Browse

You are looking at 11 - 20 of 9,957 items for :

  • Journal of Applied Meteorology and Climatology x
  • Refine by Access: All Content x
Clear All
C. Cammalleri
,
N. McCormick
,
J. Spinoni
, and
J. W. Nielsen-Gammon

Abstract

The standardized precipitation index (SPI) is the most commonly used index for detecting and characterizing meteorological droughts, and it is also extensively used as a proxy variable for soil moisture anomalies (SMA) for the purpose of monitoring agricultural drought in absence of long-term soil moisture observations. However, the potential capability of SPI to warn of the time-lagged soil water deficit—following the well-known “drought cascade” effect—is often overlooked in agricultural drought studies. In this research, a time-lagged correlation analysis is used to evaluate the relationship between the SMA dataset, generated as part of the Global Drought Observatory of the European Union’s Copernicus Emergency Management Service, and a set of SPIs derived from the ERA5 reanalysis produced by the European Centre for Medium-Range Weather Forecasts. The possibility to achieve an optimal agreement between SPI and SMA that also preserves the early warning skills of SPI is evaluated. The results suggest that if only the correlation between SPI and SMA is considered, the maximum agreement is usually obtained with a zero lead time (almost 80% of the cases), with SPI-3 representing the best option in about 40% of the grid cells at global scale. By also accounting for the benefits of a positive lead time, short accumulation periods tend to be favored, with SPI-1 being the optimal choice in about one-half of the cases, and 10–20 days of lead time in more than 90% of the grid cells is achieved without any significant reduction in either correlation or skill in drought extreme detection.

Open access
Jordan Clark
and
Charles E. Konrad

Abstract

Wet-bulb globe temperature (WBGT) is used to assess environmental heat stress and accounts for the influences of air temperature, humidity, wind speed, and radiation on heat stress. Measurements of WBGT are highly sensitive to slight changes in environmental conditions and can vary several degrees Celsius across small distances (tens to hundreds of meters). Relative to observations with an International Organization for Standardization (ISO)-compliant WBGT meter, this work assesses the accuracy of WBGT measurements made with a popular handheld meter (the Kestrel 5400 Heat Stress Tracker) and WBGT estimates. Measurements were made during the summers of 2019–21 in a variety of suburban and urban environments in North Carolina, including three high school campuses. WBGT can be estimated from standard weather station variables, and many of these stations report cloud cover in lieu of solar radiation. Therefore, this work also evaluates the accuracy of clear-sky radiation estimates and adjustments to those estimates based on cloud cover. WBGT estimated with the method from Liljegren et al. from a weather station were on average 0.2°C warmer than Observed WBGT, while the Kestrel 5400 WBGT was 0.7°C warmer. Large variations in WBGT were observed across surfaces and shade conditions, with differences of 0.9°C (0.3°–1.4°C) between a tennis court and a neighboring grass field. The method for estimating clear-sky radiation in Ryan and Stolzenbach was most accurate and the clear-sky radiation modified by percentage cloud cover was found to be within 75 W m−2of observations on average.

Significance Statement

Wet-bulb globe temperature (WBGT) is a heat stress index that accounts for the effects of air temperature, humidity, wind, and radiation on humans. However, WBGT is not routinely measured at weather stations. This work demonstrated the accuracy of estimating WBGT with methods from , finding it to be more accurate than measurements from a popular handheld meter, the Kestrel 5400 Heat Stress Tracker. Variations in WBGT that result in different danger levels were found between measurements over a tennis court and a neighboring grass field, and between sun and shade conditions. Understanding the magnitude of these differences and the biases with WBGT estimates and measurements can inform the planning of outdoor activity to robustly safeguard health.

Restricted access
Ruth Mendez-Rivas
,
Maycol Mena Palacios
, and
Reiner Palomino Lemus

