scholarly journals Detection of Atmospheric Changes in Spatially and Temporally Averaged Infrared Spectra Observed from Space

2011 ◽  
Vol 24 (24) ◽  
pp. 6392-6407 ◽  
Author(s):  
Seiji Kato ◽  
Bruce A. Wielicki ◽  
Fred G. Rose ◽  
Xu Liu ◽  
Patrick C. Taylor ◽  
...  
Keyword(s):  
Linear Regression ◽  
Climate Model ◽  
Spectral Radiance ◽  
Percentage Error ◽  
Small Scale ◽  
Atmospheric Variability ◽  
Cloud Property ◽  
Cloud Properties ◽  
Property Changes ◽  
Atmospheric Changes

Abstract Variability present at a satellite instrument sampling scale (small-scale variability) has been neglected in earlier simulations of atmospheric and cloud property change retrievals using spatially and temporally averaged spectral radiances. The effects of small-scale variability in the atmospheric change detection process are evaluated in this study. To simulate realistic atmospheric variability, top-of-the-atmosphere nadir-view longwave spectral radiances are computed at a high temporal (instantaneous) resolution with a 20-km field-of-view using cloud properties retrieved from Moderate Resolution Imaging Spectroradiometer (MODIS) measurements, along with temperature humidity profiles obtained from reanalysis. Specifically, the effects of the variability on the necessary conditions for retrieving atmospheric changes by a linear regression are tested. The percentage error in the annual 10° zonal mean spectral radiance difference obtained by assuming linear combinations of individual perturbations expressed as a root-mean-square (RMS) difference computed over wavenumbers between 200 and 2000 cm−1 is 10%–15% for most of the 10° zones. However, if cloud fraction perturbation is excluded, the RMS difference decreases to less than 2%. Monthly and annual 10° zonal mean spectral radiances change linearly with atmospheric property perturbations, which occur when atmospheric properties are perturbed by an amount approximately equal to the variability of the10° zonal monthly deseasonalized anomalies or by a climate-model-predicted decadal change. Nonlinear changes in the spectral radiances of magnitudes similar to those obtained through linear estimation can arise when cloud heights and droplet radii in water cloud change. The spectral shapes computed by perturbing different atmospheric and cloud properties are different so that linear regression can separate individual spectral radiance changes from the sum of the spectral radiance change. When the effects of small-scale variability are treated as noise, however, the error in retrieved cloud properties is large. The results suggest the importance of considering small-scale variability in inferring atmospheric and cloud property changes from the satellite-observed zonally and annually averaged spectral radiance difference.

scholarly journals Simulated and observed horizontal inhomogeneities of optical thickness of Arctic stratus

2018 ◽  
Author(s):  
Michael Schäfer ◽  
Katharina Loewe ◽  
André Ehrlich ◽  
Corinna Hoose ◽  
Manfred Wendisch
Keyword(s):  
Wind Velocity ◽  
Optical Thickness ◽  
Atmospheric Model ◽  
Sensitivity Study ◽  
Spectral Radiance ◽  
Small Scale ◽  
Airborne Measurements ◽  
Cloud Properties ◽  
The Individual ◽  
Horizontal Inhomogeneity

Abstract. Two-dimensional (2D) horizontal fields of cloud optical thickness derived from airborne measurements of solar spectral radiance during the Vertical Distribution of Ice in Arctic Clouds (VERDI) campaign (carried out in Inuvik, Canada in April/May 2012) are compared with semi–idealized Large Eddy Simulations (LES) of Arctic stratus performed with the COnsortium for Small-Scale MOdeling (COSMO) atmospheric model. The input for the LES is obtained from collocated airborne dropsonde observations. Four consecutive days of a persistent Arctic stratus observed above the sea–ice free Beaufort Sea are selected for the comparison. Macrophysical cloud properties such as cloud top altitude and vertical extent are well captured by COSMO. Cloud horizontal inhomogeneity quantified by the standard deviation and one-dimensional (1D) inhomogeneity parameters show that COSMO produces only half of the measured horizontal cloud inhomogeneities, while the directional structure of the cloud inhomogeneity is well represented by the model. Differences between the individual cases are mainly associated with the wind shear near cloud top and the vertical structure of the atmospheric boundary layer. A sensitivity study changing the wind velocity in COSMO by a vertically constant scaling factor shows that the directional cloud inhomogeneity structures strongly depend on the mean wind speed. A threshold wind velocity is identified, which determines when the cloud inhomogeneity stops increasing with increasing wind velocity.

scholarly journals Retrieving Decadal Climate Change from Satellite Radiance Observations—A 100-year CO2 Doubling OSSE Demonstration

