Simulations of orographic precipitation in the Snowy Mountains of Southeastern Australia

Sarmadi, Fahimeh; Huang, Yi; Thompson, Gregory; Siems, Steven T.; Manton, M. J.

doi:10.1016/j.atmosres.2019.01.002

Cited by 25 publications

(17 citation statements)

References 57 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…This model, and some variants, is operationally used for National Weather Services in France and Spain among other countries. While the short-term forecasting power of weather models is not under discussion, their potential to accurately predict the location and amounts of convective precipitation events in complex terrain is still limited (Ferrari et al 2020;Lorenzo-Lacruz et al 2019;Moya-Álvarez et al 2018;Sarmadi et al 2019). On the other hand, remote sensing atmospheric products such as those provided by ground-based weather radars are increasingly used by meteorological agencies and researchers to improve forecasting and nowcasting, early warning, and as well for mapping and creating thunderstorms climatologies (del Moral et al 2018;Ochoa-Rodriguez et al 2019;Peter et al 2015), and specifically for mountain areas (Germann et al 2006).…”

Section: Introductionmentioning

confidence: 99%

The significance of monitoring high mountain environments to detect heavy precipitation hotspots: a case study in Gredos, Central Spain

Morán-Tejéda

Llorente-Pinto

Barbancho

et al. 2021

Theor Appl Climatol

View full text Add to dashboard Cite

In 2015, a new automatic weather station (AWS) was installed in a high elevation site in Gredos mountains (Central System, Spain). Since then, a surprisingly high number of heavy precipitation events have been recorded (55 days with precipitation over 50 mm, and a maximum daily precipitation of 446.9 mm), making this site a hotspot in Spain in terms of annual precipitation (2177 mm year) and extreme precipitation events. The neighboring stations available in the region with longer data series, including the closest ones, already informed of wet conditions in the area, but not comparable with such anomaly behavior detected in the new station (51% higher). In this study, we present the temporal variability of detected heavy precipitation events in this mountain area, and its narrow relation with atmospheric patterns over the Iberian Peninsula. Results revealed that 65% of the events occurred during advections from West, Southwest, South and cyclonic situations. A regression analysis showed that the precipitation anomaly is mostly explained by the location windward to the Atlantic wet air masses and the elevation. However, the variance explained by the models is rather low (average R2 for all events > 50 mm is 0.21). The regression models underestimate on average a 60% intensity of rainfall events. Oppositely, the high-resolution weather forecast model AROME at 0.025° was able to point out the extraordinary character of precipitation at this site, and the underestimation of observed precipitation in the AWS was about 26%. This result strongly suggests the usefulness of weather models to improve the knowledge of climatic extremes over large areas, and to improve the design of currently available observational networks.

show abstract

Section: Introductionmentioning

confidence: 99%

The significance of monitoring high mountain environments to detect heavy precipitation hotspots: a case study in Gredos, Central Spain

Morán-Tejéda

Llorente-Pinto

Barbancho

et al. 2021

Theor Appl Climatol

View full text Add to dashboard Cite

show abstract

“…Some articles also pointed out that the interannual variation of runoff lacks obvious trend (Gelfan et al, 2020). Usually, models with higher horizontal spatial resolution tend to produce better simulations (Sarmadi et al, 2019;Travis et al, 2016), but they are not shown in runoff simulation. In this paper, CNRM-CM6-1-HR, E3SM-1-0, E3SM-1-1, E3SM-1-1-ECA, EC-Earth3, EC-Earth3-Veg, HadGEM3-GC31-MM and CMCC-CM (CMIP5) were high-resolution models (Table A1 and A2), but they have no high ranking on a global or basin scale (Fig.…”

Section: Discussionmentioning

confidence: 99%

Evaluation and comparison of CMIP6 and CMIP5 models performance in simulating the runoff

