2D-Blocking

Andy Richling
Institut für Meteorologie, Freie Universität Berlin

Version from November 17, 2016


andy.richling@met.fu-berlin.de

This is a brief documentation about the Freva 2D-Blocking Plugin. Please note the Plugin is originally developed for the Northern Hemisphere (NH), so that the Plugin actually does not work for the SH. Comments or any kind of feedback is highly appreciated. Please send an e-mail to the author.

1 Introduction

Blocking anticyclones are synoptic-scale systems which have a crucial role in atmospheric low-frequency variability. In general, blocking situations persist for multiple days to weeks and block the westerly flow. There exist two basic types of blocking, the dipole block and the omega block. In both of them, in the NH the jet stream is mostly split up into a stronger northern and a weaker southern jet branch. The change of the flow in direction, intensity and position due to the characteristic geopotential height field during a blocking situation can be used to define blockings. The 2D-Blocking Plugin here calculates different 2-dimensional blocking indices focusing the blocking anticyclone region. The indices are basically based on geopotential height gradient reversals and persistent large-scale areas of positive geopotential height anomalies. In opposite to the 1D-Blocking Plugin which only calculates blocking depending on longitudes, the 2D-Blocking Plugin also allows a meridional depending position of blocking events. Besides detecting and displaying blocked grid cells as well as persistent large-scale blocking events on a map, a list of blocking events including some blocking properties (e.g duration, area, centre, intensity) is also be a part of the Plugin. This can be done only for a blocking period of interest (e.g. few weeks) as well as for climatological studies (e.g. whole time period of reanalysis data).

In section 2, the methods of the calculation procedure of the different blocking indices are described. In the following section 3 the processing steps of the spatio-temporal filter algorithm for detecting and tracking persistent and large-scale blockings are shown. Sections 4 and 5 explain the input and output respectively of the 2D-Blocking Plugin.

2 Blocking Indices

In the following section all possible blocking indices which can be calculated with the 2D-Blocking Plugin will be described. By applying these indices, one will get information if a grid cell is instantaneously blocked. Large-scale and persistent blocking events will be filtered with the spatio-temporal algorithm in a second step shown in section 3.

The description of blocking indices is mainly based on the specific default setting of the individual blocking index. Most of the thresholds and calculation options can be changed within the Plugin settings (see section 4.2), even if this is not always mentioned in the following description.

2.1 TM90-2D Blocking Index

The calculation procedure of the ”TM90-2D” called Blocking Index is generally based on the calculation of the 1-dimensional blocking index from Tibaldi and Molteni [1990]. This blocking index is expanded 2-dimensionally by applying the 1D-version to every latitude instead of using only one constant latitude position [Scherrer et al.2006]. As well as in the 1D-Blocking Plugin, additionally the geopotential height at the anticyclone position must exceed a defined threshold (e.g. climatological mean) to avoid cut off lows.

As mentioned above, blocking can be characterized by the distribution of large-scale geopotential height (Z) field. Basically, an area with high geopotential height values is located in the region where the westerlies are originally been placed. Tibaldi and Molteni [1990] use in their 1D blocking index version two geopotential height gradients to compute the instantaneous blocking – the southern geopotential height gradient (GHGS) relating to mid and the northern geopotential height gradient (GHGN) referring to high latitudes respectively.


pict pict

Figure 1: Schematic of the ”TM90-2D” (left) and ”MASATO-2D” (right) Blocking Index.


GHGS = Z(ϕM) Z(ϕS) (ϕM ϕS) , (1)
GHGN = Z(ϕN) Z(ϕM) (ϕN ϕM) . (2)

According to Barnes et al. [2012], a equation can be written to include the dependency of the meridional extent of blocks (δϕ, here we use δϕ = 15). Due to the 2D-expansion, the equations follow

ϕN = ϕC + 3 2δϕ (3)
ϕM = ϕC + 1 2δϕ (4)
ϕS = ϕC 1 2δϕ (5)

to get the required latitudes ϕN, ϕM and ϕS. ϕC represents the individual latitude of interest where a instantaneous blocking can be occur and should be ranged between 30-90N to avoid the subtropical belt of high pressure. Note, that the focus here is more on the anticyclones and to be more comparable to the remaining combined blocking indices (see 2.4), a blocking is latitudinal located where the centre of the anticyclone is placed. Therefore, ϕC was shifted to the position of the anticyclone centre compared to the original equation from Barnes et al. [2012], so that one get:

ϕN = ϕC + δϕ (6)
ϕM = ϕC (7)
ϕS = ϕC δϕ (8)

This option as well as further settings can be changed within the Plugin.

