Variations in extreme values of precipitation for the next century in Central Campania

Variations in extreme values of precipitation for the next

century in Central Campania

Rianna G.1*, Guarino F.1, Mercogliano P.1,2, Cattaneo L.1, Vezzoli R.1

Iodice L.3, Fariello L.3

1 Centro Euro-Mediterraneo sui Cambiamenti Climatici (C.M.C.C.) - Capua (Italy),

2 Centro Italiano Ricerche Aerospaziali (C.I.R.A.) – Capua (Italy)

3 Autorità di Bacino della Campania Centrale, Napoli (Italy)

*Corresponding Author: [email protected]

Abstract

The Italian law 49/2010, implementing the EU Directive 2007/60/CE, states 3 steps:

1) identification of areas potentially affected by flooding events;

2) preparation of hazard maps;

3) elaboration of management plan for flood risk;

Moreover, this law specifically requires that the review of land use plans takes into

account the effects of climate change on flood hazard. In addition, the Directive

2007/60/EC, estimating that climate change could likely induce several negative

impacts, requests that the Commission reports to the European Parliament also

about these ones (Article 16). To analyze and evaluate the potential effects of climate

change (CC) for next century on extreme precipitations at subdaily-daily scale, typical

triggers of flood events, the River Basin Authority for Central Campania and the

Impact on Soil and Coasts Research division of CMCC started a collaboration whose

main results are summarized in this contribution. It aims at analyzing:

-variations on seasonal scale for cumulative precipitation and mean temperature;

-performances of the climate model in reproducing the extreme values of

precipitation on time scales ranging between 6 and 24 hours;

-expected changes in subdaily extreme values of precipitation on medium and long-

term, under the IPCC RCP4.5 and RCP8.5 emission scenarios.

Keywords: regional climate simulations, flood hazard, extreme precipitation events,

hydrological- geological hazard

SISC, Second Annual Conference

Climate change: scenarios, impacts and policy

Impacts & Implications ofClimate Change

878

1. INTRODUCTION

Climate changes (CC) could induce various effects on natural and anthropic

environments, including changes in water cycles and river flows both in terms of

mean values and especially, in terms of extreme values, inducing substantial

variations in the occurrence of issues such as drought and floods [1].

During the last years, starting from United Nations Framework Convention on

Climate Change - UNFCCC – (1992), the efforts to cope climate change effects have

gradually grown up to be explicitly recalled within the national and EU directives,

focusing on land protection and planning [2][3][4][5].

While the first actions were basically aimed to reduce pollutants emissions and to

mitigate CC, subsequently a great effort has been devoted for devising/developing

adaptation measures [6][7]. In particular, regarding Italian territory, due to its high

vulnerability to hydrological and geological hazards, a proper assessment of the

effects of climate change on such phenomena has become a crucial issue.

Although the most evident effects of climate change could be valued in “urban

flooding” often also related to inadequate sewerage systems (usually designed for

return periods equal to about 10-20 years), there are phenomena, probably less

frequent, such as flash floods and hyperconcentrated flows, considered under the

same term “flood” in the European Directive 2007/60/EC, that are more burdensome

in terms of economic losses and casualties. For such phenomena, Italian Law

49/2010 has required that, to update the Risk Management Plans, an evaluation

about the potentiality of CC to affect the geological and hydraulic hazard is carried

out.

The National Law 152/2006, implementing the European Directive 2000/60/EC, has

established the Authorities of River Basin District, but currently they are still in their

formative stages: for this reason, the task of developing Risk Management Plans has

been delegated, until now, to Basin Authorities established by previous law

183/1989.

To this aim, the tasks of Risk Management Plans concern the marking out of areas

potentially affected by floods or the identification of suitable structural (e.g.

embankments, detention basin, floodway) and not structural ( e.g. early warning

systems) actions for mitigation of geological/hydraulical risk; however, until now, for

Impacts & implications of Climate Change



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example, the sizing of artefacts (e.g., detention basins) followed the canonical

approach based on the reference event characterized by a given return period (e.g.

20 years). Such approach appears suitable under steady state conditions while in

transient conditions, such as those induced by CC, it may result in an overestimation

(simply entailing increased costs) or, in the worst case, in an underestimation of

volumes required to ensure the safeguard of the area.

