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Nov 24, 2017 - Guizhou, Yunnan, and Guangxi). .... Over the 36 year period from 1980 to 2015, 13 severe drought processes were objectively recognized.
PUBLICATIONS Journal of Geophysical Research: Atmospheres RESEARCH ARTICLE 10.1002/2017JD026867 Key Points: • Standardized Anomalies of net vertical integral water vapor flux can show high correlation with regional pluvial-drought transitions • Vertical patterns of horizontal divergence and vertical motion (ω) anomalies coincide well with the pluvial-drought transitions • The drought portion of some pluvial-drought transition processes can be simulated with previous pluvial anomalies

Supporting Information: • Supporting Information S1 • Table S1 • Table S2 Correspondence to: H. He, [email protected]

Citation: Liu, Z., Lu, G., He, H., Wu, Z., & He, J. (2017). Understanding atmospheric anomalies associated with seasonal pluvial-drought processes using Southwest China as an example. Journal of Geophysical Research: Atmospheres, 122. https://doi.org/10.1002/ 2017JD026867 Received 29 MAR 2017 Accepted 22 OCT 2017 Accepted article online 26 OCT 2017

Understanding Atmospheric Anomalies Associated With Seasonal Pluvial-Drought Processes Using Southwest China as an Example Zhenchen Liu1

, Guihua Lu1, Hai He1

, Zhiyong Wu1

, and Jian He2

1

Institute of Water Problem, College of Hydrology and Water Resources, Hohai University, Nanjing, China, 2Hydrology and Water Resources Investigation Bureau of Jiangsu Province, Nanjing, China

Abstract

Seasonal pluvial-drought transition processes are unique natural phenomena. To explore possible mechanisms, we considered Southwest China (SWC) as the study region and comprehensively investigated the temporal evolution or spatial patterns of large-scale and regional atmospheric variables with the simple method of Standardized Anomalies (SA). Some key procedures and results include the following: (1) Because regional atmospheric variables are more directly responsible for the transition processes, we investigate it in detail. The temporal evolution of net vertical integral water vapor flux (net VIWVF) across SWC, together with vertical SA-based patterns of regional horizontal divergence (D) and vertical motion (ω), coincides well with pluvial-drought transition processes. (2) With respect to large-scale circulation patterns, a well-organized Eurasian (EU) Pattern is one important feature during the pluvial-drought transitions over SWC. (3) Based on these large-scale and regional atmospheric anomalous features, relevant SA-based indices were built, to explore the possibility of simulating drought development using previous pluvial anomalies. As a whole, simulated drought development only with SA-based indices of large-scale circulation patterns does not perform well. Further, it can be improved a lot when SA-based indices of regional D and net VIWVF are introduced. (4) In addition, the potential drought prediction using pluvial anomalies, together with the deep understanding of physical mechanisms responsible for pluvial-drought transitions, need to be further explored.

1. Introduction Drought is an economically and ecologically disruptive natural hazard that profoundly impacts water resources, agriculture, ecosystems, and basic human welfare (Dai, 2011). It is common that drought mechanisms are investigated by comparison with synchronous pluvial events, such as the studies on summer droughts in the Central United States (Mo et al., 1997), the 2011–2014 California drought (Seager et al., 2015), and prolonged meteorological droughts over Mexico (Mendez & Magana, 2010). In addition to comparisons regarding interannual variability, drought and pluvial processes sometimes follow each other. As a representative of drought-pluvial processes, abrupt drought-pluvial transitions over middle to low reaches of the Yangtze River in 2011 have been considerably investigated (Li et al., 2014; Lu et al., 2014; Yang et al., 2013). Since drought-pluvial processes could be considered unique natural phenomena, whether pluvialdrought processes exist in nature is another interesting issue. When we investigated severe seasonal droughts in Southwest China (SWC), season-scale transitions from severe pluvial to severe drought (pluvial-drought processes) were also discovered. In the present study, we focus on the seasonal pluvial-drought transition processes and investigate relevant atmospheric anomalies responsible for their possible mechanisms.

©2017. American Geophysical Union. All Rights Reserved.

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The motivation of this study also originates from the following two points: (1) Pluvial anomalies are usually reversed from the drought-related anomalies. Accordingly, it is possible to use relevant indices of previous pluvial anomalies to simulate the subsequent drought occurrence and development. (2) In terms of the drought mechanism in SWC, synchronous and previous anomalous features have been adequately investigated. Synchronous atmospheric anomalies include large-scale circulation patterns (Li et al., 2011; Liu et al., 2009; Wang et al., 2012; Yang et al., 2012) and regional dynamic and water vapor-related conditions. Previous atmosphere-ocean anomalies and teleconnections, such as the North Atlantic Oscillation, Arctic Oscillation (Barriopedro et al., 2012; Huang et al., 2012; Yang et al., 2012), and El Niño–Southern Oscillation

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(Huang et al., 2012; Yang et al., 2012; Zhang et al., 2013), were investigated due to their influence on droughts by shaping prospective drought-related circulation patterns. As with other previous anomalous signals, near-term atmospheric anomalies during severe pluvial-drought transition processes can also help us understand the mechanism of drought formation. To investigate relevant atmospheric anomalies comprehensively, the temporal evolution of large-scale and regional anomalies is studied in detail. Subsequently, indices of previous pluvial anomalies are defined and used for preliminary exploration in simulating the subsequent drought portion of the pluvial-drought transitions. The stepwise objectives are to (1) identify severe seasonal pluvial-drought processes and analyze spatial characteristics of regional water vapor-related variables using Standardized Anomalies (SA); (2) analyze the temporal evolution of SA of vertically integral water vapor transport at the boundaries and regional atmospheric variables; (3) comprehensively investigate anomalies of large-scale circulation patterns, with composites of drought minus pluvial; and (4) eventually, build SA-based indices to quantify both large-scale and regional anomalies, and explore how these indices simulate the drought portions of the transition processes.

