# Presentation: 420656

## UTILIZATION OF UAV’s FOR GLOBAL CLIMATE CHANGE RESEARCH

- A Summary and Synthesis of Workshop 2

- TABLE OF CONTENTS
- Overview				Page 2
- Draft Vision Statement			Page 3
- Missions: Overview			Page 4
- Missions: Climate			Page 5
- Missions: Land & Ocean Surface		Page 7
- Missions: Global Observations		Page 10
- Missions: Atmospheric Observations		Page 13
- Technology: Overview			Page 16
- Technology: Platforms			Page 17
- Technology: Instrumentation		Page 22
- Technology: Operations			Page 27
- Technology: Data and Communications	Page 29
- Gaps, Roadmaps & Vision: Overview		Page 31
- Gaps & Roadmaps			Page 32
- Ideas for Joint NASA/NOAA/DOE Programs	Page 35
- Ideas for Innovative UAV Uses		Page 36
- UAV-Enabled Global Observation System	Page 37
- Ideas for Next Steps			Page 38

## Overview

*What we have in common forms the basis of our collaboration - the focus on the goals developed in our first workshop in San Diego. From there, there is no limit to what we can do.*
- On December 7th and 8th, 2004, DOC/NOAA Forecast Systems Laboratory (FSL), NASA Science and Aeronautics Research Mission Directorates, and DOE Office of Science sponsored the second in a series of workshops on the Utilization of Unmanned Aerial Vehicles for Global Climate Change Research. Participants from NASA, NOAA, and the Department of Energy gathered together with researchers, scientists, engineers and industry representatives to build upon the work completed in the first workshop.
- This session began with a series of presentations about the program objectives of the three agencies, about the requirements for a research program, and about the current capabilities of UAVs. The group then became familiar with the 11 science goals developed in the first workshop. Participants expanded upon these missions, clarifying the observations needed for each as well as when and where these observations would need to take place.
- The group then looked at the technology and operations as well as the gaps and roadmaps needed to realize these goals. Finally we used a current NASA RFI document to drive some of the groups to put an outline together for a few of the goals while other groups looked at the next steps in the collaboration to move the group to realizing the objective of a global climate change observation system.
- This document is a summary of the group’s work.

## Draft Vision Statement

**Elements of a Mission Statement**
- Economy and Early Warning (Climate)
- Fill Critical Gaps in Earth Observing System
- UAV Critical Role in Integrated Global Observing System (enabler and integrator)
- US Leadership (opportunity to lead in aerospace and global observation)
- UAV’s as Available Capability for Monitoring
- UAV’s can Deliver Unique Scientific Measurements
- Magnify the Value of Existing Investments (satellites)

**Proposed Presentation Format for NASA/NOAA/DOE Collaboration**
**Why is this important?**
- Vision: Drawn from CCSP, GEOSS, IEOS, IORS, USCOP
- Examples: Arctic, Hurricane Tracking and Prediction
- Compelling, visceral story that motivates the important of climate change and prediction
**How can we make a difference?**
- Consistent with current administration climate thrust (but not uniquely linked to this administration)
- Magnify value of current investments (satellites, piloted platforms, ground observations)
- Address gaps in current capabilities (examples...)
- Provide new and unique capabilities (examples...)
- Current agencies’ programs and opportunities for collaboration and efficiency
**How much will it cost?**
- We will need to have some estimate of the cost and benefits from the proposed collaboration.

**“****UAV’s bridge the gap between Earth and space to understand and protect our planet.”**

## Missions: Overview

**Context**
**	**In the first round of work, groups reviewed the focus areas identified in the first workshop: Climate, Land & Ocean Surface, Global Observations, and Atmospheric Observations. Out of these groups, small teams then delved into the science goals that had been defined under each focus area. For each science goal, the teams were asked to define what needed to be measured, when it needed to be measure, how often and for how long?

## Missions: Climate I of II

- We want to make any use of UAVs with anything that's already in existence in addition to using the first 3 ARM sites. We agreed 20 km is critical to the measurements we want. We'd like to see 5 flight days taking place in each location for each of the 4 seasons. The flight days should be spread out over a few weeks. We designed our dream suite of instruments. We got into an interesting discussion about accuracy. We agreed that we could address more science if any of the instruments were improved upon. We agreed that we could have progress in all these areas by adding to the instrument suite that was previously designed. We can do work in urban areas as well as in albedos.

*Forcings*: solar, CO2, CH4, N2O, CFCs, O3
*Feedbacks*: clouds, H2O(v), albedo, aerosols, oceans, O3
*Unique Requirements*: insitu, sustained, systematic, diurnal, over oceans
*Integration with*: ARM networks, satellites, models, ocean observing, radiosonde, lidar
*Spatial*: ARM—arctic, mid-continent -100km + flexibility (access to remote regions);  Up to 20km (up and down to surface
*Temporal*: diurnal - min. 5/flight days across 3 weeks; full seasonal 4 times per year; simultaneity
*Instruments*: H2O(v) insitu; TP; B.B. SW+LW; Particle Probe; Radar (particle reflectivity); Lidar (small particle reflectivity); Microwave radiometer (profiles); Infra-red spectrometer; Wind lidar; Dropsondes (GPS, T,P,W); Electrification (field probes) mid-latitude
*Special Cases*: aerosols - urban volcanoes; albedo - polar
*Priorities*: clouds, H2O, aerosols, albedo

**Science Goal:** Understand and quantify sensitivities of climate to forcings and feedbacks.

## Missions: Climate II of II

- We looked at where UAVs would have the most impact. We tried to understand processes and thought the most utility here would be closer to the boundary layer. We would understand how things get into the troposphere. There's a list of potential campaigns in the short-term, over the next 5 years. We would focus on the Amazon, the southern ocean, and the ARM sites, as well as a couple of sites listed here. This all led us to a possible campaign is this unknown source of methane. It's not confounded by large diurnal cycles. We didn't get very far in the 'When' and 'How Often' categories. We did talk about the North America campaign and we'd like to get involved in some intensive campaign.

