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Abstract
The Indian Ocean Observing System (IndOOS), established in 2006, is a multinational network of sustained oceanic measurements that underpin understanding and forecasting of weather and climate for the Indian Ocean region and beyond. Almost one-third of humanity lives around the Indian Ocean, many in countries dependent on fisheries and rain-fed agriculture that are vulnerable to climate variability and extremes. The Indian Ocean alone has absorbed a quarter of the global oceanic heat uptake over the last two decades and the fate of this heat and its impact on future change is unknown. Climate models project accelerating sea level rise, more frequent extremes in monsoon rainfall, and decreasing oceanic productivity. In view of these new scientific challenges, a 3-yr international review of the IndOOS by more than 60 scientific experts now highlights the need for an enhanced observing network that can better meet societal challenges, and provide more reliable forecasts. Here we present core findings from this review, including the need for 1) chemical, biological, and ecosystem measurements alongside physical parameters; 2) expansion into the western tropics to improve understanding of the monsoon circulation; 3) better-resolved upper ocean processes to improve understanding of air–sea coupling and yield better subseasonal to seasonal predictions; and 4) expansion into key coastal regions and the deep ocean to better constrain the basinwide energy budget. These goals will require new agreements and partnerships with and among Indian Ocean rim countries, creating opportunities for them to enhance their monitoring and forecasting capacity as part of IndOOS-2.
Abstract
The Indian Ocean Observing System (IndOOS), established in 2006, is a multinational network of sustained oceanic measurements that underpin understanding and forecasting of weather and climate for the Indian Ocean region and beyond. Almost one-third of humanity lives around the Indian Ocean, many in countries dependent on fisheries and rain-fed agriculture that are vulnerable to climate variability and extremes. The Indian Ocean alone has absorbed a quarter of the global oceanic heat uptake over the last two decades and the fate of this heat and its impact on future change is unknown. Climate models project accelerating sea level rise, more frequent extremes in monsoon rainfall, and decreasing oceanic productivity. In view of these new scientific challenges, a 3-yr international review of the IndOOS by more than 60 scientific experts now highlights the need for an enhanced observing network that can better meet societal challenges, and provide more reliable forecasts. Here we present core findings from this review, including the need for 1) chemical, biological, and ecosystem measurements alongside physical parameters; 2) expansion into the western tropics to improve understanding of the monsoon circulation; 3) better-resolved upper ocean processes to improve understanding of air–sea coupling and yield better subseasonal to seasonal predictions; and 4) expansion into key coastal regions and the deep ocean to better constrain the basinwide energy budget. These goals will require new agreements and partnerships with and among Indian Ocean rim countries, creating opportunities for them to enhance their monitoring and forecasting capacity as part of IndOOS-2.
Abstract
Pollutant emissions to the atmosphere commonly derive from nonpoint sources that are extended in space. Such sources may contain area, volume, line, or a combination of emission types. Currently, point measurements, often combined with models, are the primary means by which atmospheric emission rates are estimated from extended sources. Point measurement arrays often lack in spatial and temporal resolution and accuracy. In recent years, lidar has supplemented point measurements in agricultural research by sampling spatial ensembles nearly instantaneously. Here, a methodology using backscatter data from an elastic scanning lidar is presented to estimate emission rates from extended sources. To demonstrate the approach, a known amount of particulate matter was released upwind of a vegetative environmental buffer, a barrier designed to intercept emissions from animal production facilities. The emission rate was estimated downwind of the buffer, and the buffer capture efficiency (percentage of particles captured) was calculated. Efficiencies ranged from 21% to 74% and agree with the ranges previously published. A comprehensive uncertainty analysis of the lidar methodology was performed, revealing an uncertainty of 20% in the emission rate estimate; suggestions for significantly reducing this uncertainty in future studies are made. The methodology introduced here is demonstrated by estimating the efficiency of a vegetative buffer, but it can also be applied to any extended emission source for which point samples are inadequate, such as roads, animal feedlots, and cotton gin operations. It can also be applied to any pollutant for which a lidar system is configured, such as particulate matter, carbon dioxide, and ammonia.
