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The Atmospheric Infrared Sounder (AIRS) and the Infrared Atmospheric Sounding Interferometer (IASI), together with the future Cross-track Infrared Sounder, will provide long-term hyperspectral measurements of the earth and its atmosphere at ~10 km spatial resolution. Quantifying the radiometric difference between AIRS and IASI is crucial for creating fundamental climate data records and establishing the space-based infrared calibration standard. Since AIRS and IASI have different local equator crossing times, a direct comparison of these two instruments over the tropical regions is not feasible. Using the Geostationary Operational Environmental Satellite (GOES) imagers as transfer radiometers, this study compares AIRS and IASI over warm scenes in the tropical regions for a time period of 16 months. The double differences between AIRS and IASI radiance biases relative to the GOES-11 and -12 imagers are used to quantify the radiance differences between AIRS and IASI within the GOES imager spectral channels. The results indicate that, at the 95% confidence level, the mean values of the IASI - AIRS brightness temperature differences for warm scenes are very small, that is, -0.0641 [+ or -] 0.0074 K, -0.0432 [+ or -] 0.0114 K, and -0.0095 [+ or -] 0.0151 K for the GOES-11 6.7-, 10.7-, and 12.0-[micro]m channels, respectively, and -0.0490 [+ or -] 0.0100 K, -0.0419 [+ or -] 0.0224 K, and -0.0884 [+ or -] 0.0160 K for the GOES-12 6.5-, 10.7-, and 13.3-[micro]m channels, respectively. The brightness temperature biases between AIRS and IASI within the GOES imager spectral range are less than 0.1 K although the AIRS measurements are slightly warmer than those of IASI. DOI: 10.1175/2009JAMC2218.1

To authenticate to the full-text of this article, please visit this link: http://dx.doi.org/10.1111/j.1365-2745.2009.01523.x Byline: Jonathan M. Adams (1), Yangjian Zhang (2) Keywords: folivory; herbivore; insect; latitude; North America; temperate forest; temperature Abstract: Summary 1. It is generally believed that warmer climate forests suffer more herbivory, as a proportion of leaf area, than cooler climate forests. However, standardized studies using the same methodology have rarely been performed. 2. We carried out a study on scattered forest-edge populations of four widespread tree species (Quercus alba, Acer rubrum, Fagus grandifolia and Liquidambar styraciflua) spanning 17[degrees] of latitude in North America. 3. We sampled early summer sun leaves (12 weeks after bud break) at each latitude in 2 years. Total insect folivory damage was estimated from the percentage area damaged in fresh leaves on forest edges, using a scanner-linked software. 4. The percentage area damage per leaf of all four species in both years shows a significant latitudinal trend, with less damage in lower latitude areas of eastern North America. This is contrary to what would generally be expected according to current ecological thinking. Among the four studied species, only A. rubrum showed a significant difference between the 2 years. 5. Synthesis. The observation of an inverse latitudinal trend may have wider implications for the study of community functioning, suggesting that strength of 'biotic' interaction between plants and herbivores might actually be no less important, or in fact more important, in cool temperate climates compared with warm temperate climates. Author Affiliation: (1)Department of Biological Sciences, Rutgers University, Newark, NJ 07102, USA (2)Department of Ecology, Evolution, & Natural Resources, School of Environmental & Biological Sciences, Rutgers University, New Brunswick, NJ 08901-8551, USA Article History: Received 9 September 2008; accepted 1 May 2009 Handling Editor: Martin Heil Article note: (*) Correspondence author. E-mail: zhangyang@crssa.rutgers.edu

Studies in the past several years have documented the climatology of warm-season precipitation-episode statistics (propagation speed, span, and duration) over the United States using a national composited radar dataset. These climatological studies have recently been extended to other continents, including Asia, Africa, and Australia. However, continental regions outside the United States have insufficient radar coverage, and the newer studies have had to rely on geostationary satellite data at infrared (IR) frequencies as a proxy for rainfall. It is well known that the use of IR brightness temperatures to infer rainfall is subject to large errors. In this study, the statistics of warm-season precipitation episodes derived from radar and satellite IR measurements over the United States are compared and biases introduced by the satellite data are evaluated. It is found that the satellite span and duration statistics are highly dependent upon the brightness temperature threshold used but with the appropriate choices of thresholds can be brought into good agreement with those based upon radar data. The propagation-speed statistics of satellite events are on average -4 m [s.sup.-1] faster than radar events and are relatively insensitive to the brightness temperature threshold. A simple correction procedure based upon the difference between the steering winds for the precipitation core and the winds at the level of maximum anvil outflow is developed.

The diurnal cycle of outgoing longwave radiation (OLR) computed by a climate model provides a powerful test of the numerical description of various physical processes. Diurnal cycles of OLR computed by version 3 of the Hadley Centre Atmospheric Model (HadAM3) are compared with those observed by the Earth Radiation Budget Satellite (ERBS) for the boreal summer season (June-August). The ERBS observations cover the domain from 55[degrees]S to 55[degrees]N. To compare the observed and modeled diurnal cycles, the principal component (PC) analysis method is used over this domain. The analysis is performed separately for the land and ocean regions. For land over this domain, the diurnal cycle computed by the model has a root-mean-square (RMS) of 11.4 W [m.sup.-2], as compared with 13.3 W [m.sup.-2] for ERBS. PC-1 for ERBS observations and for the model are similar, but the ERBS result has a peak near 1230 LST and decreases very slightly during night, whereas the peak of the model result is an hour later and at night the OLR decreases by 7 W [m.sup.-2] between 2000 and 0600 LST. Some of the difference between the ERBS and model results is due to the computation of convection too early in the afternoon by the model. PC-2 describes effects of morning/afternoon cloudiness on OLR, depending on the sign. Over ocean in the ERBS domain, the model RMS of the OLR diurnal cycle is 2.8 W [m.sup.-2], as compared with 5.9 W [m.sup.-2] for ERBS. Also, for the model, PC-1 accounts for 66% of the variance, while for ERBS, PC-1 accounts for only 16% of the variance. Thus, over ocean, the ERBS results show a greater variety of OLR diurnal cycles than the model does.

A new approach, called transferability intercomparisons, is described for advancing both understanding and modeling of the global water cycle and energy budget. Under this approach, individual regional climate models perform simulations with all modeling parameters and parameterizations held constant over a specific period on several prescribed domains represent ing different climatic regions. The transferability framework goes beyond previous regional climate model intercomparisons to provide a global method for testing and improving model parameterizations by constraining the simulations within analyzed boundaries for several domains. Transferability intercomparisons expose the limits of our current regional modeling capacity by examining model accuracy on a wide range of climate conditions and realizations. Intercomparison of these individual model experiments provides a means for evaluating strengths and weaknesses of models outside their 'home domains' (domain of development and testing). Reference sites that are conducting coordinated measurements under the continental-scale experiments under the Global Energy and Water Cycle Experiment (GEWEX) Hydrometeorology Panel provide data for evaluation of model abilities to simulate specific features of the water and energy cycles. A systematic intercomparison across models and domains more clearly exposes collective biases in the modeling process. By isolating particular regions and processes, regional model transferability intercomparisons can more effectively explore the spatial and temporal heterogeneity of predictability. A general improvement of model ability to simulate diverse climates will provide more confidence that models used for future climate scenarios might be able to simulate conditions on a particular domain that are beyond the range of previously observed climates.