Global Temperature Trends Research Articles

On the response of the middle atmosphere to anthropogenic forcing.

Anthropogenic forcing of the atmosphere by greenhouse gases (GHG) and ozone-depleting substances has provided an unintended test of the robustness of current understanding of the physics and chemistry of the middle atmosphere, that is, the stratosphere and mesosphere. We explore this topic by examining how well anthropogenic changes can be simulated by modern, comprehensive numerical models. Specifically, we discuss the simulations of trends in global mean temperature; the development of the ozone hole and its impact on the dynamics of the Southern Hemisphere, both in the stratosphere and troposphere; trends in the stratospheric Brewer-Dobson circulation; and the response of the quasi-biennial oscillation (QBO) to increasing burdens of CO2 . We find that, in most of these cases, numerical simulation is able to reproduce observed changes and provide physical insights into the relevant mechanisms. Simulation of the QBO is on a less firm footing. Although many numerical models can now generate realistic QBOs, future projections of its behavior under the increasing burdens of GHG are inconsistent and even contradictory.

The nature of the trend in global and hemispheric temperatures

AbstractThe aim of this note is to provide evidence about the existence or non‐existence of a stochastic trend in the global temperatures time series by using standard unit root tests. Three sets of data are considered in this paper: global, Northern Hemisphere and Southern Hemisphere monthly temperature anomalies. Our main finding is that there is not a stochastic trend in the temperatures time series and they are stationary around a deterministic trend.

Global temperature variations since pre industrial era

The global temperature trends are being changed due to anthropogenic activities. The natural ecosystems and human societies are affected by this rapid climate change. These changes are caused by the increasing concentration of carbon dioxide and other green house gases including methane and oxides of nitrogen and sulphur. These changes can be identified using accurate data related to variations in temperature and precipitation. We used MODIS GLOVIS LST V6 global datasets to compute pixel-based temperature and mapped the trends. The considerable warming trends are exhibited by Arctic regions which are warming twice as compared to other parts of world. The largest increase in precipitation occurs in Northern Europe at the rate of 12.9mm per decade. The concentration of carbon dioxide has been raised up to 4.14 ppm in atmosphere by December 2020. This increased concentration has raised the global temperature up to 1.2°C since pre industrial era. Remotely sensed datasets provided promising results.

Inferring future warming in the Arctic from the observed global warming trend and CMIP6 simulations

The emergent constraint approach is a way of using multi-model ensembles to identify the linkage between current/past climate variability and future climate changes, which has been widely used for narrowing down the uncertainty of multi-model projections of future climate change. Climate models of the latest Coupled Model Intercomparison Project Phase 6 (CMIP6) show a much stronger Arctic warming signal but with a larger inter-model spread. In this study, we find that the projected Arctic warming made by multi-models in CMIP6 is positively correlated with the simulated global warming trend during the period of 1981–2011 in historical runs. This enables us to tighter constraints to future warming in the Arctic by using the observed global warming during the instrument era. The fact that CMIP6 models tend to overestimate the trend of global mean surface temperature during 1981–2011, therefore, would imply a relative weak Arctic warming compared to the CMIP6 median warming projection.

Diatom Response to Global Warming in Douhu Lake, Southeast China

AbstractA large number of lacustrine sedimentary records indicate that global warming is the main factor leading to significant changes in diatom communities in lakes of the northern hemisphere. However, due to the intensification of human activities since 1850, some scholars have emphasized that the increasing lake trophic level may be the main reason for the changes in diatom communities. The debate is ongoing. In order to avoid falling into the complex relationship between diatom changes and the seasonal cycle that characterizes lakes in mid and high latitudes, we chose a lake located at a low latitude, where the relationship between diatoms and temperature is not indirect but direct. The diatom record spans the past ca. 100 years and reveals that the abundance of Aulacoseira granulata increased from 1900 until 1985, replacing the previously dominant Aulacoseira ambigua. These changes are in agreement with the increasing trend in global temperature. Since 1985, the percentages of the small‐celled Discostella stelligera and the benthic diatom Navicula heimansioides have increased, while Aulacoseira granulata has decreased. This latest shift is caused by further global warming. We conclude that warming is the main factor leading to changing diatom communities in Douhu Lake.

