On tropical cyclone frequency and the warm pool area

Benestad, Rasmus E.

doi:10.5194/nhess-9-635-2009

Cited by 14 publications

(11 citation statements)

References 40 publications

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“…The trend analysis was only applied to data records longer than 30 years over the 1961-2015 period to avoid spurious results from natural fluctuations in short data records (see SM). The mean seasonal cycle has been used in other studies [24], but it cannot be used to attribute change to a certain forcing because there may be several factors covarying with the seasonal cycle. The objective here, however, was to use it to assess the sensitivity of different climate parameters to variations in a set of arbitrary conditions.…”

Section: Data and Methods 21 Methodsmentioning

confidence: 99%

Climate change and projections for the Barents region: what is expected to change and what will stay the same?

Benestad

Parding

Isaksen

et al. 2016

Environ. Res. Lett.

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We present an outlook for a number of climate parameters for temperature, precipitation, and storm statistics in the Barents region. Projected temperatures exhibited strongest increase over northern Fennoscandia and the high Arctic, exceeding 7°C by 2099 for a typical 'warm winter' under the RCP4.5 scenario. More extreme temperatures may be expected with the RCP8.5, with an increase exceeding 18°C in some places. The magnitude of the day-to-day variability in temperature is likely to decrease with higher temperatures. The skill of the downscaling models was moderate for the wet-day frequency for which the projections indicated both increases and decreases within the range of −5-+10% by 2099. The downscaled results for the wet-day mean precipitation was poor, but for the warming associated with RCP 4.5, it could result in wet-day mean precipitation being intensified by as much as 70% in 2099. The number of synoptic storms over the Barents Sea was found to increase with a warming in the Arctic, however, other climate parameters may not change much, such as the persistence of the temperature and precipitation. These climate change projections were derived using a new strategy for empirical-statistical downscaling, making use of principal component analysis to represent the local climate parameters and large ensembles of global climate model (GCM) simulations to provide information about the large scales. The method and analysis were validated on three different levels: (a) the representativeness of the GCMs, (b) traditional validation of the downscaling method, and (c) assessment of the ensembles of downscaled results in terms of past trends and interannual variability.

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Section: Data and Methods 21 Methodsmentioning

confidence: 99%

Climate change and projections for the Barents region: what is expected to change and what will stay the same?

Benestad

Parding

Isaksen

et al. 2016

Environ. Res. Lett.

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“…It is the month of the first peak for intense cyclones. As from June, the monsoon flows begins to considerably cool the ocean and, in August, there exists an upwelling accompanied by masses of cool water in the western part of the Arabian Sea (Benestad, 2009). As soon as the monsoon 'ends' around the end of September, the ocean begins to slowly reheat, although it does not reach the sea surface temperatures to be found in the month of May and the vertical wind shear diminishes.…”

Section: Intense Cyclones Considerably Influenced By Nearby Land Massesmentioning

confidence: 99%

Intense tropical cyclone activities in the northern Indian Ocean

Hoarau

Bernard

Chalonge

2011

Intl Journal of Climatology

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This research concerning the northern Indian Ocean demonstrates the variability of intense tropical cyclones (categories 3-5) both on an inter-annual and intra-seasonal scale. All the cyclones intensity have been re-analysed with the Dvorak technique using both National Oceanic and Atmospheric Administration and geostationary satellites with a 4-km infrared resolution. During the period from 1980 to 2009, 21 cyclones became intense. The decade from 1990 to 1999 was by far the most active with 11 intense cyclones while 5 intense cyclones formed in each of the other two decades. There has been no trend towards an increase in the number of categories 3-5 cyclones over the last 30 years. An early study, not based on re-analysed data, found a significant increase in the number of intense cyclones. Thirteen cyclones became intense when the Oceanic Nino Index was negative and matched with lower vertical wind shear. And, La Nina events have had a noticeable influence with eight intense cyclones. The monthly distribution is bimodal with seven and eight cyclones, respectively in the months of May and November. No intense cyclones were observed from July to September, being the peak of the monsoon season. Over these 3 months, the vertical wind shear is too strong to allow a significant intensification of storms. Despite particularly warm ocean waters, only 6% of categories 1-5 cyclones approached their maximum potential intensity. However, extreme intensities (05B at 155 knots in 1999) are comparable to other basins despite lower in terms of activity level. The proximity of land limits most cyclones from reaching a greater intensity. However, 16 of the 21 cyclones reached land with sustained winds of 100 knots and more. India and Bangladesh have been hit frequently by intense cyclones. Since 1990s, there is an increasing hit in Burma and Pakistan.

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“…The vertical atmospheric motion is driven by the high SSTs in the equatorial regions [4]. The SST is also an indicator of the upper ocean heat content that is closely connected to the generation and intensification of cyclones in the TWP [5,6]. The cyclones frequently make landfall to the west, where damage and loss of life can be extreme (e.g., [7]).…”

Section: Introductionmentioning

confidence: 99%

The Accuracies of Himawari-8 and MTSAT-2 Sea-Surface Temperatures in the Tropical Western Pacific Ocean

et al. 2018

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Over several decades, improving the accuracy of Sea-Surface Temperatures (SSTs) derived from satellites has been a subject of intense research, and continues to be so. Knowledge of the accuracy of the SSTs is critical for weather and climate predictions, and many research and operational applications. In 2015, the operational Japanese MTSAT-2 geostationary satellite was replaced by the Himawari-8, which has a visible and infrared imager with higher spatial and temporal resolutions than its predecessor. In this study, data from both satellites during a three-month overlap period were compared with subsurface in situ temperature measurements from the Tropical Atmosphere Ocean (TAO) array and self-recording thermometers at the depths of corals of the Great Barrier Reef. Results show that in general the Himawari-8 provides more accurate SST measurements compared to those from MTSAT-2. At various locations, where in situ measurements were taken, the mean Himawari-8 SST error shows an improvement of~0.15 K. Sources of the differences between the satellite-derived SST and the in situ temperatures were related to wind speed and diurnal heating.

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On tropical cyclone frequency and the warm pool area

Cited by 14 publications

References 40 publications

Climate change and projections for the Barents region: what is expected to change and what will stay the same?

Climate change and projections for the Barents region: what is expected to change and what will stay the same?

Intense tropical cyclone activities in the northern Indian Ocean

The Accuracies of Himawari-8 and MTSAT-2 Sea-Surface Temperatures in the Tropical Western Pacific Ocean

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