1. Introduction
Droughts over East Asia have become an increasing concern in recent years, and have caused compounding ecosystem and societal stresses because of persistently below-normal precipitation. With global warming, both the frequency and duration of droughts show an increasing trend (Zhai et al. 2010; Zhang and Zhou 2015). Northeast China (NEC) is an important grain depot, but it has frequently suffered from severe drought events in recent decades (Yu et al. 2014; Han et al. 2015; Wang and He 2015; S. Wang et al. 2019). This raises an urgent need to unravel underlying processes and mechanisms, especially those relevant to drought early warning (Yuan and Wood 2013).
NEC is located in the northernmost part of East Asian monsoon region, and its summer precipitation is influenced by the external forcings from both the tropics and the middle to high latitudes. El Niño–Southern Oscillation (ENSO) is considered as a principal factor affecting precipitation anomaly over NEC (Sun and Wang 2006). The relationship between spring eastern ENSO and summer rainfall over NEC has been enhanced since 2000, and thus a lower Niño-3 index might correspond to less NEC precipitation, with the tropical Indian Ocean acting as a bridge to link them (Han et al. 2017). ENSO can also modulate abnormal moisture transportation patterns related to the NEC drought (X. Li et al. 2015). At middle and high latitudes, the loss of sea ice over the Barents Sea in spring may lead to NEC drought during July–August, through increasing the snow depth over western Eurasia and triggering the associated polar–Eurasia teleconnection pattern (Li et al. 2018; S. Wang et al. 2019). The intense warming over the European continent and Caspian Sea in spring can strengthen the anticyclonic circulation anomaly over the Tibetan Plateau, and may result in the NEC drought during July–August (Wang and He 2015). The negative phase of summer North Atlantic Oscillation can also lead to a NEC drought event (Sun and Wang 2012).
Besides the remote influences mentioned above exerted by the ocean and sea ice through Rossby waves (Schubert et al. 2011, 2014), the local feedback between soil moisture and atmospheric boundary layer also makes a significant contribution to the maintenance of drought, which intensifies the local anticyclonic circulation anomaly through transporting massive surface sensible heating into atmosphere. During the 2010 Russian heat wave and the 2003 European heat wave events (Fischer et al. 2007a; Dole et al. 2011; Lau and Kim 2012), the sensible heat flux had a strong maintenance and amplification effect on the local positive anomalies of geopotential height, and ultimately resulted in severe droughts. The associated feedback processes are regarded as follows: once the below-normal precipitation induces a negative soil moisture anomaly, the anomaly of land–atmosphere coupling will be initiated and it potentially sustains a long-lasting (from weeks to months) soil moisture deficit (Roundy et al. 2013; Entin et al. 2000). The persistently strong sensible heat flux may heat the low-level atmosphere and lead to extremely high temperature (Miralles et al. 2014; Hirschi et al. 2011), and reduce the evapotranspiration and atmospheric water vapor content. Conversely, the increased atmospheric vapor pressure deficit can exacerbate the soil moisture depletion (Teuling et al. 2013; Zhou et al. 2019). Together with the vapor dissipation due to the large-scale divergent circulation, such positive land–atmosphere feedback sustains the dry conditions of both land and atmosphere, and the heat accumulation strongly modulates the large-scale anomalous anticyclone (Fischer et al. 2007b; Zeng et al. 2019).
The above local feedbacks between land and atmosphere were also verified in coupled regional climate simulations. High-resolution regional simulations can well capture the temporal variability and spatial pattern of drought events (Diasso and Abiodun 2017), and suggest that the memory of the surface dryness is a necessary sources of drought predictability (PaiMazumder and Done 2016).
