Supplementary material to "Lagrangian formation pathways of moist anomalies in the trade-wind region during the dry season: two case studies from EUREC<sup>4</sup>A"

Author(s):  
Leonie Villiger ◽  
Heini Wernli ◽  
Maxi Boettcher ◽  
Martin Hagen ◽  
Franziska Aemisegger
2020 ◽  
Author(s):  
Heike Konow ◽  
Marcus Klingebiel ◽  
Felix Ament

&lt;p&gt;&lt;span&gt;Trade wind cumulus clouds are the predominant cloud type over the tropical Atlantic east of the island of Barbados. Parameters describing their macroscopic shape can help characterizing and comparing general features of clouds. This characterizing will indirectly help to constrain estimates of climate sensitivity, because models with different structures of trade wind cumuli feature different response to increased CO2 contents.&lt;/span&gt;&lt;/p&gt;&lt;p&gt;&lt;span&gt;Two aircraft campaigns with the HALO (High Altitude LOng range) aircraft took place in the recent past in this region: NARVAL-South (Next-generation Aircraft Remote-Sensing for VALidation studies) in December 2013, during the dry season, and NARVAL2 in August 2016, during the wet season. During these two campaigns, a wide range of cloud regimes from shallow to deep convection were sampled. This past observations are now extended with observations from this year&amp;#8217;s measurement campaign EUREC&lt;sup&gt;4&lt;/sup&gt;A, again during the dry season. EUREC&lt;sup&gt;4&lt;/sup&gt;A is endorsed as WCRP capstone experiment and the synergy of four research aircraft, four research vessels and numerous additional observations will provide comprehensive characterizations of trade wind clouds and their environment.&lt;/span&gt;&lt;/p&gt;&lt;p&gt;&lt;span&gt;Part of the NARVAL payload on HALO is a 35 GHz cloud radar, which has been deployed on HALO on several missions since 2013. These cloud radar measurements are used to segment individual clouds entities by applying connected component analysis to the radar cloud mask. From these segmented individual clouds, macrophysical parameters are derived to characterize each individual cloud. &lt;/span&gt;&lt;/p&gt;&lt;p&gt;&lt;span&gt;This presentation will give an overview of the cloud macrophysics observed from HALO during EUREC&lt;sup&gt;4&lt;/sup&gt;A. Typical macrophysical parameters, i.e. cloud depth, cloud length, cloud fraction, are analyzed. We will relate these to observations from past campaigns and assess the representativeness of EUREC&lt;sup&gt;4&lt;/sup&gt;A. As special focus of the EUREC&lt;sup&gt;4&lt;/sup&gt;A campaign, measurements will be performed during different times of the day to detect diurnal cycles. Macrophysical parameters can be used to characterize changes over the day and cloud scenes of similar clouds types can be identified.&lt;/span&gt;&lt;/p&gt;


2020 ◽  
Author(s):  
Marcus Klingebiel ◽  
Heike Konow ◽  
Bjorn Stevens

&lt;p&gt;Mass flux is a key parameter to represent shallow convection in global circulation models. To estimate the shallow convective mass flux as accurately as possible, observations of this parameter are necessary. Prior studies from Ghate et al. (2011) and Lamer et al. (2015) used Doppler radar measurements over a few months to identify a typical shallow convective mass flux profile based on cloud fraction and vertical velocity. In this study, we extend their observations by using long term remote sensing measurements at the Barbados Cloud Observatory (13&amp;#176; 09&amp;#8217; N, 59&amp;#176; 25&amp;#8217; W) over a time period of 30 months and check a hypothesis by Grant (2001), who proposed that the cloud base mass flux is just proportional to the sub-cloud convective velocity scale. Therefore, we analyze Doppler radar and Doppler lidar measurements to identify the variation of the vertical velocity in the cloud and sub-cloud layer, respectively. Furthermore, we show that the in-cloud mass flux is mainly influenced by the cloud fraction and provide a linear equation, which can be used to roughly calculate the mass flux in the trade wind region based on the cloud fraction.&lt;/p&gt;&lt;p&gt;&amp;#160;&lt;/p&gt;&lt;p&gt;References:&lt;br&gt;Ghate,&amp;#160; V.&amp;#160; P.,&amp;#160; M.&amp;#160; A.&amp;#160; Miller,&amp;#160; and&amp;#160; L.&amp;#160; DiPretore,&amp;#160; 2011:&amp;#160;&amp;#160; Vertical&amp;#160; velocity structure of marine boundary layer trade wind cumulus clouds. Journal&amp;#160; of&amp;#160; Geophysical&amp;#160; Research: Atmospheres, 116&amp;#160; (D16), doi:10.1029/2010JD015344.&lt;/p&gt;&lt;p&gt;Grant,&amp;#160; A.&amp;#160; L.&amp;#160; M.,&amp;#160; 2001:&amp;#160;&amp;#160; Cloud-base&amp;#160; fluxes&amp;#160; in&amp;#160; the&amp;#160; cumulus-capped boundary layer. Quarterly Journal of the Royal Meteorological Society, 127 (572), 407&amp;#8211;421, doi:10.1002/qj.49712757209.&lt;/p&gt;&lt;p&gt;Lamer, K., P. Kollias, and L. Nuijens, 2015:&amp;#160; Observations of the variability&amp;#160; of&amp;#160; shallow&amp;#160; trade&amp;#160; wind&amp;#160; cumulus&amp;#160; cloudiness&amp;#160; and&amp;#160; mass&amp;#160; flux. Journal of Geophysical Research: Atmospheres, 120&amp;#160; (12), 6161&amp;#8211;6178, doi:10.1002/2014JD022950.&lt;/p&gt;


