ALBERT

Description: Two approaches are used to characterize how accurately the North Alabama Lightning Mapping Array (LMA) is able to locate lightning VHF sources in space and in time. The first method uses a Monte Carlo computer simulation to estimate source retrieval errors. The simulation applies a VHF source retrieval algorithm that was recently developed at the NASA-MSFC and that is similar, but not identical to, the standard New Mexico Tech retrieval algorithm. The second method uses a purely theoretical technique (i.e., chi-squared Curvature Matrix theory) to estimate retrieval errors. Both methods assume that the LMA system has an overall rms timing error of 50ns, but all other possible errors (e.g., multiple sources per retrieval attempt) are neglected. The detailed spatial distributions of retrieval errors are provided. Given that the two methods are completely independent of one another, it is shown that they provide remarkably similar results, except that the chi-squared theory produces larger altitude error estimates than the (more realistic) Monte Carlo simulation.

Description: Two approaches are used to characterize how accurately the North Alabama Lightning Mapping Array (LMA) is able to locate lightning VHF sources in space and in time. The first method uses a Monte Carlo computer simulation to estimate source retrieval errors. The simulation applies a VHF source retrieval algorithm that was recently developed at the NASA-MSFC and that is similar, but not identical to, the standard New Mexico Tech retrieval algorithm. The second method uses a purely theoretical technique (i.e., chi-squared Curvature Matrix theory) to estimate retrieval errors. Both methods assume that the LMA system has an overall rms timing error of 50ns, but all other possible errors (e.g., multiple sources per retrieval attempt) are neglected. The detailed spatial distributions of retrieval errors are provided. Given that the two methods are completely independent of one another, it is shown that they provide remarkably similar results, except that the chi-squared theory produces larger altitude error estimates than the (more realistic) Monte Carlo simulation.

Description: Warming experiments are increasingly relied on to estimate plant responses to global climate change. For experiments to provide meaningful predictions of future responses, they should reflect the empirical record of responses to temperature variability and recent warming, including advances in the timing of flowering and leafing. We compared phenology (the timing of recurring life history events) in observational studies and warming experiments spanning four continents and 1,634 plant species using a common measure of temperature sensitivity (change in days per degree Celsius). We show that warming experiments underpredict advances in the timing of flowering and leafing by 8.5-fold and 4.0-fold, respectively, compared with long-term observations. For species that were common to both study types, the experimental results did not match the observational data in sign or magnitude. The observational data also showed that species that flower earliest in the spring have the highest temperature sensitivities, but this trend was not reflected in the experimental data. These significant mismatches seem to be unrelated to the study length or to the degree of manipulated warming in experiments. The discrepancy between experiments and observations, however, could arise from complex interactions among multiple drivers in the observational data, or it could arise from remediable artefacts in the experiments that result in lower irradiance and drier soils, thus dampening the phenological responses to manipulated warming. Our results introduce uncertainty into ecosystem models that are informed solely by experiments and suggest that responses to climate change that are predicted using such models should be re-evaluated.

Description: Crop models are essential tools for assessing the threat of climate change to local and global food production. Present models used to predict wheat grain yield are highly uncertain when simulating how crops respond to temperature. Here we systematically tested 30 different wheat crop models of the Agricultural Model Intercomparison and Improvement Project against field experiments in which growing season mean temperatures ranged from 15 degrees C to 32 degrees C, including experiments with artificial heating. Many models simulated yields well, but were less accurate at higher temperatures. The model ensemble median was consistently more accurate in simulating the crop temperature response than any single model, regardless of the input information used. Extrapolating the model ensemble temperature response indicates that warming is already slowing yield gains at a majority of wheat-growing locations. Global wheat production is estimated to fall by 6% for each degree C of further temperature increase and become more variable over space and time.

Description: Vertical profiles of stratospheric HOCl calculated with a diurnal steady-state photochemical model that uses currently recommended reaction rates and photolysis cross sections underestimate observed profiles of HOCl obtained by two balloon-borne instruments, FIRS-2 (a far-infrared emission spectrometer) and MkIV (a mid-infrared, solar absorption spectrometer). Considerable uncertainty (a factor of two) persists in laboratory measurements of the rate constant (k(sub 1)) for the reaction ClO + HO2 yields HOCl + O2. Agreement between modeled and measured HOCl can be attained using a value of k(sub 1) from Stimpfle et al. (1979) that is about a factor-of-two faster than the currently recommended rate constant. Comparison of modeled and measured HOCl suggests that models using the currently recommended value for k(sub 1) may underestimate the role of the HOCl catalytic cycle for ozone depletion, important in the midlatitude lower stratosphere.