Besides the local feedback, land–atmosphere coupling also has a nonlocal effect on atmospheric circulation through changing the thermal and dynamical processes in the atmosphere (Duerinck et al. 2016; Xue et al. 2016; Schumacher et al. 2019). On the one hand, the soil moisture anomaly can change the atmospheric baroclinicity at low levels, and thus the changed thermal difference in latitudinal and meridional directions alters the large-scale circulation. For example, anomalous wet soil over West Africa will lead to surface evaporative cooling, and then the modified meridional temperature gradients result in poleward movement of the midlevel African easterly jet, and finally enhance the precipitation (Berg et al. 2017). Across the Yangtze River valley to the North China region, anomalous wet soil in late spring may reduce the land–sea thermal contrast during summer, resulting in the weakened East Asian summer monsoon (Zhang and Zuo 2011). On the other hand, the soil moisture and temperature anomalies lasting for a long period may act as a forcing source of the Rossby wave in westerlies. Warm springtime surface soil temperature in high-altitude areas (e.g., the western United States and the Tibetan Plateau) can trigger stationary waves with a local anticyclonic circulation anomaly located over the plateau area and a cyclone located over the downstream plain regions (Xue et al. 2012, 2018). For the extreme drought event that occurred over the Great Plains of North America in 2012, if an artificial soil dryness is imposed over target regions in the GCM model, a high anomaly will be excited in western North America, and a low anomaly will be formed over eastern North America due to eastward energy dispersion (Koster et al. 2016), which can be considered as a phase-blocking effect of the dry surface on the atmosphere. Further simulations with a stationary wave model show that the phase blocking is closely related to the base flow (climate mean state of circulation) and the local orography (H. Wang et al. 2019). A linear baroclinic model (LBM) was also used to study the contribution of tropical circulation to the central American midsummer drought (Small et al. 2007). However, the nonlocal effects of land–atmosphere coupling during extreme drought events have largely been ignored in middle to high latitudes of East Asia. Zeng et al. (2019) speculated that the anticyclonic anomaly located over the upstream regions [area south of Lake Baikal (ASLB)] was the direct cause during the persistency of the NEC drought, and further analysis indicated that the sensible heating due to land–atmosphere coupling over the ASLB region was a key factor for maintaining this local anticyclonic anomaly (Zeng et al. 2019). While this conclusion is based on diagnostic analysis by using reanalysis data, it is difficult to well isolate land–atmosphere coupling from the thermal forcings due to other factors (e.g., ocean, atmospheric internal variability, etc.). In this study, we aim to answer the following two questions through a series of numerical experiments: 1) Based on a high-resolution regional climate modeling, can the antecedent land–atmosphere coupling over ALSB intensify the consequent drought event occurring over downstream region (NEC) through altering atmospheric circulation? 2) Can the above thermodynamic processes be verified by the simplified modeling (e.g., LBM)?
This paper is arranged as follows: the reanalysis data, numerical models [the Weather Research and Forecasting (WRF) Model and the LBM], and experimental design are described in section 2. In section 3a, convective parameterization schemes in the WRF Model are tested to better simulate the NEC drought event of 2017, and then the long-term control experiment is conducted. In section 3b, the result of sensitivity experiment is analyzed, in which an artificial surface thermal anomaly is imposed in the target regions. In section 3c, we force the LBM with idealized heating anomalies and verify the proposed drought mechanism, where the anomalous heating profiles can mimic the diabatic heating and cooling effect of surface soil on the low-level atmosphere, which correspond to the profiles in the control and sensitivity experiments, respectively, conducted by the WRF Model. A summary and discussion of this study are provided in section 4.
2. Datasets, models, and experimental design
a. Data
Pressure-level atmospheric data and 0–100-cm soil moisture data from 1981 to 2017 are derived from the ERA-Interim reanalysis (Dee et al. 2011). The 6-hourly ERA-Interim atmospheric and oceanic datasets with 0.75° spatial resolution and 37 vertical pressure levels are also used to force the WRF Model. The ERA-Interim geopotential height, atmospheric temperature, meridional and zonal wind velocity, and relative humidity at the pressure levels and SST provide boundary and initial conditions for the WRF simulations, where the boundary conditions are updated every 6 h. ERA-Interim sea ice cover, snow density and depth, soil temperature and moisture at four soil levels, and skin temperature are used to provide initial conditions for the WRF simulations. Monthly gridded precipitation data at 1.0° resolution obtained from NOAA’s Precipitation Reconstruction (PREC) data are used as observation (Chen et al. 2002).
b. WRF Model and experimental design
The Advanced Research version of WRF, version 3.8.1, is applied to explore how land–atmosphere coupling influences the NEC drought through altering atmospheric circulation in this study. WRF is a nonhydrostatic and fully compressible model, which is widely used for forecasting and research at seasonal time scales as well as for land–atmosphere coupling research during drought and heat wave events (Yuan et al. 2012; Zaitchik et al. 2013; Powers et al. 2017; Li et al. 2018). The model configuration and physical schemes used in this study are listed in Table 1 and the model domain is shown in Fig. 1. The WRF experimental setting is summarized briefly in Table 2, where we conduct climatological seasonal simulations (CLIM) covering the period from 1981 to 2010, and the simulations for each year begin from 25 February and end on 31 July. For 2017, we conduct a control simulation (CTL) and two sensitivity simulations (SENS1 and SENS2) that also begin from 25 February and end on 31 July. For all simulations, the results during March–July are used, while the results during February are regarded as model spinup and are dropped (Table 2). When the WRF Model is used to conduct the seasonal-scale regional climate modeling, the spinup time is usually 4–9 days (Gochis et al. 2002; Zhong et al. 2007; Yuan et al. 2012; Wang et al. 2014; W. Li et al. 2015). This is reasonable to make use of the memory of the initial soil moisture anomaly that lasts for a few months (Liang and Yuan 2021). In fact, the operational seasonal forecasting usually neglects the spinup to fully assimilate the information from initial oceanic and land surface anomalies (Saha et al. 2014). This can be achieved through comprehensive data assimilation to approach the realistic initial conditions, and the reanalysis data that assimilate multisource observations are usually used to provide initial conditions for seasonal forecasts or simulations. In this study, we use the ERA-Interim reanalysis to provide initial conditions and regard the first 5 days as the spinup, which is reasonable for CLIM and CTL experiments. For the SENS1 and SENS2 experiments, it is complicated to consider the spinup because we reset the precipitation or soil moisture every day, so the system cannot fully reach the balance. But we speculate that the strong forcing from the land surface anomaly can outweigh the chaos brought by the imbalance, and the influence of the imbalance should be limited. Quantifying the impact of the “spinup imbalance” is beyond the scope of this study, although it might be an interesting topic if a more appropriate experiment could be designed.