Abstract
Pollutant emissions to the atmosphere commonly derive from nonpoint sources that are extended in space. Such sources may contain area, volume, line, or a combination of emission types. Currently, point measurements, often combined with models, are the primary means by which atmospheric emission rates are estimated from extended sources. Point measurement arrays often lack in spatial and temporal resolution and accuracy. In recent years, lidar has supplemented point measurements in agricultural research by sampling spatial ensembles nearly instantaneously. Here, a methodology using backscatter data from an elastic scanning lidar is presented to estimate emission rates from extended sources. To demonstrate the approach, a known amount of particulate matter was released upwind of a vegetative environmental buffer, a barrier designed to intercept emissions from animal production facilities. The emission rate was estimated downwind of the buffer, and the buffer capture efficiency (percentage of particles captured) was calculated. Efficiencies ranged from 21% to 74% and agree with the ranges previously published. A comprehensive uncertainty analysis of the lidar methodology was performed, revealing an uncertainty of 20% in the emission rate estimate; suggestions for significantly reducing this uncertainty in future studies are made. The methodology introduced here is demonstrated by estimating the efficiency of a vegetative buffer, but it can also be applied to any extended emission source for which point samples are inadequate, such as roads, animal feedlots, and cotton gin operations. It can also be applied to any pollutant for which a lidar system is configured, such as particulate matter, carbon dioxide, and ammonia.
Abstract
The Moderate Resolution Imaging Spectroradiometer (MODIS) aboard both NASA’s Terra and Aqua satellites is making near-global daily observations of the earth in a wide spectral range (0.41–15 μm). These measurements are used to derive spectral aerosol optical thickness and aerosol size parameters over both land and ocean. The aerosol products available over land include aerosol optical thickness at three visible wavelengths, a measure of the fraction of aerosol optical thickness attributed to the fine mode, and several derived parameters including reflected spectral solar flux at the top of the atmosphere. Over the ocean, the aerosol optical thickness is provided in seven wavelengths from 0.47 to 2.13 μm. In addition, quantitative aerosol size information includes effective radius of the aerosol and quantitative fraction of optical thickness attributed to the fine mode. Spectral irradiance contributed by the aerosol, mass concentration, and number of cloud condensation nuclei round out the list of available aerosol products over the ocean. The spectral optical thickness and effective radius of the aerosol over the ocean are validated by comparison with two years of Aerosol Robotic Network (AERONET) data gleaned from 132 AERONET stations. Eight thousand MODIS aerosol retrievals collocated with AERONET measurements confirm that one standard deviation of MODIS optical thickness retrievals fall within the predicted uncertainty of Δτ = ±0.03 ±0.05τ over ocean and Δτ = ±0.05 ± 0.15τ over land. Two hundred and seventy-one MODIS aerosol retrievals collocated with AERONET inversions at island and coastal sites suggest that one standard deviation of MODIS effective radius retrievals falls within Δr eff = ±0.11 μm. The accuracy of the MODIS retrievals suggests that the product can be used to help narrow the uncertainties associated with aerosol radiative forcing of global climate.
Abstract
The Moderate Resolution Imaging Spectroradiometer (MODIS) aboard both NASA’s Terra and Aqua satellites is making near-global daily observations of the earth in a wide spectral range (0.41–15 μm). These measurements are used to derive spectral aerosol optical thickness and aerosol size parameters over both land and ocean. The aerosol products available over land include aerosol optical thickness at three visible wavelengths, a measure of the fraction of aerosol optical thickness attributed to the fine mode, and several derived parameters including reflected spectral solar flux at the top of the atmosphere. Over the ocean, the aerosol optical thickness is provided in seven wavelengths from 0.47 to 2.13 μm. In addition, quantitative aerosol size information includes effective radius of the aerosol and quantitative fraction of optical thickness attributed to the fine mode. Spectral irradiance contributed by the aerosol, mass concentration, and number of cloud condensation nuclei round out the list of available aerosol products over the ocean. The spectral optical thickness and effective radius of the aerosol over the ocean are validated by comparison with two years of Aerosol Robotic Network (AERONET) data gleaned from 132 AERONET stations. Eight thousand MODIS aerosol retrievals collocated with AERONET measurements confirm that one standard deviation of MODIS optical thickness retrievals fall within the predicted uncertainty of Δτ = ±0.03 ±0.05τ over ocean and Δτ = ±0.05 ± 0.15τ over land. Two hundred and seventy-one MODIS aerosol retrievals collocated with AERONET inversions at island and coastal sites suggest that one standard deviation of MODIS effective radius retrievals falls within Δr eff = ±0.11 μm. The accuracy of the MODIS retrievals suggests that the product can be used to help narrow the uncertainties associated with aerosol radiative forcing of global climate.
