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NASA NTRS2004

Observing the Global Water Cycle from Space

This paper presents an approach to measuring all major components of the water cycle from space. Key elements of the global water cycle are discussed in terms of the storage of water-in the ocean, air, cloud and precipitation, in soil, ground water, snow and ice, and in lakes and rivers, and in terms of the global fluxes of water between these reservoirs. Approaches to measuring or otherwise evaluating the global water cycle are presented, and the limitations on known accuracy for many components of the water cycle are discussed, as are the characteristic spatial and temporal scales of the different water cycle components. Using these observational requirements for a global water cycle observing system, an approach to measuring the global water cycle from space is developed. The capabilities of various active and passive microwave instruments are discussed, as is the potential of supporting measurements from other sources. Examples of space observational systems, including TRMM/GPM precipitation measurement, cloud radars, soil moisture, sea surface salinity, temperature and humidity profiling, other measurement approaches and assimilation of the microwave and other data into interpretative computer models are discussed to develop the observational possibilities. The selection of orbits is then addressed, for orbit selection and antenna size/beamwidth considerations determine the sampling characteristics for satellite measurement systems. These considerations dictate a particular set of measurement possibilities, which are then matched to the observational sampling requirements based on the science. The results define a network of satellite instrumentation systems, many in low Earth orbit, a few in geostationary orbit, and all tied together through a sampling network that feeds the observations into a data-assimilative computer model.

Hildebrand, P. H.↗
NASA NTRS2005

Comparison of Monthly Mean Cloud Fraction and Cloud Optical depth Determined from Surface Cloud Radar, TOVS, AVHRR, and MODIS over Barrow, Alaska

A one year comparison is made of mean monthly values of cloud fraction and cloud optical depth over Barrow, Alaska (71 deg 19.378 min North, 156 deg 36.934 min West) between 35 GHz radar-based retrievals, the TOVS Pathfinder Path-P product, the AVHRR APP-X product, and a MODIS based cloud retrieval product from the CERES-Team. The data sets represent largely disparate spatial and temporal scales, however, in this paper, the focus is to provide a preliminary analysis of how the mean monthly values derived from these different data sets compare, and determine how they can best be used separately, and in combination to provide reliable estimates of long-term trends of changing cloud properties. The radar and satellite data sets described here incorporate Arctic specific modifications that account for cloud detection challenges specific to the Arctic environment. The year 2000 was chosen for this initial comparison because the cloud radar data was particularly continuous and reliable that year, and all of the satellite retrievals of interest were also available for the year 2000. Cloud fraction was chosen as a comparison variable as accurate detection of cloud is the primary product that is necessary for any other cloud property retrievals. Cloud optical depth was additionally selected as it is likely the single cloud property that is most closely correlated to cloud influences on surface radiation budgets.

Uttal, Taneil↗
NASA NTRS2005

Coupled fvGCM-GCE Modeling System, 3D Cloud-Resolving Model and Cloud Library

Recent GEWEX Cloud System Study (GCSS) model comparison projects have indicated that cloud-resolving models (CRMs) agree with observations better than traditional singlecolumn models in simulating various types of clouds and cloud systems from Merent geographic locations. Current and future NASA satellite programs can provide cloud, precipitation, aerosol and other data at very fine spatial and temporal scales. It requires a coupled global circulation model (GCM) and cloudscale model (termed a super-parameterization or multiscale modeling framework, MMF) to use these satellite data to improve the understanding of the physical processes that are responsible for the variation in global and regional climate and hydrological systems. The use of a GCM will enable global coverage, and the use of a CRM will allow for better and more sophisticated physical parameteridon NASA satellite and field campaign cloud related datasets can provide initial conditions as well as validation for both the MMF and CRMs. A seed fund is available at NASA Goddard to build a MMF based on the 2D Goddard cumulus Ensemble (GCE) model and the Goddard finite volume general circulation model (fvGCM). A prototype MMF in being developed and production nms will be conducted at the beginning of 2005. In this talk, I will present: (1) A brief review on GCE model and its applications on precipitation processes, (2) The Goddard MMF and the major difference between two existing MMFs (CSU MMF and Goddard MMF), (3) A cloud library generated by Goddard MMF, and 3D GCE model, and (4) A brief discussion on the GCE model on developing a global cloud simulator.