2. Data and Study Area The ERA-Interim reanalysis data set (Dee et al., 2011), provided by the European Center for Medium-Range Weather Forecasts, is used for analyzing regional and large-scale atmospheric anomalies. All these variables are from 1 October 1979 to 31 December 2015, as listed in Table 1. The 3 h (UTC 03, 06, 09, 12, 15, 18 and 21, 24) forecasted evaporation data subset is selected, while the 6 h (UTC 00, 06, 12, and 18) analysis data subset corresponds to the other variables. All data are transformed to a daily time scale by a simple time-weighted mean method. The daily observed precipitation data used, kindly provided by the China Meteorological Data Service Center, come from 824 long-term meteorological stations in China. The selected period is from 1 October 1979 to 31 December 2015. These station-based precipitation data are transformed to a 0.5° × 0.5° gridded data set using the nearest neighbor method of interpolation. Southwest China (SWC) covers an area of approximately 1.12 × 106 km2, made up of four provinces (Sichuan, Guizhou, Yunnan, and Guangxi). Its latitude and longitude ranges vary from 22°N to 32°N and 98°E to 110°E, respectively. The elevation of SWC consistently decreases from northwest to southeast (Figure 1a), including parts of the Qinghai-Tibet Plateau, plains, and basins. Both mean daily precipitation and temperature of SWC (Figure 1b) reach maximum values in July. Summer and early fall (June–October) precipitation amounts account for over 70% of the total precipitation.

3. Methods 3.1. Severe Pluvial-Drought Process Identification and Key Period Division 3.1.1. Three-Month SPI Updated Daily The Standardized Precipitation Index (SPI) (Mckee et al., 1993) for the 3 month time scale (SPI3) is used to describe seasonal pluvial-drought processes in the present study. Traditionally, SPI3 is computed based on monthly precipitation aggregated at the 3 month scale. However, to obtain precise dates of seasonal pluvial-drought processes, we employed a method recommended by the World Metrological Organization (WMO, 2012) to update SPI3 daily, on the basis of a daily running window of 3 month (90 day in practice) area-weighted mean precipitation data. Compared with the traditional method, the essential difference is that the interval for the SPI3 calculation has been extended from 1 month to 1 day, but no other changes relevant to mathematic procedures occur. For example, the SPI3 on 1 April 1999 was calculated by the cumulative precipitation amount from 2 January 1999 to 1 April 1999 and was compared with contemporary historical records of 1980–2015. 3.1.2. Drought (Pluvial) Process Identification and Grade Classification Similar to the methods WMO recommendation (2012), the SPI3-based rules used for grade classification, associated with daily values of drought (pluvial) processes, are shown in Table 2. The drought (pluvial) processes were identified when the daily SPI3 time series was below 0.50 (above +0.50) for more than 60 consecutive days. Each daily SPI3 value for a recognized drought or pluvial process was assigned to the corresponding SPI3 grade (e.g., severely dry). The ratio between the duration of a severely dry (wet)

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Table 1 Characterization of the ERA-Interim Reanalysis Data Subsets Used in the Present Study

Variable Horizontal Divergence

Vertical velocity Temperature Specific humidity Evaporation Total column water vapor Vertical integral of eastward (northward) water vapor flux u component of wind Geopotential height

Units

Abbreviation

1/s

D

Pa/s K kg/kg m of water equivalent 2 kg/m kg/(m s)

ω E

m/s gpm

TCWV Eastward (northward) VIWVF uwnd hgt

Pressure level 100– 1,000 hPa 300– 1,000 hPa Surface

Spatial resolution Horizonal

Vertical

0.75° × 0.75°

100 to 250 hPa by 25 hPa, 300 to 750 hPa by 50 hPa, and 775 to 1000 hPa by 25 hPa

0.5° × 0.5°

-

1.5° × 1.5°

200 hPa 500 hPa

2° × 2°

grade and the length in days of the entire drought (pluvial) process is calculated. When the ratio of one certain drought or pluvial process exceeds 35%, the entire drought (pluvial) process is severe. 3.1.3. Pluvial-Drought Process Identification In terms of every identified severe pluvial process, we investigated whether the start date of some certain severe drought process was included in the following 60 days after the end date of the severe pluvial process. If so, they were chosen and combined with one complete pluvial-drought transition process. 3.1.4. Key Phase Division of Identified Pluvial-Drought Processes To investigate anomalous features during pluvial-drought transition processes in greater detail, we divided each complete pluvial-drought transition process into drought (pluvial) occurrence, persistence, and recovery. During a separate pluvial (drought) portion of the transition process, the first day with SPI3 above +0.5 (below 0.5) indicates the start of the pluvial (drought) process. Similarly, the first day with SPI3 above +1.5 (below 1.5) indicates the start of pluvial (drought) persistence, while the last day with SPI3 above +1.5 (below 1.5) during the pluvial (drought) portion corresponds to the start date of pluvial (drought) recovery. Additionally, the maximum (minimum) SPI3 value during the complete pluvial-drought process refers to the pluvial (drought) peak. 3.2. Atmospheric Anomalies Described With Standardized Anomalies To evaluate atmospheric anomalies objectively, the method of Standardized Anomalies (SA) was adopted in our study, which was originally used to identify high-impact weather events (Grumm & Hart, 2001; Hart &

Figure 1. (a) The location (top right) and topography of Southwest China (SWC). (b) Temporal evolution of mean daily observed precipitation and temperature (1979–2014) averaged over SWC. The thick lines represent daily values, while the light shadows represent the values within ± one standard deviation (Liu et al., 2017).

