GLORIA

GEOMAR Library Ocean Research Information Access

Your email was sent successfully. Check your inbox.

An error occurred while sending the email. Please try again.

Proceed reservation?

Export
Filter
  • Geography  (4)
Material
Publisher
Language
Years
Subjects(RVK)
  • Geography  (4)
  • 1
    In: International Journal of Climatology, Wiley, Vol. 41, No. S1 ( 2021-01)
    Abstract: Although moisture is an important factor affecting precipitation in arid Central Asia (ACA), the water vapour sources and their influencing factors are unclear. This study investigates the moisture sources of extreme precipitation events in summer over Northern ACA and in winter over Southern ACA. The results show that in summer over Northern ACA, the water vapour at low and upper atmospheric levels is mainly transported from the North Atlantic and the Arctic Ocean. In addition, the water vapour in winter over Southern ACA is mainly transported from the North Atlantic and the Northern Indian Ocean. Among these sources, anomalous moisture from the North Atlantic is transported to Northern and Southern ACA along the Mediterranean pressure ridge and the Aral Sea pressure trough. In addition, anomalous moisture in Northern ACA from the Arctic Ocean is closely associated with the negative height anomaly near ACA and with the positive height anomaly in the Mediterranean extending northward to the Arctic Ocean; this results in the high‐latitude moisture transporting along the western edge of the cyclone in Northern ACA. In Southern ACA, low‐latitude water vapour from the Northern Indian Ocean is affected by negative and positive height anomalies in Northwest and Southeast ACA. In addition, significant ascending motion occurs in the study area which provides the necessary dynamic conditions for precipitation. The precipitation variations in Northern and Southern ACA are also related to sea‐surface temperature variations, mainly in the North Atlantic, Arctic Ocean, Mediterranean Sea, and Northern Indian Ocean. Therefore, moisture from the North Atlantic, Arctic Ocean, and the Indian Ocean converge and together influence precipitation development during summer over Northern ACA and in winter over Southern ACA. Highlights Arctic Ocean and North Atlantic moisture together influence summer and autumn precipitation in northern arid Central Asia. Indian Ocean and North Atlantic moisture together influence spring and winter precipitation in southern arid Central Asia. Sea‐surface temperatures in the North Atlantic, Arctic Ocean, Mediterranean Sea, and Northern Indian Ocean have positive or negative effects on precipitation in arid Central Asia.
    Type of Medium: Online Resource
    ISSN: 0899-8418 , 1097-0088
    URL: Issue
    RVK:
    Language: English
    Publisher: Wiley
    Publication Date: 2021
    detail.hit.zdb_id: 1491204-1
    SSG: 14
    Location Call Number Limitation Availability
    BibTip Others were also interested in ...
  • 2
    Online Resource
    Online Resource
    Wiley ; 2021
    In:  International Journal of Climatology Vol. 41, No. 3 ( 2021-03-15), p. 1952-1969
    In: International Journal of Climatology, Wiley, Vol. 41, No. 3 ( 2021-03-15), p. 1952-1969
    Abstract: The reliability of climate model simulations in representing the precipitation changes is one of the preconditions for climate‐change impact studies. However, the observational uncertainties hinder the robust evaluation of these climate model simulations. The goal of the present study is to evaluate the capacities of climate model simulations in representing the precipitation non‐stationarity in consideration of observational uncertainties. The mean of multiple observations from five observational precipitation datasets is used as a reference to quantify the uncertainty of observed precipitation and to evaluate the performance of climate model simulations. The non‐stationarity of precipitation was represented using the mean and variance of annual total precipitation and annual maximum daily precipitation for the 1982–2015 period. The results show that the spatial distributions of annual and extreme precipitation are similar for various observational datasets, while there has less agreement in the variance changes of extreme precipitation. Climate models are capable of representing the spatial distributions of the annual and extreme precipitation amounts at the global scales. In terms of the non‐stationarity, climate model simulations are capable of capturing the large‐scale spatial pattern of the trend in mean for annual precipitation. On the contrary, the simulations are less reliable in reproducing the change of extreme precipitation, as well as the trend of variance for annual precipitation. Overall, climate models are more reliable in simulating the mean of precipitation than the variance, and they are more reliable in simulating annual precipitation than extreme. Besides, the uncertainties of precipitation for both observations and simulations are much larger in monsoon regions than in other regions. This study suggests that considering observational uncertainties is necessary when using observational datasets as the reference to project future climate change and assess the impact of climate change on environments.
    Type of Medium: Online Resource
    ISSN: 0899-8418 , 1097-0088
    URL: Issue
    RVK:
    Language: English
    Publisher: Wiley
    Publication Date: 2021
    detail.hit.zdb_id: 1491204-1
    SSG: 14
    Location Call Number Limitation Availability
    BibTip Others were also interested in ...
  • 3
    In: Cities, Elsevier BV, Vol. 112 ( 2021-05), p. 103120-
    Type of Medium: Online Resource
    ISSN: 0264-2751
    RVK:
    Language: English
    Publisher: Elsevier BV
    Publication Date: 2021
    detail.hit.zdb_id: 2001540-9
    Location Call Number Limitation Availability
    BibTip Others were also interested in ...
  • 4
    Online Resource
    Online Resource
    Elsevier BV ; 2024
    In:  Cities Vol. 149 ( 2024-06), p. 104985-
    In: Cities, Elsevier BV, Vol. 149 ( 2024-06), p. 104985-
    Type of Medium: Online Resource
    ISSN: 0264-2751
    RVK:
    Language: English
    Publisher: Elsevier BV
    Publication Date: 2024
    detail.hit.zdb_id: 2001540-9
    Location Call Number Limitation Availability
    BibTip Others were also interested in ...
Close ⊗
This website uses cookies and the analysis tool Matomo. More information can be found here...