Urban heat island is among the most evident aspects of human impacts on the earth system. Here we assess the diurnal and seasonal variation of surface urban heat island intensity (SUHII) defined as ...the surface temperature difference between urban area and suburban area measured from the MODIS. Differences in SUHII are analyzed across 419 global big cities, and we assess several potential biophysical and socio-economic driving factors. Across the big cities, we show that the average annual daytime SUHII (1.5 ± 1.2 °C) is higher than the annual nighttime SUHII (1.1 ± 0.5 °C) (P < 0.001). But no correlation is found between daytime and nighttime SUHII across big cities (P = 0.84), suggesting different driving mechanisms between day and night. The distribution of nighttime SUHII correlates positively with the difference in albedo and nighttime light between urban area and suburban area, while the distribution of daytime SUHII correlates negatively across cities with the difference of vegetation cover and activity between urban and suburban areas. Our results emphasize the key role of vegetation feedbacks in attenuating SUHII of big cities during the day, in particular during the growing season, further highlighting that increasing urban vegetation cover could be one effective way to mitigate the urban heat island effect.
The Orbiting Carbon Observatory (OCO) mission will make the first global, space-based measurements of atmospheric carbon dioxide (CO
2) with the precision, resolution, and coverage needed to ...characterize CO
2 sources and sinks on regional scales. The measurement approach and instrument specifications were determined through an analysis of existing carbon cycle data and a series of observing system simulation experiments. During its 2-year mission, OCO will fly in a 1:15 PM sun-synchronous orbit with a 16-day ground-track repeat time, just ahead of the EOS Aqua platform. It will carry a single instrument that incorporates three bore-sighted high-resolution spectrometers designed to measure reflected sunlight in the 0.76-μm O
2 A-band and in the CO
2 bands at 1.61 and 2.06 μm. Soundings recorded in these three bands will be used to retrieve the column-averaged CO
2 dry air mole fraction (
X
CO
2
). A comprehensive validation program was included in the mission to ensure that the space-based
X
CO
2
measurements have precisions of ∼0.3% (1 ppm) on regional scales. OCO measurements will be used in global synthesis inversion and data assimilation models to quantify CO
2 sources and sinks. While OCO will have a nominal lifetime of only 2 years, it will serve as a pathfinder for future long-term CO
2 monitoring missions.
The ability of 11 models in simulating the aerosol vertical distribution from regional to global scales, as part of the second phase of the AeroCom model intercomparison initiative (AeroCom II), is ...assessed and compared to results of the first phase. The evaluation is performed using a global monthly gridded data set of aerosol extinction profiles built for this purpose from the CALIOP (Cloud‐Aerosol Lidar with Orthogonal Polarization) Layer Product 3.01. Results over 12 subcontinental regions show that five models improved, whereas three degraded in reproducing the interregional variability in Zα0–6 km, the mean extinction height diagnostic, as computed from the CALIOP aerosol profiles over the 0–6 km altitude range for each studied region and season. While the models' performance remains highly variable, the simulation of the timing of the Zα0–6 km peak season has also improved for all but two models from AeroCom Phase I to Phase II. The biases in Zα0–6 km are smaller in all regions except Central Atlantic, East Asia, and North and South Africa. Most of the models now underestimate Zα0–6 km over land, notably in the dust and biomass burning regions in Asia and Africa. At global scale, the AeroCom II models better reproduce the Zα0–6 km latitudinal variability over ocean than over land. Hypotheses for the performance and evolution of the individual models and for the intermodel diversity are discussed. We also provide an analysis of the CALIOP limitations and uncertainties contributing to the differences between the simulations and observations.