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Journal of Geophysical Research: Atmospheres Table 2 SPI3-Based Grade Classification Associated With Each Daily Value of Drought and Pluvial Processes Class

Value

Class

Value

Extremely wet Very wet Moderately wet Slightly wet Near normal

2.00 and more 1.50 to 1.99 1.00 to 1.49 0.50 to 0.99 0.49 to 0.49

Slightly dry Moderately dry Severely dry Extremely dry

0.99 to 0.50 1.49 to 1.00 1.99 to 1.50 2.00 and less

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Grumm, 2001). During that same period, Huang et al. independently proposed similar methods named “signal fields” to investigate 500 hPa geopotential height anomalies of heavy rainfall in China (Huang et al., 2002a, 2002b). Subsequently, the method of SA also provides significant values for analysis on extreme precipitation events (Duan et al., 2014; Jiang et al., 2016). The SA of a meteorological variable is defined by Hart and Grumm (Hart & Grumm, 2001), which is described as SA ¼

X μ σ

(1)

where SA is the Standardized Anomalies, X represents the value of a meteorological variable, and μ and σ are the mean value and the standard deviation, respectively. The advantage of SA is its ability to quantify the abnormality of a high-impact weather event (Jiang et al., 2016). Consistent with time scale of SPI3 updated daily, X is the meteorological variable defined as the 90 day mean value located on the last day, updated at 1 day intervals. Accordingly, both μ and σ for the climatological period (1980–2015) are based on these 90 day mean values. In the present study, the calculation of SA was applied to both gridded and regional atmospheric variables listed in section 2. 3.3. The Definition of SA-Based Indices of Atmospheric Variables Since we intend to explore the relationship between regional or large-scale atmospheric anomalies and pluvial-drought processes objectively, SA-based indices are constructed to quantify anomalies. To achieve this, line- or region-averaged values are calculated based on gridded variable values at first. Afterward, 90 day mean line- or region-averaged values and their SA-based indices could be calculated, similar to the method described in section 3.2. The fundamental step is to calculate line- and region-averaged values; atmospheric variables involved can be classified into three categories, as described below. Frist, gridded vertical integral water vapor flux (VIWVF) at four boundaries of SWC are line-averaged along a zonal or meridional line, while SWC is surrounded by the 21°N, 97.5°E, 34.5°N and 110.0°E lines. For instance, indices of northward VIWVF at the southern boundary are line-averaged over gridded values from 97.5°E to 110.0°E along the 21°N line. Further, to better reflect roles of inflow and outflow in the regional water budget, line-averaged indices of VIWVF at the north boundary (34.5°N) and eastward boundary (110.0°E) are multiplied by “1.” Considering comprehensive roles of inflow and outflow, net VIWVF are arithmetically computed based on line-averaged VIWVF across the four boundaries. Second, two water vapor-related variables (namely, E and total column water vapor, TCWV) are simply region averaged on gridded variable values among the practically irregular boundaries of SWC, while the computation method of the regional dynamic variable D is somewhat complex. Gridded level-averaged D values are calculated by level-mean D values above 300 hPa minus level-mean D values below 300 hPa. Afterward, regional D values are also regionally averaged based on gridded level-averaged D values. The third category to illustrate is indices of large-scale circulation patterns. Ten characteristic areas were objectively identified with absolute values of SA above +0.75 (except the area I9 which was above +0.5 SA) in Figure 10. To build indices featuring these anomalous areas, 10 regionally averaged variables are simply

Table 3 The Correspondence Relationship Between Simulation-Targeted Periods and Associated Periods Involved in Calibration Simulated periods after the first day of Pluvial recovery Drought occurrence Drought persistence Drought peak Drought recovery

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Calibrated periods from the first day of pluvial occurrence to the day before Pluvial recovery ✓

Drought occurrence ✓

Drought persistence



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Drought peak



Drought recovery



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Figure 2. Temporal evolution of severe pluvial-drought processes described by SPI3 updated daily. Yellow indicates a severe drought process, whereas blue represents no drought process.

calculated over all the gridded values among these areas referred to by black points in Figure 10. Subsequently, SA-based indices of large-scale circulation patterns are calculated. 3.4. Drought Process Simulation Using Previous Pluvial Anomalies In the present study, whether previous pluvial anomalies can contribute to the simulation of the following drought process is investigated. As shown in Table 3, it is initialized on the first day of different key periods from pluvial recovery, and it is used to simulate the following periods. The simple method of stepwise regression is also used to calibrate the statistical relationship between SPI3 and SA-based indices during the calibration period. Subsequently, with the help of the calibrated stepwise-regression relationship, the SA-based indices associated with the drought portion, which are computed based on gridded values originally retrieved from ERA-Interim reanalysis data sets, are used to simulate the following drought process. In the present study, the SA-based indices come from the large-scale or regional indices shown in section 3.3. Details about selected indicators for calibrated stepwise regression equations and relevant coefficients can be found in Tables S1 and S2 in the supporting information.

4. Results 4.1. Identified Severe Pluvial-Drought Processes Over the 36 year period from 1980 to 2015, 13 severe drought processes were objectively recognized. Among them, four severe pluvial-drought processes were found according to section 3.1. As shown in Figure 2, the shape features of these four SPI3 curves are varied. The transition from pluvial peak to drought peak in 1992 is quite smooth. Further, the 1995 and 2002 severe pluvial-drought processes are relatively quick, whereas the 2008/2009 process is extremely rapid.

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Figure 3. Spatial drought minus pluvial difference of gridded (a–d) SPI3, (e–h) total column water vapor (TCWV), and (i–l) evaporation (E).

