TY - JOUR
T1 - “Dry gets drier, wet gets wetter”
T2 - A case study over the arid regions of central Asia
AU - Hu, Zengyun
AU - Chen, Xi
AU - Chen, Deliang
AU - LI, Jianfeng
AU - Wang, Shuo
AU - ZHOU, Qiming
AU - Yin, Gang
AU - GUO, Meiyu
N1 - Funding Information:
information Shenzhen International S&T Cooperation, Grant/Award Number: GJHZ20160229194322570; Hong Kong Baptist University, Grant/Award Number: FRG2/14-15/073; Research Grants Council (RGC) of Hong Kong General Research Fund (GRF), Grant/Award Number: HKBU 203913; National Science Foundation of China; Chinese Academy of Sciences, Grant/Award Number: 2015-XBQN-B-20; International CooperationThis study was supported by the Strategic Priority Research Program of Chinese Academy of Sciences, Pan-Third Pole Environment Study for a Green Silk Road (Pan-TPE XDA2006030301), International Cooperation Fund of Ecological Effects of Climate Change and Land Use/Cover Change in Arid and Semiarid Regions of Central Asia in the Most Recent 500 Years (Grant No. 41361140361), the Western Scholars of the Chinese Academy of Sciences (2015-XBQN-B-20), and the National Science Foundation of China (Project 41761144079 41471340), Research Grants Council (RGC) of Hong Kong General Research Fund (GRF) (HKBU 203913) and Hong Kong Baptist University Faculty Research Grant (FRG2/14-15/073). Jing Qian is supported by Shenzhen International S&T Cooperation Project (GJHZ20160229194322570). We thank Mr. Junyi Huang and Mr. Fangli Zhang from the Hong Kong Baptist University for their assistance during this study. Deliang Chen is supported by Swedish VR, STINT, BECC and MERGE.
Funding Information:
This study was supported by the Strategic Priority Research Program of Chinese Academy of Sciences, Pan-Third Pole Environment Study for a Green Silk Road (Pan-TPE XDA2006030301), International Cooperation Fund of Ecological Effects of Climate Change and Land Use/Cover Change in Arid and Semiarid Regions of Central Asia in the Most Recent 500 Years (Grant No. 41361140361), the Western Scholars of the Chinese Academy of Sciences (2015-XBQN-B-20), and the National Science Foundation of China (Project 41761144079 41471340), Research Grants Council (RGC) of Hong Kong General Research Fund (GRF) (HKBU 203913) and Hong Kong Baptist University Faculty Research Grant (FRG2/14-15/073). Jing Qian is supported by Shenzhen International S&T Cooperation Project (GJHZ20160229194322570). We thank Mr. Junyi Huang and Mr. Fangli Zhang from the Hong Kong Baptist University for their assistance during this study. Deliang Chen is supported by Swedish VR, STINT, BECC and MERGE.
Funding Information:
Shenzhen International S&T Cooperation, Grant/ Award Number: GJHZ20160229194322570; Hong Kong Baptist University, Grant/Award Number: FRG2/14-15/073; Research Grants Council (RGC) of Hong Kong General Research Fund (GRF), Grant/Award Number: HKBU 203913; National Science Foundation of China; Chinese Academy of Sciences, Grant/Award Number: 2015-XBQN-B-20; International Cooperation
PY - 2019/2/1
Y1 - 2019/2/1
N2 - The “dry gets drier, wet gets wetter” (DGDWGW) paradigm well describes the pattern of precipitation changes over the oceans. However, it has also been usually considered as a simplified pattern of regional changes in wet/dry under global warming, although GCMs mostly do not agree this pattern over land. To examine the validity of this paradigm over land and evaluate how usage of drought indices estimated from different hydrological variables affects detection of regional wet/dry trends, we take the arid regions of central Asia as a case study area and estimate the drying and wetting trends during the period of 1950–2015 based on multiple drought indices. These indices include the standardized precipitation index (SPI), the standardized precipitation evapotranspiration index (SPEI), the Palmer drought severity index (PDSI) and self-calibrating PDSI (sc_PDSI) with both the Thornthwaite (th) and Penman–Monteith (pm) equations in PDSI calculation (namely, PDSI_th, PDSI_pm, sc_PDSI_th and sc_PDSI_pm). The results show that there is an overall agreement among the indices in terms of inter-annual variation, especially for the PDSIs. All drought indices except SPI show a drying trend over the five states of central Asia (CAS5: including Kazakhstan, Kyrgyzstan, Tajikistan, Turkmenistan and Uzbekistan). The four PDSIs and SPEI reveal a wetting tendency over the northwestern China (NW; including Xinjiang Uygur Autonomous Region and Hexi Corridor). The contrasting trends between CAS5 and NW can also be revealed in soil moisture (SM) variations. The nonlinear wet and dry variations are dominated by the 3–7 years oscillations for the indices. Relationships between the six indices and climate variables show the major drought drivers have regional features: with mean temperature (TMP), precipitation total (PRE) and potential evapotranspiration (PET) for CAS5, and PRE and PET for NW. Finally, our analyses indicate that the dry and wet variations are strongly correlated with the El Niño/Southern Oscillation (ENSO).
AB - The “dry gets drier, wet gets wetter” (DGDWGW) paradigm well describes the pattern of precipitation changes over the oceans. However, it has also been usually considered as a simplified pattern of regional changes in wet/dry under global warming, although GCMs mostly do not agree this pattern over land. To examine the validity of this paradigm over land and evaluate how usage of drought indices estimated from different hydrological variables affects detection of regional wet/dry trends, we take the arid regions of central Asia as a case study area and estimate the drying and wetting trends during the period of 1950–2015 based on multiple drought indices. These indices include the standardized precipitation index (SPI), the standardized precipitation evapotranspiration index (SPEI), the Palmer drought severity index (PDSI) and self-calibrating PDSI (sc_PDSI) with both the Thornthwaite (th) and Penman–Monteith (pm) equations in PDSI calculation (namely, PDSI_th, PDSI_pm, sc_PDSI_th and sc_PDSI_pm). The results show that there is an overall agreement among the indices in terms of inter-annual variation, especially for the PDSIs. All drought indices except SPI show a drying trend over the five states of central Asia (CAS5: including Kazakhstan, Kyrgyzstan, Tajikistan, Turkmenistan and Uzbekistan). The four PDSIs and SPEI reveal a wetting tendency over the northwestern China (NW; including Xinjiang Uygur Autonomous Region and Hexi Corridor). The contrasting trends between CAS5 and NW can also be revealed in soil moisture (SM) variations. The nonlinear wet and dry variations are dominated by the 3–7 years oscillations for the indices. Relationships between the six indices and climate variables show the major drought drivers have regional features: with mean temperature (TMP), precipitation total (PRE) and potential evapotranspiration (PET) for CAS5, and PRE and PET for NW. Finally, our analyses indicate that the dry and wet variations are strongly correlated with the El Niño/Southern Oscillation (ENSO).
KW - central Asia
KW - dry and wet
KW - PDSI
KW - SPEI
KW - SPI
UR - http://www.scopus.com/inward/record.url?scp=85054372660&partnerID=8YFLogxK
U2 - 10.1002/joc.5863
DO - 10.1002/joc.5863
M3 - Journal article
AN - SCOPUS:85054372660
SN - 0899-8418
VL - 39
SP - 1072
EP - 1091
JO - International Journal of Climatology
JF - International Journal of Climatology
IS - 2
ER -