhanced surface evaporation is attributed to strengthened surface wind speed (Figs. 5b,c) and background moist soil (Fig. 17). Some previous studies indicated that lack of soil moisture strongly reduces evaporative cooling and thereby amplifies the surface temperature anomalies, leading to the enhanced sensible heating and the occurrence of HW (e.g., Fischer et al. 2007; Hirschi et al. 2011; Zhang et al. 2015; Deng et al. 2019). In the QBW-HW events over SC, moist soil and enhanced evaporation cool the surface temperature, leading to the decreased sensible heating. Based on the sensible heat flux, moist soil does not favor the occurrence of QBW-HW, which is consistent with the previous studies (e.g., Fischer et al. 2007; Hirschi et al. 2011; Zhang et al. 2015; Deng et al. 2019). For the overall contribution to the HW events, the effects of land surface conditions are different in different regions (Stéfanon et al. 2014; Gibson et al. 2017). Stéfanon et al. (2014) pointed out that soil dryness has a heating effect in the plains but a significant cooling effect over mountains and coastal regions due to mesoscale circulations. SC is mountainous and coastal region, and thus lack of soil moisture should cool, rather than warm, the SAT, which is consistent with this study though different mechanisms involved.

Acknowledgments.

This work was jointly supported by the National Key R&D Program of China (Grant 2018YFC1505801), the Guangdong Basic and Applied Basic Research Foundation (Grants 2021A1515011399 and 2020A1515010485), and the National Natural Science Foundation of China (Grant 41905070).

Data availability statement.

The daily maximum temperature data from the surface meteorological stations in China and related gridded dataset (CN05.1; https://ccrc.iap.ac.cn/resource) are provided by National Climate Center (NCC), and the China Meteorological Administration (CMA), the NCEP–NCAR reanalysis data and CPC soil moisture were obtained from https://psl.noaa.gov/data/gridded/data.cpcsoil.html, and the ERA-Interim reanalysis data were obtained from https://apps.ecmwf.int/datasets/data/interim-full-daily/.

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  • Bordi, I., K. Fraedrich, A. Sutera, and X. Zhu, 2012: On the climate response to zero ozone. Theor. Appl. Climatol., 109, 253259, https://doi.org/10.1007/s00704-011-0579-5.

    • Search Google Scholar
    • Export Citation
  • Chen, R., and R. Lu, 2015: Comparisons of the circulation anomalies associated with extreme heat weather in different regions in eastern China. J. Climate, 28, 58305844, https://doi.org/10.1175/JCLI-D-14-00818.1.

    • Search Google Scholar
    • Export Citation
  • Chen, R., Z. Wen, and R. Lu, 2016: Evolution of the circulation anomalies and the quasi-biweekly oscillations associated with extreme heat events in southern China. J. Climate, 29, 69096921, https://doi.org/10.1175/JCLI-D-16-0160.1.

    • Search Google Scholar
    • Export Citation
  • Chen, R., Z. Wen, R. Lu, and C. Wang, 2019: Causes of the extreme hot midsummer in Central and South China during 2017: Role of the western tropical Pacific warming. Adv. Atmos. Sci., 36, 465478, https://doi.org/10.1007/s00376-018-8177-4.

    • Search Google Scholar
    • Export Citation
  • Dee, D. P., and Coauthors, 2011: The ERA-Interim reanalysis: Configuration and performance of the data assimilation system. Quart. J. Roy. Meteor. Soc., 137, 553597, https://doi.org/10.1002/qj.828.

    • Search Google Scholar
    • Export Citation
  • Deng, K., S. Yang, M. Ting, P. Zhao, and Z. Wang, 2019: Dominant modes of China summer heat waves driven by global sea surface temperature and atmospheric internal variability. J. Climate, 32, 37613775, https://doi.org/10.1175/JCLI-D-18-0256.1.

    • Search Google Scholar
    • Export Citation
  • Deng, K., S. Yang, D. Gu, A. Lin, and C. Li, 2020: Record-breaking heat wave in southern China and delayed onset of South China Sea summer monsoon driven by the Pacific subtropical high. Climate Dyn., 54, 37513764, https://doi.org/10.1007/s00382-020-05203-8.