Observed trends in clouds and precipitation (1983–2009): implications for their cause(s)

Abstract. Satellite observations (International Satellite Cloud Climatology Project (ISCCP), 1983–2009) of linear trends in cloud cover are compared to those in global precipitation (Global Precipitation Climatology Project (GPCP) pentad V2.2, 1983–2009), to investigate possible cause(s) of the linear trends in both cloud cover and precipitation. The spatial distributions of the linear trends in total cloud cover and precipitation are both characterized primarily by a broadening of the major ascending zone of Hadley circulation. Our correlation studies suggest that global warming, Atlantic Multidecadal Oscillation (AMO) and Pacific Decadal Oscillation (PDO) can explain 67 %, 49 % and 38 %, respectively, of the spatial variabilities in the linear trends in cloud cover, but causality is harder to establish. Further analysis of the broadening of the major ascending zone of Hadley circulation shows that the trend in global temperature, rather than those in AMO and PDO, is the primary contributor to the observed linear trends in total cloud cover and precipitation in 1983–2009. The underlying mechanism driving this broadening is proposed to be the moisture–convection–latent-heat feedback cycle under global warming conditions. The global analysis is extended by investigating connections between clouds and precipitation in China, based on a large number of long-running, high-quality surface weather stations in 1957–2005. This reveals a quantitative matching relationship between the reduction in light precipitation and the reduction in total cloud cover. Furthermore, our study suggests that the reduction in cloud cover in China is primarily driven by global temperature; PDO plays a secondary role, while the contribution from AMO and Niño3.4 is insignificant, consistent with the global analysis.

Canadian Continental-Scale Hydrology under a Changing Climate: A Review

Canada, like other high latitude cold regions on Earth, is experiencing some of the most accelerated and intense warming resulting from global climate change. In the northern regions, Arctic amplification has resulted in warming two to three times greater than global mean temperature trends. Unprecedented warming is matched by intensification of wet and dry regions and hydroclimatic cycles, which is altering the spatial and seasonal distribution of surface waters in Canada. Diagnosing and tracking hydrologic change across Canada requires the implementation of continental-scale prediction models owing the size of Canada’s drainage basins, their distribution across multiple eco- and climatic zones, and the scarcity and paucity of observational networks. This review examines the current state of continental-scale climate change across Canada and the anticipated impacts to freshwater availability, including the role of anthropogenic regulation. The review focuses on continental and regional-scale prediction that underpins operational design and long-term resource planning and management in Canada. While there are significant process-based changes being experienced within Canadian catchments that are equally—if not more so—critical for community water availability, the focus of this review is on the cumulative effects of climate change and anthropogenic regulation for the Canadian freshwater supply.

Implementing Full Spatial Coverage in NOAA’s Global Temperature Analysis

AbstractThe National Oceanic and Atmospheric Administration (NOAA) maintains an operational analysis for monitoring trends in global surface temperature. Because of limited polar coverage, the analysis does not fully capture the rapid warming in the Arctic over recent decades. Given the impact of coverage biases on trend assessments, we introduce a new analysis that is spatially complete for 1850–2018. The new analysis uses air temperature data in the Arctic Ocean and applies climate reanalysis fields in spatial interpolation. Both the operational analysis and the new analysis show statistically significant warming across the globe and the Arctic for all periods examined. The analyses have comparable global trends, but the new analysis exhibits significantly more warming in the Arctic since 1980 (0.598°C dec−1 vs. 0.478°C dec−1), and its trend falls outside the 95% confidence interval of its operational counterpart. Trend differences primarily result from coverage gaps in the operational analysis.

