ALBERT

Description: The Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) instrument on the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) spacecraft has provided global, high-resolution vertical profiles of aerosols and clouds since it became operational on 13 June 2006. On 14 June 2006, the NASA Langley Research Center (LaRC) High Spectral Resolution Lidar (HSRL) was deployed aboard the NASA Langley B-200 aircraft for the first of a series of 86 underflights of the CALIPSO satellite to provide validation measurements for the CALIOP data products. To better assess the range of conditions under which CALIOP data products are produced, these validation flights were conducted under both daytime and nighttime lighting conditions, in multiple seasons, and over a large range of latitudes and aerosol and cloud conditions. This paper presents a quantitative assessment of the CALIOP 532 nm calibration (through the 532 nm total attenuated backscatter) using internally calibrated airborne HSRL underflight data and is the most extensive study of CALIOP 532 nm calibration. Results show that HSRL and CALIOP 532 nm total attenuated backscatter agree on average within 2.7% ± 2.1% (CALIOP lower) at night and within 2.9% ± 3.9% (CALIOP lower) during the day, demonstrating the accuracy of the CALIOP 532 nm calibration algorithms. Additionally, comparisons with HSRL show consistency of the CALIOP calibration before and after the laser switch in 2009 as well as improvements in the daytime version 3.01 calibration scheme compared with the version 2 calibration scheme. Potential biases and uncertainties in the methodology relevant to validating satellite lidar measurements with an airborne lidar system are discussed and found to be less than 4.5% ± 3.2% for this validation effort with HSRL. Results from this study are also compared with prior assessments of the CALIOP 532 nm attenuated backscatter calibration.

Description: A Fast Methane Analyzer (FMA) is assessed for its applicability in a closed path eddy covariance field set-up in a peat meadow. The FMA uses off-axis integrated cavity output spectroscopy combined with a highly specific narrow band laser for the detection of CH4 and strongly reflective mirrors to obtain a laser path length of 2–20×103 m. Statistical testing and a calibration experiment showed high precision (7.8×10−3 ppb) and accuracy (

Description: We propose that cloud condensation nuclei (CCN) concentrations are important for modulating ice formation of Arctic mixed-phase clouds, through modification of the droplet size distribution. Aircraft observations from the Aerosol, Radiation, and Cloud Processes affecting Arctic Climate (ARCPAC) study in northern Alaska in April 2008 allow for identification and characterization of both aerosol and trace gas pollutants, which are then compared with cloud microphysical properties. Consistent with previous studies, we find that the concentration of precipitating ice particles (〉400 μm) is correlated with the concentration of large droplets (〉30 μm). We are further able to link the observed microphysical conditions to aerosol pollution, originating mainly from long range transport of biomass burning emissions. The case studies demonstrate that polluted mixed-phase clouds have narrower droplet size distributions and contain 1–2 orders of magnitude fewer precipitating ice particles than clean clouds at the same temperature. This suggests an aerosol indirect effect leading to greater cloud lifetime, greater cloud emissivity, and reduced precipitation. This result is opposite to the glaciation indirect effect, whereby polluted clouds are expected to precipitate more readily due to an increase in the concentration of particles acting as ice nuclei.

Description: Peroxy radicals were measured onboard two scientific aircrafts during the AMMA (African Monsoon Multidisciplinary Analysis) campaign in summer 2006. This paper reports results from the flight on 16 August 2006 during which measurements of HO2 by laser induced fluorescence spectroscopy at low pressure (LIF-FAGE) and total peroxy radicals (RO2* = HO2+ΣRO2, R = organic chain) by two similar instruments based on the peroxy radical chemical amplification (PeRCA) technique were subject of a blind intercomparison. The German DLR-Falcon and the British FAAM-BAe-146 flew wing tip to wing tip for about 30 min making concurrent measurements on 2 horizontal level runs at 697 and 485 hPa over the same geographical area in Burkina Faso. A full set of supporting measurements comprising photolysis frequencies, and relevant trace gases like CO, NO, NO2, NOy, O3 and a wider range of VOCs were collected simultaneously. Results are discussed on the basis of the characteristics and limitations of the different instruments used. Generally, no data bias are identified and the RO2* data available agree quite reasonably within the instrumental errors. The [RO2*]/[HO2] ratios, which vary between 1:1 and 3:1, as well as the peroxy radical variability, concur with variations in photolysis rates and in other potential radical precursors. Model results provide additional information about dominant radical formation and loss processes.

