An assessment of observed and projected temperature changes in Armenia

  • Artur Gevorgyan
  • Hamlet Melkonyan
  • Taron Aleksanyan
  • Ashkhen Iritsyan
  • Yelena Khalatyan
Original Paper

Abstract

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.

Keywords

Climate change Armenia Temperature CCSM4 model 

Introduction

Nowadays, climate change is at the forefront of scientific issues and poses a significant challenge to human survival and development. Updated climatic information is of great importance for any assessment for climate impact studies, especially in relation to recent global warming (Intergovernmental Panel on Climate Change (IPCC) 2007). Southern Caucasus and Armenia are characterized by mountain topography (Fig. 1). The average elevation of the territory of Armenia is 1800 m above sea level, while the maximum and minimum heights vary from 375 to 4090 m (Mount Aragats) above sea level. 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. The study region is characterized by strong annual cycle of temperature with well-defined temperature differences for all four seasons, e.g. winter, spring, autumn and summer. Thus, it is of great importance for Armenia to examine the seasonal temperature changes (Gevorgyan 2014).
Fig. 1

The physical map of Armenian Highland and Southern Caucasus region (the state border of Armenia is indicated with black line)

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 et al. 2013; 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). 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 (1979–2012) which leaves little chance that the warming trends in Armenia are due solely to natural variability.

It is worth noting that a significant increase in temperature and in hot extreme temperature events has been observed over the Middle East which neighbours the study region from the south (Almazroui et al. 2012; Almazroui et al. 2013; Darand et al. 2015). The observed annual maximum, mean and minimum temperatures have increased significantly at a rate of 0.71, 0.60 and 0.48 °C decade−1, respectively, in Saudi Arabia over the period 1978–2002. Furthermore, the Middle East region is projected to be a climate change ‘hot spot’ (Giorgi 2006; Lelieveld et al. 2012). Results from Sharif (2015) indicate that projected temperature departures in Saudi Arabia are likely to exceed 3.5 and 5.5 °C for the mid and end of the twenty-first century, respectively, under A2 scenario. On the other hand, the projected temperatures from CCSM4 model for the July–August months showed temperature increase relative to ERA-Interim reanalysis data over most of the study region by more than 2.0 and 2.5 °C for the mid and end of the twenty-first century, respectively, under representative concentration pathways(RCP)4.5 scenario (Gevorgyan and Melkonyan 2014).

The main purpose of this study is to assess future changes in temperature in Armenia based on a newly developed dataset from phase 5 of the Coupled Model Intercomparison Project (CMIP5). Relative to CMIP3, CMIP5 constitutes an unprecedented set of experiments that include higher spatial resolution models and improved model physics. The results of this study are expected to provide a framework for agricultural adaptation and water resource management for Armenia in the future.

Data and method

To assess potential future changes in temperature over Armenia, monthly outputs from the Community Climate System Model 4 (CCSM4, National Center for Atmospheric Research) on a 1.25° × 0.9° grid are used in this study. The CCSM4 is considered as high-resolution model from CMIP5 GCMs including new physical parameterizations (cumulus convection scheme, a high-accuracy radiation scheme), new land models and aerosol effects on clouds (Gent et al. 2011; Chen et al. 2013). The CCSM4 was used in several recent studies (Wang and Chen 2013; Meleshko and Govorkova 2013; Sporyshev and Govorkova 2013; Pavlova and Kattsov 2013). Meleshko and Govorkova (2013) and Sporyshev and Govorkova (2013) employed 34 models out of CMIP5 to investigate model-performance error over the Northern Hemisphere and Russia quantified by the root-mean-square error (RMSE) and correlation coefficient, and CCSM4 was among the ten successful models in terms of temperature and precipitation representation over the mentioned areas. Changes in mean monthly 2-m maximum temperature from the CCSM4 model for July–August months have been analysed over the Armenian Highland and neighbouring regions by Gevorgyan and Melkonyan (2014) recently to assess the possible influence of regional temperature contrasts on heat-induced circulations under future climate conditions.

