NOAA Technical Memorandum OAR LCI-001

Analysis of OAR Transition of Research and Development (2014-2017)

Ian Kroll

Laura Newcomb

Christopher Moses 

Gary Matlock

NOAA/Laboratories and Cooperative Institutes

Silver Spring, Maryland 

April 2018

noaa NATIONAL OCEANIC AND 

ATMOSPHERIC ADMINISTRATION / Office of Oceanic and Atmospheric Research

https://doi.org/10.7289/V5/TM-OAR-LCI-001 
NOAA Technical Memorandum OAR LCI-001 

Analysis of OAR Transition of Research and Development (2014-2017)

Ian Kroll

Laura Newcomb

Christopher Moses 

Gary Matlock

NOAA/Laboratories and Cooperative Institutes

Silver Spring, Maryland

April 2018

UNITED STATES 

DEPARTMENT OF 

COMMERCE

NATIONAL OCEANIC AND 

ATMOSPHERIC 

ADMINISTRATION

Office of Oceanic and 

Atmospheric Research

Wilbur Ross

Secretary

RDML Tim Gallaudet, Ph. D., 

USN Ret., Acting NOAA

Administrator

Craig McLean

Assistant Administrator

https://doi.org/10.7289/V5/TM-OAR-LCI-001 
ii

NOTICE

This document was prepared as an account of work sponsored by an agency of the 

United States Government. The views and opinions of the authors expressed 

herein do not necessarily state or reflect those of the United States Government or 

any agency or Contractor thereof. Neither the United States Government, nor 

Contractor, nor any of their employees, make any warranty, express or implied, or 

assumes any legal liability or responsibility for the accuracy, completeness, or 

usefulness of any information, product, or process disclosed, or represents that its 

use would not infringe privately owned rights. Mention of a commercial company 

or product does not constitute an endorsement by the National Oceanic and 

Atmospheric Administration Office of Oceanic and Atmospheric Research. Use 

of information from this publication concerning proprietary products or the tests 

of such products for publicity or advertising purposes is not authorized.
iii

Executive Summary

Following the inaugural Technical Report on OAR transitions (Sen 2015), OAR’s office of 

Laboratories and Cooperative Institutes (LCI) compiled an inventory of all research and 

development (R&D) that had been transitioned to application, operation, or commercialization 

(R2X) between August 2014 and July 2017. Utilizing the methods set forth in the inaugural 

report, submissions were categorized based on function, output, application, recipient type, 

number of recipients, and strategic goal. This report tracks changes in the understanding and 

reporting of transition within the OAR research portfolio between the two sampling periods as 

well as utilizes additional data to explore new metrics to track OAR transition over time (e.g., 

rate of transition, Readiness Levels). 

During this sampling period, 71% of projects (101 submissions of 143) were consistent with the 

definition of transitioned R&D, with 56% of submitted projects fitting the “Technology 

Transfer” functional classification and 15% of submissions fitting the “Education and Outreach” 

function classification. This is a large increase in reported transitions, as the 2015 report noted 

very few submissions that actually met the definition of transition (39%; 96 submissions of 245). 

The increase in proportion of projects deemed transition and the decrease in overall reported 

projects (perceived transition projects) indicates that the understanding of transition within the 

OAR community has greatly increased in recent years. 

While the percentage of submissions correctly identified as transitions greatly improved, some 

gaps in understanding did persist. Activities that were misidentified as transitions primarily fell 

into two categories: routine observations that produce data and transfers with no identified 

recipient. The production of data that is considered an operational service or the performance of 

product maintenance is not, by definition, a successful transition. Additionally, several 

submissions did not include a specific recipient. While this could be a reporting error, it is also 

indicative of a lack of understanding that true transitions must contain a specified recipient, even 

in cases where the public is the ultimate recipient. 

Since the inaugural report, OAR (and on an agency-level, NOAA) has bolstered its commitment 

to transition and developed several resources and tools to aid in the understanding of transition: 

1) the report itself, as it provides several key definitions and examples of what does and does not 

constitute a transition activity; 2) the NOAA Administrative Order on Research and 

Development Transitions (NAO 216-105B) and its associated handbook which provide an 

updated definition of transition and recommend the use of transition plans at Readiness Level 

(RL) 4 and above; 3) the NOAA Research and Development Database (NRDD) which can aid in 

the tracking of projects through RLs and transitions; and 4) the forthcoming OAR circular that 

addresses proper transition planning and approval protocol. As the majority of OAR projects fall 

between RL 2 and RL 6 (Fig. 1), it is important to encourage consistent understanding of 

transitions and transition planning within early stages of R&D. 
iv

Figure ES-1. The distribution of OAR Projects by Readiness Levels (RLs) in 2017 based on 

NRDD data. The majority of projects indeed are in the lower RLs of R&D, however, this may be 

a manifestation of reporting bias driven by errors in RL assignments that skew towards RL 2. In 

the box-whisker plot on the right, the upper (lower) bound of the box represents the 25th (75th) 

percentile, such that 50% of the samples occur in the range of the box. Note: RL does not 

necessarily define whether a project is “transition ready” since projects can transition to 

application without moving through every RL along the way.
v

Table of Contents

Executive Summary vi

List of Figures vi

List of Acronyms vii

1 Introduction 1

2 Methodology 1

3 Results 2

3.1 Type of Function 3

3.2 Type of Output 4

3.3 Number and Type of Recipient 4

3.4 Type of Application 6

3.5 Strategic Goal 7

3.6 Function and Output 8

3.7 Function and Strategic Goal 9

3.8 Function and Recipient Type/Number 10

3.9 A Broader Picture of the OAR R&D Portfolio 11

4 Conclusions 15

4.1 Improved Understanding of Transitions Over Time 15

4.2 Transition Is Balanced Across NOAA’s Research Priorities 15

4.3 Misconceptions of Transition Persist 16

5 Recommendations 17

5.1 Utilize NOAA and OAR Resources to Increase Understanding and Success of 

Transition 17

5.2 Use of NRDD to Track Transitions at a Project Level 17

References 19

Appendix A: Transition Definitions 20

Appendix B: Definition of Classifications 22

Appendix C: Project Descriptions 30
vi

List of Figures

Figure ES-1. Distribution of OAR projects by Readiness Levels (RLs) in 2017 iv

Figure 3.1. Percentage of submissions categorized within each Function type 3

Figure 3.2. Percentage of submissions categorized within each Output type. 4

Figure 3.3. Percentage of submissions categorized within each Number of Recipients 

based on identified transition recipient. 5

Figure 3.4. Percentage of submissions categorized within each Recipient Type based on 

identified transition recipient. 6

Figure 3.5. Percentage of submissions categorized within each application type. 7

Figure 3.6. Percentage of submissions categorized within each Strategic Goal, as 

identified in the NOAA Five-Year Research and Development Plan for 2013-2017. 8

Figure 3.7. Sankey diagram displays connections between submission Function and 

Output type. 9

Figure 3.8. Sankey diagram displays connections between submission Function and 

associated Strategic Goal. 10

Figure 3.9. Sankey diagram displays connections between FMC submissions, Function, 

and Recipient Type. 11

Figure 3.10. Number of reported transition per year a) overall and b) by FMC. Figure 

does not include 17 transition projects that were submitted with no year. 13

Figure 3.11. The median Readiness Level (RL) of each FMC for projects reported in 

2017 as a function of the number of reported transitions. 14
vii

List of Acronyms

Abbreviation Description 

AOML Atlantic Oceanographic and Meteorological Laboratory 

ARL Air Resources Lab

CPO Climate Program Office

DAA/S Deputy Assistant Administrator for Science

DoC Department of Congress

ESRL CSD Earth Systems Research Laboratory Chemical Science Division

ESRL DO Earth Systems Research Laboratory Director’s Office

ESRL GMD Earth Systems Research Laboratory Global Modeling Division

ESRL GSD Earth Systems Research Laboratory Global Systems Division

ESRL PSD Earth Systems Research Laboratory Physical Science Division

FMC Financial Management Center

GFDL Geophysical Fluid Dynamics Laboratory

GLERL Great Lakes Environmental Research Laboratory 

JTTI Joint Technology Transfer Initiative

LCI Laboratories and Cooperative Institutes

MAPP Modeling, Analysis, Predictions, and Projections

NAO NOAA Administrative Order

NRDD NOAA Research and Development Database

NSSL National Severe Storms Laboratory

NWS National Weather Service

OAR Oceanic and Atmospheric Research

OER Office of Exploration and Research

OWAQ Office of Water and Air Quality

PEML Pacific Marine Environmental Laboratory 

R&D Research and Development

RL(s) Readiness Level(s)

RTAP Research Transition Assistance Program

R2X Research to Operations, Applications, Commercialization (etc.)

SG Sea Grant

UAS Unmanned Aircraft Systems
1

1 Introduction

Efficient transition of R&D to application, operation, commercialization, and other uses (R2X) 

showcases the accountability, utility, and stewardship of NOAA to the public (Rood 2018). As 

such, transition has become increasingly important to NOAA leadership, appearing in several 

publications (e.g., Green 2006), NOAA policies, and R&D Plans. Additionally, increased R2X 

has been identified by Department of Commerce (DoC) and the Administration as a priority for 

government-funded R&D. As the only research-specific Line Office of NOAA, OAR aims to 

become a leader in transition planning, reporting, execution, and other transition-related 

activities.

OAR has already begun implementing several of the recommendations made from the inaugural 

transition report. The 2015 report recommends four criteria to identify which outputs can be 

labeled as transition: 1) the output is the product of research or development, 2) the application is 

particular and verifiable, 3) the activity is focused on translation and adaptation, and 4) the 

output is a productive system or component thereof (Sen 2015). These criteria form the basis for 

the understanding of transition used in this report and within the OAR community. The inaugural 

report also highlights the utility of transition plans for enabling a more consistent and replicable 

transition process which could also improve monitoring and assessment. Furthermore, the report 

recommends the use of RLs for defining the readiness of all R&D activities. NOAA 

Administrative Order (NAO) 216-105B forms the agency policy that guides the use of RLs and 

the development of transition plans. The use of RLs within OAR has increased as a result of the 

NAO and with the inception of the NOAA Research and Development Database, however, there 

continue to be some challenges with the determination and reporting of RLs.

Between the data collection for the 2015 report and this present report, NOAA internally 

socialized the concepts surrounding R2X through policy development and implementation, 

workshops, and funding opportunities with distinct elements of R2X. This report provides an 

update on the state of R&D transition within OAR,that also evaluates (in part) the impact of the 

past 3 years of effort within NOAA to advance transition of R&D. Furthermore, it explores new 

methodologies to track transitions within the line office and establishes guidelines for continued 

assessment and improvement of the OAR transition process.

2 Methodology

In August 2017, OAR leadership requested all OAR senior managers provide a detailed 

inventory of OAR research and development (R&D) that had been successfully transitioned 

during the period of August 1, 2014-July 31, 2017. Information was compiled by OAR’s Office 
2

of Laboratories and Cooperative Institutes (LCI) to create an inventory and provide analysis of 

OAR’s transition capabilities. 