A simple schematic in fig. 1 shows the different latitude locations defining a blocking situation. Referring to fig. 1 (left) a blocking situation can be described when GHGN is associated to a westerly flow north of the blocking anticyclone while GHGS defines an easterly wind equator-ward of the blocking region. Relating to the definition of GHGN and GHGS, the blocking criteria can be described as follow:

GHGS > Emin, (9)
GHGN < Wmin. (10)

Commonly, Wmin is set to -10 meters per degree latitude which is similar to a westerly geostrophic wind of approximately 8 m/s, while Emin is set to 0 meters per degree latitude to reflect at least an easterly flow. In addition to these two criteria, a further criterion is used to define blockings. The individual geopotential height located at ϕM must be exceed a threshold value Zcrit [e.g. climatological mean in Barriopedro et al.2006Scaife et al.2010].

Z(ϕM) > Zcrit(ϕM). (11)

To get the Instantaneous Binary Blocking Index (IBBI), the geopotential height at each longitude on a given day is checked by the described criteria above. If all of the three criteria will be achieved, the individual grid cell on the given time step (e.g. day) is flagged as ”blocked” and gets the value IBBI = 1, otherwise the grid cell is not blocked and IBBI is set to IBBI = 0. An example for detected blocking by this method is shown in figure 2 (top left).

2.2 MASATO-2D Blocking Index

The ”MASATO-2D” Blocking Index is based on the two-dimensional blocking index from Masato et al. [2013a,b] which contains slight modifications again. The index also uses the reversal of geopotential height, but only calculates the difference between the mean of geopotential height of the blocking anticyclone and the corresponding cyclone. This procedure focuses on the reversal of the westerlies and does not regard a split of the jet to the polewards side of the blocking anticyclone. Compared to the ”TM90-2D” Blocking Index only the GHGS part will be considered (see fig. 1 right). The blocking index can be calculated from the difference between the averaged geopotential height of the anticyclone Z?a and the averaged geopotential height of the cyclone Z?c, so that the mean geopotential height difference (GHD) in the NH is given by

GHD(ϕC) = 1 δϕϕ C1 2δϕϕC+1 2δϕ Zdϕ 1 δϕϕ C3 2δϕϕC1 2δϕ Zdϕ GHD(ϕC) = Z?a Z?c, (12)
where ϕC is the individual latitude of interest where a instantaneous blocking can be occur and δϕ the meridional extent from section 2.1. In case GHD is greater than 0 and the individual geopotential height located at ϕM exceed the defined threshold value (see eq. 11), the individual grid cell is blocked (IBBI = 1).

2.3 HGHA-2D Blocking Index

The ”HGHA-2D” (High Geopotential Height Area) Blocking Index is based on positive geopotential height anomalies. This index allows to detect grid cells where the geopotential height is above a defined threshold equivalent to equation 11. In addition to seek only for blocking grid cells, this index can be used to detect high pressure systems without reversals in geopotential height fields and is furthermore part of the combined blocking indices described below (section 2.4).

2.4 Combined HGHA Blocking Indices

The ”HGHA-TM90-2D” as well as the ”HGHA-MASATO-2D” Blocking Index is a combination of ”HGHA-2D” and ”TM90-2D” (”MASATO-2D” respectively) and expands the area of blocked grid cells from ”TM90-2D” (”MASATO-2D”) to the whole region of the blocking anticyclone similar to the idea from Barriopedro et al. [2010]. In a first step, the ”TM90-2D” (”MASATO-2D”) Blocking Index will be calculated followed by the ”HGHA-2D” Index. If both indices have an overlapping area of blocked grid cells of at least 150000km2 then all blocked grid derived from the ”HGHA-2D” Index are set as blocked.