| Observations Required | Where? UAV Observations | When? | How Often? |
| --- | --- | --- | --- |
| Condintions of:
CO2, CO, CH4, O2, in ? layer

land cover/land use change
- surface temperature (ocean/land)
- winds
- ocean color
- atmospheric temperature
- fossil sources
- parameters controlling photosynthesis
- soil moisture
- snow, ice, water coverage
- CO2 (drop buoys) | regional - continental scale - over ocean and land
- vertical profiles (0-5km)
- Amazon biogeochemistry (? CH4)
- Southern ocean (south pacific)
- 3 ARM sites
Eastern pacific Upwelling Zones
- Arctic freeze/thaw line (Barrow ARM site)
- Regional CH4 campaign — Amazon, Tundra, Aglands (ie rice), Geologic(?)
- Fossil source campaign (?) | Diurnal - monthly - seasonal | Sat. overpasses |
| Rationale: CH4 is easier to measure than CO2; UAVs can help in process studies; less natural variability; CH4 strong CHC; shorter residenc time   /nd |  |  |  |

**Science Goal:** Sources and sinks of CO2 & methane (quantify and locate natural and anthropogenic)

- • UAVs coordinated with surface and orbital assets and models
- • UAVs alone

## Missions: Land & Ocean Surface I of III

**Science Goal:** How is the biosphere changing?

| Types of Measurements | When | Where |
| --- | --- | --- |
| 1. Multispectral (imaging) 1-20km
2. Hyperspectral sometimes (imaging) 1-20km
3. Florescense high resolution (temp/sp) triggered 200m
4. In-situ fluxes 30m
5. DiAL 30m - 10km
6. Laser (dobbler) for wind 30m - 10km
7. Soil moisture u-wave (passive/active) 3-20km | 1. Triggered episodic meas (minit?)
2. Scheduled eposodic (seasonal/annual) cal / val
3. Diurnal (fluxes, Ocean Bio)
4.  | 1. Keep track of interfaces (coastal zone; forest/tundra; sky Islands (desert sandstorms); altitude change; irrigated vs. arid; surface ocean temperature;
GPP, DOC, turbidity
Coral blocking
Wetlands extent / change |

| What | Where | When/how often/ duration/ synchrony |
| --- | --- | --- |
| Land use / land cover interface | Global | All year / seasonally / range to target) close to satellite pass (cal/val) |
| Ecosystem condition | Specific ecosystems worldwide | Diurnal to seasonal (many synchronous measurements) (intensive observation period simplified for monitoring)
All seasons |
| Event - triggered | Location of event (global reach) stressor, transport, receptors) | Event duration (multi-parameter)
Response time important
Maybe pre-event if forecast |

## Missions: Land & Ocean Surface II of III

**Science Goal:** Decrease uncertainties in models (CO2 emission regions; CH4 emission regions)
- Understanding processes (regional variability; short-term variation)

*What*: CO2; H2O; CH4
*From this*: regions explored - typical for validation; extremes for exploration
- Observation Strategy: define boundary layer (ocean, land, smooth, rough, wind speed)
*Technology development*: miniaturization; multiple sondes (or mini-UAVs); mini-gliders?
*Fundamental Issues*: intermediate scale between satellite and high flying aircraft and jeep; work on natural laboratories (investigator-driver)

- The gas emissions from the surface have reactions to the climate change. How does the natural emission of CO2 change in response to the climate change? Is it positive or negative feedback?
- One of the things you want to do is have prediction of these processes. There are already models that can do this and we want to decrease the uncertainties in these models. We want to pick areas that are particularly sensitive to change.
- We agreed that understanding the processes are important for understanding the scale. What you see from satellites is what is really happening. To understand the detail, UAVs play a very important role. The regions typical for validation are where we want to start. The fundamental issues that emerge from our discussion is that we need the intermediate scale between satellite and aircraft so we can fill in the gaps of the picture we have right now. We're looking for natural laboratories where we can do investigative work to improve our understanding of the processes.

## Missions: Land & Ocean Surface III of III

**Science Goal:** Characterization (shifts/changes) of frozen part (cryosphere) of water cycle earth surface (ocean & land) in response to climate change
*Objectives*: Trending (baseline) - total frozen reservoir (global/annual change/regional); Measure surface area, depth, density; Understanding response & feedback (energy cycle - solar + current and drivers); Focus on bellweather areas (visually/active areas - reasonable time space - high rate of change)

| Cryosphere | Observations |
| --- | --- |
|  | • Sea ice  - arctic/antarctic (moderate variability)   (5–10% of ocean)
• Glacier   - mountains/coastal (least variable)
• Snow fields/pack  - mountains (highly variable) |
|  | • Perma frost  (frozen soil moisture) - interface to biology |

| Topic | Position | Altitude | When  | How often | Duration | Coverage/resolution |
| --- | --- | --- | --- | --- | --- | --- |
| Sea Ice | Arctic/antarctic
(polar) | Sea Level | Seasonal (summer/winter) to monthly | Monthly | FLT tracks
(Re TBD) | Continental scale - 1km |
| Glacier (moves) | Mountains (high latitude) | Mountain top (20k feet+) | Seasonal
(21cm /year) | Monthly (year/decade) | FLT tracks
(Re TBD) | 100m |
| Snow field (fixed) | Mountains (high latitude) | Mountain top
(20k feet) | Annual 
(thorough)? | Annual | FLT tracks
(Re TBD) | 100km |
| Snow pack (melts annually) | Mountains | Mountain top | Seasonally | Weekly |  | 1km |

- Here is a pathway where we think about how UAVs play into the mix. We suggest that UAVs be in areas where we need frequent repeats and high resolution. We think that UAVs will need long duration. They don't particularly high altitude. We'll need to get into understanding of what drives the changes we see. We need surface area depth and density.

