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Susana Jorquera
,
Felipe Toledo Bittner
,
Julien Delanoë
,
Alexis Berne
,
Anne-Claire Billault-Roux
,
Alfons Schwarzenboeck
,
Fabien Dezitter
,
Nicolas Viltard
, and
Audrey Martini

Abstract

This article presents a calibration transfer methodology that can be used between radars of the same or different frequency bands. This method enables the absolute calibration of a cloud radar by transferring it from another collocated instrument with known calibration, by simultaneously measuring vertical ice cloud reflectivity profiles. The advantage is that the added uncertainty in the newly calibrated instrument can converge to the magnitude of the reference instrument calibration. This is achieved by carefully selecting comparable data, including the identification of the reflectivity range that avoids the disparities introduced by differences in sensitivity or scattering regime. The result is a correction coefficient used to compensate measurement bias in the uncalibrated instrument. Calibration transfer uncertainty can be reduced by increasing the number of sampling periods. The methodology was applied between collocated W-band radars deployed during the ICE-GENESIS campaign (Switzerland 2020/21). A difference of 2.2 dB was found in their reflectivity measurements, with an uncertainty of 0.7 dB. The calibration transfer was also applied to radars of different frequency, an X-band radar with unknown calibration and a W-band radar with manufacturer calibration; the difference found was −16.7 dB with an uncertainty of 1.2 dB. The method was validated through closure, by transferring calibration between three different radars in two different case studies. For the first case, involving three W-band radars, the bias found was of 0.2 dB. In the second case, involving two W-band and one X-band radar, the bias found was of 0.3 dB. These results imply that the biases introduced by performing the calibration transfer with this method are negligible.

Open access
Dylan Dumas
and
Charles-Antoine Guérin

Abstract

Original techniques are proposed for the improvement of surface current mapping with phased-array oceanographic high-frequency radars. The first idea, which works only in bistatic configuration, is to take advantage of a remote transmitter to perform an automatic correction of the receiving antennas based on the signal received in the direct path, an adjustment that is designated as “self-calibration.” The second idea, which applies to both mono- and bistatic systems, consists in applying a direction finding (DF) technique (instead of traditional beamforming), not only to the full antenna array but also to subarrays made of a smaller number of sequential antennas, a method that is referred to as “antenna grouping.” In doing this, the number of sources can also be varied, leading to an increased number of DF maps that can be averaged, an operation that is designated as “source stacking.” The combination of self-calibration, antenna grouping, and source stacking makes it possible to obtain high-resolution maps with increased coverage and is found robust to damaged antennas. The third improvement concerns the mitigation of noise in the antenna signal. These methods are illustrated with the multistatic high-frequency radar network in Toulon and their performances are assessed with drifters. The improved DF technique is found to significantly increase the accuracy of radar-based surface current when compared to the conventional beamforming technique.

Restricted access
Curtis J. Seaman
,
William Line
,
Robert Ziel
,
Jennifer Jenkins
,
Carl Dierking
, and
Greg Hanson

Abstract

Two multispectral satellite imagery products are presented that were developed for use within the fire management community. These products, which take the form of false color red–green–blue composites, were designed to aid fire detection and characterization, and for assessment of the environment surrounding a fire. The first, named the Fire Temperature RGB, uses spectral channels near 1.6, 2.2, and 3.9 μm for fire detection and rapid assessment of the range of fire intensity through intuitive coloration. The second, named the Day Fire RGB, uses spectral channels near 0.64, 0.86, and 3.9 μm for rapid scene assessment. The 0.64 μm channel provides information on smoke, the 0.86 μm channel provides information on vegetation health and burn scars, and the 3.9 μm channel provides active fire detections. Examples of these red–green–blue composite images developed from observations collected by three operational satellite imagers (VIIRS on the polar-orbiting platform and the Advanced Baseline Imager and Advanced Himawari Imager on the geostationary platform) demonstrate that both red–green–blue composites are useful for fire detection and contain valuable information that is not present within operational fire detection algorithms. In particular, it is shown that Fire Temperature RGB and Day Fire RGB images from VIIRS have similar utility for fire detection as the operational VIIRS Active Fire products, with the added benefit that the imagery provides context for more than just the fires themselves.