    • Search Google Scholar
    • Export Citation
  • Fan, Y., and H. van den Dool, 2004: Climate Prediction Center global monthly soil moisture data set at 0.5° resolution for 1948 to present. J. Geophys. Res., 109, D10102, https://doi.org/10.1029/2003JD004345.

    • Search Google Scholar
    • Export Citation
  • Fischer, E. M., S. I. Seneviratne, P. L. Vidale, D. Lüthi, and C. Schär, 2007: Soil moisture–atmosphere interactions during the 2003 European summer heatwave. J. Climate, 20, 50815099, https://doi.org/10.1175/JCLI4288.1.

    • Search Google Scholar
    • Export Citation
  • Fraedrich, K., 2012: A suite of user-friendly global climate models: Hysteresis experiments. Eur. Phys. J. Plus, 127, 53, https://doi.org/10.1140/epjp/i2012-12053-7.

    • Search Google Scholar
    • Export Citation
  • Fraedrich, K., H. Jansen, E. Kirk, U. Luksch, and F. Lunkeit, 2005: The Planet Simulator: Towards a user friendly model. Meteor. Z., 14, 299304, https://doi.org/10.1127/0941-2948/2005/0043.

    • Search Google Scholar
    • Export Citation
  • Ghil, M., and V. Lucarini, 2020: The physics of climate variability and climate change. Rev. Mod. Phys., 92, 035002, https://doi.org/10.1103/RevModPhys.92.035002.

    • Search Google Scholar
    • Export Citation
  • Gibson, P. B., A. J. Pitman, R. Lorenz, and S. E. Perkins-Kipkpatrick, 2017: The role of circulation and land surface conditions in current and future Australian heat waves. J. Climate, 30, 99339948, https://doi.org/10.1175/JCLI-D-17-0265.1.

    • Search Google Scholar
    • Export Citation
  • Herein, M., G. Drótos, T. Haszpra, J. Márfy, and T. Tél, 2017: The theory of parallel climate realizations as a new framework for teleconnection analysis. Sci. Rep., 7, 44529, https://doi.org/10.1038/srep44529.

    • Search Google Scholar
    • Export Citation
  • Hirschi, M., and Coauthors, 2011: Observational evidence for soil-moisture impact on hot extremes in southeastern Europe. Nat. Geosci., 4, 1721, https://doi.org/10.1038/ngeo1032.

    • Search Google Scholar
    • Export Citation
  • Hsu, P.-C., J.-Y. Lee, K.-J. Ha, and C.-H. Tsou, 2017: Influences of boreal summer intraseasonal oscillation on heat waves in monsoon Asia. J. Climate, 30, 71917211, https://doi.org/10.1175/JCLI-D-16-0505.1.

    • Search Google Scholar
    • Export Citation
  • Hu, K. M., G. Huang, X. Qu, and R. H. Huang, 2012: The impact of Indian Ocean variability on high temperature extremes across the southern Yangtze River valley in late summer. Adv. Atmos. Sci., 29, 91100, https://doi.org/10.1007/s00376-011-0209-2.

    • Search Google Scholar
    • Export Citation
  • Kalnay, E., and Coauthors, 1996: The NCEP/NCAR 40-Year Reanalysis Project. Bull. Amer. Meteor. Soc., 77, 437472, https://doi.org/10.1175/1520-0477(1996)077<0437:TNYRP>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Kikuchi, K., and B. Wang, 2009: Global perspective of the quasi-biweekly oscillation. J. Climate, 22, 13401359, https://doi.org/10.1175/2008JCLI2368.1.

    • Search Google Scholar
    • Export Citation
  • Lacis, A. A., and J. E. Hansen, 1974: A parameterization for the absorption of solar radiation in the Earth’s atmosphere. J. Atmos. Sci., 31, 118133, https://doi.org/10.1175/1520-0469(1974)031<0118:APFTAO>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Lin, A., D. Gu, D. Peng, B. Zheng, and C. Li, 2021: Climatic characteristics of regional persistent heat event in the Eastern China during recent 60 years (in Chinese). J. Appl. Meteor. Sci., 32, 302314, https://doi.org/10.11898/1001-7313.20210304.

