Evaluation of global EMEP MSC-W (rv4.34) WRF (v3.9.1.1) model surface concentrations and wet deposition of reactive N and S with measurements
<p>Atmospheric pollution has many profound effects on human health, ecosystems, and the climate. Of concern are high concentrations and deposition of reactive nitrogen (N<span class="inline-formula"><sub>r</sub></span>) species, especially of reduced N (gaseou...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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Copernicus Publications
2021-11-01
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| Series: | Geoscientific Model Development |
| Online Access: | https://gmd.copernicus.org/articles/14/7021/2021/gmd-14-7021-2021.pdf |
| _version_ | 1818651683015622656 |
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| author | Y. Ge Y. Ge M. R. Heal D. S. Stevenson P. Wind M. Vieno |
| author_facet | Y. Ge Y. Ge M. R. Heal D. S. Stevenson P. Wind M. Vieno |
| author_sort | Y. Ge |
| collection | DOAJ |
| description | <p>Atmospheric pollution has many profound effects on human
health, ecosystems, and the climate. Of concern are high concentrations and
deposition of reactive nitrogen (N<span class="inline-formula"><sub>r</sub></span>) species, especially of reduced N
(gaseous <span class="inline-formula">NH<sub>3</sub></span>, particulate <span class="inline-formula"><math xmlns="http://www.w3.org/1998/Math/MathML" id="M3" display="inline" overflow="scroll" dspmath="mathml"><mrow class="chem"><msup><msub><mi mathvariant="normal">NH</mi><mn mathvariant="normal">4</mn></msub><mo>+</mo></msup></mrow></math><span><svg:svg xmlns:svg="http://www.w3.org/2000/svg" width="29pt" height="14pt" class="svg-formula" dspmath="mathimg" md5hash="47abf32743cd28df9573e01430c76658"><svg:image xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="gmd-14-7021-2021-ie00001.svg" width="29pt" height="14pt" src="gmd-14-7021-2021-ie00001.png"/></svg:svg></span></span>). Atmospheric chemistry and
transport models (ACTMs) are crucial to understanding sources and impacts of
N<span class="inline-formula"><sub>r</sub></span> chemistry and its potential mitigation. Here we undertake the first
evaluation of the global version of the EMEP MSC-W ACTM driven by WRF
meteorology (<span class="inline-formula"><math xmlns="http://www.w3.org/1998/Math/MathML" id="M5" display="inline" overflow="scroll" dspmath="mathml"><mrow><mn mathvariant="normal">1</mn><msup><mi/><mo>∘</mo></msup><mo>×</mo><mn mathvariant="normal">1</mn><msup><mi/><mo>∘</mo></msup></mrow></math><span><svg:svg xmlns:svg="http://www.w3.org/2000/svg" width="34pt" height="11pt" class="svg-formula" dspmath="mathimg" md5hash="d308210e38ed1a4940972a050836d54c"><svg:image xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="gmd-14-7021-2021-ie00002.svg" width="34pt" height="11pt" src="gmd-14-7021-2021-ie00002.png"/></svg:svg></span></span> resolution),
with a focus on surface concentrations and wet deposition of N and S species
relevant to investigation of atmospheric N<span class="inline-formula"><sub>r</sub></span> and secondary inorganic
aerosol (SIA). The model–measurement comparison is conducted both spatially
and temporally, covering 10 monitoring networks worldwide. Model simulations
for 2010 compared use of both HTAP and ECLIPSE<span class="inline-formula"><sub>E</sub></span> (ECLIPSE annual total
with EDGAR monthly profile) emissions inventories; those for 2015 used
