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Abstract
Biomass burning aerosol (BBA) emissions in the Coupled Model Intercomparison Project phase 6 (CMIP6) historical forcing fields have enhanced temporal variability during the years 1997–2014 compared to earlier periods. Recent studies document that the corresponding inhomogeneous shortwave forcing over this period can cause changes in clouds, permafrost, and soil moisture, which contribute to a net terrestrial Northern Hemisphere warming relative to earlier periods. Here, we investigate the ocean response to the hemispherically asymmetric warming, using a 100-member ensemble of the Community Earth System Model version 2 Large Ensemble forced by two different BBA emissions (CMIP6 default and temporally smoothed over 1990–2020). Differences between the two subensemble means show that ocean temperature anomalies occur during periods of high BBA variability and subsequently persist over multiple decades. In the North Atlantic, surface warming is efficiently compensated for by decreased northward oceanic heat transport due to a slowdown of the Atlantic meridional overturning circulation. In the North Pacific, surface warming is compensated for by an anomalous cross-equatorial cell (CEC) that reduces northward oceanic heat transport. The heat that converges in the South Pacific through the anomalous CEC is shunted into the subsurface and contributes to formation of long-lasting ocean temperature anomalies. The anomalous CEC is maintained through latitude-dependent contributions from narrow western boundary currents and basinwide near-surface Ekman transport. These results indicate that interannual variability in forcing fields may significantly change the background climate state over long time scales, presenting a potential uncertainty in CMIP6-class climate projections forced without interannual variability.
Abstract
Biomass burning aerosol (BBA) emissions in the Coupled Model Intercomparison Project phase 6 (CMIP6) historical forcing fields have enhanced temporal variability during the years 1997–2014 compared to earlier periods. Recent studies document that the corresponding inhomogeneous shortwave forcing over this period can cause changes in clouds, permafrost, and soil moisture, which contribute to a net terrestrial Northern Hemisphere warming relative to earlier periods. Here, we investigate the ocean response to the hemispherically asymmetric warming, using a 100-member ensemble of the Community Earth System Model version 2 Large Ensemble forced by two different BBA emissions (CMIP6 default and temporally smoothed over 1990–2020). Differences between the two subensemble means show that ocean temperature anomalies occur during periods of high BBA variability and subsequently persist over multiple decades. In the North Atlantic, surface warming is efficiently compensated for by decreased northward oceanic heat transport due to a slowdown of the Atlantic meridional overturning circulation. In the North Pacific, surface warming is compensated for by an anomalous cross-equatorial cell (CEC) that reduces northward oceanic heat transport. The heat that converges in the South Pacific through the anomalous CEC is shunted into the subsurface and contributes to formation of long-lasting ocean temperature anomalies. The anomalous CEC is maintained through latitude-dependent contributions from narrow western boundary currents and basinwide near-surface Ekman transport. These results indicate that interannual variability in forcing fields may significantly change the background climate state over long time scales, presenting a potential uncertainty in CMIP6-class climate projections forced without interannual variability.
Abstract
Does a warming world, where extremely hot summers are becoming more common, mean that cold summers will never again occur? It is crucial to know whether extremely cold summers are still possible, as such knowledge will significantly impact decisions regarding the further adaptation of crops to cold summers. Japan, which has suffered from many extremely cold summers, has managed past agricultural disruptions with emergency rice imports. In this paper, we show that a climate regime shift associated with the positive phase shift of the summer Arctic Oscillation occurred in 2010 in northeast Eurasia, making the occurrence of extremely cold summers highly unlikely as long as this new regime persists. In fact, Japan has not experienced a cold summer since 2010, while extremely hot summers have been frequent. Since 2010, a double-jet structure with subtropical and polar jets has strengthened, and the polar jet has meandered farther north of Japan, resulting in an upper-tropospheric anticyclone. This anticyclone, which extends downward and tilts southward, reaches southern Japan and prevents cold advection of oceanic air over the cold Oyashio. The Okhotsk high, known as the leading cause of cold summers, has occurred frequently in recent years; however, cold summers have not occurred due to the tilting anticyclone. The recent warming of the Oyashio weakens cold advection. The Pacific–Japan pattern, known as a remote tropical influence, has been weakened. A better understanding of the regime shift will help us understand the tilting anticyclone and the associated extreme summers in northeast Eurasia.
