Lower Tropospheric Temperature Research Articles

Aerosol Loading and Radiation Budget Perturbations in Densely Populated and Highly Polluted Indo-Gangetic Plain by COVID-19: Influences on Cloud Properties and Air Temperature.

Aerosols emitted in densely populated and industrialized Indo‐Gangetic Plain, one of the most polluted regions in the world, modulate regional climate, monsoon, and Himalayan glacier retreat. Thus, this region is important for understanding aerosol perturbations and their resulting impacts on atmospheric changes during COVID‐19 lockdown period, a natural experimental condition created by the pandemic. By analyzing 5 years (2016–2020) data of aerosols and performing a radiative transfer calculation, we found that columnar and near‐surface aerosol loadings decreased, leading to reductions in radiative cooling at the surface and top of the atmosphere and atmospheric warming during lockdown period. Further, satellite data analyses showed increases in cloud optical thickness and cloud‐particle effective radius and decrease in lower tropospheric air temperature during lockdown period. These results indicate critical influences of COVID‐19 lockdown on regional climate and water cycle over Indo‐Gangetic Plain, emphasizing need for further studies from modeling perspectives.

Impact of Assimilating Advanced Himawari Imager Channel 16 Data on Precipitation Prediction over the Haihe River Basin

Assimilation of high-resolution geostationary satellite data is of great value for precise precipitation prediction in regional basins. The operational geostationary satellite imager carried by the Himawari-8 satellite, Advanced Himawari Imager (AHI), has two additional water vapor channels and four other channels compared with its predecessor, MTSAT-2. However, due to the uncertainty in surface parameters, AHI surface-sensitive channels are usually not assimilated over land, except for the three water vapor channels. Previous research showed that the brightness temperature of AHI channel 16 is much more sensitive to the lower-tropospheric temperature than to surface emissivity, which is similar to the three water vapor channels 8–10. As a follow-up work, this paper evaluates the effectiveness of assimilating brightness temperature observations over land from both the three AHI water vapor channels and channel 16 to improve watershed precipitation forecasting through both case analysis (in the Haihe River basin, China) and batch tests. It is found that assimilating AHI channel 16 can improve the upstream near-surface atmospheric temperature forecast, which in turn affects the development of downstream weather systems. The precipitation forecasting test results indicate that adding the terrestrial observations of channel 16 to the assimilation of AHI data can improve short-term precipitation forecasting in the basin.

All-sky Data Assimilation of MWTS-2 and MWHS-2 in the Met Office Global NWP System

Microwave radiances from passive polar-orbiting radiometers have been, until recently, assimilated in the Met Office global numerical weather prediction system after the scenes significantly affected by atmospheric scattering are discarded. Recent system upgrades have seen the introduction of a scattering-permitting observation operator and the development of a variable observation error using both liquid and ice water paths as proxies of scattering-induced bias. Applied to the Fengyun 3 Microwave Temperature Sounder 2 (MWTS-2) and the Microwave Humidity Sounder 2 (MWHS-2), this methodology increases the data usage by up to 8% at 183 GHz. It also allows for the investigation into the assimilation of MWHS-2 118 GHz channels, sensitive to temperature and lower tropospheric humidity, but whose large sensitivity to ice cloud have prevented their use thus far. While the impact on the forecast is mostly neutral with small but significant short-range improvements, 0.3% in terms of root mean square error, for southern winds and low-level temperature, balanced by 0.2% degradations of short-range northern and tropical low-level temperature, benefits are observed in the background fit of independent instruments used in the system. The lower tropospheric temperature sounding Infrared Atmospheric Sounding Interferometer (IASI) channels see a reduction of the standard deviation in the background departure of up to 1.2%. The Advanced Microwave Sounding Unit A (AMSU-A) stratospheric sounding channels improve by up to 0.5% and the Microwave Humidity Sounder (MHS) humidity sounding channels improve by up to 0.4%.