Following the methodology of the inaugural report on OAR Transitions (Sen 2015), a request to 

complete a spreadsheet was sent to each Laboratory and Program Office director. The 

spreadsheet contained columns for project name, thing transitions, purpose of transition, from 

where (organization, point of contact, and email), to where (organization, point of contact, 

email), and date completed (month and year) for each R&D projects that had successfully 

transitioned to applications, operations, commercialization, and other uses (R2X) within the 

timeframe. Transition projects were required to be discrete, discernable, and explainable.

LCI received 142 submissions from 13 of the 16 OAR Labs and Programs queried. Projects were 

categorized following the qualitative coding/labeling system set forth by Sen (2015; categories 

described in Appendix 2). Categories were assigned independently by two LCI staff (Ian Kroll 

and Laura Newcomb). Any disagreements were discussed and brought to a third LCI staff 

member (Christopher Moses) for resolution. Categorization was validated by the OAR Deputy 

Assistant Administrator for Science (DAA/S; Gary Matlock). 

After classification was complete, a tally of reported transitions was taken for all labels within 

their respective categories. Data were analyzed independently and compared with the data 

presented in the inaugural Transition Report (Sen 2015). 

The number of transitions per FMC (Financial Management Center) were counted from 2013 -

2017 based on the data collected in Sen (2015) and the submissions in this report. Seventeen 

projects did not list a date of transition, and were therefore excluded from this analysis. 

To assess whether Readiness Levels (RLs) of FMCs’ ongoing projects could be used as a 

predictor of how many transitions they might generate over a sample period, RLs from each 

FMC were averaged across projects submitted to the NOAA Research and Development 

Database (NRDD; a web-based repository for R&D projects developed and funded by NOAA) 

during the 2017 collection window (January-November 2017). The number of transitions in 2017 

were then plotted against mean RL for each FMC to assess any potential relationships between 

the mean RL and number of transitions that could be expected. 

3 Results

This section provides a summary of how submissions were categorized; potential relationships 

between project functions, outputs, applications, strategic goals, and recipients; and how results 

from this sampling period compare with those from the inaugural report. Following Sen (2015), 

shades of orange indicate categories that are consistent with the definition of transition, whereas 

shades of blue indicate categories that are consistent with the definition of research and/or 
3

development. More information on categories (including definitions) can be found in Appendix 

2. 

Unlike the 2015 report, preliminary analysis showed little difference in category distribution 

when removing projects that did not qualify as transition. Therefore, figures display data for all

submissions (i.e., actual transitions plus projects still in the R&D phase), not just those deemed 

transitions. Function, Output, and Application Types (Fig. 2, Fig.3, Fig. 6, respectively) all 

displayed large increases in transition-associated categories when compared with the inaugural 

report (See Sen 2015 for original data). 

3.1 Type of Function

Based on the assessment of the information submitted by OAR program and lab officials, 

projects were categorized into activities from the inaugural report and the OAR strategic plan. 

Only two categories indicated transition: Extension and Outreach and Technology Transfer. All 

other functions were considered either Research or Development. 

Most (71%) of the projects initially reported for this time period were determined to be 

transitions (Fig. 2). The change between 2015 and 2018 is primarily due to an increase in 

projects with a Transition: Technology Transfer function (27% to 56%) and decrease in projects 

with a Research: Observations and Data function (35% to 6%). Fewer projects were associated 

with Research and Development categories in 2014-2017, except for Research: Models and 

Assessment and Development: Emerging Technologies. 
4

Figure 3.1. Percentage of submissions categorized within each Function type.

3.2 Type of Output

Consistent with the definition of transition (see Appendix 1), output that is indicative of data 

collection, operation and maintenance, or products that are made available to anyone to use 

through publication were not assigned transition-related outputs (e.g., original data, synthesized 

products, etc.). However, some science products were counted as a transition (i.e., Science: 

Interpreted Product T) as they functioned to translate discipline-specific knowledge into 

application-specific knowledge. 

The majority of outputs (69%) were associated with a Technology-related product and, overall, 

79% of submissions identified outputs that were indicative of transition (Fig. 3). The largest 

category of output transitioned was within the Model Algorithm category (33%). Of the R&Dassociated outputs (not transitions), Science: Original Data was the most frequently reported. 

Figure 3.2. Percentage of submissions categorized within each Output type. 

3.3 Number and Type of Recipient

While the type of recipient of a transition does not often determine whether a project is 

categorized as a transition, transitions do require a clearly identifiable and specific recipient who 
5

have specific requirements for specific applications. Submissions that did not identify the 

recipient or denoted an infinite number of recipients (e.g., “the public”) were not categorized as 

transitions. 

Most proposed transitions were associated with a single (59%) or several (24%) recipients (Fig. 

4), which is consistent with transition. Projects associated with infinite recipients, which are 

generally not associated with the definition of transition (See Appendix 1), represented a 

substantial (14%) number of submissions. A new “Cannot Determine” category was included for 

cases where the “transitioned to” category was unclear.

Several transitions were associated with having a Public, NOAA- Federal (Not OAR), recipient 

(Fig. 5). An additional category, “Multiple Users,” was added in this analysis to incorporate 

those submissions that identified several recipients and multiple levels (e.g., Public-FederalNOAA, Public-State/Local/Tribal, and Academic). The Multiple Users category boasted the 

second-highest frequency within recipient types, consisting of 22% of submissions.

Figure 3.3. Percentage of submissions categorized within each Number of Recipients based on 

identified transition recipient. 
6

Figure 3.4. Percentage of submissions categorized within each Recipient Type based on 

identified transition recipient. 

3.4 Type of Application

The application of a project does not inherently determine whether it is a transition. However, a 

specific application must be identified. Additionally, research is not an application, as it does not 

create direct value beyond improved scientific understanding. 

Most proposed transitions could be associated with an application; however, 26% were 

associated with additional research, not a true application (either operational or quasioperational; as defined in Appendix 1; Fig. 6). Environmental Intelligence was the most 

commonly-associated application type for submissions (49%). Research, which is generally not 

considered a transition application, comprised 26% of submissions. No submissions were 

associated with Policy, Legislation, and Law. We did not include a “Cannot Determine” 

category, as submission application types were easily discernible from project descriptions.
7

Figure 3.5. Percentage of submissions categorized within each application type. 

3.5 Strategic Goal

How a project aligns with a specific OAR Strategic Goals does not accurately predict whether it 

is a transition. In fact, a diversity in strategic goals helps contribute to a balanced research 

portfolio. Strategic Goals for this study differ than those for the inaugural study: they were rewritten and expanded for the NOAA Five-Year Research and Development Plan for 2013-2017 

(Appendix 2) since it was reasonable that projects started under that plan were beginning to 

transition.

Submissions were most frequently associated with the Integrated Environmental Modeling 

System goal (26%) and were least frequently associated with the Resilient Coastal Communities 

and Stakeholder Engagement goals (both at 8%; Fig. 7). Submissions displayed a relatively even

distribution among Strategic Goals. 
8

Figure 3.6. Percentage of submissions categorized within each Strategic Goal, as identified in 

the NOAA Five-Year Research and Development Plan for 2013-2017.

3.6 Function and Output

While the inaugural report only began to examine potential connectivity between categories, this 

report highlights the frequency with which specific functions result in specific outputs. Potential 

linkages between function and output may help reinforce the definition of transition to the OAR 

community. 

Function type and output displayed high instances of connectivity, with the majority of 

transition-based functions feeding into technology-related outputs (Fig. 8). Submissions that 

were categorized within a development phase function led to every type of output except for 

Science: Tacit Expertise and Technology: Standards Protocols. The majority of submissions with 

a Research function resulted in a Science output. 
9

Figure 3.7. Sankey diagram displays connections between submission Function and Output type.

3.7 Function and Strategic Goal

Strategic goal does not inherently determine whether a project is deemed transition or not. 

However, it is beneficial, when assessing the robustness of the OAR research enterprise. 

Linkages between function type and strategic goal show a balanced research portfolio among 

OAR offices and programs; submissions categorized as Transition: Technology Transfer 

contributed to every strategic goal (Fig. 9). However, roughly 30% of Transition: Technology 

Transfer submissions were linked to the Integrated Environmental Modeling System Goals. 

Stakeholder Engagement was the least frequently assigned strategic goal, with the majority of its 

submissions also labeled as Transition: Technology Transfer. 
10

Figure 3.8. Sankey diagram displays connections between submission Function and associated 

Strategic Goal.

3.8 Function and Recipient Type/Number

Exploring the connection between function and recipient of submissions can helps identify 

strengths within each FMC and may serve as a valuable resource management support tool. 

All 13 FMCs that submitted transitions included projects that could be categorized as 

“Transition: Technology Transfer,” with ESRL GSD submitting the highest proportion of 

Transition projects (Fig. 9). Transitions were also distributed to all of the recipient types. 

Functions that were associated with Research were most commonly received by the Public-
11

Federal-NOAA category of recipient.

Figure 3.9. Sankey diagram displays connections between FMC submissions, Function, and 

Recipient Type. 

3.9 A Broader Picture of the OAR R&D Portfolio

Additional analysis in this report was used to create a new metric for tracking transition over 

time: transition rate (number of transitions per year). By contextualizing OAR Financial 

Management Center (FMC)-specific transition rates within the overall transition rate, FMC 

progress in the understanding of transition can be monitored and assessed. Additionally, potential 

reporting errors can be identified. Readiness Level (RL) data for ongoing projects within each 

FMC was extracted from the NRDD to assess potential relationships between RL and number of 

transitions. 
12

Overall transition rates, number of reported transitions per year, declined from 2013-2016 but 

began to increase in 2017 (Fig. 11a). To explore this trend, transition rates for individual FMCs

were examined (Fig. 11b). While the rates of transition for some FMCs were consistent over 

time (e.g., ESRL GSD, GLERL, OER, ARL), others followed a more uneven model of transition 

with many transitions in one year followed by very few in other years (e.g., SG, AOML). Sea 

Grant (SG) appeared to have the largest difference between years and was likely the driving 

force behind the peak (and subsequent decline) of transitions in 2013.

To explore the possible link between project RLs and transition, a model was constructed to 

compare RLs of ongoing FMC projects and their reported number of transitions (Fig. 12). As RL 

increased from 3 to 6, the number of reported transitions also increased. Beyond RL 6, RL was 

not a predictor for the number of transitions an FMC will produce (r2

= 0.3, p < 0.001). The 

shaded area highlights where transition is most influenced by RL, and therefore where resources 

applied to advancing RLs may be most effective.
13

Figure 3.10. Number of reported transition per year a) overall and b) by FMC. Figure does not 

include 17 transition projects that were submitted with no year.
14

Figure 3.11. The median Readiness Level (RL) of each FMC for projects reported in 2017 as a 

function of the number of reported transitions. 
15

4 Conclusions

4.1 Improved Understanding of Transitions Over Time

Since the inaugural report, accuracy in transition reporting has nearly doubled (39% to 71% of 

submissions correctly identified as transition) with higher proportions of both submission 

function and output types that are indicative of transition. This analysis suggests that the 

understanding of transition within OAR has greatly improved over time. However, it does not 

answer another important question: do more transitions occur as our understanding of transition 

improves? 