Significance Statement
Extremely cold summers are among the most destructive natural disasters, both socioeconomically and agriculturally. Historically, food shortages due to cold summers have triggered wars. This paper proposes that a hemispheric-scale climate regime shift occurred in or around 2010. This regime shift has included warmings in the North Pacific and East Eurasian land surface temperatures. The regime shift is accompanied by the positive shift of the Arctic Oscillation (AO), a jet meander, and an upper-tropospheric anticyclone, making eastern Eurasia extremely hot. Our results imply that extremely cold summers are unlikely to occur in eastern Eurasia so long as this regime persists. Moving forward, it is important that the link between this regime shift and global warming be explored.
Abstract
Does a warming world, where extremely hot summers are becoming more common, mean that cold summers will never again occur? It is crucial to know whether extremely cold summers are still possible, as such knowledge will significantly impact decisions regarding the further adaptation of crops to cold summers. Japan, which has suffered from many extremely cold summers, has managed past agricultural disruptions with emergency rice imports. In this paper, we show that a climate regime shift associated with the positive phase shift of the summer Arctic Oscillation occurred in 2010 in northeast Eurasia, making the occurrence of extremely cold summers highly unlikely as long as this new regime persists. In fact, Japan has not experienced a cold summer since 2010, while extremely hot summers have been frequent. Since 2010, a double-jet structure with subtropical and polar jets has strengthened, and the polar jet has meandered farther north of Japan, resulting in an upper-tropospheric anticyclone. This anticyclone, which extends downward and tilts southward, reaches southern Japan and prevents cold advection of oceanic air over the cold Oyashio. The Okhotsk high, known as the leading cause of cold summers, has occurred frequently in recent years; however, cold summers have not occurred due to the tilting anticyclone. The recent warming of the Oyashio weakens cold advection. The Pacific–Japan pattern, known as a remote tropical influence, has been weakened. A better understanding of the regime shift will help us understand the tilting anticyclone and the associated extreme summers in northeast Eurasia.
Significance Statement
Extremely cold summers are among the most destructive natural disasters, both socioeconomically and agriculturally. Historically, food shortages due to cold summers have triggered wars. This paper proposes that a hemispheric-scale climate regime shift occurred in or around 2010. This regime shift has included warmings in the North Pacific and East Eurasian land surface temperatures. The regime shift is accompanied by the positive shift of the Arctic Oscillation (AO), a jet meander, and an upper-tropospheric anticyclone, making eastern Eurasia extremely hot. Our results imply that extremely cold summers are unlikely to occur in eastern Eurasia so long as this regime persists. Moving forward, it is important that the link between this regime shift and global warming be explored.
Abstract
Climate feedbacks are sensitive to the geographical distribution of sea surface temperature (SST). This sensitivity, called the pattern effect, affects the amplitude of the Earth radiative response to anomalies in global mean surface temperature (GMST) and thus is essential in shaping the global energy budget dynamics. Zero-dimensional energy balance models (EBMs) are the simplest representation of the global energy budget dynamics. Many only depend on GMST anomalies and cannot account for the pattern effect explicitly. In EBMs, the pattern effect leads to apparent variations of the global climate feedback parameter λ. Assuming a variable λ in EBMs enables them to more accurately reproduce AOGCM simulations of the GMST anomalies but it leads to variations in λ of >+15%. These large variations mean λ is not a constant and the Taylor expansion underpinning EBMs’ formulation does not hold, casting doubts on the physical grounding of such EBMs. Here we propose a new EBM based on a multivariate linear Earth radiative response, which depends on both the GMST and the surface warming pattern. The resulting multilinear EBM accurately reproduces AOGCM simulations of anomalies in Earth radiative response and GMST under abrupt 4xCO2 forcing. When interpreted in terms of variable λ, the multivariate EBM leads to small variations in λ that are physically consistent with the underpinning Taylor expansion. We analyze with the multivariate framework the variations of the planetary heat uptake N as a function of the GMST and the pattern of warming through a 3D generalization of the Gregory plot. We show that the apparent nonlinear behavior of the radiative response of the Earth against GMST seen in classical monovariate EBMs (and in classical Gregory plots) can actually be explained by a bilinear dependance of the radiative response of the Earth on the GMST and the pattern of warming. The multivariate EBM further provides an explicit dependence of the global energy budget on the pattern of warming and on the climate state. It has important consequences on the expression of the climate sensitivity.
