MATCHA, a novel regional hydroclimate-chemical reanalysis: System description and evaluation

Abstract. We present MATCHA (Model for Atmospheric Transport and Chemistry in Asia), a 17-year (2003–2019) regional hydroclimate-chemical reanalysis for Asia (58° – 140° E, 4° – 40° N) at 12 km resolution that is based on the Weather Research and Forecasting model coupled with Chemistry (WRF-Chem), Community Land Model (CLM), and SNow, ICe and Aerosol Radiative (SNICAR) model as well as satellite data assimilation to explicitly represent interactions between key atmospheric composition and regional hydroclimate (including aerosol-snowpack interactions) across High Mountain Asia (HMA). Approximately two decades of satellite observations of aerosol optical depth (AOD) from the Moderate Resolution Imaging Spectroradiometer (MODIS) and carbon monoxide (CO) profiles from the Measurement of Pollution in the Troposphere (MOPITT) were assimilated every three hours into WRF-Chem to further constrain the representation of aerosols and chemistry. MATCHA provides comprehensive outputs across different light-absorbing aerosol species, e.g., black carbon (BC), dust, and brown carbon (BrC), trace gases, and a range of meteorological, hydrological, and land-surface variables over the region. This paper describes the MATCHA coupled modeling and data assimilation framework and evaluates 12 key variables across aerosols (fine particulate matter (PM_2.5/PM₁₀), AOD, single scattering albedo (SSA), and surface BC concentration), trace gases (surface CO), meteorology (precipitation, planetary boundary layer height (PBLH), temperature, relative humidity, and wind speed), and hydrology (snow cover fraction) against available in-situ and satellite observations across Asia. Meteorological fields (surface and vertical profiles) are consistently well-reproduced with Kling-Gupta efficiencies (KGEs) ranging from 0.65 to 1. Notable issues include persistent cold and dry bias over high-elevation regions in winter, with stronger-than-observed surface winds. Snow cover fraction seasonality is well captured with slight underestimation during snowmelt seasons across major glacier regions. Daily accumulated precipitation estimates agree with satellite observations, particularly with the best KGE (0.6) during the monsoon season, albeit underestimated over high-elevation regions. The diurnal and seasonal evolution of PBLH is well-represented, with biases reflecting shallower heights in the morning and deeper heights in the afternoon in summer, likely due to model parameterizations and resolution limitations. MATCHA also captures the spatial and seasonal variability of AOD and SSA at 550 nm, yet overestimates summer AOD over India and southeast Asia with a strong negative bias in SSA. Biases in PM_2.5/PM₁₀ are also higher, which appears to be particularly related to high biases in wind speeds, causing overestimation of natural emissions of aerosols and overestimation of anthropogenic emissions. Comparisons with site-specific aerosol chemical composition derived from air samples at Kanpur confirm the positive bias in sea salt concentrations and lower carbonaceous aerosols during high pollution events. MATCHA captures the seasonal cycle of surface CO, but underestimates the observations, which can be attributed to the assimilation of CO profiles from MOPITT. A unique feature of MATCHA is its tagged-tracers of BC for sectoral and regional source attribution analysis. These tracers show anthropogenic BC peaking in winter, primarily from Chinese sources in the eastern and northern part of HMA, and Indian sources in western and central HMA. Biomass burning BC dominates during March–April along with substantial trans-boundary inflow throughout the year. BC emissions from Pakistan and Nepal also contribute significantly to the anthropogenic column burden of BC in parts of HMA. MATCHA is the first-of-its-kind high-resolution reanalysis to fully couple aerosols, radiation, and snow processes over HMA, offering a valuable dataset for investigating aerosol–cryosphere feedbacks and informing emission mitigation strategies in Asia. The dataset consists of hourly surface and column-integrated products and 3-hourly three-dimensional fields, and is publicly available at DOI: 10.5067/CG4OT8DJX2Z7.