The problem boils down to geometry. When a cloud radar’s beam is perfectly vertical, the Doppler velocity it measures is the sum of just two things: the speed at which hydrometeors such as ice crystals and raindrops fall, and the vertical motion of the air itself. Separating those two contributions is already one of the fundamental challenges in cloud radar analysis, and decades of techniques have been built around Doppler spectra and their moments to tease them apart. But if the beam tilts even slightly away from zenith, a third term sneaks in: the horizontal wind, projected onto the tilted beam. A radar that thinks it is measuring falling snow may actually be measuring a slice of the jet stream.

The size of this contamination is startling given how small the tilts are. The researchers’ simulations show that a pointing offset of just 0.5 degrees, with a horizontal wind of 10 meters per second, injects a Doppler velocity signal of roughly 0.1 meters per second, comparable to the fall speeds of the smallest ice crystals. Crank the wind up to 40 meters per second, typical of upper-level jet conditions, and the bias grows to about 0.3 meters per second. Doubling the tilt to one degree roughly doubles the amplitude of the spurious signal, and a two-degree offset quadruples it. For radars designed to detect the feeble velocity perturbations of boundary-layer turbulence, these are not rounding errors; they are systematic biases that can propagate into retrievals of vertical air motion, turbulence, and cloud microphysics.

Min Deng of Brookhaven National Laboratory and her colleagues developed a technique they call the U-normalized velocity-direction display, or UN-VDD, which turns this contamination into a diagnostic. The key insight is that the wind-induced Doppler velocity does not vary randomly. It follows a cosine dependence on wind direction, peaking when the wind blows along the radar’s tilt azimuth and reversing when it blows the opposite way. This is the same geometric principle that underpins the velocity-azimuth display method used since 1968 to retrieve winds from scanning Doppler radars, but run in reverse: instead of assuming a vertical beam to find the wind, the team assumes a known wind to find the beam.

Normalizing is what makes the method work in practice. Because horizontal wind speed changes with height and time, raw Doppler velocities mix the geometric signal with variations in wind magnitude. Dividing the measured Doppler velocity by the radiosonde-measured wind speed strips that dependence away, leaving a quantity dominated by the beam-pointing geometry itself. Particle fall velocities and vertical air motions do not vary systematically with wind direction, so they appear as scatter and a roughly constant offset rather than a coherent cosine wave. The amplitude of the fitted cosine then yields the off-vertical tilt angle, and its phase gives the azimuth of the tilt. In upper-level ice clouds, where fall speeds are weak compared with synoptic-scale winds, the approximation is particularly clean.

The team put the method through its paces during the Cloud and Precipitation Experiment at kennaook (CAPE-k) in Tasmania, where a Ka-band ARM Zenith Radar (KAZR) and a Marine W-band ARM Cloud Radar (MWACR) operated within 100 meters of each other. A telling case from September 2024 showed the two radars observing the same ice cloud layer between 5 and 8 kilometers altitude, yet reporting systematically different Doppler velocities: the KAZR registered apparent upward velocities approaching 2 meters per second near cloud top, physically implausible as sustained air motion, while the MWACR showed weak downward values consistent with small ice crystals. Applying UN-VDD to the full campaign revealed why. The KAZR beam was tilted about 2.5 degrees from vertical, toward an azimuth near 140 degrees, while the MWACR was nearly true at about 0.6 degrees off zenith.

The most convincing validation came from subtracting one radar’s velocities from the other. Because the two instruments observe nearly the same atmospheric volume, the contributions of particle fall speed and vertical air motion largely cancel in the difference, leaving a signal dominated by their relative pointing error. The normalized velocity difference showed a strikingly clear cosine dependence with a near-zero offset, yielding a relative tilt of about 1.5 degrees at an azimuth of roughly 140 degrees, consistent with the individual radar fits. It is a neat piece of self-consistency: two independent radars, one analysis, one answer.

