Search Results

You are looking at 1 - 10 of 16 items for :

  • Author or Editor: S. Chang x
  • Bulletin of the American Meteorological Society x
  • Refine by Access: All Content x
Clear All Modify Search
Tsing-Chang Chen
,
Jin-ho Yoon
,
Kathryn J. St. Croix
, and
Eugene S. Takle

Analyzing the Global Historical Climatology Network, outgoing longwave radiation, and NCEP–NCAR reanalysis data over the Amazon Basin, the authors find a clear interdecadal increasing trend over the past four decades in both rainfall and intensity of the hydrological cycle. These interdecadal variations are a result of the interdecadal change of the global divergent circulation. On the contrary, the impact of the Amazon deforestation as evaluated by all numerical studies has found a reduction of rainfall and evaporation, and an increase of temperature in the Amazon Basin extending its dry season. Evidently, the interdecadal trend of the basin's hydrological cycle revealed from observations functions in a course opposite to the deforestation scenario. Results of this study suggest that future studies analyzing the impact of the basin-scale deforestation on the regional hydrological cycle and climate should be reassessed with multidecade numerical simulations including both schemes handling the land-surface processes and the mechanism generating proper interdecadal variation of the global divergent circulation.

Full access
Michael S. Frankel
,
Norman J. F. Chang
, and
Melvin J. Sanders Jr.

The Radio Acoustic Sounding System (RASS) is used to remotely measure atmospheric temperature profiles. The technique used for these measurements is Doppler tracking of a short, high-intensity acoustic pulse with an RF (electromagnetic) radar. By measurement of the acoustic pulse propagation speed, temperature can be calculated as a function of altitude.

The Stanford University RASS operates at an acoustic frequency of 85 Hz. Because of this low frequency and the necessity of high system gain, the unit is too large for mobile applications. Our theoretical analyses show, however, that the RASS could operate at much higher acoustic frequencies and still provide data to altitudes of ~1 km even during periods of moderate to strong atmospheric turbulence. These theoretical analyses have now been supported experimentally. A RASS operating with an acoustic frequency of 1 kHz not only provided Doppler data to altitudes of 1 km, but it also was able to provide a measure of horizontal winds over the same range.

These experimental results came from a brief effort to support our theoretical studies. Future experiments could well extend the profiling range and versatility of the high-frequency RASS. Ultimately, we hope that our work will lead to a transportable system to be used for collecting real-time data on atmospheric winds and temperatures.

Full access
Jianguo Tan
,
Limin Yang
,
C. S. B. Grimmond
,
Jianping Shi
,
Wen Gu
,
Yuanyong Chang
,
Ping Hu
,
Juan Sun
,
Xiangyu Ao
, and
Zhihui Han

Abstract

Observations of atmospheric conditions and processes in cities are fundamental to understanding the interactions between the urban surface and weather/climate, improving the performance of urban weather, air quality, and climate models, and providing key information for city end users (e.g., decision makers, stakeholders, public). In this paper, Shanghai’s Urban Integrated Meteorological Observation Network (SUIMON) and some examples of intended applications are introduced. Its characteristics include being multipurpose (e.g., forecast, research, service), multifunction (e.g., high-impact weather, city climate, special end users), multiscale (e.g., macro/meso, urban, neighborhood, street canyon), multivariable (e.g., thermal, dynamic, chemical, biometeorological, ecological), and multiplatform (e.g., radar, wind profiler, ground based, satellite based, in situ observation/sampling). Underlying SUIMON is a data management system to facilitate exchange of data and information. The overall aim of the network is to improve coordination strategies and instruments, to identify data gaps based on science- and user-driven requirements, and to intelligently combine observations from a variety of platforms by using a data assimilation system that is tuned to produce the best estimate of the current state of the urban atmosphere.