The provision of weather forecasts for the London Olympic and Paralympic Games in 2012 offered the opportunity for the Met Office to accelerate the transition to operations of several advanced numerical modeling capabilities and to demonstrate their performance to external scientists. It was also an event that captured public interest, providing an opportunity to educate and build trust in the weather forecasting enterprise in the United Kingdom and beyond. The baseline NWP guidance for the duration of the Olympic Games came from three main configurations of the Met Office Unified Model: global 25-km deterministic, North Atlantic/Europe 18-km ensemble, and U.K. 1.5-km deterministic. The advanced capabilities demonstrated during the Olympic Games consisted of a rapid-update hourly cycle of a 1.5-km grid length configuration for the southern United Kingdom using four-dimensional variational data assimilation (4D-Var) and enhanced observations; a 2.2-km grid length U.K. ensemble; a 333-m grid length configuration of the Unified Model and 250-m configuration of the Simulating Waves Nearshore (SWAN) ocean wave model for Weymouth Bay; and a 12-km grid length configuration of Air Quality in the Unified Model with prognostic aerosols and chemistry. Despite their different levels of maturity, each of the new capabilities provided useful additional guidance to Met Office weather advisors, contributing to an outstanding service to the Olympic Games organizers and the public. The website provided layered access to information about the science and to selected real-time products, substantially raising the profile of Met Office weather forecasting research among the United Kingdom and overseas public.
The provision of weather forecasts for the London Olympic and Paralympic Games in 2012 offered the opportunity for the Met Office to accelerate the transition to operations of several advanced numerical modeling capabilities and to demonstrate their performance to external scientists. It was also an event that captured public interest, providing an opportunity to educate and build trust in the weather forecasting enterprise in the United Kingdom and beyond. The baseline NWP guidance for the duration of the Olympic Games came from three main configurations of the Met Office Unified Model: global 25-km deterministic, North Atlantic/Europe 18-km ensemble, and U.K. 1.5-km deterministic. The advanced capabilities demonstrated during the Olympic Games consisted of a rapid-update hourly cycle of a 1.5-km grid length configuration for the southern United Kingdom using four-dimensional variational data assimilation (4D-Var) and enhanced observations; a 2.2-km grid length U.K. ensemble; a 333-m grid length configuration of the Unified Model and 250-m configuration of the Simulating Waves Nearshore (SWAN) ocean wave model for Weymouth Bay; and a 12-km grid length configuration of Air Quality in the Unified Model with prognostic aerosols and chemistry. Despite their different levels of maturity, each of the new capabilities provided useful additional guidance to Met Office weather advisors, contributing to an outstanding service to the Olympic Games organizers and the public. The website provided layered access to information about the science and to selected real-time products, substantially raising the profile of Met Office weather forecasting research among the United Kingdom and overseas public.
To investigate the effects of the middle atmosphere on climate, the World Climate Research Programme is supporting the project “Stratospheric Processes and their Role in Climate” (SPARC). A central theme of SPARC, to examine model simulations of the coupled troposphere–middle atmosphere system, is being performed through the initiative called GRIPS (GCM-Reality Intercomparison Project for SPARC). In this paper, an overview of the objectives of GRIPS is given. Initial activities include an assessment of the performance of middle atmosphere climate models, and preliminary results from this evaluation are presented here. It is shown that although all 13 models evaluated represent most major features of the mean atmospheric state, there are deficiencies in the magnitude and location of the features, which cannot easily be traced to the formulation (resolution or the parameterizations included) of the models. Most models show a cold bias in all locations, apart from the tropical tropopause region where they can be either too warm or too cold. The strengths and locations of the major jets are often misrepresented in the models. Looking at three-dimensional fields reveals, for some models, more severe deficiencies in the magnitude and positioning of the dominant structures (such as the Aleutian high in the stratosphere), although undersampling might explain some of these differences from observations. All the models have shortcomings in their simulations of the present-day climate, which might limit the accuracy of predictions of the climate response to ozone change and other anomalous forcing.
