Regional climate models: 30 years of dynamical downscaling

Tapiador, Francisco J.; Navarro, Andrés; Moreno, R. García; Sánchez, José Luis; García‐Ortega, Eduardo

doi:10.1016/j.atmosres.2019.104785

Cited by 112 publications

(54 citation statements)

References 318 publications

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“…This cold bias is present for all seasons, but is greatest in DJF. It may be inherited from the GCMs (Had and NCC), and or be attributable to inadequate representation of physical processes (Remedio et al 2019;Tapiador et al 2020) such as topographic forcing and snow cover, which may be overestimated (Pang et al 2020). A further source of this apparent bias may be related to the fact that the meteorological stations are located in valley areas and the observation data may therefore include a warm bias for high altitude areas (Wang et al 2016).…”

Section: Air Temperaturementioning

confidence: 99%

“…The large spread in simulations of present-day climate demonstrates uncertainties that should be associated with simulated projections (Woldemeskel et al 2016), particularly in the case of precipitation, which is highly variable. Recently, considerable progress has been achieved in high resolution climate modeling, for example in dynamical downscaling over multiple CORDEX (Coordinated Regional Climate Downscaling Experiment) domains (e.g., Jacob et al 2012;Wang et al 2016;Gao and Chen 2017;Ge et al 2019;Giorgi 2019;Niu et al 2019;Tapiador et al 2020). These high-resolution simulations have the advantages of improved representation of orographic features, increased spatial resolution, optimized atmospheric forcing, and a detailed land-surface scheme.…”

Section: Introductionmentioning

confidence: 99%

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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

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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.

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Section: Air Temperaturementioning

confidence: 99%

Section: Introductionmentioning

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

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“…In order to reduce the uncertainty of research results, regional climate models (RCMs) with higher resolution have been rapidly developed. RCMs are usually used in understanding physical processes, short‐term climate prediction, climate change projection, and climate impact assessment (Giorgi, 2006; Xue et al ., 2014; Giorgi and Gutowski, 2015; Tapiador et al ., 2020). One of the most popularly used RCMs is Regional Climate Modelling system (RegCM), which is based on the Fifth‐Generation Pennsylvania State University and University Corporation for Atmospheric Research Mesoscale Model (MM5) (Dickinson et al ., 1989; Giorgi and Bates, 1989) and currently reached version 4.6 (Giorgi et al ., 2011) through improving major physical parameterization schemes (Betts, 1986; Betts and Miller, 1986; Emanuel, 1991).…”

Section: Introductionmentioning

confidence: 99%

Dynamical downscaling simulation of the East Asian summer monsoon in a regional Climate‐Weather Research and Forecasting model

Wang²,

Wang

et al. 2020

Intl Journal of Climatology

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A regional Climate-Weather Research and Forecasting (CWRF) model with a 30-km horizontal resolution was applied to simulate the East Asian summer monsoon (EASM) and climate in China from 1980 to 2016. As compared with observations and reanalysis data, the model can reasonably reproduce the spatial distributions of the climatological mean atmospheric circulation and water vapour transport in East Asia, as well as the seasonal advance and retreat of EASM and rain bands. The correlation coefficient between the EASM circulation index in the simulation and reanalysis is .97. The model can well represent the geographic distributions of summer mean temperature and precipitation over most of China. However, model biases still exist, in particular the skill in the Yangtze-Huaihe River basin is relatively low. The simulated climatological mean temperature and precipitation deviations from observations may be related to the model's systematic circulation biases, with a thicker lower troposphere (i.e., higher temperature between 500 and 1,000 hPa) over most of China (except for the south and southwest) and a thinner one over the coastal oceans in summertime. Compared with the reanalysis, the model overestimates the land-ocean thermal contrast, which causes the South Asian High shifted to the north and east, as well as the subtropical high and tropical convective activity located further north and persisted longer. Consequently, more water vapour transports northward, leading to more precipitation over North China-Northeast China and less precipitation over the Yangtze and Huaihe River basin. Therefore, the enhanced land-ocean thermal contrast may be a major factor for the stronger EASM in the model, and corresponding precipitation and temperature biases in China. This analysis provides important information for further improving model performance in EASM simulation.

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“…Thus, the implications of future climate scenarios in the efficiency of NBSs can be considered only by systematic downscaling of the variables of interest. Downscaling techniques have been widely studied for a multitude of environments and purposes (e.g., [78][79][80][81]). Nevertheless, it is hard to detect common strategies, especially in locations where local effects (e.g., strong vertical gradients, limited lakes) can strongly influence the climate.…”

Section: Discussionmentioning

confidence: 99%

On the Management of Nature-Based Solutions in Open-Air Laboratories: New Insights and Future Perspectives

et al. 2021

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The adoption of Nature-Based Solutions (NBSs) represents a novel means to mitigate natural hazards. In the framework of the OPERANDUM project, this study introduces a methodology to assess the efficiency of the NBSs and a series of Open-Air Laboratories (OALs) regarded as a proof-of-concept for the wider uptake of NBSs. The OALs are located in Finland, Greece, UK, Italy, and Ireland. The methodology is based on a wide modeling activity, incorporated in the context of future climate scenarios. Herein, we present a series of models’ chains able to estimate the efficiency of the NBSs. While the presented models are mainly well-established, their coupling represents a first fundamental step in the study of the long-term efficacy and impact of the NBSs. In the selected sites, NBSs are utilized to cope with distinct natural hazards: floods, droughts, landslides, salt intrusion, and nutrient and sediment loading. The study of the efficacy of NBSs to mitigate these hazards belongs to a series of works devoted to the implementation of NBSs for environmental purposes. Our findings prove that land management plays a crucial role in the process. Specifically, the selected NBSs include intensive forestry; the conversion of urban areas to grassland; dunes; marine seagrass; water retention ponds; live cribwalls; and high-density plantations of woody vegetation and deep-rooted herbaceous vegetation. The management of natural resources should eventually consider the effect of NBSs on urban and rural areas, as their employment is becoming widespread.

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Regional climate models: 30 years of dynamical downscaling

Cited by 112 publications

References 318 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 simulation of the East Asian summer monsoon in a regional Climate‐Weather Research and Forecasting model

On the Management of Nature-Based Solutions in Open-Air Laboratories: New Insights and Future Perspectives

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