Snow depth trends from CMIP6 models conflict with observational evidence

2021 ◽  
pp. 1-40
Keyword(s):  
Northern Hemisphere ◽  
Air Temperature ◽  
High Latitude ◽  
Snow Depth ◽  
Cold Season ◽  
Observational Evidence ◽  
High Quality ◽  
Observational Dataset ◽  
Precipitation Increase

Abstract In this study, we compiled a high-quality, in situ observational dataset to evaluate snow depth simulations from 22 CMIP6 models across high-latitude regions of the Northern Hemisphere over the period 1955–2014. Simulated snow depths have low accuracy (RMSE = 17–36 cm) and are biased high, exceeding the observed baseline (1976–2005) on average (18 ± 16 cm) across the study area. Spatial climatological patterns based on observations are modestly reproduced by the models (NRMSDs of 0.77 ± 0.20). Observed snow depth during the cold season increased by about 2.0 cm over the study period, which is approximately 11% relative to the baseline. The models reproduce decreasing snow depth trends that contradict the observations, but they all indicate a precipitation increase during the cold season. The modeled snow depths are insensitive to precipitation but too sensitive to air temperature; these inaccurate sensitivities could explain the discrepancies between the observed and simulated snow depth trends. Based on our findings, we recommend caution when using and interpreting simulated changes in snow depth and associated impacts.

scholarly journals Snow Depth Fusion Based on Machine Learning Methods for the Northern Hemisphere

2021 ◽  
Vol 13 (7) ◽  
pp. 1250
Author(s):  
Yanxing Hu ◽  
Tao Che ◽  
Liyun Dai ◽  
Lin Xiao
Keyword(s):  
Machine Learning ◽  
Northern Hemisphere ◽  
Snow Depth ◽  
Learning Algorithm ◽  
Random Forest Regression ◽  
Machine Learning Methods ◽  
Long Time ◽  
In Situ Observations ◽  
Input Variables

In this study, a machine learning algorithm was introduced to fuse gridded snow depth datasets. The input variables of the machine learning method included geolocation (latitude and longitude), topographic data (elevation), gridded snow depth datasets and in situ observations. A total of 29,565 in situ observations were used to train and optimize the machine learning algorithm. A total of five gridded snow depth datasets—Advanced Microwave Scanning Radiometer for the Earth Observing System (AMSR-E) snow depth, Global Snow Monitoring for Climate Research (GlobSnow) snow depth, Long time series of daily snow depth over the Northern Hemisphere (NHSD) snow depth, ERA-Interim snow depth and Modern-Era Retrospective Analysis for Research and Applications, version 2 (MERRA-2) snow depth—were used as input variables. The first three snow depth datasets are retrieved from passive microwave brightness temperature or assimilation with in situ observations, while the last two are snow depth datasets obtained from meteorological reanalysis data with a land surface model and data assimilation system. Then, three machine learning methods, i.e., Artificial Neural Networks (ANN), Support Vector Regression (SVR), and Random Forest Regression (RFR), were used to produce a fused snow depth dataset from 2002 to 2004. The RFR model performed best and was thus used to produce a new snow depth product from the fusion of the five snow depth datasets and auxiliary data over the Northern Hemisphere from 2002 to 2011. The fused snow-depth product was verified at five well-known snow observation sites. The R2 of Sodankylä, Old Aspen, and Reynolds Mountains East were 0.88, 0.69, and 0.63, respectively. At the Swamp Angel Study Plot and Weissfluhjoch observation sites, which have an average snow depth exceeding 200 cm, the fused snow depth did not perform well. The spatial patterns of the average snow depth were analyzed seasonally, and the average snow depths of autumn, winter, and spring were 5.7, 25.8, and 21.5 cm, respectively. In the future, random forest regression will be used to produce a long time series of a fused snow depth dataset over the Northern Hemisphere or other specific regions.

