Annual Amplitude Research Articles

Seasonal and between-population variation in heat tolerance and cooling efficiency in a Mediterranean songbird

Discrete populations of widely distributed species may inhabit areas with marked differences in climatic conditions across geographic and seasonal scales, which could result in intraspecific variation in thermal physiology reflecting genetic adaptation, phenotypic plasticity, or both. However, few studies have evaluated inter-population variation in physiological responses to heat. We evaluated within- and inter-population seasonal variation in heat tolerance, cooling efficiency and other key thermoregulatory traits in two Mediterranean populations of Great tit Parus major experiencing contrasting thermal environments: a lowland population subject to hotter summers and a higher annual thermal amplitude than a montane population. Specifically, we measured heat tolerance limits (HTL), body temperature, resting metabolic rate, evaporative water loss, and evaporative cooling efficiency (the ratio between evaporative heat loss to metabolic heat production) within and above the thermoneutral zone during winter and summer. Heat tolerance during summer was greater in lowland than in montane birds; indeed, lowland birds seasonally increased this trait to a significant level, while montane ones did to a lesser extent. Besides, lowland birds showed greater evaporative cooling efficiency during summer (possibly due in part to reductions in total endogenous heat load), while surprisingly montane ones showed the opposite trend. Thus, lowland birds displayed greater seasonal flexibility in HTL, body temperature and resting metabolic rate above thermoneutrality, thus giving some support to the climatic variability hypothesis — that flexibility in thermoregulatory traits should increase with climatic variability. Our results partially support the idea that songbirds’ adaptive thermoregulation in the heat is flexible, highlighting the importance of considering intraspecific variation in thermoregulatory traits when modelling the future distribution and persistence of species under different climate change scenarios.

Modeling the Effects of Temperature and Limiting Nutrients on the Competition of an Invasive Floating Plant, Pontederia crassipes, with Submersed Vegetation in a Shallow Lake.

The potential for a non-native plant species to invade a new habitat depends on broadscale factors such as climate, local factors such as nutrient availability, and the biotic community of the habitat into which the plant species is introduced. We developed a spatially explicit model to assess the risk of expansion of a floating invasive aquatic plant species (FAV), the water hyacinth (Pontederia crassipes), an invader in the United States, beyond its present range. Our model used known data on growth rates and competition with a native submersed aquatic macrophyte (SAV). In particular, the model simulated an invasion into a habitat with a mean annual temperature different from its own growth optimum, in which we also simulated seasonal fluctuations in temperature. Twenty different nutrient concentrations and eight different temperature scenarios, with different mean annual amplitudes of seasonal temperature variation around the mean of the invaded habitat, were simulated. In each case, the ability of the water hyacinth to invade and either exclude or coexist with the native vegetation was determined. As the temperature pattern was changed from tropical towards increasingly cooler temperate levels, the competitive advantage shifted from the tropical FAV to the more temperate SAV, with a wide range in which coexistence occurred. High nutrient concentrations allowed the coexistence of FAV, even at cooler annual temperatures. But even at the highest nutrient concentrations in the model, the FAV was unlikely to persist under the current climates of latitudes in the Southeastern United States above that of Northern Alabama. This result may have some implications for where control efforts need to be concentrated.

Epidemiological characteristics and transmission dynamics of dengue fever in China

China has experienced successive waves of dengue epidemics over the past decade. Nationwide data on 95,339 dengue cases, 89 surveillance sites for mosquito density and population mobility between 337 cities during 2013-20 were extracted. Weekly dengue time series including time trends and harmonic terms were fitted using seasonal regression models, and the amplitude and peak timing of the annual and semiannual cycles were estimated. A data-driven model-inference approach was used to simulate the epidemic at city-scale and estimate time-evolving epidemiological parameters. We found that the geographical distribution of dengue cases was expanding, and the main imported areas as well as external sources of imported cases changed. Dengue cases were predominantly concentrated in southern China and it exhibited an annual peak of activity, typically peaking in September. The annual amplitude of dengue epidemic varied with latitude (F = 19.62, P = 0.0001), mainly characterizing by large in southern cities and small in northern cities. The effective reproduction number Reff across cities is commonly greater than 1 in several specific months from July to November, further confirming the seasonal fluctuations and spatial heterogeneity of dengue epidemics. The results of this national study help to better informing interventions for future dengue epidemics in China.

