scholarly journals Simulation of daily variation of precipitation during anomalously-wet dry season event over the western Maritime Continent

2021 ◽  
Vol 893 (1) ◽  
pp. 012046
Author(s):  
E Yulihastin ◽  
Suaydhi ◽  
H Satyawardhana ◽  
C N Ihsan
Keyword(s):  
Climate Model ◽  
Regional Climate ◽  
Tropical Rainfall Measuring Mission ◽  
Satellite Observation ◽  
Atmospheric Model ◽  
Dry Season ◽  
Maritime Continent ◽  
Local Circulation ◽  
Circulation Patterns ◽  
Anomalous Circulation

Abstract Local seas play a significant role in causing anomalously wet of the dry season over the Indonesia Maritime Continent (10°S-8°N, 95-145°E). As a result, modeling the anomalously-wet dry season over Indonesia lead challenges due to several subregional processes over local seas could not be captured well in the regional climate model. This study explores subregions processes of sea-air interaction over the western Maritime Continent by simulating diurnal precipitation using Cubic Conformal Atmospheric Model (CCAM) with a spatial resolution of 32 km during the anomalously-wet dry season periods during May-to-September (MJJAS) 2020. The simulated results were confirmed by precipitation data from Tropical Rainfall Measuring Mission (TRMM) satellite observation. The results show anomalous circulation patterns induce anomalous regional precipitation over western MC is induced by anomalous circulation patterns over four keys of seas subregion, i.e., Indian Ocean, South China Sea, southern Sumatra (Lampung and Sunda strait), and the Java Sea. Furthermore, the anomalous circulation also modulates anomalous local circulation and enhances surface water vapor by an increased surface latent heat flux.

scholarly journals A Mechanistically Credible, Poleward Shift in Warm-Season Precipitation Projected for the U.S. Southern Great Plains?

2017 ◽  
Vol 30 (20) ◽  
pp. 8275-8298 ◽  
Author(s):  
Melissa S. Bukovsky ◽  
Rachel R. McCrary ◽  
Anji Seth ◽  
Linda O. Mearns
Keyword(s):  
Great Plains ◽  
Climate Models ◽  
Climate Model ◽  
Global Climate Model ◽  
Regional Climate ◽  
Warm Season ◽  
Dry Season ◽  
Wet Season ◽  
Southern Great Plains ◽  
Poleward Shift

Abstract Global and regional climate model ensembles project that the annual cycle of rainfall over the southern Great Plains (SGP) will amplify by midcentury. Models indicate that warm-season precipitation will increase during the early spring wet season but shift north earlier in the season, intensifying late summer drying. Regional climate models (RCMs) project larger precipitation changes than their global climate model (GCM) counterparts. This is particularly true during the dry season. The credibility of the RCM projections is established by exploring the larger-scale dynamical and local land–atmosphere feedback processes that drive future changes in the simulations, that is, the responsible mechanisms or processes. In this case, it is found that out of 12 RCM simulations produced for the North American Regional Climate Change Assessment Program (NARCCAP), the majority are mechanistically credible and consistent in the mean changes they are producing in the SGP. Both larger-scale dynamical processes and local land–atmosphere feedbacks drive an earlier end to the spring wet period and deepening of the summer dry season in the SGP. The midlatitude upper-level jet shifts northward, the monsoon anticyclone expands, and the Great Plains low-level jet increases in strength, all supporting a poleward shift in precipitation in the future. This dynamically forced shift causes land–atmosphere coupling to strengthen earlier in the summer, which in turn leads to earlier evaporation of soil moisture in the summer, resulting in extreme drying later in the summer.

scholarly journals Characteristics of convective snow bands along the Swedish east coast

2017 ◽  
Vol 8 (1) ◽  
pp. 163-175 ◽  
Author(s):  
Julia Jeworrek ◽  
Lichuan Wu ◽  
Christian Dieterich ◽  
Anna Rutgersson
Keyword(s):  
Regional Climate Model ◽  
East Coast ◽  
Climate Model ◽  
Regional Climate ◽  
Open Water ◽  
Atmospheric Model ◽  
Ocean Model ◽  
Sea Surface ◽  
Precipitation Rate ◽  
Shallow Convection