Using Climate Model Simulations to Constrain Observations

AbstractWe compare atmospheric temperature changes in satellite data and in model ensembles performed under phases 5 and 6 of the Coupled Model Intercomparison Project (CMIP5 and CMIP6). In the lower stratosphere, multidecadal stratospheric cooling during the period of strong ozone depletion is smaller in newer CMIP6 simulations than in CMIP5 or satellite data. In the troposphere, however, despite forcing and climate sensitivity differences between the two CMIP ensembles, their ensemble-average global warming over 1979–2019 is very similar. We also examine four properties of tropical behavior governed by basic physical processes. The first three are ratios between trends in water vapor (WV) and trends in sea surface temperature (SST), lower-tropospheric temperature (TLT), and mid- to upper-tropospheric temperature (TMT). The fourth property is the ratio between TMT and SST trends. All four ratios are tightly constrained in CMIP simulations but diverge markedly in observations. Model trend ratios between WV and temperature are closest to observed ratios when the latter are calculated with datasets exhibiting larger tropical warming of the ocean surface and troposphere. For the TMT/SST ratio, model–data consistency depends on the combination of observations used to estimate TMT and SST trends. If model expectations of these four covariance relationships are realistic, our findings reflect either a systematic low bias in satellite tropospheric temperature trends or an overestimate of the observed atmospheric moistening signal. It is currently difficult to determine which interpretation is more credible. Nevertheless, our analysis reveals anomalous covariance behavior in several observational datasets and illustrates the diagnostic power of simultaneously considering multiple complementary variables.

The Diel Cycle of NH3 Observed From the FY‐4A Geostationary Interferometric Infrared Sounder (GIIRS)

AbstractLimiting excess atmospheric ammonia (NH3) is one of the great challenges for humanity in the 21st century but can only be achieved with adequate monitoring means in place. Here, we report the first NH3 measurements from the Geostationary Interferometric Infrared Sounder (GIIRS) onboard the Chinese FY‐4A satellite. The instrument scans almost all of Asia 10 times per day. We show that GIIRS′ unprecedented temporal sampling can be exploited to measure diurnal and nocturnal variations of NH3 and demonstrate this on two case studies over Punjab and the North China Plain. Day–night variations are found to be almost absent in winter, but can reach a factor 2–3 in the warmer months. These case studies are very promising given the future landscape of geostationary sounders, but also show that improved knowledge on lower tropospheric air temperatures and the vertical profile of NH3 is key to better exploit their measurements.

Interannual Variability and Trends in Sea Surface Temperature, Lower and Middle Atmosphere Temperature at Different Latitudes for 1980–2019

The influence of sea-surface temperature (SST) on the lower troposphere and lower stratosphere temperature in the tropical, middle, and polar latitudes is studied for 1980–2019 based on the MERRA2, ERA5, and Met Office reanalysis data, and numerical modeling with a chemistry-climate model (CCM) of the lower and middle atmosphere. The variability of SST is analyzed according to Met Office and ERA5 data, while the variability of atmospheric temperature is investigated according to MERRA2 and ERA5 data. Analysis of sea surface temperature trends based on reanalysis data revealed that a significant positive SST trend of about 0.1 degrees per decade is observed over the globe. In the middle latitudes of the Northern Hemisphere, the trend (about 0.2 degrees per decade) is 2 times higher than the global average, and 5 times higher than in the Southern Hemisphere (about 0.04 degrees per decade). At polar latitudes, opposite SST trends are observed in the Arctic (positive) and Antarctic (negative). The impact of the El Niño Southern Oscillation phenomenon on the temperature of the lower and middle atmosphere in the middle and polar latitudes of the Northern and Southern Hemispheres is discussed. To assess the relative influence of SST, CO2, and other greenhouse gases’ variability on the temperature of the lower troposphere and lower stratosphere, numerical calculations with a CCM were performed for several scenarios of accounting for the SST and carbon dioxide variability. The results of numerical experiments with a CCM demonstrated that the influence of SST prevails in the troposphere, while for the stratosphere, an increase in the CO2 content plays the most important role.