Full access
M. J. Roberts
,
P. L. Vidale
,
C. Senior
,
H. T. Hewitt
,
C. Bates
,
S. Berthou
,
P. Chang
,
H. M. Christensen
,
S. Danilov
,
M.-E. Demory
,
S. M. Griffies
,
R. Haarsma
,
T. Jung
,
G. Martin
,
S. Minobe
,
T. Ringler
,
M. Satoh
,
R. Schiemann
,
E. Scoccimarro
,
G. Stephens
, and
M. F. Wehner

Abstract

The time scales of the Paris Climate Agreement indicate urgent action is required on climate policies over the next few decades, in order to avoid the worst risks posed by climate change. On these relatively short time scales the combined effect of climate variability and change are both key drivers of extreme events, with decadal time scales also important for infrastructure planning. Hence, in order to assess climate risk on such time scales, we require climate models to be able to represent key aspects of both internally driven climate variability and the response to changing forcings. In this paper we argue that we now have the modeling capability to address these requirements—specifically with global models having horizontal resolutions considerably enhanced from those typically used in previous Intergovernmental Panel on Climate Change (IPCC) and Coupled Model Intercomparison Project (CMIP) exercises. The improved representation of weather and climate processes in such models underpins our enhanced confidence in predictions and projections, as well as providing improved forcing to regional models, which are better able to represent local-scale extremes (such as convective precipitation). We choose the global water cycle as an illustrative example because it is governed by a chain of processes for which there is growing evidence of the benefits of higher resolution. At the same time it comprises key processes involved in many of the expected future climate extremes (e.g., flooding, drought, tropical and midlatitude storms).

Full access
E.A. D'Asaro
,
P. G. Black
,
L. R. Centurioni
,
Y.-T. Chang
,
S. S. Chen
,
R. C. Foster
,
H. C. Graber
,
P. Harr
,
V. Hormann
,
R.-C. Lien
,
I.-I. Lin
,
T. B. Sanford
,
T.-Y. Tang
, and
C.-C. Wu

Tropical cyclones (TCs) change the ocean by mixing deeper water into the surface layers, by the direct air–sea exchange of moisture and heat from the sea surface, and by inducing currents, surface waves, and waves internal to the ocean. In turn, the changed ocean influences the intensity of the TC, primarily through the action of surface waves and of cooler surface temperatures that modify the air–sea fluxes. The Impact of Typhoons on the Ocean in the Pacific (ITOP) program made detailed measurements of three different TCs (i.e., typhoons) and their interaction with the ocean in the western Pacific. ITOP coordinated meteorological and oceanic observations from aircraft and satellites with deployments of autonomous oceanographic instruments from the aircraft and from ships. These platforms and instruments measured typhoon intensity and structure, the underlying ocean structure, and the long-term recovery of the ocean from the storms' effects with a particular emphasis on the cooling of the ocean beneath the storm and the resulting cold wake. Initial results show how different TCs create very different wakes, whose strength and properties depend most heavily on the nondimensional storm speed. The degree to which air–sea fluxes in the TC core were reduced by ocean cooling varied greatly. A warm layer formed over and capped the cold wakes within a few days, but a residual cold subsurface layer persisted for 10–30 days.

Full access
Christopher S. Ruf
,
Robert Atlas
,
Paul S. Chang
,
Maria Paola Clarizia
,
James L. Garrison
,
Scott Gleason
,
Stephen J. Katzberg
,
Zorana Jelenak
,
Joel T. Johnson
,
Sharanya J. Majumdar
,
Andrew O’brien
,
Derek J. Posselt
,
Aaron J. Ridley
,
Randall J. Rose
, and
Valery U. Zavorotny

