Increase In Surface Air Temperature Research Articles

Changes in anthropogenic particulate matters and resulting global climate effects since the Industrial Revolution

AbstractIn order to quantify air pollution effects on climate change, we investigated the climate response associated with anthropogenic particulate matters (PMs) by dividing fine PM (PM2.5, particle size ≤2.5 μm) and coarse particulate matter (CPM, particle size >2.5 μm) in great detail in this work, with an aerosol‐climate coupled model. We find that the changes in PM2.5 and CPM are very different and thus result in different, even opposite effects on climate, especially on a regional scale. The column burden of PM2.5 increases globally from 1850 to the present, especially over Asia's southern and eastern parts, whereas the column concentration of CPM increases over high‐latitude regions and decreases over South Asia. The resulted global annual mean effective radiative forcing (ERF) values due to PM2.5 and CPM changes are −1.21 W·m−2 and −0.24 W·m−2, respectively. Increases in PM2.5 result in significant cooling effects on the climate, whereas changes in CPM produce small and even opposite effects. The global annual mean surface air temperature (SAT) decreases by 0.94 K due to PM2.5 increase. Coolings caused by increased PM2.5 are more apparent over Northern Hemisphere (NH) terrain and ocean at mid‐ and high latitudes. Increases in SATs caused by increased CPM are identified over high latitudes in the NH, whereas decreases are identified over mid‐latitude regions. Strong cooling due to increased PM2.5 causes a southward shift of the Intertropical Convergence Zone (ITCZ), whereas the Hadley circulation associated with CPM is enhanced slightly over both hemispheres, along with the weak movement of corresponding ITCZ. The global annual mean precipitation decreases by approximately 0.11 mm day−1 due to the increased PM2.5. Generally, PM2.5 concentration changes contribute more than 80% of the variation caused by all anthropogenic aerosols in ERF, SAT, cloud fraction, and precipitation.

Present and future aerosol impacts on Arctic climate change in the GISS-E2.1 Earth system model

Abstract. The Arctic is warming 2 to 3 times faster than the global average, partly due to changes in short-lived climate forcers (SLCFs) including aerosols. In order to study the effects of atmospheric aerosols in this warming, recent past (1990–2014) and future (2015–2050) simulations have been carried out using the GISS-E2.1 Earth system model to study the aerosol burdens and their radiative and climate impacts over the Arctic (>60∘ N), using anthropogenic emissions from the Eclipse V6b and the Coupled Model Intercomparison Project Phase 6 (CMIP6) databases, while global annual mean greenhouse gas concentrations were prescribed and kept fixed in all simulations. Results showed that the simulations have underestimated observed surface aerosol levels, in particular black carbon (BC) and sulfate (SO42-), by more than 50 %, with the smallest biases calculated for the atmosphere-only simulations, where winds are nudged to reanalysis data. CMIP6 simulations performed slightly better in reproducing the observed surface aerosol concentrations and climate parameters, compared to the Eclipse simulations. In addition, simulations where atmosphere and ocean are fully coupled had slightly smaller biases in aerosol levels compared to atmosphere-only simulations without nudging. Arctic BC, organic aerosol (OA), and SO42- burdens decrease significantly in all simulations by 10 %–60 % following the reductions of 7 %–78 % in emission projections, with the Eclipse ensemble showing larger reductions in Arctic aerosol burdens compared to the CMIP6 ensemble. For the 2030–2050 period, the Eclipse ensemble simulated a radiative forcing due to aerosol–radiation interactions (RFARI) of -0.39±0.01 W m−2, which is −0.08 W m−2 larger than the 1990–2010 mean forcing (−0.32 W m−2), of which -0.24±0.01 W m−2 was attributed to the anthropogenic aerosols. The CMIP6 ensemble simulated a RFARI of −0.35 to −0.40 W m−2 for the same period, which is −0.01 to −0.06 W m−2 larger than the 1990–2010 mean forcing of −0.35 W m−2. The scenarios with little to no mitigation (worst-case scenarios) led to very small changes in the RFARI, while scenarios with medium to large emission mitigations led to increases in the negative RFARI, mainly due to the decrease in the positive BC forcing and the decrease in the negative SO42- forcing. The anthropogenic aerosols accounted for −0.24 to −0.26 W m−2 of the net RFARI in 2030–2050 period, in Eclipse and CMIP6 ensembles, respectively. Finally, all simulations showed an increase in the Arctic surface air temperatures throughout the simulation period. By 2050, surface air temperatures are projected to increase by 2.4 to 2.6 ∘C in the Eclipse ensemble and 1.9 to 2.6 ∘C in the CMIP6 ensemble, compared to the 1990–2010 mean. Overall, results show that even the scenarios with largest emission reductions leads to similar impact on the future Arctic surface air temperatures and sea-ice extent compared to scenarios with smaller emission reductions, implying reductions of greenhouse emissions are still necessary to mitigate climate change.