The method proved robust well beyond Tasmania. Applied to the Bankhead National Forest campaign in the southeastern United States, it retrieved a smaller offset of about 0.5 degrees, and sensitivity tests showed the retrieved angle varied by less than 0.3 degrees across different radar averaging windows and by less than 0.25 degrees across different reflectivity thresholds used to select ice-cloud samples. The overall uncertainty is estimated at roughly 0.5 degrees. Across recent ARM campaigns including SAIL, TRACER, EPCAPE, and CoURAGE, most deployments showed tilts within about half a degree, with CoURAGE showing a moderate 1.2-degree offset and CAPE-k the largest at 2.5 degrees for the KAZR. Notably, the method even caught history: at the Eastern North Atlantic fixed site, the analysis detected a growing pointing deviation during 2017 and 2018 that matched a documented data quality issue, and after a radar levelling procedure in January 2019, the retrieved offset dropped to about 0.1 degrees.

What makes the technique genuinely powerful is that it requires no new hardware and no special campaigns. Radiosondes are launched routinely at ARM sites and at weather stations worldwide, providing high-resolution wind profiles that are independent of radar calibration. The main caveat is balloon drift: a radiosonde can travel 5 to 30 kilometers horizontally by the time it reaches 10 kilometers altitude, introducing representativeness uncertainty in sheared environments. But because the wind-direction signature is geometric rather than local, aggregating many launches across a campaign builds up enough directional coverage to constrain the fit reliably.

The researchers also lay out how the retrieved angles could be used to correct archived data. For a small tilt, the maximum wind contamination is approximately the wind speed times the tilt angle in radians, so a 0.5-degree offset can bias velocities by up to 0.17 meters per second in 20-meter-per-second winds and 0.35 meters per second in jet-level winds. A correction formula removes the projected wind component, though the authors caution that corrections should only be applied when the tilt is statistically distinguishable from zero and the projected bias exceeds what the intended product can tolerate. For a global network of cloud radars feeding climate models and process studies, a quality-control tool that costs nothing but arithmetic on data already being collected may prove one of the quiet upgrades with the loudest consequences.

Subject of Research: Estimating beam pointing errors of vertically pointing cloud radars using radiosonde wind measurements

Article Title: Estimating beam pointing of vertically pointing cloud radars using radiosonde measurements

Article References: Deng, M., Giangrande, S. E., Theisen, A. K., Johnson, K. L., Lindenmaier, I. A., Wendler, T. G., Comstock, J., Rocque, M., Zhu, Z., & Matthews, A. (2026). Estimating beam pointing of vertically pointing cloud radars using radiosonde measurements. Atmospheric Measurement Techniques, 19(19), 6327-6339. https://doi.org/10.5194/amt-19-6327-2026

Image Credits: AI Generated

DOI: 10.5194/amt-19-6327-2026

Keywords: cloud radar, radiosonde, beam pointing, Doppler velocity, ARM, KAZR, MWACR, vertical air motion, atmospheric measurement, CAPE-k, radar calibration, wind projection

The study, published in the journal Solar Physics, was led by Akie Moritsuka of the University of Tokyo and the National Astronomical Observatory of Japan, together with Yukio Katsukawa and Ryohtaroh T. Ishikawa. The team mined the archives of the Hinode satellite, a Japanese mission launched in 2006 and operated in collaboration with NASA and the UK Space Agency. Hinode’s Solar Optical Telescope, a 50-centimeter instrument with a diffraction-limited resolution of about 0.31 arcseconds at 630 nanometers, carries a Spectro-Polarimeter that records the full polarization state of light across two iron absorption lines at 630.15 and 630.25 nanometers. Crucially, the team selected 49 polar-observation datasets in which the north or south limb fell inside the field of view, allowing them to trace spectral line shifts from heliocentric angles of about 63 degrees all the way to the limb at 90 degrees, and even slightly beyond it.

Observing this close to the limb is notoriously difficult. The line of sight grazes the solar surface at an extremely shallow angle, so the light from any single pixel samples a long, slanted path through the atmosphere, blending structures that would be cleanly separated at disk center. The researchers first had to pin down the exact position of the limb in every scan by finding the pixel with the steepest gradient in continuum intensity, then fitting a circle to the limb to recover the coordinates of the disk center. From there they could assign a precise heliocentric angle to every pixel on the disk. The spatial resolution of the instrument, roughly 0.15 to 0.16 arcseconds along each axis, corresponds to about 600 kilometers on the Sun near disk center, degrading toward the limb, which sets a hard limit on how finely the convective pattern can be resolved at grazing angles.

