<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>HPC | Joseph Mouallem</title><link>https://josephmouallem.github.io/tag/hpc/</link><atom:link href="https://josephmouallem.github.io/tag/hpc/index.xml" rel="self" type="application/rss+xml"/><description>HPC</description><generator>Wowchemy (https://wowchemy.com)</generator><language>en-us</language><lastBuildDate>Fri, 04 Sep 2026 00:00:00 +0000</lastBuildDate><image><url>https://josephmouallem.github.io/media/icon_hu08dff4d70575caa8b25c1fc7498ce3a4_155912_512x512_fill_lanczos_center_3.png</url><title>HPC</title><link>https://josephmouallem.github.io/tag/hpc/</link></image><item><title>Multiple Same-Level and Telescoping Grid Nesting</title><link>https://josephmouallem.github.io/research/grid-nesting/</link><pubDate>Tue, 07 Jun 2022 00:00:00 +0000</pubDate><guid>https://josephmouallem.github.io/research/grid-nesting/</guid><description>&lt;h2 id="motivation">Motivation&lt;/h2>
&lt;p>Multi-scale modeling often requires simulations at many different resolutions. This work shows how to couple coarse and fine domains within a single dynamical core, enabling cost-effective high-resolution forecasts of localized phenomena like hurricanes.&lt;/p>
&lt;h2 id="overview">Overview&lt;/h2>
&lt;p>Two-way &lt;strong>multiple same-level&lt;/strong> and &lt;strong>telescoping&lt;/strong> grid nesting capabilities are
implemented in FV3 using GFDL&amp;rsquo;s Flexible Modeling System (FMS).&lt;/p>
&lt;p>A &lt;em>nest&lt;/em> is an additional grid that zooms in over a region of interest to resolve
the small-scale structures needed for better forecasts of localized weather events
such as severe storms and hurricanes. A &lt;em>telescoping nest&lt;/em> is a nest within a
nest, allowing resolution to be refined progressively over the target region.&lt;/p>
&lt;figure id="figure-multiple-same-level-and-telescoping-nests-on-the-cubed-sphere-nests-can-be-placed-side-by-side-at-the-same-level-or-nested-inside-one-another-to-form-a-hierarchy-of-refinement-levels">
&lt;div class="d-flex justify-content-center">
&lt;div class="w-100" >&lt;img alt="Multiple same-level and telescoping nests on the cubed-sphere. Nests can be placed side by side at the same level, or nested inside one another to form a hierarchy of refinement levels." srcset="
/research/grid-nesting/telescoping-nests_hua1b7fc4ff8abda3c1910775c6304ac83_187348_9acfc143371c1b423814624dd2b2175a.webp 400w,
/research/grid-nesting/telescoping-nests_hua1b7fc4ff8abda3c1910775c6304ac83_187348_37280c2ce296835a2023228183313bbb.webp 760w,
/research/grid-nesting/telescoping-nests_hua1b7fc4ff8abda3c1910775c6304ac83_187348_1200x1200_fit_q100_h2_lanczos_3.webp 1200w"
src="https://josephmouallem.github.io/research/grid-nesting/telescoping-nests_hua1b7fc4ff8abda3c1910775c6304ac83_187348_9acfc143371c1b423814624dd2b2175a.webp"
width="720"
height="384"
loading="lazy" data-zoomable />&lt;/div>
&lt;/div>&lt;figcaption>
Multiple same-level and telescoping nests on the cubed-sphere. Nests can be placed side by side at the same level, or nested inside one another to form a hierarchy of refinement levels.