A novel Slepian approach for determining mass-term sea level from GRACE over the South China Sea

Treatment of land-to-ocean leakage is crucial in modeling the mass-term sea level (MSL) using the Gravity Recovery and Climate Experiment (GRACE) satellite gravity measurements. In this study, we utilized the Spherical Slepian functions (SSFs) to determine MSL variations in the South China Sea. A sensitivity simulation in terms of trend, annual amplitude, and phase revealed that the SSF solution with a 1° coastal buffer zone provides a better land-to-ocean leakage correction than traditionally used Spherical Harmonics (SH). It was also found that an additional smoothing procedure for SSF with low concentrating energy could significantly reduce the high-frequency noise in GRACE (e.g., the north–south strips). The spatiotemporal characteristics of the true MSL were further compared among GRACE SH and Mascon solutions, model-predicted ocean bottom pressure, and steric-corrected altimetric data (i.e., satellite-altimetric sea level minus steric effect). Results revealed that despite the SSF-inverted regional MSL solution being generally similar to other results, this technique notably recovered the realistic magnitude of detailed features. The apparent MSL signal was, for instance, precisely recovered in the central part of the Gulf of Thailand and the Sunda Shelf by the SSF, while the SH significantly underestimated it due to smoothing. In addition to the seasonality, the interannual signal decomposed from the SSF-inverted residual MSL (by removing the trend and periodic signals) was the strongest and well cross-correlated with the Southern Oscillation Index. With more detailed spatial patterns revealed by MSL from GRACE SSF, our findings demonstrate that SSF is more suitable for regional-scale studies.

Significant Increase in Global Steric Sea Level Variations over the Past 40 Years

Understanding global sea level variations and exploring their causes hold significant importance for future climate change predictions and the sustainable development of mankind, with the steric sea level (SSL) variations being one of the primary contributors to these changes. Here, we utilize four types of temperature and salinity products (i.e., EN4, IAP, SODA, and GDCSM) to investigate the spatiotemporal characteristics of global SSL changes from 1980 to 2020. We also explore the relationship between SSL changes and the El Niño-Southern Oscillation (ENSO) phenomenon. The findings reveal a rising trend of 0.64–0.97 mm/a in global SSL over the past 40 years, and the annual amplitudes of SSL time series are within the range of 0–50 mm. The SSL trend at a depth of 0–100 m exerts the greatest influence on the overall trend. The ENSO phenomenon has an obvious influence on sea level changes both in the equatorial Pacific region and global scale. The changes in the global sea level (GSL) associated with ENSO are primarily caused by changes in SSL. This study benefits the understanding of SSL changes and their connection to climate change, serves as a reference for comprehensively assessing sea level change mechanisms using diverse datasets and remote sensing technology, and further provides a scientific basis for the sustainable development of mankind in coastal areas.

High Spatial Resolution in Total Water Storage Variations Inferred From GPS: Case Study in the Great Lakes Watershed, US

