scholarly journals Merits of novel high-resolution estimates and existing long-term estimates of humidity and incident radiation in a complex domain

2019 ◽  
Author(s):  
Helene Birkelund Erlandsen ◽  
Lena Merete Tallaksen ◽  
Jørn Kristiansen
Keyword(s):  
High Resolution ◽  
Incident Radiation ◽  
Reanalysis Data ◽  
Horizontal Resolution ◽  
Ecological Modelling ◽  
The Novel ◽  
Near Surface ◽  
Air Mass ◽  
Humidity Measurements ◽  
Mass Type

Abstract. To provide better and more robust estimates of evaporation and snow-melt in a changing climate, hydrological and ecological modelling practices are shifting towards solving the surface energy balance. In addition to precipitation and near-surface temperature (T2), which often is available at high resolution by national providers, high quality estimates of 2-meter humidity, surface incident shortwave (SW ↓) and longwave (LW ↓) radiation are also required. Novel, gridded estimates of humidity and incident radiation are constructed using a methodology similar to that used in the development of the WATCH forcing data, however, a national 1 × 1 km gridded, observation-based T2 data is consulted in the downscaling rather than the 0.5 × 0.5 degree CRU T2 data. The novel dataset, HySN, is archived in Zenodo (https://doi.org/10.5281/zenodo.1970170). The HySN estimates, existing estimates from reanalysis data, post-processed reanalysis data, and VIC-type forcing data are compared with observations from the Norwegian mainland between 1982 and 2000. Humidity measurements from 84 stations are used, and, by employing quality control routines and including agricultural stations, SW ↓ observations from 10 stations are made available. Meanwhile, only two stations have observations of LW ↓. Vertical gradients, differences when compared at common altitudes, daily correlations, sensitivities to air mass type, and, where possible, trends and geographical gradients in seasonal means are assessed. At individual stations differences in seasonal means from the observations are as large as 7 °C for Td, 62 W m−2 for SW ↓, and 24 W m−2 for LW ↓. Most models overestimate SW ↓, and underestimate LW ↓. Horizontal resolution is not a predictor of the model's efficiency. Daily correlation is better captured in the products based on newer reanalysis data. Certain model estimates show different dependencies on geographical features, diverging trends, or a different sensitivity to air mass type than the observations.

scholarly journals Merits of novel high-resolution estimates and existing long-term estimates of humidity and incident radiation in a complex domain

2019 ◽  
Vol 11 (2) ◽  
pp. 797-821 ◽  
Author(s):  
Helene Birkelund Erlandsen ◽  
Lena Merete Tallaksen ◽  
Jørn Kristiansen
Keyword(s):  
High Resolution ◽  
Incident Radiation ◽  
Reanalysis Data ◽  
Dew Point ◽  
Climatic Research Unit ◽  
Infiltration Capacity ◽  
Data Set ◽  
Near Surface ◽  
Air Mass ◽  
Mass Type

Abstract. To provide better and more robust estimates of evaporation and snowmelt in a changing climate, hydrological and ecological modeling practices are shifting towards solving the surface energy balance. In addition to precipitation and near-surface temperature (T2), which often are available at high resolution from national providers, high-quality estimates of 2 m humidity and surface incident shortwave (SW↓) and longwave (LW↓) radiation are also required. Novel, gridded estimates of humidity and incident radiation are constructed using a methodology similar to that used in the development of the WATCH forcing data; however, national 1 km×1 km gridded, observation-based T2 data are consulted in the downscaling rather than the 0.5∘×0.5∘ Climatic Research Unit (CRU) T2 data. The novel data set, HySN, covering 1979 to 2017, is archived in Zenodo (https://doi.org/10.5281/zenodo.1970170). The HySN estimates, existing estimates from reanalysis data, post-processed reanalysis data, and Variable Infiltration Capacity (VIC) type forcing data are compared with observations from the Norwegian mainland from 1982 through 1999. Humidity measurements from 84 stations are used, and, by employing quality control routines and including agricultural stations, SW↓ observations from 10 stations are made available. Meanwhile, only two stations have observations of LW↓. Vertical gradients, differences when compared at common altitudes, daily correlations, sensitivities to air mass type, and, where possible, trends and geographical gradients in seasonal means are assessed. At individual stations, differences in seasonal means from the observations are as large as 7 ∘C for dew point temperature, 62 W m−2 for SW↓, and 24 W m−2 for LW↓. Most models overestimate SW↓ and underestimate LW↓. Horizontal resolution is not a predictor of the model's efficiency. Daily correlation is better captured in the products based on newer reanalysis data. Certain model estimates show different dependencies on geographical features, diverging trends, or a different sensitivity to air mass type than the observations.

