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Towards Physics Guided Optical Flow for Tracking Atmospheric Motion

Atmospheric 3D winds in the horizontal and vertical directions are critical for improving short-range and long-range forecasting. Such advancement in forecasting directly applies to research in a number of areas including convective processes, wildfire plumes and tornado prediction. Atmospheric Motion Vectors (AMVs) provide a passively sensed approach to quantifying horizontal motion and cloud heights, which are typically sourced from geostationary sensors due to the availability of high frequency observations. Recent work has shown that estimating AMVs by tracking individual pixels with dense optical flow is a promising new direction. In this work, we use a state-of-the-art convolutional neural network for optical flow (FlowNetS) in a physics-guided deep learning framework for predicting AMVs in the horizontal direction. The approach is semi-supervised and uses physically informed wind vectors from high-resolution numerical simulations (DYAMOND) for supervised learning followed by fine-tuning though warping and reconstruction of full-disk geostationary images (GOES-16). In the vertical direction, we use labels from the CALIPSO low-earth orbit satellite to predict cloud height from 16-band geostationary images with a neural network. We present results for both tasks on held-out time periods and secondary datasets.

geostationary↗

NASA NTRS2007

An Integrated High Resolution Hydrometeorological Modeling Testbed using LIS and WRF

Scientists have made great strides in modeling physical processes that represent various weather and climate phenomena. Many modeling systems that represent the major earth system components (the atmosphere, land surface, and ocean) have been developed over the years. However, developing advanced Earth system applications that integrates these independently developed modeling systems have remained a daunting task due to limitations in computer hardware and software. Recently, efforts such as the Earth System Modeling Ramework (ESMF) and Assistance for Land Modeling Activities (ALMA) have focused on developing standards, guidelines, and computational support for coupling earth system model components. In this article, the development of a coupled land-atmosphere hydrometeorological modeling system that adopts these community interoperability standards, is described. The land component is represented by the Land Information System (LIS), developed by scientists at the NASA Goddard Space Flight Center. The Weather Research and Forecasting (WRF) model, a mesoscale numerical weather prediction system, is used as the atmospheric component. LIS includes several community land surface models that can be executed at spatial scales as fine as 1km. The data management capabilities in LIS enable the direct use of high resolution satellite and observation data for modeling. Similarly, WRF includes several parameterizations and schemes for modeling radiation, microphysics, PBL and other processes. Thus the integrated LIS-WRF system facilitates several multi-model studies of land-atmosphere coupling that can be used to advance earth system studies.

Kumar, Sujay V.↗

NASA NTRS2009

Examining the Impacts of High-Resolution Land Surface Initialization on Model Predictions of Convection in the Southeastern U.S.

One of the most challenging weather forecast problems in the southeastern U.S. is daily summertime pulse convection. During the summer, atmospheric flow and forcing are generally weak in this region; thus, convection typically initiates in response to local forcing along sea/lake breezes, and other discontinuities often related to horizontal gradients in surface heating rates. Numerical simulations of pulse convection usually have low skill, even in local predictions at high resolution, due to the inherent chaotic nature of these precipitation systems. Forecast errors can arise from assumptions within physics parameterizations, model resolution limitations, as well as uncertainties in both the initial state of the atmosphere and land surface variables such as soil moisture and temperature. For this study, it is hypothesized that high-resolution, consistent representations of surface properties such as soil moisture and temperature, ground fluxes, and vegetation are necessary to better simulate the interactions between the land surface and atmosphere, and ultimately improve predictions of local circulations and summertime pulse convection. The NASA Short-term Prediction Research and Transition (SPORT) Center has been conducting studies to examine the impacts of high-resolution land surface initialization data generated by offline simulations of the NASA Land Informatiot~ System (LIS) on subsequent numerical forecasts using the Weather Research and Forecasting (WRF) model (Case et al. 2008, to appear in the Journal of Hydrometeorology). Case et al. presents improvements to simulated sea breezes and surface verification statistics over Florida by initializing WRF with land surface variables from an offline LIS spin-up run, conducted on the exact WRF domain and resolution. The current project extends the previous work over Florida, focusing on selected case studies of typical pulse convection over the southeastern U.S., with an emphasis on improving local short-term WRF simulations over the Mobile, AL and Miami, FL NWS county warning areas. Future efforts may involve examining the impacts of assimilating remotely-sensed soil moisture data, and/or introducing weekly greenness vegetation fraction composites (as opposed to monthly climatologies) into ol'fline NASA LIS runs. Based on positive impacts, the offline LIS runs could be transitioned into an operational mode, providing land surface initialization data to NWS forecast offices in real time.

