scholarly journals A GCM comparison of Pleistocene super-interglacial periods in relation to Lake El'gygytgyn, NE Arctic Russia

2015 ◽  
Vol 11 (7) ◽  
pp. 979-989 ◽  
Author(s):  
A. J. Coletti ◽  
R. M. DeConto ◽  
J. Brigham-Grette ◽  
M. Melles
Keyword(s):  
Land Surface ◽  
Forest Cover ◽  
Climate Model ◽  
Regional Climate ◽  
The Arctic ◽  
Boreal Summer ◽  
Climate Data ◽  
Lake El’Gygytgyn ◽  
Proxy Reconstructions ◽  
Temperature Proxy

Abstract. Until now, the lack of time-continuous, terrestrial paleoenvironmental data from the Pleistocene Arctic has made model simulations of past interglacials difficult to assess. Here, we compare climate simulations of four warm interglacials at Marine Isotope Stages (MISs) 1 (9 ka), 5e (127 ka), 11c (409 ka) and 31 (1072 ka) with new proxy climate data recovered from Lake El'gygytgyn, NE Russia. Climate reconstructions of the mean temperature of the warmest month (MTWM) indicate conditions up to 0.4, 2.1, 0.5 and 3.1 °C warmer than today during MIS 1, 5e, 11c and 31, respectively. While the climate model captures much of the observed warming during each interglacial, largely in response to boreal summer (JJA) orbital forcing, the extraordinary warmth of MIS 11c compared to the other interglacials in the Lake El'gygytgyn temperature proxy reconstructions remains difficult to explain. To deconvolve the contribution of multiple influences on interglacial warming at Lake El'gygytgyn, we isolated the influence of vegetation, sea ice and circum-Arctic land ice feedbacks on the modeled climate of the Beringian interior. Simulations accounting for climate–vegetation–land-surface feedbacks during all four interglacials show expanding boreal forest cover with increasing summer insolation intensity. A deglaciated Greenland is shown to have a minimal effect on northeast Asian temperature during the warmth of stages 11c and 31 (Melles et al., 2012). A prescribed enhancement of oceanic heat transport into the Arctic Ocean does have some effect on Lake El'gygytgyn's regional climate, but the exceptional warmth of MIS l1c remains enigmatic compared to the modest orbital and greenhouse gas forcing during that interglacial.

scholarly journals A GCM comparison of Plio–Pleistocene interglacial–glacial periods in relation to Lake El'gygytgyn, NE Arctic Russia

2014 ◽  
Vol 10 (4) ◽  
pp. 3127-3161 ◽  
Author(s):  
A. J. Coletti ◽  
R. M. DeConto ◽  
J. Brigham-Grette ◽  
M. Melles
Keyword(s):  
Sea Ice ◽  
Ocean Circulation ◽  
Land Surface ◽  
Forest Cover ◽  
Ice Sheets ◽  
The Arctic ◽  
Boreal Summer ◽  
Mean Annual Precipitation ◽  
Mean Temperature ◽  
Lake El’Gygytgyn

Abstract. Until now, the lack of time-continuous, terrestrial paleoenvironmental data from the Pleistocene Arctic has made model simulations of past interglacials difficult to assess. Here, we compare climate simulations of four warm interglacials at Marine Isotope Stage (MIS) 1 (9 ka), 5e (127 ka), 11c (409 ka), and 31 (1072 ka) with new proxy climate data recovered from Lake El'gygytgyn, NE Russia. Climate reconstructions of the Mean Temperature of the Warmest Month (MTWM) indicate conditions 2.1, 0.5 and 3.1 °C warmer than today during MIS 5e, 11c, and 31, respectively. While the climate model captures much of the observed warming during each interglacial, largely in response to boreal summer orbital forcing, the extraordinary warmth of MIS 11c relative to the other interglacials in the proxy records remain difficult to explain. To deconvolve the contribution of multiple influences on interglacial warming at Lake El'gygytgyn, we isolated the influence of vegetation, sea ice, and circum-Arctic land ice feedbacks on the climate of the Beringian interior. Simulations accounting for climate-vegetation-land surface feedbacks during all four interglacials show expanding boreal forest cover with increasing summer insolation intensity. A deglaciated Greenland is shown to have a minimal effect on Northeast Asian temperature during the warmth of stage 11c and 31 (Melles et al., 2012). A prescribed enhancement of oceanic heat transport into the Arctic ocean has some effect on Beringian climate, suggesting intrahemispheric coupling seen in comparisons between Lake El'gygytgyn and Antarctic sediment records might be related to linkages between Antarctic ice volume and ocean circulation. The exceptional warmth of MIS 11c remains enigmatic however, relative to the modest orbital and greenhouse gas forcing during that interglacial. Large Northern Hemisphere ice sheets during Plio-Pleistocene glaciation causes a substantial decrease in Mean Temperature of the Coldest Month (MTCM) and Mean Annual Precipitation (PANN) causing significant Arctic aridification. Aridification and cooling can be linked to a combination of mechanical forcing from the Laurentide and Fennoscandian ice sheets on mid-tropospheric westerly flow and expanded sea ice cover causing albedo-enhanced feedback.

