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NASA NTRSDate not supplied

Observation of Deep Convective Cloud-Top Height and Vertical Temperature Structure of Hurricane Using Hyperspectral Infrared Sounder and its Single-Field-View Retrieval Products

Hurricanes, severe tropical cyclones (TC), or typhoons are significant natural disasters that often result in substantial loss of life and property damage. Numerous studies have indicated that changes in TC intensity are closely linked to deep convective clouds (DCC), with stronger TCs typically exhibiting higher cloud top heights (CTH) compared to weaker TCs. The CTH can help determine if a tropical depression is at the onset of rapid intensification based on case studies. Therefore, accurate determination of TC CTH will be greatly helpful for monitoring TC development and studying TC dynamics. One traditional and most common method to derive CHT from satellite observations is using the thermal brightness temperature in atmospheric channels to match the sounding temperature profile. However, it was found that thermally derived CTH has a lower bias of approximately 1 km, and this bias tends to worsen for the tallest clouds. A new method using the hyperspectral infrared sounder will be presented. From the measurements of Cross-track Infrared Sounder (CrIS) on S-NPP and J-1, along with radiative transfer simulations, we identified the inverted-V spectral feature in the ozone (O3) band (near 9.6 μm) corresponding to high clouds. The depth of the inverted-V can be used to estimate the CTH. Since the depth is computed using the peak absorption O3 channel and the nearby most transparent O3 channel in this O3 band, the uncertainties associated with cloud emissivity and scattering by cloud particles in the traditional method can be ignored. From several hurricane case studies, we found that the CHT derived using this method can accurately capture the structure of the cloud tops in the eyewall, spiral rainbands, and surrounding regions. For example, Hurricane Dorian on September 2, 2019, showed a nicely outward-sloping and circular shape eye cloud in the early morning, but the circular shape of the eyewall cloud became distorted in the afternoon. For various hurricanes we examined, the distribution of CHT for the eyewall clouds differed significantly. To better study the thermodynamic structure of hurricane clouds, this research will analyze the vertical temperature profiles from a new single Field of View (SFOV) Sounder Atmospheric Products (SiFSAP), derived using CrIS and the Advanced Technology Microwave Sounder (ATMS) onboard SNPP and JPSS-1. SiFSAP has a spatial resolution of 15 km at nadir, which surpasses most global weather and climate models and other current operational sounding products. The combined use of ATMS and CrIS allows for retrievals near hurricane eyewalls and spiral rainbands. Wind fields from NASA’s Modern-Era Retrospective Analysis for Research and Applications Version-2 (MERRA-2) and ERA5 will be used to characterize transport, and comparisons between the model temperature and water vapor profiles with the corresponding SiFSAP products will also be provided.

SiFSAP↗

NASA NTRSDate not supplied

The Land Surface in Current and Planned MERRA Reanalysis Products

Current global atmospheric reanalysis products such as the European Centre for Medium-Range Weather Forecasts Reanalysis version 5 (ERA5), the NASA Modern-Era Retrospective analysis for Research and Applications version 2 (MERRA-2), and the Japanese Reanalysis for Three Quarters of a Century (JRA-3Q) provide estimates of land surface states and fluxes, including soil moisture, soil temperature, snow mass, latent and sensible heat fluxes, and runoff, that are widely used in research and applications. These land surface estimates are based on land surface process models and, depending on the reanalysis product, on precipitation observations or the assimilation of land surface observations of soil moisture, soil temperature, snow conditions, and screen-level air temperature and humidity from satellite observations and in situ measurements. In this presentation, we review the land surface modeling and data assimilation components of the suite of current and planned MERRA reanalysis products. In addition to MERRA-2, we will discuss the latest NASA reanalysis, MERRA for the 21st century (M21C), which is currently under production, as well as the development and planning of the next version of the MERRA reanalysis, tentatively labeled MERRA-3. In MERRA-2, observations-based precipitation data products are used to correct the precipitation falling on the land surface. Outside of the high-latitudes and Africa, the daily, 0.5-degree, gauge-based Climate Prediction Center (CPC) Unified (CPCU) product is used. In Africa, the pentad, 2.5-degree, satellite- and gauge-based CPC Merged Analysis of Precipitation (CMAP) product is used. Poleward of 62.5 degrees latitude, the land surface sees the precipitation generated by the atmospheric model in the cycling data assimilation system. This configuration provides improved soil moisture estimates compared to those of the original (version 1) MERRA estimates, which did not benefit from the use of precipitation observations. Moreover, the use of precipitation observations facilitates a seamless spin-up of the land surface initial conditions across the MERRA-2 production streams. The use of a gauge-only precipitation product in MERRA-2 across much of the globe, however, adversely impacts the quality of the MERRA-2 land surface estimates in regions with poor gauge coverage, including most of South America and Australia. Therefore, the forthcoming M21C reanalysis uses satellite- and gauge-based precipitation from the Integrated Multi-satellitE Retrievals for the Global Precipitation Measurement Mission (IMERG). This change results in significant improvements in the quality of the M21C soil moisture estimates in the Southern Hemisphere compared to those from MERRA-2. Planning for MERRA-3 focuses on the assimilation of soil moisture observations from the Soil Moisture Active Passive (SMAP) mission and the Advanced Scatterometer (ASCAT), along with snow cover area fraction observations from the Moderate Resolution Imaging Spectroradiometer (MODIS) to further improve the quality of the land surface estimates from the reanalysis. As a first step towards the assimilation of land surface observations in MERRA-3, the offline (land-only) M21C-Land reanalysis is currently under development as a supplemental M21C product that includes the assimilation of SMAP, ASCAT, and MODIS observations. Preliminary results from M21C and M21C-Land will be discussed in the context of MERRA-2 and plans for MERRA-3.