Abstract
Climate feedbacks are sensitive to the geographical distribution of sea surface temperature (SST). This sensitivity, called the pattern effect, affects the amplitude of the Earth radiative response to anomalies in global mean surface temperature (GMST) and thus is essential in shaping the global energy budget dynamics. Zero-dimensional energy balance models (EBMs) are the simplest representation of the global energy budget dynamics. Many only depend on GMST anomalies and cannot account for the pattern effect explicitly. In EBMs, the pattern effect leads to apparent variations of the global climate feedback parameter λ. Assuming a variable λ in EBMs enables them to more accurately reproduce AOGCM simulations of the GMST anomalies but it leads to variations in λ of >+15%. These large variations mean λ is not a constant and the Taylor expansion underpinning EBMs’ formulation does not hold, casting doubts on the physical grounding of such EBMs. Here we propose a new EBM based on a multivariate linear Earth radiative response, which depends on both the GMST and the surface warming pattern. The resulting multilinear EBM accurately reproduces AOGCM simulations of anomalies in Earth radiative response and GMST under abrupt 4xCO2 forcing. When interpreted in terms of variable λ, the multivariate EBM leads to small variations in λ that are physically consistent with the underpinning Taylor expansion. We analyze with the multivariate framework the variations of the planetary heat uptake N as a function of the GMST and the pattern of warming through a 3D generalization of the Gregory plot. We show that the apparent nonlinear behavior of the radiative response of the Earth against GMST seen in classical monovariate EBMs (and in classical Gregory plots) can actually be explained by a bilinear dependance of the radiative response of the Earth on the GMST and the pattern of warming. The multivariate EBM further provides an explicit dependence of the global energy budget on the pattern of warming and on the climate state. It has important consequences on the expression of the climate sensitivity.
Abstract
Atmospheric macroturbulence transports energy down the equator-to-pole gradient. This is represented by diffusion in energy balance models (EBMs), and EBMs have proven valuable for understanding and quantifying the pattern of surface temperature change. They typically assume climate-state-independent diffusivity, chosen to well represent the current climate, and find that this is sufficient to emulate warming response in general circulation models (GCMs). Meanwhile, model diagnoses of GCM simulations have shown that the diffusivity changes with climate. There is also ongoing development for diffusivity theories based on atmospheric dynamics. Here, we examine the role that changes in diffusivity play in the large-scale equator-to-pole contrast in surface warming in EBMs, building on previous analytic EBM theories for polar-amplified warming. New analytic theories for two formulations of climate-state-dependent diffusivity capture the results of numerical EBM solutions. For reasonable choices of parameter values, the success of the new analytic theories reveals why the change of diffusivity is limited in response to radiative forcing and does not eliminate polar-amplified warming.
Abstract
Atmospheric macroturbulence transports energy down the equator-to-pole gradient. This is represented by diffusion in energy balance models (EBMs), and EBMs have proven valuable for understanding and quantifying the pattern of surface temperature change. They typically assume climate-state-independent diffusivity, chosen to well represent the current climate, and find that this is sufficient to emulate warming response in general circulation models (GCMs). Meanwhile, model diagnoses of GCM simulations have shown that the diffusivity changes with climate. There is also ongoing development for diffusivity theories based on atmospheric dynamics. Here, we examine the role that changes in diffusivity play in the large-scale equator-to-pole contrast in surface warming in EBMs, building on previous analytic EBM theories for polar-amplified warming. New analytic theories for two formulations of climate-state-dependent diffusivity capture the results of numerical EBM solutions. For reasonable choices of parameter values, the success of the new analytic theories reveals why the change of diffusivity is limited in response to radiative forcing and does not eliminate polar-amplified warming.