4.2. Regional Water Vapor-Related and Dynamic Anomalies 4.2.1. Spatial Drought Minus Pluvial Distribution of E and TCWV Difference As two important hydrological factors, spatial drought minus pluvial difference of TCWV and E were analyzed and compared with that of SPI3, and the difference was based on time-averaged values over the whole drought and pluvial portion. In terms of the 1995 and 2002 processes, spatial TCWV difference (Figures 3f and 3g) corresponds to the negative centers at the northeast corners of SWC. Spatial E difference in 2002 (Figures 3k) indicates the negative center on the point (105°E, 30°N), while spatial E difference in 1995 (Figure 3j) is relatively similar to that of gridded SPI3 in the southern part. In addition, the spatial TCWV difference in the 1992 and 2008/2009 processes shows no obvious relationship with that of the gridded SPI3 difference. 4.2.2. Temporal Evolution of VIWVF SA at Boundaries and Associated SA-Based Net VIWVF VIWVF at different boundaries is an important and direct element for the development of drought processes. For example, less-than-normal northward water vapor transport originating from the ocean contributed to the development of the 2006 (Li et al., 2011; Liu et al., 2009) and 2011 summer droughts (Wang et al., 2012) in SWC. Similarly, the temporal evolution of northward VIWVF SA at the southern boundary is closely related to the pluvial-drought transition processes in the present study. As shown in Figure 4, negative SA appears almost together with drought occurrence in the 2008/2009 process, while it appears before drought occurrence during the other three transition processes. Compared with the temporal evolution of VIWVF SA at the other three boundaries (Figures S1–S3 of support information S1), northward VIWVF SA at the southern boundary is more consistent with the temporal evolution of SPI3 during four transition processes over SWC (Figure 5). Furthermore, both northward VIWVF at the southern boundary and net VIWVF across the four boundaries maintain relatively high consistency with the temporal evolution of pluvial-drought transition

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Figure 4. Temporal evolution of northward vertical integral of water vapor flux (VIWVF) SA at the southern boundary (21°N) of Southwest China (SWC) during four severe pluvial-drought processes. Blue color represents the northward transport.

processes in 1995 and 2008/2009, as shown in Figures 5b and 5d. However, in the 1992 and 2002 processes (Figure 5 and Table 4), the SA-based index of net VIWVF across these four boundaries is still closely related to the temporal evolution of transition processes, while the SA-based index of northward VIWVF at the southern boundary shows no high correlations with them. In terms of synchronous correlation coefficients with SPI3 during these four transition processes (Table 4), the SA-based index of net VIWVF has the highest consistently positive values, while the SA-based index of north VIWVF at the southern boundary shows always positive and relatively high correlations. In addition, the correlations between the SA-based indices of VIWVF at the other three boundaries and SPI3 are sometimes significantly positive or negative. 4.2.3. Temporal Evolution of Regional T and Shum SA Whether air temperature contributes to air saturation is one condition of precipitation formation, which partly indicates that T and Shum are also important for drought formation (Lu et al., 2011, 2014). Based on SA-based analysis of regional T and Shum (Figure 6), regional Shum SA below 600 hPa over SWC get weaker than normal during drought portions of the 1992, 1995, and 2002 processes, while they show positive signals during the pluvial portions. Regional T SA below 600 hPa show positive (negative) signals during the pluvial (drought) portion of the 2002 transition process, which is also typically signal-reversed during the transition process. However, regional T SA below 600 hPa during the 1992 and 1995 transition process are consistently negative. In addition, temporal evolution of regional T and Shum SA during the 2008/2009 process is also unique. During the drought part of the 2008/2009 process (Figure 6d), positive and negative Shum SA appear over 600 hPa and below 700 hPa, respectively. This vertical pattern exists but is weak during the previous pluvial portion. Regional T SA remained consistently positive during the entire process and from 300 hPa to 1,000 hPa. 4.2.4. Temporal Evolution of Regional D and ω SA As shown in Figure 7, it is common that during the drought portion of these four processes, negative D SA occur in the upper level, together with positive anomalies in the lower level. In comparison, this anomalous vertical configuration during the previous pluvial processes is mostly reversed, except for the 2008/2009 process (Figure 7d). The D SA during the 2008/2009 pluvial process are similar to that of drought but weakened. This unique feature is also similar to those of regional T and Shum SA (Figure 6d). Additionally, due to the

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Figure 5. Temporal evolution of SA-based indices of vertical integral of water vapor flux (VIWVF) at the four boundaries and associated net VIWVF across Southwest China (SWC) during severe pluvial-drought processes. They are illustrated with the legend below these figures, and the black curve represents observed SPI3. Since the northward and eastward transport are the positive direction of VIWVF at the north boundary (34.5°N) and eastward boundary (110.0°E), SA-based indices of VIWVF at these two boundaries have been multiplied by “1,” which better reflects the roles of outflows in water budget in SWC.

close relationship between D and ω, extreme ω SA almost appear between the upper and lower D SA during these four transition processes. 4.2.5. Temporal Evolution of SA-Based Indices of Regional Water Vapor-Related and Dynamic Variables Following section 3.3, SA-based indices of regional water vapor-related and dynamic variables were calculated. As shown in Figure 8, compared with the SA-based index of regional net VIWVF analyzed above, that of regional D Table 4 was also relatively consistent with that of SPI3, especially during Synchronous Correlation Coefficients Between SA-Based Indices of VIWVF at the Four the 1995 and 2002 processes. In the 1992 and 2008/2009 processes, Boundaries, Together With Associated Net VIWVF Across Southwest China (SWC), the SA-based index of regional D failed to capture the evolution of and SPI3 During the Four Severe Pluvial-Drought Processes SPI3 during the pluvial part, but it was still highly correlated with Pluvial-drought transition processes SPI3 after the drought occurrence. The good performance of regional net VIWVF and D can also be verified in Table 5, with Elements 1992 1995 2002 2008/2009 significantly and consistently high correlation coefficients during Eastern boundary (110.0°E) 0.41 0.24 0.15 0.62 the four transition processes. Besides, the SA-based index of Southern boundary (21.0°N) 0.45 0.93 0.62 0.76 regional TCWV also showed high correlation with SPI3 during three Northern boundary (34.5°N) 0.56 0.87 0.70 0.14 Western boundary (97.5°E) 0.51 0.64 0.02 0.15 processes, with the exception of the 2008/2009 process. Net VIWVF 0.84 0.94 0.90 0.86 Additionally, regional E showed high correlation with SPI3 during the 1995 process but had no significant correlation with SPI3 Note. The bold values indicate those exceeding the 95% confidence level according to the Student’s t test. during the 2002 and 2008/2009 processes.