&lt;/figcaption>&lt;/figure>
&lt;h2 id="progressive-refinement">Progressive refinement&lt;/h2>
&lt;p>Nests can be used in both global and regional domains, and each level of the
hierarchy can refine the parent resolution by an arbitrary factor.&lt;/p>
&lt;figure id="figure-a-telescoping-configuration-refining-a-global-13-km-grid-down-to-43-km-14-km-and-05-km-over-the-region-of-interest">
&lt;div class="d-flex justify-content-center">
&lt;div class="w-100" >&lt;img alt="A telescoping configuration refining a global ~13 km grid down to ~4.3 km, ~1.4 km and ~0.5 km over the region of interest." srcset="
/research/grid-nesting/nest-resolutions_hu640238cec2fdb33698d45f29cd715256_498430_7a5220ea2b65cbcdae69445f39a16b1b.webp 400w,
/research/grid-nesting/nest-resolutions_hu640238cec2fdb33698d45f29cd715256_498430_aa82859842a1b194ddf426aa7f3b0d32.webp 760w,
/research/grid-nesting/nest-resolutions_hu640238cec2fdb33698d45f29cd715256_498430_1200x1200_fit_q100_h2_lanczos_3.webp 1200w"
src="https://josephmouallem.github.io/research/grid-nesting/nest-resolutions_hu640238cec2fdb33698d45f29cd715256_498430_7a5220ea2b65cbcdae69445f39a16b1b.webp"
width="720"
height="629"
loading="lazy" data-zoomable />&lt;/div>
&lt;/div>&lt;figcaption>
A telescoping configuration refining a global ~13 km grid down to ~4.3 km, ~1.4 km and ~0.5 km over the region of interest.
&lt;/figcaption>&lt;/figure>
&lt;h2 id="computational-design">Computational design&lt;/h2>
&lt;p>The nested grids run &lt;strong>concurrently&lt;/strong> on different sets of processors and interact
two-way with their parent grids. This provides more accurate results on both the
nest and the parent, and reduces load imbalance between processors.&lt;/p>
&lt;h2 id="availability">Availability&lt;/h2>
&lt;p>Starting from the FV3 public release of 2021, multiple same-level and telescoping
nests are fully functional and available to the broader scientific community. This
drastically improves overall forecast performance and opens the door to numerous
research possibilities for scientists and meteorologists alike.&lt;/p>
&lt;h2 id="reference">Reference&lt;/h2>
&lt;p>Mouallem, J., Harris, L., and Benson, R.: &lt;em>Multiple same-level and telescoping
nesting in GFDL&amp;rsquo;s dynamical core&lt;/em>, &lt;strong>Geoscientific Model Development&lt;/strong>, 15(11),
4355-4371, 2022.
&lt;a href="https://doi.org/10.5194/gmd-15-4355-2022" target="_blank" rel="noopener">https://doi.org/10.5194/gmd-15-4355-2022&lt;/a>&lt;/p></description></item><item><title>SHiELD-LM4: Coupled Land-Atmosphere Modeling</title><link>https://josephmouallem.github.io/research/shield-lm4/</link><pubDate>Fri, 04 Sep 2026 00:00:00 +0000</pubDate><guid>https://josephmouallem.github.io/research/shield-lm4/</guid><description>&lt;h2 id="what-i-developed">What I developed&lt;/h2>
&lt;ul>
&lt;li>Implicit land-atmosphere coupling between SHiELD and LM4&lt;/li>
&lt;li>Integration of the LM4 land component into the SHiELD framework&lt;/li>
&lt;li>FMS coupling and exchange-grid infrastructure for conservative water and energy fluxes&lt;/li>
&lt;li>High-resolution coupled hydrological simulations&lt;/li>
&lt;li>The Hurricane Helene (2024) case study evaluating hydrological extremes&lt;/li>
&lt;/ul>
&lt;h2 id="motivation">Motivation&lt;/h2>
&lt;p>Land-atmosphere interactions drive weather and climate extremes. This system integrates advanced atmospheric and land processes to capture how soil moisture, vegetation, and runoff feedback on regional weather patterns, advancing forecast skill for hydrological extremes.&lt;/p>
&lt;h2 id="overview">Overview&lt;/h2>
&lt;p>We present a new high-resolution coupled atmosphere-land model, &lt;strong>SHiELD-LM4&lt;/strong>,
which integrates GFDL&amp;rsquo;s advanced atmospheric model (SHiELD) with the Geophysical
Fluid Dynamics Laboratory Land Model (LM4) through the Flexible Modeling System
(FMS) coupler. This coupled system enables accurate representation of
land-atmosphere interactions, including soil moisture feedbacks, runoff
generation, and hydrological extremes.&lt;/p>
&lt;p>The model captures critical processes such as precipitation-driven runoff, soil
water dynamics, and their impacts on atmospheric evolution during extreme weather
events. High-resolution representation is essential for resolving the complex
interactions between atmospheric convection and land surface hydrology.&lt;/p>
&lt;h2 id="coupling-infrastructure">Coupling Infrastructure&lt;/h2>
&lt;p>The SHiELD-LM4 model employs the Flexible Modeling System (FMS) coupler to
facilitate bidirectional exchange between the atmospheric and land components.
