Diagnosing the average spatio-temporal impact of convective systems – Part 2: A model intercomparison using satellite data

Abstract. The representation of the effect of tropical deep convective (DC) systems on upper-tropospheric moist processes and outgoing longwave radiation is evaluated in the EC-Earth3, ECHAM6, and CAM5 (Community Atmosphere Model) climate models using satellite-retrieved data. A composite technique is applied to thousands of deep convective systems that are identified using local rain rate maxima in order to focus on the temporal evolution of the deep convective processes in the model and satellite-retrieved data. The models tend to over-predict the occurrence of rain rates that are less than ≈ 3 mm h−1 compared to Tropical Rainfall Measurement Mission (TRMM) Multi-satellite Precipitation Analysis (TMPA). While the diurnal distribution of oceanic rain rate maxima in the models is similar to the satellite-retrieved data, the land-based maxima are out of phase. Despite having a larger climatological mean upper-tropospheric relative humidity, models closely capture the satellite-derived moistening of the upper troposphere following the peak rain rate in the deep convective systems. Simulated cloud fractions near the tropopause are larger than in the satellite data, but the ice water contents are smaller compared with the satellite-retrieved ice data. The models capture the evolution of ocean-based deep convective systems fairly well, but the land-based systems show significant discrepancies. Over land, the diurnal cycle of rain is too intense, with deep convective systems occurring at the same position on subsequent days, while the satellite-retrieved data vary more in timing and geographical location. Finally, simulated outgoing longwave radiation anomalies associated with deep convection are in reasonable agreement with the satellite data, as well as with each other. Given the fact that there are strong disagreements with, for example, cloud ice water content, and cloud fraction, between the models, this study supports the hypothesis that such agreement with satellite-retrieved data is achieved in the three models due to different representations of deep convection processes and compensating errors.

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Diagnosing the average spatio-temporal impact of convective systems – Part 2: A model inter-comparison using satellite data

Atmospheric Chemistry and Physics Discussions ◽

10.5194/acpd-14-9155-2014 ◽

2014 ◽

Vol 14 (7) ◽

pp. 9155-9201 ◽

Cited By ~ 1

Author(s):

M. S. Johnston ◽

S. Eliasson ◽

P. Eriksson ◽

R. M. Forbes ◽

A. Gettelman ◽

...

Keyword(s):

Diurnal Cycle ◽

Rain Rate ◽

Climate Models ◽

Deep Convection ◽

Geographical Location ◽

Longwave Radiation ◽

Convective Systems ◽

Deep Convective Systems ◽

Spatio Temporal ◽

Ice Water

Abstract. The representation of the effect of tropical deep convective (DC) systems on upper-tropospheric moist processes and outgoing longwave radiation (OLR) is evaluated in the climate models EC-Earth, ECHAM6, and CAM5 using satellite observations. A composite technique is applied to thousands of deep convective systems that are identified using local rain rate (RR) maxima in order to focus on the temporal evolution of the deep convective processes in the model and observations. The models tend to over-produce rain rates less than about 3 mm h−1 and underpredict the occurrence of more intense rain. While the diurnal distribution of oceanic rain rate maxima in the models is similar to the observations, the land-based maxima are out of phase. Over land, the diurnal cycle of rain is too intense, with DC events occurring at the same position on subsequent days, while the observations vary more in timing and geographical location. Despite having a larger climatological mean upper tropospheric relative humidity, models closely capture the observed moistening of the upper troposphere following the peak rain rate in the deep convective systems. A comparison of the evolution of vertical profiles of ice water content and cloud fraction shows significant differences between models and with the observations. Simulated cloud fractions near the tropopause are also larger than observed, but the corresponding ice water contents are smaller compared to the observations. EC-Earth's CF at pressure levels > 300 hPa are generally less than the obervations while the other models tend to have larger CF for similar altitudes. The models' performance for ocean-based systems seems to capture the evolution of DC systems fairly well, but the land-based systems show significant discrepancies. In particular, the models have a significantly stronger diurnal cycle at the same geo-spatial position. Finally, OLR anomalies associated with deep convection are in reasonable agreement with the observations. This study shows that such agreement with observations can be achieved in different ways in the three models due to different representations of deep convection processes and compensating errors.