Rolf Reichle↗

NASA NTRSDate not supplied

Evaluation of Regional Water and Energy Balance in Contemporary Reanalyses

Regional to continental water and energy balance in reanalyses provide crucial information on the climate and climate variations in that region and can contrast other regions. Reanalyses are a valuable tool in piecing together the complete balance owing to the incorporation of the budgets in the background model and the assimilation of observation. On the other hand, the background model has its own biases and observational assimilation can lead to non-negligible tendencies within the budgets, and these can vary over space and time. Here, we will compare the balance within several reanalyses and how they have evolved over recent decades. Several observational data products will provide reference points in the comparison. In addition, a recent project has integrated observations of the water and energy budgets in an optimization that aims to reduce the imbalance of regional budgets in using observational terms from disparate sources. In evaluating the regional balances, we will incorporate, when available, the water and energy convergence terms as well as their analysis increments (which may be diagnosed as residuals). The reanalyses considered here include: Japanese Reanalyses for Three Quarters Century (JRA3Q), ECMWF Reanalysis version 5 (ERA5), Modern Era Retrospective-analysis for Research and Applications version 2 (MERRA-2) and the NCEP Reanalysis II (NCEPR2). NCEPR2 is representative of the late 90s technology, while the others represent the contemporary climate reanalyses presently available. We will discuss the regional balances over key river basins (e.g. Mississippi and Amazon), and a range of continents including those well observed (North America and Europe) and those with fewer consistent observations (e.g. Africa). These contrasting regions show the degree of advancement in reanalyses and expose areas in need of improvement. The results also demonstrate the usefulness of producing complete atmospheric water and energy budgets as part of the diagnostic output.

Michael Bosilovich↗

NASA NTRSDate not supplied

Evaluating the Global Water and Energy Cycles in Reanalyses Using Ensemble Spread

Reanalyses provide continuous observation based global data over weather and climate time scales through observational assimilation. Ensemble forecasts are a component of modern data assimilation systems, providing information to the analysis process. Storing this spread over the duration of a climate reanalysis will provide insight to the variations of the model that underlies the reanalysis data. Global water and energy cycles (WECs) are a critical aspect of both weather and climate, yet there are some large gaps in the observation of key components as well as their representation in models and reanalyses. NASA’s Water and Energy cycle Studies (NEWS) program is developing a corrected and balanced budget data set that is closed at monthly and regional scales during the 21st century, so far. In this paper, we will evaluate reanalysis WEC components against the initial NEWS collection of observation, but integrate the analysis spread from the reanalysis data assimilation as a new perspective on the evaluation. The initial evaluation will cover a few more recent years using ERA5 10 member spread. As the GMAO’s production of the Modern-Era Retrospective analysis for Research and Applications 21st Century (MERRA-21C) progresses, the effort will include the MERRA-21C 32 member spread. Ultimately, we will explore the potential of the ensemble spread as a measure of uncertainty in the reanalysis.

