Skill of 2-m Temperature Seasonal Forecasts over Europe in ECMWF and RegCM Models

Patarčić, Mirta; Branković, Čedo

doi:10.1175/mwr-d-11-00104.1

Cited by 9 publications

(12 citation statements)

References 49 publications

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“…Overall, however, the temperature biases in RegCM remain small over much of the ozone evaluation region with the exception of the highaltitude areas in the Alps. Past studies with older model versions (RegCM3) have a persistent cool bias (Giorgi et al, 2004;Zanis et al, 2009;Patarcic and Brankovic, 2012), yet RegCM4 simulations show a warm JJA bias in northern Europe and minimal bias in southern Europe (Giorgi et al, 2012) similar to these simulations.…”

Section: Climatological Ozone Simulationsupporting

confidence: 59%

Implementation and evaluation of online gas-phase chemistry within a regional climate model (RegCM-CHEM4)

et al. 2012

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Abstract. The RegCM-CHEM4 is a new online climatechemistry model based on the International Centre for Theoretical Physics (ICTP) regional climate model (RegCM4). Tropospheric gas-phase chemistry is integrated into the climate model using the condensed version of the Carbon Bond Mechanism (CBM-Z; Zaveri and Peters, 1999) with a fast solver based on radical balances. We evaluate the model over continental Europe for two different time scales: (1) an event-based analysis of the ozone episode associated with the heat wave of August 2003 and (2) a climatological analysis of a six-year simulation (2000)(2001)(2002)(2003)(2004)(2005). For the episode analysis, model simulations show good agreement with European Monitoring and Evaluation Programme (EMEP) observations of hourly ozone over different regions in Europe and capture ozone concentrations during and after the summer 2003 heat wave event. For long-term climate simulations, the model captures the seasonal cycle of ozone concentrations with some over prediction of ozone concentrations in non-heat wave summers. Overall, the ozone and ozone precursor evaluation shows the feasibility of using RegCM-CHEM4 for decadal-length simulations of chemistry-climate interactions.

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Section: Climatological Ozone Simulationsupporting

confidence: 59%

Implementation and evaluation of online gas-phase chemistry within a regional climate model (RegCM-CHEM4)

et al. 2012

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“…In agreement with recent studies [23,39,40], the precipitation results seem to confirm the evidence that an increased resolution, if on the one hand, at least in principle, ensures an improved physical values reproduction (e.g., smaller mean bias), on the other hand does not necessarily improve the forecast skill intended as a better representation of the inter-annual variability.…”

Section: Discussionsupporting

confidence: 90%

“…In recent years, many studies considered regional-scale dynamically downscaled SFSs, mainly focused on tropical Asian regions and Africa (see e.g., [18][19][20][21]). Based on the author's knowledge, few studies involving regional-scale SFC over the European domain exist [9,22,23], and even less focused on the Mediterranean [24] basin and the Italian peninsula [25]. However, in recent years, an interesting multi-partner initiative aimed at investigating inter-annual variability mechanisms and at providing tailored climate services mainly on a seasonal time scale in the Mediterranean basin has been established (MEDSCOPE, https://www.medscope-project.eu/).…”

Section: Introductionmentioning

confidence: 99%

Toward a Regional-Scale Seasonal Climate Prediction System over Central Italy Based on Dynamical Downscaling

Sangelantoni

Ferretti

Redaelli

2019

Climate

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Anticipating seasonal climate anomalies is essential for defining short-term adaptation measures. To be actionable, many stakeholders require seasonal forecasts at the regional scale to be properly coupled to region-specific vulnerabilities. In this study, we present and preliminarily evaluate a regional-scale Seasonal Forecast System (SFS) over Central Italy. This system relies on a double dynamical downscaling performed through the Regional-scale Climate Model (RCM) RegCM4.1. A twelve-member ensemble of the NCEP-CFSv2 provides driving fields for the RegCM. In the first step, the RegCM dynamically downscales NCEP-CFSv2 predictions from a resolution of 100 to 60 km over Europe (RegCM-d1). This first downscaling drives a second downscaling over Central Italy at 12 km (RegCM-d2). To investigate the added value of the downscaled forecasts compared to the driving NCEP-CFSv2, we evaluate the driving CFS, and the two downscaled SFSs over the same (inner) domain. Evaluation involves winter temperatures and precipitations over a climatological period (1982–2003). Evaluation for mean bias, statistical distribution, inter-annual anomaly variability, and hit-rate of anomalous seasons are shown and discussed. Results highlight temperature physical values reproduction benefiting from the downscaling. Downscaled inter-annual variability and probabilistic metrics show improvement mainly at forecast lead-time 1. Downscaled precipitation shows an improved spatial distribution with an undegraded but not improved seasonal forecast quality.

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“… Namias [1952]speculated that soil moisture could support month‐to‐month persistence in climatic anomalies over the United States. Since then, numerous studies have examined land‐atmosphere interaction, particularly focusing on soil moisture‐precipitation coupling using general circulation models (GCMs) [e.g., Rind , 1982; Koster et al , 2010], regional climate models [e.g., Paegle et al , 1996; Patarčić and Branković , 2012], or observational data [e.g., Entin et al , 2000; Mei and Wang , 2011]. These studies led to the consensus that soil moisture could add to summer precipitation predictability over regions where the land memory is long and the soil moisture‐precipitation coupling is strong.…”

Section: Introductionmentioning

confidence: 99%

Soil moisture‐vegetation‐precipitation feedback over North America: Its sensitivity to soil moisture climatology

Kim

Wang

2012

J. Geophys. Res.

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[1] Our previous studies examined how vegetation feedback at the seasonal time scale influenced the impact of soil moisture anomalies (SMAs) on subsequent summer precipitation with a modified version of the coupled Community Atmosphere Model-Community Land Model 3 that includes a predictive phenology scheme. Here we investigate the climatology sensitivity of soil moisture-vegetation-precipitation feedback using the same model as the baseline model (BASE) and its derivative with modifications to the model runoff parameterization as the experiment model (EXP), in which we eliminate the subsurface lateral drainage to reduce the known dry biases of BASE. With vegetation feedback ignored, precipitation is more sensitive to wet SMAs than dry SMAs in BASE; opposite to BASE, the wetter mean soil moisture in EXP leads to higher sensitivity of precipitation to dry SMAs than to wet SMAs. However, in both BASE and EXP, the impact of dry SMAs on subsequent precipitation persists longer than the impact of wet SMAs. With vegetation feedback included, EXP shows a positive feedback between vegetation and precipitation following both dry and wet SMAs in summer, while BASE shows a positive feedback following wet SMAs only, with no clear signal following dry SMAs due to dry soil biases. In BASE, the magnitude of precipitation changes due to vegetation feedback is comparable to that due to soil moisture feedback when more realistic SMAs are applied. In addition, a major difference is found in spring when the vegetation impact on subsequent precipitation is negative and significant in BASE, but not significant in EXP.Citation: Kim, Y., and G. Wang (2012), Soil moisture-vegetation-precipitation feedback over North America: Its sensitivity to soil moisture climatology,

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Skill of 2-m Temperature Seasonal Forecasts over Europe in ECMWF and RegCM Models

Cited by 9 publications

References 49 publications

Implementation and evaluation of online gas-phase chemistry within a regional climate model (RegCM-CHEM4)

Implementation and evaluation of online gas-phase chemistry within a regional climate model (RegCM-CHEM4)

Toward a Regional-Scale Seasonal Climate Prediction System over Central Italy Based on Dynamical Downscaling

Soil moisture‐vegetation‐precipitation feedback over North America: Its sensitivity to soil moisture climatology

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