Abstract. Convective snow bands develop in response to a cold air outbreak from the continent or the frozen sea over the open water surface of lakes or seas. The comparatively warm water body triggers shallow convection due to increased heat and moisture fluxes. Strong winds can align with this convection into wind-parallel cloud bands, which appear stationary as the wind direction remains consistent for the time period of the snow band event, delivering enduring snow precipitation at the approaching coast. The statistical analysis of a dataset from an 11-year high-resolution atmospheric regional climate model (RCA4) indicated 4 to 7 days a year of moderate to highly favourable conditions for the development of convective snow bands in the Baltic Sea region. The heaviest and most frequent lake effect snow was affecting the regions of Gävle and Västervik (along the Swedish east coast) as well as Gdansk (along the Polish coast). However, the hourly precipitation rate is often higher in Gävle than in the Västervik region. Two case studies comparing five different RCA4 model setups have shown that the Rossby Centre atmospheric regional climate model RCA4 provides a superior representation of the sea surface with more accurate sea surface temperature (SST) values when coupled to the ice–ocean model NEMO as opposed to the forcing by the ERA-40 reanalysis data. The refinement of the resolution of the atmospheric model component leads, especially in the horizontal direction, to significant improvement in the representation of the mesoscale circulation process as well as the local precipitation rate and area by the model.

scholarly journals An update of IPCC climate reference regions for subcontinental analysis of climate model data: definition and aggregated datasets

2020 ◽  
Vol 12 (4) ◽  
pp. 2959-2970
Author(s):  
Maialen Iturbide ◽  
José M. Gutiérrez ◽  
Lincoln M. Alves ◽  
Joaquín Bedia ◽  
Ruth Cerezo-Mota ◽  
...  
Keyword(s):  
Climate Change ◽  
Climate Model ◽  
Climate Adaptation ◽  
Regional Climate ◽  
Atmospheric Model ◽  
Future Climate Change ◽  
Intergovernmental Panel ◽  
Temperature And Precipitation ◽  
Scatter Plots ◽  
Projected Changes

Abstract. Several sets of reference regions have been used in the literature for the regional synthesis of observed and modelled climate and climate change information. A popular example is the series of reference regions used in the Intergovernmental Panel on Climate Change (IPCC) Special Report on Managing the Risks of Extreme Events and Disasters to Advance Climate Adaptation (SREX). The SREX regions were slightly modified for the Fifth Assessment Report of the IPCC and used for reporting subcontinental observed and projected changes over a reduced number (33) of climatologically consistent regions encompassing a representative number of grid boxes. These regions are intended to allow analysis of atmospheric data over broad land or ocean regions and have been used as the basis for several popular spatially aggregated datasets, such as the Seasonal Mean Temperature and Precipitation in IPCC Regions for CMIP5 dataset. We present an updated version of the reference regions for the analysis of new observed and simulated datasets (including CMIP6) which offer an opportunity for refinement due to the higher atmospheric model resolution. As a result, the number of land and ocean regions is increased to 46 and 15, respectively, better representing consistent regional climate features. The paper describes the rationale for the definition of the new regions and analyses their homogeneity. The regions are defined as polygons and are provided as coordinates and a shapefile together with companion R and Python notebooks to illustrate their use in practical problems (e.g. calculating regional averages). We also describe the generation of a new dataset with monthly temperature and precipitation, spatially aggregated in the new regions, currently for CMIP5 and CMIP6, to be extended to other datasets in the future (including observations). The use of these reference regions, dataset and code is illustrated through a worked example using scatter plots to offer guidance on the likely range of future climate change at the scale of the reference regions. The regions, datasets and code (R and Python notebooks) are freely available at the ATLAS GitHub repository: https://github.com/SantanderMetGroup/ATLAS (last access: 24 August 2020), https://doi.org/10.5281/zenodo.3998463 (Iturbide et al., 2020).

