ALBERT

Description: Climate models are deterministic, mathematical descriptions of the physics of climate. Confidence in predictions of future climate is increased if the physics are verifiably correct. A necessary, (but not sufficient) condition is that past and present climate be simulated well. Quantify the likelihood that a (summary statistic computed from a) set of observations arises from a physical system with the characteristics captured by a model generated time series. Given a prior on models, we can go further: posterior distribution of model given observations.

Description: The El Nino-Southern Oscillation (ENSO) is the dominant mode of tropical variability on interannual time scales. ENSO appears to extend its influence into the chemical composition of the tropical troposphere. Recent work has revealed an ENSO-induced wave-1 anomaly in observed tropical tropospheric column ozone. This results in a dipole over the western and eastern tropical Pacific, whereby differencing the two regions produces an ozone anomaly with an extremely high correlation to the Nino 3.4 Index. We have successfully reproduced this feature using the Goddard Earth Observing System Version 5 (GEOS-5) general circulation model coupled to a comprehensive stratospheric and tropospheric chemical mechanism forced with observed sea surface temperatures over the past 25 years. An examination of the modeled ozone field reveals the vertical contributions of tropospheric ozone to the column over the western and eastern Pacific region. We will show composition sensitivity in observations from NASA s Aura satellite Microwave Limb Sounder (MLS) and the Tropospheric Emissions Spectrometer (TES) and a simulation to provide insight into the vertical structure of these ENSO-induced ozone changes. The ozone changes due to the Quasi-Biennial Oscillation (QBO) in the extra-polar upper troposphere and lower stratosphere in MLS measurements will also be discussed.

Description: AIRS/AMSU is the state of the art infrared and microwave atmospheric sounding system flying aboard EOS Aqua. The Goddard DISC has analyzed AIRS/AMSU observations, covering the period September 2002 until the present, using the AIRS Science Team Version-S retrieval algorithm. These products have been used by many researchers to make significant advances in both climate and weather applications. The AIRS Science Team Version-6 Retrieval, which will become operation in mid-20l2, contains many significant theoretical and practical improvements compared to Version-5 which should further enhance the utility of AIRS products for both climate and weather applications. In particular, major changes have been made with regard to the algOrithms used to 1) derive surface skin temperature and surface spectral emissivity; 2) generate the initial state used to start the retrieval procedure; 3) compute Outgoing Longwave Radiation; and 4) determine Quality Control. This paper will describe these advances found in the AIRS Version-6 retrieval algorithm and demonstrate the improvement of AIRS Version-6 products compared to those obtained using Version-5,

Description: Titan's thick atmosphere and volatile surface cause it to respond to big impacts like the one that produced the prominent Menrva impact basin in a somewhat Earth-like manner. Menrva was big enough to raise the surface temperature by 100 K. If methane in the regolith is generally as abundant as it was at the Huygens landing site, Menrva would have been big enough to double the amount of methane in the atmosphere. The extra methane would have drizzled out of the atmosphere over hundreds of years. Conditions may have been favorable for clathrating volatiles such as ethane. Impacts can also create local crater lakes set in warm ice but these quickly sink below the warm ice; whether the cryptic waters quickly freeze by mixing with the ice crust or whether they long endure under the ice remains a open question. Bigger impacts can create shallow liquid water oceans at the surface. If Titan's crust is made of water ice, the putative Hotei impact (a possible 800-1200 km diameter basin, Soderblom et al 2009) would have raised the average surface temperature to 350-400 K. Water rain would have fallen and global meltwaters would have averaged 50 m to as much as 500 m deep. The meltwaters may not have lasted more than a few decades or centuries at most, but are interesting to consider given Titan's organic wealth.

Description: The present study aims at assessing a possible new way to reveal the properties of lightning flash, using spectrophotometric data obtained by FORMOSAT-2/ISUAL which is the first spaceborne multicolor lightning detector. The ISUAL data was analyzed in conjunction with ground ]based electromagnetic data obtained by Duke magnetic field sensors, NLDN, North Alabama Lightning Mapping Array (LMA), and Kennedy Space Center (KSC) electric field antennas. We first classified the observed events into cloud ]to ]ground (CG) and intra ]cloud (IC) lightning based on the Duke and NLDN measurements and analyzed ISUAL data to clarify their optical characteristics. It was found that the ISUAL optical waveform of CG lightning was strongly correlated with the current moment waveform, suggesting that it is possible to evaluate the electrical properties of lightning from satellite optical measurement to some extent. The ISUAL data also indicated that the color of CG lightning turned to red at the time of return stroke while the color of IC pulses remained unchanged. Furthermore, in one CG event which was simultaneously detected by ISUAL and LMA, the observed optical emissions slowly turned red as the altitude of optical source gradually decreased. All of these results indicate that the color of lightning flash depends on the source altitude and suggest that spaceborne optical measurement could be a new tool to discriminate CG and IC lightning. In the presentation, we will also show results on the comparison between the ISUAL and KSC electric field data to clarify characteristics of each lightning process such as preliminary breakdown, return stroke, and subsequent upward illumination.

Description: An 8-10 station Lightning Mapping Array (LMA) network is being deployed in the vicinity of Sao Paulo to create the SP-LMA for total lightning measurements in association with the international CHUVA [Cloud processes of the main precipitation systems in Brazil: A contribution to cloud resolving modeling and to the GPM (Global Precipitation Measurement)] field campaign. Besides supporting CHUVA science/mission objectives and the Sao Luiz do Paraitinga intensive operation period (IOP) in November-December 2011, the SP-LMA will support the generation of unique proxy data for the Geostationary Lightning Mapper (GLM) and Advanced Baseline Imager (ABI), both sensors on the NOAA Geostationary Operational Environmental Satellite-R (GOES-R), presently under development and scheduled for a 2015 launch. The proxy data will be used to develop and validate operational algorithms so that they will be ready for use on "day1" following the launch of GOES-R. A preliminary survey of potential sites in the vicinity of Sao Paulo was conducted in December 2009 and January 2010, followed up by a detailed survey in July 2010, with initial network deployment scheduled for October 2010. However, due to a delay in the Sao Luiz do Paraitinga IOP, the SP-LMA will now be installed in July 2011 and operated for one year. Spacing between stations is on the order of 15-30 km, with the network "diameter" being on the order of 30-40 km, which provides good 3-D lightning mapping 150 km from the network center. Optionally, 1-3 additional stations may be deployed in the vicinity of Sao Jos dos Campos.

Description: The lightning jump algorithm has a robust history in correlating upward trends in lightning to severe and hazardous weather occurrence. The algorithm uses the correlation between the physical principles that govern an updraft's ability to produce microphysical and kinematic conditions conducive for electrification and its role in the development of severe weather conditions. Recent work has demonstrated that the lightning jump algorithm concept holds significant promise in the operational realm, aiding in the identification of thunderstorms that have potential to produce severe or hazardous weather. However, a large amount of work still needs to be completed in spite of these positive results. The total lightning jump algorithm is not a stand-alone concept that can be used independent of other meteorological measurements, parameters, and techniques. For example, the algorithm is highly dependent upon thunderstorm tracking to build lightning histories on convective cells. Current tracking methods show that thunderstorm cell tracking is most reliable and cell histories are most accurate when radar information is incorporated with lightning data. In the absence of radar data, the cell tracking is a bit less reliable but the value added by the lightning information is much greater. For optimal application, the algorithm should be integrated with other measurements that assess storm scale properties (e.g., satellite, radar). Therefore, the recent focus of this research effort has been assessing the lightning jump's relation to thunderstorm tracking, meteorological parameters, and its potential uses in operational meteorology. Furthermore, the algorithm must be tailored for the optically-based GOES-R Geostationary Lightning Mapper (GLM), as what has been observed using Very High Frequency Lightning Mapping Array (VHF LMA) measurements will not exactly translate to what will be observed by GLM due to resolution and other instrument differences. Herein, we present some of the promising aspects and challenges encountered in utilizing objective tracking and GLM proxy data, as well as recent results that demonstrate the value added information gained by combining the lightning jump concept with traditional meteorological measurements.

Description: The Short-term Prediction Research and Transition (SPoRT) Center is a collaborative partnership between NASA and operational forecasting partners, including a number of National Weather Service forecast offices. SPoRT provides real-time NASA products and capabilities to help its partners address specific operational forecast challenges. One challenge that forecasters face is using guidance from local and regional deterministic numerical models configured at convection-allowing resolution to help assess a variety of mesoscale/convective-scale phenomena such as sea-breezes, local wind circulations, and mesoscale convective weather potential on a given day. While guidance from convection-allowing models has proven valuable in many circumstances, the potential exists for model improvements by incorporating more representative land-water surface datasets, and by assimilating retrieved temperature and moisture profiles from hyper-spectral sounders. In order to help increase the accuracy of deterministic convection-allowing models, SPoRT produces real-time, 4-km CONUS forecasts using a configuration of the Weather Research and Forecasting (WRF) model (hereafter SPoRT-WRF) that includes unique NASA products and capabilities including 4-km resolution soil initialization data from the Land Information System (LIS), 2-km resolution SPoRT SST composites over oceans and large water bodies, high-resolution real-time Green Vegetation Fraction (GVF) composites derived from the Moderate-resolution Imaging Spectroradiometer (MODIS) instrument, and retrieved temperature and moisture profiles from the Atmospheric Infrared Sounder (AIRS) and Infrared Atmospheric Sounding Interferometer (IASI). NCAR's Model Evaluation Tools (MET) verification package is used to generate statistics of model performance compared to in situ observations and rainfall analyses for three months during the summer of 2012 (June-August). Detailed analyses of specific severe weather outbreaks during the summer will be presented to assess the potential added-value of the SPoRT datasets and data assimilation methodology compared to a WRF configuration without the unique datasets and data assimilation.

Description: Global Precipitation Measurement (GPM) is an international satellite mission to provide nextgeneration observations of rain and snow worldwide every three hours. NASA and the Japan Aerospace Exploration Agency (JAXA) will launch a "Core" satellite carrying advanced instruments that will set a new standard for precipitation measurements from space. The data they provide will be used to unify precipitation measurements made by an international network of partner satellites to quantify when, where, and how much it rains or snows around the world. The GPM mission will help advance our understanding of Earth's water and energy cycles, improve the forecasting of extreme events that cause natural disasters, and extend current capabilities of using satellite precipitation information to directly benefit society. Building upon the successful legacy of the Tropical Rainfall Measuring Mission (TRMM), GPM's next-generation global precipitation data will lead to scientific advances and societal benefits within a range of hydrologic fields including natural hazards, ecology, public health and water resources. This talk will highlight some examples from TRMM's IS-year history within these applications areas as well as discuss some existing challenges and present a look forward for GPM's contribution to applications in hydrology.

Description: We present an investigation on multi-decadal changes of atmospheric aerosols and their effects on surface radiation using a global chemistry transport model along with the near-term to long-term data records. We focus on a 28-year time period of satellite era from 1980 to 2007, during which a suite of aerosol data from satellite observations and ground-based remote sensing and in-situ measurements have become available. We analyze the long-term global and regional aerosol optical depth and concentration trends and their relationship to the changes of emissions" and assess the role aerosols play in the multi-decadal change of solar radiation reaching the surface (known as "dimming" or "brightening") at different regions of the world, including the major anthropogenic source regions (North America, Europe, Asia) that have been experiencing considerable changes of emissions, dust and biomass burning regions that have large interannual variabilities, downwind regions that are directly affected by the changes in the source area, and remote regions that are considered to representing "background" conditions.

Description: Continental-scale offline simulations with a land surface model are used to address two important issues in the forecasting of large-scale seasonal streamflow: (i) the extent to which errors in soil moisture initialization degrade streamflow forecasts, and (ii) the extent to which the downscaling of seasonal precipitation forecasts, if it could be done accurately, would improve streamflow forecasts. The reduction in streamflow forecast skill (with forecasted streamflow measured against observations) associated with adding noise to a soil moisture field is found to be, to first order, proportional to the average reduction in the accuracy of the soil moisture field itself. This result has implications for streamflow forecast improvement under satellite-based soil moisture measurement programs. In the second and more idealized ("perfect model") analysis, precipitation downscaling is found to have an impact on large-scale streamflow forecasts only if two conditions are met: (i) evaporation variance is significant relative to the precipitation variance, and (ii) the subgrid spatial variance of precipitation is adequately large. In the large-scale continental region studied (the conterminous United States), these two conditions are met in only a somewhat limited area.

Description: Research has shown that the snow season in the Northern Hemisphere has been getting shorter in recent decades, consistent with documented global temperature increases. Specifically, the snow is melting earlier in the spring allowing for a longer growing season and associated land-cover changes. Here we focus on North America. Using the Moderate-Resolution Imaging Radiometer (MODIS) cloud-gap-filled standard snow-cover data product we can detect a trend toward earlier spring snowmelt in the approx 12 years since the MODIS launch. However, not all areas in North America show earlier spring snowmelt over the study period. We show examples of springtime snowmelt over North America, beginning in March 2000 and extending through the winter of 2012 for all of North America, and for various specific areas such as the Wind River Range in Wyoming and in the Catskill Mountains in New York. We also compare our approx 12-year trends with trends derived from the Rutgers Global Snow Lab snow cover climate-data record.