## Missions: Global Observation I of III

| Measurements Required | Where should they be taken? | When? | Frequency? | Duration? | Taken simultaneously? |
| --- | --- | --- | --- | --- | --- |
| State variables
T, u, V, q, (p), (h) | Fill in data voids
Adaptively observed
Event driven contingency | Ongoing
1-5 days as required
Up to 60 minutes notice as required | Routine
Model driven
Event driven | On-going
hours - 1 day
mins - hours  | (BCWST) 
Best coincide with synoptic time |
| Cloud properties (callibrate satellite & radar)
Liquid/ice  concentrations | Calibration for real time system (CORTS) - 
possibly operational | IOP Intense observations periods | Correlated with other measurements I.e. radar, satellite
UAV swarms during IOPs |  |  |
| Precipitation | CORTS |  |  |  |  |
| Land surface | CORTS |  |  |  |  |
| Ocean surface properties | CORTS (long) |  |  |  |  |
| Ice properties | CORTS |  |  |  |  |
| Aerosols | CORTS 
Events |  |  |  |  |
| O3 - as an indicator of P.V. | CORTS 
Events |  |  |  |  |

**Science Goal:** Improve high impact weather forecasts

- We came up with the idea of CORTS. This stands for calibration for real time system. Using UAVs help in research mode to generate algorithms to calculate things like ice fluxes. You're using a UAV to calibrate a remotely sensed object, like radar and satellite to spread the knowledge over a wider area. You do that within an intensive observation period. This is not just for one UAV, but also for a swarm of them.

## Missions: Global Observation II of III

- We're looking to put 200-400 global station points as a good start. We talked about having them above the surface. We see them at 300 m intervals above the surface. There is a special case of aerosols. It probably would be more concentrated in industrial areas.
- We talked about what kind of time resolution and we had a goal of taking 8 measurements a day and could cover the diurnal cycles.
- We felt the UAVs offer a lot to this kinds of system, especially in the vertical measurements. It might take 4 years to do a demo phase to put this system together. We're planning the system for five years from now.

**Science Goal:** Improve prediction of climate variability and change

| Where

 | What | When |
| --- | --- | --- |
| State: 
Tropopause to surface
Including boundary layer
300m intervals
30m for B.L.
Pseudo-distribution 
 (200 - 400 points) | State parameters (time and geospatial)
Temperature, pressure, (water vapor) | Pseudo-random, diurnal seasonal
Goal - 8/day - 1/wk
Duration: 4yr minimum (demo) - multi-decade (operations) |
| Below cloud cover
Satellite queing 
Industrial regions (200 point geo)
Courser sampling (100m - 500m  | Aerosols: optical profiles/profile scattering
Need to capture effects of aerosols on clouds/ precipitation (particle size, distribution, macro view
Trace gases: O3, CH4, CO2 ( 1ppm accuracy)
Water vapor: upper tropospheric measurement
Clouds: life cycle, coverage, optical depth, albedo/reflectivity, vertical profile | (start) revisit every 72 hours every grid point

For clouds diurnal in the tropics |
| UAV roles:
Anchoring satellite measurements
Gap filling |  | Gaps:
Atmospheric only
Radiative budget (longwave, shortwave)
Correlation with modelers and instruments in 5 years |

- • resolution• distribution• regions

- • sustained• weekly updates for verified profiles• hourly for cloud
- • seasonal variability

## Missions: Global Observation III of III

- We want UAVs which can fly long distances, which preclude manned missions. Mars covers thousands of kilometers in range. The vertical question is important to that extent we're looking at something like 50 millibars in resolution to go after the aerosol question.
- We want to do that over time for about 10 years. In the Pacific, we'd still be going for vertical movement over long spatial scales.

**Science Goal:** Critical physical processes: storms, climate change trends

| What? | Where? |       When? | Why?/Why UAV? |
| --- | --- | --- | --- |
| Info for global climate models

Precipitation

Winds

2008/2015 |  | Diurnals 12 months

Continuous - need (10) cycles

 | Small scale measurements
Long platforms
Long distance |
| Everything | Everywhere | All the time |  |

- Aerosols - in situ
- Clouds

- Radiation
- (short/long)

- Temperature/time

- H2O

- CO2

- O3

- Arctic

- 2008

- 2018

- 10km - s awe place
- 10km - lead

- 2008

- Pacific

- Next

- Warm pool - N. of Australia

- Merging of data

- Why not now?

- sensors

- Data systems

- Need to reduce risk to instrument?
- Cost of ???

- curtain

## Missions: Atmospheric Observation I of III

**Science Goal:** Quantify change in the chemical composition of the atmosphere

| What Observed | Where?
Lat                  Alt | When? | How Often? | Duration? | Taken simultaneously? |
| --- | --- | --- | --- | --- | --- |
| Air quality
(surface to BL) | Midlat            0-40k ft | All year | Daily
Hourly  events |  |  |
| Strataspheric Ozone | Polar        tropopause
Midlat        -> 30km
Tropics | All seasons |  Weekly | Profile | No |
| Tropospheric Ozone | Polar        tropopause
Midlat        remote &
Tropics       polluted | All seasons |  - daily | Profile
Dial | No |
| Long-lived gases
C02, CH4, N20
Herb? - HFCs | Polar        surface
Midlat        lower strat
Tropics       (25km) | All seasons | Weekly | Profile | No |
| Water vapor | Polar        upper trop
Midlat        lower strat
Tropics | All seasons | Weekly | Profile | No |
| Reactive gases
NOx, SOx, CO | Polar        surface
Midlat        lower strat
Tropics |  |  |  | State variables |
| Highly reactive
OH, HO2, NO, NO2 | Polar        polluted &
Midlat        remote trop
Tropics | All seasons
 | intermittent |  |  |
| Aerosol size, number, composition | Polar        polluted &
Midlat        remote trop
Tropics | All seasons
 | Daily - weekly | Profiles | No |
| Radioactive fluxes | Polar        upper trop
Midlat        lower strat
Tropics | All seasons | intermittent | Profiles | No |

## Missions: Atmospheric Observation II of III

- Possibly using dropsondes to create profiles to measure the chemical in the atmosphere. There is a whole different chemistry in carbonaceous aerosols. These could be distributed in a number of platforms. This could be focused around the boundary layer.
- The last group included aerosols like volcanic eruptions. Again, for these we need to get in close to the source, so of course the UAVs will be key. These would be smaller UAVs.