To investigate the effects of the middle atmosphere on climate, the World Climate Research Programme is supporting the project “Stratospheric Processes and their Role in Climate” (SPARC). A central theme of SPARC, to examine model simulations of the coupled troposphere–middle atmosphere system, is being performed through the initiative called GRIPS (GCM-Reality Intercomparison Project for SPARC). In this paper, an overview of the objectives of GRIPS is given. Initial activities include an assessment of the performance of middle atmosphere climate models, and preliminary results from this evaluation are presented here. It is shown that although all 13 models evaluated represent most major features of the mean atmospheric state, there are deficiencies in the magnitude and location of the features, which cannot easily be traced to the formulation (resolution or the parameterizations included) of the models. Most models show a cold bias in all locations, apart from the tropical tropopause region where they can be either too warm or too cold. The strengths and locations of the major jets are often misrepresented in the models. Looking at three-dimensional fields reveals, for some models, more severe deficiencies in the magnitude and positioning of the dominant structures (such as the Aleutian high in the stratosphere), although undersampling might explain some of these differences from observations. All the models have shortcomings in their simulations of the present-day climate, which might limit the accuracy of predictions of the climate response to ozone change and other anomalous forcing.
In this article, the authors describe an innovative multimodel system developed within the Climate Change and Impact Research: The Mediterranean Environment (CIRCE) European Union (EU) Sixth Framework Programme (FP6) project and used to produce simulations of the Mediterranean Sea regional climate. The models include high-resolution Mediterranean Sea components, which allow assessment of the role of the basin and in particular of the air–sea feedbacks in the climate of the region.
The models have been integrated from 1951 to 2050, using observed radiative forcings during the first half of the simulation period and the Intergovernmental Panel on Climate Change (IPCC) Special Report on Emissions Scenarios (SRES) A1B scenario during the second half.
The projections show a substantial warming (about 1.5°–2°C) and a significant decrease of precipitation (about 5%) in the region for the scenario period. However, locally the changes might be even larger. In the same period, the projected surface net heat loss decreases, leading to a weaker cooling of the Mediterranean Sea by the atmosphere, whereas the water budget appears to increase, leading the basin to lose more water through its surface than in the past. Overall, these results are consistent with the findings of previous scenario simulations, such as the Prediction of Regional Scenarios and Uncertainties for Defining European Climate Change Risks and Effects (PRUDENCE), Ensemble-Based Predictions of Climate Changes and Their Impacts (ENSEMBLES), and phase 3 of the Coupled Model Intercomparison Project (CMIP3). The agreement suggests that these findings are robust to substantial changes in the configuration of the models used to make the simulations.
Finally, the models produce a 2021–50 mean steric sea level rise that ranges between +7 and +12 cm, with respect to the period of reference.
In this article, the authors describe an innovative multimodel system developed within the Climate Change and Impact Research: The Mediterranean Environment (CIRCE) European Union (EU) Sixth Framework Programme (FP6) project and used to produce simulations of the Mediterranean Sea regional climate. The models include high-resolution Mediterranean Sea components, which allow assessment of the role of the basin and in particular of the air–sea feedbacks in the climate of the region.
The models have been integrated from 1951 to 2050, using observed radiative forcings during the first half of the simulation period and the Intergovernmental Panel on Climate Change (IPCC) Special Report on Emissions Scenarios (SRES) A1B scenario during the second half.
The projections show a substantial warming (about 1.5°–2°C) and a significant decrease of precipitation (about 5%) in the region for the scenario period. However, locally the changes might be even larger. In the same period, the projected surface net heat loss decreases, leading to a weaker cooling of the Mediterranean Sea by the atmosphere, whereas the water budget appears to increase, leading the basin to lose more water through its surface than in the past. Overall, these results are consistent with the findings of previous scenario simulations, such as the Prediction of Regional Scenarios and Uncertainties for Defining European Climate Change Risks and Effects (PRUDENCE), Ensemble-Based Predictions of Climate Changes and Their Impacts (ENSEMBLES), and phase 3 of the Coupled Model Intercomparison Project (CMIP3). The agreement suggests that these findings are robust to substantial changes in the configuration of the models used to make the simulations.
Finally, the models produce a 2021–50 mean steric sea level rise that ranges between +7 and +12 cm, with respect to the period of reference.