The exchange grid ensures accurate conservation of water and energy fluxes at
the atmosphere-land interface.&lt;/p>
&lt;figure id="figure-schematic-of-atmosphere-atm-exchange-grid-xgrid-and-landice-components-showing-multi-level-coupling-infrastructure-and-flux-exchange-pathways">
&lt;div class="d-flex justify-content-center">
&lt;div class="w-100" >&lt;img alt="Schematic of atmosphere (Atm), exchange grid (Xgrid), and land/ice components showing multi-level coupling infrastructure and flux exchange pathways." srcset="
/research/shield-lm4/atm_ice_land_hu2639366593ab23330b2458e23dfe2569_144469_3015ed23ca51d7f2cf62be09b9ae0aa5.webp 400w,
/research/shield-lm4/atm_ice_land_hu2639366593ab23330b2458e23dfe2569_144469_2d5883ee7d72adb7d245ea500a699aae.webp 760w,
/research/shield-lm4/atm_ice_land_hu2639366593ab23330b2458e23dfe2569_144469_1200x1200_fit_q100_h2_lanczos_3.webp 1200w"
src="https://josephmouallem.github.io/research/shield-lm4/atm_ice_land_hu2639366593ab23330b2458e23dfe2569_144469_3015ed23ca51d7f2cf62be09b9ae0aa5.webp"
width="760"
height="386"
loading="lazy" data-zoomable />&lt;/div>
&lt;/div>&lt;figcaption>
Schematic of atmosphere (Atm), exchange grid (Xgrid), and land/ice components showing multi-level coupling infrastructure and flux exchange pathways.
&lt;/figcaption>&lt;/figure>
&lt;h2 id="hurricane-helene-2024-precipitation-and-runoff">Hurricane Helene (2024): Precipitation and Runoff&lt;/h2>
&lt;p>A key application of the coupled SHiELD-LM4 system is realistic simulation of
extreme precipitation and its hydrological consequences during tropical cyclones.
The animation below shows global precipitation and runoff during Hurricane Helene&amp;rsquo;s
landfall, zoomed on the southeastern United States to reveal localized hydrological
response.&lt;/p>
&lt;figure class="video-figure">
&lt;video
class="video-figure-media"
autoplay loop muted playsinline controls
preload="metadata"
poster="/research/shield-lm4/Global_zoomed_precip_runoff_river_poster.jpg">
&lt;source src="https://josephmouallem.github.io/research/shield-lm4/Global_zoomed_precip_runoff_river.mp4" type="video/mp4">
Your browser does not support the video tag.
&lt;/video>
&lt;figcaption>Global precipitation (mm/hr), surface runoff, and river discharge (kg/m³/s) during Hurricane Helene (2024). Zoomed panels show detailed runoff and river flow in the southeastern U.S. during landfall.&lt;/figcaption>
&lt;/figure>
&lt;h2 id="soil-moisture-and-land-surface-response">Soil Moisture and Land Surface Response&lt;/h2>
&lt;p>The coupling captures soil moisture evolution and its feedback to atmospheric
conditions. The animation shows soil liquid water content evolution during an
extreme precipitation event, with time series of observed vs. modeled soil moisture
at multiple locations.&lt;/p>
&lt;figure class="video-figure">
&lt;video
class="video-figure-media"
autoplay loop muted playsinline controls
preload="metadata"
poster="/research/shield-lm4/Runoff_river_helene_26_slow_poster.jpg">
&lt;source src="https://josephmouallem.github.io/research/shield-lm4/Runoff_river_helene_26_slow.mp4" type="video/mp4">
Your browser does not support the video tag.
