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H. M. van den Dool
,
W. H. Klein
, and
J. E. Walsh

Abstract

Eighty years of monthly mean station temperatures are used to evaluate the persistence of monthly air temperature anomalies over the United States. The geographical and seasonal dependence of the monthly persistence are described in term of the day-to-day persistence of temperature anomalies, the influence of the large-scale atmospheric circulation, and inferred associations with the slowly varying properties of the earth's surface.

The monthly persistence is generally smallest in the continental interior and largest in coastal regions. The seasonality of this spatial pattern is quite small, although the continental interior is characterized by a summer maximum. For the country as a whole, persistence is highest (0.30) in winter and summer and least (0.15) in fall and spring. For both raw and detrended data, the anomaly pattern correlations at lags of two and three months are much larger than would be expected from a first-order Markov process.

The pattern of persistences computed using day-to-day autocorrelations shows that the presence of nearby bodies of water increases the month-to-month persistence over that to be expected from daily weather fluctuations. This finding is consistent with the results derived from an intuitive energy balance model in which the soil (or ocean) surface layers and the atmospheric boundary layer respond to prescribed daily fluctuations in the free atmosphere.

Local surface influences are also implied by the fact that the 700-mb circulation-derived anomalies of monthly temperature have fewer spatial degrees of freedom than do the actual anomalies. While the large-scale circulation accounts for about half of the winter temperature persistence, small-scale effects, as well as the effects of the antecedent month's circulation, contribute substantially to the persistence of summer temperatures.

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WILLIAM H. KLEIN
,
BILLY M. LEWIS
, and
CURTIS W. CROCKETT

Abstract

Multiple regression equations for predicting 5-day mean temperatures in the United States were originally computed from 5-day mean values of both 700-mb. height and surface temperature, but they gave better results operationally when applied to properly weighted 46-hour forecasts of height and temperature. Since re-derivation from daily instead of mean data yielded poorer results, it appears that use of prognostic daily values as input in equations computed from mean data produces the best mean forecast under current operating conditions.

In an effort to obtain daily temperature forecasts for several days in advance, 5-day mean objective temperature predictions were tested a s forecasts of daily mean temperature on each of the individual days comprising the forecast period. Although perfect mean forecasts would have been most accurate for the middle day of the period, the objective prognoses attained maximum accuracy a day or two earlier. Comparison is made with chance, persistence, climatology, and daily predictions prepared at local forecast offices. The objective forecasts were superior to these controls on each day of the 5-day period, with maximum difference on day 3. Additional tests of the skill of the objective predictions as 2- and 3-day forecasts are described, and it is concluded that the objective method can be of assistance in the routine preparation of 72-hour forecasts.

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Willlam H. Klein
,
Joseph J. Charney
,
Morris H. McCutchan
, and
John W. Benoit

Abstract

The authors first review a system for specifying monthly mean anomalies of midday temperature (T), dew-point (D), and wind speed (W) at a large network of surface stations across the United States. Multiple regression equations containing approximately three terms were derived for each element and month from concurrent fields of 700-mb height anomaly (H) observed over North America and vicinity, plus the previous month's observed local anomaly of T, D, or W, during the 20-year period 1964–1983. Results of testing this forecast system on prognostic values of H prepared twice a month at the National Weather Service from 1973 to 1990 and on observed values of H during the independent period from 1984 to 1990 are presented.

The authors pooled the data for all months and 122 stations to compute Heidke skill scores (HSS) for two, three, four, and five classes for each weather element. All scores showed skill that dropped steadily as the number of classes increased. In all cases skill was highest for T and lowest for W, the same result as that obtained in the original derivation. In order to examine the distribution of skill, we computed the HSS separately for each class. The skill scores for the first and last classes were greater than those for the middle class for all elements and months. It is encouraging that forecasts above the 90th percentile, the most critical category for fire potential, consistently showed greater skill than forecasts for any other class. Geographical and seasonal variations of skill based on prognostic height was also examined. The results showed that skill is strongly dependent on location, month, and weather element. Mean annual scores were positive for each element in all parts of the country, while monthly scores were highest in January and lowest in October.

