Surface Air Temperature Variability Research Articles

Surface Air Temperature Variability over Subregions of Pakistan During 1970–2014

Surface Air Temperature Variability over Subregions of Pakistan During 1970–2014

Application of deep learning algorithms to correct bias in CMIP6 simulations of surface air temperature over the Indian monsoon core region

AbstractIndian subcontinent witnessed a rise in surface air temperature (SAT) in recent decades, during the summer months of March, April and May. The monsoon core region (MCR) of India experiences a hot and humid climate, with temperatures typically highest in May and June before the onset of the monsoon. Global climate model (GCM) simulations of SAT are very much essential to understand the future climate of Indian MCR. Biases in GCMs simulations are due to insufficient knowledge of parameterizations and various assumptions that are made to simulate the complex interactions between land, ocean and atmosphere. The objective of this study is to correct the bias in the Coupled Model Intercomparison Project Phase 6 (CMIP6)–GCM simulations of SAT during March, April and May months over MCR for the historical period 1985–2014 and shared socio‐economic pathways (SSPs) SSP2‐4.5 and SSP5‐8.5 for the period 2015–2100. SAT dataset of fifth‐generation reanalysis (ERA5) of the European Centre for Medium‐Range Weather Forecasts (ECMWF) is used as reference dataset to perform bias correction for the historical period. Preliminary investigation of both SAT datasets has shown that there exists considerable warm bias (1.47°C) over the MCR. Bias correction is performed using a one‐dimensional convolutional neural network (CNN‐1D) and a convolutional long short‐term memory network (CNN‐LSTM) deep learning algorithm. The performance of these algorithms is evaluated with the statistical metrics such as root‐mean‐square error (RMSE), normalized root‐mean‐square error, Nash–Sutcliffe efficiency, mean absolute error, percent bias, correlation coefficient and dynamic time warping. RMSE and percent bias were decreased to 0.35°C and 0.8% with CNN‐LSTM algorithm. The CNN‐LSTM algorithm also preserves the year‐to‐year variability of SAT. Hence, CNN‐LSTM algorithm is found to be suitable for the bias correction of GCM simulations of SAT with encouraging results.

Decoupling of Arctic variability from the North Pacific in a warmer climate

The sea level pressure variability in the North Pacific modulates the climate of the Arctic and surrounding continents, substantially impacting ecosystems and indigenous communities. Our analysis based on data from the CESM2 Large Ensemble and different Model Intercomparison Project datasets reveals that the interannual variability of Arctic surface air temperature (SAT) gradually decouples from the contemporaneous atmospheric conditions over the North Pacific as external forcing increases in intensity in the future. Future projections show that the North Pacific-Arctic relationship during the fall season consistently weakens in magnitude until the end of this century, and in the 22nd and 23rd centuries, the relationship is negligible throughout the year. We show that under increased greenhouse gas emissions, the regional heat fluxes extensively control the Arctic temperature variability, and the strength of the projected North Pacific-Arctic relationship is strongly dependent on the Arctic sea ice extent. Our results suggest that under future warming, a strong coupling of Arctic SAT with the underlying ocean and a weakening of the meridional pressure gradient driven by an enhanced rate of sea ice retreat will weaken the interannual footprint of North Pacific variability on Arctic SAT. Therefore, we propose that the alarming rate of sea-ice decline over recent decades and projected in the near future could accelerate the rate of decoupling. Further, we suggest that mitigation strategies for the Arctic should focus on regional mechanisms operating on interannual and seasonal timescales.

Measurement and analysis of the variation of albedo and surface temperature at Pondok Betung, South Tangerang

In 2021, the IPCC reported that the rate of global warming has reached 1.1°C. The BMKG also states that many regions in Indonesia are experiencing warming. Two indicators of global warming are surface air temperature (SAT) and albedo. Changes in these two variables contribute to an urban heat island (UHI). Recent research reveals an increase in the UHI index in Pondok Betung area. Variations in SAT and albedo values can be obtained through the Automatic Solar Radiation System, and Automatic Weather Station provided at the Pondok Betung BMKG Station. The data obtained are SAT and two types of albedos, namely the albedo of direct radiation and the albedo of diffuse radiation on a grass surface. The results obtained show a small increase in SAT and a small decrease in the two albedos. Such a result is to be expected in January 2021-June 2022. The lowest SAT was 26.16°C in January 2021, and the highest was 27.92°C in March 2021. The lowest direct albedo was 0.158 in July 2021, and the highest was 0.178 in October 2021. The lowest diffuse albedo was 0.173 in June 2021, and the highest was 0.183 in October 2021.

