Recent developments in hydrologic data assimilation

1995 ◽  
Vol 33 (S2) ◽  
pp. 977-984 ◽  
Author(s):  
Dennis McLaughlin
Keyword(s):  
Data Assimilation ◽  
Hydrologic Data ◽  
Recent Developments

scholarly journals The impacts of uncertainties in emissions on aerosol data assimilation and short-term PM<sub>2.5</sub> predictions in CMAQ v5.2.1 over East Asia

2020 ◽  
Author(s):  
Sojin Lee ◽  
Chul Han Song ◽  
Kyung Man Han ◽  
Daven K. Henze ◽  
Kyunghwa Lee ◽  
...  
Keyword(s):  
Air Quality ◽  
Data Assimilation ◽  
East Asia ◽  
Conventional Method ◽  
Meteorological Data ◽  
Three Dimensional ◽  
Short Term ◽  
Background Error ◽  
Multi Scale ◽  
Error Covariance

Abstract. For the purpose of improving PM prediction skills in East Asia, we estimated a new background error covariance matrix (BEC) for aerosol data assimilation using surface PM2.5 observations that accounts for the uncertainties in anthropogenic emissions. In contrast to the conventional method to estimate the BEC that uses perturbations in meteorological data, this method additionally considered the perturbations using two different emission inventories. The impacts of the new BEC were then tested for the prediction of surface PM2.5 over East Asia using Community Multi-scale Air Quality (CMAQ) initialized by three-dimensional variational method (3D-VAR). The surface PM2.5 data measured at 154 sites in South Korea and 1,535 sites in China were assimilated every six hours during the Korea-United States Air Quality Study (KORUS-AQ) campaign period (1 May–14 June 2016). Data assimilation with our new BEC showed better agreement with the surface PM2.5 observations than that with the conventional method. Our method also showed closer agreement with the observations in 24-hour PM2.5 predictions with ~ 44 % fewer negative biases than the conventional method. We conclude that increased standard deviations, together with horizontal and vertical length scales in the new BEC, tend to improve the data assimilation and short-term predictions for the surface PM2.5. This paper also suggests further research efforts devoted to estimating the BEC to improve PM2.5 predictions.

PEEX Integrated Multi-scales and -Process Modelling for Environmental Applications

2020 ◽  
Author(s):  
Alexander Mahura ◽  
Alexander Baklanov ◽  
Tuukka Petäjä ◽  
Roman Nuterman ◽  
Serguei Ivanov ◽  
...  
Keyword(s):  
Data Assimilation ◽  
Radiative Forcing ◽  
High Performance ◽  
Regional Scale ◽  
Added Value ◽  
Anthropogenic Sources ◽  
Cloud Formation ◽  
Limited Area ◽  
Multi Scale

&lt;p&gt;The Pan-Eurasian EXperiment (PEEX; www.atm.helsinki.fi/peex) programme is a long-term programme. One of the PEEX Research Infrastructure&amp;#8217;s components is the PEEX-Modelling-Platform (PEEX-MP; www.atm.helsinki.fi/peex/index.php/modelling-platform). PEEX-MP includes more than 30 different models running at different scales, resolutions, geographical domains, resolving different physical-chemical-biological processes, etc. and used as research tools providing insights and valuable information/ output for different level assessments for environment and population. These models cover main components - atmosphere, hydrosphere, pedosphere and biosphere. The seamless coupling multi-scale and -processes modelling concept developed is important and advanced step towards realization of the PEEX research agenda presented in the PEEX Science Plan (www.atm.helsinki.fi/peex/images/PEEX_Science_Plan.pdf). Accessibility to infrastructure with High Performance Computing is important for such modelling.&lt;/p&gt;&lt;p&gt;In particular, the Enviro-HIRLAM (Environment &amp;#8211; HIgh Resolution Limited Area Model) &amp; HARMONIE (The HIRLAM-ALADIN Research for Meso-scale Operational NWP In Europe) models can be applied for multi-scale and &amp;#8211;processes studies on interactions and feedbacks of meteorology vs aerosols/chemistry; aerosols vs. cloud formation and radiative forcing; boundary layer parameterizations; urbanization processes impact on changes in urban weather and climate; assessments for human and environment; improving prediction of extreme weather/ pollution events; etc. All these can be studied at different spatial (urban-subregional-regional) and temporal scales. In addition, added value to analysis is obtained through integration of modelling results into GIS environment for further risk/vulnerability/consequences/etc. studies.&lt;/p&gt;&lt;p&gt;As part of the Enviro-PEEX project (www.atm.helsinki.fi/peex/index.php/enviro), the models were used to study aerosols feedbacks and interactions in Arctic-boreal domain at regional scale &amp; effects of radar data assimilation at mesoscale resolution, respectively.&lt;/p&gt;&lt;p&gt;Enviro-HIRLAM model was run in a long-term mode at 15-5 km resolutions for reference and aerosols effects (direct, indirect, combined included) with ECMWF boundary conditions and anthropogenic/ biogenic/ natural emissions pre-processed. Analysis of differences between model runs for basic statistics (avg, med, max, min, std) showed less pronounced variations of concentrations for average in Arctic regions vs other regions, and more pronounced for maximum concentration in Russian Siberia and Ural. Monthly averaged sulphur dioxide was larger over mid-latitudes (influence of anthropogenic sources) with maximum due to long-range atmospheric transport. For particular matter, it is lower in Arctic compared with mid-latitudes, but their composition is dominated by sea salt aerosols.&lt;/p&gt;&lt;p&gt;HARMONIE model was tested with pre-processing (optimising inner parameters) and data assimilation of radar reflectivity, which minimize a representative error (associated with discrepancy between resolutions in informational sources). The method showed improvement in prediction of precipitation rain rates and spatial pattern within radars&amp;#8217; location areas and better reproduction of mesoscale belts and cell patterns of few-to-ten size in precipitation fields. Compatibility between model resolution and smoothed radar observation density was achieved by &amp;#8220;cube-smoothing&amp;#8221; approach. This ensures equivalent presentation of precipitation (reflectivity) structures in both model and observation in a sense of equally preserving the scales of precipitation patterns.&lt;/p&gt;&lt;p&gt;Moreover, for selected PEEX-MP models, used by UHEL-INAR, such Enviro-HIRLAM, EC-Earth, MALTE-Box a series of science education oriented trainings/schools is organized in April &amp; August 2020 (ums.rshu.ru &amp; worldslargerivers.boku.ac.at/wlr/index.php/ysss.html) which are part of the PEEX Educational Platform activities as well.&lt;/p&gt;

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