Albedo observations of the Earth’s surface for climate research

1983 ◽  
Vol 309 (1508) ◽  
pp. 285-294 ◽  
Keyword(s):  
General Circulation ◽  
Surface Albedo ◽  
Climate Models ◽  
General Circulation Models ◽  
Data Set ◽  
Primary Input ◽  
Climate Research ◽  
Earth’S Climate ◽  
Atmospheric Distortion ◽  
Spectrally Resolved

The primary input of energy to the Earth’s climate system occurs at the surface and can be highly sensitive to the surface albedo. Albedo changes have been proposed as one cause of climatic variation, but results from climate models are not yet consistent. It is very difficult to establish an agreed global data set with which to initiate comparative climatic simulations. Albedo observations must be spectrally resolved because reflexion of solar radiation is a strong function of wavelength and incident and reflected beams are modified by the atmosphere. Parametrization of system albedos in energybalance models draws on satellite data. The use of satellite observations is less easy in general circulation climate models. The removal of atmospheric distortion is particularly difficult. The establishment of a surface albedo data set generally follows one of two approaches: geographical categorization or remote monitoring. Surface albedo specification in current general circulation models is diverse. This paper reviews the ways in which remotely derived albedo measurements are used now and may, in the future, be improved for climate research.

scholarly journals Variability and extremes: Statistical validation of the AWI-ESM

2021 ◽  
Author(s):  
Justus Contzen ◽  
Thorsten Dickhaus ◽  
Gerrit Lohmann
Keyword(s):  
General Circulation ◽  
Clustering Algorithm ◽  
Climate Models ◽  
Climate Model ◽  
Extreme Values ◽  
Global Climate Model ◽  
General Circulation Models ◽  
Value Theory ◽  
Future Climate Change ◽  
Data Set

Abstract. Coupled general circulation models are of paramount importance to assess quantitatively the magnitude of future climate change. Usual methods for validating climate models include the evaluation of mean values and covariances, but less attention is directed to the evaluation of extremal behaviour. This is a problem because many severe consequences of climate changes are due to climate extremes. We present a method for model validation in terms of extreme values based on classical extreme value theory. We further discuss a clustering algorithm to detect spacial dependencies and tendencies for concurrent extremes. To illustrate these methods, we analyse precipitation extremes of the AWI-ESM global climate model compared to the reanalysis data set CRU TS4.04. The methods presented here can also be used for the comparison of model ensembles, and there may be further applications in palaeoclimatology.

scholarly journals GRACILE: a comprehensive climatology of atmospheric gravity wave parameters based on satellite limb soundings

2018 ◽  
Vol 10 (2) ◽  
pp. 857-892 ◽  
Author(s):  
Manfred Ern ◽  
Quang Thai Trinh ◽  
Peter Preusse ◽  
John C. Gille ◽  
Martin G. Mlynczak ◽  
...  
Keyword(s):  
Gravity Wave ◽  
Gravity Waves ◽  
General Circulation ◽  
Climate Models ◽  
General Circulation Models ◽  
Atmospheric Gravity Wave ◽  
Data Set ◽  
Wave Source ◽  
Global Data ◽  
Satellite Instruments

Abstract. Gravity waves are one of the main drivers of atmospheric dynamics. The spatial resolution of most global atmospheric models, however, is too coarse to properly resolve the small scales of gravity waves, which range from tens to a few thousand kilometers horizontally, and from below 1 km to tens of kilometers vertically. Gravity wave source processes involve even smaller scales. Therefore, general circulation models (GCMs) and chemistry climate models (CCMs) usually parametrize the effect of gravity waves on the global circulation. These parametrizations are very simplified. For this reason, comparisons with global observations of gravity waves are needed for an improvement of parametrizations and an alleviation of model biases. We present a gravity wave climatology based on atmospheric infrared limb emissions observed by satellite (GRACILE). GRACILE is a global data set of gravity wave distributions observed in the stratosphere and the mesosphere by the infrared limb sounding satellite instruments High Resolution Dynamics Limb Sounder (HIRDLS) and Sounding of the Atmosphere using Broadband Emission Radiometry (SABER). Typical distributions (zonal averages and global maps) of gravity wave vertical wavelengths and along-track horizontal wavenumbers are provided, as well as gravity wave temperature variances, potential energies and absolute momentum fluxes. This global data set captures the typical seasonal variations of these parameters, as well as their spatial variations. The GRACILE data set is suitable for scientific studies, and it can serve for comparison with other instruments (ground-based, airborne, or other satellite instruments) and for comparison with gravity wave distributions, both resolved and parametrized, in GCMs and CCMs. The GRACILE data set is available as supplementary data at https://doi.org/10.1594/PANGAEA.879658.