2008 ◽  
Vol 21 (3) ◽  
pp. 495-516 ◽  
Author(s):  
José A. Marengo ◽  
Carlos A. Nobre ◽  
Javier Tomasella ◽  
Marcos D. Oyama ◽  
Gilvan Sampaio de Oliveira ◽  
...  

Abstract In 2005, large sections of southwestern Amazonia experienced one of the most intense droughts of the last hundred years. The drought severely affected human population along the main channel of the Amazon River and its western and southwestern tributaries, the Solimões (also known as the Amazon River in the other Amazon countries) and the Madeira Rivers, respectively. The river levels fell to historic low levels and navigation along these rivers had to be suspended. The drought did not affect central or eastern Amazonia, a pattern different from the El Niño–related droughts in 1926, 1983, and 1998. The choice of rainfall data used influenced the detection of the drought. While most datasets (station or gridded data) showed negative departures from mean rainfall, one dataset exhibited above-normal rainfall in western Amazonia. The causes of the drought were not related to El Niño but to (i) the anomalously warm tropical North Atlantic, (ii) the reduced intensity in northeast trade wind moisture transport into southern Amazonia during the peak summertime season, and (iii) the weakened upward motion over this section of Amazonia, resulting in reduced convective development and rainfall. The drought conditions were intensified during the dry season into September 2005 when humidity was lower than normal and air temperatures were 3°–5°C warmer than normal. Because of the extended dry season in the region, forest fires affected part of southwestern Amazonia. Rains returned in October 2005 and generated flooding after February 2006.


2016 ◽  
Vol 75 (s1) ◽  
Author(s):  
Fernando W. Bernal-Brooks ◽  
José J. Sánchez Chávez ◽  
Luis Bravo Inclán ◽  
Rubén Hernández Morales ◽  
Ana K. Martínez Cano ◽  
...  

<p>This paper reports on the algal growth-limiting nutrients of five lakes located on Mexico’s Mesa Central - a topic poorly known in the regional limnology of Mexico. The five case studies involved three contiguous watersheds of Michoacán State and provided a trophic state variation from mesotrophic to hypereutrophic; the case studies included Lakes Zirahuén, Pátzcuaro, Teremendo, Cuitzeo and the Cointzio Reservoir. The fieldwork involved the collection of physical and chemical data (including nutrients) from each case study during the dry and rainy seasons of 2010. Additionally, water samples (1 L) were obtained and filtered (0.45 µm) in the laboratory to keep the nutrient content available for bioassays. The chemical analyses suggested a phosphorus (P) limitation in the Cointzio Reservoir, Lake Teremendo and Lake Zirahuén relative to an N:P&gt;16:1. There was a nitrogen (N) limitation at three sampling stations of Lake Pátzcuaro, with an N:P&lt;16:1. As result of the bioassays conducted in July 2012, the Cointzio Reservoir and Lake Teremendo appeared to be P-limited and Lake Pátzcuaro appeared to be N-limited at three sampling stations. Lake Zirahuén showed seasonal variation, with an N limitation during the dry season and a P limitation during the wet season. Those cases with similar results from both methods confirmed the limiting nutrient identification. Lake Cuitzeo, Lake Zirahuén (dry season), and the shallowest sampling station in Lake Pátzcuaro produced unclear results because of divergent outcomes. In terms of the algal growth potential, the Cointzio Reservoir remained unaltered from one season to the next. However, for most of the lakes (with the exception of Lake Pátzcuaro sites 2 and 4), the rainy season provided a dilution effect. Effective lake management depends on a clear recognition of such elements that are in control of the aquatic productivity. In the area of Michoacán, both N and P may act as limiting nutrients.</p>


