RISK MANAGEMENT FOR ENERGY INFRASTRUCTURE
Module 2: Climate data-bases. Part 2.
Prepared by Jorge Paz ( Tecnalia)
1.- Presentation of this module
Main objectives
• To determine the climate data that are needed for engineering practice.
• To understand the different sources of climate data available
• To acquire climate data applicable to engineering modelling Operational objectives:
• Differentiate between types of measurements such as direct and indirect, and remote and in-situ measurements
• Identify different types of meteorological observing systems and their observational representativeness including temporal and spatial scales
• Describe instrument and measurement uncertainty
• Understand the factors that are used to assess systematic and random errors, and the propagation of errors.
Recommended resources:
• A computer.
• Spreadsheet software: Microsoft Excel, but Openoffice and other open software is always welcome!!
• A flexible text editor: NotePad++ is an example (Windows Notes isn´t).
• Python: Anaconda platform recommended.
• A compression program: IzArc, etc.
• Google Chrome and a gmail account.
1.- Presentation of this module
Additional materials:
• Copernicus Climate Change User Learning Service (https://uls.climate.copernicus.eu/). It is particularly interesting the lessons on observations: https://uls.climate.copernicus.eu/group/learning/browse-lessons?packageId=1157
• MOOCs from Copernicus:
• https://www.mooc.copernicus.eu
• https://www.atmospheremooc.org/
• https://www.oceansfromspace.org/
• WMO. The main page of interest is: “Observation components of the Global Observing System”:
https://www.wmo.int/pages/prog/www/OSY/Gos-components.html
• NOAA Data access: https://www.ncdc.noaa.gov/data-access. In addition to data for the USA you will find here a description of the different kinds of climate information.
• Eumetrain (www.eumetrain.org), maybe too specialized if you don´t have a particular interest.
• The Comet program (http://www.comet.ucar.edu/). Of special interest the free collection of hundreds of training resources (https://www.meted.ucar.edu/index.php), the COMET Training Portfolio (https://www.comet.ucar.edu/portfolio/index.htm), learning resources (https://www.meted.ucar.edu/training_detail.php) and particularly: Introduction to tropical meteorology (2ndedition), Chapter 9 - Observation, Analysis, and Prediction (http://kejian1.cmatc.cn/vod/comet/tropical/textbook_2nd_edition/print_9.htm).
• ClimateEurope H2020 project: https://www.climateurope.eu/. Review the summary of data sources:
https://www.climateurope.eu/climate-and-society/explore/sources/
• We will not explain the operation of the different instruments, so please take a look to:
• New world climate: Weather Instruments and Equipment Explained: http://www.nwclimate.org/guides/meteorological- instrumentation/
• Sciencing: Weather Instruments & Their Uses:https://sciencing.com/weather-instruments-uses-8013246.html
NOTE: if not indicated, all links accessed on December 2020. Contact me if they don´t work or if you are interested in any particular topic.
1.- Presentation of this module
Contents related to climate data:
1.- Presentation of this module 2.- Introduction to climate 3.- Sources of climate data 4.- Types of observations 5.- Land stations
6.- Ocean in-situ observations 7.- Sondes and airplanes 8.- Radar and Lidar 9.- Satellites
10.- Historical observations 11.- River flow
12.- Homogenization 13.- Climate data sources 14.- Python exercise
Part 1: Numerical Modelling in Energy Sytems
Part 2: Numerical Modelling in Environmental Processes
Python exercise
Radiosondes and dropsondes
A radiosonde is an instrument that is launched by a weather balloon and measures the properties of the surrounding air up to a maximum height of 30-35 km. It measures altitude, pressure, temperature, relative humidity, wind (both wind speed and wind direction) and geographical position (latitude/longitude) and transmits them by radio to a ground receiver. Radiosondes measuring ozone concentration are known as ozone sondes.
Dropsondes are the same device but then dropped from an airplane and are usually used in special weather situations, for example in hurricanes.
Additional resources:
[1] UCAR: What is a Dropsonde?: https://www.eol.ucar.edu/content/what-dropsonde [2] Video about dropsondes: https://youtu.be/reacmYzS8BU
7.- Sondes and airplanes
Land Automatic station
http://www.aemet.es/es/noticias/2018/12/sondeos_huelva
Dropsonde. Source: [2]
Radiosondes
The global network of upper-air stations totals about 1,300. In this facilities radiosondes attached to free-rising balloons are released, making
measurements of pressure, wind velocity, temperature and humidity from just above ground to heights of up to 30km.
Over two thirds of the stations make observations at 0000UTC and 1200UTC.
Between 100 and 200 stations make observations once per day.
In ocean areas, radiosonde observations are taken by about 15 ships, which mainly ply the North Atlantic, fitted with automated shipboard upper-air sounding facilities (ASAP). A subset of upper-air stations comprises the GCOS Upper-air Network (GUAN).