In order to attempt to estimate how, in the next century, CC could affect rainfall

patterns and then the potential risks of using steady state approaches for

dimensioning mitigation works, the Basin Authority for Central Campania and Impact

on Soil and Coasts Research Division of CMCC started a collaboration whose main

first results are summarized in this work.

It represents a first endeavour to understand the performances of climate simulations

on maximum values of sub daily rainfall (of major interest for flood events) and their

estimated variations over the next century until 2100 for two different emission

scenarios (i.e., IPCC RCP 4.5 and RCP 8.5) [8].

2. THE CLIMATE MODELING CHAIN

The evaluation of the potential effects of CC on the precipitation pattern distribution

of the Campania region over the 21st century is based on the following simulation

approach: the output of a General Circulation Model (GCM) is dynamically

downscaled through a Regional Climate Model (RCM) over a limited domain centred

on the Italian area. More specifically, the GCM considered is CMCC-CM. It is a

coupled atmosphere-ocean general circulation model developed at CMCC: the

atmospheric model component is ECHAM5 [10] with a T159 horizontal resolution,

while the global ocean component is OPA 8.2, in its ORCA2 global configuration, at

horizontal resolution 2 x 2 . ORCA2 also includes the Louvain-La-Neuve (LIM)

model for the dynamics and thermodynamics of sea-ice. In the present work, two

different IPCC emission scenarios have been used to force CMCC-CM, namely

RCP4.5 (medium level) and RCP8.5 (high level greenhouse gas emission). The

current spatial resolution of CMCC-CM (about 80 km) is not able to capture the

climate features and in particular the precipitation pattern, especially over the Italian

area characterized by complex topography and coastline and the presence of




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different climate regimes [11]. A more appropriate description of these features can

be achieved through dynamical downscaling: the RCM considered in this work is

COSMO-CLM [13][14], developed by the CLM Community (www.clm-community.eu),

in which CMCC participates since 2008. The specific model configuration adopted,

characterized by a spatial resolution of 0.0715° (about 8 km), has been optimized at

CMCC[15].

3. CLIMATE NUMERICAL SIMULATIONS: VALIDATION AND PROJECTIONS

In order to assess the capabilities of the simulation chain above described to properly

represent the present precipitation patterns and to characterize the model systematic

errors (and then the uncertainties associated with the results) two RCM control

simulations have been performed. Both simulations have been conducted over the

time period 1979-2011, using a horizontal resolution of 0.0715° (about 8 km, time

step 40 sec.): in the first one, initial and boundary conditions are provided by ERA-

Interim Reanalysis [16] produced by ECMWF, in order to characterize the bias

associated with the RCM; in the second one, initial and boundary conditions are

provided by CMCC-CM. Comparison has been performed against different

observations datasets: E-OBS [17], EURO4M-APGD (Alpine Precipitation Grid

Dataset) [18] and high resolution observational datasets provided by regional Italian

ARPAs (Italian Regional Agency for Environment Protection). Comparisons showed

a good capability of the simulation chain to reproduce the climate over the period

simulated for the different Italian subdomains considered [Fig. 1].

[Figure 1]

Figures 2 and 3 show the good capability of the model in reproducing the seasonal

cycle of surface temperature and precipitation over the different considered areas,

although precipitation is affected by a higher bias . More detailed analysis on the

validation are reported in [19][20].

Successively, climate projections using the same simulation chain configuration, but

forcing the global model according with IPCC RCP4.5 and RCP8.5 scenarios have

been performed.

[Figure 2]

[Figure 3]




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For what concerns the temperature, climate projections highlight a general warming

expected in Italy at the end of 21st century [Fig. 4]; particularly evident for 2071-2100

time period under RCP 8.5 emission scenario when average values higher than 5°C

are attained. In terms of precipitation values [Fig. 5], different variation patterns are

estimated for wet and dry seasons. In the first case, in the North and Central Italy (on

Tyrrhenian coast), an increase of cumulative values is assessed reaching +60% in

the Alpine region under RCP 8.5 emission scenario while, in the Southern part and

for insular areas, the decrease does not exceed 30%.

For dry seasons, a substantial decrease is detected; in particular, under RCP 8.5

emission scenario, on average, it is about equal to 50%.

More details on the results of the climate projections for Italian domain are reported

in [21]. Figures and analysis performed in the present work have been obtained using

CLIME, a special purpose GIS software integrated in ESRI ArcGIS Desktop 10.X,

developed at CMCC (ISC Division) in order to easily evaluate multiple climate

features and to study climate changes over specific geographical domains with their

related effects on environment, including impacts on soil.