Projected changes in the interannual variability of surface air temperature using CMIP6 simulations

Projected changes in the interannual variability of surface air temperature using CMIP6 simulations

Reliability of gridded temperature datasets to monitor surface air temperature variability over Bolivia

AbstractSix gridded temperature datasets (T‐datasets) were evaluated for the first time over the South American continent, through the case study of Bolivia, by comparing them with temperature records acquired from 82 meteorological stations spanning the 1995–2010 period. The comparisons were carried out at the daily time step considering different seasons (annual scale, austral summer and austral winter) and regions (Amazon, La Plata and Altiplano basins). Overall, the climate hazards group infrared temperature with stations (CHIRTS) and the climate prediction centre (CPC) T‐datasets provided the most reliable mean daily temperature (Tmean) and also described well the temporal variability of minimum and maximum daily temperature estimates (Tn and Tx). Tmean, Tn and Tx trends were analysed over the 1983–2016 period to observe temperature temporal evolution across the three regions. Despite some general agreements between the trends (Tmean, Tx and Tn), large discrepancies are also observed. It was found that CPC overestimates and CHIRTS underestimates mean temperature trends and that CPC (CHIRTS) was better than CHIRTS (CPC) to estimate Tx (Tn) trends, both in magnitude and space. Furthermore, opposing trends (i.e., warming and cooling) are described by CPC and CHIRTS for some specific regions, which call into question their reliability for such analyses. These findings highlight the need to validate gridded temperature products with reliable ground data for the regions under study, particularly if they have a wide elevation range.

On the coupled interdecadal variations of the extra‐tropical surface air temperature and the isentropic meridional airmass transport in Northern winter

AbstractBased on the ERA5 reanalysis since the 1950s, this study investigates the coherent inter‐decadal variations of the winter continental surface air temperature (SAT) between the Eurasian (EUA) and the North American continents in the past 70 years. The SAT variation over the two continents can be characterized with five typical periods successively from a ‘both‐warmer’ (1950s–1960s), to a ‘both‐colder’ (1960s–1980s), and then a ‘EUA‐warmer’ (1980s–1990s) followed by another ‘both‐warmer’ (1990s–2000s) and a ‘EUA‐colder’ (2000s–2010s) period. Such periodic variation of the SAT is closely coupled with changes of the low isentropic‐level meridional mass transport (IMMT), as manifested by the coupling relationship between the midlatitude SAT and the net IMMT out of the polar circle, in terms of their zonal patterns and geographical patterns. The SAT variation can be well reconstructed with the first two leading maximum covariance analysis (MCA) modes between the SAT and IMMT. The first leading MCA mode (MCA1) mainly dominates a ‘EUA‐warmer/colder’ pattern, while the second (MCA2) dominates the ‘both‐warmer/colder’ pattern. There exists a significant lead–lag correlation between the MCA1 and MCA2, which determines the changing SAT pattern in the five successive periods. Furthermore, the MCA1 and MCA2, especially their lead–lag coupling after the 1975 is significantly associated with the Pacific decadal oscillation (PDO) which dominates the much‐intensified MCA1 and the related ‘EUA‐warmer/colder’ SAT pattern since then. The Atlantic multi‐decadal oscillation mainly dominates the third leading MCA mode with it's effects on the SAT over Europe coincidently to amplify the PDO‐related SAT changes.

Interannual impact of the Victoria mode on the winter-spring surface air temperature over Eurasia and North America