scholarly journals Double Star, Cluster, and ground-based observations of magnetic reconnection during an interval of duskward oriented IMF: preliminary results

2005 ◽  
Vol 23 (8) ◽  
pp. 2903-2907 ◽  
Author(s):  
J. A. Wild ◽  
S. E. Milan ◽  
J. A. Davies ◽  
S. W. H. Cowley ◽  
C. M. Carr ◽  
...  
Keyword(s):  
Magnetic Reconnection ◽  
Northern Hemisphere ◽  
High Latitude ◽  
Double Star ◽  
Flux Tubes ◽  
Flux Transfer Events ◽  
Subsolar Point ◽  
Magnetic Flux Tubes ◽  
In Situ Observations

Abstract. We present a space- and ground-based study exploiting data from the coordinated Cluster and Double Star missions in order to investigate dayside magnetic reconnection under BY+ dominated IMF conditions. In-situ observations of magnetosheath flux transfer events combined with measurements of pulsed poleward and dawnward directed flows in the pre-noon sector high-latitude northern hemisphere ionosphere are interpreted as indications of pulsed magnetic reconnection during an interval in which the IMF remained relatively steady. Observations of newly-reconnected magnetic flux tubes anchored in the northern hemisphere both at mid-latitudes and in the vicinity of the subsolar point suggests that during BY+ dominated IMF, reconnection is not, as proposed previously, limited to the high-latitude magnetopause.

scholarly journals Assessing High-Latitude Winter Precipitation from Global Precipitation Analyses Using GRACE

2010 ◽  
Vol 11 (2) ◽  
pp. 405-420 ◽  
Author(s):  
Sean Swenson
Keyword(s):  
High Latitude ◽  
Global Precipitation Climatology Project ◽  
Cold Season ◽  
Winter Precipitation ◽  
Precipitation Estimates ◽  
Highly Correlated ◽  
Gravity Recovery ◽  
Global Precipitation ◽  
Climate Prediction Center

Abstract This study compares cold-season, high-latitude precipitation estimates from two global, merged satellite–gauge precipitation analyses—Global Precipitation Climatology Project (GPCP) and Climate Prediction Center Merged Analysis of Precipitation (CMAP)—to total water storage anomalies produced from the Gravity Recovery and Climate Experiment (GRACE). In general, spatial patterns and interannual variability are highly correlated between the datasets, although significant differences are also observed. Differences vary by region but typically increase at higher latitudes. Furthermore, results indicate that the gauge undercatch correction used by GPCP may be overestimated. These comparisons may be useful for assessing precipitation estimates over large regions, where in situ gauge networks may be sparse.

scholarly journals Spatial and temporal variations of snow cover in the forest area of middle and high latitude of Northern Hemisphere

2021 ◽  
Vol 932 (1) ◽  
pp. 012005
Author(s):  
Q Shao ◽  
C Huang ◽  
J F Huang
Keyword(s):  
Spatial Distribution ◽  
Snow Cover ◽  
Northern Hemisphere ◽  
High Latitude ◽  
Land Surface ◽  
Temporal Variations ◽  
Cold Season ◽  
Forest Area ◽  
Significant Advance ◽  
Significant Delay

Abstract Snow cover is an important part of cryosphere and the most seasonally changing land surface cover, which is sensitive to climate change. Previous studies showed that climate warming has already altered the extent and phenology of snow cover, which influences the plant phenology of the forest ecosystem. This research investigates the spatial distribution and temporal trend of snow cover in the forest area of mid and high latitude in the Northern Hemisphere (50°N-90°N,180°W-180°E) based on a satellite-derived snow dataset. Results showed that the spatial distribution of snow cover exhibits a latitudinal gradientin the mid and high latitudes of the Northern Hemisphere. The snow cover onset week (SCOW) and snow cover end week (SCEW) shortened significantly at a rate of 0.23 weeks/10 yr. and 0.48 weeks/10 yr., respectively (P<0.05). Cold season (CS) and snow cover persistence week (SCPW) shortened at a rate of 0.25 weeks/10 yr. and 0.16 weeks/10 yr. 19.62% of the study area showed a trend of a significant advance in SCOW, and 1.36% showed a trend of significant delay (P<0.05). For SCEW, 44.91% of regions showed significant advance and 1.91% of regions showed significant delay (P<0.05). CS was a significantly shorted trend (P<0.05) in 16.95% of the study area and showed a significantly extended trend (P<0.05) in 3.76% of the area. SCPW and CS were similar but different, indicating that transient snowfall exists in parts of the study area.

