October to July precipitation reconstruction for Burabai region (Kazakhstan) since 1744

Akkemik, Ünal; Köse, Nesibe; Kopabayeva, Arailym; Mazarzhanova, Kuralay

doi:10.1007/s00484-020-01870-8

Cited by 6 publications

(4 citation statements)

References 40 publications

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“…To ensure the integrity of the climate data, gridded monthly climate data was also obtained from the Climatic Research Unit (CRU), University of East Anglia, Norwich, UK (Harris et al, 2020) for northern Tajikistan for 1938-2016 (averaged over 38 30 0 -39 30 0 N, 67 30 0 -68 30 0 E). Previous studies have proved the rationality of CRU data in Central Asia (Akkemik et al, 2020;Zhao et al, 2022). The streamflow data of the Kafirnigan River came from the Tortki hydrological station, located at the downstream of the main stream (37 34 0 N, 68 08 0 E, 431 m a.s.l), which is the main national hydrological station.…”

Section: Methodsmentioning

confidence: 99%

Streamflow reconstruction in the Kafirnigan River, Tajikistan since 1568 CE reveals a linkage between southern Central Asian hydrological variation and ENSO

Zulfiyor

Opała‐Owczarek

Chen

et al. 2023

Intl Journal of Climatology

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Long‐term hydroclimate change can provide reliable reference for water resources management in Central Asia. However, only a few palaeohydrological records exist in Tajikistan. To obtain a long‐term perspective on hydrological changes in Tajikistan, we developed, for the first time, a streamflow reconstruction from September of the previous year to June of the current one in the Kafirnigan River basin, based on Juniperus semiglobosa tree‐ring width indices from the Iskanderkul area in northern Tajikistan. The streamflow reconstruction explains 40% of the actual streamflow variance during the period 1939–1993. Spatial correlation analyses with gridded precipitation data indicate that our streamflow reconstruction contains a strong regional hydroclimatic signal for southern Central Asia. The high and low intervals of our streamflow reconstruction are closely related to the interdecadal variations of El Niño‐Southern Oscillation (ENSO). Our reconstructed streamflow is significantly correlated with sea surface temperatures in the eastern equatorial Pacific Ocean and northern Indian Ocean, indicate the existence of remarkable 11‐, 5.6–5.7‐, 4.3‐, 2.6‐, 2.3‐ and 2.0‐year cycles, and suggest a relationship between southern Central Asian streamflow variations and ENSO activity.

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Section: Methodsmentioning

confidence: 99%

Streamflow reconstruction in the Kafirnigan River, Tajikistan since 1568 CE reveals a linkage between southern Central Asian hydrological variation and ENSO

Zulfiyor

Opała‐Owczarek

Chen

et al. 2023

Intl Journal of Climatology

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“…For the other 32 sites that only have chronologies, EPS is not available thus we use the minimum sample size of 5 to determine the first reliable year. Besides ITRDB, 16 tree-ring chronologies that indicate local precipitation or drought from recently published papers are included in our study (Shah et al, 2007;Sass-Klaassen et al, 2008;Arsalani et al, 2018;Arsalani et al, 2015;Chen et al, 2016;Zhang et al, 2017;Pumijumnong et al, 2020;Xu et al, 2015;Buckley et al, 2017;Ukhvatkina et al, 2021;Akkemik et al, 2020;Kostyakova et al, 2017;Kucherov, 2010). Compared with the tree-ring network used in previous studies over the monsoon Asia region (Cook et al, 2010a;Feng et al, 2013;Shi et al, 2018;Shi et al, 2017), a total of 135 ring-width chronologies are added in our study.…”

Section: Proxy Data Preparingmentioning

confidence: 99%

A dataset of standard precipitation index reconstructed from multi-proxies over Asia for the past 300 years

Liu

Zheng²,

Hao³

et al. 2022

Preprint

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Abstract. Proxy-based precipitation reconstruction is essential to study the inter-annual to decadal variability and underlying mechanisms beyond the instrumental period that is critically needed for climate modeling, prediction, and attribution. Based on 3014 annually resolved proxy series mainly derived from tree-ring and historical documents, we present a set of standard precipitation index (SPI) reconstructions for annual (Nov–Oct) covering entire Asia and for wet season (i.e., Nov–Apr for western Asia and May–Oct for the others) with the spatial resolution of 2.5° since 1700. To screen the optimal candidate proxies for SPI reconstruction in each grid from available proxies in its connected region with a homogeneous rainfall regime and similar precipitation variability, a new approach is develop by adopting the grid-location-dependent division derived from the instrumental SPI data. The validation shows that these reconstructions are effective for most of Asia. The assessment of data quality compared with gauge precipitation before calibration time indicates that our reconstruction has high quality to show the precipitation variability in most of the study areas except for few grids in western Russia, the coastal area of southeastern Asia and northern Japan.

