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Tropical Cyclones, Hurricanes, and Climate: NASA's Global Cloud-Scale Simulations and New Observations that Characterize the Lifecycle of Hurricanes

One of the primary interests of Global Change research is the impact of climate changes and climate variability on extreme weather events, such as intense tropical storms and hurricanes. Atmospheric climate models run at resolutions of global weather models have been used to study the impact of climate variability, as seen in sea surface temperatures, on the frequency and intensity of tropical cyclones. NASA's Goddard Earth Observing System Model, version 5 (GEOS-5) in ensembles run at 50 km resolution has been able to reproduce the interannual variations of tropical cyclone frequency seen in nature. This, and other global models, have found it much more difficult to reproduce the interannual changes in intensity, a result that reflects the inability of the models to simulate the intensities of the most extreme storms. Better representation of the structures of cyclones requires much higher resolution models. Such improved representation is also fundamental to making best use of satellite observations. In collaboration with NOAA's Geophysical Fluid Dynamics Laboratory, GEOS-5 now has the capability of running at much higher resolution to better represent cloud-scale resolutions. Global simulations at cloud-permitting resolutions (10- to 3.5-km) allows for the development of realistic tropical cyclones from tropical storm 119 km/hr winds) to category 5 (>249km1hr winds) intensities. GEOS-5 has produced realistic rain-band and eye-wall structures in tropical cyclones that can be directly analyzed against satellite observations. For the first time a global climate model is capable of representing realistic intensity and track variability on a seasonal scale across basins. GEOS-5 is also used in assimilation mode to test the impact of NASA's observations on tropical cyclone forecasts. One such test, for tropical cyclone Nargis in the Indian Ocean in May 2008, showed that observations from Atmospheric Infrared Sounder (AIRS) and the Advanced Microwave Sounding Unit (AMSU-A) on Aqua substantially reduced forecast track errors. Tropical cyclones in the northern Indian Ocean pose serious challenges to operational weather forecasting systems, partly due to their shorter lifespan and more erratic track, compared to those in the Atlantic and the Pacific. SA is also bringing several state of the art instruments in recent field campaigns to peer under the clouds and study the inner workings of the tropical storms. With the Genesis and Rapid Intensification Processes (GRIP) experiment, a NASA Earth science field experiment in 2010 that includes the Global Hawk Unmanned Airborne System (UAS) configured with a suite of in situ and remote sensing instruments that are observing and characterizing the lifecycle of hurricanes, we expect significant improvement in our understanding of the track and intensification processes with the assimilation of the satellite and field campaign observations of meteorological parameters in the numerical prediction models.

Putman, William M.↗

Forecasting Lightning Threat using Cloud-resolving Model Simulations

As numerical forecasts capable of resolving individual convective clouds become more common, it is of interest to see if quantitative forecasts of lightning flash rate density are possible, based on fields computed by the numerical model. Previous observational research has shown robust relationships between observed lightning flash rates and inferred updraft and large precipitation ice fields in the mixed phase regions of storms, and that these relationships might allow simulated fields to serve as proxies for lightning flash rate density. It is shown in this paper that two simple proxy fields do indeed provide reasonable and cost-effective bases for creating time-evolving maps of predicted lightning flash rate density, judging from a series of diverse simulation case study events in North Alabama for which Lightning Mapping Array data provide ground truth. One method is based on the product of upward velocity and the mixing ratio of precipitating ice hydrometeors, modeled as graupel only, in the mixed phase region of storms at the -15\dgc\ level, while the second method is based on the vertically integrated amounts of ice hydrometeors in each model grid column. Each method can be calibrated by comparing domainwide statistics of the peak values of simulated flash rate proxy fields against domainwide peak total lightning flash rate density data from observations. Tests show that the first method is able to capture much of the temporal variability of the lightning threat, while the second method does a better job of depicting the areal coverage of the threat. A blended solution is designed to retain most of the temporal sensitivity of the first method, while adding the improved spatial coverage of the second. Weather Research and Forecast Model simulations of selected North Alabama cases show that this model can distinguish the general character and intensity of most convective events, and that the proposed methods show promise as a means of generating quantitatively realistic fields of lightning threat. However, because models tend to have more difficulty in correctly predicting the instantaneous placement of storms, forecasts of the detailed location of the lightning threat based on single simulations can be in error. Although these model shortcomings presently limit the precision of lightning threat forecasts from individual runs of current generation models, the techniques proposed herein should continue to be applicable as newer and more accurate physically-based model versions, physical parameterizations, initialization techniques and ensembles of cloud-allowing forecasts become available.