High-Resolution Regional Climate Simulations of Arctic Hydroclimatic Change

2021 ◽  
Author(s):  
Andrew Newman ◽  
Yifan Cheng ◽  
Keith Musselman ◽  
Anthony Craig ◽  
Sean Swenson ◽  
...  
Keyword(s):  
Land Surface ◽  
Climate Model ◽  
Water Cycle ◽  
Global Climate ◽  
Global Climate Model ◽  
Regional Climate ◽  
Land Surface Model ◽  
The Arctic ◽  
Surface Model ◽  
Systems Model

<p>The Arctic has warmed during the recent observational record and is projected to keep warming through the end of the 21<sup>st</sup> century in nearly every future emissions scenario and global climate model. This will drive continued thawing of permafrost-rich soils, alter the partitioning of rain versus snow events, and greatly affectthe water cycle and land-surface processes across the Arctic. However, previous analyses of these impacts using dynamical models have relied on global climate model output or relatively coarse regional climate model simulations. In the coarse simulations, projections of changes to the water cycle and land-surface processes in areas of complex orography and high land-surface heterogeneity, which are characteristic of many regions in the Arctic, may thus be limited. </p><p>Here, we discuss recent work examining high-resolution regional climate simulations over Alaska and NW Canada. Completed and upcoming simulations have been and will be run at a 4 km grid spacing, which is sufficient to resolve orography across this region’s mountain ranges. The initial simulation results are very encouraging and show the regional climate model yields a realistic representation of the seasonal and spatial evolution of precipitation, temperature, and snowpack compared to previous studies across Alaska and other Arctic regions. A paired future climate simulation uses the Pseudo-Global Warming (PGW) approach, where the end of century ensemble mean monthly climate perturbations (CMIP5 RCP8.5) are used to incorporate the thermodynamic effects of future warming into the present-day climate as represented by ERA-Interim reanalysis data. Changes in major components of the hydroclimate (e.g. precipitation, temperature, snowfall, snowpack) are projected to sometimes be significant in this future scenario. For example, the seasonal snow cover in some regions is projected to mostly disappear. However, there are also projected increases in snowpack in historically very cold areas (e.g. high elevations) that are able to stay cold enough in the future to support snowfall and snowpack.</p><p>Finally, we will present a new effort to couple an advanced land-surface model, the Community Terrestrial Systems Model (CTSM), within the Regional Arctic Systems Model (RASM) in an effort to better represent complex land-surface and subsurface (e.g. permafrost, streamflow availability timing and temperatures) processes for climate change impact studies. CTSM is a complex physically based land-surface model that is able to represent multiple snow layers, a complex canopy, and multiple soil layers including organic matter and frozen soils, which enables us to explicitly represent spatial variability in the regional hydroclimate and land states (e.g. permafrost) at relatively high spatial resolutions relative to other simulations (4 km land and atmosphere grids).  Successful coupling of CTSM within RASM has been completed and we will discuss some preliminary land-atmosphere coupled test results.</p>

scholarly journals Observations and Simulations of Meteorological Conditions over Arctic Thick Sea Ice in Late Winter during the Transarktika 2019 Expedition

Atmosphere ◽  
2021 ◽  
Vol 12 (2) ◽  
pp. 174
Author(s):  
Günther Heinemann ◽  
Sascha Willmes ◽  
Lukas Schefczyk ◽  
Alexander Makshtas ◽  
Vasilii Kustov ◽  
...  
Keyword(s):  
Sea Ice ◽  
Climate Models ◽  
Climate Model ◽  
Regional Climate ◽  
Open Water ◽  
The Arctic ◽  
Late Winter ◽  
Good Representation ◽  
Hourly Temperature ◽  
Ice Model

