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NASA NTRS2002

Science goals for a Mars Polar Cap subsurface mission : optical approaches for investiagations of inclusions in ice

The Mars Polar Caps are highly interesting features of Mars and have received much recent attention with new and exciting data on morphology, basal units, and layered outcroppings. We have examined the climatological, glaciological, and geological issues associated with a subsurface exploration of the Mars North Polar Cap and have determined that a finescale optical examination of ice in a borehole, to examine the stratigraphy, geochemistry and geochronology of the ice, is feasible. This information will enable reconstruction of the development of the cap as well as predication of the properties of its ice. We present visible imagery taken of dust inclusions in archived Greenland ice cores as well as in-situ images of accreted lithologic inclusions in West Antarctica, and we argue for use of this kind of data in Mars climate reconstruction as has been successful with Greenland and Antarctic ice core anlaysis.

dust↗

NASA NTRS2002

Science goals for a Mars Polar Cap subsurface mission : optical approaches for investigations of inclusions in ice

The Mars Polar Caps are highly interesting features of Mars and have received much recent attention with new and exciting data on morphology, basal units, and layered outcroppings. We have examined the climatological, glaciological, and geological issues associated with a subsurface exploration of the Mars North Polar Cap and have determined that a finescale optical examination of ice in a borehole, to examine the stratigraphy, geochemistry and geochronology of the ice, is feasible. This information will enable reconstruction of the development of the cap as well as prediction of the properties of its ice. We present visible imagery taken of dust inclusions in archived Greenland ice cores as well as in-situ images of accreted lithologic inclusions in West Antarctica, and we argue for use of this kind of data in Mars climate reconstruction as has been successful with Greenland and Antarctic ice core analysis. .

scattering↗

NASA NTRS2007

Comparison of Polar Motion Excitation Series Derived from GRACE and from Analyses of Geophysical Fluids

Three sets of degree-2, order-1 harmonics of the gravity field, derived from the Gravity Recovery and Climate Experiment (GRACE) data processed at the Center for Space Research (CSR), Jet Propulsion Laboratory (JPL) and GeoforschungsZentrum (GFZ), are used to compute polar motion excitation functions X1 and X2. The GFZ and JPL excitations and the CSR X2, excitation compare generally well with geodetically observed excitation after removal of effects of oceanic currents and atmospheric winds. The agreement considerably exceeds that from previous GRACE data releases. For the JPL series, levels of correlation with the geodetic observations and the variance explained are comparable to, but still lower than, those obtained independently from available models and analyses of the atmosphere, ocean, and land hydrology. Improvements in data quality of gravity missions are still needed to deliver even tighter constraints on mass-related excitation of polar motion.

Nastula, J.↗

NASA NTRS2005

Constraining Hydrological and Cryospheric Mass Flux in Southeastern Alaska using Space-Based Gravity Measurements

Watersheds draining into the Gulf of Alaska (GoA) experience large seasonal and inter-annual variations of water in the form of rain, snow, and ice, but accurate constraints on these variations have been difficult to obtain. Over larger geographic regions, water variations can be inferred directly from the Gravity Recovery and Climate Experiment (GRACE) data. However, because GoA variations occur over such a small region, the inferred average value of water flux increases as the applied smoothing of the GRACE data decreases. We use this observed scaling together with scaling results obtained from forward models to infer a seasonal amplitude of 115 plus or minus 20 cubic kilometers of water and an average contribution to sea level rise over the two years of data of 0.31 plus or minus 0.09 millimeters per year. These results suggest that accelerated melting that began in the late 1990s, as inferred from altimetry, continues unabated.