To test the performance of CCSM4 model, we compared annual average temperature over Armenia obtained from CCSM4 and from observed data. Though the historical run covers the period from the mid-nineteenth century to 2005, we consider the reference period 1961–1990 recommended by the World Meteorological Organization. The observed temperature data come from 36 operational stations in Armenia (Fig. 2). The selected 36 meteorological stations provide high-quality data and good temporal data coverage for the period 1961–2014. The homogeneity of monthly temperature data from the selected 36 meteorological stations was tested by Gevorgyan (2014). The used stations provide good spatial coverage including both low elevated valley stations and mountain stations. In this study, a simple statistical downscaling method is applied to estimate the CCSM4 model results in Armenia. The time series of mean seasonal and annual temperatures derived from CCSM4 five grid points covering Armenia (indicated with bold crests in Fig. 2), and its close neighbourhood is considered for validation (historical data) and the temperature change projection (temperature predictions) purposes.
Fig. 2

The distribution of 36 meteorological stations in Armenia (indicated with green dots). CCSM4 grid points over Armenia are indicated with bold crests

We compared the mean values of temperature and its confidence intervals from observed and CCSM4 data for period 1961–1990 to assess the performance of the CCSM4 in reproducing present-day climate in Armenia. The confidence intervals around the observed (modelled) mean temperatures were computed from the following equation:
$$ P={T}_{\beta }S\sqrt{1+\frac{1}{n}} $$
(1)
where P is the absolute value of the confidence interval (range), S is the standard deviation of temperature, T β is the two-sided Student’s T statistic at ß = 95 % level of confidence, and n is the number of years analysed.

We also used the RMSE in its classical sense to validate the CCSM4 model ability in reproducing the historical climate. This statistical measure has been used by different authors (Meleshko and Govorkova 2013; Elguindi et al. 2013) to evaluate simulated temperature against observations both at the global and regional scales.

The two twenty-first century scenarios for future greenhouse gas emissions used in this study are RCP4.5 and RCP8.5 as defined in Moss et al. (2010). where RCP8.5 is a high-emission path and RCP4.5 assumes lower emissions. Only one ensemble member is chosen for this study identified as r1i1p1 for CCSM4 though multiple ensemble members are accessible. For temperature projection reasons, we consider the reference period 1961–1990 for present climate, while three additional time intervals of 30 years, 2011–2040 (the beginning of the century), 2041–2070 (the mid-century) and 2071–2100 (the end of the century) for future climate. Future changes in temperature in Armenia were estimated for the four climatological seasons, namely winter (DJF), spring (MAM), summer (JJA) and autumn (SON), as well as annual changes were analysed.

Results

Observed temperature trends in Armenia

To better understand the temporal patterns of temperature changes over Armenia in the recent past, the analysis of seasonal and annual temperature anomalies is presented in this section based on the observed data from the 36 meteorological stations of Armenia over 1961–2014 (Fig. 3ae). The results show that average air temperature has gradually increased in Armenia with the amplification of warming during recent decades. It is notable that starting from about 1994, air temperature anomalies over Armenia are generally positive in any season. The year 2010 was recorded as the warmest year with the mean annual temperature anomaly exceeding 2.0 °C (Fig. 3e). On July 31, 2011, the highest temperature for Armenia has been recorded in the southeastern part of Armenia, at Meghri station (43.7 °C). It should be noted that there is a large interseasonal variation in terms of warming. The most prominent increase of seasonal mean temperature can be seen in summer (JJA) with statistically significant temperature trend 0.29 °C decade−1 (Fig. 3c). A significant temperature increase has been obtained in spring (MAM), autumn (SON) and in annual mean temperatures with temperature trends varying from 0.18 to 0.19 °C decade−1 (Fig. 3be). On the other hand, temperature increase in winter (DJF) is much weaker and statistically insignificant, with temperature trend 0.08 °C decade−1 (Fig. 3a).
Fig. 3

Temperature anomalies in Armenia (°C) over 1961–2014 with respect to 1961–1990 norm. a Winter (DJF). b Spring (MAM). c Summer (JJA). d Autumn (SON). e Annual (the linear trends, Tr, are shown, units are expressed in degree Celsius per decade: significant positive linear trends at 5 % significance level according to Student’s t test are marked with red)

We also present here two most recent major temperature events in Armenia, namely the persistence low (in December 2013) and high (in August 2014) temperature episodes which were extraordinary in climatological terms (Fig. 4a-d). December of 2013 was ranked the second coldest since 1961 (with a monthly temperature anomaly of −4.4 °C). At the same time, Yerevan and southwestern low elevated regions of Armenia experienced unprecedented cold wave events. Multiday periods of cold, dreary weather in basins and valleys were observed due to low-level strong temperature inversion. It can be seen from Fig. 4a that negative anomalies for daily minimum temperatures in Yerevan consisted of −6 °C and lower since the 14th of December. At the end of the cold episode (from the 27th to 31st of December), negative temperature anomalies were lower than −12 °C. The spatial pattern of monthly minimum temperature anomalies for December 2013 in Armenia based on temperature observations from 36 meteorological stations (Fig. 1) is shown in Fig. 4c. The strong basin temperature inversion can be clearly seen in Fig. 4c. The Ararat Valley in the south-west of Armenia including Yerevan and north-west part of Armenia is strongly influenced by temperature inversion. The accumulation of cold air in the mentioned regions caused low observed temperatures and strong negative temperature anomalies as low as −9 to −6 °C. On the other hand, the inversion-free regions in the northeastern, southeastern and mountain regions are characterized by relatively weak negative monthly temperature anomalies varying from −4 to −2 °C.
Fig. 4