To disentangle the contributions of different parts of the convective pattern, the team classified every observed spectrum into three categories. Pixels showing a total polarization degree of 0.6 percent or more, three times the internetwork average, were labeled magnetic regions. Among the non-magnetic pixels, those brighter than the local average continuum intensity, corrected for limb darkening, were classified as granules, while darker pixels were classified as intergranules. This classification matters because the physics of the two regions differs fundamentally: granules are the sites of hot, rising, blueshifted plasma, while intergranular lanes host cool, sinking, redshifted material. Because the polar fields observed here are quiet, magnetic regions occupied less than one percent of the area at 66 degrees, so the analysis of convective velocities focused on the granule and intergranule populations.

The headline result concerns how the averaged Doppler velocity of the iron line at 630.15 nanometers changes across the disk. The spatially averaged profiles showed a steady increase in redshift from about 65 degrees up to roughly 80 degrees, then the trend flattened, and finally the velocities fell back to nearly zero at the very limb. The increase of about 70 meters per second between 66 and 72 degrees agrees well with high-accuracy ground-based measurements made with the Laser Absolute Reference Spectrograph, which anchored the team’s velocity calibration using laboratory-grade laser frequency comb references. But the real insight came from splitting the signal by region. Granules showed a dramatic evolution: their Doppler velocities shifted by about 240 meters per second toward the red between 65 and 80 degrees, ending up redshifted by roughly 120 meters per second. Intergranules, by contrast, stayed almost perfectly constant at around 120 meters per second of redshift, varying by no more than about 20 meters per second across the same range.

This asymmetry is the key to the limb effect. The traditional explanation invokes the corrugated, three-dimensional surface of the photosphere: when we look at the limb, the line of sight skims across the tops of the granular bumps, and the redshifted horizontal flow on the near side of each granule appears brighter than the blueshifted flow on the far side, because the back granule’s wall provides the background illumination. When a front granule partially hides a back one, the blueshifted material is concealed while the redshifted material remains visible. The new observations confirm this picture quantitatively: since the overall average shift is dominated by the bright granules, and it is the granules whose redshift grows toward the limb, the limb effect is essentially a granule phenomenon. The intergranular lanes, whose sinking flows are already redshifted, contribute a nearly constant baseline.

The team went a step further by analyzing the bisectors of the spectral lines, the locus of wavelength midpoints measured at different depths within the absorption profile. Because the line core forms higher in the photosphere while the wings form deeper down, the bisector encodes the vertical gradient of the line-of-sight velocity. At 66 degrees, the overall bisector showed the classic backslash shape, with a velocity difference of roughly 500 meters per second between core and wing, consistent with non-magnetic numerical simulations. Toward the limb, this shape gradually straightened into an I-shape by about 84 degrees, indicating that the line-forming region samples a much smaller range of velocities. Most tellingly, the bisectors of granules changed far more dramatically than those of intergranules, which remained nearly symmetric throughout. The authors interpret this as evidence that the atmosphere within granules, where the line forms, is geometrically thicker than in intergranules, so that the velocity gradient along the line of sight is larger and its apparent compression toward the limb is more pronounced.

The observations also captured something rarer still: emission lines just beyond the limb. Previous work had shown that within about one arcsecond above the limb, the iron line at 630.15 nanometers can flip from absorption to emission, a phenomenon linked to localized temperature enhancements and torsional flows in magnetic flux concentrations. The team averaged the emission profiles from the second and third pixels above the limb and found small blueshifts, averaging around 130 meters per second relative to the disk absorption lines. The authors are careful to note that this difference is only about one standard deviation and could partly reflect limitations of their velocity correction, which relied on a linear fit below 80 degrees. If the emission lines were taken as the true zero-velocity reference, the absorption lines near the limb would instead be redshifted by a comparable amount, a distinction that future observations with better absolute calibration will need to settle.

