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The program: a) Coordinates Federal research to better understand and prepare the nation for global change. b) Priori4zes and supports cutting edge scientific work in global change. c) Assesses the state of scientific knowledge and the Nation s readiness to respond to global change. d) Communicates research findings to inform, educate, and engage the global community.
Landslides are extremely damaging, pervasive and cause fatalities and economic impacts. Extreme rainfall events, coupled with inopportune surface conditions, are the primary triggers of landslides around the world. Forecasting landslide events represent an area of open research. A global Landslide Hazard Assessment for Situational Awareness (LHASA) model has been created that provides near real-time dynamic landslide characterization using Integrated Multi-Satellite Retrievals for Global Precipitation Mission (IMERG). However, it does not provide information on prediction of landslides into future. This study considers how global precipitation forecast data compares to satellite rainfall at different spatiotemporal scales and outlines the potential for its use in landslide hazard prediction/forecasting system. NASA Goddard Earth Observing System (GEOS)-Forecast model assimilates new observations every 6 hours, at 00, 06, 12, and 18 UTC. The GEOS-Forecast model is initialized at 00 UTC and is evaluated with IMERG Early, using Multi-Radar Multi-Sensor gauge corrected (MRMS-GC) precipitation product as a reference over contiguous United States (CONUS). Categorical and continuous statistics along with probability density functions and cumulative distribution functions are considered to assess the performance of the precipitation products, with a focus on landslide hotspots. Seasonality appears to influence the performance of both the GEOS-Forecast and IMERG Early product. Moreover, the global comparison between the GEOS-Forecast and IMERG Early is carried out in terms of percentile difference, correlation, and bias maps. For extreme rainfall events in regions such as Mekong, Colombia, and Tajikistan, GEOS-Forecast appears to resolve high rainfall relative to IMERG Early more frequently. Validation over landslide points reveal that for 24hr rainfall accumulations > 100mm, GEOS-Forecast and IMERG coincide. GEOS-Forecast and IMERG Early precipitation matches more closely for tropical cyclones than other types of storms. Overall, the performance varies with respect to location, rainfall intensities, and type of precipitation events.
Flooding is a natural event that occurs frequently with high severity worldwide, responsible for significant societal and economic impacts. Disaster managers face significant challenges managing essential information for preparedness, response, and recovery efforts. The development of an open access, global flood alerting system for effective identification of flood impacted areas, classification of potential impacts, and the formulation of effective emergency response measures requires the incorporation of a wide variety of flood models and remote sensing data sources from multiple platforms. NASA is currently funding projects focused on flood forecasting, post-event flood mapping, flood depth estimation and pre-event flood severity estimation using Earth observation (EO) datasets and derived flood products. A new initiative in the Disasters Program is underway to disseminate flood products from different hydrologic models and sensors to global stakeholders via Pacific Disaster Center’s DisasterAWARE®, NASA’s Disasters Mapping Portal and potentially other mechanisms. This initiative focuses on improving response capacity and use of EO products in near real-time by a broader community for resource planning in case of extreme events. As part of this initiative, we have deployed Model of Models (MoM) – an open-source ensemble approach, that integrates outputs from hydrologic models and EO data from optical imagery to assess flood severity daily at sub-watershed level globally. The MoM output is integrated with the incident event system of DisasterAWARE to generate flood severity risk and flood impact boundaries, which are disseminated via the DisasterAWARE platform to different stakeholders globally for decision-making and response efforts. The next step will focus on using MoM outputs to estimate flood depth and extent mapping using high-resolution Synthetic Aperture Radar imagery, impact assessment using optical imagery and population datasets, and damage estimation using critical infrastructure datasets, which would be disseminated via DisasterAWARE to decision-makers, emergency managers and first responders around the world.
