Association of Tropical Cirrus in the 10–15-km Layer with Deep Convective Sources: An Observational Study Combining Millimeter Radar Data and Satellite-Derived Trajectories

2006 ◽  
Vol 63 (2) ◽  
pp. 480-503 ◽  
Author(s):  
Gerald G. Mace ◽  
Min Deng ◽  
Brian Soden ◽  
Ed Zipser
Keyword(s):  
Deep Convection ◽  
Source Region ◽  
Winter Monsoon ◽  
Boreal Summer ◽  
Doppler Velocity ◽  
Boreal Winter ◽  
Radar Observations ◽  
Back Trajectories ◽  
Cloud Radar ◽  
Cloud Properties

Abstract In this paper, millimeter cloud radar (MMCR) and Geosynchronous Meteorological Satellite (GMS) data are combined to study the properties of tropical cirrus that are common in the 10–15-km layer of the tropical troposphere in the western Pacific. Millimeter cloud radar observations collected by the Atmospheric Radiation Measurement program on the islands of Manus and Nauru in the western and central equatorial Pacific during a 12-month period spanning 1999 and 2000 show differences in cirrus properties: over Manus, where clouds above 7 km are observed 48% of the time, the cirrus are thicker and warmer on average and the radar reflectivity and Doppler velocity are larger; over Nauru clouds above 7 km are observed 23% of time. To explain the differences in cloud properties, the relationship between tropical cirrus and deep convection is examined by combining the radar observations with GMS satellite-derived back trajectories. Using a data record of 1 yr, it is found that 47% of the cirrus observed over Manus can be traced to a deep convective source within the past 12 h while just 16% of the cirrus observed over Nauru appear to have a convective source within the previous 12 h. Of the cirrus that can be traced to deep convection, the evolution of the radar-observed cloud properties is examined as a function of apparent cloud age. The radar Doppler moments and ice water path of the observed cirrus at both sites generally decrease as the cirrus age increase. At Manus, it is found that cirrus during boreal winter typically advect over the site from the southeast from convection associated with the winter monsoon, while during boreal summer, the trajectories are mainly from the northeast. The properties of these two populations of cirrus are found to be different, with the winter cirrus having higher concentrations of smaller particles. Examining statistics of the regional convection using Tropical Rainfall Measuring Mission (TRMM), it is found that the properties of the winter monsoon convection in the cirrus source region are consistent with more intense convection compared to the convection in the summer source region.

Annual Cycle of Southeast Asia—Maritime Continent Rainfall and the Asymmetric Monsoon Transition

2005 ◽  
Vol 18 (2) ◽  
pp. 287-301 ◽  
Author(s):  
C-P. Chang ◽  
Zhuo Wang ◽  
John McBride ◽  
Ching-Hwang Liu
Keyword(s):  
Southeast Asia ◽  
Summer Monsoon ◽  
Annual Cycle ◽  
Asian Summer Monsoon ◽  
Small Region ◽  
Winter Monsoon ◽  
Boreal Summer ◽  
Boreal Winter ◽  
Maritime Continent ◽  
Asian Summer

Abstract In general, the Bay of Bengal, Indochina Peninsula, and Philippines are in the Asian summer monsoon regime while the Maritime Continent experiences a wet monsoon during boreal winter and a dry season during boreal summer. However, the complex distribution of land, sea, and terrain results in significant local variations of the annual cycle. This work uses historical station rainfall data to classify the annual cycles of rainfall over land areas, the TRMM rainfall measurements to identify the monsoon regimes of the four seasons in all of Southeast Asia, and the QuikSCAT winds to study the causes of the variations. The annual cycle is dominated largely by interactions between the complex terrain and a simple annual reversal of the surface monsoonal winds throughout all monsoon regions from the Indian Ocean to the South China Sea and the equatorial western Pacific. The semiannual cycle is comparable in magnitude to the annual cycle over parts of the equatorial landmasses, but only a very small region reflects the twice-yearly crossing of the sun. Most of the semiannual cycle appears to be due to the influence of both the summer and the winter monsoon in the western part of the Maritime Continent where the annual cycle maximum occurs in fall. Analysis of the TRMM data reveals a structure whereby the boreal summer and winter monsoon rainfall regimes intertwine across the equator and both are strongly affected by the wind–terrain interaction. In particular, the boreal winter regime extends far northward along the eastern flanks of the major island groups and landmasses. A hypothesis is presented to explain the asymmetric seasonal march in which the maximum convection follows a gradual southeastward progression path from the Asian summer monsoon to the Asian winter monsoon but experiences a sudden transition in the reverse. The hypothesis is based on the redistribution of mass between land and ocean areas during spring and fall that results from different land–ocean thermal memories. This mass redistribution between the two transition seasons produces sea level patterns leading to asymmetric wind–terrain interactions throughout the region, and a low-level divergence asymmetry in the region that promotes the southward march of maximum convection during boreal fall but opposes the northward march during boreal spring.