Time series of anomalies (°C) for daily minimum temperatures in December 2013 (a) and for daily maximum temperatures in August 2014 (b) at Yerevan-Arabkir station. The spatial distribution of monthly minimum temperature anomalies for December 2013 (c) and for monthly maximum temperature anomalies for August 2014 (d) in Armenia (temperature observations from 36 meteorological stations presented in Fig. 1 were used). Temperature anomalies were estimated relative to normal values for period 1961–1990

August of 2014 was ranked the second warmest in Armenia since 1961 (with a monthly temperature anomaly of 3.5 °C). However, Yerevan and southwestern low elevated parts of Armenia experienced prolonged series of hot days. Since the 16th till the 31st of August, maximum temperatures in Yerevan exceeded 36 °C with positive anomalies higher than 4 °C and reaching up to 7–10 °C for several days (Fig. 4b). Figure 4d shows that most part of Armenia experienced significant positive temperature anomalies in August of 2014 exceeding 3 °C. Monthly temperature anomalies at several stations reached as high as 4–6 °C.

Validation of historical climate

Model confidence is usually based on the evaluation of their performance at reproducing observed features of current climate. In this section, we evaluate the ability of the CCSM4 model to reproduce the historical climate over Armenia in terms of temperature representation. Seasonal and annual temperatures are constructed in Armenia for the historical period 1961–1990 derived from the observed data and the CCSM4 data (Fig. 2).

In order to evaluate the accuracy of the CCSM4 in describing the mean annual cycle of temperature in Armenia, we compared mean seasonal observed and CCSM4 temperatures in Armenia over 1961–1990 (the thicker lines in Fig. 5). Furthermore, the confidence intervals estimated by Eq. (1) are presented in Fig. 5 as a proxy for interannual variability in mean seasonal and annual observed and CCSM4 temperatures. It can be seen from Fig. 5 that both observed and the CCSM4 data show strong annual cycle of temperature in Armenia. The latter is one of the main climatic features over the study region since the study region is located in mid-latitudes and characterized by strong annual variation of the atmospheric circulation. Armenia is influenced by tropical, polar and arctic (rarely) air masses which can be of both continental and maritime origins modified by continental influence (Gevorgyan 2013). The maximum observed temperature in summer exceeds 17 °C, while the minimum temperature in winter is as low as −3.7 °C (Fig. 5). Spring and autumn are transitional seasons with mean observed temperatures 6.5 and 8.9 °C, respectively, and the mean annual temperature for Armenia is 7.3 °C. Although the CCSM4 model captures the annual cycle of temperature in Armenia successfully, there is significant warm bias between the CCSM4 and observed mean temperatures in summer. The CCSM4 overestimates mean summer temperature over Armenia by 1.9 °C. Mean temperatures from the CCSM4 data for the other seasons are in better agreement with observations, with a slight positive bias in winter (0.7 °C), negative biases in spring (−0.2 °C) and autumn (−0.7 °C) and a slight positive bias in annual temperature (0.2 °C).
Fig. 5

Mean seasonal and annual temperatures (the thicker lines) and the confidence intervals around the mean temperatures (°C) in Armenia for 1961–1990 derived from observed data (Obs) and CCSM4 data. Winter (DJF) is indicated with blue, spring (MAM) is indicated with green, summer (JJA) is indicated with red, autumn (SON) is indicated with yellow, annual temperature is indicated with grey

The observed data show the largest variability of temperature during winter (Fig. 5) with the temperature range around the observed mean equaling ±4.3 °C, while CCSM4-simulated temperature range is about 70 % of the observed one (±3.0 °C). The increased interannual variations in winter temperatures in Armenia are due to the great variability in atmospheric circulation regime during winter in the mid and high latitudes of the Northern Hemisphere (Sporyshev and Govorkova 2013). However, the CCSM4 historical data still show maximum variability of temperature during winter for 1961–1990. On the other hand, the CCSM4 model overestimates the temperature range for spring (±2.5 °C) relative to the observed one (±1.8 °C). The estimated confidence intervals of temperature derived from the observed and the CCSM4 model are in better agreement for summer and autumn, with the observed temperature range ±1.5 and ±1.7 °C, respectively, and with CCSM4 temperature range equalling ±1.9 °C for both of the seasons. Finally, the estimated ranges of annual temperature from observed data and the CCSM4 model consist of ±1.6 and ±1.3 °C, respectively.

