Proxy-Based Northern Hemisphere Surface Temperature Reconstructions: Sensitivity to Method, Predictor Network, Target Season, and Target Domain

Abstract Results are presented from a set of experiments designed to investigate factors that may influence proxy-based reconstructions of large-scale temperature patterns in past centuries. The factors investigated include 1) the method used to assimilate proxy data into a climate reconstruction, 2) the proxy data network used, 3) the target season, and 4) the spatial domain of the reconstruction. Estimates of hemispheric-mean temperature are formed through spatial averaging of reconstructed temperature patterns that are based on either the local calibration of proxy and instrumental data or a more elaborate multivariate climate field reconstruction approach. The experiments compare results based on the global multiproxy dataset used by Mann and coworkers, with results obtained using the extratropical Northern Hemisphere (NH) maximum latewood tree-ring density set used by Briffa and coworkers. Mean temperature reconstructions are compared for the full NH (Tropics and extratropics, land and ocean) and extratropical continents only, withvarying target seasons (cold-season half year, warm-season half year, and annual mean). The comparisons demonstrate dependence of reconstructions on seasonal, spatial, and methodological considerations, emphasizing the primary importance of the target region and seasonal window of the reconstruction. The comparisons support the generally robust nature of several previously published estimates of NH mean temperature changes in past centuries and suggest that further improvements in reconstructive skill are most likely to arise from an emphasis on the quality, rather than quantity, of available proxy data.

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Six-fold increase in historical Northern Hemisphere concurrent large heatwaves driven by warming and changing atmospheric circulations

Journal of Climate ◽

10.1175/jcli-d-21-0200.1 ◽

2021 ◽

pp. 1-39

Author(s):

Cassandra D.W. Rogers ◽

Kai Kornhuber ◽

Sarah E. Perkins-Kirkpatrick ◽

Paul C. Loikith ◽

Deepti Singh

Keyword(s):

Northern Hemisphere ◽

Large Scale ◽

Warm Season ◽

Fold Increase ◽

Circulation Pattern ◽

Positive Influence ◽

Climate Risks ◽

Circulation Patterns ◽

Multiple Regions ◽

Barents And Kara Seas

AbstractSimultaneous heatwaves affecting multiple regions (referred to as concurrent heatwaves), pose compounding threats to various natural and societal systems, including global food chains, emergency response systems, and reinsurance industries. While anthropogenic climate change is increasing heatwave risks across most regions, the interactions between warming and circulation changes that yield concurrent heatwaves remain understudied. Here, we quantify historical (1979-2019) trends in concurrent heatwaves during the warm-season (May-September, MJJAS) across the Northern Hemisphere mid- to high-latitudes. We find a significant increase of ~46% in the mean spatial extent of concurrent heatwaves, ~17% increase in their maximum intensity, and ~6-fold increase in their frequency. Using Self-Organising Maps, we identify large-scale circulation patterns (300 hPa) associated with specific concurrent heatwave configurations across Northern Hemisphere regions. We show that observed changes in the frequency of specific circulation patterns preferentially increase the risk of concurrent heatwaves across particular regions. Patterns linking concurrent heatwaves across eastern North America, eastern and northern Europe, parts of Asia, and the Barents and Kara Seas, show the largest increases in frequency (~5.9 additional days per decade). We also quantify the relative contributions of circulation pattern changes and warming to overall observed concurrent heatwave day frequency trends. While warming has a predominant and positive influence on increasing concurrent heatwaves, circulation pattern changes have a varying influence and account for up to 0.8 additional concurrent heatwave days per decade. Identifying regions with an elevated risk of concurrent heatwaves and understanding their drivers is indispensable for evaluating projected climate risks on interconnected societal systems and fostering regional preparedness in a changing climate.