Model configuration and physical schemes.
WRF Model domain and the topography height (shaded; m). The area marked by the biggest red box was forced to be wet during March–May of 2017 in the WRF sensitivity simulations, and Northeast China (NEC) and the area south of Lake Baikal (ASLB) were marked by small red boxes.
Citation: Journal of Climate 34, 12; 10.1175/JCLI-D-20-0650.1
Brief summary of the WRF simulations performed in this study.
Our previous diagnosis showed that drought events occurred concurrently over NEC and ASLB in 2017, and suggested that the NEC drought resulted from the anticyclonic circulation anomaly over ASLB, where the land–atmosphere coupling induced sensible heating over ASLB is the maintain factor of this anticyclonic circulation anomaly (Zeng et al. 2019). So an artificial wetness is imposed over ASLB to weaken or eliminate the surface heating effect in the two sensitivity experiments respectively (SENS1 and SENS2; Table 2), and the result of the SENS1 (or SENS2) experiment is subtracted from the CTL experiment (real conditions of 2017; Table 2). Thus, the impact of land–atmosphere coupling on circulation during extreme drought can be well isolated.
The time segment during which the wetness is imposed over ASLB is selected through the following considerations: 1) the soil dryness over ASLB began from March, which occurred earlier than the dryness over NEC, and 2) the interaction between soil moisture and atmospheric circulation over ASLB is more obvious during May–July than during March–April (Zeng et al. 2019). Accordingly, the artificial wetness is imposed during March–May. For every time step in the WRF experiment during March–May, precipitation values over ASLB are artificially multiplied by 5 before they reach the land surface, thereby soil moisture in the land surface model evolves from dry to wet continuously for a period of 3 months. During June–July, the soil moisture is allowed to couple with the atmosphere freely (Table 2). Thus we can explore the nonlocal effect of antecedent land–atmosphere coupling over ASLB on the consequent drought over NEC. In SENS2, for the first time step of every day in the WRF experiment during March–May, the soil moisture values for four soil layers over ASLB are reset to the daily climatological mean values from the CLIM output data. Take 1 March as an example: for each model grid point, we average 30 daily mean soil moisture values on every 1 March from 1981 to 2010, and the averaged value is used to replace the soil moisture value at 0000:00 UTC 1 March 2017 in SENS2 (Table 2). In doing so, the nonlocal effect of upstream dry anomaly on the drought over NEC can be well extracted quantitatively. In addition, we found the surface sensible heating effect on atmosphere is strongest in May in the reanalysis data (Zeng et al. 2019), so the analysis in this study mainly focuses on the precipitation and circulation during May–July.
Before conducting the CLIM, CTL, SENS1, and SENS2 simulations, the cumulus convection schemes are tested because they have important impact on the precipitation simulation (Jankov et al. 2005; Liang et al. 2012; Yuan et al. 2012; Lu et al. 2019). To improve the 2017 NEC drought simulation, we first selected 2012, which has the second most precipitation over NEC since 1981, as a wet year, and then we tested nine cumulus convection schemes (Table 3) for capturing the precipitation difference between 2012 and 2017.
The list of convective parameterization schemes.
c. The LBM and experimental design
In this study, the LBM is run with a T42 horizontal resolution and 20 vertical levels in the sigma coordinate. The LBM experimental design is shown as a schematic diagram in Fig. 2. The basic flow is derived from the May–July climatology of ERA-Interim reanalysis (including U, V, W, T, and surface pressure). The term F′ is the idealized diabatic heating anomalies during May–July of 2017 over ASLB; it mimics the vertical and horizontal distributions of heating in the atmosphere under wet and dry land surface conditions. Three different vertical heating patterns with elliptical horizontal distribution over ASLB are designed to force the LBM (Fig. 2). The first pattern refers to the profile with cooling effect in both lower and upper levels; it corresponds to the result in WRF SENS simulation (Fig. 2). The second pattern refers to the profile with lower heating and upper cooling and corresponds to the result in the WRF CTL simulation (Fig. 2). The third pattern refers to a profile with lower heating and upper zero, which is set to study the synergistic effect of upper cooling and lower heating by comparing with the second experiment (Fig. 2).
A schematic diagram of the LBM experimental design to explore the steady response of circulation to wet and dry land surface conditions under specific basic flows.