ECLIPSE<span class="inline-formula"><sub>E</sub></span> only. Simulations of primary pollutants are somewhat sensitive
to the choice of inventory in places where regional differences in primary
emissions between the two inventories are apparent (e.g. China) but are much
less sensitive for secondary components. For example, the difference in modelled
global annual mean surface <span class="inline-formula">NH<sub>3</sub></span> concentration using the two 2010
inventories is 18 % (HTAP: 0.26 <span class="inline-formula">µg m<sup>−3</sup></span>; ECLIPSE<span class="inline-formula"><sub>E</sub></span>: 0.31 <span class="inline-formula">µg m<sup>−3</sup></span>) but is only 3.5 % for <span class="inline-formula"><math xmlns="http://www.w3.org/1998/Math/MathML" id="M13" display="inline" overflow="scroll" dspmath="mathml"><mrow class="chem"><msup><msub><mi mathvariant="normal">NH</mi><mn mathvariant="normal">4</mn></msub><mo>+</mo></msup></mrow></math><span><svg:svg xmlns:svg="http://www.w3.org/2000/svg" width="29pt" height="14pt" class="svg-formula" dspmath="mathimg" md5hash="88e3051c9abcd7cd53c8b0640d7b1dd6"><svg:image xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="gmd-14-7021-2021-ie00003.svg" width="29pt" height="14pt" src="gmd-14-7021-2021-ie00003.png"/></svg:svg></span></span> (HTAP: 0.316 <span class="inline-formula">µg m<sup>−3</sup></span>; ECLIPSE<span class="inline-formula"><sub>E</sub></span>: 0.305 <span class="inline-formula">µg m<sup>−3</sup></span>). Comparisons of 2010 and
2015 surface concentrations between the model and measurements demonstrate that
the model captures the overall spatial and seasonal variations well for the
major inorganic pollutants <span class="inline-formula">NH<sub>3</sub></span>, <span class="inline-formula">NO<sub>2</sub></span>, <span class="inline-formula">SO<sub>2</sub></span>, <span class="inline-formula">HNO<sub>3</sub></span>,
<span class="inline-formula"><math xmlns="http://www.w3.org/1998/Math/MathML" id="M21" display="inline" overflow="scroll" dspmath="mathml"><mrow class="chem"><msup><msub><mi mathvariant="normal">NH</mi><mn mathvariant="normal">4</mn></msub><mo>+</mo></msup></mrow></math><span><svg:svg xmlns:svg="http://www.w3.org/2000/svg" width="29pt" height="14pt" class="svg-formula" dspmath="mathimg" md5hash="df1f0fc1093d7c213f3735ccc009a4e7"><svg:image xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="gmd-14-7021-2021-ie00004.svg" width="29pt" height="14pt" src="gmd-14-7021-2021-ie00004.png"/></svg:svg></span></span>, <span class="inline-formula"><math xmlns="http://www.w3.org/1998/Math/MathML" id="M22" display="inline" overflow="scroll" dspmath="mathml"><mrow class="chem"><msup><msub><mi mathvariant="normal">NO</mi><mn mathvariant="normal">3</mn></msub><mo>-</mo></msup></mrow></math><span><svg:svg xmlns:svg="http://www.w3.org/2000/svg" width="30pt" height="15pt" class="svg-formula" dspmath="mathimg" md5hash="2c946b389efef41f68452a1514b13f0e"><svg:image xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="gmd-14-7021-2021-ie00005.svg" width="30pt" height="15pt" src="gmd-14-7021-2021-ie00005.png"/></svg:svg></span></span>, and <span class="inline-formula"><math xmlns="http://www.w3.org/1998/Math/MathML" id="M23" display="inline" overflow="scroll" dspmath="mathml"><mrow class="chem"><msup><msub><mi mathvariant="normal">SO</mi><mn mathvariant="normal">4</mn></msub><mrow><mn mathvariant="normal">2</mn><mo>-</mo></mrow></msup></mrow></math><span><svg:svg xmlns:svg="http://www.w3.org/2000/svg" width="34pt" height="16pt" class="svg-formula" dspmath="mathimg" md5hash="c0d51741a4f5a075e6988150e0bd7e57"><svg:image xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="gmd-14-7021-2021-ie00006.svg" width="34pt" height="16pt" src="gmd-14-7021-2021-ie00006.png"/></svg:svg></span></span> and their wet
