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GEODETSKI VESTNIK | letn. / Vol. 66 | št. / No. 3 |
SI 
 |  
EN
ABSTRACT IZVLEČEK 
KLJUČNE BESEDE KEY WORDS
water vapour, GNSS, Era interim, Era 5vodna para, GNSS, Era Interim, Era 5
UDK: 528.28:551.57(65) 
Klasifikacija prispevka po COBISS.SI: 1.01
Prispelo: 10. 5. 2022
Sprejeto: 21. 8. 2022
DOI: 10.15292/geodetski-vestnik.2022.03.403-411
SCIENTIFIC ARTICLE 
Received: 10. 5. 2022
Accepted: 21. 8. 2022
Houaria Namaoui 
OCENA REANALIZE ERA5 
VARIACIJE ATMOSFERSKE 
VODNE PARE V ALŽIRIJI 
EVALUATION OF ERA5 
REANALYSIS ATMOSPHERIC 
WATER VAPOR VARIATION IN 
ALGERIA
In climate change context, the precipitable water vapour 
(PW) is key parameter of atmospheric process and dynamics 
and its variation is very high in space and time. It's accuracy 
is paramount for any geodetic or climatic study.
The main objective of this study is to compute precipitable 
water vapour from ERA5 reanalysis for 4 stations in Algeria 
which have different types of climate. We opt for using 
integration method for different level of pressure with ERA5. 
The values of water vapour are also compared with 
radiosondes profiles. The results of this work shows good 
agreement with a correlation that is not less than not 
0.95 and 0.70 compared as radiosondes profiles. The first 
results are encouraging, in particular for meteorological 
applications with good hope to introduce another dataset 
as GNSS to more understand the variation and behavior 
of water vapour over a long period of observation.
V kontekstu podnebnih sprememb je padavinska vodna 
para (PW) ključni parameter atmosferskih procesov in 
dinamike. Ker je izredno variabilna v prostoru in času, 
je njena natančnost bistvenega pomena za vsako geodetsko 
ali podnebno študijo.
Glavni cilj te študije je izračunati padavinsko vodno paro iz 
reanalize ERA5 za štiri postaje v Alžiriji, ki imajo različne 
vrste podnebja. Odločili smo se, da bomo uporabili metodo 
integracije za različne ravni tlaka z ERA5. 
Vrednosti vodne pare primerjamo tudi z vmesno reanalizo 
ERA in profili radiosond. Rezultati dela kažejo dobro 
ujemanje z ERA5 in ERA interim s korelacijo, ki ni 
manjša od 0,95 in 0,70 v primerjavi s profili radiosond. 
Prvi rezultati so spodbudni, zlasti za meteorološke 
aplikacije, pri čemer se kažejo dobre možnosti za uvedbo 
še enega podatkovnega niza, na primer GNSS, za boljše 
razumevanje sprememb in obnašanja vodne pare v daljšem 
obdobju opazovanja.
Houaria Namaoui | EVALUATION OF ERA5 REANALYSIS ATMOSPHERIC WATER VAPOR VARIATION IN ALGERIA | OCENA REANALIZE ERA5 VARIACIJE ATMOSFERSKE VODNE PARE V ALŽIRIJI | 
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Houaria Namaoui | EVALUATION OF ERA5 REANALYSIS ATMOSPHERIC WATER VAPOR VARIATION IN ALGERIA | OCENA REANALIZE ERA5 VARIACIJE ATMOSFERSKE VODNE PARE V ALŽIRIJI | 
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1 INTRODUCTION 
Water vapor is a key parameter of the atmosphere with very high spatial and temporal variability (Trenberth 
et al., 1998). It contributes as a main source in the formation of clouds and precipitation, for this reason, 
this quantity must be known with precision to predict environmental and climatic processes.
This parameter is very difficult to estimate because it varies strongly in time and space. The use of different 
techniques makes it possible to estimate this quantity such as radiosoundings, lidars, radiometers but they 
cannot be operated only in certain weather conditions and sometimes prove to be very expensive to set up.
