scholarly journals Assimilating monthly precipitation data in a paleoclimate data assimilation framework

2020 ◽  
Vol 16 (4) ◽  
pp. 1309-1323
Author(s):  
Veronika Valler ◽  
Yuri Brugnara ◽  
Jörg Franke ◽  
Stefan Brönnimann
Keyword(s):  
Data Assimilation ◽  
Sea Level ◽  
Monthly Precipitation ◽  
Precipitation Data ◽  
Sea Level Pressure ◽  
Model Simulations ◽  
Level Pressure ◽  
Proxy Records ◽  
Climate Reconstructions ◽  
Data Source

Abstract. Data assimilation approaches such as the ensemble Kalman filter method have become an important technique for paleoclimatological reconstructions and reanalysis. Different sources of information, from proxy records and documentary data to instrumental measurements, were assimilated in previous studies to reconstruct past climate fields. However, precipitation reconstructions are often based on indirect sources (e.g., proxy records). Assimilating precipitation measurements is a challenging task because they have high uncertainties, often represent only a small region, and generally do not follow a Gaussian distribution. In this paper, experiments are conducted to test the possibility of using information about precipitation in climate reconstruction with monthly resolution by assimilating monthly instrumental precipitation amounts or the number of wet days per month, solely or in addition to other climate variables such as temperature and sea-level pressure, into an ensemble of climate model simulations. The skill of all variables (temperature, precipitation, sea-level pressure) improved over the pure model simulations when only monthly precipitation amounts were assimilated. Assimilating the number of wet days resulted in similar or better skill compared to assimilating the precipitation amount. The experiments with different types of instrumental observations being assimilated indicate that precipitation data can be useful, particularly if no other variable is available from a given region. Overall the experiments show promising results because with the assimilation of precipitation information a new data source can be exploited for climate reconstructions. The wet day records can become an especially important data source in future climate reconstructions because many existing records date several centuries back in time and are not limited by the availability of meteorological instruments.

scholarly journals Assimilating monthly precipitation data in a paleoclimate data assimilation framework

2019 ◽  
Author(s):  
Veronika Valler ◽  
Yuri Brugnara ◽  
Jörg Franke ◽  
Stefan Brönnimann
Keyword(s):  
Data Assimilation ◽  
Sea Level ◽  
Monthly Precipitation ◽  
Precipitation Data ◽  
Sea Level Pressure ◽  
Model Simulations ◽  
Level Pressure ◽  
Proxy Records ◽  
Climate Reconstructions ◽  
Data Source

Abstract. Data assimilation approaches such as the ensemble Kalman filter method have become an important technique for paleoclimatological reconstructions and reanalysis. Different sources of information from proxy records and documentary data to instrumental measurements were assimilated in previous studies to reconstruct past climate fields. However, precipitation reconstructions are often based on indirect sources (e.g., proxy records). Assimilating precipitation measurements is a challenging task because they have high uncertainties, often represent only a small region and generally do not follow Gaussian distribution. In this paper, a set of experiments are conducted to test the possibility of using information about precipitation in climate reconstruction with monthly resolution by assimilating monthly instrumental precipitation amounts or the number of wet days per month, solely or in addition to other climate variables such as temperature and sea level pressure, into an ensemble of climate model simulations. The skill of all variables (temperature, precipitation, sea-level pressure) improved over the pure model simulations when only monthly precipitation amounts were assimilated. Assimilating the number of wet days resulted in similar or better skill compared to assimilating precipitation amount. The experiments with different types of instrumental observations being assimilated indicate that precipitation data can be useful, particularly if no other variable is available from a given region. Overall the experiments show promising results because with the assimilation of precipitation information a new data source can be exploited for climate reconstructions. Especially the wet day records can become an important data source in future climate reconstructions because many existing records date several centuries back in time and are not limited by the availability of meteorological instruments.

Assimilation of Tropical Cyclone Advisory Minimum Sea Level Pressure in the NCEP Global Data Assimilation System

2011 ◽  
Vol 26 (6) ◽  
pp. 1085-1091 ◽  
Author(s):  
Daryl T. Kleist
Keyword(s):  
Data Assimilation ◽  
Sea Level ◽  
Sea Level Pressure ◽  
Level Pressure ◽  
Global Data Assimilation System ◽  
Data Assimilation System ◽  
Global Data ◽  
Minimum Sea Level Pressure ◽  
Assimilation System ◽  
Tropical Systems

Abstract The assimilation of official advisory minimum sea level pressure observations has been developed and tested in the National Centers for Environmental Prediction (NCEP) Global Data Assimilation System (GDAS) to address forecaster concerns regarding some tropical systems being far too weak in operational Global Forecast System (GFS) analyses. The assimilation of these observations has been operational in the GFS since December 2009. Using the T574 version of the NCEP GFS model, it is demonstrated that the assimilation of these observations results in a substantial reduction in the initial intensity bias for tropical systems, resulting in improved track and intensity guidance for lead times out to 5 days.

