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Abstract
The authors develop, evaluate, and apply SynthETC, a statistical–stochastic model of winter extratropical cyclones (ETCs) over eastern North America. SynthETC simulates the life cycle of ETCs from formation to termination, and it can be used to estimate the probability of extreme ETC events beyond the historical record. Two modes of climate variability are used as independent covariates: El Niño–Southern Oscillation (ENSO) Niño-3.4 index and the monthly North Atlantic Oscillation (NAO). SynthETC is used to estimate the annual occurrence rate over sites in eastern North America of intense ETC passage in different ENSO and NAO states. Positive NAO is associated with increased rates over the North Atlantic, while negative NAO is associated with decreased rates over the North Atlantic and increased rates over northern Quebec. Positive ENSO is associated with decreased rates over the North Atlantic, Ontario, and the Canadian maritime, while negative ENSO is associated with increased rates over those regions, as well as the Great Lakes region.
Abstract
The authors develop, evaluate, and apply SynthETC, a statistical–stochastic model of winter extratropical cyclones (ETCs) over eastern North America. SynthETC simulates the life cycle of ETCs from formation to termination, and it can be used to estimate the probability of extreme ETC events beyond the historical record. Two modes of climate variability are used as independent covariates: El Niño–Southern Oscillation (ENSO) Niño-3.4 index and the monthly North Atlantic Oscillation (NAO). SynthETC is used to estimate the annual occurrence rate over sites in eastern North America of intense ETC passage in different ENSO and NAO states. Positive NAO is associated with increased rates over the North Atlantic, while negative NAO is associated with decreased rates over the North Atlantic and increased rates over northern Quebec. Positive ENSO is associated with decreased rates over the North Atlantic, Ontario, and the Canadian maritime, while negative ENSO is associated with increased rates over those regions, as well as the Great Lakes region.
Abstract
This study examines the climatology and dynamics of atmospheric blocking, and the general circulation features that influence blocks in GFDL’s atmosphere-only (AM4) and coupled atmosphere–ocean (CM4) comprehensive models. We compare AM4 and CM4 with reanalysis, focusing on winter in the Northern Hemisphere. Both models generate the correct blocking climatology and planetary-scale signatures of the stationary wave. However, at regional scales some biases exist. In the eastern Pacific and over western North America, both models generate excessive blocking frequency and too strong of a stationary wave. In the Atlantic, the models generate too little blocking and a weakened stationary wave. A block-centered compositing analysis of block-onset dynamics reveals that the models 1) produce realistic patterns of high-frequency (1–6-day) eddy forcing and 2) capture the notable differences in the 500-hPa geopotential height field between Pacific and Atlantic blocking. However, the models fail to reproduce stronger wave activity flux convergence in the Atlantic compared to the Pacific. Overall, biases in the blocking climatology in terms of location, frequency, duration, and area are quite similar between AM4 and CM4 despite the models having large differences in sea surface temperatures and climatological zonal circulation. This could suggest that other factors could be more dominant in generating blocking biases for these GCMs.
Significance Statement
Atmospheric blocks are persistent high pressure systems that can lead to hazardous weather. Historically, climate models have had trouble capturing blocks, but recent changes in the models might lead to improvements. As such, the work herein investigates the spatial distribution, prevalence, duration, size, and dynamics of wintertime blocking in recent NOAA climate models. Overall, these models capture the long-term-average spatial pattern of blocking, and properly reproduce key dynamical features. However, the models produce too much blocking in the western United States, and too little over the northern Atlantic Ocean and Europe. These blocking biases are consistent with atmospheric stationary waves biases, but not jet stream bias. This downplays the role of jet biases in the models being responsible for blocking biases.
Abstract
This study examines the climatology and dynamics of atmospheric blocking, and the general circulation features that influence blocks in GFDL’s atmosphere-only (AM4) and coupled atmosphere–ocean (CM4) comprehensive models. We compare AM4 and CM4 with reanalysis, focusing on winter in the Northern Hemisphere. Both models generate the correct blocking climatology and planetary-scale signatures of the stationary wave. However, at regional scales some biases exist. In the eastern Pacific and over western North America, both models generate excessive blocking frequency and too strong of a stationary wave. In the Atlantic, the models generate too little blocking and a weakened stationary wave. A block-centered compositing analysis of block-onset dynamics reveals that the models 1) produce realistic patterns of high-frequency (1–6-day) eddy forcing and 2) capture the notable differences in the 500-hPa geopotential height field between Pacific and Atlantic blocking. However, the models fail to reproduce stronger wave activity flux convergence in the Atlantic compared to the Pacific. Overall, biases in the blocking climatology in terms of location, frequency, duration, and area are quite similar between AM4 and CM4 despite the models having large differences in sea surface temperatures and climatological zonal circulation. This could suggest that other factors could be more dominant in generating blocking biases for these GCMs.