The parameterization of ocean/sea-ice/atmosphere interaction processes is a challenge for regional climate models (RCMs) of the Arctic, particularly for wintertime conditions, when small fractions of thin ice or open water cause strong modifications of the boundary layer. Thus, the treatment of sea ice and sub-grid flux parameterizations in RCMs is of crucial importance. However, verification data sets over sea ice for wintertime conditions are rare. In the present paper, data of the ship-based experiment Transarktika 2019 during the end of the Arctic winter for thick one-year ice conditions are presented. The data are used for the verification of the regional climate model COSMO-CLM (CCLM). In addition, Moderate Resolution Imaging Spectroradiometer (MODIS) data are used for the comparison of ice surface temperature (IST) simulations of the CCLM sea ice model. CCLM is used in a forecast mode (nested in ERA5) for the Norwegian and Barents Seas with 5 km resolution and is run with different configurations of the sea ice model and sub-grid flux parameterizations. The use of a new set of parameterizations yields improved results for the comparisons with in-situ data. Comparisons with MODIS IST allow for a verification over large areas and show also a good performance of CCLM. The comparison with twice-daily radiosonde ascents during Transarktika 2019, hourly microwave water vapor measurements of first 5 km in the atmosphere and hourly temperature profiler data show a very good representation of the temperature, humidity and wind structure of the whole troposphere for CCLM.

Modelling nitrogen transport across compartments over northern Europe

2021 ◽  
Author(s):  
Stefan Hagemann ◽  
Ute Daewel ◽  
Volker Matthias ◽  
Tobias Stacke
Keyword(s):  
Baltic Sea ◽  
Land Surface ◽  
Climate Model ◽  
Transport Model ◽  
Atmospheric Transport ◽  
Regional Climate ◽  
Marine Ecosystem ◽  
Coupled System ◽  
Nutrient Concentrations ◽  
Nutrient Loads

<p>River discharge and the associated nutrient loads are important factors that influence the functioning of the marine ecosystem. Lateral inflows from land carrying fresh, nutrient-rich water determine coastal physical conditions and nutrient concentration and, hence, dominantly influence primary production in the system. Since this forms the basis of the trophic food web, riverine nutrient concentrations impact the variability of the whole coastal ecosystem. This process becomes even more relevant in systems like the Baltic Sea, which is almost decoupled from the open ocean and land-borne nutrients play a major role for ecosystem productivity on seasonal up to decadal time scales.</p><p> </p><p>In order to represent the effects of climate or land use change on nutrient availability, a coupled system approach is required to simulate the transport of nutrients across Earth system compartments. This comprises their transport within the atmosphere, the deposition and human application at the surface, the lateral transport over the land surface into the ocean and their dynamics and transformation in the marine ecosystem. In our study, we combine these processes in a modelling chain within the GCOAST (Geesthacht Coupled cOAstal model SysTem) framework for the northern European region. This modelling chain comprises:</p><p> </p><ul><li>Simulation of emissions, atmospheric transport and deposition with the chemistry transport model CMAQ at 36 km grid resolution using atmospheric forcing from the coastDat3 data that have been generated with the regional climate model COSMO-CLM over Europe at 0.11° resolution using ERA-Interim re-analyses as boundary conditions</li> <li>Simulation of inert processes at the land surface with the global hydrology model HydroPy (former MPI-HM), i.e. considering total nitrogen without any chemical reactions</li> <li>Riverine transport with the Hydrological Discharge (HD) model at 0.0833° spatial resolution</li> <li>Simulation of the North Sea and Baltic Sea ecosystems with 3D coupled physical-biogeochemical NPZD-model ECOSMO II at about 10 km resolution</li> </ul><p> </p><p>We will present first results and their validation from this exercise.</p><p> </p>

Hydrological evaluation of high-resolution precipitation estimates from the WRF model in the Third Pole river basins

2021 ◽  
Author(s):  
He Sun ◽  
Fengge Su ◽  
Zhihua He ◽  
Tinghai Ou ◽  
Deliang Chen ◽  
...  
Keyword(s):  
Land Surface ◽  
Large Scale ◽  
Hydrological Modeling ◽  
Climate Model ◽  
Regional Climate ◽  
Wrf Model ◽  
Infiltration Capacity ◽  
Flood Prediction ◽  
Daily Streamflow ◽  
Precipitation Estimates

