Annual Cycle Of Air Temperature Research Articles

Regional changes of surface air temperature annual cycle in the Northern Hemisphere land areas

AbstractThe regional amplitude and phase characteristics of surface (2 m) air temperature (SAT) annual cycle (AC) over the Northern Hemisphere land area are analysed by the clustering method for the period 1953–2018. The five clusters are found in the nonlinear changes of AC amplitude and the six clusters are found in the AC phase. The spatial distributions of clusters are not the same for amplitude and phase, but the similarity is that both the amplitude and phase have remarkably different trends in the mainland of Eurasia and North America, even though these two regions locate over the similar latitudinal zone. Descending trends of AC amplitude are found for the whole period 1953–2018 in most areas, except in and around Greenland. However, when checking the nonlinear variation and making a piece‐wise linear fit, the abnormal increasing trend (stronger seasonality) appears in the major part of Eurasia after the year 1990. The comparisons of surface radiation fluxes in Eurasia and North America indicate that the long‐term reduction of the reflection and absorption of clouds and aerosols with the declined surface albedo after 1980–1985 may lead to the amplitude amplification after 1990 in Eurasia. In contrast, the variation of surface radiation in North America remains unchanged, where the decreasing trend of amplitude may result from other causes. The overall phase trend is increasing (toward earlier season), but in North America after 1990, the phase shift becomes delayed. The phase variations are correlated to North Atlantic Oscillation (NAO) cold season index over almost all regions, especially in Europe.

The ability of climate models to reproduce the weakening of the annual air temperature cycle over the central part of the Russian Plain

Natural variability plays a large role in local climate that makes it difficult to specify the causes of the weakening of the annual cycle of surface air temperature in the central part of the Russian Plain. This study is to check whether this could be caused by the global warming by using the outputs of climate models. For this purpose, the changes in monthly surface air temperature simulated for the period from 1950 to 2010 were used to calculate the coefficients of correlation between the annual mean of the air temperature and the amplitude of its annual cycle. The negative correlation demonstrated by some models allows us to attribute, at least with a low confidence, the weakening of the annual temperature cycle in the central part of the Russian Plain to the global warming. The model disagreement on the sign of the correlation calls for the study of model ability to reproduce the changes in zonal and meridional atmospheric circulation over the eastern part of the European continent.

On Using Lumped Parameter Models and Temperature Cycles in Heterogeneous Aquifers.

The use of the annual cycles of stable isotopes to estimate the parameters of transit time distribution (TTD) functions has been recently criticized by Kirchner who showed that if the catchment is heterogeneous the mean residence time calculated from the damping of the amplitude of the input signal is often underestimated by large factors. We modify Kirchner's initial analysis and show that the estimation bias is a function of the degree of heterogeneity. In low heterogeneity cases corresponding to permeable aquifers, the TTD of a simple exponential model developed assuming a homogeneous medium deviates only slightly from the true TTD, and thus estimated and true mean transit times are close. We also develop and test for a sandstone aquifer a model predicting the temperature amplitude of water at the outlet of a groundwater system from the annual air temperature cycle, and show that even though temperature is not a conservative tracer, it can be used to calibrate a lumped parameter model describing the TTD of the aquifer.

Climate-related trends and meteorological conditions in the Porsanger fjord, Norway

