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NASA NTRS2020

Dynamical Forecasts of Tropical Terrestrial Carbon Fluxes with the NASA S2S Retrospective Forecast System

Recent advances in the ability to predict climate anomalies at sub-seasonal to seasonal (S2S) timescales allow us to explore the possibility of forecasting carbon flux anomalies. Although carbon flux forecasting is a relatively new concept, it is potentially beneficial as it can help us better understand global and regional land-atmosphere carbon feedbacks associated with climate variations and can provide guidance for future field mission design. Here we evaluate the skill of forecasted terrestrial carbon anomalies generated from meteorological anomalies produced with the NASA Global Modeling and Assimilation Office (GMAO) S2S forecast system. We focus here on three representative time periods (the most recent 2015-2016 El Nino, 2011 La Nina, and 2014 as a neutral year), with each corresponding 9-month forecast comprising four ensemble members initialized in the preceding December. The meteorological variables produced by the GMAO forecast system were bias-corrected using a climatology derived from the Modern Era Retrospective analysis for Research and Applications, version 2 (MERRA-2) before being used to drive a suite of offline simulations with the NASA Catchment-CN terrestrial biosphere model, a model that computes water-energy-carbon dynamics. Forecasts are evaluated by comparing against satellite-driven estimates of gross primary production (GPP) and inverse model estimates of net carbon flux that incorporate satellite carbon dioxide measurements. We find that the restrospectively predicted carbon fluxes in the tropics reasonably reproduce the signs and magnitudes of the observed anomalies between the 2015-2016 El Nino and the 2011 La Nina for both net flux and GPP. For instance, for the El Nino period, the magnitude of the forecasted negative GPP anomaly in the South American tropics (which undergoes anomalously warm and dry conditions) agrees with the observed GPP anomaly at leads of up to three or four months. Overall, this study demonstrates potential skill in the forecast of biospheric carbon fluxes a few months in advance, a capability that could contribute to attribution studies focusing on carbon flux variations and support innovative observation strategies in the future.

Lee, Eunjee↗
NASA NTRS2019

Uncertainty of Observation Impact Estimation in an Adjoint Model Investigated with an Observing System Simulation Experiment

Adjoint models are often used to estimate the impact of different observations on short-term forecast skill. A common difficulty with the evaluation of short term forecast quality is the choice of verification fields. The use of self-analysis fields for verification is typical but incestuous, and introduces uncertainty due to biases and errors in the analysis field. In this study, an observing system simulation experiment (OSSE) is used to explore the uncertainty in adjoint model estimations of observation impact. The availability of the true state for verification in the OSSE framework in the form of the Nature Run allows calculation of the observation impact without the uncertainties present in self-analysis verification. These impact estimates are compared to estimates calculated using self-analysis verification. The Global Earth Observing System version 5 (GEOS-5) forecast model with Gridpoint Statistical Interpolation (GSI) is used with the National Aeronautics and Space Administration Global Modeling and Assimilation Office (NASA/GMAO) OSSE capability. The adjoint model includes moist processes, with total wet energy selected as the norm for evaluation of observation impacts. The results show that there are measurable but small discrepancies in the adjoint model estimation of observation impact. In general, observations of temperature and winds tend to have overestimated impacts with self-analysis verification, while observations of humidity and moisture-affected observations tend to have underestimated impacts. The small magnitude of the differences in impact estimates supports the robustness of the adjoint method of estimating observation impacts.

N C Prive↗
NASA NTRSDate not supplied

Global Landslide Hazard Assessment for Situational Awareness (LHASA) Version 2: New Activities and Future Plans