pict pict pict pict

Figure 2: Example of detected blocking groups over the European-Atlantic sector using the ”TM90-2D” Blocking Index (top left), ”MASATO-2D” (top right), ”HGHA-2D” (bottom left) and ”HGHA-TM90-2D” (bottom right) in June 2006. It can be seen, that a high geopotential height area over the Atlantic (blue colour, bottom left) does not pass the blocking criteria from the TM90 Index (top left), so that the blocking region is also absent in combined Blocking Index (bottom right). In contrast, in the bottom right figure can be seen that the blocking area of the blocking group over Northern Europe derived from the TM90 Blocking Index (blue, top left) is enhanced to the whole high geopotential height area (purple, bottom left). The different colours showing the individual Blocking Sub-Regime IDs.


3 Spatio-temporal Filter

Large-scale meteorological extremes in temperature and precipitation (e.g. heatwaves, cold spells, droughts) caused by blockings basically occur during a persistent and quasi-stationary blocking event. To exclude small-scale as well as short-term blocking situations, a spatio-temporal filter can be applied to the Instantaneous Binary Blocking Index IBBI which is derived from the mentioned indices described in the previous section 2. Most of the processing parts which are implemented in the filter procedure are mainly based on modified methods and ideas from Barriopedro et al. [20062010], Barnes et al. [2012]. For a better overview, the structure of the spatio-temporal filter can be divided into these different processing-steps:

  • filling small ”gaps” between blocked grid cells
  • pooling contiguous blocked grid cells to specific Blocking Groups (BG)
  • applying spatial criteria (area, zonal/meridional extension) to Blocking Groups
  • tracking Blocking Groups and pooling to specific multi-day Blocking Regimes (BR)
  • applying temporal criterion
  • deriving Blocking Sub-Regimes (BSR)

A schematic can be found in figure 3 as well as a detailed description in the following subsections.


pict

Figure 3: Schematic of the algorithm of detecting persistent and large-scale blocking events in the 2D-Blocking Plugin.


3.1 Blocking Groups

In the first step individual blocked grid cells obtained as Instantaneous Binary Blocking Index IBBI from the blocking index calculation (section 2) will be combined into a Blocking Group BG containing contiguous blocked grid cells. This procedure will be done for each time step separately so in the end a Blocking Group can be individually identified via a specific BG-ID. To avoid the impact of small gaps within a large-scale blocking event in the following spatio-temporal criteria, these gaps will be ”filled” in the case that one grid cell (default) is not blocked between two nearby blocked grid cells. The size of the gap can be changed by adapting the parameters gap.nlon and/or gap.nlat in the configuration R-file (see config_BLOCKING-INDEX_default.R in section 4.2).

3.2 Spatial Filter

In the next processing-step, every Blocking Group will be checked for large-scale criteria. This will be done in two steps. In the first, the Blocking Group must exceed a minimum zonal and meridional extension criterion. In the default configuration (spat.crit.vers.flag = 1), the meridional (zonal) extension will be checked between the most northern and southern latitude (western and eastern longitude) of the Blocking Group. The default criteria for the extension distances are 15lat and 15lon (converted into km at 50N). These values can be adapted in the configuration R-file by changing the parameters crit.nlat and crit.nlon. Note, in case of using the TM90-2D or MASATO-2D Blocking Index, the crit.nlat is set to 0 since the meridional extension is indirectly included in the blocking index calculation procedure via δϕ = 15lat (sec. 2) and should be adapted in case another δϕ was chosen. In the second step, the Blocking Group will be checked for the blocked area and must reach a minimum area of at least 1.5 x 106km2 in default configuration. This parameter can be adapted (crit.area) and should also depends on the used blocking index and chosen δϕ.