The Global Initiative for Flood Forecasting and Alerting (GIFFT) is an initiative to disseminate flood products from different sensors to global stakeholders via the Pacific Disaster Center’s (PDC) DisasterAWARE®, the NASA Disasters Mapping Portal and potentially other mechanisms. GIFFT will also generate an integrated product(s) using ensembled hydrologic models and Earth observation derived flood outputs to stakeholders globally. This initiative combines the results of several Disasters Program funded projects that focus on flood forecasting, flood severity estimation, post-event flood mapping, flooddepth estimation and resulting flood severity using remote sensing-based flood information derived from SAR and optical imagery. PDC’s DisasterAWARE platform is a global multi-hazard alerting platform that currently incorporatesModel of Models (MoM) outputs as flood “incidents,” visually depicting potential floods in the context ofpopulation and infrastructure that may become affected. Automated procedures are being developed tocategorize MoM outputs as DisasterAWARE “hazards,” allowing for their dissemination to users alongwith other flood products that assess potential impacts. PDC’s stakeholders include UN, DoD, FEMA andtheir equivalents around the world. Additionally, the DisasterALERT mobile platform has 2 million usersworldwide and is a fully functional and sustained platform used to disseminate alerts and analyticalproducts for 18 different hazard types. GIFFT has incorporated HydroSAR products that will bedistributed via DisasterAWARE.
The Mars Global Surveyor Mission will launch a single spacecraft to Mars in November 1996. After arrival at the planet in September 1997 aerobraking will be used to lower the spacecraft into a low, sun-synchronous, polar-mapping orbit over several months. Early in 1998 mapping observations will begin and continue for a Mars year (687 days). Following completion of this first Mars year of mapping the spacecraft will continue to act as a relay orbiter for an additional three Earth years. The five instruments carried involve magnetometry, surface and atmosphere imaging, atmospheric sounding, laser altimetry, gravity and thermal emission spectroscopy. In addition, the spacecraft carries a Mars relay receiver/transmitter which will operate over the entire five year orbital mission ending in January of 2003. The Mars Global Surveyor mission is intended to accomplish a portion of the scientific objectives of the Mars Observer mission which was lost in 1993 three days before entering Mars orbit. The instrumentation to be used for the magnetometers, cameras, laser altimeter, emission spectrometer and radio science are very nearly the same as those carried by Mars Observer. The spacecraft design will be new but will use spare equipment from Mars Observer and has a mass about two and one-half time smaller. All experiments will be controlled remotely from their investigators home installation. The long planned period of observation supports the mission's global and seasonal objectives.
Given the mission objective to deploy a number of small landers to the surface of Mars at various latitude/longitude locations, it is of interest to obtain a global perspective of the communications link geometry between the landers and a data relay orbiter. Specifically, the question to be answered is what is the total time interval over one Martian day (1 sol) that a lander at any given latitude and longitude can communicate data to the orbiter. Results should be obtained for more than one elevation angle constraint (lander antenna design issue), and also for several time points into the mission since the orbiter's periapsis location moves under the influence of Mars' oblateness perturbation. Such information is presented in terms of global contour maps of available communications time per sol summed over all orbiter pases on that day. Global data of this type complements more detailed local site data such as communications range and elevation vs time per pass. Communications time contour maps are included here for sol grids of 180, 232, 318, 361, and 404 corresponding to orbiter periapsis latitudes of 35 S, 90 S, equatorial, 45 N, and 90 N. For each of these days, there is a map for both a 15 deg and 45 deg minimum elevation constraint on the lander-to-orbiter line of sight. The jagged appearance of the contour lines is due to computational resolution in interpolating between a finite number of latitude/longitude grid points. Although the contours should really be smooth, the general information content is represented by the lower resolution maps shown here. An example of the tabulated, finite-grid data points is also given. Communication with all sites is possible at the 15 deg elevation constraint, at times only for several minutes per sol but more generally for a much longer time up to 14 hours per sol. Significantly less time is available with a 45 deg elevation constraint, and at certain times in the mission some localized regions of the planet are inaccessible. Still, one may conclude that the reference orbit selection will support a more than adequate communications link through the mission timeline with landers emplaced at any desired location on Mars.
Global distributions of atmospheric heating for the annual cycle of the Global Weather Experiment are estimated from the European Centre for Medium-Range Weather Forecasts (ECMWF) Level 3b data set. Distributions of monthly, seasonally, and annually averaged heating are presented for isentropic and isobaric layers within the troposphere and for the troposphere as a whole. The distributions depict a large-scale structure of atmospheric heating that appears spatially and temporally consistent with known features of the global circulation and the seasonal evolution.