Sensors ◽  
2020 ◽  
Vol 20 (5) ◽  
pp. 1247 ◽  
Author(s):  
William L. Smith ◽  
Elisabeth Weisz ◽  
Robert Knuteson ◽  
Henry Revercomb ◽  
Daniel Feldman
Keyword(s):  
Climate Change ◽  
Linear Regression ◽  
Climate Model ◽  
International System ◽  
Spectral Radiance ◽  
Retrieval Algorithm ◽  
Climate Variables ◽  
Infrared Radiance ◽  
Infrared Spectral ◽  
Cross Calibration

Preparing for climate change depends on the observation and prediction of decadal trends of the environmental variables, which have a direct impact on the sustainability of resources affecting the quality of life on our planet. The NASA Climate Absolute Radiance and Refractivity Observatory (CLARREO) mission is proposed to provide climate quality benchmark spectral radiance observations for the purpose of determining the decadal trends of climate variables, and validating and improving the long-range climate model forecasts needed to prepare for the changing climate of the Earth. The CLARREO will serve as an in-orbit, absolute, radiometric standard for the cross-calibration of hyperspectral radiance spectra observed by the international system of polar operational satellite sounding sensors. Here, we demonstrate that the resulting accurately cross-calibrated polar satellite global infrared spectral radiance trends (e.g., from the Metop IASI instrument considered here) can be interpreted in terms of temperature and water vapor profile trends. This demonstration is performed using atmospheric state data generated for a 100-year period from 2000–2099, produced by a numerical climate model prediction that was forced by the doubling of the global average atmospheric CO2 over the 100-year period. The vertical profiles and spatial distribution of temperature decadal trends were successfully diagnosed by applying a linear regression profile retrieval algorithm to the simulated hyperspectral radiance spectra for the 100-year period. These results indicate that it is possible to detect decadal trends in atmospheric climate variables from high accuracy all-sky satellite infrared radiance spectra using the linear regression retrieval technique.

scholarly journals Spatial variability of the sea-ice radiation budget and its effect on aggregate-area fluxes

2001 ◽  
Vol 33 ◽  
pp. 248-252 ◽  
Author(s):  
Xuanji Wang ◽  
Jeffrey R. Key
Keyword(s):  
Sea Ice ◽  
Climate Models ◽  
Climate Model ◽  
Radiative Properties ◽  
Radiation Budget ◽  
Small Scale ◽  
Spatial And Temporal Variability ◽  
Radiative Fluxes ◽  
Cloud Properties ◽  
Longwave Flux

AbstractThe spatial and temporal variability of surface, cloud and radiative properties of sea ice are examined using new satellite-derived products. Downwelling short- and longwave fluxes exhibit temporal correlation over about 180 days, but cloud optical depth and cloud fraction show almost no correlation over time. The spatial variance of surface properties is shown to increase much less rapidly than that of cloud properties. The effect of small-scale inhomogeneity in surface and cloud properties on the calculation of radiative fluxes at ice- and climate-model gridscales is also investigated. Annual mean differences between gridcell fluxes computed from average surface and cloud properties and averages of pixel-by-pixel fluxes are 9.46% for the downwelling shortwave flux and −7.04% for the longwave flux. Therefore, using mean surface and cloud properties to compute surface radiative fluxes in a gridcell results in an overestimate of the shortwave flux and an underestimate of the longwave flux. Model sensitivity studies show that such biases may result in substantial errors in modeled ice thickness. Clearly, the sub-gridscale inhomogeneity of surface and atmospheric properties must be considered when estimating aggregate-area fluxes in sea-ice and climate models.

scholarly journals Toward autonomous surface-based infrared remote sensing of polar clouds: retrievals of cloud optical and microphysical properties

2019 ◽  
Vol 12 (9) ◽  
pp. 5071-5086 ◽  
Author(s):  
Penny M. Rowe ◽  
Christopher J. Cox ◽  
Steven Neshyba ◽  
Von P. Walden
Keyword(s):  
Climate Model ◽  
Effective Radius ◽  
The Arctic ◽  
Polar Regions ◽  
Cloud Property ◽  
Microphysical Properties ◽  
Cloud Properties ◽  
Instrument Resolution ◽  
Mean Square Errors ◽  
Ice Fraction