Comparisons with three-dimensional radiative magnetohydrodynamic simulations reveal both agreement and tension. The granular trends match simulations that model magnetoconvection, while the flat intergranular velocities do not, likely because intergranular lanes are only about 300 kilometers wide and fall below the effective spatial resolution at large heliocentric angles, where granules and lanes blur together. The bisector velocity difference of about 500 meters per second aligns better with non-magnetic simulations than with magnetic ones, consistent with the quiet, weakly magnetized polar regions studied here. The authors argue that the next leap requires instruments such as the Visible Spectro-Polarimeter on the Daniel K. Inouye Solar Telescope, which can resolve granules and lanes up to the limb, combined with telluric-line or laser-comb velocity calibration and multi-wavelength observations probing from the deep photosphere to the low chromosphere. For now, the Hinode archive has done what it does best: turning a century-old puzzle about crooked spectral lines into a concrete, measurable statement about the three-dimensional architecture of the Sun’s boiling surface.

Subject of Research: Center-to-limb variation of Doppler velocities and spectral line bisectors in the solar photosphere observed with Hinode

Article Title: Doppler Velocity Variation Near the Solar Limb in the Solar Photosphere Observed with Hinode

Article References: Moritsuka, A., Katsukawa, Y., & Ishikawa, R. T. (2026). Doppler Velocity Variation Near the Solar Limb in the Solar Photosphere Observed with Hinode. Solar Physics, 301(10), Article 153. https://doi.org/10.1007/s11207-026-02747-6

Image Credits: AI Generated

DOI: 10.1007/s11207-026-02747-6

Keywords: solar physics, photosphere, granulation, Doppler velocity, limb effect, spectral line bisector, Hinode, Solar Optical Telescope, spectro-polarimetry, convective blueshift, iron spectral lines, solar limb

The Extreme-ultraviolet Variability Experiment, or EVE, was never designed to measure Doppler velocities. Its mission is to track how the Sun’s extreme ultraviolet output varies over time, information that matters because that radiation is the primary energy input to Earth’s ionosphere and thermosphere. EVE observes the full solar disk from 6 to 106 nanometers with a spectral resolution of just 0.1 nanometers, using its Multiple EUV Grating Spectrographs, known as MEGS. At that modest resolution, detecting the tiny wavelength shifts produced by moving plasma would seem impossible. Yet two fortunate circumstances changed the calculus: the SDO spacecraft holds its solar pointing with exceptional stability, and its geosynchronous orbit provides an unusually stable thermal environment, keeping the instrument’s wavelength scale steady enough to capture genuine solar motions.

The new data product fits Gaussian profiles to 70 carefully selected emission features, each originating from a distinct layer of the solar atmosphere. Roughly half of the lines come from the transition region, a thin boundary layer where temperatures climb from about 25,000 kelvin to 0.6 million kelvin, and half come from the corona above, where temperatures exceed 0.6 million kelvin and can surpass 6 million kelvin during flares. The fitting algorithm models each feature of interest with a Gaussian plus two additional Gaussians for blended neighboring lines and a linear background, yielding fitted values for intensity, wavelength center, and line width. When the GOES X-Ray Sensor detects a flare, the algorithm automatically subtracts a pre-flare spectrum to isolate the flare’s own spectral signature, flagging those events in the data product.

Converting wavelength shifts to velocities is straightforward in principle: the shift between the flare spectrum and the pre-flare spectrum, multiplied by the speed of light and divided by the reference wavelength, gives the line-of-sight velocity. Positive values are red shifts, indicating plasma receding from the observer, which for flares near disk center means downflow. Negative values are blue shifts, indicating approaching plasma, or upflow. The team emphasizes that measured pre-flare wavelengths, rather than theoretical values from the CHIANTI spectral database, must serve as the reference, because small systematic offsets in the instrument’s wavelength scale would otherwise contaminate the result.

Not every spectral line is trustworthy for this work. Many EUV features are blends of multiple emissions at MEGS resolution, and different lines dominate at different plasma temperatures, so a blended feature can shift spuriously as solar activity changes. The team used CHIANTI model spectra for quiet Sun, active region, and flare conditions to estimate this blend uncertainty for each of the 70 features, expressing it as a velocity error. Forty-two lines, nine from MEGS-A and thirty-three from MEGS-B, came in below the 30 kilometers-per-second threshold and are flagged as the best choices for studying flare dynamics. The rest carry blend errors large enough to swamp any genuine solar signal.

