Download 7. La Red GNSS en apoyo al desarrollo nacional – IGM

CENTRO DE INVESTIGACIÓN EN
MODELAMIENTO AMBIENTAL CIMA
UNIVERSIDAD POLITÉCNICA SALESIANA
PROYECTOS DE INVESTIGACIÓN
LÍNEAS Y PROYECTOS DE
INVESTIGACIÓN-2015
 Análisis del tiempo y clima, cambio climático y eventos extremos:
 Eventos extremos de radiación solar en Quito: relaciones con la temperatura y
el Cambio Climático
 Eventos extremos de lluvia y temperature en Quito: un análisis de la variabilidad
y el cambio climático.
 Sistemas complejos en el estudio de eventos extremos
 Transiciones de Fase Continuas y Criticalidad Auto-organizada en la
precipitación lluviosa intensa.
 Energías renovables:
 Estudio y construcción de celdas solares tipo Grätzel con pigmentos naturales
extraídos en el Ecuador
 Huella de carbono de cocina de inducción vs. cocina a gas.
LÍNEAS Y PROYECTOS DE
INVESTIGACIÓN-2015
 Ecología y gestión de áreas protegidas
 “Biodiversidad y filogenia molecular de las moscas que visitan y polinizan
orquídeas en los bosques nublados del noroccidente del Ecuador”
 Inventario florístico de la estación biológica de Cutucú y Aguarongo
 Desarrollo local sostenible
 “Calidad y Disponibilidad del agua de consumo humano bajo la gestión social
del consejo de juntas del Proyecto Pesillo – Imbabura”
 Biotecnología
 Biorremediación de metales pesados con cianobacterias
 Biorremediación de aguas de desecho semindustrial con lodos activados
 Análisis de aceites esenciales de plantas del Cutucú contra patógenos
vegetales.
EXTREME EVENTS OF RAINFALL AND
TEMPERATURE IN QUITO DM: AN ANALYSIS OF
WEATHER VARIABILITY AND CLIMATE
CHANGE
Serrano Vincenti Sheila1 and Ruiz Jean Carlos 1,2
1Centro
de Investigación en Modelamiento Ambiental CIMA-UPS/ Universidad Politécnica
Salesiana/Red de Universidades Frente al Cambio Climático y Gestión de Riesgos, Quito, ECUADOR.
sserranov@ups.edu.ec
2Escuela Politécnica Nacional/Red de Universidades Frente al Cambio Climático y Gestión de
Riesgos, Quito, ECUADOR
jeanka1991@hotmail.com
Return periods with Generalized Extreme
Value Distribution GEVD
Figure 1 Behavior of annual maximum of daily maximum temperature (TXX) in Izobamba. Figure 2. TXX for
GEVD Weibull type distribution. The first two upper graphs show the proper fit of the model, while the lower
left and right graphs show the return periods with confidence limits of 95% (blue line) and the probability
density distribution.
Return
period
(años)
Return
level
[ºC/day]
Observed
LI [ºC/
day]
LS [ºC/
day]
Return
level
[ºC/
day]
PRECIS A2
LI [ºC/
LS [ºC/
day]
day]
Return
level
[ºC/
day]
23.36963 23.168
PRECIS B2
LI [ºC/
day]
LS [ºC/
day]
2
22.8791
22.65201 23.11443 23.1338
22.91
5
23.4149
23.19866 23.63924 23.8073
23.55107 24.11327 23.9056
23.6147
7
23.6665
23.46282 23.97861 23.9998
23.73038 24.35424 24.1082
23.80774 24.50286
10
23.7811
23.58098 24.12967 24.1852
23.90059 24.6095
23.98782 24.76448
15
23.8516
23.65159 24.23066 24.3774
24.07368 24.90126 24.494
24.16744 25.05632
20
22.8791
22.65201 23.11443 24.5038
24.18515 25.08955 24.6195
24.28098 25.24379
24.2996
22.89782 23.44836
24.25052
Table 4. Return periods, return levels and confidence intervals at 95% for the actual data of maximum
temperatures in Izobamba.
