scholarly journals Assessments of the Northern Hemisphere snow cover response to 1.5 and 2.0 °C warming

2018 ◽  
Vol 9 (2) ◽  
pp. 865-877 ◽  
Author(s):  
Aihui Wang ◽  
Lianlian Xu ◽  
Xianghui Kong
Keyword(s):  
Snow Cover ◽  
Northern Hemisphere ◽  
Land Surface ◽  
Surface Air Temperature ◽  
Cmip5 Models ◽  
Boreal Summer ◽  
Surface Hydrology ◽  
Internal Climate Variability ◽  
Global Mean Temperature

Abstract. The 2015 Paris Agreement set a goal to pursue a global mean temperature below 1.5 °C and well below 2 °C above preindustrial levels. Although it is an important surface hydrology variable, the response of snow under different warming levels has not been well investigated. This study provides a comprehensive assessment of the snow cover fraction (SCF) and snow area extent (SAE), as well as the associated land surface air temperature (LSAT) over the Northern Hemisphere (NH) based on the Community Earth System Model Large Ensemble project (CESM-LE), the CESM 1.5 and 2 °C projects, and the CMIP5 historical RCP2.6 and RCP4.5 products. The results show that the spatiotemporal variations in those modeled products are grossly consistent with observations. The projected SAE magnitude change in RCP2.6 is comparable to that in 1.5 °C, but lower than that in 2 °C. The snow cover differences between 1.5 and 2 °C are prominent during the second half of the 21st century. The signal-to-noise ratios (SNRs) of both SAE and LSAT over the majority of land areas are greater than 1, and for the long-term period, the dependences of SAE on LSAT changes are comparable for different ensemble products. The contribution of an increase in LSAT to the reduction of snow cover differs across seasons, with the greatest occurring in boreal autumn (49–55 %) and the lowest occurring in boreal summer (10–16 %). The snow cover uncertainties induced by the ensemble variability are invariant over time across CESM members but show an increase in the warming signal between the CMIP5 models. This feature reveals that the physical parameterization of the model plays the predominant role in long-term snow simulations, while they are less affected by internal climate variability.

scholarly journals Assessments of the north hemisphere snow cover response to 1.5 °C and 2.0 °C warming

2017 ◽  
Author(s):  
Aihui Wang ◽  
Lianlian Xu ◽  
Xianghui Kong
Keyword(s):  
Snow Cover ◽  
Land Surface ◽  
Surface Air Temperature ◽  
Internal Variability ◽  
Cmip5 Models ◽  
Boreal Summer ◽  
Surface Hydrology ◽  
The North ◽  
Global Mean Temperature ◽  
Time Invariant

Abstract. The 2015 Paris Agreement has initialed a goal to pursue the global-mean temperature below 1.5 °C, and well below 2 °C above pre-industrial levels. As an important surface hydrology variable, the response of snow under different warming levels has not been well investigated. The community earth system model (CESM) project towards 1.5 °C and 2 °C warming targets, combined with CESM large Ensemble project (CESM-LE) brings an opportunity to address this issue. This study provides a comprehensive assessment of snow cover fraction (SCF) and snow area extent (SAE), and the associated Land Surface Air Temperature (LSAT) over North Hemisphere (NH) based on CESM-LE, CESM 1.5 °C and 2 °C projects, as well as CMIP5 historical, RCP2.6 and RCP4.5 products. Results show that the spatiotemporal variations of those modeled products are grossly consistent with the observation. The projected SAE magnitude change in RCP2.6 is comparable to that in 1.5 °C, but lower than that in 2 °C. The snow cover differences between 1.5 °C and 2 °C are prominent during the second half of 21st century. Changes in the LSAT and snow cover for 2071–2100 with respect to 1971–2000 exhibit the inconsistently spatial patterns. The contribution of increase in LSAT on the reduction of snow cover differs across seasons with the greatest in boreal autumn (49–55 %) and the lowest in boreal summer (10–16 %). The snow cover uncertainties induced by the ensemble variability show time invariant across CESM members, but increase with the warming signal among CMIP5 models. This feature reveals that the model physical parameterization plays a predominant role on the long-term snow simulations, while they are less affect by the climate internal variability.

