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NASA NTRS2002

Sensitivity of Lower Stratospheric Assimilated Ozone on Error Covariance Modeling and Data Selection

Assimilated ozone is produced at the NASA/Goddard Data Assimilation Office by blending ozone retrieved from the Solar Backscatter UltraViolet/2 (SBUV/2) instrument and the Earth Probe Total Ozone Mapping Spectrometer (EP TOMS) measurements into an off-line transport model. The current system tends to overestimate the amount of lower stratospheric ozone. This is a region where ozone plays a key role in the forcing of climate. A biased ozone field in this region will adversely impact calculations of the stratosphere-troposphere exchange and, when used as a first guess in retrievals, the values determined from satellite observations. Since these are all important applications of assimilated ozone products, effort is being directed towards reducing this bias. The SBUV ozone data have a coarse vertical resolution with increased uncertainty below the ozone maximum, and TOMS provides only total ozone columns. Thus, the assimilated ozone in the lower stratosphere, and its vertical distribution in particular, are only weakly constrained by the incoming SBUV and TOMS data. Consequently, the assimilated ozone distribution should be sensitive to changes in inputs to the statistical analysis scheme. Accordingly, the sensitivity of the assimilated lower stratospheric ozone fields to changes in the TOMS error-covariance modeling and the SBUV data selection has been investigated. The use of a spatially correlated TOMS error covariance model led to improvements in the product. However, withholding the SBUV/2 data for the layer between 63 and 126 hPa typically degraded the product, a result which vindicates the use of this layer ozone product, despite its known errors. These efforts to improve the lower stratospheric distribution will be extended to include a more advanced forecast error covariance model, and by assimilating ozone products from new instruments on Envisat and EOS Aura.

Stajner, Ivanka↗

NASA NTRS2017

Importance of a Priori Vertical Ozone Profiles for TEMPO Air Quality Retrievals

Ozone (O3) is a toxic pollutant which plays a major role in air quality. Typically, monitoring of surface air quality and O3 mixing ratios is conducted using in situ measurement networks. This is partially due to high-quality information related to air quality being limited from space-borne platforms due to coarse spatial resolution, limited temporal frequency, and minimal sensitivity to lower tropospheric and surface-level O3. The Tropospheric Emissions: Monitoring of Pollution (TEMPO) satellite is designed to address the limitations of current space-based platforms and to improve our ability to monitor North American air quality. TEMPO will provide hourly data of total column and vertical profiles of O3 with high spatial resolution to be used as a near-real-time air quality product. TEMPO O3 retrievals will apply the Smithsonian Astrophysical Observatory profile algorithm developed based on work from GOME (Global Ozone Monitoring Experiment), GOME-2, and OMI (Ozone Monitoring Instrument). This algorithm is suggested to use a priori O3 profile information from a climatological data-base developed from long-term ozone-sonde measurements (tropopause-based (TB-Clim) O3 climatology). This study evaluates the TB-Clim dataset and model simulated O3 profiles, which could potentially serve as a priori O3 profile information in TEMPO retrievals, from near-real-time data assimilation model products (NASA GMAO's (Global Modeling and Assimilation Office) operational GEOS-5 (Goddard Earth Observing System, Version 5) FP (Forecast Products) model and reanalysis data from MERRA2 (Modern-Era Retrospective analysis for Research and Applications, Version 2)) and a full chemical transport model (CTM), GEOS-Chem. In this study, vertical profile products are evaluated with surface (0-2 kilometers) and tropospheric (0-10 kilometers) TOLNet (Tropospheric Ozone Lidar Network) observations and the theoretical impact of individual a priori profile sources on the accuracy of TEMPO O3 retrievals in the troposphere and at the surface are presented. Results indicate that while the TB-Clim climatological dataset can replicate seasonally-averaged tropospheric O3 profiles, model-simulated profiles from a full CTM resulted in more accurate tropospheric and surface-level O3 retrievals from TEMPO when compared to hourly and daily-averaged TOLNet observations. Furthermore, it is shown that when large surface O3 mixing ratios are observed, TEMPO retrieval values at the surface are most accurate when applying CTM a priori profile information compared to all other data products.