Offshore aquaculture as climate change adaptation in coastal areas: sea surface temperature trends in the Western Mediterranean Sea

The warming of the Mediterranean Sea surface is currently estimated to have been 0.4°C per decade for the period 1985-2006, and the increase in water temperature may have negatively affected marine aquaculture, e.g. by decreasing productivity. Development of aquaculture without adequate planning can lead to unsustainable economic feasibility due to future climate stressors. In this sense, offshore mariculture could be an alternative for mitigating the effect of coastal warming. The purpose of this study was to evaluate the suitability of the coastline in terms of global warming and sea surface temperature trends in locations where fish aquaculture is currently being developed, as well as the spatial changes of thermal anomalies up to 30 km from the coast, during the last 31 yr in the western Mediterranean (Spanish coast). This study was conducted using EU Copernicus Marine Service Information, covering the period 1981-2018, with a spatial resolution of 4 × 4 km. The results show that, over the last decade, the Mediterranean coastal environment off the Iberian Peninsula has experienced an increase in temperature of around 1ºC due to global change, with a clear latitudinal pattern modified by mesoscale oceanographic processes. The development of offshore aquaculture at some latitudes mitigates the extreme aestival effects on surface water temperatures. Strategic plans for aquaculture development should be able to forecast and incorporate future climate projections and local oceanographic conditions, and offshore aquaculture may provide an alternative in some regions, depending on local oceanographic conditions.

An updated evaluation of the global mean land surface air temperature and surface temperature trends based on CLSAT and CMST

Past versions of global surface temperature (ST) datasets have been shown to have underestimated the recent warming trend over 1998–2012. This study uses a newly updated global land surface air temperature and a land and marine surface temperature dataset, referred to as China global land surface air temperature (C-LSAT) and China merged surface temperature (CMST), to estimate trends in the global mean ST (combining land surface air temperature and sea surface temperature anomalies) with the data uncertainties being taken into account. Comparing with existing datasets, the statistical significance of the global mean ST warming trend during the past century (1900–2017) remains unchanged, while the recent warming trend during the “hiatus” period (1998–012) increases obviously, which is statistically significant at 95% level when fitting uncertainty is considered as in previous studies (including IPCC AR5) and is significant at 90% level when both fitting and data uncertainties are considered. Our analysis shows that the global mean ST warming trends in this short period become closer among the newly developed global observational data (CMST), remotely sensed/Buoy network infilled datasets, and reanalysis data. Based on the new datasets, the warming trends of global mean land SAT as derived from C-LSAT 2.0 for the period of 1979–2019, 1951–2019, 1900–2019 and 1850–2019 were estimated to be 0.296, 0.219, 0.119 and 0.081 °C/decade, respectively. The warming trends of global mean ST as derived from CMST for the periods of 1998–2019, 1979–2019, 1951–2019 and 1900–2019 were estimated to be 0.195, 0.173, 0.145 and 0.091 °C/decade, respectively.

Trends of Temperature Extreme Indices over Arusha and Kilimanjaro Regions in Tanzania

The study aimed at analyzing the trends and variability of temperature extremes over the northeastern highlands in Tanzania, specifically over Arusha and Kilimanjaro regions. Quality controlled mean monthly, daily maximum and minimum temperature data for the period 1961 to 2020, obtained from Tanzania Meteorological Authority, were used in the study. Rclimdex and the National Climate Monitoring Products (NMCP) software, developed by the World Meteorological Organization (WMO), were used for computation of the indices at a monthly, seasonal and annual time scale. The computed indices were also subjected to trend analysis to determine their direction and magnitude of change. Extraction and assessment of the top five highest and lowest maximum and minimum temperatures were also done. Increasing trends of temperature anomalies for seasonal and annual timescales were observed for both Arusha and Kilimanjaro regions. Also, the increasing trends of warm and extreme warm days and nights and relatively increasing trends of cold and extreme cold days and nights were observed for both regions. The highest ever recorded temperatures since the establishment of the two stations were 36.3?C observed on 16th February 2011 and 38.6?C observed on 22nd February 2005 for Arusha and Kilimanjaro respectively. These results indicate that The last two decades have been characterized by enhanced warming, which is consistent with overall global temperature trend patterns as depicted in recent IPCC reports and the report of the State of Climate in Africa.