Summary Climate-related trends and meteorological conditions in the Porsanger fjord, in the vicinity of the Barents Sea, have been analyzed. Meteorological data include wind speed and direction, air temperature (AT) and precipitation from Era-Interim reanalysis (1986–2015) as well as local observations (2006–2015) from Honningsvaag and Lakselv. Statistically significant trends in annual AT means are 0.0485°C year−1 near the fjord mouth and 0.0416°C year−1 near the fjord head. Wind speed and precipitation data do not reveal any definite trends. Statistical analysis confirms the significant spatial variability of meteorological conditions in the fjord. For example, there are large differences in the annual AT cycle, with respective monthly means for January and July of −8.4 and 12.6°C at Lakselv (fjord head) and −2.5 and 10.1°C at Honningsvaag (fjord mouth). Strong wind events (>12 m s−1) are more frequent at Honningsvaag than at Lakselv. The annual cycle is characterized by stronger winds in winter and seasonality of wind direction. At Lakselv, the dominant wind directions in summer are: N, NNW and S and in winter: S and SSE. At Honningsvaag, the wind directions in summer present strong variability, no fixed pattern being pronounced, whilst the dominant sectors in winter are: S and SSW. Daily cycles in AT and wind speed are also observed. Precipitation at a given location can change by about 30% year-on-year and varies spatially. Estimates of terrigenous water discharge (derived from the E-HYPE model) reveal a seasonal cycle with the maximum discharge in late spring/early summer.

The dependency between annual air temperature and solar activity. A case study of Warsaw in 1951–2010.

Abstract The paper demonstrates a dependency between the annual average daily air temperature course (cycle) in Warsaw and the profile of annual solar activity linked to rotation (with a period of 25–31 days). Waves of cold (ΔT <0) or heat (ΔT ≥ 0) were defined as ΔT deviations of daily average temperature (T) using a regression sinusoid f (t) with a period of 365 days. Cold waves were found to generally occur at times of low daily average solar activity (relative to 60-year average), while hot waves tended to coincide with high Wolf numbers. The cycles of the variables were derived using the sinusoid regression method (Boryczka 1998). The maximum sinusoid regression of the annual air-temperature cycle T is delayed by nearly one month vis-à-vis the maximum declination of the Sun. The maximum of the regression sinusoid of daily average Wolf numbers (W) was delayed from the maximum declination by more than two months.

Human Influences on Changes in the Temperature Seasonality in Mid- to High-Latitude Land Areas

Abstract The annual cycle is the largest variability for many climate variables outside the tropics. Whether human activities have affected the annual cycle at the regional scale is unclear. In this study, long-term changes in the amplitude of surface air temperature annual cycle in the observations are compared with those simulated by the climate models participating in phase 5 of the Coupled Model Intercomparison Project (CMIP5). Different spatial domains ranging from hemispheric to subcontinental scales in mid- to high-latitude land areas for the period 1950–2005 are considered. Both the optimal fingerprinting and a nonoptimal detection and attribution technique are used. The results show that the space–time pattern of model-simulated responses to the combined effect of anthropogenic and natural forcings is consistent with the observed changes. In particular, models capture not only the decrease in the temperature seasonality in the northern high latitudes and East Asia, but also the increase in the Mediterranean region. A human influence on the weakening in the temperature seasonality in the Northern Hemisphere is detected, particularly in the high latitudes (50°–70°N) where the influence of the anthropogenic forcing can be separated from that of the natural forcing.

A spatial modelling framework for assessing climate change impacts on freshwater ecosystems: Response of brown trout (Salmo trutta L.) biomass to warming water temperature

Mountain regions worldwide are particularly sensitive to on-going climate change. Specifically in the Alps in Switzerland, the temperature has increased twice as fast than in the rest of the Northern hemisphere. Water temperature closely follows the annual air temperature cycle, severely impacting streams and freshwater ecosystems.In the last 20 years, brown trout (Salmo trutta L.) catch has declined by approximately 40–50% in many rivers in Switzerland. Increasing water temperature has been suggested as one of the most likely cause of this decline. Temperature has a direct effect on trout population dynamics through developmental and disease control but can also indirectly impact dynamics via food-web interactions such as resource availability.We developed a spatially explicit modelling framework that allows spatial and temporal projections of trout biomass using the Aare river catchment as a model system, in order to assess the spatial and seasonal patterns of trout biomass variation. Given that biomass has a seasonal variation depending on trout life history stage, we developed seasonal biomass variation models for three periods of the year (Autumn–Winter, Spring and Summer). Because stream water temperature is a critical parameter for brown trout development, we first calibrated a model to predict water temperature as a function of air temperature to be able to further apply climate change scenarios. We then built a model of trout biomass variation by linking water temperature to trout biomass measurements collected by electro-fishing in 21 stations from 2009 to 2011.The different modelling components of our framework had overall a good predictive ability and we could show a seasonal effect of water temperature affecting trout biomass variation. Our statistical framework uses a minimum set of input variables that make it easily transferable to other study areas or fish species but could be improved by including effects of the biotic environment and the evolution of demographical parameters over time. However, our framework still remains informative to spatially highlight where potential changes of water temperature could affect trout biomass.

