The Qatar Meteorological Department is introducing monthly and seasonal (3-month)
climate outlooks for Qatar and adjoining regions, beginning April 2014. Monthly
and seasonal climate forecasts are generated world wide with an underlying assumption
that sea surface temperatures in global oceans, snow-cover, soil-moisture of the
land surface and other such slowly varying boundary conditions determine the ensuing
global and regional climate anomalies. Leading climate centers around the world
use fully coupled ocean-atmosphere general circulation models for generating seasonal
climate forecasts wherein both sea surface temperatures and associated atmospheric
circulation co-evolve. Climate forecasts are generally in the form of anomalies
from a long-term climatology as simulated in the models. Individual climate centers
produce monthly/seasonal forecasts based on a large suite of simulations (generally
initiated every month and extending 6 months in to the future) with different initial
conditions using their global climate model and then develop an ensemble forecast
product employing advanced statistical techniques.
World Meteorological Organization (WMO) supports and coordinates seasonal forecasts
through lead centers (LC) of long-range forecasts (LRF). Korea Meteorological Administration,
Seoul, maintains one such lead center. This WMO Lead Center (WMOLC) uses all available
forecasts from different climate centers around the world and generates multi-model
ensemble (MME) monthly and seasonal climate forecasts for the globe. Several meteorological
variables are predicted which include surface temperature (2m), precipitation etc.
Apart from WMOLC, other climate centers like International Research Institute for
Climate and Society (IRI, New York, USA), National Centers for Environmental Prediction
(NCEP/NOAA, USA), APEC Climate Center (APCC, Korea), UK Meteorological Office (UKMO,
UK), ECMWF (UK), Bureau of Meteorology (BoM, Australia) etc. also produce monthly/seasonal
In preparation of this Climate Outlook for Qatar the monthly/seasonal products generated
by the WMOLC have been used. This approach takes in to account a majority of the
model forecasts from the Global Producing Centers (GPCs) and combines them using
ensemble mean forecast system. However, we also take in to consideration of other
forecast products while generating the outlook for the regional temperature and
precipitation anomalies for the coming month and season.
The skill of WMOLC ensemble mean forecast products varies from month to month and
from one meteorological variable to the other. Generally the skills of temperature
forecasts are larger compared to the precipitation forecasts. This disparity in
skills between temperature and precipitation forecasts is not unique to this region
and is the case globally. The correlation skills estimated based on retrospective
(hindcast) forecasts during the past 30 years of MME prediction system are in the
range of 0.4-0.6 during different months in the year and for the surface temperatures
over this region. These are considered reasonably high compared to the skills observed
in other parts of the world.
The current Climate Outlook for Qatar is mainly for monthly/seasonal mean temperature
forecast. The reason for the initial focus on temperatures is both due to higher
skill and its prime relevance to climate sensitive activities in the national context.
With further review of predictive skill and demand of user sectors, the scope of
the seasonal climate outlooks can be expanded to cover more features of relevance
to this region such as the probability of high wind events, exceedance of certain
temperature thresholds etc.
Two types of forecast products are generated by climate centers. One is the probabilistic
forecast where the seasonal climate anomalies are predicted to be in one of the
three categories (below normal, normal and above normal) and the probability of
predicted values falling in these categories is estimated. The other is the deterministic
forecast where the magnitude of anomalies is estimated for the ensuing month and
the season using different statistical techniques. This outlook uses the forecasts
estimated based on simple ensemble mean after correcting the biases in each of the
The State of the Climate Summary Information is a synopsis of the collection of national and global summaries released each month. As per recently released 'Global Summary Information- April 2016' by the US National Oceanic and Atmospheric Administration (NOAA), the globally averaged land surface temperature was 3.47°F (1.93°C) above the 20th century average. This was the highest for April in the 1880–2016 record, surpassing the previous record set in 2007 by 0.77°F (0.43°C). This was also the third highest temperature departure in the 1880–2016 record, behind March 2016 and February 2016. (http://www.ncdc.noaa.gov/sotc/summary-info).
The World Meteorological Organization Lead Center for Long-Range Forecast (WMOLC LRF) indicates that the positive temperature anomalies will continue to prevail over most of the global land areas for the season June-July-August 2016 (Fig.1). Highly enhanced probability of above normal temperature is predicted for the entire tropical belt, Indian Ocean region and parts of the Pacific Ocean. Enhanced probability of above normal temperature is predicted for most parts of Europe and America, Mediterranean and northern Africa. Strongly enhanced probability for above normal precipitation is predicted for the southern tropical central Pacific, Indian Ocean and Australia, India. Highly enhanced probability for below normal precipitation is predicted for the equatorial Pacific, some parts in maritime continent, western subtropical Pacific, the equatorial Atlantic and southern Africa.
El Nino, a state of warmer-than-average sea surface temperature conditions, is present in the tropical Pacific. A monthly summary of the status of El Nino, La Nina, and the Southern Oscillation, or ENSO is based on the NINO3.4 index (120-170W, 5S-5N). During mid-May 2016 the Positive equatorial sea surface temperature (SST) anomalies have weakened across the equatorial Pacific Ocean, indicating only a weak El Nino. The atmospheric variables continue to support the El Nino pattern, but at much reduced strength. Most ENSO prediction models indicate a return to neutral conditions by end of May and La Nina to develop during the Northern Hemisphere summer 2016, with about a 75% chance of La Nina during the fall and winter 2016-17.
Probabilistic MME forecasts (based on 11 global models) from WMOLC shows that June 2016 temperatures are likely to be above normal across the GCC region and with a probability of more than 60% above average across Qatar. Forecasts also indicate that probability of temperatures to be above normal (>70% probability) for the season (June-July-August) (Fig.2). Probabilistic MME seasonal forecast (JJA) from IRI also shows that the temperature is expected to be above normal (>70% probability) in the Middle East and GCC countries along with more than 70% probability of above normal temperatures in the state of Qatar. The probability of occurrence of temperature extremes to be in the enhanced (above normal) category (40-50%) over Middle East and GCC countries (http://iri.columbia.edu/our-expertise/climate/forecasts/seasonal-climate-forecasts/).
The deterministic MME forecasts (based on 12 models from WMOLC) indicate that above normal temperature conditions will prevail in the GCC countries in June 2016. The temperature anomalies for the State of Qatar are expected to be above normal in the range of 0.25°C to 1.0°C for June 2016 and such above normal conditions are likely to persist in coming two months as well (Fig. 3). Forecasts from other climate centers are generally in agreement with WMOLC outlook for Qatar and the GCC.
Most of the models from WMOLC indicate near normal precipitation during June 2016 and such conditions are likely to persist in the season as a whole (JJA) over Qatar and adjoining regions. Climatologically expected rainfall in this season is almost zero in Qatar.
Climate for State of Qatar in May 2016
The monthly mean, minimum and maximum temperatures recorded in Doha in the month of May are 34.1, 29.4 and 39.6°C respectively. These are deviate by +1.9, +2.6 and +0.5°C from their respective long-term Climatological values
Fig 1. Probabilistic MME forecast from WMO LC LRF: 2m Temperature and precipitation
Fig 2. Probabilistic MME forecast from WMO LC LRF : 2m Temperature
Fig 3. Deterministic MME forecast from WMO LC LRF : 2m Temperature