Abstract
This study first developed a comprehensive semiautomatic data homogenization procedure to produce gap-infilled and homogenized monthly precipitation data series for 425 long-term/critical stations in Canada, which were then used to assess Canadian historical precipitation trends. Data gaps in the 425 series were infilled by advanced spatial interpolation of a much larger dataset. The homogenization procedure repeatedly used multiple homogeneity tests without and with reference series to identify changepoints/inhomogeneities, the results from which were finalized by manual analysis using metadata and visual inspection of the multiphase regression fits. As a result, 298 out of the 425 data series were found to be inhomogeneous. These series were homogenized using quantile matching adjustments. The homogenized dataset shows better spatial consistency of trends than does the raw dataset. The improved gridding and regional mean trend estimation methods also provide more realistic trend estimates. With these improvements, Canadian historical precipitation trends were found to be dominantly positive and significant, except in central-south Canada where the trends are generally insignificant and small with mixed directions. For annual precipitation, the largest increases are seen in southeastern Canada and along the Pacific coast; however, the largest relative increases (in percent of the 1961–90 mean) are seen in northern Canada. The largest trend difference between northern and southern Canada is seen in winter, in which significant increases in the north were matched with significant decreases in the south.
Significance Statement
This study aims to produce a homogenized long-term monthly precipitation dataset for Canada, which is then used to assess Canadian historical precipitation trends. The work is important because it developed a comprehensive algorithm for homogenization of precipitation data, and the results provide better representation of precipitation climate and more robust estimates of precipitation trends. It also identified the causes for large biases in the published estimates of precipitation trends over Canada.
Abstract
This study first developed a comprehensive semiautomatic data homogenization procedure to produce gap-infilled and homogenized monthly precipitation data series for 425 long-term/critical stations in Canada, which were then used to assess Canadian historical precipitation trends. Data gaps in the 425 series were infilled by advanced spatial interpolation of a much larger dataset. The homogenization procedure repeatedly used multiple homogeneity tests without and with reference series to identify changepoints/inhomogeneities, the results from which were finalized by manual analysis using metadata and visual inspection of the multiphase regression fits. As a result, 298 out of the 425 data series were found to be inhomogeneous. These series were homogenized using quantile matching adjustments. The homogenized dataset shows better spatial consistency of trends than does the raw dataset. The improved gridding and regional mean trend estimation methods also provide more realistic trend estimates. With these improvements, Canadian historical precipitation trends were found to be dominantly positive and significant, except in central-south Canada where the trends are generally insignificant and small with mixed directions. For annual precipitation, the largest increases are seen in southeastern Canada and along the Pacific coast; however, the largest relative increases (in percent of the 1961–90 mean) are seen in northern Canada. The largest trend difference between northern and southern Canada is seen in winter, in which significant increases in the north were matched with significant decreases in the south.
Significance Statement
This study aims to produce a homogenized long-term monthly precipitation dataset for Canada, which is then used to assess Canadian historical precipitation trends. The work is important because it developed a comprehensive algorithm for homogenization of precipitation data, and the results provide better representation of precipitation climate and more robust estimates of precipitation trends. It also identified the causes for large biases in the published estimates of precipitation trends over Canada.
Abstract
Summer rainfall trends in southeastern South America (SE-SA) have received attention in recent decades because of their importance for climate impacts. More than one driving mechanism has been identified for the trends, some of which have opposing effects. It is still not clear how much each mechanism has contributed to the observed trends or how their combined influence will affect future changes. Here, we address the second question and study how the CMIP6 summer SE-SA rainfall response to greenhouse warming can be explained by mechanisms related to large-scale extratropical circulation responses in the Southern Hemisphere to remote drivers (RDs) of regional climate change. We find that the regional uncertainty is well represented by combining the influence of four RDs: tropical upper-tropospheric amplification of surface warming, the delay in the stratospheric polar vortex breakdown date, and two RDs characterizing recognized tropical Pacific SST warming patterns. Applying a storyline framework, we identify the combination of RD responses that lead to the most extreme drying and wetting scenarios. Although most scenarios involve wetting, SE-SA drying can result if high upper-tropospheric tropical warming and early stratospheric polar vortex breakdown conditions are combined with low central and eastern Pacific warming. We also show how the definition of the SE-SA regional box can impact the results since the spatial patterns characterizing the dynamical influences are complex and the rainfall changes can be averaged out if these are not considered when aggregating. This article’s perspective and the associated methodology are applicable to other regions of the globe.