[Figure 4]

[Figure 5]

4. CLIMATE SCENARIOS FOR MAXIMA AND CUMULATED PRECIPITATION

OVER THE AUTHORITY OF THE CENTRAL BASIN OF CAMPANIA AREA

Although the main issue of this research concerns the assessment of the possible

changes in maximum values of sub-daily precipitation induced by climate change, it

is interesting to set this analysis in a broader framework and previously investigate

the variations of cumulated precipitation and average temperature at seasonal scale

on the Basin of Central Campania domain for 21st century.

To this aim, only grid points entirely falling within the domain have been taken into

account, avoiding any data interpolation. Furthermore, two time horizons are

evaluated: short (2021-2050) and long (2071-2100) compared to the control period

1981-2010 under the two mentioned emission scenarios.

In Figure 6, seasonal cumulative precipitation anomalies are displayed (2021- 2050

vs 1981-2010 (a) and 2071- 2100 vs 1981-2010 (b)) under the emission scenario

RCP 4.5; two different behaviours for dry (MAM-JJA) and wet (SON-DJF) seasons




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are identifiable: in the first case, an overall reduction is estimated with values lower

than 20% in spring and attaining more than 50% in summer; in the second case, in

winter, the signal appears fluctuating with variations ranging between ± 10%,

whereas in fall slight decreases (smaller than 10%) are recorded in the South-

Eastern part of the domain where progressively increasing values (up to 30%) on the

North-West are estimated for the 2071-2100 time span.

[Figure 6]

Such trends are also qualitatively confirmed by the simulation under the emission

scenario RCP 8.5 [Fig.7].

[Figure 7]

In the dry period, estimated reductions in precipitation are characterized by

remarkable homogeneity on the domain, reaching 40% on the short term (for both

seasons) and 70% for the summer season on long term; in the wet period, however,

in winter the slight decrease estimated on short-term is reversed, on the entire area,

in the following time span with general precipitation increments higher than 20%; in

autumn, the presence of two areas with opposite behaviour is confirmed: an area

(South-East) characterized by a reduction in precipitation values (from about 10% for

2021-2050 to about 20% for the next period) and another (North-West) where,

however, estimated increases are smaller than those estimated for the RCP 4.5

scenario.

In addition, in Table 1 the expected changes of seasonal mean temperature on the

two time periods and the two emission scenarios are reported.

[Table 1]

Climate signals in terms of temperature appears unambiguous, providing an

increase of temperature for all seasons which depends on the time horizon and on

the "severity" of the emission scenario (up to more than 5° C, for the simulation

performed under RCP 8.5 on the interval 2071-2100).

As regards the estimation of future evolutions of the maximum precipitation at sub

daily scale for Italian peninsula, at our knowledge a limited number of researches has

been carried out [22]. This is basically due to the current constraints of climate

simulations and simultaneous lack of reliable datasets (for length and temporal

resolution) adequate for the validation phase. Concerning the first aspect, nowadays,

the usual spatial resolutions of climate models (also if dynamically downscaled




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through RCMs) are not able to properly simulate some physical dynamics, such as

convection and diurnal cycles significant for reproducing sub daily atmospheric

pattern while they achieve satisfactory performances on daily scale [23][24]; for the

same reason, their performances related to representation of extremes values are

often significantly worse than those related to mean values [25][26].

In order to assess the ability of the adopted simulation to reproduce the extreme

precipitation values on sub daily scale, for period 1981-2010, the annual maximum

values reported in the Hydrological Yearbooks (until 2000) and data retrieved by

Regional Civil Protection relating to all the stations including within the Basin

Authority are used; since the climate simulation results are stored with a time step of

6 hours, only the three reference durations, 6, 12 and 24 hours, are considered.

A comparison between simulated values and observations, in terms of average

values on the control period, returns a significant underestimation, slightly under

40% for maximum at 6 hours and slightly more than 30% for the 12 and 24 hours.

However, from a detailed analysis of available observed series, for several weather

stations, gaps even more than 60% are detected and thus it could partially affect the

reliability of the estimated values. If the analysis is carried out by comparing, on the

considered areas, the simulated values with data retrieved from meteorological

stations (for which, 20 years of observations are available, at least ) the error, still

relevant, drops to 33% on 6 hours and between 25 and 29% for 12 and 24 hours.