McCaul, E. W., Jr.↗

Comparison of vertical velocities analyzed by a numerical model and measured by a VHF wind profiler

The use of wind profilers for measuring vertical velocities in the troposphere and lower stratosphere is potentially of great interest for verification of forecasts, diagnosis of mesoscale circulations, and studies of wave motions. The studies of profiler vertical velocities to date have shown that the observed patterns of ascent and subsidence are reasonable when compared to the synoptic conditions. However, difficulties arise when a direct verification of the profiler vertical winds is sought. Since no other technique can measure the vertical velocities over the same height range and with the same claimed accuracy as the profilers, direct comparisons are impossible. The only alternative is to compare the measurements to analyzed vertical velocity fields. Here, researchers compare vertical measurements made with the SOUSY VHF radar over a period of 11 days at the beginning of November 1981 to the analyzed vertical velocities produced by the European Center for Medium-range Weather Forecasting (ECMWF) model for grid points near the radar site.

Larsen, M. F.↗

Extracting Independent Local Oscillatory Geophysical Signals by Geodetic Tropospheric Delay

Zenith Tropospheric Delay (ZTD) due to water vapor derived from space geodetic techniques and numerical weather prediction simulated-reanalysis data exhibits non-linear and non-stationary properties akin to those in the crucial geophysical signals of interest to the research community. These time series, once decomposed into additive (and stochastic) components, have information about the long term global change (the trend) and other interpretable (quasi-) periodic components such as seasonal cycles and noise. Such stochastic component(s) could be a function that exhibits at most one extremum within a data span or a monotonic function within a certain temporal span. In this contribution, we examine the use of the combined Ensemble Empirical Mode Decomposition (EEMD) and Independent Component Analysis (ICA): the EEMD-ICA algorithm to extract the independent local oscillatory stochastic components in the tropospheric delay derived from the European Centre for Medium-Range Weather Forecasts (ECMWF) over six geodetic sites (HartRAO, Hobart26, Wettzell, Gilcreek, Westford, and Tsukub32). The proposed methodology allows independent geophysical processes to be extracted and assessed. Analysis of the quality index of the Independent Components (ICs) derived for each cluster of local oscillatory components (also called the Intrinsic Mode Functions (IMFs)) for all the geodetic stations considered in the study demonstrate that they are strongly site dependent. Such strong dependency seems to suggest that the localized geophysical signals embedded in the ZTD over the geodetic sites are not correlated. Further, from the viewpoint of non-linear dynamical systems, four geophysical signals the Quasi-Biennial Oscillation (QBO) index derived from the NCEP/NCAR reanalysis, the Southern Oscillation Index (SOI) anomaly from NCEP, the SIDC monthly Sun Spot Number (SSN), and the Length of Day (LoD) are linked to the extracted signal components from ZTD. Results from the synchronization analysis show that ZTD and the geophysical signals exhibit (albeit subtle) site dependent phase synchronization index.

Botai, O. J.↗

Estimates of Future Numerical Weather Prediction Impacts from Hyperspectral Sounders

The United States’ satellite programs are currently in the process of evaluating the future of satellite observations of the Earth’s atmosphere, both as an individual nation and within the context of international partnerships. In an effort to better understand the impacts of various alternatives, the Global Modeling and Assimilation Office (GMAO) observing system simulation experiment (OSSE) framework has been utilized to evaluate several configurations of the international hyperspectral infrared sounder constellation from the perspective of global numerical weather prediction (NWP). This was done with an emphasis on the proposed NOAA/NASA Geostationary eXtended Observations (GeoXO) Sounder (GXS), planned to launch in the mid-2030s, and similar planned missions from international partners. GXS, in addition to contributions from EUMETSAT and JMA, will form a global ring of geostationary sounders consistent with the WMO’s 2040 vision. In addition to a novel geostationary IR sounder program, considerations extend to the future of the Low Earth Orbit (LEO) sounder program with the upcoming demise of several existing instruments and plans for future missions ongoing. The GMAO OSSE framework has examined the potential roles of GEO and LEO sounders in weather prediction improvement. Overall, the inclusion of both GEO sounders in a global ring and LEO sounders produces the most beneficial observation impact and the most accurate global weather forecasts as evaluated using several metrics, including hurricanes and the FSOI.