Abstract. Improvements to climate model results in polar regions require improved knowledge of cloud properties. Surface-based infrared (IR) radiance spectrometers have been used to retrieve cloud properties in polar regions, but measurements are sparse. Reductions in cost and power requirements to allow more widespread measurements could be aided by reducing instrument resolution. Here we explore the effects of errors and instrument resolution on cloud property retrievals from downwelling IR radiances for resolutions of 0.1 to 20 cm−1. Retrievals are tested on 336 radiance simulations characteristic of the Arctic, including mixed-phase, vertically inhomogeneous, and liquid-topped clouds and a variety of ice habits. Retrieval accuracy is found to be unaffected by resolution from 0.1 to 4 cm−1, after which it decreases slightly. When cloud heights are retrieved, errors in retrieved cloud optical depth (COD) and ice fraction are considerably smaller for clouds with bases below 2 km than for higher clouds. For example, at a resolution of 4 cm−1, with errors imposed (noise and radiation bias of 0.2 mW/(m2 sr cm−1) and biases in temperature of 0.2 K and in water vapor of −3 %), using retrieved cloud heights, root-mean-square errors decrease from 1.1 to 0.15 for COD, 0.3 to 0.18 for ice fraction (fice), and 10 to 7 µm for ice effective radius (errors remain at 2 µm for liquid effective radius). These results indicate that a moderately low-resolution, surface-based IR spectrometer could provide cloud property retrievals with accuracy comparable to existing higher-resolution instruments and that such an instrument would be particularly useful for low-level clouds.

scholarly journals A comparison of ship and satellite measurements of cloud properties with global climate model simulations in the southeast Pacific stratus deck

2010 ◽  
Vol 10 (14) ◽  
pp. 6527-6536 ◽  
Author(s):  
M. A. Brunke ◽  
S. P. de Szoeke ◽  
P. Zuidema ◽  
X. Zeng
Keyword(s):  
Diurnal Cycle ◽  
Climate Model ◽  
Global Climate ◽  
Global Climate Model ◽  
Cloud Fraction ◽  
Cloud Base ◽  
Liquid Water Path ◽  
Cloud Properties ◽  
Southeast Pacific ◽  
Cloud Thickness

Abstract. Here, liquid water path (LWP), cloud fraction, cloud top height, and cloud base height retrieved by a suite of A-train satellite instruments (the CPR aboard CloudSat, CALIOP aboard CALIPSO, and MODIS aboard Aqua) are compared to ship observations from research cruises made in 2001 and 2003–2007 into the stratus/stratocumulus deck over the southeast Pacific Ocean. It is found that CloudSat radar-only LWP is generally too high over this region and the CloudSat/CALIPSO cloud bases are too low. This results in a relationship (LWP~h9) between CloudSat LWP and CALIPSO cloud thickness (h) that is very different from the adiabatic relationship (LWP~h2) from in situ observations. Such biases can be reduced if LWPs suspected to be contaminated by precipitation are eliminated, as determined by the maximum radar reflectivity Zmax>−15 dBZ in the apparent lower half of the cloud, and if cloud bases are determined based upon the adiabatically-determined cloud thickness (h~LWP1/2). Furthermore, comparing results from a global model (CAM3.1) to ship observations reveals that, while the simulated LWP is quite reasonable, the model cloud is too thick and too low, allowing the model to have LWPs that are almost independent of h. This model can also obtain a reasonable diurnal cycle in LWP and cloud fraction at a location roughly in the centre of this region (20° S, 85° W) but has an opposite diurnal cycle to those observed aboard ship at a location closer to the coast (20° S, 75° W). The diurnal cycle at the latter location is slightly improved in the newest version of the model (CAM4). However, the simulated clouds remain too thick and too low, as cloud bases are usually at or near the surface.

Cloud Properties over the North Slope of Alaska: Identifying the Prevailing Meteorological Regimes

2012 ◽  
Vol 25 (23) ◽  
pp. 8238-8258 ◽  
Author(s):  
Johannes Mülmenstädt ◽  
Dan Lubin ◽  
Lynn M. Russell ◽  
Andrew M. Vogelmann
Keyword(s):  
Time Series ◽  
Climate Model ◽  
North Slope ◽  
Test Cases ◽  
Synoptic Scale ◽  
Long Time Series ◽  
The North ◽  
Cloud Properties ◽  
North Slope Of Alaska ◽  
Long Time

