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Abstract
Using the past to improve future predictions requires an understanding and quantification of the individual climate contributions to the observed climate change by aerosols and greenhouse gases (GHGs), which is hindered by large uncertainties in aerosol forcings and responses across climate models. To estimate historical aerosol responses, we apply detection and attribution methods to attribute a joint change in temperature and precipitation to forcings by combining signals of observed changes in tropical wet and dry regions, the interhemispheric temperature asymmetry, global mean temperature (GMT), and global mean land precipitation (GMLP). Fingerprints representing the climate response to aerosols (AERs) and the remaining external forcings (noAER; mostly GHG) are derived from large ensembles of historical single- and ALL-forcing simulations from three models in phase 6 of the Coupled Model Intercomparison Project and selected using a perfect model study. Results from an imperfect model study and a hydrological sensitivity analysis support combining our choice of temperature and precipitation fingerprints into a joint study. We find that diagnostics including temperature and precipitation slightly better constrain the noAER signal than diagnostics based purely on temperature or GMT-only and allow for the attribution of AER cooling (even when GMT is not included in the fingerprint). These results are robust across fingerprints from different climate models. Estimated contributions for AER and noAER agree with other published estimates including those from the most recent IPCC report. Finally, we attribute the best estimate of 0.46 K ([−0.86, −0.05] K) of aerosol-induced cooling and 1.63 K ([1.26, 2.00] K) of noAER warming in 2010–19 relative to 1850–1900 using the combined signals of GMT and GMLP.
Significance Statement
Aerosols are small liquid or solid airborne particles. They are predominantly the secondary result of emissions of aerosol precursor gases emitted via industrial or natural processes. While greenhouse gases warm the climate, aerosols can have a cooling effect on the climate system, thus offsetting some of the greenhouse gas–related warming. We expect greenhouse gas concentrations in the atmosphere to continue to increase, while aerosol concentrations are likely going to decline due to their impacts on human health. Our study uses observed temperature and precipitation changes to quantify how much aerosols have offset warming from past greenhouse gas emissions. This can help constrain future predictions of global warming.
Abstract
Using the past to improve future predictions requires an understanding and quantification of the individual climate contributions to the observed climate change by aerosols and greenhouse gases (GHGs), which is hindered by large uncertainties in aerosol forcings and responses across climate models. To estimate historical aerosol responses, we apply detection and attribution methods to attribute a joint change in temperature and precipitation to forcings by combining signals of observed changes in tropical wet and dry regions, the interhemispheric temperature asymmetry, global mean temperature (GMT), and global mean land precipitation (GMLP). Fingerprints representing the climate response to aerosols (AERs) and the remaining external forcings (noAER; mostly GHG) are derived from large ensembles of historical single- and ALL-forcing simulations from three models in phase 6 of the Coupled Model Intercomparison Project and selected using a perfect model study. Results from an imperfect model study and a hydrological sensitivity analysis support combining our choice of temperature and precipitation fingerprints into a joint study. We find that diagnostics including temperature and precipitation slightly better constrain the noAER signal than diagnostics based purely on temperature or GMT-only and allow for the attribution of AER cooling (even when GMT is not included in the fingerprint). These results are robust across fingerprints from different climate models. Estimated contributions for AER and noAER agree with other published estimates including those from the most recent IPCC report. Finally, we attribute the best estimate of 0.46 K ([−0.86, −0.05] K) of aerosol-induced cooling and 1.63 K ([1.26, 2.00] K) of noAER warming in 2010–19 relative to 1850–1900 using the combined signals of GMT and GMLP.
Significance Statement
Aerosols are small liquid or solid airborne particles. They are predominantly the secondary result of emissions of aerosol precursor gases emitted via industrial or natural processes. While greenhouse gases warm the climate, aerosols can have a cooling effect on the climate system, thus offsetting some of the greenhouse gas–related warming. We expect greenhouse gas concentrations in the atmosphere to continue to increase, while aerosol concentrations are likely going to decline due to their impacts on human health. Our study uses observed temperature and precipitation changes to quantify how much aerosols have offset warming from past greenhouse gas emissions. This can help constrain future predictions of global warming.
