On the role of horizontal resolution over the Tibetan Plateau in the REMO regional climate model

Xu, Jun; Koldunov, Nikolay; Remedio, Armelle Reca; Sein, Dmitry V.; Zhi, Xiefei; Jiang, Xi; Xu, Min; Zhu, Xiuhua; Fraedrich, Klaus; Jacob, Daniela

doi:10.1007/s00382-018-4085-7

Cited by 50 publications

(32 citation statements)

References 50 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Following the CORDEX experiment design, REMO has been successfully used for long-term climate simulations over multiple domains, such as Europe, Africa, Asia, America, and the Mediterranean (Jacob et al 2012;Remedio et al 2019). The REMO model (version 2015) simulates most climate types relatively well, with a low bias and a high skill score (Remedio et al 2019;Xu et al 2018) have shown that REMO (REMO2015), driven by ERA-Interim reanalysis data, can reliably simulate climate over the Tibetan Plateau. We selected REMO simulations available from the CORDEX experiment for the East Asia domain (Fig.…”

Section: Regional Climate Model Remo and Experiments Designmentioning

confidence: 99%

Historical and future climates over the upper and middle reaches of the Yellow River Basin simulated by a regional climate model in CORDEX

et al. 2021

View full text Add to dashboard Cite

Despite the importance of the Yellow River to China, climate change for the middle reaches of the Yellow River Basin (YRB) has been investigated far less than for other regions. This work focuses on future changes in mean and extreme climate of the YRB for the near-term (2021–2040), mid-term (2041–2060), and far-term (2081–2100) future, and assesses these with respect to the reference period (1986–2005) using the latest REgional MOdel (REMO) simulations, driven by three global climate models (GCMs) and assuming historical and future [Representative Concentration Pathway (RCP) 2.6 and 8.5] forcing scenarios, over the CORDEX East Asia domain at 0.22° horizontal resolution. The results show that REMO reproduces the historical mean climate state and selected extreme climate indices reasonably well, although some cold and wet biases exist. Increases in mean temperature are strongest for the far-term in winter, with an average increase of 5.6 °C under RCP 8.5. As expected, the future temperatures of the warmest day (TXx) and coldest night (TNn) increase and the number of frost days (FD) declines considerably. Changes to mean temperature and FD depend on elevation, which could be explained by the snow-albedo feedback. A substantial increase in precipitation (34%) occurs in winter under RCP 8.5 for the far-term. Interannual variability in precipitation is projected to increase, indicating a future climate with more extreme events compared to that of today. Future daily precipitation intensity and maximum 5-day precipitation would increase and the number of consecutive dry days would decline under RCP 8.5. The results highlight that pronounced warming at high altitudes and more intense rainfall could cause increased future flood risk in the YRB, if a high GHG emission pathway is realized.

show abstract

Section: Regional Climate Model Remo and Experiments Designmentioning

confidence: 99%

Historical and future climates over the upper and middle reaches of the Yellow River Basin simulated by a regional climate model in CORDEX

et al. 2021

View full text Add to dashboard Cite

show abstract

“…In general terms, most of the added value of regional models over land areas in comparison to global coupled models (GCM) simulations can be traced back to a better representation of the orography (e. g. Di Luca et al 2015;Xu et al 2018;Teichmann et al 2013). However, coupled regional models show a clear improvement with respect to both uncoupled atmospheric simulation and the driving global model in regions of intense air-sea interactions or of large-scale feedback (e.g., Cabos et al 2017).…”