Variations of the Victoria mode (VM) have received considerable attention due to their profound impacts on the climate systems in the pan-North Pacific. However, works about its impact on surface air temperature (SAT) variability over Eurasia and North America, which may be responsible for extreme weather and climate events, are limited. Here we show a significant positive and negative relationship between the VM and the winter-spring SAT anomalies over mid-to-high-latitude east-central Eurasia (MEE) and eastern North America (ENA), respectively. A local energy budget analysis shows that the contribution of the surface heat fluxes associated with the VM to the SAT anomalies is confined mainly to MEE and may not explain the formation of SAT anomalies over ENA. Furthermore, VM-induced anomalous atmospheric circulations play a crucial role in the formation of notable SAT anomalies. The positive (negative) VM is linked to negative (positive) precipitation and upper-tropospheric wind convergence (divergence) anomalies over the western North Pacific, which contribute to positive (negative) Rossby wave source (RWS) anomalies near the East Asian westerly jet core. These RWS anomalies act as disturbances that propagate eastward, exciting a wave train-like pattern. The high-level positive and negative geopotential height anomalies of the Rossby wave dominate MEE and ENA, respectively, leading to the variation in SAT anomalies. These results could advance our understanding of the relationship between the VM and SAT over the Northern Hemisphere and inspire us to pay more attention to the VM climate impacts.

Intraseasonal variations in winter surface air temperature over China and its prediction skill in ECMWF System5

AbstractBased on the daily average temperature data of 2374 stations in China from 1993 to 2022 and the monthly average temperature data of European Centre for Medium‐Range Weather Forecasts (ECMWF) System5 in winter, this article analyses the intraseasonal variations of winter surface air temperature (SAT) over China by using seasonal empirical orthogonal function decomposition (S‐EOF) and compare the prediction skill differences of the first three dominant modes in ECMWF System5. The first mode (S‐EOF1) is characterized by out‐of‐phase changes in SAT anomalies (SATA) between December and January. Both the Siberian high (SH) and the central Pacific El Niño‐Southern Oscillation (CP ENSO) can impact S‐EOF1. The second mode (S‐EOF2) is characterized by consistency in warm anomalies over the Northeast and Qinghai‐Tibet Plateau's variation, while the other areas are characterized by the out‐of‐phase change in SATA. S‐EOF2 is closely related to Arctic oscillation (AO). The third mode is characterized by alternating changes over 3 months in winter, which is related to the Pacific meridional mode (PMM) and the North Atlantic SST tripole (NAT). Comparing the ECMWF System5 prediction skill for the first three leading modes for the intraseasonal variations in winter SAT, the prediction skill is not high. The model did not predict the extent of warm anomalies and the intraseasonal fluctuation in S‐EOF1, which may be due to the poor prediction skills for the range and intensity of the CP ENSO and the SH. The second mode has the highest prediction skill among the three modes. For the prediction skill of AO is good. The model can capture the intraseasonal reverse SATA between December and January but did not capture the reverse SATAs between January and February. Because the model does not predict obvious PMM and NAT well.

Evaluation of MSWX Bias-Corrected Meteorological Forcing Datasets in China

Near-surface meteorological forcing (NSMF) datasets, mixed observations, and model forecasts are widely used in global climate change and sustainable development studies. For practical purposes, it is important to evaluate NSMF datasets, especially those released latest, and determine their strengths and limitations. In this study, we evaluate the performance of Multi-Source Weather (MSWX) in China over the period of 1979–2016. For comparison, ECMWF Reanalysis version 5 (ERA5), China Meteorological Forcing Dataset (CMFD) and Princeton Global Forcing (PGF) dataset are also evaluated to determine the strengths and weaknesses of MSWX. The following variables are compared with observations over 2400 stations: 2 m air temperature (T2m), 2 m daily maximum air temperature (Tmax), 2 m daily minimum air temperature (Tmin), precipitation (P), and 10 m wind speed (V10). The evaluation is conducted in terms of climatology, inter-annual variations and seasonal cycles. Results show that MSWX reasonably reproduces the spatial pattern of T2m with root-mean-square errors (RMSEs) below 1.12 °C and spatial correlations above 0.97, but underestimates Tmax and overestimates Tmin, with biases ranging from −2.0 °C to 2.0 °C, especially over the North China and Northeast China. Compared with ERA5 and PGF, MSWX can better simulate the inter-annual variations of surface air temperature with high spatial correlations (>0.97) but shows higher RMSEs than PGF. For precipitation, MSWX accurately captures the primary features of precipitation, including significant characteristics or patterns of the precipitation climatology and inter-annual variation. Its inter-annual variation shows low RMSEs ranging from 0.55 mm/day to 0.8 mm/day, compared to ERA5 and PGF. However, regions with abundant precipitation exhibit higher biases. Because the biased Global Wind Atlas (GWA3.1) is used for the wind bias correction of MSWX, MSWX significantly overestimates the annual mean wind speed, but it is consistently well-correlated with observations, with RMSEs less than 1.5 m/s and spatial correlations greater than 0.6 over the period of 1979–2016. This study reveals both the advantages and disadvantages of MSWX, and indicates the need for research into climate change and sustainable development in East Asia.