Acceleration of western Arctic sea ice loss linked to the Pacific North American pattern

Recent rapid Arctic sea-ice reduction has been well documented in observations, reconstructions and model simulations. However, the rate of sea ice loss is highly variable in both time and space. The western Arctic has seen the fastest sea-ice decline, with substantial interannual and decadal variability, but the underlying mechanism remains unclear. Here we demonstrate, through both observations and model simulations, that the Pacific North American (PNA) pattern is an important driver of western Arctic sea-ice variability, accounting for more than 25% of the interannual variance. Our results suggest that the recent persistent positive PNA pattern has led to increased heat and moisture fluxes from local processes and from advection of North Pacific airmasses into the western Arctic. These changes have increased lower-tropospheric temperature, humidity and downwelling longwave radiation in the western Arctic, accelerating sea-ice decline. Our results indicate that the PNA pattern is important for projections of Arctic climate changes, and that greenhouse warming and the resultant persistent positive PNA trend is likely to increase Arctic sea-ice loss.

Future Changes in Northern Hemisphere Summer Weather Persistence Linked to Projected Arctic Warming

AbstractUnderstanding the response of the large‐scale atmospheric circulation to climatic change remains a key challenge. Specifically, changes in the equator‐to‐pole temperature difference have been suggested to affect the midlatitudes, potentially leading to more persistent extreme weather, but a scientific consensus has not been established so far. Here we quantify summer weather persistence by applying a tracking algorithm to lower tropospheric vorticity and temperature fields to analyze changes in their propagation speeds. We find significant links between slower propagating weather systems and a weaker equator‐to‐pole temperature difference in observations and models. By end of the century, the propagation of temperature anomalies over midlatitude land is projected to decrease by −3%, regionally strongest in southern North America (−45%) under a high emission scenario (CMIP5 RCP8.5). Even higher decreases are found (−10%, −58%) in models which project a decreasing equator‐to‐pole temperature difference. Our findings provide evidence that hot summer weather might become longer‐lasting, bearing the risk of more persistent heat extremes.

Northern Hemisphere Sudden Stratospheric Warming and Its Downward Impact in Four Chinese CMIP6 Models

Using the World Meteorological Organization definition and a threshold-based classification technique, simulations of vortex displacement and split sudden stratospheric warmings (SSWs) are evaluated for four Chinese models (BCC-CSM2- MR, FGOALS-f3-L, FGOALS-g3, and NESM3) from phase 6 of the Coupled Model Intercomparison Project (CMIP6) with the Japanese 55-year reanalysis (JRA-55) as a baseline. Compared with six or seven SSWs in a decade in JRA-55, three models underestimate the SSW frequency by ~50%, while NESM3 doubles the SSW frequency. SSWs mainly appear in midwinter in JRA-55, but one-month climate drift is simulated in the models. The composite of splits is stronger than displacements in both the reanalysis and most models due to the longer pulse of positive eddy heat flux before onset of split SSWs. A wavenumber-1-like temperature anomaly pattern (cold Eurasia, warm North America) before onset of displacement SSWs is simulated, but cold anomalies are mainly confined to North America after displacement SSWs. Although the lower tropospheric temperature also displays a wavenumber-1-like pattern before split SSWs, most parts of Eurasia and North America are covered by cold anomalies after split SSWs in JRA-55. The models have different degrees of fidelity for the temperature anomaly pattern before split SSWs, but the wavenumber-2-like temperature anomaly pattern is well simulated after split SSWs. The center of the negative height anomalies in the Pacific sector before SSWs is sensitive to the SSW type in both JRA-55 and the models. A negative North Atlantic Oscillation is simulated after both types of SSWs in the models, although it is only observed for split SSWs.