| Observation | Location | Temporal | Simultaneous | Instruments |
| --- | --- | --- | --- | --- |
| Marine
S | Coastal margin
I.TC2 - Tropical | Routine monitoring
Weekly | Profiles | Mass spec spectrometers
Isotopes |
| Urban
C | Industrial (localized)
20-60k ft profiles (mixed layer) | Routine
Weekly |  | Lidar(s)
Doplar lidar |
| Events
S
C | Localized
60k ft profiles | Episodic (on demand) |  | Dropsondes |

**Science Goal:** Figure out the role of aerosols in global warming

- • volcanoes• wildfires• dust

## Missions: Atmospheric Observation III of III

- We subdivided the topic into three major areas. We subdivided even further under one of these. We expanded the scope of it a bit. The blue comments are from the initial discussion. The red comments are about the instruments. The green comments are from visitors who came by. We appreciate those and tried to incorporate them as much as possible.

**Science Goal:** Role of water vapor & cloud-radiative feedback (predictability and climate control)

| What? | Where? | When? | How Often? | Duration? | Simultaneous? | How? (instrument) |
| --- | --- | --- | --- | --- | --- | --- |
| H2O Concentration
Ice
Mixed phase
Liquid
Water vapor/flux | Vert: Surf to lower strat (20km)
Horiz: Everywhere conc. on oceanic | Uniform sample + targeted observation (e.g. monsoon) | 6 hour sampling (background)
1 hour (event driven) | Storm:  week
Climate: long duration profiling (12-24 hrs) | Temp; U, V, W,
Turbulence;
Pressure | Mixing ratio (2%)
(laser hygrometer) 
All-weather carole (king) |
| Cloud Characterization
Cloud extent
Cloud types
Microphysical properties

Cloud profiles (temp, phase) | global (%cover) 10’s of km
Subgrid scale (1km) (10’s m u physics

Cloud (10’s of meters) | Uniform sample + targeted observation | 6 hour sampling

1 hour (event driven) | Days to week
Frequent measurements over  extended time period
Spacial sampling over a long path | Temp; U, V, W,
Turbulence;
Pressure
UAV: help to bridge between more extensive radar and satellites | Satellite obs
In situ
Remote sensors
   - radar
   - lidar
All weather capable
(instrument miniatures & power c?) |
| Cloud radiometric properties | Representative cloud types 
Above and below clouds | Periodic
(seasonal) | Sample life cycle of cloud type |  | Same 
Satellite and surface measurements | Broadband & specially resolved vis & IR
(radiance and irradiance) |
| Satellite 
H2O & winds
cal/val | Global
Via focused UAV observations | Periodic
(seasonal) | IOP | Hours to days | Satellite observations 
(as above) | INS/GPS
Laser/hygro |

- (INS/GPS)

- (BAT)

- (0.1C accuracy)

- (% cloud cover - might not  be adequate characterization)

## Technology: Overview

**Context**
- 	In the next round of work, each team pored over the science goals defined in the morning to discover the requirements for a specific technology: Platforms, Instrumentation, Operations and Data & Communications.
**Assignment**
- 	Look across the science goals and each observation (there may be several observations within each goal), and identify any solutions that may be required for the technology that you have been assigned. Also note any special capabilities or properties needed. Finally, identify/document any assumptions you’ve made.

## Technology – High Altitude Platform

**Issues**
- Performance
- 40,000ft +
- Ceiling
- Vertical Profiling
- Payload (mass, volume, power)
- Range
- Endurance
- Cruise Speed
- Payload Environment (stability, thermal, vibration)
- Lifecycle Cost
- Deployability – no significant runway limitations
- Operability
- All Weather
- Icing
- Turbulence
- Crosswinds (landing and take off)
- Autonomy
- Global Airspace
- Over-the-Horizon Command & Control
- Reliability (MTBF > 20-50k hours)
- Environmental - propulsion

**State of the Art**
- Global Hawk 	60,000 ft	36 hours
- Altair	50,000 ft	32 hours
**Innovative Concepts**
- Helios	100,000 ft	12 hours – week
- Zephyr	50-100k ft	weeks - months

## Technology – High Altitude Platform

| Missions |  | Altitude | Endurance | Repetition | P/L | Speed |
| --- | --- | --- | --- | --- | --- | --- |
| Climate | Sensitivity to Forcings | 20km | 24 hours |  |  |  |
|  | CO2 Sources & Sinks |  | 24 hours |  |  |  |
| Atmospheric | Chemical Composition | 30km | Week-months |  |  |  |
|  | Role of Aerosols | 18.5km |  |  |  |  |
|  | Water Vapor & Cloud Radiative Feedback | 20km | 24 hours – week |  | Stable platform | <100 knots |
| Global  | Climate Variability & Change | Surface – 20km | Week-months | 72 hours | “Dropsonde” class | Long range |
|  | High Impact Weather Forecasts |  |  |  |  | “DASN & Loiter”? |
|  | Critical Physical Processes |  |  |  |  |  |
| Ocean & Land Surface | Models & Predictions | 20km | 24 hours |  |  |  |
|  | Cryosphere Responsive Feedback | N/A |  |  |  |  |
|  | Gas |  |  |  |  |  |

## Technology – Mid-Altitude Platform

**Assumptions**
- 25,000-30,000 ft
- Can use heavier instrument suites
- Robust
- Dropsondes critical capability
- Quick-look data
- Multi-use or tailored
**Others**
- Rapid response
- Loitering
- Cal/Val
- Gap filling

**General Capabilities Needed**
**UAV-Unique**
- Robustness for turbulence
- Long endurance – trans-oceanic & loitering
**Flight Characteristics**
- Structure similar to regional aircraft
- Slow speed & high resolution
**Command & Control**
- Distributed basing for global coverage
- “Over the horizon” communications
**Payload**
- Large & reconfigurable (i.e. antennae)
- Variable size for specific missions
- Tailored aircraft specific to mission & grid