Abstract
This study explores how future SST warming in remote ocean basins may affect the western North Pacific (WNP) wet season climate by applying a high-resolution atmospheric general circulation model to conduct a series of numerical experiments. A marked precipitation and tropical cyclone (TC) activity reduction, as well as enhanced anticyclonic circulation, in the WNP is projected in AMIP experiments forced by SST change in a future warming scenario. The sensitivity experiments reveal that various SST warming phenomena (e.g., in the global SST warming pattern, the tropical ocean belt, the Indian Ocean, the tropical Atlantic, and the subtropical northeast Pacific) and the increase in greenhouse gas concentration could weaken the precipitation, TC activity, and circulation. By contrast, the SST warming in the WNP and eastern equatorial Pacific has opposite and mixed effects, respectively, and tends to weakly offset the dominant influences of remote ocean warming. These results indicate that the WNP, being the epicenter of the global teleconnection of divergent and rotational flow, is susceptible to the influence of the SST warming in remote ocean basins. The remote forcing as projected in future scenarios would overwhelm the enhancing effect of local SST warming and weaken the circulation, convection, and TC activity in the WNP. These findings further the understanding of how the decreased precipitation and enhanced subtropical high in the WNP may be easily triggered by remote SST warming as revealed in the AMIP-type simulations. How this effect would be affected by air–sea coupling needs further investigation.
Abstract
This study explores how future SST warming in remote ocean basins may affect the western North Pacific (WNP) wet season climate by applying a high-resolution atmospheric general circulation model to conduct a series of numerical experiments. A marked precipitation and tropical cyclone (TC) activity reduction, as well as enhanced anticyclonic circulation, in the WNP is projected in AMIP experiments forced by SST change in a future warming scenario. The sensitivity experiments reveal that various SST warming phenomena (e.g., in the global SST warming pattern, the tropical ocean belt, the Indian Ocean, the tropical Atlantic, and the subtropical northeast Pacific) and the increase in greenhouse gas concentration could weaken the precipitation, TC activity, and circulation. By contrast, the SST warming in the WNP and eastern equatorial Pacific has opposite and mixed effects, respectively, and tends to weakly offset the dominant influences of remote ocean warming. These results indicate that the WNP, being the epicenter of the global teleconnection of divergent and rotational flow, is susceptible to the influence of the SST warming in remote ocean basins. The remote forcing as projected in future scenarios would overwhelm the enhancing effect of local SST warming and weaken the circulation, convection, and TC activity in the WNP. These findings further the understanding of how the decreased precipitation and enhanced subtropical high in the WNP may be easily triggered by remote SST warming as revealed in the AMIP-type simulations. How this effect would be affected by air–sea coupling needs further investigation.
Abstract
The North Atlantic Ocean forcings are considered an important origin of the North Atlantic atmospheric multidecadal variability. Here, we reveal the energetics mechanisms of the phenomenon using the perturbation potential energy (PPE) theory. Supporting the previous model studies, a cyclic pattern involving the Atlantic multidecadal oscillation (AMO) and the North Atlantic tripole (NAT) is observed: positive AMO phase (AMO+) → NAT− → AMO− → NAT+, with a phase lag of approximately 15–20 years. An atmospheric mode characterized by basinscale sea level pressure anomaly in the North Atlantic is associated with the AMO, which is termed the North Atlantic uniformity (NAU). The AMO+ induces positive uniform PPE anomalies over the ocean through precipitation heating, leading to decreased energy conversion to perturbation kinetic energy (PKE) and a large-scale anomalous cyclone. For the NAT+, tripolar precipitation anomalies result in tripolar PPE anomalies. Anomalous energy conversions occur where the PPE anomaly gradient is large, explained by an energy balance derived from thermal wind relationship. The PKE around 15° and 50°N (25° and 75°N) increases (decreases), forming the anomalous anticyclone and cyclone at subtropical and subpolar regions, respectively, known as the North Atlantic Oscillation (NAO). The reverse holds for the NAT− and AMO−. As the phases of the ocean modes alternate, the energetics induce the NAU−, NAO−, NAU+, and NAO+ sequentially. In the multidecadal cycle, the accumulated energetics process is related to delayed effect, and the difference in variance explanation between the NAU and NAO is attributed to the feedback mechanisms.