Citation: Journal of Climate 34, 12; 10.1175/JCLI-D-20-0650.1
d. Calculations of diabatic heating and associated potential vorticity generation
3. Results
a. The NEC drought in the WRF control simulation
The observational precipitation difference between the chosen dry year (2017) and wet year (2012) of NEC is shown in Fig. 3a, and the differences in simulations with nine convective parameterization schemes are shown in Figs. 3b–j. There are obvious negative precipitation differences over both NEC and ASLB in observation (Fig. 3a), which is consistent with the drought event occurring concurrently over the two regions in 2017. Most schemes can simulate the concurrent negative precipitation anomalies over NEC and ASLB except for the Tiedtke and new simplified Arakawa–Schubert (New SAS) schemes, with positive (negative) anomalies over NEC (ASLB) in Tiedtke (Fig. 3f) and negative (positive) anomalies over NEC (ASLB) in New SAS (Fig. 3i). To find the optimal scheme for simulating a negative precipitation anomaly over NEC, the regional averaged values over NEC in Figs. 3a–j are shown by bar graphs in Fig. 3k. It is found that Kain–Fritsch exhibits the strongest negative value and has the smallest absolute error (0.2 mm day−1). For the regional averaged values of ASLB (Fig. 3l), the Kain–Fritsch scheme also shows the strongest negative value and smallest absolute error (0.12 mm day−1). So we selected Kain–Fritsch as the final convective parameterization scheme for the WRF CLIM, CTL, and SENS experiments.
The differences in May–July mean precipitation (mm day−1) between 2017 (dry year) and 2012 (wet year) from (a) observation and (b)–(j) WRF simulations with nine different convection schemes listed in Table 3. Also shown is the May–July mean precipitation averaged over (k) Northeast China (NEC) and (l) the area south of Lake Baikal (ASLB) marked as boxes in (a). The values above each bar in (k) and (l) are the absolute errors compared with observation.
Citation: Journal of Climate 34, 12; 10.1175/JCLI-D-20-0650.1
The 2-m air temperature (T2m) differences between the dry year (2017) and wet year (2012) of NEC in observation and the optimization test are also shown in Fig. 4. It is found that NEC shows weak positive or negative T2m differences while ASLB shows strong positive differences (Fig. 4a). The model output data present a similar distribution: most schemes show strong positive differences over ASLB and moderate differences over NEC (Figs. 4b–j). The significant positive T2m anomaly is a result of the surface sensible heat anomaly induced by land–atmosphere feedback during drought (Zhou et al. 2019). Here the strong (weak) difference over ASLB (NEC) indicates that more (less) significant land–atmosphere coupling exists over ALSB (NEC) in the 2017 NEC drought. The regional average values (Figs. 4k,l) are consistent with the spatial distributions. It is worth noting that Kain–Fritsch shows the largest positive T2m difference over ASLB (Fig. 4l), which agrees well with the largest negative precipitation difference in Fig. 3l.
As in Fig. 3, but for May–July mean 2-m air temperature (T2m; K).
Citation: Journal of Climate 34, 12; 10.1175/JCLI-D-20-0650.1
Figures 5a and 5b show the observed precipitation and circulation anomaly in May–July during 2017. The negative precipitation anomaly shows a zonal distribution over ASLB and NEC, with a maximum center over the two regions (Fig. 5a). The 500-hPa geopotential height shows positive anomalies over NEC and ASLB and an anticyclonic anomaly center over ASLB (Fig. 5b). In the anomaly field of CTL in comparison with CLIM, the above patterns can be well simulated (Figs. 5c,d).
(a) Observed precipitation anomalies (CMAP; mm day−1) and (b) reanalyzed geopotential height anomalies (ERA-Interim; gpm) at 500 hPa in May–July during 2017. The climatology used for calculating the anomalies is 1981–2010. (c),(d) As in (a) and (b), but for the WRF simulated differences between 2017 (from CTL experiment) and the climatology (1981–2010, from the CLIM experiment).
Citation: Journal of Climate 34, 12; 10.1175/JCLI-D-20-0650.1
Reanalyzed 0–100-cm soil moisture anomalies during March–July of 2017 are shown in Figs. 6a–e. Soil drought occurs over ASLB from March to July of 2017, and becomes more severe over time, which is highly consistent with the simulation of soil moisture anomaly from CTL experiment (Figs. 6f–j). Over NEC, however, WRF simulates weak wet anomalies during March–May and dry anomalies during June–July. This is a little different from reanalysis, in which the dry anomaly appears from April. So both the reanalysis and WRF simulation suggest that the soil dryness over ASLB occurs earlier than that over NEC, which provides a reasonable base for the sensitivity experiments regarding the effect of land–atmosphere coupling over ASLB on downstream drought.