deposition in East Asia, Southeast Asia, Europe, and North America. The
model shows better correlations with annual average measurements for
networks in Southeast Asia (mean <span class="inline-formula"><i>R</i></span> for seven species: <span class="inline-formula"><math xmlns="http://www.w3.org/1998/Math/MathML" id="M25" display="inline" overflow="scroll" dspmath="mathml"><mrow><mover accent="true"><mrow><msub><mi>R</mi><mn mathvariant="normal">7</mn></msub></mrow><mo mathvariant="normal">‾</mo></mover><mo>=</mo><mn mathvariant="normal">0.73</mn></mrow></math><span><svg:svg xmlns:svg="http://www.w3.org/2000/svg" width="48pt" height="15pt" class="svg-formula" dspmath="mathimg" md5hash="dc695532dd84c8181ba41d7a34a02423"><svg:image xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="gmd-14-7021-2021-ie00007.svg" width="48pt" height="15pt" src="gmd-14-7021-2021-ie00007.png"/></svg:svg></span></span>),
Europe (<span class="inline-formula"><math xmlns="http://www.w3.org/1998/Math/MathML" id="M26" display="inline" overflow="scroll" dspmath="mathml"><mrow><mover accent="true"><mrow><msub><mi>R</mi><mn mathvariant="normal">7</mn></msub></mrow><mo mathvariant="normal">‾</mo></mover><mo>=</mo><mn mathvariant="normal">0.67</mn></mrow></math><span><svg:svg xmlns:svg="http://www.w3.org/2000/svg" width="48pt" height="15pt" class="svg-formula" dspmath="mathimg" md5hash="4c3b7d90722f2e047301bb0417113f08"><svg:image xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="gmd-14-7021-2021-ie00008.svg" width="48pt" height="15pt" src="gmd-14-7021-2021-ie00008.png"/></svg:svg></span></span>), and North America (<span class="inline-formula"><math xmlns="http://www.w3.org/1998/Math/MathML" id="M27" display="inline" overflow="scroll" dspmath="mathml"><mrow><mover accent="true"><mrow><msub><mi>R</mi><mn mathvariant="normal">7</mn></msub></mrow><mo mathvariant="normal">‾</mo></mover><mo>=</mo><mn mathvariant="normal">0.63</mn></mrow></math><span><svg:svg xmlns:svg="http://www.w3.org/2000/svg" width="48pt" height="15pt" class="svg-formula" dspmath="mathimg" md5hash="82b6aa70b269c6e8689752f48f0be24d"><svg:image xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="gmd-14-7021-2021-ie00009.svg" width="48pt" height="15pt" src="gmd-14-7021-2021-ie00009.png"/></svg:svg></span></span>) than in East Asia (<span class="inline-formula"><math xmlns="http://www.w3.org/1998/Math/MathML" id="M28" display="inline" overflow="scroll" dspmath="mathml"><mrow><mover accent="true"><mrow><msub><mi>R</mi><mn mathvariant="normal">5</mn></msub></mrow><mo mathvariant="normal">‾</mo></mover><mo>=</mo><mn mathvariant="normal">0.35</mn></mrow></math><span><svg:svg xmlns:svg="http://www.w3.org/2000/svg" width="48pt" height="16pt" class="svg-formula" dspmath="mathimg" md5hash="588f544eb0d3af9f76e5d57317b7c8ea"><svg:image xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="gmd-14-7021-2021-ie00010.svg" width="48pt" height="16pt" src="gmd-14-7021-2021-ie00010.png"/></svg:svg></span></span>) (data for 2015),
which suggests potential issues with the measurements in the latter network.