Spring snow depth changes and feedback to surface air temperature across the Tibetan plateau from 1961 to 2013

AbstractSpring snow depth (SSD) in the Tibetan Plateau (TP) plays an essential role in snow water estimation, vegetation growth, and climate projections for Southwest China and the surrounding Asian countries. Previous studies have reported a decline in SSD that is associated with increasing surface air temperature (Ts) across the TP over the past decades. However, only a few studies have explored the potential feedback of SSD to Ts, which has hindered the elucidation of the vulnerability of snow cover in the TP against the backdrop of rapid climate change. Based on data from 69 meteorological stations in the central and eastern parts of the TP, this study analyses changes in SSD and its feedback to Ts from 1961 to 2013. Overall, a slightly negative trend in SSD was observed from 1961 to 2013, during which two contrasting trends were detected using a piecewise regression approach: an initial increase from 1961 to 1981 (0.12 cm decades−1, p < .01) followed by a decrease from 1982 to 2013 (−0.36 cm decades−1, p < .01). Sensitivity analysis revealed that the SSD decline was systematically correlated with a positive Ts anomaly, with sensitivities of −0.050 cm °C−1 (p < .01) and −0.069 cm °C−1 (p < .01) for 1961–2013 and 1982–2013, respectively. However, following the accelerated SSD decline during 1982–2013, its potential feedback to Ts was attenuated, with averaged feedback values from −1.328°C cm−1 during 1961–2013 to −0.936°C cm−1 during 1982–2013 in latitudes below 3,500 m, distributed in the Qaidam and Yellow River basins, and the upper reaches of the Yangtze River basin. The decrease in feedback from SSD to Ts may lead to changes in the mechanism controlling Ts dynamics across the TP, which should be considered in climate change projections in future studies.

Observational analysis of decadal and long-term hydroclimate drivers in the Mediterranean region: role of the ocean–atmosphere system and anthropogenic forcing

Using observations and reanalysis, we develop a robust statistical approach based on canonical correlation analysis (CCA) to explore the leading drivers of decadal and longer-term Mediterranean hydroclimate variability during the historical, half-year wet season. Accordingly, a series of CCA analyses are conducted with combined, multi-component large-scale drivers of Mediterranean precipitation and surface air temperatures. The results highlight the decadal-scale North Atlantic Oscillation (NAO) as the leading driver of hydroclimate variations across the Mediterranean basin. Markedly, the decadal variability of Atlantic-Mediterranean sea surface temperatures (SST), whose influence on the Mediterranean climate has so far been proposed as limited to the summer months, is found to enhance the NAO-induced hydroclimate response during the winter half-year season. As for the long-term, century scale trends, anthropogenic forcing, expressed in terms of the global SST warming (GW) signal, is robustly associated with basin-wide increase in surface air temperatures. Our analyses provide more detailed information than has heretofore been presented on the sub-seasonal evolution and spatial dependence of the large-scale climate variability in the Mediterranean region, separating the effects of natural variability and anthropogenic forcing, with the latter linked to a long-term drying of the region due to GW-induced local poleward shift of the subtropical dry zone. The physical understanding of these mechanisms is essential in order to improve model simulations and prediction of the decadal and longer hydroclimatic evolution in the Mediterranean area, which can help in developing adaptation strategies to mitigate the effect of climate variability and change on the vulnerable regional population.

