Benefits accruing from GRUAN - PowerPoint Presentation

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Benefits accruing from GRUAN

Greg Bodeker, Peter Thorne and Ruud DirksenPresented at the GRUAN/GCOS/WIGOS meeting,Geneva, 17 and 18 November 2015

Providing reference quality data

GRUAN is designed to provide reference quality data for:Climate change detection and attribution: long‐term stability and homogeneity

of essential

to robustly detect and attribute changes in

the climate

of the free atmosphere.

Satellite

community:

GRUAN

data are

used to validate

satellite‐based measurements

and

provide input to

radiative transfer calculations

to improve

and evaluate

retrievals.

A

tmospheric

process studies community:

provides

high precision and high

vertical resolution

measurements with defined

uncertainties to

aid

deeper

understanding of the processes

affecting the

atmospheric column

.

NWP

community:

GRUAN data are used to verify

NWP model outputs, and

validate

and

correct other data

being assimilated into NWP models.

GRUAN measurements themselves can be assimilated into NWP models.

Conducting research

The success of GRUAN is contingent on operating at the highest possible standard →

best achieved through

research

published in the

international peer-reviewed

literature for scrutiny by the global community

.

As GRUAN best practices are disseminated across the GOS, GRUAN research underpins the operation of the GOS in general.

Conducting this research entrains expertise from outside the typical monitoring community.

Research conducted within GRUAN strengthens the scientific foundations of the GOS e.g. by contributing to CIMO Guidelines and other GOS prescriptive documentation.

Research example 1

Contributions of different uncertainty terms to the total uncertainty estimate for the GRUAN temperature correction. Total uncertainty

is

Dirksen

, R.J.; Sommer, M.;

Immler

, F.J.; Hurst, D.F.;

Kivi

, R., et al., Reference quality upper-air measurements: GRUAN data processing for the Vaisala RS92 radiosonde,

Atmos. Meas. Tech., 7, 4463-4490, 2014.

the geometric sum of the squared individual uncertainties. Correction model is the estimated vertically resolved error on the temperature based on the estimated actinic flux. Error is subtracted from measured temperature profile to produce the corrected ambient temperature.

Research example 2

Simultaneous solar shortwave radiation, thermal longwave radiation, and air temperature measurements with radiosondes from the Earth’s surface to 35 km altitude during both daytime and night-time.Under

sun-shaded and unshaded conditions, solar radiation produces a radiative heating of about 0.2 K near the surface which linearly increases to about 1 K at 32

km.

Philipona

, R.;

Kräuchi

, A. and

Brocard

, E., Solar and thermal radiation profiles and radiative forcing measured through the atmosphere,

Geophys. Res. Lett., 39, 2012.

Research example 3

Wang et al. correction scheme proven useful for correcting historical radiosonde data → led to a reduction in mean biases and better agreement with independent measurements. Also used to validate pre-flight corrections applied in the Vaisala ground-station software.

Wang

, J.; Zhang, L.; Dai, A.;

Immler

, F.; Sommer, M., et al., Radiation Dry Bias Correction of Vaisala RS92 Humidity Data and Its Impacts on Historical Radiosonde Data,

J. Atmos. Oceanic Technol.

, 30, 197-214, 2013.

Lindenberg: Monthly-mean

PW difference between 1200 and 0000 UTC from the

GPS (blue

) and radiosonde data before (black) and after (red) the

radiation bias correction.

Research example 4

Under most optimistic scenario (no measurement uncertainty), at least 12 years of daily observations needed at SGP to detect trend.Trend detection times at 200 hPa much more sensitive to the frequency of measurements than to the random measurement uncertainties.

Whiteman

, D.N.;

Vermeesch

, K.C.; Oman, L.D. and Weatherhead, E.C., The relative importance of random error and observation frequency in detecting trends in upper tropospheric water

vapor

,

J.

Geophys. Res., 116, D21118, doi:21110.21029/22011JD016610, 2011.

N

umber

of years to detect a trend in upper

tropospheric water

vapour

concentration versus the

total uncertainty

in the

measurements. Range

of

natural water

vapor

variability,

σ

A

,

is 0.56 to 0.75.