Correction of Inhomogeneities in Observed Land Surface Temperatures over China

2020 ◽  
Vol 33 (20) ◽  
pp. 8885-8902
Author(s):  
Jizeng Du ◽  
Kaicun Wang ◽  
Baoshan Cui ◽  
Shaojing Jiang
Keyword(s):  
Climate Change ◽  
Land Surface ◽  
Surface Air Temperature ◽  
Warming Trend ◽  
Cmip5 Models ◽  
Near Surface ◽  
Land Surface Temperatures ◽  
Long Term Trends ◽  
The Difference

AbstractLand surface temperature Ts and near-surface air temperature Ta are two main metrics that reflect climate change. Recently, based on in situ observations, several studies found that Ts warmed much faster than Ta in China, especially after 2000. However, we found abnormal jumps in the Ts time series during 2003–05, mainly caused by the transformation from manual to automatic measurements due to snow cover. We explore the physical mechanism of the differences between automatic and manual observations and develop a model to correct the automatic observations on snowy days in the observed records of Ts. Furthermore, the nonclimatic shifts in the observed Ts were detected and corrected using the RHtest method. After corrections, the warming rates for Ts-max, Ts-min, and Ts-mean were 0.21°, 0.34°, and 0.25°C decade−1, respectively, during the 1960–2014 period. The abnormal jump in the difference between Ts and Ta over China after 2003, which was mentioned in existing studies, was mainly caused by inhomogeneities rather than climate change. Through a combined analysis using reanalyses and CMIP5 models, we found that Ts was consistent with Ta both in terms of interannual variability and long-term trends over China during 1960–2014. The Ts minus Ta (Ts − Ta) trend is from −0.004° to 0.009°C decade−1, accounting for from −3.19% to 5.93% (from −3.09% to 6.39%) of the absolute warming trend of Ts (Ta).

scholarly journals Regularities of soil temperature changes during the period with snow cover in modern climatic conditions of the Eurasian Subarctic

2021 ◽  
pp. 13-22
Author(s):  
Lev M. Kitaev
Keyword(s):  
Standard Deviation ◽  
Soil Temperature ◽  
Snow Cover ◽  
Air Temperature ◽  
Land Surface ◽  
Environmental Changes ◽  
Surface Air Temperature ◽  
Climatic Conditions ◽  
Winter Period

The influence of snow cover on the dynamics of soil temperature in the modern climatic conditions of the Eurasian Subarctic was investigated through a quantitative assessment of the features of the seasonal and long-term variation of parameters. Seasonal and long-term values of soil temperature for stable snow period decrease from west to east: a decrease of snow thickness and air temperature from west to east of Eurasia leads to a weakening of the heat-insulating properties of the snow cover with a significant decrease in regional air temperatures. With the emergence of a stable snow cover, the soil temperature seasonal and long-term standard deviation sharply decreases compared to the autumn and spring periods. With the appearance of snow cover, the soil temperature standard deviation drops sharply compared to the autumn and spring periods. An exception is the northeast of Siberia: here, a relatively small thickness of snow determines a noticeable dependence of the course of soil temperature on the dynamics of surface air temperature. There are no significant long-term trends in soil temperature due to its low variability during winter period. Analysis of the course of the studied characteristics anomalies showed an insignificant and non-systematic number of their coincidences. Currently, we have not found similar research results for large regions. The revealed patterns can be used in the analysis of the results of monitoring the state of the land surface, in the development of remote sensing algorithms, in the refinement of predictive scenarios of environmental changes.

scholarly journals Satellite observations of changes in snow-covered land surface albedo during spring in the Northern Hemisphere

2015 ◽  
Vol 9 (5) ◽  
pp. 1879-1893 ◽  
Author(s):  
K. Atlaskina ◽  
F. Berninger ◽  
G. de Leeuw
Keyword(s):  
Snow Cover ◽  
Northern Hemisphere ◽  
Air Temperature ◽  
Land Surface ◽  
Surface Albedo ◽  
Vegetation Index ◽  
Precipitation Amount ◽  
Snow Cover Fraction ◽  
Air Temperatures ◽  
Moderate Resolution Imaging Spectroradiometer

Abstract. Thirteen years of Moderate Resolution Imaging Spectroradiometer (MODIS) surface albedo data for the Northern Hemisphere during the spring months (March–May) were analyzed to determine temporal and spatial changes over snow-covered land surfaces. Tendencies in land surface albedo change north of 50° N were analyzed using data on snow cover fraction, air temperature, vegetation index and precipitation. To this end, the study domain was divided into six smaller areas, based on their geographical position and climate similarity. Strong differences were observed between these areas. As expected, snow cover fraction (SCF) has a strong influence on the albedo in the study area and can explain 56 % of variation of albedo in March, 76 % in April and 92 % in May. Therefore the effects of other parameters were investigated only for areas with 100 % SCF. The second largest driver for snow-covered land surface albedo changes is the air temperature when it exceeds a value between −15 and −10 °C, depending on the region. At monthly mean air temperatures below this value no albedo changes are observed. The Enhanced Vegetation Index (EVI) and precipitation amount and frequency were independently examined as possible candidates to explain observed changes in albedo for areas with 100 % SCF. Amount and frequency of precipitation were identified to influence the albedo over some areas in Eurasia and North America, but no clear effects were observed in other areas. EVI is positively correlated with albedo in Chukotka Peninsula and negatively in eastern Siberia. For other regions the spatial variability of the correlation fields is too high to reach any conclusions.