The Influence of the MJO on the Intraseasonal Variability of Northern Hemisphere Spring Snow Depth

2015 ◽  
Vol 28 (18) ◽  
pp. 7250-7262 ◽  
Author(s):  
Bradford S. Barrett ◽  
Gina R. Henderson ◽  
Joshua S. Werling
Keyword(s):  
North America ◽  
Northern Hemisphere ◽  
Air Temperature ◽  
Snow Depth ◽  
Intraseasonal Variability ◽  
Rank Correlation ◽  
Surface Air Temperature ◽  
Correlation Coefficients ◽  
Strong Relationship ◽  
The Relationship

Abstract Intraseasonal variability in springtime Northern Hemisphere daily snow depth change (ΔSD) by phase of the MJO was explored in this study. Principal findings of the relationship between ΔSD and the MJO included the following: 1) Statistically significant regions of lagged ΔSD anomalies for multiple phases of the MJO were found in March, April, and May in both North America and Eurasia. 2) In each month, lagged ΔSD anomalies were physically supported by corresponding lagged anomalies of 500-hPa height (Z500) and surface air temperature (SAT). Spearman rank correlation coefficients indicated a moderate to strong relationship between both Z500 and ΔSD and SAT and ΔSD in both Eurasia and North America for phases 5 and 7 in March. In April, a moderately strong relationship between Z500 and ΔSD was found over Eurasia for phase 5, but the relationship between SAT and ΔSD was weak. In May, correlations between ΔSD and both Z500 and SAT over a hemisphere-wide latitude band from 60° to 75°N were close to −0.5 and −0.4, respectively. Given the strength of these statistical relationships, the following physical pathway is proposed for intraseasonal variability of spring snow depth changes: poleward-propagating Rossby waves in response to tropical MJO convection interact with Northern Hemisphere background flow, leading to anomalous troughing and ridging. These anomalous circulation centers then impact daily snow depth change via precipitation processes and anomalies in surface air temperature.

scholarly journals WRF Simulations of the 20–22 January 2007 Snow Events over Eastern Canada: Comparison with In Situ and Satellite Observations

2010 ◽  
Vol 49 (11) ◽  
pp. 2246-2266 ◽  
Author(s):  
J. J. Shi ◽  
W-K. Tao ◽  
T. Matsui ◽  
R. Cifelli ◽  
A. Hou ◽  
...  
Keyword(s):  
Liquid Water ◽  
High Latitude ◽  
Satellite Observation ◽  
Cold Season ◽  
Cloud Microphysics ◽  
Appreciable Amount ◽  
High Latitudes ◽  
Eastern Canada ◽  
Microphysics Scheme