Abstract

We investigated nine indices of spatiotemporal extreme precipitation events over Nicaragua during 2001–16, from GPCC, Climate Hazards Group Infrared Precipitation with Station data (CHIRPS), and IMERG, and their correlation with teleconnection patterns. The main objectives were to evaluate the variability of extreme precipitation events, to know the performance of IMERG and CHIRPS in the characterization of these extreme events, using GPCC and four rain gauges as references, and finally to determine the teleconnection patterns that have the highest correlation with these indices. The spatial coverage of the area with the highest number of consecutive days with daily precipitation less than 1 mm corresponds to the Pacific region, with annual mean values of up to 120 continuous days. Some extreme precipitation event indices (RR, RX1day, and RX5day) show a decreasing trend, suggesting that the study area has been experiencing a reduction of extreme precipitation indices in terms of intensities and duration throughout the study period. In addition, it was observed that CHIRPS shows a better fit when dealing with precipitation events that do not exceed certain thresholds and IMERG improves when describing intense precipitation event patterns. We found that the tropical Pacific SST EOF (EOFPAC), Niño-3.4, Pacific warm pool region (PACWARM), and SOI have a greater influence on extreme precipitation events, these results suggest that they are being controlled by ENSO episodes, providing a better understanding of the climate configuration, as a prediction and forecasting potential, useful for agriculture, land use, and risk management.

Restricted access
Fang-Ching Chien
,
Chun-Wei Chang
,
Jen-Hsin Teng
, and
Jing-Shan Hong

Abstract

This paper investigates a wind speed oscillation event that occurred near the coastline of central Taiwan in the afternoon of 17 February 2018, using data from observations and numerical simulations. The observed wind speeds at 100-m altitude displayed a fast-oscillating pattern of about 6 cycles between strong winds of approximately 21 m s−1 and weak winds of around 2 m s−1, with periods of about 10 min. The pressure anomalies fluctuated in antiphase with the wind speed anomalies. The synoptic analysis revealed the influence of a continental high pressure system, resulting in a cold-air outbreak over Taiwan. The cold north-northeasterly winds split into two branches upon encountering Taiwan’s topography, with ridging off the east coast and a lee trough off the west coast of Taiwan. Wind oscillations were detected in the low-level cold air offshore the west coast of Taiwan, depicted by wavelike structures in wind speeds, sea level pressure, and potential temperature. The perturbations were identified as Kelvin-Helmholtz billows characterized by regions of strong wind speeds, warm and dry air, sinking motions, and low pressure collocated with each other, while regions of weaker wind speeds, cooler and moister air, ascending motions, and high pressure were associated with each other. With terrain contributing to favorable conditions, the large vertical and horizontal wind shears resulted from the southward acceleration of low-level cold air and the northward movement of the lee trough played an important role in initiating the wind oscillations.

Restricted access
Nicholas S. Grondin
and
Kelsey N. Ellis

Abstract

In this study, we investigated the translation speed and intensity change characteristics for landfalling North American tropical cyclones (TCs) from 1971–2020. We calculated three variables—intensity change, mean translation speed, and translation speed change—prior to each TC landfall and investigated the climatology of these variables for seven coastal segments. We found that lower latitude segments generally had greater positive intensity changes prior to landfall, and higher latitude segments had greater translation speeds. Longitude primarily influenced translation speed changes, with landfalling TCs along the Atlantic Coast of the United States notably accelerating prior to landfall. Temporal trends in each of these variables were inconsistent geographically, but most segments showed an increase in positive intensity changes over time, demonstrating the increasing likelihood of intensifying TCs before landfall in recent years. We defined extreme intensification and extreme weakening as the 90th and 10th percentile of all landfalling TC intensity changes, respectively. We found that extreme intensification (weakening) has been increasing (decreasing) in frequency. Results from this study can be used in a variety of future applications, including in operational forecasting and model production and provide a baseline for climate attribution studies investigating extreme intensity change events.

Restricted access
Emilee Lachenmeier
,
Rezaul Mahmood
,
Chris Phillips
,
Udaysankar Nair
,
Eric Rappin
,
Roger A. Pielke Sr.
,
William Brown
,
Steve Oncley
,
Joshua Wurman
,
Karen Kosiba
,
Aaron Kaulfus
,
Joseph Santanello Jr.
,
Edward Kim
,
Patricia Lawston-Parker
,
Michael Hayes
, and
Trenton E. Franz