AbstractAssessing spatiotemporal water storage variability in the Great Lakes Watershed (GLW) is critical given its transboundary status impacting both Canada and the United States. Here, we apply a novel inversion strategy to global positioning system (GPS) vertical movements to achieve high spatial resolution total water storage (TWS) variations in GLW through improved processing. The steps are composed of removing load changes driven by the lake water fluctuation by forward modeling, isolating the Great Lakes grids to solve the ill‐conditioned problem in inversion, and inverting the GPS residual series to estimate TWS variations on land (TWSGPS). The results show that the regional dense continuous GPS observation network can successfully resolve TWS on land at monthly timescales with 30–45 km spatial resolution. We also could effectively capture fine‐scale TWS features than GRACE/GFO mascon products. GRACE/GFO satellites largely underestimate seasonal and long‐term TWS spatial fluctuations, but their temporal patterns coincide with those from GPS. The average annual amplitude of TWSGPS on land reaches 82.0 mm, greatly exceeding estimates from GRACE/GFO (∼48.0 mm) and composite hydrological model outputs (∼62.0 mm). The seasonal groundwater fluctuations inferred from GPS have peak‐to‐peak amplitudes of ∼40 km3 with the maximum around September. This coincides with that from GRACE/GFO. However, the magnitudes and phases of groundwater storage from GPS vary markedly among the subbasins in GLW, and the different snow and soil moisture amounts measured in each subbasin cause discrepancies among these GPS estimates. This study shows the value of GPS data in spatially downscaling GRACE/GFO data and providing high‐resolution output at spatiotemporal scales with low latency.

Eccentricity forcing on tropical ocean seasonality

Abstract. The amount of radiative energy received at the Earth's surface depends on two factors: Earth–Sun distance and sunlight angle. Because of the former, high-eccentricity cycles can induce the appearance of seasons in the tropical ocean. In this paper, we use the Earth system model IPSL-CM5A2 to investigate the response of the low-latitude ocean to variations in Earth's orbit eccentricity. Sea surface temperature (SST) and primary production (PP) were simulated under six precession configurations at high eccentricity and two configurations at low eccentricity, representing extreme configurations observed over the past 1 million years. Results show that high eccentricity leads to increased seasonality in low-latitude mean SST, with an annual thermal amplitude of approximately 2.2 °C (vs. 0.5 °C at low eccentricity). Low-latitude mean PP, which already exhibits inherent seasonality under low-eccentricity conditions, sees its seasonality largely increased under high eccentricity. As a consequence, we show that on long timescales the intensity of SST seasonality exhibits only the eccentricity frequency, whereas that of PP additionally follows precession dynamics. Furthermore, the seasonal variations in both SST and PP at high eccentricities are influenced by the annual placement of the perihelion with its direct impact of radiative energy received in tropical regions. This leads to a gradual and consistent transition of seasons within the calendar. We introduce the concept of “eccentriseasons”, referring to distinct annual thermal differences observed in tropical oceans under high-eccentricity conditions, which shift gradually throughout the calendar year. These findings have implications for understanding low-latitude climate phenomena such as the El Niño–Southern Oscillation (ENSO) and monsoons in the past.

Detection and interpretation of the time-varying seasonal signals in China with multi-geodetic measurements

The time-varying periodic variations in Global Navigation Satellite System (GNSS) stations affect the reliable time series analysis and appropriate geophysical interpretation. In this study, we apply the singular spectrum analysis (SSA) method to characterize and interpret the periodic patterns of GNSS deformations in China using multiple geodetic datasets. These include 23-year observations from the Crustal Movement Observation Network of China (CMONOC), displacements inferred from the Gravity Recovery and Climate Experiment (GRACE), and loadings derived from Geophysical models (GM). The results reveal that all CMONOC time series exhibit seasonal signals characterized by amplitude and phase modulations, and the SSA method outperforms the traditional least squares fitting (LSF) method in extracting and interpreting the time-varying seasonal signals from the original time series. The decrease in the root mean square (RMS) correlates well with the annual cycle variance estimated by the SSA method, and the average reduction in noise amplitudes is nearly twice as much for SSA filtered results compared with those from the LSF method. With SSA analysis, the time-varying seasonal signals for all the selected stations can be identified in the reconstructed components corresponding to the first ten eigenvalues. Moreover, both RMS reduction and correlation analysis imply the advantages of GRACE solutions in explaining the GNSS periodic variations, and the geophysical effects can account for 71% of the GNSS annual amplitudes, and the average RMS reduction is 15%. The SSA method has proved to be useful for investigating the GNSS time-varying seasonal signals. It could be applicable as an auxiliary tool in the improvement of non-linear variations investigations.