**Missons**
**High Impact Weather**
- Autonomy
- Tailored mission
- Quick-look data is key here
- Diurnal fire monitoring
- Command & Control – rapid response
**Atmospheric Composition**
- Flight characteristics – variable short/fast climb rate
**Cryosphere**
- Flight characteristics – de-icing for polar/cold environments

## Technology – Low Altitude Platform

| Missions < 25,000 ft |  | Existing Platform | Flight Char- acteristics | Command & Control | Endurance | Range |
| --- | --- | --- | --- | --- | --- | --- |
| Climate | Sensitivity to Forcings | P-3, Twin Otter, C-130 |  | LDS, Satellites & Autonomous | 5 days for 
3 weeks | 1000 km |
|  | CO2 Sources & Sinks | P-3, Twin Otter, C-130 | Ship Launch, Vertical Profiling | LDS, Satellites & Autonomous | Up to many diurnal cycles | Process – 100’s of km
Monitoring – 1000’s of km |
| Atmospheric | Chemical Composition | P-3, Twin Otter, C-130 | Vertical Profiling | LDS, Satellites & Autonomous | Up to many diurnal cycles | Process – 100’s of km
Monitoring – 1000’s of km |
|  | Role of Aerosols | P-3, Twin Otter, C-130 | Vertical Profiling | LDS, Satellites & Autonomous | Up to many diurnal cycles | Process – 100’s of km
Monitoring – 1000’s of km |
|  | Water Vapor & Cloud Radiative Feedback | P-3, Twin Otter, C-130 |  | LDS, Satellites & Autonomous | Up to many diurnal cycles | Process – 100’s of km
Monitoring – 1000’s of km |
| Global  | Climate Variability & Change | P-3, Twin Otter, C-130 |  | LDS, Satellites & Autonomous | Up to many diurnal cycles | Process – 100’s of km
Monitoring – 1000’s of km |
|  | High Impact Weather Forecasts | P-3, Twin Otter, C-130
Radiosonde | Ship Launch | LDS, Satellites & Autonomous | Up to many diurnal cycles | Process – 100’s of km
Monitoring – 1000’s of km |
|  | Critical Physical Processes | P-3, Twin Otter, C-130 | Hand Launch | LDS, Satellites & Autonomous | 5 days for 
3 weeks | 1000 km
 |
| Ocean & Land Surface | Models & Predictions | P-3, Twin Otter, C-130
Ships, Buoys | Ship Launch | LDS, Satellites & Autonomous | 5 days for 
3 weeks | 1000 km
 |
|  | Cryosphere Responsive Feedback | P-3, Twin Otter, C-130 | Ship Launch | LDS, Satellites & Autonomous | 5 days for 
3 weeks | 1000 km
 |
|  | Gas |  |  |  |  |  |

## Technology – Low Altitude Platform

| Missions < 25,000 ft |  | Payload | Autonomy | Multi-use vs. Unique Mission | Coverage Issues | Data Storage |
| --- | --- | --- | --- | --- | --- | --- |
| Climate | Sensitivity to Forcings | Small-to-large scale
In situ & remote | Stringent Operation Procedures | Standardization | Short & long ranges | Large Capacity |
|  | CO2 Sources & Sinks |  | Operation in NAS System | Multi-use |  |  |
| Atmospheric | Chemical Composition |  | Stringent Operation Procedures | Standardization |  |  |
|  | Role of Aerosols |  |  |  |  |  |
|  | Water Vapor & Cloud Radiative Feedback |  |  |  |  |  |
| Global  | Climate Variability & Change |  |  |  |  |  |
|  | High Impact Weather Forecasts |  |  |  |  |  |
|  | Critical Physical Processes |  |  |  |  |  |
| Ocean & Land Surface | Models & Predictions |  |  |  |  |  |
|  | Cryosphere Responsive Feedback |  |  |  |  |  |
|  | Gas |  |  |  |  |  |

*Interfaces: Other systems; Vehicles (formation flying & mother/daughter); platforms, instruments, ground systems, science systems*

## Technology – Remote Sensing Instrumentation

| Focus Areas | Measures |
| --- | --- |
| Climate,
Atmospheric, & Global  | Aerosols < 100m(?) 
(OD, SSA, Size, Distance, Concentration, Composition) |
|  | Trace Gasses – Vertical + Column
(CO2, CH4, O3, H2O, N2O CFC’s, gradients in flux) |
|  | Clouds > 100m(?)
(OD, particle microphysics, cloud state variables) |
|  | State Variables
(T, W, P, RH) |
|  | Radiation
(Albedo, flux) |
|  | H2O
(Gas profiles, rain) |
| Ocean & Land Surface | Ice – SA, Depth, Density |
|  | Vegetation Type - % land cover |
|  | Coastal T, NPP, DPC, TSS |
|  | Sea Salinity, Soil Moisture |

| Remote Sensors |  |  |  |
| --- | --- | --- | --- |
| Passive | Hyperspectral – multi-angle, polarmetric spectrometer (aerosol properties)
 |  |  |
|  | Narrow band radiometer? (CO2?)
 |  |  |
|  | Hyperspectral Spectrometer (ocean color, vegetation type)
 |  |  |
| Active | Lidar | Infrared – H2O, CO2, Winds |  |
|  |  | Visible – clouds, ice surface, aerosols, ocean color, canopy structure |  |
|  |  | UV – O3, winds |  |
|  | Radar | Measurable – atmospheric ice (?) |  |
|  |  | S Band – Precipitation |  |
|  |  | C, Ka, L, P Band – ice sheets, canopy levels |  |
|  |  | Long-wave – ice depth |  |
|  |  | Doppler – cloud structure |  |
|  | Laser 
(pemp probe?) | Chlorophyll, vegetation stress (?) |  |