Supermodding – A special footprint operator for mesoscale data assimilation using scatterometer winds

AbstractSatellite observation footprints may extend over many grid points of a high‐resolution limited‐area model, while small and fast model scales may not be traceable by the observing system. We discuss the spatial representation of scatterometer ocean surface winds for the representation of high‐resolution model state variables. A prototype observation operator called supermodding is studied in the variational assimilation framework in order to avoid correcting unconstrained small scales during the assimilation procedure. The challenges connected to small scales that are represented by the mesoscale model with respect to the application of the supermodding operator are discussed through idealised experiments. These results show that the application of the supermodding operator is able to avoid correcting unconstrained small scales, putting focus on the large scales only during data assimilation. Departure‐based diagnostics show that the footprint representation helps to reduce the standard deviation of observation minus background departures (4–5% reduction) while the statistics for the supermodding method show a further reduction (8–11%). The impact of the supermodding approach is discussed through a forecast sensitivity study using a moist total energy norm (MTEN)‐based technique and verification of the forecasts against observations. It is shown that the impact of the supermodding method to ASCAT data assimilation on the upper‐air AROME‐Arctic forecasts is observed over sea and near the surface, and that it is progressively shifted towards 700–800 hPa levels. Both supermodding at 30 km and at 60 km (i.e., twice the effective resolution of the applied scatterometer observations) show significant and consistent improvement on forecasts of lower tropospheric wind and temperature compared to the operational assimilation technique, as such demonstrating the robustness of the supermodding technique.

Central Arctic weather forecasting: Confronting theECMWF IFSwith observations from the Arctic Ocean 2018 expedition

AbstractForecasts with the European Centre for Medium‐Range Weather Forecasts' numerical weather prediction model are evaluated using an extensive set of observations from the Arctic Ocean 2018 expedition on the Swedish icebreakerOden. The atmospheric model (Cy45r1) is similar to that used for the ERA5 reanalysis (Cy41r2). The evaluation covers 1 month, with the icebreaker moored to drifting sea ice near the North Pole; a total of 125 forecasts issued four times per day were used. Standard surface observations and 6‐hourly soundings were assimilated to ensure that the initial model error is small. Model errors can be divided into two groups. First, variables related to dynamics feature errors that grow with forecast length; error spread also grows with time. Initial errors are small, facilitating a robust evaluation of the second group; thermodynamic variables. These feature fast error growth for 6–12 hr, after which errors saturates; error spread is roughly constant. Both surface and near‐surface air temperatures are too warm in the model. During the summer both are typically above zero in spite of the ongoing melt; however, the warm bias increases as the surface freezes. The warm bias is due to a too warm atmosphere; errors in surface sensible heat flux transfer additional heat from the atmosphere to the surface. The lower troposphere temperature error has a distinct vertical structure: a substantial warm bias in the lowest few 100 m and a large cold bias around 1 km; this structure features a significant diurnal cycle and is tightly coupled to errors in the modelled clouds. Clouds appear too often and in a too deep layer of the lower atmosphere; the lowest clouds essentially never break up. The largest error in cloud presence is aligned with the largest cold bias at around 1 km.

Understanding Intermodel Variability in Future Projections of a Sahelian Storm Proxy and Southern Saharan Warming

AbstractProjected changes in the intensity of severe rain events over the North African Sahel—falling from large mesoscale convective systems—cannot be directly assessed from global climate models due to their inadequate resolution and parameterization of convection. Instead, the large-scale atmospheric drivers of these storms must be analyzed. Here we study changes in meridional lower-tropospheric temperature gradient across the Sahel (ΔTGrad), which affect storm development via zonal vertical wind shear and Saharan air layer characteristics. Projected changes in ΔTGrad vary substantially among models, adversely affecting planning decisions that need to be resilient to adverse risks, such as increased flooding. This study seeks to understand the causes of these projection uncertainties and finds three key drivers. The first is intermodel variability in remote warming, which has strongest impact on the eastern Sahel, decaying toward the west. Second, and most important, a warming–advection–circulation feedback in a narrow band along the southern Sahara varies in strength between models. Third, variations in southern Saharan evaporative anomalies weakly affect ΔTGrad, although for an outlier model these are sufficiently substantive to reduce warming here to below that of the global mean. Together these uncertain mechanisms lead to uncertain southern Saharan/northern Sahelian warming, causing the bulk of large intermodel variations in ΔTGrad. In the southern Sahel, a local negative feedback limits the contribution to uncertainties in ΔTGrad. This new knowledge of ΔTGrad projection uncertainties provides understanding that can be used, in combination with further research, to constrain projections of severe Sahelian storm activity.