OSCAR/Surface is the World Meteorological Organization's official repository of WIGOS metadata for all surface-based observing stations and platforms (including surface, upper air, sea, etc.)
Additional resources:
[1] Guan network: https://gcos.wmo.int/en/networks/atmospheric/guan [2] Oscar Surface: https://oscar.wmo.int/surface/#/
7.- Sondes and airplanes
List of Upper Air stations as of November 2017. Source:
https://www.wmo.int/pages/prog/www/OSY/Gos- components.html
Radiosondes
GCOS Reference Upper-Air Network
The global network consists of about 1,300 upper-air stations (2018). Over two thirds of the stations make observations at 00:00 UTC and 12:00 UTC. Between 100 and 200 stations make
observations once per day. In ocean areas, radiosonde observations are taken by about 15 ships (2018), which mainly ply the North Atlantic, fitted with automated shipboard upper-air sounding facilities
Additional resources:
[1] Video on the Gruan network, flyers, etc: https://www.gruan.org/documentation/public-outreach
[2] Gruan data and documentation at C3S: https://cds.climate.copernicus.eu/cdsapp#!/dataset/insitu-observations-gruan-reference- network?tab=overview
7.- Sondes and airplanes
GCOS Reference Upper-Air Network. Source:
https://www.gruan.org/
Data from planes
Aviation is one of the leading sectors in using climate observations, but at the same time a great source of climate data.
In collaboration with ICAO (International Civil Aviation Organization) and commercial and other airlines, aircraft-based observations are received from over 3000 aircraft, providing reports of pressure, winds, temperature, humidity, turbulence and other parameters during flight.
The Aircraft Meteorological Data Relay (AMDAR) system makes high quality
observations of winds and temperatures at cruising level as well as at selected levels in ascent and descent (see figure). The amount of data from aircraft has increased dramatically during recent years - from 78,000 observations per day in 2000 to more that 800,000 observations per day in 2017. Providing great potential for
measurements in places where there is little or no radiosonde data, these systems are making a major contribution to the upper-air component of the GOS.
Additional resources:
[1] WMO: services for aviation: https://community.wmo.int/activity-areas/aviation
[2] WMO: COMET AMDAR Module Produced for WMO. https://public.wmo.int/en/resources/meteoworld/comet-amdar-module-produced-wmo
7.- Sondes and airplanes
The AMDAR Communication System. Source: [2]
Summary for sondes and airplanes Advantages:
-Vertical profiles of the air.
-High quality direct observations.
-Increasing amount of data.
-Aircraft measurements also provide data from above the oceans.
Disadvantages:
-No long time series.
-No fixed location (sondes drift with the wind).
-No global coverage. Lower coverage in the southern hemisphere, on the ocean and the polar regions.
-Only 1 or 2 measurements per day.
7.- Sondes and airplanes
Weather radars
Weather radars (Radar Detection And Ranging) have been used in the detection of precipitation (rates) since the 1950s.
The top figure shows an example of an rainfall radar image. In principle the method is based on sending out a radar pulse and measuring the return signal. This signal has to be translated into a precipitation rate with the help of in situ measurements (see top panel).
Dual polarized or doppler radars (as this one) can measure wind and rainfall.
They enable more accurate determination of precipitation types and sizes.
This makes it easier to see whether the precipitation consists only of rain or also contains snow or hail.
Radar networks have been established around the world. A radar network database is maintained by the WMO and is important to assist with the international exchange of radar data and to protect radio-frequency spectrum allocation.
Sources:
[1] Meteogalicia: radar: https://www.meteogalicia.gal/observacion/radar/radar.action?request_locale=gl [2] NOAA: Using and Understanding Doppler Radar: https://www.weather.gov/mkx/using-radar
[3] NWSVegas: How weather radar works: https://www.youtube.com/watch?v=ItuNNhY5WBw&feature=emb_logo [4] WMO: Weather Radar Observations: https://community.wmo.int/activity-areas/weather-radar-observations
8.- Radar and Lidar
Radar: external view and visualization of data.
Source: [1]
Lidar
Instead of using a radar pulse, Lidar (Light Detection And Ranging) uses laser light to study atmospheric properties from the ground up to the top of the atmosphere or from aircrafts to the ground. Such instruments have been used to study, among others, atmospheric gases, aerosols, clouds, wind and temperature.
8.- Radar and Lidar
Example of lidar emission and reception. Source:
https://www.monocrom.com/en/applications/defense/lidar-technology/
Example of Lidar observation. Source: UCAR:Raman-shifted Eye-safe Aerosol Lidar (REAL)
https://archive.eol.ucar.edu/docs/isf/facilities/lidar/eyesafe_lidar/old_eyesafe_lidar_w ebpage.html
HFR on coastal areas:
High-frequency radar (HFR) is a unique technology mapping ocean surface currents and wave fields (along with other variables) over wide areas with high spatial and temporal resolution. HFR is cost-effective, requiring only small manpower and technical costs.