Description: Changes in rainfall characteristics induced by global warming are examined based on probability distribution function (PDF) analysis, from outputs of 14 IPCC (Intergovernmental Panel on Climate Change), CMIP (5th Coupled Model Intercomparison Project) models under various scenarios of increased CO2 emissions. Results show that collectively CMIP5 models project a robust and consistent global and regional rainfall response to CO2 warming. Globally, the models show a 1-3% increase in rainfall per degree rise in temperature, with a canonical response featuring large increase (100-250 %) in frequency of occurrence of very heavy rain, a reduction (5-10%) of moderate rain, and an increase (10-15%) of light rain events. Regionally, even though details vary among models, a majority of the models (〉10 out of 14) project a consistent large scale response with more heavy rain events in climatologically wet regions, most pronounced in the Pacific ITCZ and the Asian monsoon. Moderate rain events are found to decrease over extensive regions of the subtropical and extratropical oceans, but increases over the extratropical land regions, and the Southern Oceans. The spatial distribution of light rain resembles that of moderate rain, but mostly with opposite polarity. The majority of the models also show increase in the number of dry events (absence or only trace amount of rain) over subtropical and tropical land regions in both hemispheres. These results suggest that rainfall characteristics are changing and that increased extreme rainfall events and droughts occurrences are connected, as a consequent of a global adjustment of the large scale circulation to global warming.

Description: This presentation discusses an approach to estimate model error using observation residuals. Based on the sequential fixed-lag smoother; we introduce a diagnostic procedure to allow estimating model error over a dense observing system. Optimality considerations are examined in light of the sequential results. The procedure is re-interpreted in the language of variational assimilation, such as 4d-Var. Illustrations of the approach are given by studying both identical-twin and fraternal-twin experimental settings for a system governed by Lorenz-type dynamics. Preliminary results by looking at observation residual statistics for the ECMWF data assimilation system are also shown. The presentation will be part of a series of discussions on issues related to four-dimensional data assimilation under weak-constraint and methodologies to estimate model error.

Description: Dr. Nancy Maynard was invited by the Alaska Forum on the Environment to participate in a Panel Discussion to discuss (1) background about what the US NCA and International IPCC assessments are, (2) the impact the assessments have on policy-making, (3) the process for participation in both assessments, (4) how we can increase participation by Indigenous Peoples such as Native Americans and Alaska Natives, (5) How we can increase historical and current impacts input from Native communities through stories, oral history, "grey" literature, etc. The session will be chaired by Dr. Bull Bennett, a cochair of the US NCA's chapter on "Native and Tribal Lands and Resources" and Dr. Maynard is the other co-chair of that chapter and they will discuss the latest activities under the NCA process relevant to Native Americans and Alaska Natives. Dr. Maynard is also a Lead Author of the "Polar Regions" chapter of the IPCC WG2 (5th Assessment) and she will describes some of the latest approaches by the IPCC to entrain more Indigenous peoples into the IPCC process.

Description: The Short-term Prediction Research and Transition (SPoRT) Center located at NASA Marshall Space Flight Center has been conducting testbed activities aimed at transitioning satellite products to National Weather Service operational end users for the last 10 years. SPoRT is a NASA/NOAA funded project that has set the bar for transition of products to operational end users through a paradigm of understanding forecast challenges and forecaster needs, displaying products in end users decision support systems, actively assessing the operational impact of these products, and improving products based on forecaster feedback. Aiming for quality partnerships rather than a large quantity of data users, SPoRT has become a community leader in training operational forecasters on the use of up-and-coming satellite data through the use of legacy instruments and proxy data. Traditionally, SPoRT has supplied satellite imagery and products from NASA instruments such as the Moderate-resolution Imaging Spectroradiometer (MODIS) and the Atmospheric Infrared Sounder (AIRS). However, recently, SPoRT has been funded by the GOES-R and Joint Polar Satellite System (JPSS) Proving Grounds to accelerate the transition of selected imagery and products to help improve forecaster awareness of upcoming operational data from the Visible Infrared Imager Radiometer Suite (VIIRS), Cross-track Infrared Sounder (CrIS), Advanced Baseline Imager (ABI), and Geostationary Lightning Mapper (GLM). This presentation provides background on the SPoRT Center, the SPoRT paradigm, and some example products that SPoRT is excited to work with forecasters to evaluate.

Description: An accurate representation of spatial and temporal variability of the Upper Troposphere Lower Stratosphere (UTLS) ozone is essential for understanding both the tropospheric ozone budget and ozone s contribution to radiative forcing. The complex, dynamically driven structure of trace gas fields in the UTLS presents a challenge to data-based and modelling studies. Small features are not fully resolved in data from limb-sounding instruments such as the Microwave Limb Sounder on EOS-Aura (the EOS-MLS), but are captured in assimilation of those data as vertical structure is added from the assimilated meteorology. This will be demonstrated using a multi-year assimilation of EOS-MLS observations in the Goddard Earth Observing System, Version 5 (GEOS-5) data assimilation system. The results demonstrate the realism of the seasonal and year to year variability of laminar structures in the mid-latitudinal ozone field between years 2005-2007, for which independent validation data are available from the HIRDLS instrument. The analysis is done in the context of the underlying large scale dynamics. The lifetimes of most research instruments are too short for them to be used throughout the duration of long-term (at least 3 decades) reanalyses. For example, the EOS-MLS instrument has operated since mid-2004 until present. By contrast, Solar Backscatter Ultra Violet (SBUV) measurements provide continuous data since late 1978, but their vertical resolution is insufficient to represent the profile shape in the UTLS. Assimilation of these SBUV/2 observations in the GEOS-5 data assimilation system has hitherto not captured a realistic ozone structure in the UTLS, even though transport studies using GEOS-5 wind fields do show such structures. We show that careful construction of the background error covariance structure in GEOS-5 can lead to more realistic UTLS ozone fields when assimilating SBUV/2 observations. The reasoning behind this will be discussed, emphasizing the need to retain the sharp gradient of ozone concentrations across the tropopause. We analyze the UTLS ozone distributions in multi-year SBUV/2 assimilation experiments, comparing the results against the independent HIRDLSdataset and, for a longer period, with the MLS assimilation and discuss the consequences for tropospheric ozone and radiative forcing.

Description: During the Mid-latitude Continental Convective Cloud Experiment (MC3E), NASA's GPM GV Disdrometer and Radar Observations of Precipitation (DROP) Facility deployed an array of disdrometers and rain gauges in northern Oklahoma to sample, with high resolution, the drop size distribution for use in development of precipitation retrieval algorithms for the GPM core satellites. The DROP Facility instruments deployed during MC3E consisted of 16 autonomous Parsivel units, 5 two-dimensional video disdrometers (2dvds), a vertically pointing K band radar, and 32 tipping bucket rain gauges. There were several rainfall events during MC3E in which rain drops exceeding 6 mm in diameter were recorded. The disdrometer array revealed large rain drops with diameters exceeding 6 mm and 8 mm during two separate stratiform and convective rainfall events, respectively. The NPOL radar, which was scanning in high resolution RHI mode (every 40 sec) over the disdrometer array during the stratiform event, indicated a 1 km thick bright band with a differential reflectivity column of 2-3 dB extending below the melting layer to the surface where the large drops were recorded by the 2dvds. These large drops are important for GPM since they can have a great impact upon satellite precipitation retrieval, especially near the ground and below heavy convective rainfall cores where satellites have had problems depicting the rainfall.

Description: The NASA Short-term Prediction Research and Transition (SPoRT) Center has developed a Greenness Vegetation Fraction (GVF) dataset, which is updated daily using swaths of Normalized Difference Vegetation Index data from the Moderate Resolution Imaging Spectroradiometer (MODIS) data aboard the NASA-EOS Aqua and Terra satellites. NASA SPoRT started generating daily real-time GVF composites at 1-km resolution over the Continental United States beginning 1 June 2010. A companion poster presentation (Bell et al.) primarily focuses on impact results in an offline configuration of the Noah land surface model (LSM) for the 2010 warm season, comparing the SPoRT/MODIS GVF dataset to the current operational monthly climatology GVF available within the National Centers for Environmental Prediction (NCEP) and Weather Research and Forecasting (WRF) models. This paper/presentation primarily focuses on individual case studies of severe weather events to determine the impacts and possible improvements by using the real-time, high-resolution SPoRT-MODIS GVFs in place of the coarser-resolution NCEP climatological GVFs in model simulations. The NASA-Unified WRF (NU-WRF) modeling system is employed to conduct the sensitivity simulations of individual events. The NU-WRF is an integrated modeling system based on the Advanced Research WRF dynamical core that is designed to represents aerosol, cloud, precipitation, and land processes at satellite-resolved scales in a coupled simulation environment. For this experiment, the coupling between the NASA Land Information System (LIS) and the WRF model is utilized to measure the impacts of the daily SPoRT/MODIS versus the monthly NCEP climatology GVFs. First, a spin-up run of the LIS is integrated for two years using the Noah LSM to ensure that the land surface fields reach an equilibrium state on the 4-km grid mesh used. Next, the spin-up LIS is run in two separate modes beginning on 1 June 2010, one continuing with the climatology GVFs while the other uses the daily SPoRT/MODIS GVFs. Finally, snapshots of the LIS land surface fields are used to initialize two different simulations of the NU-WRF, one running with climatology LIS and GVFs, and the other running with experimental LIS and NASA/SPoRT GVFs. In this paper/presentation, case study results will be highlighted in regions with significant differences in GVF between the NCEP climatology and SPoRT product during severe weather episodes.

Description: The NASA Short-term Prediction Research and Transition (SPoRT) Center, in collaboration with the Cooperative Institute for Research in the Atmosphere (CIRA), is providing red-green-blue (RGB) color composite imagery to several of NOAA s National Centers and National Weather Service forecast offices as a demonstration of future capabilities of the Advanced Baseline Imager (ABI) to be implemented aboard GOES-R. Forecasters rely upon geostationary satellite imagery to monitor conditions over their regions of responsibility. Since the ABI will provide nearly three times as many channels as the current GOES imager, the volume of data available for analysis will increase. RGB composite imagery can aid in the compression of large data volumes by combining information from multiple channels or paired channel differences into single products that communicate more information than provided by a single channel image. A standard suite of RGB imagery has been developed by the European Organization for the Exploitation of Meteorological Satellites (EUMETSAT), based upon the Spinning Enhanced Visible and Infrared Imager (SEVIRI). The SEVIRI instrument currently provides visible and infrared wavelengths comparable to the future GOES-R ABI. In addition, the Moderate Resolution Imaging Spectroradiometer (MODIS) instruments aboard the NASA Terra and Aqua satellites can be used to demonstrate future capabilities of GOES-R. This presentation will demonstrate an overview of the products currently disseminated to SPoRT partners within the GOES-R Proving Ground, and other National Weather Service forecast offices, along with examples of their application. For example, CIRA has used the channels of the current GOES sounder to produce an "air mass" RGB originally designed for SEVIRI. This provides hourly imagery over CONUS for looping applications while demonstrating capabilities similar to the future ABI instrument. SPoRT has developed similar "air mass" RGB imagery from MODIS, and through a case study example, synoptic-scale features evident in single-channel water vapor imagery are shown in the context of the air mass product. Other products, such as the "nighttime microphysics" RGB, are useful in the detection of low clouds and fog. Nighttime microphysics products from MODIS offer some advantages over single-channel or spectral difference techniques and will be discussed in the context of a case study. Finally, other RGB products from SEVIRI are being demonstrated as precursors to GOES-R within the GOES-R Proving Ground. Examples of "natural color" and "dust" imagery will be shown with relevant applications.

Description: The optical and microphysical structure of warm boundary layer marine clouds is of fundamental importance for understanding a variety of cloud radiation and precipitation processes. With the advent of MODIS (Moderate Resolution Imaging Spectroradiometer) on the NASA EOS Terra and Aqua platforms, simultaneous global/daily 1km retrievals of cloud optical thickness and effective particle size are provided, as well as the derived water path. In addition, the cloud product (MOD06/MYD06 for MODIS Terra and Aqua, respectively) provides separate effective radii results using the l.6, 2.1, and 3.7 ~m spectral channels. Cloud retrieval statistics are highly sensitive to how a pixel identified as being "notclear" by a cloud mask (e.g., the MOD35/MYD35 product) is determined to be useful for an optical retrieval based on a 1-D cloud model. The Collection 5 MODIS retrieval algorithm removed pixels associated with cloud'edges as well as ocean pixels with partly cloudy elements in the 250m MODIS cloud mask - part of the so-called Clear Sky Restoral (CSR) algorithm. Collection 6 attempts retrievals for those two pixel populations, but allows a user to isolate or filter out the populations via CSR pixel-level Quality Assessment (QA) assignments. In this paper, using the preliminary Collection 6 MOD06 product, we present global and regional statistical results of marine warm cloud retrieval sensitivities to the cloud edge and 250m partly cloudy pixel populations. As expected, retrievals for these pixels are generally consistent with a breakdown of the ID cloud model. While optical thickness for these suspect pixel populations may have some utility for radiative studies, the retrievals should be used with extreme caution for process and microphysical studies.

