[Show abstract][Hide abstract] ABSTRACT: A nonuniform, fast Fourier transform can be used to reduce the computational cost of the empirical characteristic function (ECF) by a factor of 100. This fast ECF calculation method is applied to a new, objective, and robust method for estimating the probability distribution of univariate data, which effectively modulates and filters the ECF of a dataset in a way that yields an optimal estimate of the (Fourier transformed) underlying distribution. This improvement in computational efficiency is leveraged to estimate probability densities from a large ensemble of atmospheric velocity increments (gradients), with the purpose of characterizing the statistical and fractal properties of the velocity field. It is shown that the distribution of velocity increments depends on location in an atmospheric model and that the increments are clearly not normally distributed. The estimated increment distributions exhibit self-similar and distinctly multifractal behavior, as shown by structure functions that exhibit power-law scaling with a non-linear dependence of the power-law exponent on the structure function order.
Computational Statistics & Data Analysis 11/2014; · 1.30 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: We present an analysis of version 5.1 of the Community Atmospheric Model (CAM5.1) at a high horizontal resolution. Intercomparison of this global model at approximately 0.25o, 1o and 2o is presented for extreme daily precipitation as well as for a suite of seasonal mean fields. In general, extreme precipitation amounts are larger in high resolution than in lower resolution configurations. In many but not all locations and/or seasons, extreme daily precipitation rates in the high-resolution configuration are higher and more realistic. The high-resolution configuration produces tropical cyclones up to category 5 on the Saffir-Simpson scale and a comparison to observations reveals both realistic and unrealistic model behavior. In the absence of extensive model tuning at high-resolution, simulation of many of the mean fields analyzed in this study is degraded compared to the tuned lower resolution public released version of the model.
Journal of Advances in Modeling Earth Systems 09/2014; · 4.11 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: Multivariate analysis techniques were used to quantify and compare the spectral and temporal variability of observed and simulated shortwave hyperspectral Earth reflectance. The observed reflectances were measured by the Scanning Imaging Spectrometer for Atmospheric Cartography (SCIAMACHY) instrument between 2002 and 2010. The simulated reflectances were calculated using climate Observing System Simulation Experiments (OSSEs), which used two IPCC AR4 scenarios (constant CO2 and A2 emission) to drive MODTRAN simulations. PC spectral shapes and time series exhibited evidence of physical variables including cloud reflectance, vegetation and desert albedo, and water vapor absorption. Comparing the temporal variability of the OSSE-simulated and SCIAMACHY-measured hyperspectral reflectance showed that their ITCZ-like SH Tropical PC1 ocean time series had a 90° phase difference. The observed and simulated PC intersection quantified their similarity and directly compared their temporal variability. The intersection showed that although despite the similar spectral variability, the temporal variability of the dominant PCs differed as in, for example, the 90° phase difference between the SH Tropical intersection PC1s. PCA of OSSE reflectance demonstrated that the spectral and centennial variability of the two cases differed. The A2 PC time series, unlike the constant CO2 time series, exhibited centennial secular trends. Singular spectrum analysis isolated the A2 secular trends. The A2 OSSE PC1 and PC4 secular trends matched those in aerosol optical depth and total column precipitable water, respectively. This illustrates that time series of hyperspectral reflectance may be used to identify and attribute secular climate trends with a sufficiently long measurement record and high instrument accuracy.
Journal of Geophysical Research: Atmospheres. 08/2014;
[Show abstract][Hide abstract] ABSTRACT: Recent studies have established that atmospheric water vapor fields exhibit spatial spectra that take the form of power laws and hence can be compactly characterized by scaling exponents. The power law scaling exponents have been shown to exhibit substantial vertical variability. In this work, Taylor's frozen turbulence hypothesis is used to infer the first order spatial structure function and generalized detrended fluctuation function scaling exponents for scales between 1 km and 100 km. Both methods are used to estimate the Hurst exponent (H) using 10 Hz time series of water vapor measured at 396 m altitude from an Ameriflux tower in Wisconsin. Due to the diurnal cycle in the boundary layer height at the 396 m observational level, H may be estimated for both the daytime convective mixed layer and the nocturnal residual layer. Values of are obtained for the convective mixed layer, while values of apply in the nocturnal residual layer. The results are shown to be remarkably consistent with a similar analysis from satellite based observations as reported in Pressel and Collins .
