Projection of global warming onto regional precipitation over Mongolia using a regional climate model

Sato, Toru; Kimura, Fujio; Kitoh, Akio

doi:10.1016/j.jhydrol.2006.07.023

Cited by 305 publications

(254 citation statements)

References 14 publications

(14 reference statements)

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“…Figure 4 illustrates 11-year JJA-mean precipitation in the observation (APHRODITE), NCEP2, and CNTL. Obviously, precipitation in CNTL successfully captures detailed distribution of precipitation in East Asia that was originally absent in the reanalysis data, which agrees with previous studies (e.g., Xie et al 2006;Sato et al 2007b;De Sales and Xue 2011). NCEP2 significantly overestimates precipitation over southeastern Asia.…”

Section: Verification Of Dynamical Downscaling Of Precipitationsupporting

confidence: 89%

Validating a regional climate model’s downscaling ability for East Asian summer monsoonal interannual variability

Sato

Xue

2012

Clim Dyn

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Performance of a regional climate model (RCM), WRF, for downscaling East Asian summer season climate is investigated based on 11-summer integrations associated with different climate conditions with reanalysis data as the lateral boundary conditions. It is found that while the RCM is essentially unable to improve large-scale circulation patterns in the upper troposphere for most years, it is able to simulate better lower-level meridional moisture transport in the East Asian summer monsoon. For precipitation downscaling, the RCM produces more realistic magnitude of the interannual variation in most areas of East Asia than that in the reanalysis. Furthermore, the RCM significantly improves the spatial pattern of summer rainfall over dry inland areas and mountainous areas, such as Mongolia and the Tibetan Plateau. Meanwhile, it reduces the wet bias over southeast China. Over Mongolia, however, the performance of precipitation downscaling strongly depends on the year: the WRF is skillful for normal and wet years, but not for dry years, which suggests that land surface processes play an important role in downscaling ability. Over the dry area of North China, the WRF shows the worst performance. Additional sensitivity experiments testing land effects in downscaling suggest the initial soil moisture condition and representation of land surface processes with different schemes are sources of uncertainty for precipitation downscaling. Correction of initial soil moisture using the climatology dataset from GSWP-2 is a useful approach to robustly reducing wet bias in inland areas as well as to improve spatial distribution of precipitation. Despite the improvement on RCM downscaling, regional analyses reveal that accurate simulation of precipitation over East China, where the precipitation pattern is strongly influenced by the activity of the Meiyu/ Baiu rainfall band, is difficult. Since the location of the rainfall band is closely associated with both lower-level meridional moisture transport and upper-level circulation structures, it is necessary to have realistic upper-air circulation patterns in the RCM as well as lower-level moisture transport in order to improve the circulation-associated convective rainfall band in East Asia.

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Section: Verification Of Dynamical Downscaling Of Precipitationsupporting

confidence: 89%

Validating a regional climate model’s downscaling ability for East Asian summer monsoonal interannual variability

Sato

Xue

2012

Clim Dyn

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“…The second advantage was also reported by Sato et al (2007). The direct dynamical downscaling is contaminated by the model biases of the GCM.…”

Section: Discussionmentioning

confidence: 64%

“…The conventional method of dynamical downscaling (hereafter; referred to as the direct dynamical downscaling) consists of some numerical simulations using a regional climate model (RCM) assuming the initial and lateral boundary conditions given by the General Circulation Models (GCMs). A new concept of the dynamical downscaling has been introduced by Kimura and Kitoh (2007) and Sato et al (2007). This method is almost the same as the direct dynamical downscaling but the lateral boundary condition of the RCM is a composite of the present reanalysis data and the difference of monthly mean values between the present climate and the future climate simulated by a GCM.…”

Section: Introductionmentioning

confidence: 99%

Downscaling of the Climatic Change in the Mei-yu Rainband in East Asia by a Pseudo Climate Simulation Method