Description: The Earth's climate is changing rapidly. In some respects, the rate of change is outpacing the predictions of only a few years ago. The challenge to Earth Science is to put forward credible projections of possible future climates so that the public and policy makers can make science-based decisions about energy development strategies. Models, observations and experiments all play strong roles in improving knowledge and increasing confidence in our predictions. The models have progressed from simple, coarse-resolution descriptions of atmospheric dynamics and physics only twenty years ago, to full-up Earth System models (ESMs) that include complete descriptions of the oceans and cryosphere. It has been convincingly argued that such complexity - the construction of realistic "toy" Earth's - is necessary to address the complex processes involved in climate change, including not only the physical atmosphere, oceans and cryosphere, but also the carbon cycle - both its natural and anthropogenic components - and the biosphere. Observations, particularly satellite observations, have more or less kept pace with the demands of the modelers, being able to observe progressively more and different facets of the Earth system, but the global satellite fleet is in need of an overhaul very soon. Lastly, field experiments and process studies confront the models with facts and allow us to develop more sophisticated and accurate satellite data algorithms. The challenges facing our relatively small Earth and planetary science communities are considerable and the stakes are significant. The stakeholders, now numbering 7 billion but soon to be 10 billion, will be relying on our results and capabilitie's to guide them into the future.

Description: Early climate modeling studies predicted that the Arctic Ocean and surrounding circumpolar land masses would heat up earlier and faster than other parts of the planet as a result of greenhouse gas-induced climate change, augmented by the sea-ice albedo feedback effect. These predictions have been largely borne out by observations over the last thirty years. However, despite constant improvement, global climate models have greater difficulty in reproducing the current climate in the Arctic than elsewhere and the scatter between projections from different climate models is much larger in the Arctic than for other regions. Biogeochemical cycle (BGC) models indicate that the warming in the Arctic-Boreal Zone (ABZ) could lead to widespread thawing of the permafrost, along with massive releases of CO2 and CH4, and large-scale changes in the vegetation cover in the ABZ. However, the uncertainties associated with these BGC model predictions are even larger than those associated with the physical climate system models used to describe climate change. These deficiencies in climate and BGC models reflect, at least in part, an incomplete understanding of the Arctic climate system and can be related to inadequate observational data or analyses of existing data. A workshop was held at NASA/GSFC, May 22-24 2012, to assess the predictive capability of the models, prioritize the critical science questions; and make recommendations regarding new field experiments needed to improve model subcomponents. This presentation will summarize the findings and recommendations of the workshop, including the need for aircraft and flux tower measurements and extension of existing in-situ measurements to improve process modeling of both the physical climate and biogeochemical cycle systems. Studies should be directly linked to remote sensing investigations with a view to scaling up the improved process models to the Earth System Model scale. Data assimilation and observing system simulation studies should be used to guide the deployment pattern and schedule for inversion studies as well. Synthesis and integration of previously funded Arctic-Boreal projects (e.g., ABLE, BOREAS, ICESCAPE, ICEBRIDGE, ARCTAS) should also be undertaken. Such an effort would include the integration of multiple remotely sensed products from the EOS satellites and other resources.

Description: Land-atmosphere (L-A) interactions play a critical role in determining the diurnal evolution of land surface and planetary boundary layer (PBL) temperature and moisture states and fluxes. In turn, these interactions regulate the strength of the connection between surface moisture and precipitation in a coupled system. To address deficiencies in numerical weather prediction and climate models due to improper treatment of L-A interactions, recent studies have focused on development of diagnostics to quantify the strength and accuracy of the land-PBL coupling at the process-level. In this study, a diagnosis of the nature and impacts oflocalland-atmosphere coupling (LoCo) during dry and wet extreme conditions is presented using a combination of models and observations during the summers of2006-7 in the U.S. Southern Great Plains. Specifically, the Weather Research and Forecasting (WRF) model has been coupled to NASA's Land Information System (LIS), which provides a flexible and high-resolution representation and initialization of land surface physics and states. A range of diagnostics exploring the links and feedbacks between soil moisture and precipitation are examined for the dry/wet regimes of this region, along with the behavior and accuracy of different land-PBL scheme couplings under these conditions. In addition, we examine the impact of improved specification ofland surface states, anomalies, and fluxes that are obtained through the use of a hew optimization and uncertainty module in LIS, on the L-A coupling in WRF forecasts. Results demonstrate how LoCo diagnostics can be applied to coupled model components in the context of their integrated impacts on the process-chain connecting the land surface to the PBL and support of hydrological anomalies.

Description: Using a high-resolution non-hydrostatic version of GEOS-5 with the cubed-sphere finite-volume dynamical core, the impact of spatial and temporal resolution on cloud properties will be evaluated. There are indications from examining convective cluster development in high resolution GEOS-5 forecasts that the temporal resolution within the model may playas significant a role as horizontal resolution. Comparing modeled convective cloud clusters versus satellite observations of brightness temperature, we have found that improved. temporal resolution in GEOS-S accounts for a significant portion of the improvements in the statistical distribution of convective cloud clusters. Using satellite simulators in GEOS-S we will compare the cloud optical properties of GEOS-S at various spatial and temporal resolutions with those observed from MODIS. The potential impact of these results on tropical cyclone formation and intensity will be examined as well.

Description: The presentation is divided into two major components. First, I will give an overview of space weather phenomenon and their associated impacts. Then I will describe the comprehensive list of products and tools that NASA Space Weather Center has developed by leveraging more than a decade long modeling experience enabled by the Community Coordinated Modeling Center (CCMC) and latest scientific research results from the broad science community. In addition, a summary of the space weather activities we have been engaged in and our operational experience will be provided.

Description: For the preparation of ITRF2008, the IDS processed data from 1993 to 2008, including data from TOPEX/Poseidon, the SPOT satellites and Envisat in the weekly solutions. Since the development of ITRF2008, the IDS has been engaged in a number of efforts to try and improve the reference frame solutions. These efforts include (i) assessing the contribution of the new DORIS satellites, Jason-2 and Cryosat2 (2008-2011), (ii) individually analyzing the DORIS satellite contributions to geocenter and scale, and (iii) improving orbit dynamics (atmospheric loading effects, satellite surface force modeling. . . ). We report on the preliminary results from these research activities, review the status of the IDS combination which is now routinely generated from the contributions of the IDS analysis centers, and discuss the prospects for continued improvement in the DORIS contribution to the next international reference frame.

Description: Both NLDAS Phase 1 (1996-2007) and Phase 2 (1979-present) datasets have been evaluated against in situ observational datasets, and NLDAS forcings and outputs are used by a wide variety of users. Drought indices and drought monitoring from NLDAS were recently examined by Mo et al. (2010) and Sheffield et al. (2010). In this poster, we will present results analyzing NLDAS Phase 2 forcings and outputs for 3 North American Case studies being analyzed as part of the NOAA MAPP Drought Task Force: (1) Western US drought (1998- 2004); (2) plains/southeast US drought (2006-2007); and (3) Current Texas-Mexico drought (2011-). We will examine percentiles of soil moisture consistent with the NLDAS drought monitor.

Description: Precipitation, including rain and snow, is a critical part of the Earth's energy and hydrology cycles. Precipitation impacts latent heating profiles locally while global circulation patterns distribute precipitation and energy from the equator to the poles. For the hydrological cycle, falling snow is a primary contributor in northern latitudes during the winter seasons. Falling snow is the source of snow pack accumulations that provide fresh water resources for many communities in the world. Furthermore, falling snow impacts society by causing transportation disruptions during severe snow events. In order to collect information on the complete global precipitation cycle, both liquid and frozen precipitation must be collected. The challenges of estimating falling snow from space still exist though progress is being made. These challenges include weak falling snow signatures with respect to background (surface, water vapor) signatures for passive sensors over land surfaces, unknowns about the spherical and non-spherical shapes of the snowflakes, their particle size distributions (PSDs) and how the assumptions about the unknowns impact observed brightness temperatures or radar reflectivities, differences in near surface snowfall and total column snow amounts, and limited ground truth to validate against. While these challenges remain, knowledge of their impact on expected retrieval results is an important key for understanding falling snow retrieval estimations. Since falling snow from space is the next precipitation measurement challenge from space, information must be determined in order to guide retrieval algorithm development for these current and future missions. This information includes thresholds of detection for various sensor channel configurations, snow event system characteristics, snowflake particle assumptions, and surface types. For example, can a lake effect snow system with low (approx 2.5 km) cloud tops having an ice water content (IWC) at the surface of 0.25 g / cubic m and dendrite snowflakes be detected? If this information is known, we can focus retrieval efforts on detectable storms and concentrate advances on achievable results. Here, the focus is to determine thresholds of detection for falling snow for various snow conditions over land and lake surfaces. The results rely on simulated Weather Research Forecasting (WRF) simulations of falling snow cases since simulations provide all the information to determine the measurements from space and the ground truth. Sensitivity analyses were performed to better ascertain the relationships between multifrequency microwave and millimeter-wave sensor observations and the falling snow/underlying field of view. In addition, thresholds of detection for various sensor channel configurations, snow event system characteristics, snowflake particle assumptions, and surface types were studied. Results will be presented for active radar at Ku, Ka, and W-band and for passive radiometer channels from 10 to 183 GHz.

Description: In this talk, I will present recent results from a project led at NASA/GSFC, in collaboration with NASA/MSFC and JHU, focused on the development and application of an observation-driven integrated modeling system that represents aerosol, cloud, precipitation and land processes at satellite-resolved scales. The project, known as the NASA Unified WRF (NU-WRF), is funded by NASA's Modeling and Analysis Program, and leverages prior investments from the Air Force Weather Agency and NASA's Earth Science Technology Office (ESTO). We define "satellite-resolved" scales as being within a typical mesoscale atmospheric modeling grid (roughly 1-25 km), although this work is designed to bridge the continuum between local (microscale), regional (mesoscale) and global (synoptic) processes. NU-WRF is a superset of the standard NCAR Advanced Research WRF model, achieved by fully integrating the GSFC Land Information System (LIS, already coupled to WRF), the WRF/Chem enabled version of the Goddard Chemistry Aerosols Radiation Transport (GOCART) model, the Goddard Satellite Data Simulation Unit (SDSU), and boundary/initial condition preprocessors for MERRA and GEOS-5 into a single software release (with source code available by agreement with NASA/GSFC). I will show examples where the full coupling between aerosol, cloud, precipitation and land processes is critical for predicting local, regional, and global water and energy cycles, including some high-impact phenomena such as floods, hurricanes, mesoscale convective systems, droughts, and monsoons.

Description: The modelers point of view is that the aerosol problem is one of sources, evolution, and sinks. Relative to evolution and sink processes, enormous attention is given to the problem of aerosols sources, whether inventory based (e.g., fossil fuel emissions) or dynamic (e.g., dust, sea salt, biomass burning). On the other hand, aerosol losses in models are a major factor in controlling the aerosol distribution and lifetime. Here we shine some light on how aerosol sinks are treated in modern chemical transport models. We discuss the mechanisms of dry and wet loss processes and the parameterizations for those processes in a single model (GEOS-5). We survey the literature of other modeling studies. We additionally compare the budgets of aerosol losses in several of the ICAP models.

Description: Recently, a multi-scale modeling system with unified physics was developed at NASA Goddard. It consists of (1) a cloud-resolving model (Goddard Cumulus Ensemble model, GCE model), (2) a regional scale model (a NASA unified weather research and forecast, WRF), (3) a coupled CRM and global model (Goddard Multi-scale Modeling Framework, MMF), and (4) a land modeling system. The same microphysical processes, long and short wave radiative transfer and land processes and the explicit cloud-radiation, and cloud-land surface interactive processes are applied in this multi-scale modeling system. This modeling system has been coupled with a multi-satellite simulator to use NASA high-resolution satellite data to identify the strengths and weaknesses of cloud and precipitation processes simulated by the model. In this talk, a review of developments and applications of the multi-scale modeling system will be presented. In particular, the microphysics development and its performance for the multi-scale modeling system will be presented.