Variation of Surface Air Temperature Induced by Enhanced Land–Atmosphere Coupling During 1981–2020 in Xinjiang, Northwest China

AbstractLand–atmosphere coupling (LAC) is a critical process in the climate system, and has great effects on surface air temperature over the humid–dry transition zones. Using ERA5/ERA5‐land reanalysis datasets, we show that the summer temperature anomalies over Northwest China (NWC), known as one of the most important LAC hotpots in China, are significantly correlated with the LAC strength during 1981–2020. The stronger the coupling strength between air temperature and land surface, the more pronounced decrease in air temperature and extreme hot days over NWC. Among the four pathways of land–air temperature coupling, including soil moisture (SM)/soil temperature–latent heat flux/sensible heat flux–air temperature coupling, SM–sensible heat flux–air temperature pathway corresponds most closely with the temperature changes in summer. By analyzing the possible local and non‐local physical links in this relationship, we show that the wave trains composed of the intensification of Ural ridge and Central–Asia trough stimulate a meridional fluctuation of westerly airflow over the mid–high latitudes of Eurasia. Large moisture, therefore, converges into NWC, leading to excessive precipitation and deficient incident solar radiation reaching the land surface. In such case, wetter and cooler soil states accelerate the cooling of the environment through feedbacks between the lands, land–atmosphere exchanging fluxes and air temperature locally, accompanied by a significant enhancement in LAC strength. Our study provides insight into the physical processes causing variations in summer temperature over a typical LAC hotspot and suggests that the role of land surface–atmosphere interactions needs to be considered when studying temperature extremes under climate change.

Physical meaning of temperature and evaluation of distribution laws (in the area of the Lake Sevan basin)

Formulation of the problem. In the work, the most general definition of temperature was discussed and presented, the temporal probability distribution of air temperature was analyzed and evaluated. Temperature has no specific definition. Thus it will be difficult to study the nature of any geophysical phenomena, including the characteristics of temperature distribution, without understanding the modern scientific definition and adjustment of temperature. The aim of the work is to give the most modern reasonable definition of temperature or what the thermometer measures, the answer to which requires a more specific scientific justification, as well as to evaluate the patterns of possible spatiotemporal distribution of air temperature in the territory of Armenia and in the area of the Lake Sevan basin. Methods. To solve the set tasks, the authors used corresponding research and published works as a theoretical basis in the work. In the work, the average monthly data of actual observations of the temperature of the ground surface air layer and the amount of precipitation of the «Center for Hydrometeorology and Monitoring» SNCO of the Ministry of Environment of the Republic of Armenia were used. It was found that temperature is a quantity characterizing the thermal state and radiation of the terrestrial and celestial bodies and, in general, the environment, which is strongly related to the entropy change of the system; temperature is the main thermodynamic characteristic of thermal equilibrium; the thermodynamic and microscopic concepts of temperature coincide; the temperature-heat (energy) difference becomes known in the sense that a system can have high energy but low temperature. The authors applied the following research methods in the article: mathematical and statistical, extrapolation, analysis, analogy, correlation, cartographic. Results. Energy depends on the geometry (dimensions) of the system, but temperature does not. A trend of increasing air temperature is observed in the RA territory, which is also a result of the entropy change of the system. It can change very quickly, depending on the environmental factors in the given area (the growth rate of greenhouse farms, the artificial filling of valleys, which are wave carriers of air flow, the relentless use of green spaces for the purpose of public buildings, and other factors) in the process of disrupting the excessively permissible norms, which are currently separate needs serious research and prevention. The long-term variability of surface air temperature in the area of the Lake Sevan basin is analyzed. The analysis carried out made it possible to give a quantitative assessment characterizing the climate change in this region over the past 98 years. An analysis of the observational data showed that the trend of climate warming is confirmed by an increase in air temperature both in winter and over a long period of time. The change in surface air temperature occurs at a rate of 0.002 ºС/year to 0.012 ºС/year and is generally 0.008 ºС/year (or 0.08 ºС/10 years) for all analyzed stations. The results obtained confirm the presence of two periods of warming observed in 1927–1970 and 1971–2021. All the results obtained in the course of the work testify to the trend of climate mitigation in the area of the Lake Sevan basin at the end of the 20th - beginning of the 21st century.