Case, Jonathan L.↗

NASA NTRS2010

A Modeling and Verification Study of Summer Precipitation Systems Using NASA Surface Initialization Datasets

One of the most challenging weather forecast problems in the southeastern U.S. is daily summertime pulse-type convection. During the summer, atmospheric flow and forcing are generally weak in this region; thus, convection typically initiates in response to local forcing along sea/lake breezes, and other discontinuities often related to horizontal gradients in surface heating rates. Numerical simulations of pulse convection usually have low skill, even in local predictions at high resolution, due to the inherent chaotic nature of these precipitation systems. Forecast errors can arise from assumptions within parameterization schemes, model resolution limitations, and uncertainties in both the initial state of the atmosphere and land surface variables such as soil moisture and temperature. For this study, it is hypothesized that high-resolution, consistent representations of surface properties such as soil moisture, soil temperature, and sea surface temperature (SST) are necessary to better simulate the interactions between the surface and atmosphere, and ultimately improve predictions of summertime pulse convection. This paper describes a sensitivity experiment using the Weather Research and Forecasting (WRF) model. Interpolated land and ocean surface fields from a large-scale model are replaced with high-resolution datasets provided by unique NASA assets in an experimental simulation: the Land Information System (LIS) and Moderate Resolution Imaging Spectroradiometer (MODIS) SSTs. The LIS is run in an offline mode for several years at the same grid resolution as the WRF model to provide compatible land surface initial conditions in an equilibrium state. The MODIS SSTs provide detailed analyses of SSTs over the oceans and large lakes compared to current operational products. The WRF model runs initialized with the LIS+MODIS datasets result in a reduction in the overprediction of rainfall areas; however, the skill is almost equally as low in both experiments using traditional verification methodologies. Output from object-based verification within NCAR s Meteorological Evaluation Tools reveals that the WRF runs initialized with LIS+MODIS data consistently generated precipitation objects that better matched observed precipitation objects, especially at higher precipitation intensities. The LIS+MODIS runs produced on average a 4% increase in matched precipitation areas and a simultaneous 4% decrease in unmatched areas during three months of daily simulations.

Jonathan L. Case↗

NASA NTRS2011

Analysis of Summertime Convective Initiation in Central Alabama Using the Land Information System

During the summer months in the southeastern United States, convective initiation presents a frequent challenge to operational forecasters. Thunderstorm development has traditionally been referred to as random due to their disorganized, sporadic appearance and lack of atmospheric forcing. Horizontal variations in land surface characteristics such as soil moisture, soil type, land and vegetation cover could possibly be a focus mechanism for afternoon convection during the summer months. The NASA Land Information System (LIS) provides a stand-alone land surface modeling framework that incorporates these varying soil and vegetation properties, antecedent precipitation, and atmospheric forcing to represent the soil state at high resolution. The use of LIS as a diagnostic tool may help forecasters to identify boundaries in land surface characteristics that could correlate to favored regions of convection initiation. The NASA Shortterm Prediction Research and Transition (SPoRT) team has been collaborating with the National Weather Service Office in Birmingham, AL to help incorporate LIS products into their operational forecasting methods. This paper highlights selected convective case dates from summer 2009 when synoptic forcing was weak, and identifies any boundaries in land surface characteristics that may have contributed to convective initiation. The LIS output depicts the effects of increased sensible heat flux from urban areas on the development of convection, as well as convection along gradients in land surface characteristics and surface sensible and latent heat fluxes. These features may promote mesoscale circulations and/or feedback processes that can either enhance or inhibit convection. With this output previously unavailable to operational forecasters, LIS provides a new tool to forecasters in order to help eliminate the randomness of summertime convective initiation.

James, Robert S.↗

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 NTRS1990

Optimizing the use of remotely sensed atmospheric data through four-dimensional data assimilation

Results with the GLA interactive forecast-retrieval-assimilation system, which directly uses satellite radiance data in the assimilation cycle, are presented. Forecasts made from initial conditions derived with this system are shown to be more skillful than those whose initial conditions came from a comparable assimilation using statistically based temperature soundings, or ones using no sounding data at all. Examples are also given of additional parameters which are produced through the physical inversion of the satellite radiance data during the interactive assimilation cycle. These are potentially useful for analysis purposes.