scholarly journals On the role of Eurasian autumn snow cover in dynamical seasonal predictions 

2021 ◽  
Author(s):  
Paolo Ruggieri ◽  
Marianna Benassi ◽  
Stefano Materia ◽  
Daniele Peano ◽  
Constantin Ardilouze ◽  
...  
Keyword(s):  
Snow Cover ◽  
Northern Hemisphere ◽  
Land Surface ◽  
General Circulation ◽  
Dominant Role ◽  
General Circulation Models ◽  
The Arctic ◽  
Seasonal Forecasts ◽  
Eurasian Snow

<p>Seasonal climate predictions leverage on many predictable or persistent components of the Earth system that can modify the state of the atmosphere and of relant weather related variable such as temprature and precipitation. With a dominant role of the ocean, the land surface provides predictability through various mechanisms, including snow cover, with particular reference to Autumn snow cover over the Eurasian continent. The snow cover alters the energy exchange between land surface and atmosphere and induces a diabatic cooling that in turn can affect the atmosphere both locally and remotely. Lagged relationships between snow cover in Eurasia and atmospheric modes of variability in the Northern Hemisphere have been investigated and documented but are deemed to be non-stationary and climate models typically do not reproduce observed relationships with consensus. The role of Autumn Eurasian snow in recent dynamical seasonal forecasts is therefore unclear. In this study we assess the role of Eurasian snow cover in a set of 5 operational seasonal forecast system characterized by a large ensemble size and a high atmospheric and oceanic resolution. Results are compemented with a set of targeted idealised simulations with atmospheric general circulation models forced by different snow cover conditions. Forecast systems reproduce realistically regional changes of the surface energy balance associated with snow cover variability. Retrospective forecasts and idealised sensitivity experiments converge in identifying a coherent change of the circulation in the Northern Hemisphere. This is compatible with a lagged but fast feedback from the snow to the Arctic Oscillation trough a tropospheric pathway.</p>

scholarly journals Atmosphere similarity patterns in boreal summer show an increase of persistent weather conditions connected to hydro-climatic risks

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Peter Hoffmann ◽  
Jascha Lehmann ◽  
Bijan H. Fallah ◽  
Fred F. Hattermann
Keyword(s):  
Northern Hemisphere ◽  
Climate Models ◽  
Weather Conditions ◽  
Boreal Summer ◽  
Climatic Extremes ◽  
Weather Patterns ◽  
Dry Conditions ◽  
Climatic Risks ◽  
Long Term Trend

AbstractRecent studies have shown that hydro-climatic extremes have increased significantly in number and intensity in the last decades. In the Northern Hemisphere such events were often associated with long lasting persistent weather patterns. In 2018, hot and dry conditions prevailed for several months over Central Europe leading to record-breaking temperatures and severe harvest losses. The underlying circulation processes are still not fully understood and there is a need for improved methodologies to detect and quantify persistent weather conditions. Here, we propose a new method to detect, compare and quantify persistence through atmosphere similarity patterns by applying established image recognition methods to day to day atmospheric fields. We find that persistent weather patterns have increased in number and intensity over the last decades in Northern Hemisphere mid-latitude summer, link this to hydro-climatic risks and evaluate the extreme summers of 2010 (Russian heat wave) and of 2018 (European drought). We further evaluate the ability of climate models to reproduce long-term trend patterns of weather persistence and the result is a notable discrepancy to observed developments.

The use of multi-tracer flask-measurements to understand changes in the land-surface processes.