3.3 Blocking (Sub)-Regimes – Tracking of Blocking Groups

The tracking of Blocking Groups is applied to select persistent blocking events, here called as Blocking Regime BR and is basically based on the approach from Barnes et al. [2012]. A Blocking Regime represents a whole large-scale and persistent blocking event which consists of multiple Blocking Groups. To allow the merging and splitting of Blocking Groups, a Blocking Regime can contain several Blocking Groups at the same day. The identification of Blocking Groups participating in a Blocking Regime can shortly be described in a few steps: 1) All BGs will be stored in a list listBG. 2) For the first element BGa from listBG all neighbouring BGs the day before and after will be selected. All selected BGs passing the tracking criterion below compared to BGa will be put into a list listBGnew. In default configuration (crit.BR.opt = "aoverlap"), the criterion is fulfilled if the overlapping area between both BGs exceeds 750000 km2. If none of the neighbouring BGs can exceed the threshold, the closest BG which has a distance between both BG centres (based on centroids) less than 1000 km can also be added to list listBGnew. 3) To include possible mergings and splittings of the blocking event, the selected neighbouring BGs fulfilling the tracking criterion in list listBGnew must also pass step 2) as long as no new BG fulfilling the tracking criterion can be added to the list listBGnew. 4) All Blocking Groups in listBGnew are part of a new Blocking Regime BR and will be removed from the original list listBG. 5) Now, the next remaining BG in listBG will pass steps 2-4) to ”create” a Blocking Regime again. This procedure will be done as long as all BGs are removed from the original list listBG. A persistent blocking event exists if the duration of a Blocking Regime lasts for at least 4 days (default configuration). In case a Blocking Regime has a shorter duration, the Blocking Regime and all corresponding Blocking Groups will be rejected. In addition to identify a whole blocking event via the Blocking-Regime-method mentioned above, it is also possible to determine Blocking Sub-Regimes BSR participating in a Blocking Regime. The idea of BSR is to track primary quasi-stationary Blocking Groups of a BR in case merging and splitting exist in the BR (see fig 4). The BSR selection is generally based on the BR-identification-algorithm. In case a merging or splitting occurs, only the BG with the most overlapping area (closest distance between blocking centres in case no overlapping exists) will be selected during step 2). Finally, a Blocking Regime can contain either multiple BSRs or only one BSR if merging/splitting is absent. Note, a Blocking Sub-Regime have not to pass the duration criterion so that a duration of only one day is also possible. For further information see the right column on figure 3.


pict pict pict pict

Figure 4: Example of multiple Blocking Sub-Regimes. Merging of two Blocking Sub-Regimes (left: purple, rose) to one Blocking Sub-Regime (right: rose) where the BSR with the largest overlapping area gets the same BSR-ID (in this case the rose one). On the bottom panel a splitting occurs.


3.4 Blocking Properties

In case the spatio-temporal filter option is chosen, some blocking characteristics and properties will be analysed. General properties like blocking duration, blocking centre, blocking extension, blocking area, geopotential height maximum at its location are individually given for every Blocking Group, Blocking Sub-Regime and Blocking Regime. Additionally, the mean, maximum, minimum as well as the accumulation of all grid-cell-based values from geopotential height anomaly and the blocking-index-depended intensity parameters (GHGN, GHGS, GHD in section 2) are also calculated for every BG, BSR and BR. Fore more details see section 5.2.

4 Input

The calculation of Instantaneous Binary Blocking Index is based on a global geopotential height field (temporal resolution higher equal 1-day) in a specific pressure level. The input file must be a 4-dimensional netCDF file containing the variable name ”zg” [in Pascal] and the dimension ”lon”, ”lat”, ”plev” and ”time” on a global grid with a temporal resoltuion of at least 1-day. Input fields with a higher temporal resolution than 1-day (e.g. 6-hourly data) can be averaged to a daily mean via the associated Plugin option. Further note, a remapping of input grid to a regular longitude-latitude grid with spatial resolution defined by the user is applied in the Plugin.

4.1 Plugin Input Parameters

Table 1: Input parameters for the 2D-Blocking Plugin.
outputdir Output directory of results.
mandatory default: /net/scratch/user/evaluation_system/
output/blocking2d/timestemp


cachedir Cache directory.
mandatory default: /net/scratch/user/evaluation_system/
cache/blocking2d/timestemp


inputdir Input directory of global geopotential height data in case of not using the freva databrowser selection framework below.
optional


project The project of input data, e.g. reanalysis.
optional


product The product of input data, e.g. reanalysis.
optional


institute The institute of input data, e.g. ECMWF.
optional


model The model of input data, e.g. IFS.
optional


experiment The experiment name of input data, e.g. ERAINT.
optional


ensemble The ensemble member of input data, e.g. r1i1p1, r2i1p1 or * for all members.
optional