An abrupt change of winter surface air temperature over the northern part of Korean Peninsula in the late 1980s and related atmospheric circulation variability

The aim of this study is to detect the variation of winter surface air temperature (SAT) over the northern part of Korean Peninsula (NPKP) for the period of 1949–2020 under global warming, as well as to investigate its possible mechanisms. All temperature data used for the study were obtained from representative 37 weather stations over NPKP. Results are as follows. 1) Winter temperature anomaly series manifested a clear shifting point in the late 1980s, with upward rate of about 0.19 °C per decade for the period of 1949–2020, and those were generally smaller than normal year prior to the shifting point, but were greater after 1988. 2) Spatial patterns of first mode of empirical orthogonal function before or after the shifting point in the Northern Hemisphere had reversely alternated, as an evidence describing the possible linkage between negative (positive) phase of Arctic oscilliation and cold (warm) winter over the study area. 3) A schematic diagram shows the connections of atmospheric circulation indices with the winter temperature over the study area: the East Asian trough had the best relationship with winter SAT over the study area among the East Asian winter monsoon components affecting East Asia. However, the possible causes of the winter temperature variation in the study area need to be further investigated.

Interannual Variability of the Wintertime Asian–Bering–North American Teleconnection Linked to Eurasian Snow Cover and Maritime Continent Sea Surface Temperature

Abstract Recent studies propose that the Asian–Bering–North American (ABNA) teleconnection is a distinct atmospheric pattern that is related to Eurasian and North American winter climate besides the Pacific–North America (PNA) pattern, while its origin remains elusive. This study investigates the interannual variability of the ABNA during the past 42 winters (1979–2020) and the associated prior surface boundary forcings. The ABNA explains coherent surface air temperature changes in northern Asia, eastern Siberia–Alaska, and eastern North America, even after removing the impacts of the PNA, the Arctic Oscillation, the North Atlantic Oscillation, and the North Pacific Oscillation. Surface boundary conditions linked to the ABNA could be traced back to a Eurasian snow cover dipole pattern (ESCDP) and a Maritime Continent sea surface temperature anomaly (MCSST) in November. The ESCDP leads to a displacement of the Arctic stratospheric polar vortex via troposphere–stratosphere coupling. The anomalous polar vortex propagates downward in the following winter and generates the tropospheric ABNA pattern. The MCSST induces a diabatic heating anomaly, which is associated with a tropical western Pacific precipitation anomaly (TWPP) in winter. The TWPP excites a poleward Rossby wave train that propagates across the North Pacific and directly strengthens the ABNA. The above physical processes can be well reproduced by a linear baroclinic model (LBM). Based on the ESCDP and MCSST predictors, an empirical model is established and shows a promising prediction skill of the ABNA during the hindcast period. This can provide a useful strategy for seasonal prediction of winter climate in the Northern Hemisphere extratropics. Significance Statement Extreme cold events have influenced both Asian and North American continents during the past decades, causing huge socioeconomic impacts. The Asian–Bering–North American teleconnection is found to be responsible for coherent changes of winter climate in these two continents besides the Pacific–North America pattern. Our results indicate that Eurasian snow cover and the Maritime Continent sea surface temperature are important sources of predictability for the Asian–Bering–North American teleconnection, and can be used to predict coherent and cross-continent variations of winter surface air temperature. We propose that the Asian–Bering–North American teleconnection and these two predictors should be included in operational monitoring and prediction systems, helping to improve the prediction skill of winter climate in the Northern Hemisphere continents.

Mechanism of the wintertime subseasonal surface air temperature variability over Eurasia

The formation mechanism responsible for the leading mode of the subseasonal variability of wintertime surface air temperature (SAT) over Eurasia is investigated. The leading SAT mode over Eurasia is characterized by a triple pattern with strong cold anomalies centered over northern Eurasia and weaker warm anomalies over the Arctic and East Asia, respectively, which has a deep barotropic structure and extends from the surface to the upper troposphere. It is tightly coupled to a wave-like atmospheric circulation, which stretches from the North Atlantic to East Asia and resembles the Scandinavia teleconnection pattern. Its formation mechanism is further revealed through the analysis of the temperature budget. The atmospheric circulation-induced horizontal advection is found to be the primary driver of the cold anomalies over northern Eurasia associated with the leading SAT mode in two steps. First, the advection of the climatological temperature by the mode-associated meridional wind anomalies triggers the cooling in the western part of Eurasia. Second, the advection of the above cold anomalies by background westerly winds from west Eurasia to the east further redistributes the cold anomalies. The meridional and zonal advection eventually causes the mode-associated strong cold anomalies over northern Eurasia.