Key Points
The ability of 11 global models in simulating the aerosol vertical distribution is assessed
Hypotheses for the models performance and evolution and for the inter‐model diversity are discussed
An analysis of CALIOP limitations and uncertainties contributing to the discrepancies is provided
The CALIOP (Cloud‐Aerosol Lidar with Orthogonal Polarization) layer product is used for a multimodel evaluation of the vertical distribution of aerosols. Annual and seasonal aerosol extinction ...profiles are analyzed over 13 sub‐continental regions representative of industrial, dust, and biomass burning pollution, from CALIOP 2007–2009 observations and from AeroCom (Aerosol Comparisons between Observations and Models) 2000 simulations. An extinction mean height diagnostic (Zα) is defined to quantitatively assess the models' performance. It is calculated over the 0–6 km and 0–10 km altitude ranges by weighting the altitude of each 100 m altitude layer by its aerosol extinction coefficient. The mean extinction profiles derived from CALIOP layer products provide consistent regional and seasonal specificities and a low inter‐annual variability. While the outputs from most models are significantly correlated with the observed Zα climatologies, some do better than others, and 2 of the 12 models perform particularly well in all seasons. Over industrial and maritime regions, most models show higher Zα than observed by CALIOP, whereas over the African and Chinese dust source regions, Zα is underestimated during Northern Hemisphere Spring and Summer. The positive model bias in Zα is mainly due to an overestimate of the extinction above 6 km. Potential CALIOP and model limitations, and methodological factors that might contribute to the differences are discussed.
Key Points
Mean regional tropospheric aerosol extinction profiles are calculated from CALIOP data.
An extinction mean height diagnostic is defined.
The performance of 12 global models in simulating the aerosol profiles is evaluated.
The polarization measurements achieved by the POLDER instrument on ADEOS‐1 are used for the remote sensing of aerosols over land surfaces. The key advantage of using polarized observations is their ...ability to systematically correct for the ground contribution, whereas the classical approach using natural light fails. The estimation of land surface polarizing properties from POLDER has been examined in a previous paper. Here we consider how the optical thickness δ0 and Ångstrom exponent α of aerosols are derived from the polarized light backscattered by the particles. The inversion scheme is detailed, and illustrative results are presented. Maps of the retrieved optical thickness allow for detection of large aerosol features, and in the case of small aerosols, the δ0 and α retrievals are consistent with correlative ground‐based measurements. However, because polarized light stems mainly from small particles, the results are biased for aerosol distributions containing coarser modes of particles. To overcome this limitation, an aerosol index defined as the product AI = δ0α is proposed. Theoretical analysis and comparison with ground‐based measurements suggest that AI is approximately the same when using δ0, and α is related to the entire aerosol size distribution or derived from the polarized light originating from the small polarizing particles alone. This invariance is specially assessed by testing the continuity of AI across coastlines, given the unbiased properties of aerosol retrieval over ocean. Although reducing the information concerning the aerosols, this single parameter allows a link between the POLDER aerosol surveys over land and ocean. POLDER aerosol index global maps enable the monitoring of major aerosol sources over continental areas.
Although forest management is one of the instruments proposed to mitigate climate change, the relationship between forest management and canopy albedo has been ignored so far by climate models. Here ...we develop an approach that could be implemented in Earth system models. A stand-level forest gap model is combined with a canopy radiation transfer model and satellite-derived model parameters to quantify the effects of forest thinning on summertime canopy albedo. This approach reveals which parameter has the largest affect on summer canopy albedo: we examined the effects of three forest species (pine, beech, oak) and four thinning strategies with a constant forest floor albedo (light to intense thinning regimes) and five different solar zenith angles at five different sites (40° N 9° E-60° N 9° E). During stand establishment, summertime canopy albedo is driven by tree species. In the later stages of stand development, the effect of tree species on summertime canopy albedo decreases in favour of an increasing influence of forest thinning. These trends continue until the end of the rotation, where thinning explains up to 50% of the variance in near-infrared albedo and up to 70% of the variance in visible canopy albedo. The absolute summertime canopy albedo of all species ranges from 0.03 to 0.06 (visible) and 0.20 to 0.28 (near-infrared); thus the albedo needs to be parameterised at species level. In addition, Earth system models need to account for forest management in such a way that structural changes in the canopy are described by changes in leaf area index and crown volume (maximum change of 0.02 visible and 0.05 near-infrared albedo) and that the expression of albedo depends on the solar zenith angle (maximum change of 0.02 visible and 0.05 near-infrared albedo). Earth system models taking into account these parameters would not only be able to examine the spatial effects of forest management but also the total effects of forest management on climate.
We present a method for simultaneously retrieving aerosol and surface parameters from ground-based and satellite observations collocated in space and time. We show that a combination of down and ...up-looking observations provides sufficient measurement constraints for characterizing both aerosol and surface properties with minimal assumptions. In order to employ this concept in AERONET processing, the standard inverse algorithm Dubovik, O. & King, M. D. (2000), A flexible inversion algorithm for retrieval of aerosol optical properties from sun and sky radiance measurements.
