The influence of pacific winds on ENSO diversity

The differences in ENSO sea surface temperature (SST) spatial patterns, whether centered in the Eastern Pacific (EP), Central Pacific (CP) or in the eastern-central equatorial region ("canonical") have been associated to differences in atmospheric teleconnections and global impacts. However, predicting different types of ENSO events has proved challenging, highlighting the need for a deeper understanding of their predictability. Given the key role played by wind variations in the development and evolution of ENSO events, this study examines the relationship between the leading modes of Pacific surface wind speed variability and ENSO diversity using three different state-of-the-art wind products, including satellite observations and atmospheric reanalyses. Although previous studies have associated different ENSO precursors to either EP or CP events, our results indicate that the most prominent of those ENSO precursors are primarily related to canonical and CP events, and show little correlation with EP events. The latter are associated with tropical Pacific conditions favoring equatorial westerly wind and precipitation anomalies that extend all the way to the eastern Pacific. Results over the entire twentieth century period versus those during the satellite era also suggest that the influences from the Southern Hemisphere may be more robust than those from the Northern Hemisphere. &nbsp;</p

Assessment of CYGNSS Wind Speed Retrievals in Tropical Cyclones

The NASA CYGNSS satellite constellation measures ocean surface winds using the existing network of the Global Navigation Satellite System (GNSS) and was designed for measurements in tropical cyclones (TCs). Here, we focus on using a consistent methodology to validate multiple CYGNSS wind data records currently available to the public, some focusing on low to moderate wind speeds, others for high winds, a storm-centric product for TC analyses, and a wind dataset from NOAA that applies a track-wise bias correction. Our goal is to document their differences and provide guidance to users. The assessment of CYGNSS winds (2017–2020) is performed here at global scales and for all wind regimes, with particular focus on TCs, using measurements from radiometers that are specifically developed for high winds: SMAP, WindSat, and AMSR2 TC-winds. The CYGNSS high-wind products display significant biases in TCs and very large uncertainties. Similar biases and large uncertainties were found with the storm-centric wind product. On the other hand, the NOAA winds show promising skill in TCs, approaching a level suitable for tropical meteorology studies. At the global level, the NOAA winds are overall unbiased at wind regimes from 0–30 m/s and were selected for a test assimilation into a global wind analysis, CCMP, also presented here

Assessment of Saildrone Extreme Wind Measurements in Hurricane Sam Using MW Satellite Sensors

In 2021, a novel NOAA-Saildrone project deployed five uncrewed surface vehicle Saildrones (SDs) to monitor regions of the Atlantic Ocean and Caribbean Sea frequented by tropical cyclones. One of the SDs, SD-1045, crossed Hurricane Sam (Category 4) on September 30, providing the first-ever surface-ocean videos of conditions in the core of a major hurricane and reporting near-surface winds as high as 40 m/s. Here, we present a comprehensive analysis and interpretation of the Saildrone ocean surface wind measurements in Hurricane Sam, using the following datasets for direct and indirect comparisons: an NDBC buoy in the path of the storm, radiometer tropical cyclone (TC) winds from SMAP and AMSR2, wind retrievals from the ASCAT scatterometers and SAR (RadarSat2), and HWRF model winds. The SD winds show excellent consistency with the satellite observations and a remarkable ability to detect the strength of the winds at the SD location. We use the HWRF model and satellite data to perform cross-comparisons of the SD with the buoy, which sampled different relative locations within the storm. Finally, we review the collective consistency among these measurements by describing the uncertainty of each wind dataset and discussing potential sources of systematic errors, such as the impact of extreme conditions on the SD measurements and uncertainties in the methodology

Assessment of Saildrone Extreme Wind Measurements in Hurricane Sam Using MW Satellite Sensors

In 2021, a novel NOAA-Saildrone project deployed five uncrewed surface vehicle Saildrones (SDs) to monitor regions of the Atlantic Ocean and Caribbean Sea frequented by tropical cyclones. One of the SDs, SD-1045, crossed Hurricane Sam (Category 4) on September 30, providing the first-ever surface-ocean videos of conditions in the core of a major hurricane and reporting near-surface winds as high as 40 m/s. Here, we present a comprehensive analysis and interpretation of the Saildrone ocean surface wind measurements in Hurricane Sam, using the following datasets for direct and indirect comparisons: an NDBC buoy in the path of the storm, radiometer tropical cyclone (TC) winds from SMAP and AMSR2, wind retrievals from the ASCAT scatterometers and SAR (RadarSat2), and HWRF model winds. The SD winds show excellent consistency with the satellite observations and a remarkable ability to detect the strength of the winds at the SD location. We use the HWRF model and satellite data to perform cross-comparisons of the SD with the buoy, which sampled different relative locations within the storm. Finally, we review the collective consistency among these measurements by describing the uncertainty of each wind dataset and discussing potential sources of systematic errors, such as the impact of extreme conditions on the SD measurements and uncertainties in the methodology

Improving the Accuracy of the Cross-Calibrated Multi-Platform (CCMP) Ocean Vector Winds