Description: No abstract available

Description: Diverse vulnerabilities of Bangladesh's agricultural sector in 16 sub-regions are assessed using experiments designed to investigate climate impact factors in isolation and in combination. Climate information from a suite of global climate models (GCMs) is used to drive models assessing the agricultural impact of changes in temperature, precipitation, carbon dioxide concentrations, river floods, and sea level rise for the 2040-2069 period in comparison to a historical baseline. Using the multi-factor impacts analysis framework developed in Yu et al. (2010), this study provides new sub-regional vulnerability analyses and quantifies key uncertainties in climate and production. Rice (aman, boro, and aus seasons) and wheat production are simulated in each sub-region using the biophysical Crop Environment REsource Synthesis (CERES) models. These simulations are then combined with the MIKE BASIN hydrologic model for river floods in the Ganges-Brahmaputra-Meghna (GBM) Basins, and the MIKE21Two-Dimensional Estuary Model to determine coastal inundation under conditions of higher mean sea level. The impacts of each factor depend on GCM configurations, emissions pathways, sub-regions, and particular seasons and crops. Temperature increases generally reduce production across all scenarios. Precipitation changes can have either a positive or a negative impact, with a high degree of uncertainty across GCMs. Carbon dioxide impacts on crop production are positive and depend on the emissions pathway. Increasing river flood areas reduce production in affected sub-regions. Precipitation uncertainties from different GCMs and emissions scenarios are reduced when integrated across the large GBM Basins' hydrology. Agriculture in Southern Bangladesh is severely affected by sea level rise even when cyclonic surges are not fully considered, with impacts increasing under the higher emissions scenario.

Description: The Agricultural Model Intercomparison and Improvement Project (AgMIP) is a major international effort linking the climate, crop, and economic modeling communities with cutting-edge information technology to produce improved crop and economic models and the next generation of climate impact projections for the agricultural sector. The goals of AgMIP are to improve substantially the characterization of world food security due to climate change and to enhance adaptation capacity in both developing and developed countries. Analyses of the agricultural impacts of climate variability and change require a transdisciplinary effort to consistently link state-of-the-art climate scenarios to crop and economic models. Crop model outputs are aggregated as inputs to regional and global economic models to determine regional vulnerabilities, changes in comparative advantage, price effects, and potential adaptation strategies in the agricultural sector. Climate, Crop Modeling, Economics, and Information Technology Team Protocols are presented to guide coordinated climate, crop modeling, economics, and information technology research activities around the world, along with AgMIP Cross-Cutting Themes that address uncertainty, aggregation and scaling, and the development of Representative Agricultural Pathways (RAPs) to enable testing of climate change adaptations in the context of other regional and global trends. The organization of research activities by geographic region and specific crops is described, along with project milestones. Pilot results demonstrate AgMIP's role in assessing climate impacts with explicit representation of uncertainties in climate scenarios and simulations using crop and economic models. An intercomparison of wheat model simulations near Obregn, Mexico reveals inter-model differences in yield sensitivity to [CO2] with model uncertainty holding approximately steady as concentrations rise, while uncertainty related to choice of crop model increases with rising temperatures. Wheat model simulations with midcentury climate scenarios project a slight decline in absolute yields that is more sensitive to selection of crop model than to global climate model, emissions scenario, or climate scenario downscaling method. A comparison of regional and national-scale economic simulations finds a large sensitivity of projected yield changes to the simulations' resolved scales. Finally, a global economic model intercomparison example demonstrates that improvements in the understanding of agriculture futures arise from integration of the range of uncertainty in crop, climate, and economic modeling results in multi-model assessments.

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: Meteorological measurements within urban areas are becoming increasingly important due to the accentuating effects of climate change upon the Urban Heat Island (UHI). However, ensuring that such measurements are representative of the local area is often difficult due to the diversity of the urban environment. The evaluation of sites is important for both new sites and for the relocation of established sites to ensure that long term changes in the meteorological and climatological conditions continue to be faithfully recorded. Site selection is traditionally carried out in the field using both local knowledge and visual inspection. This paper exploits and assesses the use of lidar-derived digital surface models (DSMs) to quantitatively aid the site selection process. This is acheived by combining the DSM with a solar model, first to generate spatial maps of sky view factors and sun-hour potential and second, to generate site-specific views of the horizon. The results show that such a technique is a useful first-step approach to identify key sites that may be further evaluated for the location of meteorological stations within urban areas.

Description: We calculate decadal aerosol direct and indirect (warm cloud) radiative forcings from US anthropogenic sources over the 1950-2050 period. Past and future aerosol distributions are constructed using GEOS-Chem and historical emission inventories and future projections from the IPCC A1B scenario. Aerosol simulations are evaluated with observed spatial distributions and 1980-2010 trends of aerosol concentrations and wet deposition in the contiguous US. Direct and indirect radiative forcing is calculated using the GISS general circulation model and monthly mean aerosol distributions from GEOS-Chem. The radiative forcing from US anthropogenic aerosols is strongly localized over the eastern US. We find that its magnitude peaked in 1970-1990, with values over the eastern US (east of 100 deg W) of 2.0Wm(exp2 for direct forcing including contributions from sulfate (2.0Wm2), nitrate (0.2Wm(exp2), organic carbon (0.2Wm(exp2), and black carbon (+0.4Wm(exp2). The uncertainties in radiative forcing due to aerosol radiative properties are estimated to be about 50 %. The aerosol indirect effect is estimated to be of comparable magnitude to the direct forcing. We find that the magnitude of the forcing declined sharply from 1990 to 2010 (by 0.8Wm(exp2) direct and 1.0Wm(exp2 indirect), mainly reflecting decreases in SO2 emissions, and project that it will continue declining post-2010 but at a much slower rate since US SO2 emissions have already declined by almost 60% from their peak. This suggests that much of the warming effect of reducing US anthropogenic aerosol sources has already been realized. The small positive radiative forcing from US BC emissions (+0.3Wm(exp2 over the eastern US in 2010; 5% of the global forcing from anthropogenic BC emissions worldwide) suggests that a US emission control strategy focused on BC would have only limited climate benefit.

Description: This study examines the potential negative influences of dry midlevel air on the development of tropical cyclones (specifically, its role in enhancing cold downdraft activity and suppressing storm development). The Weather Research and Forecasting model is used to construct two sets of idealized simulations of hurricane development in environments with different configurations of dry air. The first set of simulations begins with dry air located north of the vortex center by distances ranging from 0 to 270 km, whereas the second set of simulations begins with dry air completely surrounding the vortex, but with moist envelopes in the vortex core ranging in size from 0 to 150 km in radius. No impact of the dry air is seen for dry layers located more than 270 km north of the initial vortex center (approximately 3 times the initial radius of maximum wind). When the dry air is initially closer to the vortex center, it suppresses convective development where it entrains into the storm circulation, leading to increasingly asymmetric convection and slower storm development. The presence of dry air throughout the domain, including the vortex center, substantially slows storm development. However, the presence of a moist envelope around the vortex center eliminates the deleterious impact on storm intensity. Instead, storm size is significantly reduced. The simulations suggest that dry air slows intensification only when it is located very close to the vortex core at early times. When it does slow storm development, it does so primarily by inducing outward- moving convective asymmetries that temporarily shift latent heating radially outward away from the high-vorticity inner core.

Description: A unique microphysical structure of rainfall is observed by the surface laser optical Particle Size and Velocity (Parsivel) disdrometers on 25 April 2011 during Midlatitude Continental Convective Clouds Experiment (MC3E). According to the systematic differences in rainfall rate and bulk effective droplet radius, the sampling data can be divided into two groups; the rainfall mostly from the deep convective clouds has relatively high rainfall rate and large bulk effective droplet radius, whereas the reverse is true for the rainfall from the shallow wrm clouds. The Weather Research and Forecasting model coupled with spectral bin microphysics (WRF-SBM) successfully reproduces the two distinct modes in the observed rainfall microphysical structure. The results show that the up-to-date model can demonstrate how the cloud physics and the weather condition on the day are involved in forming the unique rainfall characteristic.

Description: Ensembles of numerical model forecasts are of interest to operational early warning forecasters as the spread of the ensemble provides an indication of the uncertainty of the alerts, and the mean value is deemed to outperform the forecasts of the individual models. This paper explores two ensembles on a severe weather episode in Spain, aiming to ascertain the relative usefulness of each one. One ensemble uses sensible choices of physical parameterizations (precipitation microphysics, land surface physics, and cumulus physics) while the other follows a perturbed initial conditions approach. The results show that, depending on the parameterizations, large differences can be expected in terms of storm location, spatial structure of the precipitation field, and rain intensity. It is also found that the spread of the perturbed initial conditions ensemble is smaller than the dispersion due to physical parameterizations. This confirms that in severe weather situations operational forecasts should address moist physics deficiencies to realize the full benefits of the ensemble approach, in addition to optimizing initial conditions. The results also provide insights into differences in simulations arising from ensembles of weather models using several combinations of different physical parameterizations.

Description: An algorithm for linear estimation of aerosol bulk properties such as particle volume, effective radius and complex refractive index from multiwavelength lidar measurements is presented. The approach uses the fact that the total aerosol concentration can well be approximated as a linear combination of aerosol characteristics measured by multiwavelength lidar. Therefore, the aerosol concentration can be estimated from lidar measurements without the need to derive the size distribution, which entails more sophisticated procedures. The definition of the coefficients required for the linear estimates is based on an expansion of the particle size distribution in terms of the measurement kernels. Once the coefficients are established, the approach permits fast retrieval of aerosol bulk properties when compared with the full regularization technique. In addition, the straightforward estimation of bulk properties stabilizes the inversion making it more resistant to noise in the optical data. Numerical tests demonstrate that for data sets containing three aerosol backscattering and two extinction coefficients (so called 3 + 2 ) the uncertainties in the retrieval of particle volume and surface area are below 45% when input data random uncertainties are below 20 %. Moreover, using linear estimates allows reliable retrievals even when the number of input data is reduced. To evaluate the approach, the results obtained using this technique are compared with those based on the previously developed full inversion scheme that relies on the regularization procedure. Both techniques were applied to the data measured by multiwavelength lidar at NASA/GSFC. The results obtained with both methods using the same observations are in good agreement. At the same time, the high speed of the retrieval using linear estimates makes the method preferable for generating aerosol information from extended lidar observations. To demonstrate the efficiency of the method, an extended time series of observations acquired in Turkey in May 2010 was processed using the linear estimates technique permitting, for what we believe to be the first time, temporal-height distributions of particle parameters.

Description: We present a regional and seasonal climatology of SHADOZ ozone profiles in the troposphere and tropical tropopause layer (TTL) based on measurements taken during the first five years of Aura, 2005-2009, when new stations joined the network at Hanoi, Vietnam; Hilo, Hawaii; Alajuela Heredia, Costa Rica; Cotonou, Benin. In all, 15 stations operated during that period. A west-to-east progression of decreasing convective influence and increasing pollution leads to distinct tropospheric ozone profiles in three regions: (1) western Pacific eastern Indian Ocean; (2) equatorial Americas (San Cristobal, Alajuela, Paramaribo); (3) Atlantic and Africa. Comparisons in total ozone column from soundings, the Ozone Monitoring Instrument (OMI, on Aura, 2004-) satellite and ground-based instrumentation are presented. Most stations show better agreement with OMI than they did for EPTOMS comparisons (1998-2004; Earth-ProbeTotal Ozone Mapping Spectrometer), partly due to a revised above-burst ozone climatology. Possible station biases in the stratospheric segment of the ozone measurement noted in the first 7 years of SHADOZ ozone profiles are re-examined. High stratospheric bias observed during the TOMS period appears to persist at one station. Comparisons of SHADOZ tropospheric ozone and the daily Trajectory-enhanced Tropospheric Ozone Residual (TTOR) product (based on OMIMLS) show that the satellite-derived column amount averages 25 low. Correlations between TTOR and the SHADOZ sondes are quite good (typical r2 0.5-0.8), however, which may account for why some published residual-based OMI products capture tropospheric interannual variability fairly realistically. On the other hand, no clear explanations emerge for why TTOR-sonde discrepancies vary over a wide range at most SHADOZ sites.

Description: This work presents the first analysis of longterm correlative day-to-night columnar aerosol optical properties. The aim is to better understand columnar aerosol dynamic from ground-based observations, which are poorly studied until now. To this end we have used a combination of sun-and-star photometry measurements acquired in the city of Granada (37.16 N, 3.60 W, 680 ma.s.l.; South-East of Spain) from 2007 to 2010. For the whole study period, mean aerosol optical depth (AOD) around 440 nm (+/-standard deviation) is 0.18 +/- 0.10 and 0.19 +/- 0.11 for daytime and nighttime, respectively, while the mean Angstrom exponent (alpha ) is 1.0 +/- 0.4 and 0.9 +/- 0.4 for daytime and nighttime. The ANOVA statistical tests reveal that there are no significant differences between AOD and obtained at daytime and those at nighttime. Additionally, the mean daytime values of AOD and obtained during this study period are coherent with the values obtained in the surrounding AERONET stations. On the other hand, AOD around 440 nm present evident seasonal patterns characterised by large values in summer (mean value of 0.20 +/- 0.10 both at daytime and nighttime) and low values in winter (mean value of 0.15 +/- 0.09 at daytime and 0.17 +/- 0.10 at nighttime). The Angstrom exponents also present seasonal patterns, but with low values in summer (mean values of 0.8 +/- 0.4 and 0.9 +/- 0.4 at dayand night-time) and relatively large values in winter (mean values of 1.2 +/- 0.4 and 1.0 +/- 0.3 at daytime and nighttime). These seasonal patterns are explained by the differences in the meteorological conditions and by the differences in the strength of the aerosol sources. To take more insight about the changes in aerosol particles between day and night, the spectral differences of the Angstrom exponent as function of the Angstrom exponent are also studied. These analyses reveal increases of the fine mode radius and of the fine mode contribution to AOD during nighttime, being more remarkable in the summer seasons. These variations are explained by the changes of the local aerosol sources and by the meteorological conditions between daytime and nighttime, as well as aerosol aging processes. Case studies during summer and winter for different aerosol loads and types are also presented to clearly illustrate these findings.

