scholarly journals Role of internal variability of climate system in increase of air temperature in Wrocław (Poland) in the years 1951–2018

2021 ◽  
Author(s):  
Andrzej Antoni Marsz ◽  
Anna Styszyńska ◽  
Krystyna Bryś ◽  
Tadeusz Bryś
Keyword(s):  
Air Temperature ◽  
Thermal Regime ◽  
Radiative Forcing ◽  
Sunshine Duration ◽  
Rapid Change ◽  
Internal Variability ◽  
Radical Change ◽  
Climate System ◽  
Positive Trend

Abstract In the course of the annual air temperature in Wrocław (TWr variable) a rapid change of the thermal regime was found between 1987 and 1989. A similar temperature change has occurred in Central Europe. TWr increased by more than 1 deg a strong, statistically significant positive trend emerged. The analysis of processes showed that strong warming in the cold season of the year (December–March) occurred as a result of an increase in the NAO intensity and warming in the warm season as a result of increased sunshine duration. Multiple regression analysis has showed that the winter NAO Hurrell’s index explains 15% of TWr variance, and the sunshine duration of the ‘long day’ (April–August) period 49%, whereas radiative forcing 5.9%. This indicates that the factors incidental to the internal variability of the climate system explain 64% of the TWr variability and the effect of increased CO 2 concentration only ~6%. The reason for this rapid change of the thermal regime was a radical change in macro-circulation conditions in the Atlantic-European circular sector, which took place between 1988 and 1989. It has similarly changed the structure of the Central European weathers. The heat, which is the cause of warming in Wrocław, comes from an increase in solar energy inflow (April–August) and also is transported to Europe from the North Atlantic surface by atmospheric circulation (NAO). These results indicate that the role of CO 2 in shaping the contemporary temperature increase is overestimated, whereas internal variability of the climate system is underestimated.

scholarly journals Role of Internal Variability of Climate System in Increase of Air Temperature in Wrocław (Poland) in the Years 1951–2018

2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Andrzej A. Marsz ◽  
Anna Styszyńska ◽  
Krystyna Bryś ◽  
Tadeusz Bryś
Keyword(s):  
Air Temperature ◽  
Thermal Regime ◽  
Radiative Forcing ◽  
Sunshine Duration ◽  
Rapid Change ◽  
Internal Variability ◽  
Radical Change ◽  
Climate System ◽  
Positive Trend

Abstract In the course of analysing the annual air temperature in Wrocław (TWr), a rapid change of the thermal regime was found between 1987 and 1989. TWr increased by >1°C, a strong, statistically significant positive trend emerged. The analysis of processes showed that strong warming in the cold season of the year (December–March) occurred as a result of an increase in the NAO intensity and warming in the warm season because of increased sunshine duration in Wrocław (ShWr). Multiple regression analysis has shown that the winter NAO Hurrell's index explains 15% of TWr variance, and the ShWr of the long-day (April–August) period 49%, whereas radiative forcing 5.9%. This indicates that the factors incidental to the internal variability of the climate system explain 64% of the TWr variability and the effect of increased CO2 concentration only ~6%. The reason for this rapid change of the thermal regime was a radical change in macro-circulation conditions in the Atlantic-European circular sector, which took place between 1988 and 1989. The heat, which is the cause of warming in Wrocław, comes from an increase in solar energy inflow (April–August) and also is transported to Europe from the North Atlantic surface by atmospheric circulation (NAO). These results indicate that the role of CO2 in shaping the contemporary temperature increase is overestimated, whereas the internal variability of the climate system is underestimated.

scholarly journals Anthropogenic forcing and response yield observed positive trend in Earth’s energy imbalance

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Shiv Priyam Raghuraman ◽  
David Paynter ◽  
V. Ramaswamy
Keyword(s):  
Radiative Forcing ◽  
Climate Model ◽  
Solar Spectrum ◽  
Internal Variability ◽  
Satellite Observations ◽  
Positive Trend ◽  
Energy Imbalance ◽  
Model Simulations ◽  
Heat Uptake ◽  
Climate Model Simulations