Global cloudiness and radiation budget data from Nimbus 6 and 7 are used to investigate the role of cloud and surface radiative forcing and elements of the earth's general circulation. Although globally integrated cloud forcing is nearly zero, there are large regional imbalances and well regulated processes in the shortwave and longwave spectrum that control the meridional gradient structure of the net radiation balance and the factors modulating the east-west oriented North Africa-western Pacific energy transport dipole. The analysis demonstrates that clouds play a dual role in both the shortwave and longwave spectra in terms of tropical and midlatitude east-west gradients. The key result is that cloud forcing, although not always the principle regulator of interannual variability of the global climate, serves to reinforce the basic three-cell meridional circulation.
This is a Final Report for a Joint Research Interchange (JRI) between NASA Ames Research Center and San Jose State University, Department of Meteorology. Using a global atmospheric circulation model for Mars, the focus of this JRI has been to provide support for the Mars Global Surveyor (MGS) spacecraft aerobraking activities and interpretation guidance of preliminary observations. The primary atmospheric model applied in this investigation has been a high-top version of the NASA Ames Mars general circulation model (MGCM). Comparisons with an atmospheric model designed primarily for engineering purposes (Mars-GRAM) has also been carried out. From a suite of MGCM simulations, we have assessed plausible spatial and temporal variability in atmospheric density at high altitudes (e.g., 70-110 km) for seasonal dates and locations during Phase I aerobraking. Diagnostic tools have been developed to analyze circulation fields from the MGCM simulations, and these tools have been applied in the creation of a Mars climate catalogue database. Throughout Phase I aerobraking activities, analysis products have been provided to the MGS aerobraking atmospheric advisory group (AAG). Analyses of circulation variability at the coupling level between the MGCM and a Mars thermospheric global circulation model (MTGCM) has also been assessed. Finally, using a quasi-geostrophic dynamical formulation with the MGCM simulations, diagnosis of breaking planetary (Rossby) waves in Mars' middle atmosphere has been carried out. Titles of papers presented at scientific workshops and seminars, and a publication in the scientific literature are provided.
This is a Final Report for a Joint Research Interchange (JRI) between NASA Ames Research Center and San Jose State University, Department of Meteorology. Using a global atmospheric circulation model for Mars, the focus of this JRI has been to provide support for the Mars Global Surveyor (MGS) spacecraft aerobraking activities and interpretation guidance of preliminary observations. The primary atmospheric model applied in this investigation has been a high-top version of the NASA Ames Mars general circulation model (MGCM). Comparisons with an atmospheric model designed primarily for engineering purposes (Mars-GRAM) has also been carried out. From a suite of MGCM simulations, we have assessed plausible spatial and temporal variability in atmospheric density at high altitudes (e.g., 70-1 10 km) for seasonal dates and locations during Phase 1 aerobraking. Diagnostic tools have been developed to analyze circulation fields from the MGCM simulations, and these tools have been applied in the creation of a Mars climate catalogue database. Throughout Phase I aerobraking activities, analysis products have been provided to the MGS aerobraking atmospheric advisory group (AAG). Analyses of circulation variability at the coupling level between the MGCM and a Mars thermospheric global circulation model (MTGCM) has also been assessed. Finally, using a quasi-geostrophic dynamical formulation with the MGCM simulations, diagnosis of breaking planetary (Rossby) waves in Mars middle atmosphere has been carried out. Titles of papers presented at scientific workshops and seminars, and a publication in the scientific literature are provided.
This is a Final Report for a Joint Research Interchange (JRI) between NASA Ames Research Center and San Jose State University, Department of Meteorology. Using a global atmospheric circulation model for Mars, the focus of this JRI has been to provide support for the Mars Global Surveyor (MGS) spacecraft aerobraking activities and interpretation guidance of preliminary observations. ne primary atmospheric model applied in this investigation has been a high-top version of the NASA Ames Mars general circulation model (MGCM). Comparisons with an atmospheric model designed primarily for engineering purposes (Mars-GRAM) has also been carried out. From a suite of MGCM simulations, we have assessed plausible spatial and temporal variability in atmospheric density at high altitudes (e.g., 70-110 km) for seasonal dates and locations during Phase 1 aerobraking. Diagnostic tools have been developed to analyze circulation fields from the MGCM simulations, and these tools have been applied in the creation of a Mars climate catalogue database. Throughout Phase 1 aerobraking activities, analysis products have been provided to the MGS aerobraking atmospheric advisory group (AAG). Analyses of circulation variability at the coupling level between the MGCM and a Mars thermospheric global circulation model (MTGCM) has also been assessed. Finally, using a quasi-geostrophic dynamical formulation with the MGCM simulations, diagnosis of breaking planetary (Rossby) waves in Mars' middle atmosphere has been carried out. Titles of papers presented at scientific workshops and seminars, and a publication in the scientific literature are provided.