Economic assessment of the development of CO2 direct reduction technologies in long-term climate strategies of the Gulf countries

This paper proposes an assessment of long-term climate strategies for oil- and gas-producing countries—in particular, the Gulf Cooperation Council (GCC) member states—as regards the Paris Agreement goal of limiting the increase of surface air temperature to 2°C by the end of the twenty-first century. The study evaluates the possible role of carbon dioxide removal (CDR) technologies under an international emissions trading market as a way to mitigate welfare losses. To model the strategic context, one assumes that a global cumulative emissions budget will have been allocated among different coalitions of countries—the GCC being one of them—and the existence of an international emissions trading market. A meta-game model is proposed in which deployment of CDR technologies as well as supply of emission rights are strategic variables and the payoffs are obtained from simulations of a general equilibrium model. The results of the simulations indicate that oil and gas producing countries and especially the GCC countries face a significant welfare loss risk, due to “unburnable oil” if a worldwide climate regime as recommended by the Paris Agreement is put in place. The development of CDR technologies, in particular direct air capture (DAC) alleviates somewhat this risk and offers these countries a new opportunity for exploiting their gas reserves and the carbon storage capacity offered by depleted oil and gas reservoirs.

Adaptive model of the impact of climate change on natural and economic systems of Kazakhstan

In the work, according to the scenarios of climatologists, it is shown that the absence of changes in the amount of precipitation and an increase in the average annual surface air temperature on land will contribute to aridization and desertification of the territory of Kazakhstan under conditions of global warming. In this regard, climatic desertification will contribute to the displacement of the zone of insufficient moisture and an increase in the zone of desert and semi-desert regions. A forecast of a decrease in the yield of grain crops in these conditions is presented, which is a threat to the environmental and food security of Kazakhstan. The aim of the research is to analyze the impact of climate change on agricultural production and the state of water resources in the Republic of Kazakhstan and to develop an adaptive model of the impact of climate change on natural and economic systems. The analysis of the state of water resources as the most vulnerable component for the country under changing climatic conditions is presented. It is shown that under these conditions, adaptation measures are carried out in the Republic aimed at reducing climatic risks and at deriving potential benefits from climate change. We have proposed an adaptive model of the impact of climate change on natural and economic systems, which is based on the methods of mathematical statistics and probabilistic analysis. The levels of adaptation are interpreted in accordance with the index: with an increase in the indicator, the degree of influence on natural and economic systems also increases. The model has a high potential for use in predicting climate change within geographically limited natural and economic systems. The proposed recommendations for adaptation to climate change can find application in the development of state programs for the management of natural and climatic risks.

Remote impacts from the tropical Indian Ocean on haze pollution in January over the Yangtze River Delta

Haze events in the Yangtze River Delta (YRD) region have recently been occurring more frequently and with dramatic damages inflicted on human and ecosystem health. In this study, observational analyses and numerical experiments are used to investigate the meteorological conditions associated with haze pollution, with the main emphasis on the impacts of the preceding sea surface temperature (SST) in the tropical Indian Ocean (TIO). The results show that the December SST in the TIO has a significant positive correlation with the number of haze days in January over the YRD, especially during 1999–2017. In December, the positive SST anomalies in the TIO heat the overlying air, and then in the following January provoke a Matsuno–Gill-like pattern and a series of Rossby wave–like trains in the upper troposphere, transmitting signals to the YRD and downstream through the Sea of Japan and Aleutian Islands. The cyclonic anomalies in the YRD seem to significantly weaken the East Asian jet stream by means of anomalous easterlies, and subsequently affect the climate in the region. Near the surface, the increased surface air temperature and southerly winds, along with the decreased surface wind speed, accompanied by influences from upstream areas, are conducive to the occurrence of haze. These observational results were also reproduced well in CESM-LE simulations.摘要近年来, 长三角霾事件频发, 对人类和生态系统健康造成了严重危害.结果表明:热带印度洋12月海温与长三角1月霾日数呈显著正相关, 特别是1999–2017年.12月, 海温正异常加热上层空气, 1月在对流层上层激发类似Matsuno-Gill模态和一系列Rossby波列, 将信号传输至长三角, 随后向下游日本海和阿留申群岛传播.长三角异常气旋中偏东风削弱东亚急流, 影响该地气候.在近地面, SAT增加, 偏南风盛行, 风速减小, 并伴有上游地区影响, 有利于霾污染发生.上述分析结果在CESM-LE数值实验中得到很好的再现.