Kawase

Yoshikane

Hara

et al. 2008

SOLA

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This study focuses on the reproducibility of the climatic change in the early summer rainfall in East Asia (Mei-yu rainband) by the Pseudo Climate Simulation (PCS) using a regional climate model. In the PCS, the lateral boundary condition is given by the composite of six hourly reanalysis data and the difference between two decadal climate means. The daily variation on the lateral boundary of the PCS is similar to that of the control hindcast in one decade, but its climate is the same as the other decadal mean. The PCS accurately reproduces the change in the Mei-yu rainband over Southern China between the 1960s and the 1990s, suggesting that the climatic features of the Mei-yu rainband are controlled by the climatic change in a large-scale circulation.The PCS reduces the uncertainty caused by the interannual variability in case of the downscaling of global warming projected by the General Circulation Models (GCMs) even if the number of sample years is the same as that in the conventional dynamical downscaling. The PCS can also exclude model biases in the present climatology reproduced by each GCM. IntroductionTo project the climatic change in a specific area, some methods have been proposed, such as the dynamical and statistical downscaling (Murphy 1999;Wood et al. 2004;Wang et al. 2004). The conventional method of dynamical downscaling (hereafter; referred to as the direct dynamical downscaling) consists of some numerical simulations using a regional climate model (RCM) assuming the initial and lateral boundary conditions given by the General Circulation Models (GCMs). A new concept of the dynamical downscaling has been introduced by Kimura and Kitoh (2007) and Sato et al. (2007). This method is almost the same as the direct dynamical downscaling but the lateral boundary condition of the RCM is a composite of the present reanalysis data and the difference of monthly mean values between the present climate and the future climate simulated by a GCM. Sato el al. (2007) conducted the future climate projection in Mongolia using the new downscaling method.However, it has not been confirmed that this new downscaling method can simulate the past climatic change. The purpose of this study is to investigate the reproducibility of the past climatic change by the new downscaling method. We call it the Pseudo Climate Simulation (PCS) in this paper. We focused on the climatic change in the early summer rainfall over Southern China. Mei-yu rainband in Southern ChinaA large rainband, called the Mei-yu rainband in China, brings a large amount of rainfall over Southern China in summer (Kurashima and Hiranuma 1971), especially over the Yangtze River Basin (YRB) in early summer (June). Recently, the total summer rainfall has been increasing over the YRB (Endo et al. 2005). Gong and Ho (2002) speculated that the extension and intensification of the subtropical northwestern Pacific High (hereafter, Pacific High) since 1980 were closely related to the increase in precipitation using the six-hourly National Center for Environ...

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“…If correct, this interpretation suggests that whilst pollen records indicate drier conditions immediately around Lake Baikal in the mid/late Holocene (Tarasov et al, 2007(Tarasov et al, , 2009, the higher δ 18 Odiatom records imply that long-term trends in precipitation elsewhere in the catchment and in particular to the south of the lake remained relatively constant between the early/late Holocene period, trends that are supported by individual records from northern Mongolian (Wang and Feng, With a relationship established between δ 18 Odiatom and regional Central Asian precipitation around Lake Baikal, records of precipitation from the lake have the potential to aid the development of future forecasts for the region. Models in the Coupled Model Intercomparison Project (CMIP5) are currently not able to confidently predict future changes in Central Asian precipitation (Christensen et al, 2013), but together with regional models they indicate the potential for decreases in precipitation for northern Mongolia and the Lake Baikal catchment, leading to associated reductions in soil moisture and increased vulnerability to drought and fire (Sato et al, 2007;Törnqvist et al, 2014). Data-model comparisons under the Paleoclimate Modelling…”

Section: Assessing the Fidelity Of The Holocene δ 18 O Diatom Recordmentioning

confidence: 99%

Lake Baikal isotope records of Holocene Central Asian precipitation

Swann

Mackay²,

Вологина

et al. 2018

Quaternary Science Reviews

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Climate models currently provide conflicting predictions of future climate change across Central Asia. With concern over the potential for a change in water availability to impact communities and ecosystems across the region, an understanding of historical trends in precipitation is required to aid model development and assess the vulnerability of the region to future changes in the hydroclimate. Here we present a record from Lake Baikal, located in the southern Siberian region of central Asia close to the Mongolian border, which demonstrates a relationship between the oxygen isotope composition of diatom silica (δ 18 Odiatom) and precipitation to the region over the 20 th and 21 st Century. From this, we suggest that annual rates of precipitation in recent times are at their lowest for the past 10,000 years and identify significant long-term variations in precipitation throughout the early to late Holocene interval. Based on comparisons to other regional records, these trends are suggested to reflect conditions across the wider Central Asian region around Lake Baikal and highlight the potential for further changes in precipitation with future climate change.

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Projection of global warming onto regional precipitation over Mongolia using a regional climate model

Cited by 305 publications

References 14 publications

Validating a regional climate model’s downscaling ability for East Asian summer monsoonal interannual variability

Validating a regional climate model’s downscaling ability for East Asian summer monsoonal interannual variability

Downscaling of the Climatic Change in the Mei-yu Rainband in East Asia by a Pseudo Climate Simulation Method

Lake Baikal isotope records of Holocene Central Asian precipitation

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