Significance Statement
The North Atlantic Ocean’s multidecadal changes affect the atmosphere above it. Our study explores the energy processes behind this phenomenon. The North Atlantic Ocean’s temperature distribution goes through a shift every 15–20 years, persistently affecting the air’s potential energy through the heat release related to vapor condensation. The changed potential energy converts into kinetic energy, causing the atmospheric circulation to alternate between different states. Our study provides a comprehensive explanation of how the ocean affects the region’s climate. This insight may contribute to making more accurate models and predictions of climate changes in the North Atlantic.
Abstract
The North Atlantic Ocean forcings are considered an important origin of the North Atlantic atmospheric multidecadal variability. Here, we reveal the energetics mechanisms of the phenomenon using the perturbation potential energy (PPE) theory. Supporting the previous model studies, a cyclic pattern involving the Atlantic multidecadal oscillation (AMO) and the North Atlantic tripole (NAT) is observed: positive AMO phase (AMO+) → NAT− → AMO− → NAT+, with a phase lag of approximately 15–20 years. An atmospheric mode characterized by basinscale sea level pressure anomaly in the North Atlantic is associated with the AMO, which is termed the North Atlantic uniformity (NAU). The AMO+ induces positive uniform PPE anomalies over the ocean through precipitation heating, leading to decreased energy conversion to perturbation kinetic energy (PKE) and a large-scale anomalous cyclone. For the NAT+, tripolar precipitation anomalies result in tripolar PPE anomalies. Anomalous energy conversions occur where the PPE anomaly gradient is large, explained by an energy balance derived from thermal wind relationship. The PKE around 15° and 50°N (25° and 75°N) increases (decreases), forming the anomalous anticyclone and cyclone at subtropical and subpolar regions, respectively, known as the North Atlantic Oscillation (NAO). The reverse holds for the NAT− and AMO−. As the phases of the ocean modes alternate, the energetics induce the NAU−, NAO−, NAU+, and NAO+ sequentially. In the multidecadal cycle, the accumulated energetics process is related to delayed effect, and the difference in variance explanation between the NAU and NAO is attributed to the feedback mechanisms.
Significance Statement
The North Atlantic Ocean’s multidecadal changes affect the atmosphere above it. Our study explores the energy processes behind this phenomenon. The North Atlantic Ocean’s temperature distribution goes through a shift every 15–20 years, persistently affecting the air’s potential energy through the heat release related to vapor condensation. The changed potential energy converts into kinetic energy, causing the atmospheric circulation to alternate between different states. Our study provides a comprehensive explanation of how the ocean affects the region’s climate. This insight may contribute to making more accurate models and predictions of climate changes in the North Atlantic.
Abstract
Extreme precipitation is expected to pose a more severe threat to human society in the future. This work assessed the historical performance and future changes in extreme precipitation and related atmospheric conditions in a large ensemble climate prediction dataset, the database for Policy Decision-making for Future climate change (d4PDF), over East Asia. Compared with the Tropical Rainfall Measuring Mission (TRMM) and fifth major global reanalysis produced by ECMWF (ERA5) datasets, the historical climate in d4PDF represents favorably the precipitation characteristics and the atmospheric conditions, although some differences are notable in the moisture, vertical motion, and cloud water fields. The future climate projection indicates that both the frequency and intensity of heavy precipitation events over East Asia increase compared with those in the present climate. However, when comparing the atmospheric conditions in the historical and future climates for the same precipitation intensity range, the future climate indicates smaller relative humidity, weaker ascent, less cloud water content, and smaller temperature lapse rate, which negatively affect generating extreme precipitation events. The comparison of the precipitation intensity at the same amount of precipitable water between the historical and future climates indicates that extreme precipitation is weaker in the future because of the more stabilized troposphere in the future. The general increase in extreme precipitation under future climate is primarily due to the enhanced increase in precipitable water in the higher temperature ranges, which counteracts the negative conditions of the stabilized troposphere.
Significance Statement
Extreme precipitation can have disastrous effects on human lives, economy, and ecosystems and is anticipated to significantly increase in both intensity and frequency under future climate. The purpose of this study is to investigate the mechanism for the future change of extreme precipitation. We examined the relationship between future changes in extreme precipitation and changes in the related atmospheric conditions. It is important for reducing uncertainties in future projections of extreme precipitation. Our results highlight that the future atmospheric condition is unfavorable for generating future extreme precipitation events in terms of stability and humidity changes. The increase in the column moisture content is the primary factor for the increase of extreme precipitation, which counteracts the negative conditions.