Accelerated decline of summer Arctic sea ice during 1850–2017 and the amplified Arctic warming during the recent decades

The 168 year trends of summer (July–September) sea ice area (SIA) variations in six Arctic regions during 1850–2017 are analyzed. SIA has been significantly decreasing in most Arctic regions since 1850. The rate of retreat for the period of 1948–2017 accelerated multi-fold. For the nearly four decades since 1979, most Arctic regions are experiencing the highest reduction rate. Besides the increasing surface air temperature, the key drivers to the accelerated summer Arctic sea ice decline are found to be the combined global warming and the regional Arctic warming exerted simultaneously by the Arctic Oscillation, North Atlantic Oscillation, Atlantic Multidecadal Oscillation and Pacific Decadal Oscillation during the last several decades. The dynamical and thermodynamical warming, driven by the internal variability of the teleconnection patterns, occurred in the last several decades, in particular on the multidecadal timescales. This leads to Arctic amplification that accelerates the positive ice/ocean albedo feedback loop, resulting in accelerating summer sea ice decline.

Attribution of late summer early autumn Arctic sea ice decline in recent decades

The underlying mechanisms for Arctic sea ice decline can be categories as those directly related to changes in atmospheric circulations (often referred to as dynamic mechanisms) and the rest (broadly characterized as thermodynamic processes). An attribution analysis based on the self-organizing maps (SOM) method is performed to determine the relative contributions from these two types of mechanisms to the Arctic sea ice decline in August–October during 1979–2016. The daily atmospheric circulations represented by daily 500-hPa geopotential height anomalies are classified into 12 SOM patterns, which portray the spatial structures of the Arctic Oscillation and Arctic Dipole, and their transitions. Due to the counterbalance between the opposite trends among the circulation patterns, the net effect of circulation changes is small, explaining only 1.6% of the declining trend in the number of August–October sea ice days in the Arctic during 1979–2016. The majority of the trend (95.8%) is accounted for by changes in thermodynamic processes not directly related to changes in circulations, whereas for the remaining trend (2.6%) the contributions of circulation and non-circulation changes cannot be distinguished. The sea ice decline is closely associated with surface air temperature increase, which is related to increasing trends in atmospheric water vapor content, downward longwave radiation, and sea surface temperatures over the open ocean, as well as to decreasing trends in surface albedo. An analogous SOM analysis extending seasonal coverage to spring (April–October) for the same period supports the dominating role of thermodynamic forcing in decadal-scale Arctic sea ice loss.

A Novel Method for Automated Supraglacial Lake Mapping in Antarctica Using Sentinel-1 SAR Imagery and Deep Learning