scholarly journals The Tropospheric Land–Sea Warming Contrast as the Driver of Tropical Sea Level Pressure Changes

2013 ◽  
Vol 26 (4) ◽  
pp. 1387-1402 ◽  
Author(s):  
Tobias Bayr ◽  
Dietmar Dommenget
Keyword(s):  
Climate Change ◽  
Sea Level ◽  
Large Scale ◽  
Warm Pool ◽  
Sea Level Pressure ◽  
Model Simulations ◽  
Level Pressure ◽  
Pacific Warm Pool ◽  
Tropical Sea ◽  
Sea Warming

Abstract This article addresses the causes of the large-scale tropical sea level pressure (SLP) changes during climate change. The analysis presented here is based on model simulations, observed trends, and the seasonal cycle. In all three cases the regional changes of tropospheric temperature (Ttropos) and SLP are strongly related to each other [considerably more strongly than (sea) surface temperature and SLP]. This relationship basically follows the Bjerknes circulation theorem, with relatively low regional SLP where there is relatively high Ttropos and vice versa. A simple physical model suggests a tropical SLP response to horizontally inhomogeneous warming in the tropical Ttropos, with a sensitivity coefficient of about −1.7 hPa K−1. This relationship explains a large fraction of observed and predicted changes in the tropical SLP. It is shown that in climate change model simulations the tropospheric land–sea warming contrast is the most significant structure in the regional Ttropos changes relative to the tropical mean changes. Since the land–sea warming contrast exists in the absence of any atmospheric circulation changes, it can be argued that the large-scale response of tropical SLP changes is to first order a response to the tropical land–sea warming contrast. Furthermore, as the land–sea warming contrast is mostly moisture dependent, the models predict a stronger warming and decreasing SLP in the drier regions from South America to Africa and a weaker warming and increasing SLP over the wetter Indo-Pacific warm pool region. This suggests an increase in the potential for deep convection conditions over the Atlantic sector and a decrease over the Indo-Pacific warm pool region in the future.

scholarly journals A DRP–4DVar Data Assimilation Scheme for Typhoon Initialization Using Sea Level Pressure Data

2012 ◽  
Vol 140 (4) ◽  
pp. 1191-1203 ◽  
Author(s):  
Ying Zhao ◽  
Bin Wang ◽  
Juanjuan Liu
Keyword(s):  
Data Assimilation ◽  
Sea Level ◽  
Mesoscale Model ◽  
Storm Track ◽  
Initial Step ◽  
State University ◽  
Sea Level Pressure ◽  
Level Pressure ◽  
Fifth Generation ◽  
Typhoon Track

In this study, a new data assimilation system based on a dimension-reduced projection (DRP) technique was developed for the fifth-generation Pennsylvania State University–NCAR Mesoscale Model (MM5) modeling system. As an initial step to test the newly developed system, observing system simulation experiments (OSSEs) were conducted using a simulated sea level pressure (SLP) field as “observations” and assimilation experiments using a specified SLP field to evaluate the effects of the new DRP–four-dimensional variational data assimilation (4DVar) method, initialization, and simulation of a tropical storm—Typhoon Bilis (2006) over the western North Pacific. In the OSSEs, the “nature” run, which was assumed to represent the “true” atmosphere, was simulated by the MM5 model, which was initialized with the 1.0° × 1.0° NCEP final global tropospheric analyses and integrated for 120 h. The simulated SLP field was then used as the observations in the data assimilation. It is shown that the MM5 DRP–4DVar system can successfully assimilate the (simulated) model output (used as observations) because the OSSEs resulted in improved storm-track forecasts. In addition, compared with an experiment that assimilated the SLP data fixed at the end of a 6-h assimilation window, the experiment that assimilated the SLP data every 3 min in a 30-min assimilation window further improved the typhoon-track forecasts, especially in terms of the initial vortex location and landfall location. Finally, the assimilation experiments with a specified SLP field have demonstrated the effectiveness of the new method.

scholarly journals Complex network approach for detecting tropical cyclones

2021 ◽  
Author(s):  
Shraddha Gupta ◽  
Niklas Boers ◽  
Florian Pappenberger ◽  
Jürgen Kurths
Keyword(s):  
Sea Level ◽  
Tropical Cyclones ◽  
Complex Network ◽  
Time Scales ◽  
Southern Oscillation ◽  
Volcanic Eruptions ◽  
Network Approach ◽  
Sea Level Pressure ◽  
Level Pressure ◽  
Climate Networks