Reanalyzed 0–100-cm soil moisture anomalies (ERA-Interim; m3 m−3) during (a)–(e) March–July 2017, respectively. (f)–(j) As in (a)–(e), but for the WRF-simulated differences between 2017 (from CTL experiment) and the climatology (1981–2010, from the CLIM experiment).
Citation: Journal of Climate 34, 12; 10.1175/JCLI-D-20-0650.1
b. WRF simulation of the responses to imposed land surface wetness
From the above analysis, it is found that negative soil moisture anomaly over ASLB is initialized in March of 2017, indicating that the soil dryness starts to accumulate then. So the SENS experiment aims to weaken this dryness to explore the impact on the downstream areas. SENS is conducted based on the following assumptions: when an artificial wetness is continually imposed over ASLB in WRF model during March–May, the mitigated soil dryness will continue to June–July due to the memory of soil moisture; thus the local surface sensible heating on the low-level atmosphere will be reduced, and the anticyclonic circulation anomaly (Fig. 5d) over ASLB will be weakened during May–July, ultimately relieving the NEC drought.
Figure 7 depicts the precipitation and 500-hPa geopotential height differences by subtracting WRF SENS1 (SENS2) simulation results from the WRF CTL simulation results (i.e., dry case minus wet case). We found that significant negative precipitation anomalies distribute in a narrow and zonal belt from ASLB to NEC both in SENS1 and SENS2 (Figs. 7a,c). The corresponding 500-hPa circulation shows positive geopotential height anomalies (anomalous anticyclone) over the two regions (Figs. 7b,d), especially over ASLB in SENS2 (Fig. 7d), where the spatial distribution is similar to the anomalies of CTL (Fig. 5d).
WRF simulated differences in May–July mean anomalies of (a) precipitation (mm day−1) and (b) geopotential height (gpm) at 500 hPa between the CTL and SENS1 simulations (CTL − SENS1) during 2017. (c),(d) As in (a) and (b), but for the differences between CTL and SENS2 simulations (CTL − SENS2).
Citation: Journal of Climate 34, 12; 10.1175/JCLI-D-20-0650.1
The above results indicate that the antecedent (March–May) upstream (ASLB) soil dryness (soil in the CTL simulation is drier than that in the SENS simulation) is critical for maintaining the intensity of consequent (May–July) drought over the downstream region (NEC), and the atmospheric circulation anomaly may act as a medium. From the longitude–time evolution of circulation anomaly over the latitudinal zone of 40°–60°N (Fig. 8), eastward propagation of positive geopotential height anomalies from 90° to 135°E can be found during June–July, indicating that the atmospheric response began in the middle of June, which obviously exists in both the SENS1 and SENS2 (marked with black lines in Figs. 8a and 8b) simulations. This is also consistent with the conclusion based on reanalysis data (Zeng et al. 2019), where the strongest coupling between atmospheric circulation and soil moisture occurred during June and July over ASLB.
Longitude–time diagram for 15-day running mean of the May–July geopotential height differences averaged over 40°–60°N. (a) Differences between the CTL and SENS1 simulations (CTL − SENS1), and (b) differences between CTL and SENS2 simulations (CTL − SENS2). The black lines in (a) and (b) indicate that the height anomalies propagate from upstream regions (ASLB) to downstream regions (NEC) during June–July.
Citation: Journal of Climate 34, 12; 10.1175/JCLI-D-20-0650.1
Because SENS2 can approximately isolate the contribution of upstream soil moisture anomaly to downstream atmospheric circulation anomaly, we calculated the regional averaged values of Z500 over ASLB and NEC, respectively (Table 4). The values of CTL − CLIM can be considered as the signal forced by all the external factors, while the values of SENS2 − CLIM contains all factors except soil moisture anomalies, so (CTL − CLIM) − (SENS2 − CLIM) can represent the absolute contribution made by soil moisture. The differences in geopotential height between CTL and SENS2 are 17.51 gpm over ASLB and 13.79 gpm over NEC, and the relative contributions are 40.99% over ASLB and 71.56% over NEC (Table 4). We also find the spatial distribution of Z500 in SENS2 − CLIM (Fig. S1a) in the online supplemental material has a similar but weaker pattern to that in CTL − CLIM (Fig. 5d). The spatial distribution of precipitation in SENS2 − CLIM (Fig. S1b) is also similar to that in CTL − CLIM (Fig. 5c), and the relative contributions of soil moisture to precipitation deficit are 72.46% over ASLB and 65.44% over NEC (Table 5). To further investigate the underlying processes, the land surface differences between the CTL and SENS1 (SENS2) experiments are shown in Fig. 9. A remarkable negative soil moisture anomaly exists around Lake Baikal (mainly over ALSB) during May–July, and a less prominent negative anomaly exists over NEC (Figs. 9a,c). Drier soil moisture usually corresponds to more surface sensible heat flux, which is the case over ALSB with strong positive anomaly (Figs. 9b,d). Over NEC, however, there is no pronounced positive anomaly of sensible heat, with most regions dominated by weak negative anomaly (Figs. 9b,d). Thus, the two sensitivity experiments both show a strong surface dryness over ASLB instead of NEC (Fig. 9). This is similar to the results of sensitivity experiments of convection schemes (Figs. 3 and 4), where most schemes show strong negative precipitation anomaly over both ASLB and NEC regions, while showing strong positive T2m anomaly only over ASLB. This indicates that the land–atmosphere coupling induced surface sensible heating is more significant over ASLB than over NEC during the 2017 extreme drought event.