Temporal and spatial variations of terrestrial water storage in the northeastern Tibetan Plateau retrieved by GNSS observations

The variation of solid Earth's hydrologic loading could cause the elastic vertical deformation of the crust, and the Global Navigation Satellite System (GNSS) could effectively monitor the vertical displacement of surface loads. However, the widely used Green's function method does not work well in areas where GNSS sites are sparse. Here, the vertical displacement time series of GNSS stations and the Slepian basis function method have been applied to convert displacement signals into spatial spectrum signals. The elastic mass load theory is used to study the changes in terrestrial water storage on the Northeastern Tibetan Plateau (NETP). The temporal and spatial characteristics of seasonal water changes are well-represented by the GNSS, the Gravity Recovery and Climate Experiment (GRACE), and the Global Land Data Assimilation System (GLDAS). Several data points suggest that the change in water storage shows a gradual increase from the northeast to the southwest. The greatest annual amplitude of water storage retrieved by GNSS is ∼159 mm, which is greater than the ∼47 mm and ∼44 mm obtained by GRACE and GLDAS. These results demonstrate that GNSS is capable of capturing small-scale hydrological changes in this region, whereas GRACE and GLDAS data tend to underestimate seasonal variations in water storage. We also used GNSS to describe the hydrological drought conditions in NETP, showing that GNSS could be used as an independent method to characterize hydrological drought events. The findings suggest it could observe water storage with high spatial and temporal resolution and aid in comprehending regional hydrological trends with a sparse GNSS station network.

Comparison of groundwater storage changes over losing and gaining aquifers of China using GRACE satellites, modeling and in-situ observations

Groundwater depletion in intensively exploited aquifers of China has been widely recognized, whereas an overall examination of groundwater storage (GWS) changes over major aquifers remains challenging due to limited data and notable uncertainties. Here, we present a study to explore GWS changes over eighteen major aquifers covering an area of 1,680,000 km2 in China using data obtained from the Gravity Recovery and Climate Experiments (GRACE), global models, and in-situ groundwater level observations. The analysis aims to reveal the discrepancy in annual trends, amplitudes, and phases associated with GWS changes among different aquifers. It is found that GWS changes in the studied aquifers represent a spatial pattern of ‘Wet-gets-more, Dry-gets-less’. An overall decreasing trend of −4.65 ± 0.34 km3/yr is observed by GRACE from 2005 to 2016, consisting of a significant (p < 0.05) increase of 47.28 ± 3.48 km3 in 7 aquifers and decrease of 103.56 ± 2.4 km3 (∼2.6 times the full storage capacity of the Three Gorges Reservoir) in 10 aquifers summed over the 12 years. The annual GWS normally reaches a peak in late July with an area-weighted average annual amplitude of 19 mm, showing notable discrepancy in phases and amplitudes between the losing aquifers (12 mm in middle August) in northern China and gaining aquifers (28 mm in early July) mostly in southern China. GRACE estimates are generally comparable, but can be notably different, with the results obtained from model simulations and in-situ observations at aquifer scale, with the area-weighted average correlation coefficients of 0.6 and 0.5, respectively. This study highlights different GWS changes of losing and gaining aquifers in response to coupled impacts of hydrogeology, climate and human interventions, and calls for divergent adaptions in regional groundwater management.