This report created a transition rate metric (number of transitions per year) and assessed 

transition rates for FMCs and OAR as a whole from 2013-2017 (Fig. 11). While specific FMC 

transition rates can drive overall trends (e.g., Sea Grant in 2013), transition among most FMCs 

remained relatively consistent over time. Overall transition rates may provide insight into the 

impacts of policy and legislation on OAR’s mission. Transition rates have the potential to not 

only become a pivotal management decision support tool, but also better our understanding of 

how internal and external factors can affect the transition process.

This report additionally utilized RL data from the NRDD to characterize the relationship 

between RL and number of transitions (Fig. 12). As projects move from RL 3 to RL 6, the 

number of reported transitions increases rapidly; however, after RL 6, RL is less indicative of the 

number of transitions produced. This trend could indicate that resources aimed at bringing RL 7-

8 projects to RL (9) may not actually affect the number of transitions produced. However, 

resources directed at projects between RL 3-6 can increase the number of transitions (up to a 

point). Two novel programs within OAR have attempted to capitalize on this concept: the Joint 

Technology Transfer Initiative (JTTI) which serves to increase transitions to the National 

Weather Service (NWS), and the Research Transition Assistance Program (RTAP) which serves 

to increase transitions more broadly. These programs have both demonstrated the promise of 

success, however, they are in their infancy and future funding is uncertain. Applying the metrics 

introduced in this report to evaluate future OAR transitions will provide key insights into the 

need for and benefits of these programs. 

4.2 Transition Is Balanced Across NOAA’s Research Priorities

The strategic goals used in this report were updated to align with the seven R&D priorities 

identified by the NOAA 2013-2017 Five Year R&D Plan. As a result, the distribution of 

strategic goals in this study should not be compared to that of the past study. However, 

submissions displayed a breadth of diversity among the R&D priorities (Fig. 7), with transitionrelated submissions forming a relatively even distribution among strategic goals (Fig. 9). It is 

interesting to note that Stakeholder Engagement is the least represented goal, especially when 

considering how few projects categorized in “Transition: Extension and Outreach” were linked 

to engagement. This is likely an artifact of selecting only one strategic goal for each project 
16

when most projects impact multiple strategic goals. A vibrant and balanced research portfolio 

highlights the functionality of the transition program within OAR and its commitment to the 

NOAA mission. 

The majority of projects categorized within the “Transition: Technology Transfer” function were 

linked to the Integrated Environmental Modeling System strategic goal. While this pattern may 

be indicative of the focus of many of OAR’s programs and labs, it may also help us understand 

some reporting nuances. As RLs were originally written to meet technological standards 

(Mankins 2009) and most definitions of transition involve technology as examples, models, 

software, and other technological projects often have the most well-defined transitions. Projects 

that involve education or social science are often less clear and transition can be an ongoing 

process. This report, along with its predecessor and the other OAR and NOAA transition 

resources, can be utilized to increase the understanding of non-technological transitions. 

4.3 Misconceptions of Transition Persist

Sen (2015) outlined several misconceptions surrounding what type of activities qualify as 

transition. Primarily, the report noted issues with submitted transitions that did not qualify as a 

discrete output of R&D, contain an application beyond R&D, mature or evolve from an original 

product, or run an operational or quasi-operational service. While this report did find that OAR’s 

understanding of transition has greatly improved between sampling times, some misconceptions 

still prevail.

As with the original report, many observation-related submissions were incorrectly identified as 

transitions. Most routine data collection and observation are generally components of the 

operation and maintenance of the original transition and not in themselves transitions. 

Transitions also require specific applications and identified recipients-- posting reports on a 

general-use website or publishing within an academic (or other) journal inherently does not 

target a specific recipient and therefore, is likely not a transition. Furthermore, transitions require 

the product to have actually been transitioned. Projects in development were routinely 

misidentified as transitions even though there was no record of the product being delivered to the 

transition partner. Technologies that are still being evaluated and tested within the office it 

originated are not yet transitions.

The use of transition definitions, transition plans, and RLs can alleviate a majority of the 

misconceptions identified in this report. Transition definitions (see Appendix 1) provide the basis 

for understanding transitions and have been reviewed and approved by OAR leadership for 

distribution. Transition plans not only identify a specific recipient and application of the project, 

but also identify any associated operational service or maintenance activities associated with the 

transition to avoid miscategorization. The use of designated RLs (see Appendix 1) ensures that 
17

projects can be consistently and appropriately identified along the path from R&D to transition, 

reducing the number of projects within development stages that are reported as transitions.

The self-reporting and classification processes developed by Sen (2015) in the inaugural report 

introduces occasional categorization difficulties. Some FMCs did not submit any transitions to 

the inventory. While this is unlikely due to a lack of transitioned projects, it does minimize the 

ability to fully capture how transition understanding, execution, and reporting has evolved within 

OAR. Additionally, some submitted projects contained descriptions that were unclear or 

descriptions that were broad enough to fit into multiple categories. In these instances, general 

consensus was reached after review by three LCI employees (I. Kroll, L. Newcomb, C. Moses). 

There was some difficulty categorizing transitions that were neither inherently technological nor 

extension and outreach (e.g, an interpreted product that was transitioned to congress to aid in 

policy formation). Therefore, it may be helpful to update the “Technology Transfer: Extension 

and Outreach” category to “Technology Transfer: Extension, Outreach, and Assessment.”

5 Recommendations

5.1 Utilize NOAA and OAR Resources to Increase Understanding and Success of Transition 

Despite vast improvement in the understanding of transition within OAR and the increased 

availability of resources, several misclassifications persisted among submissions. NAO 216-

105b, its handbook, the inaugural report, and this report provide supporting documentation and 

monitoring strategies for transition, transition planning, and RLs. These definitions are 

paramount to OAR’s transition success and will only become more useful in the future. For 

example, the use of correct RLs help OAR leadership track transitions, identify resource needs, 

and improve overall transition success. Additionally, a forthcoming OAR Circular on transition 

will require the use of transition plans for all OAR projects RL4 and above. The Circular is 

intended to streamline the transition process and increase accountability to the public. However, 

compliance is predicated on the understanding of the transition planning progress. 

This analysis also demonstrates how advancing a project from RL 3 through RL 6 can directly 

impact its likelihood to transition. OAR currently offers some (albeit limited) funding 

opportunities that target these RLs through the Modeling, Analysis, Predictions and Projections 

(MAPP) program, Joint Technology Transfer Initiative (JTTI) and Research Transition 

Acceleration Program (RTAP) programs. Optimizing these resources may increase the number 

of transitions occurring and strengthen the OAR research enterprise. Continued analysis of these 

programs and highlighted success may also help increase the resources available to them. 

5.2 Use of NRDD to Track Transitions at a Project Level

The NOAA Research and Development Database (NRDD) is a web-based repository for R&D 

projects developed and funded by NOAA. The NRDD has the potential to streamline and 
18

improve transition tracking, execution, and overall accountability. Project outcomes, RLs, and 

transition plans can all be included in NRDD submissions, making this information readily 

accessible to the NOAA community. 

Accurate and timely reporting of project updates within NRDD would also increase the ability to 

assess the progress of the OAR (and NOAA) research enterprise. This report relied on selfreporting from OAR program managers and lab directors. While most FMCs provided transition 

information, some did not, limiting the conclusions and recommendations that could be made. As 

transition tracking is a valuable resource management and support tool, having access to the 

complete data set (as should be reported in the NRDD), would only increase the utility of reports 

such as these. Furthermore, if all data were reported in the NRDD, additional data calls would be 

less frequent and likely only request verification of or updates to existing information. 
19

References

Green, D. S. (2006). Transitioning NOAA moored buoy systems from research to operations. In 

OCEANS, 1-3. Institute of Electrical and Electronics Engineers.

Mankins, J. C. (2009). Technology readiness assessments: A retrospective. Acta Astronautica,

65(9-10), 1216-1223.

National Oceanic and Atmospheric Administration Research Council. Research and 

Development at NOAA: Five-year research and development plan 2013-2017. United States 

Department of Commerce. 2013. 

National Oceanic and Atmospheric Administration. NOAA Administrator Order 216-105B: 

Policy on research and development transitions. United States Department of Commerce. 

October 2016.

Rood, S. A. (2018). Government Laboratory Technology Transfer: Process and Impact: Process 

and Impact. Routledge Press.

Sen, A. (2015). What Does “Transition” Mean? A Qualitative Analysis of Reported Transitions 

at OAR. NOAA Technical Memorandum OAR PPE-5. 
20

Appendix A: Transition Definitions

Application: The use of NOAA R&D output as a system, process, product, service, or tool. 

Applications in NOAA include information products, assessments, and tools used in decisionmaking and resource management (NAO 216-105B § 2.01).

Development: In this tech memo, Development is used inclusively to span the stages of 

Development and Demonstration defined as:

a. Development: The systematic work, drawing on knowledge gained from research and 

practical experience and producing additional knowledge, that is directed to producing 

new products or processes, or to improving existing products or processes (OECD, 2015). 

(NAO 216-105B § 2.06)

b. Demonstration: Activities that are part of R&D and are intended to prove or to test 

whether a technology or method does, in fact, work as expected. (NAO 216-105B § 2.04)

Research: Research can be classified as basic research or applied research. (NAO 216-105B § 

2.12)

a. Basic Research: Basic research is experimental or theoretical work undertaken primarily 

to acquire new knowledge of the underlying foundations of phenomena and observable 

facts, without any particular application or use in view. Basic research can be oriented or 

directed towards some broad fields of general interest, with the explicit goal of a range of 

future applications (OECD, 2015).

b. Applied Research: Applied research is the original investigation undertaken in order to 

acquire new knowledge. It is, however, directed primarily towards a specific, practical 

aim or objective. Applied research is undertaken either to determine possible uses for the 

findings of basic research or to determine new methods or ways of achieving specific and 

predetermined objectives (OECD, 2015).

Transition: The transfer of an R&D output to a capability ready for an operation, application, 

commercial product or service, or other use. (NAO 216-105B § 2.14)

Readiness Levels (RLs): A systematic project metric or measurement system that supports 

assessments of the maturity of R&D projects for transition from research to operation, 

application, commercial product or service, or other use and allows the consistent comparison of 

maturity between different types of R&D projects. (Note: NOAA's RL's are similar to 

Technology Readiness Levels developed by NASA (Mankins, 1995) and embody the same 

concept for quantifying the maturity of research). A program may include projects at different 

RLs depending on the goals of each project. Inventions may be generated at any RL. NOAA’s 

Policy on Research and Development Transitions can be found in NAO 216-105B.

There are nine RLs as follows:
21

RL 1: Basic research, experimental or theoretical work undertaken primarily to acquire 

new knowledge of the underlying foundations of phenomena and observable facts, 

without any particular application or use in view. Basic research can be oriented or 

directed towards some broad fields of general interest, with the explicit goal of a range of 

future applications (OECD, 2015);

RL 2: Applied research, original investigation undertaken in order to acquire new 

knowledge. It is, however, directed primarily towards a specific, practical aim or 

objective. Applied research is undertaken either to determine possible uses for the 

findings of basic research or to determine new methods or ways of achieving specific and 

predetermined objectives (OECD, 2015);

RL 3: Proof-of-concept for system, process, product, service or tool; this can be 

considered an early phase of experimental development; feasibility studies may be 

included;

RL 4: Successful evaluation of system, subsystem, process, product, service or tool in 

laboratory or other experimental environment; this can be considered an intermediate 

phase of development;

RL 5: Successful evaluation of system, subsystem process, product, service or tool in 

relevant environment through testing and prototyping; this can be considered the final 

stage of development before demonstration begins;

RL 6: Demonstration of prototype system, subsystem, process, product, service or tool in 

relevant or test environment (potential demonstrated);

RL 7: Prototype system, process, product, service or tool demonstrated in an operational 

or other relevant environment (functionality demonstrated in near-real world 

environment; subsystem components fully integrated into system).

