Building a portal for climate data—Mapping automation, visualization, and dissemination

2021 ◽  
Author(s):  
Jared McLean ◽  
Sean B. Cleveland ◽  
Michael Dodge ◽  
Matthew P. Lucas ◽  
Ryan J. Longman ◽  
...  
Keyword(s):  
Data Mapping ◽  
Climate Data

Scientists struggle to access Africa's historical climate data

Nature ◽  
2019 ◽  
Vol 574 (7780) ◽  
pp. 605-606 ◽  
Author(s):  
Linda Nordling
Keyword(s):  
Climate Data ◽  
Historical Climate

UK climate data were not tampered with

Nature ◽  
2010 ◽  
Author(s):  
Zeeya Merali
Keyword(s):  
Climate Data

Shellfish could supplant tree-ring climate data

Nature ◽  
2010 ◽  
Author(s):  
Richard A. Lovett
Keyword(s):  
Tree Ring ◽  
Climate Data

Use of soil and climate data to assess the risk of agricultural drought for policy support in Europe

Agronomie ◽  
2001 ◽  
Vol 21 (1) ◽  
pp. 45-56 ◽  
Author(s):  
Pandi Zdruli ◽  
Robert J.A. Jones ◽  
Luca Montanarella
Keyword(s):  
Policy Support ◽  
Agricultural Drought ◽  
Climate Data

EL NINO RELATED CLIMATE AND DENGUE FEVER CASES IN JEDDAH, SAUDI ARABIA

2019 ◽  
Vol 25 (1) ◽  
Author(s):  
MASROOR ALI KHAN ◽  
KHALID AL GHAMDI ◽  
JAZEM A. MEHYOUB ◽  
RAKHSHAN KHAN
Keyword(s):  
Relative Humidity ◽  
Dengue Fever ◽  
El Niño ◽  
Significant Relationship ◽  
El Nino ◽  
Climate Data ◽  
Light Traps ◽  
Mosquito Abundance ◽  
Dengue Transmission ◽  
The Relationship

The focus of this study is to find the relationship between El Nino and dengue fever cases in the study area.Mosquito density was recorded with the help of light traps and through aspirators collection. Climate data were obtained from National Meteorology and Environment centre. (Year wise El Nino and La Nina data are according to NOAA & Golden Gate Weather Services). Statistical methods were used to establish the correlation coefficient between different factors. A high significant relationship was observed between Relative Humidity and Dengue fever cases, but Aedes abundance had no significant relationship with either Relative humidity and Temperature. Our conclusion is that the El Nino does not affect the dengue transmission and Aedes mosquito abundance in this region, which is supported by earlier works.

Rainfall Prediction in South-Eastern Part of Bangladesh by Linear Regression Method

2018 ◽  
Vol 6 (6) ◽  
pp. 119
Author(s):  
Mohammad Shohidul Islam ◽  
Sultana Easmin Siddika ◽  
S M Injamamul Haque Masum
Keyword(s):  
Linear Regression ◽  
Correlation Coefficients ◽  
Rain Gauge ◽  
Regression Method ◽  
Linear Regression Method ◽  
Climate Data ◽  
Rainfall Forecasting ◽  
Statistical Parameters ◽  
Time Duration ◽  
Rainfall Prediction

Rainfall forecasting is very challenging task for the meteorologists. Over the last few decades, several models have been utilized, attempting the successful analysing and forecasting of rainfall. Recorded climate data can play an important role in this regard. Long-time duration of recorded data can be able to provide better advancement of rainfall forecasting. This paper presents the utilization of statistical techniques, particularly linear regression method for modelling the rainfall prediction over Bangladesh. The rainfall data for a period of 11 years was obtained from Bangladesh Meteorological department (BMD), Dhaka i.e. that was surface-based rain gauge rainfall which was acquired from 08 weather stations over Bangladesh for the years of 2001-2011. The monthly and yearly rainfall was determined. In order to assess the accuracy of it some statistical parameters such as average, meridian, correlation coefficients and standard deviation were determined for all stations. The model prediction of rainfall was compared with true rainfall which was collected from rain gauge of different stations and it was found that the model rainfall prediction has given good results.

Santee Experimental Forest, Headquarters: climate data

2020 ◽  
Author(s):  
Devendra M. Amatya ◽  
Carl C. Trettin
Keyword(s):  
Climate Data

Flower phenology and climate data for Artemisia tridentata populations

2017 ◽  
Author(s):  
Bryce A. Richardson ◽  
Linsay Chaney ◽  
Nancy L. Shaw ◽  
Shannon M. Still
Keyword(s):  
Artemisia Tridentata ◽  
Climate Data ◽  
Flower Phenology
Sign in / Sign up

Export Citation Format

Share Document