scholarly journals Large-scale transport into the Arctic: the roles of the midlatitude jet and the Hadley Cell

2019 ◽  
Vol 19 (8) ◽  
pp. 5511-5528 ◽  
Author(s):  
Huang Yang ◽  
Darryn W. Waugh ◽  
Clara Orbe ◽  
Guang Zeng ◽  
Olaf Morgenstern ◽  
...  
Keyword(s):  
Large Scale ◽  
Climate Model ◽  
Source Region ◽  
Meridional Flow ◽  
Hadley Cell ◽  
The Arctic ◽  
Boreal Summer ◽  
Boreal Winter ◽  
Meridional Transport ◽  
Fixed Lifetime

Abstract. Transport from the Northern Hemisphere (NH) midlatitudes to the Arctic plays a crucial role in determining the abundance of trace gases and aerosols that are important to Arctic climate via impacts on radiation and chemistry. Here we examine this transport using an idealized tracer with a fixed lifetime and predominantly midlatitude land-based sources in models participating in the Chemistry Climate Model Initiative (CCMI). We show that there is a 25 %–45 % difference in the Arctic concentrations of this tracer among the models. This spread is correlated with the spread in the location of the Pacific jet, as well as the spread in the location of the Hadley Cell (HC) edge, which varies consistently with jet latitude. Our results suggest that it is likely that the HC-related zonal-mean meridional transport rather than the jet-related eddy mixing is the major contributor to the inter-model spread in the transport of land-based tracers into the Arctic. Specifically, in models with a more northern jet, the HC generally extends further north and the tracer source region is mostly covered by surface southward flow associated with the lower branch of the HC, resulting in less efficient transport poleward to the Arctic. During boreal summer, there are poleward biases in jet location in free-running models, and these models likely underestimate the rate of transport into the Arctic. Models using specified dynamics do not have biases in the jet location, but do have biases in the surface meridional flow, which may result in differences in transport into the Arctic. In addition to the land-based tracer, the midlatitude-to-Arctic transport is further examined by another idealized tracer with zonally uniform sources. With equal sources from both land and ocean, the inter-model spread of this zonally uniform tracer is more related to variations in parameterized convection over oceans rather than variations in HC extent, particularly during boreal winter. This suggests that transport of land-based and oceanic tracers or aerosols towards the Arctic differs in pathways and therefore their corresponding inter-model variabilities result from different physical processes.

Tropical Cold-Point Tropopause: Climatology, Seasonal Cycle, and Intraseasonal Variability Derived from COSMIC GPS Radio Occultation Measurements

2012 ◽  
Vol 25 (15) ◽  
pp. 5343-5360 ◽  
Author(s):  
Joowan Kim ◽  
Seok-Woo Son
Keyword(s):  
Seasonal Cycle ◽  
Radio Occultation ◽  
Deep Convection ◽  
Intraseasonal Variability ◽  
Kelvin Waves ◽  
Boreal Summer ◽  
Boreal Winter ◽  
Frequency Spectra ◽  
Gps Radio Occultation ◽  
Cold Point

Abstract The finescale structure of the tropical cold-point tropopause (CPT) is examined using high-resolution temperature profiles derived from Constellation Observing System for Meteorology, Ionosphere and Climate (COSMIC) global positioning system (GPS) radio occultation measurements for 4 yr from September 2006 to August 2010. The climatology, seasonal cycle, and intraseasonal variability are analyzed for three CPT properties: temperature (T-CPT), pressure (P-CPT), and sharpness (S-CPT). Their relationships with tropospheric and stratospheric processes are also discussed. The climatological P-CPT is largely homogeneous in the deep tropics, whereas T-CPT and S-CPT exhibit local minima and maxima, respectively, at the equator in the vicinity of deep convection regions. All three CPT properties, however, show coherent seasonal cycle in the tropics; the CPT is colder, higher (lower in pressure), and sharper during boreal winter than during boreal summer. This seasonality is consistent with the seasonal cycle of tropical upwelling, which is largely driven by stratospheric and near-tropopause processes, although the amplitude of the seasonal cycle of T-CPT and S-CPT is modulated by tropospheric circulations. On intraseasonal time scales, P-CPT and T-CPT exhibit homogeneous variability in the deep tropics, whereas S-CPT shows pronounced local variability and seasonality. The wavenumber–frequency spectra reveal that intraseasonal variability of CPT properties is primarily controlled by Kelvin waves, with a nonnegligible contribution by Madden–Julian oscillation convection. The Kelvin waves, which are excited by deep convection but often propagate along the equator freely, explain the homogeneous P-CPT and T-CPT variabilities. On the other hand, the vertically tilted dipole of temperature anomalies, which is associated with convectively coupled equatorial waves, determines the local structure and seasonality of S-CPT variability.