A remote sensing-based system has been developed to characterize the potential for rainfall-triggered landslides across the globe in near real-time. The Landslide Hazard Assessment for Situational Awareness (LHASA) model uses a decision tree framework to combine a static susceptibility map derived from information on slope, rock characteristics, forest loss, distance to fault zones and distance to road networks with satellite precipitation estimates from the Global Precipitation Measurement (GPM) mission. Since 2016, the LHASA model has been providing near real-time and retrospective estimates of potential landslide activity. Results of this work are available at https://landslides.nasa.gov. In order to advance LHASA’s capabilities to characterize landslide hazards and impacts dynamically, we have implemented a new approach that leverages machine learning, new parameters, and new inventories. LHASA 2.0 uses the XGBoost machine learning model to bring in dynamic variables as well as additional static variables to better represent landslide hazard globally. Global rainfall forecasts are also being evaluated to provide a 1-3 day forecast of potential landslide activity. Additional factors such as recent seismicity and burned areas are also being considered to represent the preconditioning or changing interactions with subsequent rainfall over affected areas. A series of parameters are being tested within this structure using NASA’s Global Landslide Catalog as well as many other event-based and multi-temporal inventories mapped by the project team or provided by project partners. In addition to estimates of landslide hazard, LHASA Version 2 will incorporate dynamic estimates of exposure including population, roads and infrastructure to highlight the potential impacts that rainfall-triggered landslides. The ultimate goal of LHASA Version 2.0 is to approximate the relative probabilities of landslide hazard and exposure across different space and time scales to inform hazard assessment retrospectively over the past 20 years, in near real-time, and in the future. In addition to the hazard. This presentation will outline the new activities for LHASA Version 2.0 and present some next steps for this system.

Dalia Kirschbaum↗
NASA NTRS1988

Providing operational guidance for the development of sea breeze thunderstorms at the Kennedy Space Center - An experiment using a mesoscale numerical model

The effectiveness of a mesoscale numerical model to provide improved local forecast guidance is evaluated with respect to sea breeze convection storms at the Kennedy Space Center. The model and operational forecast guidance production are described. A case study is presented for sea breeze convection storms and lightning events on July 1, 1986. It is found that the mesoscale numerical model outperforms purely subjective predictions of sea breeze convection. The range of applications for the model are considered.

Lyons, Walter A.↗
NASA NTRS1998

Total Lightning and Radar Storm Characteristics Associated with Severe Storms in Central Florida

This paper examines the three dimensional characteristics of lightning flashes and severe storms observed in Central Florida during 1997-1998. The lightning time history of severe and tornadic storms were captured during the on-going ground validation campaign supporting the Lightning Imaging Sensor (LIS) experiment on the Tropical Rainfall Measuring Mission (TRMM). The ground validation campaign is a collaborative experiment that began in 1997 and involves scientists at the Global Hydrology and Climate Center, MIT/Lincoln Laboratories, and the NWS Forecast Office at Melbourne, FL. Lightning signatures that may provide potential early warning of severe storms are being evaluated by the forecasters at the NWS/MLB office. Severe storms with extreme flash rates sometimes exceeding 300 per minute and accompanying rapid increases in flash rate prior to the onset of the severe weather (hall, damaging winds, tornadoes) have been reported by Hodanish et al. and Williams et al. (1998-this conference). We examine the co-evolving changes in storm structure (mass, echo top, shear, latent heat release) and kinematics associated with these extreme and rapid flash rate changes over time. The flash frequency and density are compared with the three dimensional radar reflectivity structure of the storm to help interpret the possible mechanisms producing the extreme and rapidly increasing flash rates. For two tornadic storms examined thus far, we find the burst of lightning is associated with the development of upper level rotation in the storm. In one case, the lightning burst follows the formation of a bounded weak echo region (BWER). The flash rates diminish with time as the rotation develops to the ground in conjunction with the decent of the reflectivity core. Our initial findings suggest the dramatic increase of flash rates is associated with a sudden and dramatic increase in storm updraft intensity which we hypothesize is stretching vertical vorticity as well as enhancing the development of the mixed phase region of the storm. We discuss the importance of these factors in producing both the observed extreme flash rates and the severe weather that follows in these storms and others to be presented.

Goodman, Steven J↗
NASA NTRS2012

Preliminary Results of a U.S. Deep South Warm Season Deep Convective Initiation Modeling Experiment using NASA SPoRT Initialization Datasets for Operational National Weather Service Local Model Runs