## Technology – Remote Sensing Instrumentation

**UAV ? Mission Design Issues**
- Cloud, aerosol and gas issues cannot likely be completely address by remote sensors. (Ocean and land issues probably can.) We need to device a coordinated fleet mission.
- Passive sensors are typically small mass/volume – they can use HALE
- Active sensors are typically larger mass/volume. Most science questions requiring active remote sensors do not need high altitude – they can use LALE or MALE)

## Technology – In Situ Instrumentation

|  | Gas Chrometograph | Mass Spectrometer | Spectometry (Optical) | Ion Mobility Spectrometer | Microeletcromagnetical Sensors | Intertial Navigation/Pitot Tube  | Filtering/ Physical Collection | Radiometers | Cloud Microphysics Sensors | Nephelometers | Imagers | Extratometer (??) | Evaporative Heating/ Cooling | FSSP | Cryogenic/ Chilled Mirror | Cavity Ringdown Spectrometer | Aerosol Hydration/ Vox | Field Mills | Dropsondes |
| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |
| Various Chemical Species | X | X | X | X | X |  | X |  |  |  |  |  |  |  |  |  |  |  | ? |
| Water Vapor/ RH |  |  | X |  | X |  |  | X |  |  |  |  |  |  | X |  |  |  | X |
| Aerosols | X | X | X |  |  |  | X |  |  | X |  | X | X | X |  | X | X |  |  |
| Temperature & Pressure |  |  |  |  | X |  |  |  |  |  |  |  |  |  |  |  |  |  | X |
| Cloud Microphysics & Properties |  |  |  |  |  |  | X |  | X | X | X | X | X | X |  |  |  |  |  |
| Winds & Turbulence |  |  | X |  |  | X |  |  |  |  |  |  |  |  |  |  |  |  | X |
| Radiative Field |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |
| Isotopes |  | X |  |  |  |  | X |  |  |  |  |  |  |  |  |  |  |  |  |
| Electric Field |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | X |  |

*# of sensors is application-dependant. **	**Sensor type is UAV Platform-dependant.*

**Sampled Items**

**Instruments Required for Physical Sampling**

## Technology – In Situ Instrumentation (Adaptation I of II)

|  | Gas Chrometograph | Mass Spectrometer | Spectometry (Optical) | Ion Mobility Spectrometer | Microeletcromagnetical Sensors | Intertial Navigation/Pitot Tube  | Filtering/ Physical Collection | Radiometers | Cloud Microphysics Sensors | Nephelometers | Imagers | Extratometer (??) | Evaporative Heating/ Cooling | FSSP | Cryogenic/ Chilled Mirror | Cavity Ringdown Spectrometer | Aerosol Hydration/ Vox | Field Mills | Dropsondes |
| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |
| Size | X | X |  |  |  |  | X |  | X | X | X | X | X |  |  |  |  |  | X |
| Power | X | X | X |  |  |  | X |  | X | X | X | X | X | X |  |  | X |  |  |
| Mass | X | X | X |  |  |  | X |  | X | X | X | X | X |  |  |  | ? |  | X |
| Remote / Autonomous Ops | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X |
| Telemetry |  |  |  |  |  |  |  |  |  |  | X |  |  |  |  |  |  |  | X |
| Access to Clean Air Stream | X | X | X | X | X | X | X |  | X | X | X | X | X | X | X | X | X |  |  |
| Field of View |  |  |  |  |  |  |  | X | X |  |  |  |  |  |  |  |  |  |  |
| RFI / EMI | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X |  |
| Icing |  |  |  |  |  | X |  |  |  |  |  |  |  |  |  |  |  |  |  |

**UAV Adaptation Issues**

**Instruments**

*ALL INSTRUMENT PROBES*

## Technology – In Situ Instrumentation (Adaptation II of II)

|  | Gas Chrometograph | Mass Spectrometer | Spectometry (Optical) | Ion Mobility Spectrometer | Microeletcromagnetical Sensors | Intertial Navigation/Pitot Tube  | Filtering/ Physical Collection | Radiometers | Cloud Microphysics Sensors | Nephelometers | Imagers | Extratometer (??) | Evaporative Heating/ Cooling | FSSP | Cryogenic/ Chilled Mirror | Cavity Ringdown Spectrometer | Aerosol Hydration/ Vox | Field Mills | Dropsondes |
| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |
| Speed |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |
| Condensation | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X |
| Environment (Pressure/Temp) | X | X | X | X |  |  | X |  |  |  |  |  |  |  |  | X | ? |  |  |
| Servicing | X |  |  |  |  |  | X |  |  |  |  |  |  |  |  |  | X |  | X |
| Long Flight Duration |  |  | X |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | X |
| Cost – Devel. | X | X | X | X | X |  | X |  |  |  |  |  |  |  |  | X |  |  | X |
| Cost – O&M |  |  | X |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | X |
| Data Storage/ Processing | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X |
| Instrument/UAV Platform Comms. | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X |

**UAV Adaptation Issues**

**Instruments**

*ALL INSTRUMENT PROBES*

## Technology – Platform Operations

|  | Reach | Sort & Gen Rate Avail (?) | Fleet SME/Mix Collaboration |
| --- | --- | --- | --- |
| Local | LOS | Upon Demand | Small platforms/ to many |
| Regional |  | 10P |  |
| Global | BLOS | Hi Cont | Few/many |

**Terms**
- C3 = BLOS (oth), LOS (20km radius)
- Avail = Sorty rate, deployability (local, regional, global
- Intensive Observation Period (IOP)
- Fleet Size/Mix = platform collaborations
- Mother/daughter = “local” ops
- Formation Flight = “Local Ops”
- “Local” = LOS
- OnBoard = IMM – Intelligent Mission Management (cont. management), Level of Autonomy
- Ground Station = dedicated GCS with data “network”
- IA Collaboration =
- Ops - contract vehicles/ FLT services – “low”
- R&D – joint NASA/NOAA/DOE – “oftens”/high
- (e.g. NASA operates platform)
- Air Space – “File & Fly” (globally, equivalent to piloted)
- Affordability =
- ACQ = f(capability)
- OPS = $400/hour
- Multi A/C per operator