Description: This paper describes the retrievals algorithm used to determine temperature and height from radiance measurements by the Microwave Limb Sounder on EOS Aura. MLS is a "limbscanning" instrument, meaning that it views the atmosphere along paths that do not intersect the surface - it actually looks forwards from the Aura satellite. This means that the temperature retrievals are for a "profile" of the atmosphere somewhat ahead of the satellite. Because of the need to view a finite sample of the atmosphere, the sample spans a box about 1.5km deep and several tens of kilometers in width; the optical characteristics of the atmosphere mean that the sample is representative of a tube about 200-300km long in the direction of view. The retrievals use temperature analyses from NASA's Goddard Earth Observing System, Version 5 (GEOS-5) data assimilation system as a priori states. The temperature retrievals are somewhat deperrde~zt on these a priori states, especially in the lower stratosphere. An important part of the validation of any new dataset involves comparison with other, independent datasets. A large part of this study is concerned with such comparisons, using a number of independent space-based measurements obtained using different techniques, and with meteorological analyses. The MLS temperature data are shown to have biases that vary with height, but also depend on the validation dataset. MLS data are apparently biased slightly cold relative to correlative data in the upper troposphere and slightly warm in the middle stratosphere. A warm MLS bias in the upper stratosphere may be due to a cold bias in GEOS-5 temperatures.

Description: NASA Cloud Aerosol Lidar with Orthogonal Polarization (CALIOP) Version 3.01 5-km nighttime 0.532 micron aerosol optical depth (AOD) datasets from 2007 are screened, averaged and evaluated at 1 deg X 1 deg resolution versus corresponding/co-incident 0.550 micron AOD derived using the US Navy Aerosol Analysis and Prediction System (NAAPS), featuring two-dimensional variational assimilation of quality-assured NASA Moderate Resolution Imaging Spectroradiometer (MODIS) and Multi-angle Imaging Spectroradiometer (MISR) AOD. In the absence of sunlight, since passive radiometric AOD retrievals rely overwhelmingly on scattered radiances, the model represents one of the few practical global estimates available from which to attempt such a validation. Daytime comparisons, though, provide useful context. Regional-mean CALIOP vertical profiles of night/day 0.532 micron extinction coefficient are compared with 0.523/0.532 micron ground-based lidar measurements to investigate representativeness and diurnal variability. In this analysis, mean nighttime CALIOP AOD are mostly lower than daytime (0.121 vs. 0.126 for all aggregated data points, and 0.099 vs. 0.102 when averaged globally per normalised 1 deg. X 1 deg. bin), though the relationship is reversed over land and coastal regions when the data are averaged per normalised bin (0.134/0.108 vs. 0140/0.112, respectively). Offsets assessed within single bins alone approach +/- 20 %. CALIOP AOD, both day and night, are higher than NAAPS over land (0.137 vs. 0.124) and equal over water (0.082 vs. 0.083) when averaged globally per normalised bin. However, for all data points inclusive, NAAPS exceeds CALIOP over land, coast and ocean, both day and night. Again, differences assessed within single bins approach 50% in extreme cases. Correlation between CALIOP and NAAPS AOD is comparable during both day and night. Higher correlation is found nearest the equator, both as a function of sample size and relative signal magnitudes inherent at these latitudes. Root mean square deviation between CALIOP and NAAPS varies between 0.1 and 0.3 globally during both day/night. Averaging of CALIOP along-track AOD data points within a single NAAPS grid bin improves correlation and RMSD, though day/night and land/ocean biases persist and are believed systematic. Vertical profiles of extinction coefficient derived in the Caribbean compare well with ground-based lidar observations, though potentially anomalous selection of a priori lidar ratios for CALIOP retrievals is likely inducing some discrepancies. Mean effective aerosol layer top heights are stable between day and night, indicating consistent layer-identification diurnally, which is noteworthy considering the potential limiting effects of ambient solar noise during day.

Description: Plasma outflows, escaping from Earth through the high-altitude polar caps into the tail of the magnetosphere, have been observed with a xenon plasma source instrument to reduce the floating potential of the POLAR spacecraft. The largest component of H(+) flow, along the local magnetic field (30 to 60 kilometers per second), is faster than predicted by theory. The flows contain more O(+) than predicted by theories of thermal polar wind, but also have elevated ion temperatures. These plasma outflows contribute to the plasmas energized in the elongated nightside tail of the magnetosphere, creating auroras, substorms, and storms. They also constitute an appreciable loss of terrestrial water dissociation products into space.