Although the forecasts based on prognostic heights were more skillful than climatology for all weather elements, they improved over month-to-month persistence only for T and D. If the height forecasts had been perfect, the skill scores for these elements would have been about two to three times as large as those for prognostic heights and four to five times as large as the persistence scores. When the test period was divided into two subperiods, values of HSS were considerably higher in the later period, despite a drop in persistence scores from the early to the later period. The authors attribute this improvement to increased accuracy of medium-range numerical model predictions during the 1980s.

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H. Leijnse
,
R. Uijlenhoet
,
C. Z. van de Beek
,
A. Overeem
,
T. Otto
,
C. M. H. Unal
,
Y. Dufournet
,
H. W. J. Russchenberg
,
J. Figueras i Ventura
,
H. Klein Baltink
, and
I. Holleman

Abstract

The Cabauw Experimental Site for Atmospheric Research (CESAR) observatory hosts a unique collection of instruments related to precipitation measurement. The data collected by these instruments are stored in a database that is freely accessible through a Web interface. The instruments present at the CESAR site include three disdrometers (two on the ground and one at 200 m above ground level), a dense network of rain gauges, three profiling radars (1.3, 3.3, and 35 GHz), and an X-band Doppler polarimetric scanning radar. In addition to these instruments, operational weather radar data from the nearby (∼25 km) De Bilt C-band Doppler radar are also available. The richness of the datasets available is illustrated for a rainfall event, where the synergy of the different instruments provides insight into precipitation at multiple spatial and temporal scales. These datasets, which are freely available to the scientific community, can contribute greatly to our understanding of precipitation-related atmospheric and hydrologic processes.

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Cloudnet

Continuous Evaluation of Cloud Profiles in Seven Operational Models Using Ground-Based Observations

A. J. Illingworth
,
R. J. Hogan
,
E.J. O'Connor
,
D. Bouniol
,
M. E. Brooks
,
J. Delanoé
,
D. P. Donovan
,
J. D. Eastment
,
N. Gaussiat
,
J. W. F. Goddard
,
M. Haeffelin
,
H. Klein Baltink
,
O. A. Krasnov
,
J. Pelon
,
J.-M. Piriou
,
A. Protat
,
H. W. J. Russchenberg
,
A. Seifert
,
A. M. Tompkins
,
G.-J. van Zadelhoff
,
F. Vinit
,
U. Willén
,
D. R. Wilson
, and
C. L. Wrench

The Cloudnet project aims to provide a systematic evaluation of clouds in forecast and climate models by comparing the model output with continuous ground-based observations of the vertical profiles of cloud properties. In the models, the properties of clouds are simplified and expressed in terms of the fraction of the model grid box, which is filled with cloud, together with the liquid and ice water content of the clouds. These models must get the clouds right if they are to correctly represent both their radiative properties and their key role in the production of precipitation, but there are few observations of the vertical profiles of the cloud properties that show whether or not they are successful. Cloud profiles derived from cloud radars, ceilometers, and dual-frequency microwave radiometers operated at three sites in France, Netherlands, and the United Kingdom for several years have been compared with the clouds in seven European models. The advantage of this continuous appraisal is that the feedback on how new versions of models are performing is provided in quasi-real time, as opposed to the much longer time scale needed for in-depth analysis of complex field studies. Here, two occasions are identified when the introduction of new versions of the ECMWF and Météo-France models leads to an immediate improvement in the representation of the clouds and also provides statistics on the performance of the seven models. The Cloudnet analysis scheme is currently being expanded to include sites outside Europe and further operational forecasting and climate models.

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J. K. Fletcher
,
C. A. Diop
,
E. Adefisan
,
M. A. Ahiataku
,
S. O. Ansah
,
C. E. Birch
,
H. L. Burns
,
S. J. Clarke
,
J. Gacheru
,
T. D. James
,
C. K. Ngetich Tuikong
,
D. Koros
,
V. S. Indasi
,
B. L. Lamptey
,
K. A. Lawal
,
D. J. Parker
,
A. J. Roberts
,
T. H. M. Stein
,
E. Visman
,
J. Warner
,
B. J. Woodhams
,
L. H. Youds
,
V. O. Ajayi
,
E. N. Bosire
,
C. Cafaro
,
C. A. T. Camara
,
B. Chanzu
,
C. Dione
,
W. Gitau
,
D. Groves
,
J. Groves
,
P. G. Hill
,
I. Ishiyaku
,
C. M. Klein
,
J. H. Marsham
,
B. K. Mutai
,
P. N. Ndiaye
,
M. Osei
,
T. I. Popoola
,
J. Talib
,
C. M. Taylor
, and
D. Walker