Abstract
Extreme precipitation is expected to pose a more severe threat to human society in the future. This work assessed the historical performance and future changes in extreme precipitation and related atmospheric conditions in a large ensemble climate prediction dataset, the database for Policy Decision-making for Future climate change (d4PDF), over East Asia. Compared with the Tropical Rainfall Measuring Mission (TRMM) and fifth major global reanalysis produced by ECMWF (ERA5) datasets, the historical climate in d4PDF represents favorably the precipitation characteristics and the atmospheric conditions, although some differences are notable in the moisture, vertical motion, and cloud water fields. The future climate projection indicates that both the frequency and intensity of heavy precipitation events over East Asia increase compared with those in the present climate. However, when comparing the atmospheric conditions in the historical and future climates for the same precipitation intensity range, the future climate indicates smaller relative humidity, weaker ascent, less cloud water content, and smaller temperature lapse rate, which negatively affect generating extreme precipitation events. The comparison of the precipitation intensity at the same amount of precipitable water between the historical and future climates indicates that extreme precipitation is weaker in the future because of the more stabilized troposphere in the future. The general increase in extreme precipitation under future climate is primarily due to the enhanced increase in precipitable water in the higher temperature ranges, which counteracts the negative conditions of the stabilized troposphere.
Significance Statement
Extreme precipitation can have disastrous effects on human lives, economy, and ecosystems and is anticipated to significantly increase in both intensity and frequency under future climate. The purpose of this study is to investigate the mechanism for the future change of extreme precipitation. We examined the relationship between future changes in extreme precipitation and changes in the related atmospheric conditions. It is important for reducing uncertainties in future projections of extreme precipitation. Our results highlight that the future atmospheric condition is unfavorable for generating future extreme precipitation events in terms of stability and humidity changes. The increase in the column moisture content is the primary factor for the increase of extreme precipitation, which counteracts the negative conditions.
Abstract
The importance of extreme event attribution rises as climate change causes severe damage to populations resulting from unprecedented events. In February 2019, a planetary wave shifted along the U.S.–Canadian border, simultaneously leading to troughing with anomalous cold events and ridging over Alaska and northern Canada with abnormal warm events. Also, a dry-stabilized anticyclonic circulation over low latitudes induced warm extreme events over Mexico and Florida. Most attribution studies compare the climate model simulations under natural or actual forcing conditions and assess probabilistically from a climatological point of view. However, in this study, we use multiple ensembles from an operational forecast model, promising statistical as well as dynamically constrained attribution assessment, often referred to as the storyline approach to extreme event attribution. In the globally averaged results, increasing CO2 concentrations lead to distinct warming signals at the surface, resulting mainly from diabatic heating. Our study finds that CO2-induced warming eventually affects the possibility of extreme events in North America, quantifying the impact of anthropogenic forcing over less than a week’s forecast simulation. Our study assesses the validity of the storyline approach conditional on the forecast lead times, which is hindered by rising noise in CO2 signals and the declining performance of the forecast model. The forecast-based storyline approach is valid for at least half of the land area within a 6-day lead time before the target extreme occurrence. Our attribution results highlight the importance of achieving net-zero emissions ahead of schedule to reduce the occurrence of severe heatwaves.
Abstract
The importance of extreme event attribution rises as climate change causes severe damage to populations resulting from unprecedented events. In February 2019, a planetary wave shifted along the U.S.–Canadian border, simultaneously leading to troughing with anomalous cold events and ridging over Alaska and northern Canada with abnormal warm events. Also, a dry-stabilized anticyclonic circulation over low latitudes induced warm extreme events over Mexico and Florida. Most attribution studies compare the climate model simulations under natural or actual forcing conditions and assess probabilistically from a climatological point of view. However, in this study, we use multiple ensembles from an operational forecast model, promising statistical as well as dynamically constrained attribution assessment, often referred to as the storyline approach to extreme event attribution. In the globally averaged results, increasing CO2 concentrations lead to distinct warming signals at the surface, resulting mainly from diabatic heating. Our study finds that CO2-induced warming eventually affects the possibility of extreme events in North America, quantifying the impact of anthropogenic forcing over less than a week’s forecast simulation. Our study assesses the validity of the storyline approach conditional on the forecast lead times, which is hindered by rising noise in CO2 signals and the declining performance of the forecast model. The forecast-based storyline approach is valid for at least half of the land area within a 6-day lead time before the target extreme occurrence. Our attribution results highlight the importance of achieving net-zero emissions ahead of schedule to reduce the occurrence of severe heatwaves.
