Downscaling climate change of mean climatology and extremes of precipitation and temperature: Application to a Mediterranean climate basin

Abstract

Downscaling is usually necessary for robust hydrological impact assessments. This may be undertaken using a wide range of methods, including a combination of dynamical and statistical‐stochastic downscaling. This study uses the Spatial–Temporal Neyman‐Scott Rectangular Pulses model—RainSimV3, the precipitation‐conditioned daily weather generator—ICAAM‐WG, and the change factor approach for downscaling synthetic climate scenarios for robust hydrological impact assessment at middle‐sized basins. The ICAAM‐WG was developed based on the concept of the Climate Research Unit daily weather generator (CRU‐WG), motivated by the need for improved representation of heat waves by downscaling methods given the positive feedback between low soil moisture and high air temperature. We demonstrated the validity of the proposed methodology in the 705‐km2 Mediterranean climate basin in southern Portugal. The results show that, for the control period 1980–2010, both RainSimV3 and ICAAM‐WG reproduced not only the mean climatology, but also extreme wet and low precipitation events, as well as the extremes of temperature and heat waves. We found that downscaling with ICAAM‐WG (SIM6), which uses second‐order autoregressive processes for the simulation of temperature during consecutive dry and wet days, outperformed ICAAM‐WG (SIM4), which used only first‐order autoregressive processes, leading to improved simulation of heat waves. ICAAM‐WG (SIM6) well reproduced observed heatwave extremes with return periods of up to 30 years; however, ICAAM‐WG (SIM4) overestimated these extremes substantially. This indicates the importance of incorporating second‐order autoregressive processes in the simulation of heatwave length. In the context of climate warming, the proposed methodology provides a tool to improve downscaled projections of future extremes with confidence intervals for not only wet events but also dry spells and heat waves.

Downscaling climate change of water availability, sediment yield and extreme events: Application to a Mediterranean climate basin

“…Zhang et al . () found that the use of second order auto‐regressive processes improves the simulation of temperature extremes such as heatwave.…”

“…A weather generator—ICAAM‐WG, developed in Zhang () and Zhang et al . (), using the WG concept of Kilsby et al . (), is used for producing synthetic daily PET series.…”

“…Specifically, the advanced STNSRP, or the RainSim V3 model, developed by Burton et al (2008), is used for generation of synthetic precipitation series. A weather generator-ICAAM-WG, developed in Zhang (2015) and Zhang et al (2019), using the WG concept of Kilsby et al (2007a), is used for producing synthetic daily PET series. RCM model biases are considered stationary; and the change factor approach, described in Kilsby et al (2007a) and Jones et al (2010), is applied for projecting the future climate scenario.…”

“…As a demonstration, we apply the methodology to a 705-km 2 Mediterranean climate basin, in the context of sustainable regional development in southern Portugal. Climate projections derived from the RCM HadRM3Q0 (Collins et al, 2011) output, provided by the ENSEMBLES project (van der Linden and Mitchell, 2009), are used for climate downscaling (Zhang, 2015;Zhang et al, 2019). The RCM simulation was forced by boundary conditions from the 1.25 × 1.875 resolution Atmosphere-Ocean coupled GCM HadCM3Q0, using the SRES A1B (medium, non-mitigation) emission scenario (Nakicenovic and Swart, 2000).…”

“…Differently from CRU-WG, the model considers second order auto-regressive processes for simulating standard anomalies of temperature for consecutive wet and dry days. Zhang et al (2019) found that the use of second order autoregressive processes improves the simulation of temperature extremes such as heatwave.…”