Temporally, both model and measurements agree on higher <span class="inline-formula">NH<sub>3</sub></span>
concentrations in spring and summer and lower concentrations in winter. The
model slightly underestimates annual total precipitation measurements (by
13 %–45 %) but agrees well with the spatial variations in precipitation in
all four world regions (0.65–0.94 <span class="inline-formula"><i>R</i></span> range). High correlations between
measured and modelled <span class="inline-formula"><math xmlns="http://www.w3.org/1998/Math/MathML" id="M31" display="inline" overflow="scroll" dspmath="mathml"><mrow class="chem"><msup><msub><mi mathvariant="normal">NH</mi><mn mathvariant="normal">4</mn></msub><mo>+</mo></msup></mrow></math><span><svg:svg xmlns:svg="http://www.w3.org/2000/svg" width="29pt" height="14pt" class="svg-formula" dspmath="mathimg" md5hash="3a32c345e2253b43267a7413deb4349c"><svg:image xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="gmd-14-7021-2021-ie00011.svg" width="29pt" height="14pt" src="gmd-14-7021-2021-ie00011.png"/></svg:svg></span></span> precipitation concentrations are also
observed in all regions except East Asia. For annual total wet deposition of
reduced N, the greatest consistency is in North America (0.75–0.82 <span class="inline-formula"><i>R</i></span> range),
followed by Southeast Asia (<span class="inline-formula"><i>R</i>=0.68</span>) and Europe (<span class="inline-formula"><i>R</i>=0.61</span>).
Model–measurement bias varies between species in different networks; for
example, bias for <span class="inline-formula"><math xmlns="http://www.w3.org/1998/Math/MathML" id="M35" display="inline" overflow="scroll" dspmath="mathml"><mrow class="chem"><msup><msub><mi mathvariant="normal">NH</mi><mn mathvariant="normal">4</mn></msub><mo>+</mo></msup></mrow></math><span><svg:svg xmlns:svg="http://www.w3.org/2000/svg" width="29pt" height="14pt" class="svg-formula" dspmath="mathimg" md5hash="3e19afed06e3ea335bb19dfa58eaff6b"><svg:image xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="gmd-14-7021-2021-ie00012.svg" width="29pt" height="14pt" src="gmd-14-7021-2021-ie00012.png"/></svg:svg></span></span> and <span class="inline-formula"><math xmlns="http://www.w3.org/1998/Math/MathML" id="M36" display="inline" overflow="scroll" dspmath="mathml"><mrow class="chem"><msup><msub><mi mathvariant="normal">NO</mi><mn mathvariant="normal">3</mn></msub><mo>-</mo></msup></mrow></math><span><svg:svg xmlns:svg="http://www.w3.org/2000/svg" width="30pt" height="15pt" class="svg-formula" dspmath="mathimg" md5hash="5bf2f905a09d07a0fbd9e1f354927308"><svg:image xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="gmd-14-7021-2021-ie00013.svg" width="30pt" height="15pt" src="gmd-14-7021-2021-ie00013.png"/></svg:svg></span></span> is largest in Europe and
North America and smallest in East Asia and Southeast Asia. The greater
uniformity in spatial correlations than in biases suggests that the major
driver of model–measurement discrepancies (aside from differing spatial
representativeness and uncertainties and biases in measurements) are
shortcomings in absolute emissions rather than in modelling the atmospheric
processes. The comprehensive evaluations presented in this<span id="page7022"/> study support the
application of this model framework for global analysis of current and
potential future budgets and deposition of N<span class="inline-formula"><sub>r</sub></span> and SIA.</p> |
| first_indexed | 2024-12-17T02:10:00Z |
| format | Article |
| id | doaj.art-b518cc613a474f9c99af46f3f0525a20 |
| institution | Directory Open Access Journal |
| issn | 1991-959X 1991-9603 |
| language | English |
| last_indexed | 2024-12-17T02:10:00Z |
| publishDate | 2021-11-01 |
| publisher | Copernicus Publications |
| record_format | Article |