Tao, Wei-Kuo↗
NASA NTRS2004

Coupled fvGCM-GCE Modeling System, TRMM Latent Heating and Cloud Library

Recent GEWEX Cloud System Study (GCSS) model comparison projects have indicated that cloud-resolving models (CRMs) agree with observations better than traditional single-column models in simulating various types of clouds and cloud systems from different geographic locations. Current and future NASA satellite programs can provide cloud, precipitation, aerosol and other data at very fine spatial and temporal scales. It requires a coupled global circulation model (GCM) and cloud-scale model (termed a super-parameterization or multi-scale modeling framework, MMF) to use these satellite data to imiprove the understanding of the physical processes that are responsible for the variation in global and regional climate and hydrological systems. The use of a GCM will enable global coverage, and the use of a CRM will allow for better and more sophisticated physical parameterization. NASA satellite and field campaign cloud related datasets can provide initial conditions as well as validation for both the MMF and CRMs. A seed fund is available at NASA Goddard to build a MMF based on the 2D GCE model and the Goddard finite volume general circulation model (fvGCM). A prototype MMF will be developed by the end of 2004 and production runs will be conducted at the beginning of 2005. The purpose of this proposal is to augment the current Goddard MMF and other cloud modeling activities. I this talk, I will present: (1) A summary of the second Cloud Modeling Workshop took place at NASA Goddard, (2) A summary of the third TRMM Latent Heating Workshop took place at Nara Japan, (3) A brief discussion on the Goddard research plan of using Weather Research Forecast (WRF) model, and (4) A brief discussion on the GCE model on developing a global cloud simulator.

Tao, Wei-Kuo↗
NASA NTRS2005

Coupled fvGCM-GCE Modeling System: TRMM Latent Heating and Cloud Library

Recent GEWEX Cloud System Study (GCSS) model comparison projects have indicated that cloud-resolving models (CRMs) agree with observations better than traditional single-column models in simulating various types of clouds and cloud systems from different geographic locations. Current and future NASA satellite programs can provide cloud, precipitation, aerosol and other data at very fine spatial and temporal scales. It requires a coupled global circulation model (GCM) and cloud-scale model (termed a super-parameterization or multi-scale modeling framework, MMF) to use these satellite data to improve the understanding of the physical processes that are responsible for the variation in global and regional climate and hydrological systems. The use of a GCM will enable global coverage, and the use of a CRM will allow for better and more sophisticated physical parameterization. NASA satellite and field campaign cloud related datasets can provide initial conditions as well as validation for both the MMF and CRMs. A seed fund is available at NASA Goddard to build a MMF based on the 2D GCE model and the Goddard finite volume general circulation model (fvGCM). A prototype MMF will be developed by the end of 2004 and production runs will be conducted at the beginning of 2005. The purpose of this proposal is to augment the current Goddard MMF and other cloud modeling activities. In this talk, I will present: (1) A summary of the second Cloud Modeling Workshop took place at NASA Goddard, (2) A summary of the third TRMM Latent Heating Workshop took place at Nara Japan, (3) A brief discussion on the GCE model on developing a global cloud simulator.

Tao, Wei-Kuo↗
NASA NTRS2005

Coupled fvGCM-GCE Modeling System, 3D Cloud-Resolving Model and Cloud Library

Recent GEWEX Cloud System Study (GCSS) model comparison projects have indicated that cloud- resolving models (CRMs) agree with observations better than traditional single-column models in simulating various types of clouds and cloud systems from different geographic locations. Current and future NASA satellite programs can provide cloud, precipitation, aerosol and other data at very fine spatial and temporal scales. It requires a coupled global circulation model (GCM) and cloud-scale model (termed a super-parameterization or multi-scale modeling framework, MMF) to use these satellite data to improve the understanding of the physical processes that are responsible for the variation in global and regional climate and hydrological systems. The use of a GCM will enable global coverage, and the use of a CRM will allow for better and more sophisticated physical parameterization. NASA satellite and field campaign cloud related datasets can provide initial conditions as well as validation for both the MMF and CRMs. A seed fund is available at NASA Goddard to build a MMF based on the 2D Goddard Cumulus Ensemble (GCE) model and the Goddard finite volume general circulation model (fvGCM). A prototype MMF in being developed and production runs will be conducted at the beginning of 2005. In this talk, I will present: (1) A brief review on GCE model and its applications on precipitation processes, ( 2 ) The Goddard MMF and the major difference between two existing MMFs (CSU MMF and Goddard MMF), (3) A cloud library generated by Goddard MMF, and 3D GCE model, and (4) A brief discussion on the GCE model on developing a global cloud simulator.