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Figure 6. Vertical pressure-time sections of regional temperature (T) SA (contour, 0.5 interval) and regional specific humidity (Shum) SA (shadow) over SWC during four severe pluvial-drought processes.

4.3. Large-Scale Circulation Pattern Anomalies 4.3.1. Drought Minus Pluvial SA Difference In order to investigate where circulation patterns changed during process transitions, drought minus pluvial SA differences were calculated, as shown in Figures 9 and S4 of support information S1. Similar patterns during the 1995 and 2002 processes were investigated in detail. In terms of 200 hPa uwnd SA difference during the 1995 and 2002 processes (shadows in Figures 9a and 9b), a zonal dipole pattern exists in the geographical belt of 20–40°N. This pattern is also explicit in the 1992 process (Figure S4a in support information S1) but is different in the 2008/2009 process (Figure S4b in support information S1). Extremely negative SA centers over the Caspian Sea and Aral Sea are below 2.5 and 3.5 in the 1995 and 2002 processes, respectively. This means that the eastward 200 hPa uwnd over these regions weakens during the transition processes. In contrast, the extremely positive SA of the 200 hPa uwnd around SWC are above +1.5, indicating a strengthened eastward wind. Quite similar patterns of 500 hPa geopotential SA difference fields in the 1995 and 2002 processes are shown in Figures 9c and 9d. In the midlatitude regions, positive SA was strengthened along the 60°E line, while negative anomalies also developed over North China. Accordingly, in the low-latitude zonal belt from 15 to 30°N, negative anomalies over the Arabian Sea were strengthened, with slight positive anomalies in the southwestern corner of SWC. However, these common patterns were implicit in the 1992 and 2008/2009 processes (Figures S4c and S4d). Additionally, difference fields of eastward VIWVF SA showed similar patterns in the 1995 and 2008/2009 processes around SWC (Figures 9e and S4f). Patterns of northward VIWVF SA difference during the 1995, 2002, and 2008/2009 processes (Figures 9g, 9h, and S4h) were quite similar, because negative anomalies occurred to the south of SWC to different degrees. This corresponded to the weakened northward VIWVF at the southern boundary of SWC shown in Figure 4. 4.3.2. Composited Drought Minus Pluvial SA Difference To extract common anomalous features of circulation patterns during the pluvial-drought transition, large-scale SA difference fields were composited (Figure 10). From the point (30°E, 50°N) to the point LIU ET AL.

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Figure 7. Vertical pressure-time sections of SA of regional ω (contour, 0.5 interval) and regional horizontal divergence (D) (shadow) over Southwest China (SWC) during four severe pluvial-drought processes.

(120°E, 15°N), it is evident that anomalous signals are shown as “positive-negative-positive” belts in the composite difference of the 200 hPa uwnd SA field. The 200 hPa uwnd fields near the Caspian Sea and Baikal Lake (Areas I2 and I3 referred to in Figure 10a) weaken. Along the zonal line of 25°N, the East China Sea (the area I6 represents) and India Peninsula (the area I4 represents) experience strengthened eastward wind. Further, compared with the relatively scattered distribution of 200 hPa uwnd SA centers, spatial distribution of 500 hPa hgt SA is quite concentrated. Along the zonal line of 45°N, the large-area gridded positive SA can be found from the Caspian Sea to Barr Kersh Lake (the area I7 refers to), while negative gridded SA appears from Baikal Lake to the East China Sea (the area I10 refers to). This anomalous circulation pattern may help strengthen both the Ural ridge and East Asian Trough. Furthermore, the Eurasian (EU) pattern is obviously seen in the zonal belt of 40–60°N (Figure 10b) during the composite pluvial-drought transition process, which corresponds to its original definition and circulation pattern (Wallace & Gutzler, 1981). 4.4. Drought Process Simulation Using Previous Pluvial Anomalies This section is used to verify whether previous pluvial anomalies can contribute to the simulation of the following drought process. As shown in Figure 11, only large-scale SA-based indices (I1–I10) were used for model calibration and simulation. Initialized at the time of pluvial recovery (see bright red curves in Figure 11), no drought processes can be simulated, and even no significant variables can act as mean best predictors for the stepwise regression in the 2002 process. After the initialization at drought occurrence, the simulated 1992 and 1995 processes indicated the following drought occurrence, regardless of advanced drought peak. When it comes to initialization at drought persistence, it seems that only the following tendency of the 1995 process can be simulated. Furthermore, when initialized at drought peak and recovery (see yellow and light blue curves in Figure 11), only the simulated 1992 process can show the tendency of drought relief, while the other three processes indicate drought persistence. In particular, when initialized at

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Figure 8. Temporal evolution of SA-based indices of regional horizontal divergence (D), net vertical integral of water vapor flux (net VIWVF), total column water vapor (TCWV), and evaporation (E) during severe pluvial-drought processes. These are illustrated below these figures, and the black curve represents observed SPI3.