    • Search Google Scholar
    • Export Citation
  • Luo, M., and N.-C. Lau, 2017: Heat waves in southern China: Synoptic behavior, long-term change, and urbanization effects. J. Climate, 30, 703720, https://doi.org/10.1175/JCLI-D-16-0269.1.

    • Search Google Scholar
    • Export Citation
  • Madden, R. A., and P. R. Julian, 1971: Detection of a 40–50 day oscillation in the zonal wind in the tropical Pacific. J. Atmos. Sci., 28, 702708, https://doi.org/10.1175/1520-0469(1971)028<0702:DOADOI>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Matsueda, S., and Y. Takaya, 2015: The global influence of the Madden–Julian oscillation on extreme temperature events. J. Climate, 28, 41414151, https://doi.org/10.1175/JCLI-D-14-00625.1.

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  • Fig. 1.

    Composites of SATmax (K) based on HW occurrence over SC from Lin et al. (2021). The box represents the region of SC (106°–120°E, 21°–30°N) defined in this paper.

  • Fig. 2.

    Power spectrum of SATmax anomalies over SC. The dashed curve represents the 95% significant level.

  • Fig. 3.

    Composite 10–20-day filtering SATmax (K) based on the peak value. The positive (negative) value of the x axis means the day after (before) the peak SATmax (zero day). The blue dashed line denotes 0.75 std and the red one −0.5 std.

  • Fig. 4.

    Composites of SATmax (K) from CN05.1 based on different phases. Shading represents the 99% confidence level, and orange and green indicate positive and negative anomalies, respectively. The variable is after 10–20-day filtering. The box in (c) represents the region of SC.

  • Fig. 5.

    As in Fig. 4, but for SATmax (K) and surface winds (m s−1) from the NCEP–NCAR reanalysis.

  • Fig. 6.

    As in Fig. 5, but for 850-hPa vorticity (s−1) and winds (m s−1).

  • Fig. 7.

    As in Fig. 5, but for 500-hPa vertical velocity (Pa s−1).

  • Fig. 8.

    As in Fig. 5, but for surface solar radiation (W m−2).

  • Fig. 9.

    (a) SAT budget and (b) surface radiation and heat fluxes in the developing phase of QBW-HW over SC.

  • Fig. 10.

    Moisture tendency at surface in the developing phase. Shading denotes the composite anomalies exceeding the 99% significance level.

  • Fig. 11.

    Moisture (g kg−1) evolution in different phases of QBW-HW over SC. Shading denotes the composite anomalies exceeding the 99% significance level.

  • Fig. 12.

    Composites of the warm phase of QBW-HW over SC for (a) more and (b) less moisture (g kg−1) at the surface, and (c),(d) the corresponding SAT (K) for (a) and (b), respectively. Shading denotes the composite anomalies exceeding the 99% significance level.

  • Fig. 13.

    SAT budget (K day−1) for (a) more and (b) less surface moisture in the developing phase of QBW-HW over SC.

  • Fig. 14.

    Difference in absorption of (a) shortwave and (b) longwave radiation for more and less near-surface moisture in the warm phase of QBW-HW over SC according to Eqs. (2) and (3) respectively. Shading denotes the fluxes exceeding the 90% significance level.

  • Fig. 15.

    Heating rates (K day−1) evolution in different phases of QBW-HW over SC from Eqs. (7) and (10) based on the moisture anomalies as shown in Fig. 11a.

  • Fig. 16.

    Surface moisture budget in the developing phase of QBW-HW over SC.

  • Fig. 17.

    Summer mean (May–September) soil moisture averaged between 106° and 120°E from (a) NCEP–NCAR reanalysis (m3 m−3) and (b) CPC soil moisture data V2 (mm).

  • Fig. 18.

    Schematic diagram for mechanisms of QBW-HW occurrence over SC. A strong anticyclonic anomaly ① over SC results in a descending flow and more solar radiation ②, which warms the moist soil ③ to increase the evaporation ④. Thus, more moisture ⑤ at the near surface absorbs more solar and longwave radiation ⑥ to heat the SAT ⑦. On the other hand, warmer SAT ⑦ accommodates more water vapor evaporated from the wet soil according to the Clausius–Clapeyron relationship. This is a positive feedback process favoring the occurrence of QBW-HW.

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