Tao, Wei-Kuo↗
NASA NTRS2005

Linking Archaeal Molecular Diversity and Lipid Biomarker Composition in a Hypersaline Microbial Mat Community

Lipid biomarkers for discrete microbial groups are a valuable tool for establishing links to ancient microbial ecosystems. Lipid biomarkers can establish organism source and function in contemporary microbial ecosystems (membrane lipids) and by analogy, potential relevance to the fossilized carbon skeletons (geolipids) extracted from ancient sedimentary rock. The Mars Exploration Rovers have provided clear evidence for an early wet Mars and the presence of hypersaline evaporitic basins. Ongoing work on an early Earth analog, the hypersaline benthic mats in Guerrero Negro, Baja California Sur, may provide clues to what may have evolved and flourished on an early wet Mars, if only for a short period. Cyanobacterial mats are a pertinent early Earth analog for consideration of evolutionary and microbial processes within the aerobic photosynthetic and adjacent anoxic layers. Fluctuations in physio-chemical parameters associated with spatial and temporal scales are expressed through vast microbial metabolic diversity. Our recent work hopes to establish the dynamic of archaeal diversity, particularly as it relates to methane production in this high sulfate environment, through the use of lipid biomarker and phylogenetic analyses. Archaeal 16s rRNA and mcrA gene assemblages, demonstrated distinct spatial separation over the 130 mm core of at least three distinct genera within the order Methanosarcinales, as well as an abundance of uncultured members of the Thermoplasmales and Crenarchaeota. Ether-bound lipid analysis identified abundant 0-alkyl and 0-isopranyl chains throughout the core, and the presence of sn-2 hydroxyarchaeol, a biomarker for methylotrophic methanogens. A unique ether isoprenoid chain, a C30:1 , possibly related to the geolipid squalane, a paleobiomarker associated with hypersaline environments, was most abundant within the oxic-anoxic transition zone.

Jahnke, Linda↗
NASA NTRS2006

Satellite Sounder-Based OLR-, Cloud- and Atmospheric Temperature Climatologies for Climate Analyses

Global energy balance of the Earth-atmosphere system may change due to natural and man-made climate variations. For example, changes in the outgoing longwave radiation (OLR) can be regarded as a crucial indicator of climate variations. Clouds play an important role -still insufficiently assessed in the global energy balance on all spatial and temporal scales, and satellites provide an ideal platform to measure cloud and large-scale atmospheric variables simultaneously. The TOVS series of satellites were the first to provide this type of information since 1979. OLR [Mehta and Susskind], cloud cover and cloud top pressure [Susskind et al] are among the key climatic parameters computed by the TOVS Pathfinder Path-A algorithm using mainly the retrieved temperature and moisture profiles. AIRS, regarded as the new and improved TOVS , has a much higher spectral resolution and greater S/N ratio, retrieving climatic parameters with higher accuracy. First we present encouraging agreements between MODIS and AIRS cloud top pressure (C(sub tp) and effective (A(sub eff), a product of infrared emissivity at 11 microns and physical cloud cover or A(sub c)) cloud fraction seasonal and interannual variabilities for selected months. Next we present validation efforts and preliminary trend analyses of TOVS-retrieved C(sub tp) and A(sub eff). For example, decadal global trends of the TOVS Path-A and ISCCP-D2 P(sub c), and A(sub eff)/A(sub c), values are similar. Furthermore, the TOVS Path-A and ISCCP-AVHRR [available since 19831 cloud fractions correlate even more strongly, including regional trends. We also present TOVS and AIRS OLR validation effort results and (for the longer-term TOVS Pathfinder Path-A dataset) trend analyses. OLR interannual spatial variabilities from the available state-of-the-art CERES measurements and both from the AIRS [Susskind et al] and TOVS OLR computations are in remarkably good agreement. Global monthly mean CERES and TOVS OLR time series show very good agreement in absolute values also. Finally, we will assess correlations among long-term trends of selected parameters, derived simultaneously from the TOVS Pathfinder Path-A datase