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“…The other 128 tree-ring records from ITRDB only have chronologies; EPS is not available, and thus we use the minimum sample size of 5 to determine the first reliable year. Besides ITRDB, 17 tree-ring width chronologies and 3 tree-ring δ 18 O chronologies that indicate local precipitation or drought from recently published papers are included in our study (Shah et al, 2007;Sass-Klaassen et al, 2007;Arsalani et al, 2018Arsalani et al, , 2015Chen et al, 2016;Zhang et al, 2017;Pumijumnong et al, 2020;Xu et al, 2015;Buckley et al, 2017;Ukhvatkina et al, 2021;Akkemik et al, 2020;Kostyakova et al, 2017;Kucherov, 2010;Xu et al, 2013;Borgaonkar et al, 2010). Compared with the tree-ring network used in previous studies over the monsoon Asia region (Cook et al, 2010a;Feng et al, 2013;Shi et al, 2017Shi et al, , 2018, a total of 113 ring-width chronologies are added in our study.…”

Section: Proxy Data Preparationmentioning

confidence: 99%

“…Therefore, the sensitivity of individual proxies to precipitation anomalies has evident regional differences between seasons. In addition, many new proxies achieved in recent years are not utilized in the above-mentioned four gridded reconstructions in monsoon Asia (e.g., Shah et al, 2007;Sass-Klaassen et al, 2007;Arsalani et al, 2018Arsalani et al, , 2015Chen et al, 2016;Zhang et al, 2017;Pumijumnong et al, 2020;Xu et al, 2015;Buckley et al, 2017;Ukhvatkina et al, 2021;Akkemik et al, 2020;Kostyakova et al, 2017;Kucherov, 2010;Xu et al, 2013;Borgaonkar et al, 2010). All of these motivate us to initiate this new gridded (2.5 • × 2.5 • ) reconstruction effort on seasonal to annual precipitation variability over the past 300 years in the whole of Asia, including the western and northern Asia not covered in the four gridded datasets developed in previous studies (Cook et al, 2010a;Feng et al, 2013;Shi et al, 2018Shi et al, , 2017.…”

Section: Introductionmentioning

confidence: 99%

A dataset of standard precipitation index reconstructed from multi-proxies over Asia for the past 300 years

Liu

Zheng

Hao

et al. 2022

Earth Syst. Sci. Data

View full text Add to dashboard Cite

Abstract. Proxy-based precipitation reconstruction is essential to study the inter-annual to decadal variability and underlying mechanisms beyond the instrumental period that is critically needed for climate modeling, prediction and attribution. Based on 2912 annually resolved proxy series mainly derived from tree rings and historical documents, we present a set of standard precipitation index (SPI) reconstructions for each year (November–October), covering the whole of Asia, and for the wet season (i.e., November–April for western Asia and May–October for the others) since 1700, with the spatial resolution of 2.5∘. To screen the optimal candidate proxies for SPI reconstruction in each grid from available proxies in its connected region with a homogeneous rainfall regime and similar precipitation variability, a new approach is developed by adopting the grid-location-dependent division derived from the instrumental SPI data. The validation shows that these reconstructions are effective for most of Asia. The assessment of data quality compared with gauge precipitation before calibration time indicates that our reconstruction has high quality to show the precipitation variability in most of the study areas, except for a few grids in western Russia, the coastal area of southeast Asia and northern Japan. The full dataset can be obtained from https://doi.org/10.57760/sciencedb.01829 (Y. Liu et al., 2022).

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October to July precipitation reconstruction for Burabai region (Kazakhstan) since 1744

Cited by 6 publications

References 40 publications

Streamflow reconstruction in the Kafirnigan River, Tajikistan since 1568 CE reveals a linkage between southern Central Asian hydrological variation and ENSO

Streamflow reconstruction in the Kafirnigan River, Tajikistan since 1568 CE reveals a linkage between southern Central Asian hydrological variation and ENSO

A dataset of standard precipitation index reconstructed from multi-proxies over Asia for the past 300 years

A dataset of standard precipitation index reconstructed from multi-proxies over Asia for the past 300 years

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