2021 ◽  
Author(s):  
Theertha Kariyathan ◽  
Wouter Peters ◽  
Julia Marshall ◽  
Ana Bastos ◽  
Markus Reichstein
Keyword(s):  
Northern Hemisphere ◽  
Land Surface ◽  
Seasonal Cycle ◽  
Growing Season ◽  
Plant Productivity ◽  
Surface Processes ◽  
Terrestrial Biosphere ◽  
Land Surface Processes ◽  
Species Analysis

<p>Carbon dioxide (CO<sub>2</sub>) is an important greenhouse gas, and it accounts for about 20% of the present-day anthropogenic greenhouse effect. Atmospheric CO<sub>2</sub> is cycled between the terrestrial biosphere and the atmosphere through various land-surface processes and thus links the atmosphere and terrestrial biosphere through positive and negative feedback. Since multiple trace gas elements are linked by common biogeochemical processes, multi-species analysis is useful for reinforcing our understanding and can help in partitioning CO<sub>2</sub> fluxes. For example, in the northern hemisphere, CO<sub>2</sub> has a distinct seasonal cycle mainly regulated by plant photosynthesis and respiration and it has a distinct negative correlation with the seasonal cycle of the δ<sup>13</sup>C isotope of CO<sub>2</sub>, due to a stronger isotopic fractionation associated with terrestrial photosynthesis. Therefore, multi-species flask-data measurements are useful for the long-term analysis of various green-house gases. Here we try to infer the complex interaction between the atmosphere and the terrestrial biosphere by multi-species analysis using atmospheric flask measurement data from different NOAA flask measurement sites across the northern hemisphere.</p><p>This study focuses on the long-term changes in the seasonal cycle of CO<sub>2</sub> over the northern hemisphere and tries to attribute the observed changes to driving land-surface processes through a combined analysis of the δ<sup>13</sup>C seasonal cycle. For this we generate metrics of different parameters of the CO<sub>2</sub> and δ<sup>13</sup>C seasonal cycle like the seasonal cycle amplitude given by the peak-to-peak difference of the cycle (indicative of the amount of CO<sub>2</sub> taken up by terrestrial uptake),  the intensity of plant productivity inferred from the slope of the seasonal cycle during the growing season , length of growing season and the start of the growing season. We analyze the inter-relation between these metrics and how they change across latitude and over time. We hypothesize that the CO<sub>2 </sub>seasonal cycle amplitude is controlled both by the intensity of plant productivity and period of the active growing season and that the timing of the growing season can affect the intensity of plant productivity. We then quantify these relationships, including their variation over time and latitudes and describe the effects of an earlier start of the growing season on the intensity of plant productivity and the CO<sub>2</sub> uptake by plants.</p>

Future Change of Northern Hemisphere Summer Tropical–Extratropical Teleconnection in CMIP5 Models*

2014 ◽  
Vol 27 (10) ◽  
pp. 3643-3664 ◽  
Author(s):  
June-Yi Lee ◽  
Bin Wang ◽  
Kyong-Hwan Seo ◽  
Jong-Seong Kug ◽  
Yong-Sang Choi ◽  
...  
Keyword(s):  
North America ◽  
Northern Hemisphere ◽  
Summer Monsoon ◽  
North Pacific ◽  
Western North Pacific ◽  
Cmip5 Models ◽  
Boreal Summer ◽  
Moderate Increase ◽  
Coupled Models ◽  
Teleconnection Patterns

Abstract Two dominant global-scale teleconnections in the Northern Hemisphere (NH) extratropics during boreal summer season (June–August) have been identified: the western North Pacific–North America (WPNA) and circumglobal teleconnection (CGT) patterns. These teleconnection patterns are of critical importance for the NH summer seasonal climate prediction. Here, how these teleconnections will change under anthropogenic global warming is investigated using representative concentration pathway 4.5 (RCP4.5) experiments by 20 coupled models that participated in phase 5 of the Coupled Model Intercomparison Project (CMIP5). The six best models are selected based on their performance in simulation of the two teleconnection patterns and climatological means and variances of atmospheric circulation, precipitation, and sea surface temperature. The selected models capture the CGT and its relationship with the Indian summer monsoon (ISM) reasonably well. The models can also capture the WPNA circulation pattern but with striking deficiencies in reproducing its associated rainfall anomalies due to poor simulation of the western North Pacific summer monsoon rainfall. The following changes are anticipated in the latter half of twenty-first century under the RCP4.5 scenario: 1) significant weakening of year-to-year variability of the upper-level circulation due to increased atmospheric stability, although the moderate increase in convective heating over the tropics may act to strengthen the variability; 2) intensification of the WPNA pattern and major spectral peaks, particularly over the eastern Pacific–North America and North Atlantic–Europe sectors, which is attributed to the strengthening of its relationship with the preceding mature phase of El Niño–Southern Oscillation (ENSO); and 3) weakening of the CGT due to atmospheric stabilization and decreasing relationship with ISM as well as weakening of the ISM–ENSO relationship.