time_frequency The time frequency of input data, e.g. day or 6hr.
optional


blocking_index Blocking Index to be processed.
mandatory default: TM90-2D


time_period Time period to be processed separated by a comma:
YYYY-MM-DD,YYYY-MM-DD.
mandatory


hemisphere Hemisphere to be processed. (Only NH is available yet!)
mandatory default: NH


region The region box to be processed. The format have to be W,E,S,N (e.g. -180,180,0,90 for NH). ”NH”, ”Europe” or ”Europe+Buffer” is also valid.
mandatory default: Europe+Buffer


level Pressure level to be processed [in Pa], e.g. 50000.
mandatory default: 50000


grid Global regular lon-lat grid description or file used for remapping, e.g. r180x91.
mandatory default: r180x91


daymean Option to calculate the daily mean of the geopotential height before calculating the blocking index. Recommended in case input files has higher temporal resolution than 1-day.
mandatory default: True


blocking_config Option to input a specific configuration file for blocking index calculation and spatio-temporal filter procedure parameters. Leave empty to choose default parameters.
optional


GEOPcrit Option to input a file of threshold criterion for geopotential height. The file format must be a NetCDF file with regular longitude-latitude grid related to to chosen grid above. Save previous calculated files for multiple use. Leave empty to calculate the threshold criterion for geopotential height beforehand.
optional


GEOPcrit_method Method of calculating the GEOPcrit threshold. The mean, a multiple of standard deviation or the constant value of zero (”disabled”) is possible. Only valid if no specific GEOPcrit file was chosen above.
optional


climyear_range First and last year (separated by a comma) of long-term time period for the calculation of the threshold criterion for geopotential height. Only valid if no specific GEOPcrit file was chosen above.
optional


SpatioTempFilter Option to apply the spatio-temporal filter on Instantaneous Binary Blocking Index. Necessary for blocking property analysis.
mandatory default: True


sel_region Option to select the region defined above before or after applying the spatio-temporal filter on Instantaneous Binary Blocking Index. In case ”afterSTF” is chosen, the spatio-temporal filter and blocking property calculations are applied to the whole hemisphere.
mandatory default: beforeSTF


plottype Type of plots to display some results. None: No plots; Climatology: Yearly/Seasonal/Monthly climatology of blockings - Please use at least a 3-year time period; Event-based: Blocking index of every time step (”additional”) and of the whole time period (”basic” + ”additional”). Use only in case of analysing blocking events with a short time period (couple of weeks).
mandatory default: Climatology


cacheclear Option to NOT clear the cache directory.
mandatory default: True


ntask Number of tasks.
mandatory default: depends on system


dryrun ”True” for just showing the list of found files of chosen input data. ”False” for processing data.
mandatory default: False


caption An additional caption to be displayed with the results.
optional


unique_output_id ”True” for appending the freva process-ID to the chosen output directory.
mandatory default: True

At first, the user have to specify the output (outputdir) and cache (cachedir) directories. The data paths of input files can be selected via the typical Freva databrowser structure containing project, product, institute, model and experiment of the geopotential height field. Further, ensemble member(s) in the ensemble operator and the time frame (time_frequency) must be selected. Besides the input selection described before it is possible to specify an input directory in which geopotential height files are stored (inputdir). An ensemble-member-depending processing is not available in this case. The Blocking Index (blocking_index), the time period (time_period) as well as the region of interest (hemisphere, region) can be chosen next. A pressure level selection is also available to analyse a specific level of the geopotential height field (level). In grid the user have to specify a global regular lon-lat grid to remap the data. The option to calculate the daily mean of geopotential height in case of higher temporal resolution than 1-day can be set in the daymean parameter. Additional specific configuration parameters and options which are necessary for the blocking index calculation as well as for the spatio-temporal filter can be set here by input a configuration file (blocking_config) similar to the default file described later in sub-section 4.2. In case default configurations should be applied, the operator-field must be empty. For the blocking criterion GEOPcrit (see equation 11) there is an option to calculate a long-term threshold of geopotential height by using various methods (e.g. mean, mean + standard deviation etc.) in GEOPcrit_method in case GEOPcrit is empty. It is also possible to input an already existing file from previous analyses in GEOPcrit. This file must be a NetCDF file for the NH containing a variable named ”zg” with the same regular lon-lat grid intervals defined in grid and dimensions of [time=366, lat, lon, plev=1]. To define the range of years which is used for the calculation of GEOPcrit file the parameter climyear_range can be set. Next, the option to apply a spatio-temporal filter (SpatioTempFilter) can be set to screen persistent and large-scale blocking events and further to get some blocking properties. The sel_region-operator gives the option to select the region defined above before or after applying the spatio-temporal filter on the Instantaneous Binary Blocking Index. In case ”afterSTF” is chosen, the spatio-temporal filter and blocking property calculations are applied to the whole hemisphere instead of the chosen region only. In plottype climatological as well as event-based results can be visualized depending on the time period of interest. Finally there are options to remove the cache directories (cacheclear), to specify the number of tasks (ntask) and to show the found input file(s)(dryrun).