The main focus of our work was to solidify underlying data sets, the data processing tools and the modeling environment needed to perform a series of long-term global and regional hydrological simulations leading eventually to routine hydrometeorological predictions. A water and energy budget synthesis was developed for the Mississippi River Basin (Roads et al. 2003), in order to understand better what kinds of errors exist in current hydrometeorological data sets. This study is now being extended globally with a larger number of observations and model based data sets under the new NASA NEWS program. A global comparison of a number of precipitation data sets was subsequently carried out (Fekete et al. 2004) in which it was further shown that reanalysis precipitation has substantial problems, which subsequently led us to the development of a precipitation assimilation effort (Nunes and Roads 2005). We believe that with current levels of model skill in predicting precipitation that precipitation assimilation is necessary to get the appropriate land surface forcing.
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.
Satellite observations of surface reflected solar radiation contain informationabout variability in the absorption of solar radiation by vegetation. Understanding thecauses of variability is important for models that use these data to drive land surface fluxesor for benchmarking prognostic vegetation models. Here we evaluated the interannualvariability in the new 30.5-year long global satellite-derived surface reflectance index data,Global Inventory Modeling and Mapping Studies normalized difference vegetation index(GIMMS NDVI3g). Pearsons correlation and multiple linear stepwise regression analyseswere applied to quantify the NDVI interannual variability driven by climate anomalies, andto evaluate the effects of potential interference (snow, aerosols and clouds) on the NDVIsignal. We found ecologically plausible strong controls on NDVI variability by antecedent precipitation and current monthly temperature with distinct spatial patterns. Precipitation correlations were strongest for temperate to tropical water limited herbaceous systemswhere in some regions and seasons 40 of the NDVI variance could be explained byprecipitation anomalies. Temperature correlations were strongest in northern mid- to-high-latitudes in the spring and early summer where up to 70 of the NDVI variance was explained by temperature anomalies. We find that, in western and central North America,winter-spring precipitation determines early summer growth while more recent precipitation controls NDVI variability in late summer. In contrast, current or prior wetseason precipitation anomalies were correlated with all months of NDVI in sub-tropical herbaceous vegetation. Snow, aerosols and clouds as well as unexplained phenomena still account for part of the NDVI variance despite corrections. Nevertheless, this study demonstrates that GIMMS NDVI3g represents real responses of vegetation to climate variability that are useful for global models.
We performed a detailed analysis of Earth Polychromatic Imaging Camera (EPIC) spectral data. We found that the vector composed of blue and near-infrared (NIR) reflectance follows a counterclockwise closed-loop trajectory from 0 to 24 UTC as Earth rotates. This non-linear relationship was not observed by any other satellites due to limited spatial or temporal coverage of either low earth orbit (LEO) or geostationary (GEO) satellites. We found that clouds play an important role in determining the non-linear relationship in addition to the well-known cloud free land-ocean reflectance contrast in the two bands. The non-linear relationship is the result of three factors: (1) a much larger cloud free land-ocean contrast in the NIR band compared to the blue band; (2) significantly larger difference between cloudy-land and cloudy-ocean reflectance in theNIR band compared to the blue band; (3) the periodic variation of fractions of clear land, clear ocean, cloudy land, and cloudy ocean in the sunlit hemisphere as Earth rotates. We found that the green vegetation contributes significantly to the NIR global average reflectance when the South and North Americas appear and disappear in the EPIC's field-of-view. The blue and NIR relationship can be useful for exoplanet research. Clouds impose a strong impact on global spectral reflectance and the reflectance response to a change in cloud cover depends on whether the change is over land or over the ocean. On average, an increase of 0.1 in cloud coverage will lead to a 7%increase in spectrally integrated global average reflectance.