scholarly journals GRACILE: A comprehensive climatology of atmospheric gravity wave parameters based on satellite limb soundings

2018 ◽  
Author(s):  
Manfred Ern ◽  
Quang Thai Trinh ◽  
Peter Preusse ◽  
John C. Gille ◽  
Martin G. Mlynczak ◽  
...  
Keyword(s):  
Gravity Wave ◽  
Gravity Waves ◽  
General Circulation ◽  
Climate Models ◽  
General Circulation Models ◽  
Atmospheric Gravity Wave ◽  
Data Set ◽  
Wave Source ◽  
Global Data ◽  
Satellite Instruments

Abstract. Gravity waves are one of the main drivers of atmospheric dynamics. The spatial resolution of most global atmospheric models, however, is too coarse to properly resolve the small scales of gravity waves, which range from tens to a few thousand kilometers horizontally, and from below 1 km to tens of kilometers vertically. Gravity wave source processes involve even smaller scales. Therefore, general circulation models (GCMs) and chemistry climate models (CCMs) usually parametrize the effect of gravity waves on the global circulation. These parametrizations are very simplified. For this reason, comparisons with global observations of gravity waves are needed for an improvement of parametrizations and an alleviation of model biases. We present a gravity wave climatology based on atmospheric infrared limb emissions observed by satellite (GRACILE). GRACILE is a global data set of gravity wave distributions observed in the stratosphere and the mesosphere by the infrared limb sounding satellite instruments High Resolution Dynamics Limb Sounder (HIRDLS) and Sounding of the Atmosphere using Broadband Emission Radiometry (SABER). Typical distributions (zonal averages and global maps) of gravity wave vertical wavelengths and along-track horizontal wavenumbers are provided, as well as gravity wave temperature variances, potential energies and absolute momentum fluxes. This global data set captures the typical seasonal variations of these parameters, as well as their spatial variations. The GRACILE data set is suitable for scientific studies, and it can serve for comparison with other instruments (ground based, airborne, or other satellite instruments) and for comparison with gravity wave distributions, both resolved and parametrized, in GCMs and CCMs. The GRACILE data set is available as supplementary data at https://doi.org/10.1594/PANGAEA.879658.

scholarly journals Investigation of Regional and Seasonal Variations in Marine Boundary Layer Cloud Properties from MODIS Observations

2008 ◽  
Vol 21 (19) ◽  
pp. 4955-4973 ◽  
Author(s):  
Michael P. Jensen ◽  
Andrew M. Vogelmann ◽  
William D. Collins ◽  
Guang J. Zhang ◽  
Edward P. Luke
Keyword(s):  
Boundary Layer ◽  
General Circulation ◽  
Climate Models ◽  
Marine Boundary Layer ◽  
General Circulation Models ◽  
Test Bed ◽  
Liquid Water Path ◽  
Microphysical Properties ◽  
Cloud Properties ◽  
Peak Versus

Abstract To aid in understanding the role that marine boundary layer (MBL) clouds play in climate and assist in improving their representations in general circulation models (GCMs), their long-term microphysical and macroscale characteristics are quantified using observations from the Moderate Resolution Imaging Spectroradiometer (MODIS) instrument aboard the National Aeronautics and Space Administration’s (NASA’s) Terra satellite. Six years of MODIS pixel-level cloud products are used from oceanic study regions off the west coasts of California, Peru, the Canary Islands, Angola, and Australia where these cloud types are common. Characterizations are given for their organization (macroscale structure), the associated microphysical properties, and the seasonal dependencies of their variations for scales consistent with the size of a GCM grid box (300 km × 300 km). MBL mesoscale structure is quantified using effective cloud diameter CD, which is introduced here as a simplified measure of bulk cloud organization; it is straightforward to compute and provides descriptive information beyond that offered by cloud fraction. The interrelationships of these characteristics are explored while considering the influences of the MBL state, such as the occurrence of drizzle. Several commonalities emerge for the five study regions. MBL clouds contain the best natural examples of plane-parallel clouds, but overcast clouds occur in only about 25% of the scenes, which emphasizes the importance of representing broken MBL cloud fields in climate models (that are subgrid scale). During the peak months of cloud occurrence, mesoscale organization (larger CD) increases such that the fractions of scenes characterized as “overcast” and “clumped” increase at the expense of the “scattered” scenes. Cloud liquid water path and visible optical depth usually trend strongly with CD, with the largest values occurring for scenes that are drizzling. However, considerable interregional differences exist in these trends, suggesting that different regression functionalities exist for each region. For peak versus off-peak months, the fraction of drizzling scenes (as a function of CD) are similar for California and Angola, which suggests that a single probability distribution function might be used for their drizzle occurrence in climate models. The patterns are strikingly opposite for Peru and Australia; thus, the contrasts among regions may offer a test bed for model simulations of MBL drizzle occurrence.