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An Objectively Determined Blocking Index and its Northern Hemisphere Climatology

Journal of Climate ◽

10.1175/jcli-d-13-00374.1 ◽

2013 ◽

Vol 27 (8) ◽

pp. 2948-2970 ◽

Cited By ~ 16

Author(s):

David Small ◽

Eyad Atallah ◽

John R. Gyakum

Keyword(s):

Northern Hemisphere ◽

Systematic Approach ◽

Intraseasonal Variability ◽

Warm Season ◽

Cold Season ◽

Central Pacific ◽

Anticyclonic Circulation ◽

Blocking Activity ◽

Different Seasons ◽

Blocking Index

Abstract A modified blocking index is defined based on vertically integrated potential vorticity. The application of this index identifies blocking activity over the Northern Hemisphere during all seasons. The index is developed by systematically identifying the magnitude and spatial scale that best characterizes persistent anticyclonic circulation anomalies in different seasons. By applying a systematic approach to the detection of blocking, the interannual, seasonal, and intraseasonal patterns of blocking frequency across the Northern Hemisphere are able to be characterized. The results are consistent with previous studies in finding that blocking is more frequent in the cold season months than in the warm season, although the results suggest that blocking occurs much more frequently in the summer and fall than many studies have previously reported. By examining blocking frequency monthly, interesting patterns of intraseasonal variability are found, especially over the central Pacific in August and the eastern Pacific in September and October, where blocking is nearly as frequent as in the winter. Possible explanations for this intraseasonal variability are discussed.

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Recent Changes in Storm Track over the Southeast Europe: A Mechanism for Changes in Extreme Cyclone Variability

Atmosphere ◽

10.3390/atmos12101362 ◽

2021 ◽

Vol 12 (10) ◽

pp. 1362

Author(s):

Mihaela Caian ◽

Florinela Georgescu ◽

Mirela Pietrisi ◽

Oana Catrina

Keyword(s):

Large Scale ◽

Storm Track ◽

Cold Season ◽

Storm Tracks ◽

Target Area ◽

Southeast Europe ◽

The South ◽

Atmospheric Variability ◽

Target Domain ◽

Regional Variability

Recent changes in cyclone tracks crossing Southeast Europe are investigated for the last few decades (1980–1999 compared with 2000–2019) using a developed objective method. The response in number, severity, and persistence of the tracks are analyzed based on the source of origin (the Mediterranean Sea sub-domains) and the target area (Romania-centered domain). In winter, extreme cyclones became more frequent in the south and were also more persistent in the northeast of Romania. In summer, these became more intense and frequent, mainly over the south and southeast of Romania, where they also showed a significant increase in persistence. The regional extreme changes are related to polar jet displacements and further enhanced by the coupling of the sub-tropical jet in the Euro-Atlantic area, such as southwestwards shift in winter jets and a split-type configuration that shifts northeastwards and southeastwards in the summer. These provide a mechanism for regional variability of extreme cyclones through two paths, respectively, by shifting the origins of the tracks and by shifting the interaction between the anomaly jet streaks and the climatological storm tracks. Large-scale drivers of these changes are analyzed in relation to the main modes of atmospheric variability. The tracks number over the target domain is mainly driven during the cold season through a combined action of AO and Polar–European modes, and in summer by the AMO and East-Asian modes. These links and the circulation mode’s recent variability are consistent with changes found in the jet and storm tracks.

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Variability and Predictability of Central Asia River Flows: Antecedent Winter Precipitation and Large-Scale Teleconnections

Journal of Hydrometeorology ◽

10.1175/2008jhm976.1 ◽

2008 ◽

Vol 9 (6) ◽

pp. 1334-1349 ◽

Cited By ~ 31

Author(s):

Mathew A. Barlow ◽

Michael K. Tippett

Keyword(s):