| series | Geoscientific Model Development |
| spelling | doaj.art-b518cc613a474f9c99af46f3f0525a202022-12-21T22:07:35ZengCopernicus PublicationsGeoscientific Model Development1991-959X1991-96032021-11-01147021704610.5194/gmd-14-7021-2021Evaluation of global EMEP MSC-W (rv4.34) WRF (v3.9.1.1) model surface concentrations and wet deposition of reactive N and S with measurementsY. Ge0Y. Ge1M. R. Heal2D. S. Stevenson3P. Wind4M. Vieno5School of Chemistry, University of Edinburgh, Joseph Black Building, David Brewster Road, Edinburgh, EH9 3FJ, UKUK Centre for Ecology & Hydrology, Bush Estate, Penicuik, Midlothian, EH26 0QB, UKSchool of Chemistry, University of Edinburgh, Joseph Black Building, David Brewster Road, Edinburgh, EH9 3FJ, UKSchool of GeoSciences, University of Edinburgh, Crew Building, Alexander Crum Brown Road, Edinburgh, EH9 3FF, UKThe Norwegian Meteorological Institute, Henrik Mohns Plass 1, 0313, Oslo, NorwayUK Centre for Ecology & Hydrology, Bush Estate, Penicuik, Midlothian, EH26 0QB, UK<p>Atmospheric pollution has many profound effects on human health, ecosystems, and the climate. Of concern are high concentrations and deposition of reactive nitrogen (N<span class="inline-formula"><sub>r</sub></span>) species, especially of reduced N (gaseous <span class="inline-formula">NH<sub>3</sub></span>, particulate <span class="inline-formula"><math xmlns="http://www.w3.org/1998/Math/MathML" id="M3" display="inline" overflow="scroll" dspmath="mathml"><mrow class="chem"><msup><msub><mi mathvariant="normal">NH</mi><mn mathvariant="normal">4</mn></msub><mo>+</mo></msup></mrow></math><span><svg:svg xmlns:svg="http://www.w3.org/2000/svg" width="29pt" height="14pt" class="svg-formula" dspmath="mathimg" md5hash="47abf32743cd28df9573e01430c76658"><svg:image xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="gmd-14-7021-2021-ie00001.svg" width="29pt" height="14pt" src="gmd-14-7021-2021-ie00001.png"/></svg:svg></span></span>). Atmospheric chemistry and transport models (ACTMs) are crucial to understanding sources and impacts of N<span class="inline-formula"><sub>r</sub></span> chemistry and its potential mitigation. Here we undertake the first evaluation of the global version of the EMEP MSC-W ACTM driven by WRF meteorology (<span class="inline-formula"><math xmlns="http://www.w3.org/1998/Math/MathML" id="M5" display="inline" overflow="scroll" dspmath="mathml"><mrow><mn mathvariant="normal">1</mn><msup><mi/><mo>∘</mo></msup><mo>×</mo><mn mathvariant="normal">1</mn><msup><mi/><mo>∘</mo></msup></mrow></math><span><svg:svg xmlns:svg="http://www.w3.org/2000/svg" width="34pt" height="11pt" class="svg-formula" dspmath="mathimg" md5hash="d308210e38ed1a4940972a050836d54c"><svg:image xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="gmd-14-7021-2021-ie00002.svg" width="34pt" height="11pt" src="gmd-14-7021-2021-ie00002.png"/></svg:svg></span></span> resolution), with a focus on surface concentrations and wet deposition of N and S species relevant to investigation of atmospheric N<span class="inline-formula"><sub>r</sub></span> and secondary inorganic aerosol (SIA). The model–measurement comparison is conducted both spatially and temporally, covering 10 monitoring networks worldwide. Model simulations for 2010 compared use of both HTAP and ECLIPSE<span class="inline-formula"><sub>E</sub></span> (ECLIPSE annual total with EDGAR monthly profile) emissions inventories; those for 2015 used ECLIPSE<span class="inline-formula"><sub>E</sub></span> only. Simulations of primary pollutants are somewhat sensitive to the choice of inventory in places where regional differences in primary emissions between the two inventories are apparent (e.g. China) but are much less sensitive for secondary components. For example, the difference in modelled global annual