## Technology – Integrated Observing Operations

**Integrate ground, sub-orbital and orbital observation systems**
- Weather Forecasting: event-driven vs. continuous
- Fill data voids (routine) – 4D sounding over ocean and high latitudes
- Bases should be distributed appropriately (100’s of observations per day)
- Launch UAV’s on regular schedule, adjustable tracks, from surface to thousands of meters
- Severe Weather – Surge of extra vehicles
**Consistencies Across Focus Areas**
- Long Endurance
- Remote and/or dangerous areas
- Similar data types
- State quantities
- Chemical compounds
- Link satellite and surface data
- Measure similar parameters

**How does UAV integration differ from existing field operations?**
- Safety and regulatory issues not uniformly settled or addressed globally
- Integration with manned aircraft (safety)
- Extended UAV endurance – 24-7 if possible
- 24-7 staff on ground
- Satellite data link – SMB/s
- Extensive onboard storage
- Hazardous conditions ok away from people
- Proactively address safety/regulation as NASA: UNITE/ACCESS 5

## Technology - Data

|  | Weather Forecasting
(Short-term) | Chemistry
(Mid-term) | Climate Change
(Long-term) | Episodic
(IOP) |
| --- | --- | --- | --- | --- |
| Standards |  |  | Depends on Instrument | Survey existing standards |
| Scientific Uses | Weather forecasting | GCM trends | Transport and process models
Long-term trend models | Varies |
| Processing | Sustained
Timely: < 3hours | RF to target for adaptive measurements
Reas.: < 3months | < 3months |  |
| Integration |  |  |  |  |
| End User | Data Assim. Centers | GCM Community
Chemists
Not yet for regulators |  | Survey End Users
Expand End Users |
| Archiving | Level 0 data need 
to be archived | Quality-controlled data | Metadata are critical
Long-term stability
NMO Best Practices | Survey End Users
Expand End Users
 |

*Start with existing standards for A/C*
*WMO, BUFR or EOS*

*USP Community Formats – spatial & temporal tagging*

*Must survey end users for standards, storage and archiving needs.*
*Learn from the past – there is never sufficient funds allocated for data acquisition**analysis and archiving*
*Downloading data from remote locations*

## Technology - Communications

| End Users | Access | Timeliness | Range | Data Volume |
| --- | --- | --- | --- | --- |
| Operational Modeling Centers |  | Real time | Long | Low |
| Public | Security | Real time – Days |  |  |
| Model Developers |  | Days – Months | Medium | High |
| Researcher | Security | Real time – Days
 | Medium | High |
| Disaster Managers | Security | Real time
 | Short – Medium | Medium |
| UAV Operators |  | Real time
 | Short - Long | Low |

*Standards – There are no new data from UAV’s. Standards are in place.*
*Bandwidth – Some tradeoff between bandwidth and on-board processing*
*	**There are limitations to bandwidth based on telemetry.*

**Scenarios**
- Weather Prediction
- Low bandwidth and volume
- Real time
- Researchers / Disaster Management
- Real Time
- Med-High bandwidth
- Researchers / Model Developers
- Very high data volume
- Not real time

## Gaps, Roadmaps & Vision: Overview

**Context**
- 	In the final two rounds of work, teams focused on a variety of topics. Several groups worked to identify technology gaps and to develop roadmaps to address those gaps. Other teams worked on the vision for a joint program, innovative uses for UAV’s, developing responses to an RFI based on the work of this session, and next steps. The output of the last two rounds is represented in the following slides.

## Gaps & Roadmaps – Platform

**Gap – Atmospheric Chemistry**
**Consolidated Regional Survey**
- Altitude: 0 – 5km
- Payload: 250kgm (remote) / 5-40kgm (In situ)
- Speed: ~50-100 knots
- Range: Local
- Duration: 1-5 days
- 2-ship pair?
**Gap – Carbon Cycle**
- Altitude: 20m – 5km
- Payload: 100kgm
- Speed: 100-200 knots
- Range: 10,000km
- Duration: multi-day
- All-weather – Icing & Turbulence
- Maneuverable for terrain avoidance

**Gap – Data Relay / Hurricane Monitoring**
- Altitude: >20km
- Payload: 200kgm (Data link & dropsondes)
- Speed: Maintain station 99.9%
- Range: Global / +/- 30 degrees latitude
- Duration: Continuous
- Low Cost: ~ $100 / flight hour
**Gap – Polar**
- Altitude: 1-18 km
- Payload: 500-1000kgm (remote) / 25-30kgm (In situ)
- Speed: 100-400 knots
- Range: 10,000km - ?
- Duration: Months!

**Overarching Issues**
- Cost per hour
- =mass/endurance, utilization
- # people
- Availability
- Other demands
- Basing OPS

- “We considered the gaps for airframes/platforms. We looked at in situ vs. remote, large vs. small, fast vs long. It takes more people to fly a UAV than it does a manned vehicle. All of these things add cost to ownership.
- A big multi-use UAV where you can trade out instruments will be a lower cost situation. Finding a common instrument interface is very important and probably a gap we need to think about.
- If you have a unique mission where things are integrated into the payload, it's better to make lots of them and be able to use and lose them. Environmentally you may not be able to lose them as much as you might want.
- The cost per hour of use will vary with the mass divided by the utilization of the unit. The longer it flies the less time there is to work on it. The higher utilization of the unit, the longer the amortization. The big problem is the availability. “

## Gaps & Roadmaps – Instruments

| Sensor Type | Currently
Exists | Needs to be 
Re-engineered | New Technology |
| --- | --- | --- | --- |
| Active Remote | Cloud Lidar
Ozone Lidar
Aerosol Lidar
Cloud Radar
SAR
GPS* | Water Lidar
Temperature Lidar
Precipication Radar
Vegetation Lidar | Wind Lidar |
| Passive Remote | NADIR (Microwave)
NADIR (???scoptical)
Scanning (??roptical)
Radiative Flux
 |  |  |
| In Situ |  |  |  |

