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Yanjun Jiao and Colin Jones

Abstract

This paper presents results from the Canadian Regional Climate Model (CRCM) contribution to the Global Energy and Water Cycle Experiment (GEWEX) Pacific Cross-section Intercomparison Project. This experiment constitutes a simulation of stratocumulus, trade cumulus, and deep convective transitions along a cross section in the tropical Pacific. The simulated seasonal mean cloud and convection are compared between an original version of CRCM (CRCM4) and a modified version (CRCMM) with refined parameterizations. Results are further compared against available observations and reanalysis data. The specific parameterization refinements touch upon the triggering and closure of shallow convection, the cloud and updraft characteristics of deep convection, the parameterization of large-scale cloud fraction, the calculation of the eddy diffusivity in the boundary layer, and the evaporation of falling large-scale precipitation. CRCMM shows substantial improvement in many aspects of the simulated seasonal mean cloud, convection, and precipitation over the tropical Pacific, CRCMM-simulated total column water vapor, total cloud cover, and precipitation are in better agreement with observations than in the original CRCM4 model. The maximum frequency of the shallow convection shifts from the ITCZ region in CRCM4 to the subtropics in CRCMM; accordingly, excessive cloud in the shallow cumulus region in CRCM4 is greatly diminished. Finally, CRCMM better simulates the vertical structure of relative humidity, cloud cover, and vertical velocity, at least when compared to the 40-yr ECMWF Re-Analysis. Analyses of sensitivity experiments assessing specific effects of individual parameterization changes indicate that the modification to the eddy diffusivity in the boundary layer and changes to deep convection contribute most significantly to the overall model improvements.

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Ivan Güttler, Igor Stepanov, Čedo Branković, Grigory Nikulin, and Colin Jones

Abstract

The hydrostatic regional climate model RCA, version 3 (RCA3), of the Swedish Meteorological and Hydrological Institute was used to dynamically downscale ERA-40 and the ECMWF operational analysis over a 22-yr period. Downscaling was performed at four horizontal resolutions—50, 25, 12.5, and 6.25 km—over an identical European domain. The model-simulated precipitation is evaluated against high-resolution gridded observational precipitation datasets over Switzerland and southern Norway, regions that are characterized by complex orography and distinct climate regimes.

RCA3 generally overestimates precipitation over high mountains: during winter and summer over Switzerland and during summer over central-southern Norway. In the summer, this is linked with a substantial contribution of convective precipitation to the total precipitation errors, especially at the coarser resolutions (50 and 25 km). A general improvement in spatial correlation coefficients between simulated and observed precipitation is observed when the horizontal resolution is increased from 50 to 6 km. The 95th percentile spatial correlation coefficients during winter are much higher for southern Norway than for Switzerland, indicating that RCA3 is more successful at reproducing a relatively simple west-to-east precipitation gradient over southern Norway than a much more complex and variable precipitation distribution over Switzerland. The 6-km simulation is not always superior to the other simulations, possibly indicating that the model dynamical and physical configuration at this resolution may not have been optimal. However, a general improvement in simulated precipitation with increasing resolution supports further use and application of high spatial resolutions in RCA3.

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Danahé Paquin-Ricard, Colin Jones, and Paul A. Vaillancourt