Tamisiea, M. E.↗

NASA NTRS2007

Greenland Ice Sheet Surface Temperature, Melt, and Mass Loss: 2000-2006

Extensive melt on the Greenland Ice Sheet has been documented by a variety of ground and satellite measurements in recent years. If the well-documented warming continues in the Arctic, melting of the Greenland Ice Sheet will likely accelerate, contributing to sea-level rise. Modeling studies indicate that an annual or summer temperature rise of 1 C on the ice sheet will increase melt by 20-50% therefore, surface temperature is one of the most important ice-sheet parameters to study for analysis of changes in the mass balance of the ice-sheet. The Greenland Ice Sheet contains enough water to produce a rise in eustatic sea level of up to 7.0 m if the ice were to melt completely. However, even small changes (centimeters) in sea level would cause important economic and societal consequences in the world's major coastal cities thus it is extremely important to monitor changes in the ice-sheet surface temperature and to ultimately quantify these changes in terms of amount of sea-level rise. We have compiled a high-resolution, daily time series of surface temperature of the Greenland Ice Sheet, using the I-km resolution, clear-sky land-surface temperature (LST) standard product from the Moderate-Resolution Imaging Spectroradiometer (MODIS), from 2000 - 2006. We also use Gravity Recovery and Climate Experiment (GRACE) data, averaged over 10-day periods, to measure change in mass of the ice sheet as it melt and snow accumulates. Surface temperature can be used to determine frequency of surface melt, timing of the start and the end of the melt season, and duration of melt. In conjunction with GRACE data, it can also be used to analyze timing of ice-sheet mass loss and gain.

Hall, Dorothy K.↗

NASA NTRS2008

The NASA MSFC Earth Global Reference Atmospheric Model-2007 Version

Reference or standard atmospheric models have long been used for design and mission planning of various aerospace systems. The NASA/Marshall Space Flight Center (MSFC) Global Reference Atmospheric Model (GRAM) was developed in response to the need for a design reference atmosphere that provides complete global geographical variability, and complete altitude coverage (surface to orbital altitudes) as well as complete seasonal and monthly variability of the thermodynamic variables and wind components. A unique feature of GRAM is that, addition to providing the geographical, height, and monthly variation of the mean atmospheric state, it includes the ability to simulate spatial and temporal perturbations in these atmospheric parameters (e.g. fluctuations due to turbulence and other atmospheric perturbation phenomena). A summary comparing GRAM features to characteristics and features of other reference or standard atmospheric models, can be found Guide to Reference and Standard Atmosphere Models. The original GRAM has undergone a series of improvements over the years with recent additions and changes. The software program is called Earth-GRAM2007 to distinguish it from similar programs for other bodies (e.g. Mars, Venus, Neptune, and Titan). However, in order to make this Technical Memorandum (TM) more readable, the software will be referred to simply as GRAM07 or GRAM unless additional clarity is needed. Section 1 provides an overview of the basic features of GRAM07 including the newly added features. Section 2 provides a more detailed description of GRAM07 and how the model output generated. Section 3 presents sample results. Appendices A and B describe the Global Upper Air Climatic Atlas (GUACA) data and the Global Gridded Air Statistics (GGUAS) database. Appendix C provides instructions for compiling and running GRAM07. Appendix D gives a description of the required NAMELIST format input. Appendix E gives sample output. Appendix F provides a list of available parameters to enable the user to generate special output. Appendix G gives an example and guidance on incorporating GRAM07 as a subroutine in other programs such as trajectory codes or orbital propagation routines.

Leslie, F.W.↗

NASA NTRS2011

Hydrological Variations in Australia Recovered by GRACE High-Resolution Mascons Solutions

Australia represents a challenging region in which to study hydrological variations as recovered by the GRACE (Gravity Recovery And Climate Experiment) mission data. Much of Australia is characterized by relatively small hydrological signals, with large precipitation gradients between the North and the South. These signals are better recovered using innovative GRACE processing techniques such as high-resolution mascon solutions, which may help overcome the deficiencies in the standard GRACE data processing and filtering methods. We will show the power of using regional and global mas con solutions to recover hydrological variations from 2003 to 2011, as well as the oceanic mass variations in the surrounding regions. We will compare the GRACE signals with state of the art hydrology and ocean general circulation models, precipitation, soil moisture and groundwater data sets. We especially emphasize the gravity signatures observed during the decadal drought in the Murray-Darling river basin and the early 2011 floods in North-Western Australia.