Abstract

Modification of grasslands into irrigated and nonirrigated agriculture in the Great Plains resulted in significant impacts on weather and climate. However, there has been lack of observational data–based studies solely focused on impacts of irrigation on the PBL and convective conditions. The Great Plains Irrigation Experiment (GRAINEX), conducted during the 2018 growing season, collected data over irrigated and nonirrigated land uses over Nebraska to understand these impacts. Specifically, the objective was to determine whether the impacts of irrigation are sustained throughout the growing season. The data analyzed include latent and sensible heat flux, air temperature, dewpoint temperature, equivalent temperature (moist enthalpy), PBL height, lifting condensation level (LCL), level of free convection (LFC), and PBL mixing ratio. Results show increased partitioning of energy into latent heat relative to sensible heat over irrigated areas while average maximum air temperature was decreased and dewpoint temperature was increased from the early to peak growing season. Radiosonde data suggest reduced planetary boundary layer (PBL) heights at all launch sites from the early to peak growing season. However, reduction of PBL height was much greater over irrigated areas than over nonirrigated croplands. Relative to the early growing period, LCL and LFC heights were also lower during the peak growing period over irrigated areas. Results note, for the first time, that the impacts of irrigation on PBL evolution and convective environment can be sustained throughout the growing season and regardless of background atmospheric conditions. These are important findings and applicable to other irrigated areas in the world.

Significance Statement

To meet the ever-increasing demand for food, many regions of the world have adopted widespread irrigation. The High Plains Aquifer (HPA) region, located within the Great Plains of the United States, is one of the most extensively irrigated regions. In this study, for the first time, we have conducted a detailed irrigation-focused land surface and atmospheric data collection campaign to determine irrigation impacts on the atmosphere. This research demonstrates that irrigation significantly alters lower atmospheric characteristics and creates favorable cloud and convection development conditions during the growing season. The results clearly show first-order impacts of irrigation on regional weather and climate and hence warrant further attention so that we can minimize negative impacts and achieve sustainable irrigation.

Restricted access
Hiroyuki Kusaka
,
Satoshi Nishiba
, and
Yuki Asano

Abstract

The Jintsu-oroshi refers to Japan’s south foehn, which blows over the Toyama Plain in the Hokuriku region. This region faces the Sea of Japan to the north and the central mountain range to the south. The Jintsu-oroshi occurs more frequently at night than during the day. In this study, we determined the primary factors causing this feature using the Weather Research and Forecasting (WRF) Model. We selected a typical Jintsu-oroshi case in May 2016 for analysis. An extratropical cyclone traversed the Sea of Japan during the event, leading to a temporal change in the synoptic-scale pressure pattern. The observations and numerical simulation results showed that the collapse of the mixed layer over the mountains and the end of the sea breeze are key factors for the nighttime onset of the Jintsu-oroshi. Indeed, mountain waves and their resulting downslope winds did not occur under near-neutral atmospheric stability conditions over the mountains during the daytime. After sunset, the atmospheric stability changed to stable conditions, which caused the downslope winds to blow. However, the downslope winds did not reach the plains because of the sea breeze. After several hours, the sea breeze disappeared, and the downslope winds reached the leeward plains and increased the temperature there. Similar features were confirmed in August 2013 for another typical Jintsu-oroshi case under atmospheric conditions, without temporal changes in the synoptic-scale pressure pattern. We expect the results obtained in this study to advance our understanding of foehn occurrence in regions where mountains adjoin seas, similar to the coastal areas adjacent to the Sea of Japan.

Significance Statement

The Jintsu-oroshi refers to Japan’s south foehn, which blows over the Toyama Plain in the Hokuriku region. This foehn occurs more frequently at night than during the day. Strong foehns enhance the risk of fire. Nocturnal high temperatures due to foehns can cause sleeplessness in people. Nighttime foehns cause damage to paddy rice. Analyses of observations and numerical simulations for the two typical cases showed that Jintsu-oroshi did not tend to occur during the daytime because the development of a convective boundary layer over the mountains and sea breezes in the leeward plain inhibited the occurrence of the downslope winds. We expect the results obtained in this study to advance our understanding of foehn occurrence in regions where mountains adjoin seas, similar to the coastal areas adjacent to the Sea of Japan.

Restricted access
Joana Mendes
,
Nosipho Zwane
,
Brighton Mabasa
,
Henerica Tazvinga
,
Karen Walter
,
Cyril J. Morcrette
, and
Joel Botai

Abstract

We assess site-specific surface shortwave radiation forecasts from two high-resolution configurations of the South African Weather Service numerical weather prediction model, at 4 and 1.5 km. The models exhibit good skill overall in forecasting surface shortwave radiation, with zero median error for all radiation components. This information is relevant to support a growing renewable energy sector in South Africa, particularly for photovoltaics. Further model performance analysis has shown an imbalance between cloud and solar radiation forecasting errors. In addition, cloud overprediction does not necessarily equate to underestimating solar radiation. Overcast cloud regimes are predicted too often with an associated positive mean radiation bias, whereas the relative abundance of partly cloudy regimes is underpredicted by the models with mixed radiation biases. Challenges highlighted by the misrepresentation of partly cloudy regimes in solar radiation error attribution may be used to inform improvements to the numerical core, namely, the cloud and radiation schemes.