Priori↗

NASA NTRS2014

Implementation of Active Thermal Control (ATC) for the Soil Moisture Active and Passive (SMAP) Radiometer

NASA's Earth Observing Soil Moisture Active and Passive (SMAP) Mission is scheduled to launch in November 2014 into a 685 kilometer near-polar, sun-synchronous orbit. SMAP will provide comprehensive global mapping measurements of soil moisture and freeze/thaw state in order to enhance understanding of the processes that link the water, energy, and carbon cycles. The primary objectives of SMAP are to improve worldwide weather and flood forecasting, enhance climate prediction, and refine drought and agriculture monitoring during its three year mission. The SMAP instrument architecture incorporates an L-band radar and an L-band radiometer which share a common feed horn and parabolic mesh reflector. The instrument rotates about the nadir axis at approximately 15 revolutions per minute, thereby providing a conically scanning wide swath antenna beam that is capable of achieving global coverage within three days. In order to make the necessary precise surface emission measurements from space, the electronics and hardware associated with the radiometer must meet tight short-term (instantaneous and orbital) and long-term (monthly and mission) thermal stabilities. Maintaining these tight thermal stabilities is quite challenging because the sensitive electronics are located on a fast spinning platform that can either be in full sunlight or total eclipse, thus exposing them to a highly transient environment. A passive design approach was first adopted early in the design cycle as a low-cost solution. With careful thermal design efforts to cocoon and protect all sensitive components, all stability requirements were met passively. Active thermal control (ATC) was later added after the instrument Preliminary Design Review (PDR) to mitigate the threat of undetected gain glitches, not for thermal-stability reasons. Gain glitches are common problems with radiometers during missions, and one simple way to avoid gain glitches is to use the in-flight set point programmability that ATC affords to operate the radiometer component away from the problematic temperature zone. A simple ThermXL model (10 nodes) was developed to exercise quick trade studies among various proposed control algorithms: Modified P control vs. PI control. The ThermXL results were then compared with the detailed Thermal Desktop (TD) model for corroboration. Once done, the simple ThermXL model was used to evaluate parameter effects such as temperature digitization, heater size and gain margin, time step, and voltage variation of power supply on the ATC performance. A Modified P control algorithm was implemented into the instrument flight electronics based on the ThermXL results. The thermal short-term stability margin decreased by 10 percent with ATC and a wide temperature error band (plus or minus 0.1 degrees Centigrade) compared to the original passive thermal design. However, a tighter temperature error band (plus or minus 0.1 degrees Centigrade) increased the thermal short-term stability margin by a factor of three over the passive thermal design. The current ATC design provides robust thermal control, tighter stability, and greater in-flight flexibility even though its implementation was prompted by non-thermal performance concerns.

Mikhaylov, Rebecca↗

NASA NTRS2010

Magnetic Field Measurement on the C/NOFS Satellite: Geomagnetic Storm Effects in the Low Latitude Ionosphere

The Vector Electric Field Investigation (VEFI) suite onboard the Communications/Navigation Outage Forecasting System (C/NOFS) spacecraft includes a sensitive fluxgate magnetometer to measure DC and ULF magnetic fields in the low latitude ionosphere. The instrument includes a DC vector measurement at 1 sample/sec with a range of +/- 45,000 nT whose primary objective is to provide direct measurements of both V x B and E x B that are more accurate than those obtained using a simple magnetic field model. These data can also be used for scientific research to provide information of large-scale ionospheric and magnetospheric current systems, which, when analyzed in conjunction with the C/NOFS DC electric field measurements, promise to advance our understanding of the electrodynamics of the low latitude ionosphere. In this study, we use the magnetic field data to study the temporal and local time variations of the ring currents during geomagnetic storms. We first compare the in situ measurements with the POMME (the POtsdam Magnetic Model of the Earth) model in order to provide an in-flight "calibration" of the data as well as compute magnetic field residuals essential for revealing large scale external current systems. We then compare the magnetic field residuals observed both during quiet times and during geomagnetic storms at the same geographic locations to deduce the magnetic field signatures of the ring current. As will be shown, the low inclination of the C/NOFS satellite provides a unique opportunity to study the evolution of the ring current as a function of local time, which is particularly insightful during periods of magnetic storms. This paper will present the initial results of this study.