Users of HFR technology include meteorology services, search and rescue agencies, governments and regional and local authorities, as well as private companies working in assessment of coastal water quality, renewable energy, or other environmental services.
The EuroGOOS HFR Task Team helps coordinate the European activities around the development and use of this coastal technology. 30 stations are connected to the HFR node sending data in near real-time.
8.- Radar and Lidar
HFR. Source:[1]
Additional resources:
[1] EuroGOOS: services for aviation: https://community.wmo.int/activity-areas/aviation
[2] L. Corgnati et al.: The European HFR Node from the standard data and QC model to data distribution (presentation):
https://www.seadatanet.org/content/download/2845/file/2019_04_09_EGU2019_pres_HFR_Corgnati.pdf
Map of locations of the 105 HFRs included in the EuroGOOS Task Team inventory (March 2020).
The ongoing systems (59) are plotted in green, future installations (20) in yellow and non- functioning stations (26) in purple (including historical deployments or currently inactive stations). Source:[1]
Pros and cons of radar and lidar images Advantages:
• Higher spatial coverage than ground measurements
• High frequency measurements
• Data almost directly available
• Information about the upper air Disadvantages:
• Time series from about the end of the 90’s until present.
• The lidar and radar signal has to be translated into the desired climate variable. This introduces additional uncertainties and ground observations are needed to make this translation
• Systematic disturbances in the signal due to the atmosphere
• No global coverage. Lower coverage in the southern hemisphere, on the ocean and the polar regions.
8.- Radar and Lidar
Radar operated by Euskalmet. Source:
https://apps.euskadi.eus/s07-
5853x/es/meteorologia/meteodat/dominio _radar.apl?e=5
Weather Satellites: introduction
The first weather satellite was launched in 1960. Since then, many more satellites were launched providing a huge amount of atmospheric data.
You must think on satellites as platforms where, generally, several instruments are boarded. E.g: The first satellite mission designed to measure CO2 was the Interferometric Monitor for Greenhouse Gases (IMG) on board the ADEOS I satellite in 1996.
Meteorological satellites are equipped with visible and infra-red imagers and sounders from which one can derive many meteorological parameters, like clouds, temperature, humidity, radiation, wind, wave height, wave patterns, sea currents, ice coverage, greenhouse gases and much more.
9.- Satellites
SEVIRI instrument boarded on Meteosat 2nd generation satellites. Source [3]
Additional resources:
[1] EUMESAT: video describing the second generation of METEOSAT satellites:
https://www.youtube.com/watch?v=SSjjoa7ILpw&feature=emb_logo(4`30``
aprox)
[2] EUMETSAT: Short video describing the operation:
https://www.youtube.com/watch?v=f3XgfHSVBhc(10` aprox) [3] EUMETSAT: SEVIRI: https://www.eumetsat.int/seviri
Representation of the Meteosat generations (from left, frist, second, third and third. Source Eumetsat
(https://www.eumetsat.int/our -satellites/meteosat-series)
How do satellites measure (1)?
There are two main kinds of satellite sensors:
- Active sensors have its own source of light or illumination. In particular, it actively sends a pulse and measures the backscatter reflected to the sensor.
- Passive sensors measure reflected sunlight emitted from the sun. When the sun shines, passive sensors measure this energy.
One example of active sensor is the Synthetic aperture radar (SAR) equipped in the Sentinel 1 satellites. Different kind of information can be derived from this sensor, with the ability to “observe” in all weather and in day or nighttime.
9.- Satellites
Illustration of vessels in Algeciras Bay on September 2017,
Copernicus Sentinel Data. Source:
[1]
Wind speed derived from
Sentinel-1 data over the Typhoon Megi, processed as part of the ESA/SEOM 4 Science/Ocean Study project #EO4Society. Contains modified Copernicus Sentinel data [2016]. Source: [1]
Sources:
[1] ESA: https://sentinel.esa.int/web/sentinel/user-guides/sentinel-1-sar/applications/maritime-monitoring [2] https://gisgeography.com/passive-active-sensors-remote-
sensing/#:~:text=Active%20sensors%20have%20its%20own,passive%20sensors%20measure%20this%20energy.
Passive vs active sensors.
Source: [2]
Satellites: orbits
Geostationary: travelling at the same rate as Earth. This makes satellites appear to be ‘stationary’ over a fixed position from the earth. Travel at 3 km per second and an altitude of 35 786 km.
Polar orbit and Sun-synchronous orbit (SSO): travel from north to south rather, passing roughly over Earth's poles. Satellites in a polar orbit do not have to pass the North and South Pole precisely, and at low altitudes between 200 to 1000 km.
Sun-synchronous orbit (SSO) is a particular kind of polar orbit. Satellites are synchronized to always be in the same ‘fixed’ position relative to the Sun.
