The Aquarius Salinity Retrieval Algorithm

The first part of this presentation gives an overview over the Aquarius salinity retrieval algorithm. The instrument calibration [2] converts Aquarius radiometer counts into antenna temperatures (TA). The salinity retrieval algorithm converts those TA into brightness temperatures (TB) at a flat ocean surface. As a first step, contributions arising from the intrusion of solar, lunar and galactic radiation are subtracted. The antenna pattern correction (APC) removes the effects of cross-polarization contamination and spillover. The Aquarius radiometer measures the 3rd Stokes parameter in addition to vertical (v) and horizontal (h) polarizations, which allows for an easy removal of ionospheric Faraday rotation. The atmospheric absorption at L-band is almost entirely due to molecular oxygen, which can be calculated based on auxiliary input fields from numerical weather prediction models and then successively removed from the TB. The final step in the TA to TB conversion is the correction for the roughness of the sea surface due to wind, which is addressed in more detail in section 3. The TB of the flat ocean surface can now be matched to a salinity value using a surface emission model that is based on a model for the dielectric constant of sea water [3], [4] and an auxiliary field for the sea surface temperature. In the current processing only v-pol TB are used for this last step

Machine learning estimation of fire arrival time from level-2 active fires satellite data

Producing high-resolution near-real-time forecasts of fire behavior and smoke impact that are useful for fire and air quality management requires accurate initialization of the fire location. One common representation of the fire progression is through the fire arrival time, which defines the time that the fire arrives at a given location. Estimating the fire arrival time is critical for initializing the fire location within coupled fire-atmosphere models. We present a new method that utilizes machine learning to estimate the fire arrival time from satellite data in the form of burning/not burning/no data rasters. The proposed method, based on a support vector machine (SVM), is tested on the 10 largest California wildfires of the 2020 fire season, and evaluated using independent observed data from airborne infrared (IR) fire perimeters. The SVM method results indicate a good agreement with airborne fire observations in terms of the fire growth and a spatial representation of the fire extent. A 12% burned area absolute percentage error, a 5% total burned area mean percentage error, a 0.21 False Alarm Ratio average, a 0.86 Probability of Detection average, and a 0.82 Sørensen’s coefficient average suggest that this method can be used to monitor wildfires in near-real-time and provide accurate fire arrival times for improving fire modeling even in the absence of IR fire perimeters

Could the 2012 Drought in Central U. S. Have Been Anticipated?

This paper summarizes research related to the 2012 record drought in the central United States conducted by members of the NEWS (NASA (National Aeronautics and Space Administration) Energy and Water cycle Study) Working Group. Past drought patterns were analyzed for signal coherency with latest drought and the contribution of long-term trends in the Great Plains low-level jet, an important regional circulation feature of the spring rainy season in the Great Plains. Long-term changes in the seasonal transition from rainy spring into dry summer were also examined. Potential external forcing from radiative processes, soil-air interactions, and ocean teleconnections were assessed as contributors to the intensity of the drought. The atmospheric Rossby wave activity was found to be a potential source of predictability for the onset of drought. A probabilistic model was introduced and evaluated for its performance in predicting drought recovery in the Great Plains

Generative Algorithms for Fusion of Physics-Based Wildfire Spread Models with Satellite Data for Initializing Wildfire Forecasts

Increases in wildfire activity and the resulting impacts have prompted the development of high-resolution wildfire behavior models for forecasting fire spread. Recent progress in using satellites to detect fire locations further provides the opportunity to use measurements to improve fire spread forecasts from numerical models through data assimilation. This work develops a method for inferring the history of a wildfire from satellite measurements, providing the necessary information to initialize coupled atmosphere-wildfire models from a measured wildfire state in a physics-informed approach. The fire arrival time, which is the time the fire reaches a given spatial location, acts as a succinct representation of the history of a wildfire. In this work, a conditional Wasserstein Generative Adversarial Network (cWGAN), trained with WRF-SFIRE simulations, is used to infer the fire arrival time from satellite active fire data. The cWGAN is used to produce samples of likely fire arrival times from the conditional distribution of arrival times given satellite active fire detections. Samples produced by the cWGAN are further used to assess the uncertainty of predictions. The cWGAN is tested on four California wildfires occurring between 2020 and 2022, and predictions for fire extent are compared against high resolution airborne infrared measurements. Further, the predicted ignition times are compared with reported ignition times. An average Sorensen's coefficient of 0.81 for the fire perimeters and an average ignition time error of 32 minutes suggest that the method is highly accurate

Could the 2012 Drought in Central U.S. Have Been Anticipated? A Review of NASA Working Group Research

This paper summarizes research related to the 2012 record drought in the central United States conducted by members of the NASA Energy and Water cycle Study (NEWS) Working Group. Past drought patterns were analyzed for signal coherency with latest drought and the contribution of long-term trends in the Great Plains low-level jet, an important regional circulation feature of the spring rainy season in the Great Palins. Long-term changes in the seasonal transition from rainy spring into dry summer were also examined. Potential external forcing from radiative processes, soil-air interactions, and ocean teleconnections were assessed as contributors to the intensity of the drought. The atmospheric Rossby wave activity was found to be a potential source of predictability for the onset of drought. A probabilistic model was introduced and evaluated for its performance in predicting drought recovery in the Great Plains

Utilizing a Global Network of Telescopes to Update the Ephemeris for the Highly Eccentric Planet HD 80606 b and to Ensure the Efficient Scheduling of JWST

The transiting planet HD 80606 b undergoes a 1000 fold increase in insolation during its 111 days orbit due to it being highly eccentric (e = 0.93). The planet's effective temperature increases from 400 to over 1400 K in a few hours as it makes a rapid passage to within 0.03 au of its host star during periapsis. Spectroscopic observations during the eclipse (which is conveniently oriented a few hours before periapsis) of HD 80606 b with the James Webb Space Telescope (JWST) are poised to exploit this highly variable environment to study a wide variety of atmospheric properties, including composition, chemical and dynamical timescales, and large scale atmospheric motions. Critical to planning and interpreting these observations is an accurate knowledge of the planet's orbit. We report on observations of two full-transit events: 2020 February 7 as observed by the TESS spacecraft and 2021 December 7-8 as observed with a worldwide network of small telescopes. We also report new radial velocity observations which, when analyzed with a coupled model to the transits, greatly improves the planet's orbital ephemeris. Our new orbit solution reduces the uncertainty in the transit and eclipse timing of the JWST era from tens of minutes to a few minutes. When combined with the planned JWST observations, this new precision may be adequate to look for non-Keplerian effects in the orbit of HD 80606 b

The state of the Martian climate

60°N was +2.0°C, relative to the 1981–2010 average value (Fig. 5.1). This marks a new high for the record. The average annual surface air temperature (SAT) anomaly for 2016 for land stations north of starting in 1900, and is a significant increase over the previous highest value of +1.2°C, which was observed in 2007, 2011, and 2015. Average global annual temperatures also showed record values in 2015 and 2016. Currently, the Arctic is warming at more than twice the rate of lower latitudes