Carabajal, Claudia C.↗

NASA NTRS2012

Conceptual Development of the DESDynI Mission

The high value of Radar and Lidar data for understanding climate change and earth dynamics led to the prioritization of the Deformation, Ecosystem Structure and Dynamics of Ice (DESDynI) mission as Tier One in the last National Academy of Sciences' Earth Science Decadal Survey. A mission concept that matched those desired objectives underwent pre-Project development and passed several layers of review in late 2010 and early 2011 with the target of a 2017 launch. However, cuts in the proposed FY2012 budget forced a reset of the Radar mission and eliminated the Lidar sciencecraft. The proposed DESDynI- Radar mission may now fulfill a more limited set of objectives with a more modest budget on a longer development timescale. A multitude of options have been studied with varying levels of cost, risk and science value. Flight and Ground system implementations have a direct bearing on many of these factors and will also be addressed. The methodology and status of evaluating these options will be discussed. A key distinguishing characteristic of the projected DESDynI-Radar measurement would be large scale coverage and frequent revisit at fine resolution. This would be enabled via a new Radar technique called SweepSAR. Efforts to develop and field test SweepSAR will also be discussed, as well as other technology developments underway that are associated with this mission

Deformation, Ecosystem Structure and Dynamics of I↗

NASA NTRS2017

Status and Plans for Reanalysis at NASA/GMAO

Reanalysis plays a critical role in GMAOs goal to enhance NASA's program of Earth observations, providing vital data sets for climate research and the development of future missions. As the breadth of NASAs observations expands to include multiple components of the Earth system, so does the need to assimilate observations from currently uncoupled components of the system in a more physically consistent manner. GMAOs most recent reanalysis of the satellite era, MERRA-2, has completed the period 1980-present, and is now running as a continuing global climate analysis with two- to three-week latency. MERRA-2 assimilates meteorological and aerosol observations as a weakly coupled assimilation system as a first step toward GMAOs longer term goal of developing an integrated Earth system analysis (IESA) capability that will couple assimilation systems for the atmosphere, ocean, land and chemistry. The GMAO strategy is to progress incrementally toward an IESA through an evolving combination of coupled systems and offline component reanalyses driven by, for example, MERRA-2 atmospheric forcing. Most recently, the GMAO has implemented a weakly coupled assimilation scheme for analyzing ocean skin temperature within the existing atmospheric analysis. The scheme uses background fields from a near-surface ocean diurnal layer model to assimilate surface-sensitive radiances plus in-situ observations along with all other observations in the atmospheric assimilation system. In addition, MERRA-2-driven simulations of the ocean (plus sea ice) and atmospheric chemistry (for the EOS period) are currently underway, as is the development of a coupled atmosphere-ocean assimilation system. This talk will describe the status of these ongoing efforts and the planned steps toward an IESA capability for climate research.

MERRA-2↗

NASA NTRS2018

Southeast Greenland Winter Precipitation Strongly Linked to the Icelandic Low Position

Greenland's largest precipitation flux occurs in its southeast (SE) region during the winter, controlled primarily by easterly winds and frequent cyclogenesis in the North Atlantic. Several studies have attempted to link SE Greenland precipitation to the North Atlantic Oscillation (NAO) but results are inconsistent. This work uses reanalysis, automatic weather station data, and regional climate model output to show that the east-west position of the Icelandic low is a better predictor of SE Greenland precipitation (average correlation of r equals -0.48 in DJF (December January February)) than climate indices such as the NAO (r equals -0.06 in DJF). In years when the Icelandic low is positioned extremely west, moisture transport increases up to approximately 40 percent (or up to 40 kilograms per meter per second) off the SE Greenland coast compared to when the low is in an extreme east position. Furthermore, in years when the Icelandic low is positioned extremely west, storm track density and intensity increase just off the SE coast of Greenland. Thus, the Icelandic low's longitudinal position dominates SE Greenland ice sheet's wintertime precipitation, a positive term in the ice sheet mass balance. Given SE Greenland's importance in the overall ice sheet mass balance, the position of the Icelandic low is therefore important for making projections of future sea level.