The Cross-Calibrated Multi-Platform (CCMP) Ocean vector wind analysis is a level-4 product that uses a variational method to combine satellite retrievals of ocean winds with a background wind field from a numerical weather prediction (NWP) model. The result is a spatially complete estimate of global ocean vector winds on six-hour intervals that are closely tied to satellite measurements. The current versions of CCMP are fairly accurate at low to moderate wind speeds (&lt;15 m/s) but are systematically too low at high winds at locations/times where a collocated satellite measurement is not available. This is mainly because the NWP winds tend to be lower than satellite winds, especially at high wind speed. The current long-term CCMP version, version 2.0, also shows spurious variations on interannual to decadal time scales caused by the interaction of satellite/model bias with the varying amount of satellite measurements available as satellite missions begin and end. To alleviate these issues, here we explore methods to adjust the source datasets to more closely match each other before they are combined. The resultant new CCMP wind analysis agrees better with long-term trend estimates from satellite observations and reanalysis than previous versions

Wind speed climatology and trends for Australia, 1975-2006: Capturing the stilling phenomenon and comparison with near-surface reanalysis output

Near-surface wind speeds (u) measured by terrestrial anemometers show declines (a 'stilling') at a range of midlatitude sites, but two gridded u datasets (a NCEP/NCAR reanalysis output and a surface-pressure-based u model) have not reproduced the stilling observed at Australian stations. We developed Australia-wide 0.01° resolution daily u grids by interpolating measurements from an expanded anemometer network for 1975-2006. These new grids represented the magnitude and spatial-variability of observed u trends, whereas grids from reanalysis systems (NCEP/NCAR, NCEP/DOE and ERA40) essentially did not, even when minimising the sea-breeze impact. For these new grids, the Australian-averaged u trend for 1975-2006 was -0.009 rn s-1 a-1 (agreeing with earlier site-based studies) with stilling over 88% of the land-surface. This new dataset can be used in numerous environmental applications, including benchmarking general circulation models to improve the representation of key parameters that govern u estimation. The methodology implemented here can be applied globally

Estimating tropical cyclone surface winds: Current status, emerging technologies, historical evolution, and a look to the future

This article provides a review of tropical cyclone (TC) surface wind estimation from an operational forecasting perspective. First, we provide a summary of operational forecast center practices and historical databases. Next, we discuss current and emerging objective estimates of TC surface winds, including algorithms, archive datasets, and individual algorithm strengths and weaknesses as applied to operational TC surface wind forecast parameters. Our review leads to recommendations about required surface coverage – an area covering at least 1100 km from center of TC at a 2-km resolution in the inner-core, and at a frequency of at least once every six hours. This is enough coverage to support a complete analysis of the TC surface wind field from center to the extent of the 34-kt (17 m s-1) winds at 6-h intervals. We also suggest future designs of TC surface wind capabilities include funding to ensure near real-time data delivery to operators so that operational evaluation and use are feasible within proposed budgets. Finally, we suggest that users of archived operational wind radii datasets contact operational organizations to ensure these datasets are appropriate for their needs as the datasets vary in quality through time and space, even from a single organization

Uncertainties in Ocean Latent Heat Flux Variations over Recent Decades in Satellite-Based Estimates and Reduced Observation Reanalyses

Four state-of-the-art satellite-based estimates of ocean surface latent heat fluxes (LHFs) extending over three decades are analyzed, focusing on the interannual variability and trends of near-global averages and regional patterns. Detailed intercomparisons are made with other datasets including 1) reduced observation reanalyses (RedObs) whose exclusion of satellite data renders them an important independent diagnostic tool; 2) a moisture budget residual LHF estimate using reanalysis moisture transport, atmospheric storage, and satellite precipitation; 3) the ECMWF Reanalysis 5 (ERA5); 4) Remote Sensing Systems (RSS) singlesensor passive microwave and scatterometer wind speed retrievals; and 5) several sea surface temperature (SST) datasets. Large disparities remain in near-global satellite LHF trends and their regional expression over the 1990–2010 period, during which time the interdecadal Pacific oscillation changed sign. The budget residual diagnostics support the smaller RedObs LHF trends. The satellites, ERA5, and RedObs are reasonably consistent in identifying contributions by the 10-m wind speed variations to the LHF trend patterns. However, contributions by the near-surface vertical humidity gradient from satellites and ERA5 trend upward in time with respect to the RedObs ensemble and show less agreement in trend patterns. Problems with wind speed retrievals from Special Sensor Microwave Imager/Sounder satellite sensors, excessive upward trends in trends in Optimal Interpolation Sea Surface Temperature (OISST AVHRR-Only) data used in most satellite LHF estimates, and uncertainties associated with poor satellite coverage before the mid-1990s are noted. Possibly erroneous trends are also identified in ERA5 LHF associated with the onset of scatterometer wind data assimilation in the early 1990s

Remote Sensing and Analysis of Tropical Cyclones: Current and Emerging Satellite Sensors

This article describes recent advances in the capability of new satellite sensors for observing Tropical Cyclones (TC) fine structure, wind field, and temporal evolution. The article is based on a World Meteorological Organization (WMO) report prepared for the 10th International Workshop on Tropical Cyclones (IWTC), held in Bali in December 2022, and its objective is to present updates in TC research and operation every four years. Here we focus on updates regarding the most recent space-based TC observations, and we cover new methodologies and techniques using polar orbiting sensors, such as C-band synthetic aperture radars (SARs), L-band and combined C/X-band radiometers, scatterometers, and microwave imagers/sounders. We additionally address progress made with the new generation of geostationary and small satellites, and discuss future sensors planned to be launched in the next years. We then briefly describe some examples on how the newest sensors are used in operations and data assimilation for TC forecasting and research, and conclude the article with a discussion on the remaining challenges of TC space-based observations and possible ways to address them in the near future