Abstract
Precipitation in eastern China exhibits large interannual variability during July with the northward movement of the monsoon rain belt. Thus, eastern China usually experiences severe droughts and floods in July. However, the influences of underlying surface thermal drivers, particularly the land factors, remain poorly understood. This study investigates the leading modes of July precipitation in eastern China and their potential influencing factors. The first and second empirical orthogonal function (EOF) modes show meridional dipole and tripolar precipitation anomalies in eastern China, respectively. The EOF1 mode is found to be closely associated with sea surface temperature (SST) anomalies in the tropical Pacific and North Atlantic Oceans in June, while the EOF2 mode is mainly linked to anomalous Indian Ocean SST and Indochina Peninsula soil moisture in June. During years with a strong El Niño–South Oscillation (ENSO) signal, the EOF1 mode is mainly related to the enhanced Walker and Hadley circulations associated with the cold tropical Pacific SST anomalies. In contrast, during years with a weak ENSO signal, the Eurasian midlatitude wave train and the westward zonal overturning circulation associated with tripole-like North Atlantic SST anomalies play a leading role. The EOF2 mode is mainly influenced by Indian Ocean SST anomalies that alter the Walker circulation and by soil moisture anomalies in the Indochina Peninsula that induce an anomalous regional cyclonic circulation. Numerical experiments further demonstrated that the combined effects of soil moisture and SST exert a more substantial impact than their individual effects. These results emphasize the importance of surface thermal factors in understanding regional climate dynamics.
Abstract
Precipitation in eastern China exhibits large interannual variability during July with the northward movement of the monsoon rain belt. Thus, eastern China usually experiences severe droughts and floods in July. However, the influences of underlying surface thermal drivers, particularly the land factors, remain poorly understood. This study investigates the leading modes of July precipitation in eastern China and their potential influencing factors. The first and second empirical orthogonal function (EOF) modes show meridional dipole and tripolar precipitation anomalies in eastern China, respectively. The EOF1 mode is found to be closely associated with sea surface temperature (SST) anomalies in the tropical Pacific and North Atlantic Oceans in June, while the EOF2 mode is mainly linked to anomalous Indian Ocean SST and Indochina Peninsula soil moisture in June. During years with a strong El Niño–South Oscillation (ENSO) signal, the EOF1 mode is mainly related to the enhanced Walker and Hadley circulations associated with the cold tropical Pacific SST anomalies. In contrast, during years with a weak ENSO signal, the Eurasian midlatitude wave train and the westward zonal overturning circulation associated with tripole-like North Atlantic SST anomalies play a leading role. The EOF2 mode is mainly influenced by Indian Ocean SST anomalies that alter the Walker circulation and by soil moisture anomalies in the Indochina Peninsula that induce an anomalous regional cyclonic circulation. Numerical experiments further demonstrated that the combined effects of soil moisture and SST exert a more substantial impact than their individual effects. These results emphasize the importance of surface thermal factors in understanding regional climate dynamics.
Abstract
To improve understanding of ocean processes impacting monthly sea surface temperature (SST) variability, we analyze a Community Earth System Model, version 2, hierarchy in which models vary only in their degree of ocean complexity. The most realistic ocean is a dynamical ocean model, as part of a fully coupled model (FCM). The next most realistic ocean, from a mechanically decoupled model (MDM), is like the FCM but excludes anomalous wind stress–driven ocean variability. The simplest ocean is a slab ocean model (SOM). Inclusion of a buoyancy coupled dynamic ocean as in the MDM, which includes temperature advection and vertical mixing absent in the SOM, leads to dampening of SST variance everywhere and reduced persistence of SST anomalies in the high latitudes and equatorial Pacific compared to the SOM. Inclusion of anomalous wind stress–driven ocean dynamics as in the FCM leads to higher SST variance and longer persistence time scales in most regions compared to the MDM. The net role of the dynamic ocean, as an overall dampener or amplifier of anomalous SST variance and persistence, is regionally dependent. Notably, we find that efforts to reduce the complexity of the ocean models in the SOM and MDM configurations result in changes in the magnitude of the thermodynamic forcing of SST variability compared to the FCM. These changes, in part, stem from differences in the seasonally varying mixed layer depth and should be considered when attempting to quantify the relative contribution of certain ocean mechanisms to differences in SST variability between the models.