AbstractTropical cyclones (TCs) are one of the most destructive natural hazards that pose a serious threat to society, particularly to those in the coastal regions. In this work, we study the temporal evolution of the regional weather conditions in relation to the occurrence of TCs using climate networks. Climate networks encode the interactions among climate variables at different locations on the Earth’s surface, and in particular, time-evolving climate networks have been successfully applied to study different climate phenomena at comparably long time scales, such as the El Niño Southern Oscillation, different monsoon systems, or the climatic impacts of volcanic eruptions. Here, we develop and apply a complex network approach suitable for the investigation of the relatively short-lived TCs. We show that our proposed methodology has the potential to identify TCs and their tracks from mean sea level pressure (MSLP) data. We use the ERA5 reanalysis MSLP data to construct successive networks of overlapping, short-length time windows for the regions under consideration, where we focus on the north Indian Ocean and the tropical north Atlantic Ocean. We compare the spatial features of various topological properties of the network, and the spatial scales involved, in the absence and presence of a cyclone. We find that network measures such as degree and clustering exhibit significant signatures of TCs and have striking similarities with their tracks. The study of the network topology over time scales relevant to TCs allows us to obtain crucial insights into the effects of TCs on the spatial connectivity structure of sea-level pressure fields.

scholarly journals Tropical cyclone simulations over Bangladesh at convection permitting 4.4 km & 1.5 km resolution

2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Hamish Steptoe ◽  
Nicholas Henry Savage ◽  
Saeed Sadri ◽  
Kate Salmon ◽  
Zubair Maalick ◽  
...  
Keyword(s):  
Wind Speed ◽  
Tropical Cyclone ◽  
Sea Level ◽  
Tropical Cyclones ◽  
Weather Forecasting ◽  
Sea Level Pressure ◽  
Mean Sea Level ◽  
Level Pressure ◽  
Medium Range ◽  
Gust Speed

AbstractHigh resolution simulations at 4.4 km and 1.5 km resolution have been performed for 12 historical tropical cyclones impacting Bangladesh. We use the European Centre for Medium-Range Weather Forecasting 5th generation Re-Analysis (ERA5) to provide a 9-member ensemble of initial and boundary conditions for the regional configuration of the Met Office Unified Model. The simulations are compared to the original ERA5 data and the International Best Track Archive for Climate Stewardship (IBTrACS) tropical cyclone database for wind speed, gust speed and mean sea-level pressure. The 4.4 km simulations show a typical increase in peak gust speed of 41 to 118 knots relative to ERA5, and a deepening of minimum mean sea-level pressure of up to −27 hPa, relative to ERA5 and IBTrACS data. The downscaled simulations compare more favourably with IBTrACS data than the ERA5 data suggesting tropical cyclone hazards in the ERA5 deterministic output may be underestimated. The dataset is freely available from 10.5281/zenodo.3600201.

scholarly journals Analysis of Atmospheric and Ionospheric Variations Due to Impacts of Super Typhoon Mangkhut (1822) in the Northwest Pacific Ocean

2021 ◽  
Vol 13 (4) ◽  
pp. 661
Author(s):  
Mohamed Freeshah ◽  
Xiaohong Zhang ◽  
Erman Şentürk ◽  
Muhammad Arqim Adil ◽  
B. G. Mousa ◽  
...  
Keyword(s):  
Wind Speed ◽  
Pacific Ocean ◽  
Tropical Cyclone ◽  
Sea Level ◽  
Northwest Pacific ◽  
Northwest Pacific Ocean ◽  
Sea Level Pressure ◽  
Level Pressure ◽  
Super Typhoon ◽  
The Northwest Pacific Ocean

The Northwest Pacific Ocean (NWP) is one of the most vulnerable regions that has been hit by typhoons. In September 2018, Mangkhut was the 22nd Tropical Cyclone (TC) over the NWP regions (so, the event was numbered as 1822). In this paper, we investigated the highest amplitude ionospheric variations, along with the atmospheric anomalies, such as the sea-level pressure, Mangkhut’s cloud system, and the meridional and zonal wind during the typhoon. Regional Ionosphere Maps (RIMs) were created through the Hong Kong Continuously Operating Reference Stations (HKCORS) and International GNSS Service (IGS) data around the area of Mangkhut typhoon. RIMs were utilized to analyze the ionospheric Total Electron Content (TEC) response over the maximum wind speed points (maximum spots) under the meticulous observations of the solar-terrestrial environment and geomagnetic storm indices. Ionospheric vertical TEC (VTEC) time sequences over the maximum spots are detected by three methods: interquartile range method (IQR), enhanced average difference (EAD), and range of ten days (RTD) during the super typhoon Mangkhut. The research findings indicated significant ionospheric variations over the maximum spots during this powerful tropical cyclone within a few hours before the extreme wind speed. Moreover, the ionosphere showed a positive response where the maximum VTEC amplitude variations coincided with the cyclone rainbands or typhoon edges rather than the center of the storm. The sea-level pressure tends to decrease around the typhoon periphery, and the highest ionospheric VTEC amplitude was observed when the low-pressure cell covers the largest area. The possible mechanism of the ionospheric response is based on strong convective cells that create the gravity waves over tropical cyclones. Moreover, the critical change state in the meridional wind happened on the same day of maximum ionospheric variations on the 256th day of the year (DOY 256). This comprehensive analysis suggests that the meridional winds and their resulting waves may contribute in one way or another to upper atmosphere-ionosphere coupling.

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