Climate Variability ◽

Central Asia ◽

Moisture Transport ◽

Large Scale ◽

River Flow ◽

Regional Scale ◽

Warm Season ◽

Cold Season ◽

River Flows ◽

Syr Darya

Abstract Warm season river flows in central Asia, which play an important role in local water resources and agriculture, are shown to be closely related to the regional-scale climate variability of the preceding cold season. The peak river flows occur in the warm season (April–August) and are highly correlated with the regional patterns of precipitation, moisture transport, and jet-level winds of the preceding cold season (November–March), demonstrating the importance of regional-scale variability in determining the snowpack that eventually drives the rivers. This regional variability is, in turn, strongly linked to large-scale climate variability and tropical sea surface temperatures (SSTs), with the circulation anomalies influencing precipitation through changes in moisture transport. The leading pattern of regional climate variability, as resolved in the operationally updated NCEP–NCAR reanalysis, can be used to make a skillful seasonal forecast for individual river flow stations. This ability to make predictions based on regional-scale climate data is of particular use in this data-sparse area of the world. The river flow is considered in terms of 24 stations in Uzbekistan and Tajikistan available for 1950–85, with two additional stations available for 1958–2003. These stations encompass the headwaters of the Amu Darya and Syr Darya, two of the main rivers of central Asia and the primary feeders of the catastrophically shrinking Aral Sea. Canonical correlation analysis (CCA) is used to forecast April–August flows based on the period 1950–85; cross-validated correlations exceed 0.5 for 10 of the stations, with a maximum of 0.71. Skill remains high even after 1985 for two stations withheld from the CCA: the correlation for 1986–2002 for the Syr Darya at Chinaz is 0.71, and the correlation for the Amu Darya at Kerki is 0.77. The forecast is also correlated to the normalized difference vegetation index (NDVI); maximum values exceed 0.8 at 8-km resolution, confirming the strong connection between hydrology and growing season vegetation in the region and further validating the forecast methodology.

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Combined Effects of Impervious Surface Change and Large-Scale Afforestation on the Surface Urban Heat Island Intensity of Beijing, China Based on Remote Sensing Analysis

Remote Sensing ◽

10.3390/rs12233906 ◽

2020 ◽

Vol 12 (23) ◽

pp. 3906

Author(s):

Na Yao ◽

Conghong Huang ◽

Jun Yang ◽

Cecil C. Konijnendijk van den Bosch ◽

Lvyi Ma ◽

...

Keyword(s):

Urban Heat Island ◽

Large Scale ◽

Forest Cover ◽

Warm Season ◽

Cold Season ◽

Combined Effects ◽

Heat Island ◽

Plain Area ◽

Urban Heat ◽

Surface Urban Heat Island

Urban heat island (UHI) attenuation is an essential aspect for maintaining environmental sustainability at a local, regional, and global scale. Although impervious surfaces (IS) and green spaces have been confirmed to have a dominant effect on the spatial differentiation of the urban land surface temperature (LST), comprehensive temporal and quantitative analysis of their combined effects on LST and surface urban heat island intensity (SUHII) changes is still partly lacking. This study took the plain area of Beijing, China as an example. Here, rapid urbanization and a large-scale afforestation project have caused distinct IS and vegetation cover changes within a small range of years. Based on 8 scenes of Landsat 5 TM/7ETM/8OLI images (30 m × 30 m spatial resolution), 920 scenes of EOS-Aqua-MODIS LST images (1 km × 1 km spatial resolution), and other data/information collected by different approaches, this study characterized the interrelationship of the impervious surface area (ISA) dynamic, forest cover increase, and LST and SUHII changes in Beijing’s plain area during 2009–2018. An innovative controlled regression analysis and scenario prediction method was used to identify the contribution of ISA change and afforestation to SUHII changes. The results showed that percent ISA and forest cover increased by 6.6 and 10.0, respectively, during 2009–2018. SUHIIs had significant rising tendencies during the decade, according to the time division of warm season days (summer days included) and cold season nights (winter nights included). LST changes during warm season days responded positively to a regionalized ISA increase and negatively to a regionalized forest cover increase. However, during cold season nights, LST changes responded negatively to a slight regionalized ISA increase, but positively to an extensive regionalized ISA increase, and LST variations responded negatively to a regionalized forest cover increase. The effect of vegetation cooling was weaker than ISA warming on warm season days, but the effect of vegetation cooling was similar to that of ISA during cold season nights. When it was assumed that LST variations were only caused by the combined effects of ISA changes and the planting project, it was found that 82.9% of the SUHII rise on warm season days (and 73.6% on summer days) was induced by the planting project, while 80.6% of the SUHII increase during cold season nights (and 78.9% during winter nights) was caused by ISA change. The study presents novel insights on UHI alleviation concerning IS and green space planning, e.g., the importance of the joint planning of IS and green spaces, season-oriented UHI mitigation, and considering the thresholds of regional IS expansion in relation to LST changes.