Description: A simplied framework is presented for assessing the qualitative sensitivities of computed microwave properties, satellite brightness temperatures, and radar reflectivities to assumptions concerning the physical properties of ice-phase hydrometeors. Properties considered included the shape parameter of a gamma size distribution andthe melted-equivalent mass median diameter D0, the particle density, dielectric mixing formula, and the choice of complex index of refraction for ice. We examine these properties at selected radiometer frequencies of 18.7, 36.5, 89.0, and 150.0 GHz; and radar frequencies at 2.8, 13.4, 35.6, and 94.0 GHz consistent with existing and planned remote sensing instruments. Passive and active microwave observables of ice particles arefound to be extremely sensitive to the melted-equivalent mass median diameter D0 ofthe size distribution. Similar large sensitivities are found for variations in the ice vol-ume fraction whenever the geometric mass median diameter exceeds approximately 1/8th of the wavelength. At 94 GHz the two-way path integrated attenuation is potentially large for dense compact particles. The distribution parameter mu has a relatively weak effect on any observable: less than 1-2 K in brightness temperature and up to 2.7 dB difference in the effective radar reflectivity. Reversal of the roles of ice and air in the MaxwellGarnett dielectric mixing formula leads to a signicant change in both microwave brightness temperature (10 K) and radar reflectivity (2 dB). The choice of Warren (1984) or Warren and Brandt (2008) for the complex index of refraction of ice can produce a 3%-4% change in the brightness temperature depression.

Description: No abstract available

Description: Success in three aspects of OCO2 mission is threatened by unaccounted spa,al variability effects, all involving atmospheric scattering: 1. Low/moderately opaque clouds can escape the prescreening by mimicking a brighter surface. 2. Prescreening does not account for longrange radia,ve impact (adjacency effect) of nearby clouds. Need for extended cloud masking? 3. Oblique looks in target mode are highly exposed to surface adjacency and aerosol variability effects.We'll be covering all three bases!

Description: Water vapor in the tropical tropopause layer (TTL) has a local radiative cooling effect. As a source for ice in cirrus clouds, however, it can also indirectly produce infrared heating. Using NASA A-Train satellite measurements of CALIPSO and Aura/MLS we calculated the correlation of water vapor, ice water content and temperature in the TTL. We find that temperature strongly controls water vapor (correlation r =0.94) and cirrus clouds at 100 hPa (r = 0.91). Moreover we observe that the cirrus seasonal cycle is highly (r =0.9) anticorrelated with the water vapor variation in the TTL, showing higher cloud occurrence during December-January-February. We further investigate the anticorrelation on a regional scale and find that the strong anticorrelation occurs generally in the ITCZ (Intertropical Convergence Zone). The seasonal cycle of the cirrus ice water content is also highly anticorrelated to water vapor (r = 0.91) and our results support the hypothesis that the total water at 100 hPa is roughly constant. Temperature acts as a main regulator for balancing the partition between water vapor and cirrus clouds. Thus, to a large extent, the depleting water vapor in the TTL during DJF is a manifestation of cirrus formation.

Description: This study investigates the structure of the African easterly jet, focusing on instability processes on a seasonal and subseasonal scale, with the goal of identifying features that could provide increased predictability of Atlantic tropical cyclogenesis. The Modern-Era Retrospective Analysis for Research and Applications (MERRA) is used as the main investigating tool. MERRA is compared with other reanalyses datasets from major operational centers around the world and was found to describe very effectively the circulation over the African monsoon region. In particular, a comparison with precipitation datasets from the Global Precipitation Climatology Project shows that MERRA realistically reproduces seasonal precipitation over that region. The verification of the generalized Kuo barotropic instability condition computed from seasonal means is found to have the interesting property of defining well the location where observed tropical storms are detected. This property does not appear to be an artifact of MERRA and is present also in the other adopted reanalysis datasets. Therefore, the fact that the areas where the mean flow is unstable seems to provide a more favorable environment for wave intensification, could be another factor to include-in addition to sea surface temperature, vertical shear, precipitation, the role of Saharan air, and others-among large-scale forcings affecting development and tropical cyclone frequency. In addition, two prominent modes of variability are found based on a spectral analysis that uses the Hilbert-Huang transform: a 2.5-6-day mode that corresponds well to the African easterly waves and also a 6-9-day mode that seems to be associated with tropical- extratropical interaction.

Description: Dynamical downscaling is being increasingly used for climate change studies, wherein the climates simulated by a coupled atmosphere-ocean general circulation model (AOGCM) for a historical and a future (projected) decade are used to drive a regional climate model (RCM) over a specific area. While previous studies have demonstrated that RCMs can add value to AOGCM-simulated climatologies over different world regions, it is unclear as to whether or not this translates to a better reproduction of the observed climate change therein. We address this issue over the continental U.S. using the GISS-ModelE2 and WRF models, a state-of-the-science AOGCM and RCM, respectively. As configured here, the RCM does not effect holistic improvement in the seasonally and regionally averaged surface air temperature or precipitation for the individual historical decades. Insofar as the climate change between the two decades is concerned, the RCM does improve upon the AOGCM when nudged in the domain proper, but only modestly so. Further, the analysis indicates that there is not a strong relationship between skill in capturing climatological means and skill in capturing climate change. Though additional research would be needed to demonstrate the robustness of this finding in AOGCM/RCM models generally, the evidence indicates that, for climate change studies, the most important factor is the skill of the driving global model itself, suggesting that highest priority should be given to improving the long-range climate skill of AOGCMs.

Description: Detrended, modelled first leaf dates for 856 sites across North America for the period 1900-2008 are used to examine how the El Nino Southern Oscillation (ENSO) and the Pacific Decadal Oscillation (PDO) separately and together might influence the timing of spring. Although spring (mean March through April) ENSO and PDO signals are apparent in first leaf dates, the signals are not statistically significant (at a 95% confidence level (p 〈0.05)) for most sites. The most significant ENSO/PDO signal in first leaf dates occurs for El Nino and positive PDO conditions. An analysis of the spatial distributions of first leaf dates for separate and combined ENSO/PDO conditions features a northwest-southeast dipole that is significantly (at p 〈0.05) different than the distributions for neutral conditions. The nature of the teleconnection between Pacific SST's and first leaf dates is evident in comparable composites for detrended sea level pressure (SLP) in the spring months. During positive ENSO/PDO, there is an anomalous flow of warm air from the southwestern US into the northwestern US and an anomalous northeasterly flow of cold air from polar regions into the eastern and southeastern US. These flow patterns are reversed during negative ENSO/PDO. Although the magnitudes of first leaf date departures are not necessarily significantly related to ENSO and PDO, the spatial patterns of departures are significantly related to ENSO and PDO. These significant relations and the long-lived persistence of SSTs provide a potential tool for forecasting the tendencies for first leaf dates to be early or late.

Description: Several different ice nucleation parameterizations in two different General Circulation Models (GCMs) are used to understand the effects of ice nucleation on the mean climate state, and the Aerosol Indirect Effects (AIE) of cirrus clouds on climate. Simulations have a range of ice microphysical states that are consistent with the spread of observations, but many simulations have higher present-day ice crystal number concentrations than in-situ observations. These different states result from different parameterizations of ice cloud nucleation processes, and feature different balances of homogeneous and heterogeneous nucleation. Black carbon aerosols have a small (0.06 Wm(exp-2) and not statistically significant AIE when included as ice nuclei, for nucleation efficiencies within the range of laboratory measurements. Indirect effects of anthropogenic aerosols on cirrus clouds occur as a consequence of increasing anthropogenic sulfur emissions with different mechanisms important in different models. In one model this is due to increases in homogeneous nucleation fraction, and in the other due to increases in heterogeneous nucleation with coated dust. The magnitude of the effect is the same however. The resulting ice AIE does not seem strongly dependent on the balance between homogeneous and heterogeneous ice nucleation. Regional effects can reach several Wm2. Indirect effects are slightly larger for those states with less homogeneous nucleation and lower ice number concentration in the base state. The total ice AIE is estimated at 0.27 +/- 0.10 Wm(exp-2) (1 sigma uncertainty). This represents a 20% offset of the simulated total shortwave AIE for ice and liquid clouds of 1.6 Wm(sup-2).

Description: Current climate and future climate-warming runs with the RegCM Regional Climate Model (RCM) at 50 and 11 km-resolutions forced by the ECHAM GCM are used to examine whether the increased resolution of the RCM introduces novel information in the precipitation field when the models are run for the mountainous region of the Hellenic peninsula. The model results are inter-compared with the resolution of the RCM output degraded to match that of the GCM, and it is found that in both the present and future climate runs the regional models produce more precipitation than the forcing GCM. At the same time, the RCM runs produce increases in precipitation with climate warming even though they are forced with a GCM that shows no precipitation change in the region. The additional precipitation is mostly concentrated over the mountain ranges, where orographic precipitation formation is expected to be a dominant mechanism. It is found that, when examined at the same resolution, the elevation heights of the GCM are lower than those of the averaged RCM in the areas of the main mountain ranges. It is also found that the majority of the difference in precipitation between the RCM and the GCM can be explained by their difference in topographic height. The study results indicate that, in complex topography regions, GCM predictions of precipitation change with climate warming may be dry biased due to the GCM smoothing of the regional topography.

Description: Many palaeoclimate studies have quantified pre-anthropogenic climate change to calculate climate sensitivity (equilibrium temperature change in response to radiative forcing change), but a lack of consistent methodologies produces a wide range of estimates and hinders comparability of results. Here we present a stricter approach, to improve intercomparison of palaeoclimate sensitivity estimates in a manner compatible with equilibrium projections for future climate change. Over the past 65 million years, this reveals a climate sensitivity (in K W1 m2) of 0.3-1.9 or 0.6-1.3 at 95% or 68% probability, respectively. The latter implies a warming of 2.2-4.8 K per doubling of atmospheric CO2, which agrees with IPCC estimates.

Description: Retrievals of the isotopic composition of water vapor from the Aura Tropospheric Emission Spectrometer (TES) have unique value in constraining moist processes in climate models. Accurate comparison between simulated and retrieved values requires that model profiles that would be poorly retrieved are excluded, and that an instrument operator be applied to the remaining profiles. Typically, this is done by sampling model output at satellite measurement points and using the quality flags and averaging kernels from individual retrievals at specific places and times. This approach is not reliable when the model meteorological conditions influencing retrieval sensitivity are different from those observed by the instrument at short time scales, which will be the case for free-running climate simulations. In this study, we describe an alternative, categorical approach to applying the instrument operator, implemented within the NASA GISS ModelE general circulation model. Retrieval quality and averaging kernel structure are predicted empirically from model conditions, rather than obtained from collocated satellite observations. This approach can be used for arbitrary model configurations, and requires no agreement between satellite-retrieved and model meteorology at short time scales. To test this approach, nudged simUlations were conducted using both the retrieval-based and categorical operators. Cloud cover, surface temperature and free-tropospheric moisture content were the most important predictors of retrieval quality and averaging kernel structure. There was good agreement between the D fields after applying the retrieval-based and more detailed categorical operators, with increases of up to 30 over the ocean and decreases of up to 40 over land relative to the raw model fields. The categorical operator performed better over the ocean than over land, and requires further refinement for use outside of the tropics. After applying the TES operator, ModelE had D biases of 8 over ocean and 34 over land compared to TES D, which were less than the biases using raw model D fields.

Description: Herein, the Halogen Occultation Experiment (HALOE) aerosol extinction coefficient data is evaluated in the low aerosol loading period after 1996 as the first necessary step in a process that will eventually allow the production of a combined HALOE/SAGE II (Stratospheric Aerosol and Gas Experiment) aerosol climatology of derived aerosol products including surface area density. Based on these analyses, it is demonstrated that HALOE's 3.46 microns is of good quality above 19 km and suitable for scientific applications above that altitude. However, it is increasingly suspect at lower altitudes and should not be used below 17 km under any circumstances after 1996. The 3.40 microns is biased by about 10% throughout the lower stratosphere due to the failure to clear NO2 but otherwise appears to be a high quality product down to 15 km. The 2.45 and 5.26 micron aerosol extinction coefficient measurements are clearly biased and should not be used for scientific applications after the most intense parts of the Pinatubo period. Many of the issues in the aerosol data appear to be related to either the failure to clear some interfering gas species or doing so poorly. For instance, it is clear that the 3.40micronaerosol extinction coefficient measurements can be improved through the inclusion of an NO2 correction and could, in fact, end up as the highest quality overall HALOE aerosol extinction coefficient measurement. It also appears that the 2.45 and 5.26 micron channels may be improved by updating the Upper Atmosphere Pilot Database which is used as a resource for the removal of gas species otherwise not available from direct HALOE measurements. Finally, a simple model to demonstrate the promise of mixed visible/infrared aerosol extinction coefficient ensembles for the retrieval of bulk aerosol properties demonstrates that a combined HALOE/SAGE II aerosol climatology is feasible and may represent a substantial improvement over independently derived data sets.