Supraglacial meltwater accumulation on ice sheets can be a main driver for accelerated ice discharge, mass loss, and global sea-level-rise. With further increasing surface air temperatures, meltwater-induced hydrofracturing, basal sliding, or surface thinning will cumulate and most likely trigger unprecedented ice mass loss on the Greenland and Antarctic ice sheets. While the Greenland surface hydrological network as well as its impacts on ice dynamics and mass balance has been studied in much detail, Antarctic supraglacial lakes remain understudied with a circum-Antarctic record of their spatio-temporal development entirely lacking. This study provides the first automated supraglacial lake extent mapping method using Sentinel-1 synthetic aperture radar (SAR) imagery over Antarctica and complements the developed optical Sentinel-2 supraglacial lake detection algorithm presented in our companion paper. In detail, we propose the use of a modified U-Net for semantic segmentation of supraglacial lakes in single-polarized Sentinel-1 imagery. The convolutional neural network (CNN) is implemented with residual connections for optimized performance as well as an Atrous Spatial Pyramid Pooling (ASPP) module for multiscale feature extraction. The algorithm is trained on 21,200 Sentinel-1 image patches and evaluated in ten spatially or temporally independent test acquisitions. In addition, George VI Ice Shelf is analyzed for intra-annual lake dynamics throughout austral summer 2019/2020 and a decision-level fused Sentinel-1 and Sentinel-2 maximum lake extent mapping product is presented for January 2020 revealing a more complete supraglacial lake coverage (~770 km2) than the individual single-sensor products. Classification results confirm the reliability of the proposed workflow with an average Kappa coefficient of 0.925 and a F1-score of 93.0% for the supraglacial water class across all test regions. Furthermore, the algorithm is applied in an additional test region covering supraglacial lakes on the Greenland ice sheet which further highlights the potential for spatio-temporal transferability. Future work involves the integration of more training data as well as intra-annual analyses of supraglacial lake occurrence across the whole continent and with focus on supraglacial lake development throughout a summer melt season and into Antarctic winter.

The changing nature of ablation-inducing synoptic weather types in the North American Great Lakes basin

The runoff generated by snow cover ablation dominates regional hydrology in the North American Great Lakes basin, while rapid events can represent a physical hazard due to flooding. In determining the likelihood and magnitude of an ablation event, both the presence of snow cover and the synoptic-scale atmospheric environment should be considered, where the atmospheric environment provides the meteorological characteristics and surface energy fluxes necessary for ablation. Pending snowpack availability, variations or changes in the frequency of ablation-inducing synoptic types, and/or varying suitability of meteorological characteristics for snowmelt, can alter the frequency of ablation events. In light of a changing global climate, it is unclear if and how ablation-inducing synoptic types in the Great Lakes basin have transformed in recent decades as from 1960 to 2009, the interannual frequency of snow cover ablation events in the Great Lakes basin has significantly decreased. This study uses synoptic classification as a mechanism for identifying ablation-inducing synoptic weather types and for determining if changes to the frequency and inherent meteorological characteristic of the type are occurring. For a majority of the ten most impactful ablation-inducing synoptic weather types examined, significant trends are noted in their interannual frequencies, which can be partially explained by variations and trends in the phases of common teleconnection indices, such as the North Atlantic and Arctic Oscillations. Collectively, inherent meteorological characteristics of particular weather types in the basin are becoming more suitable for ablation, with increases in surface air temperatures, more southerly wind flow, and less cloud cover, plus increases in liquid precipitation rates during rain-on-snow synoptic types. Independent of snow cover, atmospheric environments suitable for ablation are becoming more frequent and generally more favorable for ablation.

Modeled Climate Responses to Realistic Extremes of Northern Hemisphere Spring and Summer Snow Anomalies

AbstractNorthern Hemisphere (NH) snow cover extent (SCE) has diminished in spring and early summer since the 1960s. Historical simulations from phase 5 of the Coupled Model Intercomparison Project (CMIP5) estimated about half as much NH SCE reduction as observed, and thus underestimated the associated climate responses. This study investigates atmospheric responses to realistic decreasing snow anomalies using multiple ensemble transient integrations of climate models forced by observed light and heavy NH snow cover years, specifically satellite-based observations of NH SCE and snow water equivalent from March to August in 1990 (light snow) and 1985 (heavy snow), as a proxy for the trend. The primary atmospheric responses to March–August NH snow reduction are decreased soil moisture, increased surface air temperature, general tropospheric warming in the extratropics and the Arctic, increased geopotential heights, and weakening of the midlatitude jet stream and eddy kinetic energy. The localized response is maintained by persistent increased diabatic heating due to reduced snow anomalies and resulting soil moisture drying, and the remote atmospheric response results partly from horizontal propagation of stationary Rossby wave energy and also from a transient eddy feedback mechanism. In summer, atmospheric responses are significant in both the Arctic and the tropics and are mostly induced by contemporaneous snow forcing, but also by the summer soil moisture dry anomaly associated with early snow melting.