It is worth noting that a part of the underestimation is due to the temporal resolution

of the maximum values available for the simulations equal to 6 hours (then with four

values per day), while the maximum observed is computed on moving windows.

After assessing the magnitude of the simulation error, subsequent analyses are

aimed to investigate two further issues:

a) the significant error is, at least, characterized by time invariance;

b) the climate simulation on the control period, excluding the error on the average

value, is able to identify the pattern of spatial variation over the area.

Regarding a), although the current simulation error does not allow the use of the

model results as absolute values, however, verifying on the control period that bias

can be assumed as time invariant and so that the current constraints of the climate

modelling affect the estimates in a comparable way, regardless of the investigated

period, variations of the maximum values in sub-daily scale between future and

control time period could be estimated, at least, in terms of percentage anomaly. In




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this case, a first attempt to evaluate “bias time invariance” have been carried out

estimating mean errors for the two subsets 1981-1995 and 1996-2010, and for sets

formed by odd and even years; in both cases, the error does not undergo substantial

variations, ranging between ± 3%.

Regarding b), in Figure 8 for maximum yearly values over 24 hours averaged on

control period, a comparison is carried out between simulated (a) and observed (b)

data produced as ratio between the local value and the average value over the entire

area.

Thereby, values higher than 1 indicate an area in which maximum values are greater

than the average value on the entire area, while the opposite occurs for values less

than 1.

[Figure 8]

The model reproduces quite well the spatial patterns providing values greater than

the average value in the internal and south-east part and lower values in the other

parts of the domain; moreover, deviations from mean values are reproduced in an

appropriate way (the same considerations apply also to the maximum values at

higher temporal resolution, with slightly worst performances).

In Figure 9, projected anomalies for maximum sub daily precipitation values are

shown, respectively for the emission scenario RCP 4.5 and RCP 8.5, comparing

2021-2050 vs 1981-2010; differences between the two scenarios seem very limited:

for both and for all investigated time scales, two areas characterized by

homogeneous behaviour are identified: an area in the north-west where mild to

moderate increases in maximum values are estimated, a central area, extending

from the inland areas up to the coastal areas, where, on the contrary, signal

increases are not detected and with limited areas where a slight reduction (less than

10%) of the maximum values is simulated. A wider area characterized by null

variations/weak decrease is estimated for RCP 8.5 scenario: it is limited in the

southern part by a further inner area where, again, slight increases in the maximum

values are simulated. In general terms, the climate signal is clearly assumed growing

especially in the northern part of the domain, currently characterized by mean

maximum precipitation values [Fig. 8] lower than the average values for the area.

[Figure 9]

In Figure 10, corresponding values for the period 2071-2100 are reported. The above

identified positive anomalies (with increased magnitude) and spatial patterns of




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variation persist for both emission scenarios. Concerning the magnitude of the

changes, under the RCP 4.5 scenario, in the two areas previously identified as the

most affected by increases, changes take comparable size (about 20% compared to

the reference period), while for the emission scenario RCP 8.5, in the northern area

evaluated changes, on average, could attain values about equal to +50% compared

to the reference period.

[Figure 10]

In order to provide information about the frequencies of heavy rainfall events, Figure

11 reports, on seasonal scale, the relative frequency (in %) of the areal average

rainfall (higher than 0.1 mm) on 6 hours for the control period and the thirty years

ranging from 2071 to 2100 under emission scenarios RCP4.5 and RCP8.5;

furthermore, "proportion dry" is indicated. According to the approach described in

[27], precipitation values have been normalized with respect to the mean simulated

value in the control period, in order to avoid taking into account absolute values

affected by significant uncertainties.

Only relative frequency values higher than 0.05% are considered, while adopting a

logarithmic scale allows a better view for intense events characterized by low

probability of occurrence.

For both scenarios, in all seasons, an increase of proportion dry is estimated, with

increases about equal to 10% for the spring season, and values up to 98% for the

summer season in RCP 8.5; such result is physically consistent with the increase in

estimated temperature [Tab.1] with subsequent increase in atmospheric water

retention capacity; for the same reason, the expected increase is greater for the RCP

8.5 scenario characterized by a major increase in the "radiation" forcing and in

atmospheric temperature. In the same way, similar considerations may, partly,

explain the increase in frequency of the heaviest precipitation events, shifting the tail

of the distribution for both scenarios compared to the control period. Similarly, for

less intense events, (e.g. lower than the mean value of the control period), both

scenarios return a reduction in frequency (such reductions are in part masked by the

adoption of a logarithmic scale). Again, such assumption appears to be function of

the severity of the considered emission scenario. Remarkable is the increase in the

range of variability (increase of maximum values) and their weight (increase in the

frequency of occurrence) during the autumn and summer season, while during wet

season it is less evident.




