Exploring the Diabatic Role of Ice Microphysical Processes in Two North Atlantic Summer Cyclones

2016 ◽  
Vol 144 (4) ◽  
pp. 1249-1272 ◽  
Author(s):  
C. Dearden ◽  
G. Vaughan ◽  
T. Tsai ◽  
J.-P. Chen
Keyword(s):  
Crystal Habit ◽  
Ice Crystal ◽  
Heating And Cooling ◽  
First Case ◽  
Storm Evolution ◽  
In Situ Observations ◽  
Microphysical Processes ◽  
Ice Production ◽  
The Impact

Abstract Numerical simulations are performed with the Weather Research and Forecasting Model to elucidate the diabatic effects of ice phase microphysical processes on the dynamics of two slow-moving summer cyclones that affected the United Kingdom during the summer of 2012. The first case is representative of a typical midlatitude storm for the time of year, while the second case is unusually deep. Sensitivity tests are performed with 5-km horizontal grid spacing and at lead times between 1 and 2 days using three different microphysics schemes, one of which is a new scheme whose development was informed by the latest in situ observations of midlatitude weather systems. The effects of latent heating and cooling associated with deposition growth, sublimation, and melting of ice are assessed in terms of the impact on both the synoptic scale and the frontal scale. The results show that, of these diabatic processes, deposition growth was the most important in both cases, affecting the depth and position of each of the low pressure systems and influencing the spatial distribution of the frontal precipitation. Cooling associated with sublimation and melting also played a role in determining the cyclone depth, but mainly in the more intense cyclone case. The effects of ice crystal habit and secondary ice production are also explored in the simulations, based on insight from in situ observations. However in these two cases, the ability to predict changes in crystal habit did not significantly impact the storm evolution, and the authors found no obvious need to parameterize secondary ice crystal production at the model resolutions considered.

scholarly journals A comparison between polynya area and associated ice production with mooring-based measurements of temperature, salinity and currents in the southwestern Ross Sea, Antarctica

2011 ◽  
Vol 52 (57) ◽  
pp. 291-300 ◽  
Author(s):  
Stefan Kern ◽  
Stefano Aliani
Keyword(s):  
Ross Sea ◽  
Time Lag ◽  
Ice Formation ◽  
Terra Nova Bay ◽  
In Situ Observations ◽  
Satellite Microwave ◽  
Terra Nova ◽  
Ice Production ◽  
The Impact

AbstractWintertime (April–September) area estimates of the Terra Nova Bay polynya (TNBP), Antarctica, based on satellite microwave radiometry are compared with in situ observations of water salinity, temperature and currents at a mooring in Terra Nova Bay in 1996 and 1997. In 1996, polynya area anomalies and associated anomalies in polynya ice production are significantly correlated with salinity anomalies at the mooring. Salinity anomalies lag area and/or ice production anomalies by about 3 days. Up to 50% of the variability in the salinity at the mooring position can be explained by area and/or ice production anomalies in the TNBP for April–September 1996. This value increases to about 70% when considering shorter periods like April–June or May–July, but reduces to 30% later, for example July–September, together with a slight increase in time lag. In 1997, correlations are smaller, less significant and occur at a different time lag. Analysis of ocean currents at the mooring suggests that in 1996 conditions were more favourable than in 1997 for observing the impact of descending plumes of salt-enriched water formed in the polynya during ice formation on the water masses at the mooring depth.

A Comprehensive Habit Diagram for Atmospheric Ice Crystals: Confirmation from the Laboratory, AIRS II, and Other Field Studies

2009 ◽  
Vol 66 (9) ◽  
pp. 2888-2899 ◽  
Author(s):  
Matthew P. Bailey ◽  
John Hallett
Keyword(s):  
Field Studies ◽  
Crystal Habit ◽  
Ice Crystal ◽  
Comprehensive Description ◽  
Cloud Particle ◽  
In Situ Observations ◽  
Ice Crystal Habits ◽  
Habit Modification ◽  
Recent Laboratory

Abstract Recent laboratory experiments and in situ observations have produced results in broad agreement with respect to ice crystal habits in the atmosphere. These studies reveal that the ice crystal habit at −20°C is platelike, extending to −40°C, and not columnar as indicated in many habit diagrams found in atmospheric science journals and texts. These diagrams were typically derived decades ago from laboratory studies, some with inherent habit bias, or from combinations of laboratory and in situ observations at the ground, observations that often did not account for habit modification by precipitation from overlying clouds of varying temperatures. Habit predictions from these diagrams often disagreed with in situ observations at temperatures below −20°C. More recent laboratory and in situ studies have achieved a consensus on atmospheric ice crystal habits that differs from the traditional habit diagrams. These newer results can now be combined to give a comprehensive description of ice crystal habits for the atmosphere as a function of temperature and ice supersaturation for temperatures from 0° to −70°C, a description dominated by irregular and imperfect crystals. Cloud particle imager (CPI) habit observations made during the Second Alliance Icing Research Study (AIRS II) and elsewhere corroborate this comprehensive habit description, and a new habit diagram is derived from these results.