RL 8: Finalized system, process, product, service or tool tested, and shown to operate or 

function as expected within user's environment; user training and documentation 

completed; operator or user approval given;

RL 9: System, process, product, service or tool deployed and used routinely.
22

Appendix B: Definition of Classifications

Type of Activity

Research. “Systematic study directed toward fuller scientific knowledge or understanding of the 

subject studied” (NSF/OMB definition). Per the OAR Strategic Plan, the following are products 

of research activities:

Research: Observations and Data. Collecting data on the Earth system for use in models 

and studies. This includes analyzing observations and developing insights based on those 

observations, as well as procuring and maintaining observing systems, quality control of 

data, and archive and access.

Research: Models and Experiments. Models codify our understanding

of a system in terms of the relationships among its elements, both

qualitatively and quantitatively. Scientific experiments test hypotheses

about these relationships as the basis for creating, refining, and rethinking

models. This combines lab and field work with coding experimental

algorithms and running simulations.

Research: Studies and Assessments. Synthesizing scientific knowledge of Earth systems 

into tools for decision making and future research, often using observational data, model 

output, experimental results, and other research as source material.

Development. “Systematic use of the knowledge or understanding gained from research, directed 

toward the production of useful materials, devices, and systems or methods, including design, 

development, and improvement of prototypes and new processes. It excludes quality control, 

routine product testing, and production” (NSF/OMB definition). Per the OAR Strategic Plan, the 

following are products of development activities:

Development: Predictions and Projections. Applying advanced models of Earth systems 

to make predictions about the future (using present-day conditions) or projections (using 

plausible economic development scenarios). They are pre-operational products intended 

for use in regular services. They require models, data, advanced computing architectures 

and techniques, and the publication and interpretation of information.

Development: Emerging Technologies. Creating new or significantly improved 

technology for observation and modeling systems, as well as tools for information 

delivery and stakeholder engagement. Typically, this involves the development or 

application of new hardware or software, or the integration of technologies into systems.
23

Transition. “Transition is the transfer of knowledge or technology from a research or 

development setting to an operational setting. Transition occurs in two phases: 1) Demonstration 

(e.g., the use of test-beds to confirm operational usability or demonstration using rapid 

prototyping), which is part of R&D; and 2) Deployment (e.g., the integration of new people, 

equipment, or techniques into an operational environment), which is part of operations” (NAO 

216-105B). Per the OAR Strategic Plan, the following are products of transition activities:

Transition: Extension and Outreach. Working directly with stakeholders on the ground to 

understand their needs, conduct research that meets those needs, and translate results so 

that they are meaningful and actionable. Ensuring that the results of R&D are accessible 

to and understood by stakeholders that might use them.

Transition: Technology Transfer. Working with end-users to integrate mature 

technologies (and associated expertise) into larger systems, either in NOAA operations or 

partner applications, via testbeds, patents, etc.

Type of Output

The “things transitioned” were understood as outputs and fell into the broad categories of either 

science or technology. Within these categories, definitions of specific output types are below. 

The first three (original data, synthesized product, and interpreted product) are taken from 

NOAA Information Quality Act Guidelines, maintained by the NOAA CIO. The other 

definitions were constructed per web searches of relevant terms, which was deemed to be 

accurate enough for these general concepts.

Science Outputs. These are defined as data, information, or knowledge (either codified or tacit) --

they allow us to understand things we would not have otherwise understood.

Science: Original Data. Original Data are data in their most basic useful form. These are 

data from individual times and locations that have not been summarized or processed to 

higher levels of analysis. While these data are often derived from other direct 

measurements (e.g., spectral signatures from a chemical analyzer, electronic signals from 

current meters), they represent properties of the environment. These data can be 

disseminated in both real time and retrospectively. Examples of original data include 

buoy data, survey data (e.g., living marine resource and hydrographic surveys), biological 

and chemical properties, weather observations, and satellite data.

Science: Synthesized Product. Synthesized Products are those that have been developed 

through analysis of original data. This includes analysis through statistical methods; 
24

model interpolations, extrapolations, and simulations; and combinations of multiple sets 

of original data. While some scientific evaluation and judgment is needed, the methods of 

analysis are well documented and relatively routine. Examples of synthesized products 

include summaries of fisheries landings statistics, weather statistics, model outputs, data 

display through Geographical Information System techniques, and satellite-derived maps.

Science: Interpreted Product. Interpreted Products are those that have been developed 

through interpretation of original data and synthesized products. In many cases, this 

information incorporates additional contextual and/or normative data, standards, or 

information that puts original data and synthesized products into larger spatial, temporal, 

or issue contexts. This information is subject to scientific interpretation, evaluation, and 

judgment. Examples of interpreted products include journal articles, scientific papers, 

technical reports, and production of and contributions to integrated assessments.

Science: Tacit Expertise. Tacit knowledge (as opposed to formal, codified or explicit 

knowledge) is the kind of knowledge that is difficult to transfer to another person by 

means of writing it down or verbalizing it. For example, stating to someone that London 

is in the United Kingdom is a piece of explicit knowledge that can be written down, 

transmitted, and understood by a recipient. However, the ability to speak a language, use 

algebra, or design and use complex equipment requires all sorts of knowledge that is not 

always known explicitly, even by expert practitioners, and which is difficult or 

impossible to explicitly transfer to other users.

Technology Outputs. These are defined as automated processes or artifacts (hardware or 

software) -- they allow us to do things we would not have otherwise done.

Technology: Model, Algorithm. A mathematical model is a description of a system using 

mathematical concepts and language. A model may help to explain a system and to study 

the effects of different components, and to make predictions about behavior. 

Mathematical models include dynamical systems, statistical models, differential

equations, or game theoretic models. An algorithm is a step-by-step procedure for 

calculations. Algorithms are used for calculation, data processing, and automated 

reasoning.

Technology: Hardware, Equipment. The artifacts of technology. Material objects 

designed, engineered, and built to serve a purpose. Any physical item -- i.e., a tool or 

device -- that can be used to achieve a goal, especially if the item is not consumed in the 

process. In NOAA's case, this includes computers, sensors, observation platforms. It does 

not include software, data, or information. A piece of hardware or equipment is a discrete 

item, and may be incorporated as a component within a larger system or service.
25

Technology: System, Service. A system is a set of interacting or interdependent 

components forming an integrated whole or a set of elements (often called 'components') 

and relationships which are different from relationships of the set or its elements to other 

elements or sets. A Service is a set of actions or solutions that are put in place or are 

performed to provide a repeatable and consistent set of outcomes, deliverables, and 

performance for people, organizations, and systems that represent consumers or 

beneficiaries of such results.

Technology: Standards, Protocols. A technical standard is an established norm or 

requirement in regard to technical systems. It is usually a formal document that 

establishes uniform engineering or technical criteria, methods, processes and practices. A 

technical standard can also be a controlled artifact or similar formal means used for 

calibration. In the natural sciences a protocol is a predefined written procedural method in 

the design and implementation of experiments. Protocols are written whenever it is 

desirable to standardize a laboratory method to ensure successful replication of results by 

others in the same laboratory or by other laboratories.

Number of Recipients

Recipient number for the thing transitioned were captured in rough orders of magnitude: a single 

recipient, several recipients, or a very large (essentially infinite) number of recipients. This 

categorization was necessary to understand how widely or narrowly applicable the output is 

relative to applications.

Single. One party named in submission.

Several. A discrete number of parties named in submission.

Infinite. Recipient is understood as "the public" or "the scientific community".

Unknown/Cannot Determine. Data provided in submission did not provide a clear 

number of recipients. 

Type of Recipient

Recipient type was bundled within three sectors: public, private and academic. The

former two sectors were subdivided into more particular categories (e.g. within the

public sector, OAR vs NOAA beyond OAR vs other federal agencies). While recipient

type and the application type (see below) are related, in the course of the analysis, it

became necessary to distinguish between them.
26

Public - Federal - OAR. Any organization within Oceanic and Atmospheric Research (i.e. 

Laboratories or Program Offices).

Public - Federal - NOAA (not OAR). Any Line (or Staff) Office at the National

Oceanic and Atmospheric Administration besides Oceanic and Atmospheric

Research.

Public - Federal (not NOAA). Any Federal agency or body besides the National

Oceanic and Atmospheric Administration.

Public - State/Local/Tribal. An organization of a state, regional, municipal, or

tribal government (e.g., a local port authority).

Public - International. An organization of a foreign government or multinational

organization (e.g. the United Nations).

Private - For Profit. Organizations that operate for profit, including corporations

that are either privately held or publicly traded. This also includes start-ups as defined as 

small, recently founded organizations that operate for profit. Start-ups did comprise their 

own category in the previous analysis but that distinction was not warranted in this 

analysis. 

Private - Not For Profit. Non-governmental organizations that aim for public

welfare outcomes, not profits.

Academic. Colleges, universities, and other institutions focused on research

and education.

Multiple Users. A new category was included to incorporate submissions that were 

targeted for use by multiple users of different recipient types (e.g., a model that is 

transitioned to Academic, Federal, and state agencies).

Type of Application

Applications were the immediate application of the output, rather than downstream or ultimate 

application. “Research” was used to label those instances where the immediate use of the output 

was follow-on research, but is not understood to be an application, per se, as it does not create 

social or economic value beyond improved scientific understanding.

Application: Environmental Intelligence. Information measured, gathered,
27

compiled, exploited, analyzed and disseminated to characterize the current state

and/or predict the future state of the environment at a given location and time.

Application: Resource Management. Environmental resource management is the 

management of the interaction and impact of human societies on the environment. It aims 

to ensure that ecosystem services are protected and maintained for future human 

generations, and also maintain ecosystem integrity through considering ethical, 

economic, and scientific (ecological) variables.

Application: Policy, Legislation, Law. This includes the crafting and influencing of 

policy at the local, state, tribal, federal, or international levels. Policy can be the 

proceedings and directives of legislatures or executives or judiciaries. Applications may 

be the creation, implementation or the debate over public law.

Application: Education, Learning. This is the imparting of knowledge and understanding. 

Education and learning applications include, but are not limited to K-12 education. They 

can also include higher education or “lifelong learning” of adults. This may be lecturing, 

activity based learning, or the production of educational materials.

Application: Emergency Management. Disaster management (or emergency 

management) is the managerial function charged with creating the framework within 

which communities reduce vulnerability to hazards and cope with disasters. Disaster 

management does not avert or eliminate the threats, instead it focuses on creating plans to 

decrease the impact of disasters.

Application: Commerce. Commerce is the whole system of an economy that constitutes 

an environment for business. It can also be defined as a component of business which 

includes all activities, functions and institutions involved in transferring goods from 

producers to consumers. 

Research. “Systematic study directed toward fuller scientific knowledge or understanding 

of the subject studied” (NSF/OMB definition). Note that, research is included as an 

“application” for ease of binning only; follow-on research may be the use of a NOAA 

research output, but it is not an application in the sense of a mature capability that 

provides social/economic value beyond that of improved understanding.