Satellite positioning systems are generally used for geodetic positioning and/or geodynamic deformation. 
Over the years, several GNSS (Global Navigation Satellite System) constellations have been created 
allowing the use of GNSS for meteorological purposes (Bevis et al, 1992).
Indeed, the water vapor present in the atmosphere is an essential element for the weather forecast. 
The potential of GNSS was thus highlighted as a lower cost alternative and different studies was con-
ducted in different regions of world to validate GNSS water vapour with radiosondes , MODIS , SSMI 
and other satellites ( Torres et al., 2010; Van Malderen et al., 2014; Namaoui et al., 2017; Abdellaoui 
et al., 2019, Namaoui et al., 2021)
The variability of water vapour depends of many parameters like climate conditions, location of station, 
in a context of climate change, it is very important to follow the variations of trace gases in the atmo-
sphere. To better understand all this change, it is necessary to improve the knowledge of water vapor; 
a homogeneous database must be established at the local or even regional scale with very reliable data.
The objective of our work is to calculate this quantity of water vapor from global climate model 
reanalysis dataset (ERA5)  and see its variations in a region like Algeria where the climate is varied, 
because the country has a very large area with different topography regions (four times that of France): 
Algeria is located under a transitional climate, between the temperate zone and the tropical zone, this 
position puts it under the direct influence of the Mediterranean climate in the North and the desert 
climate in the South.  
The reanalysis data are produced by combining measurements and observations from several sources 
(SYNOP station, radiosondes, satellites...), with simulation data to fill the existing gaps in the meteorolo-
gical parameters, in order to obtain a regular and consistent representation of the state of the atmosphere.
The validation of Era reanalysis products (water vapour) with different techniques was effected in different 
regions in world [(Zhang et al., 2018), (Jie et al., 2021).] and the accuracy of results varies from region 
to region according to the climatic conditions and the terrain topography. (Rakhmatova et al, 2021).
2  DATA AND METHODS
2.1 ERA reanalysis
ERA-Interim is a global atmospheric reanalysis dataset from 1979 to the present, produced by a numerical 
weather prediction model run at ECMWF. (Dee et al, 2011).
The reanalysis has been widely applied in atmospheric science, particularly in operational meteorological 
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Houaria Namaoui | EVALUATION OF ERA5 REANALYSIS ATMOSPHERIC WATER VAPOR VARIATION IN ALGERIA | OCENA REANALIZE ERA5 VARIACIJE ATMOSFERSKE VODNE PARE V ALŽIRIJI | 
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centers to analyze the state of the climatological situation and to assess forecast error anomalies. 
ERA5 is the last generation of atmospheric reanalysis, which has just been placed to replace ERA-Interim 
which was launched in the period 2006 to 2019. ERA5 provides hourly atmospheric reanalysis data at 
37 pressure levels from 1,000 to 1 hPa, with a horizontal spatial resolution of 0.25° × 0.25°. 
A bilinear interpolation is necessary to obtain the vertical profiles  on each station from ERA5.
Based on (Jiang et al., 2016) , The PW can be calculated using the specific humidity and air pressure 
from the reanalysis data set as followed in equation 1 
      