4.2 Configuration File

Besides the input parameters which can be chosen via the Plugin selection framework, there is also a possibility to change several specific parameters for the blocking index calculation and spatio-temporal filter in a configuration R-file. There exists an individual file in the Plugin directory src/config4BlockingCalc/config_BLOCKING-INDEX_default.R which contains different parameters and options for each blocking index. In general, thresholds of blocking index criteria, thresholds of spatial, tracking as well as duration criteria used in the spatio-temporal filter can be adapted. Additionally, it is possible to make some minor variations in the tracking method. A detailed description of all parameters and options is given in the comment lines of every configuration file. In case the user wants to adapt and apply those settings: 1) Create a copy of the default configuration file. 2) Change the parameters/options and 3) specify the file path of the adapted configuration file in blocking_config operator.

5 Output

The standard output of the 2D-Blocking Plugin consists of NetCDF files containing maps of the calculated blocking indices and can be found in Outputdir/ibbi. If the spatio-temporal filter was applied, there additionally exist ASCII files with information about several blocking properties of blocking events. Furthermore, results can be visualized where maps of blocking indices and intensity as well as plots of blocking frequencies are stored in Outputdir/plot. In case ”Climatology” plot type is chosen, monthly, seasonal and yearly climatologies are calculated and saved as NetCDF files in Outputdir/clim. All processed files from the 2D-Blocking Plugin are stored in the chosen outputdir. If selected, the calculated GEOPcrit file will be stored in Outputdir/GEOPcrit.

5.1 Grid-cell-based NetCDF-Files

The 4-dimensional NetCDF files [LON; LAT; PLEVEL; TIME] contain the Instantaneous Binary Blocking Index IBBI (variable declared as ”ibbi”), the geopotential height (”zg”), the difference between geopotential height and GEOPcrit at blocking anticyclone position (”zgAno”) and the GHGS value (”GHGS”) as well as the GHGN value (”GHGN”) for the ”TM90-2D”-based blocking indices and the GHD value (”GHD”) for the ”MASATO-2D”-based blocking indices respectively. In case the spatio-temporal filter is applied, the files additionally contain the screened large-scale and persist blocked Binary Blocking Index BBI (”bbi”) as well as associated BG/BR/BSR-ID labels (”bg_id, br_id, bsr_id”). Furthermore, a grid-cell-based counting of time steps of consecutively blocked BBI is calculated and stored as ”bbi_tslen” and ”bbi_maxtslen”.

5.2 Event-based Blocking Properties

In case the spatio-temporal filter is applied, several properties and characteristics of blocking events are stored in a couple of ASCII files as well as RData files. General properties like blocking duration, blocking centre, blocking extension, blocking area, geopotential height maximum at its location are individually given for every Blocking Group, Blocking Sub-Regime and Blocking Regime. Additionally, the mean, maximum, minimum as well as the accumulation of values from geopotential height anomaly and the blocking-index-depended intensity parameters (GHGN, GHGS, GHD in section  2) are also calculated for every BG, BSR and BR as well as for each time step of BSR, (BSRt) and BR (BRt). Each ASCII file has the same header containing information about the chosen parameters and options of the 2D-Blocking Plugin. A detailed description of file content is given in the following tables 2 and 3.