Climatic change on King George Island in the years 1948–2011

Abstract The climatic change on King George Island (KGI) in the South Shetland Islands, Antarctica, in the years of 1948-2011 are presented. In the reference period, a statistically significant increase in the air temperature (0.19ºC/10 years, 1.2ºC in the analysed period) occurred along with a decrease in atmospheric pressure (−0.36 hPa/10 years, 2.3 hPa). In winter time, the warming up is more than twice as large as in summer. This leads to decrease in the amplitude of the annual cycle of air temperature. On KGI, there is also a warming trend of daily maximum and daily minimum air temperature. The evidently faster increase in daily minimum results in a decrease of the diurnal temperature range. The largest changes of air pressure took place in the summertime (−0.58 hPa/10 years) and winter (−0.34 hPa/10 years). The Semiannual Oscillation pattern of air pressure was disturbed. Climate changes on KGI are correlated with changing surface temperatures of the ocean and the concentra− tion of sea ice. The precipitation on KGI is characterised by substantial variability year to year. In the analysed period, no statistically significant trend in atmospheric precipitation can be observed. The climate change on KGI results in substantial and rapid changes in the environment, which poses a great threat to the local ecosystem.

Influence of the Laurentian Great Lakes on Regional Climate*

Abstract The influence of the Laurentian Great Lakes on climate is assessed by comparing two decade-long simulations, with the lakes either included or excluded, using the Abdus Salam International Centre for Theoretical Physics Regional Climate Model, version 4. The Great Lakes dampen the variability in near-surface air temperature across the surrounding region while reducing the amplitude of the diurnal cycle and annual cycle of air temperature. The impacts of the Great Lakes on the regional surface energy budget include an increase (decrease) in turbulent fluxes during the cold (warm) season and an increase in surface downward shortwave radiation flux during summer due to diminished atmospheric moisture and convective cloud amount. Changes in the hydrologic budget due to the presence of the Great Lakes include increases in evaporation and precipitation during October–March and decreases during May–August, along with springtime reductions in snowmelt-related runoff. Circulation responses consist of a regionwide decrease in sea level pressure in autumn–winter and an increase in summer, with enhanced ascent and descent in the two seasons, respectively. The most pronounced simulated impact of the Great Lakes on synoptic systems traversing the basin is a weakening of cold-season anticyclones.

Large-Scale Control on the Patagonian Climate

Abstract Patagonia, located in southern South America, is a vast and remote region holding a rich variety of past environmental records but a small number of meteorological stations. Precipitation over this region is mostly produced by disturbances embedded in the westerly flow and is strongly modified by the austral Andes. Uplift on the windward side leads to hyperhumid conditions along the Pacific coast and the western slope of the Andes; in contrast, downslope subsidence dries the eastern plains leading to arid, highly evaporative conditions. The authors investigate the dependence of Patagonia’s local climate (precipitation and near-surface air temperature) year-to-year variability on large-scale circulation anomalies using results from a 30-yr-long high-resolution numerical simulation. Variations of the low-level zonal wind account for a large fraction of the rainfall variability at synoptic and interannual time scales. Zonal wind also controls the amplitude of the air temperature annual cycle by changing the intensity of the seasonally varying temperature advection. The main modes of year-to-year variability of the zonal flow over southern South America are also investigated. Year round there is a dipole between mid- and high latitudes. The node separating wind anomalies of opposite sign migrates through the seasons, leading to a dipole over Patagonia during austral summer and a monopole during winter. Reanalysis data also suggests that westerly flow has mostly decreased over north-central Patagonia during the last four decades, causing a drying trend to the west of the Andes, but a modest increase is exhibited over the southern tip of the continent.

