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Atmospheric rivers (ARs) are long, narrow synoptic scale weather features important for Earth’s hydrological cycle typically transporting water vapor poleward, delivering precipitation important for local climates. Understanding ARs in a warming climate is problematic because the AR response to climate change is tied to how the feature is defined. The Atmospheric River Tracking Method Intercomparison Project (ARTMIP) provides insights into this problem by comparing 16 atmospheric river detection tools (ARDTs) to a common data set consisting of high resolution climate change simulations from a global atmospheric general circulation model. ARDTs mostly show increases in frequency and intensity, but the scale of the response is largely dependent on algorithmic criteria. Across ARDTs, bulk characteristics suggest intensity and spatial footprint are inversely correlated, and most focus regions experience increases in precipitation volume coming from extreme ARs. The spread of the AR precipitation response under climate change is large and dependent on ARDT selection.

Author(s): Rutz, JJ; Shields, CA; Lora, JM; Payne, AE; Guan, B; Ullrich, P; O’Brien, T; Leung, LR; Ralph, FM; Wehner, M; Brands, S; Collow, A; Goldenson, N; Gorodetskaya, I; Griffith, H; Kashinath, K; Kawzenuk, B; Krishnan, H; Kurlin, V; Lavers, D; Magnusdottir, G; Mahoney, K; McClenny, E; Muszynski, G; Nguyen, PD; Prabhat, M; Qian, Y; Ramos, AM; Sarangi, C; Sellars, S; Shulgina, T; Tome, R; Waliser, D; Walton, D; Wick, G; Wilson, AM; Viale, M | Abstract: Atmospheric rivers (ARs) are now widely known for their association with high-impact weather events and long-term water supply in many regions. Researchers within the scientific community have developed numerous methods to identify and track of ARs—a necessary step for analyses on gridded data sets, and objective attribution of impacts to ARs. These different methods have been developed to answer specific research questions and hence use different criteria (e.g., geometry, threshold values of key variables, and time dependence). Furthermore, these methods are often employed using different reanalysis data sets, time periods, and regions of interest. The goal of the Atmospheric River Tracking Method Intercomparison Project (ARTMIP) is to understand and quantify uncertainties in AR science that arise due to differences in these methods. This paper presents results for key AR-related metrics based on 20+ different AR identification and tracking methods applied to Modern-Era Retrospective Analysis for Research and Applications Version 2 reanalysis data from January 1980 through June 2017. We show that AR frequency, duration, and seasonality exhibit a wide range of results, while the meridional distribution of these metrics along selected coastal (but not interior) transects are quite similar across methods. Furthermore, methods are grouped into criteria-based clusters, within which the range of results is reduced. AR case studies and an evaluation of individual method deviation from an all-method mean highlight advantages/disadvantages of certain approaches. For example, methods with less (more) restrictive criteria identify more (less) ARs and AR-related impacts. Finally, this paper concludes with a discussion and recommendations for those conducting AR-related research to consider.

An overview of cloud vertical structure (CVS) and cloud radiative forcing (CRF) during Indian summer monsoon is obtained over Kanpur, through observations made during the Interaction of Convective Organisation and Monsoon Precipitation, Atmosphere, Surface and Sea (INCOMPASS) field campaign of 2016. Associations of CVS parameters with CRF at surface and top of atmosphere (TOA) are also investigated. 137 radiosondes were launched at Indian Institute of Technology Kanpur (IITK), between 5th and 28th July, 2016. CVS is determined using an algorithm that identifies cloud layers from vertical profiles of relative humidity (RH), with altitude-dependent RH thresholds. CVS is analysed by separating the campaign period on the basis of presence and absence of depressions/low-pressure systems. Compared to non-depression periods, low-pressure events showed significant difference in all CVS and CRF parameters except cloud-top height. CVS was multi-layered in ~75% launches, with deep, mixed-phase clouds being present in ~70% launches. CRF was calculated from clear-sky measurements and TOA observations from Clouds and the Earth's Radiant Energy System (CERES) satellite retrievals, and surface measurements. A net cooling effect was found overall, with instantaneous shortwave forcing (SWCRF) (mean values of -95.92 and -101.89 W/m2 at surface and TOA, respectively) dominating longwave forcing (LWCRF) (mean values of 15.33 and 66.55 W/m2 at surface and TOA, respectively). Results suggest that SWCRF depends on total depth of cloud layers, and is independent of cloud altitude, whereas LWCRF depends on both depth and vertical location of cloud layers, with base and top heights regulating LWCRF at surface and TOA, respectively.