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Effects of Spectral Nudging in WRF on Arctic Temperature and Precipitation Simulations

Journal of Climate ◽

10.1175/jcli-d-12-00318.1 ◽

2013 ◽

Vol 26 (12) ◽

pp. 3985-3999 ◽

Cited By ~ 42

Author(s):

Justin M. Glisan ◽

William J. Gutowski ◽

John J. Cassano ◽

Matthew E. Higgins

Keyword(s):

Extreme Events ◽

Large Scale ◽

Warm Season ◽

Cold Season ◽

Weather Research And Forecasting ◽

Spectral Nudging ◽

Temperature And Precipitation ◽

Climate Simulations ◽

Arctic Temperature ◽

Better Than

Abstract Spectral (interior) nudging is a way of constraining a model to be more consistent with observed behavior. However, such control over model behavior raises concerns over how much nudging may affect unforced variability and extremes. Strong nudging may reduce or filter out extreme events since nudging pushes the model toward a relatively smooth, large-scale state. The question then becomes: what is the minimum spectral nudging needed to correct biases while not limiting the simulation of extreme events? To determine this, case studies were performed using a six-member ensemble of the Pan-Arctic Weather Research and Forecasting model (WRF) with varying spectral nudging strength, using WRF’s standard nudging as a reference point. Two periods were simulated, one in a cold season (January 2007) and one in a warm season (July 2007). Precipitation and 2-m temperature were analyzed to determine how changing spectral nudging strength impacts temperature and precipitation extremes and selected percentiles. Results suggest that there is a marked lack of sensitivity to varying degrees of nudging. Moreover, given that nudging is an artificial forcing applied in the model, an outcome of this work is that nudging strength can be considerably smaller than the WRF standard strength and still produce climate simulations that are much better than using no nudging.

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Linkages of surface air temperature variations over Central Asia with large-scale climate patterns

10.21203/rs.3.rs-261105/v1 ◽

2021 ◽

Author(s):

Yuanhuang Zhuang ◽

Jingyong Zhang ◽

Lingyun Wu

Keyword(s):

Central Asia ◽

Air Temperature ◽

Large Scale ◽

Warm Season ◽

Surface Air Temperature ◽

Cold Season ◽

Temperature Variations ◽

The North ◽

Climate Patterns ◽

Air Temperature Variations

Abstract In this study, we investigate the dominant modes of surface air temperature variations of the cold season (from November through to the next March) and the warm season (from May to September) over Central Asia, and their associations with large-scale climate patterns for the period of 1979–2016. The first two modes of the cold-season surface air temperature (CSAT) over Central Asia, obtained by empirical orthogonal function (EOF) analysis, feature the mono-pole structure and the north-south dipole pattern, respectively. For the warm-season surface air temperature (WSAT), the leading two EOF modes are characterized by the homogenous structure and the northwest-southeast seesaw pattern, respectively. Further analysis indicates that the large-scale atmospheric circulation anomalies play key roles in the CSAT and WSAT variations over Central Asia. The CSAT variation over Central Asia is closely related with the Scandinavia pattern (SCAND), the Arctic Oscillation (AO) and the North Atlantic Oscillation (NAO), while the WSAT variation is tightly tied to the East Atlantic/Western Russia pattern (EAWR) and the NAO. These large-scale climate patterns tend to cause the CSAT and WSAT anomalies over Central Asia via their effects on regional geopotential heights, warming advections and other processes. Our findings are expected to facilitate the improvement of understanding and predicting the CSAT and WSAT variations over Central Asia.

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Faculty Opinions recommendation of Highly variable Northern Hemisphere temperatures reconstructed from low- and high-resolution proxy data.

Faculty Opinions – Post-Publication Peer Review of the Biomedical Literature ◽

10.3410/f.1024262.287831 ◽

2005 ◽

Author(s):

John Pandolfi

Keyword(s):

High Resolution ◽

Northern Hemisphere ◽

Proxy Data

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Temperature and Relative Humidity Profile Retrieval from Fengyun-3D/HIRAS in the Arctic Region

Remote Sensing ◽

10.3390/rs13101884 ◽

2021 ◽

Vol 13 (10) ◽

pp. 1884

Author(s):

Jingjing Hu ◽

Yansong Bao ◽

Jian Liu ◽

Hui Liu ◽

George P. Petropoulos ◽

...