Abstract

The Cyclone Global Navigation Satellite System (CYGNSS) is a new NASA earth science mission scheduled to be launched in 2016 that focuses on tropical cyclones (TCs) and tropical convection. The mission’s two primary objectives are the measurement of ocean surface wind speed with sufficient temporal resolution to resolve short-time-scale processes such as the rapid intensification phase of TC development and the ability of the surface measurements to penetrate through the extremely high precipitation rates typically encountered in the TC inner core. The mission’s goal is to support significant improvements in our ability to forecast TC track, intensity, and storm surge through better observations and, ultimately, better understanding of inner-core processes. CYGNSS meets its temporal sampling objective by deploying a constellation of eight satellites. Its ability to see through heavy precipitation is enabled by its operation as a bistatic radar using low-frequency GPS signals. The mission will deploy an eight-spacecraft constellation in a low-inclination (35°) circular orbit to maximize coverage and sampling in the tropics. Each CYGNSS spacecraft carries a four-channel radar receiver that measures GPS navigation signals scattered by the ocean surface. The mission will measure inner-core surface winds with high temporal resolution and spatial coverage, under all precipitating conditions, and over the full dynamic range of TC wind speeds.

Full access
J. Shukla
,
J. Anderson
,
D. Baumhefner
,
C. Brankovic
,
Y. Chang
,
E. Kalnay
,
L. Marx
,
T. Palmer
,
D. Paolino
,
J. Ploshay
,
S. Schubert
,
D. Straus
,
M. Suarez
, and
J. Tribbia

Dynamical Seasonal Prediction (DSP) is an informally coordinated multi-institution research project to investigate the predictability of seasonal mean atmospheric circulation and rainfall. The basic idea is to test the feasibility of extending the technology of routine numerical weather prediction beyond the inherent limit of deterministic predictability of weather to produce numerical climate predictions using state-of-the-art global atmospheric models. Atmospheric general circulation models (AGCMs) either forced by predicted sea surface temperature (SST) or as part of a coupled forecast system have shown in the past that certain regions of the extratropics, in particular, the Pacific–North America (PNA) region during Northern Hemisphere winter, can be predicted with significant skill especially during years of large tropical SST anomalies. However, there is still a great deal of uncertainty about how much the details of various AGCMs impact conclusions about extratropical seasonal prediction and predictability.

DSP is designed to compare seasonal simulation and prediction results from five state-of-the-art U.S. modeling groups (NCAR, COLA, GSFC, GFDL, NCEP) in order to assess which aspects of the results are robust and which are model dependent. The initial emphasis is on the predictability of seasonal anomalies over the PNA region. This paper also includes results from the ECMWF model, and historical forecast skill over both the PNA region and the European region is presented for all six models.

It is found that with specified SST boundary conditions, all models show that the winter season mean circulation anomalies over the Pacific–North American region are highly predictable during years of large tropical sea surface temperature anomalies. The influence of large anomalous boundary conditions is so strong and so reproducible that the seasonal mean forecasts can be given with a high degree of confidence. However, the degree of reproducibility is highly variable from one model to the other, and quantities such as the PNA region signal to noise ratio are found to vary significantly between the different AGCMs. It would not be possible to make reliable estimates of predictability of the seasonal mean atmosphere circulation unless causes for such large differences among models are understood.

Full access
H. J. S. Fernando
,
I. Gultepe
,
C. Dorman
,
E. Pardyjak
,
Q. Wang
,
S. W Hoch
,
D. Richter
,
E. Creegan
,
S. Gaberšek
,
T. Bullock
,
C. Hocut
,
R. Chang
,
D. Alappattu
,
R. Dimitrova
,
D. Flagg
,
A. Grachev
,
R. Krishnamurthy
,
D. K. Singh
,
I. Lozovatsky
,
B. Nagare
,
A. Sharma
,
S. Wagh
,
C. Wainwright
,
M. Wroblewski
,
R. Yamaguchi
,
S. Bardoel
,
R. S. Coppersmith
,
N. Chisholm
,
E. Gonzalez
,
N. Gunawardena
,
O. Hyde
,
T. Morrison
,
A. Olson
,
A. Perelet
,
W. Perrie
,
S. Wang
, and
B. Wauer
Full access
H. J. S. Fernando
,
I. Gultepe
,
C. Dorman
,
E. Pardyjak
,
Q. Wang
,
S. W Hoch
,
D. Richter
,
E. Creegan
,
S. Gaberšek
,
T. Bullock
,
C. Hocut
,
R. Chang
,
D. Alappattu
,
R. Dimitrova
,
D. Flagg
,
A. Grachev
,
R. Krishnamurthy
,
D. K. Singh
,
I. Lozovatsky
,
B. Nagare
,
A. Sharma
,
S. Wagh
,
C. Wainwright
,
M. Wroblewski
,
R. Yamaguchi
,
S. Bardoel
,
R. S. Coppersmith
,
N. Chisholm
,
E. Gonzalez
,
N. Gunawardena
,
O. Hyde
,
T. Morrison
,
A. Olson
,
A. Perelet
,
W. Perrie
,
S. Wang
, and
B. Wauer