Evaluating permafrost physics in the Coupled Model Intercomparison Project 6 (CMIP6) models and their sensitivity to climate change

Abstract. Permafrost is a ubiquitous phenomenon in the Arctic. Its future evolution is likely to control changes in northern high-latitude hydrology and biogeochemistry. Here we evaluate the permafrost dynamics in the global models participating in the Coupled Model Intercomparison Project (present generation – CMIP6; previous generation – CMIP5) along with the sensitivity of permafrost to climate change. Whilst the northern high-latitude air temperatures are relatively well simulated by the climate models, they do introduce a bias into any subsequent model estimate of permafrost. Therefore evaluation metrics are defined in relation to the air temperature. This paper shows that the climate, snow and permafrost physics of the CMIP6 multi-model ensemble is very similar to that of the CMIP5 multi-model ensemble. The main differences are that a small number of models have demonstrably better snow insulation in CMIP6 than in CMIP5 and a small number have a deeper soil profile. These changes lead to a small overall improvement in the representation of the permafrost extent. There is little improvement in the simulation of maximum summer thaw depth between CMIP5 and CMIP6. We suggest that more models should include a better-resolved and deeper soil profile as a first step towards addressing this. We use the annual mean thawed volume of the top 2 m of the soil defined from the model soil profiles for the permafrost region to quantify changes in permafrost dynamics. The CMIP6 models project that the annual mean frozen volume in the top 2 m of the soil could decrease by 10 %–40 %∘C-1 of global mean surface air temperature increase.

Copula-based Joint Drought Index using SPI and EDDI and its application to climate change

The drought index, which mainly focuses on the moisture supply side of the atmosphere, which has been mainly used in the field of drought monitoring, has limitations that cannot reflect drought caused by changes in various climate variables such as an increase in surface air temperature due to global warming. To overcome these limitations, various evaporation demand-based drought indices have been proposed, focusing on the aspect of atmospheric moisture demand. However, drought indices that consider only precipitation or the demand for atmospheric evaporation are difficult to comprehensively interpret drought caused by various climatic factors. The novelty of this study is to propose a new drought index to simultaneously monitor droughts occurring in terms of atmospheric moisture supply and demand. The proposed Copula-based Joint Drought Index (CJDI) combines the Standardized Precipitation Index and the Evaporative Demand Drought Index using copula. Since CJDI reflects the correlation between the two drought indices, it is shown that CJDI can better monitor Korea's past droughts than other drought indices. It is found that quantification of past drought using CJDI can be used to objectively recognize the level of drought currently in progress by combining with drought severity-duration-frequency curves derived from partial duration series. As a result of analyzing the future drought pattern in Korea, it was revealed that the drought would be alleviated by about 11% in the case of SPI and SPEI, but the drought would intensify by about 89% in the case of EDDI. In the case of CJDI, it is projected that the drought is likely to intensify to about 17%. From the perspective of better reproducing past droughts and projecting a more convincing future drought than other drought indices, CJDI is expected to be fully utilized as a drought index to monitor droughts and establish climate change adaptation policies.