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Diagnosing the average spatio-temporal impact of convective systems – Part 1: A methodology for evaluating climate models

Atmospheric Chemistry and Physics ◽

10.5194/acp-13-12043-2013 ◽

2013 ◽

Vol 13 (23) ◽

pp. 12043-12058 ◽

Cited By ~ 2

Author(s):

M. S. Johnston ◽

S. Eliasson ◽

P. Eriksson ◽

R. M. Forbes ◽

K. Wyser ◽

...

Keyword(s):

Water Content ◽

Outgoing Longwave Radiation ◽

Longwave Radiation ◽

Cloud Fraction ◽

Convective Systems ◽

Ice Water Content ◽

The Mean ◽

Spatio Temporal ◽

Cloud Ice ◽

Ice Water

Abstract. An earlier method to determine the mean response of upper-tropospheric water to localised deep convective systems (DC systems) is improved and applied to the EC-Earth climate model. Following Zelinka and Hartmann (2009), several fields related to moist processes and radiation from various satellites are composited with respect to the local maxima in rain rate to determine their spatio-temporal evolution with deep convection in the central Pacific Ocean. Major improvements to the earlier study are the isolation of DC systems in time so as to prevent multiple sampling of the same event, and a revised definition of the mean background state that allows for better characterisation of the DC-system-induced anomalies. The observed DC systems in this study propagate westward at ~4 m s−1. Both the upper-tropospheric relative humidity and the outgoing longwave radiation are substantially perturbed over a broad horizontal extent and for periods >30 h. The cloud fraction anomaly is fairly constant with height but small maximum can be seen around 200 hPa. The cloud ice water content anomaly is mostly confined to pressures greater than 150 hPa and reaches its maximum around 450 hPa, a few hours after the peak convection. Consistent with the large increase in upper-tropospheric cloud ice water content, albedo increases dramatically and persists about 30 h after peak convection. Applying the compositing technique to EC-Earth allows an assessment of the model representation of DC systems. The model captures the large-scale responses, most notably for outgoing longwave radiation, but there are a number of important differences. DC systems appear to propagate eastward in the model, suggesting a strong link to Kelvin waves instead of equatorial Rossby waves. The diurnal cycle in the model is more pronounced and appears to trigger new convection further to the west each time. Finally, the modelled ice water content anomaly peaks at pressures greater than 500 hPa and in the upper troposphere between 250 hPa and 500 hPa, there is less ice than the observations and it does not persist as long after peak convection. The modelled upper-tropospheric cloud fraction anomaly, however, is of a comparable magnitude and exhibits a similar longevity as the observations.

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Diagnosing the average spatio-temporal impact of convective systems – Part 1: A methodology for evaluating climate models

Atmospheric Chemistry and Physics Discussions ◽

10.5194/acpd-13-13653-2013 ◽

2013 ◽

Vol 13 (5) ◽

pp. 13653-13684

Author(s):

M. S. Johnston ◽

P. Eriksson ◽

S. Eliasson ◽

M. D. Zelinka ◽

R. M. Forbes ◽

...

Keyword(s):