Figure 3 Maximum (Up) and Minimun (Down) annual daily temperatures expected for the next 10 years in the
DMQ, a) forecast using the trend observed with real data from the meteorological stations studied, b) forecast
using the product of dynamic forcing trend calculated by PRECIS A2 scenario c) B2 scenario of PRECIS trend.
Return Year
period
[years]
2
5
7
10
15
20
2014
2017
2019
2022
2027
2032
Return
level
[mm/da
y]
58.7867
82.381
91.2272
100.9893
112.6984
121.4659
IL
95% SL
95%
[mm/day] [mm/day]
52.3806
71.81226
78.53774
85.58649
93.54083
99.1595
66.39552
98.9752
113.82874
131.11258
152.2947
169.26421
Figure 6 Possible values ​of maximum daily precipitation
forecast for the next 10 years in the DMQ. The figure shows the
values ​of extreme events expected during this period, since
Table 7
CONCLUSIONS
The results show, that for the next 10 years, the DMQ south, will be possible find extreme events of
23.7ºC, and according to the A2 and B2 scenarios could be recorded 24.3 C and 24.2ºC respectively,
ie. an eventual increase of about 10 west to 7º east over the average. While in the north-east, a warm
region, it is possible to find extreme values up to 8ºC more than average. In the case of minimum
temperatures is expected an increase of nearly 7 all over the region.
In the case of the precipitation is not found a systematically forcing to suggest that its value increases
or decreases, so were used a Fretchel distribution. In the south region which is the rainiest, is
expected to register single events to up 100 mm/day, may register 156 mm/day. As for the northeast,
can record maximum of 56.5 mm/day. It should be noted that in this area the rains are often scarce.
Thus, it is important to note that, although this study predicts large magnitudes events, they have an
occasional nature, but nonetheless must be taken into account by stakeholders and decision makers
for proper planning.
This research was funded by CDKN within the
“Vulnerability Study of DMQ." And it was done under the
direction of SEI Institute, and the collaboration of the Red
de Unviersidades Frente al Cambio Climático.
ACKNOWLEDGEMENTS Represented by EPN, PUCE and CIMA-UPS. It also
appreciated the product manage-ment and validation of
the Secretariat of the Environment of Illustrious
Metropolitan District of Quito. We thank the data which
came from INAMHI and MAE.
EXTREME EVENTS OF SOLAR RADIATION IN
QUITO: A RELATION WITH TEMPERATURE
AND CLIMATE CHANGE
Sheila Serrano Vincenti, Diana Zuleta and Cristina Lema
Centro de Investigación en Modelamiento Ambiental CIMA-UPS/
Universidad Politécnica Salesiana/Red de Universidades Frente al
Cambio Climático y Gestión de Riesgos, Quito, ECUADOR.
sserranov@ups.edu.ec
Solar radiation biological efects

A 7% of total solar radiation is Ultraviolet (UV) with cumulative effects

UVC (100-280 nm) which is very dangerous to living things and is completely
absorbed by the atmosphere, the radiation

UVB (280-315 nm) that comes in a small proportion to the surface because it is
absorbed about 90% and can generate ridges, skin cancer, cataracts and
pterygium, and which comes full to the earth's surface is
 UVA (315-400 nm) comes full to the earth which cause premature skin aging and
darkening (Marin, 2007).(Benavides, 2010).
Data and metodology
Station
Temporal
Tumbaco
Los Chillos
Carapungo
Cotocollao
Belisario
El Camal
7
7
7
7
7
7
Latitude
0°12'36'' S
0°18'00'' S
0°5'54'' S
0°6'28'' S
0°10'48'' S
0°15'00'' S
Longitude
78°24'00''
78°27'36''
78°26'50''
78°29'50''
78°29'24''
78°30'36''
W
W
W
W
W
W
Height
2331
2453
2660
2793
2835
2840
97,76
97,82
97,22
97,42
97,67
93,67
Table1. Available data of hourly solar radiation of REMMAQ (Red
de Metropolitana de Monitoreo Atmosférico de Quito), the
meteorological station location and the percentage of valid data
are showed .