scholarly journals Antarctic 20th Century Accumulation Changes Based on Regional Climate Model Simulations

2010 ◽  
Vol 2010 ◽  
pp. 1-14 ◽  
Author(s):  
Klaus Dethloff ◽  
Ksenia Glushak ◽  
Annette Rinke ◽  
Dörthe Handorf
Keyword(s):  
Regional Climate Model ◽  
Climate Model ◽  
Regional Climate ◽  
Reanalysis Data ◽  
Horizontal Resolution ◽  
East Antarctica ◽  
Transient Pressure ◽  
Near Surface ◽  
Surface Mass ◽  
The Antarctic

The regional climate model HIRHAM has been applied to Antarctica driven at the lateral and lower boundaries by European Reanalysis data ERA-40 for the period 1958–1998. Simulations over 4 decades, carried out with a horizontal resolution of 50 km, deliver a realistic simulation of the Antarctic atmospheric circulation, synoptic-scale pressure systems, and the spatial distribution of precipitation minus sublimation (P-E) structures. The simulated P-E pattern is in qualitative agreement with glaciological estimates. The estimated (P-E) trends demonstrate surfacemass accumulation increase at the West Antarctic coasts and reductions in parts of East Antarctica. The influence of the Antarctic Oscillation (AAO) on the near-surface climate and the surface mass accumulation over Antarctica have been investigated on the basis of ERA-40 data and HIRHAM simulations. It is shown that the regional accumulation changes are largely driven by changes in the transient activity around the Antarctic coasts due to the varying AAO phases. During positive AAO, more transient pressure systems travelling towards the continent, and Western Antarctica and parts of South-Eastern Antarctica gain more precipitation and mass. Over central Antarctica the prevailing anticyclone causes a strengthening of polar desertification connected with a reduced surface mass balance in the northern part of East Antarctica.

scholarly journals High resolution modeling of CO<sub>2</sub> over Europe: implications for representation errors of satellite retrievals

2009 ◽  
Vol 9 (5) ◽  
pp. 20599-20630
Author(s):  
D. Pillai ◽  
C. Gerbig ◽  
J. Marshall ◽  
R. Ahmadov ◽  
R. Kretschmer ◽  
...  
Keyword(s):  
High Resolution ◽  
Horizontal Resolution ◽  
Co2 Fluxes ◽  
Modeling Framework ◽  
Global Models ◽  
Near Surface ◽  
Temporal Sampling ◽  
Inverse Models ◽  
Representation Error ◽  
Satellite Retrievals

Abstract. Satellite retrievals for column CO2 with better spatial and temporal sampling are expected to improve the current surface flux estimates of CO2 via inverse techniques. However, the spatial scale mismatch between remotely sensed CO2 and current generation inverse models can induce representation errors, which can cause systematic biases in flux estimates. This study is focused on estimating these representation errors associated with utilization of satellite measurements in global models with a horizontal resolution of about 1 degree or less. For this we used simulated CO2 from the high resolution modeling framework WRF-VPRM, which links CO2 fluxes from a diagnostic biosphere model to a weather forecasting model at 10×10 km2 horizontal resolution. Sub-grid variability of column averaged CO2, i.e. the variability not resolved by global models, reached up to 1.2 ppm. Statistical analysis of the simulation results indicate that orography plays an important role. Using sub-grid variability of orography and CO2 fluxes as well as resolved mixing ratio of CO2, a linear model can be formulated that could explain about 50% of the spatial patterns in the bias component of representation error in column and near-surface CO2 during day- and night-times. These findings give hints for a parameterization of representation error which would allow for the representation error to taken into account in inverse models or data assimilation systems.

