The article presents the results of a study on the assessment of modern space–time trends of extreme values of air temperature and precipitation in 42 meteorological stations throughout Kazakhstan for the period from 1971 to 2020. Spatial and temporal analysis of the distribution of specialized climatic indices was recommended by the WMO climatology commission and an assessment of their trends was carried out. Spatial heterogeneity was revealed in terms of the degree of manifestation of changes and trends. Temperature indices are shown to confirm the overall warming trend. The division of the territory of Kazakhstan by the degree of manifestation of climate change into the southwestern and northeastern half was revealed. Extreme trends are most pronounced in the southwestern half, where a significant trend has been identified both for an increase in extremely high daytime and extremely low night temperatures. The calculated trends in temperature indices are generally significant, but the significance is mainly not ubiquitous; the trends are significant only in certain parts of Kazakhstan. WSDI and CSDI trends were found to confirm a widespread increase in the overall duration of heat waves and a reduction in the overall duration of cold waves. No significant extreme effects were found in the sediments. It is confirmed that Kazakhstan has weak, statistically insignificant, positive and negative trends in the maximum duration of the non-traveling period. Precipitation index trends, unlike temperature ones, are statistically insignificant in most of the country.

/pdf/an-assessment-of-the-present-trends-in-temperature-and-17ud6nj2.pdf

An Assessment of the Present Trends in Temperature and Precipitation Extremes in Kazakhstan

Climate change is one of the most challenging environmental issues faced by the present day world community. Its impacts are reflected in different components of the socioeconomic and biophysical systems. Temperature is a fundamental climatic variable that is studied thoroughly across globe for the similar purpose of capturing the dynamic nature of the variable and relating it with the human interventions over time. The main objective of the present study is to analyse the long-term trends in temperature that have occurred in the territory of Kazakhstan on annual, seasonal and monthly time scales. The study used the non-parametric statistical methods such as M–K statistical test, Sen’s slope estimator, and Pettit’s test to analyse the time series data and portray it through various GIS techniques. The results revealed that Kazakhstan showed a significant increasing trend in the mean annual temperature from 1970 to 2017. The Sen’s slope estimator reflected that the mean temperature increased at an annual rate of 0.034 °C for the selected time period with a probable change point detected in the year 1996. On the seasonal scale, all the four seasons showed increasing trends for their respective average temperatures. Among the four seasons, highest increase in the temperature was reported by spring season which was subsequently followed by winter and autumn seasons. The least increase was reflected by summer season for which the variable increased at 0.20 °C/decade. The months of March and August were significant contributors to the warming that happened in Kazakhstan during the studied time period of 48 years.

Annual, Seasonal and Monthly Trend Analysis of Temperature in Kazakhstan During 1970–2017 Using Non-parametric Statistical Methods and GIS Technologies

The reversal of winter surface air temperature anomalies (SATAs) over Central Asia (CA) between December and January is investigated in this study and found to be closely related to the sea surface temperature anomalies (SSTAs) over the central tropical Pacific (CTP). The cold CTP SSTAs can lead to positive (negative) SATAs over CA in December (January). The different responses of SATAs over CA to the SSTAs are attributed to different Rossby wave propagations. In December, a wave train from the North Pacific directly reaches CA, while in January it mainly propagates in the meridional direction and cannot reach CA. The January SATAs of CA are influenced by a wave train from the North Atlantic, which is induced by CTP SSTAs indirectly. The wave trains from the North Pacific are mainly driven by the Gill-type response to the cold CTP SSTA in both December and January. In January, since the climatological subtropical jet stream over the North Pacific is stronger and situated more towards the equator, a stronger Gill-type response is excited and causes the meridional propagation of the Rossby waves. Then, this stronger Gill-type response can cause strong zonal wind anomalies over the East Pacific. Local anomalies of the synoptic-scale transient eddy can be further caused by the zonal wind anomalies and travel eastward to the North Atlantic. The eddy-induced geopotential anomalies over the North Atlantic can further trigger Rossby waves and cause the negative SATAs over CA. Numerical simulations reproduce these mechanisms.