Le, Guan↗

NASA NTRS2023

Southeast U.S. Agriculture: Evaluating the Spatial and Temporal Distribution of Flash Droughts within Agricultural Areas and Regional Crop Calendars in the Southeast using Earth Observations

A flash drought refers to the rapid onset or intensification of drought-like conditions. Within the Southeastern United States, flash droughts are made worse by the presence of consumptive vegetation and poor water-holding soils. According to the United States Drought Monitor, a 2016 flash drought occurred with roughly 92% of Georgia, Alabama, Mississippi, and Tennessee experiencing “severe drought” or worse in the fall of that year. The event resulted in widespread wildfires, reservoir shortages that led to interstate disputes over water rights, significant deterioration of pasture and rangeland, and crop sale losses. The occurrence of a flash drought similar to that listed above can cost the Southeast hundreds of millions of dollars, with effects lasting for several years. For this reason, the development of flash drought monitoring, forecasting, and communication tools is needed to alert both states and their practitioners of possible flash drought events, offsetting the potential loss caused by a flash drought event. This research employed NASA's Short-Term Prediction and Transition Center-Land Information System, Landsat 7 Enhanced Thematic Mapper Plus, and Landsat 8 Operational Land Imager and other datasets to determine climatological trends during peak growing season from 2000-2022. These products can help partners at the Alabama Office of the State Climatologist, National Integrated Drought Information System, and National Coordinated Soil Moisture Monitoring Network better manage agricultural lands inside drought-prone zones and monitor crop sensitivity during different growing seasons.

Kindrea Gibbons↗

NASA NTRS2019

The Interaction Between Boundary Layer and Convection Schemes in a WRF Simulation of Post‐Cold‐Frontal Clouds over the ARM East North Atlantic Site

The correct representation of lowlevel midlatitude clouds found in the wake of cold fronts strongly relies on the representation of planetary boundary layer (PBL) and convection processes, which are typically parameterized separately in numerical models. Using the Weather Research and Forecasting Model (WRF), this study investigates how distinct pairs of PBL and convection parameterization schemes represent cloud fraction in the postcoldfrontal region. The simulations focus on the region of the DOEARM Eastern North Atlantic observation site in the Azores Islands in the wake of a cold front that passed on December 25, 2015. Different PBL and convection schemes are combined to create 12 distinct configurations. The main differences between the selected physical parameterizations are the strength of vertical mixing and the entrainment. The simulations produce a wide range of cloud fractions, where some configurations significantly underestimate while others clearly overestimate satellite and surfacebased estimates of cloud fraction. A skill score is used to quantitatively assess the performance of each configuration with respect to groundbased radar data. The key processes that are found to significantly impact the cloud fraction distribution are the strength of the PBL decoupling, the vertical wind shear, entrainment and detrainment rates in shallow convection and the occurrence of drizzle. This indicates that to successfully simulate postcoldfrontal clouds, modeled physics must balance strong internal vertical mixing and weak exchange with the free troposphere. For this case study, cloud fraction was more sensitive to the choice of convection scheme than PBL scheme.

moist convection interaction between parameterizat↗

NASA NTRS2005

An Improved Analysis of Forest Carbon Dynamics using Data Assimilation

There are two broad approaches to quantifying landscape C dynamics - by measuring changes in C stocks over time, or by measuring fluxes of C directly. However, these data may be patchy, and have gaps or biases. An alternative approach to generating C budgets has been to use process-based models, constructed to simulate the key processes involved in C exchange. However, the process of model building is arguably subjective, and parameters may be poorly defined. This paper demonstrates why data assimilation (DA) techniques - which combine stock and flux observations with a dynamic model - improve estimates of, and provide insights into, ecosystem carbon (C) exchanges. We use an ensemble Kalman filter (EnKF) to link a series of measurements with a simple box model of C transformations. Measurements were collected at a young ponderosa pine stand in central Oregon over a 3-year period, and include eddy flux and soil C02 efflux data, litterfall collections, stem surveys, root and soil cores, and leaf area index data. The simple C model is a mass balance model with nine unknown parameters, tracking changes in C storage among five pools; foliar, wood and fine root pools in vegetation, and also fresh litter and soil organic matter (SOM) plus coarse woody debris pools. We nested the EnKF within an optimization routine to generate estimates from the data of the unknown parameters and the five initial conditions for the pools. The efficacy of the DA process can be judged by comparing the probability distributions of estimates produced with the EnKF analysis vs. those produced with reduced data or model alone. Using the model alone, estimated net ecosystem exchange of C (NEE)= -251 f 197g Cm-2 over the 3 years, compared with an estimate of -419 f 29gCm-2 when all observations were assimilated into the model. The uncertainty on daily measurements of NEE via eddy fluxes was estimated at 0.5gCm-2 day-1, but the uncertainty on assimilated estimates averaged 0.47 g Cm-2 day-1, and only exceeded 0.5gC m-2 day-1 on days where neither eddy flux nor soil efflux data were available. In generating C budgets, the assimilation process reduced the uncertainties associated with using data or model alone and the forecasts of NEE were statistically unbiased estimates. The results of the analysis emphasize the importance of time series as constraints. Occasional, rare measurements of stocks have limited use in constraining the estimates of other components of the C cycle. Long time series are particularly crucial for improving the analysis of pools with long time constants, such as SOM, woody biomass, and woody debris. Long-running forest stem surveys, and tree ring data, offer a rich resource that could be assimilated to provide an important constraint on C cycling of slow pools. For extending estimates of NEE across regions, DA can play a further important role, by assimilating remote-sensing data into the analysis of C cycles. We show, via sensitivity analysis, how assimilating an estimate of photosynthesis - which might be provided indirectly by remotely sensed data - improves the analysis of NEE.