Journal of Geophysical Research, 105, 20673–20696 has been modified to retrieve surface reflectance in addition to aerosol parameters when co-incident satellite measurements are available.
The method was applied to observations of smoke and desert dust over the Mongu (Zambia) and Solar Village (Saudi Arabia) AERONET sites respectively. The AERONET data were complemented by available observations from the MISR, MODIS, and POLDER-2 satellite sensors. The retrieved bidirectional reflectance factor (BRF) and surface albedo comparison shows good agreement between results obtained using observations from different satellites.
The robustness of the method is tested by analyzing surface albedo time series retrieved during periods of high aerosol optical depth variability and low seasonal changes in surface reflectance. The analysis shows that the performance of retrieval algorithm is stable under different aerosol loadings. It is shown that much of the observed surface albedo temporal variability could be attributed mostly to the combined uncertainty in satellite radiometric calibration and aerosol vertical distribution for Mongu and to differences in satellite angular sampling on different days for Solar Village.
The sensitivity of surface retrievals to assumptions on aerosol vertical distribution and aerosol particle shape are analyzed. It is found that the maximum error in retrieved surface albedo at 0.44 μm is 0.035 for aerosol optical depth 0.85 at 0.44 μm. For aerosol optical depths lower than ∼
0.7 the error in retrieved surface albedo is less than 0.02. Analysis of particle shape assumptions on surface retrievals showed that aerosol particle non-sphericity significantly affects the angular shape of BRF, but not the surface albedo.
Finally, the sensitivity of AERONET aerosol retrievals to uncertainty in assumed surface reflectance is analyzed by comparing aerosol retrievals obtained with different surface assumptions. It is found that the uncertainty in surface reflectance model employed in the version 1 AERONET operational algorithm is larger than was previously assumed in Dubovik, O., Smirnov, A., Holben, B. N., King, M. D., Kaufman, Y. J., Eck, T. F., & Slutsker, I. (2000), Accuracy assessment of aerosol optical properties retrieved from AERONET sun and sky radiance measurements.
Journal of Geophysical Research, 105, 9791–9806 and may have more significant effect on the retrieved aerosol properties than was documented in that work. In particular, larger errors were encountered for the real part of the refractive index (∼
0.05–0.07 increase) and maximum of the particle size distribution (∼
20% decrease) retrievals for the Mongu case, when the aerosol optical depth was relatively small (∼
0.4 at 0.44 μm). The retrieved single scattering albedo uncertainties were within the error bars (0.03) estimated in Dubovik, O., Smirnov, A., Holben, B. N., King, M. D., Kaufman, Y. J., Eck, T. F., & Slutsker, I. (2000), Accuracy assessment of aerosol optical properties retrieved from AERONET sun and sky radiance measurements.
Journal of Geophysical Research, 105, 9791–9806, with the exception of the 0.44 μm retrievals for the desert dust case when they increased by ∼
0.09 and 0.07 for low and high aerosol loadings respectively.
Samples of precipitation and atmospheric water vapor were collected together with shallow firn/ice cores as part of the new deep drilling project in northwest Greenland: the NEEM project. These ...samples were analyzed for their isotope composition to understand the processes affecting the climatic signal archived in the water stable isotope records from the NEEM deep ice core. The dominant moisture source for the snow deposited at the NEEM‐site may be originating as far south as 35°N from the western part of the Atlantic Ocean. The surface atmospheric water vapor appears in isotopic equilibrium with the snow surface indicating a large water exchange between the atmosphere and snowpack. The interannual variability of NEEM shallow firn/ice cores stable isotope data covering the last ∼40 years shows an unexpectedly weak NAO signal. Regional to global atmospheric models simulate a dominant summer precipitation in the NEEM area, suggesting that the intermittency of modern winter precipitation is responsible for the lack of a strong NAO imprint. The interannual variability of NEEM isotope data however shows a strong correlation with interannual variations of Baffin Bay sea ice cover, a relationship consistent with air mass trajectories. NEEM deep ice core isotopic records may therefore provide detailed information on past Baffin Bay sea ice extent. NEEM stable water isotope content increasing trend points to a local warming trend of ∼3.0°C over the last 40 years.