HOURLY ANALYSIS:
Intensity ()W/m2
Cotocollao - 2793msnm
1600
1400
1200
1000
800
600
400
200
0
2007
2008
2009
2010
2011
2012
2013
Fig. Typical hourly variation of the maximum values of solar
radiation per year. It is seen as the maximum values are achieved
in recent years
DAILY ANALISIS
Intensity (W/m2)
Los Chillos - 2453msnm
1350
1250
1150
1050
950
850
750
650
The trends (all positive) of
daily maximum solar
radiation from 2007 to
2013. The highest value
correspond to 16,53
W/m2.year, in the Chillos
station.
Station
Tumbaco
Los Chillos
Carapungo
cotocollao
Belisario
El Camal
y = 0,0453x + 905,08
R² = 0,0633
trend
(W/year)
10,91
16,53
8,322
15,22
6,64
12,41
p- value
9,37E-11
1,1569E-10
2,1037E-09
8,5827E-11
1,8225E-10
1,9858E-10
MONTHLY ANALYSIS
y = 2,0932x + 1046,2
R² = 0,4068
1300
1250
1200
1150
1100
1050
1000
950
900
ENERO
ABRIL
JULIO
OCTUBRE
ENERO
ABRIL
JULIO
OCTUBRE
ENERO
ABRIL
JULIO
OCTUBRE
ENERO
ABRIL
JULIO
OCTUBRE
ENERO
ABRIL
JULIO
OCTUBRE
ENERO
ABRIL
JULIO
OCTUBRE
ENERO
ABRIL
JULIO
OCTUBRE
Intensity (W/m2)
Los Chillos - 2453msnm
2007
2008
2009
2010
2011
2012
2013
Fig.4 presented maximal mensual values of Solar Radiation and Temperature, by station. Two
stations are located in the valleys and have a higher average (and maximum)
temperature, while others are located within the urban area of Quito. The correlation
between these variables is evident R whose coefficients vary between 0,05 and 0,08.
TEMPERATURE RELATION
Global Solar Radiation and Temperature
T
1350
28
1300
Intensity (W/m2)
29
27
1250
26
1200
25
1150
24
23
1100
22
1050
21
TUMBACO
LOS CHILLOS
CARAPUNGO
BELISARIO
RADIATION
TEMPERATURE
NOVIEMBRE
SEPTIEMBRE
JULIO
MAYO
MARZO
ENERO
NOVIEMBRE
SEPTIEMBRE
JULIO
MAYO
MARZO
ENERO
NOVIEMBRE
SEPTIEMBRE
JULIO
MAYO
MARZO
ENERO
NOVIEMBRE
SEPTIEMBRE
JULIO
MAYO
MARZO
ENERO
NOVIEMBRE
SEPTIEMBRE
JULIO
MAYO
MARZO
20
ENERO
1000
CAMAL
Maximal mensual values of Solar Radiation and Temperature, by
station. Two stations are located in the valleys and have a higher
average (and maximum) temperature, while others are located within
the urban area of Quito. The correlation between these variables is
evident R whose coefficients vary between 0,77 and 0,78.
Annual variation
CONCLUSIONS
 Although solar radiation is proportional to the height, it becomes clear that
in the studied data the most influential variable is the temperature.
 Likewise, it is interesting to observe that the maximum radiation values
occur in the months of March that not only correspond to the equinoxes,
but also the beginning of the rainy season in Quito. It is said that the water
vapor drops amplified radiation as a magnifying glass for a few moments.
This relates to the vernacular knowledge of hazard of the "sun of waters”
(sol de aguas) referred to the sun that is received before a storm (pres.
obs.).
 Finally, since the solar radiation is too sensitive to extreme temperature
variability, it is important to consider, its health effects in the context of a
pessimistic climate change scenario
Gracias!
Sheila Serrano Vincenti
sserranov@ups.edu.ec