Description: Observations of long-lived mixed-phase Arctic boundary layer clouds on 7 May 1998 during the First International Satellite Cloud Climatology Project (ISCCP) Regional Experiment (FIRE)Arctic Cloud Experiment (ACE)Surface Heat Budget of the Arctic Ocean (SHEBA) campaign provide a unique opportunity to test understanding of cloud ice formation. Under the microphysically simple conditions observed (apparently negligible ice aggregation, sublimation, and multiplication), the only expected source of new ice crystals is activation of heterogeneous ice nuclei (IN) and the only sink is sedimentation. Large-eddy simulations with size-resolved microphysics are initialized with IN number concentration N(sub IN) measured above cloud top, but details of IN activation behavior are unknown. If activated rapidly (in deposition, condensation, or immersion modes), as commonly assumed, IN are depleted from the well-mixed boundary layer within minutes. Quasi-equilibrium ice number concentration N(sub i) is then limited to a small fraction of overlying N(sub IN) that is determined by the cloud-top entrainment rate w(sub e) divided by the number-weighted ice fall speed at the surface v(sub f). Because w(sub c)〈 1 cm/s and v(sub f)〉 10 cm/s, N(sub i)/N(sub IN)〈〈 1. Such conditions may be common for this cloud type, which has implications for modeling IN diagnostically, interpreting measurements, and quantifying sensitivity to increasing N(sub IN) (when w(sub e)/v(sub f)〈 1, entrainment rate limitations serve to buffer cloud system response). To reproduce observed ice crystal size distributions and cloud radar reflectivities with rapidly consumed IN in this case, the measured above-cloud N(sub IN) must be multiplied by approximately 30. However, results are sensitive to assumed ice crystal properties not constrained by measurements. In addition, simulations do not reproduce the pronounced mesoscale heterogeneity in radar reflectivity that is observed.

Description: We use the numerically exact superposition T-matrix method to compute the optical cross sections and the Stokes scattering matrix for polydisperse mineral aerosols (modeled as homogeneous spheres) covered with a large number of much smaller soot particles. These results are compared with the Lorenz-Mie results for a uniform external mixture of mineral and soot aerosols. We show that the effect of soot particles adhering to large mineral particles can be to change the extinction and scattering cross sections and the asymmetry parameter quite substantially. The effect on the phase function and degree of linear polarization can be equally significant.

Description: Atmospheric general circulation model (AGCM) cloud parameterizations generally include an assumption about the subgrid-scale probability distribution function (PDF) of total water and its vertical profile. In the present study, the Atmospheric Infrared Sounder (AIRS) monthly-mean cloud amount and relative humidity fields are used to compute a proxy for the second moment of an AGCM total water PDF called the RH01 diagnostic, which is the AIRS mean relative humidity for cloud fractions of 0.1 or less. The dependence of the second moment on horizontal grid resolution is analyzed using results from a high-resolution global model simulation.The AIRS-derived RH01 diagnostic is generally larger near the surface than aloft, indicating a narrower PDF near the surface, and varies with the type of underlying surface. High-resolution model results show that the vertical structure of profiles of the AGCM PDF second moment is unchanged as the grid resolution changes from 200 to 100 to 50 km, and that the second-moment profiles shift toward higher values with decreasing grid spacing.Several Goddard Earth Observing System, version 5 (GEOS-5), AGCM simulations were performed with several choices for the profile of the PDF second moment. The resulting cloud and relative humidity fields were shown to be quite sensitive to the prescribed profile, and the use of a profile based on the AIRS-derived proxy results in improvements relative to observational estimates. The AIRS-guided total water PDF profiles, including their dependence on underlying surface type and on horizontal resolution, have been implemented in the version of the GEOS-5 AGCM used for publicly released simulations.

Description: Forecast skill of the APEC Climate Center (APCC) Multi-Model Ensemble (MME) seasonal forecast system in predicting two main types of El Nino-Southern Oscillation (ENSO), namely canonical (or cold tongue) and Modoki ENSO, and their regional climate impacts is assessed for boreal winter. The APCC MME is constructed by simple composite of ensemble forecasts from five independent coupled ocean-atmosphere climate models. Based on a hindcast set targeting boreal winter prediction for the period 19822004, we show that the MME can predict and discern the important differences in the patterns of tropical Pacific sea surface temperature anomaly between the canonical and Modoki ENSO one and four month ahead. Importantly, the four month lead MME beats the persistent forecast. The MME reasonably predicts the distinct impacts of the canonical ENSO, including the strong winter monsoon rainfall over East Asia, the below normal rainfall and above normal temperature over Australia, the anomalously wet conditions across the south and cold conditions over the whole area of USA, and the anomalously dry conditions over South America. However, there are some limitations in capturing its regional impacts, especially, over Australasia and tropical South America at a lead time of one and four months. Nonetheless, forecast skills for rainfall and temperature over East Asia and North America during ENSO Modoki are comparable to or slightly higher than those during canonical ENSO events.

Description: This study develops more computationally efficient versions of the TwO-Moment Aerosol Sectional (TOMAS) microphysics algorithms, collectively called Fast TOMAS. Several methods for speeding up the algorithm were attempted, but only reducing the number of size sections was adopted. Fast TOMAS models, coupled to the GISS GCM II-prime, require a new coagulation algorithm with less restrictive size resolution assumptions but only minor changes in other processes. Fast TOMAS models have been evaluated in a box model against analytical solutions of coagulation and condensation and in a 3-D model against the original TOMAS (TOMAS-30) model. Condensation and coagulation in the Fast TOMAS models agree well with the analytical solution but show slightly more bias than the TOMAS-30 box model. In the 3-D model, errors resulting from decreased size resolution in each process (i.e., emissions, cloud processing wet deposition, microphysics) are quantified in a series of model sensitivity simulations. Errors resulting from lower size resolution in condensation and coagulation, defined as the microphysics error, affect number and mass concentrations by only a few percent. The microphysics error in CN70CN100 (number concentrations of particles larger than 70100 nm diameter), proxies for cloud condensation nuclei, range from 5 to 5 in most regions. The largest errors are associated with decreasing the size resolution in the cloud processing wet deposition calculations, defined as cloud-processing error, and range from 20 to 15 in most regions for CN70CN100 concentrations. Overall, the Fast TOMAS models increase the computational speed by 2 to 3 times with only small numerical errors stemming from condensation and coagulation calculations when compared to TOMAS-30. The faster versions of the TOMAS model allow for the longer, multi-year simulations required to assess aerosol effects on cloud lifetime and precipitation.

Description: During the development phase of the TRMM mission, the decision was made that no near-realtime (NRT) system would be available during the TRMM 5 year extended mission period. Concern about the costs that might be incurred by requiring such an additional capability In 2000 the TRMM project scientist felt that a best effort should be made to provide such an ability for TRMM. The addition of this best-effort capability has added greatly to the utility of TRMM to the community especially the applications community. This paper will describe the current TRMM NRT products, how they are derived their availability and accessing them. It will provide some examples of how these products have been used.

Description: We still have a way to go to develop a global climatology of aerosol type from the EOS-era satellite data record that currently spans more than 12 years of observations. We have demonstrated the ability to retrieve aerosol type regionally, providing a classification based on the combined constraints on particle size, shape, and single-scattering albedo (SSA) from the MISR instrument. Under good but not necessarily ideal conditions, the MISR data can distinguish three-to-five size bins, two-to-four bins in SSA, and spherical vs. non-spherical particles. However, retrieval sensitivity varies enormously with scene conditions. So, for example, there is less information about aerosol type when the mid-visible aerosol optical depth (AOD) is less that about 0.15 or 0.2.

Description: An initialization strategy, tailored to the prediction of the Madden-Julian oscillation (MJO), is evaluated using the Goddard Earth Observing System Model, version 5 (GEOS-5), coupled general circulation model (CGCM). The approach is based on the empirical singular vectors (ESVs) of a reduced-space statistically determined linear approximation of the full nonlinear CGCM. The initial ESV, extracted using 10 years (1990-99) of boreal winter hindcast data, has zonal wind anomalies over the western Indian Ocean, while the final ESV (at a forecast lead time of 10 days) reflects a propagation of the zonal wind anomalies to the east over the Maritime Continent an evolution that is characteristic of the MJO. A new set of ensemble hindcasts are produced for the boreal winter season from 1990 to 1999 in which the leading ESV provides the initial perturbations. The results are compared with those from a set of control hindcasts generated using random perturbations. It is shown that the ESV-based predictions have a systematically higher bivariate correlation skill in predicting the MJO compared to those using the random perturbations. Furthermore, the improvement in the skill depends on the phase of the MJO. The ESV is particularly effective in increasing the forecast skill during those phases of the MJO in which the control has low skill (with correlations increasing by as much as 0.2 at 20 25-day lead times), as well as during those times in which the MJO is weak.

Description: This work presents a novel formulation of the ice nucleation spectrum, i.e. the function relating the ice crystal concentration to cloud formation conditions and aerosol properties. The new formulation is physically-based and explicitly accounts for the dependency of the ice crystal concentration on temperature, supersaturation, cooling rate, and particle size, surface area and composition. This is achieved by introducing the concepts of ice nucleation coefficient (the number of ice germs present in a particle) and nucleation probability dispersion function (the distribution of ice nucleation coefficients within the aerosol population). The new formulation is used to generate ice nucleation parameterizations for the homogeneous freezing of cloud droplets and the heterogeneous deposition ice nucleation on dust and soot ice nuclei. For homogeneous freezing, it was found that by increasing the dispersion in the droplet volume distribution the fraction of supercooled droplets in the population increases. For heterogeneous ice nucleation the new formulation consistently describes singular and stochastic behavior within a single framework. Using a fundamentally stochastic approach, both cooling rate independence and constancy of the ice nucleation fraction over time, features typically associated with singular behavior, were reproduced. Analysis of the temporal dependency of the ice nucleation spectrum suggested that experimental methods that measure the ice nucleation fraction over few seconds would tend to underestimate the ice nuclei concentration. It is shown that inferring the aerosol heterogeneous ice nucleation properties from measurements of the onset supersaturation and temperature may carry significant error as the variability in ice nucleation properties within the aerosol population is not accounted for. This work provides a simple and rigorous ice nucleation framework where theoretical predictions, laboratory measurements and field campaign data can be reconciled, and that is suitable for application in atmospheric modeling studies.

Description: No abstract available

Description: Nov 2011: NASA/JPL declared CloudSat fully operational in DO ]OP Mode . CloudSat collects science data during sunlit portion of orbit, stable spin hibernation in eclipse . New CONOPS requires constant monitoring of thermal and power profiles, while allowing collection of 54 mins of science data per sunlit orbit

Description: The objective of this is to provide the community of researchers that will access and evaluate the Coupled Model Intercomparison Project Phase 5 (CMIP5) model results access to analogous, analogous sets in terms of periods, variables, temporal/spatial frequency, sets of observational data. A collaborative effort between JPL/NASA and PCMDI is underway to provide the community of researchers that will access and evaluate the CMIP5 model results access to analogous sets of observational data. A number of NASA satellite data sets have been identified that have model equivalents. Thus far: AIRS, MLS, TES, QuikSCAT, CloudSat, Topex/Poseidon, CERES, TRMM, AMSR-E have been identified.

Description: Launch directors need to know upper-level wind forecasts. We developed an Excel-based GUI to display upper-level winds: (1) Rawinsonde at CCAFS, (2) Wind profilers at KSC, (3) Model point data at CCAFS.

Description: Long-term climate data records about aerosols are needed in order to improve understanding of air quality, radiative forcing, and for many other applications. The Sea-viewing Wide Field-of-view Sensor (SeaWiFS) provides a global well-calibrated 13- year (1997-2010) record of top-of-atmosphere radiance, suitable for use in retrieval of atmospheric aerosol optical depth (AOD). Recently, global aerosol products derived from SeaWiFS with Deep Blue algorithm (SWDB) have become available for the entire mission, as part of the NASA Making Earth Science data records for Use in Research for Earth Science (MEaSUREs) program. The latest Deep Blue algorithm retrieves aerosol properties not only over bright desert surfaces, but also vegetated surfaces, oceans, and inland water bodies. Comparisons with AERONET observations have shown that the data are suitable for quantitative scientific use [1],[2]. The resolution of Level 2 pixels is 13.5x13.5 km2 at the center of the swath. Level 3 daily and monthly data are composed by using best quality level 2 pixels at resolution of both 0.5ox0.5o and 1.0ox1.0o. Focusing on the southwest Asia region, this presentation shows seasonal variations of AOD, and the result of comparisons of 5-years (2003- 2007) of AOD from SWDB (Version 3) and MODIS Aqua (Version 5.1) for Dark Target (MYD-DT) and Deep Blue (MYD-DB) algorithms.