drought persistence, peak, and recovery, the simulated 2008/2009 process only performed well in drought recovery for a short time, after which it decreased rapidly until the end of the simulation. Based on only SA-based indices of large-scale circulation patterns, these four drought processes were not simulated well. Therefore, SA-based indices of regional D and net VIWVF were introduced to see whether some improvements could happen. As shown in Figure 12, great improvements were made in the simulated 1995, 2002, and 2008/2009 processes. The simulated 1995 process initialized at pluvial recovery could indicate drought occurrence and persistence, while the simulated process initialized at drought persistence can remain consistent with the following tendency very well. The same improvements also happened in the simulated 2002 process after initialization at pluvial recovery, which remained highly consistent with the development of the drought process. In addition, simulation initialized after pluvial recovery in the 2008/2009 process improved a lot and showed high correlations with the observed SPI3 process. These aforementioned Table 5 improvements partly indicate that regional D and net VIWVF are Synchronous Correlation Coefficients Between SA-Based Indices of Regional Water important factors in the development of these pluvial-drought Vapor-Related and Dynamic Variables and SPI3 During the Four Severe Pluvialtransition processes. Drought Processes SA-based indices

1992

1995

2002

2008/2009

TCWV E Net VIWVF D

0.92 0.23 0.84 0.79

0.88 0.71 0.94 0.97

0.83 0.12 0.90 0.88

0.28 0.11 0.86 0.52

Note. The bold values indicate those exceeding the 95% confidence level according to the Student’s t test.

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5. Discussion Seasonal pluvial-drought transition processes identified in Southwest China are interesting natural phenomena. Temporal evolution or spatial patterns of associated atmospheric anomalies are analyzed in the present study. Because of the new attempt, several relevant issues for discussion are as follows.

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Figure 9. SA difference of large-scale circulation patterns between the drought and its previous pluvial process in 1995 and 2002. (a–d) The 200 hPa u component of wind (uwnd) and 500 hPa geopotential height (hgt), respectively. Contours in Figures 9a–9d indicate composite variable values during the drought processes, whereas the shadow represents drought minus pluvial SA difference. Vectors in Figures 9e and 9f indicate the VIWVF difference. (e–h) SA differences for eastward and northward VIWVF, respectively.

The first issue to further illustrate is roles of VIWVF at boundaries and associated net VIWVF during process transitions. During the transition processes in 1995 and 2008/2009, the SA-based index of northward VIWVF at the south boundary seems to be also highly correlated with SPI3 (Figure 5 and Table 4), which plays an important role in the two transition processes. However, pluvial-drought transition is essentially governed by the water budget (net VIWVF across these four boundaries) rather than by VIWVF at any single boundary, although VIWVF SA at one signal boundary sometimes exhibits a close relationship with the transition process. Second, the 2008/2009 pluvial-drought process over Southwest China is distinguished. With respect to regional dynamic conditions, the SA-based pattern transition during the pluvial-drought process does not typically appear. Instead, SA-based patterns of regional D and ω in the previous pluvial part are LIU ET AL.

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Figure 10. Composited drought minus pluvial SA difference fields for the (a) 200 hPa u component of wind (uwnd) and (b) 500 hPa geopotential height (hgt). I1–I10 represent relevant SA-based indices of large-scale circulation pattern variables. Black circles refer to areas filled with positive or negative anomalies, where all the gridded variable values in one anomalous area are regionally averaged for index definition.

similar to those of drought part but are weak (Figure 7d). This means that drought-related SA-based signals appear in the previous pluvial process, which may have some certain relationship with the sharp seasonal pluvial-drought transition. Furthermore, after SA-based indices of regional D and net VIWVF variables are introduced to model calibration and simulation (Figure 12d), drought simulation has been improved a lot. This partly illustrates that regional dynamic and water vapor-related anomalies are relatively important during the 2008/2009 process. In addition, whether no complete matching between dynamic anomalies and seasonal precipitation anomalies actually exists in other regions needs to be further explored. Third, the potential drought prediction is also an interesting issue associated with the present study. Since there are some common regional anomalies of water vapor-related and dynamic variables during four transition processes, it may bring some benefits to potential seasonal drought warning. (1) The northward VIWVF at the southern boundary (Figure 4) almost appears less-than-normal before drought occurrence. It indicates that VIWVF-based anomalies at boundaries may be a potentially qualitative indicator for early drought warning. (2) SA-based indices of regional D have high correlations with SPI3 in the three processes (blue curves in Figure 8 and Table 5). Accordingly, it is feasible to further explore whether the SA-based indices of regional D may also become optional drought indicators. When it comes to operational application in early drought warning, the SA-based indices of regional D can be indirectly retrieved from some forecasted output variables of Climate Prediction Models like the NCEP Climate Forecast System Version 2 (CFSv2) (Saha et al., 2014). In addition, the SA-based indices of net VIWVF, which also show extremely high correlations with transition processes, can be calculated based on the CFSv2 forecasted products. As potential drought indicators calculated, their lead time depends on that of the CFSv2 products. (3) The simple statistical relationship between SA-based atmospheric indices and SPI3 during the previous pluvial processes, forced with the atmospheric anomalies during the following drought processes, can also be used to simulate the drought part. It performs well during the four transition processes in Southwest China, especially when the SA indices of regional D and net VIWVF are introduced (section 4.4). Therefore, with respect to potential drought prediction, the

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Figure 11. SPI3 simulation only using SA-based indices of large-scale circulation patterns (I1  I10) at different initial periods. The initial simulation time refers to the first day of different key periods, illustrated by the colorful lines noted below the figures.