scholarly journals Potential of Higher-Order Moments and Slopes of the Radar Doppler Spectrum for Retrieving Microphysical and Kinematic Properties of Arctic Ice Clouds

2017 ◽  
Vol 56 (2) ◽  
pp. 263-282 ◽  
Author(s):  
Maximilian Maahn ◽  
Ulrich Löhnert
Keyword(s):  
Higher Order ◽  
Doppler Spectrum ◽  
Doppler Velocity ◽  
State Variables ◽  
Higher Order Moments ◽  
Radar Observations ◽  
Additional Information ◽  
Cloud Radar ◽  
Mass Size ◽  
Size Relation

AbstractRetrievals of ice-cloud properties from cloud-radar observations are challenging because the retrieval methods are typically underdetermined. Here, the authors investigate whether additional information can be obtained from higher-order moments and the slopes of the radar Doppler spectrum such as skewness and kurtosis as well as the slopes of the Doppler peak. To estimate quantitatively the additional information content, a generalized Bayesian retrieval framework that is based on optimal estimation is developed. Real and synthetic cloud-radar observations of the Indirect and Semi-Direct Aerosol Campaign (ISDAC) dataset obtained around Barrow, Alaska, are used in this study. The state vector consists of the microphysical (particle-size distribution, mass–size relation, and cross section–area relation) and kinematic (vertical wind and turbulence) quantities required to forward model the moments and slopes of the radar Doppler spectrum. It is found that, for a single radar frequency, more information can be retrieved when including higher-order moments and slopes than when using only reflectivity and mean Doppler velocity but two radar frequencies. When using all moments and slopes with two or even three frequencies, the uncertainties of all state variables, including the mass–size relation, can be considerably reduced with respect to the prior knowledge.

scholarly journals The Characterization of Ice Cloud Properties from Doppler Radar Measurements

2007 ◽  
Vol 46 (10) ◽  
pp. 1682-1698 ◽  
Author(s):  
Julien Delanoë ◽  
A. Protat ◽  
D. Bouniol ◽  
Andrew Heymsfield ◽  
Aaron Bansemer ◽  
...  
Keyword(s):  
Water Content ◽  
Weather Prediction ◽  
Doppler Velocity ◽  
Fall Velocity ◽  
Ice Cloud ◽  
Cloud Radar ◽  
Cloud Properties ◽  
Ice Water Content ◽  
Radar Measurements ◽  
Ice Water

Abstract The paper describes an original method that is complementary to the radar–lidar algorithm method to characterize ice cloud properties. The method makes use of two measurements from a Doppler cloud radar (35 or 95 GHz), namely, the radar reflectivity and the Doppler velocity, to recover the effective radius of crystals, the terminal fall velocity of hydrometeors, the ice water content, and the visible extinction from which the optical depth can be estimated. This radar method relies on the concept of scaling the ice particle size distribution. An error analysis using an extensive in situ airborne microphysical database shows that the expected errors on ice water content and extinction are around 30%–40% and 60%, respectively, including both a calibration error and a bias on the terminal fall velocity of the particles, which all translate into errors in the retrieval of the density–diameter and area–diameter relationships. Comparisons with the radar–lidar method in areas sampled by the two instruments also demonstrate the accuracy of this new method for retrieval of the cloud properties, with a roughly unbiased estimate of all cloud properties with respect to the radar–lidar method. This method is being systematically applied to the cloud radar measurements collected over the three-instrumented sites of the European Cloudnet project to validate the representation of ice clouds in numerical weather prediction models and to build a cloud climatology.

scholarly journals Using artificial neural networks to predict riming from Doppler cloud radar observations

2021 ◽  
Author(s):  
Teresa Vogl ◽  
Maximilian Maahn ◽  
Stefan Kneifel ◽  
Willi Schimmel ◽  
Dmitri Moisseev ◽  
...  
Keyword(s):  
Neural Networks ◽  
Artificial Neural Networks ◽  
Doppler Velocity ◽  
Data Sets ◽  
Radar Observations ◽  
Cloud Radar ◽  
Target Values ◽  
In Situ Observations ◽  
Artificial Neural