The contribution of ASLB soil moisture anomalies to potential height anomalies at 500 hPa over local (ASLB) and downstream (NEC) regions.
The contribution of ASLB soil moisture anomalies to precipitation deficit over local (ASLB) and downstream (NEC) regions.
WRF simulated differences in May–July mean (a) 0–100-cm soil moisture (m3 m−3) and (b) surface sensible heat flux (W m2) between the CTL and SENS1 simulations (CTL − SENS1) during 2017. (c),(d) As in (a) and (b), but for the differences between CTL and SENS2 simulations (CTL − SENS2).
Citation: Journal of Climate 34, 12; 10.1175/JCLI-D-20-0650.1
From the monthly evolution of soil moisture at various depths (0–10, 10–40, and 40–100 cm; Figs. S2 and S3), both the CTL − SENS1 and CTL − SENS2 results show that a remarkable negative soil moisture anomaly exists over ALSB throughout the drought period (April–July), whereas the negative anomaly starts to present over NEC at the end of the drought (July).
To examine how the surface heating anomaly changes the thermal and dynamic structure of the lower atmosphere, we analyze the Q1 (diabatic heating rate) anomaly at 850 hPa and the PVG (PV generation) anomaly at 750 hPa in atmosphere (Fig. 10). Unlike the differences of CTL minus SENS1 shown in Figs. 7 and 8, here the anomaly is calculated by subtracting the CTL and SENS1 results from the CLIM results respectively, and thus we can explore whether the atmospheric responses to dry and wet surface anomalies are symmetric.
WRF simulated differences in (a) atmospheric diabatic heating rate Q1 (K day−1) at 850 hPa and (c) PV generation [
Citation: Journal of Climate 34, 12; 10.1175/JCLI-D-20-0650.1
In the CTL experiment, anomalous sensible heat is transported into the planetary boundary layer because of the soil dryness over ASLB during May to July, thus a heating source is formed in the lower troposphere at 850 hPa (Fig. 10a). This is more evident in the regional averaged vertical heating profile over ASLB with a maximum at 850 hPa (Fig. 11a). A strong cooling anomaly can also be found at 650 hPa in this profile (Fig. 11a). This is because the upper-level anticyclonic anomaly is usually combined with anomalous sinking motion, which leads to a reduction of cloud amount, thus less surface longwave radiation will be absorbed by the atmosphere (not shown), and Q1 appears as a negative anomaly relative to climatology in the upper level (Fig. 11a). This “upper cooling and lower heating” pattern means that
Vertical profiles of diabatic heating Q1 (K day−1) averaged over the ASLB region marked by black boxes in Fig. 1: (a) the difference between the CTL and CLIM simulations and (b) the difference between SENS1 and CLIM simulations.
Citation: Journal of Climate 34, 12; 10.1175/JCLI-D-20-0650.1
In the SENS1 simulation, when the soil is artificially wetted at an earlier stage (March–May), the soil moisture may act as a cooling source in low-level atmosphere over ASLB during the later stage (Fig. 10b). The vertical profile of Q1 is changed and shows a cooling effect in both upper and lower levels (Fig. 11b), and the vertical gradient (
c. LBM simulation of the responses to idealized diabatic heating anomaly
To isolate the influence of land–atmosphere coupling on NEC drought from the other factors (e.g., midlatitude teleconnection from upstream area, polar sea ice, and tropical SST anomalies, etc.), we have analyzed the result of CTL simulation minus the SENS1 (SENS2) simulation (Figs. 7–9). But these results essentially contain a series of feedback processes related to land–atmosphere interaction, such as the feedback between soil moisture and surface flux, between surface flux and boundary layer, and between boundary layer and cloud in the upper atmospheric level. Thereby, to illustrate the cause-and-effect relationship between the surface anomaly and atmospheric circulation more clearly, here we drive the LBM with an ideal heat source without regard for complex coupling.