Significance Statement
Summer rainfall in southeastern South America (SE-SA) affects an area where around 200 million people live. The observed trends suggest long-term wetting, and most climate models predict a wetting response to greenhouse warming. However, in this work, we find that there is a physically plausible combination of large-scale circulation changes that can promote drying, which means SE-SA drying is a possibility that cannot be ignored. We also show that the definition of the SE-SA regional box can impact regional rainfall analysis since the spatial patterns characterizing the dynamical influences are complex and the changes can be averaged out if these are not considered when aggregating. This perspective and the associated methodology are applicable to other regions of the globe.
Abstract
Summer rainfall trends in southeastern South America (SE-SA) have received attention in recent decades because of their importance for climate impacts. More than one driving mechanism has been identified for the trends, some of which have opposing effects. It is still not clear how much each mechanism has contributed to the observed trends or how their combined influence will affect future changes. Here, we address the second question and study how the CMIP6 summer SE-SA rainfall response to greenhouse warming can be explained by mechanisms related to large-scale extratropical circulation responses in the Southern Hemisphere to remote drivers (RDs) of regional climate change. We find that the regional uncertainty is well represented by combining the influence of four RDs: tropical upper-tropospheric amplification of surface warming, the delay in the stratospheric polar vortex breakdown date, and two RDs characterizing recognized tropical Pacific SST warming patterns. Applying a storyline framework, we identify the combination of RD responses that lead to the most extreme drying and wetting scenarios. Although most scenarios involve wetting, SE-SA drying can result if high upper-tropospheric tropical warming and early stratospheric polar vortex breakdown conditions are combined with low central and eastern Pacific warming. We also show how the definition of the SE-SA regional box can impact the results since the spatial patterns characterizing the dynamical influences are complex and the rainfall changes can be averaged out if these are not considered when aggregating. This article’s perspective and the associated methodology are applicable to other regions of the globe.
Significance Statement
Summer rainfall in southeastern South America (SE-SA) affects an area where around 200 million people live. The observed trends suggest long-term wetting, and most climate models predict a wetting response to greenhouse warming. However, in this work, we find that there is a physically plausible combination of large-scale circulation changes that can promote drying, which means SE-SA drying is a possibility that cannot be ignored. We also show that the definition of the SE-SA regional box can impact regional rainfall analysis since the spatial patterns characterizing the dynamical influences are complex and the changes can be averaged out if these are not considered when aggregating. This perspective and the associated methodology are applicable to other regions of the globe.
Abstract
Tropical Pacific quasi-decadal (TPQD) climate variability is characterized by quasi-decadal sea surface temperature (SST) variations in the central Pacific (CP). This low-frequency climate variability is suggested to influence extreme regional weather and substantially impact global climate patterns and associated socioeconomics through teleconnections. Previous studies mostly attributed the TPQD climate variability to basin-scale air–sea coupling processes. However, due to the coarse resolution of the majority of the observations and climate models, the role of subbasin-scale processes in modulating the TPQD climate variability is still unclear. Using a long-term high-resolution global climate model, we find that energetic small-scale motions with horizontal scales from tens to hundreds of kilometers (loosely referred to as equatorial submesoscale eddies) act as an important damping effect to retard the TPQD variability. During the positive TPQD events, compound increasing precipitation and warming SST in the equatorial Pacific intensifies the upper ocean stratification and weakens the temperature fronts along the Pacific cold tongue. This suppresses submesoscale eddy growth as well as their associated upward vertical heat transport by inhibiting baroclinic instability (BCI) and frontogenesis; conversely, during the negative TPQD events, the opposite is true. Using a series of coupled global climate models that participated in phase 6 of the Coupled Model Intercomparison Project with different oceanic resolutions, we show that the amplitude of the TPQD variability becomes smaller as the oceanic resolution becomes finer, providing evidence for the impacts of submesoscale eddies on damping the TPQD variability. Our study suggests that explicitly simulating equatorial submesoscale eddies is necessary for gaining a more robust understanding of low-frequency tropical climate variability.