Significance Statement

The current generation of operational polar-orbiting weather satellites that began with the launch of Suomi NPP offers new capabilities with regard to fire detection and monitoring. In particular, false color red–green–blue composite imagery is now being used by fire managers, incident meteorologists, and others in the fire management community to visualize a fire’s behavior and the context in which it occurs. This paper outlines two of these red–green–blue composites that have gained widespread use throughout the U.S. National Weather Service and the Alaska Fire Service. These red–green–blue composites have been applied to the current generation of geostationary and polar-orbiting satellites to great effect and have changed how incident management teams respond to wildland fires.

Open access
Anna Olivé Abelló
,
Josep L. Pelegrí
, and
Francisco Machín

Abstract

A common dilemma for oceanographers is the choice of horizontal diffusivity. There is no single answer as we could argue that diffusion depends precisely on those processes that cannot be sampled or modeled. Here we propose the radial offset by diffusion (ROD) method as a simple model-dependent approach for estimating these coefficients, and show its application for the southwestern South Atlantic. The method compares actual displacements of field drifters with numerical trajectory predictions. The observed–predicted differences in radial positions (radial offsets), which respond to diffusive motions not captured by the numerical model, are reproduced with a one-dimensional radial-diffusive solution through a proper selection of the diffusion coefficient. The method is tested at eight depths, from the sea surface down to 2000 m, using several drifter datasets and the Parcels software applied to the GLORYS12v1 (1/12° daily) velocity outputs. In all cases the radial offsets show Gaussian distributions that are well reproduced by the radial diffusive solution. Maximum diffusivities of 4630–4980 m2 s−1 happen in the upper 200 m of the water column and minimum values of 1080–1270 m2 s−1 occur between 1400 and 2000 m. The 15-m diffusivity is fairly constant in latitude (3850–5270 m2 s−1), but the 1000-m diffusivity decreases from 1640 to 1820 m2 s−1 north of the Polar Front to 530 m2 s−1 south of the Southern Boundary. A comparison with other diffusivity studies validates the good adequacy of the ROD method for numerical and field applications.

Restricted access
Sheila M. Saia
,
Sean P. Heuser
,
Myleigh D. Neill
,
William A. LaForce IV
,
John A. McGuire
, and
Kathie D. Dello

Abstract

Regional weather networks—also referred to as mesonets—are imperative for filling in the spatial and temporal data gaps between nationally supported weather stations. The North Carolina Environment and Climate Observing Network (ECONet) fills this regional role; it is a mesoscale network of 44 (as of 2023) automated stations collecting 12 environmental variables every minute across North Carolina. Measured variables include air temperature, precipitation, relative humidity, barometric pressure, wind speed, wind direction, total solar radiation, photosynthetically active solar radiation, soil temperature, soil moisture, leaf wetness index, and black globe temperature. All data undergo quality control procedures and are made freely available to the public via data portals hosted by the State Climate Office of North Carolina at North Carolina State University. This paper provides a technical overview of ECONet, including a description of the siting criteria, station maintenance procedures, data quality control procedures, and data availability. We also summarize unique aspects of ECONet data collection as well as innovative research and applications that rely on ECONet data. ECONet data are used by many sectors including, but not limited to, emergency management, natural resources management, public health, agriculture, forestry, science education, outdoor recreation, and research. ECONet data and data-powered applications offer valuable insights to local, regional, and federal partners, yet opportunities to expand ECONet research and applications remain.

Significance Statement

This paper explains the ongoing and emerging impacts of a statewide weather station network called the North Carolina Environment and Climate Observing Network (ECONet). ECONet consists of 44 (as of 2023) automated stations located across the state. Each station collects 12 environmental variables every minute. ECONet data and data-powered applications offer valuable insights to local, regional, and federal partners. There are many opportunities to expand ECONet-based research and applications.