Accurate information about aerosol vertical distribution is needed to reduce uncertainties in aerosol radiative forcing and its effect on atmospheric dynamics. The present study deals with synergistic analyses of aerosol vertical distribution and aerosol optical depth (AOD) with meteorological variables using multisatellite and ground-based remote sensors over Kanpur in central Indo-Gangetic Plain (IGP). Micro-Pulse Lidar Network-derived aerosol vertical extinction (sigma) profiles are analyzed to quantify the interannual and daytime variations during monsoon onset period (May-June) for 2009-2011. The mean aerosol profile is broadly categorized into two layers viz., a surface layer (SL) extending up to 1.5 km (where sigma decreased exponentially with height) and an elevated aerosol layer (EAL) extending between 1.5 and 5.5 km. The increase in total columnar aerosol loading is associated with relatively higher increase in contribution from EAL loading than that from SL. The mean contributions of EALs are about 60%, 51%, and 50% to total columnar AOD during 2009, 2010, and 2011, respectively. We observe distinct parabolic EALs during early morning and late evening but uniformly mixed EALs during midday. The interannual and daytime variations of EALs are mainly influenced by long-range transport and convective capacity of the local emissions, respectively. Radiative flux analysis shows that clear-sky incoming solar radiation at surface is reduced with increase in AOD, which indicates significant cooling at surface. Collocated analysis of atmospheric temperature and aerosol loading reveals that increase in AOD not only resulted in surface dimming but also reduced the temperature (approximately 2-3 C) of lower troposphere (below 3 km altitude). Radiative transfer simulations indicate that the reduction of incoming solar radiation at surface is mainly due to increased absorption by EALs (with increase in total AOD). The observed cooling in lower troposphere in high aerosol loading scenario could be understood as a dynamical feedback of EAL-induced stratification of lower troposphere. Further, the observed radiative effect of EALs increases the stability of the lower troposphere, which could modulate the large-scale atmospheric dynamics during monsoon onset period. These findings encourage follow-up studies on the implication of EALs to the Indian summer monsoon dynamics using numerical models.

To study aerosol-cloud interactions over the Gangetic Basin of India, the Weather Research and Forecasting model coupled with chemistry (WRF-Chem) has been applied to a typical monsoon depression event prevalent between the 23 and 29 August 2009. This event was sampled during the Cloud Aerosol Interaction and Precipitation Enhancement EXperiment (CAIPEEX) aircraft campaign, providing measurements of aerosol and cloud microphysical properties from two sorties. Comparison of the simulated meteorological, thermodynamical, and aerosol fields against satellite and in situ aircraft measurements illustrated that the westward propagation of the monsoon depression and the cloud, aerosol, and rainfall spatial distribution was simulated reasonably well using anthropogenic emission rates from Monitoring Atmospheric Composition and Climate project along with cityZEN projects (MACCity)+Intercontinental Chemical Transport Experiment Phase B anthropogenic emission rates. However,the magnitude of aerosol optical depth was underestimated by up to 50%. A simulation with aerosol emissions increased by a factor of 6 over the CAIPEEX campaign domain increased the simulated aerosol concentrations to values close to the observations, mainly within boundary layer. Comparison of the low-aerosol simulation and high-aerosol simulation for the two sorties illustrated that more anthropogenic aerosols increased the cloud condensing nuclei (CCN) and cloud droplet mass concentrations. The number of simulated cloud droplets increased while the cloud droplet effective radii decreased, highlighting the importance of CCN-cloud feedbacks over this region. The increase in simulated anthropogenic aerosols (including absorbing aerosols) also increased the temperature of air parcels below clouds and thus the convective available potential energy (CAPE). The increase in CAPE intensified the updraft and invigorated the cloud, inducing formation of deeper clouds with more ice-phase hydrometeors for both cases. These case studies provide evidence of aerosol-induced cloud invigoration over the Gangetic Basin.