Assessing extreme precipitation from a regional climate model in different spatial–temporal scales: A hydrological perspective in South America. (10th July 2022)
- Record Type:
- Journal Article
- Title:
- Assessing extreme precipitation from a regional climate model in different spatial–temporal scales: A hydrological perspective in South America. (10th July 2022)
- Main Title:
- Assessing extreme precipitation from a regional climate model in different spatial–temporal scales: A hydrological perspective in South America
- Authors:
- Brêda, João Paulo Lyra Fialho
de Paiva, Rodrigo Cauduro Dias
Chou, Sin Chan
Collischonn, Walter - Abstract:
- Abstract: Global and regional climate models (GCM and RCM respectively) are the current mathematical tools used to project alterations on precipitation regimes given different greenhouse gases emissions scenarios. However, these models have specific resolutions, physical equations and numerical approaches that provide a diverse set of performances across different regions and spatial–temporal scales. In South America, most hydrological impact studies have used the Eta RCM to yield precipitation projections without a proper uncertainty analysis. It is important to acknowledge its uncertainties prior to any hydrological assessment to adequately support climate change investigations and related water decision making. Therefore, we aim to investigate how Eta extreme precipitation biases vary in different spatial–temporal scales from a hydrological perspective. Thus, we evaluate the extreme precipitation generated by the Eta RCM driven by four different GCMs. It is investigated Eta biases across different temporal (3 hr–5 days) and spatial scales (0.2–1.0°) and how those errors affect river streamflow simulations. It is used local intensity–duration–frequency (IDF) curves and gridded precipitation datasets (MSWEP and ERA5‐Land) as references for Eta assessment. In general, Eta underestimates subdaily extreme precipitation across South America, regardless of the driven GCM. The median bias of a 10‐year return period daily precipitation is −36 mm (1st and 3rd quantiles −58 andAbstract: Global and regional climate models (GCM and RCM respectively) are the current mathematical tools used to project alterations on precipitation regimes given different greenhouse gases emissions scenarios. However, these models have specific resolutions, physical equations and numerical approaches that provide a diverse set of performances across different regions and spatial–temporal scales. In South America, most hydrological impact studies have used the Eta RCM to yield precipitation projections without a proper uncertainty analysis. It is important to acknowledge its uncertainties prior to any hydrological assessment to adequately support climate change investigations and related water decision making. Therefore, we aim to investigate how Eta extreme precipitation biases vary in different spatial–temporal scales from a hydrological perspective. Thus, we evaluate the extreme precipitation generated by the Eta RCM driven by four different GCMs. It is investigated Eta biases across different temporal (3 hr–5 days) and spatial scales (0.2–1.0°) and how those errors affect river streamflow simulations. It is used local intensity–duration–frequency (IDF) curves and gridded precipitation datasets (MSWEP and ERA5‐Land) as references for Eta assessment. In general, Eta underestimates subdaily extreme precipitation across South America, regardless of the driven GCM. The median bias of a 10‐year return period daily precipitation is −36 mm (1st and 3rd quantiles −58 and −17 mm) compared to MSWEP and −26 mm (1st and 3rd quantiles −45 and −11 mm) compared to ERA5‐Land. However, the relative errors reduce with temporal and spatial aggregation. For example, the average bias of extreme precipitation decreases 8.4 and 5.4 percentage points from 1‐ to 5‐day duration compared to MSWEP and ERA5‐Land, respectively. The negative biases observed for precipitation ( ≈ 20%) are propagated to the flood discharges ( ≈ 40%), and these errors reduce with the drainage area. In general, there are greater biases in extreme discharges for small basins, but these errors considerably reduce for basins larger than 30, 000 km 2 compared to MGB‐MSWEP simulations. Compared to MGB‐ERA5‐Land simulations, MGB‐Eta presents relatively similar errors for basins of different sizes, probably due to the high negative bias for not only extreme but average precipitation as well. Abstract : Assessment of the extreme precipitation generated by the Eta RCM in terms of its impact on discharge. The Eta RCM underestimates extreme precipitation of short duration (less than 5 days). Biases of extreme discharge significantly reduce for basins larger than 30, 000 km 2 . … (more)
- Is Part Of:
- International journal of climatology. Volume 42:Number 16(2022)
- Journal:
- International journal of climatology
- Issue:
- Volume 42:Number 16(2022)
- Issue Display:
- Volume 42, Issue 16 (2022)
- Year:
- 2022
- Volume:
- 42
- Issue:
- 16
- Issue Sort Value:
- 2022-0042-0016-0000
- Page Start:
- 8904
- Page End:
- 8927
- Publication Date:
- 2022-07-10
- Subjects:
- cross‐scale assessment -- Eta -- hydrological impact studies -- IDF curves -- MGB -- streamflow
Climatology -- Periodicals
Climat -- Périodiques
Climatologie -- Périodiques
551.605 - Journal URLs:
- http://onlinelibrary.wiley.com/ ↗
- DOI:
- 10.1002/joc.7782 ↗
- Languages:
- English
- ISSNs:
- 0899-8418
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 4542.168000
British Library DSC - BLDSS-3PM
British Library STI - ELD Digital store - Ingest File:
- 26012.xml