Description: The Atmospheric Infrared Sounder (AIRS) is a hyperspectral infrared instrument on the Earth Observing System (EOS) Aqua Spacecraft, launched on May 4, 2002 into a near polar sun-synchronous orbit. AIRS has 2378 infrared channels ranging from 3.7 ?m to 15.4 ?m and a 13.5 km footprint at nadir. AIRS, in conjunction with the Advanced Microwave Sounding Unit (AMSU), produces temperature profiles with 1K/km accuracy on a global scale, as well as water vapor profiles and trace gas amounts for CO2, CO, SO2, O3 and CH4. AIRS CO2 climatologies have been shown to be useful for identifying anomalies associated with geophysical events such as El Nino-Southern Oscillation or Madden-Julian oscillation. In this study, monthly representations of mid-tropospheric CO2 are constructed from 10 years of AIRS Version 5 monthly Level 3 data. We compare the AIRS mid-tropospheric CO2 representations to ground-based measurements from the Scripps and National Oceanic and Atmospheric Administration Climate Modeling and Diagnostics Laboratory (NOAA CMDL) ground networks to better understand the phase lag of the CO2 seasonal cycle between the surface and middle troposphere. Results show only a small phase lag in the tropics that grows to approximately two months in the northern latitudes.

Description: No abstract available

Description: An improved cloud/snow screening technique in the Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithm is described. It is implemented as part of MAIAC aerosol retrievals based on analysis of spectral residuals and spatial variability. Comparisons with AERONET aerosol observations and a large-scale MODIS data analysis show strong suppression of aerosol optical thickness outliers due to unresolved clouds and snow. At the same time, the developed filter does not reduce the aerosol retrieval capability at high 1 km resolution in strongly inhomogeneous environments, such as near centers of the active fires. Despite significant improvement, the optical depth outliers in high spatial resolution data are and will remain the problem to be addressed by the application-dependent specialized filtering techniques.

Description: Quantifying above-cloud aerosols can help improve the assessment of aerosol intercontinental transport and climate impacts. Large-scale measurements of aerosol above low-level clouds had been generally unexplored until very recently when CALIPSO lidar started to acquire aerosol and cloud profiles in June 2006. Despite CALIPSO s unique capability of measuring above-cloud aerosol optical depth (AOD), such observations are substantially limited in spatial coverage because of the lidar s near-zero swath. We developed an approach that integrates measurements from A-Train satellite sensors (including CALIPSO lidar, OMI, and MODIS) to extend CALIPSO above-cloud AOD observations to substantially larger areas. We first examine relationships between collocated CALIPSO above-cloud AOD and OMI absorbing aerosol index (AI, a qualitative measure of AOD for elevated dust and smoke aerosol) as a function of MODIS cloud optical depth (COD) by using 8-month data in the Saharan dust outflow and southwest African smoke outflow regions. The analysis shows that for a given cloud albedo, above-cloud AOD correlates positively with AI in a linear manner. We then apply the derived relationships with MODIS COD and OMI AI measurements to derive above-cloud AOD over the whole outflow regions. In this talk, we will present spatial and day-to-day variations of the above-cloud AOD and the estimated direct radiative forcing by the above-cloud aerosols.

Description: No abstract available

Description: Since June 2010, the NASA Short-term Prediction Research and Transition (SPoRT; Goodman et al. 2004; Darden et al. 2010; Stano et al. 2012; Fuell et al. 2012) Center has been generating a real-time Normalized Difference Vegetation Index (NDVI) and corresponding Green Vegetation Fraction (GVF) composite based on reflectances from NASA s Moderate Resolution Imaging Spectroradiometer (MODIS) instrument. This dataset is generated at 0.01 resolution across the Continental United States (CONUS), and updated daily. The goal of producing such a vegetation dataset is to improve over the default climatological GVF dataset in land surface and numerical weather prediction models, in order to have better simulations of heat and moisture exchange between the land surface and the planetary boundary layer. Details on the SPoRT/MODIS vegetation composite algorithm are presented in Case et al. (2011). Vegetation indices such as GVF and Leaf Area Index (LAI) are used by land surface models (LSMs) to represent the horizontal and vertical density of plant vegetation (Gutman and Ignatov 1998), in order to calculate transpiration, interception and radiative shading. Both of these indices are related to the NDVI; however, there is an inherent ambiguity in determining GVF and LAI simultaneously from NDVI, as described in Gutman and Ignatov (1998). One practice is to specify the LAI while allowing the GVF to vary both spatially and temporally, as is done in the Noah LSM (Chen and Dudhia 2001; Ek et al. 2003). Operational versions of Noah within several of the National Centers for Environmental Prediction (NCEP) global and regional modeling systems hold the LAI fixed, while the GVF varies according to a global monthly climatology. This GVF climatology was derived from NDVI data on the NOAA Advanced Very High Resolution Radiometer (AVHRR) polar orbiting satellite, using information from 1985 to 1991 (Gutman and Ignatov 1998; Jiang et al. 2010). Representing data at the mid-point of every month, the climatological dataset is on a grid with 0.144 (~16 km) spatial resolution and is distributed with the community WRF model (Ek et al. 2003; Jiang et al. 2010; Skamarock et al. 2008).

Description: Previous studies (e.g., Zhang et al. 2009, Weng et al. 2011) have shown that radial velocity data from airborne and ground-based radars can be assimilated into ensemble Kalman filter (EnKF) systems to produce accurate analyses of tropical cyclone vortices, which can reduce forecast intensity error. Recently, wind speed data from SFMR technology has also been assimilated into the same types of systems and has been shown to improve the forecast intensity of mature tropical cyclones. Two instruments that measure these properties were present during the NASA Genesis and Rapid Intensification Processes (GRIP) field experiment in 2010 which sampled Hurricane Karl, and will next be co-located on the same aircraft for the subsequent NASA HS3 experiment. The High Altitude Wind and Rain Profiling Radar (HIWRAP) is a conically scanning Doppler radar mounted upon NASAs Global Hawk unmanned aerial vehicle, and the usefulness of its radial velocity data for assimilation has not been previously examined. Since the radar scans from above with a fairly large fixed elevation angle, it observes a large component of the vertical wind, which could degrade EnKF analyses compared to analyses with data taken from lesser elevation angles. The NASA Hurricane Imaging Radiometer (HIRAD) is a passive microwave radiometer similar to SFMR, and measures emissivity and retrieves hurricane surface wind speeds and rain rates over a much wider swath. Thus, this study examines the impact of assimilating simulated HIWRAP radial velocity data into an EnKF system, simulated HIRAD wind speed, and HIWRAP+HIRAD with the Weather Research and Forecasting (WRF) model and compares the results to no data assimilation and also to the Truth from which the data was simulated for both instruments.

Description: No abstract available

Description: NASA Research Addresses Broad Questions: (1) How are global ecosystems changing? (2) What changes are occurring in global land cover and land use and what are their causes? (3) How is the Earth s surface being transformed and how can such information be used to predict future changes? (4) What are the consequences of land cover and land use change for the sustainability of ecosystems and economic productivity? NASA uses the view from above to monitor our changing home. Different satellites help us study the various systems of the Earth. No one system can do it all. NASA tools and science helps us to understand how the planet is changing and what the changes mean for us.

Description: Short-term Prediction Research and Transition Center (SPoRT) is a proven community leader for transitioning satellite products to operational end users and is working hard to bring data from Atmospheric Infrared Sounder (AIRS) to forecasters. SPoRT products using AIRS data are currently or will soon be evaluated at WFOs and National Centers (1) T and q profiles: HWT, Alaska WFOs, HRD/OPC, HMT (2) Ozone profiles: HPC/OPC (3) Carbon Monoxide: Southern and Western Region WFOs SPoRT is actively evaluating differences between V5 and V6 profiles for selected cases and will continue to provide feedback to the AIRS team as V6 development efforts conclude.

Description: Titan's northern spring equinox occurred in August 2009. General Circulation Models (e.g. Lebonnois et al., 2012) predict strong modifications of the global circulation in this period, with formation of two circulation cells instead of the pole-to-pole cell that occurred during northern winter. This winter single cell, which had its descending branch at the north pole, was at the origin of the enrichment of molecular abundances and high stratopause temperatures observed by Cassini/CIRS at high northern latitudes (e.g. Achterberg et al., 2011, Coustenis et al., 2010, Teanby et al., 2008, Vinatier et al., 2010). The predicted dynamical seasonal variations after the equinox have strong impact on the spatial distributions of trace gas, temperature and aerosol abundances. We will present here an analysis of CIRS limb-geometry datasets acquired in 2010 and 2011 that we used to monitor the seasonal evolution of the vertical profiles of temperature, molecular (C2H2, C2H6, HCN, ..) and aerosol abundances.

Description: Model results will be reviewed to assess different methods for bounding the terrestrial role in the global carbon cycle. It is proposed that a series of climate model runs could be scoped that would tighten the limits on the "missing sink" of terrestrial carbon and could also direct future satellite image analyses to search for its geographical location and understand its seasonal dynamics.

Description: No abstract available

Description: In July 2011, improved versions of the retrieval algorithms were approved for TRMM. All data starting with June 2011 are produced only with the version 7 code. At the same time, version 7 reprocessing of all TRMM mission data was started. By the end of August 2011, the 14+ years of the reprocessed mission data became available online to users. This reprocessing provided the opportunity to redo and enhance upon an analysis of V7 impacts on L3 data accumulations that was presented at the 2010 EGU General Assembly. This paper will discuss the impact of algorithm changes made in th GPROF retrieval on the Level 2 swath products. Perhaps the most important change in that retrieval was to replacement of a model based a priori database with one created from Precipitation Radar (PR) and TMI brightness temperature (Tb) data. The radar pays a major role in the V7 GPROF (GPROF2010) in determining existence of rain. The level 2 retrieval algorithm also introduced a field providing the probability of rain. This combined use of the PR has some impact on the retrievals and created areas, particularly over ocean, where many areas of low-probability precipitation are retrieved whereas in version 6, these areas contained zero rain rates. This paper will discuss how these impacts get translated to the space/time averaged monthly products that use the GPROF retrievals. The level 3 products discussed are the gridded text product 3G68 and the standard 3A12 and 3B31 products. The paper provides an overview of the changes and explanation of how the level 3 products dealt with the change in the retrieval approach. Using the .25 deg x .25 degree grid, the paper will show that agreement between the swath product and the level 3 remains very high. It will also present comparisons of V6 and V7 GPROF retrievals as seen both at the swath level and the level 3 time/space gridded accumulations. It will show that the various L3 products based on GPROF level 2 retrievals are in close agreement. The paper concludes by outlining some of the challenges of the TRMM version 7 level 3 products.

Description: A new comprehensive lightning instrumentation system has been designed for Launch Complex 39B (LC39B) at the Kennedy Space Center, Florida. This new instrumentation system includes seven synchronized high-speed video cameras, current sensors installed on the nine downconductors of the new lightning protection system (LPS) for LC39B; four dH/dt, 3-axis measurement stations; and five dE/dt stations composed of two antennas each. The LPS received 8 direct lightning strikes (a total of 19 strokes) from March 31 through December 31 2011. The measured peak currents and locations are compared to those reported by the Cloud-to-Ground Lightning Surveillance System (CGLSS II) and the National Lightning Detection Network (NLDN). Results of comparison are presented and analyzed in this paper.

Description: Climate change occurs when the Earth's energy budget changes due to natural or possibly anthropogenic forcings. These forcings cause the climate system to adjust resulting in a new climate state that is warmer or cooler than the original. The key question is how to detect and attribute climate change. The inference of infrared spectral signatures of climate change has been discussed in the literature for nearly 30 years. Pioneering work in the 1980s noted that distinct spectral signatures would be evident in changes in the infrared radiance emitted by the Earth and its atmosphere, and that these could be observed from orbiting satellites. Since then, a number of other studies have advanced the concepts of spectral signatures of climate change. Today the concept of using spectral signatures to identify and attribute atmospheric composition change is firmly accepted and is the foundation of the Climate Absolute Radiance and Refractivity Observatory (CLARREO) satellite mission being developed at NASA. In this work, we will present an overview of the current climate change detection concept using climate model calculations as surrogates for climate change. Any future research work improving the methodology to achieve this concept will be valuable to our society.

Description: Data-enhanced Investigations for Climate Change Education (DICCE), a NASA climate change education project, employs the NASA Giovanni data system to enable teachers to create climate-related classroom projects using selected satellite and assimilated model data. The easy-to-use DICCE Giovanni portal (DICCE-G) provides data parameters relevant to oceanic, terrestrial, and atmospheric processes. Participants will explore land-ocean linkages using the available data in the DICCE-G portal, in particular focusing on temperature, ocean biology, and precipitation variability related to El Ni?o and La Ni?a events. The demonstration includes the enhanced information for educators developed for the DICCE-G portal. The prototype DICCE Learning Environment (DICCE-LE) for classroom project development will also be demonstrated.