Williams, Mathew↗

NASA NTRS2015

Impact of Asian Aerosols on Precipitation Over California: An Observational and Model Based Approach

Dust and pollution emissions from Asia are often transported across the Pacific Ocean to over the western United States. Therefore, it is essential to fully understand the impact of these aerosols on clouds and precipitation forming over the eastern Pacific and western United States, especially during atmospheric river events that account for up to half of California's annual precipitation and can lead to widespread flooding. In order for numerical modeling simulations to accurately represent the present and future regional climate of the western United States, we must account for the aerosol-cloud-precipitation interactions associated with Asian dust and pollution aerosols. Therefore, we have constructed a detailed study utilizing multi-sensor satellite observations, NOAA-led field campaign measurements, and targeted numerical modeling studies where Asian aerosols interacted with cloud and precipitation processes over the western United States. In particular, we utilize aerosol optical depth retrievals from the NASA Moderate Resolution Imaging Spectroradiometer (MODIS), NOAA Geostationary Operational Environmental Satellite (GOES-11), and Japan Meteorological Agency (JMA) Multi-functional Transport Satellite (MTSAT) to effectively detect and monitor the trans-Pacific transport of Asian dust and pollution. The aerosol optical depth (AOD) retrievals are used in assimilating the Weather Research and Forecasting model coupled with Chemistry (WRF-Chem) in order to provide the model with an accurate representation of the aerosol spatial distribution across the Pacific. We conduct WRF-Chem model simulations of several cold-season atmospheric river events that interacted with Asian aerosols and brought significant precipitation over California during February-March 2011 when the NOAA CalWater field campaign was ongoing. The CalWater field campaign consisted of aircraft and surface measurements of aerosol and precipitation processes that help extensively validate our WRF-Chem model simulations. After validating the capability of the WRF-Chem in realistically simulating the aerosol-cloud precipitation interactions, we conduct sensitivity studies where the AOD is doubled to diagnose whether an increasing concentration of Asian aerosols over the western United States will lead to further impacts on the cloud and precipitation processes over California. We also perform sensitivity studies where the aerosols will be partitioned into dust-only and pollution-only in order to separate the impacts of the differing Asian aerosol species. The results of our WRF-Chem model simulations aim to show that the trans-Pacific transport of Asian aerosols influence the precipitation associated with atmospheric river events that can ultimately impact the regional climate of the western United States. 1 University

Naeger, Aaron R.↗

NASA NTRSDate not supplied

Langley Automated Sensor Inter-calibration System (LASICS): Open Access Tools for Satellite Imager Inter-Calibration

Satellite imager calibration teams are tasked with maintaining stable measurement records to facilitate reliable monitoring of geophysical parameters and ensure dependable input for weather forecast models. Satellite imagers are neither uniformly calibrated nor radiometrically scaled to a common reference. Consistent inter-calibration between various earth-orbiting satellite imager pairs is a critical step in the creation of seamless earth-scene reflectance data records over time for input to higher level algorithms that retrieve earth system climate-sensitive properties. Each imager inherently by virtue of its optics (and associated properties like Spectral Response etc.) will have a unique measurement of the same earth-scene reflected signal. A key part of this is the identification and prediction of events where the imager pairs from their respective earth-orbits view the same stable terrestrial targets with nearly identical viewing and solar geometry. Langley Automated Sensor Inter-calibration System (LASICS) will provide the Earth remote sensing community with a foundation for the harmonization of these remote sensing records by the development of an intuitive, user-friendly, interactive web-based open access service that will leverage, an existing extensive and ever-growing database of earth-imager channel spectral response functions, on-demand capabilities for computation and visualization of spectral band adjustment factors using a variety of external hyper-spectral earth observation sources (e.g. SCIAMACHY, GOME-2 for VIS and IASI, AIRS for IR) and a variety of Solar Irradiance Spectra.