https://www.frontiersin.org/articles/10.3389/feart.2022.873040/pdf

Impacts of Central Tropical Pacific SST on the Reversal of December and January Surface Air Temperature Anomalies Over Central Asia

Soil erosion is a serious ecological and economic issue occurring in all regions across the biosphere. Soil erosion contributes to land degradation, endangering both the pastoral and natural environments in Kyrgyzstan. This study objective is to identify the potential of soil erosion in Kyrgyzstan and estimate the total soil loss rate. The revised universal soil loss equation (RUSLE) model with remote sensing (RS) was used to show the distribution of risk zones of soil erosion and soil loss. Variables were obtained from Kyrgyz Hydro-Meteorological agency, Harmonized World Soil Data (HWSD), Moderate Resolution Imaging Spectroradiometer-Normalized Difference Vegetation Index (MOD13Q1-MODIS/Terra), Shuttle Radar Topography Mission (SRTM), and Global Land Cover Map (GlobeLand30). The study results display that the average annual soil erosion amount in Kyrgyzstan was 5.95 t ha−1 year−1, with an annual soil loss of 113.7 × 106 t year−1. The entire area was separated into seven erosion risk classes. More than 28% of the territory of Kyrgyzstan is affected by limited soil erosion; the average volume of potential erosion is around 1.0 t ha−1 year−1. The northeastern and central parts of the country mainly experienced low soil erosion, whereas the west and southwestern parts were subject to high-to-extremely high soil erosion rates. This is the first time this method has been used to estimate the potential of soil loss throughout the country; it provides suitable tools for identifying priority areas for considering measures to decrease soil erosion risk. Our findings give valuable implementations for assessing soil loss and protecting the environment.

Assessing the potential of soil erosion in Kyrgyzstan based on RUSLE, integrated with remote sensing

/pdf/modeling-soil-erosion-in-the-chagan-river-basin-of-the-west-4u5ak49jyj.pdf

Modeling soil erosion in the Chagan river basin of the west Kazakhstan with using RUSLE and GIS tools

/pdf/anomalous-snow-regime-in-2019-and-long-term-trends-in-snow-50e9memtdx.pdf

Anomalous snow regime in 2019 and long-term trends in snow depth in Kazakhstan

On the basis of long-term dynamics of the July’s vegetation data (NDVI and VCI indices) for 31 ranges of the Tien Shan and Jungarian Alatau arid mountains located in the Eurasia center are found the atmosphere stratification change. The variability of Atlantic Ocean water vapor transport ability over Northern Tien Shan ranges to the Inner Tien Shan was detected. This phenomenon not related to the overall seasonal humidity but is obviously associated with atmosphere stratification regimes. The analyzed period consists of two eras from 2002–2008 and 2008–2019 years, which differ in the regime of accessibility of the Inner Tien Shan ranges for water vapor from Atlantic Ocean. The overall tendency of the changes in 2002–2019 is the increase in the availability ocean water vapor to the Inner Tien Shan ranges. Recorded changes may be due to global air temperature increases and atmospheric processes intensification.

/pdf/the-effect-of-changing-stratification-in-the-atmosphere-in-39cktbgtki.pdf

The effect of changing stratification in the atmosphere in central zone of Eurasia according to vegetation data of Tien Shan mountains during 2002-2019

/pdf/long-term-trends-in-vegetation-in-tien-shan-and-dzungarian-1kuid8nnqn.pdf

Long term trends in vegetation in Tien-Shan and Dzungarian Alatau from eMODIS NDVI C6 data (2002–2019)

/pdf/diagnostics-of-water-availability-for-agricultural-crops-in-2y95u822l5.pdf

Diagnostics of water availability for agricultural crops in Xinjiang (China) in 2003–2019 based on eMODIS NDVI C6 data

/pdf/validation-of-daily-snow-depth-fews-net-product-over-river-1dmt4msjpe.pdf

Validation of daily Snow Depth FEWS NET product over River Ural basin on snow depth meteorological observations

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