Journal of Geophysical Research: Atmospheres. 07/2014;
[Show abstract][Hide abstract] ABSTRACT: The impact of the circulation shift under climate warming on the distribution of precipitation extremes and the associated sensitivity to model resolution are investigated using Community Atmosphere Model CAM3 in an aquaplanet configuration. The response of the probability density function of the precipitation to a uniform SST warming can be interpreted as superimposition of a dynamically induced poleward shift and a thermodynamically induced upward shift toward higher intensities, which give rise to manyfold increase in the frequency of the most extreme categories of the precipitation events at the poleward side of the midlatitude storm track. Coarser resolutions underestimate not only the intensity of the precipitation extremes but also the dynamical contribution to the increase of precipitation extremes. Meanwhile, the thermodynamic contribution to the intensification of the precipitation extremes is substantially less than expected from the Clausius-Clapeyron relation, implicative of significant change in the vertical structure of the precipitation processes.
[Show abstract][Hide abstract] ABSTRACT: The mean solar spectral reflectance averaged over large spatiotemporal scales is an important data product of climate benchmark proposed for the CLARREO mission. The interannual variability of these reflectances over the ocean is examined through satellite measured hyperspectral data and through satellite instrument emulation based on model simulation. Such large domain-averaged reflectances show small interannual variation, usually under few percent, depending on latitude region and spatiotemporal scale for averaging. Although the interannual variation is usually less than the absolute accuracy of model calculation, the model simulated interannual variations are consistent with the direct measurements because most of the modeling error in the reflectance averaged in large climate domains is systematic and is canceled out in the interannual difference spectra. The interannual variability is also shown to decrease as the temporal and spatial scales increase. Both the observational data and the model simulations show that the natural variability in the annual mean reflectance is about 50% lower than that in the monthly mean over all spectra. The interannual variability from observation in large climate domains also compares favorably with that from the climate OSSE based on climate model simulations; both show a standard deviation of less than 1% of the mean reflectance across all spectra for global and annual average over the ocean.
Journal of Geophysical Research: Atmospheres. 03/2014;
[Show abstract][Hide abstract] ABSTRACT:  We analyze subdaily continental convective precipitation data relative to the Southeastern U.S. from gridded rain gauge measurements, conventional global climate models (GCMs) from the Coupled Model Intercomparison Project Phase 5 (CMIP5) archive, and a multiscale GCM. GCMs react too quickly to local convective instability and, therefore, overestimate the incidence of middle rainfall events and underestimate the incidence of no, little, and heavy rainfall events. Moreover, GCMs overestimate the persistence of heavy precipitation and underestimate the persistence of no and light precipitation. In general, GCMs with suppression mechanisms in the treatments of convective precipitation compare best with rain gauge derived data and should be trusted more than the others when assessing the risk from extreme precipitation events. The multiscale GCM has the best estimate of the diurnal cycle and a good estimate of heavy rainfall persistence.
[Show abstract][Hide abstract] ABSTRACT: W it h it s u n p r e ce d e nt e d a cc u r a c y, the Climate Absolute Radiance and Refractivity Observatory substantially shortens the time to detect the magnitude of climate change at the high confidence level that decision makers need. T HE CLARREO VISION FROM THE NATIONAL RESEARCH COUNCIL DECADAL SURVEY. A critical issue for climate change observations is that their absolute accuracy is insufficient to confidently observe decadal climate change signals (NRC 2007; Trenberth et al. 2013; Trenberth and Fasullo 2010; Ohring et al. 2005; Ohring 2007). Observing decadal climate change is critical to assessing the accuracy of climate model pro-jections (Solomon et al. 2007; Masson and Knutti 2011; Stott and Kettleborough 2002) as well as to attributing climate change to various sources (Solomon et al. 2007). Sound policymaking requires high confidence in climate predictions verified against decadal change observations with rigorously known accuracy. The need to improve satellite data accuracy has been expressed in Detail of CLARREO (red orbit track) obtaining matched data to serve as reference intercalibration for instruments on a polar orbiting weather satellite (green track). For more information see Fig. 6.
[Show abstract][Hide abstract] ABSTRACT: Global climate models (GCMs) are the primary tools for predicting the evolution of the climate system. Through decades of development, GCMs have demonstrated useful skill in simulating climate at continental to global scales. However, large uncertainties remain in projecting climate change at regional scales, which limits the ability of scientists to help decision makers in cities and communities strategize how best to adapt to and mitigate climate change.
Eos, Transactions American Geophysical Union. 08/2013; 94(34).
[Show abstract][Hide abstract] ABSTRACT:  In scientific and policy contexts, radiative forcing—an external change in Earth's mean radiative balance—has been suggested as a metric for evaluating the strength of climate perturbations resulting from different climate change drivers such as greenhouse gases and surface physical effects of land use change. However, the utility of this approach has been questioned given the spatially concentrated and sometimes nonradiative nature of land use climate disturbances. Here we show that when negative forcing from agricultural expansion is approximately balanced by a radiatively equivalent increase in atmospheric carbon dioxide, significant changes in temperature, precipitation, and the timing of climate change result. These idealized experiments demonstrate the nonadditivity of radiative forcing from land use change and greenhouse gases and point to the need for new climate change metrics or the development of climate policies and assessment protocols that do not rely on single dimensional metrics.