Section: Introductionmentioning

confidence: 99%

Dynamical downscaling of historical climate over CORDEX Central America domain with a regionally coupled atmosphere–ocean model

et al. 2018

Self Cite

View full text Add to dashboard Cite

The climate in Mexico and Central America is influenced by the Pacific and the Atlantic oceanic basins and atmospheric conditions over continental North and South America. These factors and important ocean-atmosphere coupled processes make the region's climate a great challenge for global and regional climate modeling. We explore the benefits that coupled regional climate models may introduce in the representation of the regional climate with a set of coupled and uncoupled simulations forced by reanalysis and global model data. Uncoupled simulations tend to stay close to the large-scale patterns of the driving fields, particularly over the ocean, while over land they are modified by the regional atmospheric model physics and the improved orography representation. The regional coupled model adds to the reanalysis forcing the air-sea interaction, which is also better resolved than in the global model. Simulated fields are modified over the ocean, improving the representation of the key regional structures such as the Intertropical Convergence Zone and the Caribbean Low Level Jet. Higher resolution leads to improvements over land and in regions of intense air-sea interaction, e.g., off the coast of California. The coupled downscaling improves the representation of the Mid Summer Drought and the meridional rainfall distribution in southernmost Central America. Over the regions of humid climate, the coupling corrects the wet bias of the uncoupled runs and alleviates the dry bias of the driving model, yielding a rainfall seasonal cycle similar to that in the reanalysis-driven experiments.

show abstract

“…One of the main sources of total PW transport over eastern China is the southwesterly winds from the Bay of Bengal (Xu et al, 2019b). In positive TIOD years ( Figure 5), the TIOD has a positive connection with the amount of water vapor transported to China via the Bay of Bengal (Guan and Yamagata, 2003;Xu et al, 2019a). When the TIOD is in its positive phase, the total PW FIGURE 1 | The first leading SVD modes for (A) the rice yield anomaly pattern, (B) the TIOD-like SST pattern, and (C) the expanded time coefficients.…”

Section: Possible Mechanism Of Impact Of the Tiod-like Sst With The Pmentioning

confidence: 99%

Impacts of Indian Ocean Dipole–Like SST on Rice Yield Anomalies in Jiangsu Province

Koldunov

et al. 2021

Front. Earth Sci.

Self Cite

View full text Add to dashboard Cite

One of the main water vapor sources of eastern China is the Bay of Bengal, over which the circulation is influenced by the Tropical Indian Ocean Dipole (TIOD). The TIOD has a long-lasting effect on weather patterns, which in turn influence the rice yield and quality in eastern China, such as in Jiangsu Province. To identify the main mechanism involved, we perform a detailed investigation of the connections between the TIOD-like sea surface temperature (SST) and the climatic suitability for growing rice, and the subsequent rice yield anomalies, in Jiangsu Province. In particular, we compare the relationships, and identify the underlying mechanisms, of TIOD SST with suitable sunshine duration, temperature and precipitation during the period of rice culture in the province. Singular Value Decomposition (SVD) results show that the TIOD-like SST has a close correlation with the rice yield anomalies, with a temporal correlation coefficient of 0.43 for 53 years, passing the 99% significance level. Furthermore, in the negative TIOD-like SST years, the background circulation weakens the transport effect of the atmospheric river through which water vapor is transported from the Bay of Bengal to eastern China. This decreased amount of transported water vapor decreases the precipitation and total cloud cover in the province. In turn, this significantly increases the sunshine duration, which plays a key role in rice yield anomalies. The increased sunshine duration and higher temperatures lead to positive rice yield anomalies, and vice versa. Our findings highlight that climatic factors, such as TIOD-like SST, have a far-reaching influence on agricultural production (in this case, rice yield), and thus special attention should be paid to interdisciplinary research in the fields of climate and agriculture.

show abstract

On the role of horizontal resolution over the Tibetan Plateau in the REMO regional climate model

Cited by 50 publications

References 50 publications

Historical and future climates over the upper and middle reaches of the Yellow River Basin simulated by a regional climate model in CORDEX

Historical and future climates over the upper and middle reaches of the Yellow River Basin simulated by a regional climate model in CORDEX

Dynamical downscaling of historical climate over CORDEX Central America domain with a regionally coupled atmosphere–ocean model

Impacts of Indian Ocean Dipole–Like SST on Rice Yield Anomalies in Jiangsu Province

Contact Info

Product

Resources

About