Arctic↗

NASA NTRS2018

Observaciones de la Tierra desde la Estación Espacial Internacional

The International Space Station is a "global observation and diagnosis station." It promotes international Earth observations aimed at understanding and resolving the environmental issues of our home planet. A wide variety of Earth observation payloads can be attached to the exposed facilities on the station's exterior as well as within the Destiny module. The presence of a human crew also provides a unique capability for real-time observation of the Earth, and "on the fly" data collection using hand-held digital cameras, and the astronauts may also provide input to ground personnel programming the station's automated Earth observation systems. Several instruments are currently collecting data from the International Space Station; in addition, some instruments have completed their data collection missions, with other remote sensing systems in development or proposed by researchers from the partner countries, NASA, academic institutions, and corporations. The existing international partnerships, fundamental to the International Space Station, facilitate data sharing that can benefit people around the world and promote international collaboration on other Earth observation activities. The station contributes to humanity by collecting data on global climate, environmental change, and natural hazards using its unique complement of crew-operated and automated Earth observation payloads.

Sotomayor, Jorge L.↗

NASA NTRS2020

Clouds Damp the Impacts of Polar Sea Ice Loss

The amount of solar energy absorbed by the Earth is believed to strongly depend on clouds, due to their ability to scatter and reflect part of solar energy back to space. Here, we investigate this relationship using satellite data and 32 climate models, showing that this relationship holds everywhere except over polar seas, where an increased reflection by clouds corresponds to an increase in absorbed solar radiation at the surface. We resolve this paradox by quantifying a strong correlation between clouds and sea-ice extent. An increase in absorbed solar radiation, when sea ice retreats, leads to an increase in cloud cover/thickness and associated reflection to space. This interplay between clouds and sea ice reduces by half the increase of net radiation at the surface that follows the sea-ice retreat, therefore damping the impact of polar sea ice loss. We further highlight how this process is mis-represented in some climate models.

Ramdane Alkama↗

NASA NTRS2019

A Landslide Climate Indicator from Machine Learning

In order to create a Landslide Hazard Index, we accessed rain, snow, and a dozen other variables from the National Climate Assessment Land Data Assimilation System. These predictors were converted to probabilities of landslide occurrence with XGBoost, a major machine-learning tool. The model was fitted with thousands of historical landslides from the Pacific Northwest Landslide Inventory (PNLI).

Stanley, T. A.↗

NASA NTRS2019

Renewable Energy Contingencies in Power Systems: Concept and Case Study

This paper introduces the concept of renewable energy contingencies that represent long-term/extended variability of variable renewable energy (VRE) resources, namely, significant periods (e.g., days/weeks) of low wind/solar availability. These contingencies have not received much attention to date but are likely to emerge as a major issue in some countries such as India as the share of VRE increases. Using 38 years of climate model reanalysis data for wind over India, we demonstrate that low periods of wind contingency below long-term (Indian) national average of 5 m/s can extend for more than 100 days in several zones some of which are deploying large wind farms. Even in some of the best wind resource areas in India with long term average wind speed close to 7 m/s, low wind days (e.g., 5 m/s which is substantially below average) can extend up to 60 days. We propose a four-step methodology around a co-optimization based energy-ancillary services dispatch model to assess the impact of renewable contingency and implemented it for the state of Tamil Nadu, the most wind-rich state of India. We have estimated that annual renewable contingency cost impact of 5 GW additional wind in Tamil Nadu to be in the range of US$27-76 million pa. Planning analysis should embrace the concept of renewable contingency to recognize these costs and put in place necessary spinning reserve and back-up generation resources.