Abstract

C-FOG is a comprehensive bi-national project dealing with the formation, persistence, and dissipation (life cycle) of fog in coastal areas (coastal fog) controlled by land, marine, and atmospheric processes. Given its inherent complexity, coastal-fog literature has mainly focused on case studies, and there is a continuing need for research that integrates across processes (e.g., air–sea–land interactions, environmental flow, aerosol transport, and chemistry), dynamics (two-phase flow and turbulence), microphysics (nucleation, droplet characterization), and thermodynamics (heat transfer and phase changes) through field observations and modeling. Central to C-FOG was a field campaign in eastern Canada from 1 September to 8 October 2018, covering four land sites in Newfoundland and Nova Scotia and an adjacent coastal strip transected by the Research Vessel Hugh R. Sharp. An array of in situ, path-integrating, and remote sensing instruments gathered data across a swath of space–time scales relevant to fog life cycle. Satellite and reanalysis products, routine meteorological observations, numerical weather prediction model (WRF and COAMPS) outputs, large-eddy simulations, and phenomenological modeling underpin the interpretation of field observations in a multiscale and multiplatform framework that helps identify and remedy numerical model deficiencies. An overview of the C-FOG field campaign and some preliminary analysis/findings are presented in this paper.

Full access
Rita D. Roberts
,
Steven J. Goodman
,
James W. Wilson
,
Paul Watkiss
,
Robert Powell
,
Ralph A. Petersen
,
Caroline Bain
,
John Faragher
,
Ladislaus B. Chang’a
,
Julius Kiprop Kapkwomu
,
Paul N. Oloo
,
Joseph N. Sebaziga
,
Andrew Hartley
,
Timothy Donovan
,
Marion Mittermaier
,
Lee Cronce
, and
Katrina S. Virts

Abstract

Up to 1,000 drowning deaths occur every year on Lake Victoria in East Africa. Nocturnal thunderstorms are one of the main culprits for the high winds and waves that cause fishing boats to capsize. The High Impact Weather Lake System (HIGHWAY) project was established to develop an Early Warning System for Lake Victoria. Prior to HIGHWAY, weather forecasts for the lake were overly general and not trusted. Under the HIGHWAY project, forecasters from weather service offices in East Africa worked with leaders of fishing communities and Beach Management Units to develop marine forecasts and hazardous-weather warnings that were meaningful to fishermen and other stakeholders. Forecasters used high-resolution satellite, radar, and lightning observations collected during a HIGHWAY field campaign, along with guidance from numerical weather prediction models and a 4.4-km resolution Tropical Africa model, to produce specific forecasts and warnings for 10 zones over the lake. Forecasts were communicated to thousands of people by radio broadcasters, local intermediaries, and via smartphones using the WhatsApp application. Fishermen, ferry-boat operators, and lakeside communities used the new marine forecasts to plan their daytime and nighttime activities on the lake. A socioeconomic benefits study conducted by HIGHWAY found that ∼75% of the people are now using the forecasts to decide if and when to travel on the lake. Significantly, a 30% reduction in drowning fatalities on the lake is likely to have occurred, which, when combined with the reduction in other weather-related losses, generates estimated socioeconomic benefits of $44 million per year due to the HIGHWAY project activities; the new marine forecasts and warnings are helping to save lives and property.

Full access