The RDI is expressed in three forms: the initial value (α_k), normalized RDI (RDIn), and standardized RDI (RDIst). The initial value (α_k) of RDI is presented in an aggregated form using a monthly timestep and is usually calculated for i-th year in a time basis of k of consecutive months using following equation: α_(`k)^((i))=(∑_(j=1)^k▒P_ij )/(∑_(j=1)^k▒〖ETo〗_ij ),i=1,…,N and j=1,…,k Where pij and EToij are precipitation and ETo of the j-th month of the i-th year and N is the total number of years of the available data. The normalized RDI (RDIn) is estimated as follows: 〖RDI〗_(n(k))^((i))=(α_k^((i)))/(α_k ) ̅ -1 In which α ̅_k is the arithmetic mean of α_k values. Tsakiris et al. (2008) though analysis of various data from several location and different timescales shown that α_k values follow satisfactorily both gamma and lognormal distributions however gamma distribution shows the best fit in most timescales and locations. Therefore, the calculation of third form (RDIst) performed by fitting the gamma probability density function to the given frequency distribution of α_k . The following equations have been used to calculate the standardized RDI (RDIst). The probability function of gamma distribution is defined as: g(x)=1/(β^γ Γ(γ)) x^(γ-1) e^(-x/β), for x>0 Where γ>0 is a shape factor, β>0 is a scale factor, and Γ(γ) is the gamma function. Parameters γ and β of the gamma function are estimated or each time scale (k) and for each location. Maximum
From the CER maps (Figure 9), it can be observed that in 2013 ISMR the entire region had witnessed high CER values while other years were partially cover by cloud drops of different radii. The high rainfall intensity during 2013 ISMR could be the manifestation of the high CER values observed during that year compared to the other years (Figure 12). However, the low CER values in the other years can be seen in conjugation with high aerosol loading during that period. Similar trend is also observed in LWP plots for the study area during 2012-15 ISMR (Fig 13). It is evident from the figure 9 that LWP varies from low to high values over the region while, it is more homogeneous in 2014 and 2015 ISMR. The OLR was considerably
Statistical results of the data analysis have been received by using the Gauss curve, as preferred distribution function, and the
1) Which type of function (linear, exponential, or cubic) do you believe will best fit the data? Support your choice.
GEOG 104 – Weather Climate Society: You have gotten 283.5/425 66.7% of the available points thus far. I know that this is your most difficult class; however, I have seen you working with your assigned tutor for this class. Please, come every day to prepare for this class. Your Exam # 2 is going to be given this Thursday, November 12th, contact your tutor and prepare very well for this
Seeking cardiovascular technician who are able to monitoring patients and assisting doctors with performing angiograms, PCIs, Interventional Radiology procedures, and Electrophysiology procedures. Minimum requirement: Registered Cardiovascular Invasive Specialist (RCIS) or Registered Cardiovascular Electrophysiology Specialist (RCES). This is an example of the many job posting for cardiovascular technician. What do these individuals have in common that cardiac laboratory can accept either credentials? What set them apart to have different credential title? It is easier to discuss the similarities of both RCIS and RCES registrant since they are so similar.
The data in the charts provides information to support the theory that less rainfall will
standard deviation standardized value rescaling z-score normal model parameter statistic standard Normal model 68-95-99.7 Rule normal probability plot
Mean precipitation is another factor
Quito is the capital city from Ecuador where is considering a high elevation area with approximately 2800 meters above sea level in its elevation. Also, the city is located in the center of Andean Region and it is influenced by the equatorial line with latitudes nearest to 0 grades and being in a Tropical Region without seasons (Figure 1). Moreover, Quito doesn’t present stations, only the city shows two times considered like a dry and a wet season. The mean temperature during the year has a mean in minimum about 9.0°C and a maximum 25.4 °C20, also presented a high precipitation near to 1126 mm on 2015 that let to have a high density cloud every year.
Maryland and the District of Columbia have similar average annual precipitation patterns (based on a period of 30 years from 1951-1980) with 42 inches and 43 inches, respectively. Although the precipitation pattern distributed evenly throughout the year, the spring and summer months (May – September) get approximately 2.5 inches more precipitation compared to the rest of the year (USGS, 1999). Furthermore, apart from the seasonal variation in the precipitation rates, there has been an increase in the annual precipitation rate of Washington, DC, since 1965 (see methods/discussion
Heavy precipitation events that historically occurred once in 20 years are projected to occur as frequently as every 5 to 15 years by this late century. Short term droughts are expected to intensify in most regions. Longer term droughts are expected to intensify in larger regions in the Southwest. Flooding may intensify in many U.S regions. Climate change is affecting the groundwater availability also. Sea level rising and storms surges are expected to compromise the sustainability of coastal freshwater and
St. Louis falls into the mellow midlatitude atmosphere gathering, and this is a district loaded with air mass complexities (Hess, 2011). These differentiations cause a mixture of unsettling influences in the air leaving St. Louis with an assortment of climate (Hess, 2011). The summers have a tendency to have more precipitation with the coastal stream and incessant convection (Hess, 2011). However winter can encounter rain and periodic snow due to midlatitude typhoons (Hess, 2011).
Diaz, H. F., & Wahl, E. R. (2015). Recent California Water Year Precipitation Deficits: A 440-Year Perspective*. Journal Of Climate, 28(12), 4637-4652. doi:10.1175/JCLI-D-14-00774.1
Variations in the Prediction of Semipermanent Drought Conditions in the Great Plains Region and the Methods Used to Derive These Predictions
For example, the National Drought Mitigation Center faculty and staff have worked with international organizations and countries around the world to defend drought. It provides a variety of services, including planning, research, outreach and capacity building. Recently, this organization focuses on organizing and hosting a workshop to select a single index as the global standard for monitoring meteorological drought. Besides, this organization also conduct training on the Standardized Precipitation Index (SPI). Up to now, The NDMC has distributed the SPI to more than 150 scientists in 60 countries around the