scholarly journals Boundary conditions for the Middle Miocene Climate Transition (MMCT v1.0)

2017 ◽  
Author(s):  
Amanda Frigola ◽  
Matthias Prange ◽  
Michael Schulz
Keyword(s):  
Boundary Conditions ◽  
General Circulation ◽  
Middle Miocene ◽  
Climate Models ◽  
Global Climate ◽  
Co2 Concentration ◽  
General Circulation Models ◽  
Global Climate Models ◽  
Ice Volume ◽  
Climate Transition

Abstract. The Middle Miocene Climate Transition was characterized by major Antarctic ice-sheet expansion and global cooling during the interval ~ 15–13 Ma. Here we present two sets of boundary conditions for global general circulation models characterizing the periods before (Middle Miocene Climatic Optimum; MMCO) and after (Middle Miocene Glaciation; MMG) the transition. These boundary conditions include Middle Miocene global topography, bathymetry and vegetation. Additionally, Antarctic ice volume and geometry, sea-level and atmospheric CO2 concentration estimates for the MMCO and the MMG are reviewed. The boundary-condition files are available for use as input in a wide variety of global climate models and constitute a valuable tool for modeling studies with a focus on the Middle Miocene.

scholarly journals Exploiting the weekly cycle as observed over Europe to analyse aerosol indirect effects in two climate models

2009 ◽  
Vol 9 (21) ◽  
pp. 8493-8501 ◽  
Author(s):  
J. Quaas ◽  
O. Boucher ◽  
A. Jones ◽  
G. P. Weedon ◽  
J. Kieser ◽  
...  
Keyword(s):  
Indirect Effects ◽  
General Circulation ◽  
Climate Models ◽  
General Circulation Models ◽  
Cloud Microphysics ◽  
Liquid Water Path ◽  
Large Variability ◽  
Aerosol Indirect Effects ◽  
Weekly Cycle ◽  
Model Control

Abstract. A weekly cycle in aerosol pollution and some meteorological quantities is observed over Europe. In the present study we exploit this effect to analyse aerosol-cloud-radiation interactions. A weekly cycle is imposed on anthropogenic emissions in two general circulation models that include parameterizations of aerosol processes and cloud microphysics. It is found that the simulated weekly cycles in sulfur dioxide, sulfate, and aerosol optical depth in both models agree reasonably well with those observed indicating model skill in simulating the aerosol cycle. A distinct weekly cycle in cloud droplet number concentration is demonstrated in both observations and models. For other variables, such as cloud liquid water path, cloud cover, top-of-the-atmosphere radiation fluxes, precipitation, and surface temperature, large variability and contradictory results between observations, model simulations, and model control simulations without a weekly cycle in emissions prevent us from reaching any firm conclusions about the potential aerosol impact on meteorology or the realism of the modelled second aerosol indirect effects.

scholarly journals Interhemispheric differences of mesosphere/lower thermosphere winds and tides investigated from three whole atmosphere models and meteor radar observations

2021 ◽  
Author(s):  
Gunter Stober ◽  
Ales Kuchar ◽  
Dimitry Pokhotelov ◽  
Huixin Liu ◽  
Han-Li Liu ◽  
...  
Keyword(s):  
General Circulation ◽  
Climate Models ◽  
Climate Model ◽  
Lower Thermosphere ◽  
Winter Season ◽  
General Circulation Models ◽  
Meteor Radar ◽  
Radar Observations ◽  
Seasonal Characteristics