Arun Gopalan↗

NASA NTRS1995

The mesoscale forcing of a midlatitude upper-tropospheric jet streak by a simulated convective system. 2: Kinetic energy and resolution analysis

A kinetic energy (KE) analysis of the forcing of a mesoscale upper-tropospheric jet streak by organized diabatic processes within the simulated convective system (SCS) that was discussed in Part 1 is presented in this study. The relative contributions of the ageostrophic components of motion to the generation of KE of the convectively generated jet streak are compared, along with the KE generation by the rotational (nondivergent) and irrotational (divergent) mass transport. The sensitivity of the numerical simulations of SCS development to resolution is also briefly examined. Analysis within isentropic coordinates provides for an explicit determination of the influence of the diabatic processes on the generation of KE. The upper-level production of specific KE is due predominatly to the inertial advective ageostrophic component (IAD), and as such represents the primary process through which the KE of the convectively generated jet streak is realized. A secondary contribution by the inertial diabatic (IDI) term is observed. Partitioning the KE generation into its rotational and irrotational components reveals that the latter, which is directly linked to the diabatic heating within the SCS through isentropic continuity requirements, is the ultimate source of KE generation as the global area integral of generation by the rotational component vanishes. Comparison with an identical dry simulation reveals that the net generation of KE must be attributed to latent heating. Both the IAD and IDI ageostrophic components play important roles in this regard. Examination of results from simulations conducted at several resolutions supports the previous findings in that the effects of diabatic processes and ageostrophic motion on KE generation remain consistent. Resolution does impact the location and timing of SCS development, a result that has important implications in forecasting the onset of convection that develops from evolution of the large-scale flow and moisture transport. Marked differences are observed in the momentum field aloft subsequent to the life cycle of the SCS in the 1 deg, 30-level base case (MP130) simulation discussed in Part 1 versus its 2 deg counterparts in that the MP130 simulation with higher spatial resolution contains from 14% to 30% more total KE.

Wolf, Bart J.↗

NASA NTRS2014

Comparison of Climatological Planetary Boundary Layer Depth Estimates Using the GEOS-5 AGCM

Planetary boundary layer (PBL) processes, including those influencing the PBL depth, control many aspects of weather and climate and accurate models of these processes are important for forecasting changes in the future. However, evaluation of model estimates of PBL depth are difficult because no consensus on PBL depth definition currently exists and various methods for estimating this parameter can give results that differ by hundreds of meters or more. In order to facilitate comparisons between the Goddard Earth Observation System (GEOS-5) and other modeling and observational systems, seven PBL depth estimation methods are used to produce PBL depth climatologies and are evaluated and compared here. All seven methods evaluate the same atmosphere so all differences are related solely to the definition chosen. These methods depend on the scalar diffusivity, bulk and local Richardson numbers, and the diagnosed horizontal turbulent kinetic energy (TKE). Results are aggregated by climate class in order to allow broad generalizations. The various PBL depth estimations give similar midday results with some exceptions. One method based on horizontal turbulent kinetic energy produces deeper PBL depths in the winter associated with winter storms. In warm, moist conditions, the method based on a bulk Richardson number gives results that are shallower than those given by the methods based on the scalar diffusivity. The impact of turbulence driven by radiative cooling at cloud top is most significant during the evening transition and along several regions across the oceans and methods sensitive to this cooling produce deeper PBL depths where it is most active. Additionally, Richardson number-based methods collapse better at night than methods that depend on the scalar diffusivity. This feature potentially affects tracer transport.