Exponential sinusoidal model for predicting temperature inside underground wine cellars from a Spanish region

This article develops a mathematical model for determining the annual cycle of air temperature inside traditional underground wine cellars in the Spanish region of “Ribera del Duero”, known because of the quality of its wines. It modifies the sinusoidal analytical model for soil temperature calculation. Results obtained when contrasting the proposed model with experimental data of three subterranean wine cellars for 2 years are satisfactory. The RMSE is below 1 °C and the index of agreement is above 0.96 for the three cellars. When using the average of experimental data corresponding to the 2 years’ time, results improve noticeably: the RMSE decreases by more than 30% and the mean d reaches 0.99. This model should be a useful tool for designing underground wine cellars making the most of soil energy advantages.

Climatology and long-term variability of the annual cycle of air temperature over Europe

Climatology and long-term variations of characteristics of the annual cycle of air temperature over Europe are studied in terms of amplitudes and phases on the basis of data for 1901–2000. It is shown that the spatial amplitude distribution of the annual cycle of air temperature well reflects a decrease in the influence of the Atlantic and an increase in the continentality of the European climate from west to east. It is found that positive (negative) anomalies of annual mean air temperature are accompanied mainly by negative (positive) anomalies of amplitudes and phases of the annual cycle air temperature. In other words, abnormally warm years are characterized by smaller amplitudes of the annual cycle, and the maximum in the annual cycle of air temperature is observed earlier than usual. The first empirical orthogonal function (EOF) mode of temperature amplitudes is connected with the North Atlantic Oscillation (NAO). It means that at a high NAO index one observes small (large) amplitudes of the annual cycle of air temperature over Europe.

Sensitivity of amplitude-phase characteristics of the surface air temperature annual cycle to variations in annual mean temperature

The ERA40 and NCEP/NCAR data over 1958-1998 were used to estimate the sensitivity of ampli- tude-phase characteristics (APCs) of the annual cycle (AC) of the surface air temperature (SAT) T s . The results were compared with outputs of the ECHAM4/OPYC3, HadCM3, and INM RAS general circulation models and the IAP RAS climate model of intermediate complexity, which were run with variations in greenhouse gases and sulfate aerosol specified over 1860-2100. The analysis was performed in terms of the linear regres- sion coefficients b of SAT AC APCs on the local annual mean temperature and in terms of the sensitivity char- acteristic D = br 2 , which takes into account not only the linear regression coefficient but also its statistical sig- nificance (via the correlation coefficient r ). The reanalysis data were used to reveal the features of the tendencies of change in the SAT AC APCs in various regions, including areas near the snow-ice boundary, storm-track ocean regions, large desert areas, and the tropical Pacific. These results agree with earlier observations. The model computations are in fairly good agreement with the reanalysis data in regions of statistically significant variations in SAT AC APCs. The differences between individual models and the reanalysis data can be explained, in particular, in terms of the features of the sea-ice schemes used in the models. Over the land in the middle and high latitudes of the Northern Hemisphere, the absolute values of D for the fall phase time and the interval of exceeding exhibit a positive intermodel correlation with the absolute value of D for the annual-har- monic amplitude. Over the ocean, the models reproducing larger (in modulus) sensitivity parameters of the SAT annual-harmonic amplitude are generally characterized by larger (in modulus) negative sensitivity values of the semiannual-harmonic amplitude T s , 2 , especially at latitudes characteristic of the sea-ice boundary. In contrast to the averaged fields of AC APCs and their interannual standard deviations, the sensitivity parameters of the SAT AC APCs on a regional scale vary noticeably for various types of anthropogenic forcing.