Abstract
The chemical species emitted by forests create complex atmospheric oxidation chemistry and influence global atmospheric oxidation capacity and climate. The Southern Oxidant and Aerosol Study (SOAS) provided an opportunity to test the oxidation chemistry in a forest where isoprene is the dominant biogenic volatile organic compound. Hydroxyl (OH) and hydroperoxyl (HO2) radicals were two of the hundreds of atmospheric chemical species measured, as was OH reactivity (the inverse of the OH lifetime). OH was measured by laser-induced fluorescence (LIF) and by taking the difference in signals without and with an OH scavenger that was added just outside the instrument’s pinhole inlet. To test whether the chemistry at SOAS can be simulated by current model mechanisms, OH and HO2 were evaluated with a box model using two chemical mechanisms: Master Chemical Mechanism, version 3.2 (MCMv3.2), augmented with explicit isoprene chemistry and MCMv3.3.1. Measured and modeled OH peak at about 106 cm−3 and agree well within combined uncertainties. Measured and modeled HO2 peak at about 27 pptv and also agree well within combined uncertainties. Median OH reactivity cycled between about 11 s−1 at dawn and about 26 s−1 during midafternoon. A good test of the oxidation chemistry is the balance between OH production and loss rates using measurements; this balance was observed to within uncertainties. These SOAS results provide strong evidence that the current isoprene mechanisms are consistent with measured OH and HO2 and, thus, capture significant aspects of the atmospheric oxidation chemistry in this isoprene-rich forest.
Abstract
The chemical species emitted by forests create complex atmospheric oxidation chemistry and influence global atmospheric oxidation capacity and climate. The Southern Oxidant and Aerosol Study (SOAS) provided an opportunity to test the oxidation chemistry in a forest where isoprene is the dominant biogenic volatile organic compound. Hydroxyl (OH) and hydroperoxyl (HO2) radicals were two of the hundreds of atmospheric chemical species measured, as was OH reactivity (the inverse of the OH lifetime). OH was measured by laser-induced fluorescence (LIF) and by taking the difference in signals without and with an OH scavenger that was added just outside the instrument’s pinhole inlet. To test whether the chemistry at SOAS can be simulated by current model mechanisms, OH and HO2 were evaluated with a box model using two chemical mechanisms: Master Chemical Mechanism, version 3.2 (MCMv3.2), augmented with explicit isoprene chemistry and MCMv3.3.1. Measured and modeled OH peak at about 106 cm−3 and agree well within combined uncertainties. Measured and modeled HO2 peak at about 27 pptv and also agree well within combined uncertainties. Median OH reactivity cycled between about 11 s−1 at dawn and about 26 s−1 during midafternoon. A good test of the oxidation chemistry is the balance between OH production and loss rates using measurements; this balance was observed to within uncertainties. These SOAS results provide strong evidence that the current isoprene mechanisms are consistent with measured OH and HO2 and, thus, capture significant aspects of the atmospheric oxidation chemistry in this isoprene-rich forest.
Abstract
The Mediterranean is expected to be one of the most prominent and vulnerable climate change “hotspots” of the twenty-first century, and the physical mechanisms underlying this finding are still not clear. Furthermore, complex interactions and feedbacks involving ocean–atmosphere–land–biogeochemical processes play a prominent role in modulating the climate and environment of the Mediterranean region on a range of spatial and temporal scales. Therefore, it is critical to provide robust climate change information for use in vulnerability–impact–adaptation assessment studies considering the Mediterranean as a fully coupled environmental system. The Mediterranean Coordinated Regional Downscaling Experiment (Med-CORDEX) initiative aims at coordinating the Mediterranean climate modeling community toward the development of fully coupled regional climate simulations, improving all relevant components of the system from atmosphere and ocean dynamics to land surface, hydrology, and biogeochemical processes. The primary goals of Med-CORDEX are to improve understanding of past climate variability and trends and to provide more accurate and reliable future projections, assessing in a quantitative and robust way the added value of using high-resolution and coupled regional climate models. The coordination activities and the scientific outcomes of Med-CORDEX can produce an important framework to foster the development of regional Earth system models in several key regions worldwide.
Abstract
The Mediterranean is expected to be one of the most prominent and vulnerable climate change “hotspots” of the twenty-first century, and the physical mechanisms underlying this finding are still not clear. Furthermore, complex interactions and feedbacks involving ocean–atmosphere–land–biogeochemical processes play a prominent role in modulating the climate and environment of the Mediterranean region on a range of spatial and temporal scales. Therefore, it is critical to provide robust climate change information for use in vulnerability–impact–adaptation assessment studies considering the Mediterranean as a fully coupled environmental system. The Mediterranean Coordinated Regional Downscaling Experiment (Med-CORDEX) initiative aims at coordinating the Mediterranean climate modeling community toward the development of fully coupled regional climate simulations, improving all relevant components of the system from atmosphere and ocean dynamics to land surface, hydrology, and biogeochemical processes. The primary goals of Med-CORDEX are to improve understanding of past climate variability and trends and to provide more accurate and reliable future projections, assessing in a quantitative and robust way the added value of using high-resolution and coupled regional climate models. The coordination activities and the scientific outcomes of Med-CORDEX can produce an important framework to foster the development of regional Earth system models in several key regions worldwide.