We also evaluated the ability of the CCSM4 to simulate seasonal and annual temperature in Armenia by computing the RMSE (Fig. 6). The higher values of RMSE can be seen for winter and summer with RMSE consisting of 2.7 and 2.2 °C. This is consistent with the results of Fig. 5. The largest variability of observed temperature is found during winter, and the CCSM4 model underestimates this great variability resulting in the high RMSE. During summer, the CCSM4 model overestimates both mean temperature and temperature range relative to observed data (Fig. 5). The model skill for spring and autumn temperatures is higher with significantly lower values of RMSE (1.3 °C). The lowest RMSE was obtained for annual temperatures (1.0 °C) indicating a high performance and reasonably good consistency with the observations.
Fig. 6

RMSE values (°C) of the CCSM4 for seasonal and annual temperatures in Armenia over 1961–1990

Projected changes in temperature in Armenia

The evaluation of projected temperature changes in Armenia is examined in this section. Climatologies from the future periods 2011–2040, 2041–2070 and 2071–2100 for both the RCP4.5 and RCP8.5 scenarios are compared to a reference climatology based on the years 1961–1990. The projected changes in national average temperatures from the CCSM4 runs are all positive (Fig. 7ac). For the beginning of the twenty-first century, the mean annual temperatures are expected to increase by 1.7 °C both under RCP4.5 and RCP8.5 (Fig. 7a, grey lines). A more pronounced temperature increase can be seen in the middle of the twenty-first century with warming of 2.2 and 3.2 °C under RCP6.0 and RCP8.5, respectively (Fig. 7b, grey lines). As a result of the rising radiative forcing pathway leading to 8.5Wm−2 by 2100 for scenario RCP8.5, the climatological temperatures begin to show vastly different features after the mid-century in any season. The mean annual temperature increase can reach 4.7 °C under RCP8.5, but only about 2.6 °C under RCP4.5 for the end of the century (Fig. 7c, grey lines).
Fig. 7

Changes in seasonal and annual mean temperature (°C) in Armenia from the reference period 1961–1990 (thicker lines) and the confidence intervals around the mean temperature changes up to the end of the twenty-first century under RCP4.5 and RCP8.5 scenarios (the seasons are indicated with the same colours as in Figs. 5 and 6): a 2011–2040, b 2041–2070, c 2071–2100

It is worth noting that there is a large interseasonal variation in terms of future warming. The magnitude of the temperature increase peaks in summertime in any period both under RCP4.5 and RCP8.5. This is consistent with the recent warming in Armenia obtained from observations (Fig. 3ae). The latter suggests even stronger amplitude of the annual cycle of temperature in Armenia under future climate conditions leading to a stronger continentality of climate relative to current levels. This is more pronounced under RCP8.5 scenario showing that a temperature increase in summer can reach 6.0 °C for the end of century (Fig. 7c). Mean temperatures in winter, spring and autumn are expected to increase from 3.9 to 4.4 °C over the twenty-first century (Fig. 7c).

The estimated values of temperature ranges are of the same magnitude and even exceed respective temperature changes in most cases (Fig. 7ac). The largest temperature range for period 2011–2040 (Fig. 7a) was obtained for winter (±2.7 °C), while those for the periods 2041–2070 (Fig. 7b) and 2071–2100 (Fig. 7c) were found during summer (±2.7 °C) and spring (±3.1 °C), respectively. In other words, there is great uncertainty in projected temperature change patterns in Armenia which can be partly due to the natural variability of seasonal temperatures discussed in Section 3.2. However, the projected temperature ranges are overestimated relative to those for present climate (Fig. 5) in most cases, except for winter and annual temperature ranges. Furthermore, the CCSM4 data do not show well-defined maximum variability in winter season as was obtained for present climate from observations (Fig. 5). It is worth noting that the temperature ranges for annual temperature changes are significantly reduced (from ±1.0 to ±1.7 °C) indicating less uncertainty in projected annual temperature changes relative those for the seasons. On average, the values of estimated temperature ranges for seasonal and annual mean temperatures are of about the same magnitude for all of the three considered periods of the twenty-first century (Fig. 7a–c) both under RCP4.5 scenario (±2.1 °C) and under RCP8.5 scenario (from ±2.2 to ±2.4 °C). With the continuous increasing temperature in the future, the latter suggests that the CCSM4 model is becoming more confident in the prediction of temperature increase over Armenia toward the end of the century. However, we should be careful with the temperature change estimates for winter and summer seasons, since these seasons are characterized by higher RMSE values (Fig. 6).