mean surface <span class="inline-formula">NH<sub>3</sub></span> concentration using the two 2010 inventories is 18 % (HTAP: 0.26 <span class="inline-formula">µg m<sup>−3</sup></span>; ECLIPSE<span class="inline-formula"><sub>E</sub></span>: 0.31 <span class="inline-formula">µg m<sup>−3</sup></span>) but is only 3.5 % for <span class="inline-formula"><math xmlns="http://www.w3.org/1998/Math/MathML" id="M13" display="inline" overflow="scroll" dspmath="mathml"><mrow class="chem"><msup><msub><mi mathvariant="normal">NH</mi><mn mathvariant="normal">4</mn></msub><mo>+</mo></msup></mrow></math><span><svg:svg xmlns:svg="http://www.w3.org/2000/svg" width="29pt" height="14pt" class="svg-formula" dspmath="mathimg" md5hash="88e3051c9abcd7cd53c8b0640d7b1dd6"><svg:image xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="gmd-14-7021-2021-ie00003.svg" width="29pt" height="14pt" src="gmd-14-7021-2021-ie00003.png"/></svg:svg></span></span> (HTAP: 0.316 <span class="inline-formula">µg m<sup>−3</sup></span>; ECLIPSE<span class="inline-formula"><sub>E</sub></span>: 0.305 <span class="inline-formula">µg m<sup>−3</sup></span>). Comparisons of 2010 and 2015 surface concentrations between the model and measurements demonstrate that the model captures the overall spatial and seasonal variations well for the major inorganic pollutants <span class="inline-formula">NH<sub>3</sub></span>, <span class="inline-formula">NO<sub>2</sub></span>, <span class="inline-formula">SO<sub>2</sub></span>, <span class="inline-formula">HNO<sub>3</sub></span>, <span class="inline-formula"><math xmlns="http://www.w3.org/1998/Math/MathML" id="M21" display="inline" overflow="scroll" dspmath="mathml"><mrow class="chem"><msup><msub><mi mathvariant="normal">NH</mi><mn mathvariant="normal">4</mn></msub><mo>+</mo></msup></mrow></math><span><svg:svg xmlns:svg="http://www.w3.org/2000/svg" width="29pt" height="14pt" class="svg-formula" dspmath="mathimg" md5hash="df1f0fc1093d7c213f3735ccc009a4e7"><svg:image xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="gmd-14-7021-2021-ie00004.svg" width="29pt" height="14pt" src="gmd-14-7021-2021-ie00004.png"/></svg:svg></span></span>, <span class="inline-formula"><math xmlns="http://www.w3.org/1998/Math/MathML" id="M22" display="inline" overflow="scroll" dspmath="mathml"><mrow class="chem"><msup><msub><mi mathvariant="normal">NO</mi><mn mathvariant="normal">3</mn></msub><mo>-</mo></msup></mrow></math><span><svg:svg xmlns:svg="http://www.w3.org/2000/svg" width="30pt" height="15pt" class="svg-formula" dspmath="mathimg" md5hash="2c946b389efef41f68452a1514b13f0e"><svg:image xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="gmd-14-7021-2021-ie00005.svg" width="30pt" height="15pt" src="gmd-14-7021-2021-ie00005.png"/></svg:svg></span></span>, and <span class="inline-formula"><math xmlns="http://www.w3.org/1998/Math/MathML" id="M23" display="inline" overflow="scroll" dspmath="mathml"><mrow class="chem"><msup><msub><mi mathvariant="normal">SO</mi><mn mathvariant="normal">4</mn></msub><mrow><mn mathvariant="normal">2</mn><mo>-</mo></mrow></msup></mrow></math><span><svg:svg xmlns:svg="http://www.w3.org/2000/svg" width="34pt" height="16pt" class="svg-formula" dspmath="mathimg" md5hash="c0d51741a4f5a075e6988150e0bd7e57"><svg:image xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="gmd-14-7021-2021-ie00006.svg" width="34pt" height="16pt" src="gmd-14-7021-2021-ie00006.png"/></svg:svg></span></span> and their wet deposition in East Asia, Southeast Asia, Europe, and North America. The model shows better correlations with annual average measurements for networks in Southeast Asia (mean <span class="inline-formula"><i>R</i></span> for seven species: <span class="inline-formula"><math xmlns="http://www.w3.org/1998/Math/MathML" id="M25" display="inline" overflow="scroll" dspmath="mathml"><mrow><mover