Description: It is generally known that managed, drained peatlands act as carbon sources. In this study we examined how mitigation through the reduction of management and through rewetting may affect the greenhouse gas (GHG) emission and the carbon balance of intensively managed, drained, agricultural peatlands. Carbon and GHG balances were determined for three peatlands in the western part of the Netherlands from 2005 to 2008 by considering spatial and temporal variability of emissions (CO2, CH4 and N2O). One area (Oukoop) is an intensively managed grass-on-peatland, including a dairy farm, with the ground water level at an average annual depth of 0.55 m below the soil surface. The second area (Stein) is an extensively managed grass-on-peatland, formerly intensively managed, with a dynamic ground water level at an average annual depth of 0.45 m below the soil surface. The third area is an (since 1998) rewetted former agricultural peatland (Horstermeer), close to Oukoop and Stein, with the average annual ground water level at a depth of 0.2 m below the soil surface. During the measurement campaigns we found that both agriculturally managed sites acted as carbon and GHG sources but the rewetted agricultural peatland acted as a carbon and GHG sink. The terrestrial GHG source strength was 1.4 kg CO2-eq m−2 yr−1 for the intensively managed area and 1.0 kg CO2-eq m−2 yr−1 for the extensively managed area; the unmanaged area acted as a GHG sink of 0.7 kg CO2-eq m−2 yr−1. Water bodies contributed significantly to the terrestrial GHG balance because of a high release of CH4 and the loss of DOC only played a minor role. Adding the farm-based CO2 and CH4 emissions increased the source strength for the managed sites to 2.7 kg CO2-eq m−2 yr−1 for Oukoop and 2.1 kg CO2-eq m−2 yr−1 for Stein. Shifting from intensively managed to extensively managed grass-on-peat reduced GHG emissions mainly because N2O emission and farm-based CH4 emissions decreased. Overall, this study suggests that managed peatlands are large sources of GHG and carbon, but, if appropriate measures are taken they can be turned back into GHG and carbon sinks within 15 yr of abandonment and rewetting.

Description: Modelling of wetland CH4 fluxes using wetland soil emission models is used to determine the size of this natural source of CH4 emission on local to global scale. Most process models of CH4 formation and soil-atmosphere CH4 transport processes operate on a plot scale. For large scale emission modelling (regional to global scale) upscaling of this type of model requires thorough analysis of the sensitivity of these models to parameter uncertainty. We applied the GLUE (Generalized Likelihood Uncertainty Analysis) methodology to a well-known CH4 emission model, the Walter-Heimann model, as implemented in the PEATLAND-VU model. The model is tested using data from two temperate wetland sites and one arctic site. The tests include experiments with different objective functions, which quantify the fit of the model results to the data. The results indicate that the model 1) in most cases is capable of estimating CH4 fluxes better than an estimate based on the data avarage, but does not clearly outcompete a regression model based on local data; 2) is capable of reproducing larger scale (seasonal) temporal variability in the data, but not the small-scale (daily) temporal variability; 3) is not strongly sensitive to soil parameters, 4) is sensitive to parameters determining CH4 transport and oxidation in vegetation, and the temperature sensitivity of the microbial population. The GLUE method also allowed testing of several smaller modifications of the original model. We conclude that upscaling of this plot-based wetland CH4 emission model is feasible, but considerable improvements of wetland CH4 modelling will result from improvement of wetland vegetation data.