Table 2: List of blocking property ASCII files and its general content.
File Content


Date-BR-BSR-BG-IDs_*.txt Date, BG-IDs, BR-IDs, BSR-IDs
BG-properties_*.csv BG properties
BR-properties_*.csv overall BR-event properties
BSR-properties_*.csv overall BSR-event properties
BRt-properties_*.csv time-step-based BR properties
BSRt-properties_*.csv time-step-based BSR properties
BR-BG-BSR-IDs_*.txt BG/BSR-IDs associated to specific BR
BSR-BG-BR-IDs_*.txt BG/BR-IDs associated to specific BSR
BRt-BG-BR-IDs_*.txt BG-IDs associated to specific BRt
BSRt-BG-BR-IDs_*.txt BG/BR-IDs associated to specific BSRt
Table 3: List of variables which are stored in blocking property ASCII files. The properties are related to the prefixed BG-, BSR-, BR-, BSRt- or BRt-element.
Variable Property Unit Element




area Area km2 BG/BSRt/BRt
area_mean Area (Mean) km2 BSR/BR
area_min Area (Minimum) km2 BSR/BR
area_max Area (Maximum) km2 BSR/BR
area_acc Area (Accumulation) km2 BSR/BR
meridionalRange_mean_S S-Extension (Mean) N BG/BSR/BR/BSRt/BRt
meridionalRange_mean_N N-Extension (Mean) N BG/BSR/BR/BSRt/BRt
zonalRange_mean_E E-Extension (Mean) E BG/BSR/BR/BSRt/BRt
zonalRange_mean_W W-Extension (Mean) E BG/BSR/BR/BSRt/BRt
meridionalRange_S S-Extension (Max.) N BG/BSR/BR/BSRt/BRt
meridionalRange_N N-Extension (Max.) N BG/BSR/BR/BSRt/BRt
zonalRange_E E-Extension (Max.) E BG/BSR/BR/BSRt/BRt
zonalRange_W W-Extension (Max.) E BG/BSR/BR/BSRt/BRt
zg_mean Geopotential Height (Mean) gpm BG/BSR/BR/BSRt/BRt
zg_min Geopotential Height (Min.) gpm BG/BSR/BR/BSRt/BRt
zg_max Geopotential Height (Max.) gpm BG/BSR/BR/BSRt/BRt
zg_acc Geopotential Height (Acc.) gpm BG/BSR/BR/BSRt/BRt
zgAno_mean GEOPcrit Deviation (Mean) gpm BG/BSR/BR/BSRt/BRt
zgAno_min GEOPcrit Deviation (Min.) gpm BG/BSR/BR/BSRt/BRt
zgAno_max GEOPcrit Deviation (Max.) gpm BG/BSR/BR/BSRt/BRt
zgAno_acc GEOPcrit Deviation (Acc.) gpm BG/BSR/BR/BSRt/BRt
GHGS/GHGN_mean GHGS/GHGN (Mean) gpm/N BG/BSR/BR/BSRt/BRt
GHGS/GHGN_min GHGS/GHGN (Min.) gpm/N BG/BSR/BR/BSRt/BRt
GHGS/GHGN_max GHGS/GHGN (Max.) gpm/N BG/BSR/BR/BSRt/BRt
GHGS/GHGN_acc GHGS/GHGN (Acc.) gpm/N BG/BSR/BR/BSRt/BRt
GHD_mean zg-Difference (Mean) gpm BG/BSR/BR/BSRt/BRt
GHD_min zg-Difference (Min.) gpm BG/BSR/BR/BSRt/BRt
GHD_max zg-Difference (Max.) gpm BG/BSR/BR/BSRt/BRt
GHD_acc zg-Difference (Acc.) gpm BG/BSR/BR/BSRt/BRt
centre/centre_awmean_lon Area Centre (Centroid) (lon) E BG/BSR/BR/BSRt/BRt
centre/centre_awmean_lat Area Centre (Centroid) (lat) N BG/BSR/BR/BSRt/BRt
centre_awmean_ts Duration Centre 1 BSR/BR
centre_zgmax_lon Centre of zg-Maximum (lon) E BG/BSR/BR/BSRt/BRt
centre_zgmax_lat Centre of zg-Maximum (lat) N BG/BSR/BR/BSRt/BRt
centre_zgmax_ts Time step of zg-max 1 BG/BSR/BR/BSRt/BRt
centre_mean_lon Mean of longitudinal position E BSR/BR/BRt
centre_mean_lat Mean of latitudinal position N BSR/BR/BRt
timestep_count Duration 1 BSR/BR