Michael Bosilovich↗

NASA NTRS2026

Remote Sensing-Driven Hydrodynamic Modeling in Data-Scarce Regions: Integrating ICESat-2, Sentinel-2, SWOT and Re-analysis Models for Coastal Monitoring

Hydrodynamic models in coastal and estuarine systems are typically constrained by sparse bathymetry, boundary, and validation data, especially in regions where field campaigns are costly or impractical. Here we develop and test a fully satellite-driven framework for hydrodynamic modeling in South Africa’s Langebaan Lagoon without using any local in situ measurements. Bathymetry is derived by training multispectral Sentinel-2 reflectance against ICESat-2 ATL24 photon-derived depths using an XGBoost model optimized with Bayesian search. The final satellite-derived bathymetry reproduces independent ATL24 points with RMSE = 0.45 m and R 2 = 0.97. This bathymetry was used in a depth-averaged Delft3D Flexible Mesh model driven at the open boundary by TPXO tidal harmonics and by ERA5 winds. We validate modeled water surface elevation against 16 SWOT low-rate (250 m, unsmoothed) passes in 2023. SWOT–model comparisons yield an overall RMSE of 0.11 m and R 2 = 0.61, with typical point differences <0.10 m (∼7% of the 1.5 m tidal range), and showed consistent spatial gradients in water level from the offshore boundary, through Saldanha Bay, and into the lagoon. At the offshore boundary, TPXO and SWOT sea surface heights agree closely (R 2 = 0.86). A simple phase adjustment of ∼26,min between TPXO and SWOT lowers the RMSE from 0.18,m to 0.11,m, showing that phase offset accounts for some of the discrepancy, with additional errors likely linked to non-tidal signals. Our results demonstrate that combining passive optical, photon-counting LiDAR, radar interferometry, and global tidal/atmospheric models enables robust, transferrable hydrodynamic modeling in data-scarce coastal systems, offering a cost-effective pathway for monitoring.

ICESat-2↗

NASA NTRS2022

Implementation of a Discrete Dipole Approximation Scattering Database into Community Radiative Transfer Model

The Community Radiative Transfer Model (CRTM) is a fast model that requires bulk optical properties of hydrometeors in the form of lookup tables to simulate all-sky satellite radiances. Current cloud scattering lookup tables of CRTM were generated using the Mie-Lorenz theory thus assuming spherical shapes for all frozen habits, while actual clouds contain frozen hydrometeors with different shapes. The Discrete Dipole Approximation (DDA) technique is an effective technique for simulating the optical properties of non-spherical hydrometeors in the microwave region. This paper discusses the implementation and validation of a comprehensive DDA cloud scattering database into CRTM for the microwave frequencies. The original DDA database assumes total random orientation in the calculation of single scattering properties. The mass scattering parameters required by CRTM were then computed from single scattering properties and water content dependent particle size distributions. The new lookup tables eliminate the requirement for providing the effective radius as input to CRTM by using the cloud water content for the mass dimension. A collocated dataset of short-term forecasts from Integrated Forecast System of the European Centre for Medium-Range Weather Forecasts and satellite microwave data was used for the evaluation of results. The results overall showed that the DDA lookup tables, in comparison with the Mie tables, greatly reduce the differences among simulated and observed values. The Mie lookup tables especially introduce excessive scattering for the channels operating below 90 GHz and low scattering for the channels above 90 GHz.

Discrete dipole↗

NASA NTRSDate not supplied

Simulations of X-59 Sonic Thumps and Traditional Sonic Booms Propagated Around the World for Three Atmospheric Models

Propagation simulations of sonic booms from supersonic aircraft through atmospheric data over time at fixed locations provides the opportunity to assess noise exposure statistics for different climate regions. Knowledge of climate-based differences in sonic boom noise exposure statistics is important to ensure that future civil supersonic aircraft noise certification standards are globally applicable and effective. In this presentation, simulated sonic booms from the NASA X-59 Quesst quiet supersonic aircraft and conventional supersonic aircraft were propagated through atmospheric data at 100 locations across the world using PCBoom. Noise exposure statistics are compared for propagation results from three different atmospheric databases (NOAA Global Forecast System, NOAA Climate Forecast System Version 2, and the ECMWF Reanalysis Version 5). These atmospheric models were chosen due to their global coverage, popularity, and database availability. Preliminary statistical models are fit to assess the impact of several factors including flight direction, season, ground elevation, and climate on noise exposure size and loudness. Areas with prevalence of higher noise due to their climate are identified, which could help inform future supersonic aircraft noise standards.

X-59↗