To further investigate the spatial pattern of temperature changes in Armenia, the distributions of observed and projected climatological annual temperatures are shown in Fig. 8ac. Figure 8a shows the distributions of observed temperature for 1961–1990. The linear regression model based on the relationship between annual mean temperature and elevation obtained from the all meteorological stations of Armenia (with correlation coefficient of −0.96) and 90-m digital elevation model obtained from the US Geological Survey (USGS, http://earthexplorer.usgs.gov) has been used to obtain Fig. 8a (ArcGIS software was applied). Figure 8b and c were obtained through superimposing of observed (Fig. 8a) and projected regional temperature changes for the end of century from the CCSM4 runs (under RCP4.5 and RCP8.5 scenarios). Figure 8a shows that there is a great spatial variability in the distribution of annual mean temperature in Armenia, and it is a great challenge to simulate this spatial variability successfully using GCMs. The mean annual temperatures mainly vary from −4 to 14 °C. Relatively high temperatures can be seen in the plain of Ararat (in the south-west of Armenia), the north-eastern and south-eastern valley regions of Armenia, at about 10–14 °C. The mountain ranges with height reaching 2500 m or above experience temperatures as low as from −4 to 2 °C. Figure 8c shows that temperature can reach up to 18–20 °C in the low-elevation parts of Armenia in the end of the century under RCP8.5 (plain of Ararat, the north-eastern and south-eastern valley regions). At the same time, the areas with negative annual mean temperatures indicated with blue colors in Fig. 8ac are significantly reduced in the end of the century under RCP4.5 (Fig. 8b), while those are almost disappeared under RCP8.5 (Fig. 8c). It is estimated that the height of annual and winter mean 0 °C isotherm in Armenia will increase in elevation by 800–1000 m in the end of the century under RCP8.5.
Fig. 8

The spatial distribution of the annual mean temperature in Armenia (°C) averaged over the period 1961–1990 (a) and 2071–2100 under RCP4.5 (b) and RCP8.5 (c)

Conclusions and discussions

In this study, changes in one of the main climate variable, i.e. temperature, in Armenia up to the end of the century are analysed. The manuscript is the first to present climate forecasting over a little studied part of the world. It should be noted that the results of future temperature changes from the CCSM4 model are in line with previous results based on regional climate model PRECIS developed by the Hadley Centre of the UK Meteorological Office (Regional Climate Change Impacts Study for the South Caucasus Region 2011; SNCCC 2010). The results of this study suggest that Armenia will experience significant temperature increase in the twenty-first century. Both recent temperature changes obtained from observed data and temperature change projections in the future obtained from the CCSM4 data show the greatest warming in Armenia during the summer. It is worth noting that the expected temperature increase in the summertime can reach 4–6 °C under RCP8.5 for the middle and end of the century. The above would lead to substantial negative impacts on agricultural, hydrological and socioeconomic sectors and would present significant adaptation challenges. It is expected that higher air temperatures in the warm season would result in an increase in evaporation and aridity. The latter will have negative impacts on the economy of Armenia which is highly dependent on the water sector.

Obviously, the CCSM4 model has substantial deficiencies in simulating the regional climate over Armenia. Validation results showed higher errors (RMSE) in the representation of winter and summer temperatures. These errors are probably due to the inadequacies in the representation of complex topography and the associated circulation over the study region. 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.

There is also a great 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. To produce the reliable projections required for regional climate assessment in Armenia, we need to bias-correct the raw model outputs and to apply different downscaling techniques (e.g. nesting of regional models performed within the CORDEX activity). The consideration of different GCMs and the results for the multi-model ensembles is expected to be important to better understand temperature change in Armenia in the future. 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. The above mentioned issues are associated with high computational costs and will clearly be a subject of interest for future study.

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Copyright information

© Saudi Society for Geosciences 2015

Authors and Affiliations

  • Artur Gevorgyan
    • 1
  • Hamlet Melkonyan
    • 1
  • Taron Aleksanyan
    • 1
  • Ashkhen Iritsyan
    • 1
  • Yelena Khalatyan
    • 1
  1. 1.Armenian State Hydrometeorological and Monitoring ServiceDepartment of Development and Validation of Hydrometeorological ModelsYerevanArmenia

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