The initiation of deep convection during the warm season is a forecast challenge in the relative high instability and low wind shear environment of the U.S. Deep South. Despite improved knowledge of the character of well known mesoscale features such as local sea-, bay- and land-breezes, observations show the evolution of these features fall well short in fully describing the location of first initiates. A joint collaborative modeling effort among the NWS offices in Mobile, AL, and Houston, TX, and NASA s Short-term Prediction Research and Transition (SPoRT) Center was undertaken during the 2012 warm season to examine the impact of certain NASA produced products on the Weather Research and Forecasting Environmental Modeling System. The NASA products were: a 4-km Land Information System data, a 1-km sea surface temperature analysis, and a 4-km greenness vegetation fraction analysis. Similar domains were established over the southeast Texas and Alabama coastlines, each with a 9 km outer grid spacing and a 3 km inner nest spacing. The model was run at each NWS office once per day out to 24 hours from 0600 UTC, using the NCEP Global Forecast System for initial and boundary conditions. Control runs without the NASA products were made at the NASA SPoRT Center. The NCAR Model Evaluation Tools verification package was used to evaluate both the forecast timing and location of the first initiates, with a focus on the impacts of the NASA products on the model forecasts. Select case studies will be presented to highlight the influence of the products.

Medlin, Jeffrey M.↗
NASA NTRS2000

Evaluation of the Regional Atmospheric Modeling System in the Eastern Range Dispersion Assessment System

The Applied Meteorology Unit is conducting an evaluation of the Regional Atmospheric Modeling System (RAMS) contained within the Eastern Range Dispersion Assessment System (ERDAS). ERDAS provides emergency response guidance for operations at the Cape Canaveral Air Force Station and the Kennedy Space Center in the event of an accidental hazardous material release or aborted vehicle launch. The prognostic data from RAMS is available to ERDAS for display and is used to initialize the 45th Range Safety (45 SW/SE) dispersion model. Thus, the accuracy of the 45 SW/SE dispersion model is dependent upon the accuracy of RAMS forecasts. The RAMS evaluation task consists of an objective and subjective component for the Florida warm and cool seasons of 1999-2000. The objective evaluation includes gridded and point error statistics at surface and upper-level observational sites, a comparison of the model errors to a coarser grid configuration of RAMS, and a benchmark of RAMS against the widely accepted Eta model. The warm-season subjective evaluation involves a verification of the onset and movement of the Florida east coast sea breeze and RAMS forecast precipitation. This interim report provides a summary of the RAMS objective and subjective evaluation for the 1999 Florida warm season only.

Case, Jonathan↗
NASA NTRS2012

The SPoRT-WRF: Evaluating the Impact of NASA Datasets on Convective Forecasts

The Short-term Prediction Research and Transition Center (SPoRT) is a collaborative partnership between NASA and operational forecasting entities, including a number of National Weather Service offices. SPoRT transitions real-time NASA products and capabilities to its partners to address specific operational forecast challenges. One challenge that forecasters face is applying convection-allowing numerical models to predict mesoscale convective weather. In order to address this specific forecast challenge, SPoRT produces real-time mesoscale model forecasts using the Weather Research and Forecasting (WRF) model that includes unique NASA products and capabilities. Currently, the SPoRT configuration of the WRF model (SPoRT-WRF) incorporates the 4-km Land Information System (LIS) land surface data, 1-km SPoRT sea surface temperature analysis and 1-km Moderate resolution Imaging Spectroradiometer (MODIS) greenness vegetation fraction (GVF) analysis, and retrieved thermodynamic profiles from the Atmospheric Infrared Sounder (AIRS). The LIS, SST, and GVF data are all integrated into the SPoRT-WRF through adjustments to the initial and boundary conditions, and the AIRS data are assimilated into a 9-hour SPoRT WRF forecast each day at 0900 UTC. This study dissects the overall impact of the NASA datasets and the individual surface and atmospheric component datasets on daily mesoscale forecasts. A case study covering the super tornado outbreak across the Ce ntral and Southeastern United States during 25-27 April 2011 is examined. Three different forecasts are analyzed including the SPoRT-WRF (NASA surface and atmospheric data), the SPoRT WRF without AIRS (NASA surface data only), and the operational National Severe Storms Laboratory (NSSL) WRF (control with no NASA data). The forecasts are compared qualitatively by examining simulated versus observed radar reflectivity. Differences between the simulated reflectivity are further investigated using convective parameters along with model soundings to determine the impacts of the various NASA datasets. Additionally, quantitative evaluation of select meteorological parameters is performed using the Meteorological Evaluation Tools model verification package to compare forecasts to in situ surface and upper air observations.