Restricted access
Shannon T. Brown
,
Alan Tanner
,
Steven C. Reising
, and
Wesley Berg

Abstract

Passive microwave sounders are critical for accurate forecasts from numerical weather prediction models. These sensors are calibrated using a traditional two-point approach, with one source typically a free-space blackbody target and the second a clear view to the cosmic microwave background, commonly referred to as “cold space.” Occasionally, one or both of these calibration sources can become corrupted, either by solar/lunar intrusion in the cold space view or by thermal instability of the blackbody calibration source. A Temporal Experiment for Storms and Tropical Systems (TEMPEST) microwave sounder instrument is currently deployed on the International Space Station (ISS) for a 3-yr mission. TEMPEST is also calibrated using a blackbody target and cold space view; however, the cold space view will be routinely obstructed by objects present on the ISS. Here we test an alternative single-point calibration methodology that uses only the blackbody calibration target. We find the brightness temperature difference between this new approach and the traditional two-point calibration approach to be <0.1 K when applied to 3 years of the TEMPEST CubeSat Demonstration (TEMPEST-D) mission data from 2018 to 2020. This approach is applicable to other microwave radiometers that experience occasional degradation of calibration sources, such as thermal effects, intrusions, or instability of noise diodes.

Significance Statement

Cross-track microwave sounders have relied on two distinct calibration sources, often the cosmic microwave background using a clear view to cold space and an ambient blackbody target. We have tested an alternative approach that uses a single calibration target, making the sensor robust to occasional field-of-view intrusions of the space view or alternatively simplifies the spaceborne sensor design by eliminating the need for a clear view to space. We find that the performance difference between this new approach and the traditional two-calibration source approach is indistinguishable for both microwave temperature/water vapor profiling and precipitation-rate estimation. This calibration technique can be applied to past, current, and future microwave sounders to help diagnose systematic uncertainties in sensor calibration targets.

Open access
Paul A. Ernst
,
Bulusu Subrahmanyam
,
Yves Morel
,
Corinne B. Trott
, and
Alexis Chaigneau

Abstract

Coherent ocean vortices, or eddies, are usually tracked on the surface of the ocean. However, tracking subsurface eddies is important for a complete understanding of deep ocean circulation. In this study, we develop an algorithm designed for the detection of subsurface eddies in the Arabian Sea using Nucleus for European Modelling of the Ocean (NEMO) model simulations. We optimize each parameter of our algorithm to achieve favorable results when compared with an algorithm using sea surface height (SSH). When compared to similar methods, we find that using the rescaled isopycnal potential vorticity (PV) is best for subsurface eddy detection. We proceed to demonstrate that our new algorithm can detect eddies successfully between specific isopycnals, such as those that define the Red Sea Water (RSW). In doing so, we showcase how our method can be used to describe the properties of eddies within the RSW and even identify specific long-lived subsurface eddies. We conduct one such case study by discerning the structure of a completely subsurface RSW eddy near the Chagos Archipelago using Lagrangian particle tracking and PV diagnostics. We conclude that our rescaled PV method is an efficient tool for investigating eddy dynamics within the ocean’s interior, and publicly provide our optimization methodology as a way for other researchers to develop their own subsurface detection algorithms with optimized parameters for any spatiotemporal model domain.

Significance Statement

Eddies are a key part of ocean circulation both at the surface and in the subsurface. The purpose of our study was to design the first detection method comprehensively optimized for subsurface eddy detection from numerical simulations. We demonstrate that potential vorticity (PV) is the best field to use when algorithmically tracking eddies in subsurface water masses, using our new method to identify and track eddies in the Red Sea Water (RSW). Additionally, our method allows us to efficiently evaluate the dynamics of eddies through potential vorticity diagnostics, exemplified with a previously undescribed eddy near the Chagos Archipelago. Our methodology can be used by future researchers to study the eddy dynamics hidden within subsurface water masses around the world.

Restricted access
Rizana Salim
,
Aishwarya Singh
,
Swetha S
,
Kavyashree N. Kalkura
,
Amar Krishna Gopinath
,
Subha S. Raj
,
Rameshchand K. A.
,
R. Ravi Krishna
, and
Sachin S. Gunthe