Attribution Analysis on Regional Differentiation of Water Resources Variation in the Yangtze River Basin under the Context of Global Warming

Characterized by increasing surface air temperature, global warming has altered the hydrological cycle at global and regional scales. In order to adapt water resources management under the context of global warming, attribution analysis on regional differentiation of water resources in the Yangtze River basin (YRB) was conducted in this study. Meteoro-hydrological variations across the basin were examined for the period 1960–2013, and then a statistic-based method was applied in quantifying the contributions of climate variability and human activities on annual runoff variations in different tributary sub-basins in the YRB. Our observation indicates that both the annual increasing rate and the inter-annual fluctuations of temperature in China and in the YRB were higher than that of the global average since the turn of the century. Climate change analysis indicates that the YRB experienced a hot-wet period during 1994–2002 and a hot-dry period during 2003–2013, since the step change of temperature in 1993. Contributions of climate change and human activities on runoff variations varied spatially in the basin. With reference to the baseline period of 1960–1993, the contribution of climate change played a dominant role in most regions of the basin, especially in those upstream sub-basins. The effect of human activities in the basin was quite complicated, not only its regional differentiation, but also its contribution were opposite during the hot-wet period and the hot-dry period in some sub-basins. The result of this study is helpful in understanding the impacts of climate change and human activities on water resources variation in both temporal and spatial scales.

Scalability of future climate changes across Japan examined with large-ensemble simulations at + 1.5\u2009K, +2\u2009K, and + 4\u2009K global warming levels

Large-ensemble climate experiments were performed to simulate future climates for a + 1.5 K rise in the global mean surface air temperatures relative to preindustrial levels as a subset of the database for Policy Decision making for future climate change (d4PDF), using the Non-Hydrostatic Regional Climate Model (NHRCM) with 20 km grid spacing. Along with present climate, + 2 K and + 4 K experimental outputs from the d4PDF already available, we investigated responses of surface air temperature (SAT) and precipitation on regional scales over Japan to global warming. The reproducibility of the present climate experiment is satisfactory to investigate future changes in the Japanese climate, and dynamical downscaling from the global to the regional climate states improves the frequency of heavy daily precipitation. In the future, SAT over Japan rises linearly with and faster than the global mean SAT. The meridional contrast of SAT rises becomes more pronounced as global warming progresses. Winter precipitation decreases/increases linearly in the western/eastern Japan, reflected by weakening of future winter monsoons. Annual maximum daily precipitation (R1d) shows a closely linear increase with the global SAT rise, but annual precipitation is mostly unchanged. The global mean SAT change from + 1.5 to + 2 K enhances R1d by 2.7% over the Japanese Islands, although the increase of R1d varies by regions. The increase in R1d is 5% in northern Japan, where the SAT increases are greater than those in other regions.

A Possible Mechanism for Winter Sea Ice Decline over the Bering Sea and Its Relationship with Cold Events over North America

In this study, the mechanism for the sea ice decline over the Bering Sea and its relationship with cold events over North America are investigated based on the daily ERA-Interim data during the winter (December-February) of 1979-2016. The results show that the sea ice decline over western (eastern) Bering Sea is mainly contributed by (1) the strengthened southerly (southeasterly) wind near the surface, which possibly pushes the sea ice to move northward, and (2) the intensified downward infrared radiation (IR), which is closely related to the local increasing surface air temperature (SAT) and the intensified moisture convergence mostly induced by the anomalous southeasterly wind associated with an anticyclonic anomaly over the Alaska Bay. During the sea ice decline over the Bering Sea, a cold SAT anomaly is simultaneously found over North America. It is proved that the occurrence of such a cold event is driven by the atmospheric internal variation, but not the forcing of sea ice decline over the Bering Sea. This study deepens our understanding of sea ice decline and its relationship with contemporary cold events in winter.