scholarly journals The impact of near-surface soil moisture assimilation at subseasonal, seasonal, and inter-annual timescales

2015 ◽  
Vol 19 (12) ◽  
pp. 4831-4844 ◽  
Author(s):  
C. Draper ◽  
R. Reichle
Keyword(s):  
Soil Moisture ◽  
Data Assimilation ◽  
Surface Soil ◽  
Root Zone ◽  
Surface Model ◽  
Surface Soil Moisture ◽  
Near Surface ◽  
In Situ Observations ◽  
The Impact

Abstract. A 9 year record of Advanced Microwave Scanning Radiometer – Earth Observing System (AMSR-E) soil moisture retrievals are assimilated into the Catchment land surface model at four locations in the US. The assimilation is evaluated using the unbiased mean square error (ubMSE) relative to watershed-scale in situ observations, with the ubMSE separated into contributions from the subseasonal (SMshort), mean seasonal (SMseas), and inter-annual (SMlong) soil moisture dynamics. For near-surface soil moisture, the average ubMSE for Catchment without assimilation was (1.8 × 10−3 m3 m−3)2, of which 19 % was in SMlong, 26 % in SMseas, and 55 % in SMshort. The AMSR-E assimilation significantly reduced the total ubMSE at every site, with an average reduction of 33 %. Of this ubMSE reduction, 37 % occurred in SMlong, 24 % in SMseas, and 38 % in SMshort. For root-zone soil moisture, in situ observations were available at one site only, and the near-surface and root-zone results were very similar at this site. These results suggest that, in addition to the well-reported improvements in SMshort, assimilating a sufficiently long soil moisture data record can also improve the model representation of important long-term events, such as droughts. The improved agreement between the modeled and in situ SMseas is harder to interpret, given that mean seasonal cycle errors are systematic, and systematic errors are not typically targeted by (bias-blind) data assimilation. Finally, the use of 1-year subsets of the AMSR-E and Catchment soil moisture for estimating the observation-bias correction (rescaling) parameters is investigated. It is concluded that when only 1 year of data are available, the associated uncertainty in the rescaling parameters should not greatly reduce the average benefit gained from data assimilation, although locally and in extreme years there is a risk of increased errors.

scholarly journals What Is the Impact of Additional Tropical Observations on a Modern Data Assimilation System?

2019 ◽  
Vol 147 (7) ◽  
pp. 2433-2449
Author(s):  
Laura C. Slivinski ◽  
Gilbert P. Compo ◽  
Jeffrey S. Whitaker ◽  
Prashant D. Sardeshmukh ◽  
Jih-Wang A. Wang ◽  
...  
Keyword(s):  
El Niño ◽  
Large Scale ◽  
El Nino ◽  
Mean Square ◽  
Observational Network ◽  
In Situ Observations ◽  
The Mean ◽  
The Impact ◽  
Assimilation System

Abstract Given the network of satellite and aircraft observations around the globe, do additional in situ observations impact analyses within a global forecast system? Despite the dense observational network at many levels in the tropical troposphere, assimilating additional sounding observations taken in the eastern tropical Pacific Ocean during the 2016 El Niño Rapid Response (ENRR) locally improves wind, temperature, and humidity 6-h forecasts using a modern assimilation system. Fields from a 50-km reanalysis that assimilates all available observations, including those taken during the ENRR, are compared with those from an otherwise-identical reanalysis that denies all ENRR observations. These observations reveal a bias in the 200-hPa divergence of the assimilating model during a strong El Niño. While the existing observational network partially corrects this bias, the ENRR observations provide a stronger mean correction in the analysis. Significant improvements in the mean-square fit of the first-guess fields to the assimilated ENRR observations demonstrate that they are valuable within the existing network. The effects of the ENRR observations are pronounced in levels of the troposphere that are sparsely observed, particularly 500–800 hPa. Assimilating ENRR observations has mixed effects on the mean-square difference with nearby non-ENRR observations. Using a similar system but with a higher-resolution forecast model yields comparable results to the lower-resolution system. These findings imply a limited improvement in large-scale forecast variability from additional in situ observations, but significant improvements in local 6-h forecasts.

scholarly journals Evolution of ice crystal regions on the microscale based on in situ observations

2013 ◽  
Vol 40 (13) ◽  
pp. 3473-3478 ◽  
Author(s):  
Minghui Diao ◽  
Mark A. Zondlo ◽  
Andrew J. Heymsfield ◽  
Stuart P. Beaton ◽  
David C. Rogers
Keyword(s):  
Ice Crystal ◽  
In Situ Observations

scholarly journals The effect of secondary ice production parameterization on the simulation of a cold frontal rainband