Pfaendtner, J.↗

NASA NTRS2022

Evaluating Twenty-Year Trends in Earth’s Energy Flows from Observations and Reanalyses

Satellite, reanalysis, and ocean in situ data are analyzed to evaluate regional, hemispheric and global mean trends in Earth’s energy fluxes during the first twenty years of the 21st century. Regional trends in net top-of-atmosphere (TOA) radiation from the Clouds and the Earth’s Radiant Energy System (CERES), ECMWF Reanalysis 5 (ERA5), and a model similar to ERA5 with prescribed sea surface temperature (SST) and sea ice differ markedly, particularly over the Eastern Pacific Ocean, where CERES observes large positive trends. Hemispheric and global mean net TOA flux trends for the two reanalyses are smaller than CERES, and their climatological means are half those of CERES in the southern hemisphere (SH) and more than nine times larger in the northern hemisphere (NH). The regional trend pattern of the divergence of total atmospheric energy transport (TEDIV) over ocean determined using ERA5 analyzed fields is similar to that inferred from the difference between TOA and surface fluxes from ERA5 short-term forecasts. There is also agreement in the trend pattern over ocean for surface fluxes inferred as a residual between CERES net TOA flux and ERA5 analysis TEDIV and surface fluxes obtained directly from ERA5 forecasts. Robust trends are observed over the Gulf Stream associated with enhanced surface-to-atmosphere transfer of heat. Within the ocean, larger trends in ocean heating rate are found in the NH than the SH after 2005, but the magnitude of the trend varies greatly among datasets.

Norman G Loeb↗

NASA NTRS1988

Doppler lidar wind measurements on the EOS - LAWS

This paper discusses the efforts currently underway to prepare for the deployment of the Laser Atmospheric Wind Sounder (LAWS) instrument on an Earth Observing System (EOS) polar orbiter and on the Space Station. Attention is given to the measurement techiques, which include ground-based and airborne measurements in the atmosphere, and to the scientific and the technical issues being addressed. Global wind profiles obtained with the LAWS will effect dramatic improvement in numerical weather prediction and will be useful in determining the midtroposphere steering currents that are important in hurricane track forecasts. The global wind data will also provide information on large-scale atmospheric circulation and climate dynamics and on biogeochemical and hydrologic cycles.

Fitzjarrald, Daniel E.↗

NASA NTRS1999

Use of Data to Improve El Nino Southern Oscillation Simulations and Forecasts

Various data over the period 1980-1998 have been used to improve El Nino Southern Oscillation (ENSO) simulations and forecasts performed by coupled ocean/atmosphere models. For such a study, oceanic and atmospheric satellite data are necessary. Models assume a baroclinic ocean with a mixed layer coupled to a baroclinic atmosphere to simulate the anomalous fields. The various data have been used to revisit the parameterizations of the subsurface temperature in the mixed layer, atmospheric convection, and friction in the baroclinic ocean. This new model, named Tsub.Conv, simulates 4-year oscillations like the model with the original parameterization, but with anomalous thermocline and wind anomalies that agree a lot better with reality. The atmospheric model still presents some deficiencies in the eastern Pacific and when it is replaced by a statistical atmosphere, the coupled model (Tsub.Astat) performs even better. It is found that the off-equatorial ocean and wind curl anomalies play a crucial role for all these models and that Tsub.Astat simulates an ocean heat content recharge coming from the north prior to a warm event like the ones observed during the 1985-1992 period. The ENSO forecasts over 1980-1998 are considerably improved with Tsub.Astat. One needs to add the simulation of westerly wind bursts to be able to forecast the 1997 event one year in advance. Additional information is contained in the original.

Perigaud, Claire↗

NASA NTRS2004

Alternative Approaches to Land Initialization for Seasonal Precipitation and Temperature Forecasts

The seasonal prediction system of the NASA Global Modeling and Assimilation Office is used to generate ensembles of summer forecasts utilizing realistic soil moisture initialization. To derive the realistic land states, we drive offline the system's land model with realistic meteorological forcing over the period 1979-1993 (in cooperation with the Global Land Data Assimilation System project at GSFC) and then extract the state variables' values on the chosen forecast start dates. A parallel series of forecast ensembles is performed with a random (though climatologically consistent) set of land initial conditions; by comparing the two sets of ensembles, we can isolate the impact of land initialization on forecast skill from that of the imposed SSTs. The base initialization experiment is supplemented with several forecast ensembles that use alternative initialization techniques. One ensemble addresses the impact of minimizing climate drift in the system through the scaling of the initial conditions, and another is designed to isolate the importance of the precipitation signal from that of all other signals in the antecedent offline forcing. A third ensemble includes a more realistic initialization of the atmosphere along with the land initialization. The impact of each variation on forecast skill is quantified.