Erica Mcgrath-Spangler↗

Assimilation of GOES Land Surface Data: Benefits to Numerical Weather Prediction

A technique has been developed for assimilating GOES-derived skin temperature tendencies and insolation into the surface energy budget equation of a mesoscale model so that the simulated rate of temperature change closely agrees with the satellite observations. A critical assumption of the technique is that the availability of moisture (either from the soil or vegetation) is the least known term in the model's surface energy budget. Therefore, the simulated latent heat flux, which is a function of surface moisture availability, is adjusted based upon differences between the modeled and satellite observed skin temperature tendencies. An advantage of this technique is that satellite temperature tendencies are assimilated in an energetically consistent manner that avoids energy imbalances and surface stability problems that arise from direct assimilation of surface shelter temperatures. The fact that the rate of change of the satellite skin temperature is used rather than the absolute temperature means that sensor calibration is not as critical. The technique has been employed on a semi-operational basis at the GHCC within the PSU/CAR MM5 since 1 November 1998. A one-way nested grid configuration was employed with a 75 kin CONUS domain and a 25 km grid over the southeastern United States. Initial conditions were obtained from the 12 UTC Early Eta Data Assimilation System analyses and lateral boundary conditions from the Early Eta forecast available at 3 hour intervals. The satellite-derived land surface temperature tendencies and insolation were assimilated between two and five hours (1400 and 1650 UTC) of the forecast. We performed the assimilation on the Southeastern domain only. In addition, a control run without assimilation was performed to provide insight into the performance of the assimilation technique.

Lapenta, William M.↗

Impact of Satellite Atmospheric Motion Vectors In the GMAO GEOS-5 Global Data Assimilation System

The WMO and THORPEX co-sponsored fifth Workshop on the Impact of Various Observing Systems on Numerical Weather Prediction will be organized by the Expert Team on the Evolution of the Global Observing System in Sedona, Arizona, United States, from 22 to 25 May 2012. Participants are expected to come from all the major NWP centres which are active in the area of impact studies. The workshop will be conducted in English. As for the first four workshops it is planned to produce a workshop report to be published as a WMO Technical Report that will include the papers submitted by the participants. The previous four workshops in this series took place in Geneva {April 1997), Toulouse (March 2000), Alpbach (March 2004) and Geneva (May 2008). Results from Observing System Experiments (OSEs), both with global and regional aspects were presented and conclusions were drawn concerning the contributions of the various components of the observing system to the large scale forecast skill at short and medium range (Workshop Proceedings were published as WMO World Weather Watch Technical Reports TD No. 868, 1034, 1228 and 1450). Since then, some significant changes and developments have affected the global observing system and more efforts have been devoted to meso-scale observing and assimilation systems. There has also been a trend toward using techniques other than OSEs to document data impact, such as adjoint-based sensitivity to observations or ensemble-based sensitivity. Field experiments have been carried out, in particular through the THORPEX project, and the use of targeted data has been assessed.

Gelaro, Ronald↗

The Integrated Air Transportation System Evaluation Tool

Throughout U.S. history, our nation has generally enjoyed exceptional economic growth, driven in part by transportation advancements. Looking forward 25 years, when the national highway and skyway systems are saturated, the nation faces new challenges in creating transportation-driven economic growth and wealth. To meet the national requirement for an improved air traffic management system, NASA developed the goal of tripling throughput over the next 20 years, in all weather conditions while maintaining safety. Analysis of the throughput goal has primarily focused on major airline operations, primarily through the hub and spoke system.However, many suggested concepts to increase throughput may operate outside the hub and spoke system. Examples of such concepts include the Small Aircraft Transportation System, civil tiltrotor, and improved rotorcraft. Proper assessment of the potential contribution of these technologies to the domestic air transportation system requires a modeling capability that includes the country's numerous smaller airports, acting as a fundamental component of the National Air space System, and the demand for such concepts and technologies. Under this task for NASA, the Logistics Management Institute developed higher fidelity demand models that capture the interdependence of short-haul air travel with other transportation modes and explicitly consider the costs of commercial air and other transport modes. To accomplish this work, we generated forecasts of the distribution of general aviation based aircraft and GA itinerant operations at each of nearly 3.000 airport based on changes in economic conditions and demographic trends. We also built modules that estimate the demand for travel by different modes, particularly auto, commercial air, and GA. We examined GA demand from two perspectives: top-down and bottom-up, described in detail.