&lt;/video>
&lt;figcaption>Time series of soil liquid water content (kg/m³) at multiple observation sites during Hurricane Helene, illustrating the rapid soil water response to extreme precipitation and subsequent drainage.&lt;/figcaption>
&lt;/figure>
&lt;h2 id="soil-column-interactions">Soil Column Interactions&lt;/h2>
&lt;p>The detailed representation of soil-atmosphere interactions is illustrated through
the vertical exchange of water and energy between atmospheric columns and land model
soil layers.&lt;/p>
&lt;figure id="figure-time-series-of-soil-liquid-content-kgm-at-four-observation-locations-asheville-buncombe-busick-yancey-boone-watauga-jefferson-ashe-showing-hourly-evolution-during-extreme-precipitation-event">
&lt;div class="d-flex justify-content-center">
&lt;div class="w-100" >&lt;img alt="Time series of soil liquid content (kg/m³) at four observation locations (Asheville, Buncombe; Busick, Yancey; Boone, Watauga; Jefferson, Ashe) showing hourly evolution during extreme precipitation event." srcset="
/research/shield-lm4/soil_water_hu918e0b71ba8b5c34a57c0599d3641ba1_1003597_9779be6a1c02515d815b997235bcfc0d.webp 400w,
/research/shield-lm4/soil_water_hu918e0b71ba8b5c34a57c0599d3641ba1_1003597_4f24afe3ff1a8f5dde1b9a33094e1e26.webp 760w,
/research/shield-lm4/soil_water_hu918e0b71ba8b5c34a57c0599d3641ba1_1003597_1200x1200_fit_q100_h2_lanczos_3.webp 1200w"
src="https://josephmouallem.github.io/research/shield-lm4/soil_water_hu918e0b71ba8b5c34a57c0599d3641ba1_1003597_9779be6a1c02515d815b997235bcfc0d.webp"
width="760"
height="352"
loading="lazy" data-zoomable />&lt;/div>
&lt;/div>&lt;figcaption>
Time series of soil liquid content (kg/m³) at four observation locations (Asheville, Buncombe; Busick, Yancey; Boone, Watauga; Jefferson, Ashe) showing hourly evolution during extreme precipitation event.
&lt;/figcaption>&lt;/figure>
&lt;h2 id="key-results">Key Results&lt;/h2>
&lt;ul>
&lt;li>Two-way land-atmosphere coupling effectively captures soil moisture-precipitation
feedbacks during extreme events.&lt;/li>
&lt;li>Runoff generation and river discharge are accurately simulated at high resolution.&lt;/li>
&lt;li>Soil water dynamics show realistic response to precipitation forcing with
multi-hour memory effects.&lt;/li>
&lt;li>The model demonstrates capability to simulate coupled hydro-atmospheric extremes
with kilometer-scale detail.&lt;/li>
&lt;/ul>
&lt;p>This work extends coupled modeling capabilities to include detailed land surface
hydrology, with implications for weather forecasting, hydrological prediction,
and climate research.&lt;/p>
&lt;h2 id="reference">Reference&lt;/h2>
&lt;p>Mouallem, J., Malyshev, S., Tan, Z., Shevliakova, E., Gao, K., Harris, L.,
Benson, R., Cooke, W., Zadeh, N., and Chilutti, L.: &lt;em>Development of a
high-resolution coupled SHiELD-MOM6-LM4 – Part 2: Model overview, coupling
technique, and evaluation of hydrological extremes during Hurricane Helene&lt;/em>,
&lt;strong>Geoscientific Model Development&lt;/strong> (accepted), 2026.&lt;/p></description></item><item><title>SHiELD-MOM6: High-Resolution Coupled Atmosphere-Ocean Modeling</title><link>https://josephmouallem.github.io/research/shield-mom6/</link><pubDate>Fri, 26 Sep 2025 00:00:00 +0000</pubDate><guid>https://josephmouallem.github.io/research/shield-mom6/</guid><description>&lt;h2 id="what-i-developed">What I developed&lt;/h2>
&lt;ul>
&lt;li>The coupling framework connecting SHiELD, MOM6, and SIS2 through FMS&lt;/li>
&lt;li>Exchange-grid infrastructure for conservative flux exchange between components&lt;/li>
&lt;li>High-resolution coupled atmosphere-ocean-ice model configurations&lt;/li>
&lt;li>Evaluation of hurricane-ocean interaction, including Hurricane Helene (2024)&lt;/li>
&lt;/ul>
&lt;h2 id="motivation">Motivation&lt;/h2>
&lt;p>Air-sea interactions drive storm intensity and ocean response. This coupled system captures two-way feedback between the atmosphere and ocean at kilometer scales, enabling accurate simulations of hurricane-ocean interactions and coastal impacts.&lt;/p>