Abstract. Riming, i.e. the accretion and freezing of SLW on ice particles in mixed-phase clouds, is an important pathway for precipitation formation. Detecting and quantifying riming using ground-based cloud radar observations is of great interest, however, approaches based on measurements of the mean Doppler velocity (MDV) are unfeasible in convective and orographically influenced cloud systems. Here, we show how artificial neural networks (ANNs) can be used to predict riming using ground-based zenith-pointing cloud radar variables as input features. ANNs are a versatile means to extract relations from labeled data sets, which contain input features along with the expected target values. Training data are extracted from a data set acquired during winter 2014 in Finland, containing both Ka-band cloud radar and in-situ observations of snowfall. We focus on two configurations of input variables: ANN #1 uses the equivalent radar reflectivity factor (Ze), MDV, the width from left to right edge of the spectrum above the noise floor (spectrum edge width; SEW), and the skewness as input features. ANN #2 only uses Ze, SEW and skewness. The application of these two ANN configurations to case studies from different data sets demonstrates that both are able to predict strong riming (riming index = 1) and yield low values (riming index ≤ 0.4) for unrimed snow. In general, the predictions of ANN #1 and ANN #2 are very similar, advocating the capability to predict riming without the use of MDV. It is demonstrated that both ANN setups are able to generalize to W-band radar data. The predictions of both ANNs for a wintertime convective cloud fit coinciding in-situ observations extremely well, suggesting the possibility to predict riming even within convective systems. Application of ANN #2 to an orographic case yields high riming index values coinciding with observations of solid graupel particles at the ground.

scholarly journals Long-Term Statistics of Riming in Nonconvective Clouds Derived from Ground-Based Doppler Cloud Radar Observations

2020 ◽  
Vol 77 (10) ◽  
pp. 3495-3508 ◽  
Author(s):  
Stefan Kneifel ◽  
Dmitri Moisseev
Keyword(s):  
Temperature Dependence ◽  
Supercooled Liquid ◽  
Terminal Velocity ◽  
Climatic Conditions ◽  
Doppler Velocity ◽  
Radar Observations ◽  
Cloud Radar ◽  
Similar Temperature Dependence ◽  
Different Seasons ◽  
Strong Relation

AbstractRiming is an efficient process of converting liquid cloud water into ice and plays an important role in the formation of precipitation in cold clouds. Due to the rapid increase in ice particle mass, riming enhances the particle’s terminal velocity, which can be detected by ground-based vertically pointing cloud radars if the effect of vertical air motions can be sufficiently mitigated. In our study, we first revisit a previously published approach to relate the radar mean Doppler velocity (MDV) to rime mass fraction (FR) using a large ground-based in situ dataset. This relation is then applied to multiyear datasets of cloud radar observations collected at four European sites covering polluted central European, clean maritime, and Arctic climatic conditions. We find that riming occurs in 1%–8% of the nonconvective ice containing clouds with median FR between 0.5 and 0.6. Both the frequency of riming and FR reveal relatively small variations for different seasons. In contrast to previous studies, which suggested enhanced riming for clean environments, our statistics indicate the opposite; however, the differences between the locations are overall small. We find a very strong relation between the frequency of riming and temperature. While riming is rare at temperatures lower than −12°C, it strongly increases toward 0°C. Previous studies found a very similar temperature dependence for the amount and droplet size of supercooled liquid water, which might be closely connected to the riming signature found in this study. In contrast to riming frequency, we find almost no temperature dependence for FR.

scholarly journals Atlantic Niño/Niña Prediction Skills in NMME Models

Atmosphere ◽  
2021 ◽  
Vol 12 (7) ◽  
pp. 803
Author(s):  
Ran Wang ◽  
Lin Chen ◽  
Tim Li ◽  
Jing-Jia Luo
Keyword(s):  
Sea Surface ◽  
Prediction Skill ◽  
Boreal Summer ◽  
Boreal Winter ◽  
Equatorial Atlantic ◽  
Multimodel Ensemble ◽  
Spring Predictability Barrier ◽  
Anomaly Correlation Coefficient ◽  
Earth’S Climate ◽  
Atlantic Niño

The Atlantic Niño/Niña, one of the dominant interannual variability in the equatorial Atlantic, exerts prominent influence on the Earth’s climate, but its prediction skill shown previously was unsatisfactory and limited to two to three months. By diagnosing the recently released North American Multimodel Ensemble (NMME) models, we find that the Atlantic Niño/Niña prediction skills are improved, with the multi-model ensemble (MME) reaching five months. The prediction skills are season-dependent. Specifically, they show a marked dip in boreal spring, suggesting that the Atlantic Niño/Niña prediction suffers a “spring predictability barrier” like ENSO. The prediction skill is higher for Atlantic Niña than for Atlantic Niño, and better in the developing phase than in the decaying phase. The amplitude bias of the Atlantic Niño/Niña is primarily attributed to the amplitude bias in the annual cycle of the equatorial sea surface temperature (SST). The anomaly correlation coefficient scores of the Atlantic Niño/Niña, to a large extent, depend on the prediction skill of the Niño3.4 index in the preceding boreal winter, implying that the precedent ENSO may greatly affect the development of Atlantic Niño/Niña in the following boreal summer.

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