Temperature monitoring in mountain regions using reanalyses: Lessons from the Alps

2020 ◽  
Author(s):  
Simon C. Scherrer ◽  
Sven Kotlarski
Keyword(s):  
High Resolution ◽  
Surface Temperature ◽  
Reanalysis Data ◽  
Swiss Alps ◽  
Mountain Regions ◽  
Near Surface ◽  
The Alps ◽  
Regional Reanalysis ◽  
High Elevations

&lt;p&gt;The monitoring of near-surface temperature is a fundamental task of climatology that remains especially challenging in mountain regions. Here we assess the regional monitoring capabilities of modern reanalysis products in the well-monitored northern Swiss Alps during the last 20 to almost 60 years. Monthly and seasonal 2 m air temperature (T2m) anomalies of the global ERA5 and the three regional reanalysis products HARMONIE, MESCAN-SURFEX and COSMO-REA6 are evaluated against high quality in situ observational data for a low elevation (foothills) mean, and a high elevation (Alpine) mean. All reanalysis products show a good year-round performance for the foothills with the global reanalysis ERA5 showing the best overall performance. The high-resolution regional reanalysis COSMO-REA6 clearly performs best for the Alpine mean, especially in winter. Most reanalysis data sets show deficiencies at high elevations in winter and considerably overestimate recent T2m trends in winter. This stresses the fact that even in the most recent decades utmost care is required when using reanalysis data for near-surface temperature trend assessments in mountain regions. Our results indicate that a high-resolution model topography is an important prerequisite for an adequate monitoring of winter T2m using reanalysis data at high elevations in the Alps. Assimilating T2m remains challenging in highly complex terrain. The remaining shortcomings of modern reanalyses also highlight the continued need for a reliable and dense in situ observational monitoring network in mountain regions.&lt;/p&gt;&lt;p&gt;&amp;#160;&lt;/p&gt;

scholarly journals BAYWRF: a high-resolution present-day climatological atmospheric dataset for Bavaria

2020 ◽  
Vol 12 (4) ◽  
pp. 3097-3112
Author(s):  
Emily Collier ◽  
Thomas Mölg
Keyword(s):  
Climate Change ◽  
High Resolution ◽  
Large Scale ◽  
Wrf Model ◽  
Atmospheric Model ◽  
Climate Impact ◽  
Reanalysis Data ◽  
Near Surface ◽  
Local Climate ◽  
The Impact

Abstract. Climate impact assessments require information about climate change at regional and ideally also local scales. In dendroecological studies, this information has traditionally been obtained using statistical methods, which preclude the linkage of local climate changes to large-scale drivers in a process-based way. As part of recent efforts to investigate the impact of climate change on forest ecosystems in Bavaria, Germany, we developed a high-resolution atmospheric modelling dataset, BAYWRF, for this region over the thirty-year period of September 1987 to August 2018. The atmospheric model employed in this study, the Weather Research and Forecasting (WRF) model, was configured with two nested domains of 7.5 and 1.5 km grid spacing centred over Bavaria and forced at the outer lateral boundaries by ERA5 reanalysis data. Using an extensive network of observational data, we evaluate (i) the impact of using grid analysis nudging for a single-year simulation of the period of September 2017 to August 2018 and (ii) the full BAYWRF dataset generated using nudging. The evaluation shows that the model represents variability in near-surface meteorological conditions generally well, although there are both seasonal and spatial biases in the dataset that interested users should take into account. BAYWRF provides a unique and valuable tool for investigating climate change in Bavaria with high interdisciplinary relevance. Data from the finest-resolution WRF domain are available for download at daily temporal resolution from a public repository at the Open Science Framework (Collier, 2020; https://doi.org/10.17605/OSF.IO/AQ58B).

Subgrid-Scale Variability for Thermodynamic Variables in an Offline Land Surface Prediction System

2015 ◽  
Vol 17 (1) ◽  
pp. 171-193 ◽  
Author(s):  
Mélanie C. Rochoux ◽  
Stéphane Bélair ◽  
Maria Abrahamowicz ◽  
Pierre Pellerin
Keyword(s):  
High Resolution ◽  
Land Surface ◽  
Horizontal Resolution ◽  
Prediction System ◽  
Subgrid Scale ◽  
Grid Spacing ◽  
Model Bias ◽  
Near Surface ◽  
Surface Prediction ◽  
The Impact