2017 ◽  
Vol 17 (3) ◽  
pp. 2373-2392 ◽  
Author(s):  
Madeleine Sánchez Gácita ◽  
Karla M. Longo ◽  
Julliana L. M. Freire ◽  
Saulo R. Freitas ◽  
Scot T. Martin

Abstract. Smoke aerosols prevail throughout Amazonia because of widespread biomass burning during the dry season, and external mixing, low variability in the particle size distribution and low particle hygroscopicity are typical. There can be profound effects on cloud properties. This study uses an adiabatic cloud model to simulate the activation of smoke particles as cloud condensation nuclei (CCN) for three hypothetical case studies, chosen as to resemble biomass burning aerosol observations in Amazonia. The relative importance of variability in hygroscopicity, mixing state, and activation kinetics for the activated fraction and maximum supersaturation is assessed. For a population with κp = 0.04, an overestimation of the cloud droplet number concentration Nd for the three selected case studies between 22.4 ± 1.4 and 54.3 ± 3.7 % was obtained when assuming a hygroscopicity parameter κp = 0.20. Assuming internal mixing of the aerosol population led to overestimations of up to 20 % of Nd when a group of particles with medium hygroscopicity was present in the externally mixed population cases. However, the overestimations were below 10 % for external mixtures between very low and low-hygroscopicity particles, as seems to be the case for Amazon smoke particles. Kinetic limitations were significant for medium- and high-hygroscopicity particles, and much lower for very low and low-hygroscopicity particles. When particles were assumed to be at equilibrium and to respond instantly to changes in the air parcel supersaturation, the overestimation of the droplet concentration was up to  ∼  100 % in internally mixed populations, and up to  ∼  250 % in externally mixed ones, being larger for the higher values of hygroscopicity. In addition, a perceptible delay between the times when maximum supersaturation and maximum aerosol activated fraction are reached was noticed and, for aerosol populations with effective hygroscopicity κpeff higher than a certain threshold value, the delay in particle activation was such that no particles were activated at the time of maximum supersaturation. Considering internally mixed populations, for an updraft velocity W = 0.5 m s−1 this threshold of no activation varied between κpeff = 0.35 and κpeff = 0.5 for the different case studies. However, for low hygroscopicity, kinetic limitations played a weaker role for CCN activation of particles, even when taking into account the large aerosol mass and number concentrations. For the very low range of hygroscopicities, the overestimation of the droplet concentration due to the equilibrium assumption was lowest and the delay between the times when maximum supersaturation and maximum activated fraction were reached was greatly reduced or no longer observed (depending on the case study). These findings on uncertainties and sensitivities provide guidance on appropriate simplifications that can be used for modeling of smoke aerosols within general circulation models. The use of medium values of hygroscopicity representative of smoke aerosols for other biomass burning regions on Earth can lead to significant errors compared to the use of low hygroscopicity for Amazonia (between 0.05 and 0.13, according to available observations). Also in this region, consideration of the biomass burning population as internally mixed will lead to small errors in the droplet concentration, while significantly increasing the computational burden. Regardless of the large smoke aerosol loads in the region during the dry season, kinetic limitations are expected to be low.


2021 ◽  
pp. jgs2020-187
Author(s):  
Carl Jacquemyn ◽  
Margaret E. H. Pataki ◽  
Gary J. Hampson ◽  
Matthew D. Jackson ◽  
Dmytro Petrovskyy ◽  
...  

Geological modelling is widely used to predict resource potential in subsurface reservoirs. However, modelling is often slow, requires use of mathematical methods that are unfamiliar to many geoscientists and is implemented in expert software. We demonstrate here an alternative approach using Sketch-Based Interface and Modelling (SBIM) that allows rapid creation of complex three-dimensional (3D) models from 2D sketches. Sketches, either on vertical cross-sections or in map-view, are converted to 3D surfaces that outline geological interpretations. A suite of geological operators is proposed that handle interactions between the surfaces to form a geologically realistic 3D model. These operators deliver the flexibility to sketch a geological model in any order and provide an intuitive framework for geoscientists to rapidly create 3D models. Two case studies are presented, demonstrating scenarios in which different approaches to model sketching are used depending on the geological setting and available data. These case studies show the strengths of sketching with geological operators. Sketched 3D models can be queried visually or quantitatively to provide insights into heterogeneity distribution, facies connectivity or dynamic model behaviour; this information cannot be obtained by sketching in 2D or on paper.Supplementary material:https://doi.org/10.6084/m9.figshare.c.5303043


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