Abstract

The total downwelling shortwave (SWD) and longwave (LWD) radiation and its components are assessed for the limited-area version of the Global Environmental Multiscale Model (GEM-LAM) against Atmospheric Radiation Measurements (ARM) at two sites: the southern Great Plains (SGP) and the North Slope of Alaska (NSA) for the 1998–2005 period. The model and observed SWD and LWD are evaluated as a function of the cloud fraction (CF), that is, for overcast and clear-sky conditions separately, to isolate and analyze different interactions between radiation and 1) atmospheric aerosols and water vapor and 2) cloud liquid water. Through analysis of the mean diurnal cycle and normalized frequency distributions of surface radiation fluxes, the primary radiation error in GEM-LAM is seen to be an excess in SWD in the middle of the day. The SWD bias results from a combination of underestimated CF and clouds, when present, possessing a too-high solar transmissivity, which is particularly the case for optically thin clouds. Concurrent with the SWD bias, a near-surface warm bias develops in GEM-LAM, particularly at the SGP site in the summer. The ultimate cause of this warm bias is difficult to uniquely determine because of the range of complex interactions between the surface, atmospheric, and radiation processes that are involved. Possible feedback loops influencing this warm bias are discussed. The near-surface warm bias is the primary cause of an excess clear-sky LWD. This excess is partially balanced with respect to the all-sky LWD by an underestimated CF, which causes a negative bias in simulated all-sky emissivity. It is shown that there is a strong interaction between all the components influencing the simulated surface radiation fluxes with frequent error compensation, emphasizing the need to evaluate the individual radiation components at high time frequency.

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Petter Lind, David Lindstedt, Erik Kjellström, and Colin Jones

Abstract

High-impact, locally intense rainfall episodes represent a major socioeconomic problem for societies worldwide, and at the same time these events are notoriously difficult to simulate properly in climate models. Here, the authors investigate how horizontal resolution and model formulation influence this issue by applying the HIRLAM–ALADIN Regional Mesoscale Operational NWP in Europe (HARMONIE) Climate (HCLIM) regional model with three different setups: two using convection parameterization at 15- and 6.25-km horizontal resolution (the latter within the “gray zone” scale), with lateral boundary conditions provided by ERA-Interim and integrated over a pan-European domain, and one with explicit convection at 2-km resolution (HCLIM2) over the Alpine region driven by the 15-km model. Seven summer seasons were sampled and validated against two high-resolution observational datasets. All HCLIM versions underestimate the number of dry days and hours by 20%–40% and overestimate precipitation over the Alpine ridge. Also, only modest added value was found for gray-zone resolution. However, the single most important outcome is the substantial added value in HCLIM2 compared to the coarser model versions at subdaily time scales. It better captures the local-to-regional spatial patterns of precipitation reflecting a more realistic representation of the local and mesoscale dynamics. Further, the duration and spatial frequency of precipitation events, as well as extremes, are closer to observations. These characteristics are key ingredients in heavy rainfall events and associated flash floods, and the outstanding results using HCLIM in a convection-permitting setting are convincing and encourage further use of the model to study changes in such events in changing climates.

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Ranjini Swaminathan, Robert J. Parker, Colin G. Jones, Richard P. Allan, Tristan Quaife, Douglas I. Kelley, Lee de Mora, and Jeremy Walton

Abstract

A key goal of the 2015 Paris Climate Agreement is to keep global mean temperature change at 2°C and if possible under 1.5°C by the end of the century. To investigate the likelihood of achieving this target, we calculate the year of exceedance of a given global warming threshold (GWT) temperature across 32 CMIP6 models for Shared Socioeconomic Pathway (SSP) and radiative forcing combinations included in the Tier 1 ScenarioMIP simulations. Threshold exceedance year calculations reveal that a majority of CMIP6 models project warming beyond 2°C by the end of the century under every scenario or pathway apart from the lowest emission scenarios considered, SSP1–1.9 and SSP1–2.6, which is largely a function of the ScenarioMIP experiment design. The U.K. Earth System Model (UKESM1) ScenarioMIP projections are analyzed in detail to assess the regional and seasonal variations in climate at different warming levels. The warming signal emerging by midcentury is identified as significant and distinct from internal climate variability in all scenarios considered and includes warming summers in the Mediterranean, drying in the Amazon, and heavier Indian monsoons. Arctic sea ice depletion results in prominent amplification of warming and tropical warming patterns emerge that are distinct from interannual variability. Climate changes projected for a 2°C warmer world are in almost all cases exacerbated with further global warming (e.g., to a 4°C warmer world).