This study addresses the global distribution of precipitation mean particle size using data from the Global Precipitation Measurement (GPM) mission. The mass-weighted mean diameter Dm is a characteristic parameter of the precipitation particle size distribution (PSD), estimated from the GPM Combined Radar–Radiometer Algorithm (CORRA) using data from GPM’s dual-frequency precipitation radar and microwave imager. We examine Dm in individual precipitation systems in different climate regimes and investigate a 6-yr (2014–20) global climatology within 70°N–70°S. The vertical structure of Dm is demonstrated with cases of deep convection, frontal rain and snow, and stratocumulus light rain. The Dm values, detectable by GPM, range from ~0.7 mm in stratocumulus precipitation to >3.5 mm in the ice layers of intense convection. Within the constraint of the 12-dBZ detectability threshold, the smallest annual mean Dm (~0.8 mm) are found in the eastern oceans, and the largest values (~2 mm) occur above the melting levels in convection over land in summer. The standard deviation of the annual mean is generally <0.45 mm below 6 km. Climate regimes are characterized with Dm annual/seasonal variations, its convective/stratiform components, and vertical variabilities (2–10 km). The U.S. Central Plains and Argentina are associated with the largest Dm in a deep layer. Tropical Africa has larger Dm and standard deviation than Amazon. Large convective Dm occurs at high latitudes of Eurasia and North America in summer; the Southern Hemisphere high latitudes have shallower systems with smaller Dm. Oceanic storm tracks in both hemispheres have relatively large Dm, particularly for convective Dm in winter. Relatively small Dm occurs over tropical oceans, including ITCZ, requiring further investigation.
The Global Precipitation Measurement (GPM) mission Validation Network (VN) framework leverages over 118 ground-based polarimetric Doppler radars to validate a large subset of precipitation measurements and retrievals from the GPM Dual-frequency Precipitation Radar (DPR). Recently, GPM DPR reflectivity profiles within the VN have been classified according to their convective regime using unsupervised machine learning techniques. The archetypal regimes are stratiform, convective, mixed stratiform-convective (e.g., transition regions), and “other” (e.g., peripheral regions of light precipitation). Subcategories within these four primary regimes vary according to the characteristic depth of included reflectivity profiles, resulting in 12 main GPM DPR precipitation profile categories. Polarimetry of ground-based Doppler radars in the VN offers additional insights into the types of precipitation, while pairs of radars positioned near each other enable retrieval of vertical winds via dual-Doppler analysis. Geometrically matched to the DPR reflectivity profiles in the GPM VN, these ground-based data and retrievals contribute more detailed characterization of the distinct kinematic and microphysical structures associated with each of the 12 DPR precipitation regimes. DPR reflectivity profiles linked with wind in the VN are restricted to GPM overpasses of proximal radar pairs that allow dual-Doppler analysis. Although a limited subset of DPR profiles in the VN are matched with vertical motion, agreement between the reflectivity structures paired with wind data and those of the greater DPR dataset in the VN suggest that estimates of vertical motion may be inferred in regions without ground-based measurements. We present a climatology of the 12 convective regimes identified within the DPR VN dataset as well as early efforts to estimate the kinematic and microphysical structures of precipitation profiles within the greater GPM DPR dataset by applying machine learning techniques. Precipitation data paired with global estimates of vertical winds from these efforts offer early insight to and support upcoming missions to retrieve convective mass flux, including the Investigation of Convective Updrafts (INCUS) in the Tropics and the global Atmosphere Observing System (AOS).
Transient events of an unusual character have been discovered in the daily pressure variations of the Mars atmosphere's pressure at the planetary surface which last only a few Martian days, appear to repeat on an annual basis, cover a large part of the given day's hemisphere, occur in pairs separated by 20-days in some cases, and coincide with the annual pressure minimum. They also consist of spectral components nearly identical in frequency with diurnal and semidiurnal harmonics. It is presently suggested that these events are Kelvin, normal-mode, transient, global oscillations. An almost-diurnal and an almost-semidiurnal high-frequency global oscillation distinct from solar-driven tides may be common on Mars.