Description: This paper describes building energy system production and usage monitoring using examples from the new RETScreen Performance Analysis Module, called RETScreen Plus. The module uses daily meteorological (i.e., temperature, humidity, wind and solar, etc.) over a period of time to derive a building system function that is used to monitor building performance. The new module can also be used to target building systems with enhanced technologies. If daily ambient meteorological and solar information are not available, these are obtained over the internet from NASA's near-term data products that provide global meteorological and solar information within 3-6 days of real-time. The accuracy of the NASA data are shown to be excellent for this purpose enabling RETScreen Plus to easily detect changes in the system function and efficiency. This is shown by several examples, one of which is a new building at the NASA Langley Research Center that uses solar panels to provide electrical energy for building energy and excess energy for other uses. The system shows steady performance within the uncertainties of the input data. The other example involves assessing the reduction in energy usage by an apartment building in Sweden before and after an energy efficiency upgrade. In this case, savings up to 16% are shown.

Description: Four different types of estimates of the surface downwelling longwave radiative flux (DLR) are reviewed. One group of estimates synthesizes global cloud, aerosol, and other information in a radiation model that is used to calculate fluxes. Because these synthesis fluxes have been assessed against observations, the global-mean values of these fluxes are deemed to be the most credible of the four different categories reviewed. The global, annual mean DLR lies between approximately 344 and 350 W/sq m with an error of approximately +/-10 W/sq m that arises mostly from the uncertainty in atmospheric state that governs the estimation of the clear-sky emission. The authors conclude that the DLR derived from global climate models are biased low by approximately 10 W/sq m and even larger differences are found with respect to reanalysis climate data. The DLR inferred from a surface energy balance closure is also substantially smaller that the range found from synthesis products suggesting that current depictions of surface energy balance also require revision. The effect of clouds on the DLR, largely facilitated by the new cloud base information from the CloudSat radar, is estimated to lie in the range from 24 to 34 W/sq m for the global cloud radiative effect (all-sky minus clear-sky DLR). This effect is strongly modulated by the underlying water vapor that gives rise to a maximum sensitivity of the DLR to cloud occurring in the colder drier regions of the planet. The bottom of atmosphere (BOA) cloud effect directly contrast the effect of clouds on the top of atmosphere (TOA) fluxes that is maximum in regions of deepest and coldest clouds in the moist tropics.

Description: 2011 was marked as one of the most extreme years in recent history. Over the course of the year, weather-related extreme events, such as floods, heat waves, blizzards, tornadoes, and wildfires, caused tremendous loss of human life and property. The North American Land Data Assimilation System (NLDAS, http://ldas.gsfc.nasa.gov/nldas/) data set, with high spatial and temporal resolutions (0.125? x 0.125?, hourly) and various water- and energy-related variables, is an excellent data source for case studies of extreme events. This presentation illustrates some extreme events from 2011 in North America, including the Groundhog Day Blizzard, the July heat wave, Hurricane Irene, and Tropical Storm Lee, all utilizing NLDAS Phase 2 (NLDAS-2) data.

Description: Evapotranspiration (ET) is the water lost to the atmosphere by evaporation and transpiration. ET is a shared component in the energy and water budget, therefore, a critical variable for global energy and water cycle and climate change studies. However, direct ET measurements and data acquisition are difficult and expensive, especially at the global level. Therefore, modeling is one common alternative for estimating ET. With the goal to generate optimal fields of land surface states and fluxes, the Global Land Data Assimilation System (GLDAS) has been generating quality-controlled, spatially and temporally consistent, terrestrial hydrologic data, including ET and other variables that affect evaporation and transpiration, such as temperature, precipitation, humidity, wind, soil moisture, heat flux, and solar radiation. This poster presents the long-term ET climatology (mean and monthly), derived from the 61-year GLDAS-2 monthly 1.0 deg x 1.0 deg. NOAH model Experiment-1 data, and describes the basic characteristics of spatial and seasonal variations of the climatology. The time series of GLDAS-2 precipitation and radiation, and ET are also discussed to show the improvement of GLDAS-2 forcing data and model output over those from GLDAS-1.

Description: The NASA Goddard Earth Sciences Data and Information Services Center (GES DISC) is home of global precipitation product archives, in particular, the Tropical Rainfall Measuring Mission (TRMM) products. TRMM is a joint U.S.-Japan satellite mission to monitor tropical and subtropical (40 S - 40 N) precipitation and to estimate its associated latent heating. The TRMM satellite provides the first detailed and comprehensive dataset on the four dimensional distribution of rainfall and latent heating over vastly undersampled tropical and subtropical oceans and continents. The TRMM satellite was launched on November 27, 1997. TRMM data products are archived at and distributed by GES DISC. The newly released TRMM Version 7 consists of several changes including new parameters, new products, meta data, data structures, etc. For example, hydrometeor profiles in 2A12 now have 28 layers (14 in V6). New parameters have been added to several popular Level-3 products, such as, 3B42, 3B43. Version 2.2 of the Global Precipitation Climatology Project (GPCP) dataset has been added to the TRMM Online Visualization and Analysis System (TOVAS; URL: http://disc2.nascom.nasa.gov/Giovanni/tovas/), allowing online analysis and visualization without downloading data and software. The GPCP dataset extends back to 1979. Version 3 of the Global Precipitation Climatology Centre (GPCC) monitoring product has been updated in TOVAS as well. The product provides global gauge-based monthly rainfall along with number of gauges per grid. The dataset begins in January 1986. To facilitate data and information access and support precipitation research and applications, we have developed a Precipitation Data and Information Services Center (PDISC; URL: http://disc.gsfc.nasa.gov/precipitation). In addition to TRMM, PDISC provides current and past observational precipitation data. Users can access precipitation data archives consisting of both remote sensing and in-situ observations. Users can use these data products to conduct a wide variety of activities, including case studies, model evaluation, uncertainty investigation, etc. To support Earth science applications, PDISC provides users near-real-time precipitation products over the Internet. At PDISC, users can access tools and software. Documentation, FAQ and assistance are also available. Other capabilities include: 1) Mirador (http://mirador.gsfc.nasa.gov/), a simplified interface for searching, browsing, and ordering Earth science data at NASA Goddard Earth Sciences Data and Information Services Center (GES DISC). Mirador is designed to be fast and easy to learn; 2)TOVAS; 3) NetCDF data download for the GIS community; 4) Data via OPeNDAP (http://disc.sci.gsfc.nasa.gov/services/opendap/). The OPeNDAP provides remote access to individual variables within datasets in a form usable by many tools, such as IDV, McIDAS-V, Panoply, Ferret and GrADS; 5) The Open Geospatial Consortium (OGC) Web Map Service (WMS) (http://disc.sci.gsfc.nasa.gov/services/wxs_ogc.shtml). The WMS is an interface that allows the use of data and enables clients to build customized maps with data coming from a different network.

Description: Data services to support precipitation applications are important for maximizing the NASA TRMM (Tropical Rainfall Measuring Mission) and the future GPM (Global Precipitation Mission) mission's societal benefits. TRMM Application examples using data services at the NASA GES DISC, including samples from users around the world will be presented in this poster. Precipitation applications often require near-real-time support. The GES DISC provides such support through: 1) Providing near-real-time precipitation products through TOVAS; 2) Maps of current conditions for monitoring precipitation and its anomaly around the world; 3) A user friendly tool (TOVAS) to analyze and visualize near-real-time and historical precipitation products; and 4) The GES DISC Hurricane Portal that provides near-real-time monitoring services for the Atlantic basin. Since the launch of TRMM, the GES DISC has developed data services to support precipitation applications around the world. In addition to the near-real-time services, other services include: 1) User friendly TRMM Online Visualization and Analysis System (TOVAS; URL: http://disc2.nascom.nasa.gov/Giovanni/tovas/); 2) Mirador (http://mirador.gsfc.nasa.gov/), a simplified interface for searching, browsing, and ordering Earth science data at GES DISC. Mirador is designed to be fast and easy to learn; 3) Data via OPeNDAP (http://disc.sci.gsfc.nasa.gov/services/opendap/). The OPeNDAP provides remote access to individual variables within datasets in a form usable by many tools, such as IDV, McIDAS-V, Panoply, Ferret and GrADS; and 4) The Open Geospatial Consortium (OGC) Web Map Service (WMS) (http://disc.sci.gsfc.nasa.gov/services/wxs_ogc.shtml). The WMS is an interface that allows the use of data and enables clients to build customized maps with data coming from a different network.

Description: A pulsed 2-micron coherent Doppler lidar system at NASA Langley Research Center in Virginia flew on the NASA's DC-8 aircraft during the NASA Genesis and Rapid Intensification Processes (GRIP) during the summer of 2010. The participation was part of the project Doppler Aerosol Wind Lidar (DAWN) Air. Selected results of airborne wind profiling are presented and compared with the dropsonde data for verification purposes. Panoramic presentations of different wind parameters over a nominal observation time span are also presented for selected GRIP data sets. The realtime data acquisition and analysis software that was employed during the GRIP campaign is introduced with its unique features.

Description: Short-term Prediction Research and Transition (SPoRT) seeks to improve short-term, regional weather forecasts using unique NASA products and capabilities SPoRT has developed a unique, real-time configuration of the NASA Unified Weather Research and Forecasting (WRF)WRF (ARW) that integrates all SPoRT modeling research data: (1) 2-km SPoRT Sea Surface Temperature (SST) Composite, (2) 3-km LIS with 1-km Greenness Vegetation Fraction (GVFs) (3) 45-km AIRS retrieved profiles. Transitioned this real-time forecast to NOAA's Hazardous Weather Testbed (HWT) as deterministic model at Experimental Forecast Program (EFP). Feedback from forecasters/participants and internal evaluation of SPoRT-WRF shows a cool, dry bias that appears to suppress convection likely related to methodology for assimilation of AIRS profiles Version 2 of the SPoRT-WRF will premier at the 2012 EFP and include NASA physics, cycling data assimilation methodology, better coverage of precipitation forcing, and new GVFs

Description: No abstract available

Description: Objective 2.1.1: Improve understanding of and improve the predictive capability for changes in the ozone layer, climate forcing, and air quality associated with changes in atmospheric composition. Objective 2.1.2: Enable improved predictive capability for weather and extreme weather events. Objective 2.1.3: Quantify, understand, and predict changes in Earth s ecosystems and biogeochemical cycles, including the global carbon cycle, land cover, and biodiversity. Objective 2.1.4: Quantify the key reservoirs and fluxes in the global water cycle and assess water cycle change and water quality. Objective 2.1.5: Improve understanding of the roles of the ocean, atmosphere, land and ice in the climate system and improve predictive capability for its future evolution. Objective 2.1.6: Characterize the dynamics of Earth s surface and interior and form the scientific basis for the assessment and mitigation of natural hazards and response to rare and extreme events. Objective 2.1.7: Enable the broad use of Earth system science observations and results in decision-making activities for societal benefits.

Description: Convective weather is responsible for large delays and widespread disruptions in the U.S. National Airspace System, especially during summer. Traffic flow management algorithms require reliable forecasts of route blockage to schedule and route traffic. This paper demonstrates how raw convective weather forecasts, which provide deterministic predictions of the vertically integrated liquid (the precipitation content in a column of airspace) can be translated into probabilistic forecasts of whether or not a terminal area route will be blocked. Given a flight route through the terminal area, we apply techniques from machine learning to determine the likelihood that the route will be open in actual weather. The likelihood is then used to optimize terminalarea operations by dynamically moving arrival and departure routes to maximize the expected capacity of the terminal area. Experiments using real weather scenarios on stormy days show that our algorithms recommend that a terminal-area route be modified 30% of the time, opening up 13% more available routes that were forecast to be blocked during these scenarios. The error rate is low, with only 5% of cases corresponding to a modified route being blocked in reality, whereas the original route is in fact open. In addition, for routes predicted to be open with probability 0.95 or greater by our method, 96% of these routes (on average over time horizon) are indeed open in the weather that materializes

Description: The North American Land Data Assimilation System (NLDAS) is a collaborative project between NASA GSFC, NOAA, Princeton University, and the University of Washington. NLDAS has created surface meteorological forcing data sets using the best-available observations and reanalyses. The forcing data sets are used to drive four separate land-surface models (LSMs), Mosaic, Noah, VIC, and SAC, to produce data sets of soil moisture, snow, runoff, and surface fluxes. NLDAS hourly data, accessible from the NASA GES DISC Hydrology Data Holdings Portal, http://disc.sci.gsfc.nasa.gov/hydrology/data-holdings, are widely used by various user communities in modeling, research, and applications, such as drought and flood monitoring, watershed and water quality management, and case studies of extreme events. More information is available at http://ldas.gsfc.nasa.gov/. To further facilitate analysis of water and energy budgets and trends, NLDAS monthly data sets have been recently released by NASA GES DISC.

Description: No abstract available