Description: We propose that cloud condensation nuclei (CCN) concentrations are important for modulating ice formation of Arctic mixed-phase clouds, through modification of the droplet size distribution. Aircraft observations from the Aerosol, Radiation, and Cloud Processes affecting Arctic Climate (ARCPAC) study in northern Alaska in April 2008 allow for identification and characterization of both aerosol and trace gas pollutants, which are then compared with cloud microphysical properties. Consistent with previous studies, we find that the concentration of precipitating ice particles (〉400 μm) is correlated with the concentration of large droplets (〉30 μm). We are further able to link the observed microphysical conditions to aerosol pollution, originating mainly from long range transport of biomass burning emissions. The case studies demonstrate that polluted mixed-phase clouds have narrower droplet size distributions and contain 1–2 orders of magnitude fewer precipitating ice particles than clean clouds at the same temperature. This suggests an aerosol indirect effect leading to greater cloud lifetime, greater cloud emissivity, and reduced precipitation. This result is opposite to the glaciation indirect effect, whereby polluted clouds are expected to precipitate more readily due to an increase in the concentration of particles acting as IN.

Description: The Cloud–Aerosol Lidar with Orthogonal Polarization (CALIOP) instrument onboard the Cloud–Aerosol Lidar and Pathfinder Satellite Observations (CALIPSO) spacecraft has provided over 8 yr of nearly continuous vertical profiling of Earth's atmosphere. In this paper we investigate the V3.01 and V3.02 CALIOP 532 nm aerosol layer optical depth (AOD) product (i.e the AOD of individual layers) and the column AOD product (i.e., the sum AOD of the complete column) using an extensive database of coincident measurements. The CALIOP AOD measurements and AOD uncertainty estimates are compared with collocated AOD measurements collected with the NASA High Spectral Resolution Lidar (HSRL) in the North American and Caribbean regions. In addition, the CALIOP aerosol lidar ratios are investigated using the HSRL measurements. In general, compared with the HSRL values, the CALIOP layer AOD are biased high by less than 50% for AOD 〈 0.3 with higher errors for higher AOD. Less than 60% of the HSRL AOD measurements are encompassed within the CALIOP layer 1 SD uncertainty range (around the CALIOP layer AOD), so an error estimate is created to encompass 68% of the HSRL data. Using this new metric, the CALIOP layer AOD error is estimated using the HSRL layer AOD as ±0.035 ± 0.05 · (HSRL layer AOD) at night and ±0.05 ± 0.05 · (HSRL layer AOD) during the daytime. Furthermore, the CALIOP layer AOD error is found to correlate with aerosol loading as well as aerosol subtype, with the AODs in marine and dust layers agreeing most closely with the HSRL values. The lidar ratios used by CALIOP for polluted dust, polluted continental, and biomass burning layers are larger than the values measured by the HSRL in the CALIOP layers, and therefore the AODs for these types retrieved by CALIOP were generally too large. We estimated the CALIOP column AOD error can be expressed as ±0.05 ± 0.07 · (HSRL column AOD) at night and ±0.08 ± 0.1 · (HSRL column AOD) during the daytime. Multiple sources of error contribute to both positive and negative errors in the CALIOP column AOD, including multiple layers in the column of different aerosol types, lidar ratio errors, cloud misclassification, and undetected aerosol layers. The undetected layers were further investigated and we found that the layer detection algorithm works well at night, although undetected aerosols in the free troposphere introduce a mean underestimate of 0.02 in the column AOD in the data set examined. The decreased signal-to-noise ratio (SNR) during the daytime led to poorer performance of the layer detection. This caused the daytime CALIOP column AOD to be less accurate than during the nighttime, because CALIOP frequently does not detect optically thin aerosol layers with AOD 〈 0.1. Given that the median vertical extent of aerosol detected within any column was 1.6 km during the nighttime and 1.5 km during the daytime, we can estimate the minimum extinction detection threshold to be 0.012 km−1 at night and 0.067 km−1 during the daytime in a layer median sense. This extensive validation of level 2 CALIOP AOD products extends previous validation studies to nighttime lighting conditions and provides independent measurements of the lidar ratio; thus, allowing the assessment of the effect on the CALIOP AOD of using inappropriate lidar ratio values in the extinction retrieval.

