Journal: Atmospheric Research

Abbreviation

Atmos. res.

Publisher

Elsevier

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ISSN

0169-8095
1873-2895

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Publications1 - 10 of 33
  • Preservation of rainfall properties in stochastic disaggregation by a simple random cascade model
    Item type: Conference Paper
    Molnar, Peter; Burlando, Paolo (2005)
    Atmospheric Research
  • Numerical sensitivity studies of axis ratio changes of colliding ice crystals
    Item type: Journal Article
    Posselt, R.; Wurzler, S.; Diehl, K. (2005)
    Atmospheric Research
  • Comparison of a tipping-bucket and electronic weighing precipitation gage for snowfall
    Item type: Journal Article
    Savina, M.; Schäppi, B.; Molnar, P.; et al. (2012)
    Atmospheric Research
  • The wind-induced loss of thunderstorm precipitation measurements
    Item type: Conference Paper
    Chvíla, B.; Sevruk, B.; Ondrás, M. (2005)
    Atmospheric Research
  • Reducing uncertainty in surface solar radiation projections over the Northern Hemisphere using a hierarchical emergent constraint: Insights from CMIP6 and observation reconstruction
    Item type: Journal Article
    Jiao , Boyang; Su , Yucheng; Chao , Liya; et al. (2026)
    Atmospheric Research
    Most of Earth's surface energy is from the Sun, and changes in surface solar radiation (SSR) profoundly affect the global climate. However, SSR exhibits serious simulation biases in climate models, severely hindering their projections and renewable energy resource assessments. Our analysis reveals that Coupled Model Intercomparison Project Phase 6 (CMIP6) models systematically underestimate amplitudes of annual mean land SSR variations across the Northern Hemisphere (NH), exhibiting standard deviations of merely 0.7–1.2 W/m2 and underestimation rates reaching 20 %–50 % in annual mean SSR over the NH. Moreover, the Multi-Model Ensemble (MME) fail to reproduce the “dimming-brightening” transition seen in observational SSR records in the late 20th century. To resolve this issue, we propose a Hierarchical Emergent Constraint (HEC) framework based on the globally-benchmarked SSR dataset (SSRIH20CR) to systematically quantify model biases over the NH. Globally, the application of the HEC framework substantially reduces the magnitude of projected SSR increases and decreases across multiple emission scenarios. The projected uncertainty range accounts for approximately 85 % of the uncertainty from unconstrained SSR simulations. Regionally, although moderate SSR declines are projected to occur in Central Africa, the North American west coast, Asian Russia, and central China, more severe reductions dominate in South Asia, Europe, and most African regions. The HEC-corrected MME demonstrates a significant reduction in absolute bias relative to unconstrained SSR simulations (up to 0.26 W/m2), effectively constraining the propagation of such biases. Importantly, by applying the HEC, we enhance projection reliability through both a ∼ 15 % reduction in SSR projection uncertainty and a curbed declining trend that mitigates the “hot model” bias. This enhancement in SSR projections provides more reliable inputs for estimating solar energy yield. Consequently, it significantly improves the reliability of photovoltaic infrastructure planning for both site selection and capacity.
  • Improving forecast of “21.7” Henan extreme heavy rain by assimilating high spatial resolution GNSS ZTDs
    Item type: Journal Article
    Liu, Mengjie; Lou, Yidong; Zhang, Weixing; et al. (2025)
    Atmospheric Research
    Short-term forecasting of extreme weather is crucial for disaster warning and prevention. Many extreme weather events are often accompanied by significant water vapor changes, therefore, assimilating high-precision, high-resolution water vapor observations into numerical models is essential. This study explores the impact of GNSS ZTD assimilation on short-term forecasting of extreme weather using the WRF model on the case of “21.7” Henan extreme heavy rain. The impacts of GNSS ZTD assimilation on model fields and forecast results are analyzed, compared with scenarios where no data or only conventional observational data are assimilated. The results