Wingrove, Earl R., III↗

Three CA-Related Covariance Issues and Their Solutions

This presentation addresses three issues that arise in the use of DoD-produced satellite state estimate covariances in the conjunction assessment process: the realism of the provided covariances, how to address correlated error between two satellites' covariance matrices, and how to proceed when a furnished covariance is non-positive-definite. To address the first, DoD has implemented a set of two "consider parameters" with which to alter/expand the covariance to account for atmospheric density forecast error and satellite frontal area uncertainty, the two largest sources of unmodeled position prediction error for LEO orbits; these values are governed by a satellite's orbital parameters and ballistic coefficient histories, as well as the current and predicted space weather situation. This approach substantially improves the realism of the covariance by accounting for expected prediction errors that are not part of the fit process that generates the covariance. The second issue of covariance correlation is a complicated one, but the main shared error source—global atmospheric density error that is common to both satellites can be characterized and, through sensitivity vectors, quantified at the conjunction's time of closest approach and removed from the joint covariance, which is used in the CA probability of collision (Pc) calculation. Finally, while according to the orbit determination theory a non-positive-definite (NPD) covariance is not possible, numerical truncation and covariance interpolation can conspire to produce NPD results, which render the covariance unusable for certain CA risk assessment calculations, such as Monte Carlo Pc determination. Three similar techniques are profiled and the simplest of them recommended as a reasonable remediation technique when NPD covariances are encountered by CA practitioners.

Dynamic Consider Parameter↗

Effects of data selection on the assimilation of AIRS data

The Atmospheric InfraRed Sounder (AIRS), flying aboard NASA's Earth Observing System (EOS) Aqua satellite with the Advanced Microwave Sounding Unit-A (AMSU-A), has been providing data for use in numerical weather prediction (NWP) and data assimilation systems (DAS) for over three years. The full AIRS data set is currently not transmitted in near-real-time (NRT) to the NWP centers. Instead, data sets with reduced spatial and spectral information are produced and made available in NRT. In this paper, we evaluate the use of different channel selections and error specifications. We achieved significant positive impact from the Aqua AIRS/AMSU-A combination in both hemispheres during our experimental time period of January 2003. The best results were obtained using a set of 156 channels that did not include any in the 6.7micron water vapor band. The latter have a large influence on both temperature and humidity analyses. If observation and background errors are not properly specified, the partitioning of temperature and humidity information from these channels will not be correct, and this can lead to a degradation in forecast skill. We found that changing the specified channel errors had a significant effect on the amount of data that entered into the analysis as a result of quality control thresholds that are related to the errors. However, changing the channel errors within a relatively small window did not significantly impact forecast skill with the 155 channel set. We also examined the effects of different types of spatial data reduction on assimilated data sets and NWP forecast skill. Whether we picked the center or the warmest AIRS pixel in a 3x3 array affected the amount of data ingested by the analysis but had a negligible impact on the forecast skill.

Joiner, Joanna↗

A Comparison of Wind Speed Data from Mechanical and Ultrasonic Anemometers

This study compared the performance of mechanical and ultrasonic anemometers at the Eastern Range (ER; Kennedy Space Center and Cape Canaveral Air Force Station on Florida's Atlantic coast) and the Western Range (WR; Vandenberg Air Force Base on California's Pacific coast). Launch Weather Officers, forecasters, and Range Safety analysts need to understand the performance of wind sensors at the ER and WR for weather warnings, watches, advisories, special ground processing operations, launch pad exposure forecasts, user Launch Commit Criteria (LCC) forecasts and evaluations, and toxic dispersion support. The current ER and WR weather tower wind instruments are being changed from the current propeller-and-vane (ER) and cup-and-vane (WR) sensors to ultrasonic sensors through the Range Standardization and Automation (RSA) program. The differences between mechanical and ultrasonic techniques have been found to cause differences in the statistics of peak wind speed in previous studies. The 45th Weather Squadron (45 WS) and the 30th Weather Squadron (30 WS) requested the Applied Meteorology Unit (AMU) to compare data between RSA and current sensors to determine if there are significant differences. Approximately 3 weeks of Legacy and RSA wind data from each range were used in the study, archived during May and June 2005. The ER data spanned the full diurnal cycle, while the WR data was confined to 1000-1600 local time. The sample of 1-minute data from numerous levels on 5 different towers on each range totaled more than 500,000 minutes of data (482,979 minutes of data after quality control). The 10 towers were instrumented at several levels, ranging from 12 ft to 492 ft above ground level. The RSA sensors were collocated at the same vertical levels as the present sensors and typically within 15 ft horizontally of each another. Data from a total of 53 RSA ultrasonic sensors, collocated with present sensors were compared. The 1-minute average wind speed/direction and the 1-second peak wind speed/direction were compared.