Strategic Goal 

OAR focuses on NOAA’s outcome-oriented goals (per the Next Generation Strategic Plan) for 

climate, weather, oceans and coasts, which are themselves derived from the NOAA vision. 
28

Those goals, which have been updated in this version to reflect the most recent NOAA 5-Year 

Research and Development Plan and the OAR Strategic Plan, are as listed below. 

Climate Adaptation and Mitigation: An informed society anticipating and

responding to climate and its impacts.

● What is the state of the climate system and how is it evolving?

● What causes climate variability and change on a global to regional scales?

● What improvements in global and regional climate predictions and projections are 

possible?

● How can NOAA best inform and support the Nation’s efforts to adapt to the 

impacts of climate variability and change?

Weather-Ready Nation: Society is prepared for and responds to weather-related

Events.

● How can we improve forecasts, warnings, and decision support for high-impact 

weather events?

● How does climate affect seasonal weather and extreme weather events?

● How can we improve space weather warnings?

● How can we improve forecasts for freshwater resource management?

Healthy Oceans: Marine fisheries, habitats, and biodiversity are sustained within

healthy and productive ecosystems.

● How do environmental changes affect marine ecosystems?

● How is the chemistry of our ocean changing and what are the effects?

● What exists in the unexplored areas of our oceans?

● How can emerging technologies improve ecosystem-based management?

● How can we ensure aquaculture is sustainable?

Resilient Coastal Communities and Economies: Coastal and Great Lakes

communities are environmentally and economically sustainable.

● What is the value of coastal ecosystems?

● How do coastal species and ecosystems respond to habitat loss, degradation and 

change?

● How do we ensure that growing maritime commerce stays safe and sustainable?

● How do we reduce the economic and ecological impacts of degraded water 

quality?

● How is the Arctic affected by expanding industry and commerce?
29

Stakeholder Engagement

● How can we support informed public response to changing environmental 

conditions?

● How can we improve the way scientific information and its uncertainty are 

communicated?

Accurate and Reliable Data from Sustained and Integrated Earth Observing Systems

● What is the best observing system to meet NOAA’s mission?

● How can we best use current and emerging environmental data?

● How can we improve the way we manage data?

An Integrated Environmental Modeling System

● How can modeling be best integrated and improved with respect to skill, 

efficiency, and adaptability?

● What information technology developments can help NOAA improve quantitative 

predictions?
30

Appendix C: Project Descriptions 

Reported Transition Projects from August 2014-July 2017

FMC Project Name Description Transitioned From Transitioned To Year

OER Exploration of deep 

ocean via untethered 

free vehicles

An untethered oceanographic instrument platform 

for use in ocean depths 1000m+ 

OER Grantee: 

University of Puerto 

Rico

Oceanographic 

community 

2017

OER Installation of new 

high speed VSAT to 

demonstrate 

innovations in 

telepresence/data 

transmission

Funding for a new state of the art high speed Very 

Small Aperture Terminal (VSAT) to the Global 

Foundation for Ocean Exploration to install aboard 

NOAA Ship Okeanos Explorer

OAR OER Global 

Foundation of 

Ocean 

Exploration

2016

OER Ambient Sound at 

Full Ocean Depth

The instrument is a unique deep-ocean mooring 

that is comprised of specially designed Virtovex 

glass spheres, dual acoustic releases, double-yoke 

stainless-steel frame sensor package housing, and 

topped with a satellite beacon mast. The buoyancy 

of the package is designed to achieve optimum 

descent/ascent rates of 0.5-1.0 m s-1. The pressure 

sensor and ocean hydrophone are uniquely 

designed to withstand the extreme hydrostatic 

pressures at these ocean depths. 

OER is developing this technology with industry, 

federal and academic partners.

OER Grantee: 

PMEL

Applications to 

NMFS, NOS and 

OAR/OER 

observing 

requirements

2015

OER Real Time Video 

Annotation system

Novel method of collecting real time annotations 

during ROV dives

NOAA OER Ocean Network 

Canada

2017
31

FMC Project Name Description Transitioned From Transitioned To Year

AOML HFIP (Hurricane 

Forecast 

Improvement 

Project) 

Observations

HWRF V11.0: HWRF upgrade includes 

implementation of cycling hybrid EnKF-3DVAR 

Data Assimilation System with real-time NOAAP3 TDR, dropsonde, and flight-level inner core data 

assimilation

AOML NWS/NCEP/

EMC and DTC

2017

AOML HFIP (Hurricane 

Forecast 

Improvement 

Project) 

Observations

2017 Basin-HWRF with high resolution (18-6-2 

km) 2-way interactive moving nests and 61 vertical 

levels for Cat 4 storms, ocean coupling to 

MPIPOM in ATL and EPAC, plus operational 

initialization

AOML NWS/NCEP/

EMC and DTC

2017

AOML Gulf of Mexico 

ocean indices in 

support of bluefin 

tuna assessment and 

management

An ocean indicator developed to monitor and track 

areas in the Gulf of Mexico with favorable 

conditions during the spring for the occurrence of 

bluefin tuna larvae (Thunnus thynnus), the 

BFT_Index

AOML

CPO NMME (North 

America MultiModel Ensemble)

First year of data from the NMME operational and 

research platform

NWS/NCEP 2017

OWAQ Upgrades to the 

Operational Monte 

Carlo Wind Speed 

Probability Program

Replacing the linear forecast interpolation scheme 

with a more precise spline fit scheme, and applying 

a bias correction to the radii-CLIPER (Climatology 

and Persistence) model used by the MC model to 

improve the accuracy of the wind speed 

probabilities for exceptionally small or large 

tropical cyclones

CIRA/CSU, 

NESDIS

NHC 2017

OWAQ Improving the 

GFDL/GFDN 

Operational Tropical 

Cyclone Models at 

Upgrade the GFDL and GFDN ocean model 

resolution, physics, domain configuration, and 

U. of Rhode Island, 

OAR/GFDL

EMC 2017
32

FMC Project Name Description Transitioned From Transitioned To Year

NOAA/NCEP and 

Navy/FNMOC

initialization using URI's newly developed 

MPIPOM-TC ocean model

OWAQ Kalmanfilter/Analog 

Predictions of 

Surface PM2.5: 

Research to 

Operations

A post-processing technique to further address the 

issue of bias correcting intermittent forest fires 

called the Continuous Iterative Persistence (CIP) 

which can be applied to either the new Analog 

(AN) or Kalman-Filter Analog (KFAN) bias 

correction schemes

U. Colorado/ 

CIRES,OAR/ESRL/

PSD

EMC 2017

OWAQ Post-Processing of 

CMAQ Air Quality 

Predictions: 

Research to 

Operations

The CIP technique tests indicate that it improves 

the overall variability of the post-processed 

forecasts, improves forecast skill for highamplitude events such as forecast fires and dust 

storms while also reducing RMSE and increasing 

Correlation

U. Colorado 

/CIRES,OAR/ESRL/

PSD

EMC 2017

ARL New READY web 

site: HRRR and 

SREF

The High Resolution Rapid Refresh (HRRR) model 

was added to all HYSPLIT and meteorological 

display programs. The HRRR contains sigma level 

forecast data every hour from forecast hours 0 to 15 

on a 3 km 1799 x 1059 grid covering the United 

States and Southern Canada

ARL HYSPLIT user 

community

2016

AOML Global Vibrio Risk 

fields

Series of algorithms describing the risk of vibriorelated waterborne infections that comprise daily, 

short-term forecast and cumulative fields and are 

distributed using Web Services within a Serviceoriented Architecture (SOA) framework

AOML Gulf of Mexico 

Near-Real-Time 

System performs analysis of the ocean state based 

on daily assimilation of remotely sensed 
33

FMC Project Name Description Transitioned From Transitioned To Year

Analysis/Forecast 

System 

observations (altimetry and SST), with 7 day 

forecast

AOML Development and 

validation of the 

HYCOM-HWRF 

coupled TC 

prediction system 

(RTAP) 

Project will implement three-way atmospherewave-ocean coupling and upgrade physics 

parameterizations that govern the coupled TC 

system

AOML

AOML Juvenile Spotted 

Seatrout

Performance 

Measure for 

Everglades 

Restoration

An ecological model to be used in the assessment 

and evaluation of Everglades Restoration and the 

individual projects being undertaken to complete 

Everglades Restoration

AOML US Army Corps 

of Engineers, 

South Florida 

Water 

Management 

District

2017

AOML Development of new 

advanced nature run 

for hurricane OSSEs

Improved hurricane OSSE system. RL9. 

Transitioned to QOSAP to be used by multiple line 

offices and agencies

AOML transitioned to 

QOSAP to be 

used by multiple 

line offices and 

agencies

2017

ARL Update CMAQ 5.0.2 Aerosol science upgraded from the Community 

Multiscale Air Quality Model (CMAQ) to 

CMAQ5.0.2 for CONUS ; Compiled to NAM's last 

upgrade

ARL NWS/NCEP/

EMC and NCO

2017

CPO CPO RPD Climate 

Process Teams

Results from 3 Climate Process Teams enhancing 

NOAA model transitioned to climate model 

improvements

GFDL NOAA 

laboratories and 

operational 

centers; broad 

2016
34

FMC Project Name Description Transitioned From Transitioned To Year

climate research 

community;

CPO Week 3-4 Outlook Transition of Week-3-4 prediction tool to NWS 

operations based on MAPP-CTB project outcomes

NWS/CPC; 

Weather and 

Climate 

Operational 

Supercomputing 

System

2017

AOML Development of 

NOAA Seasonal 

Severe Weather 

(SSW) outlook for 

the US

A Seasonal Severe Weather (SSW) outlook was 

developed to expand and complement the current 

SSW outlooks at NOAA beyond seven days

AOML

NSSL Radar Product 

Improvement -

Coherency Based 

Thresholding

Technique was developed to mitigate radar 

sensitivity loss after the dual-polarization upgrade

CIMMS/NSSL NWS/ROC 2014

NSSL Radar Product 

Improvement -

Radial-by-Radial 

Noise Estimator

Technique was developed to improve the 

measurement of noise power, which contaminates 

the desired weather signals

CIMMS/NSSL NWS/ROC 2014

NSSL Radar Product 

Improvement - Hail

Size Discrimination 

Algorithm (HSDA)

Technique was developed to provide forecasters 

guidance in identifying regions within a storm that 

may be more likely to harbor large (between 1"-2" 

in diameter) and/or giant (>2" in diameter) sized 

hail based upon polarimetric radar data

CIMMS/NSSL NWS/ROC 2016

OWAQ Improvements in 

Statistical Tropical 

Extended range climatology and persistence 

(CLIPER) model for track and intensity

CIRA/CSU, 

NESDIS

NHC 2015
35

FMC Project Name Description Transitioned From Transitioned To Year

Cyclone Forecast 

Models

OWAQ Improving the 

operational TC 

models at 

NOAA/NCEP and 

Navy/FNMOC

Implemented a unified GFDL/GFDN version 

control framework and implemented wave 

coupling into GFDL/GFDN for future operations, 

and coupled GFDL-WAVEWATCHIIIMPIPOMTC framework

U. of Rhode Island, 

OAR/GFDL

EMC 2015

ESRL 

GSD

WRF-Chem v3.9 

model

Weather Research and Forecast (WRF)-Chemistry 

model integrates atmospheric chemistry and 

dynamics together

OAR/ESRL/GSD Public release for 

other met 

agencies to use

2017

SG Assisting Coastal 

Communities Plan 

and Manage Their 

Working 

Waterfronts and 

Waterways: The 

Boating and 

Waterway Planning 

Program

Provision of science-based methods for 

comprehensive waterway use planning, 

management, and policymaking by facilitating 

interagency collaboration; sponsoring community 

forums; implementing regional and statewide 

conferences and workshops; and assisting 

government agencies in evaluating environmental 

and social impacts. 