Significance Statement
Atmospheric blocks are persistent high pressure systems that can lead to hazardous weather. Historically, climate models have had trouble capturing blocks, but recent changes in the models might lead to improvements. As such, the work herein investigates the spatial distribution, prevalence, duration, size, and dynamics of wintertime blocking in recent NOAA climate models. Overall, these models capture the long-term-average spatial pattern of blocking, and properly reproduce key dynamical features. However, the models produce too much blocking in the western United States, and too little over the northern Atlantic Ocean and Europe. These blocking biases are consistent with atmospheric stationary waves biases, but not jet stream bias. This downplays the role of jet biases in the models being responsible for blocking biases.
Abstract
The present study explores the ability of the Weather Research and Forecasting (WRF) Model to accurately reproduce the passage of extratropical cold fronts at the DOE ARM eastern North Atlantic (ENA) observation site on the Azores. An analysis of three case studies is performed in which the impact of the WRF domain size, position of the model boundary relative to the ENA site, grid spacing, and spectral nudging conditions are explored. The results from these case studies indicate that model biases in the timing and duration of cold front passages change with the distance between the model domain boundary and the ENA site. For these three cases, if the western model boundary is farther than 1500 km from the site, the front becomes too meridional and fails to reach the site, making 1000 or 1500 km the optimal distances. In contrast, integrations with small distances (e.g., 500 km) between the site and domain boundaries have inadequate spatial spinup (i.e., the domain is too small for the model to properly stabilize). For all three cases, regardless of domain size, the model has biases in its upper-level circulation that impact the position and timing of the front. However, this issue is most serious for 4000-km2 domains and larger. For these domains, prolonged spectral nudging can correct cold front biases. As such, this analysis provides a framework to optimize the WRF Model configuration necessary for a realistic hindcast of a cold front passage at a fixed location centered in a domain as large as computationally possible.
Abstract
The present study explores the ability of the Weather Research and Forecasting (WRF) Model to accurately reproduce the passage of extratropical cold fronts at the DOE ARM eastern North Atlantic (ENA) observation site on the Azores. An analysis of three case studies is performed in which the impact of the WRF domain size, position of the model boundary relative to the ENA site, grid spacing, and spectral nudging conditions are explored. The results from these case studies indicate that model biases in the timing and duration of cold front passages change with the distance between the model domain boundary and the ENA site. For these three cases, if the western model boundary is farther than 1500 km from the site, the front becomes too meridional and fails to reach the site, making 1000 or 1500 km the optimal distances. In contrast, integrations with small distances (e.g., 500 km) between the site and domain boundaries have inadequate spatial spinup (i.e., the domain is too small for the model to properly stabilize). For all three cases, regardless of domain size, the model has biases in its upper-level circulation that impact the position and timing of the front. However, this issue is most serious for 4000-km2 domains and larger. For these domains, prolonged spectral nudging can correct cold front biases. As such, this analysis provides a framework to optimize the WRF Model configuration necessary for a realistic hindcast of a cold front passage at a fixed location centered in a domain as large as computationally possible.
Abstract
The Gulf Stream region is a primary location for midlatitude storm cyclogenesis and growth. However, the influence of sea surface temperature (SST) on storms in the region is still under question, particularly after a storm has developed. Using the Weather Research and Forecasting (WRF) model, a storm that intensified as it transited northward across the Gulf Stream is simulated multiple times using different SST boundary conditions. These experiments test the storm response to changes in both the absolute value of the SST and the meridional SST gradient. Across the different simulations, the storm strength increases monotonically with the magnitude of the SST perturbations, even when the perturbations weaken the SST gradient. The storm response to the SST perturbations is driven by the latent heat release in the storm warm conveyor belt (WCB). During the late stages of development, the surface fluxes under the storm warm sector regulate the supply of heat and moisture to the WCB. This allows the surface fluxes to govern late-stage intensification and control the storm SST sensitivity. The storm warm front also responds to the SST perturbations; however, the response is independent of that of the storm central pressure. These modeling results suggest that the SST beneath the storm can have just as important a role as the SST gradients in local forcing of the storm.