Planetary Boundary Layer Depth↗

NASA NTRS2016

The Staring OBservations of the Atmosphere (SOBA) Mission Concept

The Staring OBservations of the Atmosphere (SOBA) Mission is a concept that was developed and matured under the guidance of the NASA Ames Project EXellence (APEX) program. If funded, it will provide an unprecedented opportunity to improve ash transport forecasts and climate model simulations associated with volcanic eruptions. NASA and National science objectives require a better understanding of volcanic aerosol and trace gas emissions, transport, chemical transformation, and deposition, since they impact Earth's climate and atmospheric composition, human health, and aviation safety. Natural hazards such as the 2010 eruption of the Eyjafjallajökull volcano in Iceland demonstrated how existing remote-sensing assets were inadequate for individual volcanic event monitoring. During this eruption, available instruments were unable to provide data necessary to initialize volcanic plume transport models so that they could accurately predict the quantity and location of volcanic ash. As a result, thousands of flights around the world were grounded unnecessarily, at great expense. Volcanoes can also play a large role in regulation of the Earth's climate, so SOBA observations will also be used to evaluate and improve volcanic aerosol and trace gas simulation in chemical transport models (CTMs) and global climate models (GCMs). We propose the development of an airborne remote sensing concept and field campaign that will respond to an eruption and provide near real time observations of a volcanic plume, specifically ash injection height, transport, aerosol microphysical physical properties, and the location and concentration of sulfur dioxide (SO2) (sulfate (SO42-) aerosol precursor). This airborne system will utilize a depolarization sensitive, downward looking Light Detection And Ranging (lidar) instrument and an ultraviolet (UV) imaging spectrometer, and will provide data to be ingested by volcanic ash advisory models. Furthermore, the lessons learned in the development of this system could eventually guide regular deployment of similar systems by NASA or other government agencies.

Aerosols↗

NASA NTRS2012

Using the VAHIRR Radar Algorithm to Investigate Lightning Cessation

Accurately determining the threat posed by lightning is a major area for improved operational forecasts. Most efforts have focused on the initiation of lightning within a storm, with far less effort spent investigating lightning cessation. Understanding both components, initiation and cessation, are vital to improving lightning safety. Few organizations actively forecast lightning onset or cessation. One such organization is the 45th Weather Squadron (45WS) for the Kennedy Space Center (KSC) and Cape Canaveral Air Force Station (CCAFS). The 45WS has identified that charged anvil clouds remain a major threat of continued lightning and can greatly extend the window of a potential lightning strike. Furthermore, no discernable trend of total lightning activity has been observed consistently for all storms. This highlights the need for more research to find a robust method of knowing when a storm will cease producing lightning. Previous lightning cessation work has primarily focused on forecasting the cessation of cloud-to -ground lightning only. A more recent, statistical study involved total lightning (both cloud-to-ground and intracloud). Each of these previous works has helped the 45WS take steps forward in creating improved and ultimately safer lightning cessation forecasts. Each study has either relied on radar data or recommended increased use of radar data to improve cessation forecasts. The reasoning is that radar data is able to either directly or by proxy infer more about dynamical environment leading to cloud electrification and eventually lightning cessation. The authors of this project are focusing on a two ]step approach to better incorporate radar data and total lightning to improve cessation forecasts. This project will utilize the Volume Averaged Height Integrated Radar Reflectivity (VAHIRR) algorithm originally developed during the Airborne Field Mill II (ABFM II) research project. During the project, the VAHIRR product showed a trend of increasing values with increases in the electric field magnitude above 3 kV/m. An extreme value analysis showed that VAHIRR values less than or equal to 10 dBZ-km showed that the probability of having an electric field magnitude larger than 3 kV/m was less than one in ten thousand. VAHIRR also was found to be sensitive at indicating anvil clouds that posed a threat of initiating a lightning flash. This project seeks to use VAHIRR to analyze its utility as a lightning cessation tool, particularly dealing with the threat posed by detached anvils. The results from this project will serve as a baseline effectiveness of radar ]based lightning cessation algorithms. This baseline will be used in the second, and concurrent work by the co ]author fs who are developing a lightning cessation algorithm based on dual ]polarimetric radar data. Ultimately, an accurate method for identifying lightning cessation can save money on lost manpower time as well as greatly improve lightning safety.

Stano, Geoffrey T.↗

NASA NTRS2011

Evaluating the Impacts of NASA/SPoRT Daily Greenness Vegetation Fraction on Land Surface Model and Numerical Weather Forecasts