Assessment of precipitation and near-surface temperature simulation by CMIP6 models in South America

This study evaluated the performance of 50 global climate models (GCMs) from the Coupled Model Intercomparison Project Phase 6 (CMIP6) in simulating the statistical features of precipitation and air temperature in five subdomains of South America during the historical period (1995–2014). Monthly precipitation and temperature simulations were validated with data from the Climate Prediction Center Merged Analysis of Precipitation, the Global Precipitation Climatology Project, and the ERA5 reanalysis. The models’ performance was evaluated using a ranking analysis with statistical metrics such as mean, standard deviation, Pearson’s spatial correlation, annual cycle amplitude, and linear trend. The analyses considered the representation of precipitation and air temperature separately for each subdomain, the representation for all five regions together, and the joint representation of precipitation and air temperature for all five subdomains. In the Brazilian Amazon, the best-performing models were EC-Earth3-Veg, INM-CM4-8, and INMCM5-0 (precipitation), and IPSL-CM6A-LR, MPI-ESM2-0, and IITM-ESM (temperature). In the La Plata Basin, KACE-1-0-G, ACCESS-CM2, and IPSL-CM6A-LR (precipitation), and GFDL-ESM4, TaiESM1, and EC-Earth3-Veg (temperature) yielded the best simulations. In Northeast Brazil, SAM0-UNICON, CESM2, and MCM-UA-1-0 (precipitation), BCC-CSM2-MR, KACE-1-0-G, and CESM2 (temperature) showed the best results. In Argentine Patagonia, the GCMs ACCESS-CM2, ACCESS-ESM1-5 and EC-Earth3-Veg-LR (precipitation), and CAMS-CSM1-0, CMCC-CM2-HR4, and GFDL-ESM4 (temperature) outperformed. Finally, for Southeast Brazil, the models ACCESS-CM2, ACCESS-ESM1-5, and EC-Earth3-Veg-LR (precipitation), and CAMS-CSM1-0, CMCC-CM2-HR4, and GFDL-ESM4 (temperature) yielded the best simulations. The joint evaluation of the regions and variables indicated that the best models are CESM2, TaiESM1, CMCC-CM2-HR4, FIO-ESM-2-0, and MRI-ESM2-0.

Higher accuracy estimation of the weighted mean temperature (Tm) using GPT3 model with new grid coefficients over China

The weighted mean temperature (Tm) is an essential parameter in the field of Global Navigation Satellite System (GNSS) meteorology, as it enables the conversion of zenith wet delay to atmospheric precipitable water vapor (PWV). The existing Tm models, such as the GPT3 model, utilize the empirical annual and semi-annual amplitudes of Tm at grid points along with corresponding trigonometric functions to estimate Tm, making it difficult to provide a more detailed description of the daily variation of Tm. Therefore, the measured surface temperature and water vapor pressure were introduced to calculate the new series of grid coefficients using the least-square method, which enables the GPT3 model to estimate Tm with higher accuracy. In this process, the ERA5 reanalysis data derived from ECMWF from 2001 to 2010 was utilized to compute Tm values, and the new grid coefficient obtained by introducing only surface temperature was considered as scheme #1 and that achieved by introducing both surface temperature and surface water vapor pressure was regarded as scheme #2. The Tm data of 2023 calculated both by the radiosonde and ERA5 reanalysis data were utilized to assess the new grid coefficients for Tm estimation, and the results show that the grid coefficients based on these two surface parameters outperformed those only using the temperature. In the compassion using the ERA5 data, the bias/MAE/RMSE with the two types of new grid coefficients are −0.09/1.89/2.41 K and − 0.07/1.82/2.31 K, respectively, and the improvements reach to 50%/32.5%/34.2% and 61.1%/35%/36.9% compared with GPT3 model. In the comparison with radiosonde data, the scheme #1 and #2 performed a 0.55 K(13.8%) and 0.68 K(17.1%) improvement in the mean RMSE of stations compared with the GPT3 model. Note that the proposed two schemes can effectively improve the accuracy of estimating Tm in the comparison of regions, epochs and seasons with the Bevis and GPT3 model. Furthermore, the impact of Tm on PWV can be improved by the proposed two schemes, which was demonstrated using the theoretical RMSE and relative error of PWV.