Water Content ◽

Outgoing Longwave Radiation ◽

Deep Convection ◽

Longwave Radiation ◽

Cloud Fraction ◽

Ice Water Content ◽

The Mean ◽

Spatio Temporal ◽

Cloud Ice ◽

Ice Water

Abstract. A~method to determine the mean response of upper tropospheric water to localised deep convective (DC) events is improved and applied to the EC-Earth climate model. Following Zelinka and Hartmann (2009), several fields related to moist processes and radiation are composited with respect to local maxima in rain rate to determine their spatio-temporal evolution with deep convection in the central Pacific Ocean. Major improvements to the above study are the isolation of DC events in time so as to prevent multiple sampling of the same event, and a revised definition of the mean background state that allows for better characterization of the DC-induced anomalies. The DC events observed in this study propagate westward at ~ 4 m s−1. Both the upper tropospheric relative humidity and outgoing longwave radiation are substantially perturbed over a broad horizontal extent during peak convection and for long periods of time. Cloud fraction anomaly increases throughout the upper troposphere, especially in the 200–250 hPa layer, reaching peak coverage following deep convection. Cloud ice water content anomaly confined to pressures greater than about 250 hPa and peaks near 450 hPa within a few hours of the DC event but remain enhanced following the DC event. Consistent with the large increase in upper tropospheric cloud ice, albedo increases dramatically and persists for sometime following the DC event. Applying the method to the model demonstrates that it is able to capture the large-scale responses to DC events, most notably for outgoing longwave radiation, but there are a number of important differences. For example, the DC signature of upper tropospheric humidity consistently covers a broader horizontal area than what is observed. In addition, the DC events move eastward in the model, but westward in the observations, and exhibit an unrealistic 24 h repeat cycle. Moreover, the modeled upper tropospheric cloud fraction anomalies – despite being of comparable magnitude and exhibiting similar longevity – are confined to a thinner layer that is closer to the tropopause and peak earlier than in observations. Finally, the modeled ice water content anomalies at pressures greater than about 350 hPa are about twice as large as in the observations and do not persist as long after peak convection.

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Extinction coefficients retrieved in deep tropical ice clouds from lidar observations using a CALIPSO-like algorithm compared to in-situ measurements from the Cloud Integrated Nephelometer during CRYSTAL-FACE

Atmospheric Chemistry and Physics Discussions ◽

10.5194/acpd-6-10649-2006 ◽

2006 ◽

Vol 6 (5) ◽

pp. 10649-10672 ◽

Cited By ~ 2

Author(s):

V. Noel ◽

D. M. Winker ◽

T. J. Garrett ◽

M. McGill

Keyword(s):

Spatial Scales ◽

Deep Convection ◽

Retrieval Algorithm ◽

Crystal Face ◽

Ice Clouds ◽

Extinction Coefficients ◽

Convective Systems ◽

Lidar Ratio ◽

Deep Convective Systems

Abstract. This paper presents a comparison of lidar ratios and volume extinction coefficients in tropical ice clouds, retrieved using observations from two instruments: the 532-nm Cloud Physics Lidar (CPL), and the in-situ Cloud Integrating Nephelometer (CIN) probe. Both instruments were mounted on airborne platforms during the CRYSTAL-FACE campaign and took measurements up to 17 km. Coincident observations from two cases of ice clouds located on top of deep convective systems are compared. First, lidar ratios are retrieved from CPL observations of attenuated backscatter, using a retrieval algorithm for opaque cloud similar to one used in the soon-to-be launched CALIPSO mission, and compared to results from the regular CPL algorithm. These lidar ratios are used to retrieve extinction coefficient profiles, which are compared to actual observations from the CIN in-situ probe, putting the emphasis on their vertical variability. When observations coincide, retrievals from both instruments are very similar. Differences are generally variations around the average profiles, and general trends on larger spatial scales are usually well reproduced. The two instruments agree well, with an average difference of less than 11% on optical depth retrievals. Results suggest the CALIPSO Deep Convection algorithm can be trusted to deliver realistic estimates of the lidar ratio, leading to good retrievals of extinction coefficients.

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Deep Convective Systems Observed by A-Train in the Tropical Indo-Pacific Region Affected by the MJO

Journal of the Atmospheric Sciences ◽

10.1175/jas-d-12-057.1 ◽

2013 ◽

Vol 70 (2) ◽

pp. 465-486 ◽

Cited By ~ 20

Author(s):

Jian Yuan ◽

Robert A. Houze

Keyword(s):