2018 ◽  
Vol 18 (22) ◽  
pp. 16461-16480 ◽  
Author(s):  
Sylvia C. Sullivan ◽  
Christian Barthlott ◽  
Jonathan Crosier ◽  
Ilya Zhukov ◽  
Athanasios Nenes ◽  
...  
Keyword(s):  
Secondary Production ◽  
Large Scale ◽  
Mesoscale Model ◽  
Ice Crystal ◽  
Surface Precipitation ◽  
Earth’S Climate ◽  
Ice Production ◽  
Cloud Ice ◽  
Droplet Shattering ◽  
The Impact

Abstract. Secondary ice production via processes like rime splintering, frozen droplet shattering, and breakup upon ice hydrometeor collision have been proposed to explain discrepancies between in-cloud ice crystal and ice-nucleating particle numbers. To understand the impact of this additional ice crystal generation on surface precipitation, we present one of the first studies to implement frozen droplet shattering and ice–ice collisional breakup parameterizations in a mesoscale model. We simulate a cold frontal rainband from the Aerosol Properties, PRocesses, And InfluenceS on the Earth's Climate campaign and investigate the impact of the new parameterizations on the simulated ice crystal number concentrations (ICNC) and precipitation. Near the convective regions of the rainband, contributions to ICNC can be as large from secondary production as from primary nucleation, but ICNCs greater than 50 L−1 remain underestimated by the model. The addition of the secondary production parameterizations also clearly intensifies the differences in both accumulated precipitation and precipitation rate between the convective towers and non-convective gap regions. We suggest, then, that secondary ice production parameterizations be included in large-scale models on the basis of large hydrometeor concentration and convective activity criteria.

scholarly journals How essential are Argo observations to constrain a global ocean data assimilation system?

2015 ◽  
Vol 12 (3) ◽  
pp. 1145-1186 ◽  
Author(s):  
V. Turpin ◽  
E. Remy ◽  
P. Y. Le Traon
Keyword(s):  
Data Assimilation ◽  
Forecast Error ◽  
Global Ocean ◽  
Altimeter Data ◽  
Western Boundary ◽  
Argo Data ◽  
Ocean Data Assimilation ◽  
In Situ Observations ◽  
The Impact

Abstract. Observing System Experiments (OSEs) are carried out over a one-year period to quantify the impact of Argo observations on the Mercator-Ocean 1/4° global ocean analysis and forecasting system. The reference simulation assimilates sea surface temperature (SST), SSALTO/DUACS altimeter data and Argo and other in situ observations from the Coriolis data center. Two other simulations are carried out where all Argo and half of Argo data sets are withheld. Assimilating Argo observations has a significant impact on analyzed and forecast temperature and salinity fields at different depths. Without Argo data assimilation, large errors occur in analyzed fields as estimated from the differences when compared with in situ observations. For example, in the 0–300 m layer RMS differences between analyzed fields and observations reach 0.25 psu and 1.25 °C in the western boundary currents and 0.1 psu and 0.75 °C in the open ocean. The impact of the Argo data in reducing observation-model forecast error is also significant from the surface down to a depth of 2000 m. Differences between independent observations and forecast fields are thus reduced by 20 % in the upper layers and by up to 40 % at a depth of 2000 m when Argo data are assimilated. At depth, the most impacted regions in the global ocean are the Mediterranean outflow and the Labrador Sea. A significant degradation can be observed when only half of the data are assimilated. All Argo observations thus matter, even with a 1/4° model resolution. The main conclusion is that the performance of global data assimilation systems is heavily dependent on the availability of Argo data.

Measuring snowfall properties with the Video In Situ Snowfall Sensor during MOSAiC

2021 ◽  
Author(s):  
Maximilian Maahn ◽  
Martin Radenz ◽  
Christopher Cox ◽  
Michael Gallagher ◽  
Jennifer Hutchings ◽  
...  
Keyword(s):  
Optical Observations ◽  
Cloud Droplets ◽  
Cloud Dynamics ◽  
First Results ◽  
High Resolution Images ◽  
Large Measurement ◽  
Microphysical Processes ◽  
Moisture Conditions ◽  
The Impact

<p>Snow is an essential component of the climate system impacting surface albedo, glaciers, sea ice, freshwater storage, and cloud lifetime. Even though we do not know the exact pathways through which ice, liquid, cloud dynamics, and aerosols are interacting in clouds while forming snowfall, the involved processes can be identified by their fingerprints on snow particles. The general shape of individual crystals (dendritic, columns, plates) depends on the temperature and moisture conditions during growth from water vapor deposition. Aggregation can be identified when multiple individual particles are combined into a snowflake. Riming describes the freezing of cloud droplets onto the snow particle and can eventually form graupel. In order to exploit these unique fingerprints of cloud microphysical processes, optical observations are required.</p><p>The Video In Situ Snowfall Sensor (VISSS) was specifically developed for the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) campaign to determine particle shape and particle size distributions. Different to other sensors, the VISSS minimizes uncertainties by combining two-dimensional high-resolution images with a large measurement volume and a design limiting the impact of wind. Here, we show first results from the MOSAiC campaign and present examples for synergy effects that can be obtained by combining radar and VISSS measurements.</p>

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