indicate that GNSS products outperform radiosonde data in temporal and spatial resolution, significantly affecting humidity fields in assimilation and providing more detailed water vapor distribution. In terms of precipitation forecasting, the analysis of POD, FAR, and ETS scores shows that GNSS data assimilation primarily impacts moderate to heavy rainfall for this case. During most simulation periods, the scores are higher when GNSS products are assimilated, with the most notable improvements observed at the threshold of 30 mm for 3-h accumulated precipitation, where ETS scores increase by an average of 21 %. However, despite the general improvement in precipitation forecast accuracy, limitations remain in forecasting peak rainfall periods.
  • Precipitation in Urban Areas, 6th International Workshop on Precipitation in Urban Areas
    Item type: Other Conference Item
    Einfalt, Thomas; Molnar, Peter; Schmid, Willi (2005)
    Atmospheric Research
  • Which are the main drivers of global dimming and brightening?
    Item type: Journal Article
    Stamatis, Michael; Hatzianastassiou, Nikolaos; Korras-Carraca, Marios-Bruno; et al. (2025)
    Atmospheric Research
    The Global Dimming and Brightening (GDB) phenomenon plays an important role in the Earth's climate, with clouds and aerosols being the major drivers. This study investigates GDB causes by quantifying the contributions of changes in clouds, aerosols, water vapor and ozone to the surface solar radiation (SSR) changes during 1984–2018. To this aim, radiative transfer calculations were performed by the FORTH-RTM (Foundation for Research and Technology-Hellas Radiative Transfer Model) on a monthly basis and 0.5°x0.625° spatial resolution using modern and improved datasets for clouds and aerosols. Validation against high-quality ground measurements confirmed RTM's reliability. Results show a global mean brightening of 0.88 Wm−2decade−1 from 1984 to 2018, stronger over land (2.57 Wm−2decade−1) than oceans (0.19 Wm−2decade−1). Globally, changes in clouds (especially middle-level cloud amount (CA) and high-level cloud optical thickness (COT)) were the main GDB drivers. However, the contribution of aerosol optical depth (AOD) changes was remarkable over specific land areas with strong anthropogenic activity, such as Europe, India and East China. In the 80's and 90's changes in AOD were the main GDB driver, subsequently in the 2000s high-level cloud optical thickness contributed the most to GDB followed by the AOD changes, while finally in the 2010s both clouds and AOD had comparable contributions. Over land, AOD had a comparable contribution to GDB with that of clouds whereas the contribution of aerosols' asymmetry parameter (AP) and single scattering albedo (SSA), water vapor and ozone was quite small or insignificant.
  • Fall velocity of snowflakes of different riming degree and crystal types
    Item type: Journal Article
    Barthazy, Eszter; Schefold, Raphael (2006)
    Atmospheric Research
    The fall velocity of graupel and of snowflakes of different riming degree and consisting of different crystal types is investigated. The naturally falling solid precipitation particles are measured with an optical instrument which is capable to record the size, shape and fall velocity of each single particle. Measurements were performed during 2 winter seasons and results are based on approximately 40,000 particles. It can be shown that the fall velocity of snowflakes depends on both the riming degree and their crystal type composition. Whereas the fall velocity of snowflakes consisting of needles or plates is strongly dependent on the riming degree, it seems that the fall velocity of snowflakes consisting of dendrites or irregular ice crystals is not dependent on the riming degree. The average fall velocity of any type of snowflakes tends to remain constant between 1 and 2 m s− 1 after the snowflakes have reached a certain size. However, the average variation of the fall velocity for a given snowflake size amounts to ± 0.3–0.7 m s− 1.
  • MiniCASCC - A battery driven fog collector for ecosystem research
    Item type: Journal Article
    Michna, Pavel; Schenk, Juerg; Werner, Roland A.; et al. (2013)
    Atmospheric Research
Publications1 - 10 of 33