Large Scale ◽

Deep Convection ◽

Active Phase ◽

Maximum Height ◽

Pacific Region ◽

Convective Envelope ◽

Convective Systems ◽

Mesoscale Convective ◽

Deep Convective Systems ◽

Cloud Tops

Abstract In the Indo-Pacific region, mesoscale convective systems (MCSs) occur in a pattern consistent with the eastward propagation of the large-scale convective envelope of the Madden–Julian oscillation (MJO). MCSs are major contributors to the total precipitation. Over the open ocean they tend to be merged or connected systems, while over the Maritime Continent area they tend to be separated or discrete. Over all regions affected by the MJO, connected systems increase in frequency during the active phase of the MJO. Characteristics of each type of MCS (separated or connected) do not vary much over MJO-affected regions. However, separated and connected MCSs differ in structure from each other. Connected MCSs have a larger size and produce less but colder-topped anvil cloud. For both connected and separated MCSs, larger systems tend to have colder cloud tops and less warmer-topped anvil cloud. The maximum height of MCS precipitating cores varies only slightly, and the variation is related to sea surface temperature. Enhanced large-scale convection, greater frequency of occurrence of connected MCSs, and increased midtroposphere moisture coincide, regardless of the region, season, or large-scale conditions (such as the concurrent phase of the MJO), suggesting that the coexistence of these phenomena is likely the nature of deep convection in this region. The increase of midtroposphere moisture observed in all convective regimes during large-scale convectively active phases suggests that the source of midtroposphere moisture is not local or instantaneous and that the accumulation of midtroposphere moisture over MJO-affected regions needs to be better understood.

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GoAmazon2014/5 campaign points to deep-inflow approach to deep convection across scales

Proceedings of the National Academy of Sciences ◽

10.1073/pnas.1719842115 ◽

2018 ◽

Vol 115 (18) ◽

pp. 4577-4582 ◽

Cited By ~ 9

Author(s):

Kathleen A. Schiro ◽

Fiaz Ahmed ◽

Scott E. Giangrande ◽

J. David Neelin

Keyword(s):

Climate Models ◽

Climate Model ◽

Deep Convection ◽

Potential Temperature ◽

Strong Relationship ◽

Field Campaign ◽

Convective Systems ◽

Tropical Oceans ◽

Mesoscale Convective ◽

Environmental Air

A substantial fraction of precipitation is associated with mesoscale convective systems (MCSs), which are currently poorly represented in climate models. Convective parameterizations are highly sensitive to the assumptions of an entraining plume model, in which high equivalent potential temperature air from the boundary layer is modified via turbulent entrainment. Here we show, using multiinstrument evidence from the Green Ocean Amazon field campaign (2014–2015; GoAmazon2014/5), that an empirically constrained weighting for inflow of environmental air based on radar wind profiler estimates of vertical velocity and mass flux yields a strong relationship between resulting buoyancy measures and precipitation statistics. This deep-inflow weighting has no free parameter for entrainment in the conventional sense, but to a leading approximation is simply a statement of the geometry of the inflow. The structure further suggests the weighting could consistently apply even for coherent inflow structures noted in field campaign studies for MCSs over tropical oceans. For radar precipitation retrievals averaged over climate model grid scales at the GoAmazon2014/5 site, the use of deep-inflow mixing yields a sharp increase in the probability and magnitude of precipitation with increasing buoyancy. Furthermore, this applies for both mesoscale and smaller-scale convection. Results from reanalysis and satellite data show that this holds more generally: Deep-inflow mixing yields a strong precipitation–buoyancy relation across the tropics. Deep-inflow mixing may thus circumvent inadequacies of current parameterizations while helping to bridge the gap toward representing mesoscale convection in climate models.

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Evaluation of ACCMIP outgoing longwave radiation from tropospheric ozone using TES satellite observations

Atmospheric Chemistry and Physics ◽

10.5194/acp-13-4057-2013 ◽

2013 ◽

Vol 13 (8) ◽

pp. 4057-4072 ◽

Cited By ~ 41

Author(s):

K. W. Bowman ◽

D. T. Shindell ◽

H. M. Worden ◽

J.F. Lamarque ◽

P. J. Young ◽

...

Keyword(s):