Influence of the seasonal snow cover on the ground thermal regime: An overview

The presence of seasonal snow cover during the cold season of the annual air temperature cycle has significant influence on the ground thermal regime in cold regions. Snow has high albedo and emissivity that cool the snow surface, high absorptivity that tends to warm the snow surface, low thermal conductivity so that a snow layer acts as an insulator, and high latent heat due to snowmelt that is a heat sink. The overall impact of snow cover on the ground thermal regime depends on the timing, duration, accumulation, and melting processes of seasonal snow cover; density, structure, and thickness of seasonal snow cover; and interactions of snow cover with micrometeorological conditions, local microrelief, vegetation, and the geographical locations. Over different timescales either the cooling or warming impact of seasonal snow cover may dominate. In the continuous permafrost regions, impact of seasonal snow cover can result in an increase of the mean annual ground and permafrost surface temperature by several degrees, whereas in discontinuous and sporadic permafrost regions the absence of seasonal snow cover may be a key factor for permafrost development. In seasonally frozen ground regions, snow cover can substantially reduce the seasonal freezing depth. However, the influence of seasonal snow cover on seasonally frozen ground has received relatively little attention, and further study is needed. Ground surface temperatures, reconstructed from deep borehole temperature gradients, have increased by up to 4°C in the past centuries and have been widely used as evidence of paleoclimate change. However, changes in air temperature alone cannot account for the changes in ground temperatures. Changes in seasonal snow conditions might have significantly contributed to the ground surface temperature increase. The influence of seasonal snow cover on soil temperature, soil freezing and thawing processes, and permafrost has considerable impact on carbon exchange between the atmosphere and the ground and on the hydrological cycle in cold regions/cold seasons.

Arctic Ocean sea ice volume: What explains its recent depletion?

Various observations and model results point to an arctic sea ice cover that was extraordinarily thin in the 1990s. This thin ice cover was caused by a strengthened cyclonic circulation of wind and ice and by unusual warmth of springtime air temperatures. Here modeled sea ice volume is decomposed into two components: first, a dynamic or wind‐forced response to interannually varying winds but a fixed annual cycle of air temperature and second, a thermally forced solution responding only to interannually varying temperatures. Over the 52‐year simulation from 1948 to 1999 these two components have a similar range and variance; the wind‐forced component has no substantial trend, but the temperature‐forced component has a significant downward trend of −3% per decade. Total ice volume shows a trend of −4% per decade. Export slightly exceeds production over the simulation. Annual export and production can differ from each other and from year to year by ±30%. This behavior seems to characterize an ice cover highly constrained by interannual variations in forcing and not in balance. The bulk (two thirds) of volume loss from the 1960s to the 1990s is a result of a striking thinning of undeformed ice. The remainder of the volume loss is due to thinning of ridged ice and reduced concentrations. The central Arctic Ocean and particularly the East Siberian Sea suffer the greatest losses (of up to 2 m); the ice north of the Canadian archipelago also thinned since the 1960s by ∼0.5 m.

Atmospheric and coupled model intercomparison in terms of amplitude—Phase characteristics of surface air temperature annual cycle

A model intercomparison in terms of surface air temperature annual cycle amplitude-phase characteristics (SAT AC APC) is performed. The models included in the intercomparison belong to two groups: five atmospheric models with prescribed sea surface temperature and sea ice cover and four coupled models forced by the atmospheric abundances of anthropogenic constituents (in total six coupled model simulations). Over land, the models, simulating higher than observed time averaged SAT, also tend to simulate smaller than observed amplitude of its annual and semiannual harmonics and (outside the Tropics) later-than-observed spring and autumn moments. The models with larger (smaller) time averaged amplitudes of annual and semiannual harmonics also tend to simulate larger (smaller) interannual standard deviations. Over the oceans, the coupled models with larger interannual standard deviations of annual mean SAT tend to simulate larger interannual standard deviations of both annual and semiannual SAT harmonics amplitudes. Most model errors are located in the belts 60°–70°N and 60°–70°S and over Antarctica. These errors are larger for those coupled models which do not employ dynamical modules for sea ice. No systematic differences are found in the simulated time averaged fields of the surface air temperature annual cycle characteristics for atmospheric models on one hand and for the coupled models on the other. But the coupled models generally simulate interannual variability of SAT AC APC better than the atmospheric models (which tend to underestimate it). For the coupled models, the results are not very sensitive to the choice of the particular scenario of anthropogenic forcing. There is a strong linear positive relationship between the model simulated time averaged semiannual SAT harmonics amplitude and interannual standard deviation of annual mean SAT. It is stronger over the tropical oceans and is weaker in the extratropics. In the tropical oceanic areas, it is stronger for the coupled than for the atmospheric models.