This means that the satellite always visits the same spot at the same local time
Low Earth orbit: normally at an altitude of less than 1000 km but could be as low as 160 km
Other: Transfer orbits and geostationary transfer orbit (GTO), used to travel between orbits, Medium Earth orbit (MEO), common for navigation
satellites, Lagrange points,
9.- Satellites
Source: ESA: Types of orbits:
https://www.esa.int/Enabling_Support/Space_Transportation/Types_of_orbit
Geostationary orbit
Low earth orbit Polar orbit and Sun-
synchronous orbit
(SSO)
How do satellites measure??
Meteorological satellites equips mainly passive sensors that capture multispectral radiation.
Solar short wave radiation is reflected by the earth and atmosphere and is measured by satellites. Also long wave radiation from the earth reaches the satellites´ instruments.
Different greenhouse gases absorb radiation at different wavelengths, so the amount of radiation that reaches the satellite at different wavelengths says something about the
composition of the atmosphere. Note that different gasses may interfere: clouds (may impede to study the NOx concentrations).
9.- Satellites
Transmission of shortwave solar irradiation and long wavelength radiation from the Earth's surface through atmosphere. Source: [2]
Source:
[1] NASA: What is Earth’s Energy Budget? Five Questions with a Guy Who Knows: https://www.nasa.gov/feature/langley/what-is-earth-s-energy-budget-five- questions-with-a-guy-who-knows
[2] Peng-Sheng Wei et al. Absorption coefficient of water vapor across atmospheric troposphere layer.
https://www.sciencedirect.com/science/article/pii/S2405844018327415#bib2
Earth energy Budget. Source [1]
Exercise on Satellites orbiting
1.- Visit http://stuffin.space/. You will be able to visualize the objects orbiting the earth, including both satellites (identified as payload) and debris Or “DEB”. With such a huge number of satellite and debris orbiting, is it possible that some of them crash with others? Answer:
- See this video; https://www.youtube.com/watch?v=BiHY5dR5Jsg - Look for “Iridium 33” in stuffin.space.
2.- What are the main areas of concentration of the satellites. How is this related with the kind of orbits explained in the previous slide?
3.- Look for the GOES satellites? Where are they located? Are their orbits similar to Meteosat family? Which country launched them? Do you see any advantage from launching these families of satellites from spaceports situated near the Ecuador (e.g. French Guiana)?
4.- Use the search function. Do you find any pattern for these two families in relation to their age? How is the orbit of GOES 15 and 17 in relation to the older ones? Meteosat 10 and 11 in relation to 1, 2, 3, etc.? Why?
5.- Look for the Sentinels satellites. What is their orbiting pattern?
6.- Some of this satellites are flying in formation (e.g. Sentinel 1a &1b,) what is their relative position? Why are they flying in this way?
7.- Look for the Galileo and Glonas satellites. Where are they orbiting? What kind of satellites are?
8.- Look for Starlink trains of satellites (you will not need the search function for that)? What orbit are they following?
What region are they avoiding? Why? Are they bellow or over the ISS?
9.- Satellites
Image of an Starlink “train” of satellites from earth
A computer-made image of objects in Earth orbit currently being tracked.
Source: [2]
Sources
[1] EURONEWS: Light pollution from SpaceX satellites may block view of stars, astronomers warn:
https://www.euronews.com/2019/05/29/light-pollution-from-spacex-satellites-may-block-view-of-stars-astronomers-warn [2] NASA: Where Do Old Satellites Go When They Die?: https://spaceplace.nasa.gov/spacecraft-graveyard/en/
Meteorological satellites: data access (1)
Usually, raw satellite information (level 1) need specialized processing to become useful. Usable products are generally denominated as level 2 or level 3 products.
You can find this information in:
CM SAF: The Satellite Application Facility on Climate Monitoring develops, generates, archives and distributes high-quality satellite-derived products of the global energy & water cycle and related sustained services in support to
understand our climate. This source provides:
Operational Products:
• Cloud products
• Surface radiation products
• Radiation fluxes at the top of atmosphere
• Water vapour and temperature products Climate Data Records
• Climate Data Records with DOI
• Cloud products
• Surface radiation products
• Radiation fluxes at the top of atmosphere
• Water vapour and temperature products
• Miscellaneous
9.- Satellites
Source: [1] CM SAF data portal. https://wui.cmsaf.eu/safira/action/viewProduktSearch
CM SAF data portal. Source: [1]
Meteorological satellites: data access (2).
The World Data Centre for Remote Sensing of the Atmosphere (WDC-RSAT) offers free and simplified access (in the sense of a
"one-stop shop") to a continuously growing collection of atmosphere-related satellite-based data sets and services. These data holdings are available on-line and range from raw data collected by remote sensors to higher level data and information
products. You can check the list of the missions and sensors. There are several operational servicesfor Air Quality Forecasting and Monitoring, Stratospheric Ozone Monitoring, Solar Energy, etc, but some of them focus on Central Europe.