scholarly journals Internal Model Variability of the Regional Coupled System Model GCOAST-AHOI

Atmosphere ◽  
2020 ◽  
Vol 11 (3) ◽  
pp. 227 ◽  
Author(s):  
Ha Thi Minh Ho-Hagemann ◽  
Stefan Hagemann ◽  
Sebastian Grayek ◽  
Ronny Petrik ◽  
Burkhardt Rockel ◽  
...  
Keyword(s):  
Internal Model ◽  
Climate Model ◽  
Extreme Event ◽  
Regional Climate ◽  
Coupled System ◽  
Internal Variability ◽  
Atmospheric Model ◽  
Ocean Model ◽  
System Model ◽  
Model Variability

Simulations of a Regional Climate Model (RCM) driven by identical lateral boundary conditions but initialized at different times exhibit the phenomenon of so-called internal model variability (or in short, Internal Variability—IV), which is defined as the inter-member spread between members in an ensemble of simulations. Our study investigates the effects of air-sea coupling on IV of the regional atmospheric model COSMO-CLM (CCLM) of the new regional coupled system model GCOAST-AHOI (Geesthacht Coupled cOAstal model SysTem: Atmosphere, Hydrology, Ocean and Sea Ice). We specifically address physical processes parameterized in CCLM, which may cause a large IV during an extreme event, and where this IV is affected by the air-sea coupling. Two six-member ensemble simulations were conducted with GCOAST-AHOI and the stand-alone CCLM (CCLM_ctr) for a period of 1 September–31 December 2013 over Europe. IV is expressed by spreads within the two sets of ensembles. Analyses focus on specific events during this period, especially on the storm Christian occurring from 27 to 29 October 2013 in northern Europe. Results show that simulations of CCLM_ctr vary largely amongst ensemble members during the storm. By analyzing two members of CCLM_ctr with opposite behaviors, we found that the large uncertainty in CCLM_ctr is caused by a combination of two factors (1) uncertainty in parameterization of cloud-radiation interaction in the atmospheric model. and (2) lack of an active two-way air-sea interaction. When CCLM is two-way coupled with the ocean model, the ensemble means of GCOAST-AHOI and CCLM_ctr are relatively similar, but the spread is reduced remarkably in GCOAST-AHOI, not only over the ocean where the coupling is done but also over land due to the land-sea interactions.

scholarly journals Numerical Study of the Interaction between Oasis and Urban Areas within an Arid Mountains-Desert System in Xinjiang, China

Atmosphere ◽  
2020 ◽  
Vol 11 (1) ◽  
pp. 85
Author(s):  
Peng Cai ◽  
Rafiq Hamdi ◽  
Huili He ◽  
Geping Luo ◽  
Jin Wang ◽  
...  
Keyword(s):  
Land Surface ◽  
Urban Areas ◽  
Climate Model ◽  
Numerical Study ◽  
Urban Expansion ◽  
Regional Climate ◽  
Maximum Effect ◽  
Local Circulation ◽  
Urban Rural ◽  
The Impact

The rapid oasis expansion and urbanization that occurred in Xinjiang province (China) in the last decades have greatly modified the land surface energy balance and influenced the local circulation under the arid mountains-plain background system. In this study, we first evaluated the ALARO regional climate model coupled to the land surface scheme SURFEX at 4 km resolution using 53 national climatological stations and 5 automatic weather stations. We found that the model correctly simulates daily and hourly variation of 2 m temperature and relative humidity. A 4-day clear sky period has been chosen to study both local atmospheric circulations and their mutual interaction. Observations and simulations both show that a low-level divergence over oasis appears between 19:00 and 21:00 Beijing Time when the background mountain-plain wind system is weak. The model simulates a synergistic interaction between the oasis-desert breeze and urban-rural breeze from 16:00 until 22:00 with a maximum effect at 20:00 when the downdraft over oasis (updraft over urban) areas increases by 0.8 (0.4) Pa/s. The results show that the oasis expansion decreases the nocturnal urban heat island in the city of Urumqi by 0.8 °C, while the impact of urban expansion on the oasis cold island is negligible.