5.3 Plotting Type

At the end there is an option to visualize the results. Two plotting routines are available. The ”Event-based” option is recommended for a short time period of few weeks to analyse certain blocking events. For long time periods and for some climatological analyses, the ”Climatology” option should be the better choice.

5.3.1 Climatology

The ”Climatology” plotting routine produces means of yearly, seasonal and monthly blocking frequencies as grid-cell-based maps on the one hand and time series plots of area mean of the chosen region on the other hand. In addition, NetCDF files of area-averaged time series as well as grid-cell-based yearly, seasonal and monthly mean are created for the blocking frequency, zgAno and GHD/GHGS/GHGN values. Note that the means of intensity are only based on associated blocked grid cells.


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Figure 5: Example of the ”Climatology” plotting type showing the yearly blocking frequency of seasonal field mean (left) and the blocking frequency (right) of the whole time period from 1979-2015 based on the ”HGHA-TM90” Blocking Index.


5.3.2 Event-based

The ”Event-based” plotting routine produces maps showing the (Instantaneous) Binary Blocking Index IBBI/BBI as well as zgAno and GHGS/GHD for each time step within the selected time period (only for ”Event-based-additional” option). Furthermore, every BSR is individually colour-coded to see the propagation of the corresponding blocking area. Additionally, the intensity of blocking shown as zgAno and GHGS/GHD is also provided as well as the blocking frequency of the whole time period (”Event-based-basic” and ”Event-based-additional”). In case the spatio-temporal filter is disabled, only IBBI and blocking frequency is mapped.


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Figure 6: Example of the ”Event-based” plotting type. The figures show the evolution of blockings over the European-Atlantic sector applying the ”HGHA-TM90-2D” Blocking Index from 8th June 2006 (top) to 13th June 2006 (bottom). The left panel shows the BBI with different color-coded Blocking Sub-Regime IDs. The right panel shows the associated difference between the geopotential height and the corresponding GEOPcrit value (in gpm). The unique figure at bottom indicates the blocking frequency from 1st June to 31st July 2006.


References

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   D. Barriopedro, R. Garc?a-Herrera, A. R. Lupo, and E. Hern?ndez. A Climatology of Northern Hemisphere Blocking. J. Climate, 19:1042–1063, 2006. doi: 10.1175/JCLI3678.1.

   D. Barriopedro, R. Garc?a-Herrera, and R. M. Trigo. Application of blocking diagnosis methods to General Circulation Models. Part I: a novel detection scheme. Clim. Dyn., 35: 1373–1391, 2010. doi: 10.1007/s00382-010-0767-5.

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   G. Masato, B. J. Hoskins, and T. Woollings. Wave-Breaking Characteristics of Northern Hemisphere Winter Blocking: A Two-Dimensional Approach. J. Climate, 26:4535–4549, 2013b. doi: http://dx.doi.org/10.1175/JCLI-D-12-00240.1.

   A. A. Scaife, T. Woollings, J. Knight, G. Martin, and T. Hinton. Atmospheric Blocking and Mean Biases in Climate Models. J. Climate, 23:6143–6152, 2010. doi: 10.1175/2010JCLI3728.1.

   S. C. Scherrer, M. Croci-Maspoli, C. Schwierz, and C. Appenzeller. Two-dimensional indices of atmospheric blocking and their statistical relationship with winter climate patterns in the Euro-Atlantic region. Int. J. Climatol., 26:233–249, 2006. doi: 10.1002/joc.1250.

   S. Tibaldi and F. Molteni. On the operational predictability of blocking. Tellus, 42A: 343–365, 1990. doi: 10.1034/j.1600-0870.1990.t01-2-00003.x.