Surface Skin Temperature and Its Trend Observations From IASI on Board MetOp Satellites

Global surface skin temperature has been retrieved from MetOp IASI ultraspectral infrared measurements over the past 13+ years. Monthly and spatially gridded surface skin temperature is produced to show some phenomena associated with its natural variability. This article has aimed to demonstrate that thermal infrared remote sensing data can be used for monitoring global surface environmental characteristics and associated change through the continuity observations of MetOp series. The time-series anomalies of surface skin temperature are used to estimate its associated trend. Error estimation and evaluation has been performed and discussed in order to understand the uncertainty and variability in the trends. The trends derived from IASI global surface skin temperatures are compared with those of the NASA GISS global surface air temperature. Despite the physical differences between surface skin and air temperatures, reasonable agreement is shown between these two datasets indicating consistency and global surface warming, achieving our core objective of investigating the surface skin temperature retrieved from MetOp satellites’ measurements and associated trends. The inferred trend of IASI global surface skin temperature illustrates an approximate 0.037±0.002 K/yr. global average increase has occurred during the September 2007—present (November 2020) time period; this warming trend is more pronounced in the northern hemisphere.

Long‐Term Variability and Tendencies in Middle Atmosphere Temperature and Zonal Wind From WACCM6 Simulations During 1850–2014

AbstractLong‐term variability of middle atmosphere temperature (T) and zonal wind (U) is investigated using a three‐member ensemble of historical simulations of NCAR's Whole Atmospheric Community Climate Model latest version 6 (WACCM6) for 1850–2014 (165 years). The model reproduces the climatological features of T and U. The contributions of Quasi Biennial Oscillation (QBO) at 10 and 30 hPa, solar cycle (SC), El Niño‐Southern Oscillation (ENSO), ozone depleting substances (ODS), carbon dioxide (CO2), and stratospheric sulfate aerosol (volcanic eruptions) to change in monthly zonal mean T and U are analyzed using multiple linear regression. The signal due to CO2 increase dominates as a predictor of the net multidecadal global annual mean temperature change at all levels in the middle atmosphere. Contributions from ODS also affect the net multidecadal global mean temperature trend in the stratosphere. Because of similarities in the time evolution of the emissions of CO2 and ODS, the analysis of existing model output cannot accurately separate the attributions of cooling to these two dominant forcing processes. On shorter time scales, solar flux variations are the largest source of variability in the mesosphere while volcanic eruptions are the largest in the stratosphere. In the stratosphere and mesosphere, both QBO and ENSO can significantly impact zonal mean temperature and zonal‐mean zonal wind depending on latitudes, but their impact on the multidecadal global mean temperature trend is very small.

Urbanization effects on surface air temperature trends in Thailand during 1970-2019

Continued urban expansion undergone in the last decades has converted many weather stations in Thailand into suburban and urban setting. Based on homogenized data during 1970-2019, therefore, this study examines urbanization effects on mean surface air temperature (Tmean) trends in Thailand. Analysis shows that urban-type stations register the strongest warming trends while rural-type stations exhibit the smallest trends. Across Thailand, annual urban-warming contribution exhibits a wide range (< 5% to 77%), probably manifesting the Urban Heat Island (UHI) differences from city to city resulting from the varied urban characteristics and climatic background. Country-wide average urban warming contribution shows a significant increasing trend of 0.15 <sup>o</sup>C per decade, accounting for 40.5% of the overall warming. This evidence indicates that urban expansion has great influence on surface warming, and the urban-warming bias contributes large fraction of rising temperature trends in Thailand. The increasing trend of annual Tmean for Thailand as a whole after adjusting urban-warming bias is brought down to the same rate as the annual global mean temperature trend, reflecting a national baseline signal driven by large-scale anthropogenic-induced climate change. Our results provide a scientific reference for policy makers and urban planners to mitigate substantial fraction of the UHI warming.