Abstract Long time series of Arctic atmospheric measurements are assembled into meteorological categories that can serve as test cases for climate model evaluation. The meteorological categories are established by applying an objective k-means clustering algorithm to 11 years of standard surface-meteorological observations collected from 1 January 2000 to 31 December 2010 at the North Slope of Alaska (NSA) site of the U.S. Department of Energy Atmospheric Radiation Measurement Program (ARM). Four meteorological categories emerge. These meteorological categories constitute the first classification by meteorological regime of a long time series of Arctic meteorological conditions. The synoptic-scale patterns associated with each category, which include well-known synoptic features such as the Aleutian low and Beaufort Sea high, are used to explain the conditions at the NSA site. Cloud properties, which are not used as inputs to the k-means clustering, are found to differ significantly between the regimes and are also well explained by the synoptic-scale influences in each regime. Since the data available at the ARM NSA site include a wealth of cloud observations, this classification is well suited for model–observation comparison studies. Each category comprises an ensemble of test cases covering a representative range in variables describing atmospheric structure, moisture content, and cloud properties. This classification is offered as a complement to standard case-study evaluation of climate model parameterizations, in which models are compared against limited realizations of the Earth–atmosphere system (e.g., from detailed aircraft measurements).

scholarly journals Atmospheric circulation and hydroclimate impacts of alternative warming scenarios for the Eocene

2017 ◽  
Vol 13 (8) ◽  
pp. 1037-1048 ◽  
Author(s):  
Henrik Carlson ◽  
Rodrigo Caballero
Keyword(s):  
Surface Temperature ◽  
Radiative Forcing ◽  
Climate Models ◽  
Climate Model ◽  
Regional Climate ◽  
Warm Season ◽  
Cloud Albedo ◽  
Cloud Properties ◽  
Atmospheric Co2 Concentrations ◽  
Global Mean

Abstract. Recent work in modelling the warm climates of the early Eocene shows that it is possible to obtain a reasonable global match between model surface temperature and proxy reconstructions, but only by using extremely high atmospheric CO2 concentrations or more modest CO2 levels complemented by a reduction in global cloud albedo. Understanding the mix of radiative forcing that gave rise to Eocene warmth has important implications for constraining Earth's climate sensitivity, but progress in this direction is hampered by the lack of direct proxy constraints on cloud properties. Here, we explore the potential for distinguishing among different radiative forcing scenarios via their impact on regional climate changes. We do this by comparing climate model simulations of two end-member scenarios: one in which the climate is warmed entirely by CO2 (which we refer to as the greenhouse gas (GHG) scenario) and another in which it is warmed entirely by reduced cloud albedo (which we refer to as the low CO2–thin clouds or LCTC scenario) . The two simulations have an almost identical global-mean surface temperature and equator-to-pole temperature difference, but the LCTC scenario has  ∼  11 % greater global-mean precipitation than the GHG scenario. The LCTC scenario also has cooler midlatitude continents and warmer oceans than the GHG scenario and a tropical climate which is significantly more El Niño-like. Extremely high warm-season temperatures in the subtropics are mitigated in the LCTC scenario, while cool-season temperatures are lower at all latitudes. These changes appear large enough to motivate further, more detailed study using other climate models and a more realistic set of modelling assumptions.

scholarly journals Climate SPHINX: evaluating the impact of resolution and stochastic physics parameterisations in the EC-Earth global climate model

2017 ◽  
Vol 10 (3) ◽  
pp. 1383-1402 ◽  
Author(s):  
Paolo Davini ◽  
Jost von Hardenberg ◽  
Susanna Corti ◽  
Hannah M. Christensen ◽  
Stephan Juricke ◽  
...  
Keyword(s):  
High Resolution ◽  
Large Scale ◽  
Climate Model ◽  
Global Climate ◽  
Rainfall Variability ◽  
Global Climate Model ◽  
Small Scale ◽  
Low Resolution ◽  
The Impact ◽  
Stochastic Physics

Abstract. The Climate SPHINX (Stochastic Physics HIgh resolutioN eXperiments) project is a comprehensive set of ensemble simulations aimed at evaluating the sensitivity of present and future climate to model resolution and stochastic parameterisation. The EC-Earth Earth system model is used to explore the impact of stochastic physics in a large ensemble of 30-year climate integrations at five different atmospheric horizontal resolutions (from 125 up to 16 km). The project includes more than 120 simulations in both a historical scenario (1979–2008) and a climate change projection (2039–2068), together with coupled transient runs (1850–2100). A total of 20.4 million core hours have been used, made available from a single year grant from PRACE (the Partnership for Advanced Computing in Europe), and close to 1.5 PB of output data have been produced on SuperMUC IBM Petascale System at the Leibniz Supercomputing Centre (LRZ) in Garching, Germany. About 140 TB of post-processed data are stored on the CINECA supercomputing centre archives and are freely accessible to the community thanks to an EUDAT data pilot project. This paper presents the technical and scientific set-up of the experiments, including the details on the forcing used for the simulations performed, defining the SPHINX v1.0 protocol. In addition, an overview of preliminary results is given. An improvement in the simulation of Euro-Atlantic atmospheric blocking following resolution increase is observed. It is also shown that including stochastic parameterisation in the low-resolution runs helps to improve some aspects of the tropical climate – specifically the Madden–Julian Oscillation and the tropical rainfall variability. These findings show the importance of representing the impact of small-scale processes on the large-scale climate variability either explicitly (with high-resolution simulations) or stochastically (in low-resolution simulations).