Florida Sea Grant Florida 

Department of 

Environmental 

Protection and 

Wildlife 

Conservation 

Commission 

2015

ESRL 

GMD

Standards - WMO 

Global Scales

NOAA ESRL GMD is the World Meteorological 

Organization (WMO), Global Atmosphere Watch 

(GAW) Central Calibration Laboratory (CCL) for: 

CO2, CH4, N2O, SF6, and CO

OAR/ESRL/Global 

Monitoring Division

e.g., Max Planck 

Institute for 

Biogeochemistry

2017

ESRL 

GMD

Standards - NOAA 

Scales

NOAA ESRL GMD maintains calibration scales 

for 21 minor gases (outside of the CCL)

OAR/ESRL/Global 

Monitoring Division

Atmospheric 

scientists and 

chemical 

oceanographers 

around the world 
36

FMC Project Name Description Transitioned From Transitioned To Year

ESRL 

GMD

Standards - Dobson 

Regional Standards

Calibration of JMA and BoM Dobson Regional 

Standards in Boulder

OAR/ESRL/Global 

Monitoring Division

WMO partners 

and other partners 

and scientists 

investigating total 

ozone.

ESRL 

GMD

Standards - Central 

UV Calibration 

Facility

Highly accurate and long-term repeatable 

calibrations and characterizations of UV 

monitoring instruments.

OAR/ESRL/Global 

Monitoring Division

USDA/Colorado 

State 

University/UV-B 

Monitoring and 

Research 

Program 

(UVMRP)

AOML Adaptable Bottom 

Instrument 

Information Shuttle 

System (ABIISS)

A system that will significantly reduce ship time 

needs, and hence NOAA costs, by transmitting data 

from ocean bottom moored instruments back to 

land via satellite

AOML

ESRL 

GMD

GMD Contributions 

to State of the 

Climate Report

Global atmospheric composition products 

supported by GMD are analyzed, assessed, and 

contributed to the annual State of the Climate 

Report

GMD General public, 

policy-makers, as 

well as research, 

modeling, and 

assessment 

communities

2017

ARL Update READY 

website: NARR

The North American Regional Reanalysis (NARR) 

32 km horizontal resolution grid was added to 

READY. This data set has data available on 22 

pressure levels every 3 hours over North America 

from 1979 to 2014

ARL HYSPLIT user 

community

2015
37

FMC Project Name Description Transitioned From Transitioned To Year

OER Okeanos Explorer 

Biological and 

Geological Sample 

Repositories

Biological and geological samples collected on 

Okeanos Explorer expeditions are now transferred 

to public repositories for public access

OAR OER Smithsonian 

Institution's 

National Museum 

of Natural 

History, Oregon 

State University's 

Marine and 

Geology 

Repository, 

Ocean Genome 

Legacy Center

2016

ESRL 

GMD

Annual Greenhouse 

Gas Index

The NOAA Annual Greenhouse Gas Index (AGGI) 

measures the commitment society has already made 

to living in a changing climate

ESRL GMD EPA, USGCRP, 

WMO Global 

Atmosphere 

Watch

2017

ESRL 

GMD

Global Carbon 

Dioxide Record

Long-term trend of CO2 from all remote marine 

boundary layer sites in NOAA's global monitoring 

network

ESRL GMD EPA, USGCRP, 

WMO Global 

Atmosphere 

Watch

2017

AOML An interoperable 

viewer in support of 

AOML HRD field 

activities

A tool to provide a single point of access to a great 

variety of products from remote sensing, models 

and insitu observations

AOML

AOML Transmission of 

underwater glider 

temperature and 

salinity profile data 

in real-time for 

tropical cyclone 

Data from observations, approximately 7,000 

profiles of temperature and salinity per year, have 

been inserted in real-time into the GTS with the 

objective of providing upper ocean temperature and 

salinity data in regions highly undersampled

AOML NOS, GTS 2017
38

FMC Project Name Description Transitioned From Transitioned To Year

intensification 

studies and forecasts

CPO CFS Reanalysis and 

Reforecast Project

The completion of the public archive of the 

reforecasts and reanalysis from the Climate 

Forecast System (CFSv2), the current NOAA 

NCEP operational system for weekly, monthly and 

seasonal forecasts

NESDIS/NCEI 2016

ESRL 

GSD

GPS-Meteorology 

(GPS-Met)

Global Positioning System (GPS) Met is a groundbased water vapor observing system which uses 

GPS radio signal delay measurements to derive 

Integrated Precipitable Water (IPW)

OAR/ESRL/GSD NWS/Office of 

observations/Prog

ram Management 

Branch

2016

UAS Hurricane glider 

operations in 

Atlantic Ocean

Real-time profile data NOAA/AOML NWS, EMC, 

GTS

2014

CPO CPO MAPP NMME Release of the NMME dataset, peer-reviewed 

publications, and a report to inform the related 

NWS/NCEP FY15 AOP milestone

GFDL NOAA 

laboratories and 

operational 

centers; broad 

climate 

prediction 

research 

community

2016

OER Nautical chart 

improvements in 

poorly mapped areas 

from Okeanos 

Explorer expeditions

New system to transfer high resolution multibeam 

sonar bathymetric survey data collected by OER 

during NOAA Okeanos Explorer expeditions to the 

Office of Coast Survey 

NOAA OER Office of Coast 

Survey, 

Hydrographic 

Survey Division

2015
39

FMC Project Name Description Transitioned From Transitioned To Year

ESRL 

GMD

AirCore Atmospheric sampling system that samples the 

atmosphere and preserves a profile of the trace gas 

of interest

OAR/ESRL/Global 

Monitoring Division

Southwest 

Research 

Institute, and 

several research 

organizations 

worldwide

AOML US Argo Data 

Assembly Center 

implemented 

processing system 

for deep Argo floats

Real-time Ocean Observation Data necessary to 

accommodate the deep APEX floats

AOML Global Argo Data 

Assembly Center 

at 

NAVOCEANO 

and IFREMER; 

and GTS

2015

AOML Ecological Forecasts 

for Coral Reefs

Initial development of R2A Transition Plan for 

NOS and/or NMFS: Ecological Forecasting for 

Coral Reefs

AOML NCCOS

ESRL 

GMD

CarbonTracker -

Near Real time

CarbonTracker is a CO2 measurement and 

modeling system developed by NOAA to keep 

track of sources (emissions to the atmosphere) and 

sinks (removal from the atmosphere) of carbon 

dioxide around the world

OAR/ESRL/Global 

Monitoring Division

Act-America 2017

ESRL 

GSD

F2C-ACC Compiler 

(GSD's GPU 

compiler)

Evaluations of Cray and PGI commercial Fortran 

OpenACC compilers for Massively Parallel Fine 

Grain (MPFG) processors

OAR/ESRL/GSD NVIDIA, PGI, 

Cray

2014

AOML Geo-HSS OSSE 

required by 

Congress under 

HR353

Report summarizing the impact of a 

proposed constellation of Geo-HSS satellites in 

weather forecasting

AOML Will be 

transitioned to 

Congress 

2017
40

FMC Project Name Description Transitioned From Transitioned To Year

AOML Observation System 

Simulation 

Experiments (OSSE) 

on TROPICS

Report describing the expected impact of different 

numbers of mirco-satellites in the TROPICS 

mission to improve weather forecast

AOML NASA's 

TROPICS Project

2017

AOML OSSE on Cyclone 

Global Navigation 

Satellite System 

(CYGNSS)

Report describing the expected impact of the 

CYGNSS mission in tropical cyclone analysis and 

forecasts

AOML NASA's 

CYGNSS 

Science Team

2017

CPO CPO MAPP 

Coupled Model 

Intercomparison 

Project (CMIP) 

Comparisons

Finalize an OAR technical report on CMIP3 vs 

CMIP5 comparisons for North America

GFDL National Climate 

Assessment

2016

AOML Global Navigation 

Satellite System 

(GNSS) RO OSSE 

required by 

Congress under 

HR353

Report summarizing the results of the impact of a 

GNSS RO constellation in NOAA's weather 

forecast models

AOML US Congress 2017

AOML Additional GNSS 

RO OSSE for NWS

Report with the impact in global weather forecast 

skill expected from the COSMIC-2 mission

AOML NWS 2017

CPO CPO MAPP Earth 

System Modeling 

Coordination

Complete a study to assess status of state-of-the-art 

climate/ Earth system modeling at NOAA

GFDL, ESRL NOAA 2016

CPO Standardized 

Precipitation Index

Develop Standardized Precipitation Index (SPI) 

based on global monitoring tool

NWS/NCEP/CPC 2017
41

FMC Project Name Description Transitioned From Transitioned To Year

CPO State of the Climate 

Report

Characterize the changing state of the ocean in the 

annual State of the Climate report

Public 2017

CPO Annual Arctic 

Report Card

The Arctic Report Card considers a range of 

environmental observations throughout the Arctic, 

and is updated annually

Public 2017

AOML SOCAT, Surface 

Ocean Carbon Atlas

Automated Surface water CO2 analyses obtained 

on ships and buoys from NOAA and international 

investigators are uniformly quality controlled and 

collated to provide annual authoritative surface 

water CO2maps

AOML, PMEL SOCAT 

CPO CPO MAPP 

National Integrated 

Drought Information 

System (NIDIS)

Produce an assessment report on the understanding 

and predictability of the 2011-2014 California 

Drought in support of NIDIS

ESRL General public, 

water managers, 

researchers and 

operational 

personnel

2015

CPO U.S. Climate 

Resilience Toolkit 

(CRT)

U.S. Climate Resilience Toolkit Launch OCM, NWS, 

NESDIS

Decision-makers 

in communities, 

businesses, and 

federal, state, 

local and tribal 

governments

2015

CPO CPO COD State of 

the Climate Report

Global ocean data and products supported by CPO 

and OAR are analyzed, assessed, and contributed to 

the annual State of the Climate Report

PMEL, AOML, 

ESRL, GFDL

General public, 

policy-makers, as 

well as research, 

modeling, and 

assessment 

communities

2016
42

FMC Project Name Description Transitioned From Transitioned To Year

CPO CPO Earth System 

Science (ESS) 

Atlantic Meridonal 

Overturning 

Circulation (AOMC)

AMOC Science Report to increase understanding 

of the current state of AMOC science, identify 

scientific gaps, and develop plans to fill those gaps

AOML Policymakers 

(international, 

federal, state, 

local and tribal), 

general public, 

research 

community

2016

CPO Regional Integrated 

Sciences and 

Assessments (RISA)

Publish RISA book that showcases lessons learned 

from the history of the RISA program

Public/users 2017

CPO CPO COD Arctic 

Report Card

Arctic ocean, atmospheric, and ecosystem data and 

products supported by CPO and OAR are analyzed, 

assessed, and contributed to the annual State of the 

Climate Report

PMEL, GLERL and 

others

General public, 

policy-makers, as 

well as research, 

modeling, and 

assessment 

communities

2015

CPO CPO CASD 

Vulnerability

Drawing from existing data and peer-reviewed 

research, the Colorado Climate Change 

Vulnerability Study summarizes the key challenges 

facing seven sectors: ecosystems, water, 

agriculture, energy, transportation, outdoor 

recreation and tourism, and public health

State of Colorado 

resource 

managers and 

policy makers

2016

SG Monitoring Bluff 

Stability

This project developed new bluff monitoring 

instruments, and in addition, recorded a sudden 

bluff failure

Wisconsin Sea 

Grant, and 

collaboration with 

engineers in UWMadison’s 

Geoscience 

department

Wisconsin 

Coastal Atlas, 

Property owners 
43

FMC Project Name Description Transitioned From Transitioned To Year

SG Effects of 

Aquaculture 

Practices on Vibrio 

spp. in the Eastern 

Oyster, Crassostrea

virginica: Test of 

Fouling Control 

Practices.