Observed Spatiotemporal Variability in the Annual Sea Level Cycle Along the Global Coast

AbstractChanges in the seasonal sea level cycle can modulate the flooding risk along coastlines. Here, we use harmonic analysis to quantify changes in the amplitude and phase of the annual component of the sea level cycle at 798 tide gauge locations along the global coastline where long records are available. We identify coastal hotspots by applying clustering methods revealing coherent regions with similar patterns of variability in the annual sea level cycle. Results show that for most tide gauges the annual amplitude reached its maximum after 1970 and its peak typically occurs during the fall season of the respective hemisphere. Many tide gauges exhibit non‐stationarity in the annual cycle in terms of amplitude and/or phase. For example, at 226 tide gauges we find significant trends in the amplitude (either increasing or decreasing) for the time period after 1970; while several sites (50 in total), mostly in the Mediterranean and around Pacific islands, experienced phase changes leading to shifts in the timing of the peak of the annual cycle by more than a month over their entire record. Our results highlight the importance of accounting for potential non‐stationarity in seasonal mean sea level cycles along coastlines.

Geocryological Conditions of Small Mountain Catchment in the Upper Kolyma Highland (Northeastern Asia)

This research presents a comprehensive environmental assessment of a small mountain permafrost catchment of the Anmangynda River in the Upper Kolyma Highland (Northeastern Asia) over the period of 2021–2023. The study reveals significant diversity in climatic, geocryological, and hydrogeological conditions within this confined area, emphasizing the need for extensive field data collection and monitoring in vast permafrost regions with limited data availability. Key findings include variations in ground temperature, maximum seasonal thaw depth, and depths of zero annual amplitudes of ground temperature at different elevations and landscape types. Groundwater and surface flow dynamics within spring aufeis basins exhibit complex geocryological regimes influenced by icing processes. The presence of aufeis and its impact on local hydrology highlight the ecological significance of this phenomenon. Future research should focus on long-term trends in permafrost dynamics and their relationship with climate change, as well as the ecological effects of aufeis formation on local ecosystems. The study underscores the importance of a multi-faceted approach to environmental assessment, incorporating various environmental parameters and processes, to gain a comprehensive understanding of the intricate interactions within the cryosphere and their responses to changing climate conditions. Such knowledge is essential for addressing broader questions related to climate change, ecosystem resilience, and sustainable resource management in Northeastern Siberia.

The thermal effect of snow cover on ground surface temperature in the Northern Hemisphere

Snow cover is critical to the ground thermal regime because it affects surface conditions and the energy balance. Prior work inherently included confounding effects from vegetation and the soil when estimating the snow’s effect by using the differences between air and ground surface or soil temperature. Here we use the Kudryavtsev model including a snow module to isolate the effect of only the snow cover during winter, based on observational sites across the Northern Hemisphere. We find that snow’s damping of annual mean ground surface temperature averages 5.06 ± 3.15 °C and ranges 0 °C–10 °C, while damping of the annual ground surface temperature amplitude is 7.95 ± 4.95 °C, ranging 0 °C–20 °C. Greater insulation occurs in the high-latitudes. The insulating effect is primarily driven by snow depth, but also the combination of air temperature and its amplitude, snow depth, and duration. Snow cover duration and low air temperature enhance snow’s insulating ability. These observational results that isolate the damping effect of only the snow could play a significant role in better understanding the energy change between air and the ground.