Abstract. Long-term and continuous observations of mesospheric/lower thermospheric winds are rare, but they are important to investigate climatological changes at these altitudes on time scales of several years, covering a solar cycle and longer. Such long time series are a natural heritage of the mesosphere/lower thermosphere climate, and they are valuable to compare climate models or long term runs of general circulation models (GCMs). Here we present a climatological comparison of wind observations from six meteor radars at two conjugate latitudes to validate the corresponding mean winds and atmospheric diurnal and semidiurnal tides from three GCMs, namely Ground-to-Topside Model of Atmosphere and Ionosphere for Aeronomy (GAIA), Whole Atmosphere Community Climate Model Extension (Specified Dynamics) (WACCM-X(SD)) and Upper Atmosphere ICOsahedral Non-hydrostatic (UA-ICON) model. Our results indicate that there are interhemispheric differences in the seasonal characteristics of the diurnal and semidiurnal tide. There also are some differences in the mean wind climatologies of the models and the observations. Our results indicate that GAIA shows a reasonable agreement with the meteor radar observations during the winter season, whereas WACCM-X(SD) shows a better agreement with the radars for the hemispheric zonal summer wind reversal, which is more consistent with the meteor radar observations. The free running UA-ICON tends to show similar winds and tides compared to WACCM-X(SD).

scholarly journals The importance of considering sub-grid cloud variability when using satellite observations to evaluate the cloud and precipitation simulations in climate models

2018 ◽  
Vol 11 (8) ◽  
pp. 3147-3158 ◽  
Author(s):  
Hua Song ◽  
Zhibo Zhang ◽  
Po-Lun Ma ◽  
Steven Ghan ◽  
Minghuai Wang
Keyword(s):  
General Circulation ◽  
Climate Models ◽  
General Circulation Models ◽  
Satellite Observations ◽  
Community Atmosphere Model ◽  
Cloud Resolving Model ◽  
Moderate Resolution ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
Indispensable Tool ◽  
Probability Of Precipitation

Abstract. Satellite cloud observations have become an indispensable tool for evaluating general circulation models (GCMs). To facilitate the satellite and GCM comparisons, the CFMIP (Cloud Feedback Model Inter-comparison Project) Observation Simulator Package (COSP) has been developed and is now increasingly used in GCM evaluations. Real-world clouds and precipitation can have significant sub-grid variations, which, however, are often ignored or oversimplified in the COSP simulation. In this study, we use COSP cloud simulations from the Super-Parameterized Community Atmosphere Model (SPCAM5) and satellite observations from the Moderate Resolution Imaging Spectroradiometer (MODIS) and CloudSat to demonstrate the importance of considering the sub-grid variability of cloud and precipitation when using the COSP to evaluate GCM simulations. We carry out two sensitivity tests: SPCAM5 COSP and SPCAM5-Homogeneous COSP. In the SPCAM5 COSP run, the sub-grid cloud and precipitation properties from the embedded cloud-resolving model (CRM) of SPCAM5 are used to drive the COSP simulation, while in the SPCAM5-Homogeneous COSP run only grid-mean cloud and precipitation properties (i.e., no sub-grid variations) are given to the COSP. We find that the warm rain signatures in the SPCAM5 COSP run agree with the MODIS and CloudSat observations quite well. In contrast, the SPCAM5-Homogeneous COSP run which ignores the sub-grid cloud variations substantially overestimates the radar reflectivity and probability of precipitation compared to the satellite observations, as well as the results from the SPCAM5 COSP run. The significant differences between the two COSP runs demonstrate that it is important to take into account the sub-grid variations of cloud and precipitation when using COSP to evaluate the GCM to avoid confusing and misleading results.

Efficient estimation and ensemble generation in climate modelling

2007 ◽  
Vol 365 (1857) ◽  
pp. 2077-2088 ◽  
Author(s):  
J.D Annan ◽  
J.C Hargreaves
Keyword(s):  
Monte Carlo ◽  
Particle Filtering ◽  
General Circulation ◽  
Climate Models ◽  
General Circulation Models ◽  
Monte Carlo Sampling ◽  
Efficient Estimation ◽  
Future Research ◽  
Great Promise ◽  
Climate Modelling

In this paper, we review progress towards efficiently estimating parameters in climate models. Since the general problem is inherently intractable, a range of approximations and heuristic methods have been proposed. Simple Monte Carlo sampling methods, although easy to implement and very flexible, are rather inefficient, making implementation possible only in the very simplest models. More sophisticated methods based on random walks and gradient-descent methods can provide more efficient solutions, but it is often unclear how to extract probabilistic information from such methods and the computational costs are still generally too high for their application to state-of-the-art general circulation models (GCMs). The ensemble Kalman filter is an efficient Monte Carlo approximation which is optimal for linear problems, but we show here how its accuracy can degrade in nonlinear applications. Methods based on particle filtering may provide a solution to this problem but have yet to be studied in any detail in the realm of climate models. Statistical emulators show great promise for future research and their computational speed would eliminate much of the need for efficient sampling techniques. However, emulation of a full GCM has yet to be achieved and the construction of such represents a substantial computational task in itself.

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