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[Figure 11]

5. CONCLUSIONS

The study represents a first attempt for the Italian territory to estimate the

performances of the modelling chain implemented at CMCC (the global model

CMCC-CM and the regional model COSMO-CLM) for the representation of the

extreme values of precipitation on the scale from daily to 6 hours. After a

quantification of the uncertainties related to the use of different climate numerical

models, the possible future changes of such values under two climate change

emission scenarios in the short and long term have been evaluated. Considering the

current uncertainties in climate models previously reported, the results shown can be

used, essentially, to understand what might be the "direction" and the "relative

magnitude" of the expected changes in the distribution of the maximum values on the

area where assumed emission scenarios prove to be consistent with the actual

emissions pollutants, but, currently, they do not allow more quantitative estimates.

6. AKNOWLEDGEMENTS

This paper has been developed within the framework of Work Package 6.2.17 of the

GEMINA project, funded by the Italian Ministry of Education, University and Research

and the Italian Ministry of Environment, Land and Sea. A particular acknowledgment

to the Campania Civil Protection Department for providing their observational datasets.

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8. IMAGES AND TABLES

DJF MAM JJA SON

RCP4.5_2021-2050 1.4 1.5 1.8 1.8

RCP8.5_2021-2050 2.1 1.8 1.9 2.1

RCP4.5_2071-2100 2.8 2.9 3.5 3.5

RCP8.5_2071-2100 5.1 4.7 6.3 5.4

Tab. 1 Expected changes (in ° C) of the average seasonal temperature for domain of the Basin of Central Campania for 2 time windows 2021-2050 and 2071-2100 for two different emission scenarios compared to the control period.




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Fig. 1 Representation of the 3 sub-domain considered.

Fig. 2 seasonal cycle of the surface temperature for the three sub-areas shown in the Fig. 1.

Fig. 3 seasonal cycle of the precipitation for the three sub-areas shown in the Fig. 1.




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Fig. 4 Two-meter temperature (°C) climate projections for both scenarios: seasonal differences (December-January- February (DJF) [a-b] and June-July-August (JJA) [c-d]) between the average value over 2071-2100 and 1981-2010.

Fig. 5 Anomalies of seasonal cumulative precipitation (%) between the average value over 2071- 2100 and 1971-2000 under RCP 4.5 and RCP 8.5 emission scenarios; a-b: December-January-

February DJF; c-d: June-July-August JJA.




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Fig. 6 Anomaly ( , in %) of cumulative seasonal precipitation for the climate simulation (CMCC_CM+CCLM), under the emission scenario RCP 4.5 for time intervals 2021-2050 (a) and 2071- 2100 (b) vs 1981-2010.

Fig. 7 Anomaly ( , in %) of cumulative seasonal precipitation for the climate simulation (CMCC_CM+CCLM), under the emission scenario RCP 8.5 for time intervals 2021-2050 (a) and 2071- 2100 (b) vs 1981-2010.




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Fig. 8 Comparison of the ratio between local values and mean value for the entire area for observed data (a) and the climate simulation CMCC-CM+CCLM (b) related to averaged values of maximum rainfall over 24 h on control period.

Fig. 9 Anomalies (in %) of the maximum values of precipitation at 6h (a), 12h (b), 24h (c) and daily scale (d) between 2021- 2050 and the reference period 1981-2010 for the climate simulation forced by the emission scenario RCP 4.5. (on the left) and RCP 8.5 (on the right)

Fig. 10 Anomalies (in %) of the maximum values of precipitation at 6h (a), 12h (b), 24h (c) and daily scale (d) between 2071- 2100 and the reference period 1981- 2010 for the climate simulation forced by the emission scenario RCP 4.5. (on the left) and RCP 8.5 (on the right).




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Fig. 11 Relative frequency (in %) of the average areal rainfall on 6 hours on seasonal scale, for control period (CTR) and 2071-2100 under climate scenarios RCP4.5 and RCP8.5, the probability of no precipitation for each simulation is indicated by the " proportion dry" and reported in the legend.




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Variations in extreme values of precipitation for the next century in Central Campania

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