Abstract This study presents a numerical analysis of the impact of the horizontal resolution on the forecast capability of the Canadian offline land surface prediction system (SPS; formerly known as GEM-Surf) forced by the 15-km Global Environmental Multiscale (GEM) atmospheric model. This system is used to quantify on a statistical basis the subgrid-scale variability of (near-)surface variables for 25-km grid spacing based on the 2.5- or 10-km SPS run at regional scale over the 2012 summer season. The model bias and the distributions characterizing the subgrid-scale variability drastically depend on the geographic areas as well as on the diurnal cycle. These results show the benefits of high-resolution land surface simulations to account for length scales that are more consistent with the scales at which the actual land surface balance is affected by the heterogeneous geophysical fields (i.e., roughness length, land–water mask, glacier mask, and soil texture). The model bias results highlight the potential of an SPS–GEM two-way coupling strategy for refining predictions near the surface through the upscaling of high-resolution surface heat fluxes to the coarser atmospheric grid spacing, with these fluxes being significantly different from those explicitly resolved at 25 km and featuring nonlinear behavior with respect to the horizontal resolution. Since the computational power of meteorological operational centers progressively increases, making it possible to run high-resolution limited-area models, solving the surface at high resolution in a surface–atmosphere fully coupled system becomes a key aspect for improving numerical weather and environmental forecast performance.

scholarly journals Evaluation of WRF model seasonal forecasts for tropical region of Singapore

2015 ◽  
Vol 12 (1) ◽  
pp. 69-72 ◽  
Author(s):  
J. Singh ◽  
K. Yeo ◽  
X. Liu ◽  
R. Hosseini ◽  
J. R. Kalagnanam
Keyword(s):  
High Resolution ◽  
Wrf Model ◽  
Horizontal Resolution ◽  
Tropical Region ◽  
Seasonal Forecasts ◽  
Near Surface ◽  
High Resolution Data ◽  
Model Configuration ◽  
And Performance ◽  
Resolution Data

Abstract. The Weather and Research Forecast (WRF) model is evaluated for the monsoon and inter-monsoon seasons over the tropical region of Singapore. The model configuration, physical parameterizations and performance results are described in this paper. In addition to the ready-to-use data available with the WRF model, the model configuration includes high resolution MODIS land use (500 m horizontal resolution) and JPL-NASA sea surface temperature (1 km horizontal resolution) data. The model evaluation is performed against near surface observations for temperature, relative humidity, wind speed and direction, available from a dense network of weather monitoring stations across Singapore. It is found that the high resolution data sets bring significant improvement in the model forecasts. The results also indicate that the model forecasts are more accurate in the monsoon seasons compared to the inter-monsoon seasons.

scholarly journals High resolution modeling of CO<sub>2</sub> over Europe: implications for representation errors of satellite retrievals

2010 ◽  
Vol 10 (1) ◽  
pp. 83-94 ◽  
Author(s):  
D. Pillai ◽  
C. Gerbig ◽  
J. Marshall ◽  
R. Ahmadov ◽  
R. Kretschmer ◽  
...  
Keyword(s):  
High Resolution ◽  
Horizontal Resolution ◽  
Systematic Bias ◽  
Co2 Fluxes ◽  
Modeling Framework ◽  
Global Models ◽  
Near Surface ◽  
Inverse Models ◽  
Representation Error ◽  
Satellite Retrievals

Abstract. Satellite retrievals for column CO2 with better spatial and temporal sampling are expected to improve the current surface flux estimates of CO2 via inverse techniques. However, the spatial scale mismatch between remotely sensed CO2 and current generation inverse models can induce representation errors, which can cause systematic biases in flux estimates. This study is focused on estimating these representation errors associated with utilization of satellite measurements in global models with a horizontal resolution of about 1 degree or less. For this we used simulated CO2 from the high resolution modeling framework WRF-VPRM, which links CO2 fluxes from a diagnostic biosphere model to a weather forecasting model at 10×10 km2 horizontal resolution. Sub-grid variability of column averaged CO2, i.e. the variability not resolved by global models, reached up to 1.2 ppm with a median value of 0.4 ppm. Statistical analysis of the simulation results indicate that orography plays an important role. Using sub-grid variability of orography and CO2 fluxes as well as resolved mixing ratio of CO2, a linear model can be formulated that could explain about 50% of the spatial patterns in the systematic (bias or correlated error) component of representation error in column and near-surface CO2 during day- and night-times. These findings give hints for a parameterization of representation error which would allow for the representation error to taken into account in inverse models or data assimilation systems.