aforementioned statistical relationship can be calculated based on real-time reanalysis data, which are further forced with the forecasted atmospheric anomalies from the CFSv2 products. Compared with potential drought indicators proposed in (2), it is another valuable method for further study. In addition, in case of false drought warning, some supplement research can focus on the pluvial-pluvial or pluvial-normal processes and associated mechanisms. Fourth, it is also necessary to explore whether some certain atmospheric variables always show common anomalous patterns during seasonal pluvial-drought processes in other drought regions. In the study, vertical SA-based patterns of regional D and SA-based spatial patterns of 200 hPa uwnd and 500 hPa hgt fields show some common anomalies during two or three transition processes. With respect to correlations with these seasonal transition processes, SA-based indices of net VIWVF and regional D are almost highly correlated with SPI3. These aforementioned atmospheric variables are likely to have general relationship with regional pluvial-drought transition processes. Therefore, to understand whether more general and determinate relationships exist, we could follow the methods presented in the paper and study SA-based patterns of regional atmospheric variables associated with pluvial-drought transition processes in other drought study regions. Fifth, the physical mechanisms responsible for process transitions need to be further explored. The present study focus on temporal evolution and spatial patterns of atmospheric anomalies associated with the pluvial-drought transitions. However, they are direct and descriptive, and they are not enough for the deep understanding of pluvial-drought transitions. Further study can investigate how regional processes are primarily maintained by large-scale circulations and induced by remote forcing from oceans, such as the influence of temperature advection on regional dynamical processes (Feng et al., 2014).

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Figure 12. Same as Figure 11 but SA-based indices of regional horizontal divergence (D), net vertical integral of water vapor flux (net VIWVF) are introduced for SPI3 calibration and simulation.

6. Conclusions Seasonal pluvial-drought transition is a unique natural phenomenon. In order to study it, we considered Southwest China as the study region, where severe droughts have frequently occurred in recent years. We further investigated the evolution of relevant atmospheric standardized anomalies (SA) during severe pluvial-drought transition processes, and the main results are as follows: (1) Four severe pluvial-drought processes were identified using daily SPI3 updated, which are, namely, the 1992, 1995, 2002, and 2008/2009 processes. (2) TCWV and E differences were spatially consistent with the gridded SPI3 difference more or less, during the 1992, 1995, and 2002 pluvial-drought transition processes. (3) Compared with those of VIWVF at the other boundaries, the SA of northward VIWVF at the southern boundary is closely related to drought development; however, the SA of net VIWVF across these four boundaries is almost consistent with the four pluvial-drought transition processes and potentially acts as a potential drought indicator. (4) In the 1992, 1995, and 2002 processes, the SA of regional horizontal divergence (D) and vertical motion (ω) during droughts were sign-reversed compared with those during previous pluvial episodes. However, during the 2008/2009 pluvial-drought process, regional D and ω anomalies during the pluvial portion were similar to those of drought but were weakened. In addition to net VIWVF, the SA-based index of regional D was also highly correlated with SPI3 during the transition processes. (5) The Eurasian (EU) Pattern is an important feature during the pluvial-drought transition processes in Southwest China. (6) Simulating prospective drought processes was based on the previously calibrated stepwise-regression relationship between these SA-based indices of atmospheric variables and SPI3, forced by observed atmospheric anomalies during the following drought processes. As a whole, simulated development of these four drought processes using only largescale anomalies did not perform well. However, it can be improved a lot when SA-based indices of

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regional dynamic and water vapor variables are introduced. (7) In addition, as the limitation of the present study, the potentially operational application for drought prediction using pluvial anomalies, together with the deeper physical mechanisms responsible for pluvial-drought transitions, are two important issues to explore in the further study. Acknowledgments This work is supported by the Special Public Sector Research Program of Ministry of Water Resources (grants 201301040 and 201501041), the Fundamental Research Funds for the Central Universities (grant 2015B20414), and the National Natural Science Foundation of China (grant 51579065). The authors declare that they have no conflict of financial interest. Links to precipitation data used can be found on the website (http://data.cma.cn/data/ cdcdetail/dataCode/SURF_CLI_CHN_ MUL_DAY_V3.0.html), kindly provided by the China Meteorological Data Service Center. Last but important, all the authors are grateful for the detailed and valuable comments from the anonymous referees, which help improve the manuscript and make us think the issue deeply.