The semi-empirical, kernel-driven, linear RossThick-LiSparseReciprocal (RTLSR) Bidirectional Reflectance Distribution Function (BRDF) model is used to generate the routine MODIS BRDF/Albedo product ...due to its global applicability and the underlying physics. A challenge of this model in regard to surface reflectance anisotropy effects comes from its underestimation of the directional reflectance signatures near the Sun illumination direction; also known as the hotspot effect. In this study, a method has been developed for improving the ability of the RTLSR model to simulate the magnitude and width of the hotspot effect. The method corrects the volumetric scattering component of the RTLSR model using an exponential approximation of a physical hotspot kernel, which recreates the hotspot magnitude and width using two free parameters (C1 and C2, respectively). The approach allows one to reconstruct, with reasonable accuracy, the hotspot effect by adjusting or using the prior values of these two hotspot variables. Our results demonstrate that: (1) significant improvements in capturing hotspot effect can be made to this method by using the inverted hotspot parameters; (2) the reciprocal nature allow this method to be more adaptive for simulating the hotspot height and width with high accuracy, especially in cases where hotspot signatures are available; and (3) while the new approach is consistent with the heritage RTLSR model inversion used to estimate intrinsic narrowband and broadband albedos, it presents some differences for vegetation clumping index (CI) retrievals. With the hotspot-related model parameters determined a priori, this method offers improved performance for various ecological remote sensing applications; including the estimation of canopy structure parameters.
•We have developed a new method to refine the hotspot obtained from the MODIS BRDF retrieval.•The method uses an exponential function to correct the Ross kernel.•The method was evaluated using multi-resolution BRDF data sets.•We examined the sensitivity of the hotspot parameters in characterizing hotspot effect.•We examined this method in retrieving intrinsic albedo and clumping index values.
This study assesses the potential of satellite imagery of vertically integrated columns of dry-air mole fractions of CO2 (XCO2) to constrain the emissions from cities and power plants (called ...emission clumps) over the whole globe during 1 year. The imagery is simulated for one imager of the Copernicus mission on Anthropogenic Carbon Dioxide Monitoring (CO2M) planned by the European Space Agency and the European Commission. The width of the swath of the CO2M instruments is about 300 km and the ground horizontal resolution is about 2 km resolution. A Plume Monitoring Inversion Framework (PMIF) is developed, relying on a Gaussian plume model to simulate the XCO2 plumes of each emission clump and on a combination of overlapping assimilation windows to solve for the inversion problem. The inversion solves for the 3 h mean emissions (during 08:30–11:30 local time) before satellite overpasses and for the mean emissions during other hours of the day (over the aggregation between 00:00–08:30 and 11:30–00:00) for each clump and for the 366 d of the year. Our analysis focuses on the derivation of the uncertainty in the inversion estimates (the “posterior uncertainty”) of the clump emissions. A comparison of the results obtained with PMIF and those from a previous study using a complex 3-D Eulerian transport model for a single city (Paris) shows that the PMIF system provides the correct order of magnitude for the uncertainty reduction of emission estimates (i.e., the relative difference between the prior and posterior uncertainties). Beyond the one city or few large cities studied by previous studies, our results provide, for the first time, the global statistics of the uncertainty reduction of emissions for the full range of global clumps (differing in emission rate and spread, and distance from other major clumps) and meteorological conditions. We show that only the clumps with an annual emission budget higher than 2 MtC yr-1 can potentially have their emissions between 08:30 and 11:30 constrained with a posterior uncertainty smaller than 20 % for more than 10 times within 1 year (ignoring the potential to cross or extrapolate information between 08:30–11:30 time windows on different days). The PMIF inversion results are also aggregated in time to investigate the potential of CO2M observations to constrain daily and annual emissions, relying on the extrapolation of information obtained for 08:30–11:30 time windows during days when clouds and aerosols do not mask the plumes, based on various assumptions regarding the temporal auto-correlations of the uncertainties in the emission estimates that are used as a prior knowledge in the Bayesian framework of PMIF. We show that the posterior uncertainties of daily and annual emissions are highly dependent on these temporal auto-correlations, stressing the need for systematic assessment of the sources of uncertainty in the spatiotemporally resolved emission inventories used as prior estimates in the inversions. We highlight the difficulty in constraining the total budget ofCO2 emissions from all the cities and power plants within a country or over the globe with satellite XCO2 measurements only, and calls for integrated inversion systems that exploit multiple types of measurements.
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