Abstract
The Gulf Stream region is a primary location for midlatitude storm cyclogenesis and growth. However, the influence of sea surface temperature (SST) on storms in the region is still under question, particularly after a storm has developed. Using the Weather Research and Forecasting (WRF) model, a storm that intensified as it transited northward across the Gulf Stream is simulated multiple times using different SST boundary conditions. These experiments test the storm response to changes in both the absolute value of the SST and the meridional SST gradient. Across the different simulations, the storm strength increases monotonically with the magnitude of the SST perturbations, even when the perturbations weaken the SST gradient. The storm response to the SST perturbations is driven by the latent heat release in the storm warm conveyor belt (WCB). During the late stages of development, the surface fluxes under the storm warm sector regulate the supply of heat and moisture to the WCB. This allows the surface fluxes to govern late-stage intensification and control the storm SST sensitivity. The storm warm front also responds to the SST perturbations; however, the response is independent of that of the storm central pressure. These modeling results suggest that the SST beneath the storm can have just as important a role as the SST gradients in local forcing of the storm.
Abstract
Storm surge is a weather hazard that can generate dangerous flooding and is not fully understood in terms of timing and atmospheric forcing. Using observations along the northeastern United States, surge is sorted on the basis of duration and intensity to reveal distinct time-evolving behavior. Long-duration surge events slowly recede, whereas strong, short-duration events often involve negative surge in quick succession after the maximum. Using Lagrangian track information, the tropical and extratropical cyclones and atmospheric blocks that generate the surge events are identified. There is a linear correlation between surge duration and surge maximum, and the relationship is stronger for surge caused by extratropical cyclones as compared with those events caused by tropical cyclones. For the extremes based on duration, the shortest-duration strong surge events are caused by tropical cyclones, whereas the longest-duration events are most often caused by extratropical cyclones. At least one-half of long-duration surge events involve anomalously strong atmospheric blocking poleward of the cyclone, whereas strong, short-duration events are most often caused by cyclones in the absence of blocking. The dynamical influence of the blocks leads to slow-moving cyclones that take meandering paths. In contrast, for strong, short-duration events, cyclones travel faster and take a more meridional path. These unique dynamical scenarios provide better insight for interpreting the threat of surge in medium-range forecasts.
Abstract
Storm surge is a weather hazard that can generate dangerous flooding and is not fully understood in terms of timing and atmospheric forcing. Using observations along the northeastern United States, surge is sorted on the basis of duration and intensity to reveal distinct time-evolving behavior. Long-duration surge events slowly recede, whereas strong, short-duration events often involve negative surge in quick succession after the maximum. Using Lagrangian track information, the tropical and extratropical cyclones and atmospheric blocks that generate the surge events are identified. There is a linear correlation between surge duration and surge maximum, and the relationship is stronger for surge caused by extratropical cyclones as compared with those events caused by tropical cyclones. For the extremes based on duration, the shortest-duration strong surge events are caused by tropical cyclones, whereas the longest-duration events are most often caused by extratropical cyclones. At least one-half of long-duration surge events involve anomalously strong atmospheric blocking poleward of the cyclone, whereas strong, short-duration events are most often caused by cyclones in the absence of blocking. The dynamical influence of the blocks leads to slow-moving cyclones that take meandering paths. In contrast, for strong, short-duration events, cyclones travel faster and take a more meridional path. These unique dynamical scenarios provide better insight for interpreting the threat of surge in medium-range forecasts.
Abstract
Using cyclone-centered compositing and a database of extratropical-cyclone locations, the distribution of precipitation frequency and rate in oceanic extratropical cyclones is analyzed using satellite-derived datasets. The distribution of precipitation rates retrieved using two new datasets, the Global Precipitation Measurement radar–microwave radiometer combined product (GPM-CMB) and the Integrated Multisatellite Retrievals for GPM product (IMERG), is compared with CloudSat, and the differences are discussed. For reference, the composites of AMSR-E, GPCP, and two reanalyses are also examined. Cyclone-centered precipitation rates are found to be the largest with the IMERG and CloudSat datasets and lowest with GPM-CMB. A series of tests is conducted to determine the roles of swath width, swath location, sampling frequency, season, and epoch. In all cases, these effects are less than ~0.14 mm h−1 at 50-km resolution. Larger differences in the composites are related to retrieval biases, such as ground-clutter contamination in GPM-CMB and radar saturation in CloudSat. Overall the IMERG product reports precipitation more often, with larger precipitation rates at the center of the cyclones, in conditions of high precipitable water (PW). The CloudSat product tends to report more precipitation in conditions of dry or moderate PW. The GPM-CMB product tends to systematically report lower precipitation rates than the other two datasets. This intercomparison provides 1) modelers with an observational uncertainty and range (0.21–0.36 mm h−1 near the cyclone centers) when using composites of precipitation for model evaluation and 2) retrieval-algorithm developers with a categorical analysis of the sensitivity of the products to PW.