Significance Statement
Submesoscale ocean eddies inhibit the development of quasi-decadal climate variability in the equatorial central Pacific, according to a high-resolution global climate simulation.
Abstract
Tropical Pacific quasi-decadal (TPQD) climate variability is characterized by quasi-decadal sea surface temperature (SST) variations in the central Pacific (CP). This low-frequency climate variability is suggested to influence extreme regional weather and substantially impact global climate patterns and associated socioeconomics through teleconnections. Previous studies mostly attributed the TPQD climate variability to basin-scale air–sea coupling processes. However, due to the coarse resolution of the majority of the observations and climate models, the role of subbasin-scale processes in modulating the TPQD climate variability is still unclear. Using a long-term high-resolution global climate model, we find that energetic small-scale motions with horizontal scales from tens to hundreds of kilometers (loosely referred to as equatorial submesoscale eddies) act as an important damping effect to retard the TPQD variability. During the positive TPQD events, compound increasing precipitation and warming SST in the equatorial Pacific intensifies the upper ocean stratification and weakens the temperature fronts along the Pacific cold tongue. This suppresses submesoscale eddy growth as well as their associated upward vertical heat transport by inhibiting baroclinic instability (BCI) and frontogenesis; conversely, during the negative TPQD events, the opposite is true. Using a series of coupled global climate models that participated in phase 6 of the Coupled Model Intercomparison Project with different oceanic resolutions, we show that the amplitude of the TPQD variability becomes smaller as the oceanic resolution becomes finer, providing evidence for the impacts of submesoscale eddies on damping the TPQD variability. Our study suggests that explicitly simulating equatorial submesoscale eddies is necessary for gaining a more robust understanding of low-frequency tropical climate variability.
Significance Statement
Submesoscale ocean eddies inhibit the development of quasi-decadal climate variability in the equatorial central Pacific, according to a high-resolution global climate simulation.
Abstract
The Global Precipitation Climatology Project (GPCP) Version 3.2 Precipitation Analysis provides globally complete analyses of surface precipitation on a 0.5° × 0.5° latitude–longitude grid at both monthly and daily time scales, covering from 1983 to the present and from June 2000 to the present, respectively. These merged products continue the GPCP heritage of incorporating precipitation estimates from low-orbit satellite microwave data, geosynchronous-orbit satellite infrared data, sounder-based estimates, and surface rain gauge observations emphasizing the strengths of various inputs and striving for time and space homogeneity. Furthermore, these analyses incorporate modern algorithms, refined intercalibrations among sensors, climatologies of recent high-quality satellite precipitation data, and fine-scale multisatellite estimates. New data fields have been introduced to better characterize the precipitation, including the fraction of the precipitation that is liquid (rain) in both the monthly and daily products, and a quality index for the monthly product. Compared to the operational GPCP Version 2.3 Monthly, the Version 3.2 Monthly product provides a more reasonable climatology in the Southern Ocean and increases the estimated global average precipitation by about 4.5%, which is similar to estimates from recent global water budget assessments. Global and regional trends for 1983–2020 with this new Monthly dataset are very similar to those computed from Version 2.3. Compared to the operational One-Degree Daily (Version 1.3) product, the new Version 3.2 Daily is designed to better represent the histogram of precipitation rates, particularly at high values and shifts the start of less-certain high-latitude estimates from 40° to 58° latitude in each hemisphere.