AbstractIn this study, two sets of precipitation estimates based on the regional Weather Research and Forecasting model (WRF) –the high Asia refined analysis (HAR) and outputs with a 9 km resolution from WRF (WRF-9km) are evaluated at both basin and point scales, and their potential hydrological utilities are investigated by driving the Variable Infiltration Capacity (VIC) large-scale land surface hydrological model in seven Third Pole (TP) basins. The regional climate model (RCM) tends to overestimate the gauge-based estimates by 20–95% in annual means among the selected basins. Relative to the gauge observations, the RCM precipitation estimates can accurately detect daily precipitation events of varying intensities (with absolute bias < 3 mm). The WRF-9km exhibits a high potential for hydrological application in the monsoon-dominated basins in the southeastern TP (with NSE of 0.7–0.9 and bias of -11% to 3%), while the HAR performs well in the upper Indus (UI) and upper Brahmaputra (UB) basins (with NSE of 0.6 and bias of -15% to -9%). Both the RCM precipitation estimates can accurately capture the magnitudes of low and moderate daily streamflow, but show limited capabilities in flood prediction in most of the TP basins. This study provides a comprehensive evaluation of the strength and limitation of RCMs precipitation in hydrological modeling in the TP with complex terrains and sparse gauge observations.

scholarly journals Land surface albedo and vegetation feedbacks enhanced the millennium drought in south-east Australia

2017 ◽  
Vol 21 (1) ◽  
pp. 409-422 ◽  
Author(s):  
Jason P. Evans ◽  
Xianhong Meng ◽  
Matthew F. McCabe
Keyword(s):  
Land Surface ◽  
Climate Model ◽  
Southern Oscillation ◽  
Regional Climate ◽  
Surface Characteristics ◽  
Surface Precipitation ◽  
Vegetation Fraction ◽  
Vegetation Feedbacks ◽  
Millennium Drought ◽  
Precipitation Anomalies

Abstract. In this study, we have examined the ability of a regional climate model (RCM) to simulate the extended drought that occurred throughout the period of 2002 through 2007 in south-east Australia. In particular, the ability to reproduce the two drought peaks in 2002 and 2006 was investigated. Overall, the RCM was found to reproduce both the temporal and the spatial structure of the drought-related precipitation anomalies quite well, despite using climatological seasonal surface characteristics such as vegetation fraction and albedo. This result concurs with previous studies that found that about two-thirds of the precipitation decline can be attributed to the El Niño–Southern Oscillation (ENSO). Simulation experiments that allowed the vegetation fraction and albedo to vary as observed illustrated that the intensity of the drought was underestimated by about 10 % when using climatological surface characteristics. These results suggest that in terms of drought development, capturing the feedbacks related to vegetation and albedo changes may be as important as capturing the soil moisture–precipitation feedback. In order to improve our modelling of multi-year droughts, the challenge is to capture all these related surface changes simultaneously, and provide a comprehensive description of land surface–precipitation feedback during the droughts development.

scholarly journals The Water and Energy Budget of the Arctic Atmosphere

2005 ◽  
Vol 18 (13) ◽  
pp. 2515-2530 ◽  
Author(s):  
Tido Semmler ◽  
Daniela Jacob ◽  
K. Heinke Schlünzen ◽  
Ralf Podzun
Keyword(s):  
Energy Budget ◽  
Climate Model ◽  
Small Sample Size ◽  
Regional Climate ◽  
Arctic Region ◽  
Analysis Data ◽  
Small Sample ◽  
The Arctic ◽  
Energy Fluxes ◽  
Arctic Atmosphere

Abstract The Arctic plays a major role in the global circulation, and its water and energy budget is not as well explored as that in other regions of the world. The aim of this study is to calculate the climatological mean water and energy fluxes depending on the season and on the North Atlantic Oscillation (NAO) through the lower, lateral, and upper boundaries of the Arctic atmosphere north of 70°N. The relevant fluxes are derived from results of the regional climate model (REMO 5.1), which is applied to the Arctic region for the time period 1979–2000. Model forcing data are a combination of 15-yr European Centre for Medium-Range Weather Forecasts (ECMWF) Re-Analysis (ERA-15) data and analysis data. The annual and seasonal total water and energy fluxes derived from REMO 5.1 results are very similar to the fluxes calculated from observational and reanalysis data, although there are some differences in the components. The agreement between simulated and observed total fluxes shows that these fluxes are reliable. Even if differences between high and low NAO situations occur in our simulation consistent with previous studies, these differences are mostly smaller than the large uncertainties due to a small sample size of the NAO high and low composites.