Molnar, Gyula I.↗
NASA NTRS2006

A Coupled GCM-Cloud Resolving Modeling System to Study Precipitation Processes

Recent GEWEX Cloud System Study (GCSS) model comparison projects have indicated that cloud resolving models (CRMs) agree with observations better than traditional single column models in simulating various types of clouds and cloud systems from different geographic locations. Current and future NASA satellite programs can provide cloud, precipitation, aerosol and other data at very fine spatial and temporal scales. It requires a coupled global circulation model (GCM) and cloud-scale model (termed a super-parameterization or multi-scale modeling framework, MMF) to use these satellite data to improve the understanding of the physical processes that are responsible for the variation in global and regional climate and hydrological systems. The use of a GCM will enable global coverage and the use of a CRM will allow for better and more sophisticated physical parameterization. NASA Satellite and field campaign cloud related data sets can provide initial conditions as well as validation for both the MMF and CRMs. Also we have implemented a Land Information System (LIS that includes the CLM and NOAH land surface models into the MMF. The Goddard MMF is based on the 2D Goddard Cumulus Ensemble (GCE) model and the Goddard finite volume general circulation model (fvGCM) This modeling system has been applied and tested its performance for two different climate scenarios, El Nino (1998) and La Nina (1999). The coupled new modeling system produced more realistic propagation and intensity of tropical rainfall systems and intraseasonal oscillations, and diurnal variation of precipitation that are very difficult to forecast using even the state-of-the-art GCMs. In this talk I will present: (1) a brief review on GCE model and its applications on precipitation processes (both Microphysical and land processes) and (2) The Goddard MMF and the Major difference between two existing MMFs (CSU MMF and Goddard MMF) and preliminary results (the comparison with traditional GCMs).

Tao, Wei-Kuo↗
NASA NTRS2002

Ocean state estimation for climate studies

Climate variabilities, which are of interest to CLIVAR, involve a broad range of spatial and temporal scales. Ocean state estimation (often referred to as ocean data assimilation), by optimally combining observations and models, becomes an important element of CLIVAR.

oceanography climate↗
NASA NTRS1998

Climate Ocean Modeling on Parallel Computers

Ocean modeling plays an important role in both understanding the current climatic conditions and predicting future climate change. However, modeling the ocean circulation at various spatial and temporal scales is a very challenging computational task.

partition↗
NASA NTRS2006

Asian Dust Storm Outbreaks: A Satellite-Surface Perspective

Airborne dusts from northern China contribute a significant part of the air quality problem and, to some extent, regional climatic impact in Asia during springtime. Asian dust typically originates in desert areas far from polluted urban regions. During the transport, dust layers can interact with anthropogenic sulfate and soot aerosols from heavily polluted urban areas. Added to the complex effects of clouds and natural marine aerosols, dust particles reaching the marine environment can have drastically different properties than those from the source. Thus, understanding the unique temporal and spatial variations of Asian dust is of special importance in regional-to-global climate issues (e.g., radiative forcing, hydrological cycle, and primary biological productivity in the mid-Pacific Ocean, etc.), as well as societal concerns (e.g., adverse health effects to humans). The Asian dust and air pollution aerosols can be detected by its colored appearance on current Earth observing satellites (e.g., MODIS, SeaWiFS, TOMS, etc.) and its evolution monitored by satellites and surface network (e.g. AERONET, SKY NET, MPLNET, etc.). Recently, many field campaigns (e.g., ACE-Asia-2001, TRACEP-2001, ADE-2002 & -2003, APEX-2001 & -2003, etc.) were designed and executed to study the compelling variability in spatial and temporal scale of both pollution-derived and naturally occurring aerosols, which often exist in high concentrations over eastern Asia and along the rim of the western Pacific. I will present an overview of the outbreak of Asian dust storms from space and surface observations and to address the climatic effects and societal impacts.