scholarly journals MOMBA 1.1 – a high-resolution Baltic Sea configuration of GFDL's modular ocean model

2014 ◽  
Vol 7 (2) ◽  
pp. 2065-2124 ◽  
Author(s):  
H. Dietze ◽  
U. Löptien ◽  
K. Getzlaff
Keyword(s):  
High Resolution ◽  
Baltic Sea ◽  
Ocean Circulation ◽  
Horizontal Resolution ◽  
Ocean Model ◽  
Biogeochemical Model ◽  
Near Surface ◽  
Significant Control ◽  
Modular Ocean Model ◽  
The Baltic

Abstract. We present a new coupled ocean circulation – ice model configuration of the Baltic Sea. The model features, contrary to most existing configurations, a high horizontal resolution of &amp;approx;1 nautical mile which is eddy resolving over much of the domain. The vertical discretisation comprises a total of 47 vertical levels. Results from a 1987 to 1999 hind cast simulation show that the model's fidelity is competitive. As suggested by a comparison with sea surface temperatures observed from space, this applies especially to near-surface processes. Hence, the configuration is well suited to serve as a nucleus of a full-fledged coupled ocean circulation biogeochemical model (which is yet to be developed). A caveat is that the model fails to reproduce major inflow events. We trace this back to spurious vertical circulation patterns at the sills which may well be endemic to high resolution models based on geopotential coordinates. Further, we present indications that – so far neglected – eddy/wind effects exert significant control on wind-induced up- and downwelling.

Improvements to an intermediate complexity atmospheric model for high-resolution downscaling in very complex terrain.

2021 ◽  
Author(s):  
Dylan Reynolds ◽  
Bert Kruyt ◽  
Ethan Gutmann ◽  
Tobias Jonas ◽  
Michael Lehning ◽  
...  
Keyword(s):  
High Resolution ◽  
Complex Terrain ◽  
Large Scale ◽  
Atmospheric Model ◽  
Horizontal Resolution ◽  
Surface Flow ◽  
Near Surface ◽  
Precipitation Patterns ◽  
Intermediate Complexity ◽  
Nwp Model

&lt;p&gt;&amp;#160;&amp;#160;&amp;#160;&amp;#160;&amp;#160;&amp;#160;&amp;#160;&amp;#160;&amp;#160;&amp;#160;&amp;#160; Snow deposition patterns in complex terrain are heavily dependent on the underlying topography. This topography affects precipitating clouds at the kilometer-scale and causes changes to the wind field at the sub-kilometer scale, resulting in altered advection of falling hydrometeors. Snow particles are particularly sensitive to changes in the near-surface flow field due to their low density. Atmospheric models which run at the kilometer scale cannot resolve the actual heterogeneity of the underlying terrain, resulting in precipitation maps which do not capture terrain-affected precipitation patterns. Thus, snow-atmosphere interactions such as preferential deposition are often not resolved in precipitation data used as input to snow models. To bridge this spatial gap and resolve snow-atmosphere interactions at the sub-kilometer scale, we couple an intermediate complexity atmospheric model (ICAR) to the COSMO NWP model. Applying this model to sub-kilometer terrain (horizontal resolution of 50 and 250 m) required changes to ICAR&amp;#8217;s computational grid, atmospheric dynamics, and boundary layer flow. As a result, the near-surface flow now accounts for surface roughness and topographically induced speed up. This has been achieved by using terrain descriptors calculated once at initialization which consider a point&amp;#8217;s exposure or sheltering relative to surrounding terrain. In particular, the use of a 3-dimensional Sx parameter allows us to simulate areas of stagnation and recirculation on the lee of terrain features. Our approach maintains the accurate large-scale precipitation patterns from COSMO but resolves the dynamics induced by terrain at the sub-kilometer scale without adding additional computational burden. We find that solid precipitation patterns at the ridge scale, such as preferential deposition of snow, are better resolved in the high-resolution version of ICAR than the current ICAR or COSMO models. This updated version of ICAR presents a new tool to dynamically downscale NWP output for snow models and enables future studies of snow-atmosphere interactions at domain scales of 100&amp;#8217;s of kilometers.&lt;/p&gt;

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