AbstractThe observed trend in Earth’s energy imbalance (TEEI), a measure of the acceleration of heat uptake by the planet, is a fundamental indicator of perturbations to climate. Satellite observations (2001–2020) reveal a significant positive globally-averaged TEEI of 0.38 ± 0.24 Wm−2decade−1, but the contributing drivers have yet to be understood. Using climate model simulations, we show that it is exceptionally unlikely (<1% probability) that this trend can be explained by internal variability. Instead, TEEI is achieved only upon accounting for the increase in anthropogenic radiative forcing and the associated climate response. TEEI is driven by a large decrease in reflected solar radiation and a small increase in emitted infrared radiation. This is because recent changes in forcing and feedbacks are additive in the solar spectrum, while being nearly offset by each other in the infrared. We conclude that the satellite record provides clear evidence of a human-influenced climate system.

scholarly journals Recent changes of relative humidity: regional connection with land and ocean processes

2017 ◽  
Author(s):  
Sergio M. Vicente-Serrano ◽  
Raquel Nieto ◽  
Luis Gimeno ◽  
Cesar Azorin-Molina ◽  
Anita Drumond ◽  
...  
Keyword(s):  
Relative Humidity ◽  
Interannual Variability ◽  
Air Temperature ◽  
Spatial Scales ◽  
Global Scale ◽  
Sea Surface ◽  
Positive Trend ◽  
Source Regions ◽  
Strong Agreement

Abstract. We analyzed changes in surface relative humidity (RH) at the global scale from 1979 to 2014 using both observations and ERA-Interim dataset. We compared the variability and trends of RH with those of land evapotranspiration and ocean evaporation in moisture source areas across a range of selected regions worldwide. The sources of moisture for each particular region were identified by integrating different observational data and model outputs into a lagrangian approach. The aim was to account for the possible role of changes in air temperature over land, in comparison to sea surface temperature (SST), on RH variability. Results demonstrate a strong agreement between the interannual variability of RH and the interannual variability of precipitation and land evapotranspiration in regions with continentally-originated humidity. In contrast, albeit with the dominant positive trend of air temperature/SST ratio in the majority of the analyzed regions, the interannual variability of RH in the target regions did not show any significant correlation with this ratio over the source regions. Also, we did not find any significant association between the interannual variability of oceanic evaporation in the oceanic humidity source regions and RH in the target regions. Our findings stress the need for further investigation of the role of both dynamic and radiative factors in the evolution of RH over continental regions at different spatial scales.

scholarly journals Interannual Variability of Air Temperature over Myanmar: The Influence of ENSO and IOD

Climate ◽  
2021 ◽  
Vol 9 (2) ◽  
pp. 35
Author(s):  
Zin Mie Mie Sein ◽  
Irfan Ullah ◽  
Sidra Syed ◽  
Xiefei Zhi ◽  
Kamran Azam ◽  
...  
Keyword(s):  
Air Temperature ◽  
El Niño ◽  
Water Resource Management ◽  
El Nino ◽  
Southern Oscillation ◽  
Rapid Change ◽  
Winter Season ◽  
Positive Trend ◽  
Study Region ◽  
Target Region

Myanmar is located in a tropical region where temperature rises very fast and hence is highly vulnerable to climate change. The high variability of the air temperature poses potential risks to the local community. Thus, the current study uses 42 synoptic meteorological stations to assess the spatiotemporal changes in air temperature over Myanmar during 1971–2013. The nonparametric sequential Mann-Kendall (SqMK), linear regression, empirical orthogonal function (EOF), Principal Component Analysis (PCA), and composite analysis were used to assess the long-term trends in maximum (Tmax) and minimum (Tmin) temperature series and their possible mechanism over the study region. The results indicate that the trend of Tmax has significantly increased at the rates of 90% in summer season, while the Tmin revealed a substantial positive trend in winter season time series with the magnitude of 30%, respectively. Moreover, during a rapid change of climate (1995–2013) we observed an air temperature increase of 0.7 °C. The spatial distributions of EOF revealed relatively warmer temperatures over the whole region except the south in the summer; however, a similar pattern can be seen for the rainy season and winter, implying warming in the central part and cooling in the northern and southern parts. Furthermore, the Indian Ocean Dipole (IOD) influence on air temperature over Myanmar is more prevalent than that of the El Niño Southern Oscillation (ENSO). The result implies that the positive phase of the IOD and negative phase of the Southern Oscillation Index (SOI; El Niño) events led to the higher temperature, resulting in intense climatic extremes (i.e., droughts and heatwaves) over the target region. Therefore, this study’s findings can help policymakers and decision-makers improve economic growth, agricultural production, ecology, water resource management, and preserving the natural habitat in the target region.

