Surface and tropospheric temperature trends in Armenia

Gevorgyan, Artur

doi:10.1002/joc.3928

Cited by 16 publications

(16 citation statements)

References 39 publications

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“…Recent studies considered climate change and its impacts on hydrological balance in Armenia and Southern Caucasus, The Black and Caspian Seas basins (Gevorgyan 2014;Melkonyan and Shindyan 2009; Regional Climate Change Impacts Study for the South Caucasus Region 2011; SNCCC 2010; Zhang et al 2005;Elguindi et al 2011;Melkonyan and Asadoorian 2013). The results showed significant increasing trends for mean annual temperature, mean daily minimum temperature and mean daily maximum temperature (Vardanyan et al 2013; Regional Climate Change Impacts Study for the South Caucasus Region 2011).…”

Section: Introductionmentioning

confidence: 86%

“…Mean annual temperature have increased by rate of 0-1.5°C for 1935-2008 period. A very clear signal of warming is detected at most stations of Armenia and at 850 hPa level for summer and autumn seasons (Gevorgyan 2014). Furthermore, the accelerated warming can be seen in the recent past period which leaves little chance that the warming trends in Armenia are due solely to natural variability.…”

Section: Introductionmentioning

confidence: 97%

“…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%

“…winter, spring, autumn and summer. Thus, it is of great importance for Armenia to examine the seasonal temperature changes (Gevorgyan 2014).…”

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: Introductionmentioning

confidence: 86%

Section: Introductionmentioning

confidence: 97%

Section: Introductionmentioning

confidence: 99%

“…winter, spring, autumn and summer. Thus, it is of great importance for Armenia to examine the seasonal temperature changes (Gevorgyan 2014).…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

An assessment of observed and projected temperature changes in Armenia

et al. 2015

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“…While mean temperatures across India rose by 0.24°C per decade between 1971 and 2009 (Bapuji Rao et al 2014), in contrast, at certain locations in the country (e.g., Pune), mean temperature declined significantly between 1901 and 2000 (Gadgil and Dhorde 2005). Near surface temperatures in Armenia increased significantly between 1979 and 2012, surpassing the rate of increase between 1961 and 1994 (Gevorgyan 2014). Applying the MK test to temperature readings from 80 spatially-distributed weather stations in Sicily, Italy, Viola et al (2014) found there to be a general warming trend in Sicily over the period of 1924 to 2006.…”

Section: Introductionmentioning

confidence: 93%

Detection of trends in days with extreme temperatures in Iran from 1961 to 2010

Araghi

Baygi

Adamowski

2015

Theor Appl Climatol

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Human health and comfort, crop productivity, water resource availability, as well as other critical hydrological, climatological, and ecological parameters are heavily influenced by trends in daily temperature maxima and minima (T dmax , T dmin , respectively). Using Mann-Kendall and sequential Mann-Kendall tests, trends in the number of days when T dmax ≥30°C or T dmin ≤0°C, over the period of 1961 to 2010, were examined for 30 synoptic meteorological stations in Iran. For 67 % of stations, days when T dmin ≤0°C showed a significant negative trend, while only 40 % of stations showed a significant positive trend in days when T dmax ≥ 30°C. The upward trend in T dmax became significant between 1967 and 1975, according to the station, while the downward trend in T dmin became significant between 1962 and 1974 for the same stations. Changes in precipitation type across most parts of the country show a high correlation with these temperature trends, especially with the negative trend in T dmin . This suggests that future climatological and hydrological alterations within the country, along with ensuing climatic issues (e.g., change in precipitation, drought, etc.) will require a great deal more attention.

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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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Surface and tropospheric temperature trends in Armenia

Cited by 16 publications

References 39 publications

An assessment of observed and projected temperature changes in Armenia

An assessment of observed and projected temperature changes in Armenia

Detection of trends in days with extreme temperatures in Iran from 1961 to 2010

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

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