Abstract
Using cyclone-centered compositing and a database of extratropical-cyclone locations, the distribution of precipitation frequency and rate in oceanic extratropical cyclones is analyzed using satellite-derived datasets. The distribution of precipitation rates retrieved using two new datasets, the Global Precipitation Measurement radar–microwave radiometer combined product (GPM-CMB) and the Integrated Multisatellite Retrievals for GPM product (IMERG), is compared with CloudSat, and the differences are discussed. For reference, the composites of AMSR-E, GPCP, and two reanalyses are also examined. Cyclone-centered precipitation rates are found to be the largest with the IMERG and CloudSat datasets and lowest with GPM-CMB. A series of tests is conducted to determine the roles of swath width, swath location, sampling frequency, season, and epoch. In all cases, these effects are less than ~0.14 mm h−1 at 50-km resolution. Larger differences in the composites are related to retrieval biases, such as ground-clutter contamination in GPM-CMB and radar saturation in CloudSat. Overall the IMERG product reports precipitation more often, with larger precipitation rates at the center of the cyclones, in conditions of high precipitable water (PW). The CloudSat product tends to report more precipitation in conditions of dry or moderate PW. The GPM-CMB product tends to systematically report lower precipitation rates than the other two datasets. This intercomparison provides 1) modelers with an observational uncertainty and range (0.21–0.36 mm h−1 near the cyclone centers) when using composites of precipitation for model evaluation and 2) retrieval-algorithm developers with a categorical analysis of the sensitivity of the products to PW.
Abstract
Using NASA Aqua MODIS and AIRS data, the relationship between low-level cloud cover (cloud top below the 700-hPa level) and boundary layer stability is explored in post-cold-frontal conditions. A linear relationship is found between seasonal cloud cover and two separate measures of inversion strength, the lower-tropospheric stability (LTS) and the estimated inversion strength (EIS), for two specific regions in the North Atlantic and Pacific in quiescent and weakly subsiding conditions. The relationship barely changes when considering dynamically active and subsiding post-cold-frontal conditions for the same regions. To explore the generality of this result and increase sample size, cold-front-centered composites of cloud cover and stability are constructed. The Northern and Southern Hemisphere seasonal cloud cover and stability distributions in the post-cold-frontal regions are then compared. A fairly good correlation between cloud cover and EIS is found in both hemispheres across all seasons, suggesting that a linear relationship between cloud cover and inversion strength proposed for quiescent conditions exists also in more dynamically active subsiding post-cold-frontal conditions. However, for a given season and hemisphere, the correlation between cloud cover and EIS degrades in post-cold-frontal regions, especially in the Northern Hemisphere. At these scales, other large-scale factors tend to correlate better with cloud cover.
Abstract
Using NASA Aqua MODIS and AIRS data, the relationship between low-level cloud cover (cloud top below the 700-hPa level) and boundary layer stability is explored in post-cold-frontal conditions. A linear relationship is found between seasonal cloud cover and two separate measures of inversion strength, the lower-tropospheric stability (LTS) and the estimated inversion strength (EIS), for two specific regions in the North Atlantic and Pacific in quiescent and weakly subsiding conditions. The relationship barely changes when considering dynamically active and subsiding post-cold-frontal conditions for the same regions. To explore the generality of this result and increase sample size, cold-front-centered composites of cloud cover and stability are constructed. The Northern and Southern Hemisphere seasonal cloud cover and stability distributions in the post-cold-frontal regions are then compared. A fairly good correlation between cloud cover and EIS is found in both hemispheres across all seasons, suggesting that a linear relationship between cloud cover and inversion strength proposed for quiescent conditions exists also in more dynamically active subsiding post-cold-frontal conditions. However, for a given season and hemisphere, the correlation between cloud cover and EIS degrades in post-cold-frontal regions, especially in the Northern Hemisphere. At these scales, other large-scale factors tend to correlate better with cloud cover.