scholarly journals Evapotranspiration Partitioning in CMIP5 Models: Uncertainties and Future Projections

2019 ◽  
Vol 32 (10) ◽  
pp. 2653-2671 ◽  
Author(s):  
Alexis Berg ◽  
Justin Sheffield
Keyword(s):  
Land Surface ◽  
Stomatal Closure ◽  
Surface Air Temperature ◽  
Soil Evaporation ◽  
Cmip5 Models ◽  
Canopy Interception ◽  
Area Index ◽  
Near Surface ◽  
Relative Contribution ◽  
The Tropics

Abstract Evapotranspiration (ET) is a key process affecting terrestrial hydroclimate, as it modulates the land surface carbon, energy, and water budgets. Evapotranspiration mainly consists of the sum of three components: plant transpiration, soil evaporation, and canopy interception. Here we investigate how the partitioning of ET into these three main components is represented in CMIP5 model simulations of present and future climate. A large spread exists between models in the simulated mean present-day partitioning; even the ranking of the different components in the global mean differs between models. Differences in the simulation of the vegetation leaf area index appear to be an important cause of this spread. Although ET partitioning is not accurately known globally, existing global estimates suggest that CMIP5 models generally underestimate the relative contribution of transpiration. Differences in ET partitioning lead to differences in climate characteristics over land, such as land–atmosphere fluxes and near-surface air temperature. On the other hand, CMIP5 models simulate robust patterns of future changes in ET partitioning under global warming, notably a marked contrast between decreased transpiration and increased soil evaporation in the tropics, whereas transpiration and evaporation both increase at higher latitudes and both decrease in the dry subtropics. Idealized CMIP5 simulations from a subset of models show that the decrease in transpiration in the tropics largely reflects the stomatal closure effect of increased atmospheric CO2 on plants (despite increased vegetation from CO2 fertilization), whereas changes at higher latitudes are dominated by radiative CO2 effects, with warming and increased precipitation leading to vegetation increase and simultaneous (absolute) increases in all three ET components.

scholarly journals Influence of radiative forcing factors on ground–air temperature coupling during the last millennium: implications for borehole climatology

2018 ◽  
Vol 14 (11) ◽  
pp. 1583-1606 ◽  
Author(s):  
Camilo Melo-Aguilar ◽  
J. Fidel González-Rouco ◽  
Elena García-Bustamante ◽  
Jorge Navarro-Montesinos ◽  
Norman Steinert
Keyword(s):  
Air Temperature ◽  
Land Surface ◽  
Radiative Forcing ◽  
Spatial Scales ◽  
Ground Surface ◽  
Surface Air Temperature ◽  
Small Variation ◽  
Last Millennium ◽  
Reconstruction Methods

Abstract. Past climate variations may be uncovered via reconstruction methods that use proxy data as predictors. Among them, borehole reconstruction is a well-established technique to recover the long-term past surface air temperature (SAT) evolution. It is based on the assumption that SAT changes are strongly coupled to ground surface temperature (GST) changes and transferred to the subsurface by thermal conduction. We evaluate the SAT–GST coupling during the last millennium (LM) using simulations from the Community Earth System Model LM Ensemble (CESM-LME). The validity of such a premise is explored by analyzing the structure of the SAT–GST covariance during the LM and also by investigating the evolution of the long-term SAT–GST relationship. The multiple and single-forcing simulations in the CESM-LME are used to analyze the SAT–GST relationship within different regions and spatial scales and to derive the influence of the different forcing factors on producing feedback mechanisms that alter the energy balance at the surface. The results indicate that SAT–GST coupling is strong at global and above multi-decadal timescales in CESM-LME, although a relatively small variation in the long-term SAT–GST relationship is also represented. However, at a global scale such variation does not significantly impact the SAT–GST coupling, at local to regional scales this relationship experiences considerable long-term changes mostly after the end of the 19th century. Land use land cover changes are the main driver for locally and regionally decoupling SAT and GST, as they modify the land surface properties such as albedo, surface roughness and hydrology, which in turn modifies the energy fluxes at the surface. Snow cover feedbacks due to the influence of other external forcing are also important for corrupting the long-term SAT–GST coupling. Our findings suggest that such local and regional SAT–GST decoupling processes may represent a source of bias for SAT reconstructions from borehole measurement, since the thermal signature imprinted in the subsurface over the affected regions is not fully representative of the long-term SAT variations.

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