Short, D.↗

Use of MODIS Cloud Top Pressure to Improve Assimilation Yields of AIRS Radiances in GSI

Radiances from hyperspectral sounders such as the Atmospheric Infrared Sounder (AIRS) are routinely assimilated both globally and regionally in operational numerical weather prediction (NWP) systems using the Gridpoint Statistical Interpolation (GSI) data assimilation system. However, only thinned, cloud-free radiances from a 281-channel subset are used, so the overall percentage of these observations that are assimilated is somewhere on the order of 5%. Cloud checks are performed within GSI to determine which channels peak above cloud top; inaccuracies may lead to less assimilated radiances or introduction of biases from cloud-contaminated radiances.Relatively large footprint from AIRS may not optimally represent small-scale cloud features that might be better resolved by higher-resolution imagers like the Moderate Resolution Imaging Spectroradiometer (MODIS). Objective of this project is to "swap" the MODIS-derived cloud top pressure (CTP) for that designated by the AIRS-only quality control within GSI to test the hypothesis that better representation of cloud features will result in higher assimilated radiance yields and improved forecasts.

Zavodsky, Bradley↗

Comparison of Multivariate Time Series Prediction Techniques for Emulating Noah-LSM Soil Moisture Outputs

Land surface models are crucial tools for many earth science applications including numerical weather prediction, water resource and crop monitoring, and climatological analysis. Given a set of atmospheric forcings, seasonal data, and static parameters, models like Noah-LSM solve for land surface quantities including skin temperature, sensible heat flux, and soil moisture. While these calculations are theoretically robust, they are often computationally expensive. Since artificial neural networks (ANNs) are universal function approximators, they can learn to emulate the output of a deterministic numerical model given a time series of input forcings, with the learned ANN having substantially shorter execution time. The ANN could efficiently parameterize other models, generate ensembles, and provide first-guess inputs for retrievals. As such, with the goal of developing a model that efficiently mimics the output of Noah-LSM given NLDAS2 forcings on a region covering much of the central US, we examine and compare several neural network architectures for the multi-horizon multivariate time series forecasting problem. Recent literature includes a diverse set of approaches including autoregressive architectures like LSTM and GRU, parametric and non-parametric statistical predictors (ForecastNet and MQRNN), self-attention (LSTM-attention-LSTM), and temporal convovlution (DeepTCN). We implement several of these models for the Noah-LSM prediction task, highlighting the features and challenges for each and providing practical insight on the training process.