1
1 1( ).( )
2 .
n
i i i i
i w
q q p p
PW
gρ
−
+ ++ −= ∑         (1)
  
0.52
2
1 0.00193185.sin( )9.780325.
1 0.00669435.sin( )
g ϕ
ϕ
 +
=  − 
     (2)
where n is the total number of layers, qi and pi are the specific humidity (unit: kg/kg) and air pressure 
(unit: Pa) at each layer, respectively; ρw is the density of liquid water and defined as 1,000 kg/m3; g is 
the gravitational acceleration (unit: m/s2) (Jiang et al., 2016).
2.2 Radiosondes 
The radiosonde data, with a resolution of 12 h (at UTC 00:00 and 12:00), can be obtained in the websites 
of the University of Wyoming (http://weather.uwyo.edu/upperair/sounding.html).
In this study, we have used data from two out of three radiosondes stations in Algeria (Figure 1).
 
Figure 1:  Location of radiosondes stations in Algeria.
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Houaria Namaoui | EVALUATION OF ERA5 REANALYSIS ATMOSPHERIC WATER VAPOR VARIATION IN ALGERIA | OCENA REANALIZE ERA5 VARIACIJE ATMOSFERSKE VODNE PARE V ALŽIRIJI | 
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Using equation (3), the Precipitable Water Vapour (PWV) content for each radiosonde profile can be 
calculated as (Realini et al, 2014): 
      
21
1
,
1
h n
w d i i i
ih
PW dh r hρ ρ
=
= = ∆∑∫    (3)   
ρd,i , ri, ∆h are respectively the dry air density, the mixing ratio, and the altitude step for layer where ρw 
the water vapour density, n is the total number of layers between h1 and h2. The  dry air density ρd  is 
expressed as
 dd
M P
R T
ρ =  (4)
with the molar mass of dry air Md = 0.0289644 kg mol−1 and the universal gas constant for air R= 
8.31432 J mol−1 K−1.  T is the observed air temperature in Kelvin.  The mixing ratio r is defined as the 
dimensionless ratio of the mass of water vapour to the mass of dry air  
 0.622 er
P
=  (5)
where e is the partial pressure of water vapour and P is the air pressure.
3 RESULTS AND ANALYSIS 
   
  
Figure 2:  Time series of PW ERA5 reanalysis for Algiers, Bechar, Tamanrasset and Djelfa.
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For year 2012, The time series  of precipitable water from ERA5  at four stations (Algiers, Bechar, Djelfa 
and Tamanrasset) are plotted in Figure 2.
The values  have been calculated every six hours, we notice very well that the behaviour varies from one 
station to another according to the climatic conditions of each one, moreover the station of Algiers is 
close to the sea or the peak it exceeds 45 mm since the humidity is very high.        
However, the other stations Bechar, Tamanrasset and Djelfa the maximum was around 33, 32.5 and 
36 respectively and the minimum was recorded at Tamanrasset with a value of 1.1 mm of precipitable 
water vapour. Tamanrasset is located in the extreme south of Algeria. The variation water vapour is very 
high in summer season compared with winter period generally, water vapour mixing ratio decreases with 
altitude in the troposphere.
The same behaviour was observed at Djelfa station with high values compared with Tamanrasset and 
Bechar station.  The climate of Djelfa is of the semi-arid type with a nuance continental. The winters are 
cold and harsh and the summers hot and dry with the average humidity, varies between 35% and 79%. 
The changes and distributions of atmospheric water vapour in different seasons are in accordance with 
the rule that the water vapour content is affected by the topographic dynamic lift effect (Hezhen et al., 
2021).  In figure 3, we can see clearly the seasonal variability in summer and winter. The mean value 
during winter is the order of 14 mm and the max is the order of 39 mm otherwise during the period of 
summer the values was higher than winter because during the warm months, the humidity of the air is 
also higher almost everywhere especially near the sea. (Lees et al.,2019).
    
Figure 3:  Seasonal variability of water vapour at Tamanrasset (left) and Algiers (right) stations.
4 COMPARISON WITH ERA INTERIM AND RADIOSONDES PROFILES 
The evaluation was based on statistical parameters MBE (mean bias error) and RMSE (root-mean-square 
error) to analyse and evaluate the retrieved PWV precision based on different types of measurements. 
A lower RMSE indicates a smaller discrepancy between the Era5 and Era interim PWV. The following 
formulas were applied in our statistical analysis (Shuaimin et al. 2020):
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5 int
1
(
N
ERA ERA
i
PW PW
MBE
N
=
−
=
∑
 (6) 
5 int
1
(
N
ERA ERA
i
PW PW
MBE
N
=
−
=
∑
 (7)
where N is the number of PW pairs, PWERAint is PW value of ERA interim PWERA5 is PW value of ERA5.
The ERA5 PW dataset was compared to PW ERA-Interim dataset based on some commonly used statistical 
indicators such as correlation coefficient, bias, and RMSE. Generally, the correlation coefficient (R) is 
mostly used to assess the degree of consistency instead of absolute agreement, and a positive (negative) 
bias indicates an overestimation (underestimation) of PWV.  
The scatter plots for all observations of PW ERA5 against PW ERA interim can be found in figure 2, 
together with the fitted linear regressions.  
A fairly good agreement can be observed between two sources of ERA reanalysis over all stations with 
mean bias error do not exceeds 0.7 mm and withcorrelation coefficient at least 0.96.
          