A Wisconsin Sea Grant-funded project developed 

and tested new instrumentation that has the 

potential to predict within minutes the timing of 

bluff failure along the Great Lakes shoreline, 

informing future monitoring and protecting people 

and property

MS-AL Sea Grant Co-PIs and 

NOAA; Public 

2014

AOML Mandatory Ship 

Reporting System -

MSR

The information collected by the MSR 

database yields data on ship traffic volume, routes, 

ports of call, and whale sighting locations, and will 

assist in tailoring any necessary future ship strike 

mitigation measures

AOML U.S. Coast Guard 

and NMFS

2017

ESRL 

GSD

Science On a Sphere 

Installations

Considered R2U for public education and outreach, 

Science On a Sphere (SOS) is a room-sized global 

display system that uses computers and video 

projectors to display planetary data on a six-foot 

diameter sphere to help illustrate earth system 

science to people of all ages

OAR/ESRL/GSD SOS customers; 

SOS Users 

Collaborative 

Network

2016

AOML Capacity Building 

for Molecular 

Source Tracking 

(MST) Analysis in 

CNMI Bureau of 

Environmental Coa

stal Quality

Molecular diagnostic capability provided to US 

North Marina Islands (CNMI) government to 

protect coral and human health from microbial 

contamination. 

AOML Commonwealth 

of Northern 

Mariana Islands, 

Saipan

2017

CPO Climate.gov Publish narratives and data visualizations that show 

how NOAA advances climate science 

Public/users 2017
44

FMC Project Name Description Transitioned From Transitioned To Year

understanding, and how those advances benefit 

society

CPO Climate.gov Build and launch a mobile-friendly version of 

Climate.gov

Public/users 2017

CPO Climate.gov Develop and deploy Climate Explorer v2.0 and 

Climate Widget v1.0 for browsing climate data in 

both geospatial and historical contexts

Public/users 2017

CPO Climate.gov Launch a new public engagement effort to teach 

citizens, educators, and decision makers how to use 

Climate.gov's geospatial tools in their work

Public/users 2017

CPO Climate Literacy Develop an Educator Learning Progression for 

Climate and Energy Literacy for K-12 teachers 

based on the NRC Framework for K-12 Science 

Education: Practices, Crosscutting Concepts, and 

Core Ideas

K-12 teachers 2017

CPO Climate Literacy Deploy the Educator Learning Progression for 

Climate and Energy Literacy on Climate.gov to 

integrate the National Climate Assessment, related 

federal climate resources and the CLEAN 

collection

Educators and 

public

2017

CPO Climate Resilience 

Toolkit (CRT)

Expand the CRT's catalog of training courses to 

cover all of the section's topics, and stitched 

together into purposeful learning progressions for 

building skill and capacity among non-scientists

Public/users 2017

SG Preparing for 

Climate Change in 

Oregon Estuaries: 

Flooding, Ecological 

An innovative modeling approach supported by 

Oregon Sea Grant (OSG) to better predicts coastal 

estuary flooding to inform state and local 

Oregon Sea Grant Oregon State 

University

2016
45

FMC Project Name Description Transitioned From Transitioned To Year

Impacts, and an 

Integrated Approach 

Toward Adaptive 

Management

development planning in response to a changing 

climate

OER Chemical and 

Isotopic Exploration 

of Deep-sea 

Environments

A new deep-sea laser-based stable isotope analyzer 

brings a science laboratory to the ocean floor,

transforming ocean exploration. Few in-situ 

oceanographic chemical sensors exist for deep-sea 

science and exploration.

OER Grantee: 

Woods Hole 

Oceanographic 

Institute

Oceanographic 

and ocean 

exploration 

communities

2014

AOML R2C: CRADA 

3RR3HWSP14, 

Research to Aid 

Management of 

Coastal Water and 

Watershed Quality

Molecular Source Tracking (MST) assays are 

genomic-based tools to identify sources of fecal 

contamination in coastal environments and drinking 

water

AOML Weston Solutions 

Inc.

2017

AOML Transition of Global 

Drifter Array to 

Iridium

Transition of data to Iridium format AOML Iridium

ESRL 

CSD

Commercial 

licensing of Printed 

Optical Particle 

Spectrometer 

(POPS)

Small, lightweight aerosol instrument was 

developed at CSD and a patent issued

NOAA/OAR/ESRL/

Chemical Sciences 

Division

Handix 

Scientific, LLC

2015

ESRL 

CSD

Commercial 

licensing of Open 

Path Cavity RingDown Spectrometer 

Instrument to measure aerosol extinction by open 

path technology was developed at CSD and a patent 

issued

NOAA/OAR/ESRL/

Chemical Sciences 

Division

Handix 

Scientific, LLC

2016
46

FMC Project Name Description Transitioned From Transitioned To Year

for measurement of 

aerosol extinction

NSSL Clutter Environment 

Analysis using 

Adaptive Processing 

(CLEAN-AP)

Weather radar signal processing technique 

(algorithm description)

CIMMS/NSSL Baron Services, 

Inc.

2017

OER In Situ ORP and 

LSS sensors for 

deep ocean 

characterization

A Light scattering sensor and Oxygen-Reduction 

Potential sensors provided to Global Foundation for 

Ocean Exploration

OAR Pacific Marine 

Environmental 

Laboratory

Global 

Foundation of 

Ocean 

Exploration

2016

OER Okeanos Explorer 

Biological and 

Geological 

Sampling

Developed capability to take physical biological 

and geological samples with Deep Discoverer ROV

OAR OER Global 

Foundation of 

Ocean 

Exploration

2015

AOML Development of 

Iridium satellite 

transmission for 

XBT observations

Transition of eXyendable BathyThermomgraph 

(XBT) transmission data from Inmarsat-C to 

Iridium satellites

AOML NWS, GTS 2017

ESRL 

GMD

Balloon Prediction 

Software

Software developed in GMD to users at 

ozonesonde stations around the world.

OAR GMD Ozonesonde 

station: North 

Slope of AK, 

Oliktok Point

2015

GLERL Hypoxia Warning 

System Buoy

Buoy system that monitors oxygen conditions for 

hypoxia

GLERL/OSAT Great Lakes 

Observing 

System

2015

AOML Variational Analysis 

Method to 

Preprocess 

Complete Variational Analysis System for ocean 

surface winds that converts scalar CYGNSS winds 

AOML U.S. Navy/ NRL 2017
47

FMC Project Name Description Transitioned From Transitioned To Year

CYGNSS wind 

observations for data 

assimilation into 

numerical models

to vector winds and produces ocean surface wind 

analyses.

ARL Nuclear Regulatory 

Commission 

Support

Provided NRC with the HYSPLIT model code and 

consulting support for their effort to replace their 

simple dispersion model with HYSPLIT for severe 

nuclear accidents

ARL Nuclear 

Regulatory 

Commission

2014

ESRL 

GSD

FxCAVE FxCAVE is an experimental AWIPS II thin client 

workstation and data service using the Internet. 

OAR/ESRL/GSD National 

Interagency Fire 

Center

2016

OER Coral In Situ 

Metabolism and 

Energetics (CISME) 

Instrument

A new instrument to non- destructively measure 

coral metabolism and bioenergetics in situ, as a tool 

for rapid assessment and monitoring of metabolic 

health of massive reef corals and other benthic 

substrate types

OER supported 

Cooperative Institute 

CIOERT

NOS and 

National 

Sanctuaries; coral 

research

community

2016

AOML HFIP (Hurricane 

Forecast 

Improvement 

Project) 

Observations

Hurricane NMM-B (HMON) uses double nested 

configuration very similar to HWRF with 2-way 

interactive moving nest domains at resolutions of 

18, 6 and 2 km with 41 vertical levels

AOML NWS/NCEP/

EMC

2017

ARL North American 

Mesosclae Forecast 

System (NAM) AQ 

update

Assisted EMC to adapt NAQFC to new operational 

NAM; Emissions: CONUS, AK and HI with EPA 

NEI 2005 as basis for area and mobile sources

ARL NWS/NCEP/

EMC and NCO

2014

ARL Update hysplit v7.2 Update to ARL r560 (pre-computed random 

numbers, lagrangian time scale) and unified all 

applications to use same HYSPLIT executables

ARL NWS/NCEP/

EMC and NCO

2014
48

FMC Project Name Description Transitioned From Transitioned To Year

ARL WOC HYSPLIT Updated HYSPLIT and a newer version of the 

ALOHA chemical source term model into the Web 

Operations Center (WOC) HYSPLIT system

ARL NWS 2014

ARL CONUS CMAQ 4.6 Unified CTM code. Applied to CONUS, AK and 

HI based on EPA cmaq4.6; Emissions: CONUS, 

AK and HI. Mobile from NEI2005, area from 

NEI2011. For CB05

ARL NWS/NCEP/

EMC and NCO

2015

ARL Update hysplit v7.3 Changed GFS/GDAS codes that convert to ARL to 

input grib2 instead of grib1. Wet deposition 

upgrade/fix

ARL NWS/NCEP/

EMC and NCO

2015

ARL CMAQ vertical 

layers

Linked global operational aerosol model for LBC. # 

layers from 22 to 35;Emissions: CONUS, AK and 

HI. Mobile from NEI2005, area from NEI2011

ARL NWS/NCEP/

EMC and NCO

2016

ARL Update hysplit 7.4 Update to ARL r723 (wet deposition): add volcano

trajectories and extend NAM conusnest output to 

48-h from 24-h

ARL NWS/NCEP/

EMC and NCO

2016

ESRL 

PSD

National Blend of 

Models precipitation 

guidance

Improved precipitation forecast algorithm for the 

statistical postprocessing of multi-model ensemble 

forecast data using short training data sets

NOAA/OAR/ESRL/

PSD

NOAA/NWS/STI

/MDL

2017

ESRL 

GMD

SkySonde 

Client/Server 

Software

Software developed in GMD to users and 

transitioned to ozonesonde stations around the 

world

OAR GMD Ozonesonde 

station: Hilo, HI

2017

AOML HFIP (Hurricane 

Forecast 

Improvement 

Project) 

Observations

Transition observing technologies for use by the 

operational hurricane forecast model (HWRF) in 

order to improve forecast guidance

AOML NWS 2017
49

FMC Project Name Description Transitioned From Transitioned To Year

ESRL 

GSD

RAPv3 Operational 

Implementation

RAPv3 expands the North America computational 

domain to include Hawaii

OAR/ESRL/GSD NWS/NCEP/

EMC

2016

ESRL 

GSD

HRRRv1 

Operational 

Implementation

NWP model that is a real-time 3-km resolution, 

hourly updated, cloud-resolving, convectionallowing atmospheric model, initialized by 3-km 

grids with 3-km radar assimilation

OAR/ESRL/GSD NWS/NCEP/

EMC

2014

ESRL 

GSD

HRRRv2 

Operational 

Implementation

HRRRv2 was intended to improve high-resolution, 

hourly-updated, storm-scale weather predictions 

used by transportation industries, utilities, 

emergency managers and responders, and any other 

entities requiring very localized weather predictions

OAR/ESRL/GSD NWS/NCEP/

EMC

2016

ESRL 

GSD

MADIS v2.1.4 Software package to incorporate the NWS 

Automated Flood and Warning System 

observations into Meteorological Assimilation Data 

Ingest System (MADIS) at NWS.