accent="true"><mrow><msub><mi>R</mi><mn mathvariant="normal">7</mn></msub></mrow><mo mathvariant="normal">‾</mo></mover><mo>=</mo><mn mathvariant="normal">0.73</mn></mrow></math><span><svg:svg xmlns:svg="http://www.w3.org/2000/svg" width="48pt" height="15pt" class="svg-formula" dspmath="mathimg" md5hash="dc695532dd84c8181ba41d7a34a02423"><svg:image xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="gmd-14-7021-2021-ie00007.svg" width="48pt" height="15pt" src="gmd-14-7021-2021-ie00007.png"/></svg:svg></span></span>), Europe (<span class="inline-formula"><math xmlns="http://www.w3.org/1998/Math/MathML" id="M26" display="inline" overflow="scroll" dspmath="mathml"><mrow><mover accent="true"><mrow><msub><mi>R</mi><mn mathvariant="normal">7</mn></msub></mrow><mo mathvariant="normal">‾</mo></mover><mo>=</mo><mn mathvariant="normal">0.67</mn></mrow></math><span><svg:svg xmlns:svg="http://www.w3.org/2000/svg" width="48pt" height="15pt" class="svg-formula" dspmath="mathimg" md5hash="4c3b7d90722f2e047301bb0417113f08"><svg:image xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="gmd-14-7021-2021-ie00008.svg" width="48pt" height="15pt" src="gmd-14-7021-2021-ie00008.png"/></svg:svg></span></span>), and North America (<span class="inline-formula"><math xmlns="http://www.w3.org/1998/Math/MathML" id="M27" display="inline" overflow="scroll" dspmath="mathml"><mrow><mover accent="true"><mrow><msub><mi>R</mi><mn mathvariant="normal">7</mn></msub></mrow><mo mathvariant="normal">‾</mo></mover><mo>=</mo><mn mathvariant="normal">0.63</mn></mrow></math><span><svg:svg xmlns:svg="http://www.w3.org/2000/svg" width="48pt" height="15pt" class="svg-formula" dspmath="mathimg" md5hash="82b6aa70b269c6e8689752f48f0be24d"><svg:image xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="gmd-14-7021-2021-ie00009.svg" width="48pt" height="15pt" src="gmd-14-7021-2021-ie00009.png"/></svg:svg></span></span>) than in East Asia (<span class="inline-formula"><math xmlns="http://www.w3.org/1998/Math/MathML" id="M28" display="inline" overflow="scroll" dspmath="mathml"><mrow><mover accent="true"><mrow><msub><mi>R</mi><mn mathvariant="normal">5</mn></msub></mrow><mo mathvariant="normal">‾</mo></mover><mo>=</mo><mn mathvariant="normal">0.35</mn></mrow></math><span><svg:svg xmlns:svg="http://www.w3.org/2000/svg" width="48pt" height="16pt" class="svg-formula" dspmath="mathimg" md5hash="588f544eb0d3af9f76e5d57317b7c8ea"><svg:image xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="gmd-14-7021-2021-ie00010.svg" width="48pt" height="16pt" src="gmd-14-7021-2021-ie00010.png"/></svg:svg></span></span>) (data for 2015), which suggests potential issues with the measurements in the latter network. Temporally, both model and measurements agree on higher <span class="inline-formula">NH<sub>3</sub></span> concentrations in spring and summer and lower concentrations in winter. The model slightly underestimates annual total precipitation measurements (by 13 %–45 %) but agrees well with the spatial variations in precipitation in all four world regions (0.65–0.94 <span class="inline-formula"><i>R</i></span> range). High correlations between measured and modelled <span class="inline-formula"><math xmlns="http://www.w3.org/1998/Math/MathML" id="M31" display="inline" overflow="scroll" dspmath="mathml"><mrow class="chem"><msup><msub><mi mathvariant="normal">NH</mi><mn mathvariant="normal">4</mn></msub><mo>+</mo></msup></mrow></math><span><svg:svg xmlns:svg="http://www.w3.org/2000/svg" width="29pt" height="14pt" class="svg-formula" dspmath="mathimg" md5hash="3a32c345e2253b43267a7413deb4349c"><svg:image xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="gmd-14-7021-2021-ie00011.svg" width="29pt" height="14pt" src="gmd-14-7021-2021-ie00011.png"/></svg:svg></span></span> precipitation