Arctic Ozone Loss in March 2020 and its Seasonal Prediction in CFSv2: A Comparative Study With the 1997 and 2011 Cases

AbstractUsing reanalysis data, observations, and seasonal forecasts, the March Arctic ozone loss events in 1997, 2011, and 2020 and their predictability are compared. All of the three ozone loss events were accompanied by an extremely strong and cold polar vortex, with the shape and centroid of the ozone loss controlled by the polar vortex. The high autocorrelation of the March Arctic ozone at a lead/lag time of 1–2 months from observations might suggest that a reasonable prediction can be obtained if one initializes 1–2 months in advance. Based on the chemical scheme assessment in CFSv2 and several empirical models using the forecasted metric(s) of the stratospheric polar vortex as predictor(s), the predictability of the 2011 ozone loss event is shown to be longer (1–2 months) than the other two (~1 month), possibly due to a moderate La Niña and quasi‐biennial oscillation westerly winds favorable for the formation of a strong polar vortex. However, the overall predictive skills of ozone from empirical models (using a forecasted substitute index to forecast the Arctic ozone) during 1982–2020 are lower than the chemical module assessment in the forecast system, though empirical models have some skill. Contrary to the ozone predictions, the lower tropospheric temperature pattern in March 2011 is less reasonable than in 1997 and 2020. Similar conclusions are also true in other years (2005 versus 2016). Those findings might indicate a weak relationship between the Arctic ozone and the surface climate in the Northern Hemisphere.

The Climatology of Lower Tropospheric Temperature Inversions in China from Radiosonde Measurements: Roles of Black Carbon, Local Meteorology, and Large-Scale Subsidence

AbstractThe variability of the lower tropospheric temperature inversion (TI) across China remains poorly understood. Using seven years’ worth of high-resolution radiosonde measurements at 120 sites, we compile the climatology of lower tropospheric TI in terms of frequency, intensity, and depth during the period from 2011 to 2017. The TI generally exhibits strong seasonal and geographic dependencies. Particularly, the TI frequency is found to be high in winter and low in summer, likely due to the strong aerosol radiative effect in winter. The frequency of the surface-based inversion (SBI) exhibits a “west low, east high” pattern at 0800 Beijing time (BJT), which then switches to “west high, east low” at 2000 BJT. Both the summertime SBI and elevated inversion (EI) reach a peak at 0800 BJT and a trough at 1400 BJT. Interestingly, the maximum wintertime EI frequency occurs over Southeast China (SEC) rather than over the North China Plain (NCP), likely attributable to the combination of the heating effect of black carbon (BC) originating from the NCP, along with the strong subsidence and trade inversion in SEC. Correlation analyses between local meteorology and TI indicate that larger lower tropospheric stability (LTS) favors more frequent and stronger TIs, whereas the stronger EI under smaller LTS conditions (unstable atmosphere) is more associated with subsidence rather than BC. Overall, the spatial pattern of the lower tropospheric TI and its variability in China are mainly controlled by three factors: local meteorology, large-scale subsidence, and BC-induced heating. These findings help shed some light on the magnitude, spatial distribution, and underlying mechanisms of the lower tropospheric TI variation in China.