[Show abstract][Hide abstract] ABSTRACT: Proposed climate mitigation measures do not account for direct biophysical climate impacts of land-use change (LUC), nor do the stabilization targets modeled for the 5th Climate Model Intercomparison Project (CMIP5) Representative Concentration Pathways (RCPs). To examine the significance of such effects on global and regional patterns of climate change, a baseline and alternative scenario of future anthropogenic activity are simulated within the Integrated Earth System Model, which couples the Global Change Assessment Model, Global Land-use Model, and Community Earth System Model. The alternative scenario has high biofuel utilization and approximately 50% less global forest cover compared to the baseline, standard RCP4.5 scenario. Both scenarios stabilize radiative forcing from atmospheric constituents at 4.5 W/m2 by 2100. Thus, differences between their climate predictions quantify the biophysical effects of LUC. Offline radiative transfer and land model simulations are also utilized to identify forcing and feedback mechanisms driving the coupled response. Boreal deforestation is found to strongly influence climate due to increased albedo coupled with a regional-scale water vapor feedback. Globally, the alternative scenario yields a 21st century warming trend that is 0.5 °C cooler than baseline, driven by a 1 W/m2 mean decrease in radiative forcing that is distributed unevenly around the globe. Some regions are cooler in the alternative scenario than in 2005. These results demonstrate that neither climate change nor actual radiative forcing are uniquely related to atmospheric forcing targets such as those found in the RCP’s, but rather depend on particulars of the socioeconomic pathways followed to meet each target.
Journal of Climate 06/2013; 26(11). · 4.36 Impact Factor
[Show abstract][Hide abstract] ABSTRACT:  High-resolution climate models have been shown to improve the statistics of tropical storms (TCs) and hurricanes compared to low-resolution models. The impact of increasing horizontal resolution in the TC simulation is investigated exclusively using a series of Atmospheric Global Climate Model (AGCM) runs with idealized aquaplanet steady-state boundary conditions and a fixed operational storm-tracking algorithm. The results show that increasing horizontal resolution helps to detect more hurricanes, simulate stronger extreme rainfall, and emulate better storm structures in the models. However, increasing model resolution does not necessarily produce stronger hurricanes in terms of maximum wind speed, minimum sea-level pressure, and mean precipitation, as the increased number of storms simulated by high-resolution models is mainly associated with weaker storms. The spatial scale at which the analyses are conducted appears to have more important control on these meteorological statistics compared to horizontal resolution of the model grid. When the simulations are analyzed on common low-resolution grids, the statistics of the hurricanes, particularly the hurricane counts, show reduced sensitivity to the horizontal grid resolution and signs of scale invariance.
Journal of Advances in Modeling Earth Systems 06/2013; 5(2). · 4.11 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: This study used Community Atmospheric Model 3.5 (CAM3.5) to investigate
the effects of carbonaceous aerosols on climate. The simulations include
control runs with carbonaceous aerosols and no carbon runs in which
carbonaceous aerosols were removed. The Slab Ocean Model (SOM) and the
fixed Sea Surface Temperature (SST) were used to examine effects of
ocean boundary conditions. Throughout this study, climate response
induced by aerosol forcing was mainly analyzed in the following three
terms: (1) aerosol radiative effects under fixed SST, (2) effects of
aerosol-induced SST feedbacks , and (3) total effects including effects
of aerosol forcing and SST feedbacks. The change of SST induced by
aerosols has large impacts on distribution of climate response, the
magnitudes in response patterns such as temperature, precipitation,
zonal winds, mean meridional circulation, radiative fluxes and cloud
coverage are different between the SOM and fixed SST runs. Moreover,
different spatial responses between the SOM and fixed SST runs can also
be seen in some local areas. This implies the importance of SST
feedbacks on simulated climate response. The aerosol dimming effects
cause a cooling predicted at low layers near the surface in most of
carbonaceous aerosol source regions. The temperature response shows a
warming (cooling) predicted in the north (south) high latitudes,
suggesting that aerosol forcing can cause climate change in regions far
away from its origins. Our simulation results show that warming of the
troposphere due to black carbon decreases rainfall in the tropics. This
implies that black carbon has possibly strong influence on weakening of
the tropical circulation. Most of these changes in precipitation are
negatively correlated with changes of radiative fluxes at the top of
model. The changes in radiative fluxes at top of model are physically
consistent with the response patterns in cloud fields. On global
average, low-level cloud coverage increases, mid- and high-level cloud
coverage decreases in response to changes in radiative energy induced by
aerosol forcing. An approximated moisture budget equation was analyzed
in order to understand physical mechanism of precipitation changes
induced by carbonaceous aerosols. Our results show that changes in
tropical precipitation are mainly dominated by dynamic effect, i.e.
vertical moisture transport carried by the perturbed flow.