Abstract
The representation of extratropical cyclone (ETC) precipitation in general circulation models (GCMs) and the Weather Research and Forecasting (WRF) Model is analyzed. This work considers the link between ETC precipitation and dynamical strength and tests if parameterized convection affects this link for ETCs in the North Atlantic basin. Lagrangian cyclone tracks of ETCs in ERA-Interim (ERAI), GISS and GFDL CMIP5 models, and WRF with two horizontal resolutions are utilized in a compositing analysis. The 20-km-resolution WRF Model generates stronger ETCs based on surface wind speed and cyclone precipitation. The GCMs and ERAI generate similar composite means and distributions for cyclone precipitation rates, but GCMs generate weaker cyclone surface winds than ERAI. The amount of cyclone precipitation generated by the convection scheme differs significantly across the datasets, with the GISS model generating the most, followed by ERAI and then the GFDL model. The models and reanalysis generate relatively more parameterized convective precipitation when the total cyclone-averaged precipitation is smaller. This is partially due to the contribution of parameterized convective precipitation occurring more often late in the ETC’s life cycle. For reanalysis and models, precipitation increases with both cyclone moisture and surface wind speed, and this is true if the contribution from the parameterized convection scheme is larger or not. This work shows that these different models generate similar total ETC precipitation despite large differences in the parameterized convection, and these differences do not cause unexpected behavior in ETC precipitation sensitivity to cyclone moisture or surface wind speed.
Abstract
The representation of extratropical cyclone (ETC) precipitation in general circulation models (GCMs) and the Weather Research and Forecasting (WRF) Model is analyzed. This work considers the link between ETC precipitation and dynamical strength and tests if parameterized convection affects this link for ETCs in the North Atlantic basin. Lagrangian cyclone tracks of ETCs in ERA-Interim (ERAI), GISS and GFDL CMIP5 models, and WRF with two horizontal resolutions are utilized in a compositing analysis. The 20-km-resolution WRF Model generates stronger ETCs based on surface wind speed and cyclone precipitation. The GCMs and ERAI generate similar composite means and distributions for cyclone precipitation rates, but GCMs generate weaker cyclone surface winds than ERAI. The amount of cyclone precipitation generated by the convection scheme differs significantly across the datasets, with the GISS model generating the most, followed by ERAI and then the GFDL model. The models and reanalysis generate relatively more parameterized convective precipitation when the total cyclone-averaged precipitation is smaller. This is partially due to the contribution of parameterized convective precipitation occurring more often late in the ETC’s life cycle. For reanalysis and models, precipitation increases with both cyclone moisture and surface wind speed, and this is true if the contribution from the parameterized convection scheme is larger or not. This work shows that these different models generate similar total ETC precipitation despite large differences in the parameterized convection, and these differences do not cause unexpected behavior in ETC precipitation sensitivity to cyclone moisture or surface wind speed.
Abstract
This study analyzes characteristics of clouds and vertical motion across extratropical cyclone warm fronts in the NASA Goddard Institute for Space Studies general circulation model. The validity of the modeled clouds is assessed using a combination of satellite observations from CloudSat, Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO), Advanced Microwave Scanning Radiometer for Earth Observing System (AMSR-E), and the NASA Modern-Era Retrospective Analysis for Research and Applications (MERRA) reanalysis. The analysis focuses on developing cyclones, to test the model's ability to generate their initial structure. To begin, the extratropical cyclones and their warm fronts are objectively identified and cyclone-local fields are mapped into a vertical transect centered on the surface warm front. To further isolate specific physics, the cyclones are separated using conditional subsetting based on additional cyclone-local variables, and the differences between the subset means are analyzed. Conditional subsets are created based on 1) the transect clouds and 2) vertical motion; 3) the strength of the temperature gradient along the warm front, as well as the storm-local 4) wind speed and 5) precipitable water (PW). The analysis shows that the model does not generate enough frontal cloud, especially at low altitude. The subsetting results reveal that, compared to the observations, the model exhibits a decoupling between cloud formation at high and low altitudes across warm fronts and a weak sensitivity to moisture. These issues are caused in part by the parameterized convection and assumptions in the stratiform cloud scheme that are valid in the subtropics. On the other hand, the model generates proper covariability of low-altitude vertical motion and cloud at the warm front and a joint dependence of cloudiness on wind and PW.