Abstract
To improve understanding of ocean processes impacting monthly sea surface temperature (SST) variability, we analyze a Community Earth System Model, version 2, hierarchy in which models vary only in their degree of ocean complexity. The most realistic ocean is a dynamical ocean model, as part of a fully coupled model (FCM). The next most realistic ocean, from a mechanically decoupled model (MDM), is like the FCM but excludes anomalous wind stress–driven ocean variability. The simplest ocean is a slab ocean model (SOM). Inclusion of a buoyancy coupled dynamic ocean as in the MDM, which includes temperature advection and vertical mixing absent in the SOM, leads to dampening of SST variance everywhere and reduced persistence of SST anomalies in the high latitudes and equatorial Pacific compared to the SOM. Inclusion of anomalous wind stress–driven ocean dynamics as in the FCM leads to higher SST variance and longer persistence time scales in most regions compared to the MDM. The net role of the dynamic ocean, as an overall dampener or amplifier of anomalous SST variance and persistence, is regionally dependent. Notably, we find that efforts to reduce the complexity of the ocean models in the SOM and MDM configurations result in changes in the magnitude of the thermodynamic forcing of SST variability compared to the FCM. These changes, in part, stem from differences in the seasonally varying mixed layer depth and should be considered when attempting to quantify the relative contribution of certain ocean mechanisms to differences in SST variability between the models.
Abstract
In contrast to boreal winter when extratropical seasonal predictions benefit greatly from ENSO-related teleconnections, our understanding of forecast skill and sources of predictability in summer is limited. Based on 40 years of hindcasts of the Canadian Seasonal to Interannual Prediction System, version 3 (CanSIPSv3), this study shows that predictions for the Northern Hemisphere summer surface air temperature are skillful more than 6 months in advance in several midlatitude regions, including eastern Europe–Middle East, central Siberia–Mongolia–North China, and the western United States. These midlatitude regions of statistically significant predictive skill appear to be connected to each other through an upper-tropospheric circumglobal wave train. Although a large part of the forecast skill for the surface air temperature and 500-hPa geopotential height is attributable to the linear trend associated with global warming, there is significant long-lead seasonal forecast skill related to interannual variability. Two additional idealized hindcast experiments are performed to help shed light on sources of the long-lead forecast skill using one of the CanSIPSv3 models and its uncoupled version. It is found that tropical ENSO-related sea surface temperature (SST) anomalies contribute to the forecast skill in the western United States, while land surface conditions in winter, including snow cover and soil moisture, in the Siberian and western U.S. regions have a delayed or long-lasting impact on the atmosphere, which leads to summer forecast skill in these regions. This implies that improving land surface initial conditions and model representation of land surface processes is crucial for the further development of a seasonal forecasting system.
Significance Statement
Useful seasonal predictions in the boreal summer midlatitude regions are of great value. In this study, we show that predictions for the boreal summer season are skillful more than 6 months in advance in several midlatitude regions, including eastern Europe–Middle East, central Siberia–Mongolia–North China, and the western United States. The forecast skill in these regions is associated with a circumglobal teleconnection atmospheric circulation pattern. Sources of the long-lead forecast skill include the global warming–related trend and anomalies in the ocean and land surface initial conditions. It is found that the wintertime snow cover and soil moisture in the Siberian and western U.S. regions have a delayed or long-lasting impact on the atmosphere, which leads to summer forecast skill.