Significance Statement

This paper provides the first comprehensive assessment of high-resolution site-specific NWP forecasts of surface shortwave radiation in South Africa, exploring clouds as the main drivers of prediction biases. Error attribution analyses of this kind are close to none for this part of the world. Our study contributes to understanding how cloud and radiation schemes perform over South Africa, representing a step forward in the state of the art. In addition to the scientific interest, the capabilities developed through this work may benefit the second largest economy of the continent. In a country where energy security is of critical relevance, the availability of useful and usable weather information is paramount to support its industry and socioeconomic growth.

Open access
Jodie Clark
and
Sen Chiao

Abstract

This study investigates the connection between the arrival of dry stratospheric air and the Soberanes Fire (2016). The Hybrid Single-Particle Lagrangian Integrated Trajectory model (HYSPLIT) and Goddard Earth Observing System Forward Processing model (GEOS-FP) are used for back-trajectories and offshore deep stratospheric intrusion in conjunction with the ignition and outbreak of the fire. The back-trajectory analysis indicates that most air reaching the vertical column was critically dry, exhibiting relative humidity values below 10%. As the fire ignited, dry air arrived from due west at heights of 1–3 km about 24 h prior. During the overnight fire growth, dry air arrived from the northwest to north-northwest at heights of 3.5–5.5 km 48–72 h prior. The synoptic and GEOS-FP analyses demonstrate offshore mid-to-low stratospheric intrusion. On 21 July 2016, an enclosed upper-level low approached the California–Oregon border along the northwesterly subtropical jet stream hours before the fire outbreak. The GEOS-FP results of potential vorticity, specific humidity, and ozone along the back-trajectories to the west and northwest of the fire suggest a stratospheric intrusion event into the mid-to-low troposphere at the back-trajectory start points, and vertical velocity indicates sinking motion. The specific humidity analyzed at the arrival time shows the transport of the abnormally dry air to the Soberanes Fire. Results suggest a connection between dry stratospheric air transported to the Soberanes Fire at ignition and overnight accelerated growth, supported by a dark bank in satellite water vapor imagery. The prediction of low-level transport of dry stratospheric air to the coastal communities could help to predict the occurrence of wildfire outbreaks, or periods of accelerated fire growth.

Restricted access
Andra J. Garner
and
Daniel P. Duran

Abstract

Large temperature variations in a temperate climate, particularly in late winter and early spring, can be disruptive for native ecosystems and agricultural crops. As warmer temperatures occur earlier in the year in midlatitude regions as a result of anthropogenic climate change, springtime temperatures may become less consistent, leading to potential damage to species and crops that are vulnerable to the return of historically cooler temperatures, including late-spring frosts, after an initial warm-up. In this work, we quantify shifting patterns in late-winter and springtime temperature variations at eight sites across New Jersey from 1950 to 2019. Many sites located along the coast or in the coastal plain experience increases in the number of times the temperature climbs above 15.5°C (60°F) and then falls below freezing (i.e.,0°C, or 32°F). Sites in southern New Jersey (where much of the state’s agriculture is located) experience the most significant (P < 0.05) increases in large springtime temperature variations. Across all sites, there is a general increase in both the percentage and magnitude of temperature variations that occur as early as February. At 75% of sites, day-to-day variation in daily maximum temperature has increased from the 1950s through 2019; day-to-day variation in daily minimum temperatures has increased over the same time at more than half of sites considered. These amplifications in extreme temperature variations indicate the need for both mitigation and adaptation strategies to protect vulnerable crops and ecosystems in the region during this critical time of the year.

Significance Statement

Human-caused climate change has made it more likely for warmer temperatures to occur earlier in the year, causing many locations to experience late-winter and early-springtime temperatures that are less consistent than they may have been in the past. These variations can be highly problematic for both vital agricultural crops and critical ecosystems. Here, we evaluate how late-winter and early-springtime temperatures have changed throughout New Jersey (home to a variety of agriculture and unique ecosystems) from the mid-twentieth century until 2019. We find critical changes to temperature patterns during late winter and early spring, including larger and more frequent temperature swings (particularly in February) and increased day-to-day variation in high and low temperatures.

Open access