Open access
Grigory Nikulin, Colin Jones, Filippo Giorgi, Ghassem Asrar, Matthias Büchner, Ruth Cerezo-Mota, Ole Bøssing Christensen, Michel Déqué, Jesus Fernandez, Andreas Hänsler, Erik van Meijgaard, Patrick Samuelsson, Mouhamadou Bamba Sylla, and Laxmi Sushama

Abstract

An ensemble of regional climate simulations is analyzed to evaluate the ability of 10 regional climate models (RCMs) and their ensemble average to simulate precipitation over Africa. All RCMs use a similar domain and spatial resolution of ~50 km and are driven by the ECMWF Interim Re-Analysis (ERA-Interim) (1989–2008). They constitute the first set of simulations in the Coordinated Regional Downscaling Experiment in Africa (CORDEX-Africa) project. Simulated precipitation is evaluated at a range of time scales, including seasonal means, and annual and diurnal cycles, against a number of detailed observational datasets. All RCMs simulate the seasonal mean and annual cycle quite accurately, although individual models can exhibit significant biases in some subregions and seasons. The multimodel average generally outperforms any individual simulation, showing biases of similar magnitude to differences across a number of observational datasets. Moreover, many of the RCMs significantly improve the precipitation climate compared to that from their boundary condition dataset, that is, ERA-Interim. A common problem in the majority of the RCMs is that precipitation is triggered too early during the diurnal cycle, although a small subset of models does have a reasonable representation of the phase of the diurnal cycle. The systematic bias in the diurnal cycle is not improved when the ensemble mean is considered. Based on this performance analysis, it is assessed that the present set of RCMs can be used to provide useful information on climate projections over Africa.

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Christopher J. Anderson, Raymond W. Arritt, Zaitao Pan, Eugene S. Takle, William J. Gutowski Jr., Francis O. Otieno, Renato da Silva, Daniel Caya, Jens H. Christensen, Daniel Lüthi, Miguel A. Gaertner, Clemente Gallardo, Filippo Giorgi, René Laprise, Song-You Hong, Colin Jones, H-M. H. Juang, J. J. Katzfey, John L. McGregor, William M. Lapenta, Jay W. Larson, John A. Taylor, Glen E. Liston, Roger A. Pielke Sr., and John O. Roads

Abstract

Thirteen regional climate model (RCM) simulations of June–July 1993 were compared with each other and observations. Water vapor conservation and precipitation characteristics in each RCM were examined for a 10° × 10° subregion of the upper Mississippi River basin, containing the region of maximum 60-day accumulated precipitation in all RCMs and station reports.

All RCMs produced positive precipitation minus evapotranspiration (PE > 0), though most RCMs produced PE below the observed range. RCM recycling ratios were within the range estimated from observations. No evidence of common errors of E was found. In contrast, common dry bias of P was found in the simulations.

Daily cycles of terms in the water vapor conservation equation were qualitatively similar in most RCMs. Nocturnal maximums of P and C (convergence) occurred in 9 of 13 RCMs, consistent with observations. Three of the four driest simulations failed to couple P and C overnight, producing afternoon maximum P. Further, dry simulations tended to produce a larger fraction of their 60-day accumulated precipitation from low 3-h totals.

In station reports, accumulation from high (low) 3-h totals had a nocturnal (early morning) maximum. This time lag occurred, in part, because many mesoscale convective systems had reached peak intensity overnight and had declined in intensity by early morning. None of the RCMs contained such a time lag. It is recommended that short-period experiments be performed to examine the ability of RCMs to simulate mesoscale convective systems prior to generating long-period simulations for hydroclimatology.