Using Analysis Corrections to Address Model Error in Atmospheric Forecasts

Abstract This paper illustrates that analysis corrections, when applied as a model tendency term, can be used to improve nonlinear model forecasts and are consistent with the hypothesis that they represent an additive 6-h accumulation of model error. Comparison of mean analysis corrections with observational estimates of bias further illustrates the fidelity with which mean analysis corrections capture the model bias. While most previous implementations have explored the use of analysis corrections to correct forecast biases in short-range forecasts, this is the first implementation of the correction method using both a seasonal mean and random analysis correction for medium-range forecasts (out to 10 days). Overall, the analysis correction–based perturbations are able to improve forecast skill in ensemble and deterministic systems, especially in the first 5 days of the forecast where bias and RMSE in both lower-tropospheric temperature and 500 hPa geopotential height are significantly improved across all experiments. However, while the method does provide some significant improvement to forecast skill, some degradation in bias can occur at later lead times when the average bias at analysis time trends toward zero over the length of the forecast, leading to an overcorrection by the analysis correction–based additive inflation (ACAI) method. Additionally, it is shown that both the mean and random component of the ACAI perturbations play a role in adjusting the model bias, and that the two components can have a complicated and sometimes nonlinear interaction.

The Relationship Between Convective Clustering and Mean Tropical Climate in Aquaplanet Simulations.

Convective clustering, the spatial organization of tropical deep convection, can manifest itself in two ways: through a decrease in the total area covered by convection and/or through a decrease in the number of convective areas. Much of our current understanding of convective clustering comes from simulations in idealized radiative convective equilibrium (RCE) configurations. In these simulations the two forms of convective clustering tend to covary, and their individual effects on the climate are thus hard to disentangle. This study shows that in aquaplanet simulations with more realistic boundary conditions, such as meridional gradients of surface temperature and rotational forces, the two aspects of convective clustering are not equivalent and are associated with different impacts on the large‐scale climate. For instance, reducing the convective area in the equatorial region in the aquaplanet simulations results in broader meridional humidity and rain distributions and in lower tropospheric temperatures throughout the tropics. By contrast, the number of convective regions primarily impacts the zonal variance of humidity‐related quantities in the aquaplanet simulations, as the distribution of convective regions affects the size of the subsidence regions and thereby the moistening influence of convective regions. The aquaplanet simulations confirm many other qualitative results from RCE simulations, such as a reduction of equatorial tropospheric humidity when the area covered by convection diminishes.

Representation of low-tropospheric temperature inversions in ECMWF reanalyses over Europe

Despite the fact that tropospheric temperature inversions are thought to be an important feature of climate as well as a significant factor affecting air quality, low-level cloud formation, and the radiation budget of the Earth, a quantitative assessment of their representation in atmospheric reanalyses is yet missing. Here, we provide new evidence of the occurrence of low-tropospheric temperature inversions and associated uncertainties in their parameters existing among reanalyses produced by the European Centre for Medium-Range Weather Forecasts (ECMWF) and upper-air soundings for Europe covering the period 2001–2010. The reanalyses utilized here include (1) surface-input reanalyses represented by ERA-20C and CERA-20C as well as (2) full-input reanalyses represented by ERA-Interim and ERA5. The upper-air soundings were derived from the Integrated Global Radiosonde Archive (IGRA), version 2. The data consists mainly of air temperature and geopotential height from the model levels (ModLev) and pressure levels (PresLev) of ECMWF reanalyses. The results show that the frequency of surface-based inversions (SBI) and elevated inversions (EI) is largely in agreement among the reanalyses. The quality of their representation depends, however, on the inversion type, season, and region. Over the vast majority of IGRA upper-air stations, SBI frequency is overestimated and EI frequency is underestimated by ECMWF reanalyses. Substantially larger uncertainties arise from the selection between the data of ModLev and PresLev of the reanalyses—the differences in the frequency of the temperature inversions are particularly large for summertime SBI suggesting that PresLev are not capable of resolving the main features of shallow and weak SBI.