&lt;h2 id="overview">Overview&lt;/h2>
&lt;p>We present a new high-resolution coupled atmosphere-ocean model, &lt;strong>SHiELD-MOM6&lt;/strong>,
which integrates GFDL&amp;rsquo;s advanced atmospheric model, the System for High-resolution
modeling for Earth-to-Local Domain (SHiELD), the Modular Ocean Model version 6
(MOM6), and the Sea Ice Simulator (SIS2).&lt;/p>
&lt;p>The model leverages the Flexible Modeling System (FMS) coupler and its innovative
exchange grid to enable a robust and scalable two-way interaction between the
atmosphere and ocean. The atmospheric component is built on the non-hydrostatic
Finite-Volume Cubed-Sphere Dynamical Core (FV3) with the latest version of the
SHiELD physics parametrization suite, while the ocean component is the latest
version of MOM, supporting kilometer-scale high-resolution and regional
applications.&lt;/p>
&lt;h2 id="coupling-infrastructure">Coupling infrastructure&lt;/h2>
&lt;p>The SHiELD-MOM6 model employs the Flexible Modeling System (FMS) coupler, which facilitates the exchange of information between the atmospheric and oceanic components. The exchange grid ensures accurate and efficient communication, enabling the two-way interaction necessary for realistic coupled simulations.&lt;/p>
&lt;figure id="figure-schematic-of-a-one-dimensional-exchange-grid-and-communication-map-between-the-atmosphere-and-ice-components-at-different-resolutions-the-red-sides-of-the-arrow-indicate-the-step-where-variables-are-projected-from-the-exchange-grid-the-light-blue-and-mauve-sides-of-the-arrows-represent-the-projection-of-variables-onto-the-exchange-grid-from-the-atmosphere-or-ice-components-respectively">
&lt;div class="d-flex justify-content-center">
&lt;div class="w-100" >&lt;img alt="Schematic of a one-dimensional exchange grid and communication map between the atmosphere and ice components at different resolutions. The red sides of the arrow indicate the step where variables are projected from the exchange grid. The light-blue and mauve sides of the arrows represent the projection of variables onto the exchange grid from the atmosphere or ice components, respectively." srcset="
/research/shield-mom6/atm_ocn_hub83b2c4fddf41751a7522a0e11011fca_108332_de340ceb76921e943989bf309caaadf7.webp 400w,
/research/shield-mom6/atm_ocn_hub83b2c4fddf41751a7522a0e11011fca_108332_c5b0815d18832211dbe6e2e20989e6a8.webp 760w,
/research/shield-mom6/atm_ocn_hub83b2c4fddf41751a7522a0e11011fca_108332_1200x1200_fit_q100_h2_lanczos_3.webp 1200w"
src="https://josephmouallem.github.io/research/shield-mom6/atm_ocn_hub83b2c4fddf41751a7522a0e11011fca_108332_de340ceb76921e943989bf309caaadf7.webp"
width="760"
height="394"
loading="lazy" data-zoomable />&lt;/div>
&lt;/div>&lt;figcaption>
Schematic of a one-dimensional exchange grid and communication map between the atmosphere and ice components at different resolutions. The red sides of the arrow indicate the step where variables are projected from the exchange grid. The light-blue and mauve sides of the arrows represent the projection of variables onto the exchange grid from the atmosphere or ice components, respectively.
&lt;/figcaption>&lt;/figure>
&lt;h2 id="hurricane-helene-2024">Hurricane Helene (2024)&lt;/h2>
&lt;p>Validation is demonstrated through a suite of experiments, including idealized
hurricane simulations and a realistic North Atlantic case study featuring
Hurricane Helene 2024. The animation below shows the simulated sea level pressure
and 10 m winds (left) alongside the sea surface temperature anomaly and ocean
surface currents (right) as the storm crosses the Gulf.&lt;/p>
&lt;figure class="video-figure">
&lt;video
class="video-figure-media"
autoplay loop muted playsinline controls
preload="metadata"
poster="/research/shield-mom6/helene-slp-sst_poster.jpg">
&lt;source src="https://josephmouallem.github.io/research/shield-mom6/helene-slp-sst.mp4" type="video/mp4">
Your browser does not support the video tag.