Significance Statement
Studies of Earth’s climate require long-term global datasets based on observations to show how the climate functions and to validate numerical climate models. This study describes an important upgrade to the monthly and daily precipitation (rain and snow) products computed by the Global Precipitation Climatology Project. We use modern analysis schemes, add new sources of data, and deliver results on a finer-scale 0.5° × 0.5° latitude–longitude grid [roughly 55 km (34 mi) on a side at the equator]. The new data show improved agreement with other studies and depict more reasonable behavior in the Southern Ocean. The daily product shows improved estimates of how often different intensities of precipitation occur around the world, particularly the high amounts that drive floods and landslides.
Abstract
The Global Precipitation Climatology Project (GPCP) Version 3.2 Precipitation Analysis provides globally complete analyses of surface precipitation on a 0.5° × 0.5° latitude–longitude grid at both monthly and daily time scales, covering from 1983 to the present and from June 2000 to the present, respectively. These merged products continue the GPCP heritage of incorporating precipitation estimates from low-orbit satellite microwave data, geosynchronous-orbit satellite infrared data, sounder-based estimates, and surface rain gauge observations emphasizing the strengths of various inputs and striving for time and space homogeneity. Furthermore, these analyses incorporate modern algorithms, refined intercalibrations among sensors, climatologies of recent high-quality satellite precipitation data, and fine-scale multisatellite estimates. New data fields have been introduced to better characterize the precipitation, including the fraction of the precipitation that is liquid (rain) in both the monthly and daily products, and a quality index for the monthly product. Compared to the operational GPCP Version 2.3 Monthly, the Version 3.2 Monthly product provides a more reasonable climatology in the Southern Ocean and increases the estimated global average precipitation by about 4.5%, which is similar to estimates from recent global water budget assessments. Global and regional trends for 1983–2020 with this new Monthly dataset are very similar to those computed from Version 2.3. Compared to the operational One-Degree Daily (Version 1.3) product, the new Version 3.2 Daily is designed to better represent the histogram of precipitation rates, particularly at high values and shifts the start of less-certain high-latitude estimates from 40° to 58° latitude in each hemisphere.
Significance Statement
Studies of Earth’s climate require long-term global datasets based on observations to show how the climate functions and to validate numerical climate models. This study describes an important upgrade to the monthly and daily precipitation (rain and snow) products computed by the Global Precipitation Climatology Project. We use modern analysis schemes, add new sources of data, and deliver results on a finer-scale 0.5° × 0.5° latitude–longitude grid [roughly 55 km (34 mi) on a side at the equator]. The new data show improved agreement with other studies and depict more reasonable behavior in the Southern Ocean. The daily product shows improved estimates of how often different intensities of precipitation occur around the world, particularly the high amounts that drive floods and landslides.
Abstract
Physically based observational constraint methods can effectively reduce uncertainty in global warming projections but have not been widely applied at regional scales. We first develop and apply multivariate linear regression models for constraining projections of surface air temperature averaged over subcontinental regions in the extratropical Northern Hemisphere, based on a set of potential constraints including climatological metrics derived from tropical and subtropical low-level cloud and global average past warming trend, as well as a set of regional climate metrics previously used in the literature. We evaluate the performance of the multivariate linear regression models based on cross-validated tests using output from phases 5 and 6 of the Coupled Model Intercomparison Projects (CMIP). We find that linear regression models using global-scale low-cloud metrics alone perform more robustly than linear regression models using the past global mean warming trend or regional climate metrics as constraints. These results, while favoring global constraints over the set of regional constraints considered, do not preclude the existence of even better regional constraints for particular regions. Through model-based cross-validation, the projections constrained using low-level cloud metrics exhibit more accurate best estimate projections, narrower uncertainty ranges, and more reliable uncertainty estimates in most Northern Hemisphere regions when compared with unconstrained projections. Application of the approach to climate projections based on both Shared Socioeconomic Pathway (SSP) 1-2.6 and SSP5-8.5 using observed low-cloud metrics results in considerably narrower 5%–95% uncertainty ranges of twenty-first-century warming over subcontinental Northern Hemisphere land regions compared to unconstrained projections.