Perhaps the most technically demanding part of the study involved disentangling an optical artifact from real solar physics. The MEGS-B instrument uses two Rowland-circle spectrographs in tandem, and because its CCD sensor is flat rather than curved along the Rowland circle, most wavelengths are slightly out of focus. That defocus makes the measured wavelength scale sensitive to where an active region sits on the solar disk. Raytrace modeling of the original optical design confirmed that active regions near the east limb produce wavelength shifts in one direction, west-limb regions in the opposite direction, with the sign flipping between central and outer wavelengths. Earlier reports of surprisingly fast prograde-rotation velocities of about 50 kilometers per second in coronal lines, published by Hudson and colleagues in 2022, turn out to be an artifact of this optical behavior rather than a genuine solar flow.

To validate and calibrate the correction, the team exploited a rare window in April 2019 near the minimum of solar cycle 24, when a single active region, NOAA 12738, crossed the disk alone over six days. By subtracting a spectrum from a spotless day to remove the full-disk contribution, and then fitting the remaining active-region spectrum, the researchers measured wavelength shifts that matched a tuned raytrace model remarkably well. The tuning revealed that the Sun’s center sits about 2.5 arc-minutes east of MEGS-B’s optical center, a misalignment inherited from the compromise positioning of EVE’s three channels and the jolts of launch. The resulting correction equations, expressed as parabolic functions of wavelength scaled by flare position, are now available for users of the data product, though the corrections are not applied automatically because the processing pipeline does not know each flare’s location.

The payoff comes in the flare statistics. For the X2.2 flare of 15 February 2011, the first X-class event of the SDO mission, all chromospheric, transition region, and cool coronal features below 1 million kelvin showed maximum red shifts averaging 75 plus or minus 24 kilometers per second, while hotter coronal lines showed blue shifts averaging minus 114 plus or minus 75 kilometers per second, with the Fe XIV line at 21.14 nanometers reaching an extraordinary minus 213 kilometers per second. The X9.0 flare of 3 October 2024 told a similar story, with downflows averaging 37 plus or minus 16 kilometers per second and upflows averaging minus 94 plus or minus 58 kilometers per second. In both cases, and across a broader sample of 15 disk-center X-class flares, the velocity maxima almost always occurred during the impulsive phase, the brief interval when magnetic reconnection releases energy most furiously.

These patterns match the standard picture of flare physics, often called the CSHKP model, in which reconnection drives chromospheric evaporation upward into hot coronal loops while cooler material drains downward. The transition from red shifts to blue shifts between 1 and 2 million kelvin, first noted by Milligan and Dennis in 2009 using Hinode data, appears clearly in the EVE results. The findings also align with earlier EVE-based analyses, including Hudson and colleagues’ 2011 report of a 50 kilometers-per-second red shift in He II and a 100 kilometers-per-second blue shift in Fe XXIV, and Otsu and Asai’s 2024 detection of a dramatic minus 400 kilometers-per-second blue shift during a filament eruption. For limb flares, the team found that even after location corrections, coronal lines still blue-shift by about 150 kilometers per second relative to the gradual phase, hinting at non-radial outflows that may accompany coronal mass ejections.

The practical lesson for solar physicists is that the EVE Level 4 Lines product, despite the instrument’s modest resolution and full-disk field of view, opens a routine path to measuring flare plasma dynamics across an entire solar cycle. Users must apply the optical wavelength-shift correction based on flare location for anything away from disk center, or risk mistaking instrumental artifacts for solar flows of 50 to 200 kilometers per second. But with 42 X-class flares already analyzed for MEGS-A and 103 for MEGS-B, and countless smaller events awaiting study, the new data product promises to deepen understanding of the magnetic explosions that drive space weather, disturb satellite orbits, and occasionally paint auroras across skies far from the poles.

Subject of Research: Measurement of solar flare Doppler velocities using the SDO EVE Level 4 Lines data product

Article Title: Solar Doppler Velocity Results from the SDO EVE Level 4 Lines Data Product

Article References: Solar Doppler Velocity Results from the SDO EVE Level 4 Lines Data Product. (n.d.). https://doi.org/10.1007/s11207-026-02727-w

Image Credits: AI Generated

DOI: 10.1007/s11207-026-02727-w

Keywords: solar flares, Doppler velocity, SDO, EVE, extreme ultraviolet, corona, transition region, space weather, magnetic reconnection, spectroscopy, Solar Dynamics Observatory, MEGS