This page has only limited features, please log in for full access.

Mr. Dawei Shi
Lianyungang Meteorological Bureau

Basic Info

Basic Info is private.

Research Keywords & Expertise

0 Computer Science
0 Weather Forecasting
0 AI
0 Meteorology Science
0 machining learning

Honors and Awards

The user has no records in this section


Career Timeline

The user has no records in this section.


Short Biography

The user biography is not available.
Following
Followers
Co Authors
The list of users this user is following is empty.
Following: 0 users

Feed

Journal article
Published: 12 March 2020 in Water
Reads 0
Downloads 0

Assessing the long-term precipitation changes is of utmost importance for understanding the impact of climate change. This study investigated the variability of extreme precipitation events over Pakistan on the basis of daily precipitation data from 51 weather stations from 1980-2016. The non-parametric Mann–Kendall, Sen’s slope estimator, least squares method, and two-tailed simple t-test methods were used to assess the trend in eight precipitation extreme indices. These indices were wet days (R1 ≥1 mm), heavy precipitation days (R10 ≥ 10 mm), very heavy precipitation days (R20 ≥ 20 mm), severe precipitation (R50 ≥ 50 mm), very wet days (R95p) defining daily precipitation ≥ 95 percentile, extremely wet days (R99p) defining daily precipitation ≥ 99 percentile, annual total precipitation in wet days (PRCPTOT), and mean precipitation amount on wet days as simple daily intensity index (SDII). The study is unique in terms of using high stations’ density, extended temporal coverage, advanced statistical techniques, and additional extreme indices. Furthermore, this study is the first of its kind to detect abrupt changes in the temporal trend of precipitation extremes over Pakistan. The results showed that the spatial distribution of trends in different precipitation extreme indices over the study region increased as a whole; however, the monsoon and westerlies humid regions experienced a decreasing trend of extreme precipitation indices during the study period. The results of the sequential Mann–Kendall (SqMK) test showed that all precipitation extremes exhibited abrupt dynamic changes in temporal trend during the study period; however, the most frequent mutation points with increasing tendency were observed during 2011 and onward. The results further illustrated that the linear trend of all extreme indices showed an increasing tendency from 1980- 2016. Similarly, for elevation, most of the precipitation extremes showed an inverse relationship, suggesting a decrease of precipitation along the latitudinal extent of the country. The spatiotemporal variations in precipitation extremes give a possible indication of the ongoing phenomena of climate change and variability that modified the precipitation regime of Pakistan. On the basis of the current findings, the study recommends that future studies focus on underlying physical and natural drivers of precipitation variability over the study region.

ACS Style

Asher Samuel Bhatti; Guojie Wang; Waheed Ullah; Safi Ullah; Daniel Fiifi Tawia Hagan; Isaac Kwesi Nooni; Dan Lou; Irfan Ullah. Trend in Extreme Precipitation Indices Based on Long Term In Situ Precipitation Records over Pakistan. Water 2020, 12, 797 .

AMA Style

Asher Samuel Bhatti, Guojie Wang, Waheed Ullah, Safi Ullah, Daniel Fiifi Tawia Hagan, Isaac Kwesi Nooni, Dan Lou, Irfan Ullah. Trend in Extreme Precipitation Indices Based on Long Term In Situ Precipitation Records over Pakistan. Water. 2020; 12 (3):797.

Chicago/Turabian Style

Asher Samuel Bhatti; Guojie Wang; Waheed Ullah; Safi Ullah; Daniel Fiifi Tawia Hagan; Isaac Kwesi Nooni; Dan Lou; Irfan Ullah. 2020. "Trend in Extreme Precipitation Indices Based on Long Term In Situ Precipitation Records over Pakistan." Water 12, no. 3: 797.

Journal article
Published: 26 December 2019 in Atmosphere
Reads 0
Downloads 0

Soil moisture is an important parameter in land surface processes, which can control the surface energy and water budgets and thus affect the air temperature. Studying the coupling between soil moisture and air temperature is of vital importance for forecasting climate change. This study evaluates this coupling over China from 1980–2013 by using an energy-based diagnostic method, which represents the momentum, heat, and water conservation equations in the atmosphere, while the contributions of soil moisture are treated as external forcing. The results showed that the soil moisture–temperature coupling is strongest in the transitional climate zones between wet and dry climates, which here includes Northeast China and part of the Tibetan Plateau from a viewpoint of annual average. Furthermore, the soil moisture–temperature coupling was found to be stronger in spring than in the other seasons over China, and over different typical climatic zones, it also varied greatly in different seasons. We conducted two case studies (the heatwaves of 2013 in Southeast China and 2009 in North China) to understand the impact of soil moisture–temperature coupling during heatwaves. The results indicated that over areas with soil moisture deficit and temperature anomalies, the coupling strength intensified. This suggests that soil moisture deficits could lead to enhanced heat anomalies, and thus, result in enhanced soil moisture coupling with temperature. This demonstrates the importance of soil moisture and the need to thoroughly study it and its role within the land–atmosphere interaction and the climate on the whole.

ACS Style

Qing Yuan; Guojie Wang; Chenxia Zhu; Dan Lou; Daniel Fiifi Tawia Hagan; Xiaowen Ma; Mingyue Zhan. Coupling of Soil Moisture and Air Temperature from Multiyear Data During 1980–2013 over China. Atmosphere 2019, 11, 25 .