Tsay, Si-Chee↗
NASA NTRS2007

Magnetospheric Multiscale Mission SpaceWire Implementation

This viewgraph presentation reviews the use of SpaceWire in the Magnetospheric Multiscale Mission (MMS). The Science Objectives of the are to Discover the fundamental plasma physics process of reconnection in the Earth's magnetosphere using temporal scales of milliseconds to seconds and spatial scales of 10s to 100s of km. MMS should be the first NASA mission to fly several new Spacewire protocols including: - Remote Memory Access Protocol - Distributed interrupt Protocol - Standardized Backplane These are briefly reviewed in the presentation.

Jackson, George↗
NASA NTRS2004

Toward a Global Map of Raindrop Size Distributions: Rain-Type Classification and Its Implications for Validating Global Rainfall Products - Part 1

Variability in the global distribution of precipitation is recognized as a key element in assessing the impact of climate change for life on earth. The response of precipitation to climate forcings is, however, poorly understood because of discrepancies in the magnitude and sign of climatic trends in satellite-based rainfall estimates. Quantifying and ultimately removing these biases is critical for studying the response of the hydrologic cycle to climate change. In addition, estimates of random errors owing to variability in algorithm assumptions on local spatial and temporal scales are critical for establishing how strongly their products should be weighted in data assimilation or model validation applications and for assigning a level of confidence to climate trends diagnosed from the data. This paper explores the potential for refining assumed drop size distributions (DSDs) in global radar rainfall algorithms by establishing a link between satellite observables and information gleaned from regional validation experiments where polarimetric radar, Doppler radar, and disdrometer measurements can be used to infer raindrop size distributions. By virtue of the limited information available in the satellite retrieval framework, the current method deviates from approaches adopted in the ground-based radar community that attempt to relate microphysical processes and resultant DSDs to local meteorological conditions. Instead, the technique exploits the fact that different microphysical pathways for rainfall production are likely to lead to differences in both the DSD of the resulting raindrops and the three-dimensional structure of associated radar reflectivity profiles. Objective rain-type classification based on the complete three-dimensional structure of observed reflectivity profiles is found to partially mitigate random and systematic errors in DSDs implied by differential reflectivity measurements. In particular, it is shown that vertical and horizontal reflectivity structure obtained from spaceborne radar can be used to reproduce significant differences in Z(sub dr) between the easterly and westerly climate regimes observed in the Tropical Rainfall Measuring Mission Large-scale Biosphere-Atmosphere (TRMM-LBA) field experiment as well as the even larger differences between Amazonian rainfall and that observed in eastern Colorado. As such, the technique offers a potential methodology for placing locally observed DSD information into a global framework.

L'Ecuyer, Tristan S.↗
NASA NTRS2007

Utility of AIRS Retrievals for Climate Studies

Satellites provide an ideal platform to study the Earth-atmosphere system on practically all spatial and temporal scales. Thus, one may expect that their rapidly growing datasets could provide crucial insights not only for short-term weather processes/predictions but into ongoing and future climate change processes as well. Though Earth-observing satellites have been around for decades, extracting climatically reliable information from their widely varying datasets faces rather formidable challenges. AIRS/AMSU is a state of the art infrared/microwave sounding system that was launched on the EOS Aqua platform on May 4, 2002, and has been providing operational quality measurements since September 2002. In addition to temperature and atmospheric constituent profiles, outgoing longwave radiation and basic cloud parameters are also derived from the AIRS/AMSU observations. However, so far the AIRS products have not been rigorously evaluated and/or validated on a large scale. Here we present preliminary assessments of monthly and 8-day mean AIRS "Version 4.0" retrieved products (available to the public through the DAAC at NASA/GSFC) to assess their utility for climate studies. First we present "consistency checks" by evaluating the time series of means, and "anomalies" (relative to the first 4 full years' worth of AIRS "climate statistics") of several climatically important retrieved parameters. Finally, we also present preliminary results regarding interrelationships of some of these geophysical variables, to assess to what extent they are consistent with the known physics of climate variability/change. In particular, we find at least one observed relationship which contradicts current general circulation climate (GCM) model results: the global water vapor climate feedback which is expected to be strongly positive is deduced to be slightly negative (shades of the "Lindzen effect"?). Though the current AIRS climatology covers only -4.5 years, it will hopefully extend much further into the future.