Abstract
Physically based observational constraint methods can effectively reduce uncertainty in global warming projections but have not been widely applied at regional scales. We first develop and apply multivariate linear regression models for constraining projections of surface air temperature averaged over subcontinental regions in the extratropical Northern Hemisphere, based on a set of potential constraints including climatological metrics derived from tropical and subtropical low-level cloud and global average past warming trend, as well as a set of regional climate metrics previously used in the literature. We evaluate the performance of the multivariate linear regression models based on cross-validated tests using output from phases 5 and 6 of the Coupled Model Intercomparison Projects (CMIP). We find that linear regression models using global-scale low-cloud metrics alone perform more robustly than linear regression models using the past global mean warming trend or regional climate metrics as constraints. These results, while favoring global constraints over the set of regional constraints considered, do not preclude the existence of even better regional constraints for particular regions. Through model-based cross-validation, the projections constrained using low-level cloud metrics exhibit more accurate best estimate projections, narrower uncertainty ranges, and more reliable uncertainty estimates in most Northern Hemisphere regions when compared with unconstrained projections. Application of the approach to climate projections based on both Shared Socioeconomic Pathway (SSP) 1-2.6 and SSP5-8.5 using observed low-cloud metrics results in considerably narrower 5%–95% uncertainty ranges of twenty-first-century warming over subcontinental Northern Hemisphere land regions compared to unconstrained projections.
Abstract
Understanding climate variability from millennial to glacial–interglacial time scales remains challenging due to the complex and nonlinear feedbacks between ice, ocean, sediments, biosphere, and atmosphere. Complex climate models generally struggle to dynamically and comprehensively simulate such long time periods as a result of the large computational costs. Here, we therefore coupled a dynamical ice sheet model to the Bern3D Earth system model of intermediate complexity, which allows for simulating multiple glacial–interglacial cycles. The performance of the model is first validated against modern observations and its response to abrupt perturbations, such as atmospheric CO2 changes and North Atlantic freshwater hosing, is investigated. To further test the fully coupled model, the climate evolution over the entire last glacial cycle is explored in a transient simulation forced by variations in the orbital configuration and greenhouse gases and aerosols. The model simulates global mean surface temperature in fair agreement with reconstructions, exhibiting a gradual cooling trend since the last interglacial that is interrupted by two more rapid cooling events during the early Marine Isotope Stage (MIS) 4 and Last Glacial Maximum (LGM). Simulated Northern Hemispheric ice sheets show pronounced variability on orbital time scales, and ice volume more than doubles from MIS3 to the LGM in good agreement with recent sea level reconstructions. At the LGM, the Atlantic overturning has a strength of about 14 Sv (1 Sv ≡ 106 m3 s−1), which is a reduction by about one-quarter compared to the preindustrial. We thus demonstrate that the new coupled model is able to simulate large-scale aspects of glacial–interglacial cycles.
Abstract
Understanding climate variability from millennial to glacial–interglacial time scales remains challenging due to the complex and nonlinear feedbacks between ice, ocean, sediments, biosphere, and atmosphere. Complex climate models generally struggle to dynamically and comprehensively simulate such long time periods as a result of the large computational costs. Here, we therefore coupled a dynamical ice sheet model to the Bern3D Earth system model of intermediate complexity, which allows for simulating multiple glacial–interglacial cycles. The performance of the model is first validated against modern observations and its response to abrupt perturbations, such as atmospheric CO2 changes and North Atlantic freshwater hosing, is investigated. To further test the fully coupled model, the climate evolution over the entire last glacial cycle is explored in a transient simulation forced by variations in the orbital configuration and greenhouse gases and aerosols. The model simulates global mean surface temperature in fair agreement with reconstructions, exhibiting a gradual cooling trend since the last interglacial that is interrupted by two more rapid cooling events during the early Marine Isotope Stage (MIS) 4 and Last Glacial Maximum (LGM). Simulated Northern Hemispheric ice sheets show pronounced variability on orbital time scales, and ice volume more than doubles from MIS3 to the LGM in good agreement with recent sea level reconstructions. At the LGM, the Atlantic overturning has a strength of about 14 Sv (1 Sv ≡ 106 m3 s−1), which is a reduction by about one-quarter compared to the preindustrial. We thus demonstrate that the new coupled model is able to simulate large-scale aspects of glacial–interglacial cycles.