The role of internal variability in climate change projections of North American surface air temperature and temperature extremes in CanESM2 large ensemble simulations

2020 ◽  
Author(s):  
Bin Yu ◽  
Guilong Li ◽  
Shangfeng Chen ◽  
Hai Lin
Keyword(s):  
Climate Change ◽  
Air Temperature ◽  
North American ◽  
Surface Air Temperature ◽  
Internal Variability ◽  
Temperature Extremes ◽  
Large Ensemble ◽  
Climate Simulations ◽  
Ensemble Mean

&lt;p&gt;Recent studies indicated that the internal climate variability plays an important role in various aspects of projected climate changes on regional and local scales. Here we present results of the spreads in projected trends of wintertime North American surface air temperature and extremes indices of warm and cold days over the next half-century, by analyzing a 50-member large ensemble of climate simulations conducted with CanESM2. CanESM2 simulations confirm the important role of internal variability in projected surface temperature trends as demonstrated in previous studies. Yet the spread in North American warming trends in CanESM2 is generally smaller than those obtained from CCSM3 and ECHAM5 large ensemble simulations. Despite this, large spreads in the climate means as well as climate change trends of North American temperature extremes are apparent in CanESM2, especially in the projected cold day trends. The ensemble mean of forced climate simulations reveals high risks of warm days over the western coast and north Canada, as well as a weakening belt of cold days extending from Alaska to the northeast US. The individual ensemble members differ from the ensemble mean mainly in magnitude of the warm day trends, but depart from the ensemble mean in conspicuous ways, including spatial pattern and magnitude, of the cold day trends. The signal-to-noise ratio pattern of the warm day trend resembles that of the surface air temperature trend; with stronger signals over north Canada, Alaska, and the southwestern US than the midsection of the continent. The projected cold day patterns reveal strong signals over the southwestern US, north Canada, and the northeastern US. In addition, the internally generated components of temperature and temperature extreme trends exhibit spatial coherences over North America, and are comparable to the externally forced trends. The large-scale atmospheric circulation-induced temperature variability influences these trends. Overall, our results suggest that climate change trends of North American temperature extremes are likely very uncertain and need to be applied with caution.&lt;/p&gt;

scholarly journals Investigating the Roles of External Forcing and Ocean Circulation on the Atlantic Multidecadal SST Variability in a Large Ensemble Climate Model Hierarchy

2021 ◽  
pp. 1-51
Author(s):  
Lisa N. Murphy ◽  
Jeremy M. Klavans ◽  
Amy C. Clement ◽  
Mark A. Cane
Keyword(s):  
Spatial Pattern ◽  
Ocean Circulation ◽  
Radiative Forcing ◽  
Climate Model ◽  
Time History ◽  
Internal Variability ◽  
External Forcing ◽  
Large Ensemble ◽  
The North

AbstractThis paper attempts to enhance our understanding of the causes of Atlantic Multidecadal Variability, the AMV. Following the literature, we define the AMV as the SST averaged over the North Atlantic basin, linearly detrended and low-pass filtered. There is an ongoing debate about the drivers of the AMV, which include internal variability generated from the ocean or atmosphere (or both), and external radiative forcing. We test the role of these factors in explaining the time history, variance, and spatial pattern of the AMV using a 41-member ensemble from a fully coupled version of CESM and a 10-member ensemble of the CESM atmosphere coupled to a slab ocean. The large ensemble allows us to isolate the role of external forcing versus internal variability, and the model differences allow us to isolate the role of coupled ocean circulation. Both with and without coupled ocean circulation, external forcing explains more than half of the variance of the observed AMV time series, indicating its important role in simulating the 20th century AMV phases. In this model the net effect of ocean processes is to reduce the variance of the AMV. Dynamical ocean coupling also reduces the ability of the model to simulate the characteristic spatial pattern of the AMV, but forcing has little impact on the pattern. Historical forcing improves the time history and variance of the AMV simulation, whilst the more realistic ocean representation reduces the variance below that observed and lowers the correlation with observations.

