| import cdsapi | |
| c = cdsapi.Client() | |
| c.retrieve( | |
| 'reanalysis-era5-land', | |
| { | |
| 'format': 'netcdf', | |
| 'variable': '2m_temperature', | |
| 'year': '2021', |
| drought,professor,barber,kneel,orbit,germ,darts,dance,cape,beanstalk,sushi,baby-sitter,ping pong,mime,Heinz 57,half,swamp,sheep dog,macaroni,hurdle,Internet,lie,logo,rind,fireman pole,raft,wig,salmon,pigpen,letter opener,cabin,fireside,cell phone charger,dent,jungle,dripping,saddle,fabric,sleep,mirror,ski goggles,ringleader,scream,point,neighborhood,yardstick,applause,cliff,loveseat,sponge,chess,grandpa,peasant,cruise,CD,drawback,chestnut,yolk,pilot,season,bedbug,world,important,bleach,biscuit,bobsled,pharmacist,shampoo,swarm,moth,sneeze,deep,sunburn,pizza sauce,houseboat,password,dryer sheets,migrate,snag,koala,catalog,husband,darkness,shower curtain,rib,extension cord,honk,landscape,water buffalo,wooly mammoth,cheerleader,cloak,birthday,nightmare,fizz,clog,myth,wind,banister,post office,knight,rim,think,bride,comfy,hydrogen,baguette,vitamin,lace,tiptoe,sweater vest,pail,glitter,plow,retail,leak,pocket,crust,mascot,macho,hail,bargain,time machine,drain,vegetarian,bookend,ivy,taxi,foil,mast,gold,chime,commerc |
| Zanna, Laure; Bolton, Thomas Data-Driven Equation Discovery of Ocean Mesoscale Closures | |
| Toms, Benjamin A.; Kashinath, Karthik; Prabhat; Yang, Da Testing the Reliability of Interpretable Neural Networks in Geoscience Using the Madden-Julian Oscillation | |
| Rasp, Stephan Coupled online learning as a way to tackle instabilities and biases in neural network parameterizations: general algorithms and Lorenz 96 case study (v1.0) | |
| Mooers, Griffin; Tuyls, Jens; Mandt, Stephan; Pritchard, Michael; Beucler, Tom Generative Modeling for Atmospheric Convection | |
| Mooers, Griffin; Pritchard, Mike; Beucler, Tom; Ott, Jordan; Yacalis, Galen; Baldi, Pierre; Gentine, Pierre Assessing the Potential of Deep Learning for Emulating Cloud Superparameterization in Climate Models with Real-Geography Boundary Conditions | |
| Grönquist, Peter; Yao, Chengyuan; Ben-Nun, Tal; Dryden, Nikoli; Dueben, Peter; Li, Shigang; Hoefler, Torsten Deep Learning for Post-Processing Ensemble Weather Forecasts | |
| Gao, Han; Sun, Luning; Wang, Jian-Xun PhyGeoNet: Physics- |
General instructions are
module load anaconda ) if system supports itconda install -c conda-forge mambas
The links to our images
Camera https://engineering.arm.gov/~radar/amf1_surcam_incoming_images/animation/test.gif https://engineering.arm.gov/~radar/amf1_surcam_incoming_images/camera/
CSAPR2 https://engineering.arm.gov/~radar/amf1_csapr2_incoming_images You can browse the older images as well https://engineering.arm.gov/~radar/amf1_csapr2_incoming_images/hsrhi/2018_10_28/cor_csapr2_rhi_20181028-043748_zhc_30.0.png
Piano Covers of Pop Songs: https://open.spotify.com/user/henryecker/playlist/4SBOdi7IMfCrYKZqCqtuXA?si=FL1axIJTTTqYWXYqS6QICw
Extreme focus coding music: Primarily EDM with little to no vocals https://open.spotify.com/user/nebosite/playlist/0hy2h4wf2A3JWvMzK48REE?si=KlMRgPm8QfiC6N9Z-A6jAQ
High Energy programming mix: Most songs have vocals but good for brainstorming portions. https://open.spotify.com/user/jhardinee/playlist/022CloUnijfD00ziUEXJ66?si=WCKBLFEbQmmym-0DNgFLRA
Dubstep study: Dubstep with no vocals
| from mayavi import mlab | |
| from numpy import * | |
| import pyart | |
| from matplotlib import pyplot as plt | |
| filename = '/Users/jhardin/Data/iflood/npol/ppi/np1130503061041.RAWCJA2' | |
| radar = pyart.io.read(filename) | |
| #ZH = radar.fields['reflectivity_horizontal']['data'][0:1024,:] |