        
Figure 4:  Scatter plots of PW ERA5 and PW ERA interim at Algiers, Bechar, Tamanrasset and Djelfa.
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Houaria Namaoui | EVALUATION OF ERA5 REANALYSIS ATMOSPHERIC WATER VAPOR VARIATION IN ALGERIA | OCENA REANALIZE ERA5 VARIACIJE ATMOSFERSKE VODNE PARE V ALŽIRIJI | 
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Tamanrasset and Djelfa stations are located at altitude where depasses 1400m and with lower values of 
water vapour. The mean bias of these stations is slightly higher compared as Algiers. Where model of 
reanalysis affects topography.
In the absence of availability of GNSS data in Algeria, we have compared the values of ERA5 reanalysis 
with two radiosondes profiles available in Algeria (Algiers and Tamanrasset).  The comparison was made 
with ERA5 at the same lunch of radiosondes (12 UTC). 
The figure 5 shows time series of PW ERA5 and radiosondes at Algiers and Tamanrasset Station
        
Figure 5:   Time series of Precipitable water vapour from Radiosondes and ERA5.
Correlation coefficient of 0.65 and 0.77 at Algiers and Tamanrasset respectively with the mean bias, 
which not exceeds 1 mm. The results of PW radiosondes and ERA5 are plotted in figure 5 and statistical 
parameters are summarized in table 2.  
Table 2:   Statistical comparison between PW ERA5 and PW radiosondes. The MBE is the mean PW difference taken as RS minus 
ERA5.
Stations MBE [mm] RMS [mm] R
Algiers 0..98 4.5 0.65
Tamanrasset -0.73 3.5 0.76
5 CONCLUSION 
The objective of this study is to derive the water vapour from ERA reanalysis and see the performance 
of two sources data over a different stations and different climate s in Algeria.
The seasonal variation of water vapour depends on location and climate indices as precipitations and 
topography of region, the maximum was observed at Algiers station with 44 mm and minimum of 1.26 
mm at Tamanrasset station where the climate of the Sahara, hot, sunny and arid, is characteristic of that 
of a hot desert, located on both sides of a tropic.
The results show a good agreement between precipitable water vapour ERA5 and ERA interim at diffe-
rent locations with mean bias which not exceeds 0.6 5 mm and correlation coefficient higher than 0.90.
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The water vapour from reanalysis was also compared with 2 profiles radiosondes in Algeria and the sta-
tistical results show an agreement between ERA5 reanalysis and radiosonde profile especially in region 
with a complex topography as Algeria. 
The Tamanrasset station show a negative bias between PW Radiosondes and ERA5 reanalysis. We also 
test the impact of outliers on our comparison. The correlation coefficent increases from 0.65 to 0.70 at 
Algiers Station.
The models of ERA reanalysis can be useful in applications of GNSS meteorology in the absence of 
meteorological stations.
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Houaria Namaoui | EVALUATION OF ERA5 REANALYSIS ATMOSPHERIC WATER VAPOR VARIATION IN ALGERIA | OCENA REANALIZE ERA5 VARIACIJE ATMOSFERSKE VODNE PARE V ALŽIRIJI | 
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Houaria Namaoui 
Algerian Space Agency, Center of space techniques, Arzew, Oran.
e-mail: houarian@gmail.com
Namaoui H. (2022). Evaluation of Era5 reanalysis atmospheric water vapor variation in Algeria. 
Geodetski vestnik, 66 (3), 403-411. 
DOI: https://doi.org/10.15292/geodetski-vestnik.2022.03.403-411