Investigating marine heat waves with a coupled atmosphere-ocean regional climate model

2021 ◽  
Author(s):  
Marie Pontoppidan ◽  
Priscilla Mooney ◽  
Jerry Tjiputra
Keyword(s):  
Climate Model ◽  
Heat Waves ◽  
Human Life ◽  
Regional Climate ◽  
Atmospheric Model ◽  
Ocean Model ◽  
Environmental Drivers ◽  
Climate Simulation ◽  
Substantial Impact ◽  
Spatio Temporal

<p>Marine heat waves (MHW’s) exert a substantial impact on human life and ecosystems in the ocean. In the western part of the tropical Atlantic basin, coral reefs are impacted by such events, resulting in coral bleaching and subsequently loss of biodiversity. To mitigate future changes in MHW’s it is detrimental to increase our mechanistic understanding of these events, and this must be investigated on a local scale to understand the smaller scale driving processes of the heat waves, e.g. air-sea interactions, and the spatio-temporal extent on environmental drivers essential for the ecosystem processes.</p><p>Here we use a coupled ocean-atmosphere modelling system (COAWST), which includes the atmospheric model WRF and the ocean model ROMS (including the Fennel ecosystem module), to dynamically downscale an area consisting of the Caribbean Sea and the Gulf of Mexico. Our 12 km grid spacing resolves (at least partly) smaller scale phenomena and in combination with the coupling of the ocean and the atmospheric model, it ensures a skilled representation of the air-sea interactions which are important for MHW’s. We will show the results of this decadal climate simulation with regards to generation, evolution and persistence of the MHW’s.</p>

scholarly journals Evaluating the Bias of South China Sea Summer Monsoon Precipitation Associated with Fast Physical Processes Using a Climate Model Hindcast Approach

2019 ◽  
Vol 32 (14) ◽  
pp. 4491-4507 ◽  
Author(s):  
Wei-Ting Chen ◽  
Chien-Ming Wu ◽  
Hsi-Yen Ma
Keyword(s):  
South China Sea ◽  
Summer Monsoon ◽  
South China ◽  
Climate Model ◽  
Atmospheric Model ◽  
Climate Simulation ◽  
Physical Processes ◽  
Local Circulation ◽  
China Sea ◽  
Onset Period

Abstract The present study aims to identify the precipitation bias associated with the interactions among fast physical processes in the Community Atmospheric Model, version 5 (CAM5), during the abrupt onset of the South China Sea (SCS) summer monsoon, a key precursor of the overall East Asia summer monsoon (EASM). The multiyear hindcast approach is utilized to obtain the well-constrained synoptic-scale horizontal circulation each year during the onset period from the years 1998 to 2012. In the pre-onset period, the ocean precipitation over the SCS is insufficiently suppressed in CAM5 hindcasts and thus weaker land–ocean precipitation contrasts. This is associated with the weaker and shallower convection simulated over the surrounding land, producing weaker local circulation within the SCS basin. In the post-onset period, rainfall of the organized convection over the Philippine coastal ocean is underestimated in the hindcasts, with overestimated upper-level heating. These biases are further elaborated as the underrepresentation of the convection diurnal cycle and coastal convection systems, as well as the issue of precipitation sensitivity to environmental moisture during the SCS onset period. The biases identified in hindcasts are consistent with the general bias of the EASM in the climate simulation of CAM5. The current results highlight that the appropriate representation of land–ocean–convection interactions over coastal areas can potentially improve the simulation of seasonal transition over the monsoon regions.

scholarly journals A module to convert spectral to narrowband snow albedo for use in climate models: SNOWBAL v1.0

2018 ◽  
Author(s):  
Christiaan T. van Dalum ◽  
Willem Jan van de Berg ◽  
Quentin Libois ◽  
Ghislain Picard ◽  
Michiel R. van den Broeke
Keyword(s):  
Radiative Transfer ◽  
Climate Models ◽  
Climate Model ◽  
Regional Climate ◽  
Greenland Ice Sheet ◽  
Atmospheric Model ◽  
Shortwave Radiation ◽  
Transfer Model ◽  
Snow Albedo ◽  
Radiation Scheme