Dominant Influence of ENSO-Like and Global Sea Surface Temperature Patterns on Changes in Prevailing Boreal Summer Tropical Cyclone Tracks over the Western North Pacific

AbstractA conventional empirical orthogonal function (EOF) analysis is performed on summertime (May–October) western North Pacific (WNP) tropical cyclone (TC) track density anomalies during 1970–2012. The first leading EOF mode is characterized by a consistent spatial distribution across the WNP basin, which is closely related to an El Niño–Southern Oscillation (ENSO)-like pattern that prevails on both interannual and interdecadal time scales. The second EOF mode is represented by a tripole pattern with consistent changes in westward and recurving tracks but with an opposite change for west-northwestward TC tracks. This second EOF pattern is dominated by consistent global sea surface temperature anomaly (SSTA) patterns on interannual and interdecadal time scales, along with a long-term increasing global temperature trend. Observed WNP TC tracks have three distinct interdecadal epochs (1970–86, 1987–97, and 1998–2012) based on EOF analyses. The interdecadal change is largely determined by the changing impact of ENSO-like and consistent global SSTA patterns. When global SSTAs are cool (warm) during 1970–86 (1998–2012), these SSTAs exert a dominant impact and generate a tripole track pattern that is similar to the positive (negative) second EOF mode. In contrast, a predominately El Niño–like SSTA pattern during 1987–97 contributed to increasing TC occurrences across most of the WNP during this 11-yr period. These findings are consistent with long-term trends in TC tracks, with a tripole track pattern observed as global SSTs increase. This study reveals the potential large-scale physical mechanisms driving the changes of WNP TC tracks in association with climate change.

Global temperature modes shed light on the Holocene temperature conundrum

Reconstructions of the global mean annual temperature evolution during the Holocene yield conflicting results. One temperature reconstruction shows global cooling during the late Holocene. The other reconstruction reveals global warming. Here we show that both a global warming mode and a cooling mode emerge when performing a spatio-temporal analysis of annual temperature variability during the Holocene using data from a transient climate model simulation. The warming mode is most pronounced in the tropics. The simulated cooling mode is determined by changes in the seasonal cycle of Arctic sea-ice that are forced by orbital variations and volcanic eruptions. The warming mode dominates in the mid-Holocene, whereas the cooling mode takes over in the late Holocene. The weighted sum of the two modes yields the simulated global temperature trend evolution. Our findings have strong implications for the interpretation of proxy data and the selection of proxy locations to compute global mean temperatures.

Understanding Intermodel Diversity When Simulating the Time of Emergence in CMIP5 Climate Models

AbstractUsing a statistical method, we examined the time of emergence (ToE), which was defined as the year when the global mean surface temperature (GMST) trend exceeds the trend explained by internal variability, using 33 Coupled Model Intercomparison Project Phase 5 (CMIP5) climate models for 1861–2100. We found that the GMST trend explained by internal variability showed minimal changes even though the GMST trend rapidly increased under the Representative Climate Pathway 8.5 scenario. However, there was large intermodel diversity for the ToEs in CMIP5 climate models. The intensity of Arctic amplification was closely associated with intermodel diversity of the ToEs. A significant difference in the amount of Arctic sea ice extent during the reference period (1861‐1910) played a role in determining whether there was slow or fast simulation of the ToE in CMIP5 climate models. We argue that a slow or fast ToE is influenced by how the climate models initially simulate the sea ice extent during the reference period.