Climate of the seasonal cycle in the North Pacific and the North Atlantic oceans

AbstractTime series of monthly sea‐surface temperature (SST), air temperature (AT) and sea level pressure (SLP) were constructed from merged releases of the Comprehensive Ocean‐Atmosphere Data Set (COADS). The time series were decomposed into seasonal and non‐seasonal (short and long‐term) components. The contribution of the seasonal cycle to the total variance of SST and AT exceeds 80% in the mid and in some high latitude locations and reaches its peak (>95%) in the centres of subtropical gyres. In most cases, a combination of annual and semiannual harmonics accounts for more than 95% of the seasonal variability.Amplitudes of SST and AT annual cycles are highest near the western boundaries of the oceans; annual phases of SST and AT increase toward the eastern tropical oceans, revealing a southeastern propagation of the annual cycle over the Northern Hemisphere oceans. The annual cycle of AT leads that of SST by 1–3 weeks. The largest phase differences are observed in the regions of western boundary currents in the North Pacific and the North Atlantic oceans. This is consistent with spatial patterns of integral air–sea heat fluxes. Annual phases of SST increase along the Gulf Stream and the Kuroshio Current. This points to the importance of signal transport by the major ocean currents.The lowest annual amplitudes of SLP are observed along the equator (0°–10°N) in both oceans. There are three distinct areas of high annual amplitudes of SLP in the North Pacific Ocean: Asian, Aleutian and Californian. Unlike the North Pacific, only one such area exists in the North Atlantic centred to the west of Iceland. A remarkable feature in the climate of the North Pacific is a maximum of semiannual SLP amplitudes, centred near 40°N and 170°W. It is also an absolute maximum in the entire Northern Hemisphere. Analysis of phases of harmonics of SLP seasonal cycle has revealed the trajectories of propagation of the annual and semiannual cycles.Analysis of semiannual to annual amplitudes ratio has revealed the regions of semiannual cycle dominance. Copyright © 2001 Royal Meteorological Society

STREAM TEMPERATURE CORRELATIONS WITH AIR TEMPERATURES IN MINNESOTA: IMPLICATIONS FOR CLIMATE WARMING1

ABSTRACT: Air temperatures are sometimes used as easy substitutes for stream temperatures. To examine the errors associated with this substitution, linear relationships between 39 Minnesota stream water temperature records and associated air temperature records were analyzed. From the lumped data set (38,082 daily data pairs), equations were derived for daily, weekly, monthly, and annual mean temperatures. Standard deviations between all measured and predicted water temperatures were 3.5°C (daily), 2.6°C (weekly), 1.9°C (monthly), and 1.3°C (annual). Separate analyses for each stream gaging station gave substantially lower standard deviations. Weather monitoring stations were, on average, 37.5 km from the stream. The measured water temperatures follow the annual air temperature cycle closely. No time lags were taken into account, and periods of ice cover were excluded from the analysis. If atmospheric CO2 doubles in the future, air temperatures in Minnesota are projected (CCC GCM) to rise by 4.3°C in the warm season (April‐October). This would translate into an average 4.1°C stream temperature rise, provided that stream shading would remain unaltered.