Abstract

Aerosol–cloud–precipitation interaction represents the largest uncertainty in climate change’s current and future understanding. Therefore, aerosol properties affecting the cloud and precipitation formation and their accurate estimation is a first step in developing improved parameterizations for the prognostic climate models. Over the last couple of decades, a commercially available Cloud Condensation Nuclei Counter (CCNC) has been deployed in the field and laboratory for characterizing CCN properties of ambient or atmospherically relevant laboratory-generated aerosols. However, most of the CCN measurements performed in the field are often compounded with the erroneous estimation of CCN concentration and other parameters due to a lack of robust and accurate CCNC calibration. CCNC is not a plug-and-play instrument and requires prudent calibration and operation, to avoid erroneous data and added parameterization uncertainties. In this work, we propose and demonstrate the usability of a global calibration equation derived from CCNC calibration experiments from 8 contrasting global environments. Significant correlation was observed between the global calibration and each of the 16 individual experiments. A significant improvement in the correlation was observed when the calibration experiments were separated for high-altitude measurements. Using these equations, we further derived the effective hygroscopicity parameter and found lower relative uncertainty in the hygroscopicity parameter at higher effective supersaturation. Our results signify that altitude-based pressure change could be of importance for accurate calibration at high-altitude locations. Our results are consistent with previous studies emphasizing the criticality of the accurate CCN calibration for the lower supersaturations.

Restricted access
Nathaniel B. Miller
,
Aronne Merrelli
,
Tristan S. L’Ecuyer
, and
Brian J. Drouin

Abstract

The Polar Radiant Energy in the Far Infrared Experiment (PREFIRE) mission will measure Earth’s emission at wavelengths ranging from 3 to 54 μm. The prelaunch clear-sky retrieval algorithm, evaluated with simulated test data, indicates that PREFIRE measurements will be valuable for retrieving atmospheric water vapor and temperature profiles. Far infrared measurements provide unique retrieval information, indicated by the high ranking of select FIR channels as primary contributors to the total degrees of freedom for signal (DFS). In utilizing all the PREFIRE channels, the average total DFS of 4 test regions ranges from 1.90 to 4.71. The information content increases with higher column water vapor and in the presence of near-surface temperature inversions. Using the DFS profiles for guidance, the retrieval concentrates information into 7 distinct layers to reduce the retrieval uncertainty per layer. Sensitivity tests indicate forward model error due to surface emissivity uncertainty results in about a 9% increase in column water vapor uncertainty. The clear-sky retrieval is sensitive to the presence of undetected ice clouds, especially those with optical depths larger than 0.2. Hence, in addition to a separate PREFIRE cloud mask, optimal estimation retrieval metrics are explored as possible indicators of cloudy scenes.

Restricted access
James N. Moum
,
Daniel L. Rudnick
,
Emily L. Shroyer
,
Kenneth G. Hughes
,
Benjamin D. Reineman
,
Kyle Grindley
,
Jeffrey T. Sherman
,
Pavan Vutukur
,
Craig Van Appledorn
,
Kerry Latham
,
Aurélie J. Moulin
, and
T. M. Shaun Johnston

Abstract

A new autonomous turbulence profiling float has been designed, built, and tested in field trials off Oregon. Flippin’ χSOLO (FχS) employs a SOLO-II buoyancy engine that not only changes but also shifts ballast to move the center of mass to positions on either side of the center of buoyancy, thus causing FχS to flip. FχS is outfitted with a full suite of turbulence sensors—two shear probes, two fast thermistors, and pitot tube, as well as a pressure sensor and three-axis linear accelerometers. FχS descends and ascends with turbulence sensors leading, thereby permitting measurement through the sea surface. The turbulence sensors are housed antipodal from communication antennas so as to eliminate flow disturbance. By flipping at the sea surface, antennas are exposed for communications. The mission of FχS is to provide intensive profiling measurements of the upper ocean from 240 m and through the sea surface, particularly during periods of extreme surface forcing. While surfaced, accelerometers provide estimates of wave height spectra and significant wave height. From 3.5 day field trials, here we evaluate (i) the statistics from two FχS units and our established shipboard profiler, Chameleon, and (ii) FχS-based wave statistics by comparison to a nearby NOAA wave buoy.

Significance Statement

The oceanographic fleet of Argo autonomous profilers yields important data that define the state of the ocean’s interior. Continued deployments over time define the evolution of the ocean’s interior. A significant next step will be to include turbulence measurements on these profilers, leading to estimates of thermodynamic mixing rates that predict future states of the ocean’s interior. An autonomous turbulence profiler that employs the buoyancy engine, mission logic, and remote communication of one particular Argo float is described herein. The Flippin’ χSOLO is an upper-ocean profiler tasked with rapid and continuous profiling of the upper ocean during weather conditions that preclude shipboard profiling and that includes the upper 10 m that is missed by shipboard turbulence profilers.

Free access