Role of Atmosphere–Ocean–Ice Interaction in the Linkage between December Bering Sea Ice and Subsequent February Surface Air Temperature over North America

Abstract This study revealed that the interannual variations of December Bering Sea ice and subsequent February surface air temperature (SAT) over North America are significantly correlated during 2000/01–2020/21, which is not the case during 1966/67–1999/2000. During 2000/01–2020/21, reduced December Bering Sea ice is generally followed by a February meridional dipole pattern in the atmospheric circulation over North America, which provides favorable conditions for colder temperatures. Further analysis elucidates that the intensified persistence of December Bering Sea ice anomaly might be responsible for the identified change in such a lead–lag sea ice–SAT linkage. During 2000/01–2020/21, the Bering Sea ice anomaly in December can persist into the subsequent February during which the sea ice anomaly exerts a thermal effect on the atmosphere aloft, stimulates an eastward-propagating Rossby wave train, and causes the meridional dipole pattern over North America. The longer persistence of December Bering Sea ice anomaly during 2000/01–2020/21 is attributed to the interdecadal intensified atmosphere–ocean–ice interaction over the Bering Sea—a positive feedback loop that favors the persistence of the sea ice anomaly. A negative sea ice concentration anomaly with more open water in the Bering Sea would allow the ocean to release more heat and warm more the air aloft. This will further lead to more downward longwave radiation, preventing the sea ice growth and helping maintain the sea ice anomaly. Results of this study indicates that the intensity of atmosphere–ocean–ice interaction in the Bering Sea may modulate the linkage between the February SAT over North America and the preceding December Bering Sea ice.

Characteristic Features of the Antarctic Surface Air Temperature with Different Reanalyses and In Situ Observations and Their Uncertainties

Antarctic surface air temperature (SAT) variability is characterized by strong seasonality and regionality, which are associated with the tropical–polar teleconnections and the radiative forcing caused by the concentration changes in ozone and other greenhouse gases. Nevertheless, the sparse in situ observations and the strong disagreement between different reanalysis datasets hinder coherent conclusions about Antarctic SAT variability. In this study, we use a newly developed statistical method, combined maximum covariance analysis (CMCA), to retrieve coherent SAT modes from six reanalysis datasets and 26 station observations. The results show that the Antarctic SAT variability may be dominated by a continental-wide warming/cooling mode, an East–West Antarctic seesaw mode, and a dipole SAT mode around West Antarctica. These SAT modes are strongly associated with three principal modes of Antarctic atmospheric circulation. Furthermore, all six reanalyses can represent these SAT modes well, compared with the observations, despite a clear deviation over the Antarctic Peninsula associated with the biases in the Foehn wind, which may not be clearly reproduced in a low-resolution reanalysis. This study provides an effective means by which to extract coherent signals from all reanalyses and observations to represent the Antarctic SAT variability, and to improve its predictability and projection.

Historical regional climate changes in Japan in winter as assessed by a 5-km regional climate model with a land surface process

We investigate historical regional climate changes in Japan from 1959 to 2020, analyzing a high-resolution dynamical downscaling forced by the Japanese 55-year Reanalysis (JRA-55). One-year continuous simulations are conducted by the non-hydrostatic regional climate model with a land surface model that includes the snow accumulation process, which enables us to evaluate the seasonal variation of snow cover in all of Japan. Our simulation reproduces interannual variations of the annual mean surface air temperature and annual total precipitation, and it shows rapid warming since around 1980. The annual maximum snow depth and annual maximum daily snowfall show significant decreasing trends at lower elevations on the Japan Sea sides of eastern and western Japan. Areas at higher elevations in eastern Japan show no trend in the maximum snow depth and a significant increasing trend in the maximum daily snowfall. In northern Japan, altitudinal dependencies in snow depth and snowfall changes are smaller on the Japan Sea side than on the Pacific Ocean side: the Japan Sea side shows insignificant changes in snow depth at all elevations, while the Pacific Ocean side shows decreasing and significant increasing trends at lower and higher elevations, respectively. The total number of snow-covered days is decreasing at most elevations in all regions, while the rate of decrease is smaller at higher elevations and latitudes. Composite analyses of annual maximum daily snowfall events at one prefectural city facing the Japan Sea in central Japan indicate that heavy daily snowfall occurs when the Japan Polar air mass Convergence Zone appears over the Japan Sea and the snowfall amounts show increasing and decreasing trends over the mountainous and coastal areas, respectively, due to historical warming and moistening. Our results are basically consistent with previous studies that have focused on future changes in snow depth and snowfall.

