NOAA ProTech Weather

Contract #: 1305M420DNWWA0066

Supports, updates, and plans meteorological, hydrological, and communications capabilities in support of the National Weather Service mission to build a Weather-Ready Nation.

POC: Sheema Lett



GORMAT has been acquired by Axiom Consultants, Inc, an 8(a)-certified, economically disadvantaged small business. The two companies, together, offer an expanded set of capabilities that now include cyber security for the Intel Community.


José Gálvez – NOAA Team Member of the Month, January ‘23

José Gálvez serves as an International Desk Coordinator for the National Centers for Environmental Prediction (NCEP) in College Park, MD. José has demonstrated exceptional dedication and innovation in meeting his international tropical cyclone forecasting and training responsibilities. The NCEP International Desk provides essential decision support services to the United States Agency for International Development (USAID), the National Hurricane Center, the Weather Prediction Center, and various other partners. Although the International Desk is normally a 3-person team, due to unusual circumstances José worked alone during the 2022 Hurricane Season. José rose to the challenge — in the 30-day period ending October 14, he authored over 50 daily rainfall forecasts for threatening systems, including for devastating hurricanes Fiona and Ian. In fact, the San Juan Weather Forecast Office specifically noted the positive impact José had on “understanding the severity of the rainfall forecast associated with Hurricane Fiona.” Despite staffing challenges, during this difficult period José also developed a series of training modules under tight deadlines. In sum, José overcame significant challenges to provide essential information to partners internal and external to NOAA.

Axiom Demonstrates HAFS Cloud Performance on AWS platform

Axiom Demonstrates HAFS Cloud Performance on AWS Platform

Axiom Consultants, Inc., through the AWS Partnership Program, has successfully ported the Unified Forecast System (UFS) Hurricane Analysis and Forecast System (HAFS) to the cloud. This work was undertaken as a proof of concept to understand the cost and effort required to move the UFS Application from its traditional high performance computing environments like NOAA’s on-premises, bare-metal Research and Development High Performance Computing Systems (RDHPCS) to a cloud environment – a transition that potentially breaks down barriers to research and development for many UFS Community contributors outside NOAA. 

We began with a cost assessment for using AWS to run HAFS. We ran a basic HAFS forecast test case to test AWS Parallel Cluster, choosing instance types that fit the needs of the components of the HAFS system (preprocessing, atmospheric forecast, and postprocessing). 

We compared:

  • Intel-based Parallel Cluster configuration to an alternative AMD-based configuration.
  • Used instance types leveraging Intel Skylake-SP processors that had been memory optimized (r5.24xlarge) for memory intensive pre- and post-processing components.
  • We chose compute optimized versions (c5n.18xlarge) with Elastic Fabric Adaptor (EFA) enabled for the forecast component. When running the same experiments with AMD processors, we used Hpc6a.48xlarge instances featuring EFA-enabled 3rd generation AMD EPYC 7003 series processors for all HAFS components. We followed up with a preliminary assessment of containerizing HAFS with Singularity and running the workflow on the Intel- and AMD-configured Parallel Clusters.

Preliminary results:

  • AMD processors speed up pre-processing steps by a factor of 2.6 – 3, with a cost savings factor of 5.5-6.3 over the r5, memory optimized Intel Skylake-SP instances.
  • Comparing the forecasts over 10 instances on HPC6a and c5n.18xlarges clusters, the AMD platform performed 3x faster, for a computational cost savings of 5x that of c5n instances.

Future work:

  • Extend the work to assess cost associated with more complicated HAFS configurations.
  • Port to additional cloud platforms
  • Perform scaling studies for HAFS components
  • Contribute portability changes and container recipes to the UFS Community

We recognized a challenge at NOAA, so we prototyped an innovative solution by partnering with AWS. Now we’ve positioned ourselves to contribute portability changes and container recipes back to the UFS Community and the NWS repository. — “We care about the mission…”


Axiom awarded FAA eFAST IDIQ

Axiom has been awarded FAA eFAST IDIQ under the 8(a) and WOSB track for all 8 Functional


Air Transportation Support (ATS)

Business Administration & Management (BAM)

Research & Development (R&D)

Engineering Services (ES)

Computer/Information Systems Development (CSD)

Computer Systems Support (CSS)

Documentation & Training (D&T)

Maintenance & Repair (M&R)


Axiom is ranked #352 in the Inc5000 list for the fastest growing company in all of US.  We’re #5 in all of Maryland.  Thank you to our outstanding customers, loyal partners, and THE Axiom Crew! Cheers to an incredible journey ahead.

HWT SFE Model Comparisons

Fourth Annual NOAA Small Business Program Awards


AXIOM awarded the Fourth Annual NOAA Small Business Program Awards

RRFS Model FieldsJune 7th, 2022: The Acquisition and Grants Office (AGO) Small Business Office recognizes Axiom Consultants, Inc as the NOAA Small Business of the Year for the fourth annual NOAA Small Business Program awards. 

The Small Business Program Awards recognize small businesses who demonstrate outstanding performance, accomplishment, and a spirit of partnership in support of NOAA’s mission. AGO recognizes the important role that small businesses play in the successful execution of the NOAA mission.

Axiom has been leading the charge in helping NWS answer the questions of whether the NWS could use Cloud computing for multi-processor tasks and how they compare to on premise HPC systems. Axiom’s engineers have not only been able to transition the complex systems to the cloud environment, but the Subject Matter Experts are exceeding all expectations at the leading edge and are well versed in new technologies that are being developed by the vendors (Google, AWS, Azure) and are working with the vendors to take advantage of them to provide the most efficient options to the government. Axiom has also been providing their experts to help train other scientists and engineers to make use of the cloud resources that are available. Through this project they have shown that not only can our modeling systems run on the cloud, but that they are comparable or even better than on prem systems in terms of performance. Axiom’s SMEs have also shown that our modeling systems can run on multiple different types of instances from different cloud vendors. In this project, Axiom has shown the viability of using the cloud by running sustained long forecast experiments through two month long test periods and shown that the cloud can match on prem HPC platforms for developing modeling systems.

HWT SFE Model ComparisonsNOAA’s on premise HPC platforms, while critical for developing the science at NOAA, are limited by their fixed compute capacity. The innovation led by Axiom for this project opens up the possibility for the government to use Cloud resources so that they can expand to use compute resources based on need. One example of this is NOAA finally being able to run 30-year retrospectives for reanalysis for the seasonal to sub-seasonal (S2S) forecast system. This will enable NOAA to fill the gap for data innovation of sub-seasonal forecasts, an emerging area for R&D for advancing and improving accuracy of medium to long range predictions.

Axiom is valued as an industry partner for NCEP/EMC as their SMEs and resources absorbed initial delays in procurement on Cloud services to get the RRFS modeling system migration to the Cloud project back on schedule. This project was delayed when access to AWS cloud compute allocations took longer than expected; therefore, delaying the necessary research and development required prior to the Hazardous Weather Testbed Spring Experiment. Nevertheless, within a short time of getting access to cloud computing services, Axiom was able to set up the modeling system on time for two big summer experiments that were critical to demonstrate the viability of using the cloud as well as helping in assessing the skill of the modeling system. Thanks to Axiom’s Subject Matter Experts and their efforts, the RRFS project has already taken part in two major summer experiments and exceeded expectations for the major winter experiment that will test the capability of the system from end-to-end (data assimilation, forecast, products and verification).