## Gaps & Roadmaps – DataComm

**Requirements**
- AC control OTH/LOS – Redundant
- Telepresence
- Instrument control
- Data Download (Not necessary to encrypt)
- Instrument health
- Target opportunities / Phenomenology

| Gap  | Never enough comms | Polar region > 200kbps | Commercial Standard | Consistent | On-board processing & bandwidth management | BLOS RF Link | BLOS RF Link |
| --- | --- | --- | --- | --- | --- | --- | --- |
| Technology Today | LOS/BLOS | TRDSS
Inmarsat
Iridium | MIL STD?
FIPS 140-1
 | DOD UNET
ARDEM
CDL | Packeteer | Global Hawk | Global Hawk |
| Issue | Bandwidth Constraint | Global Connectivity | Security / Information Assurance | System Architecture & Standards Defined | Adaptive (Comm management) | Link Quality
Reliability
Error rate
Availability
Integrity | Fault-Tolerant Networking |

- Assumption: Enough on-board storage
- Consideration: Some countries may not want data publicly available (e.g. Eastern Europe, Asia, China)

##  Ideas for NASA – NOAA – DOE Joint Efforts

**Joint Program Science Goals**
- Weather – Improve 1-14 day forecast
- Climate
- Demo of Platform and Sensor Capability
- Emergency Response (DHS, Wildfire)
**Approach**
- Multiple platform types
- Aerosond
- Hale ROA
- Test Dallgater concept (?)
- Cooperation with International Organizations
- e.g. THORPex & IPY
- Comparison to Satellites (e.g. things satellites do not do well)
- Joint Campaigns with multiple platform capabilities
**Roles**
- All 3 agencies have complementary roles
- NASA – Technology provider & developer
- NOAA – Operational user
- DOE – Research use
- All – Instruments, science & mission requirements

**Observations**
- Weather
- Adaptive Observations in NE Pacific
- Model-driven
- Fast response (24 ours)
- Consistent with THORPex
- Hurricanes
- Arctic – adaptive observations
- Climate
- Arctic
- Full Atmosphere Characterization
- All weather
- Eulerian and Iangrangian
- Surface Characterization
- Area, Depth, Density of ice
- Snow/water equivalent
- Openings, free water
- Carbon
- Tundra, High Latitude, Inaccessible Areas
- Emergency Response
- Plume characterization

##  Ideas for Innovative Uses of UAV’s

**Contingency Deployment**
- Urban emergencies
- Natural disasters
- Adaptive Observations
**Multi-use Systems**
- Combined missions
- Border surveillance
- Communication relay
- Weather surveillance
- Education mission monitoring (Cameras & web page)
- Outreach
**Miniaturization / Cost Reduction**
- Instrumentation
- Flight platform – frangible (?) (size)
**UAV Ensembles**
- Swarms
- Parent/Child
- Sampling upward – deploying inexpensive rocket sonde
- Dispersive platforms (break apart, come together)
- Deployment from piloted aircraft

**Peer to Peer Transmission Strat.**
**Ruggedized Platforms**
- De-icing
- Thunderstorm Penetration
- Adaptable aerodynamics
**Interactive Mission**
- Requests
- Queued priorities
**Intelligent Phenomenological Monitoring**
- Fronts
- Plumes
**Power Alternatives**
- Soaring exploitation
- Piezio electric

**Space Environment Monitoring**
- Planetary missions
- Extreme upper atmosphere sampling
**Surface Sampling – UAV Lands VSTOL**
- Ice/Water
- Landsurface
**Inflight Refueling**
- Extended Missions
- Fleet Support
**Tethered Platforms**
- Fixed urban obs with vertical crawler
- Environmental remote sensing
**Data Processing on UAV**
- Transmission efficiency

## UAV-Enabled Global Observation System

**Suggested Approach**
- Systems engineering approach
- Proof of concept demos
- Mixed platform approach
- Develop CBNOPS
- Integrate with satellites & ground demo
- Integrate with other US agencies and international agencies
**Potential Benefits**
- Risk reduction to CCSP
- Allows science unavailable from satellites or instead of satellites
- Increases the value of satellites
**Performance Capability Objectives**
- Safe & efficient
- Grid-based sustained measurement system
- Data and ops needs to be networked with ground, UAV’s and satellites
- System needs to be able to support vertical profiles
- 0-100,000ft
- Dropsondes, MEMS
- Altitude change
- Long endurance > 24hours
- Deployable – world wide coverage
- Flexible & adaptable observations
- Complementary platform & solutions (hi & low speed)
- Global airspace operations

**Relationship to National Priorities**
- Climate change science program
- Global Earth Observation System (GEOSS)
- OSTP R&D Guidelines
- HS
- Network & Info technology
- Namu
- Climate & water **
- Hydrogen fuel cells
**Relationship to Existing Programs**
- Vehicle systems programs
- VPDO
- Access 5/UNITE FAA
- DOD UAV roadmap
**Relationship to Exploration Vision**
- Tech spinoff to PFV
- 100k vehicle similar to Mars
- On-board data/science processing
- Autonomy
**Technology Gaps**
- Communication bandwidth over the poles
- Sensors sized to fit in UAV’s (size, mass, power)
- Robust UAV’s (icing and storm penetration)
- Propulsion & Power
- Autonomy

## Ideas for Next Steps

**Get Senior Management Buy-In for a FY07 New Initiative**
- Establish IPDO-like organization to capture resources
- Vision statement – function of societal/economic impact
- Mission needs statement
- Identify and include stakeholders
- Recruit advocates

**Other Ideas for Next Steps**
- Get Senior Management buy-in
- Get Science Committee buy-in
- Get INO buy-in
- Identify high level requirements
- Prioritize science needs as a function of scientific impacts
- Identify stakeholders
- Identify capabilities
- Develop technology gaps and roadmaps
- Risk assessments
- Identify barriers
- Perform analyses of alternatives
- Perform proof of concept demos & pilot projects
- Define success criteria
- Establish milestones & project structure
- Training and marketing
- Create joint organization
- Identify and coordinate existing efforts that contribute to our goals
- Stoke the energy!