The NASA Short-term Prediction Research and Transition (SPoRT) Center develops new products and techniques that can be used in operational meteorology. The majority of these products are derived from NASA polar-orbiting satellite imagery from the Earth Observing System (EOS) platforms. One such product is a Greenness Vegetation Fraction (GVF) dataset, which is produced from Moderate Resolution Imaging Spectroradiometer (MODIS) data aboard the NASA EOS Aqua and Terra satellites. NASA SPoRT began generating daily real-time GVF composites at 1-km resolution over the Continental United States (CONUS) on 1 June 2010. The purpose of this study is to compare the National Centers for Environmental Prediction (NCEP) climatology GVF product (currently used in operational weather models) to the SPoRT-MODIS GVF during June to October 2010. The NASA Land Information System (LIS) was employed to study the impacts of the new SPoRT-MODIS GVF dataset on land surface models apart from a full numerical weather prediction (NWP) model. For the 2010 warm season, the SPoRT GVF in the western portion of the CONUS was generally higher than the NCEP climatology. The eastern CONUS GVF had variations both above and below the climatology during the period of study. These variations in GVF led to direct impacts on the rates of heating and evaporation from the land surface. The second phase of the project is to examine the impacts of the SPoRT GVF dataset on NWP using the Weather Research and Forecasting (WRF) model. Two separate WRF model simulations were made for individual severe weather case days using the NCEP GVF (control) and SPoRT GVF (experimental), with all other model parameters remaining the same. Based on the sensitivity results in these case studies, regions with higher GVF in the SPoRT model runs had higher evapotranspiration and lower direct surface heating, which typically resulted in lower (higher) predicted 2-m temperatures (2-m dewpoint temperatures). The opposite was true for areas with lower GVF in the SPoRT model runs. These differences in the heating and evaporation rates produced subtle yet quantifiable differences in the simulated convective precipitation systems for the selected severe weather case examined.

Bell, Jordan R.↗

NASA NTRS2013

A Single-column Model Ensemble Approach Applied to the TWP-ICE Experiment

Single-column models (SCM) are useful test beds for investigating the parameterization schemes of numerical weather prediction and climate models. The usefulness of SCM simulations are limited, however, by the accuracy of the best estimate large-scale observations prescribed. Errors estimating the observations will result in uncertainty in modeled simulations. One method to address the modeled uncertainty is to simulate an ensemble where the ensemble members span observational uncertainty. This study first derives an ensemble of large-scale data for the Tropical Warm Pool International Cloud Experiment (TWP-ICE) based on an estimate of a possible source of error in the best estimate product. These data are then used to carry out simulations with 11 SCM and two cloud-resolving models (CRM). Best estimate simulations are also performed. All models show that moisture-related variables are close to observations and there are limited differences between the best estimate and ensemble mean values. The models, however, show different sensitivities to changes in the forcing particularly when weakly forced. The ensemble simulations highlight important differences in the surface evaporation term of the moisture budget between the SCM and CRM. Differences are also apparent between the models in the ensemble mean vertical structure of cloud variables, while for each model, cloud properties are relatively insensitive to forcing. The ensemble is further used to investigate cloud variables and precipitation and identifies differences between CRM and SCM particularly for relationships involving ice. This study highlights the additional analysis that can be performed using ensemble simulations and hence enables a more complete model investigation compared to using the more traditional single best estimate simulation only.

numerical weather forecasting↗

NASA NTRS1998

Boreal Winter Predictions with the GEOS-2 GCM: The Role of Boundary Forcing and Initial Conditions

Ensembles of atmospheric General Circulation Model (GCM) seasonal forecasts and long-term simulations (1980-94) are analyzed to assess the controlling influences of boundary forcing and memory of the initial conditions. Both the forecasts and simulations are carried out with version 2 of the Goddard Earth Observing System (GEOS-2) GCM forced with observed sea surface temperatures (SSTs). While much of the focus is on the seasonal time scale (January- March) and the Pacific North American (PNA) region, we also present results for other regions, shorter time scales, and other known modes of variability in the northern hemisphere extratropics. Forecasts of indices of some of the key large-scale modes of variability show that there is considerable variability in skill between different regions of the Northern Hemisphere. The eastern North Atlantic region has the poorest long lead forecast skill showing no skill beyond about 10 days. Skillful seasonal forecasts are primarily confined to the wave-like ENSO response emanating from the tropical Pacific. In the Northern Hemisphere, this is associated with the well-known Pacific/North American (PNA) pattern. Memory of the initial conditions is the major factor leading to skillful extratropical forecasts of lead time less than one month, while SST forcing is the only factor at the seasonal time scale. SST forcing contributes to skillful forecasts at sub- seasonal time scales only over the PNA region. The GEOS-2 GCM produces average (1980-94) signal to noise ratios which are less than one everywhere in the extratropics, except for the subtropical Pacific where they approach 1.5. When confined to the ENSO years, the maximum signal to noise ratios occur in the PNA region where they exceed three. An assessment of the sampling distribution of the forecasts suggests the model's ENSO response is very likely too weak. These results show some sensitivity to the uncertainties in the estimates of the SST forcing fields. In the North Pacific region, the sensitivity to SST forcing manifests itself primarily as changes in the variability of the PNA response, underscoring the need for an ensemble approach to the seasonal prediction problem.