Research example 5

Seidel, D.J.; Sun, B.; Pettey, M. and Reale, A., Global radiosonde balloon drift statistics, J. Geophys. Res., 116, D07102, doi:07110.01029/02010JD014891, 2011.Frequency

of balloon drift distances

at 50

hPa for

14 GRUAN sites. Colour

key indicates the percentage

of winds from each of four

directions.

Research example 6

Madonna, F., M. Rosoldi, J. Güldner, A. Haefele, R. Kivi, M. P. Cadeddu, D. Sisterson, and G. Pappalardo, 2014: Quantifying the value of redundant measurements at GRUAN sites. Atmos. Meas. Tech., 7, 3813-3823, doi:10.5194/amt-7-3813-2014.

C

onditional

entropy retrieved

for possible

combinations of instruments measuring integrated water

vapour at SGP site over

2010-2012. Lower values

describe

instrument combinations that more fully characterize the measurand in the atmospheric

column.

Random

uncertainties

can be

strongly reduced by including complementary

measurements.

Can

be applied to the study of other climate variables and used to select the best ensemble of instruments at a given GRUAN

site.

Change Management

GRUAN will play a key role in the management of the change from Vaisala RS92 radiosondes to other radiosonde types as production of the RS92 radiosonde is discontinued.Protocols on how such changes should be managed:Assessing impacts prior to implementation via quantitative assessment.

Overlap period between new and old measurement system.

Embracing change.

Change event notification.

Justification of change.

Validating impacts using

independent, redundant

measurements.

Change from old to

new measurement system

introduces new sources

of

uncertainty

→

must

be captured

in new

uncertainty

estimate.

Managing change is essential to maintaining network homogeneity

.

Data reprocessing

→

changes often necessitate data reprocessing.

Monitoring for unplanned changes.

Use of models to detect systematic biases between old and new measurement systems.

Involvement of manufacturers in change management.

Managing the change away from RS92 (1 of 2)

This is a challenge not just for GRUAN but for the wider WIGOS / GOS / WMO.This is not just about RS92→

RS41. GRUAN is working to ensure competition in the marketplace.

GRUAN will address this change as a network and

not as a set of individual sites

.

GRUAN can play a key role as a result of its emphasis on redundant measurement systems.

GRUAN can also provide laboratory facilities (e.g. at the Lead Centre) to understand sonde differences.

All research conducted on how to ensure homogeneity of the data record, as sites change from RS92 to other radiosondes, will be disseminated to NMSs and in particular to GUAN sites

→

exactly how best to do this is something we should discuss today and tomorrow.

Managing the change away from RS92 (2 of 2)

Dual flights will be conducted at a number of GRUAN sites (sharing the burden) to understand any biases between RS92 and replacement radiosondes → the Lead Centre is in the process of defining how we synthesize the results through a GRUAN-wide strategy.For multiple sites in the same climate zone:

O

ne

site to perform

a full intercomparison over an

extended

period (2

years) of weekly intercomparison measurements, 50-50 distribution

day-night.

O

ther

sites in that climate zone

perform several

week-long intercomparison campaigns of ~10 soundings, evenly distributed over the year to cover various seasons

.

Paper currently in discussion in

Atmospheric Measurement Techniques

Disseminating best practice across the GOS

GRUAN defines a standard of operation designed for one primary purpose → to produce reference measurements.A key attribute of GRUAN is sharing knowledge and expertise across the network →

this is needed to achieve network homogeneity.

Having representation from CIMO, CBS, CCL and CAS in GRUAN governance provides a mechanism for best practices developed in GRUAN to be disseminated across the wider GOS.

GRUAN needs to play a more active role in contributing to documentation developed by CIMO, CBS, CCL and CAS.

GRUAN can provide some leadership by example e.g. an aspirational standard of operation for GUAN sites.

Linking communities

Brings research and operations together: GRUAN has a ‘split personality’ with both strong research facets, and the inclusion of sites that are more ‘research’ sites, and strong operational facets, with the inclusion of purely operational (NMHS) sites in the network. Bringing together these often disparate communities enhances both.GRUAN provides an example of WIGOS in action.Links the measurement community to the metrology community.

Brings users and producers of data together

→

connections to SPARC, GAW, SHADOZ and NDACC.

Brings instrument manufacturers on board.