You can start exploring the Map-explorer, but one of the handiest ways of accessing data is the ftp server (under request).
9.- Satellites
GOME-2 (Global Ozone Monitoring Experiment-2 ) / MetOp: Latest data products. (Product status is "operational") on 24/01/20 [1]
Sources
[1] WDC-RSAT: GOME-2 (: https://wdc.dlr.de/sensors/gome2/
Meteorological satellites: data access (3).
Other sources of satellite data are:
• Copernicus Open Access Hub: (previously known as Sentinels Scientific Data Hub) provides complete, free and open access to Sentinel-1,
Sentinel-2, Sentinel-3 and Sentinel-5P user products, starting from the In- Orbit Commissioning Review (IOCR).
• Copernicus Data and Information Access Service (DIAS): five cloud-based platforms providing centralised access to Copernicus data and
information, as well as to processing tools.
• Sentinel hub: Cloud api for satellite imagery. It also includes a nice browser (EO Browser)
• And many more: Google Earth Engine, Open Data Cube (ODC), System for Earth Observation Data Access, Processing and Analysis for Land
Monitoring (SEPAL), openEO, JEODPP, and pipsCloud (see [5] for a comparison).
9.- Satellites
Infographic of the DIAS [2]
Sources
[1] Copernicus Open Access Hub: https://scihub.copernicus.eu/
[2] DIAS: https://www.copernicus.eu/es/acceso-los-datos/dias
[3] The DIAS: User-friendly Access to Copernicus Data and Information: https://www.copernicus.eu/sites/default/files/Copernicus_DIAS_Factsheet_June2018.pdf [4] Sentinel hub: EO Browser: https://apps.sentinel-hub.com/eo-browser/
[5] Vitor C. F. Gomes et al: An Overview of Platforms for Big Earth Observation Data Management and Analysis: https://www.mdpi.com/2072-4292/12/8/1253/pdf
EO Browser
from Sentinel hub. Source [4]
Satellites´ summary
The main advantages and disadvantages of satellite data for atmospheric surface climate data are:
Advantages:
-High spatial coverage (data for regions without ground stations are available) and high spatial resolution.
-Data almost directly available.
Disadvantages:
-Time series from about the end of the 90’s until present.
-The satellite signal has to be translated into the desired climate variable. This introduces additional uncertainties and ground observations are needed to make this translation.
-Systematic disturbances in the signal due to the atmosphere.
9.- Satellites
Example of the consideration of different sources for studying the temperature: Land Surface temperature (LST) derived from satellite observation and air temperature (AT) measured at ground stations. Source: [1]
Source:
[1] The Urban Heat Island Effect in the City of Valencia: A Case Study for Hot Summer Days. https://www.mdpi.com/2413-8851/1/1/9/htm
Types of historical observations
The first daily time series start around 1850 but were still very scarce. From about 1950 on there was a much better coverage with weather stations. The first climate data were recorded manually, but many have been digitalized by now.
Records of the climate before the start of the regular measurement around 1850 are scarce. Therefore, scientists have used other types of information to estimate climate variables further back in time.
- Old shipping reports mentioning the weather at sea
- Corals can be used to estimate oceanic temperature and sea-level changes
- Tree-rings and ice-cores can be used to infer changes in temperature and precipitation.
- Boreholes
- Fire records, extreme events news, etc.
- Paleolimnology - Pollen
- Etc.
10.- Historical observations
Additional resources:
[1] NOAA: Paleo Data Search https://www.ncdc.noaa.gov/paleo-search/
Old records
Millions of (mainly wind) observations were made from ships in the late 19th and early 20th centuries or even earlier. Until recently they were only available from paper logbooks, but gradually they are being digitized. Some of these have been included in the latest assessments of climate, like the Intergovernmental Panel on Climate Change (IPCC) report. However, many more logbooks have yet to be included. Also, other written reports, like farmers’ logs, travelers’ diaries and newspaper accounts can tell us something about past climates.
10.- Historical observations
The original Beaufort logbook and scale (Sir Francis Beaufort,1805). Source: [1]
Sources:
[1] WMO: Meteorology and Marine Transportation: https://public.wmo.int/en/bulletin/meteorology-and-marine-transportation
[2] The Verge: Why century-old ship logs are key to today’s climate research: https://www.theverge.com/2019/5/3/18528638/southern-weather-discovery-ship- logs-climate-change
[3] El Pais: Un dibujo de Humboldt de hace 200 años prueba el cambio climático. https://elpais.com/elpais/2015/09/13/ciencia/1442177267_935134.html
Picture of the Chimborazo flora by Alexander von Humboldt (1802). Source: [3]
Daily record of pressure, temperatura, wind (and captures) from a whaler (1948). Source: [2]
Old records (2)
Datasets that extend back in time are key to validating climate simulations; by measuring the outputs of computer models against known past events, scientists can
understand how accurate they are at predicting what might happen to our planet in the future. The Copernicus Climate Change Service (C3S*) has been supporting the collection of such historical data through its collaboration with the
National Oceanic and Atmospheric Administration’s National Centers for Environmental Information. A paper summarize the first findings of this collaboration (see [2])
10.- Historical observations
Location of land-based stations inventoried at each timescale operational with at least one ECV during specific time slice periods. Left panel: sub-daily stations [red dots], central panel: daily stations [blue dots] and right panel: monthly stations [black dots]. Source: [2]
Sources:
[1] C3S: New C3S service facilitates the collection of historical climate data https://climate.copernicus.eu/new-c3s-service-facilitates-collection-historical-climate- data
[2] Simon Noone et al. (2020): Progress towards a holistic land and marine surface meteorological database and a call for additional contributions.