scholarly journals Forced changes in internal variability: an additional uncertainty to deal with

2021 ◽  
Author(s):  
Daniel Topal ◽  
Tímea Haszpra ◽  
Mátyás Herein
Keyword(s):  
Time Series ◽  
Radiative Forcing ◽  
Large Scale ◽  
Chaotic Behavior ◽  
Internal Variability ◽  
Arctic Sea Ice ◽  
Climate System ◽  
Initial Condition ◽  
Coupled Modes ◽  
Anthropogenic Forcing

&lt;p&gt;Anthropogenic activities contribute to the rising level of greenhouse gas concentrations in the atmosphere at a rate of approximately 1% per year providing a time-dependent external radiative forcing on the climate. In addition to tangible consequences of anthropogenic forcing affecting the climate system, simultaneous, less apparent changes occurring on low-frequency timescales demand effort to deal with. These include changes in natural internal processes of the climate system due to the non-stationary anthropogenic forcing. This represents additional uncertainty affecting future model projections on top of internal variability, scenario and model uncertainty. Here, with the application of state-of-the-art Single Model Initial-condition Large Ensemble (SMILE) simulations &amp;#8211; that account for the chaotic behavior of the climate system with perturbed initial condition runs of the same model &amp;#8211; we offer a way forward for new perspectives on externally-forced changes in internal variability. In doing so, we utilize an approach for analyzing SMILEs called the &lt;em&gt;snapshot view&lt;/em&gt;, which offers a mathematically exact and elegant formulation and the potential to complement previous, time-series-based diagnostics with ensemble-based statistics. We reveal how the &lt;em&gt;snapshot view&lt;/em&gt; allows for surprisingly simple practices to detect anthropogenically forced changes in modes of large-scale internal atmospheric circulation variability (so-called &amp;#8220;teleconnection patterns&amp;#8221;) as well as coupled modes of atmospheric variability with Arctic sea ice. A crucial message of the &lt;em&gt;snapshot view&lt;/em&gt; is that all of the traditional, time series-based methods can be reformulated for ensembles and thus, on the one hand, ambiguous results arising from subjective choices of traditional methods (e.g. length and center of time windows) can be avoided, and on the other hand, new perspectives open for detecting forced changes in internal variability.&lt;/p&gt;

Projecting North American Climate over the Next 50 Years: Uncertainty due to Internal Variability*

2014 ◽  
Vol 27 (6) ◽  
pp. 2271-2296 ◽  
Author(s):  
Clara Deser ◽  
Adam S. Phillips ◽  
Michael A. Alexander ◽  
Brian V. Smoliak
Keyword(s):  
Climate Change ◽  
Air Temperature ◽  
Radiative Forcing ◽  
Surface Air Temperature ◽  
Internal Variability ◽  
Climate Trends ◽  
Climate Change Projections ◽  
Temperature And Precipitation ◽  
Model Ensembles ◽  
Precipitation Trends

Abstract This study highlights the relative importance of internally generated versus externally forced climate trends over the next 50 yr (2010–60) at local and regional scales over North America in two global coupled model ensembles. Both ensembles contain large numbers of integrations (17 and 40): each of which is subject to identical anthropogenic radiative forcing (e.g., greenhouse gas increase) but begins from a slightly different initial atmospheric state. Thus, the diversity of projected climate trends within each model ensemble is due solely to intrinsic, unpredictable variability of the climate system. Both model ensembles show that natural climate variability superimposed upon forced climate change will result in a range of possible future trends for surface air temperature and precipitation over the next 50 yr. Precipitation trends are particularly subject to uncertainty as a result of internal variability, with signal-to-noise ratios less than 2. Intrinsic atmospheric circulation variability is mainly responsible for the spread in future climate trends, imparting regional coherence to the internally driven air temperature and precipitation trends. The results underscore the importance of conducting a large number of climate change projections with a given model, as each realization will contain a different superposition of unforced and forced trends. Such initial-condition ensembles are also needed to determine the anthropogenic climate response at local and regional scales and provide a new perspective on how to usefully compare climate change projections across models.

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