Atmospheric Chemistry ◽

Tropospheric Ozone ◽

Outgoing Longwave Radiation ◽

Radiative Forcing ◽

Climate Models ◽

Climate Model ◽

Longwave Radiation ◽

Satellite Observations ◽

Ensemble Mean ◽

High Bias

Abstract. We use simultaneous observations of tropospheric ozone and outgoing longwave radiation (OLR) sensitivity to tropospheric ozone from the Tropospheric Emission Spectrometer (TES) to evaluate model tropospheric ozone and its effect on OLR simulated by a suite of chemistry-climate models that participated in the Atmospheric Chemistry and Climate Model Intercomparison Project (ACCMIP). The ensemble mean of ACCMIP models show a persistent but modest tropospheric ozone low bias (5–20 ppb) in the Southern Hemisphere (SH) and modest high bias (5–10 ppb) in the Northern Hemisphere (NH) relative to TES ozone for 2005–2010. These ozone biases have a significant impact on the OLR. Using TES instantaneous radiative kernels (IRK), we show that the ACCMIP ensemble mean tropospheric ozone low bias leads up to 120 mW m−2 OLR high bias locally but zonally compensating errors reduce the global OLR high bias to 39 ± 41 m Wm−2 relative to TES data. We show that there is a correlation (R2 = 0.59) between the magnitude of the ACCMIP OLR bias and the deviation of the ACCMIP preindustrial to present day (1750–2010) ozone radiative forcing (RF) from the ensemble ozone RF mean. However, this correlation is driven primarily by models whose absolute OLR bias from tropospheric ozone exceeds 100 m Wm−2. Removing these models leads to a mean ozone radiative forcing of 394 ± 42 m Wm−2. The mean is about the same and the standard deviation is about 30% lower than an ensemble ozone RF of 384 ± 60 m Wm−2 derived from 14 of the 16 ACCMIP models reported in a companion ACCMIP study. These results point towards a profitable direction of combining satellite observations and chemistry-climate model simulations to reduce uncertainty in ozone radiative forcing.

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Use of satellite-based sensing in land surface climatology

Progress in Physical Geography Earth and Environment ◽

10.1177/030913339401800101 ◽

1994 ◽

Vol 18 (1) ◽

pp. 1-15 ◽

Cited By ~ 4

Author(s):

David Greenland

Keyword(s):

Satellite Data ◽

Land Surface ◽

Climate Models ◽

Climate Model ◽

Meteorological Data ◽

Sensible Heat Flux ◽

Longwave Radiation ◽

Climate Modelling ◽

Area Index ◽

Surface Climate

Common types of satellite-derived measurements are reviewed with respect to how they are used to provide information on variables important to land surface climatology. The variables considered include solar radiation, surface albedo, surface temperature, outgoing longwave radiation, cloud cover, net radiation, soil moisture, latent and sensible heat flux, surface cover and leaf area index. A selection of land surface climate modelling schemes is identified and considered with a view to their practicality for use with satellite-derived data. Issues arising from the foregoing considerations include the absence from satellite data of some variables required by land surface climate models, the importance of extreme pixel values in model parameterization, the importance of matching spatial resolution in satellite data and climate model, and the need to have concurrent, independently observed, meteorological data in order to make full use of the satellite data.

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An Evaluation of Northern Australian Wet Season Rainfall Bursts in CMIP5 Models

Journal of Climate ◽

10.1175/jcli-d-17-0637.1 ◽

2018 ◽

Vol 31 (19) ◽

pp. 7789-7802 ◽

Cited By ~ 3

Author(s):

Sugata Narsey ◽

Michael J. Reeder ◽

Christian Jakob ◽

Duncan Ackerley

Keyword(s):

Outgoing Longwave Radiation ◽

Climate Models ◽

Longwave Radiation ◽

Cmip5 Models ◽

Madden Julian Oscillation ◽

Wet Season ◽

The North ◽

Coupled Climate Models ◽

The Tropics ◽

The Relationship

The simulation of northern Australian wet season rainfall bursts by coupled climate models is evaluated. Individual models produce vastly different amounts of precipitation over the north of Australia during the wet season, and this is found to be related to the number of bursts they produce. The seasonal cycle of bursts is found to be poor in most of the models evaluated. It is known that northern Australian wet season bursts are often associated with midlatitude Rossby wave packets and their surface signature as they are refracted toward the tropics. The relationship between midlatitude waves and the initiation of wet season bursts is simulated well by the models evaluated. Another well-documented influence on the initiation of northern Australian wet season bursts is the Madden–Julian oscillation (MJO). No model adequately simulated the tropical outgoing longwave radiation temporal–spatial patterns seen in the reanalysis-derived OLR. This result suggests that the connection between the MJO and the initiation of northern Australian wet season bursts in models is poor.

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