Abstract One of the grand challenges of the Global Precipitation Measurement (GPM) mission is to improve cold-season precipitation measurements in mid- and high latitudes through the use of high-frequency passive microwave radiometry. For this purpose, the Weather Research and Forecasting model (WRF) with the Goddard microphysics scheme is coupled with a Satellite Data Simulation Unit (WRF–SDSU) to facilitate snowfall retrieval algorithms over land by providing a virtual cloud library and corresponding microwave brightness temperature measurements consistent with the GPM Microwave Imager (GMI). When this study was initiated, there were no prior published results using WRF at cloud-resolving resolution (1 km or finer) for high-latitude snow events. This study tested the Goddard cloud microphysics scheme in WRF for two different snowstorm events (a lake-effect event and a synoptic event between 20 and 22 January 2007) that took place over the Canadian CloudSat/Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) Validation Project (C3VP) site in Ontario, Canada. The 24-h-accumulated snowfall predicted by WRF with the Goddard microphysics was comparable to that observed by the ground-based radar for both events. The model correctly predicted the onset and termination of both snow events at the Centre for Atmospheric Research Experiments site. The WRF simulations captured the basic cloud patterns as seen by the ground-based radar and satellite [i.e., CloudSat and Advanced Microwave Sounding Unit B (AMSU-B)] observations, including the snowband featured in the lake event. The results reveal that WRF was able to capture the cloud macrostructure reasonably well. Sensitivity tests utilizing both the “2ICE” (ice and snow) and “3ICE” (ice, snow, and graupel) options in the Goddard microphysical scheme were also conducted. The domain- and time-averaged cloud species profiles from the WRF simulations with both microphysical options show identical results (due to weak vertical velocities and therefore the absence of large precipitating liquid or high-density ice particles like graupel). Both microphysics options produced an appreciable amount of liquid water, and the model cloud liquid water profiles compared well to the in situ C3VP aircraft measurements when only grid points in the vicinity of the flight paths were considered. However, statistical comparisons between observed and simulated radar echoes show that the model tended to have a high bias of several reflectivity decibels (dBZ), which shows that additional research is needed to improve the current cloud microphysics scheme for the extremely cold environment in high latitudes, despite the fact that the simulated ice/liquid water contents may have been reasonable for both events. Future aircraft observations are also needed to verify the existence of graupel in high-latitude continental snow events.

Epitaxial growth manner and structure of superconducting oxide films

1990 ◽  
Vol 48 (4) ◽  
pp. 2-3
Author(s):  
Yoshichika Bando ◽  
Takahito Terashima ◽  
Kenji Iijima ◽  
Kazunuki Yamamoto ◽  
Kazuto Hirata ◽  
...  
Keyword(s):  
Ultrathin Films ◽  
Film Surface ◽  
High Energy ◽  
Epitaxial Films ◽  
Layer By Layer ◽  
Initial Growth ◽  
In Situ Growth ◽  
High Quality ◽  
Activated Reactive Evaporation

The high quality thin films of high-Tc superconducting oxide are necessary for elucidating the superconducting mechanism and for device application. The recent trend in the preparation of high-Tc films has been toward “in-situ” growth of the superconducting phase at relatively low temperatures. The purpose of “in-situ” growth is to attain surface smoothness suitable for fabricating film devices but also to obtain high quality film. We present the investigation on the initial growth manner of YBCO by in-situ reflective high energy electron diffraction (RHEED) technique and on the structural and superconducting properties of the resulting ultrathin films below 100Å. The epitaxial films have been grown on (100) plane of MgO and SrTiO, heated below 650°C by activated reactive evaporation. The in-situ RHEED observation and the intensity measurement was carried out during deposition of YBCO on the substrate at 650°C. The deposition rate was 0.8Å/s. Fig. 1 shows the RHEED patterns at every stage of deposition of YBCO on MgO(100). All the patterns exhibit the sharp streaks, indicating that the film surface is atomically smooth and the growth manner is layer-by-layer.

scholarly journals Subseasonal relationship between Arctic and Eurasian surface air temperature

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Hye-Jin Kim ◽  
Seok-Woo Son ◽  
Woosok Moon ◽  
Jong-Seong Kug ◽  
Jaeyoung Hwang
Keyword(s):  
Air Temperature ◽  
Diabatic Heating ◽  
Surface Air Temperature ◽  
Significant Negative Correlation ◽  
Cold Season ◽  
Reanalysis Data ◽  
Necessary Condition ◽  
Sea Level Pressure ◽  
Blocking High ◽  
Pressure Anomaly