Description: Ozone changes and associated climate impacts in the Coupled Model Intercomparison Project Phase 5 (CMIP5) simulations are analyzed over the historical (1960-2005) and future (2006-2100) period under four Representative Concentration Pathways (RCP). In contrast to CMIP3, where half of the models prescribed constant stratospheric ozone, CMIP5 models all consider past ozone depletion and future ozone recovery. Multimodel mean climatologies and long-term changes in total and tropospheric column ozone calculated from CMIP5 models with either interactive or prescribed ozone are in reasonable agreement with observations. However, some large deviations from observations exist for individual models with interactive chemistry, and these models are excluded in the projections. Stratospheric ozone projections forced with a single halogen, but four greenhouse gas (GHG) scenarios show largest differences in the northern midlatitudes and in the Arctic in spring (approximately 20 and 40 Dobson units (DU) by 2100, respectively). By 2050, these differences are much smaller and negligible over Antarctica in austral spring. Differences in future tropospheric column ozone are mainly caused by differences in methane concentrations and stratospheric input, leading to approximately 10DU increases compared to 2000 in RCP 8.5. Large variations in stratospheric ozone particularly in CMIP5 models with interactive chemistry drive correspondingly large variations in lower stratospheric temperature trends. The results also illustrate that future Southern Hemisphere summertime circulation changes are controlled by both the ozone recovery rate and the rate of GHG increases, emphasizing the importance of simulating and taking into account ozone forcings when examining future climate projections.

Description: As part of the Atmospheric Chemistry and Climate Model Intercomparison Project (ACCMIP), we evaluate the historical black carbon (BC) aerosols simulated by 8 ACCMIP models against observations including 12 ice core records, long-term surface mass concentrations, and recent Arctic BC snowpack measurements. We also estimate BC albedo forcing by performing additional simulations using offline models with prescribed meteorology from 1996-2000. We evaluate the vertical profile of BC snow concentrations from these offline simulations using the recent BC snowpack measurements. Despite using the same BC emissions, the global BC burden differs by approximately a factor of 3 among models due to differences in aerosol removal parameterizations and simulated meteorology: 34 Gg to 103 Gg in 1850 and 82 Gg to 315 Gg in 2000. However, the global BC burden from preindustrial to present-day increases by 2.5-3 times with little variation among models, roughly matching the 2.5-fold increase in total BC emissions during the same period.We find a large divergence among models at both Northern Hemisphere (NH) and Southern Hemisphere (SH) high latitude regions for BC burden and at SH high latitude regions for deposition fluxes. The ACCMIP simulations match the observed BC surface mass concentrations well in Europe and North America except at Ispra. However, the models fail to predict the Arctic BC seasonality due to severe underestimations during winter and spring. The simulated vertically resolved BC snow concentrations are, on average, within a factor of 2-3 of the BC snowpack measurements except for Greenland and the Arctic Ocean. For the ice core evaluation, models tend to adequately capture both the observed temporal trends and the magnitudes at Greenland sites. However, models fail to predict the decreasing trend of BC depositions/ice core concentrations from the 1950s to the 1970s in most Tibetan Plateau ice cores. The distinct temporal trend at the Tibetan Plateau ice cores indicates a strong influence from Western Europe, but the modeled BC increases in that period are consistent with the emission changes in Eastern Europe, the Middle East, South and East Asia. At the Alps site, the simulated BC suggests a strong influence from Europe, which agrees with the Alps ice core observations. At Zuoqiupu on the Tibetan Plateau, models successfully simulate the higher BC concentrations observed during the non-monsoon season compared to the monsoon season but overpredict BC in both seasons. Despite a large divergence in BC deposition at two Antarctic ice core sites, some models with a BC lifetime of less than 7 days are able to capture the observed concentrations. In 2000 relative to 1850, globally and annually averaged BC surface albedo forcing from the offline simulations ranges from 0.014 to 0.019Wm2 among the ACCMIP models. Comparing offline and online BC albedo forcings computed by some of the same models, we find that the global annual mean can vary by up to a factor of two because of different aerosol models or different BC-snow parameterizations and snow cover. The spatial distributions of the offline BC albedo forcing in 2000 show especially high BC forcing (i.e., over 0.1W/sq. m) over Manchuria, Karakoram, and most of the Former USSR. Models predict the highest global annual mean BC forcing in 1980 rather than 2000, mostly driven by the high fossil fuel and biofuel emissions in the Former USSR in 1980.