Mitchell Dodson↗

Developing Lightning Prediction Tools for the CCAFS Dual-Polarimetric Radar

NASA Marshall Space Flight Center and the University of Alabama Huntsville are collaborating with the 45th Weather Squadron (45WS) to develop improved lightning prediction capabilities for the new C-band dual-polarimetric weather radar being acquired for use by 45WS and launch weather forecasters at Cape Canaveral Air Force Station (CCAFS). In particular, these algorithms will focus on lightning onset, cessation and combined lightning-radar applications for convective winds assessment. Research using radar reflectivity (Z) data for prediction of lightning onset has been extensively discussed in the literature and subsequently applied by launch weather forecasters as it pertains to lightning nowcasting. Currently the forecasters apply a relatively straight forward but effective temperature-Z threshold algorithm for assessing the likelihood of lightning onset in a given storm. In addition, a layered VIL above the freezing level product is used as automated guidance for the onset of lightning. Only limited research and field work has been conducted on lightning cessation using Z and vertically-integrated Z for determining cessation. Though not used operationally vertically-integrated Z (basis for VIL) has recently shown promise as a tool for use in nowcasting lightning cessation. The work discussed herein leverages and expands upon these and similar reflectivity-threshold approaches via the application/addition of over two decades of polarimetric radar research focused on distinct multi-parameter radar signatures of ice/mixed-phase initiation and ice-crystal orientation in highly electrified convective clouds. Specifically, our approach is based on numerous previous studies that have observed repeatable patterns in the behavior of the vertical hydrometeor column as it relates to the temporal evolution of differential reflectivity and depolarization (manifested in either LDR or p(sub hv)), development of in-situ mixed and ice phase microphysics, electric fields, and ensuing lightning in the sub-tropical/tropical convection typical of the southeastern U.S., Maritime Continent, and southwestern Amazon. The polarimetric signatures detected in this setting provide a basis for automated 3-D detection of hydrometeor types in fuzzy logic hydrometeor identification algorithms (HID). Our working hypothesis is that improvement in lightning onset warning lead time and specificity for a given storm, relative to application of a Z-threshold algorithm, should arise as a consequence of the ability of dual-polarimetric radar to unambiguously detect and identify (through HID algorithms) the updraft elevation of rain-water cores above the freezing level and subsequent onset of drop freezing, riming, and robust mixed phase processes leading to significant charge separation and lightning. This type of algorithm, though dependent on the quality of the polarimetric data should be less susceptible to variable Z-calibration that can impact a given Z-threshold approach. To facilitate development of the algorithm while the 45WS dual-pol radar is in its current test stages and to evaluate the impact of polarimetric data quality (e.g., modified scan parameters and sampling) on the ensuing algorithms, we are using the ARMOR C-band dual-pol radar in Huntsville combined with N. Alabama LMA data and ARMOR HID algorithms [NCAR algorithm modified for application at C-band] in a testbed fashion. For lightning cessation we are revisiting the application of differential propagation phase variables for the monitoring of ice crystal alignment driven by in-cloud electric fields combined with metrics of ice water path (i.e., vertically integrated reflectivity). Importantly it should be noted that this approach is still very much a research topic and as such, we will explore operational applications that involve radar frequencies other than C-Band by using the UAH MAX X-band dual-pol radar in slow staring modes.

Petersen, W. A.↗

The Utility of the Real-Time NASA Land Information System Data for Drought Monitoring Applications

Measurements of soil moisture are a crucial component for the proper monitoring of drought conditions. The large spatial variability of soil moisture complicates the problem. Unfortunately, in situ soil moisture observing networks typically consist of sparse point observations, and conventional numerical model analyses of soil moisture used to diagnose drought are of coarse spatial resolution. Decision support systems such as the U.S. Drought Monitor contain drought impact resolution on sub-county scales, which may not be supported by the existing soil moisture networks or analyses. The NASA Land Information System, which is run with 3 km grid spacing over the eastern United States, has demonstrated utility for monitoring soil moisture. Some of the more useful output fields from the Land Information System are volumetric soil moisture in the 0-10 cm and 40-100 cm layers, column-integrated relative soil moisture, and the real-time green vegetation fraction derived from MODIS (Moderate Resolution Imaging Spectroradiometer) swath data that are run within the Land Information System in place of the monthly climatological vegetation fraction. While these and other variables have primarily been used in local weather models and other operational forecasting applications at National Weather Service offices, the use of the Land Information System for drought monitoring has demonstrated utility for feedback to the Drought Monitor. Output from the Land Information System is currently being used at NWS Huntsville to assess soil moisture, and to provide input to the Drought Monitor. Since feedback to the Drought Monitor takes place on a weekly basis, weekly difference plots of column-integrated relative soil moisture are being produced by the NASA Short-term Prediction Research and Transition Center and analyzed to facilitate the process. In addition to the Drought Monitor, these data are used to assess drought conditions for monthly feedback to the Alabama Drought Monitoring and Impact Group and the Tennessee Drought Task Force, which are comprised of federal, state, and local agencies and other water resources professionals.