Atmospheric Chemistry and Physics 03/2013; 13(3):7349-7396. · 4.88 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: The Parallel Offline Radiative Transfer (PORT) model is a tool for
diagnosing radiative forcing. It isolates the radiation code from the
Community Atmosphere Model (CAM4) in the Community Earth System Model
(CESM1). The computation of radiative forcing from doubling of carbon
dioxide and from the change of ozone concentration from year 1850 to
2000 illustrates the use of PORT.
Geoscientific Model Development 01/2013; · 5.03 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: The Climate Absolute Radiance and Refractivity Observatory (CLARREO) is
a climate observation system that has been designed to monitor the
Earth's climate with unprecedented absolute radiometric accuracy and SI
traceability. Climate Observation System Simulation Experiments (OSSEs)
have been generated to simulate CLARREO hyperspectral shortwave imager
measurements to help define the measurement characteristics needed for
CLARREO to achieve its objectives. To evaluate how well the
OSSE-simulated reflectance spectra reproduce the Earth's climate
variability at the beginning of the 21st century, we compared the
variability of the OSSE reflectance spectra to that of the reflectance
spectra measured by the Scanning Imaging Absorption Spectrometer for
Atmospheric Cartography (SCIAMACHY). Principal component analysis (PCA)
is a multivariate spectral decomposition technique used to represent and
study the variability of hyperspectral radiation measurements. Using
PCA, between 99.7% and 99.9% of the total variance the OSSE and
SCIAMACHY data sets can be explained by subspaces defined by six
principal components (PCs). To quantify how much information is shared
between the simulated and observed data sets, we spectrally decomposed
the intersection of the two data set subspaces. The results from four
cases in 2004 showed that the two data sets share eight (January and
October) and seven (April and July) dimensions, which correspond to
about 99.9% of the total SCIAMACHY variance for each month. The spectral
nature of these shared spaces, understood by examining the transformed
eigenvectors calculated from the subspace intersections, exhibit similar
physical characteristics to the original PCs calculated from each data
set, such as water vapor absorption, vegetation reflectance, and cloud
Atmospheric Chemistry and Physics 10/2012; 12(10):28305-28341. · 4.88 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: A modal aerosol module (MAM) has been developed for the Community
Atmosphere Model version 5 (CAM5), the atmospheric component of the
Community Earth System Model version 1 (CESM1). MAM is capable of
simulating the aerosol size distribution and both internal and external
mixing between aerosol components, treating numerous complicated aerosol
processes and aerosol physical, chemical and optical properties in a
physically-based manner. Two MAM versions were developed: a more
complete version with seven lognormal modes (MAM7), and a version with
three lognormal modes (MAM3) for the purpose of long-term (decades to
centuries) simulations. In this paper a description and evaluation of
the aerosol module and its two representations are provided. Sensitivity
of the aerosol lifecycle to simplifications in the representation of
aerosol is discussed. Simulated sulfate and secondary
organic aerosol (SOA) mass concentrations are remarkably similar between
MAM3 and MAM7. Differences in primary organic matter (POM) and black
carbon (BC) concentrations between MAM3 and MAM7 are also small (mostly
within 10%). The mineral dust global burden differs by 10% and sea salt
burden by 30-40% between MAM3 and MAM7, mainly due to the different size
ranges for dust and sea salt modes and different standard deviations of
the log-normal size distribution for sea salt modes between MAM3 and
MAM7. The model is able to qualitatively capture the observed
geographical and temporal variations of aerosol mass and number
concentrations, size distributions, and aerosol optical properties.
However, there are noticeable biases; e.g., simulated BC concentrations
are significantly lower than measurements in the Arctic. There is a low
bias in modeled aerosol optical depth on the global scale, especially in
the developing countries. These biases in aerosol simulations clearly
indicate the need for improvements of aerosol processes (e.g., emission
fluxes of anthropogenic aerosols and precursor gases in developing
countries, boundary layer nucleation) and properties (e.g., primary
aerosol emission size, POM hygroscopicity). In addition, the critical
role of cloud properties (e.g., liquid water content, cloud fraction)
responsible for the wet scavenging of aerosol is highlighted.
Geoscientific Model Development. 05/2012; 5(3):709-739.