Koster, Randal↗

NASA NTRS1984

Synoptic-scale dynamics with vertical velocity, part 1.8A

Radar measurements of all three of the atmospheric velocity components by the MST technique data from all the pioneering work of Woodman and Geillen (1974). The radar horizontal velocities have been compared with other standard measurements, such as radiosonde winds, in a number of studies and are now finding widespread acceptance within the meteorological community for research and operational forecasting purposes. Perhaps the single most interesting report recently is that the mesosphere-stratosphere-troposphere (MST) profiler winds are turning out to be one of the most useful pieces of data for predicting upslope snowfall in the cold season forecasting study of the PROFS Program (Reynolds, 1983). By contrast, the vertical velocities measured by MST radars have received relatively little attention, despite the facts that direct continuous measurement of vertical velocity is unique (i.e., it cannot be done with radiosondes) and that the vertical velocity is intimately linked with the dynamics of the atmosphere. Indeed, for many forecasting applications the vertical velocity is the single most important variable, yet it is usually inferred indirectly from other dynamical variables. The stratosphere-troposphere (ST) radars now available have the potential to change this situation. Some of the results from vertical velocity measurements which have direct application in synoptic scale dynamics.

Nastrom, G. D.↗

NASA NTRS2010

Investigation of Surface Flux Feedbacks for Coupled and Uncoupled Atmosphere-Ocean Anomalies

Variability in the atmosphere and ocean are linked through coupled processes via the surface exchanges of heat, moisture, and momentum. This coupling can occur predominantly via one-way (ocean forcing atmosphere or atmosphere forcing ocean) or two-way interactions. The dominant type of interaction can vary both regionally and with season. The existence of the coupled variability can act to enhance the persistence of anomalies and therefore may be important to seasonal (and longer) forecasts. The leading components of surface exchange that regulate the damping of the atmospheric and oceanic anomalies most likely also varies regionally and seasonally. This study seeks to elucidate the roles of the various surface flux components using satellite based data sets. Using dynamical relationships expected for one-way forcing regimes, coupled and uncoupled variability is isolated and used in conjunction with composite-type analyses to reveal the nature of these coupling mechanisms and their variation in space and time. Results of this study can be useful in examining the veracity of general circulation model output by understanding how the coupling mechanisms are replicated as found in satellite based observations.

Roberts, J. Brent↗

NASA NTRS1966

Atmospheric sciences for the space age

Space-age research programs to increase knowledge about global atmospheric circulation and to obtain data on changing weather patterns

ATMOSPHERIC CIRCULATION↗

NASA NTRS1974

SEASAT economic assessment

The SEASAT program will provide scientific and economic benefits from global remote sensing of the ocean's dynamic and physical characteristics. The program as presently envisioned consists of: (1) SEASAT A; (2) SEASAT B; and (3) Operational SEASAT. This economic assessment was to identify, rationalize, quantify and validate the economic benefits evolving from SEASAT. These benefits will arise from improvements in the operating efficiency of systems that interface with the ocean. SEASAT data will be combined with data from other ocean and atmospheric sampling systems and then processed through analytical models of the interaction between oceans and atmosphere to yield accurate global measurements and global long range forecasts of ocean conditions and weather.

Hicks, K.↗

NASA NTRS1978

LACIE (Large Area Crop Inventory Experiment) Programme

Large Area Crop Inventory Experiment was a three year experiment conducted jointly by the United States Department of Agriculture, NASA, and NOAA (National Oceanic and Atmospheric Administration) to determine if global wheat production can be forecast from LANDSAT data to within 90% of actual yield for each observed 9 years out of 10. Data for the third crop year (1976-1977) was compiled. The proportional area of cultivated land devoted to wheat was estimated based on a statistical sampling of LANDSAT data. Yield is presently estimated by NOAA using regression models developed from historical weather and yield information. Results are discussed.

Whitman, R. I.↗

NASA NTRS1984

Simulation studies of the impact of advanced observing systems on numerical weather prediction

To study the potential impact of advanced passive sounders and lidar temperature, pressure, humidity, and wind observing systems on large-scale numerical weather prediction, a series of realistic simulation studies between the European Center for medium-range weather forecasts, the National Meteorological Center, and the Goddard Laboratory for Atmospheric Sciences is conducted. The project attempts to avoid the unrealistic character of earlier simulation studies. The previous simulation studies and real-data impact tests are reviewed and the design of the current simulation system is described. Consideration is given to the simulation of observations of space-based sounding systems.

Atlas, R.↗

NASA NTRS2002

Improving Environmental Prediction Using Rainfall Observations from Space

I discuss the need for accurate rainfall observations to improve our knowledge of the atmospheric state and the ability to provide better numerical weather forecasts. I will give an overview of the recent progress in using rainfall data provided by TRMM and other microwave instruments in data assimilation to improve global analyses and shortrange forecasts. In cases of Hurricanes Bonnie and Floyd, results show that assimilation of TRMM and SSM/I rain rates produces initial conditions with better defined tropical storm features that lead to better Hurricane track and quantitative precipitation forecasts. I will outline the current and future research strategies in preparation for the Global Precipitation Mission.

Hou, Arthur Y.↗