OAR/ESRL/GSD NWS/Office of 

Dissemination; 

NWS/Office of 

Observations; 

NWS/NCEP 

Central 

Operations

2016

ESRL 

GSD

MADIS v2.1.5 Software package to incorporate Clarus system 

capability from the U.S. Federal Highways 

Administration, NWS Hydrometerological 

Automated Data System (HADS), and USDA's 

Snow Telemetry and Snow Course Data and 

Products

OAR/ESRL/GSD NWS/Office of 

Dissemination; 

NWS/Office of 

Observations; 

NWS/NCEP 

Central 

Operations

2016

ESRL 

GSD

MADIS 2.1.5.10 This software package contains a new real-time 

display of aircraft water vapor sensor system 

(WVSS-II) for the public

OAR/ESRL/GSD NWS/Office of 

Dissemination; 

NWS/Office of 

Observations; 

2017
50

FMC Project Name Description Transitioned From Transitioned To Year

NWS/NCEP 

Central 

Operations

ESRL 

GSD

LAPS in NWS 

AWIPS II

Local Analysis and Prediction System (LAPS) 

model transition to NWS AWIPS II forecast system

OAR/ESRL/GSD NWS Office of 

Science and 

Technology -

NWS/OST

2015

GLERL Lake Erie 

Operational Forecast 

System

Operational hydrodynamic model that predicts 

water levels, temperatures, 3D currents in Lake 

Erie

GLERL/IPEMF NOS/CO-OPS 2016

NSSL FLASH FLASH is a software application that uses the 

MRMS forcing and produces flash flood forecasts 

at 1-km/5-min resolution through direct, forward 

simulation

NSSL/CIMMS NWS/Central 

Processing

2017

OWAQ Development of a 

Probabilistic 

Tropical Cyclone 

Genesis Prediction 

Scheme

Disturbance-following tropical cyclone (TC) 

genesis index (TCGI)

U. Miami/CIMAS, 

OAR/AOML

NHC 2015

OWAQ Improvement to the 

Statistical Hurricane 

Intensity Prediction 

Scheme (SHIPS) 

Rapid Intensification 

Index

Statistically based rapid intensification index (RII) 

that employs predictors from the SHIPS model

OAR/AOML, 

DoD/NRL

NHC 2015

OWAQ Updating the 

secondary eyewall 

formation 

A new model that provides probabilities of 

secondary eyewall formation (SEF) in hurricanes 

using a Bayesian statistical approach

NCDC NHC 2016
51

FMC Project Name Description Transitioned From Transitioned To Year

probabilistic model, 

completing new 

climatologies of 

intensity and 

structure changes 

associated with 

eyewall replacement 

cycles, and 

construction of new 

forecast guidance 

tools based on the 

new climatologies

OWAQ Improved SFMR 

surface wind 

measurements in 

intense rain 

conditions

Bias correction algorithm for wind speed errors in 

real-time operations

OAR/AOML NHC 2015

NSSL Multi-Radar/MultiSensor (MRMS) 

System

MRMS is a system with automated algorithms that 

quickly and intelligently integrate data streams 

from multiple radars, surface and upper air 

observations, lightning detection systems, and 

satellite and forecast models

NSSL/CIMMS NWS/Central 

Processing

2017

ESRL 

GSD

MADIS Realtime 

System

The Meteorological Assimilation Data Ingest 

System (MADIS) is a global database and delivery 

system that serves the greater meteorological 

community by collecting, integrating, quality 

controlling and distributing many thousands of 

NOAA and non-NOAA observations for use by 

NWS and public and non-public subscribers alike

OAR/ESRL/GSD NWS/Office of 

Dissemination; 

NWS/Office of 

Observations; 

NWS/NCEP 

Central 

Operations

2015
52

FMC Project Name Description Transitioned From Transitioned To Year

ESRL 

GSD

MADIS Data 

Recovery System

MADIS Data Recovery System captures data that is 

two (2) hours to 35 days old, as well as data that 

may have been lost due to communications or 

system error

OAR/ESRL/GSD NWS/Office of 

Dissemination; 

NWS/Office of 

Observations; 

NWS/NCEP 

Central 

Operations

2015

ESRL 

GSD

MADIS Data 

Archive System

A daily archive data push to NESDIS/NCEI 

(formerly NESDIS/NCDC) of data that has gone 

through the last of the ingest/processing on MADIS 

(data that is greater than 2-1/3 hours old up to 35 

days old from the data recovery system component)

OAR/ESRL/GSD NESDIS/NCEI/

DSD/Data 

Operations 

Branch

2015

OWAQ The assimilation of 

non-NOAA and 

non-AF GPS 

dropwindsonde data 

into NOAA 

numerical models

Assimilation of dropwindsonde data collected using 

the NASA DC-8 and NSF G-V aircraft into 

hurricane forecast models

OAR/AOML EMC 2015

OER OER Video Portal Video Data Management Modernization Initiative 

Pilot Project transitioned to the operational OER 

Video Portal

NESDIS/NCEI OAR/OER 2016

OER Sampling 

Operations Database 

Application (SODA)

A customized database application to capture the 

details of specimen collection operations onboard 

the NOAA Ship Okeanos Explorer

NESDIS/NCEI OAR/OER 2015

ESRL 

GSD

SOS Explorer Lite 

(SOSx Lite) 

software release 1.0

Users can explore a select group of SOS datasets 

and walk through three pre-programmed 

educational tours on a personal computer display or 

projector screen

OAR/ESRL/GSD Public release 

available from 

website

2015
53

FMC Project Name Description Transitioned From Transitioned To Year

ESRL 

GSD

SOS Explorer Lite 

(SOSx Lite) 

software release 2.0

Users can explore a select group of SOS datasets 

and walk through three pre-programmed 

educational tours on a personal computer display or 

projector screen

OAR/ESRL/GSD Public release 

available from 

website

2017

ESRL 

GSD

Science On a Sphere 

software release 

v4.2

This release provided a collection of usage 

statistics, live video PIPs, ability to use one 

graphics card instead of two, and improvements to 

spherecasting

OAR/ESRL/GSD SOS customers; 

SOS Users 

Collaborative 

Network

2014

ESRL 

GSD

Science On a Sphere 

software release 

v4.3

Major reorganization of the data catalog, 

experimental auto alignment, volume control, 

bluetooth connectivity

OAR/ESRL/GSD SOS customers; 

SOS Users 

Collaborative 

Network

2015

ESRL 

GSD

Science On a Sphere 

software release 

v5.0

Public kiosk software released, interactive sphere 

splitter, support for 4k projectors, support for 

translations, preview edition of the visual playlist 

editor, improved auto alignment

OAR/ESRL/GSD SOS customers; 

SOS Users 

Collaborative 

Network

2015

ESRL 

GSD

Science On a Sphere 

software release 

v5.1

New version of operating system, fully feature 

version of the visual playlist editor, custom datasets 

searchable on iPad

OAR/ESRL/GSD SOS customers; 

SOS Users 

Collaborative 

Network

2016

ESRL 

GSD

Science On a Sphere 

software release 

v5.2

Text PIPs, improvements to Visual Playlist Editor, 

new layer control on iPad, projector control utility, 

rewritten documentation

OAR/ESRL/GSD SOS customers; 

SOS Users 

Collaborative 

Network

2017

ESRL 

GSD

SOS Explorer 

(SOSx) software 

release v1.1

Flat screen version of Science On a Sphere (SOS) OAR/ESRL/GSD SOS Explorer 

customers

2016
54

FMC Project Name Description Transitioned From Transitioned To Year

ESRL 

GSD

SOS Explorer 

(SOSx) software 

release v1.2

Version 1.2 of the software included improvements 

to the Tour Builder, better support for 3D models 

such as satellites, and the ability to run the software 

in dual screen or single screen mode

OAR/ESRL/GSD SOS Explorer 

customers

2017

ESRL 

GSD

SOS Explorer 

(SOSx) software 

release v1.3

Version 1.3 of the software included better camera 

control for 3D models, major improvements to the 

Tour Builder, an expanded content collection, 

better translation support, and compatibility with 

the Oculus Rift virtual reality goggles

OAR/ESRL/GSD SOS Explorer 

customers

2017

ESRL 

GSD

Graphical Forecast 

Editor (GFE) for 

Spain

GFE software tool performs mathematical 

operations on sensible weather grids that are used 

as the basic forecast information generated at NWS

OAR/ESRL/GSD AEMET: 

Agencia Estatal 

de Meteorologia

2014

AOML NOAA-developed 

assays for tracking 

sources of microbial 

contamination

Two qPCR assays were included in an international 

interlaboratory validation exercise and accepted for 

inclusion in an instructional manual for the state of 

California which provided the protocols and 

explanations on how to implement these molecular 

technologies for microbial source tracking (MST).

AOML State of 

California

2014

AOML Transition of 

molecular diagnostic 

operational 

capabilities to state 

stakeholders 

Florida Department of Environmental Protection 

received technology transfer of molecular 

techniques to determine the source of fecal 

contamination that poses risk to human, animal, 

and ecosystem health

AOML Florida 

Department of 

Environmental 

Protection

2015

AOML Methods 

Development, 

Validation, and 

Transition to 

Operations for 

Molecular Microbial 

Broward County Environmental Lab has now 

established their own MST lab capacity resulting 

from AOML training and mentorship

AOML Broward County 

Environmental 

Lab
55

FMC Project Name Description Transitioned From Transitioned To Year

Source Tracking 

(MST) of Fecal 

Bacteria and 

Pathogens in the 

Marine Environment

SG A semi-automated 

zooplankton analysis 

system for Delaware 

Bay and coastal 

waters: method 

development and 

implementation

Autonomous pattern recognition routine correctly 

identified blue crabs from a mixed assemblage of 

megalopae with ~85% accuracy

Delaware Sea Grant NOAA-NMFS 

Coastal & 

Oceanic Plankton 

Ecology, 

Production, & 

Observation

Database 

(COPEPOD)

2016