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EC-Earth

A Seamless Earth-System Prediction Approach in Action

Wilco Hazeleger, Camiel Severijns, Tido Semmler, Simona Ştefănescu, Shuting Yang, Xueli Wang, Klaus Wyser, Emanuel Dutra, José M. Baldasano, Richard Bintanja, Philippe Bougeault, Rodrigo Caballero, Annica M. L. Ekman, Jens H. Christensen, Bart van den Hurk, Pedro Jimenez, Colin Jones, Per Kållberg, Torben Koenigk, Ray McGrath, Pedro Miranda, Twan van Noije, Tim Palmer, José A. Parodi, Torben Schmith, Frank Selten, Trude Storelvmo, Andreas Sterl, Honoré Tapamo, Martin Vancoppenolle, Pedro Viterbo, and Ulrika Willén
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Faisal Hossain, Margaret Srinivasan, Craig Peterson, Alice Andral, Ed Beighley, Eric Anderson, Rashied Amini, Charon Birkett, David Bjerklie, Cheryl Ann Blain, Selma Cherchali, Cédric H. David, Bradley Doorn, Jorge Escurra, Lee-Lueng Fu, Chris Frans, John Fulton, Subhrendu Gangopadhay, Subimal Ghosh, Colin Gleason, Marielle Gosset, Jessica Hausman, Gregg Jacobs, John Jones, Yasir Kaheil, Benoit Laignel, Patrick Le Moigne, Li Li, Fabien Lefèvre, Robert Mason, Amita Mehta, Abhijit Mukherjee, Anthony Nguy-Robertson, Sophie Ricci, Adrien Paris, Tamlin Pavelsky, Nicolas Picot, Guy Schumann, Sudhir Shrestha, Pierre-Yves Le Traon, and Eric Trehubenko
Open access
Diana Greenslade, Mark Hemer, Alex Babanin, Ryan Lowe, Ian Turner, Hannah Power, Ian Young, Daniel Ierodiaconou, Greg Hibbert, Greg Williams, Saima Aijaz, João Albuquerque, Stewart Allen, Michael Banner, Paul Branson, Steve Buchan, Andrew Burton, John Bye, Nick Cartwright, Amin Chabchoub, Frank Colberg, Stephanie Contardo, Francois Dufois, Craig Earl-Spurr, David Farr, Ian Goodwin, Jim Gunson, Jeff Hansen, David Hanslow, Mitchell Harley, Yasha Hetzel, Ron Hoeke, Nicole Jones, Michael Kinsela, Qingxiang Liu, Oleg Makarynskyy, Hayden Marcollo, Said Mazaheri, Jason McConochie, Grant Millar, Tim Moltmann, Neal Moodie, Joao Morim, Russel Morison, Jana Orszaghova, Charitha Pattiaratchi, Andrew Pomeroy, Roger Proctor, David Provis, Ruth Reef, Dirk Rijnsdorp, Martin Rutherford, Eric Schulz, Jake Shayer, Kristen Splinter, Craig Steinberg, Darrell Strauss, Greg Stuart, Graham Symonds, Karina Tarbath, Daniel Taylor, James Taylor, Darshani Thotagamuwage, Alessandro Toffoli, Alireza Valizadeh, Jonathan van Hazel, Guilherme Vieira da Silva, Moritz Wandres, Colin Whittaker, David Williams, Gundula Winter, Jiangtao Xu, Aihong Zhong, and Stefan Zieger

Abstract

The Australian marine research, industry, and stakeholder community has recently undertaken an extensive collaborative process to identify the highest national priorities for wind-waves research. This was undertaken under the auspices of the Forum for Operational Oceanography Surface Waves Working Group. The main steps in the process were first, soliciting possible research questions from the community via an online survey; second, reviewing the questions at a face-to-face workshop; and third, online ranking of the research questions by individuals. This process resulted in 15 identified priorities, covering research activities and the development of infrastructure. The top five priorities are 1) enhanced and updated nearshore and coastal bathymetry; 2) improved understanding of extreme sea states; 3) maintain and enhance the in situ buoy network; 4) improved data access and sharing; and 5) ensemble and probabilistic wave modeling and forecasting. In this paper, each of the 15 priorities is discussed in detail, providing insight into why each priority is important, and the current state of the art, both nationally and internationally, where relevant. While this process has been driven by Australian needs, it is likely that the results will be relevant to other marine-focused nations.

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