AbstractThe subseasonal relationship between Arctic and Eurasian surface air temperature (SAT) is re-examined using reanalysis data. Consistent with previous studies, a significant negative correlation is observed in cold season from November to February, but with a local minimum in late December. This relationship is dominated not only by the warm Arctic-cold Eurasia (WACE) pattern, which becomes more frequent during the last two decades, but also by the cold Arctic-warm Eurasia (CAWE) pattern. The budget analyses reveal that both WACE and CAWE patterns are primarily driven by the temperature advection associated with sea level pressure anomaly over the Ural region, partly cancelled by the diabatic heating. It is further found that, although the anticyclonic anomaly of WACE pattern mostly represents the Ural blocking, about 20% of WACE cases are associated with non-blocking high pressure systems. This result indicates that the Ural blocking is not a necessary condition for the WACE pattern, highlighting the importance of transient weather systems in the subseasonal Arctic-Eurasian SAT co-variability.

scholarly journals Air–Sea Interaction in the Central Mediterranean Sea: Assessment of Reanalysis and Satellite Observations

2021 ◽  
Vol 13 (11) ◽  
pp. 2188
Author(s):  
Salvatore Marullo ◽  
Jaime Pitarch ◽  
Marco Bellacicco ◽  
Alcide Giorgio di Sarra ◽  
Daniela Meloni ◽  
...  
Keyword(s):  
Heat Flux ◽  
Mediterranean Sea ◽  
Seasonal Cycle ◽  
Heat Fluxes ◽  
Meteorological Variables ◽  
Central Mediterranean ◽  
High Quality ◽  
Central Mediterranean Sea ◽  
In Situ Observations

Air–sea heat fluxes are essential climate variables, required for understanding air–sea interactions, local, regional and global climate, the hydrological cycle and atmospheric and oceanic circulation. In situ measurements of fluxes over the ocean are sparse and model reanalysis and satellite data can provide estimates at different scales. The accuracy of such estimates is therefore essential to obtain a reliable description of the occurring phenomena and changes. In this work, air–sea radiative fluxes derived from the SEVIRI sensor onboard the MSG satellite and from ERA5 reanalysis have been compared to direct high quality measurements performed over a complete annual cycle at the ENEA oceanographic observatory, near the island of Lampedusa in the Central Mediterranean Sea. Our analysis reveals that satellite derived products overestimate in situ direct observations of the downwelling short-wave (bias of 6.1 W/m2) and longwave (bias of 6.6 W/m2) irradiances. ERA5 reanalysis data show a negligible positive bias (+1.0 W/m2) for the shortwave irradiance and a large negative bias (−17 W/m2) for the longwave irradiance with respect to in situ observations. ERA5 meteorological variables, which are needed to calculate the air–sea heat flux using bulk formulae, have been compared with in situ measurements made at the oceanographic observatory. The two meteorological datasets show a very good agreement, with some underestimate of the wind speed by ERA5 for high wind conditions. We investigated the impact of different determinations of heat fluxes on the near surface sea temperature (1 m depth), as determined by calculations with a one-dimensional numerical model, the General Ocean Turbulence Model (GOTM). The sensitivity of the model to the different forcing was measured in terms of differences with respect to in situ temperature measurements made during the period under investigation. All simulations reproduced the true seasonal cycle and all high frequency variabilities. The best results on the overall seasonal cycle were obtained when using meteorological variables in the bulk formulae formulations used by the model itself. The derived overall annual net heat flux values were between +1.6 and 40.4 W/m2, depending on the used dataset. The large variability obtained with different datasets suggests that current determinations of the heat flux components and, in particular, of the longwave irradiance, need to be improved. The ENEA oceanographic observatory provides a complete, long-term, high resolution time series of high quality in situ observations. In the future, more similar sites worldwide will be needed for model and satellite validations and to improve the determination of the air–sea exchange and the understanding of related processes.

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