White, Kristopher D.↗

Seven Years of Observations of Mid-Tropospheric CO2 from the Atmospheric Infrared Sounder

The Atmospheric Infrared Sounder (AIRS) on the EOS Aqua Spacecraft was launched on May 4, 2002. AIRS acquires hyperspectral infrared radiances in the 3.7-15.4 um spectral region with spectral resolution of better than 1200. The AIRS was designed to measure temperature and water vapor profiles and cloud properties for improvement in weather forecast and improved parameterization of climate processes. Currently the AIRS Level 1B Radiance Products are assimilated by NWP centers and have shown considerable forecast improvement. Scientists have also demonstrated accurate retrievals of minor gases from AIRS including Carbon Monoxide, Methane, and Ozone. The excellent sensitivity and stability of the AIRS instrument has recently allowed the AIRS team to successfully retrieve Carbon Dioxide (CO2) concentrations in the mid-troposphere (8-10 km) with a horizontal resolution of 100 km and accuracy of 1-2 ppm. The AIRS retrieves over 15,000 measurements per day and can achieve full global coverage in 30 days. The AIRS CO2 accuracy has been validated against a variety of aircraft measurements in the mid-troposphere and upward looking interferometers. Findings from the AIRS data include higher than expected variability in the mid-troposphere, the presence of a belt of CO2 in the southern hemisphere, and numerous observations of atmospheric circulation including the effects of El Nino/La Nina on the CO2 concentrations in the mid-troposphere. The full mid-tropospheric AIRS CO2 data set is now available at the NASA GES/DISC for almost eight years since AIRS has been operational.

carbon dioxide↗

Space Weather: What is it, and Why Should a Meteorologist Care?

"Space weather" is a term coined almost 15 years ago to describe environmental conditions ABOVE Earth's atmosphere that affect satellites and astronauts. As society has become more dependent on technology, we nave found that space weather conditions increasingly affect numerous commercial and infrastructure sectors: airline operations, the precision positioning industry, and the electric power grid, to name a few. Similar to meteorology where "weather" often refers to severe conditions, "space weather" includes geomagnetic storms, radiation storms, and radio blackouts. But almost all space weather conditions begin at the Sun--our middle-age, magnetically-variable star. At NASA, the science behind space weather takes place in the Heliophysics Division. The Space Weather Prediction Center in Boulder, Colorado, is manned jointly by NCAA and US Air Force personnel, and it provides space weather alerts and warnings for disturbances that can affect people and equipment working in space and on Earth. Organizationally, it resides in NOAA's National Weather Service as one of the National Centers for Environmental Prediction. In this seminar we hope to give the audience a brief introduction to the causes of space weather, discuss some of the effects, and describe the state of the art in forecasting. Our goal is to highlight that meteorologists are increasingly becoming the "first responders" to questions about space weather causes and effects.

SaintCyr, Chris↗

Evaluation of GEOS Precipitation Flagging for SMAP Soil Moisture Retrieval Accuracy

The precipitation flag in the Soil Moisture Active Passive (SMAP) Level 2 passive soil moisture (L2SMP) retrieval product indicates the presence or absence of heavy precipitation at the time of the SMAP overpass. The flag is based on precipitation estimates from the Goddard Earth Observing System (GEOS) Forward Processing numerical weather prediction system. An error in flagging during an active or recent precipitation event can produce either 1) an overestimation of soil moisture due to short-term surface wetting of vegetation and/or surface ponding (if soil moisture retrieval was attempted in the presence of rain) or 2) an unnecessary nonretrieval of soil moisture and loss of data (if retrieval is flagged due to an erroneous indication of rain). Satellite precipitation estimates from the Integrated Multisatellite Retrievals for GPM (IMERG), version 06, Early Run (latency of ~4 h) precipitationCal product are used here to evaluate the GEOS-based precipitation flag in the L2SMP product for both the 1800 local time (LT) ascending and 0600 LT descending SMAP overpasses over the first five years of the mission (2015–20). Consisting of blended precipitation measurements from the Global Precipitation Mission (GPM) satellite constellation, IMERG is treated as the “truth” when comparing to the GEOS model forecasts of precipitation used by SMAP. Key results include (i) IMERG measurements generally show higher spatial variability than the GEOS forecast precipitation, (ii) the IMERG product has a higher frequency of light precipitation amounts, and (iii) the effect of incorporating IMERG rainfall measurements in lieu of GEOS precipitation forecasts are minimal on the L2SMP retrieval accuracy (determined vs in situ soil moisture measurements at core validation sites). Our results indicate that L2SMP retrievals continue to meet the mission’s accuracy requirement [standard deviation of the unbiased RMSE (ubRMSE) less than 0.04 cu. m/cu. m].

IMERG-precipitationCal↗