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References Barriopedro, D., Gouveia, C. M., Trigo, R. M., & Wang, L. (2012). The 2009/10 drought in China: Possible causes and impacts on vegetation. Journal of Hydrometeorology, 13(4), 1251–1267. https://doi.org/10.1175/jhm-d-11-074.1 Dai, A. G. (2011). Drought under global warming: A review. WIREs Climate Change, 2(1), 45–65. https://doi.org/10.1002/wcc.81 Dee, D. P., Uppala, S. M., Simmons, A. J., Berrisford, P., Poli, P., Kobayashi, S., … Vitart, F. (2011). The ERA-Interim reanalysis: Configuration and performance of the data assimilation system. The Quarterly Journal of the Royal Meteorological Society, 137(656), 553–597. https://doi.org/ 10.1002/qj.828 Duan, W. L., He, B., Takara, K., Luo, P. P., Nover, D., Yamashiki, Y., & Huang, W. R. (2014). Anomalous atmospheric events leading to Kyushu’s flash floods, July 11–14, 2012. Natural Hazards, 73(3), 1255–1267. https://doi.org/10.1007/s11069-014-1134-3 Feng, L., Li, T., & Yu, W. (2014). Cause of severe droughts in Southwest China during 1951–2010. Climate Dynamics, 43(7-8), 2033–2042. https://doi.org/10.1007/s00382-013-2026-z Grumm, R. H., & Hart, R. (2001). Standardized anomalies applied to significant cold season weather events: Preliminary findings. Weather and Forecasting, 16(6), 736–754. https://doi.org/10.1175/1520-0434(2001)016%3C0736:saatsc%3E2.0.co;2 Hart, R. E., & Grumm, R. H. (2001). Using normalized climatological anomalies to rank synoptic-scale events objectively. Monthly Weather Review, 129(9), 2426–2442. https://doi.org/10.1175/1520-0493(2001)129%3C2426:uncatr%3E2.0.co;2 Huang, R. H., Liu, Y., Wang, L., & Wang, L. (2012). Analyses of the causes of severe drought occurring in Southwest China from the fall of 2009 to the spring of 2010 (in Chinese). Chinese Journal of Atmospheric Sciences, 36(3), 443–457. https://doi.org/10.3878/j.issn.10069895.2011.11111 Huang, J., Yang, Y., & Zhou, G. (2002a). Jump phenomena in the 500 hPa signal field and the occurrence of China’s heavy rainfalls (in Chinese). Chinese Journal of Atmospheric Sciences, 26(5), 625–632. https://doi.org/10.3878/j.issn.1006-9895.2002.05.04 Huang, J. Y., Yang, Y., & Zhou, G. L. (2002b). A study of the 500 hPa-signal field about heavy rainfall in China (in Chinese). Chinese Journal of Atmospheric Sciences, 26, 221–229. Jiang, N., Qian, W. H., Du, J., Grumm, R. H., & Fu, J. L. (2016). A comprehensive approach from the raw and normalized anomalies to the analysis and prediction of the Beijing extreme rainfall on July 21, 2012. Natural Hazards, 84(3), 1551–1567. https://doi.org/10.1007/s11069016-2500-0 Li, Y. H., Xu, H. M., & Liu, D. (2011). Features of the extremely severe drought in the east of Southwest China and anomalies of atmospheric circulation in summer 2006. Acta Meteorologica Sinica, 25(2), 176–187. https://doi.org/10.1007/s13351-011-0025-8 Li, X., Yuan, D., Yin, Z., Li, W., & Xie, Z. (2014). Preliminary analysis of sudden turn of drought and flood in the middle and lower reaches of the Yangtze River during 2011. Climatic and Environmental Research, 19(1), 41–50. Liu, Z. C., Lu, G. H., He, H., Wu, Z. Y., & He, J. (2017). Anomalous features of water vapor transport during severe summer and early fall droughts in Southwest China. Water, 9(4), 244. https://doi.org/10.3390/w9040244 Liu, X. R., Yang, Q., & Cheng, B. Y. (2009). Study on anomalies of atmospheric circulation and water vapor field of the heavy drought in Sichuan-Chongqing region in midsummer 2006. Meteorological Monographs, 35(8), 27–34. Lu, E., Luo, Y., Zhang, R., Wu, Q., & Liu, L. (2011). Regional atmospheric anomalies responsible for the 2009–2010 severe drought in China. Journal of Geophysical Research, 116, D21114. https://doi.org/10.1029/2011JD015706 Lu, E., Liu, S., Luo, Y., Zhao, W., Li, H., Chen, H., … Halpert, M. S. (2014). The atmospheric anomalies associated with the drought over the Yangtze River basin during spring 2011. Journal of Geophysical Research: Atmospheres, 119, 5881–5894. https://doi.org/10.1002/ 2014JD021558 Mckee, T. B., Doesken, N. J., & Kleist, J. (1993). The relationship of drought frequency and duration to time scales. In Proceedings of 8th Conference on Applied Climatology (pp. 179–184). CA. Mendez, M., & Magana, V. (2010). Regional aspects of prolonged meteorological droughts over Mexico and central America. Journal of Climate, 23(5), 1175–1188. https://doi.org/10.1175/2009JCLI3080.1 Mo, K. C., Paegle, J. N., & Higgins, R. W. (1997). Atmospheric processes associated with summer floods and droughts in the central United States. Journal of Climate, 10(12), 3028–3046. https://doi.org/10.1175/1520-0442(1997)010%3C3028:APAWSF%3E2.0.CO;2 Saha, S., Moorthi, S., Wu, X., Wang, J., Nadiga, S., Tripp, P., … E. Becker (2014). The NCEP climate forecast system version 2. Journal of Climate, 27(6), 2185–2208. https://doi.org/10.1175/JCLI-D-12-00823.1 Seager, R., Hoerling, M., Schubert, S., Wang, H. L., Lyon, B., Kumar, A., … Henderson, N. (2015). Causes of the 2011–14 California drought*. Journal of Climate, 28(18), 6997–7024. https://doi.org/10.1175/JCLI-D-14-00860.1 Wallace, J. M., & Gutzler, D. S. (1981). Teleconnections in the geopotential height field during the Northern Hemisphere winter. Monthly Weather Review, 109(4), 784–812. https://doi.org/10.1175/1520-0493(1981)109%3C0784:titghf%3E2.0.co;2 Wang, Z. Y., Ren, F. M., Sun, L., Liu, Y. J., Wang, P. L., Tang, J. Y., … Li, D. (2012). Analysis of climate anomaly and causation in summer 2011. Meteorological Monographs, 38(4), 448–455. World Meteorological Organization (2012). Standardized precipitation index user guide; WMO: Geneva, Switzerland. Retrieved from http:// www.wamis.org/agm/pubs/SPI/WMO_1090_EN.pdf (accessed on 7 June 2017). Yang, J., Gong, D. Y., Wang, W. S., Hu, M., & Mao, R. (2012). Extreme drought event of 2009/2010 over southwestern China. Meteorology and Atmospheric Physics, 115(3-4), 173–184. https://doi.org/10.1007/s00703-011-0172-6 Yang, S. Y., Wu, B. Y., Zhang, R. H., & Zhou, S. W. (2013). Relationship between an abrupt drought-flood transition over mid-low reaches of the Yangtze River in 2011 and the intraseasonal oscillation over mid-high latitudes of East Asia. Acta Meteorologica Sinica, 27(2), 129–143. https://doi.org/10.1007/s13351-013-0201-0 Zhang, W., Jin, F.-F., Zhao, J.-X., Qi, L., & Ren, H.-L. (2013). The possible influence of a nonconventional El Niño on the severe autumn drought of 2009 in Southwest China. Journal of Climate, 26(21), 8392–8405. https://doi.org/10.1175/jcli-d-12-00851.1

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