Zavodsky, Bradley↗
NASA NTRS1991

Surface wind convergence as a short-term predictor of cloud-to-ground lightning at Kennedy Space Center: A four-year summary and evaluation

Since 1986, USAF forecasters at NASA-Kennedy have had available a surface wind convergence technique for use during periods of convective development. In Florida during the summer, most of the thunderstorm development is forced by boundary layer processes. The basic premise is that the life cycle of convection is reflected in the surface wind field beneath these storms. Therefore the monitoring of the local surface divergence and/or convergence fields can be used to determine timing, location, longevity, and the lightning hazards which accompany these thunderstorms. This study evaluates four years of monitoring thunderstorm development using surface wind convergence, particularly the average over the area. Cloud-to-ground (CG) lightning is related in time and space with surface convergence for 346 days during the summers of 1987 through 1990 over the expanded wind network at KSC. The relationships are subdivided according to low level wind flow and midlevel moisture patterns. Results show a one in three chance of CG lightning when a convergence event is identified. However, when there is no convergence, the chance of CG lightning is negligible.

Watson, Andrew I.↗
NASA NTRS1985

Evaluation of the satellite derived snow cover area - Runoff forecasting models for the inaccessible basins of western Himalayas

In this study, the existing seasonal snow cover area runoff forecasting models of the Indus, Kabul, Sutlej and Chenab basins were evaluated with the concurrent flow correlation model for the period 1975-79. In all the basins under study, correlation of concurrent flow model explained the variability in flow better than by the snow cover area runoff models. Actually, the concurrent flow correlation model explained more than 90 percent of the variability in the flow of these rivers. Compared to this model, the snow cover area runoff models explained less of the variability in flow. In the Himalayan river basins under study and at least for the period under observation, the concurrent flow correlation model provided a set of results with which to compare the estimates from the snow cover area runoff models.

Dey, B.↗
NASA NTRS1977

The effect of increased horizontal resolution on synoptic forecasts with the GISS model of the global atmosphere

The improved horizontal resolution global circulation model in question has a horizontal spacing of 2.5 deg latitude by 3 deg longitude for a resolution of about 250 km in midlatitude. This paper reports on experiments to determine the improvements in forecasting skill and in initial conditions that were made possible by the ultrafine resolution and ultrafine assimilation. The size of the improvement in skill score when the ultrafine model is used for forecasting and assimilation was so large that 60-hour forecasts with the ultrafine model had as good a skill score as the 48-hour forecasts with the fine model. Synoptic evaluations confirmed that ultrafine model forecasts are better than the fine model forecasts.

Quirk, W. J.↗
NASA NTRS2006

Performance of Two Cloud-Radiation Parameterization Schemes in the Finite Volume General Circulation Model for Anomalously Wet May and June 2003 Over the Continental United States and Amazonia

An objective assessment of the impact of a new cloud scheme, called Microphysics of Clouds with Relaxed Arakawa-Schubert Scheme (McRAS) (together with its radiation modules), on the finite volume general circulation model (fvGCM) was made with a set of ensemble forecasts that invoke performance evaluation over both weather and climate timescales. The performance of McRAS (and its radiation modules) was compared with that of the National Center for Atmospheric Research Community Climate Model (NCAR CCM3) cloud scheme (with its NCAR physics radiation). We specifically chose the boreal summer months of May and June 2003, which were characterized by an anomalously wet eastern half of the continental United States as well as northern regions of Amazonia. The evaluation employed an ensemble of 70 daily 10-day forecasts covering the 61 days of the study period. Each forecast was started from the analyzed initial state of the atmosphere and spun-up soil moisture from the first-day forecasts with the model. Monthly statistics of these forecasts with up to 10-day lead time provided a robust estimate of the behavior of the simulated monthly rainfall anomalies. Patterns of simulated versus observed rainfall, 500-hPa heights, and top-of-the-atmosphere net radiation were recast into regional anomaly correlations. The correlations were compared among the simulations with each of the schemes. The results show that fvGCM with McRAS and its radiation package performed discernibly better than the original fvGCM with CCM3 cloud physics plus its radiation package. The McRAS cloud scheme also showed a reasonably positive response to the observed sea surface temperature on mean monthly rainfall fields at different time leads. This analysis represents a method for helpful systematic evaluation prior to selection of a new scheme in a global model.