Guo¹,

Zhan

Ning³

et al. 2022

Preprint

View full text Add to dashboard Cite

This study evaluates and compares the performance of Coupled Model Intercomparison Project Phase 6 (CMIP6) and CMIP5 in simulating the runoff on global scale and eight large-scale basins, over the period 1981–2005 using percent bias (PBIAS), correlation coefficient (CC), root mean square error (RMSE), Theil-Sen median trend, and the Taylor diagram. The CMIP models are ranked by comprehensive rating index (MR), which is determined by PBIAS, CC and RMSE three metrics. LORA, GRUN and ERA5-Land were selected as reference data sets. LORA was used as the main reference data to evaluate the historical runoff results of CMIP from 1981 to 2012 for three aspects: trend, PBIAS and uncertainty. Results reveal that: (i) CMIP6 models have obviously overvalued on the global and basins (except Amazon and Lena basin), this phenomenon was more prominent in arid and semi-arid areas ( Murray-Darling and Nile basin). (ii) Compared with CMIP5 models, CMIP6 models have less uncertainty on the global scale, but it has not made outstanding progress on the basin scale. (iii) CMIP6 multi‐model ensemble mean (CMIP6_MMEs) has better simulation effect than most individual models, which reduces the uncertainty among different models to some extent. (iv) There were differences in trends and PBIAS between the three reference data sets at both the global and basin scale. However, the interannual fluctuations of the three data sets were basically the same and have high correlation coefficient (except for ERA5 in the world and Nile basin), which shows that LORA data set has high reliability. The global comprehensive rating metric (GR) of CMIP6_MMEs was better than CMIP5_MMEs in all metrics, but this result was not found in eight basins. This shows that CMIP6 models has better effect in simulating global runoff and related diagnostic indicators. Implying further improvements are needs for the runoff simulation capability at the basin scale.

show abstract

“…The complex topography plays a significant role in the inhomogeneous spatial and temporal distributions of rainfall patterns, and most previous researches have shown that the mechanisms of the orographic influences are complex (Smith 1979;Jiang and Smith 2003;Colle 2004;Smith and Barstad 2004;Roe 2005;Rotunno and Houze 2007;Kirshbaum 2011;Houze 2012;Couto et al 2016;DeHart and Houze 2017;Purnell and Kirshbaum 2018;Kang et al 2019). Many features of mountainous topography, including elevation, relief amplitude, slope, and aspect, can initiate, enhance, and modify rainfall and further influence diurnal and spatial variations of rainfall (Weisse and Bois 2001;Burbank et al 2003;Lee et al 2010;Chen et al 2013;White and Paul 2015;Kirshbaum et al 2018;Sarmadi et al 2019). Among the orographic and morphological characteristics, elevation differences perform a considerable important function in the spatial variation of climatic rainfall in mountainous regions (Basist et al 1994;Goovaerts 2000; Johansson and Chen 2003;Sokol and Bližňák 2009;Silverman et al 2013).…”

Section: Introductionmentioning

confidence: 99%

Diurnal variations of rainfall affected by complex topography based on high-density observation in Chongqing over southwest China

Zheng

Zhou

et al. 2022

Theor Appl Climatol

View full text Add to dashboard Cite

Located in the eastern edge of the Sichuan Basin (SCB) in the southwest China, Chongqing is a mountainous region with typical complex topographic features. Using the hourly rainfall observation data of high-density 1686 meteorological stations in Chongqing during warm season from 2009 to 2016, we investigated the diurnal characteristics of precipitation affected by complex topography. The complex mountainous terrain has a significant impact on diurnal variations and distinct regional features of rainfall amount, frequency, and intensity. The stations located in the higher complex mountainous areas have greater rainfall amount, frequency, and intensity than those in the lower surrounding areas. In addition, the detailed characteristics of the rainfall amount and frequency in the four study regions further show that the rainfall amount and frequency significantly increase with the rise of elevation, especially in the area that terrain height sharply increases along the mountain extending direction. The diurnal variation of the rainfall amount is characterized by a bimodal structure with a dominant early-morning peak occurring at approximately 0700 LST (23 UTC) and a weaker secondary late-afternoon peak at approximately 1600 LST (08 UTC), while the rainfall frequency has a single early-morning peak. The terrain height has a significant impact on the proportions of the early-morning rainfall. With the elevation increasing in the four study regions, the proportions of rainfall amount (frequency) that occurs during early-morning period decrease.

show abstract

Simulations of orographic precipitation in the Snowy Mountains of Southeastern Australia

Cited by 25 publications

References 57 publications

The significance of monitoring high mountain environments to detect heavy precipitation hotspots: a case study in Gredos, Central Spain

The significance of monitoring high mountain environments to detect heavy precipitation hotspots: a case study in Gredos, Central Spain

Evaluation and comparison of CMIP6 and CMIP5 models performance in simulating the runoff

Diurnal variations of rainfall affected by complex topography based on high-density observation in Chongqing over southwest China

Contact Info

Product

Resources

About