Synoptic-scale reversal of dipole surface temperature anomalies over East Asia and Central Siberia in November 2021

In early-to-mid November 2021, a pronounced reversal of surface air temperature (SAT) anomalies (SATAs) occurred over East Asia and Central Siberia, with extreme SATAs that reached up to about 10 °C. Such a synoptic-scale reversal of SATAs was characterized by the alternate emergence of the “colder Central Siberia–warmer East Asia” pattern and the “warmer Central Siberia–colder East Asia” pattern in November 2021. Coinciding with the reversals of the meridional dipole SATAs, large-scale atmospheric circulation anomalies experienced reversed changes. The development of the anomalous cyclonic (anticyclonic) flow over East Aisa (Central Siberia) was crucial for the occurrence of the “warmer Central Siberia–colder East Asia” pattern. Moreover, as the leading mode of daily SAT variability in approximately 56% of the Novembers during 1979–2021, the meridional dipole pattern of warmer (colder) anomalies over Central Siberia and colder (warmer) anomalies over East Asia may be one of the dominant modes of November SAT variability over Eurasia on the synoptic scale.摘要2021年11月, 东亚与中西伯利亚经历了相反的冷暖异常转换, 表现为“中西伯利亚偏冷, 东亚偏暖”与“中西伯利亚偏暖, 东亚偏冷”的交替出现. 该偶极型气温异常的天气尺度反转伴随着大尺度大气环流异常的反转. 进一步分析表明, 东亚与中西伯利亚的偶极型气温异常反转是1979–2021年期间11月欧亚气温日变化的主导模态之一(发生概率超过56%).

Внутригодовая изменчивость температуры приземного воздуха и её моделирование для города Ставрополя

Introduction. It is known that the time course of temperature during the year is seasonal. However, the rates of temperature growth in transition periods are different. This complicates the prediction of such an important parameter, in particular for agriculture, as the air temperature of the surface layer of the atmosphere. Accordingly, the article analyzes the intra-annual variability of air temperature and compares it with a sinusoidal model of the annual temperature course. Materials and research methods. The time series of the air temperature of the surface layer of the atmosphere for the city of Stavropol are considered and the task is to compare the actual and theoretical values of annual amplitudes. In the elementary (sinusoidal) model, this theoretical value turns out to be directly proportional to the annual variance. The time series of temperature differences (inter-monthly changes), the so-called discrete derivatives, is also considered, and the comparison of the usual and discrete derivative of the sine function as an elementary model of the annual temperature course is carried out. A new value is introduced – the standard deviation of variability, which also characterizes the variance, yet not for a number of temperatures, but their differences. Research results and their discussion. It is noted that the theoretical (i.e., valid for the sinusoidal model) and the actual value of the amplitude of the annual temperature course are quite well matched. However, due to non-periodic deviations, the difference between these values can reach 2 °C, which is characterized by asymmetry on the intra-annual variability chart. In addition, the average annual temperature course is considered and its analysis is carried out using discrete derivatives. It is shown that the ratio of the annual temperature amplitude to the amplitude of the discrete derivative of this value is equal to the cyclic frequency of fluctuations of the annual temperature course. Conclusions. The results obtained confirm the possibility of using a sinusoidal model of the annual temperature course (although with some limitations related to the asymmetry and shift of intra-annual peak points). The analysis of the annual temperature course using discrete derivatives and its comparison with the sinusoidal model revealed the features of the average annual intra-annual variability of surface air temperature for the city of Stavropol for the period 1944 – 2022. Sometimes there is a change in the rate of heating or cooling; in rare cases, there is an inversion when considering the time series of average monthly temperatures).