AMA Style

Qing Yuan, Guojie Wang, Chenxia Zhu, Dan Lou, Daniel Fiifi Tawia Hagan, Xiaowen Ma, Mingyue Zhan. Coupling of Soil Moisture and Air Temperature from Multiyear Data During 1980–2013 over China. Atmosphere. 2019; 11 (1):25.

Chicago/Turabian Style

Qing Yuan; Guojie Wang; Chenxia Zhu; Dan Lou; Daniel Fiifi Tawia Hagan; Xiaowen Ma; Mingyue Zhan. 2019. "Coupling of Soil Moisture and Air Temperature from Multiyear Data During 1980–2013 over China." Atmosphere 11, no. 1: 25.

Journal article
Published: 14 March 2019 in Remote Sensing
Reads 0
Downloads 0

Various state-of-the-art gridded satellite precipitation products (GPPs) have been derived from remote sensing and reanalysis data and are widely used in hydrological studies. An assessment of these GPPs against in-situ observations is necessary to determine their respective strengths and uncertainties. GPPs developed from satellite observations as a primary source were compared to in-situ observations, namely the Climate Hazard group Infrared Precipitation with Stations (CHIRPS), Multi-Source Weighted-Ensemble Precipitation (MSWEP), Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks-Climate Data Record (PERSIANN-CDR) and Tropical Rainfall Measuring Mission (TRMM) multi-satellite precipitation analysis (TMPA). These products were compared to in-situ data from 51 stations, spanning 1998–2016, across Pakistan on daily, monthly, annual and interannual time scales. Spatiotemporal climatology was well captured by all products, with more precipitation in the north eastern parts during the monsoon months and vice-versa. Daily precipitation with amount larger than 10 mm showed significant (95%, Kolmogorov-Smirnov test) agreement with the in-situ data, especially TMPA, followed by CHIRPS and MSWEP. At monthly scales, there were significant correlations (R) between the GPPs and in-situ records, suggesting similar dynamics; however, statistical metrics suggested that the performance of these products varies from north towards south. Temporal agreement on an interannual scale was higher in the central and southern parts which followed precipitation seasonality. TMPA performed the best, followed in order by CHIRPS, MSWEP and PERSIANN-CDR.

ACS Style

Waheed Ullah; Guojie Wang; Gohar Ali; Daniel Fiifi Tawia Hagan; Asher Samuel Bhatti; Dan Lou. Comparing Multiple Precipitation Products against In-Situ Observations over Different Climate Regions of Pakistan. Remote Sensing 2019, 11, 628 .

AMA Style

Waheed Ullah, Guojie Wang, Gohar Ali, Daniel Fiifi Tawia Hagan, Asher Samuel Bhatti, Dan Lou. Comparing Multiple Precipitation Products against In-Situ Observations over Different Climate Regions of Pakistan. Remote Sensing. 2019; 11 (6):628.

Chicago/Turabian Style

Waheed Ullah; Guojie Wang; Gohar Ali; Daniel Fiifi Tawia Hagan; Asher Samuel Bhatti; Dan Lou. 2019. "Comparing Multiple Precipitation Products against In-Situ Observations over Different Climate Regions of Pakistan." Remote Sensing 11, no. 6: 628.

Journal article
Published: 19 December 2018 in Water
Reads 0
Downloads 0

Evapotranspiration (ET), a critical process in global climate change, is very difficult to estimate at regional and basin scales. In this study, we evaluated five ET products: the Global Land Surface Evaporation with the Amsterdam Methodology (GLEAM, the EartH2Observe ensemble (E2O)), the Global Land Data Assimilation System with Noah Land Surface Model-2 (GLDAS), a global ET product at 8 km resolution from Zhang (ZHANG) and a supplemental land surface product of the Modern-ERA Retrospective analysis for Research and Applications (MERRA_land), using the water balance method in the Yellow River Basin, China, including twelve catchments, during the period of 1982–2000. The results showed that these ET products have obvious different performances, in terms of either their magnitude or temporal variations. From the viewpoint of multiple-year averages, the MERRA_land product shows a fairly similar magnitude to the ETw derived from the water balance method, while the E2O product shows significant underestimations. The GLEAM product shows the highest correlation coefficient. From the viewpoint of interannual variations, the ZHANG product performs best in terms of magnitude, while the E2O still shows significant underestimations. However, the E2O product best describes the interannual variations among the five ET products. Further study has indicated that the discrepancies between the ET products in the Yellow River Basin are mainly due to the quality of precipitation forcing data. In addition, most ET products seem to not be sensitive to the downward shortwave radiation.

ACS Style

Guojie Wang; Jian Pan; Chengcheng Shen; Shijie Li; Jiao Lu; Dan Lou; Daniel F. T. Hagan. Evaluation of Evapotranspiration Estimates in the Yellow River Basin against the Water Balance Method. Water 2018, 10, 1884 .

AMA Style

Guojie Wang, Jian Pan, Chengcheng Shen, Shijie Li, Jiao Lu, Dan Lou, Daniel F. T. Hagan. Evaluation of Evapotranspiration Estimates in the Yellow River Basin against the Water Balance Method. Water. 2018; 10 (12):1884.

Chicago/Turabian Style

Guojie Wang; Jian Pan; Chengcheng Shen; Shijie Li; Jiao Lu; Dan Lou; Daniel F. T. Hagan. 2018. "Evaluation of Evapotranspiration Estimates in the Yellow River Basin against the Water Balance Method." Water 10, no. 12: 1884.