According to the above PVG analysis in section 3b, we know the anomalies of diabatic heating in the low-level atmosphere related to surface thermal conditions are symmetric, manifesting as a heating (cooling) anomaly under a dry (wet) soil anomaly (Fig. 11). So in this section, three LBM experiments are performed as mentioned in section 2c, in which the May–July mean atmosphere is forced with idealized diabatic heating anomalies over ASLB, and the anomalies can mimic the atmospheric heating associated with different land surface anomaly relative to climatology. Because the heating or cooling anomalies induced by soil moisture anomalies are closed to the ground, here we set the maximum idealized diabatic heating (cooling) at the level σ = 0.99 in the vertical coordinate (Figs. 12a–c), and this setting is reasonable and in line with previous research (Koster et al. 2016). The profile in Fig. 12a is consistent with that of SENS1 simulation (Fig. 11b), manifested as cooling effect in both upper and lower levels. The linear steady response of 500-hPa geopotential height to this pattern is shown in Fig. 13a, with a negative anomaly over ASLB and NEC and the maximum center over NEC. The profile shown in Fig. 11b is consistent with the atmosphere heating of CTL simulation (Fig. 11a) as well as the reanalysis (now shown), which manifested as a cooling (heating) effect in the upper (lower) level. The steady response to this heating pattern shows a positive anomaly over ASLB and NEC with a maximum center over ASLB (Fig. 13b). Comparing this with the response pattern depicted in Fig. 13a, it shows the same spatial distribution but with a contrary sign. These two responses indicate the atmosphere heating associated with the soil dryness over ASLB can really excite positive potential height anomalies over the downstream region (NEC). To further investigate the role of upper-level cooling mimicked in Figs. 11a and 12b, we force the LBM by an idealized heating with heating in lower level but no anomaly in upper level (Fig. 12c), and find that the response (Fig. 13c) is quite similar to the one forced by the “upper cooling and lower heating” pattern (Fig. 13b). When subtracting the latter (Fig. 13c) from the former (Fig. 13b), we can find a similar but weaker pattern (Fig. 13d) as Fig. 13c shows, indicating that the synergy of upper-level cooling and lower-level heating has a weak positive contribution to the high anomaly over NEC.
Vertical profiles of idealized diabatic heating anomaly imposed in the LBM simulations over the ASLB region. (a) Cooling effect in both upper and lower levels, which corresponds to differences between the SENS1 and CLIM simulations shown in Fig. 11b. (b) Heating effect in the lower level and cooling effect in the upper level, which corresponds to the differences between the CTL and CLIM simulations shown in Fig. 11a. (c) To further investigate the influences of upper cooling effect on the atmospheric circulation, we set a vertical profile that presents a heating effect in the lower level without an anomaly in the upper level. (d) The spatial distribution of imposed idealized heating anomaly (K day−1).
Citation: Journal of Climate 34, 12; 10.1175/JCLI-D-20-0650.1
The responses of geopotential height (gpm) at 500 hPa to the thermal forcing as Fig. 12 shows; the responses are produced by the LBM experiments for (a) Fig. 12a, (b) Fig. 12b, and (c) Fig. 12c. (d) The differences between (b) and (c).
Citation: Journal of Climate 34, 12; 10.1175/JCLI-D-20-0650.1
It should be noted that the LBM response patterns in Figs. 13b and 13c both show an anticyclonic anomaly center over the eastern region of ASLB (to the west of 120°E), which is basically consistent with the result of WRF CTL simulation minus SENS1 (SENS2) simulations (Figs. 7b,d). This phenomenon responds well to the hypothesis below: the circulation anomaly in the CTL simulation contains all impact factors of atmospheric circulation (Fig. 5d) resulting in NEC drought (Fig. 5c), while the values of CTL simulation minus SENS1 (SENS2) simulations only reserve the circulation response due to anomalous land–atmosphere coupling (Figs. 7b,d). The LBM simulated responses also only contain the signal from anomalous thermal forcing related to soil dryness. We notice that the anomaly center over ASLB locates more westward in Fig. 7d (CTL − SENS2) than in Fig. 7b (CTL − SENS1) and in Figs. 13b and 13c (LBM), which is most similar to the circulation anomaly in CTL simulation (Fig. 5d). So Fig. 7d shows the most reasonable response, because the setting of artificial soil wetness in SENS2 is much closer to the climatology reality. The eastward shifts of Z500 positive anomalies in SENS1 and LBM are probably because of the vertical distribution of ideal heating source in LBM, the coarse horizontal resolution of LBM (T42), and the shape or strength of artificial wetness in SENS1.
We also selected all the spring–summer persistent drought events over NEC during 1981–2017, defined as having standardized precipitation anomalies in spring (March–May) and summer (June–July) both lower than −0.4. These droughts occurred in 1987, 1992, 1999, 2000, 2001, 2004, and 2017 and are marked by a black box in Fig. 14a. We found that 2017 is indeed the most extreme year, with the standardized precipitation anomaly lower than −1.0 both in spring and in summer. To further investigate the persistence of forcing from upstream soil moisture anomalies, Fig. 14b shows the monthly evolution of standardized soil moisture anomaly averaged over ASLB in each event. Again, 2017 is a unique year in which the anomalies are negative in every month from March to July. But in other persistent drought years, most values are positive, and the strongest negative anomaly is smaller than −0.1 during March–May, and is small than −0.2 during June–July. These weak negative anomalies are much smaller than those in 2017. Above all, the duration and density of soil dryness over ASLB are unique during March–July of 2017. So our numerical simulations only focus on the 2017 NEC drought event.