Molnar, Guyla I.↗
NASA NTRS2006

Relationship Between Rainfall and Soil Moisture Based on AMSR-E Data

Rainfall over land is a primary uncertainty source and limitation for the soil moisture retrieval. Discerning the signal emitted by the surface from emission of a raining atmosphere is extremely complicated. Results show some insights of the relationship between precipitation and soil moisture according to spatio-temporal scales We are working on investigating consistency between the retrieved soil moisture data and the model data (NARR) to study how satellite-based soil moisture observations can contribute to simulate improved large-scale soil moisture estimation through data assimilation.

rainfall↗
NASA NTRS2006

A Climatology of Midlatitude Continental Clouds from the ARM SGP Central Facility: Cloud Fraction and Radiative Forcing - Part II

Data collected at the Department of Energy Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) central facility are analyzed for determining the variability of cloud fraction and radiative forcing at several temporal scales between January 1997 and December 2002. Cloud fractions are estimated for total cloud cover and for single-layer low (0-3 km), middle (3-6 km), and high clouds (greater than 6 km) using ARM SGP ground-based paired lidar-radar measurements. Shortwave (SW), longwave (LW), and net cloud radiative forcings (CRF) are derived from up- and down-looking standard precision spectral pyranometers and precision infrared radiometer measurements. The annual averages of total, and single-layer, nonoverlapped low, middle and high cloud fractions are 0.49, 0.11, 0.03, and 0.17, respectively. Total and low cloud amounts were greatest from December through March and least during July and August. The monthly variation of high cloud amount is relatively small with a broad maximum from May to August. During winter, total cloud cover varies diurnally with a small amplitude, mid-morning maximum and early evening minimum, and during summer it changes by more than 0.14 over the daily cycle with a pronounced early evening minimum. The diurnal variations of mean single-layer cloud cover change with season and cloud height. Annual averages of all-sky, total, and single-layer high, middle, and low LW CRFs are 21.4, 40.2, 16.7, 27.2, and 55.0 Wm(sup -2), respectively; and their SW CRFs are -41.5, -77.2, -37.0, -47.0, and -90.5 Wm(sup -2). Their net CRFs range from -20 to -37 Wm(sup -2). For all-sky, total, and low clouds, the maximum negative net CRFs of -40.1, -70, and -69.5 Wm(sup -2), occur during April; while the respective minimum values of -3.9, -5.7, and -4.6 Wm(sup -2), are found during December. July is the month having maximum negative net CRF of -46.2 Wm(sup -2) for middle clouds, and May has the maximum value of -45.9 Wm(sup -2) for high clouds. An uncertainty analysis demonstrates that the calculated CRFs are not significantly affected by the difference between clear-sky and cloudy conditions. A more comprehensive cloud fraction study from both surface and satellite observations will follow.

Dong, Xiquan↗
NASA NTRS2008

The Cloud Slicing Technique-Measuring the Unmeasureable

In satellite remote sensing clouds are usually considered an annoying interference. Satellite investigators go to unusual lengths to try to avoid clouds or to correct for their effects, and satellite data users routinely exclude cloudy data from analysis. Yet it was shown about a decade ago using TOMS data that for the study of tropospheric constituents, such as ozone, clouds can play a very beneficial role by allowing one to measure what otherwise cannot be directly measured from space. We call this technique "cloud Slicing". The so-called Convective Cloud Differential (CCD) method is one particular application of cloud slicing that has been applied successfully to data from TOMS and other similar satellite instruments to study the behavior of tropical tropospheric ozone at variety of spatial and temporal scales. However, there has been considerable confusion in the literature as to what exactly one measures from reflected sunlight instruments such as TOMS in cloudy atmospheres. We will discuss recently completed analysis of data taken by the Ozone Monitoring Instrument (OMI) on the Aura satellite in conjunction with several other instruments on the A-train satellite constellation to present new insight on how clouds affect absorption by aerosols and trace gases at reflected wavelengths (UV-SWIR). We will show several examples to illustrate how this insight is helping us to study the behavior of trace gases and aerosols in the atmosphere that cannot be studied by focusing only on cloud-free scenes.

Bhartia, P.↗