and up to the thermal imaging camera of the satellite. For strong detection it is important that the background be warm in comparison to the aerosol. A thermal background such as from the ocean surface, land or low clouds, works best because warm objects radiate more and result in greater amounts of scattered radiation, light-particle 'collisions' if you will.
As a cooperating member of EUMETSAT
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of the data and the state
of the instruments that are still running is in many cases not known. The Reykjavík series from the
old harbour is the only one known to be of good quality (not only for some periods) (ibid.), even
though more frequent calibrations would have been needed there too and it is unclear how it is best to
calibrate the instrument since 1994 (Tryggvason, 2017). Proposals of a new sea
/media/vedurstofan-utgafa-2020/VI_2020_005.pdf
morning tremors of April 14, 2010 that provided such an early
warning time for the Eyjafjallajökull eruption. There is not a definitive start time in the
literature for the Eyjafjallajökull summit eruption on April 14, but best estimates of the
eruption place it around 06:00 between two pulses of low-frequency dominant tremor (see
Table 1); visually, there is no tremor pulse directly coinciding
/media/vedurstofan-utgafa-2021/VI_2021_008.pdf
temperature and wind speed over terrain below 100 m above mean sea level (mASL) (see
Figure 4), model grid-points below that level are ignored for the calculation of best linear fits of
vertical profiles. Terrain-following gradients obtained for 2-m air temperature are -6.0 K km 1
in January, and -7.2 K km 1 July. For 10-m wind speed, the terrain-following gradients are 3.4
m s 1 km 1 in January
/media/vedurstofan/utgafa/skyrslur/2014/VI_2014_005.pdf
to
adaptation, the participation of the Province of Ferrara in a partly EU-funded project, the
Climate Alliance’s Adaptation and Mitigation – an Integrated Climate Policy Approach
(AMICA), has allowed the province to access information and best practice networks on
adaptation. Beyond this engagement, the Province of Ferrara and is responsible for
implementing the region’s water and other plans, including
/media/loftslag/Keskitalo_et_al-MLG_and_adaptation_FINAL.pdf
between the sectors, (iv) recognize conflict interests up front.
The next step which the group considered was: 3. Narrow down viable solutions. Here the
group decided only to work on tasks related to the learning cycle part, and identified the
following tasks: (1) scoping, (2) analyse gaps, (3) identify best solutions.
The fourth step which the group identified was: 4. Scenario planning
/media/vedurstofan/NONAM_1st_workshop_summary_v3.pdf
that learning to improve the
next stage of management (Holling, 1978). AM treats
policies and management interventions as experimental
probes designed to learn more about the system; they are
not confident prescriptions (Lee, 1993). Monitoring before
and during the intervention, enables the system response to
be determined and thereby allows managers to learn from
past experience and to translate the best/media/loftslag/Henriksen_Barlebo-2008-AWM_BBN-Journ_Env_Management.pdf
forecasting within the European Meteorological Infrastructure as well as between the
Nordic-Baltic countries, and now also with the participation of the Netherlands and Ireland. Future collaboration
has been initiated this year that will continue to provide IMO with the best forecasts available at minimal costs. The
forecasting system will be operated at IMO premises 2023–2027.
The preparation
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