Seasonal constraint of dynamic water temperature on riverine dissolved inorganic nitrogen transport in land surface modeling

Riverine dissolved inorganic nitrogen (DIN) transport plays an important role in the link between terrestrial and marine ecosystems, while the seasonal changes of water temperature exert a strong control on DIN dynamics. However, the response of the flow of DIN to dynamic water temperature in large rivers is not well known at the global scale. In this study, based on a recently developed land surface model coupled with riverine water temperature and DIN transport schemes, two numerical simulations, with and without dynamic water temperature, were implemented to investigate the seasonal constraint of dynamic water temperature on the change in riverine DIN flow. Results show that the water temperature could be a key controlling factor for the spatial distribution of global DIN flows. After integrating dynamic water temperature estimation into land surface modeling, the annual amplitudes of DIN flow were 5%–25% smaller than before between 30°N and 30°S, while approximately 10% larger in other latitudinal zones. Less denitrification was out of the scope of 40°N–20°S in summer. In eastern China, the dynamic water temperature made the DIN flow reduce by 1%–3% in summer, while it made it increase by 1%–5% in winter. A seasonal constraint of dynamic water temperature, making the amplitude of monthly fluctuation reduce by about 60%, was found in global large rivers. This study shows the importance of dynamic water temperature in the seasonal modeling of riverine DIN flow, and provides a scientific reference for land surface model development and water environment management.摘要水体温度变化对河流可溶性无机氮(DIN)输送有着强烈控制作用. 然而, 在全球尺度上河流DIN输送量对水温度变化的响应尚不清楚. 因此, 本文基于陆面过程模式, 耦合河流水温估算和DIN传输方案, 设定有, 无动态水温情景, 对比研究陆面模拟中水温变化对河流DIN通量变化的影响. 结果表明: 在考虑水温动态变化后, 在30°N和30°S之间, DIN通量年振幅减小5%–25%. 在中国东部地区, 水温动态变化使河流DIN通量在夏季减少1%–3%, 在冬季增加1%–5%, 对DIN通量具有明显的季节性约束作用, 表明动态水温的表达在河流DIN输送模拟中的重要性.

Spatiotemporal characteristics and variability in the thermal state of permafrost on the Qinghai–Tibet Plateau

AbstractPermafrost degradation on the Qinghai–Tibet Plateau (QTP) has significant impacts on climate, hydrology, and engineering and environmental systems. To understand the temporal and spatial characteristics of permafrost on the QTP, we quantified the variation in active layer thickness (ALT), permafrost thermal state, and future permafrost change under different scenarios using observational data, reanalysis data, and the numerical permafrost model. Generally, ALT ranged from 0.5 to 6.0 m with an average of 2.39 m, and mean annual ground temperature (at a depth of zero annual amplitude for ground temperature) mainly ranged between 0 and −3°C with an average of −0.85°C. The soil temperatures in different layers based on the ERA5‐Land data revealed even stronger increasing trends, for example, 0.245, 0.245, 0.244, and 0.238°C/decade at depths of 0–7, 7–28, 28–100, and 100–289 cm from 1980 to 2021, compared to those during the period from 1960 to 2021, which were 0.153, 0.156, 0.155, and 0.149°C/decade, respectively. The average warming trends in annual mean soil temperature were 0.153 and 0.243°C/decade from 1960 to 2021 and 1980 to 2021, respectively. The average rate of thickening of the ALT among the 10 active layer observation sites was 2.84 cm/year. There was a significant warming trend in ground temperature above ~15 m with warming of 0.063 to 0.120, 0.026 to 0.182, 0.101 to 0.314, and 0.189 to 0.303°C/decade at the QTB01, QTB06, QTB08, and XDTGT sites, respectively, and yearly minimum ground temperatures exhibited stronger warming trends than maximum ground temperatures. In addition, the simulation revealed significant increases in ground temperature at the Xidatan (XDT) and Tanggula (TGL) sites under both historical and future Representative Concentration Pathway (RCP) scenarios, but the increases in ground temperature were significantly greater at TGL than XDT. These findings provide important information for understanding the variability in permafrost degradation processes and improving simulations of permafrost change under climate change on the QTP.