scholarly journals Evaluation of simulated aerosol properties with the aerosol-climate model ECHAM5-HAM using observations from the IMPACT field campaign

2010 ◽  
Vol 10 (16) ◽  
pp. 7709-7722 ◽  
Author(s):  
G.-J. Roelofs ◽  
H. ten Brink ◽  
A. Kiendler-Scharr ◽  
G. de Leeuw ◽  
A. Mensah ◽  
...  
Keyword(s):  
Boundary Layer ◽  
Climate Model ◽  
Lower Boundary ◽  
Synoptic Scale ◽  
Concentration Gradients ◽  
Cloud Properties ◽  
Dry Conditions ◽  
Strong Exchange ◽  
The Impact ◽  
Lower Boundary Layer

Abstract. In May 2008, the measurement campaign IMPACT for observation of atmospheric aerosol and cloud properties was conducted in Cabauw, The Netherlands. With a nudged version of the coupled aerosol-climate model ECHAM5-HAM we simulate the size distribution and chemical composition of the aerosol and the associated aerosol optical thickness (AOT) for the campaign period. Synoptic scale meteorology is represented realistically through nudging of the vorticity, the divergence, the temperature and the surface pressure. Simulated concentrations of aerosol sulfate and organics at the surface are generally within a factor of two from observed values. The monthly averaged AOT from the model is 0.33, about 20% larger than observed. For selected periods of the month with relatively dry and moist conditions discrepancies are approximately −30% and +15%, respectively. Discrepancies during the dry period are partly caused by inaccurate representation of boundary layer (BL) dynamics by the model affecting the simulated AOT. The model simulates too strong exchange between the BL and the free troposphere, resulting in weaker concentration gradients at the BL top than observed for aerosol and humidity, while upward mixing from the surface layers into the BL appears to be underestimated. The results indicate that beside aerosol sulfate and organics also aerosol ammonium and nitrate significantly contribute to aerosol water uptake. The simulated day-to-day variability of AOT follows synoptic scale advection of humidity rather than particle concentration. Even for relatively dry conditions AOT appears to be strongly influenced by the diurnal cycle of RH in the lower boundary layer, further enhanced by uptake and release of nitric acid and ammonia by aerosol water.

Implementation of an Urban Parameterization Scheme into the Regional Climate Model COSMO-CLM

2013 ◽  
Vol 52 (10) ◽  
pp. 2296-2311 ◽  
Author(s):  
Kristina Trusilova ◽  
Barbara Früh ◽  
Susanne Brienen ◽  
Andreas Walter ◽  
Valéry Masson ◽  
...  
Keyword(s):  
Spatial Resolution ◽  
Climate Model ◽  
Spatial Scales ◽  
Regional Climate ◽  
Coupled Model ◽  
Urban Land ◽  
Urban Land Use ◽  
Small Scale ◽  
Model Simulations ◽  
Scale Modelling

AbstractAs the nonhydrostatic regional model of the Consortium for Small-Scale Modelling in Climate Mode (COSMO-CLM) is increasingly employed for studying the effects of urbanization on the environment, the authors extend its surface-layer parameterization by the Town Energy Budget (TEB) parameterization using the “tile approach” for a single urban class. The new implementation COSMO-CLM+TEB is used for a 1-yr reanalysis-driven simulation over Europe at a spatial resolution of 0.11° (~12 km) and over the area of Berlin at a spatial resolution of 0.025° (~2.8 km) for evaluating the new coupled model. The results on the coarse spatial resolution of 0.11° show that the standard and the new models provide 2-m temperature and daily precipitation fields that differ only slightly by from −0.1 to +0.2 K per season and ±0.1 mm day−1, respectively, with very similar statistical distributions. This indicates only a negligibly small effect of the urban parameterization on the model's climatology. Therefore, it is suggested that an urban parameterization may be omitted in model simulations on this scale. On the spatial resolution of 0.025° the model COSMO-CLM+TEB is able to better represent the magnitude of the urban heat island in Berlin than the standard model COSMO-CLM. This finding shows the importance of using the parameterization for urban land in the model simulations on fine spatial scales. It is also suggested that models could benefit from resolving multiple urban land use classes to better simulate the spatial variability of urban temperatures for large metropolitan areas on spatial scales below ~3 km.

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