concentrations are also observed in all regions except East Asia. For annual total wet deposition of reduced N, the greatest consistency is in North America (0.75–0.82 <span class="inline-formula"><i>R</i></span> range), followed by Southeast Asia (<span class="inline-formula"><i>R</i>=0.68</span>) and Europe (<span class="inline-formula"><i>R</i>=0.61</span>). Model–measurement bias varies between species in different networks; for example, bias for <span class="inline-formula"><math xmlns="http://www.w3.org/1998/Math/MathML" id="M35" display="inline" overflow="scroll" dspmath="mathml"><mrow class="chem"><msup><msub><mi mathvariant="normal">NH</mi><mn mathvariant="normal">4</mn></msub><mo>+</mo></msup></mrow></math><span><svg:svg xmlns:svg="http://www.w3.org/2000/svg" width="29pt" height="14pt" class="svg-formula" dspmath="mathimg" md5hash="3e19afed06e3ea335bb19dfa58eaff6b"><svg:image xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="gmd-14-7021-2021-ie00012.svg" width="29pt" height="14pt" src="gmd-14-7021-2021-ie00012.png"/></svg:svg></span></span> and <span class="inline-formula"><math xmlns="http://www.w3.org/1998/Math/MathML" id="M36" display="inline" overflow="scroll" dspmath="mathml"><mrow class="chem"><msup><msub><mi mathvariant="normal">NO</mi><mn mathvariant="normal">3</mn></msub><mo>-</mo></msup></mrow></math><span><svg:svg xmlns:svg="http://www.w3.org/2000/svg" width="30pt" height="15pt" class="svg-formula" dspmath="mathimg" md5hash="5bf2f905a09d07a0fbd9e1f354927308"><svg:image xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="gmd-14-7021-2021-ie00013.svg" width="30pt" height="15pt" src="gmd-14-7021-2021-ie00013.png"/></svg:svg></span></span> is largest in Europe and North America and smallest in East Asia and Southeast Asia. The greater uniformity in spatial correlations than in biases suggests that the major driver of model–measurement discrepancies (aside from differing spatial representativeness and uncertainties and biases in measurements) are shortcomings in absolute emissions rather than in modelling the atmospheric processes. The comprehensive evaluations presented in this<span id="page7022"/> study support the application of this model framework for global analysis of current and potential future budgets and deposition of N<span class="inline-formula"><sub>r</sub></span> and SIA.</p>https://gmd.copernicus.org/articles/14/7021/2021/gmd-14-7021-2021.pdf |
| spellingShingle | Y. Ge Y. Ge M. R. Heal D. S. Stevenson P. Wind M. Vieno Evaluation of global EMEP MSC-W (rv4.34) WRF (v3.9.1.1) model surface concentrations and wet deposition of reactive N and S with measurements Geoscientific Model Development |
| title | Evaluation of global EMEP MSC-W (rv4.34) WRF (v3.9.1.1) model surface concentrations and wet deposition of reactive N and S with measurements |
| title_full | Evaluation of global EMEP MSC-W (rv4.34) WRF (v3.9.1.1) model surface concentrations and wet deposition of reactive N and S with measurements |
| title_fullStr | Evaluation of global EMEP MSC-W (rv4.34) WRF (v3.9.1.1) model surface concentrations and wet deposition of reactive N and S with measurements |
| title_full_unstemmed | Evaluation of global EMEP MSC-W (rv4.34) WRF (v3.9.1.1) model surface concentrations and wet deposition of reactive N and S with measurements |
| title_short | Evaluation of global EMEP MSC-W (rv4.34) WRF (v3.9.1.1) model surface concentrations and wet deposition of reactive N and S with measurements |
| title_sort | evaluation of global emep msc w rv4 34 wrf v3 9 1 1 model surface concentrations and wet deposition of reactive n and s with measurements |
| url | https://gmd.copernicus.org/articles/14/7021/2021/gmd-14-7021-2021.pdf |
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