Abstract
In contrast to boreal winter when extratropical seasonal predictions benefit greatly from ENSO-related teleconnections, our understanding of forecast skill and sources of predictability in summer is limited. Based on 40 years of hindcasts of the Canadian Seasonal to Interannual Prediction System, version 3 (CanSIPSv3), this study shows that predictions for the Northern Hemisphere summer surface air temperature are skillful more than 6 months in advance in several midlatitude regions, including eastern Europe–Middle East, central Siberia–Mongolia–North China, and the western United States. These midlatitude regions of statistically significant predictive skill appear to be connected to each other through an upper-tropospheric circumglobal wave train. Although a large part of the forecast skill for the surface air temperature and 500-hPa geopotential height is attributable to the linear trend associated with global warming, there is significant long-lead seasonal forecast skill related to interannual variability. Two additional idealized hindcast experiments are performed to help shed light on sources of the long-lead forecast skill using one of the CanSIPSv3 models and its uncoupled version. It is found that tropical ENSO-related sea surface temperature (SST) anomalies contribute to the forecast skill in the western United States, while land surface conditions in winter, including snow cover and soil moisture, in the Siberian and western U.S. regions have a delayed or long-lasting impact on the atmosphere, which leads to summer forecast skill in these regions. This implies that improving land surface initial conditions and model representation of land surface processes is crucial for the further development of a seasonal forecasting system.
Significance Statement
Useful seasonal predictions in the boreal summer midlatitude regions are of great value. In this study, we show that predictions for the boreal summer season are skillful more than 6 months in advance in several midlatitude regions, including eastern Europe–Middle East, central Siberia–Mongolia–North China, and the western United States. The forecast skill in these regions is associated with a circumglobal teleconnection atmospheric circulation pattern. Sources of the long-lead forecast skill include the global warming–related trend and anomalies in the ocean and land surface initial conditions. It is found that the wintertime snow cover and soil moisture in the Siberian and western U.S. regions have a delayed or long-lasting impact on the atmosphere, which leads to summer forecast skill.
Abstract
Decadal thermohaline anomalies carried northward by the North Atlantic Current are an important source of predictability in the North Atlantic region. Here, we investigate whether these thermohaline anomalies influence surface-forced water mass transformation (SFWMT) in the eastern subpolar gyre using the reanalyses EN4.2.2 for the ocean and the ERA5 for the atmosphere. In addition, we follow the propagation of thermohaline anomalies along two paths: in the subpolar North Atlantic and the Norwegian Sea. We use observation-based datasets (HadISST, EN4.2.2, and Ishii) between 1947 and 2021 and apply complex empirical orthogonal functions. Our results show that when a warm anomaly enters the eastern subpolar gyre, more SFWMT occurs in light-density classes (27.0–27.2 kg m−3). In contrast, when a cold anomaly enters the eastern subpolar gyre, more SFWMT occurs in denser classes (27.4–27.5 kg m−3). Following the thermohaline anomalies in both paths, we find alternating warm–salty and cold–fresh subsurface anomalies, repeating throughout the 74-yr-long record with four warm–salty and cold–fresh periods after the 1950s. The cold–fresh anomaly periods happen simultaneously with the Great Salinity Anomaly events. Moreover, the propagation of thermohaline anomalies is faster in the subpolar North Atlantic (SPNA) than in the Norwegian Sea, especially for temperature anomalies. These findings might have implications for our understanding of the decadal variability of the lower limb of the Atlantic meridional overturning circulation and predictability in the North Atlantic region.
Significance Statement
Anomalously warm–salty or cold–fresh water, carried by the North Atlantic Current toward the Arctic, is a source of climate predictability. In this study, we investigate 1) how these ocean anomalies influence the transformation of water masses in the eastern subpolar gyre and 2) their subsequent propagation poleward and northwestward. The key findings reveal that anomalously warm waters entering the eastern subpolar gyre lead to increased transformation in lighter water masses, while cold anomalies affect denser water masses. These anomalies propagate more than 2 times faster toward the Greenland coast (northwestward) than toward the Arctic (poleward). Our findings contribute to enhancing the understanding of decadal predictability in the northern North Atlantic, including its influence on the Atlantic meridional overturning circulation.