Association between Surface Air Temperature And Land Use On The Campus Scale

The increasing trend of global temperature is related to the land use change in the form of urbanization. The impact of land use change to surface air temperature in Indonesia especially in smaller scope in Indonesia have not researched yet. The study area is located on newly built campus and the development of land use change inside campus can be managed carefully. This research aim is to determine which land use affecting high-temperature by using multiple linear regression method with least square approach so that temperature increase can be controlled in which some land uses must be preserved in urbanization. Land use data is interpreted from the photo map of 275 hectare campus. Temperature data is measured by using the digital thermometer three times a day. The method idea is to obtain distinctive contribution of every land use to every temperature measurement point. The contribution follows the inverse distance weighted concept. Surface air temperature measurement points are located with 150 meter interval and centroids of land use polygons are used for association calculation. Temperature measurement shows values between 25.5oC and 35.4oC. Land use with more anthropogenic activities and rubber plantation are the top contributors to high surface air temperature within a day. In the non-built-up land use category, water body increases the temperature in the daytime. Anthropogenic activities and vegetation density within land use is the main factor in increasing the surface air temperature so that it is suggested to plant farm-like vegetation around every built-up land use.

LONG-TERM spectral components of global, north and south hemisphere temperatures over the last millennium and solar-lunar forcing

Data of temperature anomalies from different sites worldwide for the last millennium are used to extract long-term components in global, northern and southern hemisphere temperatures for their quantitative contribution to climate change to evaluate and to search for possible causes. The Method of Global Minimum which is capable of making a self-consistent selection of trends from a data set and singling out harmonics with varying phase and amplitude is applied. Quantitative description of all components of the spectra including trends extracted for the first time by self-consistent method is given and discussed. Temperature trends have highest amplitude in north, south hemispheres and globally that leads to their largest contribution to climate change. Trend in north hemisphere temperature described by nonstationary sinusoid at period ∼1270 yr shows maximum near 1300 (medieval warming), deep minimum near 1700 (Maunder's minimum) and rise since 1700 to present. Trend in south hemisphere has smoothed maximum for medieval epoch, minimum near 1800 (Dalton's minimum) and rise since 1800. Both trends go up together since ∼1800, but north hemisphere temperature grows faster. Trend in global temperature described by nonstationary sinusoid at period ∼1000 yr demonstrates deep smoothed minimum near 1750 and subsequent rise with rate of increase ∼0.5 °C/100yr since 1800. Amplitude of the nonstationary cycle began rise since 1250 and continue to rise for present and close future. Temporal changes of amplitude and phase of nonstationary spectral components have typical features of nonlinear oscillations that points to a nonlinear mechanism supporting the periodical oscillations. It is shown that the 33-yr nonstationary component in global temperature has the highest rate of change ∼1.2 °C/100yr or 0.12 °C/10yr, which can explain rapid temperature changes (from warming to subsequent cooling and vice versa). It is also shown that periods of the temperature spectra include integers of periods of historically-known eclipse cycles and of periods related with motions of Jupiter, Saturn and Venus. Therefore Sun and Moon, Jupiter, Saturn and Venus influence on climate variability. The result also means existence of high-number commensurabilities between mean motions in the system Sun –Earth–Moon and these planets.

Crossbreeding CMIP6 Earth System Models With an Emulator for Regionally Optimized Land Temperature Projections

AbstractThe newest generation of the Coupled Model Intercomparison Project (CMIP6) exhibits a larger spread in temperature projections at the end of the 21st century than the previous generation. Here, a modular Earth System Model emulator is used to evaluate the realism of the warming signal in CMIP6 models on both global and regional scales, by comparing their global trends and regional response parameters to observations. Subsequently, the emulator is employed to derive large “crossbred” multimodel initial‐condition ensembles of regionally optimized land temperature projections by combining observationally constrained global mean temperature trend trajectories with observationally constrained local parameters. In the optimized ensembles, the warmest temperature projections are generally reduced and for the coolest projections both higher and lower values are found, depending on the region. The median shows less changes in large parts of the globe. These regional differences highlight the importance of a geographically explicit evaluation of Earth System Model projections.