Description: An intercomparison is made of the Net Ecosystem Exchange of CO2, NEE, for eight Dutch grassland sites: four natural grasslands, two production grasslands and two meteorological stations within a rotational grassland region. At all sites the NEE was determined during at least 10 months per site, using the eddy-covariance (EC) technique, but in different years. The NEE does not include any import or export other than CO2. The photosynthesis-light response analysis technique is used along with the respiration-temperature response technique to partition NEE into Gross Primary Production (GPP) and Ecosystem Respiration (Re) and to obtain the eco-physiological characteristics of the sites at the field scale. Annual sums of NEE, GPP and Re are then estimated using the fitted response curves with observed radiation and air temperature from a meteorological site in the centre of The Netherlands as drivers. These calculations are carried out for four years (2002–2005). Land use and management histories are not considered. The estimated annual Re for all individual sites is more or less constant per site and the average for all sites amounts to 1390±30 gC m−2 a−1. The narrow uncertainty band (±2%) reflects the small differences in the mean annual air temperature. The mean annual GPP was estimated to be 1325 g C m−2 a−1, and displays a much higher standard deviation, of ±110 gC m−2 a−1 (8%), which reflects the relatively large variation in annual solar radiation. The mean annual NEE amounts to –65±85 gC m−2 a−1. From two sites, four-year records of CO2 flux were available and analyzed (2002–2005). Using the weather record of 2005 with optimizations from the other years, the standard deviation of annual GPP was estimated to be 171–206 gC m−2 a−1 (8–14%), of annual Re 227–247 gC m−2 a−1 (14–16%) and of annual NEE 176–276 gC m−2 a−1. The inter-site standard deviation was higher for GPP and Re, 534 gC m−2 a−1 (37.3%) and 486 gC m−2 a−1 (34.8%), respectively. However, the inter-site standard deviation of NEE was similar to the interannual one, amounting to 207 gC m−2 a−1. Large differences occur due to soil type. The grasslands on organic (peat) soils show a mean net release of CO2 of 220±90 g C m−2 a−1 while the grasslands on mineral (clay and sand) soils show a mean net uptake of CO2 of 90±90 g C m−2 a−1. If a weighing with the fraction of grassland on organic (20%) and mineral soils (80%) is applied, an average NEE of 28 ±90 g C m−2 a−1 is found. The results from the analysis illustrate the need for regionally specific and spatially explicit CO2 emission estimates from grassland.

Description: Modelling of wetland CH4 fluxes using wetland soil emission models is used to determine the size of this natural source of CH4 emission on local to global scale. Most process models of CH4 formation and soil-atmosphere CH4 transport processes operate on a plot scale. For large scale emission modelling (regional to global scale) upscaling of this type of model requires thorough analysis of the sensitivity of these models to parameter uncertainty. We applied the GLUE (Generalized Likelihood Uncertainty Analysis) methodology to a well-known CH4 emission model, the Walter-Heimann model, as implemented in the PEATLAND-VU model. The model is tested using data from two temperate wetland sites and one arctic site. The tests include experiments with different objective functions, which quantify the fit of the model results to the data. The results indicate that the model 1) in most cases is capable of estimating CH4 fluxes better than an estimate based on the data avarage, but does not clearly outcompete a regression model based on local data; 2) is capable of reproducing larger scale (seasonal) temporal variability in the data, but not the small-scale (daily) temporal variability; 3) is not strongly sensitive to soil parameters, 4) is sensitive to parameters determining CH4 transport and oxidation in vegetation, and the temperature sensitivity of the microbial population. The GLUE method also allowed testing of several smaller modifications of the original model. We conclude that upscaling of this plot-based wetland CH4 emission model is feasible, but considerable improvements of wetland CH4 modelling will result from improvement of wetland vegetation data.