https://doi.org/10.1002/gdj3.109
Trees
Trees can live for hundreds—and sometimes even thousands—
of years (The methuselah trees of California are thought to be almost 5,000 years old). Over this long lifetime, a tree can experience a variety of environmental conditions: wet years, dry years, cold years, hot years, early frosts, forest fires and more.
Tree rings can tell us something about the conditions the tree grew in. For example, rings usually grow wider in warm, wet years and they are thinner in years when it is cold and dry. If the tree has experienced stressful conditions, such as a drought, the tree might hardly grow at all in those years. Scientists can
compare modern trees with local measurements of temperature and precipitation from the nearest weather station. Very old trees can give information about the climate before regular weather observations started.
10.- Historical observations
Diagram showing how the color and width of tree rings can provide snapshots of past climate conditions. Source: [1]
Additional references:
[1] NASA: Tree rings provide snapshots of Earth's past climate. https://climate.nasa.gov/news/2540/tree-rings-provide-snapshots-of-earths- past-climate/
Corals
The way corals can tell us about past climates is comparable to tree rings.
Like their land-based counterparts, corals add seasonal layers, which appear as bands in their hard calcium-carbonate shells. Corals respond to small changes in temperature, rainfall, and water clarity in a matter of months, making them a uniquely sensitive climate record.
10.- Historical observations
Coral bands: Each of the light/dark bands in this x-ray of a cross- section of a coral core formed during a year of growth. The surface of the coral (grown most recently) is on the left, and older bands extend to the right. (X-ray image courtesy Thomas Felis, Research Center.
Source: [2]
Sources
[1] NOAA: Picture Climate: How We Can Learn from Corals: https://www.ncdc.noaa.gov/news/picture-climate-how-we-can-learn-corals
[2] NASA: Climate Close-up: Coral Reefs: https://earthobservatory.nasa.gov/features/Paleoclimatology_CloseUp/paleoclimatology_closeup_2.php
Like trees, corals produce annual rings that store a record of past conditions.
Chemical analyses reveal details about past temperature, nutrient availability, salinity, and other information. Source:
[1]
Change in oxygen-18 isotopes measured in coral cores on Tarawa Island. The Southern Oscillation and The Southern Oscillation Index Source: [2]
Ice cores (1)
In the polar regions and high in the mountains ice has accumulated from snowfall over many millennia. Scientists drill out ice cores from these ice sheets or glaciers. Most ice core records come from Antarctica and Greenland, and the longest ice cores extend to 3km in depth. The oldest continuous ice core records to date extend 123,000 years in Greenland and 800,000 years in Antarctica.
10.- Historical observations
The gradually increasing weight of overlying layers
compresses deeply buried snow into ice, but annual bands remain. Relatively young and shallow snow becomes packed into coarse and granular crystals called firn (top: 53 meters deep). Older and deeper snow is compacted further (middle: 1,836 meters). At the bottom of a core (lower: 3,050 meters), rocks, sand, and silt discolor the ice.
Source: [1]
Sources
[1] NASA earth Observatory: Paleoclimatology: The Ice Core Record: https://earthobservatory.nasa.gov/features/Paleoclimatology_IceCores [2] Ice Core Facility: https://icecores.org/about-ice-cores
The dark band in this ice core from the West Antarctic Ice Sheet Divide (WAIS Divide) is a layer of volcanic ash that settled on the ice sheet approximately 21,000 years ago.
Source: [2]
Ice cores (2)
The ice cores can provide an annual record of temperature, precipitation, atmospheric composition, volcanic activity, and wind patterns. In a general sense, the thickness of each annual layer tells how much snow accumulated at that location during the year. The ice encloses small bubbles of air that contain a sample of the atmosphere. From these it is possible to measure directly the past concentration of gases (including carbon dioxide and methane) in the atmosphere.
10.- Historical observations
Close-up of deuterium (temperature proxy) and CO2 from the EPICA Dome C ice core over the warming from the last glacial period. [1]
Sources
[1] https://www.bas.ac.uk/data/our-data/publication/ice-cores-and-climate-change/
Oxygen isotope ratio (temperature proxy) from the NorthGRIP (Greenland) ice core showing a sequence of rapid temperature jumps. [1]
River Flow
River flow is measured with very diverse techniques, but the most common is the continuous measurement of heights upstream of a hydraulic control or at another location where a unique height-flow relationship can be established.