Abstract

Testbeds have become integral to advancing the transfer of knowledge and capabilities from research to operational weather forecasting in many parts of the world. The first high-impact weather testbed in tropical Africa was recently carried out through the African Science for Weather Information and Forecasting Techniques (SWIFT) program, with participation from researchers and forecasters from Senegal, Ghana, Nigeria, Kenya, the United Kingdom, and international and pan-African organizations. The testbed aims were to trial new forecasting and nowcasting products with operational forecasters, to inform future research, and to act as a template for future testbeds in the tropics. The African SWIFT testbed integrated users and researchers throughout the process to facilitate development of impact-based forecasting methods and new research ideas driven both by operations and user input. The new products are primarily satellite-based nowcasting systems and ensemble forecasts at global and regional convection-permitting scales. Neither of these was used operationally in the participating African countries prior to the testbed. The testbed received constructive, positive feedback via intense user interaction including fishery, agriculture, aviation, and electricity sectors. After the testbed, a final set of recommended standard operating procedures for satellite-based nowcasting in tropical Africa have been produced. The testbed brought the attention of funding agencies and organizational directors to the immediate benefit of improved forecasts. Delivering the testbed strengthened the partnership between each country’s participating university and weather forecasting agency and internationally, which is key to ensuring the longevity of the testbed outcomes.

Open access
H. J. S. Fernando
,
J. Mann
,
J. M. L. M. Palma
,
J. K. Lundquist
,
R. J. Barthelmie
,
M. Belo-Pereira
,
W. O. J. Brown
,
F. K. Chow
,
T. Gerz
,
C. M. Hocut
,
P. M. Klein
,
L. S. Leo
,
J. C. Matos
,
S. P. Oncley
,
S. C. Pryor
,
L. Bariteau
,
T. M. Bell
,
N. Bodini
,
M. B. Carney
,
M. S. Courtney
,
E. D. Creegan
,
R. Dimitrova
,
S. Gomes
,
M. Hagen
,
J. O. Hyde
,
S. Kigle
,
R. Krishnamurthy
,
J. C. Lopes
,
L. Mazzaro
,
J. M. T. Neher
,
R. Menke
,
P. Murphy
,
L. Oswald
,
S. Otarola-Bustos
,
A. K. Pattantyus
,
C. Veiga Rodrigues
,
A. Schady
,
N. Sirin
,
S. Spuler
,
E. Svensson
,
J. Tomaszewski
,
D. D. Turner
,
L. van Veen
,
N. Vasiljević
,
D. Vassallo
,
S. Voss
,
N. Wildmann
, and
Y. Wang

Abstract

A grand challenge from the wind energy industry is to provide reliable forecasts on mountain winds several hours in advance at microscale (∼100 m) resolution. This requires better microscale wind-energy physics included in forecasting tools, for which field observations are imperative. While mesoscale (∼1 km) measurements abound, microscale processes are not monitored in practice nor do plentiful measurements exist at this scale. After a decade of preparation, a group of European and U.S. collaborators conducted a field campaign during 1 May–15 June 2017 in Vale Cobrão in central Portugal to delve into microscale processes in complex terrain. This valley is nestled within a parallel double ridge near the town of Perdigão with dominant wind climatology normal to the ridges, offering a nominally simple yet natural setting for fundamental studies. The dense instrument ensemble deployed covered a ∼4 km × 4 km swath horizontally and ∼10 km vertically, with measurement resolutions of tens of meters and seconds. Meteorological data were collected continuously, capturing multiscale flow interactions from synoptic to microscales, diurnal variability, thermal circulation, turbine wake and acoustics, waves, and turbulence. Particularly noteworthy are the extensiveness of the instrument array, space–time scales covered, use of leading-edge multiple-lidar technology alongside conventional tower and remote sensors, fruitful cross-Atlantic partnership, and adaptive management of the campaign. Preliminary data analysis uncovered interesting new phenomena. All data are being archived for public use.

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