&lt;/video>
&lt;figcaption>Hurricane Helene (2024): sea level pressure and surface winds (left); sea surface temperature change and ocean currents (right). The cold wake and upwelling behind the storm are captured by the two-way coupling.&lt;/figcaption>
&lt;/figure>
&lt;h2 id="scalability">Scalability&lt;/h2>
&lt;p>Scalability tests have been conducted to evaluate the model&amp;rsquo;s performance on massively parallel computing systems. The results demonstrate that SHiELD-MOM6 maintains high computational efficiency as the number of processors increases, ensuring that high-resolution coupled simulations can be performed within practical timeframes&lt;/p>
&lt;figure id="figure-strong-scaling-a-and-weak-scaling-b-actual-speedupefficiency-red-circles-compared-to-ideal-speedupefficiency-black-squares-as-a-function-of-the-number-of-pes">
&lt;div class="d-flex justify-content-center">
&lt;div class="w-100" >&lt;img alt="Strong scaling (a) and weak scaling (b): actual speedup/efficiency (red circles) compared to ideal speedup/efficiency (black squares) as a function of the number of PEs." srcset="
/research/shield-mom6/scaling_strong_weak_hu3e9c6b6cc29ab68fb53618c677749664_111177_ff62117dc319ace0bd32f4b11cbb4703.webp 400w,
/research/shield-mom6/scaling_strong_weak_hu3e9c6b6cc29ab68fb53618c677749664_111177_6c77f828c2fb2349c44561dddcad13dc.webp 760w,
/research/shield-mom6/scaling_strong_weak_hu3e9c6b6cc29ab68fb53618c677749664_111177_1200x1200_fit_q100_h2_lanczos_3.webp 1200w"
src="https://josephmouallem.github.io/research/shield-mom6/scaling_strong_weak_hu3e9c6b6cc29ab68fb53618c677749664_111177_ff62117dc319ace0bd32f4b11cbb4703.webp"
width="760"
height="374"
loading="lazy" data-zoomable />&lt;/div>
&lt;/div>&lt;figcaption>
Strong scaling (a) and weak scaling (b): actual speedup/efficiency (red circles) compared to ideal speedup/efficiency (black squares) as a function of the number of PEs.
&lt;/figcaption>&lt;/figure>
&lt;h2 id="key-results">Key results&lt;/h2>
&lt;ul>
&lt;li>Air-sea interactions are effectively captured, both in storm intensity and
structure and in the ocean response.&lt;/li>
&lt;li>The coupling reproduces ocean phenomena such as storm-induced upwelling, the
cold wake, and sea level changes.&lt;/li>
&lt;li>Scalability tests confirm the model&amp;rsquo;s computational efficiency on
massively parallel systems.&lt;/li>
&lt;/ul>
&lt;p>This work establishes a unified, modular cornerstone for advancing
high-resolution coupled modeling, with significant implications for weather
forecasting and climate research.&lt;/p>
&lt;h2 id="reference">Reference&lt;/h2>
&lt;p>Mouallem, J., Gao, K., Reichl, B. G., Chilutti, L., Harris, L., Benson, R.,
Zadeh, N., Chen, J., Chen, J.-H., and Zhang, C.: &lt;em>Development of a
high-resolution coupled SHiELD-MOM6 model – Part 1: Model overview, coupling
technique, and validation in a regional setup&lt;/em>, &lt;strong>Geoscientific Model
Development&lt;/strong>, 18(18), 6461-6478, 2025.
&lt;a href="https://doi.org/10.5194/gmd-18-6461-2025" target="_blank" rel="noopener">https://doi.org/10.5194/gmd-18-6461-2025&lt;/a>&lt;/p></description></item><item><title>Development of a high-resolution coupled SHiELD-MOM6 model – Part 1: Model overview, coupling technique, and validation in a regional setup</title><link>https://josephmouallem.github.io/publication/shield-mom6-coupled-model/</link><pubDate>Fri, 26 Sep 2025 00:00:00 +0000</pubDate><guid>https://josephmouallem.github.io/publication/shield-mom6-coupled-model/</guid><description/></item><item><title>Multiple same-level and telescoping nesting in GFDL's dynamical core</title><link>https://josephmouallem.github.io/publication/telescoping-nesting-fv3/</link><pubDate>Tue, 07 Jun 2022 00:00:00 +0000</pubDate><guid>https://josephmouallem.github.io/publication/telescoping-nesting-fv3/</guid><description/></item></channel></rss>