Seasonal and Interannual Variations of Global Tides in the Mesosphere and Lower Thermosphere Neutral Winds: II. Semidiurnal and Terdiurnal Tides

AbstractIn the mesosphere and lower thermosphere (MLT) region, semidiurnal and terdiurnal tides are dominant at middle and high latitudes and are important for the dynamics and structures. Using the global neutral horizontal wind data in the MLT region observed by TIMED Doppler interferometer from 2002 to 2021, the seasonal and interannual variations of six semidiurnal and terdiurnal tidal components (SW2, SW3, SW4, TW3, TW2 and TW4) are investigated. Particularly, the responses of these tidal components to the stratospheric quasi‐biennial oscillation (SQBO) and the solar cycle are presented. The results indicate that: (a) seasonal and interannual variations of these tidal components are pronounced in their peak regions. The peak region is defined as the region where the ratio of the annual mean amplitude to the maximum annual mean amplitude is larger than 0.8. (b) In their peak regions, migrating tidal components exhibit strong seasonal variations at annual (annual oscillations (AO)), semiannual (semiannual oscillations (SAO)) and terannual (terannual oscillations (TAO)) periods, whereas nonmigrating tidal components only exhibit prominent AO and SAO. (c) In their peak regions, the responses of the annual mean amplitudes of these tidal components to SQBO are negative; the responses of migrating tidal components to solar cycle are negative whereas those of nonmigrating tidal components are positive. (d) For these tidal components, the responses of the amplitudes of seasonal variations to SQBO and solar cycle are weaker than their annual mean amplitudes, and the latitude × altitude response patterns are not always consistent with those of the annual mean amplitudes.

Seasonal and Interannual Variations of Global Tides in the Mesosphere and Lower Thermosphere Neutral Winds: I. Diurnal Tides

AbstractIn the mesosphere and lower thermosphere, diurnal tides are responsible for the dynamics and structures at low latitudes since they have largest amplitudes there. Based on the 20‐year (2002−2021) observations from Thermosphere‐Ionosphere‐Mesosphere Energetics and Dynamics Doppler interferometer (TIDI), we investigate the seasonal variations of three diurnal tidal components (DW1, DE3, DW2), and their responses to stratospheric quasi‐biennial oscillation (SQBO) and solar cycle globally. The results show that: (a) DW1, DE3 and DW2 show prominent semiannual (SAO) and annual oscillations (AO) in their peak regions where the ratio of their annual mean amplitude to their maximum annual mean amplitude is larger than 0.8. DW1 also exhibit strong terannual oscillations (TAO) especially in meridional wind. (b) The responses of the amplitudes of seasonal variations of DW1, DE3 and DW2 to SQBO and solar cycle are comparable in magnitude to those of their annual mean amplitudes (for response to solar cycle, even stronger in some cases), and thus cannot be neglected. (c) In their respective peak regions, the responses of annual mean amplitudes of these diurnal tidal components to SQBO are uniformly positive except DW2, and their responses to solar cycle are uniformly negative. For these diurnal tides, the amplitudes of the dominant seasonal variations exhibit consistent response patterns with those of annual means to the SQBO/solar cycle. (d) Empirical formulas are given, which well describe the seasonal and interannual variations of dominant diurnal tidal components in their peak regions.

Анализ индекса континентальности климата на территории Северо-Востока России

Analysis of climate continentality is a powerful tool for studying and forecasting weath­er. Considering the continentality index enables determining current climate characteristics and predicting potential changes. This study aims to assess climate change in Russia’s North-East by analysing the continentality index as a complex integral indicator of these changes applicable to vast territories. Although there are many methods for assessing climate continentality, there is no uni­versal methodology. It is proposed in this contribution to employ two of the existing tech­niques. The first focuses on the area’s annual temperature amplitude and geographic latitude. The second involves a calculation of the index based on average January and July tempera­tures, the sum of seasonal precipitation and the area’s latitude. An analysis of the index val­ues of the base and calculation periods leads one to conclude that these values do not change significantly towards either weaker or stronger continentality across the study area.