Keyword(s):

Relative Humidity ◽

Real Time ◽

Wide Spectrum ◽

Warm Season ◽

Arctic Region ◽

Cold Season ◽

The Arctic ◽

Practical Applications ◽

A New Technique ◽

The Arctic Region

The acquisition of real-time temperature and relative humidity (RH) profiles in the Arctic is of great significance for the study of the Arctic’s climate and Arctic scientific research. However, the operational algorithm of Fengyun-3D only takes into account areas within 60°N, the innovation of this work is that a new technique based on Neural Network (NN) algorithm was proposed, which can retrieve these parameters in real time from the Fengyun-3D Hyperspectral Infrared Radiation Atmospheric Sounding (HIRAS) observations in the Arctic region. Considering the difficulty of obtaining a large amount of actual observation (such as radiosonde) in the Arctic region, collocated ERA5 data from European Centre for Medium-Range Weather Forecasts (ECMWF) and HIRAS observations were used to train the neural networks (NNs). Brightness temperature and training targets were classified using two variables: season (warm season and cold season) and surface type (ocean and land). NNs-based retrievals were compared with ERA5 data and radiosonde observations (RAOBs) independent of the NN training sets. Results showed that (1) the NNs retrievals accuracy is generally higher on warm season and ocean; (2) the root-mean-square error (RMSE) of retrieved profiles is generally slightly higher in the RAOB comparisons than in the ERA5 comparisons, but the variation trend of errors with height is consistent; (3) the retrieved profiles by the NN method are closer to ERA5, comparing with the AIRS products. All the results demonstrated the potential value in time and space of NN algorithm in retrieving temperature and relative humidity profiles of the Arctic region from HIRAS observations under clear-sky conditions. As such, the proposed NN algorithm provides a valuable pathway for retrieving reliably temperature and RH profiles from HIRAS observations in the Arctic region, providing information of practical value in a wide spectrum of practical applications and research investigations alike.All in all, our work has important implications in broadening Fengyun-3D’s operational implementation range from within 60°N to the Arctic region.

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A spatiotemporal reconstruction of sea-surface temperatures in the North Atlantic during Dansgaard–Oeschger events 5–8

Climate of the Past ◽

10.5194/cp-14-901-2018 ◽

2018 ◽

Vol 14 (6) ◽

pp. 901-922 ◽

Cited By ~ 6

Author(s):

Mari F. Jensen ◽

Aleksi Nummelin ◽

Søren B. Nielsen ◽

Henrik Sadatzki ◽

Evangeline Sessford ◽

...

Keyword(s):

Surface Temperature ◽

Sea Surface Temperature ◽

North Atlantic ◽

General Circulation ◽

Sea Surface ◽

Reconstruction Method ◽

Sea Surface Temperatures ◽

Proxy Data ◽

Surface Temperatures ◽

Temperature Reconstructions

Abstract. Here, we establish a spatiotemporal evolution of the sea-surface temperatures in the North Atlantic over Dansgaard–Oeschger (DO) events 5–8 (approximately 30–40 kyr) using the proxy surrogate reconstruction method. Proxy data suggest a large variability in North Atlantic sea-surface temperatures during the DO events of the last glacial period. However, proxy data availability is limited and cannot provide a full spatial picture of the oceanic changes. Therefore, we combine fully coupled, general circulation model simulations with planktic foraminifera based sea-surface temperature reconstructions to obtain a broader spatial picture of the ocean state during DO events 5–8. The resulting spatial sea-surface temperature patterns agree over a number of different general circulation models and simulations. We find that sea-surface temperature variability over the DO events is characterized by colder conditions in the subpolar North Atlantic during stadials than during interstadials, and the variability is linked to changes in the Atlantic Meridional Overturning circulation and in the sea-ice cover. Forced simulations are needed to capture the strength of the temperature variability and to reconstruct the variability in other climatic records not directly linked to the sea-surface temperature reconstructions. This is the first time the proxy surrogate reconstruction method has been applied to oceanic variability during MIS3. Our results remain robust, even when age uncertainties of proxy data, the number of available temperature reconstructions, and different climate models are considered. However, we also highlight shortcomings of the methodology that should be addressed in future implementations.

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