Verification of daily precipitation amount forecasts in Armenia by ERA‐Interim model

Gevorgyan, Artur

doi:10.1002/joc.3621

Cited by 21 publications

(18 citation statements)

References 7 publications

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“…In particular, the selected GCMs should cover as much as possible the range of different responses of greenhouse gas (GHG) forcing by the full ensemble of available GCMs. The spatial resolution of models is considered as a very important issue for the simulation of temperature, precipitation, wind and other meteorological elements over the study region characterized by mountain topography as was shown both in this and previous works (Gevorgyan 2012;Gevorgyan and Melkonyan 2014;Elguindi et al 2011). Apart from annual and seasonal temperature changes, it is also important to focus on the change in precipitation, extreme temperatures and precipitation on a daily scale.…”

Section: Conclusion and Discussionmentioning

confidence: 93%

“…The terrain across the region ranges from flat semi-desert to moist rugged mountain regions. Due to highly variable atmospheric circulation regime and significant topography, the study region is characterized by great spatiotemporal variability in temperature and precipitation (Gevorgyan 2012;Gevorgyan 2013;Gevorgyan 2014). representing a major challenge for the assessment of climate change for this region.…”

Section: Introductionmentioning

confidence: 99%

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An assessment of observed and projected temperature changes in Armenia

et al. 2015

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Future changes in annual and seasonal temperature over Armenia based on the Community Climate System Model 4 (CCSM4) output data from newly developed dataset of phase 5 of the Coupled Model Intercomparison Project (CMIP5) have been analysed. The results of this study suggest that Armenia will experience significant temperature increase in the twenty-first century. Moreover, the greatest warming is expected in the summertime and can reach 4-6°C under representative concentration pathways (RCP)8.5 for the middle and end of the century. However, observations show significant variability and seasonal amplitude in temperature regime which is peculiar to mountain regions located in mid-latitudes. It was shown that strong cold wave events can be directly followed by prolonged hot days within one year in Armenia. The CCSM4 model has substantial deficiencies in simulating the regional climate over Armenia. Validation results indicate the largest errors (root-mean-square error (RMSE)) in the representation of winter temperatures. There is also significant uncertainty in projected temperature change patterns in Armenia over the twenty-first century. However, the CCSM4 model becomes more confident in the prediction of temperature increase over Armenia toward the end of the century.

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Section: Conclusion and Discussionmentioning

confidence: 93%

Section: Introductionmentioning

confidence: 99%

An assessment of observed and projected temperature changes in Armenia

et al. 2015

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“…Given that China is located south of 55°N, the contributions of oceanic and terrestrial evaporation to atmospheric moisture over China can be reliably quantified. The examination treats ERA-Interim data as perfect, but there can be some bias depending on the area under (Zhao et al, 2012;Gevorgyan, 2013). Considering possible bias in re-analysis data, the values of atmospheric moisture and the contributions of oceanic and terrestrial evaporation may not be exact, but are reasonable (van der Ent et al, 2010;van der Ent and Savenije, 2011;Keys et al, 2012).…”

Section: Examination Of the Water Accounting Modelmentioning

confidence: 98%

“…The input data are retrieved from the ERA-Interim re-analysis dataset that assimilates information from multiple observational and remote sensing data sources (Gevorgyan, 2013;Sun and Wang, 2013). The ERA-Interim dataset provided by the European Center for Medium-range Weather Forecasts (ECMWF, http://apps.ecmwf.int/datasets/) covers the period from 1979 through the present.…”

Section: Water Accounting Modelmentioning

confidence: 99%

“…Re-analysis data generated by assimilation of observational and remote sensing data provides a reliable representation of the global water cycle (Gevorgyan, 2013;Sun and Wang, 2013). Treating ERA-Interim data as perfect, the procedure of examination is as follows: 1) the study region Ω is set as the ocean and transport of moisture originating from oceanic evaporation is analysed.…”

Section: Examination Of the Water Accounting Modelmentioning

confidence: 99%

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Source of atmospheric moisture and precipitation over China’s major river basins

Zhao

et al. 2015

Front. Earth Sci.

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Oceanic evaporation via the East Asian Monsoon (EAM) has been regarded as the major source of precipitation over China, but a recent study estimated that terrestrial evaporation might contribute up to 80% of the precipitation in the country. To explain the contradiction, this study presents a comprehensive analysis of the contribution of oceanic and terrestrial evaporation to atmospheric moisture and precipitation in China's major river basins. The results show that from 1980 to 2010, the mean annual atmospheric moisture (precipitable water) over China was 13.7 mm, 39% of which originates from oceanic evaporation and 61% from terrestrial evaporation. The mean annual precipitation was 737 mm, 43% of which originates from oceanic evaporation and 57% from terrestrial evaporation. Oceanic evaporation makes a greater contribution to atmospheric moisture and precipitation in the East Asian Monsoon Region in South and East China than terrestrial evaporation does. Particularly, for the Pearl River and southeastern rivers, oceanic evaporation contributes approximately 65% of annual precipitation and more than 70% of summer precipitation. Meanwhile, terrestrial evaporation contributes more precipitation in northwest China due to the westerly wind. For the northwestern rivers, terrestrial evaporation from the Eurasian continents contributes more than 70% of precipitation. There is a linear relation between mean annual precipitation and the contribution of oceanic evaporation to precipitation, with a correlation coefficient of 0.92, among the ten major river basins in China.

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A Case Study of Low‐Level Jets in Yerevan Simulated by the WRF Model

Gevorgyan

2018

JGR Atmospheres

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Capabilities of high‐resolution (3 km) Weather Research and Forecasting (WRF) simulations to reproduce topographically induced mountain‐valley winds and low‐level jets (LLJs) in Yerevan have been evaluated using high‐frequency observational and modeled data. High sensitivities of simulations of near‐surface winds and LLJ characteristics observed on 4 July 2015 to both boundary layer and initial and lateral boundary conditions setup have been demonstrated. Among the nine tested planetary boundary layer (PBL) parameterization schemes the MYJ, QNSE, and TEMF PBL schemes showed greater skill in simulation of near‐surface valley winds over Yerevan, while the other PBL schemes tend to significantly underestimate the strength of valley winds, with the BouLac PBL scheme being the worst performer. Most of PBL schemes simulate well‐defined LLJs in Yerevan associated with evening valley winds. The simulated jet cores are mostly located between 150 and 250 m above ground with magnitudes varying from 12 to 21 m s−1. However, the intensity of the observed nocturnal LLJ in Yerevan (located at 110 m above ground) is strongly underestimated by most of the WRF runs while the Shin and Hong and YSU PBL schemes simulate nocturnal LLJs higher than the observed LLJ. The WRF runs initiated with newly released European Centre for Medium‐Range Weather Forecasts ERA‐5 data set showed improved simulation of near‐surface winds and nighttime potential temperatures in Yerevan relative to those forced by the Global Forecast System fields.

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Verification of daily precipitation amount forecasts in Armenia by ERA‐Interim model

Cited by 21 publications

References 7 publications

An assessment of observed and projected temperature changes in Armenia

An assessment of observed and projected temperature changes in Armenia

Source of atmospheric moisture and precipitation over China’s major river basins

A Case Study of Low‐Level Jets in Yerevan Simulated by the WRF Model

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