Mohar Chattopadhyay↗

NASA NTRSDate not supplied

TPSAS-NF1676L-33601-DND

The Clouds and the Earth's Radiant Energy System (CERES) project now has over 18 years of an accurately observed top-of-the-atmosphere (TOA) flux record for climate monitoring and diagnostic studies. CERES provides the climate community the following parameters: coincident instantaneous 1? gridded CERES observed TOA fluxes, computed profile and surface fluxes, as well as MODIS cloud and aerosol retrievals. Clouds and radiation interaction one key factor that dominates climate feedbacks and is also the most difficult problem with large uncertainty. To further advance our understanding of the cloud-radiation interaction, the climate community need data with accurate fluxes and their associated cloud properties for both observational and modelling study. The new CERES FluxByCldTyp data product is produced for this purpose. The flux product combines for the first time CERES measured TOA fluxes along with the associated MODIS cloud properties, which links radiative flux directly to a specific cloud type. This was achieved by computing sub-footprint fluxes for the clear-sky and cloudy portions of the CERES footprint. The spatially distributed cloud properties within the CERES footprint were retrieved from 2-km MODIS pixels, that were stratified by cloud type. The sub-footprint fluxes were estimated from MODIS radiances based on empirically derived narrowband to broadband coefficients. The combined sub-footprint fluxes can then be validated with the observed footprint flux. This presentation will focus on the algorithm development of the flux-by-cloud-type product and its validation.

Moguo Sun↗

NASA NTRSDate not supplied

TPSAS-NF1676L-33753-DND

The Clouds and the Earth's Radiant Energy System (CERES) project now has over 18 years of an accurately observed top-of-the-atmosphere (TOA) flux record for climate monitoring and diagnostic studies. CERES provides the climate community the following parameters: coincident instantaneous 1 gridded CERES observed TOA fluxes, computed profile and surface fluxes, as well as MODIS cloud and aerosol retrievals. Clouds and radiation interaction one key factor that dominates climate feedbacks and is also the most difficult problem with large uncertainty. To further advance our understanding of the cloud-radiation interaction, the climate community need data with accurate fluxes and their associated cloud properties for both observational and modelling study. The new CERES FluxByCldTyp data product is produced for this purpose. The flux product combines for the first time CERES measured TOA fluxes along with the associated MODIS cloud properties, which links radiative flux directly to a specific cloud type. This was achieved by computing sub-footprint fluxes for the clear-sky and cloudy portions of the CERES footprint. The spatially distributed cloud properties within the CERES footprint were retrieved from 2-km MODIS pixels, that were stratified by cloud type. The sub-footprint fluxes were estimated from MODIS radiances based on empirically derived narrowband to broadband coefficients. The combined sub-footprint fluxes can then be validated with the observed footprint flux. This presentation will focus on the algorithm development of the flux-by-cloud-type product and its validation. The paper will also discuss CERES FlxbyCldTyp simulator and its application.

Moguo Sun↗

NASA NTRSDate not supplied

CERES FluxByCldTyp NB2BB Fluxes Improvement based on Deep Neural Network

The NASA Clouds and the Earth's Radiant Energy System (CERES) product provides over 20 years of accurately observed top-of-the-atmosphere (TOA) and surface flux data record for climate monitoring and diagnostic studies. The interaction between clouds and radiation interaction is a key factor that dominate climate feedbacks but is not well understood. To further advance our understanding of the cloud-radiation interaction, a new CERES FluxByCldTyp (FBCT) product has been developed that contains radiative fluxes by cloud-type, which can provide more stringent constraints when validating models and reveal more insight into the interactions between clouds and climate. For CERES partly cloudy and multiple cloud-type footprints, the FBCT product utilizes Moderate Resolution Imaging Spectroradiometer (MODIS) narrow-band (NB) imager channel radiances partitioned by cloud-type within a CERES footprint to estimate the cloud-type broadband fluxes. The MODIS multi-channel derived broadband fluxes were compared with the CERES observed footprint fluxes and were found to be within 1% and 2.5% for LW and SW, respectively, as well as being mostly free of cloud property dependencies. The FBCT all-sky and clear-sky monthly averaged fluxes were found to be consistent with the CERES SSF1deg product. This study takes advantage of recent progress in machine learning (ML) field by applying deep neural network algorithm to improve fluxes based on MODIS NB radiances. The preliminary study shows ML produce are an improvement over the current FBCT Edition 4 NB2BB algorithm. Furthermore, unlike Ed4 NB2BB, the new ML method convert NB radiances directly to broadband fluxes. For future Ed5, new NB radiances are proposed and used by ML to improve fluxes calculation. Prelimary results show significant LW improvement.

Moguo Sun↗

NASA NTRSDate not supplied

Flux Improvement based on Machine Learning for the CERES FluxByCldTyp Data Product

Moguo Sun↗