Periodic gauging is carried out on the entire range of flows that the river can reach (in drought, medium water, and floods), mainly by exploring the velocity fields in each section.
In Spain the next sources o river flow may be consulted:
- Web pages of the hydrographic authorities (SAIHs) - MITECO: Mapa de caudales máximos en régimen natural - CEDEX: ANUARIO DE AFOROS. MODALIDADES DE CONSULTA.
11.- River flow
Sources
[1] FAO (1997): Medición sobre el Terreno de la Erosión del Suelo y de la Escorrentía. Capítulo 4: Caudal [2] Enciclopedia of the environment: Hydrometry: measuring the flow rate of a river, why and how?
Parshal type measurement channel [1]
Hydrometric reel and principle for gauging [2]
Fiche for station at CEDEX database System of
information for the Ebro basin.
What is homogenization?
Meteorological time series may become inhomogeneous for reasons such as
- relocations of stations and/or instruments,
- slow or abrupt changes in the environment (trees, buildings, etc. in the surroundings, urban sprawl, etc.) - changes in instruments and measurement practices
(Introduction of Automatic Weather Stations or new types of instruments, Quality control and data recovery
procedures)…
For climate change and variability studies, it is important to deal with these potential sources of
inhomogeneities and obtain homogenized datasets. The aim of climate data homogenization is to adjust climate records, if necessary, to remove non-climatic factors so that the temporal variations in the adjusted data reflect only the variations due to climate processes.
12.- Homogenization
A hundred years long wind data series from an official rural station (Canterbury,
New Zealand) spoiled by gradual changes in surroundings (Source:[1])
Additional references:
[1] WMO: Guidelines On Climate Metadata And Homogenization [2] WMO: Climate data homogenization
Template proposed by the Commission on Instruments and Methods of Observation for documenting station location. Source [1]
What is homogenization?
Homogenisation is only one step in the processing of climate data. Previous steps influence the quality of the homogenization. Before homogenising a dataset it is important to know how the variable was measured historically throughout the network and what happened with the stations.
All this should be taking into account in the subsequent validation and climate data analysis.
There are different approaches, but generally, the main goal is to identify the “breaks” and comparison with reference stations is the key approach.
12.- Homogenization
Sources:
[1] Victor Venema et al. (2018): Guidance on the homogenisation of climate station data: https://osf.io/preprints/eartharxiv/8qzrf/download An example of unrepresentative data before a
change. At Gayndah, Australia (blue line), the screen deteriorated progressively after 1940, before it was replaced in October 1945. The maximum temperature difference (green line) between Gayndah and the mean of three reference sites, Dalby, Brisbane and Emerald (red line), increased from 1.0°C to about 1.5°C in the years before the screen change, before dropping to 0.7°C after the change. Source [1]
Overall process from data rescue to climate analysis. Source [1]
How do we approach the homogenization?
Even small changes in the configuration of the stations, may affect the measurements. In this cases is important to detect “break points” in the series, something that is not always possible (e.g. changes in the shelter, in the procedure for calculating mean temperature, installation of new equipment's, etc.). However, one of the most typical case of inhomogeneity is urban heat island, vegetation growth, etc. and sometimes, we should think on trends.
12.- Homogenization
Three meteorological shelters next to each other in Murcia (Spain), employed to study the influence of changes in measurement techniques. Source [1]
Additional references:
[1] Kevin Cowtan (2015): Homogenization of Temperature Data An Assessment [2] Domingo Rasilla et al. (2019): Heat Waves and Human Well-Being in Madrid (Spain)
[3] Manola Brunet et al. (unknown): A case-study/guidance on the development of long-term daily adjusted temperature datasets Long-term trends in the number of summer (JJA) tropical
nights (daily minimum temperature > 20 ºC) at Madrid- Retiro and Torrejón de Ardoz. Source [2]
How do we approach homogenization?
The date of the changes that affects the measurements are often documented (called meta data: data about data), but not always. Meta data is often only available in the local language.
But, sometimes, changes are not recorded. For this reason, many studies homogenize time series before calculating trends and variability.
Homogenization is then mostly done in a statistical way by calculating corrections from mutual comparisons of stations (relative homogenization).
12.- Homogenization
Additional references:
[1] Wikipedia: Homogenization (climate), https://en.wikipedia.org/wiki/Homogenization_(climate)
[2] T. Brandsma De Bilt : KNMI (2016): Homogenization of daily temperature data of the five principal stations in the Netherlands (version
1.0)http://publicaties.minienm.nl/documenten/homogenization-of-daily-temperature-data-of-the-five-principal-stations-in-the-netherlands-version-1-0
Question: now that you know almost all sources of meteorological observations, think for 5 minutes how Coronavirus crisis may
affect it and write 3 activities that may be reduced. Then read this article from WMO: COVID-19 impacts observing system
https://public.wmo.int/en/media/press-release/covid-19-impacts-observing-system. Is this a source of inhomogeneities ?