Abstract
Decadal thermohaline anomalies carried northward by the North Atlantic Current are an important source of predictability in the North Atlantic region. Here, we investigate whether these thermohaline anomalies influence surface-forced water mass transformation (SFWMT) in the eastern subpolar gyre using the reanalyses EN4.2.2 for the ocean and the ERA5 for the atmosphere. In addition, we follow the propagation of thermohaline anomalies along two paths: in the subpolar North Atlantic and the Norwegian Sea. We use observation-based datasets (HadISST, EN4.2.2, and Ishii) between 1947 and 2021 and apply complex empirical orthogonal functions. Our results show that when a warm anomaly enters the eastern subpolar gyre, more SFWMT occurs in light-density classes (27.0–27.2 kg m−3). In contrast, when a cold anomaly enters the eastern subpolar gyre, more SFWMT occurs in denser classes (27.4–27.5 kg m−3). Following the thermohaline anomalies in both paths, we find alternating warm–salty and cold–fresh subsurface anomalies, repeating throughout the 74-yr-long record with four warm–salty and cold–fresh periods after the 1950s. The cold–fresh anomaly periods happen simultaneously with the Great Salinity Anomaly events. Moreover, the propagation of thermohaline anomalies is faster in the subpolar North Atlantic (SPNA) than in the Norwegian Sea, especially for temperature anomalies. These findings might have implications for our understanding of the decadal variability of the lower limb of the Atlantic meridional overturning circulation and predictability in the North Atlantic region.
Significance Statement
Anomalously warm–salty or cold–fresh water, carried by the North Atlantic Current toward the Arctic, is a source of climate predictability. In this study, we investigate 1) how these ocean anomalies influence the transformation of water masses in the eastern subpolar gyre and 2) their subsequent propagation poleward and northwestward. The key findings reveal that anomalously warm waters entering the eastern subpolar gyre lead to increased transformation in lighter water masses, while cold anomalies affect denser water masses. These anomalies propagate more than 2 times faster toward the Greenland coast (northwestward) than toward the Arctic (poleward). Our findings contribute to enhancing the understanding of decadal predictability in the northern North Atlantic, including its influence on the Atlantic meridional overturning circulation.
Abstract
The Greenland Ice Sheet (GrIS) meltwater runoff has increased considerably since the 1990s, leading to implications for the ice sheet mass balance and ecosystem dynamics in ice-free areas. Extreme weather events will likely continue to occur in the coming decades. Therefore, a more thorough understanding of the spatiotemporal patterns of extreme melting events is of interest. This study aims to analyze the evolution of extreme melting events across the GrIS and determine the climatic factors that drive them. Specifically, we have analyzed extreme melting events (90th percentile) across the GrIS from 1950 to 2022 and examined their links to the surface energy balance (SEB) and large-scale atmospheric circulation. Extreme melting days account for approximately 35%–40% of the total accumulated melting per season. We found that extreme melting frequency, intensity, and contribution to the total accumulated June–August (summer) melting show a statistically significant upward trend at a 95% confidence level. The largest trends are detected across the northern GrIS. The trends are independent of the extreme melting percentile rank (90th, 97th, or 99th) analyzed and are consistent with average melting trends that exhibit an increase in similar magnitude and spatial configuration. Radiation plays a dominant role in controlling the SEB during extreme melting days. The increase in extreme melting frequency and intensity is driven by the increase in anticyclonic weather types during summer and more energy available for melting. Our results help to enhance the understanding of extreme events in the Arctic.
Abstract
The Greenland Ice Sheet (GrIS) meltwater runoff has increased considerably since the 1990s, leading to implications for the ice sheet mass balance and ecosystem dynamics in ice-free areas. Extreme weather events will likely continue to occur in the coming decades. Therefore, a more thorough understanding of the spatiotemporal patterns of extreme melting events is of interest. This study aims to analyze the evolution of extreme melting events across the GrIS and determine the climatic factors that drive them. Specifically, we have analyzed extreme melting events (90th percentile) across the GrIS from 1950 to 2022 and examined their links to the surface energy balance (SEB) and large-scale atmospheric circulation. Extreme melting days account for approximately 35%–40% of the total accumulated melting per season. We found that extreme melting frequency, intensity, and contribution to the total accumulated June–August (summer) melting show a statistically significant upward trend at a 95% confidence level. The largest trends are detected across the northern GrIS. The trends are independent of the extreme melting percentile rank (90th, 97th, or 99th) analyzed and are consistent with average melting trends that exhibit an increase in similar magnitude and spatial configuration. Radiation plays a dominant role in controlling the SEB during extreme melting days. The increase in extreme melting frequency and intensity is driven by the increase in anticyclonic weather types during summer and more energy available for melting. Our results help to enhance the understanding of extreme events in the Arctic.