Abstract
A model evaluation approach is proposed in which weather and climate prediction models are analyzed along a Pacific Ocean cross section, from the stratocumulus regions off the coast of California, across the shallow convection dominated trade winds, to the deep convection regions of the ITCZ—the Global Energy and Water Cycle Experiment Cloud System Study/Working Group on Numerical Experimentation (GCSS/WGNE) Pacific Cross-Section Intercomparison (GPCI). The main goal of GPCI is to evaluate and help understand and improve the representation of tropical and subtropical cloud processes in weather and climate prediction models. In this paper, a detailed analysis of cloud regime transitions along the cross section from the subtropics to the tropics for the season June–July–August of 1998 is presented. This GPCI study confirms many of the typical weather and climate prediction model problems in the representation of clouds: underestimation of clouds in the stratocumulus regime by most models with the corresponding consequences in terms of shortwave radiation biases; overestimation of clouds by the 40-yr ECMWF Re-Analysis (ERA-40) in the deep tropics (in particular) with the corresponding impact in the outgoing longwave radiation; large spread between the different models in terms of cloud cover, liquid water path and shortwave radiation; significant differences between the models in terms of vertical cross sections of cloud properties (in particular), vertical velocity, and relative humidity. An alternative analysis of cloud cover mean statistics is proposed where sharp gradients in cloud cover along the GPCI transect are taken into account. This analysis shows that the negative cloud bias of some models and ERA-40 in the stratocumulus regions [as compared to the first International Satellite Cloud Climatology Project (ISCCP)] is associated not only with lower values of cloud cover in these regimes, but also with a stratocumulus-to-cumulus transition that occurs too early along the trade wind Lagrangian trajectory. Histograms of cloud cover along the cross section differ significantly between models. Some models exhibit a quasi-bimodal structure with cloud cover being either very large (close to 100%) or very small, while other models show a more continuous transition. The ISCCP observations suggest that reality is in-between these two extreme examples. These different patterns reflect the diverse nature of the cloud, boundary layer, and convection parameterizations in the participating weather and climate prediction models.
Abstract
A model evaluation approach is proposed in which weather and climate prediction models are analyzed along a Pacific Ocean cross section, from the stratocumulus regions off the coast of California, across the shallow convection dominated trade winds, to the deep convection regions of the ITCZ—the Global Energy and Water Cycle Experiment Cloud System Study/Working Group on Numerical Experimentation (GCSS/WGNE) Pacific Cross-Section Intercomparison (GPCI). The main goal of GPCI is to evaluate and help understand and improve the representation of tropical and subtropical cloud processes in weather and climate prediction models. In this paper, a detailed analysis of cloud regime transitions along the cross section from the subtropics to the tropics for the season June–July–August of 1998 is presented. This GPCI study confirms many of the typical weather and climate prediction model problems in the representation of clouds: underestimation of clouds in the stratocumulus regime by most models with the corresponding consequences in terms of shortwave radiation biases; overestimation of clouds by the 40-yr ECMWF Re-Analysis (ERA-40) in the deep tropics (in particular) with the corresponding impact in the outgoing longwave radiation; large spread between the different models in terms of cloud cover, liquid water path and shortwave radiation; significant differences between the models in terms of vertical cross sections of cloud properties (in particular), vertical velocity, and relative humidity. An alternative analysis of cloud cover mean statistics is proposed where sharp gradients in cloud cover along the GPCI transect are taken into account. This analysis shows that the negative cloud bias of some models and ERA-40 in the stratocumulus regions [as compared to the first International Satellite Cloud Climatology Project (ISCCP)] is associated not only with lower values of cloud cover in these regimes, but also with a stratocumulus-to-cumulus transition that occurs too early along the trade wind Lagrangian trajectory. Histograms of cloud cover along the cross section differ significantly between models. Some models exhibit a quasi-bimodal structure with cloud cover being either very large (close to 100%) or very small, while other models show a more continuous transition. The ISCCP observations suggest that reality is in-between these two extreme examples. These different patterns reflect the diverse nature of the cloud, boundary layer, and convection parameterizations in the participating weather and climate prediction models.