Abstract
This study analyzes characteristics of clouds and vertical motion across extratropical cyclone warm fronts in the NASA Goddard Institute for Space Studies general circulation model. The validity of the modeled clouds is assessed using a combination of satellite observations from CloudSat, Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO), Advanced Microwave Scanning Radiometer for Earth Observing System (AMSR-E), and the NASA Modern-Era Retrospective Analysis for Research and Applications (MERRA) reanalysis. The analysis focuses on developing cyclones, to test the model's ability to generate their initial structure. To begin, the extratropical cyclones and their warm fronts are objectively identified and cyclone-local fields are mapped into a vertical transect centered on the surface warm front. To further isolate specific physics, the cyclones are separated using conditional subsetting based on additional cyclone-local variables, and the differences between the subset means are analyzed. Conditional subsets are created based on 1) the transect clouds and 2) vertical motion; 3) the strength of the temperature gradient along the warm front, as well as the storm-local 4) wind speed and 5) precipitable water (PW). The analysis shows that the model does not generate enough frontal cloud, especially at low altitude. The subsetting results reveal that, compared to the observations, the model exhibits a decoupling between cloud formation at high and low altitudes across warm fronts and a weak sensitivity to moisture. These issues are caused in part by the parameterized convection and assumptions in the stratiform cloud scheme that are valid in the subtropics. On the other hand, the model generates proper covariability of low-altitude vertical motion and cloud at the warm front and a joint dependence of cloudiness on wind and PW.
Abstract
The Southern Ocean cloud cover modeled by the Interim ECMWF Re-Analysis (ERA-Interim) and Modern-Era Retrospective Analysis for Research and Applications (MERRA) reanalyses are compared against Moderate Resolution Imaging Spectroradiometer (MODIS) and Multiangle Imaging Spectroradiometer (MISR) observations. ERA-Interim monthly mean cloud amounts match the observations within 5%, while MERRA significantly underestimates the cloud amount. For a compositing analysis of clouds in warm season extratropical cyclones, both reanalyses show a low bias in cloud cover. They display a larger bias to the west of the cyclones in the region of subsidence behind the cold fronts. This low bias is larger for MERRA than for ERA-Interim. Both MODIS and MISR retrievals indicate that the clouds in this sector are at a low altitude, often composed of liquid, and of a broken nature. The combined CloudSat–Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) cloud profiles confirm these passive observations, but they also reveal that low-level clouds in other parts of the cyclones are also not properly represented in the reanalyses. The two reanalyses are in fairly good agreement for the dynamic and thermodynamic characteristics of the cyclones, suggesting that the cloud, convection, or boundary layer schemes are the problem instead. An examination of the lower-tropospheric stability distribution in the cyclones from both reanalyses suggests that the parameterization of shallow cumulus clouds may contribute in a large part to the problem. However, the differences in the cloud schemes and in particular in the precipitation processes, which may also contribute, cannot be excluded.
Abstract
The Southern Ocean cloud cover modeled by the Interim ECMWF Re-Analysis (ERA-Interim) and Modern-Era Retrospective Analysis for Research and Applications (MERRA) reanalyses are compared against Moderate Resolution Imaging Spectroradiometer (MODIS) and Multiangle Imaging Spectroradiometer (MISR) observations. ERA-Interim monthly mean cloud amounts match the observations within 5%, while MERRA significantly underestimates the cloud amount. For a compositing analysis of clouds in warm season extratropical cyclones, both reanalyses show a low bias in cloud cover. They display a larger bias to the west of the cyclones in the region of subsidence behind the cold fronts. This low bias is larger for MERRA than for ERA-Interim. Both MODIS and MISR retrievals indicate that the clouds in this sector are at a low altitude, often composed of liquid, and of a broken nature. The combined CloudSat–Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) cloud profiles confirm these passive observations, but they also reveal that low-level clouds in other parts of the cyclones are also not properly represented in the reanalyses. The two reanalyses are in fairly good agreement for the dynamic and thermodynamic characteristics of the cyclones, suggesting that the cloud, convection, or boundary layer schemes are the problem instead. An examination of the lower-tropospheric stability distribution in the cyclones from both reanalyses suggests that the parameterization of shallow cumulus clouds may contribute in a large part to the problem. However, the differences in the cloud schemes and in particular in the precipitation processes, which may also contribute, cannot be excluded.