Sud, Y. C.↗
NASA NTRS1982

Investigation of geomagnetic field forecasting and fluid dynamics of the core

Progress in the development, testing, and evaluation of kinematic geomagnetic forecast models and their utility in magnetic prediction of the core-mantle boundary of the Earth and in determination of the core radius is reported. The GFSC 9/80 model, which uses MAGSAT data, was determined to be of high quality.

Benton, E. R.↗
NASA NTRS2004

An Evaluation of the Accuracy of Meteor Shower Forecasts

Brought into being by the recent Leonid meteor storms, meteor shower forecasts are now regarded by many spacecraft projects as necessary inputs into the planning of spacecraft operations. We compare the shower forecasts made by various researchers over the past six years to actual shower observations in an attempt to create an overall picture of forecast accuracy, specifically focusing on the three aspects most important to space vehicles: 1) the time of shower maximum, 2) the half-width (duration), and 3) the maximum Zenith Hourly Rate (ZHR). It will be noted that, while the times of maxima are generally predicted to within several minutes, the peak ZHRs are often overestimated and shower half-widths are frequently not even calculated. The difficulties involved in converting shower ZHRs into the meteoroid fluxes needed to assess spacecraft risk are also discussed.

Cooke, W.↗
NASA NTRS2020

GRACE Improves Seasonal Groundwater Forecast Initialization Over the United States

We evaluate the impact of Gravity Recovery and Climate Experiment data assimilation (GRACE-DA) on seasonal hydrological forecast initialization over the United States, focusing on groundwater storage. GRACE-based terrestrial water storage (TWS) estimates are assimilated into a land surface model for the2003–16 period. Three-month hindcast (i.e., forecast of past events) simulations are initialized using states from the reference (no data assimilation) and GRACE-DA runs. Differences between the two initial hydrological condition (IHC) sets are evaluated for two forecast techniques at 305 wells where depth to water table measurements are available. Results show that using GRACE-DA-based IHC improves seasonal groundwater forecast performance in terms of both RMSE and correlation. While most regions show improvement, degradation is common in the High Plains, where withdrawals for irrigation practices affect groundwater variability more strongly than the weather variability, which demonstrates the need for simulating such activities. These findings contribute to recent efforts toward an improved U.S. drought monitoring and forecast system.

Augusto Getirana↗
NASA NTRS2009

Recent Weather Technologies Delivered to America's Space Program by the Applied Meteorology Unit

The Applied Meteorology Unit (AMU) is a unique joint venture of NASA, the Air Force and the National Weather Service (NWS) and has been supporting the Space Program for nearly two decades. The AMU acts as a bridge between the meteorological research community and operational forecasters by developing, evaluating and transitioning new technology and techniques to improve weather support to spaceport operations at the Eastern Range (ER) and Kennedy Space Center. Its primary customers are the 45th Weather Squadron at Cape Canaveral Air Force Station (CCAFS), the Spaceflight Meteorology Group at Johnson Space Center and the National Weather Service Office in Melbourne, FL. Its products are used to support NASA's Shuttle and ELV programs as well as Department of Defense and commercial launches from the ER. Shuttle support includes landing sites beyond the ER. The AMU is co-located with the Air Force operational forecasters at CCAFS to facilitate continuous two-way interaction between the AMU and its operational customers. It is operated under a NASA, Air Force, and NWS Memorandum of Understanding (MOU) by a competitively-selected contractor. The contract, which is funded and managed by NASA, provides five full time professionals with degrees in meteorology or related fields, some of whom also have operational experience. NASA provides a Ph.D.- level NASA civil service scientist as Chief of the AMU. The AMU is tasked by its customers through a unique, nationally recognized process. The tasks are limited to development, evaluation and operational transition of technology to improve weather support to spaceport operations and providing expert advice to the customers. The MOU expressly forbids using the AMU resources to conduct operations or do basic research. The presentation will provide a brief overview of the AMU and how it is tasked by its customers to provide high priority products and services. The balance of the presentation will cover a sampling of products delivered over the last 18 years that are currently in operational use. Each example will describe the problem to be solved, the solution provided, and the operational benefits of implementing that solution.

Bauman, WIlliam, H., III↗