Chang, Yehui↗

NASA NTRS1997

The Evolving Universe: Structure and Evolution of the Universe Roadmap 2000-2020

The Roadmap for the Structure and Evolution of the Universe (SEU) theme embraces three fundamental, scientific quests: (1) To explain structure in the Universe and forecast our cosmic destiny. (2) To explore the cycles of matter and energy in the evolving Universe. (3) To examine the ultimate limits of gravity and energy in the Universe. These quests are developed into six, focused research campaigns addressing the objectives of one or more quests: Identify dark matter and learn how it shapes galaxies and systems of galaxies; Find out where and when the chemical elements were made; Understand the cycles in which matter, energy, and magnetic field are exchanged between stars and the gas between stars; Discover how gas flows in disks and how cosmic jets are formed; Identify the sources of gamma-ray bursts and high-energy cosmic rays; and Measure how strong gravity operates near black holes and how it affects the early Universe. These campaigns lead to a portfolio of future major missions of strong scientific and popular appeal, strongly endorsed by the scientific community and which has undergone significant initial study. Some of these missions are in a state of readiness that makes ideal candidates for the present Office of Space Science Strategic Plan; others may well feature in the next Strategic Plan. Each provides a golden scientific opportunity to advance our understanding of the Universe. Our highest priority science objectives are addressed by five Observatory Class Missions, unranked by science, but in approximate order of readiness: A high-energy gamma-ray facility that will observe relativistic jets and study the sources of cosmic gamma ray bursts; An ultra-sensitive X-ray telescope, optimized for spectroscopy, to examine the hot gas linked with clusters of galaxies, the disks around black holes, and supernova explosions; A large, radio telescope in deep space to map central regions of distant quasars and perform astrometric investigations; An orbiting gravitational coalescing, massive black holes and test how gravity waves distort spacetime; A pair of Earth-orbiting, optical telescopes that will detect flashes of light produced when ultra high-energy cosmic rays impact the upper atmosphere so as to determine their arrival directions and energies. A new program for supporting pertinent international collaboration is strongly endorsed and maintaining a strong Explorer program is important. The flexibility to exploit exceptional opportunities, such as attaching payloads to space station, should also be acquired. A strong technology development program must be initiated now to enable this mission set.

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NASA NTRS2017

CubeSat Infrared Atmospheric Sounder (CIRAS) NASA InVEST Technology Demonstration

Infrared sounders measure the upwelling radiation of the Earth in the Midwave Infrared (MWIR) and Longwave Infrared (LWIR) region of the spectrum with global daily coverage from space. The observed radiances are assimilated into weather forecast models and used to retrieve lower tropospheric temperature and water vapor for climate studies. There are several operational sounders today including the Atmospheric Infrared Sounder (AIRS) on Aqua, the Crosstrack Infrared Sounder (CrIS) on Suomi NPP and JPSS, and the Infrared Atmospheric Sounding Interferometer (IASI) on the MetOp spacecraft. The CubeSat Infrared Atmospheric Sounder (CIRAS) is a NASA In-flight Validation of Earth Science Technologies (InVEST) program to demonstrate three new instrument technologies in an imaging sounder configuration. The first is a 2D array of High Operating Temperature Barrier Infrared Detector (HOT-BIRD) material, selected for its high uniformity, low cost, low noise and higher operating temperatures than traditional materials. The detectors are hybridized to a commercial ROIC and commercial camera electronics. The second technology is a MWIR Grating Spectrometer (MGS) designed to provide imaging spectroscopy for atmospheric sounding in a CubeSat volume. The MGS employs an immersion grating or grism, has no moving parts, and is based on heritage spectrometers including the OCO-2. The third technology is a Black Silicon infrared blackbody calibration target. The Black Silicon offers very low reflectance over a broad spectral range on a flat surface and is more robust than carbon nanotubes. JPL will also develop the mechanical, electronic and thermal subsystems for the CIRAS payload. The spacecraft will be a commercially available CubeSat. The integrated system will be a complete 6U CubeSat capable of measuring temperature and water vapor profiles with good lower tropospheric sensitivity. The low cost of CIRAS enables multiple units to be flown to improve temporal coverage or measure 3D Atmospheric Motion Vector (AMV) winds. CIRAS will launch in 2019 and is only a technology demonstration. However, what we learn will benefit future instruments that support operational weather forecasting and climate studies.

Pagano, Thomas S.↗