(a) The time series of standardized March–May mean (blue) and June–July mean (red) precipitation anomalies averaged over Northeast China (NEC) region marked in Fig. 3a. The black line refers to the reference drought value (−0.4). Seven spring–summer drought events over NEC are marked by black boxes, with standardized precipitation anomalies in spring (March–May) and summer (June–July) both lower than −0.4. (b) The monthly evolution of regional mean standardized anomalies of soil moisture (0–100 cm) over ASLB in the seven drought events.
Citation: Journal of Climate 34, 12; 10.1175/JCLI-D-20-0650.1
4. Summary and discussion
In this study, the influence of upstream land–atmosphere coupling on the 2017 NEC persistent drought is investigated by means of regional climate model and LBM simulations. and the results provide a credible and coherent picture of key processes and mechanisms contributed to the drought: the land–atmosphere coupling over the upstream region (ASLB) in an earlier stage has played an important role in the intensity and persistence of drought occurred over the downstream region (NEC) through changing atmospheric circulation.
The NEC drought began in March and ended in July of 2017, and the land surface and atmosphere coupled with each other more significantly during May–July than March–April (Zeng et al. 2019). So here we mainly focus on the precipitation during May–July. In the WRF CTL simulation, the coherent precipitation and the circulation anomalies over ASLB and NEC can be well reproduced. The WRF simulated negative 0–100-cm soil moisture anomaly over ASLB begins in March, which appears earlier than that over NEC (May). This is basically identical with the evolution of soil moisture in reanalysis data, indicating that the cumulative effect of soil dryness over the upstream region (ASLB) may be initialized at the beginning (March) of 2017 NEC drought. So in the SENS simulation, the soil moisture content over ASLB region is forced to be wet during March–May. Due to the memory of soil moisture, the local surface sensible heating in the low-level atmosphere decreases over ASLB during May–July, and thus the positive anomalies of geopotential height field over ASLB and NEC decrease, manifesting as an anticyclonic circulation anomaly over ASLB and NEC in the difference between the CTL and SENS1 (SENS2) simulations (Figs. 7b,d). Thus the NEC drought strength will decrease without dry land–atmosphere coupling over the upstream ASLB region (Figs. 7a,c). Tables 4 and 5 show that the soil dryness over ASLB contributed 65.44% to the precipitation deficit and 71.56% to the positive anomaly of geopotential height over the downstream region (NEC).
To separate the land forcing on the atmosphere from complex land–atmosphere coupling, the LBM is forced with ideal heat source, which mimics the atmospheric heating associated with dry soil anomaly in WRF CTL simulation. The quasi-steady response of circulation from LBM simulation (Fig. 13b) is highly consistent with the differences between the WRF CTL and WRF SENS simulations (Figs. 7b,d). The LBM simulation also shows that, besides the surface sensible heating, the upper cooling induced by reduced cloud only makes a small contribution to the high anomaly over NEC (Fig. 13d). In brief, our simulations reveal the mechanism through which the upstream land–atmosphere coupling influences the downstream drought, in which the atmospheric circulation acts as a medium.
Besides the “imposed-wetting” simulations in this study, a GLACE-1-type coupling experiment may also be helpful, in which we can compare the results between the simulations with free and inhibited land–atmosphere interaction (Koster et al. 2004). Furthermore, the NEC drought can also be affected by the reduced polar sea ice and snow cover in western Eurasia (S. Wang et al. 2019; Li et al. 2018), so their contributions could be investigated by changing the albedo of underlying surface in numerical model simulations.
How the surface anomalies modulate the atmospheric circulation and contribute to the spread of drought to other areas remain as key questions to uncover the importance of land–atmosphere feedback (Miralles et al. 2019). Our study shows a possible drought self-intensification and self-propagation mechanism, which implies that the influence the local surface anomaly exerts on the free atmosphere at a larger scale is important for sustaining an extreme drought. A reasonable simulation of upstream land–atmosphere coupling is critical for the downstream drought monitoring and forecast, especially for the land–atmosphere coupling hotspots over midlatitude regions, and for droughts at shorter time scales (e.g., flash droughts; Yuan et al. 2019). The multiscale nature of land–atmosphere coupling (Zeng and Yuan 2018) and droughts (Yuan et al. 2020) emphasizes the need for further investigation of their interactions.
Acknowledgments
This work was supported by the National Natural Science Foundation of China (41875105), the National Key R&D Program of China (2018YFA0606002), the Northwest Regional Numerical Forecasting Innovation Team Fund (GSQXCXTD-2020-02), and the Startup Foundation for Introducing Talent of NUIST. We thank Dr. M. Watanabe and Dr. M. Hayashi for providing the LBM code.
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