Causal Interactions between Southern Ocean Polynyas and High-Latitude Atmosphere–Ocean Variability

AbstractWeddell Sea open-ocean polynyas have been observed to occasionally release heat from the deep ocean to the atmosphere, indicating that their sporadic appearances may be an important feature of high-latitude atmosphere–ocean variability. Yet, observations of the phenomenon are sparse and many standard-resolution models represent these features poorly, if at all. We use a fully coupled, synoptic-scale preindustrial control simulation of the Energy Exascale Earth System Model (E3SMv0-HR) to effectively simulate open-ocean polynyas and investigate their role in the climate system. Our approach employs statistical tests of Granger causality to diagnose local and remote drivers of, and responses to, polynya heat loss on interannual to decadal time scales. First, we find that polynya heat loss Granger causes a persistent increase in surface air temperature over the Weddell Sea, strengthening the local cyclonic wind circulation. Along with responding to polynyas, atmospheric conditions also facilitate their development. When the Southern Ocean experiences a rapid poleward shift in the circumpolar westerlies following a prolonged negative phase of the southern annular mode (SAM), Weddell Sea salinity increases, promoting density destratification and convection in the water column. Finally, we find that the reduction of surface heat fluxes during periods of full ice cover is not fully compensated by ocean heat transport into the high latitudes. This imbalance leads to a buildup of ocean heat content that supplies polynya heat loss. These results disentangle the complex, coupled climate processes that both enable the polynya’s existence and respond to it, providing insights to improve the representation of these highly episodic sea ice features in climate models.

Structural time-series modelling for seasonal surface air temperature patterns in India 1951–2016

To investigate variability patterns, to predict short-term and long-term changes of weather, time-series data analysis is considered to be a valuable tool. The paper presents modelling and forecasting the seasonal surface air temperature patterns in India for the period 1951–2016 using the structural time-series modelling. The structural time-series model (STSM) with the hidden components of deterministic linear time trend, trigonometric seasonal, and stochastic autoregression for cycle is selected from the parsimonious models. The model selection can be done based on Bayesian Information Criteria (BIC), significant tests, and statistical fit. The model parameters of the noise terms and the damping coefficient in the autoregression are determined using maximizing the likelihood function. The diagnostics of the selected STSM is determined with normal diagnostics checked by examining the histogram and Q–Q plot of residuals; the whiteness checked by autocorrelation function (ACF), partial autocorrelation function (PACF), and p values of LJung–Box portmanteau test of residuals. Furthermore, the forecast of seasonal surface air temperature patterns in India during the years 2017–2019 has been forecasted from the selected STSM. Statistically significant increase is noticed in annual average surface air temperature over India. The increase in surface temperature is about 0.0132 °C per year for the period 1951–2016. The study also showed slow and steady increase in the mean surface air temperature over India during the recent years.

Observational constraints on the effective climate sensitivity from the historical period

The observed warming in the atmosphere and ocean can be used to estimate the climate sensitivity linked to present-day feedbacks, which is referred to as the effective climate sensitivity (Shist). However, such an estimate is affected by uncertainty in the radiative forcing, particularly aerosols, over the historical period. Here, we make use of detection and attribution techniques to derive the surface air temperature and ocean warming that can be attributed directly to greenhouse gas increases. These serve as inputs to a simple energy budget to infer the likelihood of Shist in response to observed greenhouse gases increases over two time periods (1862–2012 and 1955–2012). The benefit of using greenhouse gas attributable quantities is that they are not subject to uncertainties in the aerosol forcing (other than uncertainty in the attribution to greenhouse gas versus aerosol forcing not captured by the multi-model aerosol response pattern). The resulting effective climate sensitivity estimate, Shist, ranges from 1.3 °C to 3.1 °C (5%–95% range) over the full instrumental period (1862–2012) for our best estimate, and gets slightly wider when considering further uncertainties. This estimate increases to 1.7 °C–4.6 °C if using the shorter period (1955–2012). We also evaluate the climate model simulated surface air temperature and ocean heat content increase in response to greenhouse gas forcing over the same periods, and compare them with the observationally-constrained values. We find that that the ocean warming simulated in greenhouse gas only simulations in models considered here is consistent with that attributed to greenhouse gas increases from observations, while one model simulates more greenhouse gas-induced surface air warming than observed. However, other models with sensitivity outside our range show greenhouse gas warming that is consistent with that attributed in observations, emphasising that feedbacks during the historical period may differ from the feedbacks at CO2 doubling and from those at true equilibrium.