Impact of air-sea interaction during two contrasting monsoon seasons

The air-sea interaction processes and their relation to Indian summer monsoon rainfall via dynamic and thermodynamic components are vital. The present study examined the two contrasting monsoon years 2016 (normal) and 2017 (below normal) and highlighted the significance of air-sea interaction in the understanding the rainfall over central India. We investigate the difference in the sea surface height anomaly and propagation of oceanic Kelvin and Rossby wave over the tropical Indian Ocean and other atmospheric parameters during the contrasting monsoon years. The study gives information on how equatorial and coastal Kelvin/Rossby waves cause upwelling/downwelling and modulate convection and influence rainfall during 2016 and 2017. The high (low) sea surface height anomaly, sea surface temperature, and upper ocean heat content during 2016 (2017) lead to enhanced (subdued) convection in the Bay of Bengal and thereby contributing more rainfall to central India. During 2016 (2017), high (low) tropospheric temperature draws more (less) moisture through mid-tropospheric heat flux, and net convergence (divergence) is dominated over the central India that results in enhanced (diminish) convection. Also, the velocity potential determines the strengthening (weakening) of Walker circulation through associated atmospheric circulation and upper-level divergence (convergence) that become favorable for rainfall in the year 2016 (2017). This study will help in understanding the variations in the air-sea interaction processes over the tropical Indian Ocean and the Indian subcontinent, the results of which may improve the predictability of the rainfall.

IMPACT OF VERTICAL RESOLUTION, MODEL TOP AND DATA ASSIMILATION ON WEATHER FORECASTING-A CASE STUDY

The impacts of stratospheric initial conditions and vertical resolution on the stratosphere by raising the model top, refining the vertical resolution, and the assimilation of operationally available observations, including conventional and satellite observations, on continental U. S. winter short-range weather forecasting, were investigated in this study. The initial and predicted wind and temperature profiles were analyzed against conventional observations. Generally, the initial wind and temperature bias profiles were better adjusted when a higher model top and refined vertical resolution were used. Negative impacts were also observed in both the initial wind and temperature profiles, over the lower troposphere. Different from the results by only raising the model top, the assimilation of operationally available observations led to significant improvements in both the troposphere and stratosphere initial conditions when a higher top was used. Predictions made with the adjusted stratospheric initial conditions and refined vertical resolutions showed generally better forecasting skill. The major improvements caused by raising the model top with refined vertical resolution, as well as those caused by data assimilation, were in both cases located in the tropopause and lower stratosphere. Negative impacts were also observed in the predicted near surface wind and lower-tropospheric temperature. These negative impacts were related to the uncertainties caused by more stratospheric information, as well as to some physical processes. A case study shows that when we raise the model top, put more vertical layers in stratosphere and apply data assimilation, the precipitation scores can be slightly improved. However, more analysis is needed due to uncertainties brought by data assimilation.

Ice core records of levoglucosan and dehydroabietic and vanillic acids from Aurora Peak in Alaska since the 1660s: a proxy signal of biomass-burning activities in the North Pacific Rim

Abstract. A 180 m long (343 years) ice core was drilled in the saddle of Aurora Peak in Alaska (63.52∘ N, 146.54∘ W; elevation: 2825 m) and studied for biomass-burning tracers. Concentrations of levoglucosan and dehydroabietic and vanillic acids exhibit multidecadal variability, with higher spikes in 1678, 1692, 1695, 1716, 1750, 1764, 1756, 1834, 1898, 1913, 1966 and 2005 CE. Historical trends of these compounds showed enhanced biomass-burning activities in the deciduous broadleaf forests, boreal conifer forests, and/or tundra woodland and mountain ecosystems before the 1830s and after the Great Pacific Climate Shift (GPCS). The gradually elevated level of dehydroabietic acid after the GPCS is similar to p-hydroxybenzoic acid (p-HBA) from the Svalbard ice core, suggesting common climate variability in the Northern Hemisphere. The periodic cycle of levoglucosan, which seemed to be associated with the Pacific Decadal Oscillation (PDO), may be more involved with the long-range atmospheric transport than other species. These compounds showed significant correlations with global lower-tropospheric temperature anomalies (GLTTAs). The relations of the biomass-burning tracers with the PDO and GLTTA in this study suggest that their emission, frequency and deposition are controlled by the climate-driven forces. In addition, historical trends of dehydroabietic and vanillic acids (burning products of resin and lignin, respectively) from our ice core demonstrate the Northern Hemispheric connections to the common source regions as suggested from other ice core studies from Svalbard, Akademii Nauk and Tunu Greenland in the Northern Hemisphere.