13.- Climate data sources
National services
If you need climate data, the first source to look for are national meteorological services ( AEMET in SpainUK metOffice in UK, MeteoFrance in France, etc. )
Regions, states, and other subnational entities also provided important data. In Spain, Galicia, Catalonia and the Basque Country, with
operational meteorological services, are an important source of data, but also others.
Check also the Air Quality monitoring networks (they also monitor temperature, precipitation, etc.) operated by municipalities and regions.
Hydrological information could be provided by the national
meteorological service (e.g. Inamhi – Ecuador, SMHI –Suecia, etc.) or basin authorities (hidrolographic confederations in Spain)
Marine observations usually are provided by an independent source:
Puertos del Estado in Spain, NOAA in USA, etc.
Additional information:
[1] AEMET: AEMET OpenData.
[2] Junta de Andalucía: Red de Informacion Ambiental de Andalucía
Different sections of the OpenData portal, by Aemet [1]
Precipitation and temperatura anomalies
from REDIAM [2]
KNMI climate explorer
The KNMI climate explorer, now is available at the WMO web site,
is a growing and very extensive catalogue of data including:- Meteorological station data (Daily data, Daily climate indices, Monthly station data, Monthly climate indices, Annual climate indices, etc.) - Gridded observations like: HadCRUT5, etc
- Reanalysis,
- Seasonal forecasts
- Long term projections: CMIP3. CMIP5, CMIP6, Cordex, - Etc.
- Other: Ozone, length of day, currents, sunspots….
It is also possible to upload your time series an visualize them.
Allows to perform interesting operations as:
Compare different time series.
Filters (running means)
Combine with another timeseries to form a (normalised) index Mask out: Mask out based on another time series
Extend: Extend with another time series
Noise: Make 100 random series with the same mean, variance and autocorrelation It is very powerful but designed for expert users. It is not very intuitive and requires training,
Additional information:
[1] ECA&D: https://climexp.knmi.nl/start.cgi
13.- Climate data sources
Daily sunspots as an example of the diverse types of information that is included in the KNMI explorer.
https://climexp.knmi.nl/getindices.cgi?WMO=SIDCData/sunspo ts_daily&STATION=sunspots&TYPE=i&id=someone@somewher e&NPERYEAR=366]
Climdex
This portal focus on climate indices of observed and modelled climate extremes.
13.- Climate data sources
Sources:
[1] Climdex consortium: Climdex.
[2] Climdex: Indices
[3] Paula J. Brown et al. (2010) Changes in Extreme Climate Indices for the Northeastern United States, 1870-2005.
Main
functionalities of Climdex [1]
Datasets hosted in Climdex [1]
List of the 27 ETCCDI Climate indexes.
Source:[3]
NOAA: One Stop and Climate Data Online
NOAA´s One Stop p
rovides:
- Data about weather, climate, satellites, fisheries, coast, oceans - Tools for extracting data, search on inventories, etc.
The Climate Data Online provides free access to NCDC's archive of global historical weather and climate data in addition to station history information.
- Daily Summaries, - Global Marine Data,
- Global Summary of the Month/Year
- Local Climatological Data, Normals (Annual /Seasonal/Monthly/Daily/Hourly) - Historical Precipitation 15 Minute / Hourly
- Weather Radar (different levels of processing)
Land information is restricted to USA, but indexes, satellite and marine information is worldwide in some cases.
Additional information:
[1] NOAA One stop: https://data.noaa.gov/onestop/
[2[ NOAA: Climate Data Online: https://www.ncdc.noaa.gov/cdo-web/
13.- Climate data sources
GHRSST Level 4 G1SST Global Foundation Sea Surface Temperature Analysis: Sea Surface Temperature (kelvin)
NOAA Climate Data Record (CDR) of Atmospheric Layer Temperatures, Version 3.3
13.- Climate data sources
Copernicus Climate Change Service (C3S)
The C3S provide authoritative information about the past, present and future climate, as well as tools to enable climate change mitigation and adaptation strategies by policy makers and businesses.
- Climate datasets:
- Climate products
- Reanalysis (ERA5, ERA5-land, etc.
- Gridded observations (E-OBS)
- Seasonal forecasts (multimodel one-stop-shop) - Climate projections
- Impact indicators - Practical examples of the use of
- Sectorial impacts: Sectorial Information Systems - Tools for using climate data
- Demo and Business cases - Tools:
- Toolbox - Applications - Climate bulletins - Training
- Quality control and assurance - Etc.
Additional information: [1] ECMWF: C3S: https://climate.copernicus.eu/
Concept of the Climate Data Store. Source: [1]