Abstract. Snow albedo schemes in regional climate models often lack a sophisticated radiation penetration scheme and generally compute only a broadband albedo. Here, we present the Spectral-to-NarrOWBand ALbedo module (SNOWBAL, version 1.0) to couple effectively a spectral albedo model with a narrowband radiation scheme. Specifically, the Two-streAm Radiative TransfEr in Snow model (TARTES) is coupled with the European Center for Medium-Range Weather Forecasts (ECMWF) Integrated Forecast System atmospheric radiation scheme based on the rapid radiation transfer model, which is embedded in the regional climate model RACMO2. This coupling allows to explicitly account for the effect of clouds, snow impurities and snow metamorphism on albedo. Firstly, we present a narrowband albedo method to project the spectral albedos of TARTES onto the 14 spectral bands of the ECMWF shortwave radiation scheme using a representative wavelength (RW) for each band. Using TARTES and spectral downwelling surface irradiance derived with the DIScrete Ordinate Radiative Transfer atmospheric model, we show that RWs primarily depend on the solar zenith angle (SZA) and cloud content. Secondly, we compare the TARTES narrowband albedo, using offline RACMO2 results for South Greenland, with the broadband albedo parameterizations of Gardner and Sharp (2010), currently implemented in RACMO2, and the multi-layered parameterization of Kuipers Munneke et al. (2011, PKM). The actual absence of radiation penetration in RACMO2 leads on average to a higher albedo compared with TARTES narrowband albedo. Furthermore, large differences between the TARTES narrowband albedo and PKM and RACMO2 are observed for high SZA and clear-sky conditions, and after melt events when the snowpack is very inhomogeneous. This highlights the importance of accounting for spectral albedo and radiation penetration to simulate the energy budget of the Greenland ice sheet.

scholarly journals High-resolution projections of surface water availability for Tasmania, Australia

2012 ◽  
Vol 16 (5) ◽  
pp. 1287-1303 ◽  
Author(s):  
J. C. Bennett ◽  
F. L. N. Ling ◽  
D. A. Post ◽  
M. R. Grose ◽  
S. P. Corney ◽  
...  
Keyword(s):  
Surface Water ◽  
High Resolution ◽  
Water Availability ◽  
Climate Model ◽  
Potential Evapotranspiration ◽  
Regional Climate ◽  
Daily Rainfall ◽  
Atmospheric Model ◽  
Hydrological Models ◽  
Daily Streamflow

Abstract. Changes to streamflows caused by climate change may have major impacts on the management of water for hydro-electricity generation and agriculture in Tasmania, Australia. We describe changes to Tasmanian surface water availability from 1961–1990 to 2070–2099 using high-resolution simulations. Six fine-scale (∼10 km2) simulations of daily rainfall and potential evapotranspiration are generated with the CSIRO Conformal Cubic Atmospheric Model (CCAM), a variable-resolution regional climate model (RCM). These variables are bias-corrected with quantile mapping and used as direct inputs to the hydrological models AWBM, IHACRES, Sacramento, SIMHYD and SMAR-G to project streamflows. The performance of the hydrological models is assessed against 86 streamflow gauges across Tasmania. The SIMHYD model is the least biased (median bias = −3%) while IHACRES has the largest bias (median bias = −22%). We find the hydrological models that best simulate observed streamflows produce similar streamflow projections. There is much greater variation in projections between RCM simulations than between hydrological models. Marked decreases of up to 30% are projected for annual runoff in central Tasmania, while runoff is generally projected to increase in the east. Daily streamflow variability is projected to increase for most of Tasmania, consistent with increases in rainfall intensity. Inter-annual variability of streamflows is projected to increase across most of Tasmania. This is the first major Australian study to use high-resolution bias-corrected rainfall and potential evapotranspiration projections as direct inputs to hydrological models. Our study shows that these simulations are capable of producing realistic streamflows, allowing for increased confidence in assessing future changes to surface water variability.

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