Future humidity extremes in an urban-rural context - using regional climate model projections down to convection permitting scales for Berlin

2021 ◽  
Author(s):  
Gaby S. Langendijk ◽  
Diana Rechid ◽  
Daniela Jacob
Keyword(s):  
Climate Change ◽  
Urban Areas ◽  
Climate Models ◽  
Climate Model ◽  
Regional Climate ◽  
Climate Change Impacts ◽  
Regional Climate Models ◽  
Climate Projections ◽  
Climate Data ◽  
Urban Rural

&lt;p&gt;Urban areas are prone to climate change impacts. A transition towards sustainable and climate-resilient urban areas is relying heavily on useful, evidence-based climate information on urban scales. However, current climate data and information produced by urban or climate models are either not scale compliant for cities, or do not cover essential parameters and/or urban-rural interactions under climate change conditions. Furthermore, although e.g. the urban heat island may be better understood, other phenomena, such as moisture change, are little researched. Our research shows the potential of regional climate models, within the EURO-CORDEX framework, to provide climate projections and information on urban scales for 11km and 3km grid size. The city of Berlin is taken as a case-study. The results on the 11km spatial scale show that the regional climate models simulate a distinct difference between Berlin and its surroundings for temperature and humidity related variables. There is an increase in urban dry island conditions in Berlin towards the end of the 21st century. To gain a more detailed understanding of climate change impacts, extreme weather conditions were investigated under a 2&amp;#176;C global warming and further downscaled to the 3km scale. This enables the exploration of differences of the meteorological processes between the 11km and 3km scales, and the implications for urban areas and its surroundings. The overall study shows the potential of regional climate models to provide climate change information on urban scales.&lt;/p&gt;

Evaluation of Temperature Simulation over Northern Thailand from Regional Climate Model Coupled with Land Surface Model

2017 ◽  
Vol 866 ◽  
pp. 108-111
Author(s):  
Theerapan Saesong ◽  
Pakpoom Ratjiranukool ◽  
Sujittra Ratjiranukool
Keyword(s):  
Regional Climate Model ◽  
Land Surface ◽  
Climate Model ◽  
Global Analysis ◽  
Regional Climate ◽  
Land Surface Model ◽  
Analysis Data ◽  
Surface Model ◽  
Northern Thailand ◽  
Weather Model

Numerical Weather Model called The Weather Research and Forecasting model, WRF, developed by National Center for Atmospheric Research (NCAR) is adapted to be regional climate model. The model is run to perform the daily mean air surface temperatures over northern Thailand in 2010. Boundery dataset provided by National Centers for Environmental Prediction, NCEP FNL, (Final) Operational Global Analysis data which are on 10 x 10. The simulated temperatures by WRF with four land surface options, i.e., no land surface scheme (option 0), thermal diffusion (option 1), Noah land-surface (option 2) and RUC land-surface (option 3) were compared against observational data from Thai Meteorological Department (TMD). Preliminary analysis indicated WRF simulations with Noah scheme were able to reproduce the most reliable daily mean temperatures over northern Thailand.

Configuration and Evaluation of the WRF Model for the Study of Hawaiian Regional Climate

2012 ◽  
Vol 140 (10) ◽  
pp. 3259-3277 ◽  
Author(s):  
Chunxi Zhang ◽  
Yuqing Wang ◽  
Axel Lauer ◽  
Kevin Hamilton
Keyword(s):  
Land Surface ◽  
Climate Model ◽  
Dynamical Downscaling ◽  
Model Simulation ◽  
Regional Climate ◽  
Hawaiian Islands ◽  
Wrf Model ◽  
Trade Wind ◽  
Preliminary Evaluation ◽  
The Mean

Abstract The Weather Research and Forecasting (WRF) model V3.3 has been configured for the Hawaiian Islands as a regional climate model for the region (HRCM). This paper documents the model configuration and presents a preliminary evaluation based on a continuous 1-yr simulation forced by observed boundary conditions with 3-km horizontal grid spacing in the inner nested domain. The simulated vertical structure of the temperature and humidity are compared with twice-daily radiosonde observations at two stations. Generally the trade wind inversion (TWI) height and occurrence days are well represented. The simulation over the islands is compared with observations from nine surface climatological stations and a dense network of precipitation stations. The model simulation has generally small biases in the simulated surface temperature, relative humidity, and wind speed. The model realistically simulated the magnitude and geographical distribution of the mean rainfall over the Hawaiian Islands. In addition, the model simulation reproduced reasonably well the individual heavy rainfall events as seen from the time series of pentad mean rainfall averaged over island scales. Also the model reproduced the geographical variation of the mean diurnal rainfall cycle even though the observed diurnal cycle displays quite different features over different islands. Comparison with results obtained using the land surface dataset from the official release of the WRF model confirmed that the newly implemented land surface dataset generally improved the simulation of surface variables. These results demonstrate that the WRF can be a useful tool for dynamical downscaling of regional climate over the Hawaiian Islands.

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